Radionuclide Transport Models Under Ambient Conditions Rev 01, ICN 00

MDL-NBS-HS-000008

November 2003

1. PURPOSE 
The purpose of this Model Report is to document the Unsaturated Zone Radionuclide Transport 
Model (UZ RTM), which evaluates, by means of three-dimensional (3-D) numerical models, the 
transport of radioactive solutes and colloids in the UZ under ambient conditions from the 
repository horizon to the water table at Yucca Mountain, Nevada. This Model Report also 
addresses comments made in the Model Validation Status Review (BSC 2001 [156257]), 
validates the Active Fracture Model with Matrix Diffusion, and justifies the values of sorption 
coefficients (Kds). This is in accordance with the Technical Work Plan (TWP) for: Performance 
Assessment Unsaturated Zone (BSC 2002 [160819], Section 1.11). This Model Report used flow 
fields provided by Model Report UZ Flow Models and Submodels (BSC 2003 [163045]). The 
output of this Model Report is a set of breakthrough curves for use as benchmarks to validate 
another model, FEHM, which is to be used for UZ transport calculations for Total System 
Performance Assessment for License Application (TSPA-LA). Validation of the FEHM based 
model is documented in Model Report Particle Tracking Model and Abstraction of Transport 
Processes (BSC 2003 [163933]). This validation is also specified in Section I-2-2-2 of the TWP 
(BSC 2002 [160819]) under the validation of the FEHM particle tracking model, where it states 
Agreement with other codes will be demonstrated by running the same problem that has 
previously been run with DCPT, T2R3D, or TOUGH2. Transport calculations presented in this 
report using DCPT and T2R3D are intended to be used as part of the validation of the FEHM 
particle tracking model. 
In the UZ RTM simulations presented in this Model Report, radionuclides are considered to be 
uniformly distributed at time zero in the fractures throughout the repository elements, and their 
subsequent transport to the water table is simulated. The UZ RTM does not consider the waste 
form, waste package, drip shield, or any other component of the Engineered Barrier System, and 
therefore the results are not to be construed as predictions of potential radionuclide transport 
after the repository closure, but only as examples of radionuclide transport calculations for this 
initial condition (i.e., corresponding to a time frame starting at the onset of radionuclide release). 
This Model Report documents the UZ RTM. This model considers 
1. The transport of radionuclides through fractured tuffs 
2. The effects of changes in the intensity and characteristics of fracturing between different 
hydrogeologic units 
3. Colloid transport 
4. Physical and retardation processes 
5. The effects of different conceptual representations of the matrix-fracture system 
6. The effects of different modeling approaches in the description of the transport problem. 

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In the present Model Report, we document the capabilities of the UZ RTM, which can describe 
flow (saturated and/or unsaturated) and transport, and accounts for (a) advection, (b) molecular 
diffusion, (c) hydrodynamic dispersion (with full 3-D tensorial representation), (d) kinetic or 
equilibrium physical and/or chemical sorption (linear, Langmuir, Freundlich, or combined), (e) 
first-order linear chemical reaction, (e) radioactive decay and tracking of daughters, (f) colloid 
filtration (equilibrium, kinetic, or combined), and (g) colloid-assisted solute transport. The 
present Model Report also includes determination and discussion of the distribution coefficients 
Kd of the various sorbing radioactive solutes in the UZ rocks, as well as a corresponding 
uncertainty analysis (see Attachment I, this Model Report). 
Transport of radioactive solutes and colloids (incorporating the processes described above) from 
the repository horizon to the water table are simulated to support model development and studies 
for Performance Assessment (PA). The results of the simulations are used to evaluate the 
transport of radioactive solutes and colloids, and to determine the processes, mechanisms, and 
geologic features that have a significant effect on transport. We evaluated the contribution of 
radioactive-decay daughter products to the total radionuclide inventory transport and from the 
bottom of the repository to the water table, as well as the effect on transport of different 
conceptual models for fracture-matrix systems. We also consider the effect of different 
modeling approaches on transport predictions. 
The primary uncertainty for using the modeling results documented in this report is that the input 
transport parameters were based on limited site data. For some input parameters, best estimates 
were used because no specific data were available. An additional uncertainty is that the RTM is 
based on the conceptual models and numerical approaches used for developing flow fields and 
infiltration maps, and thus they share the same limitations (see BSC 2003 [163045]). 
Compared to the TWP (BSC 2002 [160819]), there are some variations from the criteria used in 
the validation component of this study. For the validation of the Radionuclide Transport Model 
(RTM) using the numerical codes, their simulation results are compared to relevant analytical 
solutions. The validation criterion we used in this case is one or more of the following: 
(a) Mass fractions agree within 5% when CR = C/C0 = 10-4, or 
(b) The location of the tracer fronts agree within 5% when CR = C/C0 = 10-4, or 
(c) The tracer mass balances agree within 5%. 
The results presented in Section 7.2.1 show that this criterion was met in all instances. Note that 
the criterion presented above is somewhat different from that discussed in BSC (2002 [160819], 
Section I-2-1-1) and listed in Section 7.1.1 of this Model Report because the latter (a) is 
inadequate in that it captures only one of the three possible aspects for quantitative agreement, 
and (b) can be unrealistic near the tail end of the CR curve (where CR values are very low, and 
both analytical and numerical predictions may be unreliable because of roundoff error). 
For calibration and additional validation of the RTM using numerical codes (through comparison 
of their predictions to field measurementsMethod 1), the criterion used is the following: 

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(1) Overall agreement between predictions and field measurements are within 50% of 
each other, and, 
(2) If this agreement is not possible, document the analysis and discussion of the reasons 
for the observed deviations. 
Note that inability of the RTM model to match/predict field observations is not necessarily a sign 
of inability to validate the model if: (a) the quality of the field measurements are suspect (i.e., the 
test design may be responsible for uncertainties in the measurement), (b) there is insufficient 
information to fully describe the field test, or (c) field data involve very steep gradients 
(involving very significant parameter changes over a short distance or time) that lead to 
measurements prone to uncertainties and inaccuracies. 
The approach and criteria for the Method 1 validation in this Model Report is somewhat 
different from the one discussed in BSC (2002 [160819], Section I-2-1-1) and listed in Section 
7.1.1 of this Model Report. This is because the TWP criterion is inadequate because it only 
addresses the option of time-series data (i.e., breakthrough) without accounting for the 
possibility of data involving concentration distribution in space at a particular time. The 
validation criterion used addresses this shortcoming, is more inclusive, and is also stricter. 

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2. QUALITY ASSURANCE 
Development of this Model Report and the supporting modeling activities have been determined 
to be subject to the Yucca Mountain Projects quality assurance (QA) program as indicated in 
Technical Work Plan for: Performance Assessment Unsaturated Zone (BSC 2002 [160819], 
Section 8.2, Work Package (WP) AUZM07). Approved QA procedures identified in the TWP 
(BSC 2002 [160819], Section 4) have been used to conduct and document the activities 
described in this Model Report. The TWP also identifies the methods used to control the 
electronic management of data (BSC 2002 [160819], Section 8.4, WP AUZM07) during the 
modeling and documentation activities. 
This Model Report discusses ambient radionuclide transport through hydrogeologic units 
(HGUs) which are a natural barrier and are classified in the Q-List (BSC 2003 [165179]) as 
Safety Category because it is important to waste isolation, as defined in AP-2.22Q, 
Classification Analyses and Maintenance of the Q-List. The results of this report are important 
to the demonstration of compliance with the postclosure performance objectives prescribed in 10 
CFR 63.113 [156605]. The report contributes to the analysis data used to support performance 
assessment; the conclusions do not directly impact engineered features important to safety, as 
defined in AP-2.22Q. 

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3. USE OF SOFTWARE 
The software codes and routines used in this study are listed in Table 3-1. All the software items 
used in this study, i.e., TOUGH2 V1.11MEOS9NTV1.0 (LBNL 1999 [113943]), TOUGH2 V1.4 
Module EOS9 V1.4 (LBNL 2000 [146496]), TOUGH2 V1.6 Module EOS9 (LBNL 2003 
[160242]; LBNL 2003 [161491]), T2R3D V1.4 (LBNL 1999 [146654]), DCPT V1.0 (LBNL 
2000 [132448]), DCPT V2.0 (LBNL 2001 [154342]), iTOUGH2 V4.0 (LBNL 1999 [139918]), 
PHREEQC V2.3 (BSC 2001 [155323]), Bkread.f V1.0 (LBNL 2002 [162143]), XtractG.f90 
V1.0 (LBNL 2003 [162786]), and Smesh.f V1.0 (LBNL 2002 [162142]), were appropriate for 
the intended application used only within the range of their software validation, and obtained 
from software configuration management per AP-SI.1Q, Software Management. 
Table 3-1. Qualified Software Used in this Report 
Software 
Name 
Version Software Tracking Number 
(STN) 
Document Input Reference 
System (DIRS) Number 
iTOUGH2 4.0 10003-4.0-00 139918 
TOUGH2 1.11MEOS9NTV1.0 10065-1.11MEOS9NTV1.0-00 113943 
TOUGH2 1.4 10007-1.4-01 146496 
TOUGH2 1.6 10007-1.6-01 161491 
TOUGH2 1.6 10007-1.6-00 160242 
T2R3D 1.4 10006-1.4-00 146654 
DCPT 1.0 10078-1.0-00 132448 
DCPT 2.0 10078-2.0-00 154342 
PHREEQC 2.3 10068-2.3-00 155323 
Bkread.f 1.0 10894-1.0-00 162143 
XtractG.f90 1.0 10930-1.0-00. 162786 
Smesh.f 1.0 10896-1.0-00 162142 
The software code TOUGH2 V1.11MEOS9NTV1.0 (Module EOS9nTV1.0) (LBNL 1999 
[113943]) simulates flow and the decoupled transport of multiple radioactive solutes and/or 
colloids (parents and daughters) in complex subsurface systems involving porous and/or 
fractured media. The transport equations account for advection, molecular/colloidal diffusion, 
hydrodynamic dispersion, kinetic or equilibrium physical and chemical sorption (linear, 
Langmuir, Freundlich or combined), first-order linear chemical reaction, colloid filtration, and 
colloid-assisted solute transport. 
The code T2R3D V1.4 (LBNL 1999 [146654]) simulates flow and the coupled transport of a 
single radioactive solute tracer in complex subsurface systems involving porous and/or fractured 
media. The transport equations account for advection, molecular diffusion, hydrodynamic 
dispersion, and linear equilibrium sorption. 

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The software codes TOUGH2 V1.4 (Module EOS9 V1.4) (LBNL 2000 [146496]) and TOUGH2 
V1.6 (Module EOS9 V1.6) (LBNL 2002 [160242]; LBNL 2003 [161491]) solve the Richards 
equation to simulate flow in complex subsurface systems (involving porous and/or fractured 
media). 
The software codes DCPT V1.0 (LBNL 2000 [132448]) and DCPT V2.0 (LBNL 2001 [154342]) 
involve the particle-tracking method to simulate transport of a single radioactive solute tracer in 
complex subsurface systems involving porous and/or fractured media. The transport equations 
account for advection, molecular diffusion, hydrodynamic dispersion, and linear equilibrium 
sorption. 
The software iTOUGH2 V4.0 (LBNL 1999 [139918]) and Bkread.f V1.0 (LBNL 2002 [162143]) 
are used for model calibration and prediction of Alcove 8/Niche 3 tests documented in Section 
7.4. A numerical model, generated with a software routine Smesh.f V1.0 (LBNL 2002 
[162142]), was developed for the test site to compare the simulation results with the relevant 
field observations. 
For elements that sorb primarily through surface complexation reactions, the experimental data 
are augmented with the results of modeling calculations using PHREEQC V2.3 (BSC 2001 
[155323]). The inputs for the modeling calculations include groundwater compositions, surface 
areas, binding constants for the elements of interest, and thermodynamic data for solution 
species. These modeling calculations provide a basis for interpolation and extrapolation of the 
experimentally derived sorption distribution coefficient dataset (see Attachment I). 
The software XtractG.f90 (LBNL 2003 [162786]) was used to prepare the mesh files for the 
EOS9nT simulations, for the preparation of the corresponding initial conditions files, and the 
extraction of desired data subsets for plotting. 
Standard visual display graphics programs (i.e., IGOR Pro. 4, Tecplot V8.0, Adobe Illustrator 
V8.0) were also used to illustrate information but are not subject to software quality assurance 
requirements under Quality Assurance Requirements and Description (QARD) per Section 2.0 of 
AP-SI.1Q. 
This Model Report documents the UZ RTM. 

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4. INPUTS 
The input used in this Model Report consist of the following: 
 Transport properties 
 Calibrated fracture and matrix properties 
 Base case flow fields 
 Geochemical data 
 Numerical grids. 
4.1 DIRECT INPUT 
Specific input data sets and their associated Data Tracking Numbers (DTNs) and sources are 
listed in Table 4.1-1. The Q-status of these data is provided in the DIRS. Discussions of 
uncertainties in the input data and parameters, and detailed explanations about the selection of 
corresponding choice of values, are addressed in Section 6. 
The molecular diffusion coefficients and half lives of radionuclides were obtained from accepted 
sources and have been qualified in the TDMS. Sorption coefficients were measured on rock 
samples from YM and using approved procedures, rock properties, including matrix permeability 
and porosity, fracture permeability and spacing were calibrated with field tests on YM. The grid 
for numerical simulation was based upon the Geological Framework Model of YM. Therefore, 
these data are all appropriate for simulations of radionuclide transports. 
Table 4.1-1. Input Data 
Description Parameters Data Tracking Number / Technical 
Information Source 
Molecular diffusion coefficient Lide 1992 [166224], pp. 5-1115-112, 
LA000000000034.002 [148603] 
Half-life for the first-order 
radioactive decay T1/2 
Lide 1992 [166224], pp. 11-1311-133 
Sorption distribution coefficient 
Kd 
LA0305AM831341.001 [163789] 
LA0306AM831343.001 [164949] 
LA0309AM831341.002 [165523] 
LA0309AM831341.003 [165524] 
LA0309AM831341.004 [165525] 
LA0309AM831341.005 [165526] 
LA0309AM831341.006 [165527] 
LA0309AM831341.007 [165528] 
LA0310AM831341.001 [165865] 
Properties of the main 
radionuclides in the transport 
simulations (Tc, Np, Pu, U, Pa, 
U, Th, Am, Cs, Ra, Sr) (Section 
6.5 to Section 6.18) 

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Table 4.1-1. Input Data (continued) 
Description Parameters Data Tracking Number / Technical 
Information Source 
Data for 3-D site-scale 
radionuclide (solute) transport 
modeling (Section 6.5 to 
Section 6.18) 
3-D site-scale grid, hydraulic 
properties/parameters of the 
various hydrogeologic units, 
pressures, water saturations, 3- 
D flow fields for three scenarios 
(mean, high and low) for each of 
three climatic conditions 
(present-day, monsoon and 
glacial) 
LB03013DSSCP3I.001 [162379], 
LB03023DSSCP9I.001 [163044] 
Rock physical properties of the 
various hydrogeologic units 
LB0210THRMLPRP.001 [160799] 
EOS9nT 3-D site-scale 
simulations of colloid transport 
(perched-water model #1, 
mean present-day infiltration) 
(Section 6.7) 
3-D site-scale grid, hydraulic 
properties/parameters of the 
various hydrogeologic units, 
pressures, water saturations, 3- 
D flow fields 
LB03013DSSCP3I.001 [162379], 
LB03023DSSCP9I.001 [163044] 
Pore size data for pore size 
exclusion estimation 
GS950608312231.008 [144662] 
GS980908312242.039 [145272] 
EOS9nT 3-D site-scale 
simulations (radioactive solutes 
and colloids, Section 6.15 to 
Section 6.18) 
3-D grid used in the simulations LB03023DSSCP9I.001 [163044] 
4.1.1 Data Used Corroboratively 
Specific data sets used corroboratively are listed in Table 4.1-2. These data were either used to 
simulate UZ tracer test at Busted Butte, or are field data from that test. Additional data 
previously cited in Table 4.1-1 were also used for Busted Butte simulations. 
Discussions of uncertainties in the input data and parameters, and detailed explanations about the 
selection of corresponding choice of values, are addressed in Section 7. 

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Table 4.1-2. Data Used for Busted Butte Simulations 
Description Parameters Data Tracking Number / Technical 
Information Source 
Modeling the Phase1A test of 
Busted Butte (Section 7.3.3) 
Matrix porosity f, permeability k, 
initial saturation, and rock grain 
density .s 
of the field samples 
GS990308312242.007 [107185], 
GS990708312242.008 [109822] 
Diffusion coefficient and sorption 
parameters 
Cussler (1984 [146653]), Benson and 
Bowman (1994 [122788]) 
Model validationPhase1A 
test of Busted Butte (Section 
7.3.3) 
Field measurements/data LA0302WS831372.001 [162765], 
LA9910WS831372.008 [147156] 
Modeling the Phase1B test of 
Busted Butte (Section 7.3.4) 
Matrix porosity, permeability, and 
initial saturation of the field 
samples 
GS990308312242.007 [107185], 
GS990708312242.008 [109822] 
Diffusion coefficient for Li+ and 
2,6-DFBA 
Cussler (1984 [146653]), Benson and 
Bowman (1994 [122788]) 
Sorption parameters LA9912WS831372.001 [156586] 
Field measurements/data LA0201WS831372.008 [162766] 
Model ValidationPhase 2C 
test of Busted Butte (Section 
7.3.5) 
Field measurements/data LA0008WS831372.001 [156582] 
LA0112WS831372.001 [157100] 
LA0112WS831372.002 [157115] 
LA0112WS831372.003 [157106] 
LA0211WS831372.001 [162763] 
NOTE: The data in this table are being used as reference only to support model validation. 

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4.2 CRITERIA 
The licensing criteria for postclosure performance assessment are stated in 10 CFR 63.114 
[156605]. The requirements to be satisfied by TSPA are identified in the Yucca Mountain 
Project Requirements Document (Canori and Leitner 2003 [161770]). Acceptance criteria that 
will be used by the Nuclear Regulatory Commission (NRC) to determine whether the technical 
requirements have been met are identified in Yucca Mountain Review Plan, Final Report 
(YMRP; NRC 2003 [163274]). The pertinent requirements and criteria for this Model Report are 
summarized in Table 4.2-1. 
Table 4.2-1. Project Requirements and YMRP Acceptance Criteria Applicable to This Model Report 
Requirement 
Numbera 
Requirement Titlea 10 CFR 63 Link YMRP Acceptance Criteria 
PRD-002/T-016 
PRD-002/T-015 
Requirements for 
Performance Assessment 
Requirements for Multiple 
Barriers 
10 CFR 
63.114(a-c) 
[156605] 
10 CFR 
63.115(a-c) 
[156605] 
Criteria 1 to 4 for Radionuclide Transport in 
the Unsaturated Zone b 
Criteria 1 to 3 for Demonstration of Multiple 
Barriers c 
NOTES: a from Canori and Leitner (2003 [161770]) 
b from NRC (2003 [163274], Section 2.2.1.3.7.3) 
c from NRC (2003 [163274], Section 2.2.1.1.3) 
The acceptance criteria identified in Section 2.2.1.3.7.3 of the YMRP (NRC 2003 [163274]) are 
given below, followed by a short description of their applicability to this Model Report: 
 Acceptance Criterion 1, System Description and Model Integration Are Adequate: 
Transport relationships at the interface between the waste emplacement drift and the rock are 
accounted for in a manner that is consistent with the various flow and transport model 
abstractions used in the TSPA. The methodology accounts for important design features and 
physical phenomena at a level consistent with the available data and uncertainty such that the 
radionuclide transport in the unsaturated zone is not underestimated. In particular, this 
model provides suitable estimates for the boundary conditions for the UZ mountain-scale 
transport abstraction in terms of the partitioning of radionuclide releases from waste 
emplacement drifts to the fractures and rock matrix supporting the inclusion of related FEPs. 
Information supporting Acceptance Criterion 1 is presented in the following Sections: 6.1 to 
6.2, 6.5 to 6.23, and 6.25. 
 Acceptance Criterion 2, Data Are Sufficient for Model Justification: 
Geological and hydrological characteristics used in the safety case are adequately justified. 
Adequate descriptions of how the data were used, interpreted, and appropriately synthesized 
into the parameters are provided. Data on the geology and hydrology of the UZ, including 
fracture distributions, fracture properties and stratigraphy, used in the TSPA, are based on 
appropriate techniques. 

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Data that are input to the model are identified in Section 4.1. Comparison of data not used as 
input to simulation for model validation is presented in Section 7. Information supporting 
Acceptance Criterion 2 is presented in the following Sections: 6.2, 6.5 to 6.11, 6.23, and 
6.25. 
 Acceptance Criterion 3, Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction 
The parameters used in and derived by the radionuclide transport process model are 
technically defensible; they are based on and consistent with available data from Yucca 
Mountain; uncertainties and variabilities are evaluated and reasonably accounted for and 
adequately represented. Uncertainty is adequately represented in parameter development for 
conceptual models, process-level models, and alternative conceptual models, considered in 
developing the abstraction of radionuclide transport in the unsaturated zone. 
Information supporting Acceptance Criterion 3 is presented in the following Sections: 6.5, 
6.6, 6.12 to 6.14, 6.23, and 6.25. 
 Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
Alternative modeling approaches of features, events, and processes are considered and are 
consistent with available data and current scientific understanding, and the results and 
limitations are appropriately considered in the abstraction. Conceptual model uncertainties 
are adequately defined and documented, and effects on conclusions regarding performance 
are properly assessed. Appropriate alternative modeling approaches are consistent with 
available data and current scientific knowledge, and appropriately consider their results and 
limitations. 
Information supporting Acceptance Criterion 4 is presented in the following Sections: 6.5, 
6.6, 6.12 to 6.23, and 6.25. 
The acceptance criteria identified in Sections 2.2.1.1.3 of the YMRP (NRC 2003 [163274]) are 
given below, followed by a short description of their applicability to this Model Report: 
 Acceptance Criterion 1, Identification of Barriers Is Adequate: 
The unsaturated rock layers below the repository (and above the water table) form a natural 
barrier important to waste isolation. This barrier functions by delaying radionuclide 
movement. The barrier capability is determined by the hydrological and transport properties 
as implemented in this model for UZ transport. 
Information supporting Acceptance Criterion 1 is presented in the following Sections: 6.6 to 
6.10, 6.12 to 6.23, and 6.25. 
 Acceptance Criterion 2, Description of Barrier Capability to Isolate Waste Is Acceptable: 

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The capability of the identified barrier to substantially delay the movement of radionuclides 
is adequately identified and described. The uncertainty associated with barrier capabilities is 
adequately described. 
Information supporting Acceptance Criterion 2 is presented in the following Sections: 6.6 to 
6.10, 6.12 to 6.23, and 6.25. 
 Acceptance Criterion 3, Technical Basis for Barrier Capability Is Adequately Presented: 
The technical bases are consistent with the technical basis for the performance assessment. 
The technical basis for assertions of barrier capability is commensurate with the importance 
of each barriers capability and the associated uncertainties. 
Information supporting Acceptance Criterion 3 is presented in Section 6.25. 
Two of these criteria (criteria 3 and 4 for Radionuclide Transport in the UZ, Section 2.2.1.3.7.3 
of NRC 2003 [163274]) were not identified in the TWP (BSC 2002 [160819], Table 3.1), but are 
appropriate for this Model Report. One criterion that was identified for this Model Report 
(criterion 2 for Flow Paths in the UZ, Section 2.2.1.3.6.3 of NRC 2003 [163274], Flow Paths in 
the Unsaturated Zone: Data are Sufficient for Model Justification) is not appropriate for this 
Model Report. 
4.3 CODES AND STANDARDS 
No specific formally established codes or standards have been identified as applying to this 
Model Report. 

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5. ASSUMPTIONS 
In this section we discuss the basic data assumptions involved in the transport model, and we 
provide a short discussion of the supporting rationale. 
The main data assumptions in this study are listed in Table 5-1. 
A physical basis for an assumption for the tortuosity factor is provided by Farrell and Reinhard 
(1994 [122803], p. 64) and Grathwohl (1998 [141512], pp. 2835), while the work of Hu and 
Brusseau (1995 [122846]) experimentally validated this approach. A more thorough analysis on 
this subject can be found in Section 6.1.2.4. No further confirmation is required for the 
assumptions listed in Table 5-1. 
The transfer coefficient Ki indicates the ratio of the concentration of dissolved species in 
immobile and mobile water. By setting Ki = 1, it is assumed that immobile water is equilibrated 
instantaneously with mobile water. This assumption was also made by de Marsily (1986 
[100439], pp. 238239) and is consistent with the assumption of linear adsorptive equilibrium. 
This topic is discussed further in Section 6.2.3.1; no further confirmation is required. 
James and Chrysikopoulos (1999 [109517], p. 707) found that larger colloidal particles travel in 
fractures faster than smaller particles. With a parabolic velocity profile (James and 
Chrysikopoulos (1999 [109517], Figure 1) between parallel plates, the maximum liquid velocity 
is 1.5 times the average velocity. Therefore the largest particles (450 nm) were assigned that 
velocity adjustment factor as shown in Table 5-1 and Table 6.18-1. No further confirmation is 
required for this assumption. 
Dispersivity values ranging from 0.06 m to 2.63 m were measured in gas-tracer experiments 
conducted in Yucca Mountain (LeCain et al. 2000 [144612], Tables 18 and 19). Based on those 
measurements, the values shown in Table 5-1 were assumed. Further discussion of longitudinal 
dispersivity is presented in section 6.1.2.2. For both solutes and colloids, advection is much 
more important than dispersion; the assumption is therefore adequate for the purpose of 
predicting radionuclide transport, and no further confirmation is required. 
The kinetics of declogging (release of colloidal particles after being immobilized) is not well 
understood. Therefore, a wide range of values have been assumed (Section 6.18.3). Simulation 
results shown in Sections 6.18.4 through 6.18.7 show that transport is not sensitive to the 
declogging kinetic coefficient; the assumption is therefore adequate for the purpose of predicting 
radionuclide transport, and no further confirmation is required. 
Because a fracture is by definition devoid of matrix material, assigning a porosity of 1 to 
fractures is reasonable and requires no confirmation. 

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Table 5-1. Main data assumptions used in this study 
Parameter Sections Value Justification 
Tortuosity t 6.6, 6.8 to 6.20 f See Table 6.8-1 
Transfer coefficient Ki for 
solutes 
6.8 to 6.20 1 Conventionally used value 
Velocity adjustment factor fv 6.18 1.5, 1.2, 1.1, 1.0 
for the 450, 200, 
100, 6 nm 
Reasonable estimates 
(covers entire range of fv 
values, see Section 
6.2.4.1) 
Longitudinal dispersivity aL 
(solutes) 
6.7 to 6.17, 
6.20 
1 m in fracture, 
0.1 m in matrix 
Scientific judgment (based 
on LeCain et al. (2000 
[144612]). 
Longitudinal dispersivity aL 
(colloids) 
6.18 0.5 m in fracture, 
0.05 m in matrix 
Scientific judgment (based 
on LeCain et al. (2000 
[144612]). 
Backward (reverse) kinetic 
filtration (declogging) 
coefficient .- 
6.18 100 .+, 0.1 .+, 0 Reasonable estimates 
bracketing the range of .- 
(ranges are sufficiently 
wide to cover likely values) 
Fracture porosity f 6.6 to 6.17, 
6.20 
1 Reasonable estimate 
(reasonable for open 
fractures) 
The immediately preceding upstream document to this Model Report is entitled UZ Flow Models 
and Submodels (BSC 2003 [163045]). No assumptions involving numerical values of input 
parameters were used in that report. However, several approximations and idealization were 
used for the model development of the UZ Flow Models and Submodels Model Report. 

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6. MODEL DISCUSSION 
The objective of this Model Report is to provide a defensible and credible model of radionuclide 
transport in individual vertical quasi 2-D slices of the UZ and in large 3-D systems using the 
flow fields submitted for use in TSPA calculations. This is in accordance with the Technical 
Work Plan (TWP) for: Performance Assessment Unsaturated Zone (BSC 2002 [160819], Section 
1.11). The output/product of this Model Report is a set of breakthrough curves for use as 
benchmarks for the particle-tracking calculations performed for TSPA (BSC 2003 [163933]). In 
this section, we describe the development of the RTM. The primary objectives of the RTM are: 
 Using the comprehensive calibrated 3-D model of the unsaturated flow developed in 
BSC (2003 [163045], Section 6.2), to integrate the available data for the development of 
a comprehensive model of radionuclide transport through the UZ of Yucca Mountain 
under a range of current and future climate conditions. 
 To identify the controlling transport processes and phenomena, and to evaluate the 
effectiveness of matrix diffusion and sorption as retardation processes. 
 To identify the geologic features that are important to radionuclide transport. 
 To estimate the migration of important radionuclide solutes and their daughter products 
from the repository toward the water table. 
 To evaluate the effects of various climatic conditions on radionuclide transport. 
 To estimate the migration of radioactive colloids from the repository toward the water 
table, and to determine the sensitivity of colloid transport to the kinetic coefficients of 
colloid filtration. 
 To evaluate the effect of fracture spacing, intensity and configuration on radionuclide 
transport and retardation through important hydrogeologic units. 
The RTM is a dual permeability model that uses steady state flow fields, and simulates transports 
of solutes and colloids advectively and by diffusion between fracture and matrix. The solutes 
also are subject to sorption and filtrations for the case of colloids. 
This section consists of the following subsections: 
Section 6.1. Geological Model and Physical Processes. In this section we focus on (a) the 
geology and stratigraphy in the UZ of Yucca Mountain, the site for the repository, (b) the 
processes and phenomena involved in and affecting transport, and (c) important issues that may 
have an impact on predictions about and understanding of transport behavior of radioactive 
solutes and colloids in the UZ. We also list the basic modeling approaches. 

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Section 6.2. Mathematical Model of Transport. In this section we present the mathematical 
basis and discuss the implications of the various processes and phenomena involved in the 
transport of solutes and colloids in the UZ. 
Section 6.3. The Numerical Models. In this section, we discuss the codes that implement the 
numerical models developed from the principles discussed in Section 6.2. These codes are 
T2R3D V1.4 (hereafter referred to as T2R3D; LBNL 1999 [146654]) and TOUGH2 
V1.11MEOS9NTV1.0 (hereafter referred to as EOS9nT; LBNL 1999 [113943]), and were used 
for the simulations discussed in Sections 6.6 to 6.20, and in Section 7. 
Section 6.4. Features, Events and Processes (FEPs). This section focuses on the discussion of 
selected Features, Events and Processes (FEPs) taken from the Licensing Application FEP List, 
and which are associated with the subject matter of this Model Report. 
Section 6.5. Sorption Model and Parameters. This section focuses on the sorption behavior of 
the radionuclides of interest in the various UZ rocks and discusses the determination of the 
sorption coefficients used in this Model Report. 
Section 6.6. A Preliminary Conceptual Model of Transport Based on Geology and 
Stratigraphy. In this section, we develop a conceptual model of radionuclide transport in vertical 
columns covering the geologic spectrum from the repository to the water table based on the 
geology and stratigraphy at three representative UZ locations. 
Section 6.7. Three-Dimensional Transport Simulations. In this section, we discuss the grids, 
climatic conditions, perched water model, radionuclides, flow fields, and general approach used 
in the ensuing 3-D site-scale simulations of transport through the UZ (Sections 6.8 to 6.18, and 
6.20), as well as the conditions and general options used in these EOS9nT simulations. 
Section 6.8. Three-Dimensional Simulations of 99Tc TransportInstantaneous Release. In 
this section, we study the migration of 99Tc through the UZ following a single release event 
(instantaneous release). We investigate the effects of various climatic scenarios on transport, as 
well as the impact of uncertainty in the contribution of diffusion (as quantified by the choice of 
the molecular diffusion coefficient) on transport. We also identify transport-controlling geologic 
features, transport patterns, and important retardation mechanisms. 
Section 6.9. Three-Dimensional Transport of 237NpInstantaneous Release. In this section, 
we investigate the transport of 237Np through the UZ under various climatic scenarios following 
a single radionuclide release event. We also study the sensitivity of transport to uncertainty in 
matrix diffusion. We identify transport-controlling geologic features and important retardation 
mechanisms, and we compare the concentration distributions and the transport patterns of 237Np 
to those of 99Tc. 
Section 6.10. Three-Dimensional Transport of 239PuInstantaneous Release. In this section, 
we study the transport of 239Pu through the UZ under various climatic scenarios following a 
single radionuclide release event, and for various levels of matrix diffusion (as controlled by the 
choice of the diffusion coefficient). We identify transport-controlling geologic features and 

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important retardation mechanisms, and we compare the concentration distributions and the 
transport patterns of 239Pu to those of 99Tc and 237Np. 
Section 6.11. Three-Dimensional Transport of 233U and 235UInstantaneous Release. In this 
section, we study the transport of 233U and 235U through the UZ under various climatic scenarios 
following a single radionuclide release event. 
Section 6.12. Three-Dimensional Transport of 241Am and 90Sr Instantaneous Release. This 
section focuses on the transport of 241Am and 90Sr through the UZ under various climatic 
scenarios following a single radionuclide release event. 
Section 6.13. Three-Dimensional Transport of 135CsInstantaneous Release. This section 
addresses the issue of transport of 135Cs through the UZ under various climatic scenarios 
following a single radionuclide release event. 
Section 6.14. Three-Dimensional Transport of 226Ra, 229Th, and 231PaInstantaneous 
Release. In this section, we study the transport of 226Ra, 229Th, and 221Pa, all of which sorb very 
strongly onto the Yucca Mountain rocks. We also study the effect of various climatic scenarios 
on transport following a single radionuclide release event. 
Section 6.15. Three-Dimensional Simulations of 99Tc, 237Np, and 239Pu Transport 
Continuous Release. In this section, we investigate the migration of 99Tc, 237Np, and 239Pu 
through the UZ when the radioactive species are released continuously from a decaying source. 
We identify transport-controlling geologic features, transport patterns, and important retardation 
mechanisms, and discuss the differences from the instantaneous release scenario. 
Section 6.16. Three-Dimensional Transport of the 239Pu 235U 231Pa Chain 
Continuous Release. In this section, we study the transport of the three-member 239Pu chain 
through the UZ when the radioactive species are continuously released from a decaying source. 
The importance of accounting for the transport of the whole chain rather than individual species 
is discussed. 
Section 6.17. Three-Dimensional Transport of the 241Am 237Np 233U 229Th 
ChainContinuous Release. In this section, we study the transport of the four-member 241Am 
chain through the UZ when the radioactive species are continuously released from a decaying 
source. The importance of accounting for the transport of the whole chain rather than individual 
species is discussed. 
Section 6.18. Three-Dimensional Site-Scale Transport of PuO2 ColloidsContinuous 
Release. In this section, we study the transport of four radioactive colloids through the UZ for a 
mean present-day infiltration. We identify transport-controlling geological features and 
important retardation mechanisms, and discuss the differences between the transport patterns of 
the four colloids. 
Section 6.19. Alternative Models. In this section, we investigate 

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1. Different representations of the matrix-fracture system (multiple interactive continua 
vs. dual-permeability systems), and 
2. Different conceptual methods of describing the transport problem (particle tracking vs. 
conventional representation). 
We investigate the effect of these alternative approaches on predictions of transport through a 
2-D vertical cross section of the UZ at Yucca Mountain. 
Section 6.20. Barrier Evaluation, Uncertainties, and a Note of Caution. In this section, we 
review the results of the analysis and discuss the overall barrier performance of the geological 
setting underneath the repository. Additionally, we review the issue of uncertainty in the 
predictions, and possible implications stemming from this analysis. Finally, we discuss the 
framework within which the results of this Model Report should be interpreted. 
The scientific notebooks (SN) used for the activities in this Model Report are listed in Table 6.1. 
Table 6.1. Scientific Notebooks Used for Model Report 
LBNL Scientific 
Notebook 
YMP M&O Scientific 
Notebook ID 
Page Numbers Citation 
YMP-LBNL-GJM-5 SN-LBNL-SCI-099-V3 1-109 Wang 2003 [164021] 
YMP-LBNL-GJM-YS-1 SN-LBNL-SCI-230-V1 890 Wang 2003 [164021] 
YMP-LBNL-GJM-GZ-1 SN-LBNL-SCI-235-V1 937 Wang 2003 [164021] 
YMP-LBNL-GSB-LHH-3 SN-LBNL-SCI-215-V1 107109, 111112, 114115 Wang 2003 [164021] 
YMP-LBNL-GSB-QH-1 SN-LBNL-SCI-168-V1 138 Hu 2001 [163148] 

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6.1 GEOLOGICAL MODEL AND PHYSICAL PROCESSES 
6.1.1 Geological Layering 
The geological model used in this Model Report is based on the Geological Framework Model 
(GFM2000) and Integrated Site Model (ISM). The subsurface formations at Yucca Mountain 
consist of heterogeneous layers of anisotropic, fractured volcanic rocks. There are alternating 
layers of welded and nonwelded ash flow and air fall tuffs. The cooling history of these volcanic 
rock units determines their mechanical and hydrological properties. Beginning from the land 
surface, the Yucca Mountain geologic units are the Tiva Canyon, Yucca Mountain, Pah Canyon, 
the Topopah Spring Tuffs, and interbedded tuffs of the of the Paintbrush Group. Underlying 
these are the Calico Hills Formation, and the Prow Pass, Bullfrog, and Tram Tuffs of the Crater 
Flat Group. These formations have been divided into major hydrogeologic units based roughly 
on the degree of welding. These are the Tiva Canyon welded units (TCw); the Paintbrush 
nonwelded units (PTn), consisting primarily of the Yucca Mountain and Pah Canyon members 
and the interbedded tuffs; the Topopah Spring welded units (TSw); the Calico Hills nonwelded 
units (CHn); and the Crater Flat undifferentiated (CFu) hydrogeologic units (Scott and Bonk 
1984 [104181]; BSC 2003 [160109], Section 6). 
Conceptual models of flow and transport at Yucca Mountain are described in BSC (2003 
[163045], Section 6). In the present Model Report, we focus on the subject of radionuclide 
transport in the hydrogeologic units beneath the repository horizon. The repository will be sited 
in the TSw unit (CRWMS M&O 1999 [103773]), and more specifically the tsw34, tsw35, and 
tsw36 layers of the unsaturated zone (UZ), depending on the location. More information on these 
layers can be found in BSC (2003 [160109], Section 6) and BSC (2003 [161773], Section 6). 
Unsaturated flow in the TSw is primarily through the fractures, because the matrix permeability 
in many of the TSw layers can support flows of only a few millimeters per year, and the average 
fracture spacing in the TSw layers is on the order of 0.5 m (BSC 2003 [161773], Section 6). 
The CHn unit and the Prow Pass (PP) unit (formally a part of CHn, but studied separately in the 
present Model Report) below the repository horizon are complex geological systems with 
strongly heterogeneous distributions of fracture and matrix hydrological properties, which are 
expected to have pronounced effects on flow and transport of radionuclides in the UZ. There is 
limited information on the CHn unit, and even less on PP. The permeability of nonwelded tuffs 
is strongly dependent on the degree of alteration of the rock minerals into zeolites. Zeolitic 
alteration in the CHn (a common occurrence in its lower layers) can reduce the matrix 
permeability by orders of magnitude in relation to that of the welded tuffs (BSC 2003 [161773], 
Section 6). In nonwelded vitric tuffs, the matrix and fracture permeabilities are on the same order 
of magnitude (BSC 2003 [161773], Section 6). Thus, the non-zeolite layers behave as porous 
(rather than fractured) media, and flow is matrix dominated. This has important implications for 
transport, because the longer contact times in these nonwelded tuff units allow increased 
radionuclide sorption. 
The CHn major hydrogeologic unit is composed of Calico Hills vitric (CHv) and Calico Hills 
zeolitic (CHz) units (BSC 2003 [160109], Section 6). Typically, radionuclides are more strongly 
adsorbed onto zeolitic units than onto vitric units (see Attachment I and Table 6.5-1). For 
example, the Kd (see Equation 6-9) of 237Np in the vitrified and the zeolitic tuffs is 0.5 mL/g and 

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1 mL/g, respectively (Output-Data Tracking Number (DTN): LA0302AM831341.002, see 
Section 6.5). Consequently, migration of 237Np is expected to be more retarded in the zeolitic 
than in the vitrified units, if the contact time is the same. 
Flow in the CHz units is expected to be concentrated in the fractures because of the large 
permeability contrast between matrix and fractures (BSC 2003 [161773], Section 6); the 
permeability in the fractures is about four orders of magnitude larger than in the matrix (DTNs: 
LB0205REVUZPRP.001 [159525] and LB0207REVUZPRP.002 [159672]). Fracture-dominated 
flow is associated with short contact times, limited radionuclide removal through diffusion and 
sorption, and thus transport over longer distances. 
The fracture and matrix permeability values of the zeolitized Calico Hills unit are based on 
product outputs from the report Calibrated Properties Model (BSC 2003 [160240] and the report 
Analysis of Hydrological Properties Data (BSC 2003 [161773]). These hydrological properties, 
derived by inverse modeling to match pneumatic responses through fracture network and watercontent 
and potential values in the matrix, are regarded as reasonable representation of the actual 
fracture and matrix permeability values of the zeolitized Calico Hills unit. 
6.1.2 Transport 
Radioactive contaminants can escape from the wastes stored in the repository. These 
contaminants can migrate through the UZ as a dissolved molecular species or in colloidal form. 
Transport of these radioactive solutes or colloids involves advection, hydrodynamic dispersion, 
sorption (solutes) or filtration (colloids), matrix diffusion, and radioactive decay. The transport 
of radionuclides is also affected by factors such as solubility limits, the presence of perched 
water, and heating effects from the repository. In this section, we briefly discuss the phenomena, 
processes, and factors affecting transport. 
6.1.2.1 Advection 
Advection is the transport of dissolved or colloidal species by flowing water. In the Yucca 
Mountain UZ, flow is predominately downward (in response to gravitational differentials), and 
so is advective transport (DOE 1998 [100550], p. 3-112). Some lateral advection is also expected 
in response to lateral flow diversion at the boundaries of hydrogeologic units with sharp contrast 
in their hydraulic properties. Such diversion occurs in the perched-water bodies of the UZ (BSC 
2003 [163045], Section 6.2.2; DOE 1998 [100550], p. 3112). Laterally diverted flow ultimately 
finds a pathway to the water table through other, more permeable zones (e.g., faults). 
Advection is probably the most important transport process in this study, because it controls the 
speed at which radionuclides move through the UZ to reach the water table. Advection in the 
fractures is expected to be the dominant transport mechanism in many layers of the various 
hydrogeologic units. This is because the expected flow rates in the matrix exceed the matrix 
permeability (which gives the measure of flow capacity under the gravitational gradient). This 
leads inevitably to flow focusing in the more permeable fractures. Advection is the dominant 
transport mechanism in the fractures because of high permeability, limited fracture pore 
volumes, limited contact area, and short contact times between the radionuclide-carrying liquid 
phase and the matrix (only at the fracture walls). In a few hydrogeologic units, such as the CHv, 

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matrix flow is dominant, resulting in much slower transport velocities (compared to those in the 
fractures of other units) and longer radionuclide-matrix contact times (DOE 1998 [100550], p. 
3-112). 
6.1.2.2 Hydrodynamic Dispersion 
Hydrodynamic dispersion combines mechanical dispersion, caused by localized velocity 
variations, with molecular diffusion, caused by Brownian motion and is proportional to the 
concentration gradient. The dispersion of the radionuclides can occur both along and transverse 
to the average flow direction. Hydrodynamic dispersion leads to the smoothing of sharp 
concentration fronts and reduces the breakthrough time (which can be defined as the arrival time 
of the edge of the contaminant front) at the water table. 
Little information exists on the values of the longitudinal (aL) and transverse (aT) dispersivity 
([L]) in the various hydrogeologic units of the UZ. In past simulations (DOE 1998 [100550], 
p. 3-122), the longitudinal dispersivity (aL) values for both the fractures and the matrix of all 
units had a mean of 20 m and a standard deviation of 5 m. Analysis of the Northern Ghost 
Dance Fault test (LeCain et al. 2000 [144612], Tables 1819) indicates an aL in the 0.06 m to 
2.63 m range, but the validity of these estimates is uncertain because they are based on gas 
(rather than liquid) phase transport, short transport times (<200 min), and a small scale 
experiment (<10 m). Analysis of the C-well transport test indicate that aL ranged between 1.9 
and 6.2 m (BSC 2003 [162415], Section 6.3) however, these results corresponded to the 
saturated conditions in the deeper formations of YM. Note that dispersion is not expected to 
play a significant part in the transport of radionuclides in the fractures because of the 
predominant role of advection as the main transport mechanism and the limited water flow into 
the matrix. 
Dispersion is affected by the scale of observation. The value of dispersivity appears to increase 
with the scale of observation (Gelhar et al. 1992 [122808], p. 1955; Fetter 1993 [102009], pp. 
6566). Thus, aL increased from 102 to 104 m when the observation scale increased from 10-1 to 
105 m, and its value did not appear to be significantly affected by the texture (porous versus 
fractured) of the aquifer medium (Gelhar et al. 1992 [122808], p. 1955). 
The ratio aL / aT controls the shape of a contaminant plume in multidimensional transport. There 
is a paucity of data on the relationship between aL and aT. Based on that limited field data, Fetter 
(1993 [102009], pp. 6566) reported that aL /aT ranged between 6 and 20. Gelhar et al. (1992 
[122808], p. 1955) indicated that vertical aT is typically an order of magnitude smaller than the 
horizontal aL. 
6.1.2.3 Sorption 
Sorption is a general term that describes a combination of chemical interactions between the 
dissolved radionuclides and the solid phases, that is, either the immobile rock matrix or colloids 
(mobile or immobile). In transport studies, the concept of sorption does not identify the specific 
underlying interactions, such as surface adsorption, precipitation, and ion exchange. By 
removing a portion of the dissolved species from the mobile liquid phase and transferring it to 
the immobile solid phase, sorption reduces the rate of advance of (i.e., retards) the concentration 
front of a dissolved or suspended species. 

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In Yucca Mountain studies, the effective Kd approach (see Equation 6-9) is employed to quantify 
the extent of radionuclide-rock interactions by measuring the overall partitioning between the 
aqueous and the solid phase. Three basic rock types (devitrified tuffs, vitric tuffs, and zeolitic 
tuffs) have been studied as having distinctively different (i.e., from each other) sorption 
interactions with the radionuclides (DOE 1998 [100550], p. 3-118). The estimation of Kd values 
for several radionuclides in each of these rock types is the subject of the detailed analysis of 
Section 6.4. Note that sorption is not only a function of the sorptive strength (as quantified by the 
value of Kd), but also of the contact time of the radionuclides with the rock matrix during 
transport through the UZ. 
The Kd values used in the Yucca Mountain studies have been estimated from batch experiments 
using crushed tuffs with a particle size of 75500 m under saturated conditions (Section 6.4, 
this Model Report; BSC 2001 [160828], Section 6.4). Under true linear equilibrium sorption 
conditions, the Kd value is independent of concentration or of the time of contact. The effective 
Kd value of a particular radionuclide sorbing onto a rock can vary depending on the estimation 
approach. Dependence of the effective Kd on concentration indicates nonlinear sorption, and Kd 
dependence on contact time indicates kinetic behavior. The importance of kinetic, nonlinear, 
and irreversible sorption may need to be evaluated against the linear equilibrium isotherm 
assumed in UZ transport studies. 
The Kd values obtained from experiments involving low concentration solutions tend to be 
higher than those from higher concentration ones because the most active sorption sites are 
immediately occupied by the dilute solutes (while denser solutes will involve less active ones, 
i.e., indicating nonlinear sorption isotherms such as Langmuir or Freundlich). The obvious 
implication is that Kd values from experiments involving concentrations similar to those 
expected in the field should be used to avoid overestimation or underestimation. Lower 
Kd values can be estimated if (a) the duration of the sorption experiments is short, and (b) a 
linear equilibrium sorption model is assumed but sorption is actually kinetically controlled. Note 
that the determination approach in the YM studies (Attachments I and II of present Model 
Report) tends to underestimate the Kd values because (a) it involves an averaging of Kd values 
obtained from experiments using both low and high solution concentrations, while (b) the release 
concentrations are expected to be low at the repository. 
If kinetic behavior is not an issue, batch experiments with dilute concentrations may 
overestimate the Kd values because of the aforementioned reasons, and because the prevailing 
conditions (involving saturated crushed rock samples in complete contact with a large amount of 
solute-bearing liquid relative to the sample mass) may not be representative of the UZ, which is 
characterized by unsaturated conditions, a limited contact area, and a limited amount of solute in 
the finite invading stream (see Section 6.1.3.1 for a more thorough discussion). 
Sorption kinetics could be important, especially for radionuclides sorbing onto zeolitic tuffs. 
Column experiments of 237Np transport in tuffs (Viswanathan et al. 1998 [134579], p. 267) 
indicate the existence of kinetic sorption under flowing conditions, possibly as a result of the 
slow diffusion of 237Np into the tuff pores. It is not possible to analyze these experimental data 
without considering a kinetic sorption model. Kinetic sorption can have a substantial effect on 
transport in fast fracture flow because it reduces sorption in the matrix, thus allowing larger 

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radionuclide concentrations and migration over longer distances in the fractures. Nonlinear and 
irreversible sorption are evident from the diffusion and transport studies discussed in BSC (2001 
[160828], Section 6.4). Note that, although there is an appreciation of the potential kinetic 
behavior, sorption is treated as a linear equilibrium process in this Model Report because (a) the 
kinetic effects are unlikely to persist over the long time frames (up to a million years) of this 
study, the duration of which strongly suggests an equilibrium process after a relatively short 
initial kinetic period, and (b) the generally low Kd values used in this study account for the early 
kinetic effects. 
6.1.2.4 Matrix Diffusion 
Diffusion can play an important role in radionuclide exchange between the fractures and the rock 
matrix. This process transfers radionuclides into the matrix (where water flow is slow and 
sorption occurs), thus removing them from (and slowing the advance of their front in) the fast 
fracture flow. Diffusive flux across a given interface is a function of the concentration gradient, 
the temperature, the size of the dissolved species and its electric charge, the matrix pore 
structure, and the water saturation (DOE 1998 [100550], pp. 3-1163-117). 
Matrix diffusion is a linear function of the tortuosity coefficient t, which describes the tortuous 
nature of the pore networks (Grathwohl 1998 [141512], pp. 2835), including dead-end pores 
and steric hindrance (in extremely narrow pores). The term t is defined as the distance between 
any two given points in a porous medium over the actual travel path through the pores between 
these two points, i.e., t < 1. There are very limited experimental data on the t distribution in the 
various Yucca Mountain hydrogeologic units. In this study, t is approximated by the value of 
porosity f (Farrell and Reinhard 1994 [122803], p. 64; Grathwohl 1998 [141512], pp. 2835). 
This approach to define t was confirmed experimentally from rock diffusion experiments using 
devitrified tuffs where the effective diffusion coefficient De (= f t Sw D0, where D0 is the 
molecular diffusion coefficient [L2 T-1] and Sw is the water saturation) for tritiated water was 
obtained from six tuff samples. Based on the literature value of D0 for tritiated water (Hu and 
Brusseau 1995 [122846]), a t estimate of 0.08060.035 was obtained for media in which the 
reported average porosity was 0.07670.019 (Triay et al. 1993 [145123], p. 1530 and Scientific 
Notebook SN-LBNL-SCI-168-V1 (Hu 2001 [163148], p. 23)). The good match between these 
two numbers validates the approach of using the porosity value as the tortuosity coefficient. 
Even less information exists on the effect of Sw on De. Porter et al. (1960 [123115]) reported that 
the t f Sw product decreased consistently in medium- and fine-textured soils as the capillary 
pressure increased from 0.33 to 15 atm. The effect of saturation on De may be more complex 
than the linear relationship currently assumed. Supporting evidence was provided from 
experiments by Conca and Wright (1990 [101582]), who determined De values for K+ ions for a 
variety of water contents and grain sizes on four types of angular crushed gravel. For volumetric 
water contents ranging from 0.5% to 6%, the De ranged from 1014 m2/s to 1011 m2/s, i.e., the 
dependence was much stronger than what could be expected from the linear relationship between 
De and Sw. The linear relationship assumed in this Model Report results in more conservative 
transport estimates because diffusion from the fractures into the matrix is reduced. 

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6.1.2.5 Solubility 
The concentration of any radionuclide (released from the stored radioactive wastes at the 
repository) in the water cannot exceed the radionuclide solubility limit, unless suspended 
colloids are involved. Limitations to radionuclide solubility in the water infiltrating the 
repository constitute the first barrier to transport and can reduce the extent of radionuclide 
migration by limiting the available source. 
The solubilities of the radionuclide of interest are reported in BSC (2001 [160828], Section 6). 
The lower solubility of many radionuclides can lead to slower and continuous release over time 
at the outer boundaries of engineered barrier systems surrounding the radioactive wastes because 
the source is not exhausted. For example, the solubility of 237Np is sufficiently low to extend the 
period of its release to tens of thousands of years (Viswanathan et al. 1998 [134579], p. 273). 
Note that, by using relative concentrations, radionuclide solubility is not explicitly accounted for 
in this Model Report. 
6.1.2.6 Colloids 
Colloids are fine particles, between 0.001 and 1 m in diameter, that become suspended and are 
transportable in a moving liquid. The generation and mobilization of colloids are considered 
important issues in contaminant transport, particularly the transport of radioactive true (intrinsic) 
colloids (e.g., colloidal Pu(IV) and Pu(V)) and the colloid-assisted transport of radioactive 
species (e.g., 239Pu, 237Np, 243Am, and 247Cm from high-level radionuclide wastes, or 137Cs, 90Sr, 
and 60Co from low-level radioactive wastes, see BSC (2001 [160828], Section 6)) sorbed on 
pseudocolloids (e.g., naturally occurring clay colloids). See Sections 6.1.3.3 to 6.1.3.6 for a more 
detailed discussion. 
6.1.2.7 Perched Water 
Perched water is defined as a saturated zone located at a higher elevation than the static water 
table, to which it is not directly connected. Perched water usually occurs where low permeability 
horizons do not permit the rapid downward flow of water. Such bodies have been reported at 
several locations in UZ boreholes (Wu et al. 1999 [117167]). The presence of perched water has 
implications for the travel times and flow paths of water and radionuclides through the UZ. 
The majority of the perched-water bodies detected in the UZ boreholes were observed in 
formations overlaying relatively impermeable matrix material, such as the TSw basal vitrophyre 
(a glassy cooling unit). Although the vitrophyre is extensively fractured, many of the fractures 
have been filled with zeolitic material, thus limiting flow. A portion of the Calico Hills 
formation has been extensively altered to zeolites, creating perched-water bodies (Bodvarsson et 
al. 1999 [120055], pp. 1415). The blockage of fracture flow which occurs below these perchedwater 
bodies can lead to lateral diversion of radionuclide migration if the percolation flux is 
sufficiently large. 
Three perched-water models, namely no perched water, perched-water model #1 (flow through 
the perched water), and perched-water model #2 (flow bypassing the perched water) have been 
proposed in BSC (2003 [163045], Sections 6.2.2 and 6.2.5). The effects of each of these 

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perched-water models on radionuclide transport will be investigated in the 3-D site-scale 
simulations discussed in Section 6.15. 
6.1.2.8 Daughter Products 
Chain-decay adds another layer of complexity because of the need to account for the transport of 
the daughter products, i.e., the new radionuclides created from the decay of a parent 
radionuclide. The daughter products may have significantly different transport behavior than the 
parent radionuclide. Thus, the migration and fate of all the important members of the decay chain 
must be considered, rather than just the parent radionuclide. 
6.1.2.9 Effect of Heat on Transport 
Radionuclide transport may also be influenced by the heat generated by the decaying radioactive 
waste, which affects the ambient hydrological and chemical conditions and can thermally alter 
the rock near the repository. For example, if the zeolitic layers below the repository horizon are 
thermally altered, the sorption of radionuclides is reduced. In addition to the thermal effect on 
the flow field and radionuclide sorption coefficient, temperature also enhances diffusion by 
increasing Brownian motion. This effect is quantified by an increase in the D0 of radionuclides. 
The temperature-dependent D0 is described by the following equation (Robin et al. 1987 
[123119], pp. 11051106): 
2 1 
0 0 
T T T 
D 
T 
D 
.. 
. 
.. 
.  
= .. 
. 
.. 
.  
where T is the absolute temperature and  is the viscosity of water. 
The effect of temperature on sorption has been discussed in BSC (2001 [160828], Section 6.4.6). 
In general, an increase in temperature leads to increased sorption of cationic species and 
decreased sorption of anionic species. In addition to theoretical predictions, BSC (2001 
[160828], Section 6.4.6) includes a discussion of experimental data that show an increase of 
sorption by an order of magnitude when temperature increases from 25C to 75C. 
Temperatures in the UZ increase naturally with depth because of the geothermal gradient. 
Additionally, heat from the stored waste is expected to lead to higher temperatures over a large 
volume of the UZ for as long as 100,000 years (BSC 2003 [162050], Section 6.5). The combined 
effect of higher temperatures is increased retardation of the radionuclides because of (a) 
increased diffusion from the fractures into the matrix and (b) increased sorption. The assumption 
of isothermal 25C conditions in the studies of the present Model Report reflects a conservative 
approach and yields results that describe the worst-case scenario. 
6.1.3 Important Transport Issues 
6.1.3.1 Measurements of Kd Values 
The sorption behavior of radionuclides is usually described by the distribution coefficients (Kd), 
which quantifies the partitioning of radionuclides between the solid and aqueous phases under a 
linear equilibrium isotherm. Most of the Kd values are obtained from batch experiments using 

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crushed rock. Effective Kd values obtained from batch experiments involving high concentration 
solutions will tend to underestimate the field Kd values if (a) the expected field concentrations 
are low and (b) nonlinear and/or kinetic sorption are involved (see discussion in Section 6.1.2.3, 
this Model Report). Conversely, batch experiments using crushed rock samples may 
overestimate the Kd values (compared to intact rock samples and for the same solute 
concentration) if kinetic effects are involved and the contact time is short, but the difference in 
the Kd estimates from the two sample types vanish for sufficiently long contact times. Crushing 
of the material creates new contact surfaces and also increases the radionuclide accessibility to 
pores that may not contribute to sorption to intact rocks. Comparison of the Kd values obtained 
from batch sorption experiments and from through-diffusion experiments (which involve 
relatively large samples) show significant differences, which are attributed to differences in the 
surface area of the samples and the water/solid ratio. 
A detailed discussion of sorption of important radionuclides onto various UZ rocks, and a listing 
of the corresponding Kd values, can be found in Triay et al. (1997 [100422], p. 181). Note that 
the Triay et al. (1997 [100422], p. 181) study involved analysis of laboratory data, a large 
portion of which are included in the Kd determination discussed in this Model Report (see 
Attachments I and II) is based. 
Bradbury and Stephen (1986 [122792]) investigated the sorption of 85Sr, 85Tc, 125I, and 137Cs 
onto Darley Dale sandstone samples. Comparing Kd values obtained from batch (using <0.1 mm 
and 12 mm) and diffusion-sorption experiments (using disks of 25 mm in diameter and about 5 
mm in thickness), they determined that crushed rock tests can overestimate sorption by as much 
as one or two orders of magnitude. They concluded that the magnitude of the difference in the 
value of Kd depends on the radionuclide, its concentration, the rock, the water/solid ratio, and the 
particle size distribution in the batch tests. 
Holtta et al. (1997 [122832]) studied the effect of specific surface area on the sorption of 22Na, 
45Ca, and 85Sr on crushed crystalline rocks of six size fractions (0.0710.15, 0.150.20, 0.20.3, 
0.30.85, 0.851.25, >1.25 mm). Sorption of 22Na, 45Ca, and 85Sr on unaltered tonalite and mica 
gneiss was slight and exhibited virtually no dependence on the fraction size. Considerably higher 
sorption of 22Na and 85Sr occurred on altered tonalites of smaller fractions because of their larger 
specific surface areas. Kd values from thin sections (0.030 mm in thickness) were in good 
agreement with those obtained from batch experiments, possibly because the thin-section 
thickness is within the range of the crushed-rock size fractions. 
Johansson et al. (1997 [123001]; 1998 [123004]) conducted batch sorption tests of alkali- and 
alkaline earth metals (22Na, 137Cs, 45Ca, 85Sr, and 133Ba) using six crushed size fractions 
(0.045-0.090, 0.090-0.25, 0.250.5, 0.51, 12, 24 mm) of medium-grained Aspo diorite and 
fine-grained granite. The Kd increased with decreasing particle size and differed by 
approximately one order of magnitude between the largest and smallest particle (because of 
different specific surface areas). They also determined that the best agreement between the 
Kd values from diffusion experiments (using 20 mm rock disks) and from batch experiments was 
observed for the largest size fractions (2-4 mm) in the batch studies. They explained this 
observation by suggesting that, unlike the smaller fractions, the largest size fraction involved a 
large number of whole mineral grains. 

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Tachi et al. (1998 [134571]) studied the sorption and diffusion behavior of Se in Tono tuffs in 
batch experiments (using crushed rock with sample sizes ranging between 0.075 and 0.355 mm) 
and in through-diffusion experiments (using samples 30 mm in diameter and 5 mm in thickness). 
The Kd values from the diffusion experiments were one order of magnitude lower than those 
from the batch experiments. Correcting for the difference in the specific surface areas could not 
fully account for the Kd discrepancy. Mercury porosimetry suggested that the differences were 
caused by sorption in microscopic pores (less than 20 nm in diameter) in the crushed rock 
samples. When the contribution of these pores to sorption was not considered, the Kd values from 
the batch sorption experiments and from the diffusion experiments were consistent. 
The effect of the specific area surface of ground rock samples on the sorption of 137Cs, 85Sr, and 
237Np was studied in nine size fractions (< 0.038, 0.0380.063, 0.0630.075, 0.0750.106, 
0.1060.25, 0.250.50, 0.51, 12, 24 mm) of devitrified Topopah Spring tuff and zeolitized 
Calico Hills tuff (Rogers and Meijer 1993 [123127]). They showed that the grinding process 
does not influence the sorption behavior for particle sizes larger than about 63 m. They also 
indicated that ground samples must be washed carefully to remove very fine particles generated 
during the grinding process, which could lead to irreproducible or anomalously high Kd values. 
6.1.3.2 Solute Sorption Issues 
6.1.3.2.1 Potential Sorption of Anions 
Adsorption of negatively charged ionic species from the aqueous phase onto mineral substrates 
is likely to occur whenever the mineral surface exhibits a net positive surface charge. Under 
typical ambient conditions in shallow systems (saturated or unsaturated), most rock-forming 
alumino-silicate minerals have negatively charged surfaces. It is possible, however, for these 
surfaces to become positively charged in the presence of acids or if the surfaces dry out and only 
residual oligolayers of water remain. 
The transition from negatively to positively charged surface occurs at the point of zero charge 
(PZC), where the surface charge is zero and is usually expressed in terms of pH. The PZC differs 
from one mineral to another, but for most rock-forming minerals it is less than 4. However, in 
some materials (such as iron oxides, sulfides, and some organic matter), the PZC can be as high 
as 8 or 9. 
These minerals display a tendency to adsorb anionic species such as I and 4 TcO- under ambient 
water table conditions. For example, the extent of 3
4 AsO - sorption on hydrous ferric oxide is a 
function of pH (Dzombak and Morel 1990 [105483], pp. 200204). The edge sites on clays are 
also reported to contain positive sites. Under low pH conditions (e.g., pH = 5), significant 
sorption of anionic tracers occurs in systems with high concentrations of iron oxides and 
kaolinite (Boggs and Adams 1992 [122790]; Seaman 1998 [134563]). 
Despite the availability of positively charged adsorption sites, 129I and 99 
4 TcO- are in 
competition with other anionic species in solution, such as 24 
SO - , 3 NO- , OH, etc., which are 
usually present in concentrations an order of magnitude larger than either 129I or 99 
4 TcO- . 

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Because of competition, their effective sorption is minimal. There are, however, exceptions, and 
these should be taken into account when evaluating their retardation. 
Kaplan and Serne (1995 [123010]) determined that iodine sorbed on all Hanford sediments, and 
its Kd ranged from 0.7 to 15 mL/g, with a median value of 7 mL/g. This finding could have 
significant implications for radionuclide transport. Positively charged adsorption sites may exist 
on the edges of 2:1 clays such as smectite and illite, on Al- and Fe-oxide surfaces, and on 1:1 
clays such as kaolinite. Anions may sorb onto these locally positive-charged sites, even though 
their numbers are limited under typical pH conditions. 
Note that the study of Kaplan and Serne (1995 [123010]) involved extremely low iodine 
concentrations (approximately 12 parts per trillion (ppt)). Therefore, only a small number of 
positively charged sites would be needed for the sorption of a measurable portion of the 
dissolved iodine. Had an initially larger concentration been used in these experiments (e.g., 1 
ppm), it is reasonable to expect that a small fraction of iodine would have sorbed onto the solid 
phase, resulting in practically undetectable iodine sorption. It must be pointed out that in a 
low-level waste plume 129I concentrations are expected to be in the ppt range (Kaplan and Serne 
1995 [123010]). 
Similarly, significant sorption of technetium could occur in soils containing considerable 
amounts of natural organic matter, which tends to sorb anionic species and could reduce 
technetium to its +4 oxidation state, causing precipitation and/or sorption (Kaplan and Serne 
1995 [123010]). In the Yucca Mountain UZ, however, conditions are both oxidizing and 
deficient in organic matter. Therefore, significant sorption is unlikely to occur until more 
reducing conditions are encountered within the saturated zone. 
Currently, there is no information on the occurrence and extent of localized positively charged 
sorption sites in Yucca Mountain tuffs. But the existence of such sites cannot be ruled out. Clays 
and oxides can potentially contribute to positively charged sites. Smectite is a significant 
constituent of some unwelded tuff horizons at Yucca Mountain. Although hematite and illite are 
present in minor or trace amounts in the unwelded tuffs, hematite is widely distributed in the 
matrix of the devitrified units. Smectite and hematite also coat fracture walls in Yucca Mountain 
tuffs (BSC 2001 [160828], Section 6). No estimate exists of the potential effects of such sites on 
the site-scale transport of radioactive anionic species. 

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6.1.3.2.2 Solute Size Effects 
Another aspect of technetium and iodine transport is the exclusion effect resulting from their 
relatively large ionic radius and low charge density. Technetium travels faster than tritium in 
both diffusion and column studies (BSC 2001 [160828], Section 6). This is attributable to the 
large size of the pertechnetate anion, which is excluded from tuff pores. In contrast, in 
crushed-rock column experiments, anion-exclusion effects for pertechnetate are essentially 
negligible, except in the case of technetium transport through zeolitic tuffs in the J-13 well 
water. In this case, the anion-exclusion effect was small but measurable (BSC 2001 [160828], 
Section 6). 
It should be emphasized that 3H+ can sorb weakly onto tuffs, as can 4 TcO- The faster 
4 TcO- breakthrough curves (compared to those for 3H+) reported in BSC (2001 [160828], Section 
6.5.3.3) should not be necessarily interpreted to indicate 4 TcO- size-exclusion, but could also 
denote larger 3H+ sorption. This is supported by the slight retardation of 3H2O reported by Hu 
and Brusseau (1996 [122849]). The apparent sorption is in essence ion-exchange and has been 
postulated to occur via OH exchange on the clay lattices. 
6.1.3.3 Colloidal Behavior 
Radioactive true colloids or radionuclides adsorbed onto pseudocolloids can be transported over 
significant distances (McCarthy and Zachara 1989 [100778], pp. 496497). The significant 
migration of strongly sorbing Pu and Am (more than 30 m) from a low-level nuclear waste site at 
Los Alamos National Laboratory through unsaturated tuff over a period of approximately 30 
years is attributed to colloid and/or colloid assisted transport, a hypothesis confirmed by 
laboratory experiments (Buddemeier and Hunt 1988 [100712], p. 536). Using the 240Pu/239Pu 
isotope ratio to fingerprint the source of Pu in the water table, Kersting et al. (1999 [103282], pp. 
5659) recently demonstrated that the soluble (ionic) Pu is practically immobile in the 
subsurface of the Nevada Test Site (NTS) because of its strong sorption, but can be transported 
over significant distances (1.3 km over a 30-year period) in a colloidal form. 
Colloids are very fine particles (such as clay minerals, metal oxides, viruses, bacteria, and 
organic macromolecules) that range in size between 1 and 10,000 nm (McCarthy and Zachara 
1989 [100778], pp. 497498) and have high specific surface areas (~300 m2/g). Their chemical 
behavior is dominated by surface processes (EPRI 1999 [113923], p. 3-1), and can have a high 
sorptive capacity for contaminants. Colloids are deposited on porous and fractured media by 
surface filtration, straining filtration, and physical-chemical filtration. Colloid transport differs 
from solute transport because the colloidal particle interactions (e.g., flocculation), mechanical 
clogging effects, and surface reactions (e.g., deposition or attachment) are substantially different 
from solute processes and phenomena. 
A complete description of colloid-facilitated radionuclide transport requires consideration of a 
large number of processes (EPRI 1999 [113923], pp. 4-5 to 4-6), including advection, diffusion, 
colloid generation, colloid stability, colloid-solute-matrix interactions, affinity of colloids for the 
gas-water interface, colloid filtration (surface and straining), and kinetically controlled 
physical-chemical filtration. 

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6.1.3.3.1 Colloid Types and Classes 
The analysis in BSC (2003 [161620], Section 6.3.1) identifies the following types of colloids 
based on their origin and characteristics: 
(a) True (or intrinsic) colloids are generated from a solute when its concentration exceeds 
its solubility (Saltelli et al. 1984 [117338]). Such true Pu(IV) colloids have been 
produced by the agglomeration of hydrolyzed Pu(IV) ions under acidic conditions 
(EPRI 1999 [113923], p. 3-2). When immature, actinide true colloids display 
hydrophilic properties, but become hydrophobic with increasing age. 
(b) Waste form colloids are formed from the nucleation of colloids from waste form 
dissolution and from spallation of colloid-sized waste from alteration products. 
Waste form colloids are believed to be one of the most significant contributors to 
radionuclide transport in the UZ. 
(c) Pseudocolloids are all other colloidal particles, i.e., natural colloids that can be 
inorganic (e.g., clay, iron oxyhydroxides, silica) or organic (microbes and humic 
acids (Ibaraki and Sudicky 1995 [109297], p. 2945). Pseudocolloids become 
radioactive when solute actinides sorb onto them. (Note that in BSC (2003 [161620], 
Section 6.3.1) only radioactive pseudocolloids are referred to as such, while nonradioactive 
ones are referred to as seepage/groundwater colloids). 
In terms of mathematical description of their radioactive and transport behavior, these colloids 
are classified as follows: 
Class I: In this class the entire non-aqueous component of the colloidal particle is radioactive. 
True colloids and waste form colloids are Class I colloids. It is not generally known if decayinduced 
recoil in such colloids is sufficiently strong to cause ejection of daughters and shrinkage 
of the colloidal particle, if the colloidal size is maintained but its density is reduced after 
daughter ejection, or if the daughters remain trapped within the colloidal structure. If there is 
ejection, then either the colloidal size or the density decreases at a rate one-third that of decay 
(leading to larger diffusion). 
Class II: In this class only a portion of the colloidal particle (usually a very small one) is 
radioactive. This class includes radioactive pseudocolloids, in which the actinide is irreversibly 
sorbed onto the colloid or incorporated into the colloidal structure (e.g., through ion exchange). 
In this case, the actinide remains confined onto the colloid and does not exchange mass with its 
surroundings (i.e., the liquid phase or adjacent colloids). If the time of actinide production is the 
same (a valid approximation in YM studies, especially in radionuclides with long half lives), 
then the colloidal particle concentration in the liquid and solid phases, and the radionuclide 
concentration on each colloid are independent of each other and can be computed separately. 
Radioactive decay does not change the dimensions of Class II colloids because, even in the event 
of daughter ejection due to recoil, the actinide mass represents a very small portion of the total 
colloid mass and the colloidal structure is maintained. Compared to the transport of Class I 
colloids of the same size with decaying sources, Class II colloids result in lower radioactivity 

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concentrations (because actinides are a small portion of the total mass), but the relative 
concentrations (with respect to that at the release points) are the same. 
Class III: Class III includes radioactive pseudocolloids in which actinides are reversibly 
sorbed onto the underlying natural colloid. As in Class II colloids, only a small portion of the 
colloidal particle is radioactive. In this case, the actinide remains is not confined onto the colloid, 
but can exchange mass with its surroundings (i.e., the liquid phase or adjacent colloids). For the 
same reasons discussed in Class II colloids, radioactive decay does not change the dimensions of 
Class III colloids. However, determination of the radioactivity concentration is much more 
complex in Class III colloids than in Class I and II colloids (the transport equations of which can 
be linearized) because the corresponding equations are nonlinear (see Equation 6-17, Section 6- 
2). 
A fourth class of colloids, Class IV colloids, includes all non-radioactive colloids, and can 
belong to any colloid type (true colloids, waste form colloids, or pseudocolloids). Such colloids 
are not considered in this study of UZ transport. The study of transport of these colloids is 
identical to that of the colloidal particle of Class II hydrates. More details on the mathematical 
treatment of the transport of colloids can be found in Section 6.2 (present Model Report). 
6.1.3.3.2 Colloid Generation and Stability 
The formation of mobile colloidal suspensions in the subsurface is attributed to a number of 
mechanisms: (1) matrix dissolution caused by changes in pH or redox conditions; (2) 
supersaturation with respect to the inorganic species; (3) disruption of the mineral matrix by 
large changes in the flow regimes due to injection, pumping, or large episodic rainfall 
infiltrations; (4) release and movement of viruses and bacteria; and (5) formation of micelles 
from the agglomeration of humic acids (Abdel-Salam and Chrysikopoulos 1995 [146647], pp. 
199200). Buddemeier and Hunt (1988 [100712], p. 536) indicate that submicrometer colloids 
can easily be released from mineral and glass surfaces that are chemically, hydrodynamically, or 
mechanically stressed. 
Colloid stabilization/destabilization include steric stabilization by mechanisms such as organic 
coating of inorganic colloids, and the effects of pH and ionic strength on coagulation and 
precipitation. The stability of colloid suspension is very sensitive to changes in ionic strength 
(EPRI 1999 [113923], p. 4-6). 
6.1.3.3.3 Colloid Deposition 
Colloid deposition (physical-chemical filtration) during saturated flow through a porous medium 
is commonly assumed to occur in two steps: (1) transport of colloids to matrix surfaces by 
Brownian diffusion, interception, or gravitational sedimentation (i.e., colloid-matrix collision) 
and (2) attachment of colloids to matrix surfaces. The attachment efficiency (i.e., the fraction of 
collisions resulting in attachment) is strongly influenced by interparticle forces between colloids 
and matrix surfaces, such as van der Waals and electric double-layer interactions, steric 
stabilization, and hydrodynamic forces (Kretzschmar et al. 1995 [123019], p. 435). Kretzschmar 
et al. (1997 [123029], p. 1,129) demonstrated that colloid deposition generally follows a 

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first-order kinetic rate law and experimentally determined the corresponding collision 
efficiencies. 
6.1.3.3.4 ColloidContaminantMatrix Interactions 
Colloid attachment to the host rock is strongly dependent on electrostatic interactions. Once 
attached, colloid detachment (declogging) is generally slow to irreversible. Sorption of 
radionuclides on colloids is controlled by a range of chemical processes such as ion exchange, 
surface complexation, and organic complexation (EPRI 1999 [113923], p. 49). 
If sorption of metal ions onto colloids is assumed to follow an equilibrium isotherm, metals are 
stripped very fast from the colloids when these enter a clean part of the porous medium. This 
approach was incapable of explaining the long transport distances observed in field experiments 
(van de Weerd and Leijnse 1997 [109249], p. 246). The problem was addressed by assuming (a) 
kinetic sorption of radionuclides onto the humic colloids and (b) kinetic colloid deposition (van 
de Weerd and Leijnse 1997 [109249], pp. 245, 255). The sorption of dissolved ionic Pu(IV) onto 
hematite, goethite, montmorillonite, and silica colloids in both natural and carbonate-rich 
synthetic water table was reported to be fast (BSC 2001 [160828], Section 6). Under equilibrium 
conditions, the Kd values of Pu(V) was about 100 mL/g for hematite and montmorillonite 
colloids. These very large values indicate that iron oxide and clay colloids in the water table can 
significantly enhance the transport of 239Pu. Very large Kd values of actinide sorption are also 
confirmed in BSC (2003 [161620], Section 6.3.3.1). The values are so large that they can 
support an approximation of treating such radioactive Class III colloids as Class II colloids. 
6.1.3.3.5 Colloid Migration in Macroporous and Fractured Systems 
In conducting infiltration experiments with intact structured sandy loam cores using two types of 
colloidal suspensions, Jacobsen et al. (1997 [122995], pp. 185186) observed significant 
transport of clay and silt colloid particles through the macropores. Macropores can enhance the 
transport of colloids because all types of filtration are less pronounced in large pores, and the 
large water velocities can lead to increased detachment (as the large hydrodynamic forces can 
overcome the colloid-grain bonding forces). 
In a study of colloid-facilitated transport of radionuclides through fractured media, Smith and 
Degueldre (1993 [144658], pp. 143, 162163) determined that the assumption of fast, linear, and 
reversible radionuclide sorption onto colloids is non-conservative. They observed that the time 
for radionuclide desorption (days or weeks) significantly exceeded the time for sorption (seconds 
or minutes). Such radionuclide-laden colloids can migrate over long distances in macropores and 
fractures, and the larger colloids exhibit little retardation because their size prevents them from 
entering the wall-rock pores. The Smith and Degueldre (1993 [144658], pp. 143, 162163) study 
concluded that the transport of radionuclides sorbed irreversibly on to colloids depends strongly 
on the extent of colloid interaction with the fractures. 
Vilks and Bachinski (1996 [109252], pp. 269, 272278) studied particle migration and 
conservative tracer transport in a natural fracture within a large granite block, with overall 
dimensions of 839060 cm. Flushing experiments showed that suspended particles as large as 
40,000 nm could be mobilized from the fracture surface. The mobility of suspended particles 

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with diameters of 1,00040,000 nm was significantly less than that of colloids (<90 nm). They 
observed that the conservative tracer lagged slightly behind the colloid front, but colloid 
mobility was significantly reduced when the average water table velocity decreased. Compared 
to dissolved tracers, the migration of colloids was more affected by the flow path and flow 
direction. This tendency can have a significant effect in the fracture-dominated flow of the 
Yucca Mountain UZ. 
In field-scale colloid migration experiment, Vilks et al. (1997 [109254], pp. 203, 212-213) 
showed that silica colloids as small as 20 nm can migrate through open fractures over distances 
of 17 m, when a colloidal suspension was injected at average flow velocities of 1.6 and 2.9 m/h 
(orders of magnitude higher than the natural flow rates at the site). Based on the analysis of the 
results of the study, they also suggested that although colloid migration appeared to behave 
conservatively, colloids may have followed different pathways than dissolved conservative 
tracers. 
6.1.3.4 Colloidal Behavior in Unsaturated Media 
Most of the available literature focuses on the behavior of colloids in saturated media. The 
behavior of colloids in unsaturated media (BSC 2003 [162729]) is a relatively new area of study 
and has significant additional complexity. 
6.1.3.4.1 Filtration as a Function of Water Saturation 
Colloid filtration is a physical retardation process. Wan and Tokunaga (1997 [108285], p. 2413) 
distinguish two types of straining: conventional staining (if the colloid is larger than the pore 
throat diameter or the fracture aperture) and film straining (if the colloid is larger than the 
thickness of the adsorbed water film coating the grains of the rock). 
Wan and Tokunaga (1997 [108285], pp. 2413, 2419) developed a conceptual model to describe 
colloid transport in unsaturated media as a function of water saturation Sw. If the rock Sw exceeds 
a critical saturation value Sc, colloids move through the system entirely within the aqueous 
phase. For Sw < Sc, colloids can only move in the thin film of water that lines the grain 
boundaries, and colloid transport through the water film depends on two parameters: the ratio of 
the colloid size to the film thickness, and the flow velocity. Temporal variations in the Sw in the 
subsurface profile and in the infiltration rate can lead to strongly nonlinear colloid mobility in 
the vicinity of Sc. 
McGraw and Kaplan (1997 [123043], p. 5.2) investigated the effect of colloid size (from 52 to 
1900 nm) and Sw (from 6 to 100%) on colloid transport through unsaturated media in Hanford 
sediments. They showed a very strong dependence of filtration on the colloid size under 
unsaturated conditions. At a volumetric water content of 6%, (the expected water content in the 
Hanford vadose zone), colloid removal increased exponentially with colloid size. The decrease 
in colloid mobility at low volumetric contents was attributed to resistance due to friction (as the 
colloids were dragged along the sand grains). Colloid retardation increased as the ratio between 
the water film thickness and colloid diameter decreased. 

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6.1.3.4.2 GasWater Interface 
Under unsaturated conditions, colloid transport may be either inhibited or enhanced (compared 
to saturated conditions) because of the presence of the air-water interface. Wan and Wilson 
(1994 [114430], pp. 857, 863) determined that retention of both hydrophilic and hydrophobic 
colloids increased with the gas content of the porous medium. They showed that colloids 
preferentially concentrate in the gas-water interface rather than on the matrix surface. This 
tendency increases with the colloid surface hydrophobicity or contact angle, with hydrophobic 
colloids having the strongest affinity for the gas-water interface. 
The implications of this colloid behavior are important. Colloid affinity for the gas-water 
interface may retard their transport through the unsaturated zone. Conversely, if the subsurface 
conditions permit the stability and migration of bubbles, colloid transport may be enhanced. 
6.1.3.5 Colloids at Yucca Mountain 
The available data on colloid occurrence and concentrations at the Yucca Mountain site are 
limited, and pertain to saturated zone studies. There is no published information on colloids in 
the unsaturated zone. The current state of understanding is that (a) the natural colloid 
concentrations in native waters at the Yucca Mountain site are in the 1061010 particles/mL 
range, and (b) waste-form colloids will be the dominant colloidal species of concern to transport 
studies (Kung 1999 [146992], pp. L-I-5, L-8-3 to L-8-5). This conclusion is supported by BSC 
(2003 [161620], Section 6), which includes the most recent information on colloid occurrence, 
generation, stability, properties and transport behavior. 
Additional information from nearby sites, however, cannot be ignored. Preliminary results from 
a survey of the water table from the Nevada Test Site (NTS) have shown that, in the Pahute 
Mesa, drainage (both on and off the NTS) has colloidal particle (>3 nm in diameter) loadings of 
0.86.9 mg/L. Such relatively high concentrations can explain the observed transport of strongly 
sorbing radionuclides over significant distances, particularly because the ionic composition of 
the NTS water table is not expected to promote the coagulation of clay colloids (Buddemeier and 
Hunt 1988 [100712], p. 537). This is because NTS water table is oxygenated and low in organic 
matter, and a substantial fraction of the colloidal material is composed of stable natural minerals 
(Buddemeier and Hunt 1988 [100712], pp. 543544). 
In addition to natural colloids, anthropogenic colloids may be created from the waste itself or 
from repository construction and sealing materials. Waste- and repository-derived colloids at 
Yucca Mountain are likely to include organic colloids, iron oxyhydroxides, and aluminosilicate 
colloids (EPRI 1999 [113923], p. 2-2, 6-22). In a 50-month experiment involving simulated 
weathering of a high-level nuclear waste glass, spallation and nucleation were identified as the 
main mechanisms of colloid genesis (Bates et al. 1992 [100704]). The created colloids were 
identified as inorganic. The same study determined that Pu and Am released from waste were 
predominantly in the colloidal, rather than in the dissolved, form. 
6.1.3.6 Impact of Colloids on Radionuclide Transport in Yucca Mountain 
EPRI (1999 [113923], pp. xvxvii and 2-2) indicated that it is important for the Yucca Mountain 
Project (YMP) to consider the migration of radionuclides, and to assess the potential role of 

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colloids on radionuclide transport, within both the saturated and the unsaturated systems. 
Furthermore, EPRI (1999 [113923], pp. 4-6 to 4-7) identified the following key areas of 
uncertainty for further study: 
1. Colloid-matrix interactions. 
2. Thermodynamic data for certain radionuclides and kinetic data to describe virtually all 
rate-dependent reactions. 
3. Representation of the hydrological system: colloid transport differs from the transport 
of conservative tracers and is influenced by the details of the permeability structure, 
such as fracture geometry and the hydraulic conditions within the fracture zones. 
4. The effects of partially saturated conditions on colloid transport. 
6.1.4 Important Points for Consideration in Colloid Transport 
The assessment of the potential role of colloids in the transport of radionuclides at Yucca 
Mountain is particularly challenging for the reasons discussed in the previous sections, and is 
further complicated by the following factors: 
1. Different types of colloids (minerals, organics, microbes, and polymeric actinide 
colloids) are involved, with substantially different characteristics and properties (e.g., 
hydrophobicity and surface charges) that strongly affect their behavior in the 
subsurface. 
2. Colloid generation, stability, size distribution, and concentration are dynamic. 
Knowledge about the temporal and spatial distributions of colloid populations in the 
different hydrogeologic units of the UZ is difficult to obtain. Changes in the ionic 
strength of the aqueous solution (e.g., when percolating water in an episodic infiltration 
event encounters resident pore water) can affect colloid stability. There are also 
uncertainties about the colloid stability in the aqueous phase of the UZ and about the 
colloid generation from mineral-coated fracture walls (given the predominance of 
fracture flow in the UZ). 
3. Measurements of colloid concentration in the UZ are difficult. Because of the low 
concentrations and low saturations in the UZ, the determination of colloid 
concentration in pore water is challenging, and serious questions arise about sample 
representativity and integrity. 
4. The concentration of waste-form colloids is a key uncertainty. There is evidence to 
suggest that the low concentration of natural colloids in the Yucca Mountain UZ will 
not lead to significant colloid-assisted transport, and that waste-form colloids will be 
the dominant colloidal transport problem (Kung 1999 [146992], pp. L-1-5, L-8-3 to L- 
8-5). Thus, there is a need for reliable estimates of the types and generation rates of 
waste-form colloids. Currently, there is considerable uncertainty on this subject (EPRI 
1999 [113923], p. 6-7). 

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Important processes to consider are: 
6.1.4.1 Colloid Diffusion 
Colloids diffuse more slowly than dissolved species because of their larger size (see Section 
6.2.5, Equation 6-23). For the largest colloids, diffusion is approximately three orders of 
magnitude slower than that for molecular species (Nuttall et al. 1991 [123103], p. 189). For 
example, the diffusion coefficient D0 of a 0.1 m colloid at 20C is 4.2910-12 m2 /sec (see 
Equation 6-23 in the present Model Report), while the D0 of -
r B is 2.0810-9 m2 /sec (Cussler 
1984 [146653], p.147). 
6.1.4.2 Pore Exclusion 
Using mercury porosimetry, Roberts and Lin (1997 [101710], pp. 577578) determined that the 
average pore diameters of welded and densely welded TSw tuff samples were 53.1 nm and 19.7 
21.4 nm, respectively. These extremely small pores are certain to exclude a significant 
proportion of colloids. It is possible for colloids to accumulate on the fracture walls and thus 
clog the matrix pores open to the fracture. This can lead to reduction in the matrix permeability 
and in the colloid diffusion into the matrix. Pore exclusion is not expected to be significant in the 
fractures, and colloids can travel significant distances in the fractures (especially given the 
limited diffusion into the matrix). 
6.1.4.3 Role of Air-Water Interface 
The affinity of colloids for the air-water interface depends on their hydrophobicity and 
electrostatic charge. Hydrophilic colloids, such as mineral fragments, have a low affinity for the 
interface, in contrast to hydrophobic colloids (such as organic colloids and microbes). This 
affinity increases with the positive charge on the colloids (EPRI 1999 [113923], p. 6-11). The 
flow and saturation conditions in the UZ will determine whether this will enhance or retard 
transport. Note that the potential impact of the air-water interfaces on colloid transport has not 
yet been quantified. 
6.1.5 Modeling Stipulations 
In this section we discuss the basic stipulations in the mathematical basis of the transport model, 
and we provide a short discussion of the supporting rationale. This section is structured as 
follows: 
Section 6.1.5.1 addresses the general stipulations underlying the flow component of the transport 
model of the Yucca Mountain unsaturated zone (UZ). Section 6.1.5.2 lists the assumptions of the 
transport processes. The stipulations involved in the treatment and mathematical representation 
of the fractured rocks using the dual-continuum approach are discussed in Section 6.1.5.3. 
Stipulations related to the initial and boundary conditions of the model domain are presented in 
Section 6.1.5.4. Sections 6.1.5.1 to 6.1.5.4 address issues related to large-scale 3-D numerical 
simulations. 

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6.1.5.1 Stipulations Involved in the Flow Component of the Transport Processes 
The transport phenomena and processes in the Yucca Mountain UZ have a flow component and 
a transport component, each of which are described by a set of governing equations. These 
conserve mass, energy and momentum in the system under study, while quantifying the system 
response to external mass and energy inputs and interrelationships between the various processes 
involved. 
The basic flow stipulations are consistent with those discussed in UZ Flow Models and 
Submodels (BSC 2003 [163045], Sections 5 and 6). They share identical conceptual models, 
which are stated below. 
1. The macroscopic-continuum approach is a valid concept for the description of the flow 
and transport processes in the fractured UZ rocks. 
Justification: The rationale for this approach is provided in BSC (2003 [163045], 
Section 6.1). 
Applicability: This approach is used in all numerical (i.e., 3-D site-scale) simulations 
of flow and transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No 
further confirmation is required for the purposes of this study. 
2. Darcys law is a valid model to describe the flow of gas and water in the matrix and 
fractures of the UZ. 
Justification: Given the applicability of the macroscopic continuum approach, the 
gaseous and aqueous flows under ambient conditions in the UZ are sufficiently slow to 
correspond to a Reynolds number = 10, i.e., the upper limit of applicability of Darcys 
law (Bear 1972 [156269], p. 127). 
Applicability: This approach is used in all 3-D site-scale simulations of flow and 
transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No further 
confirmation is required for the purposes of this study. 
3. Richards equation (Richards 1931 [104252]) is a valid model of unsaturated water 
flow in both the matrix and the fractures of the UZ. 
Justification: Under ambient conditions, the gas-phase pressure in the UZ is 
atmospheric, corrected for elevation. The absence of gas pressurization makes possible 
the adoption of Richards equation, because the gas phase can be neglected and the 
aqueous phase flow occurs in response to gravitational and capillary pressure 
differentials. 
Applicability: This approach is used in all 3-D site-scale simulations of flow and 
transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No further 
confirmation is required for the purposes of this study. 

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4. Relative permeabilities and capillary pressures follow the van Genuchten (1980 
[100610]) and Mualem (1976 [100599]) model and are continuous functions of the 
effective liquid and gas saturations. 
Justification: This model is consistent with the macroscopic continuum approach, has 
been successfully used to determine relative permeability and capillary pressure 
parameters from UZ rocks (matrix blocks), and is reasonable for fractures (BSC 2003 
[160240], Section 6.1). 
Applicability: This approach is used in all 3-D site-scale simulations of flow and 
transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No further 
confirmation is required for the purposes of this study. 
5. The water flow is isothermal. 
Justification: This is a reasonable approximation. The flow parameters affected by 
temperature are water density and water viscosity. Ambient temperature extremes at 
the domain boundaries are about 20C at the top and about 30C at the water table at 
the bottom (BSC 2003 [163045], Section 6.3). Between 20C and 30C, the water 
density decreases from 998.21 kg/m3 to 995.65 kg/m3 (Lide 1993 [123032], p. 610), 
i.e., the change is very small. 
The effect on viscosity is more pronounced. Between 20C and 30C, the water 
viscosity decreases from 1.002x103 Pa  s to 0.977x104 Pa  s (Lide 2002 [160832], 
p. 610), i.e., a reduction of about 20%. Although this variation is not excessive (given 
the uncertainty in the values of the UZ system hydraulic properties), its effects are 
minimized by conducting the isothermal flow simulations at 25C. 
Isothermal flow may be a less valid approximation in the immediate vicinity of the 
waste package because of the heat generated by the radioactive decay process. The 
nonisothermal flow under these conditions is the subject of another report (BSC 2003 
[162050]). 
Applicability: This approximation is used in all 3-D site-scale simulations of flow and 
transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No further 
confirmation is required for the purposes of this study. 
6. Water flow through the UZ in the numerical simulations of radionuclide transport is 
considered time-invariant (steady-state). 
Justification: This is a reasonable approximation, given the very long simulation 
periods (= 100,000 years). This approach allows the determination of the transportbehavior 
envelope by considering nine different infiltration scenarios (and, 
consequently, flow fields), and is consistent with the flow regimes discussed in BSC 
(2003 [163045], Section 6). 

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Applicability: This approximation is used in all 3-D site-scale simulations of flow and 
transport in this Model Report (Sections 6.8 to 6.20, and Section 7). No further 
confirmation is required for the purposes of this study. 
6.1.5.2 Stipulations/Approaches/Simplifications Involved in Transport Processes 
7. The individual and combined effects of diffusion (molecular and/or colloidal), surface 
diffusion, and hydrodynamic dispersion follow a Fickian model. 
Justification: Given the macroscopic continuum approach, this is a valid model (de 
Marsily 1986 [100439], pp. 228277). 
Applicability: This model is used in all studies in this Model Report (Sections 6.8 
6.20, and Section 7). No further confirmation is required for the purposes of this study. 
8. Transport occurs isothermally at 25C. 
Justification: Isothermal transport at the average ambient temperature of the UZ is 
consistent with the assumption of isothermal flow at the same temperature. The 
transport parameters affected by temperature are (a) the diffusion coefficient D0 of the 
dissolved or colloidal species and (b) the sorption parameters of the dissolved species 
or the filtration parameters of the suspended colloid. Natural temperature differentials 
in the undisturbed UZ profile occur because of the geothermal gradient. Substantial 
temperature increases over the ambient are expected after radioactive waste 
emplacement in the repository (BSC 2003 [162050], Section 6). 
An increasing temperature leads to a higher D0 value according to the relationship 
discussed in Section 6.1.2.9 of this Model Report. Based on this relationship, an 
increase in temperature from 20C (at the top of the UZ domain) to 30C (at the water 
table, i.e., the bottom of the UZ domain) leads to an increase of D0 by about 30%. 
The effect of temperature on sorption and/or filtration is less well-defined. The general 
effect of an increasing temperature is a decrease in the sorption of anionic species and 
an increase in the sorption of cationic species. Theoretical and experimental studies 
indicate an increase of the distribution coefficient Kd with temperature when sorption 
follows a linear equilibrium isotherm (BSC 2003 [162050], Section 6). 
Colloid filtration (deposition) generally follows a kinetic process (see Sections 6.2.3 
and 6.18.2 in this Model Report). Equation 6-31 in this Model Report indicates that an 
increase in temperature increases the forward filtration coefficient .+, indicating an 
increase in the filtration (deposition, clogging) rate. There is no information on the 
effect of temperature on the reverse filtration coefficient .. 
Thus, an increasing temperature in the UZ enhances diffusion (a particularly important 
mechanism in species mass transfer from the flow-dominating fractures to the matrix) 
and increases sorption and/or filtration. The cumulative effect is slower transport. The 
assumption of isothermal transport should not be viewed as an approximation of the 

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prevailing conditions in the UZ, but rather as a condition that reflects a worst-case 
transport scenario and leads to conservative estimates of radionuclide travel times to 
the water table. Investigation of the effect of water-phase changes on transport may be 
included in future revisions of the present Model Report. 
Applicability: This simplification is used in all studies in this Model Report (Sections 
6.8 to 6.20, Section 7). No further confirmation is required for the purposes of this 
study. 
9. The concentration of the radioactive solutes or colloids is at a tracer level, i.e., too low 
to have any measurable effect on the flow regime. 
Justification: Ambient tracers and radionuclides escaping from the repository are 
expected to occur at concentrations that are too low to affect the aqueous solution 
density (BSC 2003 [162050], Section 6). 
Applicability: This approximation is used in all studies in this Model Report (Sections 
6.8 to 6.20 and Section 7). No further confirmation is required for the purposes of this 
study. 
10. There is no phase change, i.e., no water evaporation and condensation. 
Justification: The rationale for this simplification is covered by the discussion in 
Stipulation (5). Water evaporation and condensation resulting from the heat generated 
by the radioactive decay of the wastes is covered by BSC (2003 [162050], Section 6), 
in which it is shown that phase changes are not expected to last longer than the first 
10,000 years after waste emplacement (i.e., a rather short time compared to the 
100,000 to 1,000,000 years covered by the studies in this Model Report) and are 
limited to a rather small volume in the immediate vicinity of the repository. However, 
investigation of the effect of water-phase changes on transport may be included in 
future revisions of the present Model Report. 
Applicability: This simplification applies to all studies in this Model Report (Sections 
6.8 to 6.20, and Section 7). No further confirmation is required for the purposes of this 
study. 
11. Filtration of colloids is limited to deep filtration, i.e., it does not affect the medium 
porosity and permeability. 
Justification: Pseudocolloids (i.e., colloidal waste forms) and natural pseudocolloids 
(such as clays) under natural conditions are present in sufficiently small concentrations 
(Kung 1999 [146992], pp. L-1-5, L-8-3 to L-8-5) to justify this simplification. This 
reference also indicates that, as a result of adverse chemical conditions (e.g., pH, ionic 
strength) in the immediate vicinity of the repository, true colloids (i.e., radionuclides 
in colloidal form) will be released in low concentrations for a long time. 

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Applicability: This simplification applies to the colloid studies in this Model Report 
(Section 6.18). No further confirmation is required for the purposes of this study. 
These stipulations allow decoupling of the flow and transport equations. Richards equation is 
first solved in the flow component of transport, followed by the sequential solution of the n 
independent tracer transport equations. 
6.1.5.3 Stipulations Involved in the Dual-Continuum Approach 
The treatment of fracture-matrix interactions is a critical issue in the simulation of flow and 
transport under the two-phase flow conditions of the fractured UZ rocks. This Model Report 
closely follows the approach of UZ Flow Models and Submodels (BSC 2003 [163045], Section 
6): 
12. The dual-permeability model is a valid approximation for flow and transport 
simulations of the fractured UZ rocks. 
Justification: In addition to its computational efficiency, this model has a strong 
conceptual basis because it describes the matrix and fractures as separate but 
interconnected gridblocks and permits flow and transport between matrix gridblocks, 
fracture gridblocks, and fractures and matrix. A more detailed discussion on the 
rationale for this assumption can be found in (BSC 2003 [162267], Section 5) 
Applicability: This approach applies to all 3-D site-scale studies in this Model Report 
(Sections 6.8 to 6.20). No further confirmation is required for the purposes of this 
study. 
6.1.5.4 Stipulations Involving Initial and Boundary Conditions 
13. In the numerical simulations the top boundary of the UZ model domain is maintained 
at spatially variable conditions of 
(a) Temporally constant gas pressure and saturation; 
(b) Temporally constant temperature; 
(c) Temporally constant infiltration rates (steady state). 
Justification: The spatial variations of the parameters reflect differences in elevation, 
climate and topography, and represent realistic approximations of the prevailing 
conditions. For sufficiently long simulation periods, temporal variations in these 
parameters tend to diminish. Moreover, at a relatively short distance below the land 
surface, such temporal variations diminish rapidly. 
Applicability: These boundary conditions are used in all 3-D site-scale studies in this 
Model Report (Sections 6.8 to 6.20). No further confirmation is required for the 
purposes of this study. 

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14. The bottom boundary of the UZ model domain in the 3-D simulations coincides with 
the water table. It is maintained at spatially variable conditions of 
(a) Temporally constant water pressure and saturation; 
(b) Temporally constant temperature. 
Justification: This is a good representation of conditions in the saturated zone, for the 
reasons discussed in the rationale for Assumption 13. 
Applicability: These boundaries conditions apply to all 3-D site-scale studies in this 
Model Report (Sections 6.8 to 6.20). No further confirmation is required for the 
purposes of this study. 
15. In the numerical studies of radionuclide transport, the boundaries of the UZ domain 
through which flow and transport occur are the top and bottom boundaries (i.e., the 
ground surface and the groundwater, respectively). No lateral flow and/or transport 
occur across any other boundaries. 
Justification: The flow and transport through the top and bottom boundaries is 
consistent with the patterns of rainfall-fed infiltration and gravity-driven flow and 
drainage. The distance between the repository and these boundaries is sufficiently 
large to justify the assumption of no lateral flow and/or transport. 
Applicability: These boundaries conditions apply to all 3-D site-scale studies in this 
Model Report (Sections 6.8 to 6.20). No further confirmation is required for the 
purposes of this study. 

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6.2 MATHEMATICAL MODEL OF TRANSPORT 
The mathematical model of the flow component in this Model Report is thoroughly discussed in 
BSC (2003 [163045], Section 6). Here we focus on the mathematical model of transport and 
discuss the implications of the various processes for radionuclide transport. 
There are eight subsections in Section 6.2. The basic mass-balance equation of solutes and 
colloids are discussed in Section 6.2.1. Section 6.2.2 focuses on the accumulation terms of the 
mass balance equation. The equations of sorption (for solutes), filtration (for colloids) and 
colloid-assisted transport of solutes are described in Sections 6.2.3, 6.2.4, and 6.2.5, respectively. 
The flux terms of the mass-balance equation (Section 6.2.1) are described mathematically in 
Section 6.2.6. Radioactive decay is discussed in Section 6.2.7, and Section 6.2.8 describes the 
equations of transport for the daughter products of radioactive decay. 
6.2.1 General Mass Balance Equations 
Following Pruess (1987 [100684]; 1991 [100413]), mass balance considerations in a control 
volume dictates that 
d 
dt 
()
Vn 
M.dV = ()
Gn
F.ndG + ()
Vn 
q.dV 
(Eq. 6-1) 
where 
V, Vn = volume, volume of subdomain n[ L3] 
M. = mass accumulation term of component (tracer) . [ML - 3] 
G, Gn = surface area, surface area of subdomain n [ L2] 
F. = Darcy flux vector of component . [ML - 2T - 1] 
n = inward unit normal vector [ L0] 
q. = source/sink term of tracer . [ML - 3T - 1] 
t = time [ T] . 
The conservation of mass for any subdomain n is given by Equation 6-1, which in 
space-discretized form assumes the form of the following ordinary differential equation: 
. . .dM. 
dt . . . 
n 
= 1 
Vn .m Anm( F.) nm + ( q.) n 
(Eq. 6-2) 
where Anm is the surface segment between elements n and m [L2] , (F.)nm is the mass flux of 
tracer . between elements n and m [M L-2 T -1], and (qi)n is the mass rate of the source/sink of 
tracer . in element n [ML - 3T - 1] . Equation 6-2 is general, and applies to solutes and colloids. 

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6.2.2 Accumulation Terms 
6.2.2.1 Equations of the Accumulation Terms 
The accumulation term M of a tracer . (solute or colloid) in a porous or fractured medium (PFM) 
is given by 
M M 
M M M 
M 
. , . , 
. , . , . , 
. 
+ 
d + + ... 
= 
F L 
c A c g A L 
s d i o l l o c r o f 
s e t u l o s r o f 
(Eq. 6-3) 
where 
ML,. = the mass of tracer . in the aqueous phase [ML - 3] 
MAg,. = the mass of solute tracer . adsorbed onto the PFM grains [ML - 3] 
MAc,. = the mass of solute tracer . adsorbed onto colloidal particles [ML-3] 
MF,. = the mass of filtered colloidal tracer . [ML-3] 
and the parameter 
. . . 
. . .
= d 
solutes for 0 
colloid III Class for 1 
C (Eq. 6-4) 
A detailed discussion on the different colloid classes can be found in Section 6.1.3.3.1 of this 
Model Report. Omitting for simplicity the . subscript, ML is obtained from 
ML = f ( Sw - Sr) . X + fSr . X (Eq. 6-5) 
where 
X = the mass fraction of the tracer in the mobile fraction of the aqueous phase [M/M] 
X = the mass fraction of the tracer in the immobile fraction of the aqueous phase [M/M] 
Sw = the water saturation [L3/L3] 
Sr = the immobile water saturation (can be set equal to the irreducible) [L3/L3] 
f = the porosity (matrix or fracture) [L3/L3] 
. = the water density [M L-3]. 
Equation 6-5 reflects the fact that solute concentrations are different in the mobile and immobile 
water fractions. Because water is very strongly bound (in electric double layers) to the PFM 
grain surface, Brownian motion is limited and solubility in the immobile water is lower than in 
the mobile water fraction. The importance of this boundary layer has been recognized by de 
Marsily (1986 [100439], p. 234), who differentiates X and X, and Moridis (1999 [117241]), who 
used the mobile fraction of water in the analysis of diffusion experiments. Using the linear 
equilibrium relationship (Moridis 1999 [117241]), 

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X = X Ki (Eq. 6-6) 
where Ki is a dimensionless mass transfer coefficient, for solutes 1 =Ki >0. Because of their 
double layers and their relatively large size (compared to solutes), colloids are expected to 
concentrate in the mobile water fraction and to be less abundant in the immobile water fraction. 
Thus, a good approximation for colloids is Ki < 1, but there is no supporting information on the 
subject. 
Substitution into Equation 6-5 then leads to 
ML = fh . X, where h = Sw - Sr + Ki Sr (Eq. 6-7) 
6.2.2.2 Implications for Transport in the UZ 
For rocks with high irreducible water saturations at the Yucca Mountain UZ, Ki<1 can lead to 
smaller h values, indicating lower accumulation in the liquid phase. Under conditions of 
steady-state release, this can result in faster breakthroughs and, consequently, shorter travel 
times to the water table. 
6.2.3 Sorption Terms 
The discussion in this section is limited to sorption onto the matrix and fractures. Sorption onto 
pseudocolloids will be discussed in Section 6.2.4. 
6.2.3.1 Equilibrium Physical Sorption 
Omitting again for simplicity the . subscript, the mass of a solute sorbed onto the PFM grains 
and following a linear equilibrium isotherm is given by 
MAg = ( 1 - f) .s F 
(Eq. 6-8) 
where 
.s = the rock density [ML - 3] ; 
F = Fp+Fc, the total sorbed mass of solute per unit mass of the PFM, [M/M] ; 
Fp = the physically sorbed mass of solute per unit mass of the PFM [M/M] ; 
Fc = the chemically sorbed mass of solute per unit mass of the PFM [M/M] ; 
Following the concepts of de Marsily (1986 [100439], p. 234) and considering that sorption onto 
the soil grains occurs as the dissolved species diffuses through the immobile water fraction 
(Moridis 1999 [117241]), the equilibrium physical sorption is described by the equation 

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X K K 
X K K 
X K K 
X K K 
F 
i 
i
i F 
i d 
p 
) ( 
. + 
. 
, ) ( ) . ( 
, ) ( . ........... 
= 
n o i t p r o s E A L m u i r b i l i u q e r i u m g n a L r o f 
1 
n o i t p r o s E F m u i r b i l i u q e h c i l d n u e r F r o f 
n o i t p r o s E L m u i r b i l i u q e r a e n i l r o f 
 
2 
1 
(Eq. 6-9) 
where Kd [M -1L3], KF [M -L3], , K1[M -1L3], and K2 [M -1L3] are sorption parameters specific to 
each solute and rock type. Of particular interest is the parameter Kd, called the distribution 
coefficient, which is the constant slope of the linear equilibrium adsorption isotherm of a solute 
in relation to the medium. The sorption of the various radionuclides in this Model Report follows 
a linear equilibrium isotherm (See Section 6.1.5.2). 
6.2.3.2 Kinetic Physical Sorption 
If a kinetic isotherm is followed, then sorption is described by equations given by 
F 
X K K 
X K K 
k 
F X K K k 
F X K K k 
t d
F d 
p 
i 
i 
L 
p i F F 
p p i d 
p 
, ) ( 
... 
- 
. + 
. ... 
, ) ( ] - ) . ( [ 
, ) ( ) d - . ( ........... 
= 
l 
n o i t p r o s P K A L c i t e n i k r i u m g n a L r o f 
1 
n o i t p r o s P K F c i t e n i k h c i l d n u e r F r o f 
n o i t p r o s P K L c i t e n i k r a e n i l r o f 
 
2 
1 
(Eq. 6-10) 
where 
, ) ( 
; ) ( 
... 
= dp 
n o i t p r o s P I L l a c i s y h p e l b i s r e v e r r i r a e n i l r o f 0 
n o i t p r o s P K L l a c i s y h p c i t e n i k r a e n i l r o f 1 
(Eq. 6-11) 
and kl, kF, and kL are the kinetic constants for linear, Freundlich and Langmuir sorption, 
respectively [T -1] (de Marsily (1986 [100439]). For dp=0, the linear kinetic expression in 
Equation 6-9 can also be used to describe the chemical process of salt precipitation. 
6.2.3.3 Kinetic Chemical Sorption 
The first-order reversible chemical sorption is represented by the linear kinetic chemical (LKC) 
model 
c c i c 
c F k X K k 
dt 
dF - + - = . (Eq. 6-12) 

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where kc
+ [M - 1L3T - 1] and kc
- [ T - 1] are the forward and backward kinetic constants, 
respectively. Note that Equation 6-11 can be used in conjunction with the physical sorption 
equations to describe combined sorption (Cameron and Klute 1977 [117172]), e.g., physical and 
chemical sorption. Combined sorption accounts for the different rates at which a species is 
sorbed onto different PFM constituents. Thus, sorption onto organic components may be 
instantaneous (LE), while sorption onto mineral surfaces may be much slower and kinetically 
controlled (Cameron and Klute 1977 [117172]). 
6.2.3.4 Implications for Transport in the UZ 
Sorption is the main mechanism of radionuclide mass removal from the transporting liquid 
phase. Nonsorbing radionuclides (such as 3H or 99Tc) will not be retarded. Strongly sorbing 
radionuclides (such as Np, Pu, U, Th, Am) will exhibit much longer arrival times to the water 
table. The transfer coefficient Ki is obviously quite important, because a Ki<1 reduces the 
radionuclide sorbed onto the particle surfaces. Thus, the larger Ki is, the more the radionuclide is 
retarded. Although this may not be significant in the case of strong sorbers, it may be important 
in less-strongly sorbing tracers. 
Also of interest is sorption onto the fracture surfaces, as opposed to the volume-base sorption in 
the matrix. Currently, no information exists on the subject. The conventional approach in 
fractures with f=1 results in zero sorption. It is possible to obtain an estimate of surface sorption 
by (a) assuming a reasonable grain size for a matrix, (b) computing the internal surface area 
(available for sorption) per unit volume of the matrix, and (c) computing the surface area of a 
corresponding fracture for the same grain size. This approach usually produces very small 
surface Kd values. 
6.2.4 Colloid Filtration Terms 
6.2.4.1 Equations of Colloid Filtration 
Colloidal particles moving through porous media are subject to filtration, the mechanisms of 
which have been the subject of several investigations (e.g., Herzig et al. 1970 [117519]). The 
mass of filtered colloids is then given by 
. . . s . = , , c F M (Eq. 6-13) 
where .c,. is the density of the colloidal particles of colloid . [ML - 3] and s. is the filtered 
concentration of the colloid expressed as volume of colloids per volume of the porous medium. 
When colloid deposition is a relatively fast process compared to the water velocity, it is possible 
to describe colloid filtration as a linear equilibrium process (James and Chrysikopoulos 1999 
[109517]). Omitting the . subscript, linear equilibrium filtration is then described by 
s = KsKi . X (Eq. 6-14) 
where Ks is a distribution coefficient [M - 1L3] . 

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Colloid filtration is more accurately described by a linear kinetic model (orapioglu et al. 1987 
[117300], pp. 269342), which can take the following form: 
s . - . = s d - . . = 
s - + 
s X X K K 
dt 
d 
p i ) ( (Eq. 6-15) 
where . [ T - 1] is a kinetic coefficient, and .+ and .- [ T - 1] are the kinetic forward and reverse 
colloid deposition rates (clogging and declogging coefficients), respectively, which are specific 
to each colloid and rock type. The term .- is commonly assumed to be zero (Bowen and Epstein 
1979 [117219]), but there is insufficient evidence to support this. As will be seen in Section 6.18 
of the present Model Report, colloid transport in the UZ is very sensitive to this parameter. The 
parameter dp is analogous to that for sorption in Equations 6-10 and 6-11, and describes the 
reversibility of filtration. 
From de Marsily (1986 [100439], p. 273) and Ibaraki and Sudicky (1995 [109297], p. 2,948), the 
following expression for the .+ coefficient can be derived: 
G u f e = .+ (Eq. 6-16) 
where e is the filter coefficient of the porous medium [ L - 1] , f is a velocity modification factor, 
u is the Darcy velocity [L T - 1] , and G is a dynamic blocking function that describes the 
variation of the PFM porosity and specific surface with s (James and Chrysikopoulos 1999 
[109517]). The factor f (1=f =1.5) accounts for the velocity of the colloidal particle flow being 
larger than that of water (Ibaraki and Sudicky 1995 [109297], p. 2,948). This results from the 
relatively large size of the colloids, which tends to concentrate them in the middle of the pores 
where the water velocity is larger than the bulk average velocity. The factor f tends to increase 
with decreasing ionic strength, but cannot exceed 1.5 because colloids cannot move faster than 
the maximum water velocity, which occurs at the middle of the pores and is equal to 1.5 the 
average pore velocity (Ibaraki and Sudicky 1995 [109297], p. 2,948). 
For deep filtration (i.e., in the case of very dilute colloidal suspensions), there is no interaction 
among the colloidal particles and no effects on the medium porosity and permeability, i.e., f is 
constant, and G=1. Note that it is possible for EOS9nT to have combined filtration, in which two 
different types of filtration (e.g., equilibrium and kinetic, or two kinetic filtrations with different 
.+ and .-) occur simultaneously. 
6.2.4.2 Implications for Transport in the UZ 
Filtration is one of the main mechanisms of radioactive colloid removal from the transporting 
liquid phase, the others being chemical destabilization (e.g., because of pH changes) and 
flocculation. Three types of filtration mechanisms may affect the transport of colloids through 
the PFM: surface filtration, straining filtration and physical-chemical filtration. Surface filtration 
occurs when particles are larger than the pores, in which case a filter cake is formed. 
Straining filtration is determined by the ratio Rd = dg/dp, where dg is the diameter of the grains of 
the porous medium and dp is the suspended particle diameter. Based on the experimental data of 

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Sakthivadivel (1969 [134556]), Rd =10 leads to cake filtration, 10 < Rd =20 corresponds to 
substantial straining filtration (permeability reductions by a factor of 715 and particles 
occupying 0.3 f), and Rd > 20 results in limited straining (only 25 % of f occupied by particles 
and permeability reductions by 1050%). Herzig et al. (1970 [117519], p. 15) indicated that little 
straining was expected when Rd > 12, and calculated that when Rd = 50, only 0.053 % of f would 
be occupied by particles. 
A detailed discussion of the physical-chemical filtration of colloids can be found in orapioglu 
et al. (1987 [117300], pp. 269342). The physical-chemical colloidal filtration by the 
porous/fractured medium incorporates three mechanisms: (a) contact with the pore walls, (b) 
colloid fixation onto the walls, and (c) release of previously fixed colloids (Herzig et al. 1970 
[117519]; orapioglu et al. 1987 [117300]). 
Contact with the pore walls and colloidal capture can be the result of sedimentation (caused by a 
density differential between the colloidal particle and the carrier liquid), inertia (deviation of 
colloidal trajectories from the liquid streamlines because of their mass), hydrodynamic effects 
(caused by a variation in the velocity field of the liquid), direct interception (caused by collisions 
with the pore walls at convergent areas) and diffusion (Brownian motion causing colloids to 
move toward pore walls or dead-end pores). 
Fixation on the pore walls occurs at retention sites that include edges between two convex 
surfaces, pore throats smaller than the colloidal size, and dead-end pores or regions of near-zero 
liquid velocity. Fixation is caused by retentive forces, which include axial pressure of the fluid at 
constriction sites, friction forces, Van der Waals forces, electrical forces and chemical forces 
(Herzig et al. 1970 [117519], pp. 4, 1117). Finally, remobilization of colloidal particles may be 
caused by a number of factors, including collision between a loosely held colloid with a moving 
particle, an increase in pressure as colloids constrict flow, and a change in external conditions. 
All three mechanisms are expected to be present in the Yucca Mountain UZ. The EOS9nT 
simulations can account for surface filtration by using a particle size versus pore size criterion, 
and by not allowing colloidal entry into media that do not meet this criterion. Straining filtration 
(pore-size exclusion) is described by using appropriate colloid accessibility factors (see Section 
6.18), and physical-chemical filtration is represented by using appropriate parameters in 
Equations 6-14 or 6-15. 
Note that it is not possible to account for cake filtration or for the effects of filtration on 
permeability and porosity, as this would violate the linearity in the models. However, these 
scenarios would be unlikely in the Yucca Mountain UZ because (a) natural pseudocolloids (such 
as clays) under natural conditions occur in small concentrations, (b) it is expected that, owing to 
adverse chemical conditions (e.g., pH, ionic strength) in the immediate vicinity of the repository, 
true colloids will be released at low concentrations for a long time, and (c) the expected 
concentrations of the waste form colloids (BSC 2003 [161620], Section 6.3.2) are insufficient to 
support cake filtration. 

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6.2.5 Colloid-Assisted Transport Terms 
6.2.5.1 Equations of Colloid-Assisted Transport 
The mass of a tracer . sorbed onto pseudocolloids is described by 
X M j j j j 
N
j c A , . = . , ) . + s . ( = . 1 
c F 
(Eq. 6-17) 
where F.,j denotes the sorbed mass of solute . per unit mass of the pseudocolloid j [M/M] and 
Nc is the total number of pseudocolloid species (Moridis et al. 1999 [123093]). The first term in 
the sum inside the parenthesis of Equation 6-17 describes the filtered (deposited) colloid 
concentration, and the second describes the concentration of the suspended colloids in the liquid 
phase. F.,j is computed from any combination of Equations 6-96-12, with the appropriate 
sorption parameters corresponding to each colloid. Note that Equation 6-17 applies to Class III 
colloids only. 
6.2.5.2 Implications for Transport in the UZ 
The formulation of Equation 6-17 allows consideration of the whole size spectrum of a particular 
colloid, as each size would have different transport behavior (see Equation 6-16) and different 
sorption properties (resulting from different surface area). 
Of particular interest in UZ radioactive transport models is the potential of colloid-assisted 
transport to significantly enhance the migration of tracers whose normally strong sorbing 
behavior would confine them to the vicinity of the release point. Sorption of such a radionuclide 
(e.g., Pu) onto pseudocolloids renders the whole colloid radioactive. The transport of such a 
colloid is no longer dictated by the strong Pu sorption behavior, but by the kinetics of colloid 
filtration. Coupled with the fact that colloids can move at velocities that can be up to 50% higher 
than the Darcy velocity (and especially so in fractures, where most of the UZ flow occurs; see 
Equation 6-16), this can result in travel times to the water table orders of magnitude shorter than 
the ones predicted for the corresponding sorbing solute. Note that the higher colloid velocities 
are not a function of the water flow, but depend entirely on the colloid size (see discussion in 
Section 6.2.4.1). 
6.2.6 Flux Terms 
6.2.6.1 Equations of the Flux Terms 
The flux term has contributions from advective, diffusive, and dispersive transport processes and 
is given by 
F. = F.X. - . D. . X. - Fs, . (Eq. 6-18) 
where Fs, . is the flux due to surface diffusion and D. is the dispersion tensor of tracer ., a second 
order symmetric tensor with a principal axis aligned with the Darcy flow vector. Omitting the 
. subscript, D. is described by the equations 

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u u I D , + =D 
u 
D D T T L -
2 (Eq. 6-19) 
DL = f ( Sw - Sr) tD0 + f Sr tD0 + aL u , (Eq. 6-20) 
DT = f ( Sw - Sr) tD0 + f Sr tD0 + aT u , (Eq. 6-21) 
where 
I = the unit vector 
t = the tortuosity coefficient of the pore paths [L/L] 
D0 = the molecular diffusion coefficient of tracer i in water [ L2T - 1] 
aL, aT = longitudinal and transverse dispersivities, respectively [L] 
u = the Darcy velocity vector [ LT - 1] 
Equation 6-18 accounts for surface diffusion, which can be responsible for significant transport 
in strongly sorbing media (Moridis 1999 [117241]; Cook 1989 [117314]). The surface diffusion 
flux is given by Jahnke and Radke (1987 [117398]) as 
Fs = ( 1 - f) .stsDs.Fp, 
(Eq. 6-22) 
where ts is the tortuosity coefficient of the surface path [L0], Ds is the surface diffusion 
coefficient [L2T -1], and Fp is the physical diffusion computed from equations (19) or (10). There 
is theoretical justification for the relationship t = t 
3
2 
s (Cook 1989 [117314], p. 10). 
6.2.6.2 Application to Colloid Fluxes 
Equations 6-17 through 6-20 apply to solutes, but need the following modifications to render 
them suitable to colloidal transport. More specifically: 
1. Fs = 0 because surface diffusion does not occur in colloids. 
2. The flux Fs and the Darcy velocities u are multiplied by the factor f (see Section 
6.2.4.1). 
3. The dispersivities aL and aT are generally different from those for solutes Ibaraki and 
Sudicky (1995 [109297]) and may be a function of the colloidal particle size. 
4. The term D0 is the colloidal diffusion coefficient in water [L2T-1] and is described by 
the Stokes-Einstein equation, according to Bird et al. (1960 [103524], p. 514), as 
D0 = k T 
3p wdp 
, 
(Eq. 6-23) 

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where k is the Boltzmann constant (1.38 10 - 23JK - 1 in SI units), T is the absolute 
water temperature [K] , w is the dynamic viscosity of water [ML - 1T - 1] , and dp is 
the colloid diameter [L]. 
5. The fluxes in Equation 6-18 are multiplied by the colloid accessibility factors 
fc (0 =fc =1) at the interface of different media. The fc factor describes the portion of the 
colloidal concentration in a medium that is allowed to enter an adjacent medium of 
different characteristics, and quantifies pore size exclusion (straining). 
In the treatment of the general 3-D dispersion tensor, velocities are averaged by using the 
projected area weighting method (Wu et al. 1996 [100649], p. 23), in which a velocity 
component uj (j =x,y,z) of the vector u is determined by vectorial summation of the components 
of all local connection vectors in the same direction, weighted by the projected area in that 
direction. This approach allows the solution of the transport problem in irregularly shaped grids, 
in which the velocities normal to the interface areas are not aligned with the principal axes. 
6.2.6.3 Implications for Transport in the UZ 
Because it is directly proportional to the water fluxes, advection in the fractures is by far the 
dominant mechanism of transport in the UZ of Yucca Mountain. This is further enhanced by 
longitudinal dispersion, molecular diffusion, and (possibly) surface diffusion (in decreasing 
order). Coupled with the fracture orientation and gravitational differentials, the result of the 
fracture and flow characteristics is a mainly downward migration of the radionuclides. Note that 
advection also occurs in the matrix (and is accounted for in the simulations), albeit at 
significantly lower rates. 
Lateral spreading of the contaminants can be achieved through transverse dispersion, molecular 
diffusion, and (possibly) surface diffusion. As sorption occurs from the liquid phase onto the 
solids, and fractures are by far the main conduits of water, retardation of sorbing radionuclides 
will be controlled by the rate of tracer movement from the fractures to the sorbing matrix. This is 
represented by the sum of diffusive, dispersive, and surface diffusion fluxes, and results in the 
lateral migration of the contaminants. 
Currently, field study estimates of aL and aT in the UZ are very limited. When not ignored in the 
numerical simulations (justified by the relative magnitude of advection), reasonable aL estimates 
are used, and aT is usually set to zero (especially in the fractures). In past simulations (DOE 
1998 [100550], p. 3-122), an estimate of aL = 20 m was used. From the Northern Ghost Dance 
Fault test (LeCain et al. 2000 [144612]) aL estimates in the 0.4 m to 2.6 m range were obtained 
but their validity is uncertain because they are based on gas (rather than liquid) phase transport, 
short transport times (<200 min), and a small scale experiment (<10 m). Accurate values of D0, 
coupled with reasonable tortuosity coefficients (shown from laboratory experiments to be 
approximated by the porosity, see Section 5, this Model Report), provide a rather representative 
estimate of diffusive fluxes in the UZ simulations. 
No information exists on whether the UZ media support surface diffusion (a possibility in 
zeolites). Surface diffusion can be important in tracers that exhibit strong sorption (e.g., Pu). A 

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larger Kd clearly indicates stronger sorption, but this does not mean immobilization of the 
dissolved species when the porous/fractured medium supports surface diffusion. On the contrary, 
the stronger the sorption (i.e., the larger the Kd), the larger the diffusion rate, with practically all 
of it attributable to the surface process (Moridis 1999 [117241], pp. 1,7351,736). 
6.2.7 Radioactive Decay 
6.2.7.1 Equations of Radioactive Decay 
When a tracer . undergoes radioactive decay, the rate of mass change is described by the 
first-order decay law 
dM. 
dt 
= - .. 
M. , where .. = ln2 
( T1/2) . (Eq. 6-24) 
and (T1/2). is the half life of tracer .. Substitution of Equations 6-18 and 6-24 into Equation 6-2 
yields (Moridis et al. 1999 [123093] Eq. 32) 
[ ] . . . . . . . . 
. + - . . - = . + .. 
. 
.. 
. 
m 
n s nm nm 
n 
n 
n 
q X X F A 
V 
M 
dt 
dM ) ( F D 1 ) ( , (Eq. 6-25) 
6.2.7.2 Implications for Transport in the UZ 
The decay of radioactive substance is completely predictable and well documented. Thus, the 
decay of radioactive substances in UZ simulations can be computed very reliably. 
6.2.8 Daughter Products of Radioactive Decay 
6.2.8.1 Transport Equations of Daughters 
If a radioactive tracer . is a daughter product of the decay of tracer j, then the mass accumulation 
terms are adjusted (de Marsily 1986 [100439], pp. 265266) to yield the equation of transport of 
the daughter products as 
) ( + - . . - [ = 
) ( . - ) ( . + ... ... 
q X X F A 
V 
M m M 
t d
M d 
. , . . 
. . 
. 
n k s i m n m n 
m n 
n j r j n 
n 
1 . F D 
(Eq. 6-26) 
where mr =W./Wj, and W. and Wj are the molecular weights of the daughter and parent species. 
Equation 6-26 applies to radioactive solutes or radioactive true colloids. 
For daughters following an isotherm other than LE, Equations 6-9 and 6-10 need to account for 
the generation of daughter mass from the decay of the sorbed parent, and become 

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.F. 
.t 
+ ..F. - .. - 1mr ..F. - 1 = kA . X. - kB ( F. + mr ..F. - 1) 
(Eq. 6-27) 
where F.-1 is the sorbed mass of the parent, 
. . .
= + sorption LKC for 
sorption LKP/LIP for 
i c 
i d 
A K k 
K K k 
k l 
kB = 
. . 
.kpdp for LKP/LIP sorption, 
k - 
c for LKC sorption, (Eq. 6-28) 
and .. is the fraction of the mass of the decayed sorbed parent that remains sorbed as a daughter 
(0 = .. =1). The term .. is introduced to account for the different sorption behavior of parents and 
daughters, and the fact that daughters can be ejected from grain surfaces due to recoil (e.g., the 
ejection of 234Th from grain surfaces during the alpha decay of 238U) (Faure 1977 [122805], pp. 
288289). 
6.2.8.2 Implications for Transport in the UZ 
If decay results in radioactive daughters, UZ simulations must compute the total radioactivity 
distribution, i.e., the sum of the concentrations of all the members of the radioactive chain. This 
is especially true if the daughters have long half lives. Intermediate chain products with short 
half lives relative to the simulation periods can be ignored with impunity. 
Although the EOS9nT can theoretically obtain the transport scenario of any number of daughters 
in the radioactive chain, this is especially true for daughters with short half lives. With longer 
half-lives (such as for 237Np, 239Pu, etc.), machine accuracy considerations and roundoff errors 
(with the daughter concentrations becoming increasingly smaller moving down the radioactive 
chain) limit their number to a maximum of four or five with comparable half lives. 
The . factor is a function of the type of decay, as well as of the chemical form of the sorbed 
cation. In alpha decay (e.g., 237Np, 239Pu), .=0. There is no information on the behavior of . for 
other types of decay. The . factor can have significant implications for the transport behavior of 
daughters if (a) the large sorbed masses of strongly sorbing parents are ejected back into the 
aqueous phase after decay, (b) the daughter is a much weaker sorber, and (c) its sorption is 
kinetically controlled. Such a possibility could arise in the kinetic sorption of radionuclides onto 
pseudocolloids (BSC 2001 [160828], Section 6). For equilibrium isotherms, this is not an issue. 

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6.3 THE NUMERICAL MODELS 
In mathematical simulations, the conventional meaning of the term model is the mathematical 
description of the physics governing the behavior of the simulated system, whereas the term code 
is the implementation of the mathematical model in a computer language. Because model and 
code are intertwined, these terms have historically been used interchangeably. In the context of 
T2R3D and EOS9nT applications in the present Model Report, when the word model is used, it 
is preceded by the qualifying words numerical or semianalytical. 
6.3.1 The T2R3D Code 
The code T2R3D V1.4 (LBNL 1999 [146654]; Wu et al. 1996 [100649]) simulates the flow 
(saturated and/or unsaturated) and coupled transport of a single radioactive solute tracer in 
complex subsurface systems involving porous and/or fractured media. The transport equations 
account for advection, molecular diffusion, hydrodynamic dispersion, and linear equilibrium 
sorption. 
T2R3D can simulate problems involving the coupled (a) flow of subsurface liquids, (b) transport 
of a solute, and (c) the transport of heat in complex heterogeneous subsurface systems. When a 
flow system has reached a steady state, T2R3D allows the option of solving only the solute 
transport equation. 
6.3.2 The EOS9nT Code 
The code used for the 3-D site-scale transport simulations in the Model Report is TOUGH2 
V1.11MEOS9NTV1.0 (LBNL 1999 [113943]; Moridis et al. 1999 [123093]; 2003 [161902]), 
which is a member of the TOUGH2 family of codes (Pruess 1991 [100413]). It can simulate 
flow and transport of an arbitrary number n of nonvolatile tracers (solutes and/or colloids) in the 
subsurface. EOS9nT first solves the Richards equation, which describes saturated or unsaturated 
water flow in subsurface formations, and obtains the flow regime. The set of n linearly 
independent transport equations (corresponding to the n solutes/colloids) are then solved 
sequentially. The n tracer transport equations account for (a) advection, (b) molecular diffusion, 
(c) hydrodynamic dispersion (with full 3-D tensorial representation), (d) kinetic or equilibrium 
physical and chemical sorption (linear, Langmuir, Freundlich, or combined), (e) first-order linear 
chemical reaction, (e) radioactive decay, (f) colloid filtration (equilibrium, kinetic or combined), 
and (g) colloid assisted solute transport. A total of n -1 daughter products of radioactive decay 
(or of a linear, first-order reaction chain) can be tracked. 
EOS9nT includes two types of Laplace transform formulations of the tracer equations, in 
addition to conventional timestepping. The Laplace transform is applicable to steady-state flow 
fields and allows a practically unlimited time-step size and more accurate solution (as numerical 
diffusion is significantly reduced). Additional information on the EOS9nT numerical model can 
be found in BSC (2001 [161340], Attachment I). For the simulation of isothermal transport of a 
tracer that follows a linear equilibrium isotherm, T2R3D and EOS9nT have been shown to 
produce identical results (Section 7.1, this Model Report; DTN: LB03093RADTRNS.001 
[166225]). 

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6.3.3 Other Computational Tools 
In addition to T2R3D and EOS9nT, the following computational tools were used: 
1. The software codes TOUGH2 V1.4 Module EOS9 (LBNL 2000 [146496]) and 
TOUGH2 V1.6 Module EOS9 (LBNL 2002 [160242]; LBNL 2003 [161491]), which 
solve the Richards equation to simulate flow (saturated and/or unsaturated) in complex 
subsurface systems (involving porous and/or fractured media). These codes were used 
to obtain the flow fields for the various climatic scenarios discussed in BSC (2003 
[163045], Section 6). 
2. The software code PHREEQC V2.3 (BSC 2001 [155323]) to perform the 
computations for the estimations of the Kd (Section 6.4). 
3. The XtractG.f90 V1.0 routine (LBNL 2003 [162786]), which was used for the 
EOS9nT runs for the following applications: 
(a) To modify the grid system for use in the EOS9nT runs. The modifications 
involved (1) determining the grid elements corresponding to the repository, (2) 
moving them to the end of the element file, where (3) the upper and lower 
boundary elements are also moved. This was necessitated by the fact that the 
scenario of continuous contaminant release was investigated in this Model Report. 
Thus the repository elements represent internal boundary points. After moving 
these elements to the bottom of the element file, the volume of the first element is 
set to zero or a negative number. Then, these elements are considered in the 
determination of fluxes but are not included in mass balance computations. 
Additionally, XtractG.f90 can be used to render inactive all the elements above a 
given height (e.g., the highest repository element) which do not contribute to 
transport, thus significantly reducing the size of the problem and making possible 
the solution within the array sizes of EOS9nT. 
(b) To obtain initial condition files (INCON) using the SAVE files from the EOS9 runs. 
(c) To create steady state velocity profiles using the flow field output files from the 
EOS9 runs. 
(d) To extract concentrations at desired grid elements within the domain. 

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6.4 FEATURES, EVENTS, AND PROCESSES (FEPS) 
6.4.1 FEPs Addressed in this Model Report 
The following table of Features, Events, and Processes (FEPs) were taken from the LA FEP List 
(DTN: MO0307SEPFEPS4.000 [164527]). The LA FEP List is a revision to the previous 
project FEP list (Freeze et al. 2001 [154365]) used to develop the list of included FEPs in the 
Technical Work Plan for: Performance Assessment Unsaturated Zone (BSC 2002 [160819], 
Table 2-6). The selected FEPs are those taken from the LA FEP List that are associated with the 
subject matter of this report, regardless of the anticipated status for exclusion or inclusion in 
TSPA-LA as represented in BSC (2002 [160819]). The results of this model (or analysis) are 
part of the basis for the treatment of FEPs as discussed in the Total System Performance 
Assessment-License Application Methods and Approach (BSC 2002 [160146], Section 3.2.2). 
The cross-reference for each FEP to the relevant section (or sections) of this report is also given 
below. 
Table 6.4-1. FEPs Addressed in This Model Report 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
1.2.02.01.0A Fractures The effects of fractures on radionuclide transport 
are addressed through the use of fracturecontinuum 
flow fields (output from the UZ Flow 
Model) that are part of the input data used for 
transport simulations (Section 4.1). 
Simulations showing the effects of fractures are 
presented in Section 6.8.1.2, and in Attachments 
IV and V. 
Groundwater flow in the Yucca 
Mountain region and transport of any 
released radionuclides may take 
place along fractures. The rate of 
flow and the extent of transport in 
fractures are influenced by 
characteristics such as orientation, 
aperture, asperity, fracture length, 
connectivity, and the nature of any 
linings or infills. 
1.2.02.02.0A Faults The effects of faults are addressed through the 
use of dual-continuum flow fields that are part of 
the input data used for transport simulations 
(Section 4.1). 
Simulations showing the effects of faults are 
presented in Sections 6.8.1.2 and 6.20.2. 
Numerous faults of various sizes 
have been noted in the Yucca 
Mountain Region and in the 
repository area in specific. Faults 
may represent an alteration of the 
rock permeability and continuity of the 
rock mass, alteration or shortcircuiting 
of the flow paths and flow 
distributions close to the repository, 
and represent unexpected pathways 
through the repository. 
1.3.01.00.0A Climate 
change 
Climate change is addressed through the use of 
different dual-continuum flow fields (output from 
the UZ Flow Model), for different future climates, 
that are part of the input data used for transport 
simulations (Section 4.1). 
Simulations for different climates are presented 
in Section 6.8.1 and 6.8.2. The effect of varying 
infiltration resulting from climate change is shown 
in Figures 6.8-1, 6.8-26, and 6.8-27. Additional 
discussion is presented in Sections 6.7.1, and 
6.8 through 6.14. Simulations are presented in 
this Model Report to evaluate the effects of 
climate change. 
Climate change may affect the longterm 
performance of the repository. 
This includes the effects of long-term 
change in global climate (e.g., 
glacial/interglacial cycles) and 
shorter-term change in regional and 
local climate. Climate is typically 
characterized by temporal variations 
in precipitation and temperature. 

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Table 6.4-1. FEPs Addressed in this Model Report (Continued) 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
1.4.01.01.0A Climate 
modification 
increases 
recharge 
Steady state dual-continuum flow fields (output 
from the UZ Flow Model) that are part of the 
input data used for transport simulations (Section 
4.1) account for changes in recharge resulting 
from climate changes. 
Simulations for different climates are presented 
in Section 6.8.1.2. Additional discussion is 
presented in Sections 6.7.1, and 6.8 through 
6.14. 
Climate modification causes an 
increase in recharge in the Yucca 
Mountain region. Increased recharge 
might lead to increased flux through 
the repository, perched water, or 
water table rise. 
2.1.08.01.0A Water influx 
at the 
repository 
Water influx at the repository under present and 
projected future climates is addressed through 
the use of dual-continuum flow fields (output 
from the UZ Flow Model) that are part of the 
input data used for transport simulations (Section 
4.1). 
Water influx at the repository may result in 
seepage into drifts (The process model for 
seepage is presented in another Model Report, 
BSC 2003 [163226]). Seepage may result in 
radionuclide transport. Sections 6.8 through 6.14 
present the transport simulations for 
radionuclides instantly released from drifts to 
fractures. Additional discussion is presented in 
Sections 6.7.1, 6.8.2, 6.9.2, 6.11.1 and 6.11.2. 
An increase in the unsaturated water 
flux at the repository affects thermal, 
hydrologic, chemical, and mechanical 
behavior of the system. Increases in 
flux could result from climate change, 
but the cause of the increase is not 
an essential part of the FEP. 
2.2.03.01.0A Stratigraphy Stratigraphy is addressed in the conceptual 
model of transport presented in Section 6.6. In 
3-D simulations, it is addressed in the material 
properties included in input data for simulations 
by using the grid developed in BSC 2003 
[160109] and used as direct input in Section 4.1. 
Stratigraphy affects radionuclide transport 
through its effects on flow (predominantly matrix 
flow or fracture flow depending upon the 
hydrogeologic unit) and through the differing 
sorptive properties of different hydrogeologic 
units. The effect of sorption on transport is 
presented in Sections 6.9.1.6 and 6.10.1.4. 
Additional discussion is presented in Sections 
6.1 and 6.1.1 . 
Stratigraphic information is necessary 
information for the performance 
assessment. This information should 
include identification of the relevant 
rock units, soils and alluvium, and 
their thickness, lateral extents, and 
relationships to each other. Major 
discontinuities should be identified. 
2.2.03.02.0A Rock 
properties of 
host rock 
and other 
units 
Rock Properties are addressed in the conceptual 
model of transport presented in Section 6.6. In 
3-D simulations, rock properties are addressed in 
the material properties included in input data for 
simulations by using the grid developed in BSC 
2003 [160109] and used as direct input in 
Section 4.1. 
Rock physical properties affect radionuclide 
transport through their effects on flow as shown 
in the transport simulations shown in Section 6.8 
and Attachments IV through VI. The effect of 
sorption on transport is presented in Sections 
6.9.1.6 and 6.10.1.4. 
Physical properties such as porosity 
and permeability of the relevant rock 
units, soils, and alluvium are 
necessary for the performance 
assessment. Possible heterogeneities 
in these properties should be 
considered. Questions concerning 
events and processes that may cause 
these physical properties to change 
over time are considered in other 
FEPs. 

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Table 6.4-1. FEPs Addressed in this Model Report (Continued) 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
2.2.07.02.0A Unsaturated 
groundwater 
flow in the 
geosphere 
Unsaturated groundwater flow is addressed 
through the use of dual-continuum flow fields 
(output from the UZ Flow Model) that are part of 
the input data used for transport simulations 
(Section 4.1). 
The effect of unsaturated flow on advective 
transport is evident in the simulations presented 
in Section 6.8 and Attachments IV through VI. 
Groundwater flow occurs in 
unsaturated rocks in most locations 
above the water table at Yucca 
Mountain, including at the location of 
the repository. See related FEPs for 
discussions of specific issues related 
to unsaturated flow. 
2.2.07.04.0A Focusing of 
unsaturated 
flow (fingers, 
weeps) 
Steady state dual-continuum flow fields (output 
from the UZ Flow Model) that are part of the 
input data used for transport simulations 
(Section 4.1) account for focusing of 
unsaturated flow at the gridblock scale. Subgridblock 
scale flow focusing in the fracture 
continuum is accounted for through the active 
fracture model (Section 7.7.1). This is 
incorporated into the RTM as input data through 
the flow fields used for transport simulations 
(Section 4.1). 
Unsaturated flow can differentiate into 
zones of greater and lower saturation 
(fingers) that may persist as 
preferential flow paths. 
Heterogeneities in rock properties, 
including fractures and faults, may 
contribute to focusing. Focused flow 
may become locally saturated. 
2.2.07.06.0B Long-term 
release of 
radionuclides 
from the 
repository 
The effects of long-term release of 
radionuclides are addressed in Sections 6.15 to 
6.18. 
Simulation results presented in Attachments V 
through VII show the effects of long-term 
release. 
The release of radionuclides from the 
repository may occur over a long 
period of time, as a result of the 
timing and magnitude of the waste 
packages and drip shield failures, 
waste form degradation, and 
radionuclide transport through the 
invert. 
2.2.07.07.0A Perched 
water 
develops 
The effects of perched water are addressed 
through the use of dual-continuum flow fields 
that are part of the input data used for transport 
simulations (Section 4.1). 
The transport simulations presented in this 
Model Report include the effect of perched 
water. Additional discussion is presented in 
Sections 6.1.2, 6.1.2.7, 6.7.2, 6.18.5.2, and 
8.2.1 (conclusion 7). 
Zones of perched water may develop 
above the water table. If these zones 
occur above the repository, they may 
affect UZ flow between the surface 
and the waste packages. If they 
develop below the repository, for 
example at the base of the Topopah 
Spring welded unit, they may affect 
flow pathways and radionuclide 
transport between the waste 
packages and the saturated zone. 
2.2.07.08.0A Fracture flow 
in the UZ 
The effects of fractures on radionuclide 
transport are addressed through the use of 
fracture-continuum flow fields (output from the 
UZ Flow Model) that are part of the input data 
used for transport simulations (Section 4.1). 
Simulations showing the effects of fractures are 
presented in Section 6.8.1.2, and in 
Attachments IV and V.A discussion is presented 
in Sections 6.1.2.1 and 6.1.5.3. 
Fractures or other analogous 
channels act as conduits for fluids to 
move into the subsurface to interact 
with the repository and as conduits 
for fluids to leave the vicinity of the 
repository and be conducted to the 
SZ. Water may flow through only a 
portion of the fracture network, 
including flow through a restricted 
portion of a given fracture plane. 

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Table 6.4-1. FEPs Addressed in This Model Report (Continued) 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
2.2.07.09.0A Matrix 
imbibition in 
the UZ 
Steady state dual-continuum flow fields (output 
from the UZ Flow Model) that are part of the 
input data used for transport simulations 
(Section 4.1) account for matrix imbibition by 
changes between one climate stage and the 
next. 
Figures showing radionuclide concentrations in 
the matrix in Section 6.8.1.2 and Attachments 
IV through VII include the effects of both matrix 
flow and imbibition from fractures into the 
matrix. An alternative treatment of matrix 
imbibition is discussed in Section 6.19. 
Water flowing in fractures or other 
channels in the unsaturated zone is 
imbibed into the surrounding rock 
matrix. This may occur during 
steady flow, episodic flow, or into 
matrix pores that have been dried 
out during the thermal period. 
2.2.07.15.0B Advection and 
dispersion in 
the UZ 
Advection is more important than dispersion for 
radionuclide transport. The effects of advection 
are discussed in the transport model in Sections 
6.1.2.1, 6.2.6 and 6.8.1.3. Advective transport 
is calculated using the fracture-continuum flow 
fields (output from the UZ Flow Model) that are 
part of the input data used for transport 
simulations (Section 4.1). All transport 
simulations presented in this Model Report 
show the effect of advection. 
The effects of dispersion are discussed in the 
transport model in Section 6.1.2.2, 6.2.6. and 
6.18.4. 
Advection and dispersion processes 
may affect contaminant transport in 
the UZ. 
2.2.08.01.0B Chemical 
characteristics 
of groundwater 
in the UZ 
This FEP is included; the TSPA Disposition is 
provided in Section 6.4.2. Attachment I, 
Section I.4 also discusses the chemical 
characteristics of UZ groundwater. 
Chemistry and other characteristics 
of groundwater in the unsaturated 
zone may affect groundwater flow 
and radionuclide transport of 
dissolved and colloidal species. 
Groundwater chemistry and other 
characteristics, including 
temperature, pH, Eh, ionic strength, 
and major ionic concentrations, may 
vary spatially throughout the system 
as a result of different rock 
mineralogy. 
2.2.08.05.0A Diffusion in the 
UZ 
Diffusion in the UZ is addressed in the 
simulation codes described in Sections 6.3.1, 
6.3.2, and 6.3.3. 
Molecular diffusion processes may 
affect radionuclide transport in the 
UZ. This includes osmotic 
processes in response to chemical 
gradients. 
2.2.08.06.0B Complexation 
in the UZ 
This FEP is included; the TSPA Disposition is 
provided in Section 6.4.2. 
Complexation on mobile complexing agents 
such as humic and fulvic acids is treated as part 
of colloid transport in Section 6.1.3 and 6.18. 
Complexation on mineral surfaces is treated as 
part of sorption in Attachment I, Section I.7. 
Complexing agents such as humic 
and fulvic acids present in natural 
groundwaters could affect 
radionuclide transport in the UZ. 

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Table 6.4-1. FEPs Addressed in This Model Report (Continued) 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
2.2.08.08.0B Matrix 
diffusion in 
the UZ 
Matrix diffusion is addressed in Section 6.1.2.4. 
Figures showing radionuclide concentrations in 
the matrix in Section 6.8.1.2 and Attachments 
IV and V include the effects of both diffusion 
from fractures into the matrix. 
Uncertainty of radionuclide transport is 
addressed in Sections 6.8.3.2, 6.9.3.1 and 
6.10.2. 
Matrix diffusion is the process by 
which radionuclides and other 
species transported in the UZ by 
advective flow in fractures or other 
pathways move into the matrix of the 
porous rock by diffusion. Matrix 
diffusion can be a very efficient 
retarding mechanism, especially for 
strongly sorbed radionuclides due to 
the increase in rock surface 
accessible to sorption. 
2.2.08.09.0B Sorption in 
the UZ 
This FEP is included; the TSPA Disposition is 
provided in Section 6.4.2. 
The sorption model and the distributions of Kd 
values are presented in 6.1 and Table 6.5-1. 
Data supporting the Kd distributions are 
presented in Attachment I. Colloid transport is 
addressed in Section 6.1.3 and 6.2.3. The 
model for colloid filtration in the UZ and 
simulation results are presented in Section 
6.18. 
Sorption of dissolved and colloidal 
radionuclides in the UZ can occur on 
the surfaces of both fractures and 
matrix in rock or soil along the 
transport path. Sorption may be 
reversible or irreversible, and it may 
occur as a linear or nonlinear 
process. Sorption kinetics and the 
availability of sites for sorption should 
be considered. Sorption is a function 
of the radioelement type, mineral 
type, and groundwater composition. 
2.2.08.10.0B Colloidal 
transport in 
the UZ 
Colloidal transport in the UZ is addressed in 
Section 6.18. 
Mathematical model of colloid transport is 
addressed in Sections 6.2.4 and 6.2.5. 
The effect of transport of PuO2 colloidal 
particles is shown in Attachments VI and VII. 
Radionuclides may be transported in 
groundwater in the UZ as colloidal 
species. Types of colloids include 
true colloids, pseudo colloids, and 
microbial colloids. 
2.2.09.01.0B Microbial 
activity in the 
UZ 
This FEP is included; the TSPA Disposition is 
provided in Section 6.4.2. 
The effects of Microbial activity on colloid 
transport and on complexing agents are 
addressed in Sections 6.1.3 and 6.18. The 
presence of representative biota in sorption 
experiments is addressed in Section I.5. 
Microbial activity in the UZ may affect 
radionuclide mobility in rock and soil 
through colloidal processes, by 
influencing the availability of 
complexing agents, or by influencing 
groundwater chemistry. Changes in 
microbial activity could be caused by 
the response of the soil zone to 
changes in climate. 

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Table 6.4-1. FEPs Addressed in This Model Report (Continued) 
LA FEP Number FEP Name Section Where FEP is Addressed Summary Description 
3.1.01.01.0A Radioactive 
decay and 
ingrowth 
Radioactive decay and ingrowth are addressed 
in the simulations of transport of radionuclide 
chains in Sections 6.2.7, 6.2.8, 6.7.4, 6.7.6, 
6.8.1.1, 6.16, and 6.17. 
Radioactivity is the spontaneous 
disintegration of an unstable atomic 
nucleus that results in the emission of 
subatomic particles. Radioactive 
isotopes are known as radionuclides. 
Radioactive decay of the fuel in the 
repository changes the radionuclide 
content in the fuel with time and 
generates heat. Radionuclide 
quantities in the system at any time 
are the result of the radioactive decay 
and the growth of daughter products 
as a consequence of that decay (i.e., 
ingrowth). Over a 10,000-year 
performance period, these processes 
will produce daughter products that 
need to be considered in order to 
adequately evaluate the release and 
transport of radionuclides to the 
accessible environment. 
6.4.2 FEPs Included for TSPA 
2.2.08.01.0B, Chemical Characteristics of Groundwater in the UZ 
FEP Description: Chemistry and other characteristics of groundwater in the unsaturated zone 
may affect groundwater flow and radionuclide transport of dissolved and colloidal species. 
Groundwater chemistry and other characteristics, including temperature, pH, Eh, ionic strength, 
and major ionic concentrations, may vary spatially throughout the system as a result of different 
rock mineralogy. 
Screening Decision and Regulatory Basis: Included 
Screening Argument: None. 
TSPA Disposition: The effects of groundwater chemical characteristics are included in the 
radionuclide sorption coefficients under ambient conditions. The sorption coefficient data on 
which the distributions are based are obtained in laboratory experiments in which crushed rock 
samples from the Yucca Mountain site are contacted with groundwaters (or simulated 
groundwaters) representative of the site, spiked with one or more of the elements of interest (this 
Model Report, Section I.5). The chemistry of pore waters and perched waters in the UZ along 
potential flowpaths to the accessible environment is discussed in BSC (2002 [160247]). In the 
UZ, two distinct water types exist in the ambient system. One is perched water and the other is 
pore water. Perched water is generally more dilute than pore water. The J-13 and UE p#1 waters 
were used in sorption experiments as end-member compositions intended to bracket the impact 
of water composition on sorption coefficients (see Section I.4, this Model Report). Some spatial 
trends in water composition through the TSw and CHn geologic units have been noted (BSC 

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2002 [160247], Section 6.5.3.1). However, the uncertainty in these spatial variations (BSC 2003 
[162050], Section 6.2.2.1) and the uncertainty with respect to the effects of the bounding water 
compositions on sorption (see Sections I.8.C, I.8.D, and I.8.I of this Model Report) have led to 
the treatment of natural variability in water composition as uncertainty. Sorption experiments 
have been carried out as a function of time, element concentration, atmospheric composition, 
particle size, and temperature. In some cases, the solids remaining from sorption experiments 
were contacted with unspiked groundwater in desorption experiments. The experimental data 
used to determine the sorption Kds are provided in the following DTNs: LA0305AM831341.001 
[163789], LA0309AM831341.002 [165523], LA0309AM831341.003 [165524], 
LA0309AM831341.004 [165525], LA0309AM831341.005 [165526], LA0309AM831341.006 
[165527], LA0309AM831341.007 [165528], and LA0310AM831341.001 [165865]. The 
sorption and desorption experiments together provide information on the equilibration rates of 
the forward and backward sorption reactions. For elements that sorb primarily through surface 
complexation reactions, the experimental data are augmented with the results of modeling 
calculations using PHREEQC V2.3 (BSC 2001 [155323]). The inputs for the modeling 
calculations include groundwater compositions, surface areas, binding constants for the elements 
of interest, and thermodynamic data for solution species. These modeling calculations provide a 
basis for interpolation and extrapolation of the experimentally derived sorption coefficient 
dataset. The effects of nonlinear sorption are approximated by capturing the effective Kd range 
(this Model Report, Section I.8). 
The effects of groundwater composition with respect to sorption coefficients are provided in 
terms of probability distributions for the sorption coefficient of each element of interest among 
the three major rock types (devitrified, zeolitic, and vitric) found in the UZ. The influence of 
expected variations in water chemistry, radionuclide concentrations, and variations in rock 
surface properties within one of the major rock types are incorporated into these probability 
distributions. These distributions are specified for each radionuclide/rock type combination (this 
Model Report, Section I.2 and I.4) and are sampled in the TSPA to account for the effects of 
natural variations in pore water chemistry and mineral surfaces on sorption. Correlations for 
sampling sorption coefficient probability distributions have been derived for the elements 
investigated (this Model Report, Section II). To derive the correlations, a rating system was first 
developed to rate the impact of six different variables on the sorption coefficient for a given 
element in each of the three major rock types. The six variables are pH, Eh, water chemistry, 
rock composition, rock surface area, and radionuclide concentration. Water chemistry refers to 
the major ion concentrations and silica. Rock composition refers to both the mineralogic 
composition of the rocks and the chemical composition of the minerals (e.g., zeolite 
compositions). The output DTN for the sorption Kds and correlations is LA0302AM831341.002. 
2.2.08.06.0B, Complexation in the UZ 
FEP Description: Complexing agents such as humic and fulvic acids present in natural 
groundwaters could affect radionuclide transport in the UZ. 
Screening Decision and Regulatory Basis: Included 
Screening Argument: None. 

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TSPA Disposition: The effects of complexation are implicitly included in the radionuclide 
sorption coefficients under ambient conditions. The sorption coefficient data on which the 
distributions are based are obtained in laboratory experiments in which crushed rock samples 
from the Yucca Mountain site are contacted with groundwaters (or simulated groundwaters) 
representative of the site, spiked with one or more of the elements of interest (this Model Report, 
Section I.5). As such, the sorption experiments contain representative ligands responsible for 
complex formation, such as carbonates (Triay et al. 1997 [100422], p. 85). Sorption experiments 
have been carried out as a function of time, element concentration, atmospheric composition, 
particle size, and temperature. In some cases, the solids remaining from sorption experiments 
were contacted with unspiked groundwater in desorption experiments. The experimental data 
used to determine the sorption Kds are provided in the following DTNs: LA0305AM831341.001 
[163789], LA0309AM831341.002 [165523], LA0309AM831341.003 [165524], 
LA0309AM831341.004 [165525], LA0309AM831341.005 [165526], LA0309AM831341.006 
[165527], LA0309AM831341.007 [165528], and LA0310AM831341.001 [165865]. The 
sorption and desorption experiments together provide information on the equilibration rates of 
the forward and backward sorption reactions. For elements that sorb primarily through surface 
complexation reactions, the experimental data are augmented with the results of modeling 
calculations using PHREEQC V2.3 (BSC 2001 [155323]). The inputs for the modeling 
calculations include groundwater compositions, surface areas, binding constants for the elements 
of interest, and thermodynamic data for solution species. These modeling calculations provide a 
basis for interpolation and extrapolation of the experimentally derived sorption coefficient 
dataset. The effects of nonlinear sorption are approximated by capturing the effective Kd range 
(this Model Report, Section I.8). 
The effects of organics on sorption were also investigated by Triay et al. (1997 [100422], 
Section IV.B). Their experiments tested the effects of organic materials (DOPA 
(dihydroxyphenylalanine) and NAFA (Nordic Aquatic Fulvic Acid)) on the sorption of Pu and 
Np on tuff materials. The results of these tests showed very little effect of the organic materials 
for sorption of these radionuclides in tuffs. 
The effects of complexation with respect to sorption coefficients are provided in terms of 
probability distributions for the sorption coefficient of each element of interest among the three 
major rock types (devitrified, zeolitic, and vitric) found in the UZ. The influence of expected 
variations in water chemistry, radionuclide concentrations, and variations in rock surface 
properties within one of the major rock types are incorporated into these probability 
distributions. These distributions are specified for each radionuclide/rock type combination (this 
Model Report, Section I.2 and I.4) and are sampled in the TSPA to account for the effects of 
natural variations in pore water chemistry and mineral surfaces on sorption. Correlations for 
sampling sorption coefficient probability distributions have been derived for the elements 
investigated (this Model Report, Section II). To derive the correlations, a rating system was first 
developed to rate the impact of six different variables on the sorption coefficient for a given 
element in each of the three major rock types. The six variables are pH, Eh, water chemistry, 
rock composition, rock surface area, and radionuclide concentration. Water chemistry refers to 
the major ion concentrations and silica. Rock composition refers to both the mineralogic 
composition of the rocks and the chemical composition of the minerals (e.g., zeolite 

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compositions). The output DTNs for the sorption Kds and correlations are 
LA0302AM831341.002 and LA0311AM831341.001. 
2.2.08.09.0B, Sorption in the UZ 
FEP Description: Sorption of dissolved and colloidal radionuclides in the UZ can occur on the 
surfaces of both fractures and matrix in rock or soil along the transport path. Sorption may be 
reversible or irreversible, and it may occur as a linear or nonlinear process. Sorption kinetics and 
the availability of sites for sorption should be considered. Sorption is a function of the 
radioelement type, mineral type, and groundwater composition. 
Screening Decision and Regulatory Basis: Included 
Screening Argument: None. 
TSPA Disposition: Sorption is included in the TSPA model for mountain-scale unsaturated zone 
radionuclide transport as a linear equilibrium sorption (Kd) model (this Model Report, 
Attachment I). Sorption is only accounted for in the matrix continuum; there is no sorption 
modeled in the fracture continuum. Sorption characteristics of the rock minerals are assumed to 
be static in time. Sorption Kds have been derived for the elements Am, Cs, Np, Pa, Pu, Ra, Sr, 
Th, and U. Other radionuclide elements treated by TSPA (e.g. Tc) are modeled as non-sorbing. 
The sorption coefficient data on which the distributions are based are obtained in laboratory 
experiments in which crushed rock samples from the Yucca Mountain site are contacted with 
groundwaters (or simulated groundwaters) representative of the site, spiked with one or more of 
the elements of interest (this Model Report, Section I.5). Sorption experiments have been carried 
out as a function of time, element concentration, atmospheric composition, particle size, and 
temperature. In some cases, the solids remaining from sorption experiments were contacted with 
unspiked groundwater in desorption experiments. The experimental data used to determine the 
sorption Kds are provided in the following DTNs: LA0305AM831341.001 [163789], 
LA0309AM83341.002 [165523], LA0309AM83341.003 [165524], LA0309AM83341.004 
[165525], LA0309AM83341.005 [165526], LA0309AM83341.006 [165527], 
LA0309AM83341.007 [165528], and LA0310AM831341.001 [165865]. The sorption and 
desorption experiments together provide information on the equilibration rates of the forward 
and backward sorption reactions. For elements that sorb primarily through surface complexation 
reactions, the experimental data are augmented with the results of modeling calculations using 
PHREEQC V2.3 (BSC 2001 [155323]). The inputs for the modeling calculations include 
groundwater compositions, surface areas, binding constants for the elements of interest, and 
thermodynamic data for solution species. These modeling calculations provide a basis for 
interpolation and extrapolation of the experimentally derived sorption coefficient dataset. The 
effects of nonlinear sorption are approximated by capturing the effective Kd range (this Model 
Report, Section I.8). 
Sorption coefficients are provided in terms of probability distributions for the sorption 
coefficient of each element of interest among the three major rock types (devitrified, zeolitic, and 
vitric) found in the UZ. The influence of expected variations in water chemistry, radionuclide 
concentrations, and variations in rock surface properties within one of the major rock types are 

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incorporated into these probability distributions. These distributions are specified for each 
radionuclide/rock type combination (this Model Report, Section I.2 and I.4) and are sampled in 
the TSPA to account for the effects of natural variations in pore water chemistry and mineral 
surfaces on sorption. Correlations for sampling sorption coefficient probability distributions have 
been derived for the elements investigated (this Model Report, Section II). To derive the 
correlations, a rating system was first developed to rate the impact of six different variables on 
the sorption coefficient for a given element in each of the three major rock types. The six 
variables are pH, Eh, water chemistry, rock composition, rock surface area, and radionuclide 
concentration. Water chemistry refers to the major ion concentrations and silica. Rock 
composition refers to both the mineralogic composition of the rocks and the chemical 
composition of the minerals (e.g., zeolite compositions). The output DTNs for the sorption Kds 
and correlations are LA0302AM831341.002 and LA0311AM831341.001. 
2.2.09.01.0B, Microbial Activity in the UZ 
FEP Description: Microbial activity in the UZ may affect radionuclide mobility in rock and soil 
through colloidal processes, by influencing the availability of complexing agents, or by 
influencing groundwater chemistry. Changes in microbial activity could be caused by the 
response of the soil zone to changes in climate. 
Screening Decision and Regulatory Basis: Included 
Screening Argument: None. 
TSPA Disposition: The effects of microbes on sorption are included in the distributions for 
sorption coefficients used in TSPA. The sorption coefficient data on which the distributions are 
based are obtained in laboratory experiments in which crushed rock samples from the Yucca 
Mountain site are contacted with groundwaters (or simulated groundwaters) representative of the 
site, spiked with one or more of the elements of interest (this Model Report, Section I.5). The 
basic technique for the laboratory determination of sorption coefficients involved the contact of a 
groundwater sample, spiked with the radionuclide of interest, with a crushed sample of tuff or 
alluvium. The rock sample was generally obtained as a core sample. The rock and water samples 
were not sterilized and therefore contain representative microbial biota from the UZ. Sorption 
experiments have been carried out as a function of time, element concentration, atmospheric 
composition, particle size, and temperature. In some cases, the solids remaining from sorption 
experiments were contacted with unspiked groundwater in desorption experiments. The 
experimental data used to determine the sorption Kds are provided in the following DTNs: 
LA0305AM831341.001 [163789], LA0309AM831341.002 [165523], LA0309AM831341.003 
[165524], LA0309AM831341.004 [165525], LA0309AM831341.005 [165526], 
LA0309AM831341.006 [165527], LA0309AM831341.007 [165528], and 
LA0310AM831341.001 [165865]. The sorption and desorption experiments together provide 
information on the equilibration rates of the forward and backward sorption reactions. For 
elements that sorb primarily through surface complexation reactions, the experimental data are 
augmented with the results of modeling calculations using PHREEQC V2.3 (BSC 2001 
[155323]). The inputs for the modeling calculations include groundwater compositions, surface 
areas, binding constants for the elements of interest, and thermodynamic data for solution 
species. These modeling calculations provide a basis for interpolation and extrapolation of the 

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experimentally derived sorption coefficient dataset. The effects of nonlinear sorption are 
approximated by capturing the effective Kd range (this Model Report, Section I.8). 
The effects of microbial activity with respect to sorption coefficients are provided in terms of 
probability distributions for the sorption coefficient of each element of interest among the three 
major rock types (devitrified, zeolitic, and vitric) found in the UZ. The influence of expected 
variations in water chemistry, radionuclide concentrations, and variations in rock surface 
properties within one of the major rock types are incorporated into these probability 
distributions. These distributions are specified for each radionuclide/rock type combination (this 
Model Report, Section I.2 and I.4) and are sampled in the TSPA to account for the effects of 
natural variations in pore water chemistry and mineral surfaces on sorption. Correlations for 
sampling sorption coefficient probability distributions have been derived for the elements 
investigated (this Model Report, Section II). To derive the correlations, a rating system was first 
developed to rate the impact of six different variables on the sorption coefficient for a given 
element in each of the three major rock types. The six variables are pH, Eh, water chemistry, 
rock composition, rock surface area, and radionuclide concentration. Water chemistry refers to 
the major ion concentrations and silica. Rock composition refers to both the mineralogic 
composition of the rocks and the chemical composition of the minerals (e.g., zeolite 
compositions). The output DTNs for the sorption Kds and correlations are 
LA0302AM831341.002 and LA0311AM831341.001. 

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6.5 SORPTION MODEL, DIFFUSION, RADIOACTIVE DECAY, AND PARAMETERS 
In this section we discuss the radionuclide sorption model. The diffusion coefficients and the 
decay parameters of the radionuclides considered in this Model Report are also discussed. 
Based on the analysis in Attachments I and II, we substantiate the arguments for the validity of 
the linear equilibrium sorption model assumed to govern sorption in the UZ. The corresponding 
distribution coefficients Kd of the various radionuclides (describing sorption onto the UZ rocks) 
are listed in Table 6.5-1. A detailed discussion of the derivation process of these estimates and of 
the supporting laboratory data can be found in Attachment I. In this Model Report, all 
computations involving sorption are based on the linear equilibrium model and use Kd estimates 
of Table 6.5-1. 
Table 6.5-1. Kd in the Rocks of the Unsaturated Zone 
Species Unit/Analysis Distributiona Coefficients describing distributionb (ml/g) 
U Zeolitic Cumulative (Kd value, probability) (0, 0) (0.5, 0.5) (30, 1.0) 
Devitrified Cumulative (Kd value, probability) (0, 0) (0.2, 0.5) (4, 1.0) 
Vitric Cumulative (Kd value, probability) (0, 0) (0.2, 0.5) (3, 1.0) 
Np Zeolitic Cumulative (Kd value, probability) (0, 0) (0.5, 0.5) (6, 1.0) 
Devitrified Cumulative (Kd value, probability) (0, 0) (0.5, 0.5) (6, 1.0) 
Vitric Cumulative (Kd value, probability) (0, 0) (1.0, 0.5) (3, 1.0) 
Pu Zeolitic Cumulative (Kd value, probability) (10, 0) (100, 0.5) (200, 1.0) 
Devitrified Cumulative (Kd value, probability) (10, 0) (70, 0.5) (200, 1.0) 
Vitric Cumulative (Kd value, probability) (10, 0) (100, 0.5) (200, 1.0) 
Am Zeolitic Uniform Range = 100  1000 (500) 
Devitrified Uniform Range = 100  2000 (1,000) 
Vitric Cumulative (Kd value, probability) (100, 0) (400, 0.5) (1,000, 1.0) 
Pa Zeolitic Uniform Range = 1000  20,000 (10,000) 
Devitrified Uniform Range = 1000  20,000 (10,000) 
Vitric Uniform Range = 1000  20,000 (10,000) 
Cs Zeolitic Cumulative (Kd value, probability) (425, 0) (5,000, 0.5) (20,000, 1.0) 
Devitrified Uniform Range = 1  15 (7.5) 
Vitric Cumulative (Kd value, probability) (0, 0) (2, 0.5) (100, 1.0) 
Sr Zeolitic Uniform Range = 50  2000 (1000) 
Devitrified Uniform Range = 10  70 (40) 
Vitric Uniform Range = 0  50 (25) 
Ra Zeolitic Uniform Range = 1000  5,000 (2,500) 
Devitrified Uniform Range = 100  1,000 (500) 
Vitric Uniform Range = 50  600 (300) 
Th Zeolitic Uniform Range = 1,000 - 30,000 (15,000) 
Devitrified Uniform Range = 1,000 - 10,000 (5,000) 
Vitric Uniform Range = 1,000 - 10,000 (5,000) 
Output-DTN: LA0302AM831341.002 
NOTE: a The term cumulative indicates a piecewise linear distribution 
b The numbers in boldface were used in the simulations 

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The diffusion coefficients and the decay properties are listed in Table 6.5-2. Of the listed D0, 
only the first ones were used for the base 3-D simulations, while the rest were used for 
uncertainty bounding and sensitivity analysis (Sections 6.7). 
Table 6.5-2. Properties of Radionuclides in the Transport Simulations 
Radionuclide D0 (m2/s) T1/2 (years)  ) ( 2 ln 1 
2 / 1 
- = . s 
T 
Decay Mode  
99Tc 4.55 10-10 (a) 
4.55 10-11 (f) 
10-9 (f) 
2.13 105 1.031 10-13 - 
237Np 1.65 10-10 (b) 
7.12 10-10 (f) 
1.65 10-11 (f) 
10-9 (f) 
2.14 106 1.026 10-14 a 
239Pu 4.81 10-10 (c) 
4.81 10-11 (f) 
6.08 10-10 (f) 
10-9 (f) 
2.41 104 9.114 10-13 a 
241Am 3.6910-10(d) 4.322102 5.082 10-11 - 
233U 4.9410-10(c) 1.59105 1.381410-13 a 
235U 4.8910-10(c) 7.08108 3.102310-17 a 
231Pa 4.9810-10(c) 3.25104 6.758310-13 a 
229Th 5.0210-10(c) 7.90103 2.780310-12 a 
226Ra 8.8910-10(e) 1.599103 1.37410-11 a 
135Cs 2.0610-9(e) 2.30106 9.5510-15 - 
90Sr 7.911010(e) 2.90101 7.57410-10 - 
NOTE: (a): DTN: LA000000000034.002 [148603] 
(b): Using Mn+2 as analog, corrected for mass, see Lide (1992 [166224], pp. 5-111, 5-112) 
(c): Using UO+2 as analog, corrected for mass, see Lide (1992 [166224], pp. 5-111, 5-112) 
(d): Using Sm+3 and Ce+3 as analogs, corrected for mass, see Lide (1992 [166224], pp. 5- 
111, 5-112 
(e):directly used, see Lide (1992 [166224], 5-111, 5-112) 
(f): Values used for sensitivity analysis, see Section 6.8.3.2 
 : From Lide (1992 [166224], pp. 11-28  11-133) 
 : Values adjusted from Lide (1992 [166224], 11-13  11-133) 

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6.6 A PRELIMINARY CONCEPTUAL MODEL OF TRANSPORT BASED ON 
GEOLOGY AND STRATIGRAPHY 
6.6.1 General Issues 
This section focuses on the development of a conceptual model of radionuclide transport in 
composite vertical cross sections at select locations of the UZ. The conceptual model is based 
on the geology, stratigraphy and transport properties of the geohydrologic units in the profiles 
from the repository horizon to the water table at these locations. The focus is on the expected 
difference of transport patterns at different UZ locations (because of different geologies and 
conditions), and on the relative importance of particular geohydrologic units on overall transport. 
6.6.2 Hydrogeologic Profiles 
Transport is considered in three hydrogeologic profiles (columns) called Cross Sections 1, 2, and 
3. The three cross sections are located in the vicinity of the USW SD-6, SD-12, and UZ-14 
boreholes, respectively. The locations of the three boreholes in the context of the UZ site-scale 
model are shown in Figure 6.6-1. Thus, Cross Section 3 is located in the northern part of the 
repository site, while Cross Sections 1 and 2 are located in the southern part. The geologic 
profiles in Cross Sections 1, 2, and 3, including the layers of all the hydrogeologic units involved 
in radionuclide transport, their elevations and thicknesses, are shown in Figures 6.6-2 through 
6.6-4. Additional information on the three profiles can be found in Attachment III. 
6.6.3 Conceptual Model of Transport in Cross Sections 1 and 2 
Figure 6.6-5 illustrates a conceptual model of transport in Cross Sections 1 and 2. Water-borne 
radionuclides enter the TSw formation through the bottom of the repository. Radionuclide 
transport in the TSw hydrogeologic unit occurs mostly in the fractures. 
At this location the vitric layers in the underlying CHn unit (i.e., layers ch1v through ch5v) 
behave as porous (rather than fractured) media because of the parity of permeability in the 
matrix and in the fractures (BSC 2001 [161340], Section 6.7.2). Thus, transport occurs in both 
the matrix and the fractures, and the contact times between the radionuclides and the media is 
longer. The vitric layers are effective transport barriers because of the increased sorption (for 
sorbing radionuclides) and retardation (see Section 6.5, this Model Report). Once the 
radionuclide reaches the zeolitic ch6z unit, flow becomes again fracture-dominated, and, 
consequently, so does transport. 
Transport in the pp4 layer, the top layer in the PP hydrogeologic unit, is controlled by its zeolitic 
nature, which leads to fractured-dominated flow and transport. The next two layers (i.e., pp3 and 
pp2) are devitrified and behave similarly to the vitric layers in the CHn unit. Transport in the 
thick zeolitic pp1 layer (the last layer in the PP unit) is again fractured-dominated, as is transport 
in the underlying layers of the BF unit. 

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LEGEND 
UZ2002 Model Boundary 
2002 Repository Boundary 
2002 Repository Lower Block 
ESF and ECRB 
GFM2000 Faults 
Sever 
Wash 
Fault 
Exile 
Hill 
Fault 
Solitario 
Canyon 
Fault 
Ghost 
Dance 
(West) 
Fault 
Ghost 
Dance 
(West) 
Fault 
Solitario 
Canyon 
Fault 
(West) 
Dune 
Wash 
Fault 
Dune 
(West 
1) 
Ghost 
Dance 
Fault 
Imbricate 
Fault 
"Toe" 
Fault 
Splay 
"S" 
Dune 
"X" 
Bow 
Ridge 
Fault 
Pagany 
Wash 
Fault 
"SolJFat" 
Fault 
"SolJFat" 
Fault 
Drill 
Hole 
Wash 
Fault 
Sundance 
Fault 
Sundance 
Fault 
Splay 
"g" 
Splay 
"g" 
Splay 
"N" 
Splay 
"N" 
NSP Northing (m) 
NSP Easting (m) 
UZ-14 
SD-6 
SD-12 
Source: Modified from BSC 2003 [160109], Section 6, Figure 1a 
Figure 6.6-1. Two-Dimensional (Plan View) of the Yucca Mountain Site Identifying the Locations of 
Boreholes USW SD-6, SD-12, and UZ-14, Representing Cross Sections 1, 2, and 3 

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750 
850 
950 
1050 
1150 
0 100 
Elevation (m) 
tsw35 
tsw36 
tsw37 
tsw39 
ch1v 
ch4v 
ch3v 
ch2v 
ch5v
ch6v 
pp4 
pp2 
pp3 
pp1 
bf3 
groundwater table 
Repository 
tsw38 
DTN: LB03013DSSCP31.001 [162379] 
Figure 6.6-2. Hydrogeologic Units (and their Layers) of the UZ Model Domain from the Repository to the 
Groundwater in Cross Section 1 Near the USW SD-6 Borehole 

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MDL-NBS-HS-000008 REV 01 93 November 2003 
700 
800 
900 
1000 
1100 
0 100 
Elevation (m) 
tsw36 
tsw37 
tsw38 
tsw39 
ch1v 
ch4z 
ch3v 
ch2v 
ch5v 
ch6z 
pp4 
pp2 
pp3 
tsw35 
pp1 
groundwater table 
tsw34 
Repository 
ch1z 
DTN: LB03013DSSCP31.001 [162379] 
Figure 6.6-3. Hydrogeologic Units (and their Layers) of the UZ Model Domain from the Repository to the 
Groundwater Table in Cross Section 2 Near the USW SD-12 Borehole 

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700 
800 
900 
1000 
1100 
0 100 
Elevation (m) 
tsw35 
tsw36 
tsw37 
tsw38 
tsw39 
ch1z 
ch4z 
ch3z 
ch2z 
ch5z 
ch6z 
pp4 pp2 
pp3 
tsw35 
groundwater table 
Repository 
DTN: LB03013DSSCP31.001 [162379] 
Figure 6.6-4. Hydrogeologic Units (and their Layers) of the UZ Model Domain from the Repository to the 
Groundwater in Cross Section 3 Near the USW UZ-14 Borehole 

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MDL-NBS-HS-000008 REV 01 95 November 2003 
Repository 
ch (1-5)v 
tsw 36-39 
ch6z 
pp4 
pp3 
pp2 
pp1 
bf3 
bf2 
SOURCE: Modified from CRWMS M&O 2000 [151940], Figure 3.11-3. 
Figure 6.6-5. A Conceptual Model of Transport in Cross Section 1. 

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6.6.4 Conceptual Model of Transport in Cross Section 3 
Figure 6.6-6 illustrates a conceptual model of transport in Cross Section 3. Water-borne 
radionuclides enter the TSw formation through the bottom of the repository. Radionuclide 
transport in the TSw hydrogeologic unit occurs mostly in the fractures. In contrast to Cross 
Section 1, Cross Section 3 is characterized by the absence of vitric layers in the underlying CHn. 
The zeolitic layers here have fracture spacing and fracture permeability similar to those in Cross 
Section 1, but the matrix permeability is about five orders of magnitude lower than that in the 
fractures (BSC 2003 [163045], Section 6; BSC 2001 [161340], Section 6). The disparity in 
permeability directs practically all flow into the fractures, leading to fast transport. 
The pp4 layer, the top layer in the PP hydrogeologic unit, behaves like a zeolitic layer, leading to 
fractured-dominated flow and transport. The next two layers (i.e., pp3 and pp2) are devitrified 
and behave like porous media, and the pp1 layer (a thick zeolitic layer, and last one in the PP 
unit) is again fracture-dominated. 
6.6.5 Synopsis and Discussion 
A review of the conceptual model in Section 6.6 indicates that while the geological profiles in 
Cross Sections 1 and 2 appear likely to afford good retardation of radionuclide transport (and 
especially of strongly sorbing radionuclides), this is unlikely to be the case in the domain of 
Cross Section 3, because of the preponderance of highly permeable (compared to the matrix) 
fractures of the zeolitic layers at this location. Based on general transport principles, a 
decreasing Kd is expected to lead to faster transport to the water table, although strongly sorbing 
radionuclides (such as 239Pu, 231Pa, 229Th) are unlikely to be significantly affected. 
Increases in the infiltration rate, brought about by possible changes in climatic patterns, can have 
a substantial impact on breakthrough times, especially at the Cross Section 3 location. The effect 
of changes in infiltration is likely to become more pronounced with weaker-sorbing 
radionuclides. 
The conceptual models supported by these results are consistent with the observations that were 
based on a simplified 2-D analysis included in the previous revision of this Model Report 
(CRWMS M&O 2000 [122799], Section 6) and in CRWMS M&O 2000 [151940], from which 
Figures 6.6-4 and 6.6-5 originated. 

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UZPMR3.11-3REV1 
tsw35 
tsw36 
tsw37 
tsw38 
tsw39 
ch6z 
ch5z 
ch4z 
ch3z 
ch2z 
ch1z 
pp4 
pp3 
pp2 
pp1 
Repository 
SOURCE: Modified from CRWMS M&O 2000 [151940], Figure 3.11-3. 
Figure 6.6-6. A Conceptual Model of Transport in Cross Section 3. 

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6.7 THREE-DIMENSIONAL TRANSPORT SIMULATIONS 
In this section, we discuss the general issues involved in the 3-D radionuclide transport through 
the UZ of Yucca Mountain, i.e., climatic conditions, hydrologic conceptual model, grids, flow 
systems, the radioactive species considered and the mode of their release, data inputs and 
outputs, in addition to the general approach and basic stipulations. All the 3-D numerical studies 
of radionuclide transport use a grid identical to that employed in the flow analysis documented in 
the Model Report UZ Flow Models and Submodels (BSC 2003 [163045]). The development and 
features of the 3-D grids for this numerical modeling effort are documented in the Analysis 
Report Development of Numerical Grids for UZ Flow and Transport Modeling (BSC 2003 
[160109]) and further discussed in BSC (2003 [163045], Section 6). 
6.7.1 Climatic Conditions 
The three climatic scenarios investigated here are identical to those discussed in BSC (2003 
[163045], Section 6): present-day, monsoon and glacial. In this Model Report, reference to a 
glacial regime is intended to indicate glacial transition climate, as described in USGS 2001 
[158378], Table 2, p. 66, rather than a full glacial climate. For each climatic scenario, a high, 
mean and low infiltration case was studied. The annual infiltration rates corresponding to each of 
the nine climatic cases are listed in Table 6.7-1. 
6.7.2 Conceptual Hydrologic Model, Grids and Flow Simulations 
The grid, properties, and calibrated hydraulic parameters used in the transport simulations (DTN: 
LB03023DSSCP9I.001 [163044]) were identical to those used for the analysis of flow in BSC 
(2003 [163045], Section 6), in the course in which they were derived. These correspond to the #1 
conceptual model of perched water (BSC 2001 [158726], Section 6.2). This is the permeability 
barrier model, which uses the calibrated perched-water parameters for fractures and matrix in the 
northern part of the model domain, and modified property layers (including the tsw38, tsw39, 
CH1z and CH2z layers) where the lower basal vitrophyre of the TSw is above the zeolites of the 
CHn. A detailed discussion of this perched-water model can be found in BSC (2003 [163045], 
Section 6.2). 
A 2-D (plan view) of the grid at the repository level is shown in Figure 6.7-1. All 3-D transport 
simulations that involved the use of the T2R3D numerical model were conducted using this grid 
and the steady-state flow fields from BSC (2003 [163045], Section 6) for the 9 climatic scenarios 
(DTN: LB03023DSSCP9I.001 [163044]). Table 6.7-1 provides averaged percolation values of 
all 9 climatic scenarios in order to show how there is more percolation flux under some climates 
than others. 
For the 3-D EOS9nT simulations, the same grid was used, but its numbering was altered. This 
modification involved a very minor rearrangement of the element order number using the 
XtractG.f90 routine, which moved (a) the elements above the repository, (b) those corresponding to 
the location of the repository, and (c) the bottom boundary elements (corresponding to the water 
table) to the bottom of the element file. Moving these elements to the bottom of the element file 
made use of the ability of the TOUGH2 family of codes to treat them as inactive elements (i.e., 
elements that have time-invariant properties and conditions, contribute to flow and transport as 

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boundaries, and are not accounted for in mass and energy balances). To accomplish that, the only 
modification was making the volume of the first repository element zero or negative. In the 
TOUGH2 convention, this rendered all the following elements inactive, thus maintaining their 
properties and conditions constant throughout the simulations. 
Making these elements inactive was possible because (a) the steady state of the flow fields is 
unaffected by making these elements inactive, (b) in the EOS9nT simulations the release rate was 
considered constant over time, a condition which necessitated treating the repository elements as 
internal boundary elements, and (c) the elements above the repository do not contribute to transport 
and can also be treated as boundary elements. This modification reduced the number of active 
elements by about 50% in the EOS9nT calculations, made the simulation possible within the array 
size of the code, and significantly reduced the execution times, with absolutely no effect on or 
compromise of the transport computations . 
Note that all the properties and the attributes of the original grid were maintained, and the only 
change was the numbering sequence of the elements. Because the element names remained 
unaltered, the initial pressure and saturation conditions from the flow computations BSC (2003 
[163045], Section 6) were applied unchanged, but the flow field could not be used as was provided 
by the simulations in BSC (2003 [163045], Section 6) because those did not reflect the changed 
element numbers. 
Thus, an updated steady state flow field (involving the same information as the old one, but in a 
different sequence) was obtained from a single TOUGH 2 V1.4 (Module EOS9 V1.4) (LBNL 
2000 [146496]) simulation that used the modified grid and the initial pressure and saturation 
conditions from the flow computations (BSC 2003 [163045], Section 6). Only a single run was 
needed because all the EOS9nT simulations were made assuming a mean present-day infiltration 
scenario (see Table 6.7-1). After the EOS9 simulation, the output file SAVE was compared to 
those from the simulations using the unmodified grids to confirm that they were identical. Note 
that EOS9nT (LBNL 1999 [113943]) shares identical flow solution routines with EOS9, and 
confirmatory tests confirmed the identity of the flow solutions predicted by both EOS9 and 
EOS9nT. It was decided, however, to use the EOS9 module in the TOUGH2 flow simulations to 
ensure complete compatibility with the results in BSC (2003 [163045], Section 6). 
The velocity distribution (stored in the input file VELOC for the EOS9nT simulations) was then 
extracted from the EOS9 output by using the XtractG.f90 routine. The DTN of the modified grid, 
the XtractG.f90 input and output, and the EOS9 input (modified) and output files are Output- 
DTN: LB0307MR0060R1.003. 
Table 6.7-1. Percolation Fluxes (mm/year) for Different Climatic Regimes 
Value Present-Day Infiltration Monsoon Infiltration Glacial Infiltration 
Lower 1.25 4.43 2.35 
Mean 4.43 11.83 17.02 
Upper 10.74 19.23 31.69 
Values averaged from DTN: GS000308311221.005 [147613] 

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6.7.3 Modes of Radionuclide Release 
In all the ensuing 3-D studies of site-scale radionuclide transport, the radioactive substances 
were released in the liquid phase in the fractures of the elements corresponding to the repository. 
The initial radionuclide concentration was spatially uniform in the area of release, which covered 
the entire footprint of the repository. We investigated two modes of radionuclide release: 
instantaneous release and continuous release. 
6.7.3.1 Instantaneous release 
An instantaneous release scenario corresponds to a single catastrophic event during which a 
finite mass of radionuclides is suddenly released in the liquid phase of the fractures of the 
repository. Study of the system performance following an instantaneous release provides the 
measure of the ability of the UZ to store and retard the migration of a limited mass of radioactive 
substances. 
6.7.3.2 Continuous release 
Under a continuous release scenario, radionuclides are continuously released into the fractures of 
the elements corresponding to the repository. This is a realistic scenario, given the mass of the 
radioactive substances to be stored at the site, the expected deterioration of the canisters, and the 
planned closure of the repository after the storage of the radioactive materials (thus preventing 
access and repairs that might control continuous release). 
The concentration of the released radionuclides changes over time because the released 
radionuclides undergo radioactive decay at the input points (boundaries). Such an approach 
involves the assumption that all the radionuclides were produced as a batch at the same time, and 
is valid for all but the shortest-lived isotopes. This is far more consistent with reality than an 
assumption of a constant-boundary concentration, which implies continuous radionuclide 
production at the release point. 
Study of an instantaneous release scenario provides a criterion of absolute system performance 
and evaluates the time for a given radionuclide mass to migrate past the UZ boundaries. Such a 
measure of performance is inadequate and inapplicable under a continuous-release regime, the 
study of which necessitates a criterion of a relative system performance based on the relationship 
of inflow and outflows across the system boundaries. This provides a measure of the ability or 
capacity of the domain to accumulate radionuclide mass that enters its boundary at a given rate, 
and is just as important (if not more so) than the conventional breakthrough study that can only 
describe response to a finite mass release. Thus, under instantaneous releases, masses are 
compared, while in continuous release the relationship of fluxes is established. For a complete 
evaluation of the repository, performance under both release scenarios must be evaluated. 

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Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
Solitario 
Canyon 
Fault 
D 
rillho 
le 
Wash 
Fault 
PaganyWash 
Fault 
S 
ever 
Wash 
Fault 
Ghost 
Dance 
Fault 
Bow Ridge Fault 
Imbricate 
Fault 
Repository block 
DTN: LB990701233129.001 [106785] 
Figure 6.7-1. Two-Dimensional (Plan View) of the UZ Model Grid Design at the Repository Level 

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6.7.4 Radionuclides Considered 
The following radioactive solutes were considered: 
(a) 99Tc (nonsorbing), 
(b) 237Np, 235U, 233U (moderately sorbing), 
(c) 241Am, 239Pu, 231Pa, 229Th, 226Ra, 90Sr (strongly sorbing). 
Their properties are listed in Tables 6.5-1 and 6.6-1. The radionuclides are released at the 
gridblocks corresponding to the location of the repository. Additionally, for the 3-D EOS9nT 
simulations of continuous release, all the important members in the decay chains of 241Am and 
239Pu were considered, according to the decay equations (Pigford et al. 1980 [123113]) 
241Am 237 Np 233 U 229 Th (Eq. 6-29) 
239Pu 235 U 231 Pa (Eq. 6-30) 
Note that only the most important members of the radioactive chain are included in these decay 
equations, which omit daughters with short half-lives. Given that alpha decay is the decay mode 
of all the members in the 237Np and 239Pu chains, .=0 (Equation 6-27) in all the simulations 
reported in this Model Report because the daughters are ejected from grain surfaces due to recoil 
(Faure 1977 [122805], pp. 288289). 
The transport of radioactive colloids was also investigated. Spherical PuO2 colloids with 
diameters of 6 nm, 100 nm, 200 nm and 450 nm were used in this study. 
6.7.5 Important Geologic Features 
As will be clearly shown in the ensuing Sections 6.7 through 6.17, the role of faults in the 3-D 
site-scale transport model is very important because faults provide fast pathways for the 
radionuclide migration to the water table. In the EOS9, T2R3D and EOS9nT simulations, the 
faults are represented as thin vertical domains characterized by large permeabilities. More 
detailed description of the faults, their properties and their role in water flow, can be found in 
BSC (2003 [161773], Section 6.4), BSC (2002 [159124], Sections 6.2, 6.4, and 6.5), and BSC 
(2003 [163045], Section 6). 
6.7.6 Transport Simulation Options 
The 3-D simulations involving the instantaneous release of radionuclides were conducted using 
the T2R3D code with the steady-state flow field option. T2R3D employs conventional timestepping. 
All the 3-D simulations describing continuous release of solutes and colloids were conducted by 
using the EOS9nT code with the De Hoog et al. (1982 [117308]) implementation of the Laplace 
transform formulation. This formulation was selected because of its speed and accuracy, its 

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MDL-NBS-HS-000008 REV 01 103 November 2003 
ability to provide information over the whole spectrum of the simulation period, and its ability to 
drastically reduce numerical diffusion. The resulting matrices were very well behaved, requiring 
no more than 1015 conjugate gradient iterations to reduce residuals to below the 10-11 level in a 
matrix of order of about 220,000. Thus, simulations were very fast and efficient, requiring 
1,8002,200 seconds of execution time to cover a simulation period of 1,000,000 years. 
EOS9nT allows the simultaneous solution of the concentration profiles of any number of 
radionuclides. Thus, all three parents (99Tc, 237Np, 239Pu) were considered simultaneously in the 
runs. Similarly, exploiting the fact that EOS9nT allows the tracking of any daughter products, 
the solutions for each of the parent radionuclides and its daughters in the decay Equations 6-29 
and 6-30 were obtained simultaneously. 
6.7.7 Basic Data Inputs and Outputs 
All the 3-D T2R3D simulations for all radionuclides used the same grid, calibrated hydraulic 
parameters, and steady-state flow field. The initial condition files were different, as they 
reflected the nine different climatic conditions. All the corresponding data files were provided 
(and used without modification) from the flow analysis studies of BSC (2003 [163045]). Input 
files were developed for the T2R3D simulations for the radionuclides studied in this Model 
Report. 
The 3-D EOS9nT radionuclide simulations and the T2R3D simulations shared the same 
calibrated hydraulic parameters and initial flow conditions. The EOS9nT simulations used a 
slightly modified grid from that in T2R3D (Section 6.7.2) (composed of the same elements as the 
T2R3D grid, but with different ordering), and the corresponding flowfield for mean present-day 
infiltration. Using the latter, input files conforming to the EOS9nT requirements (including both 
flow and transport information for the various radionuclides under study) were created. 
The DTNs of the input and output files used and created in the course of this study of 
radionuclide transport through the UZ are listed in Table 6.7-2. 
6.7.8 Review of the Approach and Basic Approximations in the 3-D Site-Scale 
Radionuclide Transport Studies 
For a better understanding and a more realistic interpretation of the results of the 3-D 
simulations, it is important to understand the basic approach and approximations employed in the 
study of transport in the UZ. Analysis of the simulation results without considering the 
extremely conservative approach and the succession of worst-case scenarios involved in the 3-D 
studies can lead to erroneous conclusions and a distorted view of the transport regimes through 
the UZ. To that effect, the note of caution discussed in Section 6.20.3 should be carefully 
reviewed. 
The numerical simulations are based on the following approximations and approach (not all of 
which will be incorporated in the TSPA model): 
(a) No drip shields are considered, and flow through the canisters is assumed. Thus, 
water from the drift roof is allowed to fall onto, and then flow uninhibited through the 

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waste package, carrying radionuclides as it emerges from the ruptured container. 
This is a worst-case scenario, and rather unrealistic. 
(b) All the radioactive packages in the entire repository rupture simultaneously, with all 
of them releasing their contents simultaneously at the beginning of the simulation 
time. This is an improbable (if not outright impossible) release scenario. 
(c) The radionuclides are released directly into the fractures. The retardation effects of 
the invert (with porous media properties) underneath the waste packages are ignored. 
The presence of the invert can significantly delay the onset of radionuclide release 
into the underlying fractures. 
(d) The effects of the shadow zone are ignored. However, the presence of the shadow 
zone can lead to significant retardation of radionuclide transport (BSC 2003 
[164889]). The presence of the shadow zone can lead to significant retardation of 
radioactive solute transport (BSC 2003 [164889]) because of the generally lower 
saturations. These lead to drastically lower water velocities in the shadow zone (into 
which water moves mainly in response to capillary pressure differentials), and to 
significantly lower diffusive fluxes across the matrix-fracture interfaces. The effect of 
the shadow zone on the transport of colloids is expected to be far more severe 
because advective fluxes are extremely low, and diffusive fluxes (the only 
mechanism capable of transporting radionuclides past the boundaries of the shadow 
zone) are dramatically depressed (as the colloid diffusion coefficient is generally 
orders of magnitude lower than the molecular diffusion coefficient of solutes). 
(e) The vertical fractures are modeled as continuous throughout the UZ from the 
repository to the water table. Additionally, all the vertical fractures are open (i.e., 
they are not even partially filled with a porous medium), and do not retard transport 
through solute sorption and/or colloid attachment onto the fracture walls. The 
implication of this approach/assumption of uninterrupted vertical fractures is fast and 
unimpeded advective transport of radionuclides from the repository to the water table. 
This worst-case scenario is highly unlikely. 
(f) The horizontal fractures are modeled as interconnected, and are also connected 
(directly or indirectly) to the vertical fractures. This scenario leads to accelerated 
migration of radionuclides to the water table. 
(g) The radioactive tracers (solutes or colloids) are stable, unaffected by the near field 
conditions (thermal, geochemical, physical), and are not subject to chemical 
immobilization (e.g., through irreversible sorption or precipitation) anywhere in the 
UZ. 
(h) The distribution coefficients were estimated over longer concentration intervals using 
an approach that results in milder slopes and lower Kd values. This results in lower 
overall sorption, and leads to more conservative estimates of transport that 
correspond to faster radionuclide arrivals at the water table. 

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(i) For simulation of the instantaneous radionuclide release scenario, the relative 
concentration (CR = C/C0) in the water saturation of all the elements corresponding to 
the fractures of the repository subdomain is set at an initial value of CR = 1, i.e. the 
initial release concentration is uniformly distributed in the repository fractures. Note 
that the water saturation in the fractures is that corresponding to the steady state flow 
field for the given infiltration regime. 
Given these simplifications (each one of which can accelerate release by thousands of years), the 
simulation results reflect a rather unrealistically conservative radionuclide release scenario, and 
are relevant (though by no means representative) after the radioactive species escape the 
immediate vicinity of the repository in a stable form. The onset of such release can occur a long 
time (thousands to hundreds of thousands) of years after the initial placement of the radioactive 
wastes in the repository. Thus, the radionuclide arrival times discussed in the following sections 
are meaningful only after (a) the drip shield and the canisters fail completely, (b) the 
radionuclides escape the effects of near-field hydrology, chemistry, and hydrology, and (c) enter 
a fully interconnected fracture system. 
Note that the transport model discussed here is intertwined with the UZ flow model discussed in 
BSC (2003 [163045]). As such, it shares the same conceptual strengths and weaknesses. 
Changes in the conceptual model of flow can and will have a significant effect on transport. In 
particular, if an alternative flow model (in which faults act as barriers rather than conduits to 
flow) is validated, dramatic changes in the transport performance of the UZ are not just possible 
but likely. 

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Table 6.7-2. DTNs of Input and Output Files of the 3-D Site-Scale Transport Simulations 
Item DTN 
3-D grid for T2R3D runs LB03023DSSCP9I.001 [163044] 
Steady state 3-D flow fields for 9 climatic scenarios (Table 6.7-1) LB03023DSSCP9I.001 [163044] 
Calibrated rock properties, hydraulic parameters, flow parameters LB03023DSSCP9I.001 [163044], 
LB0210THRMLPRP.001 [160799] 
Input/Output files for the UZ radionuclide transport studies under 
instantaneous release (11 radionuclides, 9 climatic scenarios, 
sensitivity analyses, with direct radionuclide release into the fault 
fracture) 
LB0307MR0060R1.001 
Data summaries and plot files corresponding to DTN: 
LB0307MR0060R1.001 
LB0307MR0060R1.002 
Input/Output files for the UZ radionuclide transport studies under 
mean present-day infiltration-continuous release (3 radioactive 
parent species, a 3- and a 4- member radioactive chain, 4 
radioactive colloids, sensitivity analyses, with direct radionuclide 
release into the fault fracture) 
LB0307MR0060R1.003 
Data summaries and plot files corresponding to DTN: 
LB0307MR0060R1.003 
LB0307MR0060R1.004 
Input/Output files for UZ radionuclide transport studies without 
direct releases in the faults-continuous and instantaneous release 
(4 radionuclides, mean present-day infiltration) 
LB0307MR0060R1.005 
Data summaries and plot files corresponding to DTN: 
LB0307MR0060R1.005 
LB0307MR0060R1.006 
Data summaries and corresponding breakthrough curves for the 
radionuclide transport scenarios in DTNs: 
LB0307MR0060R1.001; LB0307MR0060R1.003; and 
LB0307MR0060R1.005 
LB0307MR0060R1.007 
Supplemental Radionuclide Transport Simulations: Input/Output 
files (Influence of three main geologic units (TSw, CHv and CHz), 
irreversibly sorbed radionuclides onto colloids, transport of Tc, 
Np, and Pu with no diffusion (instantaneous, continuous 
releases)) 
LB0310MR0060R1.010 
Data summaries and plot files corresponding to DTN: 
LB0310MR0060R1.010 
LB0310MR0060R1.011 

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6.8 3-D SIMULATIONS OF 99Tc TRANSPORT-INSTANTANEOUS RELEASE 
In this section we investigate the transport of 99Tc by means of 3-D site-scale simulations 
representing the entire UZ system of Yucca Mountain. The study analyzes the migration of this 
finite radionuclide mass through the UZ, and investigates the processes and phenomena that 
affect its arrival at the water table. 
Section 6.8 includes three subsections. In Section 6.8.1, we discuss the transport of the nonsorbing 
99Tc for three levels of present-day infiltration. The results of this study are shown in 
Figures 6.8-11 to 6.8-24. In Section 6.8.2, we study the transport of 99Tc for three levels of (a) 
monsoon infiltration (Figure 6.8-25) and (b) glacial infiltration (Figure 6.8-26). Finally, in 
Section 6.8.3, we discuss uncertainties involved in the predictions, and we conduct sensitivity 
analyses to develop the envelop of possible solutions (Figure 6.8-27). 
6.8.1 99Tc Transport Under Present-Day Infiltration 
The DTNs of the input and output files for the three present-day infiltration scenarios are listed 
in Table 6.7-2. The input parameters used in the T2R3D simulations of 3-D transport of the 
nonsorbing 99Tc are listed in Table 6.8-1. 
6.8.1.1 Breakthrough Curves 
The release of a finite amount of radionuclide mass allows the use of the conventional concept of 
breakthrough. This is quantified by the evolution over time of the cumulative breakthrough of 
the 99Tc mass fraction arriving at the Yucca Mountain water table RM, defined as 
RM = 
M0 -M 
M0 
, 
where M0 is the instantaneously released initial mass of the radionuclide (at t=0) and M is the 
radionuclide mass remaining in the domain of interest (i.e., in the UZ) at the time of observation. 
Note that the radionuclide mass M undergoes radioactive decay and decreases over time. In the 
instantaneous release studies, only the mass of the parent radionuclide is considered, i.e. the 
daughter products are not tracked. The RM of 99Tc at the repository in Figure 6.8-1 shows a very 
strong dependence on the infiltration regime. 
As the infiltration rate increases from low to mean, the t10 time, defined as the time at which 
RM = 0.1, decreases from about 13,900 years to about 83 years. Thus, t10 is an indicator of the 
effects of the most conductive geologic features (i.e., certain fractures) on transport. The t50, 
defined as the time at which RM =0.5, is not reached within 1,000,000 years for the low 
infiltration regime, but is at 6,640 years for mean infiltration regime. Further increase of 
infiltration to high present-day levels leads to a decrease of t10 to about 6 years, and of t50 to 230 
years. The t10 and t50 of all the radionuclides discussed in this Model Report are summarized in 
tabular form in Tables 6.20-1, 6.20-2 and 6.20-3. It should be kept in mind that the term RM is 
relative, and these findings are only important if the magnitude of the released mass at the 
repository becomes significant. Figure 6.8-1 also shows that the maximum attainable 
RM increases with the infiltration rate. This is expected because lower infiltration results in lower 
velocities and longer travel times through UZ, and more radioactive decay occurs. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
99 Tc - Present Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007 data submitted with this Model Report 
Figure 6.8-1. Cumulative Breakthrough of the 99Tc Mass Fraction RM at the Water Table for Varying 
Present-Day Climatic Scenarios 
Table 6.8-1. Input Parameters for the 3-D Site-Scale Simulations of Solute Transport 
(#1 Perched-Water Model) 
Parameters Source 
Tortuosity t f Grathwohl (1998 [141512], pp. 28-35), Farrell and Reinhard 
(1994 [122803], p. 64) 
Properties and characteristics of the 
geologic units, steady-state pressures, 
water saturations and flow fields 
Table 6.7-2 (DTN: LB03023DSSCP9I.001 
[163044], LB0210THRMLPRP.001 [160799]) 
Sorption distribution coefficients Kd Table 6.5-1 (see Attachment I) 
Molecular diffusion coefficient D0 Table 6.5-2 
NOTE: See Section 5, Table 5-1 for assumptions 

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6.8.1.2 Transport-Controlling Features and Flow Patterns 
In the study of radionuclide transport, we use the relative mass fraction XR, defined as 
XR = X 
X0 
= C 
C0 
= CR 
where X is the tracer mass fraction in the liquid phase (M/M), C is the tracer concentration in the 
liquid phase (M/L3), and the subscript 0 denotes the value of the subscripted parameter in the 
water released from the repository. For mean present-day infiltration, the distribution of the 99Tc 
XR in the aqueous phase within fractures and the matrix in the gridblocks directly above the 
TSw-CHn interface (i.e., at the bottom of the TSw, corresponding to the tsw39 layer) is given in 
Figures 6.8-2 through 6.8-11 for t = 10, 100, 1,000, 10,000, and 100,000 years. Note that the 
XR distributions in Figures 6.8-2 through 6.8-11 do not correspond to a plan view of a horizontal 
cross section, but follow the uneven topography of the bottom of the tsw39 layer. The 
XR distributions of 99Tc in the fractures and in the matrix immediately above the water table at 
the same times are given in Figures 6.8-12 through 6.8-21. 
From the comparison of these figures with Figure 6.7-1, it becomes apparent that transport in the 
RTM is both dominated and controlled by the faults. From the distribution of the fracture XR at 
the bottom of the TSw, it is evident that, immediately above the TSw-CHn interface (i.e., in the 
tsw39 layer), the Pagany Wash fault and the Drillhole Wash fault in the northern part of are the 
main transport-facilitating feature. As expected, radionuclide transport to that layer 
(immediately below the repository) is rapid. The impact of the faults on transport is evident as 
early as t=10 yrs, at which time the Pagany Wash fault appears to provide the fastest pathway 
(Figure 6.8-2), as indicated by the early appearance of radionuclides. Although 99Tc arrives later 
at the Drillhole Wash fault, it appears to have a larger contribution than the Pagany Wash fault 
for t =100 years. Both faults register a strong signature, and their presence is easily identified 
from the 99Tc distributions (Figure 6.8-4). At the same time, it is noteworthy that the Sundance 
fault is beginning to cast a faint shadow on the fracture XR map. 
The predominance of the Drillhole Wash fault and the Pagany Wash fault as the main 
transport-facilitating geologic features at the tsw39 level is pervasive during the entire 
simulation period, as evidenced by Figures 6.8-6, 6.8-8, and 6.8-10. At later times 
(t =10,000 years), the Solitario Canyon fault becomes an important transport conduit. The 
northern reach of the Ghost Dance fault becomes visible at t =1,000 years, but appears to be of 
secondary importance to transport to the tsw39 layer. 
Review of the fracture XR distributions at the water table (Figures 6.8-12, 6.8-14, 6.8-16, 6.8-18, 
and 6.8-20) indicates that the Drillhole Wash fault and the Pagany Wash fault continue to be the 
main transport conduits throughout the geologic profile, from the level of the repository to the 
water table. It is remarkable that these two faults show measurable radionuclide presence at the 
water table as early as t = 10 years, and at concentrations that are higher and more widely 
distributed than those observed at the bottom of the TSw (Figures 6.8-4 and 6.8-6). In other 
words, transport through these two faults is so fast that the water table concentrations of 99Tc 
exceed those immediately below the release point at t = 10 years because the radionuclides 
released into the repository fractures have already reached the water table. 

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In general, the appearance of 99Tc at the water table appears to be earlier and more pronounced at 
the water table than at the bottom of the TSw. Additionally, more faults active in radionuclide 
transport are evident at the water table. Note the early and strong signature of the Sundance fault 
and of the Sever Wash fault (which appears to intersect the radionuclide-carrying fractures 
emanating from the Pagany Wash fault) at t=10 years (Figure 6.8-12). 
The significance of the Drillhole Wash fault as the dominant conduit of 99Tc to the water table is 
further confirmed in Figure 6.8-14 (t = 100 years), where it is shown to have resulted in a large 
zone of high 99Tc concentrations that extends outward from the fault axis. At this time, in 
addition to the Sundance fault, the northern portion of the Ghost Dance fault and the Solitario 
Canyon fault appear to be making significant contributions to transport. 
Analysis of the matrix XR distributions at the bottom of the TSw and at the water table offers 
additional insights into the transport patterns. It is remarkable that, in tsw39, the matrix 
XR distributions at early times (Figures 6.8-3 and 6.8-5) show the highest concentrations in the 
southern part of the repository, in sharp contrast to the fractures that indicate transport 
exclusively in the northern part at the same times (Figures 6.8-2 and 6.8-4) and practically no 
sign of significant 99Tc presence in the matrix next to the rapidly transporting fractures. 
The reason for these vastly diverse transport patterns is the significantly different geology at the 
base of the TSw, which is dominated by the vitric CHv layers below the southern part of the 
repository, while the zeolitic CHz layers are predominant in the north. The permeabilities of the 
fractures and of the matrix of the vitric layers are similar in magnitude (BSC 2003 [160240], 
Section 6). This permeability parity, coupled with a large fracture spacing, result in a behavior 
similar to that of a nonfractured porous medium (BSC 2003 [160240], Section 6). Thus there is 
no early evidence of fracture flow in the southern part of the repository. 
In contrast, although the zeolitic CHz layers in the northern part of the repository have fracture 
spacing and fracture permeability similar to the vitric CHv layers in the south, their matrix 
permeability is about five orders of magnitude lower than their fracture permeability (BSC 2003 
[160240], Section 6). Consequently, matrix flow in the zeolitic layers in the northern part of the 
repository is extremely slow and practically all the flow occurs in the fractures, leading to the 
fast transport observed in the fractures. 
The eastward movement of 99Tc in the matrix (Figures 6.8-5, 6.8-7 and 6.8-9) results from site 
geology. Once contamination reaches the interface, it moves primarily eastward, moving with 
the draining water that hugs the downward sloping (in this direction) low-permeability 
TSw-CHn interface. At later times, the matrix XR footprint shifts northward, as 99Tc diffusing 
from the fractures advances in matrix. This is evidenced by the transition apparent in Figures 
6.8-5, 6.8-7 and 6.8-9). 
The presence of 99Tc in the matrix at the water table is significantly delayed, and we do not 
observe a pattern similar to that at the bottom of the TSw at early times. Despite significant 
radionuclide concentrations in the fractures associated with the faults discussed earlier, the 
matrix shows scant evidence of 99Tc presence (Figures 6.8-13 and 6.8-15). When it occurs, it 
follows the fault geometry and orientation, and is localized and limited to the immediate vicinity 

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MDL-NBS-HS-000008 REV 01 111 November 2003 
of the faults, indicating an origin consistent with diffusion from the fault fractures with no sign 
of downward migration through the matrix. 
This matrix concentration pattern further attests to the preponderance of fractures as the main 
transport-facilitating features. A pervasive feature of the transport pattern at the water table is 
that the area affected by significant radionuclide concentration is significantly larger in the 
fracture system than in the matrix. This is the opposite of what we observe at the bottom of the 
TSw, where the areal distribution of the matrix XR exceeds the footprint of the fracture XR. The 
obvious conclusion is that the fractures are practically the exclusive source of radionuclides 
appearing in the matrix, and that the large water velocities in the fractures lead to the limited 
areal extent and penetration of 99Tc into the matrix. 
6.8.1.3 Evidence Supporting the Transport Patterns 
Of particular interest is the emerging transport pattern, which indicates that radionuclide 
transport to the water table is faster in the northern part of the repository, where it is also areally 
concentrated. Based on the properties of the layers beneath the repository, this appears to be 
qualitatively consistent with expectations of transport in the vertical cross sections discussed in 
Section 6.6. 
Thus, the general area of fastest, largest, and most extensive transport is in the northern part of 
the repository site, where the very low matrix permeability of the CHz directs practically all flow 
through the fractures. Figures 6.8-22a and 6.8-22b show the areally increasing extent of the 
fractured zeolitic tuffs with depth (Output-DTN: LB0307MR0060R1.002). As the distance 
from the repository increases, an increasing portion of the water flow occurs through the zeolites, 
in which the matrix permeability is very small and the fractured dominated flow (and, 
consequently, the advective transport) is fast. 
In addition to geology, support for the observed transport pattern is provided by the infiltration 
and percolation distributions. A review of the infiltration pattern (Figure 6.8-23) at the surface, 
the percolation flux at the repository level (Figure 6.8-24) and the percolation flux at the 
groundwater level (Figure 6.8-25) indicates that they closely reflect the transport patterns in 
Figures 6.8-2 through 6.8-21. These figures indicate that the water flow pattern dictates the 
advective transport pattern. 
The dominance of fracture flow (and, consequently, of advection-dominated transport) is 
supported by the relative magnitudes of hydraulic properties in the fractures and in the matrix. 
The permeability of the fractures in the faults can be as high as hundreds of darcies (BSC 2003 
[160240], Section 6; Bodvarsson et al. 1999 [120055], p. 15), i.e., orders of magnitude larger. 
The resulting fast advective transport is the reason for the transport pattern observed in Figures 
6.8-2 through 6.8-21. 

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Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-01 
9.50E-02 
9.00E-02 
8.50E-02 
8.00E-02 
7.50E-02 
7.00E-02 
6.50E-02 
6.00E-02 
5.50E-02 
5.00E-02 
4.50E-02 
4.00E-02 
3.50E-02 
3.00E-02 
2.50E-02 
2.00E-02 
1.50E-02 
1.00E-02 
5.00E-03 
0.00E+00 
Tc-TSw-FL-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-2. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the tsw39 Layer at 
t = 10 Years for Mean Present-Day Infiltration 

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Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Tc-TSw-ML-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-3. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 Layer at 
t = 10 Years for Mean Present-Day Infiltration 

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Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Tc-TSw-FL-100 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-4. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the tsw39 Layer at 
t = 100 Years for Mean Present-Day Infiltration 

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Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-ML-100 Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-5. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 layer at 
t = 100 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 116 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Tc-TSw-FL-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-6. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the tsw39 Layer at 
t = 1,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 117 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Tc-PM-TSw-M-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-7. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 Layer at 
t = 1,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 118 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-TSw-FL-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-8. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the tsw39 Layer at 
t = 10,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 119 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-TSw-ML-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-9. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 Layer at 
t = 10,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 120 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-07 
9.50E-08 
9.00E-08 
8.50E-08 
8.00E-08 
7.50E-08 
7.00E-08 
6.50E-08 
6.00E-08 
5.50E-08 
5.00E-08 
4.50E-08 
4.00E-08 
3.50E-08 
3.00E-08 
2.50E-08 
2.00E-08 
1.50E-08 
1.00E-08 
5.00E-09 
0.00E+00 
Tc-TSw-FL-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-10. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the tsw39 Layer at 
t = 100,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 121 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Tc-TSw-ML-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-11. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 Layer at 
t = 100,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 122 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Tc-WT-FL-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-12. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures Immediately Above 
the Water Table at t = 10 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 123 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-PM-WT-M-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-13 Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately Above the 
Water Table at t = 10 Years for a Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 124 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Relative Mass Fraction 
Tc-WT-FL-100 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-14 Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures Immediately Above 
the Water Table at t = 100 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 125 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-PM-WT-M-100 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-15 Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately Above the 
Water Table at t = 100 Years for a Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 126 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-WT-FL-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-16 Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures Immediately Above 
the Water Table at t = 1,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 127 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-WT-ML-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-17 Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately Above the 
Water Table at t = 1000 years for a Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 128 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-WT-FL-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-18 Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures Immediately Above 
the Water Table at t = 10,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 129 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-WT-ML-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-19 Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately Above the 
Water Table at t = 10,000 Years for a Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 130 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Tc-WT-FL-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-20 Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures Immediately Above 
the Water Table at t = 100,000 Years for Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 131 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Tc-WT-ML-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002, data submitted with this Model Report 
Figure 6.8-21 Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately Above the 
Water Table at t = 100,000 Years for a Mean Present-Day Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 132 November 2003 
ch1 ch2 
NSP Northing (m) 
NSP Northing (m) 
NSP Easting (m) NSP Easting (m) 
tsw39 
NSP Easting (m) 
NSP Northing (m) 
LEGEND 
Boreholes 
Vitric Region 
UZ Model Boundary 
Fault 
UZ#16 
NOTE: Non-hachured areas within 
UZ Model boundary indicate 
"zeolitic" material 
Source: BSC 2003 [160109], Figure 6a 
Figure 6.8-22a Mineralogy Model Plots Below the Repository 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 133 November 2003 
ch5 ch6 
ch4 ch3 
NSP Easting (m) 
NSP Northing (m) 
NSP Easting (m) 
NSP Northing (m) 
NSP Easting (m) 
NSP Northing (m) 
NSP Easting (m) 
NSP Northing (m) 
Source: BSC 2003 [160109], Figure 6b 
Figure 6.8-22b Mineralogy Model Plots Below the Repository 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 134 November 2003 
15 
14.25 
13.5 
12.75 
12 
11.25 
10.5 
9.75 
9
8.25 
7.5 
6.75 
6
5.25 
4.5 
3.75 
3
2.25 
1.5 
0.75 
0 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
Solitario 
Canyon 
Fault 
Drillhole 
Wash 
Fault 
PaganyWash 
Fault 
Sever 
Wash 
Fault 
Ghost 
Dance 
Fault 
Bow Ridge Fault 
Imbricate 
Fault 
(mm/year) 
Present Day Infiltration (Mean) 
Source: BSC 2003 [163045], Figure 6.1-2 
Figure 6.8-23 Mean Present-Day Infiltration Rates at the Surface 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 135 November 2003 
15 
14.25 
13.5 
12.75 
12 
11.25 
10.5 
9.75 
9
8.25 
7.5 
6.75 
6
5.25 
4.5 
3.75 
3
2.25 
1.5 
0.75 
0 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
S 
olitario 
Canyon 
Fault 
Drillhole 
Wash 
Fault 
PaganyWash 
Fault 
Sever 
Wash 
Fault 
Ghost 
Dance 
Fault 
Bow Ridge Fault 
Imbricate 
Fault 
Vertical flux for preq_mA at repository layer
mm/year 
Source: BSC 2003 [163045], Figure 6.6-1 
Figure 6.8-24 Percolation Fluxes at the Repository Level 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 136 November 2003 
15 
14.25 
13.5 
12.75 
12 
11.25 
10.5 
9.75 
9
8.25 
7.5 
6.75 
6
5.25 
4.5 
3.75 
3
2.25 
1.5 
0.75 
0 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
S 
olitario 
Canyon 
Fault 
Drillhole 
Wash 
Fault 
PaganyWash 
Fault 
Sever 
Wash 
Fault 
Ghost 
Dance 
Fault 
Bow Ridge Fault 
Imbricate 
Fault 
Vertical flux for preq_mA at bottom boundary 
mm/year 
Source: BSC 2003 [163045], Figure 6.6-6 
Figure 6.8-25. Percolation Fluxes at the Water Table Level 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 137 November 2003 
6.8.2 99Tc Transport Under Monsoon and Glacial Infiltrations 
The DTNs of the input and output files for the three monsoon and the three glacial infiltration 
scenarios are listed in Table 6.7-2. The monsoon and glacial infiltration rate is higher than that 
for present-day infiltration of the same level (Table 6.7-1). The simulation results are consistent 
with the observations made in Section 6.8.1. 
The higher infiltration rates result in lower t10 and t50 values than those for present-day 
infiltration. Thus, for low, mean, and high monsoon infiltration, the t10 is 22, 9.4 and 2.4 years, 
respectively (Figure 6.8-26). For the same infiltration regimes, the corresponding t50 is 1,310, 
417, and 92.4 years. These times are significantly smaller than the ones for the present-day 
infiltration scenario (Figure 6.8-1), indicating faster transport through the system and earlier 
appearance of 99Tc at the water table. Because transport is faster than under present-day 
infiltration, travel times to the water table are shorter and thus the amount of 99Tc lost to 
radioactive decay is smaller. This is evident in Figure 6.8-26, in which the maximum attainable 
RM values are shown (a) to increase with the infiltration rate and (b) to be higher and closer to 
each other than those for present-day infiltration (Figure 6.8-1). 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
99 Tc - Monsoon Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.8-26 Cumulative Breakthrough of the 99Tc Mass Fraction RM at the Water Table for Varying 
Monsoon Climatic Scenarios 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 138 November 2003 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
99 Tc - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.8-27 Cumulative Breakthrough of the 99Tc Mass Fraction RM at the Water Table for Varying 
Glacial Climatic Scenarios 
For transport under glacial infiltration, Figure 6.8-27 indicates very early arrivals at the water 
table. Thus, the t10 for high, mean and low glacial infiltration are only 1.25, 5.68, and 102 years, 
respectively, while the corresponding t50 values are 42.3, 164, and 8,140 years, respectively. As 
in the case of monsoon infiltration (Figure 6.8-26), the maximum attainable RM for high and 
mean glacial infiltration is almost 1, indicating fast transport through the 3-D system. 
6.8.3 Uncertainties in 99Tc Transport Predictions 
The predictions of 99Tc transport are subject to three general types of uncertainties. 
6.8.3.1 Uncertainties in the Estimates of Flow and Hydraulic Properties 
The impact of uncertainties in the estimate of flow and hydraulic properties is in the estimation 
of the magnitude and relative sizes of flows and saturations in the fractures and in the matrices of 
the UZ. These directly affect both advective transport (and, consequently, travel times to the 
water table) and diffusive fluxes (see Equations 6-18 - 6-21). Although the importance of these 
uncertainties is readily recognized, addressing them is beyond the scope of this study, but rather 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 139 November 2003 
the subject of the Model Report on the UZ Flow Model (BSC 2003 [163045], Section 6). 
Because the radionuclide transport study is intertwined with UZ flow model (from which it 
derives its flow fields), it has the same flow-related limitations and uncertainties. 
6.8.3.2 Uncertainties in the Retardation Processes 
The only non-decay mechanisms of 99Tc retardation in the process of transport through the UZ is 
matrix diffusion (including dispersion) because it is nonsorbing and chemical immobilization is 
not considered. Uncertainties in matrix diffusion are reflected in the values of the diffusion 
coefficient D0. Given the uncertainties in the estimation of the parameters in Equations 6-20 and 
6-21, the choice of D0 in general influences the effective diffusion coefficient. 
To address this issue, we investigated the sensitivity of the 99Tc transport through the UZ for the 
D0 values shown in Table 6.5-2, which cover the possible D0 range. The results are shown in 
Figure 6.8-28. As expected, D0 has a significant impact on breakthrough predictions, resulting in 
faster arrival times for lower D0 values. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
99 Tc - Diffusion Coefficients 
Base case (Do=4.55x10-10 m2/s) 
Low Do (Do=4.55x10-11 m2/s) 
High Do (Do=10-9 m2/s) 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.8-28 Effect of Uncertainty in D0 on the Cumulative Breakthrough of the 99Tc Mass Fraction RM 

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6.8.3.3 Climatic Uncertainties 
As the results in the previous sections on 99Tc transport attest to, climatic changes affect the 
infiltration regime and can have a profound effect on transport. This uncertainty was addressed 
by estimating transport under all possible nine climatic scenarios of Table 6.7-1 (Figures 6.8-1, 
6.8-26, and 6.8-27), thus bounding the possible solution. 

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6.9 3-D TRANSPORT OF 237Np  INSTANTANEOUS RELEASE 
In this section we investigate the transport of 237Np through the UZ of Yucca Mountain 
following an instantaneous release (Section 6.7). The 3-D site-scale simulations are conducted 
by means of T2R3D. 
Section 6.9 includes three subsections. In Section 6.9.1 we discuss the transport of the 
moderately sorbing 237Np for three levels of present-day infiltration. The results of this study are 
shown in Figure 6.9-1, and in Figures IV.1 to IV.24 of Attachment IV. In Section 6.9.2, we 
study the transport of 237Np for three levels of (a) monsoon infiltration (Figure 6.9-3) and (b) 
glacial infiltration (Figure 6.9-4). Section 6.9.3 addresses uncertainties involved in the 
predictions of 237Np transport, and involves sensitivity analyses to develop the envelope of 
possible solutions. 
6.9.1 Transport of 237Np Under Present-Day Infiltration 
The grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in the 
T2R3D simulations of 3-D transport of the moderately sorbing 237Np are listed in Tables 6.5-1, 
6.6-1, 6.7-1 and 6.7-2. The DTN of the input and output files for the three present-day 
infiltration scenarios is Input/Output-DTN: LB0307MR0060R1.001 (Table 6.7-2), and Output 
DTN: LB0307MR0060R1.002. 
6.9.1.1 Breakthrough Curves 
The moderate sorption of 237Np results in retardation of its transport through the UZ system, as 
the cumulative breakthrough RM of the 237Np mass fraction at the water table indicates (Figure 
6.9-1). Comparison to that of the nonsorbing 99Tc (Figure 6.8-1) reveals a very different pattern. 
Thus, the moderate sorption of 237Np is sufficient to result in a large increase in t10 and 
t50 compared to those for the nonsorbing 99Tc. 
Increased infiltration rate leads to faster transport and shorter travel times to the repository. 
When infiltration increases from mean to high, t10 and t50 are reduced from 410 and 25,400 to 4.5 
and 1,600 years, respectively. Reduction of infiltration to the low present-day level results in 
analogous increase of t10 to 33,800, while t50 is not reached until after 1,000,000 years. 
Because of significant retardation, the maximum attainable RM varies over a larger value range 
and does not necessarily reach a plateau within the simulation period. At t = 1,000,000 years, 
RM for mean and low infiltration is 0.96 and 0.48, respectively, and the maximum possible values 
for either infiltration are not yet reached. At the same time, the RM for high infiltration is 
approaching its maximum at RM=0.99. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
237Np - Present-Day Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.9-1 Cumulative Breakthrough of the 237Np Mass Fraction RM at the Water Table for Varying 
Present-Day Climatic Scenarios 
6.9.1.3 Transport Mechanisms and Patterns 
The importance of fractures on the 237Np transport becomes evident in Figure IV.1 (DTN: 
LB0307MR0060R1.002), which shows the areal distribution of XR (see Section 6.9.2.2) in the 
aqueous phase in the fractures immediately above the TSw-CHn interface (i.e., in the tsw39 
layer) at t = 10 years (under mean present-day infiltration). As in the case of 237Np, the Drillhole 
Wash fault and Pagany Wash fault are clearly identified, as they define the extent of radionuclide 
presence and distribution at this level. The contrast with the distribution of XR in the aqueous 
phase of the matrix (Figure IV.2), which shows no discernible difference from the background 
XR = 0 in the vicinity of these faults, is dramatic. Figure IV.2 shows significant concentrations in 
the matrix in the southern part of the repository, where the permeability in the fractures is about 
the same as that in the matrix (see discussion in Sections 6.8.1.2 and 6.8.1.3). 
Figures IV.3 and IV.4 show the fracture XR and the matrix XR distribution of 237Np in the tsw39 
layer at t = 100 years. Note the significant similarities to the corresponding distribution patterns 
in Figures IV.1 and IV.2. It is noteworthy that the fracture XR distribution shows significantly 
lower peak values, and that the contributions of the Sever Wash fault and the Sundance fault to 
transport to the tsw39 unit are becoming apparent at this time. 

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The fracture XR and matrix XR at t = 1,000 years are shown in Figures IV.5 and IV.6, 
respectively. The magnitude of the fracture XR follows the downward trend identified in Figure 
IV.3, although the areal distribution of 237Np occurrence in the fracture continuum expands, and 
the signatures of the main faults (Drillhole Wash, Pagany Wash, Sever Wash, Sundance) become 
more prominent. The matrix XR in Figure IV.6 shows the same footprint as those at t = 10 years 
and t = 100 years (Figures IV.2 and IV.4), but the maximum XR level is substantially lower. This 
indicates that the bulk of the mass of the instantaneously released 237Np has moved past the 
tsw39 level at t=100 years in the southern part of the repository. 
Figures IV.7 and IV.8 show the fracture XR and the matrix XR distribution of 237Np in the tsw39 
layer at t = 10,000 years, respectively, and reveal a change in the transport regimes. The areal 
extent of the fracture XR increases compared to that at earlier times. This is attributed to 
transport through fractures over a larger area, as 237Np arrives from the repository at the bottom 
of the TSw through less conductive fractures, and/or after the radionuclide reaches such fractures 
(following diffusion into the matrix from the main fast fractures). The matrix XR distribution in 
Figure IV.8 confirms the earlier indication that the bulk of the 237Np mass has moved past the 
tsw39 layer because the extent and magnitude of the radionuclide signature in the southern part 
keeps decreasing. Conversely, the matrix in the vicinity of the main faults in the northern part of 
the repository is showing increasing evidence of 237Np, the source of which is diffusion into the 
matrix through the fracture walls (since sufficient time has elapsed to allow it) and/or direct 
matrix flow. 
At t = 100,000 years, the Solitario Canyon fault begins to contribute to the fracture XR (Figure 
IV.9), although the matrix XR values continue to decrease as the radionuclide mass moves toward 
the water table and some of it sorbs onto the UZ rocks. This is further supported by the matrix 
XR distribution of 237Np at the same time (Figure IV.10), which shows a faint signal practically 
everywhere as the bulk of the 237Np mass has already receded past the tsw39 layer. At t = 
1,000,000 years (Figures IV.11 and IV.12), there is only very faint evidence of 237Np in the 
vicinity of the Pagany Wash fault. 
The XR distribution immediately above the water table provides another indication of the 
importance of fractures. For mean present-day infiltration, the fracture XR of 237Np immediately 
above the water table at t = 10 years (Figures IV.13) clearly defines the Drillhole Wash and 
Pagany Wash faults. The corresponding matrix XR (Figure IV.14) shows a much weaker 
signature along the Drillhole Wash fault. At t = 100 years, the fracture XR (Figure IV.15) 
indicates concentration of the radionuclide along the main faults (i.e., the Drillhole Wash and 
Pagany Wash faults, and, to a lesser extent, the Sever Wash and Sundance faults). It is 
remarkable that the matrix XR at the same time (Figure IV.16) does not show the same pattern, 
but begins to show the effect of transport through the Sundance fault. Thus, the fast-conducting 
faults limit the extent of the 237Np lateral penetration into the matrix through the fracture walls 
because of the limited radionuclide mass, the high water velocity (which does not permit 
substantial diffusion), and the 237Np sorption onto the matrix. 
At 1,000 and 10,000 years, the patterns described in Figures IV.15 and IV.16 persist. The 
Drillhole Wash and Pagany Wash faults continue to dominate transport (Figure IV.17 and 
IV.19), while the vicinity of the Sundance fault is the location of significant matrix XR values 

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(Figures IV.18 and IV.20 at t=1,000 years and t=10,000 years, respectively). The larger areal 
extent of fracture XR at t = 10,000 years results in the very low matrix XR signature of the 
Drillhole Wash fault. The faults lead to relatively fast transport from the repository to the water 
table, resulting in short residence times and limited penetration into the matrix (and, 
consequently, limited retardation through sorption). 
At longer times, the effects of limited radionuclide mass (a consequence of the instantaneous 
release scenario), sorption, and decay are demonstrated by the decreasing magnitude and areal 
extent of the fracture and matrix XR (Figures IV.21 to IV.24). 
6.9.1.4 Transport-Controlling Features 
Review of Figures IV.1 through IV.24 (see Attachment IV), and comparison to the 
corresponding 99Tc figures (Figures 6.8-2 through 6.8-17) indicate that transport is both 
dominated and controlled by the same faults identified and discussed in Sections 6.8.1.2 and 
6.8.1.3. Thus, the Drillhole Wash fault and the Pagany Wash fault are the main 
transport-facilitating geologic features, and leads to the early appearance of 237Np in the tsw39 
layer and at the water table. What is remarkable in the case of 237Np is that that the Drillhole 
Wash fault and the Pagany Wash fault play an even more important role in transport, as they 
appear to convey a larger portion of the released mass and in a shorter time than in the case of 
99Tc. These faults are very clearly identified as conduits of very fast transport to the water table. 
The Sever Wash fault and the Sundance fault are important at later times, but their contributions 
to transport are of lesser importance. The faults appear to act as barriers to the lateral migration 
of radionuclides. 
As in the case of 99Tc transport, radionuclide transport to the groundwater is much faster in the 
northern part of the repository, where it is also areally concentrated. This is caused by (a) the 
infiltration and percolation patterns, (b) the fast conduit to transport provided by the faults; (c) 
the permeability regimes (and their effect on flow and to transport) in the northern part; and (d) 
the distribution, fracture characteristics, and flow behavior of the CHz and CHv layers. A 
detailed discussion of transport patterns can be found in Section 6.9.2.3. 
6.9.1.5 Comparison to the 99Tc Transport 
The obvious reason for the difference between the 99Tc and the 237Np transport behavior is 
sorption. This results in (a) the universally lower (than 99Tc) concentrations and the more limited 
areal extent (footprint) of 237Np in the fractures and in the matrix at the same times, (b) the 
persistence over a longer time of the area underneath the southern part of the repository in tsw39 
as the location where the matrix XR is significant (Figures IV.6 and IV.8, vs. Figures 6.8-7 and 
6.8-9), (c) the slower breakthroughs indicated by Figures IV.12 through IV.24 and Table 6.20-1, 
and (d) the more limited extent of the radionuclide penetration into the UZ. 
6.9.1.6 Effect of Sorption in the Main Geologic Units on 237Np Transport 
Of particular interest is the effect of the main hydrogeologic units (i.e., TSw, CHv and CHz) on 
the transport and retardation of 237Np. This was investigated by setting the corresponding 
distribution coefficients Kd in the all the layers of each of these units to zero, and then comparing 
the resulting cumulative breakthrough curve to that for the base case. 

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The results (for a mean present-day infiltration scenario) are shown in Figure 6.9-2, and indicate 
that TSw is by far the most important unit in the transport and retardation of 237Np. By 
eliminating sorption in the all the TSw layers, water table arrivals of 237Np occur significantly 
earlier. The effect of no sorption in the CHz and CHv units are secondary (if not marginal), and 
become apparent only at later times. Given that no sorption occurs in the fractures, the lack of 
any appreciable retardation during advection through the CHz and CHv tends to further indicate 
that fracture flow is the overwhelmingly dominant mechanism of transport through these units, 
while advection through matrix flow does not play a significant role. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
237 Np 
Base case 
Kd = 0 in TSw 
Kd = 0 in CHz 
Kd = 0 in CHv 
Output-DTN: LB0310MR0060R1.010, data submitted with this Model Report 
Figure 6.9-2. The effect of sorption in TSw, CHz and CHv on the cumulative breakthrough of 237Np at 
the water table (mean present-day simulation). 
6.9.2 237Np Transport Under Monsoon and Glacial Infiltration 
The DTN of the input and output files for the three monsoon infiltration scenarios is 
Input/Output-DTN: LB0307MR0060R1.001 (Table 6.7-2), Output DTN: 

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LB0307MR0060R1.002. The higher monsoon and glacial infiltration rates (compared to those in 
present-day regimes, see Table 6.7-1) lead to the faster transport indicated in Figures 6.9-3 and 
6.9-4 (when compared to that shown in Figure 6.9-1). 
The t10 for low, mean, and high monsoon infiltration is 14.8, 8.5, and 1.6 years, respectively. The 
corresponding t50 are 6,140, 2,120, and 714 years, respectively. These times are significantly 
lower than the ones for the present-day infiltration scenario, as the faster transport through the 
system would warrant. Because transport is faster than under present-day infiltration, radioactive 
decay of the released 237Np has a less pronounced effect in the reduction of the RM at a given 
time. 
The t10 for low, mean, and high glacial infiltration is 1830, 4 and 0.8 years, respectively. The 
corresponding t50 are 34,400, 1,070, and 336 years, respectively. For high and mean glacial 
infiltration, the t10 and t50 times are the shortest in the three infiltration regimes. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
237Np - Monsoon Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report). 
Figure 6.9-3. Cumulative Breakthrough of the 237Np Mass Fraction RM at the Yucca Mountain Water 
Table for Varying Monsoon Climatic Scenarios 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
237 Np - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.9-4. Cumulative Breakthrough of the 237Np Mass Fraction RM at the Yucca Mountain Water 
Table for Varying Glacial Climatic Scenarios 
6.9.3 Uncertainties in 237Np Transport Predictions 
The predictions of 237Np transport are subject to three general types of uncertainties discussed in 
Section 6.8.3. For the reasons discussed in that section, here we will limit our discussion to the 
issue of uncertainties in the transport retardation processes. Because 237Np is a sorbing 
radionuclide, uncertainties involve both diffusion and sorption issues. 
6.9.3.1 Uncertainties in Matrix Diffusion 
As previously indicated, uncertainties in matrix diffusion are reflected in the values of the 
diffusion coefficient D0. To address this issue, we investigated the sensitivity of the 237Np 
transport through the UZ for the D0 values shown in Table 6.5-2, which cover the possible 
D0 range. The results are shown in Figure 6.9-5. 

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As expected, D0 has a significant impact on breakthrough predictions, resulting in faster arrival 
times for lower D0 values. Note that the relative effect of the D0 uncertainty in predicting 
transport of the sorbing 237Np is comparatively less pronounced than that of the nonsorbing 99Tc, 
i.e., the impact of D0 uncertainty on radionuclide breakthrough predictions appears to be 
mitigated by sorption. 
6.9.3.2 Uncertainties in Sorption 
Such uncertainties in sorption are reflected in the values of the distribution coefficient Kd. To 
address this issue, we investigated the sensitivity of the 237Np transport through the UZ for the 
Kd values shown on Figure 6.9-6. These cover the range between zero (no sorption, in which 
case behavior similar to that of 99Tc was expected) to the maximum values reported in Table 6.5- 
1. The results are shown in Figure 6.9-6. 
As expected, Kd has a significant impact on breakthrough predictions, resulting in faster arrival 
times for lower Kd values. Note that the relative effect of Kd uncertainty predicting transport of 
the sorbing 237Np appears to be much more pronounced than that for the D0 uncertainty for the 
range tested here. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 10-1 100 101 102 103 104 105 106 
Time (year) 
237 Np - Diffusion Coefficients 
Base case (Do =1.65x10-10 m2/s) 
Low Do (Do=1.65x10-11 m2/s) 
High Do (Do=7.12x10-10 m2/s) 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.9-5 Effect of Uncertainty in D0 on 237Np Breakthrough at the UZ 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (year) 
237 Np - Sorption Coefficients 
Base Case (K d=0.3-0.5 mL/g) 
Low K (Kd d =0 mL/g) 
High Kd (Kd=3-6 mL/g) 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.9-6 Effect of Uncertainty in Kd on 237Np Breakthrough at the UZ 

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6.10 THREE DIMENSIONAL TRANSPORT OF 239Pu  INSTANTANEOUS RELEASE 
In this section we investigate the transport of 239Pu through the UZ of Yucca Mountain following 
an instantaneous release (Section 6.7). The 3-D site-scale simulations are conducted by using 
the T2R3D code. 
In Section 6.10.1, we discuss the transport of the strongly sorbing 239Pu for three levels of (a) 
present-day, (b) monsoon, and (c) glacial infiltration. The results of this study are shown in 
Figures 6.10-1 and 6.10-2. In Section 6.10.2 we address the issue of uncertainty involved in the 
predictions of 239Pu transport and conduct sensitivity analyses to develop the envelope of 
possible solutions (Figure 6.10-4). In Section 6.10.3, we discuss the applicability of the 
uncertainty studies conducted thus far on other radionuclides. 
6.10.1 Transport of 239 Pu Under Present-Day Infiltration 
The grids, flow fields, and conditions discussed in Section 6.7 are used in the simulation of all 
infiltration regimes. The parameters used in the EOS9nT simulations of 3-D transport of the 
strongly sorbing 239Pu are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The DTN of the input 
and output files for the three present-day infiltration scenarios is Input/Output-DTN: 
LB0307MR0060R1.001 and Output DTN: LB0307MR0060R1.002. The t10 and t50 of 239Pu for 
the various infiltration regimes are listed in Table 6.20-1. 
6.10.1.1 Breakthrough Curves 
The cumulative breakthrough RM of the 239Pu mass fraction at the water table for present-day 
infiltration is shown in Figure 6.10-1. If the contributions of the daughter products (i.e., 235U and 
231Pa) are not accounted for, RM first reaches a plateau at the RM= 0.1 level (at t = 20 years, a 
clear indication of fracture flow), and then a second plateau at about 100,000 years (denoting 
matrix flow). This behavior results from the strong sorption of 239Pu. 
The faster transport depicted in Figures 6.10-2 is the result of the higher monsoon and glacial 
infiltration rates, respectively. The changes in climatic conditions lead to breakthrough curves 
that follow the same pattern established in the 239Pu present-day transport. A higher infiltration 
results in two plateaus that are higher than those for present-day infiltration, but occurs at about 
the same times (denoting fracture and matrix transport). As in the cases of 99Tc and 237Np, a 
higher infiltration leads to earlier arrival of 239Pu at the water table. However, the mass arriving 
at the water table represents a very small portion of the initial release because of strong sorption. 
6.10.1.2 Transport Mechanisms and Patterns, and Transport-Controlling Features 
The importance of fractures on the 239Pu transport is very significant, as can be attested to by the 
contour plots available in the output submitted with this Model Report (Output-DTN: 
LB0307MR0060R1.002). Thus, the fracture XR at times as early as t = 10 years shows a sizable 
239Pu presence in tsw39 and a measurable presence at the water table. Review of the transport 
patterns of the fracture XR in tsw39 and at the water table confirms the earlier observations (from 
the 99Tc and 237Np studies) that the Drillhole Wash and the Pagany Wash faults are the main 
conduits of fast radionuclide transport through the UZ to the water table. The Sever Wash and 
the Sundance faults also contribute to transport at later times, but the Solitario Canyon fault 

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appears to have no effect because of the strong sorption of 239Pu onto the UZ rocks. The matrix 
XR distribution closely follows that of the fracture XR, but has a more limited areal extent and 
substantially lower magnitude. This is consistent with a 239Pu transport pattern dominated by the 
fault fractures, with practically no matrix-to-matrix advection, and with 239Pu occurrence in the 
matrix due to diffusion from the fractures. 
6.10.1.3 Comparison to the 99Tc and 237Np Transport 
A comparison of the 239Pu transport to the transport of 99Tc (Section 6.8) and 237Np (Section 6.9 
and Attachment IV) clearly indicates the same general patterns. They all exhibit the same 
behavior, are affected by the same mechanisms and are controlled by the same geologic features, 
but the magnitude of the observed fracture and matrix XR varies considerably because of the very 
different sorption affinity of these radionuclides onto the various UZ rocks. Increasing sorption 
affinity leads to lower concentrations (especially in the fractures), and consequently more limited 
areal distributions of mobile radionuclides. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
239Pu - Present-Day Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.10-1. Cumulative Breakthrough of the 239Pu Mass Fraction RM at the Water Table for Varying 
Present-Day Climatic Scenarios 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
239Pu - Monsoon Infiltration 
Lower 
Mean 
Upper 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
239Pu - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.10-2. Cumulative Breakthrough of the 239Pu Mass Fraction RM at the Water Table for (a) 
Monsoon and (b) Glacial Infiltration 
Thus, 239Pu transport exhibits (a) a XR that is universally lower than in the mildly sorbing 237Np, 
and even more so than in the nonsorbing 99Tc, and a more limited areal extent (footprint) of 239Pu 
in the fractures and in the matrix at the same times, (b) persistence over a longer time of the area 
underneath the southern part of the repository in tsw39 as the location where the matrix XR is 
significant, (c) slower breakthroughs, and (d) a more limited extent of the radionuclide 
penetration into the UZ. 

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6.10.1.4 Effect of Sorption in the Main Geologic Units on 239Pu Transport 
The effect of the main hydrogeologic units (i.e., TSw, CHv and CHz) on the transport and 
retardation of 239Pu was also investigated. The cumulative breakthrough curves corresponding to 
a zero Kd for the TSw, CHv and CHz units are shown in Figure 6.10-3. 
The results (for a mean present-day infiltration scenario) are analogous to, but far more 
pronounced than, those discussed in the case of 237Np transport (see Section 6.9.1.6, this Model 
Report). By setting the Kd to zero in the all the TSw layers, larger amounts of 239Pu arrive earlier 
at the water table, and a much higher RM value is attained, indicating that much larger amounts 
of 239Pu can cross the UZ. The overall effect of no sorption in the CHz and CHv units is 
practically insignificant compared to the base case. As in the case of 237Np transport, these 
results further underscore the importance of the TSw unit on the transport and retardation of 
239Pu, and illustrate the overwhelming dominance of fractures in UZ transport. 
0.4 
0.3 
0.2 
0.1 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
239 Pu 
Base case 
Kd = 0 in TSw 
Kd = 0 in CHz 
Kd = 0 in CHv 
Output-DTN: LB0310MR0060R1.010, data submitted with this Model Report 
Figure 6.10-3. The Effect of Sorption in TSw, CHz and CHv on the Cumulative Breakthrough of 239Pu at 
the Water Table (Mean Present-Day Simulation). 

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6.10.2 Uncertainties in 239Pu Transport Predictions 
The predictions of 239Pu transport are subject to three general types of uncertainties discussed in 
Sections 6.8.3 and 6.9.3. For the reasons discussed in these sections, here we will limit our 
discussion to the issue of uncertainties in the transport retardation processes. Although 239Pu is a 
sorbing radionuclide subject to the impact of uncertainties in diffusion and sorption, only 
uncertainty in diffusion is addressed here. The reason for this approach is that 239Pu exhibits 
sorbing behavior that is so exceptionally strong that it would be physically unrealistic to reduce 
Kd to levels that may have an impact on transport. Even order-of-magnitude reduction in Kd is 
insufficient to significantly affect 239Pu transport behavior. 
The study of uncertainties in diffusion follows the pattern discussed in Sections 6.8.3 and 6.9.3. 
Uncertainties in matrix diffusion are reflected in the values of the diffusion coefficient D0. We 
investigated the sensitivity of the 239Pu transport through the UZ for the D0 values shown in 
Table 6.5-2, which cover the possible D0 range. The results are shown in Figure 6.10-3. 
As expected, D0 has an impact on breakthrough predictions, resulting in faster arrival times for 
lower D0 values. However, the relative effect of D0 uncertainty in predicting transport of the 
strongly sorbing 239Pu is comparatively even less pronounced than that of the mildly sorbing 
237Np. That is, the impact of D0 uncertainty on radionuclide breakthrough predictions appears to 
be mitigated by sorption. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
239 Pu - Diffusion Coefficients 
Base case (Do=4.81x10-10 m2/s) 
Low Do (Do=4.81x10-11 m2/s) 
High Do (Do=10-9 m2/s) 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.10-4. Effect of Uncertainty in D0 on the 239Pu Breakthrough at the UZ 

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6.10.3 Applicability of Uncertainty Studies to Other Radionuclides. 
The insights obtained from the analysis of uncertainty in the cases of 99Tc, 237Np, and 239Pu are 
directly applicable to all the other radionuclides studied in this Model Report. By covering the 
spectrum of sorption behavior and diffusion in the uncertainty study, it is possible to develop 
general rules to broadly predict the effect of uncertainty. Thus, the effect of uncertainties in the 
breakthrough of nonsorbing radionuclides will be akin to that of 99Tc. Mildly sorbing 
radionuclides can be described by using the 237Np analog, while strong sorbers will be described 
by the 239Pu behavior. 

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6.11 THREE DIMENSIONAL TRANSPORT OF 233U AND 235U  INSTANTANEOUS 
RELEASE 
Here we study the transport of 233U and 235U through the Yucca Mountain UZ system after an 
instantaneous release scenario (Section 6.7). The two isotopes share the same physical 
properties (e.g., diffusion and sorption behavior), but differ in their half-lives (Table 6.5-2). 
The grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in 
these T2R3D simulations of 3-D transport of the moderately sorbing 233U and 235U are listed in 
Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The DTN of the input and output files for the nine 
present-day infiltration scenarios is Input/ Output-DTN: LB0307MR0060R1.001, and Output 
DTN LB0307MR0060R1.002 (Table 6.7-2). 
6.11.1 Transport of 233 U Under Different Climatic Conditions 
The breakthrough curves of 233U (a mildly sorbing species; see Table 6.5-1) transport through 
the UZ are shown in Figure 6.11-1(a), (b), and (c), for mean present-day, monsoon and glacial 
infiltration regimes, respectively. A comparison of these figures to those of 237Np (Figure 6.9-1 
through 6.9-3) indicates that their behavior is analogous at early times, but deviates at later times 
because of the larger T1/2 of 233U (leading to different maximum attainable RM values). The 
t10 and t50 of 233U for the various infiltration regimes are listed in Table 6.20-1. 
6.11.2 Transport of 235U Under Different Climatic Conditions 
The breakthrough curves of 235U transport through the UZ are shown in Figure 6.11-2(a), (b), 
and (c), for mean present-day, monsoon and glacial infiltration regimes, respectively. Compared 
to the equivalent figures for 233U, the breakthrough curves show differences at later times (e.g., 
in the maximum attainable RM level), reflecting the differences in T1/2 (Table 6.5-1). Because of 
the isotopic relationship to 233U, the behavior 235U (a mildly sorbing species, see Table 6.5-2) is 
analogous to that 237Np. The t10 and t50 of 235U for the various infiltration regimes are listed in 
Table 6.20-1. 
A review of the figures in this section confirms the well-established pattern observed thus far: 
increasing infiltration enhances transport by resulting in a shorter travel time through the UZ and 
leads to a higher maximum attainable RM. 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
233 U - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
233 U - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
233 U - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.11-1. Cumulative Breakthrough of the 233U Mass Fraction RM at the Water Table for (a) 
Present-Day, (b) Monsoon and (c) Glacial Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
235 U - Present Infiltration 
Lower 
Mean 
Upper 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
235 U - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
235 U - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.11-2. Cumulative Breakthrough of the 235U Mass Fraction RM at the Water Table for (a) 
Present-Day, (b) Monsoon and (c) Glacial Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
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6.12 THREE DIMENSIONAL TRANSPORT OF 241Am AND 90Sr  INSTANTANEOUS 
RELEASE 
In this section, we analyze the transport of 241Am and 90Sr through the Yucca Mountain UZ after 
an instantaneous release scenario (Section 6.7). Both 241Am and 90Sr are very strong sorbers 
(even stronger than Pu; see Table 6.5-1), but have the two shortest T1/2 among the radionuclides 
studied in this Model Report (Table 6.5-2). 
The grids, flow fields, and conditions are as discussed in Section 6.7.2. The parameters used in 
these T2R3D simulations are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The DTN of the 
input and output files for the nine infiltration scenarios is Input/Output-DTN: 
LB0307MR0060R1.001 (Table 6.7-2). 
6.12.1 241Am Transport 
The breakthrough curves of 241Am transport through the UZ are shown in Figure 6.12-1(a), (b) 
and (c), for mean present day, monsoon, and glacial infiltration regimes, respectively. These 
figures indicate that the maximum attainable RM is quite low, and that, although an increasing 
infiltration results invariably in a larger RM, the increase is not significant. As in all 
radionuclides in this Model Report, the breakthrough curves are characterized by early arrival at 
the water table and an early single plateau at a low RM level (below 0.2), denoting fracture 
transport. A second plateau (denoting matrix transport, as observed in the case of the 233Pu 
transport) does not materialize because of (a) the much stronger sorption of 241Am onto the 
matrix (thus reducing the radionuclide available for matrix transport) and (b) its rather short halflife 
(4.322102 years, Table 6.5-2). The t10 and t50 of 241Am for the various infiltration regimes 
are listed in Table 6.20-1. 
6.12.2 90Sr Transport 
The breakthrough curves of 90Sr transport through the UZ are shown in Figures 6.12-2(a), (b) 
and (c), for mean present day, monsoon, and glacial infiltration regimes, respectively. As 
expected because of the similarity to 241Am, the maximum attainable RM is quite low and does 
not increase significantly with an increasing infiltration. The breakthrough curves are 
characterized by early arrival at the water table and an early single plateau at a low RM level 
(below 0.15), denoting fracture transport. The second plateau (denoting matrix transport) 
observed in the case of 233Pu transport (Section 6.10) does not materialize because of (a) the 
much stronger sorption of 90Sr onto the matrix (thus reducing the radionuclide available for 
matrix transport) and (b) its very short half-life (2.9101 years, Table 6.5-2). The t10 and t50 of 
90Sr for the various infiltration regimes are listed in Table 6.20-1. 

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(a) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 
Time (years) 
241Am - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 
Time (years) 
241Am - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 
Time (years) 
241Am - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.12-1. Cumulative Breakthrough of the 241Am Mass Fraction RM at the Water Table for 
(a) Present-day, (b) Monsoon and (c) Glacial Infiltration 

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(a) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
90 Sr - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
90 Sr - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
90 Sr - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.12-2. Cumulative Breakthrough of the 90Sr Mass Fraction RM at the Water Table for 
(a) Present-Day, (b) Monsoon and (c) Glacial Infiltration 

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6.13 THREE DIMENSIONAL TRANSPORT OF 135Cs  INSTANTANEOUS RELEASE 
In this section, we analyze the transport of 135Cs through the Yucca Mountain UZ following an 
instantaneous release event. 135Cs is a very strong sorber (even stronger than Pu on zeolitic 
rocks, but less on vitric and devitrified; see Table 6.5-1), but is also among the most diffusive 
species (Table 6.5-2). 
The grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in the 
T2R3D simulations of 3-D transport of 135Cs are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. 
The DTN of the input and output files for all nine scenarios is Input/Output-DTN: 
LB0307MR0060R1.001 (Table 6.7-2). 
The breakthrough curves of 135Cs transport through the UZ are shown in Figures 6.13-1(a), (b) 
and (c), for mean present-day, monsoon, and glacial infiltration regimes, respectively. In all 
climatic scenarios, the very strong sorption of 135Cs demonstrates itself by the very low RM level, 
which persists for a very long time. The very strong diffusion of 135Cs into the matrix prevents its 
early arrival at the water table through advective transport in the fractures, taking about 1,000 
years for concentrations at the water table to register an upward trend. After this initial delay 
(during which the effect of the infiltration rates do not substantially affect transport), significant 
RM values are attainable, and breakthrough begins to be affected by the climatic regime. The 
t10 and t50 of 135Cs for the various infiltration regimes are listed in Table 6.20-1. 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
135 Cs - Present-day Infiltration 
Lower 
Mean 
Upper 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
135 Cs - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
135 Cs - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.13-1. Cumulative Breakthrough of the 135Cs Mass Fraction RM at the Water Table for 
(a) Present-Day, (b) Monsoon and (c) Glacial Infiltration 

Radionuclide Transport Models Under Ambient Conditions U0060 
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6.14 THREE DIMENSIONAL TRANSPORT OF 226Ra, 229Th AND 231Pa 
INSTANTANEOUS RELEASE 
In this section, we analyze the transport 226Ra, 229Th and 231Pa, three radionuclides that are 
among the most insoluble species and the strongest known sorbers. These are instantaneously 
released at the repository level, and their migration through the UZ zone and breakthrough at the 
water table is studied. These three radionuclides have medium half-lives, ranging from a few 
thousand to a few tens of thousands of years (Table 6.5-2). 
The grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in 
these T2R3D 3-D simulations are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The DTN of the 
input and output files for the all nine scenarios is Input/Output-DTN: LB0307MR0060R1.001. 
Breakthrough curves of 226Ra transport through the UZ are shown in Figures 6.14-1(a), (b), and 
(c), for mean present day, monsoon, and glacial infiltration regimes, respectively. The 
corresponding figures for the 229Th breakthrough are 6.14-2(a), (b), and (c), and those for 231Pa 
are 6.14-3(a), (b), and (c), respectively. As expected, these three radionuclides exhibit very 
similar behavior, and similar to those of 241Am and 90Sr. Their maximum attainable RM is quite 
low, and although larger infiltration results invariably in a larger RM, the increase is not 
significant. Breakthrough curves are characterized by early arrival at the water table and an 
early plateau at a low RM level (below 0.2), denoting fracture transport. The second plateau 
(denoting matrix transport) that was observed in the case of the 239Pu transport does not 
materialize because of (a) their much stronger sorption onto the matrix that does not permit 
transport through it, and (b) their medium half-life (dwarfed by the 1,000,000-year-long period 
of observation depicted in the figures; see Table 6.5-2). The t10 and t50 of 226Ra, 229Th, and 231Pa 
for the various infiltration regimes are listed in Table 6.20-1. 

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(a) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
226 Ra - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
226 Ra - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 
Time (years) 
226 Ra - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.14-1. Cumulative Breakthrough of the 226Ra Mass Fraction RM at the Water Table for 
(a) Present-Day, (b) Monsoon and (c) Glacial Infiltration 

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(a) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
229 Th - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
229 Th - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
229 Th - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.14-2. Cumulative Breakthrough of the 229Th Mass Fraction RM at the Water Table for 
(a) Present-Day, (b) Monsoon and (c) Glacial Infiltration. 

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(a) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
231 Pa - Present-Day Infiltration 
Lower 
Mean 
Upper 
(b) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
231 Pa - Monsoon Infiltration 
Lower 
Mean 
Upper 
(c) 
0.20 
0.15 
0.10 
0.05 
0.00 
Normalized Mass Fraction 
10-1 100 101 102 103 104 105 106 
Time (years) 
231 Pa - Glacial Infiltration 
Lower 
Mean 
Upper 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.14-3. Cumulative Breakthrough of the 231Pa Mass Fraction RM at the Water Table for 
(a) Present-Day, (b) Monsoon and (c) Glacial Infiltration 

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6.15 THREE DIMENSIONAL SIMULATIONS OF 99Tc, 237Np AND 239Pu 
TRANSPORT - CONTINUOUS RELEASE 
In this section, we investigate the three radionuclides discussed in Sections 6.8 to 6.10 under a 
scenario of continuous release. 
6.15.1 The Continuous-Release Scenario 
The concept of the continuous-release scenario investigated in these simulations was discussed 
in Section 6.7.3.2. Only mean present-day infiltration was considered in these simulations. The 
grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in these 
EOS9nT simulations of 3-D transport of 99Tc, 237Np, and 239Pu are listed in Tables 6.5-1, 6.6-1, 
6.7-1, and 6.7-2. The DTN of the input and output files for the three present-day infiltration 
scenarios is Input/Output-DTN: LB0307MR0060R1.003 (Table 6.7-2). 
6.15.2 The Definition of the Breakthrough Curves for Continuous Release 
As the radionuclide concentration in the repository and in the bottom boundary elements 
(corresponding to the water table) remain constant over time, the breakthrough concept is based 
on the normalized or relative release rate RF, which is defined as 
RF = 
] [ repository proposed at the rate release Mass 
] [ boundary r groundwate at the rate release Mass 
1 - 
-1 
MT 
MT 
Thus, RF involves a ratio of rates, while the conventional RM is a ratio of masses. As in RM, 
t10 and t50 are defined as the times at which RF = 0.1 and RF = 0.5, respectively. For radioactive 
chains, the quantity in the denominator reflects the sum of the fluxes of all members in the 
release stream. For decaying release concentration, the denominator reflects the original 
radionuclide release rate from repository elements. 
Of particular interest is the distribution of the relative sorbed or filtered concentration FR [ML-3] 
defined as 
FR = F 
X0 
where F is as defined in Equation 6-8, and X0 is the species mass fraction in the water released 
from the repository. This is important in the evaluation of sorbing radionuclides such as 237Np 
and 239Pu. 
6.15.3 Transport of Continuously Released 99Tc, 237Np, and 239Pu Under Present-Day 
Infiltration 
The breakthrough curves for continuously released 99Tc, 237Np and 239Pu are shown in Figure 
6.15-1, which also shows the decaying fluxes (reflecting decaying concentrations, as the water 
fluxes remain time-invariant) for reference. The t10 and t50 of 99Tc, 237Np and 239Pu under a 
continuous release scenario for a mean present-day infiltration are listed in Table 6.20-2. 

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Comparison of the t10 and t50 from Figure 6.15-1 to those from the instantaneous-release 
scenarios (Sections 6.8, 6.9, and 6.10) shows that, in this case, they are generally consistent. 
Note, however, that in general, the two can be very different. Of interest is the shape of the RF 
curves, which begin to show a decline after reaching a maximum before the point where of the 
influx and outflow curves coincide. The existence of such a maximum is a direct consequence of 
considering a decaying source. RF, the ratio of outflow to initial inflow, initially increases as 
radionuclides reach the water table in increasing quantities. However, the increase can only 
proceed up to a point, beyond which there is a balance between influx and outflow (indicating by 
the coincidence of the two curves in Figure 6.15-1), which involves ever-declining radionuclide 
concentrations. 
6.15.4 Transport Patterns of Continuously Released 99Tc, 237Np, and 239Pu Under 
Present-Day Infiltration 
The distribution of 99Tc fracture and matrix XR in tsw39 and at the watertable at various times 
after the radionuclide release are shown in Attachment V. Under continuous release, it is 
expected that the radionuclide distributions at early times would be similar to those from 
instantaneous release, but the two would diverge at later times because of the different masses 
involved in each scenario. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
101 102 103 104 105 106 
Time (years) 
WATER TABLE 
99Tc 
237Np 
239Pu 
REPOSITORY 
99Tc 
237Np 
239Pu 
0.1 fraction line 
0.5 fraction line 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.15-1. Normalized Relative Release RF of 99Tc, 237Np and 239Pu at the Water Table for 
Continuous Release and Mean Present-Day Climatic Scenarios 

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One of the objectives of this study was to determine whether transport under continuous release 
is dominated by different geologic features than those controlling instantaneous release. 
Comparison of Figures V.1 through V.12 to Figures 6.8.2 to 6.8-11 indicate that at early times (t 
= 100 years) the concentration distributions in tsw39 show the same patterns and are in line with 
expectations. The magnitude of concentrations is different, but this was entirely expected 
because the total radionuclide mass in the UZ is substantially larger in a continuous release 
scenario. Differences are observed for t = 1,000 years, which show increasing fracture and 
matrix concentrations over time. The Drillhole Wash and Pagany Wash faults are the main 
geologic features responsible for fast transport to the bottom of the TSw and the water table. 
Note that the shift of the matrix concentrations from underneath the southern part toward the 
northern part of the repository (Figures 6.8-7, 6.8-9, 6.8-11) does not occur under continuous 
release, and the southern part continues to exhibit the largest concentrations. The areal extent of 
radionuclide distribution in both the fractures and the matrix appears to reach a maximum at t = 
1,000 years (Figures V.7 and V.8). Although these footprints appear constant after this time, the 
concentrations change over time and reach a maximum at t = 10,000 years (Figures V.9 and 
V.10), after which time they decline because of radioactive decay. An important observation is 
the large footprint and the corresponding high values of the matrix XR under continuous release. 
Thus, the amount of 99Tc in the mobile liquid in the matrix is larger and over a larger area under 
continuous release. 
Comparison of Figures V.11 through V.24 to Figures 6.8-12 to 6.8-21 indicates that the 
concentration distributions above the water table show the same general patterns. For obvious 
reasons, the magnitude of concentrations is different, but the areal distributions are remarkably 
similar. Significant differences are observed at t = 100,000 years, when both the areal extent and 
the magnitude of the 99Tc concentrations are significantly larger under continuous release. This 
is entirely consistent with the much larger total radionuclide mass released in the UZ. 
The corresponding distributions of 237Np and 239Pu, respectively, in tsw39 and at the water table 
under continuous release for a mean present-day infiltration are included in Output-DTN: 
LB0307MR0060R1.004, which also include figures with the FR distributions. Comparison to the 
figures for 237Np and 239Pu to those for 99Tc in Attachment V indicate that the same general 
patterns persist. The differences in the magnitude and areal extent of concentrations are mainly 
due to the different sorbing behavior of the radionuclides. Thus, with an increasing sorption 
affinity to the UZ rocks from 99Tc to 237Np to 239Pu, the areal extent of the radionuclide 
occurrence decreases and the corresponding maximum XR in the fractures decrease, the 
maximum XR in the matrix decreases even more severely, and the matrix XR increases. Note that 
at t = 100,000 years, significant amounts of 237Np and 239Pu are sorbed over areas that exceed the 
footprint of the repository at both the tsw39 level and at the water table. The implication is that 
these sorbed radionuclides can become sources for long-term release to the water table even if 
releases from the repository cease. 

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6.16 THREE DIMENSIONAL TRANSPORT OF THE 239Pu 235U 231Pa CHAIN  
CONTINUOUS RELEASE 
In this section we investigate the transport of the three-member chain 239Pu 235U 231Pa 
chain continuously released from the repository. We study the transport of the members of this 
chain by means of EOS9nT 3-D site-scale simulations of the entire UZ system of Yucca 
Mountain. 
Only mean present-day infiltration was considered in these simulations. The grids, flow fields, 
and conditions are as discussed in Section 6.7, and the parameters used in these EOS9nT 
simulations are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The DTN of the input and output 
files for the three present-day infiltration scenarios is Input/Output-DTN: 
LB0307MR0060R1.003 (Table 6.7-2). 
The evolution of the mass fractions RF in the release stream at the repository and at the water 
table are shown in Figures 6.16-1(a) and (b). Figure 6.16-1(a) reflects decay and generation of 
each of the members of the 239Pu chain, and, being a boundary condition, is unaffected by flow 
or transport conditions in the UZ. Note that the released stream becomes depleted in 239Pu due to 
decay after about 100,000 years, at which time 235U is practically the only species entering the 
UZ from the repository. 
The mass fractions at the water table in Figure 6.16-1(b) incorporate the cumulative effects of 
migration through the UZ, and reflect the effects of matrix diffusion and sorption on the effluent 
concentration. Comparison of Figures 6.16-1(a) and (b) reveals a very important difference. The 
radionuclide stream at the water table shows a much earlier enrichment in 235U, and 235U is the 
increasingly dominant species after t=2000 years. The reason for the difference is the much 
stronger sorption of 239Pu in the UZ, coupled with the relatively weak sorption of 235U. The 
contribution of 231Pa appears practically insignificant in the first 1,000,000 years because of the 
very long half-life of 235U and its very strong affinity for sorption (Section 6.11). 
Note that Figures 6.16-1(a) and (b) reflect relative concentrations of radionuclides in the inflow 
and outflow streams, but provide no information on the actual inflow and outflow relationship. 
This is addressed by the relative release rates at the water table in Figure 6.16-2, computed as the 
ratio of the total outflow rates (i.e., sum of individual member fluxes) versus the total inflow 
rates at the repository. A comparison of Figure 6.16-2 to that for the 239Pu in Figure 6.16-1(a) 
(obtained under the same conditions and in the same domain) indicates the importance of 
considering all the members of the chain in the computations, and the significant error that will 
be introduced if only the parents are considered. The t10 and t50 of this chain under a continuous 
release scenario for a mean present-day infiltration are listed in Table 6.20-2. Given the long 
half-life of 239Pu and the much longer half-life of 235U (see Table 6.5-2), the daughter 
contributions are very important and cannot be neglected. 

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(a) 
10-8 
10-7 
10-6 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
Mass fraction in release stream at repository 
101 102 103 104 105 106 
Time (years) 
239Pu 
235U 
231Pa 
(b) 
10-8 
10-7 
10-6 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
Mass fraction in release stream at the water table 
101 102 103 104 105 106 
Time (years) 
239Pu 
235U 
231Pa 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.16-1. Mass Fractions of Each Member of the 239Pu Chain in the Release Stream at (a) the 
Repository and (b) the Water Table  Continuous Release Mean Present-Day Climatic 
Scenarios 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized release rate at the water table 
101 102 103 104 105 106 
Time (years) 
0.1 fraction line 
0.5 fraction line 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.16-2. Normalized Relative Release RF of the Sum of All Members of the 239 Pu Chain at the 
Water Table  Continuous Release Mean Present-Day Climatic Scenarios 

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6.17 THREE DIMENSIONAL TRANSPORT OF THE 241Am 237Np 233U 
229Th CHAIN  CONTINUOUS RELEASE 
In this section, we investigate the transport of the four-member 241Am 237Np 233U 
229Th chain continuously released from the repository. Each member of the chain has its 
own distinct transport behavior. Only mean present-day infiltration was considered in these 
simulations. The grids, flow fields, and conditions are as discussed in Section 6.7. The 
parameters used in these EOS9nT simulations are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. 
The DTN of the input and output files for the three present-day infiltration scenarios is 
Input/Output-DTN: LB0307MR0060R1.003 (Table 6.7-2). 
The evolution of the mass fractions RF in the release stream at the repository and at the water 
table is shown in Figures 6.17-1(a) and (b). Figure 6.17-1(a) is a straightforward representation 
of decay and generation for each member of the 241Am chain, and is unaffected by flow or 
transport conditions in the UZ because it reflects boundary conditions. Note that, because of the 
short half-life of 241Am, its concentration in the release stream falls to practically zero after about 
3,000 years, at which time 237Np is overwhelmingly the dominant species leaving the repository. 
The mass fractions at the water table in Figure 6.17-1(b) reflect the cumulative effects of passage 
through the UZ, i.e., the effects of matrix diffusion and sorption on the radionuclide 
concentration. Comparison of Figures 6.17-1(a) and (b) reveals that, as in the 239Pu chain case, 
the effluent at the water table is enriched in 237Np much earlier (about t=500 years). This 
behavior is caused by the much stronger sorption of 241Am in the UZ, coupled with the relatively 
weak sorption of 237Np (Table 6.5-1 and Section 6.9). The contribution of 233U exceeds only 1% 
after about 1,000,000 years, while the long cumulative half-lives of its parents make the 
contribution of 229Th negligible. 
The relative release rate at the water table is computed as the ratio of the total outflow rates (i.e., 
sum of individual member fluxes) versus the total inflow rates at the repository, and is shown in 
Figure 6.17-2. For the reasons discussed in Section 6.15, it is important to consider all the 
members of the chain in the computations of transport. Given the long half-life of 237Np (much 
longer than that of its 241Am parent; see Table 6.5-2), the daughter contributions cannot be 
neglected with impunity. The daughter contributions are even more important under wetter 
infiltration scenarios. The t10 and t50 of this chain under a continuous release scenario for a mean 
present-day infiltration are listed in Table 6.20-2. 

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(a) 
10-6 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
Mass fraction in the release stream at the repository 
101 102 103 104 105 
Time (years) 
241Am 
237Np 
233U 
229Th 
(b) 
10-6 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
Mass fraction in the release stream at the water table 
101 102 103 104 105 
Time (years) 
241Am 
237Np 
233U 
229Th 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.17-1. Mass Fractions of Each Member of the 241Am Chain in the Release Stream at (a) the 
Repository and (b) the Water Table  Continuous Release Mean Present-Day Climatic 
Scenarios 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized release rate at the water table 
101 102 103 104 105 
Time (years) 
0.1 fraction line 
0.5 fraction line 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.17-2. Normalized Relative Release RF of the Sum of All Members of the 241Am Chain at the 
Water Table  Continuous Release Mean Present-Day Climatic Scenario 

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6.18 THREE DIMENSIONAL SITE-SCALE TRANSPORT OF PuO2 COLLOIDS  
CONTINUOUS RELEASE 
In this section, we study the large-scale 3-D site-scale transport of true colloids in the Yucca 
Mountain UZ for mean present-day infiltration. The flow field and the 3-D grid are identical to 
the ones discussed in Sections 6.14 to 6.17. Radioactive colloids undergoing decay at the source 
were continuously released into the fractures of the elements corresponding to the repository. 
Section 6.18 includes eight subsections. In Section 6.18.1, we discuss the colloidal forms and 
properties. In Section 6.18.2 we present the mathematical model of filtration used in EOS9nT 
and discuss its parameters for the four colloids considered in the simulations. In Section 6.18.3, 
we describe the four cases of colloid transport investigated in this Model Report, and in Sections 
6.18.4 to 6.18.8 we discuss the simulation results for each case. 
6.18.1 Colloidal Forms and Properties 
Two classes of colloids, Class I and Class II, were considered in this study (see Section 
6.1.3.3.1). Class I includes true colloids and waste form colloids, in which the entire nonaqueous 
component of the colloid is composed of the radioactive substance. Those were taken to 
have the properties of PuO2 and are subject to radioactive decay. Additionally, the Class I 
colloid size and density were considered invariable during the simulation. This results in more 
conservative predictions because (a) matrix diffusion does not increase in response to a smaller 
colloid diameter, and (b) colloid filtration (the parameters of which are based on the actinide 
mass per unit volume) does not decrease due to lower concentrations. 
Class II colloids (i.e., pseudocolloids onto which radionuclides have sorbed irreversibly) rather 
than Class III colloids were considered because of the extraordinarily strong sorption of 
radionuclides on natural colloids (BSC 2003 [161620], Section 6.3.3.1). Computation of the 
transport of Class II colloids involves solution of the transport equation of the underlying nonradioactive 
pseudocolloid (i.e., that of the corresponding Class IV colloid -- see Section 
6.1.3.3.1, this Model Report). Then the radioactivity concentration is computed from 
Cr = CcXr0 ft (Eq. 6-31) 
where Cr is the actinide concentration [ML-3], Cc is the underlying non-radioactive colloid 
particle (Class IV colloid) concentration [ML-3], Xr0 is the initial mass fraction (i.e., at the time of 
release) of the irreversibly sorbed radionuclide in the colloidal particle, and ft is the remaining 
radionuclide mass fraction at time t. For a parent radionuclide, ft = exp(- .t). In this study, the 
irreversibly sorbed radionuclide in the Class II colloids was assumed to be 239Pu. 
In both colloidal classes considered in this study, four different colloid sizes were considered. 
Their sizes and their accessibility factors were calculated based on DTNs: 
GS950608312231.008 [144662], and GS980908312242.039 [145272], as reported in CRWMS 
M&O (2000 [122799], Section 6.2.1) and are shown in Table 6.18-1. The parameters used in 
these EOS9nT simulations of 3-D transport of the colloids are listed in Table 6.7-1, 6.7-2, 6.18- 
1, and 6.18-2. The DTN of the input and output files for the three present-day infiltration 
scenarios is Input/Output-DTN: LB0307MR0060R1.003 (Table 6.7-2). 

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6.18.2 Colloid Filtration Model and Coefficients 
Pore-size exclusion (straining filtration) was described using the accessibility factors shown in 
Table 6.18-1. The linear kinetic model of colloid filtration described by Equation 6-15 was used 
in the simulations. The forward kinetic coefficient .+ was computed from Equation 6-16, in which 
the velocity coefficients are as shown in Table 6.18-1, and the filter coefficient e is computed using 
Equations 2 and 6 of Harvey and Garabedian (1991 [109256]). In our nomenclature, this is 
e = 1.5
1 - f 
dm 
ac .c 
(Eq. 6-32) 
where dm is the particle size of the medium grains or the fracture aperture [L], ac is the collision 
efficiency factor and, and . is the single collector efficiency, and 
u 
gd 
d
d 
u d d 
T k c 
c 
m
c 
m c w 
B 
c  
. - . + . .. 
. 
. .. 
. 
+ . .. 
. 
. .. 
. 
 
= . 
18 
) ( 5 . 1 9 . 0 
2 2 3 / 2 
(Eq. 6-33) 
in which kB is the Boltzmann constant, dc is the colloid diameter [L], T is the absolute 
temperature, and all other terms remain as previously defined. The clogging (forward) kinetic 
coefficients .+ are computed internally in EOS9nT. 
No information exists on the kinetic declogging (reverse) coefficient .-. To alleviate the 
problem, .- in the EOS9nT coefficients was entered as a fraction of .+ (see Table 5-1). We 
believe that this is a sounder approach than the constant .- employed in CRWMS M&O (2000 
[122799], Section 6) because it maintains dependence on the flow velocity. Because the kinetic 
coefficient .+ is a linear function of the flow velocity, dependence of .- on velocity is 
conceptually sounder than the constant value approach. 
Table 6.18-1. Properties of the Four Colloids in the EOS9nT Simulations 
Parameter 450 nm 200 nm 100 nm 6 nm 
Diffusion coefficient D0 (m2/s) * 9.5310-13 2.1510-12 4.2910-12 7.1510-11 
Velocity adjustment factor f  1.5 1.2 1.1 1.0 
Accessibility factor f c in the TSw  0.05 0.10 0.20 0.65 
Accessibility factor f c in the CHv  0.45 0.50 0.55 0.80a 
Accessibility factor f c in the CHz  0.20 0.25 0.25 0.65 
NOTES: *: From Grathwohl 2000 [141512] 
: Reasonable estimates, see Table 5-1 
: DTN: GS950608312231.008 [144662], GS980908312242.039 [145272], CRWMS M&O (2000 
[122799], Section 6.2.1) 
a: Although a value of 0.85 was reported in CRWMS M&O [122799], the 0.8 value fits better the lognormal 
distribution of pore size exclusion. 

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Table 6.18-2. Input Parameters for the EOS9nT 3-D Site-scale Simulations of Colloid Transport 
(# 1 perched-water model, mean present-day infiltration) 
Parameters Source 
aTortuosity t ~ f Farrell and Reinhard (1994 [122803], p. 64) 
Properties and characteristics of the geologic 
units, steady-state pressures, water saturations 
and flow fields 
DTN: LB0210THRMLPRP.001 [160799], 
LB03023DSSCP9I.001 [163044] (Table 6.8-1) 
Colloid density .c = 11,640 kg/m3 (PuO2) Lide (1993 [123032], p. 4-83) 
Forward kinetic filtration (clogging) coefficient 
.+: from Equations 6-6, 6-32, and 6-33, 
parameters computed at 25 o C 
Harvey and Garabedian 1991 [109256], p. 180, 
Equation 6 
NOTE: a see Section 5, Table 5-1 for the assumption 
6.18.3 The Class I Colloid Transport Simulation Cases 
The following four cases were investigated: 
Case 1. .- = 0. This corresponds to a case of no declogging, in which colloids, once 
filtered, do not detach from the pore/fracture walls. 
Case 2. .-/.+ = 100. This corresponds to strong kinetic declogging and will provide an 
estimate of maximum colloidal transport. 
Case 3. .-/.+ = 0.1. This corresponds to weak kinetic declogging and approaches 
equilibrium filtration behavior. 
Case 4. Same as in Case 2, but the fractures are assumed to have the same colloidal 
transport properties as the corresponding matrix. This study provides an estimate 
of the importance of fractures in the transport of colloids. Note that the change in 
the filtration properties affects only 1% of the fracture pore volume (because f = 
0.99 in the fractures; see Equation 6-30). 
There is no filtration (attachment) of colloids onto the fracture walls in Cases 1 to 3. The t10 and 
t50 of the 239PuO2 colloid transport under a continuous release scenario and for a mean presentday 
infiltration are listed in Table 6.20-3. 
6.18.4 Colloid Transport Case 1 (Class I) 
This simulation assumes that no declogging occurs once colloids are attached to the matrix. 
Figure 6.18-1(a) shows the relative release rate RF of the four colloid sizes at the water table. For 
reference, the decaying release rate of the colloids at the repository (the same for all 239Pu 
colloids) is included in the figure. Two observations appear particularly important. The first is 
the very fast breakthrough of the larger colloids (characterized by a rapid rise of the 
breakthrough curves). The fast breakthrough is about the same for all the larger colloids. The 

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t10 for the three larger colloids is only about 5 years. After the fast rise, t50 is not reached for any 
colloid, and the RF begins declining as decay affects concentrations. The second observation is 
that, contrary to expectations, the smallest colloid (6 nm) exhibits the slowest breakthrough. It is 
really noteworthy that this colloid never reaches the 0.1 fraction level, indicating that it is 
sufficiently small to enter the matrix and get attached to the fracture walls. This behavior results 
from a combination of the following factors: 
1. The faster transport velocity of larger colloids, which, by virtue of their size, can only 
move in the center of pores/fractures where velocities are larger than the average water 
velocity. In this case, the 450 nm colloid moves at 1.5 times the water velocity (i.e., 
f=1.5; see Equation 6-16 in Section 6.2.4.1). 
2. Larger colloids are unable to penetrate the matrix from the fractures because of size 
exclusion. Thus, the colloid mass in the fractures is not reduced through colloidal 
diffusion and/or hydrodynamic dispersion, and practically all of it moves exclusively in 
the fractures. The 6 nm colloid can diffuse into the matrix, a process which in Figure 
6.18-1(a) manifests itself by the substantially slower breakthrough, the very slow and 
mild rise of the curve, and the low maximum RF value. 
After the initial rapid rise, the slope of the RF curve in the larger colloids becomes much milder, 
and is then followed by a short upward trend again, before it begins to decline at a point that 
coincides with the beginning of the rapid decline in concentration due to decay. This second 
upward trend is associated with the beginning of matrix flow of colloids. A similar trend, but 
much delayed, is observed in the 6 nm colloid. 
6.18.5 Colloid Transport Case 2 (Class I) 
6.18.5.1 Breakthrough Curves 
Figure 6.18-1(b) shows the relative release rate RF of the four colloid sizes at the water table. 
The differences between Case 1 and Case 2 are very small, and are most prominent in the case of 
the 6 nm colloid. The FR is higher in Case 2 because the few colloids that manage to enter the 
matrix are not irreversibly attached as in Case 1, but declog rather rapidly. The relative 
insensitivity to the clogging model in the matrix indicates the dominant role of the fractures in 
the 3-D site scale system, with the matrix appearing to have a minuscule contribution. Because 
of the similarity between Figures 6.18-1(a) and (b), the comments made in Case 1 apply here too. 
6.18.5.2 Transport Mechanisms and Patterns of the 6 nm Colloid 
The importance of fractures on the transport of the 6 nm colloid (Co0060) is evident in Figure 
VI.1 (see Attachment VI), which shows the areal distribution of XR in the aqueous phase in the 
fractures in the tsw39 layer at t = 10 years. Despite the very early time, the colloid concentration 
in the fracture is substantial. The reasons for the significant presence (in terms of areal extent 
and level of concentration) of the 6 nm colloid are that (a) diffusion into the matrix is limited 
because of its relatively large size (compared to solutes) and pore exclusion, and (b) the tsw39 
layer is above the TSw-CHn interface, where significant filtration occurs. Note that the 
distribution pattern of the fracture XR in Figure VI.1 indicates that the colloids accumulate at the 

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TSw-CHn interface and, unable to cross it, move along the sloping interface in an easterly 
direction. This transport is more pronounced in the 6 nm colloid than in the solutes. 
In contrast to Figure VI.1, the matrix XR in Figure VI.2 shows no difference from the background 
at the same time. In Figure VI.3, the distribution of matrix FR at t = 10 years shows a sizable 
presence of the 6 nm colloid filtered onto the matrix of the tsw39 layer. As in the case of sorbing 
solutes, the area of nonzero FR (Figure VI.3) is larger than that of the fracture XR footprint 
(Figure VI.3) at the same time, and shows the presence of filtered 6 nm colloids at locations 
where there appear to be no colloids suspended in the aqueous phase in the fractures. 
At t = 100 years, the fracture XR in Figure VI.4 is significant over a large area (larger than that 
for solutes at the same time) and is at its maximum value over a large portion of this area. 
Although the fracture XR (Figure VI.5) does not register a measurable difference from the UZ 
background, the matrix FR (Figure VI.6) shows a significant presence of the 6 nm colloid over an 
area larger than that covered by the fracture XR (Figure VI.4). Note that the matrix 
FR distribution indicates more filtration in the northern part of the repository. This is consistent 
with the permeability barriers that result in the perched-water bodies at this location. 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (years) 
REPOSITORY 
dc = 450 nm 
dc = 200 nm 
dc = 100 nm 
dc = 6 nm 
WATER TABLE 
dc = 450 nm 
dc = 200 nm 
dc = 100 nm 
dc = 6 nm 
Colloid transport 
Case 1 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (year) 
REPOSITORY 
450 nm 
200 nm 
100 nm 
6 nm 
WATER TABLE 
450 nm 
200 nm 
100 nm 
6 nm 
Colloid transport 
Case 2 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.18-1. Normalized Release at the Water Table in (a) Case 1 and (b) Case 2 of Colloidal 
Transport for Mean Present-Day Infiltration (All the Release Curves at the Repository are 
Superimposed). 

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A comparison of the matrix FR of the 6 nm colloid (Figure VI.6) to that of the dissolved 239 Pu 
(Figure VIII.3) shows a drastically different pattern. While the matrix FR distribution of 239 Pu 
shows concentration of sorption in the southern part of the repository, the FR of the 6 nm colloid 
shows filtration in both the northern and the southern part, i.e., colloids and sorbing radioactive 
solutes (Sections 6.12 to 6.15) are not similarly affected under the #1 perched-water model. The 
reason for the different behavior is attributed to (a) the lower diffusion of the colloid into (and 
the lack of filtration onto) the matrix (thus the faster transport of colloids in larger amounts than 
solutes to the TSw-CHn interface), (b) the lack of sorption and (c) the combined effects of 
pore-size exclusion and filtration at the interface that are quantitatively larger than the effects of 
sorption of the limited dissolved 239Pu amounts. 
The fracture XR, matrix XR, and matrix FR distributions at t = 1,000 years and t = 10,000 years are 
shown in Figures IX.7 to IX.12, and they follow the same pattern. The matrix XR registers 
measurable deviations from background at t = 1,000 years (Figure IX.8), and it shows extensive 
areas of relatively high concentrations at t = 10,000 years (Figure IX.11). At t = 10,000 years, 
the concentration in the fractures exceeds that in the water released from the repository (i.e., XR = 
1.07 in tsw39). This is caused by pore-exclusion (straining) at the TSw-CHn interface, which 
leads to the accumulation of the 6 nm colloid in the tsw39. 
Transport at the water table is shown in Figures VI.13 to VI.24, and follows patterns analogous 
to those in the tsw39 layer. The high concentrations at the water table at early times (t = 100 
years) are noteworthy. Matrix XR begins to show signs of colloid presence at t = 1,000 years, and 
shows highly localized areas of large concentration at t = 10,000 years. The nonzero area of the 
matrix FR is consistently larger than that for fracture XR. 
Note that the fracture XR above the water table exceeds that in the water released from the 
repository, and the differences between the two increases with time. At t = 10,000 years, the 
maximum fracture XR > 2, i.e., the concentration of the 6 nm colloid in the fractures above the 
water table is more than double that in the water released at the repository. This occurs because 
of the fast transport of the colloids in the fractures (where limited attachment occurs because of 
the large fracture porosity, i.e., f = 1.0) and their accumulation. This accumulation is caused by 
the very significant pore-size exclusion and kinetic (physical-chemical) filtration at the water 
table, which prevent colloids from entering the saturated zone while allowing water to flow into 
it. This occurs because the saturated zone behaves as a porous (rather than a fractured) medium 
with the properties of the TSw matrix. 
Review of Figures VI.1 through VI.24 indicates that transport of the 6 nm colloid is dominated 
by the faults identified and discussed in Sections 6.10 to 6.12. Diffusion from the fractures into 
the matrix is delayed for the reasons discussed earlier, but the areal extent and the magnitude of 
the filtered concentration (indicated by the FR distribution) indicates that its effect is sizable. 
6.18.5.3 Transport Mechanisms and Patterns of the 450 nm Colloid 
The fracture XR, matrix XR and matrix FR distributions of the 450 nm colloid (Co450) in the 
tsw39 and above the water table are shown in Figures VII.1VII.24 (see Attachment VII). These 
figures correspond to the same times discussed in the 6 nm colloid. 

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Comparison of the figures in Attachment VII to those for the 6 nm colloid (Attachment VI) 
indicates that fractures are far more important to the transport of the 450 nm colloid. Supporting 
evidence is provided by (a) the larger areal extent and values of the fracture XR, (b) the smaller 
areal extent and lower values of the matrix FR, and (c) the substantial delay in the appearance of 
450 nm colloids in the matrix aqueous phase, when compared to the 6 nm case. 
Thus, the fracture XR in Figure VII.4 (t = 100 years) indicates contributions from the whole area 
(at least) of the repository, and shows a much larger footprint than the one corresponding to the 6 
nm colloid. At the water table and at early times (<10,000 years), the maximum fracture 
XR exceeds 1 (=1.50) because of straining (pore-size exclusion). Because of its larger size, the 
straining is more pronounced for the 450 nm colloid than in the 6 nm colloid, and leads to higher 
concentrations at earlier times behind the interface. An XR>1 does not necessarily mean 
clogging and decrease in permeability (at least for a long time) if the concentrations of the 
colloid waste form are sufficiently low. 
Compared to the 6 nm colloid, the 450 nm colloid exhibits consistently lower matrix FR values 
over smaller areas (see Figures VII.3, VII.6, VII.9, VII.12, VII.15, VII.18, VII.21, VII.24). This 
is consistent with the expectation of lower diffusion from the fractures into the matrix and 
increased straining because of its larger size. 
6.18.6 Colloid Transport Case 3 (Class I) 
The change in the magnitude of the reverse kinetic filtration coefficient .- (as a fraction of .+ ) 
has a very small effect on colloid transport (Figure 6.18-2(a)), attesting to the fact that the role of 
advection through fracture flow (the same in Cases 1 through 3) is by far the dominant 
mechanism of colloid transport. Although this case is closer to equilibrium filtration, the effect 
on transport is apparent only in the case of the 6 nm colloid (which can enter the pores, and thus 
be subject to filtration), which shows an RF even lower than that of Case 2. 
The insensitivity of transport of the larger colloids to the sorption model in the matrix indicates 
that the matrix has practically no participation in the retardation, which is attributed to straining 
at matrix/fracture interfaces. The pattern that emerges is the same as the one discussed in Case 1, 
and all the comments made and conclusions reached therein apply. 
6.18.7 Colloid Transport Case 4 (Class I) 
By assigning a porosity of 1% to the fractures, and setting the fracture filtration properties equal 
to those of the matrix in Case 2, we create a system in which the fractures are partially filled with 
a porous medium. The simulation results are shown in Figure 6.18-2(b). The effect of limited 
diffusion on transport (because of pore-size exclusion and filtration) becomes more obvious in 
this case. While the more-freely-diffusing 6 nm colloids exhibit a behavior similar to the one in 
Cases 1 through 4, the effect on the larger colloids is more dramatic. The occurrence of even a 
minor fillup retards the colloid transport, increasing t10 to about 30 years, and registering a t50 of 
about 100 (for the 450 nm colloid) to 150 years (for the 200 nm colloid). The maximum RF 
exceeds that in Case 2 because of temporary colloid storage in (and subsequent release from) the 
porous medium that partially fills the fractures in Case 4. 

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Additionally, the breakthrough curve assumes a decidedly different shape in the larger colloids, 
marked by a sudden and dramatic reversal that is consistent in all the three larger colloids. As the 
occurrence of this phenomenon coincides with the onset of rapid decline in concentrations due to 
radioactive decay, it is assumed that the kinetic filtration model is very sensitive to minute 
changes in concentration at this pointhence the sudden slope reversal. However, this issue is 
not well understood and will require further investigation. 
Note that the significant differences among Figures 6.18-2(b) and 6.18-1(a), 6.18-1(b), and 6.18- 
2(a) result from assigning matrix filtration properties to only 1% of the pore volume of the 
fractures (by no means an unphysical or unlikely scenario). The significant retardation of the 
colloids gives a measure of the importance of fractures and their relative contribution to the total 
colloid transport through the UZ system. 
6.18.8 Transport of Class II Colloids (Case 2 and 3) 
The transport simulations were repeated for Class II colloids with the filtration behavior of Cases 
2 and 3 (see Section 6.18.3). As discussed earlier, radioactive concentrations (and fluxes) were 
obtained by first computing the transport of the non-radioactive corresponding Class IV colloid, 
and then multiplying it by the remaining radionuclide mass fraction ft (see Eq. 6-31, Section 
6.18.1). 
Given the approximation of constant colloid size in the Class I simulations, the RF results of the 
Class II simulations were not expected to be very different. Although the radioactive 
concentrations are much lower in the transport of Class II colloids than in Class I (of the same 
size and colloid population per unit volume) because of the radioactive component constitutes a 
small fraction of the total mass, the relative release rate RF (with respect to the initial release rate 
at the repository) in both cases are practically identical. This is explained by the fact that, 
mathematically speaking, there is very little difference in the transport equations between these 
two classes of colloids of the same sizes when the same colloid filtration parameters are 
assumed. Realistic differences between these two colloid classes are certain to exist in the 
properties of these two very different (physically and chemically) colloid classes, which will 
affect their filtration behavior and the corresponding filtration parameters. However, 
information on the subject is scant. 
Figure 6.18-3 confirms the expectation discussed above. A comparison of the RF curves over 
time shows practically no difference from the corresponding results for the Class I colloids in 
Figures 6.18-1 and 6.18-2. 
6.18.9 Uncertainties and Limitations 
While the results in this section provide some elucidation of colloid transport, caution should be 
exercised in the interpretation of the simulation results. The reason for this caution is the 
realization of the substantial knowledge gaps that hamper the study of colloid behavior. Thus, 
these results should be viewed as indicative and qualitative, rather than quantitative and 
predictive. 

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Thus, it must be pointed out that basic knowledge about the kinetic clogging and declogging 
coefficients .+ and .- is embryonic at best, thus severely limiting our predictive capabilities. 
Despite the insensitivity of transport to the filtration parameters in Cases 1 through 3, the 
significant change in transport behavior when 1% of the fracture volume is given the attributes 
of the matrix should provide grounds for caution. 
There are significant uncertainties in colloid modeling. It is not known whether the applicability 
limits of the currently available kinetic models, developed from theoretical principles (Herzig et 
al. 1970 [117519]) and tested in uniform sandy laboratory experiments (van de Weerd and 
Leijnse 1997 [109249]) or small-scale field tests (Harvey and Garabedian 1991 [109256]), are 
breached under the UZ conditions at Yucca Mountain. The C-Well experiments (BSC 2003 
[162729]) addressed some of the colloid-related uncertainties under realistic field conditions. 
However, the applicability of the information gleaned from those tests (conducted in the 
saturated zone) to the UZ has not been established. The affinity of colloids for air-water 
interfaces can have a significant effect on their transport. The limitations in the equations for the 
prediction of the forward kinetic filtration (clogging coefficient) have not been tested under the 
UZ conditions, and the subject of the kinetic declogging coefficient has barely been raised (let 
alone studied). Additionally, it is unclear how representative the current size-exclusion (straining 
filtration) models are. Additional challenges and uncertainties are discussed in detail in Section 
6.1.3. 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (year) 
REPOSITORY 
450 nm 
200 nm 
100 nm 
6 nm 
WATER TABLE 
450 nm 
200 nm 
100 nm 
6 nm 
Colloid transport 
Case 3 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (years) 
REPOSITORY 
dc= 450 nm 
dc= 200 nm 
dc= 100 nm 
dc= 6 nm WATER TABLE 
dc = 450 nm 
dc = 200 nm 
dc = 100 nm 
dc = 6 nm 
Colloid transport 
Case 4 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.18-2. Normalized Release at the Water Table in (a) Case 3 and (b) Case 4 of Colloidal 
Transport for Mean Present-Day Infiltration (all the release curves at the repository are 
superimposed). 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current at water table / initial at repository) 
100 101 102 103 104 105 106 
Time (years) 
WATER TABLE 
dc = 450 nm 
dc = 200 nm 
dc = 100 nm 
dc = 6 nm 
Case 2 - Transport of Colloids 
With Irreversibly Sorbed 239Pu 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current at water table / initial at repository) 
100 101 102 103 104 105 106 
Time (years) 
WATER TABLE 
dc = 450 nm 
dc = 200 nm 
dc = 100 nm 
dc = 6 nm 
Case 3 - Transport of Colloids 
With Irreversibly Sorbed 239Pu 
Output-DTN: LB0310MR0060R1.010, data submitted with this Model Report 
Figure 6.18-3. Normalized Release at the Water Table in (a) Case 2 and (b) Case 3 of Colloidal 
Transport with irreversibly sorbed radionuclide (Mean Present-Day Infiltration) 

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6.19 ALTERNATIVE MODELS 
6.19.1 Alternative Representations and Methods 
In this section, we investigate alternative conceptual models involving: 
a) Different representations of the matrix-fracture system (multiple interactive continua 
versus dual-permeability systems) 
b) Different conceptual methods of describing the transport problem (particle tracking 
versus conventional representation). 
Thus, we consider the effects of employing the concept of the Multiple Interactive Continua 
(MINC, as implemented by the development of a different grid system in TOUGH2 simulations) 
(Pruess and Narasimhan 1985 [101707]) on transport predictions related to the RTM. In the 
MINC method, the steep gradients at the matrix fracture surface are resolved by subgridding of 
the matrix blocks in an appropriate number of shells. The MINC concept is based on the notion 
that changes at the fracture-matrix interface will propagate rapidly through the fracture system, 
while invading the tight matrix comparatively slowly. Thus, changes in the matrix conditions are 
controlled locally by the distance from the fractures, leading to the creation of a system of nested 
subdomains. The MINC behavior is expected to result in slower breakthrough curves (as the 
enhanced fracture-matrix interaction allows for increased diffusion), longer contact times, and 
more effective sorption (in sorbing media/solute systems). As members of the TOUGH2 family 
of codes, both T2R3D and EOS9nT are capable of handling MINC grids. Additionally, we 
investigate the potential of analyzing the transport problem using particle-tracking-based 
numerical models (DCPT V1.0; LBNL 2000 [132448]; DCPT V2.0; LBNL 2002 [154342]) that 
appear attractive in terms of execution and storage requirements compared to the conventional 
models (e.g., T2R3D and EOS9nT). 
The grid that described transport of a conservative tracer through a 2-D vertical cross section 
(slice) of the UZ was provided by DTN: LB0308AMRU0185.001 [165172]. The input and 
output files and data for this study are in DTNs: LB03093RADTRNS.001 [166225] and 
LB03093RADTRNS.002 [166071]. 
The results of the simulation are shown in Figure 6.19-1. Predictions from T2R3D and EOS9nT 
with a conventional dual-permeability grid and a MINC grid are in very good agreement. The 
result with the MINC grid conforms to expectations, resulting in slower breakthrough curves. 
Note that despite its scientific and conceptual appeal, the application of the MINC concept to the 
3-D UZ site-scale model is challenging because it necessitates replacement of the single matrix 
block in the current dual permeability system with several MINC subdomains. This increases the 
already large size of the problem, the memory requirements, and the execution times. 
The DCPT V1.0 and DCPT V2.0 (LBNL 2000 [132448]; 2002 [154342]) particle-tracking code 
could provide an alternative, because it enjoys the advantages of low memory requirements and 
fast execution. Figure 6.19-1 shows that the DCPT V1.0 and V2.0 (LBNL 2000 [132448]; 2002 
[154342]) solutions are close to the predictions from the MINC grid (although somewhat more 
diffusive). 

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6.19.2 Alternative Diffusion Model 
As shown in Sections 6.8 to 6.18, the main mechanism of radionuclide retardation in the UZ is 
diffusion from the fractures into the matrix. This process transfers radionuclides from the 
fractures (the pathways of fast flow and the main conduits of transport) to the matrix, where their 
transport is retarded because of the much slower water velocities and matrix sorption. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
100 101 102 103 104 105 106 
Time (years) 
EOS9nT 
Dual k, D = 0 
Dual k, D  0 
MINC, D = 0 
MINC, D  0 
T2R3D 
Dual k, D = 0 
Dual k, D  0 
MINC, D = 0 
MINC, D  0 
YM 2-D 
DCPT, Dual k 
v2.0, D  0 
v1.0, D  0 
DTNs: LB03093RADTRNS.001 [166225] and LB03093RADTRNS.002 [166071] 
Figure 6.19-1. Effect of (a) the MINC Concept and (b) Application of Particle-Tracking Approaches on 
Breakthrough Predictions at a 2-D Vertical Cross Section of the UZ 
In this section, we investigate the effect on transport of an alternative conceptual model that does 
not consider matrix diffusion. In other words, transport in this alternative model is limited to 
advection in the matrix and in the fractures. Thus, there is no mechanism for radionuclide 
removal from the fractures other than (a) the relatively small sorption on the fracture walls where 
the majority in fracture flow (the dominant portion of flow) and (b) sorption in the matrix, where 
only a small fraction of flow occurs. For non- and moderately sorbing radionuclides, this means 
that there is no means of retardation, and the contaminants in the fractures are transported 
virtually unhindered to the groundwater. 

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Note that this alternative model is far more relevant to solutes than to colloids. Because of the 
very small diffusion coefficient of colloids, transport is advection dominated and diffusive fluxes 
for the larger colloids (100 nm to 450 nm colloids) are minuscule, as attested to by the practical 
coincidence of the early portions of the RF curves (see Section 6.18, this Model Report). 
6.19.2.1 Instantaneous release 
The grids, flow fields, and conditions are identical to those in Section 6.7. The parameters used 
in these T2R3D simulations are listed in Tables 6.5-1, 6.7-1, and 6.7-2. The input and output 
files for these simulations are included in DTNs: LB0310MR0060R1.010 and 
LB0310MR0060R1.011, respectively (Table 6.7-2). 
For instantaneous release and a mean present-day infiltration, the cumulative breakthrough 
curves of the normalized mass fraction RM in Figure 6.19-2 confirm the expectation of virtually 
unimpeded transport to the groundwater. The contrast to the RM evolution when matrix diffusion 
is considered (also included in Figure 6.19-2) is dramatic. Despite their very different sorption 
affinity to the UZ rocks, all three radionuclides (the nonsorbing 99Tc, the moderately sorbing 
237Np and the strongly-sorbing 239Pu) move unhindered in the fractures in the absence of matrix 
diffusion, and their breakthrough curves to t = 100 years coincide. Transport in this case is 
extremely fast. The t10 and t50 of all three radionuclides are about 5 years and 20 years, 
respectively. 
The very fast early transport and the coincidence of the RM curves are the result of advection 
(linked to the to rapid fracture flow) and the lack of matrix diffusion. This result is consistent 
with expectation because there is no other mechanism that can affect transport during this early 
stage. Note that, by setting f = 1 in the fractures, sorption onto the fracture walls is not 
considered in these simulations. 
After the very fast rise of RM (indicated by the steep slope for t > 100 years in figure 6.19-2), the 
RM slope becomes much flatter and the three breakthrough curves begin to differentiate because 
of contributions of matrix flow (and advection) to transport. The change of the slope indicates 
exhaustion of the radionuclide supply in the fractures (from the initial from the instantaneous 
release). The breakthrough curve of 239Pu daughters shows a plateau after the initial steep rise 
portion. This is caused by the very strong 239Pu sorption onto the matrix of the UZ rocks, which 
does not allow 239Pu in the matrix flow to reach the water table. Thus, all the 239Pu in the 
fractures reaches the water table in a very short time, and all 239Pu in the matrix is trapped by 
sorption. 
Because of its moderate sorption affinity to the UZ rocks, the 237Np breakthrough shows a very 
mild increase from t = 100 years to t = 20000 years, after which time it registers a fast rise. This 
is attributed to arrival at the water table (through matrix flow and advection) of 237Np that had 
sorbed onto and traveled through the matrix, into which it had been transported by fracture-tomatrix 
flow. Because of lack of sorption, the 99Tc breakthrough curve is marked by a shorter 
period of the mild slope (up to about t = 3,000 years) and an earlier arrival of 99Tc through 
matrix advection. 

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The results of this study emphasize the importance of diffusion from the fractures into the matrix 
as the main mechanism for retardation of radionuclide transport. When this process is not 
considered in the simulations, radionuclides reach the water table in significant quantities in less 
than 5 years. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized mass fraction 
100 101 102 103 104 105 106 
Time (years) 
D = 0 
99Tc 
237Np 
239Pu 
D > 0 
99Tc 
237Np 
239Pu 
0.1 fraction line 
0.5 fraction line 
Figure 6.19-2. Cumulative breakthrough of radioactive solutes at the water table for the no-diffusion 
alternative model (mean present-day infiltration, instantaneous release). 
6.19.2.2 Continuous release 
The grids, flow fields, and conditions are identical to those in Section 6.15. The parameters used 
in these EOS9nT simulations are listed in Tables 6.5-1, 6.7-1, and 6.7-2. The input and output 
files for these simulations are included in DTN: LB0310MR0060R1.010 and 
LB0310MR0060R1.011, respectively (Table 6.7-2). 

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For continuous release and a mean present-day infiltration, the relative release rate RF curves in 
Figure 6.19-3 confirm the expectation of virtually unimpeded transport to the groundwater. For 
reference, the relative release rates of the decaying parents at the repository are also included. 
The contrast to the RF evolution when matrix diffusion is considered (see Figure 6.15-1, this 
Model Report) is remarkable. Despite their very different sorption affinity to the UZ rocks, all 
three radionuclides (the nonsorbing 99Tc, the moderately sorbing 237Np, and the strongly-sorbing 
239Pu) move unhindered in the fractures in the absence of matrix diffusion, and their 
breakthrough curves to t = 70 years practically coincide. Transport in this case is extremely fast. 
The t10 of all three radionuclides is about 2.5 years, while t50 ranges from 70 (for 99Tc) to 80 (for 
237Np) to 85 years (for 239Pu). The early behavior reflects fracture transport exclusively, and the 
identity of the RF curves of the three radionuclides results from the absence of diffusion into the 
matrix. Note that, by setting f = 1 in the fractures, sorption onto the fracture walls is not 
considered in these simulations. 
The RF curves show a very mildly sloping region (almost a plateau) at t = 30 years. The near-flat 
portion of the RF curves indicates a roughly constant radionuclide release rate at the water table, 
all of which is attributable to fracture flow. The matrix effects begin to become evident for t > 
70 years, when matrix flow (and the contaminants it transports) begins to arrive at the water 
table, at which time the RF curves of the three radionuclides begin to diverge. The arrival of 
matrix flow is indicated by the rising (steeper) portion of the RF curve after the first plateau 
(associated with fracture-based advection). 
After t = 100 years, the nonsorbing 99Tc is not retarded during matrix flow and arrives at the 
water table earlier (indicated by higher RF values) than the moderately sorbing 237Np, while the 
239Pu arrival at the water table is the slowest of the three and consistent with its strong sorption 
affinity to the UZ rocks. After attaining maxima at different times (consistent with the different 
half-lives of the actinides), RF curves begin to decline because of radioactive decay 
Accounting for the 239Pu daughters leads to a somewhat different pattern. A plateau in RF is 
observed from t = 1,000 to t = 10,000 years (denoting stability of the ratio of repository and 
water table fluxes), followed by a sharp increase. This is attributed (almost exclusively) to the 
arrival at the water table of larger amounts of the 235U daughter, which sorbs less strongly and 
has a longer half-life than 239Pu. The 235U arriving at the water table originates from direct 235U 
source releases at the repository (transported mostly by fracture advection), and from the decay 
of both free and sorbed 239Pu in the matrix of the UZ rocks. The difference in the RF patterns 
and the much higher levels of RF attained in this case underscore the importance of accounting 
for daughters in radionuclide transport studies (see Sections 6.16 and 6.17). 
The results of this study confirm the observations made in the case of instantaneous release on 
the importance of diffusion from the fractures into the matrix as the main mechanism for 
retardation of radionuclide transport. When this process is not considered in the simulations, 
very fast travel times are observed, and radionuclides reach the water table in less than 5 years. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate 
101 102 103 104 105 106 
Time (years) 
REPOSITORY 
99Tc 
237Np 
239Pu 
239Pu+235U+231Pa 
WATER TABLE 
99Tc 
237Np 
239Pu 
239Pu+235U+231Pa 
0.1 fraction line 
0.5 fraction line 
Figure 6.19-3. Relative release rate of radioactive solutes at the water table for the no-diffusion 
alternative model (mean present-day infiltration, continuous release). 

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6.20 BARRIER EVALUATION, UNCERTAINTIES, AND A NOTE OF CAUTION 
In this section, we distill the results presented in Sections 6.6 to 6.20 into an overall evaluation 
of the performance of the Yucca Mountain UZ as a barrier. We discuss the issue of uncertainty 
and the effect it may have on predictions of barrier performance. Finally, we address the issue of 
the framework within which the results and predictions in the Model Report should be 
understood and interpreted. 
6.20.1 Barrier Performance 
The t10 and t50 values for all the radionuclides, all the climatic scenarios, and the two release 
scenarios (instantaneous and continuous) are listed in Tables 6.20-1 to 6.20-3. A long t10 and a 
long t50 are desirable because they indicate desirable barrier performance. Of the two, 
t10 provides a measure of influence for the most conductive fractures on the UZ barrier behavior, 
while t50 accounts for the effects of both fractures and matrix. A short t10 and a short t50 could be 
an indication of inadequate barrier performance. A short t10 but an adequately long t50 is an 
indication of a system with strong early arrivals at the water table because of fracture-dominated 
flow (and, consequently, transport), but with an adequate overall barrier performance in the long 
run. 
A review of the results in Tables 6.20-1 to 6.20-3 indicates that, in conformance with 
expectations, the barrier performance of the UZ is a function of the radionuclide under 
investigation. Additionally, there is an almost universal early arrival of a small portion of the 
total released mass (usually = 10%) at the water table. The early arrivals are caused by the very 
permeable fractures at the Drillhole Wash fault and the Pagany Wash fault, and, to a much lesser 
extent, the Sundance fault, which lead to fast advective transport. Thus, by having the repository 
footprint straddling important faults, and by following an approach that releases radionuclides 
throughout the repository, the barrier of the UZ is breached, once the WP and EBS systems are 
breached. 
Based on the flow model described in BSC (2003 [163045], Section 6) and incorporated into this 
transport study (and despite the adverse release patterns and approaches discussed above), the 
UZ appears to be an effective barrier in the transport of the following radionuclides: 
a) 90Sr and 226Ra: In the 1,000,000-year study period, their migration through the UZ registers 
arrivals of less than 10% of the original mass (under instantaneous release) at the water 
table, even under the most humid of the present-day and monsoon infiltration regimes, and 
for low and mean glacial infiltration. This is caused by an early arrival (related to fracture 
flow and the related advection) of a small portion of the total mass (>10%) only for an 
upper glacial infiltration. Early arrivals are caused by the very permeable fractures at the 
faults discussed earlier. The low fraction of the total mass reaching the water table is 
caused by diffusion into the matrix, strong sorption in the matrix, and the relatively short 
half lives of these radionuclides, combining to prevent any matrix-associated radionuclide 
advection to the water table. 
b) 229Th: With the exception of the upper monsoon and glacial infiltrations, less than 10% of 
the initially released mass reaches the water table. Although a short t10 is observed for the 

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most humid of the glacial and monsoon infiltration regimes, only a small portion of the 
total mass (<20%) arrives at the water table in the 1,000,000-year study period. This is 
attributed to the strong sorption (after diffusion into the matrix) and the relatively short 
half-life of 229Th, which eliminate any matrix-related 229Th advection to the water table. 
c) 241Am and 221Pa: With the exception of the most humid (upper) conditions of all three 
climatic scenarios (present-day, monsoon, and glacial), less than 10% of the initially 
released mass reaches the water table. As appears to be the case with all radionuclides, 
there is an early arrival, but only a small portion of the total mass (<20%) arrives at the 
water table in the 1,000,000-year study period. This is caused by diffusion into the matrix, 
strong sorption in the matrix, and the relatively short half lives of these radionuclides. 
Thus, radionuclide arrivals are limited to early advection due to fracture flow, with no 
apparent contributions of matrix transport to water table arrivals. 
d) 239Pu: The transport of 239Pu is characterized by the early arrival (common to all 
radionuclides at the UZ) of a small portion of the total released mass. As in the case of 
241Am and 221Pa, with the exception of the most humid (upper) conditions of all three 
climatic scenarios (present-day, monsoon, and glacial), less than 10% of the initially 
released mass reaches the water table in this early arrival. Although 239Pu sorbs strongly 
onto the matrix after diffusion from the fractures (the overwhelmingly dominant transport 
features), the breakthrough curves in Figures 6.10.1 to 6.10.3 indicate contributions of 
matrix-related advection to transport (indicated by the second plateau in the figures). This 
is possible because of the long half-life of 239Pu, which exceeds the travel time of matrix 
flow to the water table. However, the fraction of the total mass that arrives at the water 
table over the 1,000,000-year study period does not exceed the 50% level under any 
climatic conditions. 
The effects of having (a) the repository straddle important faults and releasing radionuclides 
directly into the fault fractures (the approach followed in this study) and (b) the improbably 
conservative (if not practically impossible) approach described in Section 6.7.8, are apparent in 
the UZ barrier performance in the transport of the remaining radionuclides considered in this 
study. By allowing these conditions, the barrier appears far less effective, as indicated by the 
breakthrough curves of the variably sorbing 135Cs (strongly on zeolites, much less on other 
rocks), the mildly sorbing 233U, 235U, 237Np, and the nonsorbing 99Tc. All these radionuclides 
have long half-lives (indicating matrix-based advective contributions to transport) and show 
substantial arrivals at the water table at times that are shorter than their half-lives. Ensuring that 
the repository is not extended across the important faults discussed earlier is deemed critical in 
maintaining the integrity of the UZ barrier. 

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Table 6.20-1. Radionuclide Travel Times to the Water Table (Instantaneous Release) 
Present-Day Monsoon Glacial-Transition Radionuclide 
Infiltration 
Scenario t10 (years) t50 (years) t10 (years) t50 (years) t10 (years) t50 (years) 
241Am Lower - - - - - - 
Mean - - - - - - 
Upper 12 - 3 - 1 - 
237Np Lower 33,800 >1,000,000 15 6,160 185 34,400 
Mean 410 25,400 8 2,120 4 1,070 
Upper 4 1,600 2 714 1 336 
231Pa Lower - - - - - - 
Mean - - - - - - 
Upper 13 - 4 - 2 - 
239Pu Lower - - 86,000 - - - 
Mean - - 10,400 - 3,710 - 
Upper 1,530 - 4 - 2 - 
226Ra Lower - - - - - - 
Mean - - - - - - 
Upper - - - - 3 - 
90Sr Lower - - - - - - 
Mean - - - - - - 
Upper - - - - 3 - 
99Tc Lower 13,900 >1,000,000 22 1,310 102 8,140 
Mean 83 6,640 9 417 6 164 
Upper 6 230 2 92 1 42 
229Th Lower - - - - - - 
Mean - - - - - - 
Upper - - 4 - 2 - 
233U Lower 65,200 >1,000,000 103 6,730 549 36900 
Mean 433 29,100 34 2,130 16 893 
Upper 12 1,120 3 458 2 208 
235U Lower 55,300 784,800 101 6480 540 32,600 
Mean 430 26,500 34 2080 15 882 
Upper 12 1,100 3 450 2 206 
135Cs Lower >1,000,000 >1,000,000 22,400 >1,000,000 150,000 >1,000,000 
Mean 52,500 >1,000,000 4,690 309,000 2,460 120,000 
Upper 2,170 71,200 753 24,500 305 990 
Output-DTN: LB0307MR0060R1.007 
NOTE: (-): t10 or t50 has never been reached because of radioactive decay. 
(>1,000,000): Simulations only up to 1,000,000 years. The t10 or t50 can be reached after 1,000,000 years. 

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Table 6.20-2. Radionuclide Travel Times to the Water Table under Continuous Release 
Case Species t10 (years) t50 (years) 
Three-Parents 99Tc 74 3,901 
237Np 781 22,940 
239Pu - - 
239Pu-Chain 239Pu+235U+231Pa 6,419(a) 33,660(a) 
241Am-Chain 241Am+237Np+233U+229Th 1,027(a) 23,450(a) 
Output-DTN: LB0307MR0060R1.007 
NOTE: (a) Corresponds to the sum of the chain members 
(-):t10 or t50 has never been reached because of radioactive decay. 
Table 6.20-3. Colloid Travel Times to the Water Table (Continuous Release) 
Casea Colloid Size (nm) t10 (years) t50 (years) 
1 450 4.35 - 
200 4.39 - 
100 4.53 - 
6 - - 
2 450 4.35 - 
200 4.39 - 
100 4.53 - 
6 - - 
3 450 4.35 - 
200 4.39 - 
100 4.52 - 
6 - - 
4 450 32.4 243 
200 27.8 251 
100 27.6 - 
6 - - 
Output-DTN: LB0307MR0060R1.007 
NOTE: (-):t10 or t50 has never been reached because of radioactive decay. 
a=Cases are defined in Section 6.18.3 

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6.20.2 The Effect of Radionuclide Release Directly Into The Fault Fractures 
Based on the breakthrough results and the transport patterns determined in Sections 6.8 to 6.19, 
the early arrival of radionuclides at the Yucca Mountain water table (indicated by the low 
t10 values) was attributed to advective transport through the fractures associated with the 
Drillhole Wash fault and the Pagany Wash fault. The concentration distributions in the fractures 
at both the bottom of the TSw and at the water table even at very early times (t = 10 years) and 
for both types of release (instantaneous and continuous) coincide with the fault outline. Thus, it 
was important to evaluate the impact of releasing radionuclides directly into the fractures of 
these faults. 
This was accomplished by repeating select radionuclide transport simulations in which the initial 
radionuclide concentration in repository gridblocks (a) representing the fault or (b) being 
adjacent to it had been set to zero. In essence, radionuclide sources were removed from the 
faults and from gridblocks on either side of them. These simulations were limited to (a) meanpresent 
day infiltration and (b) the radioactive solutes 99Tc, 237Np, 239Pu and 235U, which cover 
the spectrum of sorption behavior. Both release scenarios (instantaneous and continuous) were 
investigated. 
The grids, flow fields, and conditions are as discussed in Section 6.7. The parameters used in 
3-D simulations are listed in Tables 6.5-1, 6.6-1, 6.7-1, and 6.7-2. The initial condition files 
INCON were the only difference between the input files and those of the corresponding 
simulations discussed in Sections 6.8 to 6.11 and 6.15. The DTN of the input and output files for 
the three present-day infiltration scenarios is Input/Output-DTN: LB0307MR0060R1.005 
(Table 6.7-2). 
Contrary to expectations, eliminating potential sources from the vicinity of the fault fractures 
appears to have only a small effect on transport and arrivals at the water table. For instantaneous 
release (when a finite radionuclide mass is involved), the RM breakthrough curves in Figures 
6.20-1 and 6.20-2 show a small increase in t10 (in line with expectations because there is no 
release into the fast-conducting fault fractures), but t50 is practically unchanged. The RF 
breakthrough curves in Figures 6.20-3 and 6.20-4 for continuous release show practically no 
discernible difference from those that account for release into the faults (Section 6.15). 
The reason for this is demonstrated in the contour plots of the 99Tc distribution of XR in 
Attachment VIII. The effects of eliminating releases from the immediate vicinity of the faults 
are obvious at the bottom of the TSw, at which level the radionuclide distribution shows 
significant retardation compared to that shown in Figures 6.8-2 to 6.8-11. This is particularly 
evident in the northern part of the repository, where the outlines of the Drillhole Wash fault and 
of the Pagany Wash fault (which dominated transport when radionuclides were released 
throughout the area of the repository) are absent from the contour plots in Figures VIII.1 to 
VIII.10. Remarkably, the XR distribution at the water table (Figures VIII.11 to VIII.20) is very 
similar to that with direct releases into the faults (Figures 6.8-12 to 6.8-21), and is dominated by 
transport through the Drillhole Wash fault and the Pagany Wash fault. 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
100 101 102 103 104 105 106 
Time (years) 
99Tc - Instantaneous Release 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
100 101 102 103 104 105 106 
Time (years) 
237Np - Instantaneous Release 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.20-1. Cumulative Breakthrough of the 99Tc and 237Np Mass Fractions RM at the Water Table 
(Instantaneous Release, Mean present-day infiltration, no Fault Releases) 

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(a) 
0.10 
0.08 
0.06 
0.04 
0.02 
0.00 
Normalized Mass Fraction 
100 101 102 103 104 105 106 
Time (years) 
239Pu - Instantaneous Release 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Normalized Mass Fraction 
100 101 102 103 104 105 106 
Time (years) 
235U - Instantaneous Release 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.20-2. Cumulative Breakthrough of the 239Pu and 235U Mass Fractions RM at the Water Table 
(Instantaneous Release, Mean present-day infiltration, No Fault Releases) 

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(a) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (years) 
Repository 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
99Tc - Continuous Release 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (years) 
Repository 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
237Np - Continuous Release 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.20-3. Cumulative Breakthrough of the 99Tc and 237Np Normalized Release Rates RF at the 
Water Table (Continuous Release of Decaying Source, Mean present-day infiltration, No 
Fault Releases) 

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(a) 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
Relative release rate (current/initial at the repository) 
100 101 102 103 104 105 106 
Time (years) 
Repository 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
235Pu - Continuous Release 
(b) 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
Relative release rate (current/initial at the repository) 100 101 102 103 104 105 106 
Time (years) 
Repository 
WATER TABLE 
No release in vicinity of faults 
Release directly into faults 
235U - Continuous Release 
Output-DTN: LB0307MR0060R1.007, data submitted with this Model Report 
Figure 6.20-4. Cumulative Breakthrough of the 239Pu and 235U Normalized Release Rates RF at the 
Water Table (Continuous Release of Decaying Source, Mean present-day infiltration, No 
Fault Releases) 

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This pattern indicates that (a) avoiding radionuclide releases directly into and in the vicinity of 
fractures does retard transport to shallow planes of reference such as the bottom of the TSw, but, 
(b) given a sufficient deep UZ, lateral transport through an interconnected (both vertically and 
horizontally) fracture network compensates for the lack of direct releases into the faults. Thus, 
the interconnected fracture system leads to radionuclide transport to (and emergence at) the 
water table through fault fractures into which no direct releases at the repository ever occurred. 
The same pattern is evident in the XR distribution of all other radionuclides and release scenarios 
investigated here (see Output-DTN: LB0307MR0060R1.006). 
6.20.3 Interpreting the Model Report Results 
While the results presented in this Model Report provide some elucidation of the issue of tracer 
(solute and colloid) transport in the UZ, caution should be exercised in their interpretation. This 
is because of the conceptual approach and assumptions of this study, and some knowledge gaps 
(especially in the area of colloid behavior). 
It is important to keep in mind that this study uses relative quantities (with respect to the tracer 
concentration in the water released from the repository), and consequently, all the concentration 
predictions are relative in nature and presuppose the ability (by no means guaranteed) of the 
radioactive solutes and colloids to reach the underlying fractures. Thus, predictions of large 
relative concentrations may mean little unless and until the tracer release becomes possible, 
significant, and known. Moreover, the presented analysis assumes that conditions for the 
creation and stability of solute and colloidal species exist, and that the effects of the near-field 
chemical, physical, mineralogical, and thermal conditions on their creation and stability over 
time can be ignored. While these assumptions may provide a worst-case scenario, they may be 
unrealistically conservative. 
Note that the 3-D site-scale simulations discussed here do not describe a realistic (expected-case) 
scenario: radioactive tracer release is modeled as occurring continuously, uniformly (even into 
faults), over the whole area of the repository. This presupposes the near-simultaneous rupture of 
all the waste-containing vessels, the ability of water dripping into the repository to focus 
exclusively on the ruptured vessels and to flow through them, the spatially and temporally 
constant contaminant release from each waste package, and the lack of any immobilization 
process (e.g., precipitation, colloid flocculation, etc.) before they enter the fractures. The 
geologic model used in the analysis involves continuous fracture-to-fracture flow in certain 
portions of the UZ, greatly facilitating transport from the repository to the groundwater. While 
these assumptions provide the upper limit of a worst-case scenario, this is an implausible (if not 
a virtually impossible) situation. In that respect, the results discussed here should be viewed as 
an attempt to identify and evaluate the mechanisms, processes, and geological features that 
control UZ transport using the largest possible input signal (i.e., the worst-case scenario), rather 
than as an effort to quantitatively predict the effects of a realistic radionuclide release regime. 
Finally, there are significant uncertainties in colloid modeling. The currently available kinetics 
models were developed from theoretical principles (Herzig et al. 1970 [117519]; Yao et al. 1971 
[101169]) and were tested under saturated conditions, in uniform sandy laboratory experiments 
(van de Weerd and Leijnse 1997 [109249]), and small-scale field tests (Harvey and Garabedian 
1991 [109256]) that involved microspheres or bacteria. It is not known if these models are 

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applicable to the unsaturated complex fracture-matrix system and the expected colloidal waste 
forms in the UZ of Yucca Mountain. The limitations of the equations predicting .+ have not been 
tested under the UZ conditions, and the subject of .- has barely been raised. 

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INTENTIONALLY LEFT BLANK 

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7. VALIDATION 
Section 7 is composed of seven subsections. In Section 7.1 we discuss the main approach and 
validation criteria for the UZ Radionuclide Transport Model (RTM). In Section 7.2 we validate 
the RTM by means of 3-D and 2-D simulations, respectively. The validation of the matrix 
diffusion model is discussed in Section 7.4, while the sorption model is discussed in Section 7.5. 
The colloid model is discussed in Section 7.6. Finally, the Active Fracture Model (AFM) with 
matrix diffusion is addressed in Section 7.7. 
7.1 VALIDATION OF THE RADIONUCLIDE TRANSPORT MODEL (RTM) 
7.1.1 Stipulated Validation Requirements, Methods, and Criteria 
In this section we discuss the validation requirements for the RTM and the corresponding 
criteria. The validation approaches and criteria are based on the Technical Work Plan (TWP) 
stipulations (BSC 2002 [160819], Section I-2-1-1), which indicate the following: 
Quantitative, qualitative, and review criteria will be used for the model validation. One or more 
of following quantitative criteria will be used: 
 Method 1Corroboration with Experimental Data: 
The Busted Butte Unsaturated Zone Transport Test (UZTT) will be simulated, and the 
predicted and experimental results (normalized concentration vs. time) will be compared. 
The validation criteria is: the time at which UZ RTM predicts a value of normalized 
concentration between 0.03 and 0.97 will be less than twice as long, (or any amount shorter 
than), the time indicated by a smoothed breakthrough curve fit through the data. 
The following section (Section 7.1.2) explains that Method 1 is not applicable to the 
analysis of Busted Butte test data. However, for purposes of post-development model 
validation for RTM field measurements of porewater chloride concentrations from the ESF 
and of gas-phase 14C ages from boreholes were used. The latter model validation activities 
are described in detail in BSC (2003 [163045], Section 7), and summarized in Section 
7.3.6. 
 Method 3Corroboration with Data from Literature: 
Comparison with the results of laboratory studies that have been described in peerreviewed 
journals and to which the model can be applied. This validation step will be 
considered successful if the difference between the model and the laboratory data (value of 
normalized concentration at a given location and time) does not exceed 50%. 
 Method 2Corroboration with Alternative Mathematical Models: 
Comparison to analytical solutions (when available). This step is necessary, but not 
sufficient. This validation step will be considered successful if the difference between the 

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model and the analytical solutions does not exceed 1% (value of concentration at a given 
location and time). 
 Method 5 Independent Technical Review 
 Publication in a Refereed Professional Journal (for corroboration) 
7.1.2 Validation Approach and Criteria 
The UZ RTM was validated using the numerical codes (T2R3D and EOS9nT, see Sections 7.2 
and 7.3). The validation process is based on a combination of (a) comparisons to known 
analytical solutions and models (Method 2), (b) scientific acceptance, as demonstrated by 
publications in refereed journals, (c) model acceptance by other organizations involved in 
radionuclide transport studies (Method 5). 
Comparisons and model performance evaluation in the study of the Busted Butte field tests (or 
other field data) of tracer transport are also presented in Section 7.3 as a calibration and 
validation exercise conducted during model development to enhance confidence in the RTM. In 
addition, field measurements of porewater chloride concentrations from the ESF and of gasphase 
14C ages from boreholes were used in post-development model validation of the RTM. 
The latter model validation activities are described in detail in BSC (2003 [163045], Section 7), 
and summarized in Section 7.3.6. 
For the RTM validation through predictions of the numerical (TOUGH2 V1.11 MEOS9nTV1.0 
(LBNL 1999 [113943]) and T2R3D V1.4 (LBNL 1999 [146654])) codes, three conditions must 
be met: 
(1) The relevant physical processes must be accounted for and accurately represented by 
the mathematics. 
(2) The mathematical equations must be accurately solved by the numerical methods. 
(3) The physical properties of the rocks must be correct. 
For the validation of the RTM using the numerical code, their simulation results are compared to 
relevant analytical solutions (Method 2). The validation criterion we used in this case is one or 
more of the following 
(a) Mass fractions agree within 5% when CR = C/C0 = 10-4, or 
(b) The location of the tracer fronts agree within 5% when CR = C/C0 = 10-4, or 
(c) The tracer mass balances agree within 5%. 
The results presented in Table 7.2-6 show that this criterion was met in all instances. Note that 
the criterion here is somewhat different from the one discussed in BSC (2002 [160819], Section 
I-2-1-1) and listed in Section 7.1.1 of this Model Report because the latter (a) is inadequate in 
that it captures only one of the three possible aspects for quantitative agreement, and (b) can be 

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unrealistic near the tail end of the CR curve (where CR values are very low, and both analytical 
and numerical predictions may be unreliable because of roundoff error). 
For validation through scientific acceptance, the criterion we used is publication (or acceptance 
for publication) in peer-reviewed journals in the fields of hydrology and contaminant transport. 
Similarly, the criterion through acceptance by other organizations is involvement of the 
organization in radionuclide transport studies, and reporting of the results of these studies in 
topical reports or peer-reviewed journals. 
For additional validation of the RTM using numerical codes through comparison of their 
predictions to field measurements, the criterion we used is 
(1) Overall agreement within 50% of each other, and, 
(2) If this is not possible, capturing the correct trend, accompanied by a documented 
analysis and discussion of the reasons for the observed deviations. 
Note that inability of the model to match/predict field observations is not necessarily a sign of 
inability to validate the model if (a) the quality of the measurements is suspect, (b) the test 
design may be responsible for uncertainties in the measurements, (c) there is insufficient 
information to fully describe the field test, or (d) the problem is demonstrated to involve very 
steep gradients (involving very significant parameter changes over a short distance or time) that 
lead to measurements prone to uncertainties and inaccuracies. 

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7.2 RTM VALIDATION THROUGH COMPARISON TO ANALYTICAL SOLUTIONS 
AND SCIENTIFIC ACCEPTANCE 
The two numerical codes used for the transport studies in this Model Report are TOUGH2 V1.11 
Module EOS9nT V1.0 (LBNL 1999 [113943]) and T2R3D V1.4 (LBNL 1999 [146654]). The 
software code TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 1999 [113943]) simulates flow 
(saturated and/or unsaturated) and the decoupled transport of multiple radioactive solutes and/or 
colloids (parents and daughters) in complex subsurface systems involving porous and/or 
fractured media. The transport equations account for radioactive decay, advection, 
molecular/colloidal diffusion, hydrodynamic dispersion, kinetic or equilibrium physical and 
chemical sorption (linear, Langmuir, Freundlich, or combined), first-order linear chemical 
reaction, colloid filtration, and colloid-assisted solute transport. EOS9nT can employ 
conventional time stepping or two Laplace transform formulations. 
The code T2R3D V1.4 (LBNL 1999 [146654]) simulates flow (saturated and/or unsaturated) and 
the coupled transport of a single radioactive solute tracer in complex subsurface systems 
involving porous and/or fractured media. The transport equations account for radioactive decay, 
advection, molecular diffusion, hydrodynamic dispersion, and linear equilibrium sorption. 
These two codes have been shown to produce identical results in simulations of transport 
involving (a) conventional time stepping and (b) nonsorbing tracers or tracers whose sorption 
follows an equilibrium linear sorption model. A comparison of the performance of the two 
codes is shown in Figure 7.2-1, which depicts predictions of transport of a conservative 
(nondecaying, nonsorbing) tracer along a vertical plane (slice) of Yucca Mountain. The data 
corresponding to this simulation can be found in DTN: LB0308AMRU0185.001 [165172]. 
Figure 7.2-1 (Section 7.2, this Model Report) shows that the EOS9nT and T2R3D results 
practically coincide. Further evidence of the identity of the EOS9nT and T2R3D predictions is 
provided in BSC (2001 [161340], Figure 6.4.5) and in DTNs: LB03093RADTRNS.001 
[166225], LB03093RADTRNS.002 [166071]. 
7.2.1 Validation Through Comparison to Analytical Solutions 
In this validation phase, several problems (relevant to conditions and possible transport scenarios 
at Yucca Mountain) with known analytical solutions were studied. The specifics of these 
problems and the code performance are discussed in detail below. 
7.2.1.1 Test 1: Transport of a Nonsorbing, Nondecaying Tracer 
This problem involved transport of a nonsorbing, nondecaying tracer through a porous medium. 
A family of analytical solutions to this problem were developed by Bear (1979 [105038]). The 
properties and parameters for this problem are listed in Table 7.2-1, and the comparison of the 
analytical to the numerical solutions is listed in Table 7.2-6. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
10-1 100 101 102 103 104 105 106 
Time (years) 
Dual k system 
EOS9nT 
T2R3D 
YM 1-D Column @SD9 
DTN: LB03093RADTRNS.001 [166225] AND LB03093RADTRNS.002 [166071] 
Figure 7.2-1. Comparison between the Numerical Predictions of Breakthrough from TOUGH2 V1.11 
Module EOS9nT V1.0 (LBNL 1999 [113943]) and from T2R3D V1.4 (LBNL 1999 
[146654]). 
Both T2R3D V1.4 (LBNL 1999 [146654]) and TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 
1999 [113943]) were used in this test. Figure 7.2-2 shows a comparison between the analytical 
solution and the numerical model predictions, and includes solutions from three different time 
treatments (designated by T, H, S to indicate regular time stepping, De Hoog Laplace space 
solution and Stehfest Laplace space solution, respectively). Note that the results for regular time 
stepping (i.e., the T-solutions) reflect both the EOS9nT and T2R3D estimates, which are not 
shown separately because they are practically indistinguishable from each other, and from the 
Laplace space formulation solutions. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
60 50 40 30 20 10 0 
Distance (m) 
t = 400 days 
R = 1 
D = 0.1 m2 day-1 
V = 0.1 m day-1 
t = 50 days 
.x = 0.25 m 
H,S,T solutions 
Analytical 
DTN: LB0308MR0060R1.009 [Output] 
NOTE: Note that the results from three different time treatments (designated by T, H, S to indicate regular time 
stepping, De Hoog Laplace space solution, and Stehfest Laplace space solution, respectively) are 
indistinguishable. 
Figure 7.2-2. Comparison between the Analytical Solution and the Numerical Predictions in Test 1 
7.2.1.2 Test 2: Transport of Sorbing Radioactive Tracers 
The transport of three sorbing radioactive tracers is studied in this test. The analytical solutions 
to this problem were developed by Bear (1979 [105038]). Properties and parameters for this 
problem are listed in Table 7.2-2, and the comparison of the analytical to the numerical solutions 
is listed in Table 7.2-6. The input and output files for this test are in DTN: 
LB0308MR0060R1.008. 
Both T2R3D V1.4 (LBNL 1999 [146654]) and TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 
1999 [113943]) were used in this test. Figure 7.2-3 shows a comparison between the analytical 
solution and the numerical solutions, and includes solutions from three different time treatments 

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MDL-NBS-HS-000008 REV 01 213 November 2003 
(i.e., the T, H, S solutions). As in Test 1, the results for regular time stepping reflect both the 
EOS9nT and T2R3D estimates. They are not shown separately because they are practically 
indistinguishable from each other, and from the Laplace space formulation solutions. 
7.2.1.3 Test 3: Transport of the 234U -> 230Th -> 226Ra Chain 
This problem involved transport of the 3-member radioactive chain 234U -> 230Th -> 226Ra 
through a porous medium. All the members of this chain exist in species that sorb onto the 
porous medium. The analytical solution to this problem was developed by Pigford et al. (1980 
[123113]). The properties and parameters for this problem are listed in Table 7.2-3, and the 
comparison of the analytical to the numerical solutions is listed in Table 7.2-6. The input and 
output files for this test are in DTN: LB0308MR0060R1.008 [Output]. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
60 50 40 30 20 10 0 
Distance (m) 
T1/2 = 69.32 days 
R = 1 
.x = 0.25 m 
t = 200 days 
D = 0.05 m2 day-1 
V = 0.2 m day-1 
T1/2 = 138.63 days 
R = 2 
T1/2 = 1039.72 days 
R = 1.5 
Analytical 
Numerical 
DTN: LB0308MR0060R1.009 [Output] 
Figure 7.2-3. Comparison between the Numerical Predictions (TOUGH2 V1.11 Module EOS9nT V1.0 
(LBNL 1999 [113943]) and T2R3D V1.4 (LBNL 1999 [146654])) and the Analytical 
Solutions (Bear 1979 [105038]) in Test 2 

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10-6 
10-5 
10-4 
10-3 
10-2 
10-1 
100 
1 10 100 1000 
Distance (m) 
T solutions 
H solutions 
S solutions 
Analytical 
U-234 
Th-230 
Ra-226 
DTN: LB0308MR0060R1.009 [Output] 
NOTE: While the results from regular timestepping and the De Hoog Laplace space solution (designated by T and 
H, respectively) are in excellent agreement with the analytical solutions, the results from the Stehfest 
Laplace space solution for the daughters become increasingly inaccurate. 
Figure 7.2-4. Comparison between the Analytical Solution and the TOUGH2 V1.11 Module EOS9nT 
V1.0 (LBNL 1999 [113943]) Predictions in Test 3 
Because it involves transport of parent and daughter species, T2R3D cannot be used for this 
study. The results in Figure 7.2-4 were obtained with EOS9nT, and show a practical coincidence 
of the T- and H-solutions with the analytical solution. When the Stehfest algorithm is 
implemented (S-solution), accurate estimates of the parent species are obtained, but significant 
deviations occur in the transport prediction of daughter species. Thus, the Stehfest formulation 
should not be used for transport studies of radioactive chains. 

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Table 7.2-1. Parameters in Test 1 
Parameter Value 
V (m/day) 0.1 
D (m2/day) - Equation 20 0.1 
Kd (m3/kg) 0 
Water saturation Sw 1 
t 1 
NOTE: DTN: LB0308MR0060R1.008 [Output] 
Table 7.2-2. Parameters in Test 2 
Parameter Value 
V (m/day) 0.2 
D (m2/day) - 
Equation 20 
0.05 
Water saturation Sw 1 
Tortuosity factor t 1 
. (kg/m3) 2600 
Kd (m3/kg) 0, 2.13675x10-5, 4. 2735x10-5 
T1/2 (days) 69.32, 1039.72,138.63 
NOTE: DTN: LB0308MR0060R1.008 [Output] 
Table 7.2-3. Parameters in Test 3 
Parameter Value 
V (m/day) 0.273785 
D (m2/day) - Equation 20 2.73785 
Water saturation Sw 1 
Tortuosity factor t 1 
. (kg/m3) 2600 
Kd (m3/kg) 0, 2.13675x10-5, 4. 2735x10-5 
T1/2 (days) 69.32, 1039.72,138.63 
Kd of 234U (m3/kg) 1.64819 
Kd of 230Th (m3/kg) 8.24159 
Kd of 226Ra (m3/kg) 0.0822528 
T1/2 of 234U (years)a 2.45x105 
T1/2 of 230Th (years)a 7.54x104 
T1/2 of 226Ra (years)a 1.60x103 
NOTE: a From Pigford et al. (1980 [123113]) 
NOTE: DTN: LB0308MR0060R1.008 [Output] 

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7.2.1.4 Test 4: 3H Transport in a Fracture-Matrix System 
This problem describes the transport of a radioactive substance in a system of parallel fractures. 
Advection, dispersion, and diffusion occur in the fractures, while the species diffuses through the 
fracture walls into the matrix. The analytical solution to this problem was developed by Sudicky 
and Frind (1982 [105043]). Properties and parameters for this problem are as in Sudicky and 
Frind (1982 [105043]), and are listed in Table 7.2-4. The comparison of the analytical to the 
numerical solutions is listed in Table 7.2-6. The input and output files for this test are in DTN: 
LB0308MR0060R1.008 [Output]. 
Both T2R3D V1.4 (LBNL 1999 [146654]) and TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 
1999 [113943]) were used in this test. Figure 7.2-5 shows a comparison between the analytical 
solution and the numerical solutions, and includes solutions from three different time treatments 
(i.e., the T, H, S solutions). As in Tests 1 and 2, the results for regular time stepping reflect both 
the EOS9nT and T2R3D estimates. The numerical results are not reported separately because, at 
a minimum, they coincide in the first three decimal digits. 
Table 7.2-4. Parameters in Test 4 
Parameter a Value 
S 1 
. (kg/m3) 2600 
D0 (m2/day) 1.6x10-9 
Fracture aperture (m) 10-4 
Fracture V (m/day) 0.1 
Fracture S 1 
Fracture f 1 
Fracture t 1 
aL (m) 0.1 
Matrix V (m/day) 0 
Matrix block width (m) 0.5 
Matrix S 1 
Matrix f 1 
Matrix t 1 
Kd (m3/kg) 0 (in fractures and matrix) 
T1/2 (years) 12.35 
NOTE: a From Sudicky and Frind (1982 [105043]) 
DTN: LB0308MR0060R1.008 

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10-5 
10-4 
10-3 
10-2 
10-1 
100 
25 20 15 10 5 0 
Distance z (m) 
Analytical 
Numerical 
3H Transport in Fractures 
DTN: LB0308MR0060R1.009 [Output] 
NOTE: The numerical results from the two codes and the three different time treatments are indistinguishable, and 
are indicated by the single curve. 
Figure 7.2-5. Comparison between the analytical solution of Sudicky and Frind (1982 [105043]) and the 
Numerical (TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 1999 [113943]) and T2R3D 
V1.4 (LBNL 1999 [146654])) Predictions in Test 4 
7.2.1.5 Test 5: Colloid and Colloid-Assisted Radionuclide Transport 
This transport of a colloid and a solute is described in this problem. The colloid filtration 
(attachment) is controlled by a kinetic process. The analytical solution to the problem of 
transport of colloids undergoing kinetic filtration is presented by de Marsily (1986 [100439], pp. 
273-274). The solute is radioactive and is irreversibly sorbed onto the colloid; thus, it cannot 
enter the liquid phase and is transported only by the mobile colloids. All the radionuclides 
(produced in a single batch at the same time) that enter the system (through the boundaries or 
through sources) are sorbed onto colloids. This being the case, the radionuclide decays 
uniformly, and its concentration is the same on all colloids. The radionuclide concentration on 
each colloid is controlled by radioactive decay, and by choosing an observation time equal to 
T1/2, its relative concentration is 0.5. 

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Properties and parameters for this problem are listed in Table 7.2-5, and the comparison of the 
analytical to the numerical solutions is listed in Table 7.2-6. The input and output files are in 
Output-DTN: LB0308MR0060R1.008. Because it involves transport of a kinetically filtering 
colloid, T2R3D cannot be used for this study. The numerical results in Figure 7.2-6 were 
obtained with EOS9nT and show a practical coincidence with the analytical solution, while the 
radionuclide relative concentration on the colloids is confirmed to be a uniform 0.5. This is 
validation by Method 2. 
Table 7.2-5. Parameters in Test 5 
Parameter Value 
S 1 
. (kg/m3) 2600 
D0 (m2/day) From Eq. 23 (Section 6.2) 
.c (kg/m3) 1000 
U (m/day) 2 
S 1 
f 0.3 
t 1 
aL (m) 0.15 
e (1/m) 30 
DTN: LB0308MR0060R1.008 
Table 7.2-6. Model-validation  Comparison of Numerical to Analytical Solutions in Tests 1 to 5 
Test # 
% Difference 
Pass/Fail 
Criterion 
1 0.48 (max of T,S,H solutions) Pass 
2 0.93 (max of T,S,H solutions, 3 cases) Pass 
3 234U: 0.93 (T solution), 0.09 (H-solution), 0.97 (H-solution) 
230Th: 0.87 (T solution), 0.16 (H-solution) 
226Ra: 0.98 (T solution), 0.21 (H-solution) 
Pass 
4 0.83 (max of T,S,H solutions) Pass 
5 0.33 (max of T,S,H solutions) Pass 
DTN: LB0308MR0060R1.009 

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0.001
2
3
4
5
6
7 8 9 
0.01
2
3
4
5
6
7 8 9 
0.1
2
3
4
5
6
7 8 9 
1
0.001 
2 3 4 5 6 7 8
0.01 
2 3 4 5 6 7 8
0.1 
2 3 4 5 6 7 8 
1 
Distance (m) 
Analytical 
EOS9nT 
t = 7200 s 
Colloid transport 
DTN: LB0308MR0060R1.009 [Output] 
Figure 7.2-6. Comparison between the Numerical (TOUGH2 V1.11 Module EOS9nT V1.0 (LBNL 1999 
[113943])) and the Analytical (de Marsily 1986 [100439]) Solution of Colloid Transport in 
Test 5. 

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7.2.2 Validation through Scientific Acceptance 
Using T2R3D, Wu and Pruess (2000 [153972]) studied the site-scale 3-D transport of radioactive 
solutes in the journal Advances in Water Resources. A scientific study by Moridis et al. (2003 
[161902]) of site-scale 3-D transport of radioactive colloids in the UZ of Yucca Mountain using 
EOS9nT was recently published in the Journal of Contaminant Hydrology. Both studies are 
based on essentially the same RTM as the one discussed here, but it involved a 3-D grid from the 
previous revision of the relevant Model Reports (BSC 2001 [161340]; BSC 2001 [158726]). 
Additionally, EOS9nT is currently in use by Gesellschaft fr Anlagen und Reaktorsicherheit 
(GRS) mbH, a research and engineering organization owned by the Federal Government of 
Germany, the State of Bavaria, the state of North Rhine-Westphalia, the Technical Inspection 
Organization (TV) and the Germanischer Lloyd. GRS has a substantial involvement in 
radioactivity issues, focusing on studies of the effects of potential radioactivity releases. The 
work of GRS using the RTM embodied in EOS9nT is documented in two GRS reports (Javeri 
2001 [161966]; 2002 [161967]). This is validation by Method 3. 

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7.3 RTM VALIDATION THROUGH CORROBORATION WITH THE BUSTED BUTTE 
FIELD TESTS, CHLORIDE DATA FROM THE ESF, AND THE 14C DATA 
The Busted Butte studies analyzed in the Model Report are presented in Section 7.3.1 through 
7.3.5 as a calibration and validation exercise conducted during model development to enhance 
confidence in the RTM. Section 7.3.6 summarizes the post-development validation of the RTM 
using field measurements of pore water chloride concentrations and gas-phase 14C ages. 
7.3.1 The Busted Butte Tests 
The Busted Butte Unsaturated Zone Transport Test (UZTT) was a long-term experiment 
conducted in Busted Butte near Yucca Mountain (BSC 2001 [160828]) to investigate flow and 
transport issues in the UZ site-process models for Yucca Mountain, including: 
1) The effect of heterogeneities on flow and transport under unsaturated conditions in the CHn 
hydrogeologic unit near the TSw-CHn interface, particularly fracture-matrix interactions and 
permeability contrast boundaries; 
2) The migration behavior of colloids in the CHn layers; 
3) The validation of laboratory sorption results; 
4) Scaling effects (from laboratory to field to site) on 3-D site-scale flow and transport 
simulations. 
The site was selected because of the presence of a readily accessible interface of the TSw and 
CHv units, and the similarity of these layers to those beneath the potential repository horizon. 
The study of the TSw/CHv interface is important because of the significant role that the vitric 
layers of the CHv unit play in radionuclide retardation (see Section 6.10, this Model Report). 
The test proceeded in two phases that differ in design, purpose, and experimental scales, among 
other factors. A detailed description of the tests can be found in BSC (2001 [160828], Section 
6.8). 
The Busted Butte studies analyzed in this Model Report are presented as a calibration and 
validation exercise conducted during model development to enhance confidence in the RTM. 
This analysis and modeling includes portions of the data sets obtained during the main phases of 
the test, namely Phases 1A, 1B, and 2C. The reasons for the choice of tracers and of the data set 
segments used in this analysis are discussed in detail in the following sections. 
7.3.2 Calibration vs. Validation 
It is important to articulate the approach employed in the RTM calibration and validation using 
the Busted Butte test data in this Model Report, and emphasize the difference between validation 
and calibration. It would be extremely desirable and convenient to be able to describe the flow 
and transport properties of particular hydrogeologic units (and especially ones that extend over 
large areas of Yucca mountain) using a set of uniform, homogeneous and isotropic values. 
Unfortunately, this is not possible because of (a) heterogeneity and anisotropy in hydraulic and 
transport parameters are unavoidable even in small-scale systems (let alone the mountain scale 
domain under consideration in the study of the UZ), and (b) scale effects (an issue entirely 
separate from heterogeneity), which further compound the problem. 

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The expected variability in hydraulic and transport parameters makes problematic (if not unwise) 
the use of single parameters derived from large-scale inversion processes (such as the process 
involved in the determination of the hydraulic properties of the various hydrogeologic units in 
this Model Report) to describe the small-scale experiments at the Busted Butte site. Thus, it was 
necessary to calibrate the RTM model at each one of the three sites involved in the three phases 
of the field test (i.e., phases 1A, 1B and 2C). The process of calibration was intended to 
determine the main hydraulic parameters of the medium under consideration. The calibrated 
hydraulic parameters were then used in an attempt to validate and enhance confidence in the 
transport model using transport parameters available from other independent sources. 
To accomplish the task, two separate data sets of tracer concentrations were used from each of 
the three test phases, of which one was used for calibration and the other for validation. This is a 
valid approach because the transport behavior of the two tracers used for calibration and 
validation was completely independent, i.e., there is no sorption-related correlation. If a 
particular tracer was known (or expected) to have a sorbing affinity for the tested rock, the 
corresponding data set was used for the calibration effort, which included an estimation of the 
tracers transport parameters (i.e., the Kd distribution coefficient and tortuosity) in addition to the 
hydraulic parameters. The non-sorbing tracer (Br in all three of the test phases) was used for 
validation because (a) it is more demanding as a conservative species, and (b) it has a wellknown 
(and independently determined) Kd (= 0) and a molecular diffusion coefficient D0 
(=2.080x10-9 m2/s, see Table 7.3-1). 
In Test Phases 1A and 1B, the tracer used for calibration was either non-sorbing (fluorescein in 
Test Phase 1A) or very mildly sorbing (2,6-DFBA in Test Phase 1B). Thus, the retardation of 
the calibration tracer was none or very small, and the time frame used for calibration and 
validation was the same. In the case of the Li tracer in Test Phase 2C, its relatively strong 
sorption resulted inevitably in a significant retardation, leading to later appearance (than the Br) 
at the collection point. When Li began registering significant concentrations, the Br 
concentration was invariant at the collection point because it had already reached a maximum 
(equal to the injection concentration). In this case, the Li data set corresponding to the later 
times was used for calibration, while the earlier Br data set was used for validation. This further 
strengthens validation because of the further degree of separation between the Li and Br data 
sets. 
7.3.3 Phase 1A Test 
The purpose of this modeling study was to calibrate and validate the model through the 
reconciliation of field measurements and predictions of the concentration and water saturation, 
following the injection of nonreactive tracers into the ch1v, and the subsequent flow and 
transport in the ch1v and ch2v layers. Of the four tracers injected during the field experiment, 
only the transport of two (the nonsorbing Br and fluorescein) is analyzed here because of the 
poor quality and unreliability of the data from the other two tracers. In this analysis, 
(a) the fluorescein data are used for calibration, while 
(b) the Br data are used for validation. 
Additional discussion on the calibration and validation approach can be found in Section 7.3.2 of 
this Model Report. 

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7.3.3.1 Procedure and Layout 
A schematic of the borehole layout in the Phase 1A test can be found in BSC (2001 [161340], 
Attachment VI), while more detailed information is provided in BSC (2001 [160828], Section 
6.8). Parameters describing the site conditions and test operation (and the corresponding 
sources) are listed in Table 7.3-1. Only injection into borehole 3 (located in the ch1v layer of the 
CHn unit) was considered. Borehole 3 is located in the ch1v layer and is about 20 cm above the 
ch1v-ch2v interface. The injection tests into boreholes 1 (located in the ch1v layer, but is further 
removed from the interface), 2 and 4 (located in the ch2v layer of the CHn unit) were not 
analyzed because of the poor quality of the data. An extensive discussion of the test can be found 
in BSC (2001 [160828], Section 6.8). 
Mineback of the Phase1A test block provided the field data for this analysis. During mineback, 
as successive vertical slices were being removed, digital photographs under visible and 
ultraviolet light were taken to record the distribution of moisture and fluorescein. This 
distribution in the vicinity of Borehole 3 is used for the calibration of the simulation results 
discussed in the present section because it is the largest fluorescein plume (in addition to being 
the most uniform). Additionally, rock samples were collected by augering, and the exposed 
plane was accurately surveyed. These samples were analyzed for tracer concentration and are 
the basis for the validation of the Br transport. 
7.3.3.2 Conceptual and Numerical Model 
For this 3-D numerical study, the underlying geologic model considered a homogeneous and 
anisotropic unfractured rock matrix with the properties of the ch1v and ch2v layers. Because of 
the injection configuration (as described in BSC 2001 [160828], Section 6.8), only half the 
domain (i.e., the portion of the domain to the right of the injection point; see Figure 7.3-1) was 
simulated using a grid consisting of 22,463 elements. The TOUGH2 V1.11MEOS9nTV1.0 
(LBNL 1999 [113943]) was used for the simulation. 
The determination of the hydraulic parameters was a significant component of the calibration 
effort. Initial estimates for these parameters were provided by two different sources: the UZ99 
calibrated flow parameter set (DTN: LB997141233129.001 [104055]) and a data set based on 
hydraulic property measurements from field-collected samples (DTNs: GS990308312242.007 
[107185], GS990708312242.008 [109822]). Initial (uncalibrated) data, as well as all relevant 
flow and transport parameters, are listed in Table 7.3-1 (which also includes the DTN of the field 
data and measurements used in the validation) and Table 7.3-2. The DTN of the input and output 
files of this simulation is DTN: LB0308MR0060R1.008 [Output]. 
7.3.3.3 Calibration Using the Fluorescein Data 
Figures 7.3-1 and 7.3-2 show the fluorescein distribution (as recorded digitally in the field using 
a UV light) and the corresponding numerically predicted distribution (calibrated) at the y = 0.90 
m mineback face. The final (calibrated) transport properties that resulted in the distribution of 
Figure 7.3-2 are listed in Table 7.3-3. Note that the scale included in Figure 7.3-1 is incorrect, 
the correct one being the faint feature in the middle of the photograph below the plume. This 

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was confirmed by reviewing the original scientific notebooks describing the mineback operation 
(Bussod 1999 [146978], p. 130). 
A comparison of the two figures indicates good agreement between predictions and observations. 
The absence of stringers and other features indicative of fracture presence, coupled with the 
ellipsoidal size of the plume, indicating that the assumption of an unfractured (porous) medium 
is valid (visual evidence of local heterogeneity in Figure 7.3-1 notwithstanding, the plume is 
quite uniform at the scale of observation). 
Although the size of the numerically predicted horizontal axis is somewhat larger than the 
observed one, the compressed shape of the fluorescein plume is accurately captured, the 
compression of the lower half of the plume due to its vicinity with the less permeable ch2v is 
accurately rendered, and the size of the vertical axis of the ellipsoid fluorescein plume is in very 
good agreement with that measured in Figure 7.3-1. However, it is not possible to further refine 
the calibration because critical information on the minimum concentration at which the tracer 
will fluoresce is unavailable, thus depriving the study of more reliable information on the extent 
of the outer boundaries of the plume. Additionally, the lack of scaling information in any of the 
other digital photographs from the mineback did not allow the use of a larger data set to more 
accurately determine of the appropriate parameters (and the site heterogeneity distribution) and 
effectively constrain the solution. 
A quantitative measure of the model calibration stemming from the comparison of field 
observations to model predictions is provided in Table 7.3-9. 

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Table 7.3-1. Operational, Transport, and Field Parameters in the Analysis of the Busted Butte Phase 1 
Field Test 
Parameter Value Source 
Phase 1A: 
Injection rate (mL/hr) 
7 LA0008WS831372.001 [156582] 
Phase 1A: 
Injection duration (days) 
286 LA0008WS831372.001 [156582] 
Phase 1B: 
Injection rate (mL/hr) 
8 LA0008WS831372.001 [156582] 
Phase 1B: 
Injection duration (days) 
191 LA0008WS831372.001 [156582] 
aL (m) - Ch1v and Ch2v 0.1 Reasonable estimate 
aT (m) - Ch1v and Ch2v 0 Reasonable estimate 
D0 of Br (m2/s) 2.08x10-9 Lide (1992 [166224]), p. 5-111 
D0 of Fluorescein (m2/s) 8x10-10 Initial estimate 
D0 of 2,6-DFBA (m2/s) 7.6x10-10 Benson and Bowman (1994 
[122788]) 
Kd of Br (m3/kg) 0 LA0203WS831372.002 [161526] 
Kd of Fluorescein (m3/kg) 0 LA0203WS831372.002 [161526] 
Kd of 2,6-DFBA (m3/kg) 0 LA0203WS831372.002 [161526] 
Phase 1A: 
Br concentration measurements 
LA9910WS831372.008 [147156] 
Phase 1A: 
Fluorescein distribution (plume 
images) in the rock 
LA0302WS831372.001 [162765] 
Phase 1B: 
Br concentration measurements 
LA0201WS831372.008 [162766] 
Phase 1A: 
2,6-DFBA concentration 
measurements 
LA0201WS831372.008 [162766] 
Table 7.3-2. Hydrological Parameters in the Analysis of the Busted Butte Phase 1A Field Test 
Parametera Ch1va Ch2va Ch1vb Ch2vb 
f 0.273 0.345 0320 0.360 
kx = ky= kz (m2) 9.9x10-13 9.27x10-14 3.14x10-13 1.82x10-14 
t 0.7 0.7 0.7 0.7 
a (1/m) c 0.140 0.503 0.471 0.741 
n c 1.538 1.427 1.332 1.200 
Sr 0.03 0.07 0.07 0.07 
Initial Sw 0.3 0.3 0.3 0.3 
NOTE: aUZ99 calibrated properties, DTN: LB997141233129.001 [104055] 
bbased on USGS measured properties, DTNs: 
GS990308312242.007 [107185], GS990708312242.008 [109822], 
as reported in DTN: LB991220140160.010 [164858] 
cvan Genuchten (1980 [100610]) model parameter 

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7.3.3.4 Validation of the Bromide Transport Model 
Figure 7.3-3 shows the numerically predicted distribution at the y = 0.90 m mineback face (at 
validation), as well as the field measurements of the Br relative concentration (obtained from 
samples acquired during the mineback operations). The properties that resulted in the 
distribution of Figure 7.3-3 are those listed in Table 7.3-3, and were provided by the calibration 
of the fluorescein data (Section 7.3.3.3). For the prediction of Br transport, the simulations were 
conducted using the fluorescein-derived calibrated parameters (without any adjustment) and the 
known D0 of Br. 
A comparison of the two concentration curves in Figure 7.3-3 indicates good agreement between 
predictions and observations. The model accurately reproduces the rather uniform 
concentrations along the x-axis that passes by the injection point, as well as the magnitude of the 
observed concentrations. 
Toward the outer extents of the horizontal axis of the plume, there appear to exist discrepancies 
between observations and predictions. Some of the discrepancies are consistent with the rather 
elongated shape of the predicted tracer plume. Part of this may be attributed to the fact that these 
occur in areas of steep gradients (i.e., in areas of condensation of the contour lines, when large 
differences occur within a short distance). An additional issue is uncertainty in the 
measurements, as reflected by a measured relative concentration of 2.77 (with respect to the 
injection concentration) in the center of the plume. While this high concentration is possible (if, 
for example, the sample was inadvertently allowed to dry), it may be indicative of some error in 
the measurements. 
Based on these results, the Br transport model is validated because it was based on calibrated 
parameters from a different data set (that of fluorescein). 
7.3.3.5 Remarks and Observations 
For all calibrations, we adjust the following parameters: f, k, t, Kd (for known sorbing species), 
D0 (only if not available from Lide (1992 [166224])). For validation, the relevant calibrated 
parameters are used unchanged, and only the fixed parameters that uniquely describe individual 
transport behavior (i.e., the known D0 of Br) are different. 
A review of the parameters obtained in the process of calibration in Table 7.3-3 indicates that 
they are within a reasonable range and they are not in obvious conflict with the initial data listed 
in Table 7.3-2. While the possibility of a non-unique solution cannot be summarily dismissed, 
the calibrated solution (fluorescein) and the corresponding validated solution (of Br transport) 
are both mathematically correct and physically meaningful. A quantitative measure of the model 
validation, stemming from the comparison of field observations to model predictions, is provided 
in Table 7.3-9. Although there are some discrepancies, the agreement between observations and 
numerical predictions is sufficiently good to enhance confidence in the RTM. 

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DTN: LA0302WS831372.001 [162765] 
Figure 7.3-1. Fluorescein Plume at the y = 0.9 m Mineback Face at Borehole 3. 
Table 7.3-3. Calibrated Parameters of Flow and Transport from the Analysis of the Busted Butte Phase 
1A Field Test 
Parametera Ch1v Ch2v 
f 0.320 0.360 
kx (m2) 2.14x10-13 8.20x10-13 
ky (m2) 4.14x10-13 2.82x10-13 
kz(m2) 6.28x10-14 3.64x10-14 
t 0.22 0.12 
a (1/m) c 0.471 0.741 
n c 1.332 1.200 
Sr 0.07 0.07 
D0 of Fluorescein (m2/s) 4x10-10 
DTN: LB0308MR0060R1.008 [Output] 
NOTE: aAll other parameters remaining as in Tables 
7.3-1 and 7.3-2. 

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-2.0 
-1.5 
-1.0 
-0.5 
0.0 
Z (m) 
1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 
X (m) 
0.9 
0.9 0.8 
0.8 0.7 0.6 
0.5 
0.4 
0.3 
0.2 
0.1 
TpTpv1 
Tac 
Test 1A 
Fluorescein distribution 
DTN: LB0308MR0060R1.009 
Figure 7.3-2. Numerical Prediction of the Fluorescein Plume Using Calibrated Parameters (Busted 
Butte Test Phase 1A) 

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-2.0 
-1.5 
-1.0 
-0.5 
0.0 
Z (m) 
1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 
X (m) 
0.8 
0.8 0.7 0.6 0.5 0.4 
0.3 0.2 0.1 
TpTpv1 
Tac 
Test 1A 
0.74 
0.49 
0.00 
0.00 
2.77 
0.87 0.75 0.81 
0.79 0.32 0.01 
0.75 
Bromide distribution 
DTN: LB0308MR0060R1.009 [Output] 
Figure 7.3-3. Field Measurements and Numerical Prediction of the Bromide Distribution in Busted Butte 
Test Phase 1A. The Solid Circles Indicate the Location of Measurements (DTN: 
LA9910WS831372.008 [147156]), Which Appear in the Corresponding Boxes. 
7.3.4 Phase 1B Test 
The purpose of this modeling study was to calibrate and validate the model through the 
reconciliation of field measurements and predictions for breakthrough curves of tracers injected 
into Borehole 5 (located in the tsw39 layer, see BSC 2001 [160828], Section 6.8). Of the five 
tracers injected during Phase 1B of the Busted Butte test, only Br (nonsorbing) and 2,6- 
difluorobenzoic acid (2,6-DFBA, assumed to be nonsorbing) were used due to the poor quality 
of other tracer data. Of these, the 2,6-DFBA data were used for calibration, and the Br data set 

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was used for validation. Additional discussion on the calibration and validation approach can be 
found in Section 7.3.2 of this Model Report. 
7.3.4.1 Procedure and Layout 
An extensive discussion of the Phase 1B test can be found in BSC (2001 [160828], Section 6.8). 
Only a short description is presented here. 
In the Phase 1B field test, the tracers were injected into the lower portion of the Topopah Spring 
basal vitrophyre (Tptpv2 in the lithostratigraphic units; tsw39 in the UZ99 layers of the 
hydrogeologic units), which is a relatively low-permeability fractured rock. The design, 
configuration, and important dimensions of the Phase 1B test are shown in BSC (2001 [161340], 
Attachment VI, while more detailed information is provided in BSC (2001 [160828], Section 
6.8), which depicts the injection/collection pair of boreholes 5 and 6. The tracer solution was 
injected at y = 1.30 m from the rock face into boreholes 5. Water samples from boreholes were 
collected and analyzed regularly during the injection period. 
The parameters describing the site conditions and test operation (and the corresponding sources) 
are listed in Table 7.3-1, which also includes the DTN of the data used for this validation effort. 
Although the Phase 1B test involved injection and collection into another set of boreholes 
(boreholes 7 and 8, respectively), that portion of the test is not needed for this discussion. 
The determination of the hydraulic parameters was a significant component of the calibration 
effort. Initial estimates for these parameters (listed in Table 7.3-3) were provided by two 
different sources: the UZ99 calibrated flow parameter set (DTN: LB997141233129.001 
[104055]) and a data set based on hydraulic property measurements from field-collected core 
samples (DTNs: GS990308312242.007 [107185], GS990708312242.008 [109822]). 
7.3.4.2 Conceptual and Numerical Model 
The initial (uncalibrated) input parameters of flow and transport for the simulation of the Phase 
1B test are listed in Tables 7.3-1 and 7.3-4. For this 3-D numerical study, the geologic model 
treated the domain as a homogeneous and anisotropic unfractured rock matrix. Although this 
geologic layer is known to be fractured, the assumption of an unfractured rock matrix as the 
domain model in the simulation appears to be a valid one because the system behavior during the 
injections did not exhibit evidence of fracture flow. The same grid used in the simulation of 
Phase 1A was used here, but with the appropriate domain properties, i.e., those of the Tptpv2 
unit. The DTN of the input and output files of this simulation is DTN: LB0308MR0060R1.008 
[Output]. The TOUGH2 V1.11MEOS9nTV1.0 (LBNL 1999 [113943]) was used for the 
simulation. 
For this calibration and validation process, only the data from the first 100 days of the Phase 1B 
test were used. The reason for this selective truncation of the data set was the existence of 
obvious inconsistencies and errors in the data. More specifically, measured concentrations of 
both Br and 2,6-DFBA exhibited pronounced fluctuations and appeared to drop to zero 
(undetectable) levels after 100 days. This occurred at a time when injection not only proceeded 
uninterrupted, but also continued to do so at the same injection levels for another 90 days. If 

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sampling and measurement errors are not considered a possibility, then the only reasonable 
explanation for such a response would be a sudden and practically infinite dilution (e.g., if very 
large amounts of pure water reached the sample collection point), a scenario not supported by the 
facts. This being the case, the data beyond 100 days were deemed unreliable, and thus they were 
not included in the validation. 
7.3.4.3 Calibration Using the 2,6-DFBA Data 
The calibrated parameters obtained from the 2,6-DFBA transport model in Phase 1B of the 
Busted Butte test are listed in Table 7.3-5. A comparison of the measured and the numerically 
predicted breakthrough curves of 2,6-DFBA (based on the calibrated parameters) in Figure 7.3-4 
shows a very good agreement. Note that the pattern and response of the breakthrough curves 
confirm the visual observation that the system did not exhibit fracture flow behavior during the 
Phase 1B test, thus supporting the validity of the unfractured medium approach made in the 
simulations. 
7.3.4.4 Validation of the Br transport model 
The calibrated parameters (based on the 2,6-DFBA transport analysis, Table 7.3-5) were used for 
the prediction of the Br transport in Phase 1B of the Busted Butte test. The known D0 of Br and 
its Kd = 0 value were used in the validation process. A comparison of the measured and the 
numerically predicted breakthrough curves of Br in Figure 7.3-5 shows a very good agreement. 
A quantitative measure of the model validation stemming from the comparison of field 
observations to model predictions is provided in Table 7.3-9. The level of agreement between 
observations and numerical predictions enhances confidence in the RTM. 
7.3.4.5 Remarks and Observations 
A review of the calibrated parameters in Table 7.3-5 indicates that they are within a reasonable 
range, and that they are not in obvious conflict with the initial data listed in Tables 7.3-1 and 7.3- 
3. The only possible deviation between initial estimates and the final parameters is the need for 
a nonzero (although small) Kd for 2,6-DFBA. This appears to be in conflict with the 
conventional (though not fully supported) assumption that 2,6-DFBA is nonsorbing. 
Careful consideration of the chemistry of the system indicates that it is entirely possible for an 
organic substance to sorb onto a rock. In this case, the very low permeability of the rock allows 
a long contact time, making such a sorption scenario plausible, especially given the fact that 
organic substances are generally considered to be slow sorbers (Cameron and Klute 1977 
[117172]). Additionally, the long residence time in the rock may allow a slow reaction of 2,6- 
DFBA (a weak acid) with minerals in the rock, a process that would result in a response 
consistent with an apparent sorption. 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
100 80 60 40 20 0 
Time (days) 
2,6-Difluorobenzoic Acid Test 1B 
Measurements 
Model predictions 
Sensitivity study 
Figure 7.3-4. Observed and Numerically Predicted (Calibrated) Breakthrough Curves of 2,6-DFBA in 
the Busted Butte Phase 1B Test. Measurements from DTN: LA0201WS831372.008 
[162766]). Prediction from DTN: LB0308MR0060R1.009 [Output] 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
100 80 60 40 20 0 
Time (days) 
Test 1B Bromide 
Measurements 
Model predictions 
Sensitivity study 
Figure 7.3-5. Observed and Numerically Predicted (at Validation) Breakthrough Curves of Br in the 
Busted Butte Phase 1B Test. Measurements from DTN: LA0201WS831372.008 
[162766]), Prediction from DTN: LB0308MR0060R1.009 

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To investigate the system sensitivity to spatial resolution, Figures 7.3-4 and 7.3-5 include 
breakthrough curves at points 0.05 m below the collection point. It is obvious that 
concentrations in the vicinity of the collection points exhibit very steep gradients. This indicates 
that minor inaccuracies in the recording of the location of the collection point can register as a 
strong deviation. In light of this spatial sensitivity, the agreement between predictions and 
observations is deemed very good, and the observed small deviations can be easily explained. 
Table 7.3-4. Initial Parameters in the Analysis of the Busted Butte Phase 1B Field Test 
Parametera UZ99a USGSb 
f 0.173 0.360 
kx = ky= kz (m2) 5.46x10-19 1.82x10-14 
t 0.7 0.7 
a (1/m) c 0.225 0.225 
n c 1.612 1.612 
Sr 0.29 0.29 
Initial Sw 0.3 0.3 
D0 of 2,6-DFBA (m2/s) 7.6x10-10 
NOTE: aBased on UZ99 calibrated properties, DTN: 
LB997141233129.001 [104055], as reported in DTN 
LB991220140160.010 [164858] 
bBased on USGS measured properties, DTNs: 
GS990308312242.007 [107185], GS990708312242.008 
[109822], as reported in DTN LB991220140160.010 [164858] 
cvan Genuchten (1980 [100610]) model parameter 
Table 7.3-5 Calibrated Flow and Transport Parameters from the Analysis of the Busted Butte Phase 1B 
Field Test 
Parametera Value 
f 0.270 
kx (m2) 3.06x10-17 
ky (m2) 4.06x10-17 
kz(m2) 1.53x10-17 
t 0.07 
Kd of 2,6-DFBA (m3/kg) 1.47x10-5 
DTN: LB0308MR0060R1.008 [Output] 
NOTE: a All other parameters remaining as in Table 
7.3-1 and 7.3-3. 

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7.3.5 Phase 2C Test 
Phase 2 differs from Phase 1 in that the injection systems were designed to activate large 
volumes of the rock. A detailed description of this test phase can be found in BSC (2001 
[160828], Section 6.8, Figure 38). The injection points in this phase were distributed in 
horizontal parallel planes at locations designed to test the properties of the lower Topopah 
Spring Tuff (Tptpv2) and the underlying Calico Hills (Tptpv1) unit. 
7.3.5.1 Procedure and Layout 
In this study, we limit our analysis to Phase 2C, which appears to have yielded the best quality 
data. In Phase 2C, injection occurred in three horizontal boreholes (#18, #20 and #21), each 
instrumented with nine injectors located at 0.61 m intervals along the borehole. All three 
boreholes were located in the Tptpv2 unit. Because of the relatively short injection spacing and 
the long injection period (695 days), the injection can be considered uniform along the three 
boreholes. While this assumption introduces an inaccuracy, it is rather small, is limited to the 
very early stages of injection (when flow is spherical rather than the quasi-cylindrical at the later 
stages), and keeps decreasing over time. The implication of this uniformity is that it is possible 
to model the system using a 2-D grid, thus allowing higher spatial resolution. 
After reviewing the tracer concentrations recorded at the various collection boreholes, this study 
concentrated in borehole #16 because it is the closest to the horizontal plane of the three 
injection wells and, thus, has registered the strongest signals (in terms of tracer concentrations). 
Borehole #16 run was located on a horizontal plane (roughly coinciding with the Tptpv2- Tptpv1 
interface) about 0.6 m below that of the injection boreholes and perpendicular to their main axis. 
A rather large number of tracers were injected in the injection boreholes. After reviewing the 
concentration data, the analysis was limited to the transport of two tracers: Br and Li. This 
decision was reached because the data quality of the other tracers was rather poor and often 
devoid of any logical pattern (possibly attributed to the sample collection method that entailed 
removal and reintroduction of the same collection pads in the collection boreholes, replacement 
of pads with new ones, and difficulty in consistently placing the pads at their exact previous 
location following removal for sampling and testing). The nonsorbing Br and the sorbing Li had 
registered rather strong and generally (but not always) consistent signals in borehole #16. In 
addition, having being injected as a solution of LiBr, Li and Br were intertwined and offered an 
additional level of checking through their very different transport properties and the need to 
maintain mass balance. 
The parameters describing the site conditions and test operation of Phase 2C (and the 
corresponding sources) are listed in Table 7.3-6, which also includes the DTN of the data used 
for the exercise. In this analysis, the Li data were used for calibration, and the Br data for 
validation. Additional discussion on the calibration and validation approach can be found in 
Section 7.3.2 of this Model Report. 

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7.3.5.2 Conceptual and Numerical Model 
Early exploratory studies indicated that, if the porous medium (unfractured rock) assumption 
were made, it was very difficult to reproduce the individual responses of Br or Li, and 
impossible to obtain a consistent joint Br and Li behavior. Using just a consistent fracture 
domain (i.e., limiting the study to fracture flow and transport) produced a very fast breakthrough 
for Br and an impossibly fast one for the sorbing Li, because of the inability to account for 
matrix diffusion and the lack of Li sorption. Thus, modeling the domain as a fracture-matrix 
system was the only alternative. A dual-permeability model was employed. The 2-D grid had a 
rather fine resolution ( .x = .y = 0.05 m). The initial (uncalibrated) input parameters of flow and 
transport for the simulation of the Phase 2C test are listed in Table 7.3-7. The DTN of the input 
and output files of this simulation is DTN: LB0308MR0060R1.008 [Output]. The TOUGH2 
V1.11MEOS9nTV1.0 (LBNL 1999 [113943]) was used for the simulation. 
The initial steady-state flow field was obtained by setting an infiltration rate corresponding to 5 
mm/yr at the top of the domain and running the flow simulation to steady state. Note that these 
runs were needed at every phase of the validation because the changes in the hydraulic 
parameters in the process of validation affected the flow field. 
For the Li calibration process, only the data for t = 337 days and t = 440 days were used. 
Because of the sorbing behavior of Li, the data for t<337 days were marked by very low 
concentrations, significant variability, and the corresponding uncertainty. Concentration data for 
t>440 days showed rather inconsistent behavior (attributed to issues discussed in Section 
7.3.5.3). 
For the Br validation process, only the data for t = 125 days and t = 183 days were used. The 
data for t<125 days were marked by very low concentrations and significant variability 
(inevitable because of the relatively large component of error, inaccuracy, and heterogeneity in 
the early data). Concentration data for t>183 days indicated a rather uniform distribution along 
the well bore (as the concentration peak had already been reached), differed only in the extent of 
the zone that had reached the maximum concentration (not a very reliable source of information 
for reasons explained later), and were not very useful. 
A quantitative measure of the model calibration and validation stemming from the comparison of 
field observations to model predictions is provided in Table 7.3-9. 

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Table 7.3-6. Operational, Transport, and Field Parameters in the Analysis of the Busted Butte Phase 2 
Field Test 
Parameter Value Source 
Injection rate (mL/hr) 120 LA0008WS831372.001 [156582] 
Injection duration (days) 695 LA0008WS831372.001 [156582] 
aL (m) - Fractures 0.1 Reasonable estimate 
aL (m) - Matrix 0.0 Reasonable estimate 
aT (m) - Everywhere 0 Reasonable estimate 
D0 of Br (m2/s) 2.08x10-9 Lide (1992 [166224], p. 5-111) 
D0 of Li (m2/s) 1.03x10-9 Lide (1992 [166224], p. 5-111) 
Concentration 
measurements 
LA0112WS831372.001 [157100] 
LA0112WS831372.002 [157115] 
LA0112WS831372.003 [157106] 
LA0211WS831372.001 [162763] 
Table 7.3-7. Hydrological and Transport Parameters in the Analysis of the Busted Butte Phase 2 
Field Test 
Parameter F-TpTpv1b M-TpTpv1b F-TpTpv2 M-TpTpv2 
fa 1 0.354 1 0.457 
kx = ky= kz (m2) a 2.2x10-13 6.649x10-13 8.1x10-13 1.488x10-13 
ta 1 0.7 1 0.7 
a (1/m) a,c 21.582 0.856 14.715 0.477 
n a,c 2.725 1.316 2.725 1.414 
Sr
a 0.01 0.06 0.01 0.13 
Kd of Br (m3/kg)d - 0 - 0 
Kd of Br (m)e 0 - 0 - 
Kd of Li (m3/kg)f - 3.5x10-5 - 8.8x10-5 
Kd of Li (m)g 0 - 0 - 
NOTE: aDTNs: LB03013DSSCP3I.001 [162379], LB0210THRMLPRP.001 [160799] 
bF: fracture properties, M: matrix properties 
cvan Genuchten (1980 [100610]) model parameter 
dDTN: LA0203WS831372.002 [161526] 
eKd denotes surface distribution coefficient - reasonable estimate 
fDTN: LA9912WS831372.001 [156586], LA0203WS831372.002 [161526] 
gInitial estimate 

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7.3.5.3 Calibration Using the Li Data 
The parameters from the calibration of the Li transport model in Phase 2C of the Busted Butte 
test are listed in Table 7.3-8. Figure 7.3-6 shows the measured and the numerically predicted Li 
distributions along the collection borehole. Note that the Kd values in Table 7.3-8 are consistent 
with previously reported data (DTN: LA9912WS831372.001 [156586], LA0203WS831372.002 
[161526]). Note that the data set used for the Li-based calibration corresponds to the later part of 
the field test because of the sorption-induced retardation (see discussion in Section 7.3.2 of this 
Model Report). 
The Li distribution in Figure 7.3-6 shows a rather good match between predictions and 
measurements. The peaks, their rough locations, and the distributions are matched. For t>440 
days, Li concentrations start decreasing, and then they resume increasing. This is consistent with 
concentrations in the pad being diluted by Li-poor water until the main Li front arrives at the 
collection pad (at which time concentrations begin increasing again). Note that the analysis is 
complicated by lack of knowledge about the sorption behavior of Li in the pad (see discussion in 
Section 7.3.5.4). 
7.3.5.4 Validation of the Br Transport Model 
Figure 7.3-7 shows the measured and the numerically predicted Br distribution along the 
collection borehole. This distribution was obtained by using the calibrated properties (Table 7.3- 
8) from the analysis of the Li data, and the known D0 and Kd (=0 m3/kg) of Br. Compared to Li, 
the Br distribution indicates a less diffusive behavior, attributed to the lack of sorption. Although 
different magnitudes are involved, the concentration distributions patterns (both observed and 
predicted) are consistent between the two tracers. Note that the data set used for the Br-based 
validation corresponds to the earlier part of the field test because of the reasons discussed in 
Section 7.3.2 of this Model Report. 
A review of the Br predicted distribution reveals that the numerical solution accurately predicts 
the location and magnitude of the concentration peaks, but exhibits a narrower, more focused 
pattern and registers deviations away from these peaks. More specifically, the measured 
concentration of Br is more uniform along the collection borehole axis than what the numerical 
simulation predicts. 
In other words, the measurements indicate a system that is more diffusive than the advective one 
indicated by the simulation. However, adjustment of permeabilities and diffusive fluxes through 
further calibration was not the correct approach (even disregarding the obvious danger that, to 
increase the diffusive component, one would have to reach rather unreasonable relations between 
the permeabilities of the fractures and the matrix). 

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1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
CR 
9 8 7 6 5 4 3 2 
X (m) 
Model 
t = 337 d 
t = 440 d 
Measurements 
t = 337 d 
t = 440 d 
Well #16 
Lithium 
Observed Data from DTN: LA0201WS831372.007 [164721], Prediction from DTN: LB0308MR0060R1.009 [Output]. 
Figure 7.3-6. Observed and Numerically Predicted (Calibrated) Breakthrough Curves of Li in the 
Busted Butte Phase 2C Test. 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
CR 
9 8 7 6 5 4 3 2 
X (m) 
Measurements 
t = 125 d 
t = 183 d 
Model 
t = 125 d 
t = 183 d 
Well #16 
Bromide 
Observed Data from DTN: LA0112WS831372.003 [157106], Prediction from DTN: LB0308MR0060R1.009 [Output]. 
Figure 7.3-7. Observed and Numerically Predicted Breakthrough Curves of Br in the Busted Butte 
Phase 2C Test (at Validation). 

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The discrepancy problem had to be recast under the light of what the measurements meant. Use 
of the collection pad introduced a system with drastically different properties than the host rock, 
characterized by high permeability, porosity, irreducible water saturation, and capillary pressure. 
Tracer carrying fracture flow first reaching the collection pad arrives at distinct points (the points 
where the fractures intercept the borehole), and is quickly redistributed on the initially dry pad, 
thus leading to an apparently more uniform distribution than the one in the overlying rock. This 
is more evident on the left lobe of the distribution, corresponding to borehole #18. Being 
relatively far from the other boreholes, it receives no cross contribution of fracture flow from 
injection into the other boreholes, and the distribution on the pad shows a more diffusive pattern 
than what the simulation predicts. In other words, the collection pads skew the data in a 
direction that indicates a more diffusive system. This being the case, it is expected that the most 
accurate data will be at early times and roughly under the injection boreholes (not necessarily 
directly underneath, as the fracture density, distribution, and orientation are anything but known 
a priori). Thus, it is expected that matching the peaks is a sufficient indication of validation. 
Heterogeneity of fracture property and distribution is also a substantial issue at this small scale, 
and it is possible to create the appearance of enhanced diffusion if the fracture frequency is 
locally higher (e.g., on the left lobe of the curve). 
If the effect of the pad is as described above, it is expected that it will lead to decreasing peak 
concentrations and more uniform spatial distribution as time advances. This is because after the 
arrival of tracers in the faster flowing fractures, the contributions of slower-flowing fractures 
(with more interactions with the matrix) and of the matrix itself release water of lower 
concentration that is mixed and redistributed on the pad, and leads to temporarily lower 
concentrations resulting from dilution. Of course, once the solute front crosses the matrix, 
concentrations are expected to rise again. A review of the Br measurement data indicates this 
exact pattern. 
An attempt was made to simulate the effect of the pad. However, these simulations indicated 
that its behavior is sensitive to the initial conditions (whether it is an old one or a new 
replacement), its location (whether the old pad is placed at the exact same location from where it 
was removed), its wettability properties vis--vis the host rock, etc. This being the case, and 
given the uncertainties and the lack of an adequate description of the fracture-matrix system at 
the gridblock scale of this problem (0.05 m)after all, the mathematical description of the 
matrix-fracture system is averaging even at this scale, and can be quite different from the actual 
system no further attempt was made to refine the solution. The solution currently reflects 
concentration predictions in the overlying rock and not in the pad. 
A quantitative measure of the model validation stemming from the comparison of field 
observations to model predictions is provided in Table 7.3-9. The level of agreement between 
observations and numerical predictions enhances confidence in the RTM. 

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Table 7.3-8. Calibrated Flow and Transport Parameters from the Analysis of the Busted Butte Phase 2C 
Field Test 
Parametera F-TpTpv1 M-TpTpv1 F-TpTpv2 M-TpTpv2 
f 1 0.354 1 0.060 
kx (m2) 3x10-13 1.3x10-13 1.96x10-12 1.2x10-13 
kz(m2) 10-13 8x10-14 7.1x10-13 8x10-14 
t 2 0.9 2 0.654 
Kd of Li (m3/kg) - 5.5x10-4 - 9.3x10-4 
Kd of Li (m)b 2.5x10-6 - 4.3x10-6 - 
DTN: LB0308MR0060R1.009 [Output] 
NOTE: aAll other parameters remaining as in Tables 7.3-6 and 7.3-7 
bKd denotes surface distribution coefficient in fractures 
Table 7.3-9. Comparison of Numerical Solutions to Field Tests 
Field 
Test # 
Difference* 
1A Bromide <50% (concentration, distribution) 
1B Bromide: <50% (breakthrough) 
2C Bromide: <50% (breakthrough) 
NOTE: * The 50% agreement refers to either 
concentration comparison or arrival time 
comparison. 
7.3.5.5 Remarks and Observations 
A review of the calibration parameters in Table 7.3-8 indicates that they are within a reasonable 
range, and that they are not in obvious conflict with the initial data listed in Tables 7.3-6 and 
7.3-7. Note that the distribution parameter Kd of Li is within the experimentally determined 
range (DTN: LA9912WS831372.001 [156586], LA0203WS831372.002 [161526]). A surface 
sorption distribution coefficient had to be considered for the fractureswhich is consistent with 
the rather strong sorbing behavior of Li. Given the degree of match between predictions and 
observations and the uncertainties involved in this study, the level of agreement between 
observations and numerical predictions is deemed acceptable and supports the claim of model 
validation. 
7.3.6 Post-Development Validation Using Chloride and 14C Field Data 
Post-development validation of the RTM on a larger scale is provided by the analysis of field 
measurements of 14C ages in the gas samples, and of pore water Cl concentrations in the ESF. 
These studies and the corresponding validation-supported analysis were conducted using the 
T2R3D numerical model, and are discussed in detail in BSC (2003 [163045]), Sections 7.5 and 
7.8, respectively. 

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7.4 VALIDATION OF THE MATRIX DIFFUSION MODEL BY CORROBORATION 
WITH DATA FROM ALCOVE 8/NICHE 3 FAULT TEST 
Matrix diffusion can play an important role in radionuclide exchange between the fractures and 
the rock matrix (Moridis et al. 2003 [161902], p. 255). This process transfers a radionuclide into 
the matrix (where water flow is slow), thus removing them from fast fracture flow. The diffusive 
flux is a function of the concentration gradient at the corresponding fracture-matrix interface, 
fracture interface area, and molecular diffusion coefficient (Section 6.2 of this report). The 
matrix diffusion model is an important component of the UZ Transport Model. 
This section validates the Matrix Diffusion Model by corroboration with data from the Alcove 
8/Niche 3 fault test. The criteria for validation is that the predicted breakthrough curves collected 
at Niche 3 qualitatively agree with data and predicted tracer transport time is not longer than 
observed (BSC 2002 [160819], Section I-2-1-2, Attachment I, p. 26). As demonstrated in the 
subsections below discussing modeling results, the criteria are met. This modeling activity is 
also documented in a Scientific Notebook by Wang (2003 [164021], SN-LBNL-SCI-215-V1, pp. 
107-109). 
The Alcove 8/Niche 3 fault test is described in Section 7.4.1. Data from this test include both 
hydrologic data and tracer data. The numerical model of the test is described in Section 7.4.2. 
Rock properties in the model were calibrated to the hydrologic data in two calibration runs as 
described in Section 7.4.3.1. Tracer transport with matrix diffusion was then simulated as 
described in Section 7.4.3.2, where it is demonstrated that the validation criteria are met. 
7.4.1 Field Observations 
This section highlights experimental observations used in this model analyses. The test was 
carried out in the upper lithophysal and middle nonlithophysal subunits in the Yucca Mountain 
UZ. These geological subunits correspond to model layers tsw33 and tsw34, respectively, in the 
site-scale model for the Yucca Mountain UZ. The tsw33 has some lithophysal cavities that may 
intersect fractures. Liquid water with and without tracers was released at the floor of an alcove 
along the fault (about 5 m long (DTN: GS020508312242.001 [162129])) within tsw33. Seepage 
from the fault into a niche and tracer concentrations of seeping liquid as a function of time were 
monitored. The niche is located within tsw34, about 20 m below the floor of the alcove; the 
interface between tsw33 and tsw34 is about 15 m below the floor of the alcove (DTN: 
LB0301N3SURDAT.001 [162130]). 
A water-pressure head of 2 cm was applied at an infiltration plot along the fault at the alcove. 
The plot consists of four trenches that have different infiltration rates as a result of subsurface 
heterogeneity along the fault. Figure 7.4-1 shows the total infiltration rate as a function of time 
(DTNs: GS020508312242.001 [162129] and GS020908312242.002 [162141]; Wang 2003 
[164021], SN-LBNL-SCI-215-V1, p. 107). For simplicity, our model considers the uniformly 
distributed infiltration rate along the infiltration plot to be consistent with the use of the uniform 
property distribution in the site-scale model of the Yucca Mountain UZ. One consideration in 
our modeling study is to evaluate approaches used in the site-scale model. Considerable 
temporal variability of infiltration rate occurred during the test, as a result of infill materials 
within the fault just below the infiltration plot (Figure 7.4-1). In other words, the effective 

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permeability of the fault just below the plot changed with time. It is also expected that most 
portions of the fault and the surrounding fractures away from the plot would still be unsaturated, 
although capillary pressure at the plot was positive during the test. Based on these observations, 
total infiltration rate (instead of a pressure head of 2 cm) was used as the boundary condition in 
our model. 
Seepage from the fault into the niche was measured during the test, with a number of trays used 
to cover the areas where seepage might occur. Seepage was found to be highly spatially variable. 
The total seepage rate as a function of time is given in Figure 7.4-2 (DTN: 
LB0303A8N3LIQR.001 [162570]). Several boreholes were installed around the niche. Water 
arrival times at these boreholes were monitored through electrical resistivity probes. Figure 7.4-3 
shows average water travel velocities determined from the arrival times from two boreholes just 
above the ceiling of the niche (DTN: LB0303A8N3LIQR.001 [162570]). The fault is about 2 m 
from the borehole collars in Figure 7.4-3 (DTN: LB0303A8N3LIQR.001 [162570]). Note that 
relatively uniform water-travel-velocity distribution within and near the fault was observed from 
these two boreholes. 
After 209 days, two tracers with different molecular diffusion coefficients (Br and PFBA) were 
introduced into infiltrating water at the infiltration plot. Tracer concentrations in three of the 
trays (at the niche) capturing seeping water from the fault were measured (DTN: 
LB0303A8N3LIQR.001 [162570]). For technical reasons, seepage rates corresponding to these 
three trays were not measured during the period of tracer concentration measurement. In this 
study, a flux-averaged breakthrough curve (concentration as a function of time) from these trays 
was used to represent average breakthrough curve for all trays at the niche where seepage was 
captured (Wang 2003 [164021], SN-LBNL-SCI-215-V1, pp. 108109). A constant flux value for 
each of the three trays was used for calculating the flux-averaged breakthrough curve shown in 
Figure 7.4-4. The constant flux values for the three trays were determined as the averaged value 
over 56 days before tracers were introduced. This flux-averaged breakthrough curve is 
comparable to simulation results. 
7.4.2 Numerical Model 
A numerical model, generated with a software routine Smesh.f V1.0 (LBNL 2002 [162142]), 
was developed for the fault test site to compare the simulation results with the relevant field 
observations. While comparison results will be presented below in Section 7.4.3, here we will 
focus on schemes used for developing the numerical model. 
A three-dimensional numerical grid was constructed for simulating the fault test (Figure 7.4-5). 
The fault was represented as a vertical fracture, and surrounding fractured rock is approximated 
as a dual-continuum system consisting of overlapped, interacting fracture and matrix continua. 
Global water flow and solute transport are allowed to occur in both continua. Figure 7.4-5 shows 
a cross section of the grid within the fault. The thickness of the grid in the direction 
perpendicular to fault walls is 3 m along each side of the fault. The fracture frequency used for 
generating the dual-continuum grid is 1.03 m-1 for tsw33 (determined from the fracture map at 
the alcove floor) and 1.72 m-1 for tsw34 (determined from the fracture map at the ceiling of the 
niche) (DTN: GS030108314224.001 [162131]; Wang 2003 [164021], SN-LBNL-SCI-215-V1, 
pp. 111-112). As shown in Figure 7.4-5, within a cross section of the grid along the fault, the 

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grid spacing is 10 cm just above the ceiling of the niche, enabling the seepage process to be 
accurately simulated. Grid spacings in the direction perpendicular to the fault are 0.024 m, 0.168 
m, 0.456 m, 0.756 m and 1.44 m, respectively. The smallest spacing is adjacent to the fault, so 
that water imbibition and tracer diffusion into the fractured rock from the fault can be accurately 
captured. Cross sections parallel to the fault walls have identical grid meshes (Figure 7.4-5) for 
different distances from the fault. The niche is represented by an opening at the bottom of the 
grid (Figure 7.4-5), with the geometry of the opening determined from the survey data of the 
niche near the fault. Note that this is only an approximation of the geometry of the test site; a 
three-dimensional geometry of the niche with an underground tunnel connected to the niche is 
not incorporated into the model. However, since our main concern is flow and transport 
processes within the fault, this geometry representation should be adequate. 
Temporally variable inflow rates are imposed on the top boundary, corresponding to the 
infiltration plot at the alcove floor. The side boundary corresponds to zero-flow (in the direction 
perpendicular to the simulation domain) conditions. The niche wall boundary is modeled by a 
zero capillary-pressure condition, representing capillary barrier effects (Birkholzer et al. 1999 
[105170]). The bottom boundary was assigned a constant matrix saturation of 0.85, which is 
consistent with field observations under ambient conditions (Flint 1998 [100033]). Also based 
on field observations of Flint (1998 [100033]), matrix saturations are initially assigned to be 0.72 
for tsw33 and 0.85 for tsw34. Other initial conditions for the rock mass within the model 
domain are absence of solutes and low water saturation (1.05E-2) in both the fractures and the 
fault. Rock properties used in model simulations are presented in the next section. 
Model calibration was performed using an inverse modeling code iTOUGH2 V4.0 (LBNL 1999 
[139918]). The model calibration is defined herein as the adjustment of rock hydraulic 
parameters to make simulation results match the corresponding data. The goodness of match is 
measured using the standard least-squares approach, which minimizes the sum of the squared 
residuals weighted by the inverse of variance of the data. T2R3D V1.4 (LBNL 1999 [146654]), 
was used for modeling tracer transport. 
7.4.3 Model Simulations and Discussions 
The numerical model was first calibrated against the seepage and water-travel-velocity data to 
obtain the calibrated rock properties and the corresponding water flow field. Then, tracer 
transport simulations with different transport parameters were carried out to evaluate the effects 
of matrix diffusion and other related processes on solute transport in the fault. 
7.4.3.1 Calibration of Rock Properties using Seepage-Rate Data and the Average 
Water-Travel-Velocity Data 
Both fracture and matrix properties were assumed to be homogeneous within each geological 
subunit (tsw33 and tsw34). Fault properties were assumed to be homogeneous within both units. 
This is based mainly on the following three considerations: 
(1) Consideration of the heterogeneity within each subunit would introduce a large 
number of rock properties that need to be determined by more data than was available 
from the test site; 

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(2) As previously indicated, these treatments have been used by the site-scale model of 
the Yucca Mountain UZ. It is of interest to examine how well this simple 
representation of subsurface heterogeneity can be used to model the fault test. 
(3) A recent study by Zhou et al. (2003 [162133]) indicates that flow and transport in the 
Yucca Mountain UZ are mainly determined by large-scale heterogeneity, 
characterized by property differences between different geological units, rather than 
by property variability within a geological unit. 
Rock hydraulic properties needed as inputs into the model include fracture and matrix 
permeabilities, fracture and matrix porosities, fault aperture and permeabilities, van Genuchten 
(1980 [100610]) parameters (for matrix, fractures, and the fault), and the parameter of the active 
fracture model, ., for fractures (DTNs: LB997141233129.001 [104055], LB980901233124.101 
[136593], LB990861233129.001 [110226] and LB990501233129.001 [106787]; Wang 2003 
[164021], SN-LBNL-SCI-215-V1, pp. 114115). Because fracture van Genuchten parameters 
for tsw33 and tsw34 are similar, a simple average of these parameters was used as the 
corresponding parameters for the fault. The averaged k/f (where k is fracture permeability and f 
is the corresponding fracture porosity) was calculated as fault permeability. Note that in this 
section 7.4.3, fracture porosity refers to the volume fraction of fractures in the entire rock 
volume, rather than the void space within the fracture. Also, note that because there is no matrix 
in the fault in our model (or f =1), the weighted k/f (rather than weighted k) is employed for 
estimating fault permeability. The aperture of the fault was estimated as the average of fracture 
apertures of the two subunits. Note that the active fracture model was developed for fracture 
networks rather than for a single fracture. Consequently, the active fracture model does not apply 
to the fault here. In fact, most of the parameter values mentioned above and given in Table 7.4-1 
are not site specific for the fault test site. These values were used as initial guesses for model 
calibration against the seepage rate and water-travel-velocity data observed from the fault test. 
To reduce the number of variables in model calibration (or inverse modeling), parameters 
expected to significantly affect simulated water travel time and seepage rate were varied in the 
calibration, while other parameters were kept unchanged. The varied parameters were fracture 
and fault permeabilities, fracture porosity, fault aperture, and fracture and fault van Genuchten 
values. 
Infiltration-seepage processes in the fault and the surrounding fractured rock were determined by 
several mechanisms. Liquid water applied at the alcove floor (Figure 7.4-5) flowed first into the 
fault and then into fractured networks connected to the fault. Matrix imbibition occurred at 
interfaces between fractures and the matrix and between the fault and the matrix. When water 
arrived at the intersection between the fault and the niche, it could not immediately seep into the 
niche until the capillary pressure became zero because of capillary barrier effects (Philip et al. 
1989 [105743]; Birkholzer et al. 1999 [105170]). The capillary barrier can divert flow away 
from the opening, resulting in only a portion of the water arriving at the niche ceiling actually 
seeping into the niche. Water travel time was determined by fracture porosity, fault aperture, 
and the matrix imbibition process. 
Figure 7.4-6 shows a comparison between seepage-rate data and the simulation result from a 
model calibration (Run #1) without considering the water-travel-velocity data. In this calibration 

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run, fracture porosity and fault aperture were not varied. A fairly good match was obtained 
(Figure 7.4-6); however, water travel velocity is significantly overestimated (Figure 7.4-7). 
Water travel velocities were calculated from water arrival times at locations about 1 m above the 
middle of the opening in Figure 7.4-5. The travel time was defined as the time when fault or 
fracture saturation was increased from the initial value of 1.05E-2 to 1.06E-2. This comparison 
implies that seepage rate as a function of time may be mainly controlled by rock properties near 
seepage locations (influence zone of capillary barrier (Liu et al. 2002 [160230])). On the other 
hand, water travel velocities are determined by rock properties from the infiltration plot to the 
locations where water travel velocities are monitored. Table 7.4-2 gives the calibrated properties 
obtained from Run #1. 
The overestimation of the water travel velocities may result from the following: (1) some 
cavities in tsw33 are connected to fractures and could contribute to increasing the storage in the 
fracture continuum; (2) in reality, the fault is a zone rather than a single fracture. The effective 
aperture from this zone may be much larger than the assumed aperture value for the fault (Table 
7.4-1). Neither of these factors was considered in Run #1 (first calibration). Taking these factors 
into consideration, the new calibration (Run #2) allowed both fault aperture and fracture porosity 
in tsw33 to be varied. The resultant values are 3 cm for fault aperture and 0.066 for fracture 
porosity of tsw33 (Table 7.4-3). While the actual width of the fault zone is unknown, the 
estimated equivalent fault aperture (3 cm) is considered to be acceptable. The estimated fracture 
porosity is consistent with those estimated from water release tests performed in the same 
geological unit (BSC 2001 [158463], Section 6.11.3.1, p. 246). 
Figure 7.4-7 shows a comparison among calculated water travel velocities from two calibration 
runs and the velocity data observed from the fault test. The simulated water travel velocities 
from Run #2 are much closer to the observed data than those from Run #1 (especially near the 
fault). However, the water travel velocities away from the fault are still overestimated. One 
possible explanation is that matrix imbibition from fractures above the niche were 
underestimated because the dual-continuum approach considerably underestimates the pressure 
gradient near a fracture matrix interface during transient flow conditions (Pruess and Narasimhan 
1985 [101707]). While this problem could be resolved with the multiple interacting continua 
model of Pruess and Narasimhan (1985 [101707]), the computational intensity of the inverse 
model problem under consideration would be significantly increased. Note that a model 
calibration involves a great number of forward simulation runs. Considering that (1) the transient 
flow effects would be considerably reduced at later time of the test and that (2) our focus here is 
on flow and transport within and near fault, simulated flow field and calibrated rock properties 
from Run #2 were used for simulating tracer transport at the test site. Figure 7.4-8 also shows a 
comparison between simulated seepage rates as a function of time (Run #2) and field 
observations. The match is reasonable. 
7.4.3.2 Prediction of Tracer Transport with Matrix Diffusion 
Tracer transport within the fault is controlled by several processes, including advection, 
diffusion into the matrix blocks (matrix diffusion), mass exchange between the fault and the 
surrounding fracture networks, and dispersion. Our special attention in this study is given to 
evaluating the relative importance of matrix diffusion. To do so, we used the flow field obtained 
from Run #2 to simulate tracer transport processes and compare simulation results with field 

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observations (Figure 7.4-4). The breakthrough curve is obtained from the output of T2R3D V1.4 
(LBNL 1999 [146654]) using a software routine Bkread.f V1.0 (LBNL 2002 [162143]). 
Two conservative tracers with different molecular diffusion coefficients (2.08 E-9 m2/s for Br 
(Lide 2002 [160832], p. 5-96) and 7.60 E-10 m2/s for PFBA (Benson and Bowman 1996 
[122788])) were used in the fault test. Based on analyses of the relevant diffusion experiment 
results for tuff matrix samples in the Yucca Mountain UZ, Moridis et al. (2003 [161902], Table 
1) reported that the tortuosity factor for the tuff matrix could be approximated by the 
corresponding matrix porosity. As a consequence, the average matrix porosity for tsw33 and 
tsw34 (0.13) was used as the tortuosity factor. The effective diffusion coefficient for the matrix 
diffusion process is the product of the molecular diffusion coefficient and tortuosity factor. 
Figure 7.4-9 compares simulated breakthrough curves at the niche with the observed data. In 
this simulation, the dispersivity is assumed set to zero. (The relative importance of the dispersion 
will be discussed below.) Since the diffusive flux from the fault to the matrix is proportional to 
the product of the tortuosity factor and the fault-matrix interface area, changes in the interface 
area for a given tortuosity factor are equivalent to changes in tortuosity factor for a given 
interface area. For simplicity, the tortuosity factor value was changed in actual simulations, but 
the numerical grid (defining the interface area) was kept unchanged. Note that changes in the 
interface area should not significantly alter the flow field during the period of the tracer test. 
Tracers were introduced into infiltrating water at about 200 days after infiltration started, 
resulting in the matrix near the fault being almost saturated during the tracer test and the matrix 
imbibition being insignificant. As shown in Figure 7.4-9, the simulated breakthrough curve 
exhibits a much larger concentration peak values but only slightly earlier arrival times for the 
tracer peaks. This meets the specified validation criteria. 
7.4.3.3 A Further Discussion of Matrix Diffusion Effects 
Although the Matrix Diffusion Model has been validated sufficiently for the purposes of License 
Application, it is of interest to study its sensitivity to the interface area between fault and matrix. 
The need to increase interface areas between fractures (or faults) and the matrix in matching the 
field observations of tracer transport in fractured rock has been recently reported by several 
researchers. Shapiro (2001 [162132]) reported an interpretation of concentration measurements 
for tritium and dichlorodifluoromethane collected from a glacial drift and fractured crystalline 
rock over 4 km2 in central New Hampshire. He found that the effective diffusion coefficient at 
the kilometer scale is at least three orders of magnitude greater than laboratory estimates of 
diffusion in crystalline rock. Neretnieks (2002 [162140]) presented comparisons between several 
analytical solutions with tracer test results at the sp site and reported a need for a factor 3050 
times larger for the fracture-matrix interface area than expected. He also indicated that nine other 
research groups reached a similar conclusion in their interpretation of the same test data set. Our 
results in this study are consistent with these previous findings. 
Several mechanisms regarding the increase in the interface area have been reported in the 
literature. They include (1) advective mass exchanges from high-permeability fractures to lowpermeability 
fractures (Shapiro 2001 [162132]), (2) diffusion into stagnant water zones 
(Neretnieks 2002 [162140]), and (3) enhanced fracture-matrix interface areas for fractures with 
small-trace lengths that do not contribute to global flow and are not considered in the survey data 

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(and therefore in the numerical grid). In addition to these potential mechanisms, two other 
factors also contribute to the increase in the interface area. First, in the relevant analytical and 
numerical solutions to tracer transport, fracture walls are generally assumed to be flat. However, 
it is now well known that fracture walls are rough and characterized by fractal geometry 
(National Research Council 1996 [139151]). Consequently, the actual interface areas between 
fractures (and faults) and the matrix are larger than what are calculated using flat fracture walls. 
Second, a fault zone may include a great number of crushed matrix blocks that have smaller sizes 
than the fracture spacing in a nonfault zone. These crushed matrix blocks can make a significant 
contribution to the matrix diffusion within the fault, but are not considered in our numerical grid, 
where the fault is simply treated as a vertical fracture. To compensate for the effects of these 
mechanisms mentioned above, the models fault-matrix interface areas obviously need to be 
increased. 
Also shown in Figure 7.4-9 is a simulation with the interface area increased by a factor of 45, 
which is within the range reported by Neretnieks (2002 [162140]). With this adjustment, the 
simulations match the data more closely. Although simulation results with the increased 
interface area reasonably match the observed data (Figure 7.4-9), the concentration difference at 
a given time for the two tracers is generally overestimated by the model. One plausible 
explanation is that the crushed matrix blocks within the fault zone have much smaller sizes than 
the fracture spacing. This, however, is not considered in our model, in which the matrix block 
size is characterized by fracture spacing. The smaller sizes correspond to shorter times needed by 
the equilibrating tracer concentration at the center and outer surface of a matrix block, reducing 
the difference between the effects of matrix diffusion on overall solute transport behavior for 
different molecular-diffusion coefficients. This can be further illustrated by an extreme case: an 
infinitely small block size within the fault and without mass exchange between the fault and 
nonfault fractured rock. In this case, the concentrations of the matrix block within the fault can 
be equilibrated simultaneously with those at the outer surface of the block for two tracers with 
different molecular diffusion coefficients. Consequently, although the existence of this kind of 
matrix block can still significantly retard tracer transport within the fault, identical breakthrough 
curves should be observed at Niche 3 for the two tracers. This issue was not further explored in 
the current modeling study because the matrix block-size distribution within the fault cannot be 
independently estimated or observed. 
Compared with matrix diffusion, the macrodispersion process is not considered to be significant 
within the fault for this particular test. Field measurements indicate that water travel-velocity 
distribution is quite uniform within and near the fault (Figure 7.4-3), whereas macrodispersion 
results from variability in water velocity. This is further confirmed by observed breakthrough 
curves from three flow paths within the fault. They have arrival times similar to peak 
concentrations (DTN: LB0303A8N3L1QR.001 [162570]). These experimental observations are 
consistent with the findings from our model analyses: the observed data were very difficult to 
match when a considerable degree of dispersion was included in the model. For example, Figure 
7.4-10 shows simulated breakthrough curves with a longitudinal dispersivity value of 1 m and a 
transverse dispersivity value of 0.1 m (and with the increased fault-matrix interface area), 
compared to results in Figure 7.4-9 (without considering dispersion). Larger dispersivity values 
generally correspond to earlier arrival times of peak concentrations and to a larger difference 
between these peak concentrations for the two different tracers. 

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The Yucca Mountain site (where the fault test was carried out) is the proposed geological 
disposal site for high-level nuclear waste in the United States. Radionuclide transport from the 
repository horizon to the water table is a key factor affecting the performance of the proposed 
repository. The study results herein have some important implications for the performance 
assessment of the proposed site. 
Matrix diffusion has been identified as a key mechanism for retarding the radionuclide transport 
in both unsaturated and saturated fractured rock (e.g., Bodvarsson et al. 2001 [160133]; 
Neretnieks 2002 [162140]). The enhancement of the fracture (fault)-matrix interface area (or 
effective matrix diffusion coefficient) seems to be common for matching field-scale solute 
transport observations, as suggested by this study and previous studies (Shapiro 2001 [162132]; 
Neretnieks 2002 [162140]). Some physical explanations for this enhancement are available, as 
discussed in Section 7.4.3.2. The current site-scale model for the Yucca Mountain UZ does not 
consider the effects of this enhancement. Consequently, the performance of the proposed 
repository, estimated based on the site-scale model, may be underestimated. 
The other related issue is the effects of cavities (existing in several geological layers at the 
Yucca Mountain site) on water flow and radionuclide transport processes. One may intuitively 
expect the cavities connected to fractures to act as capillary barriers under unsaturated 
conditions, because the cavity openings are much larger than fracture apertures. However, both 
this study and analyses of water-release tests performed in the related geological units at the 
Yucca Mountain site suggest that cavities are accessible by water within fracture networks, and 
therefore are retarding the downward water flow and radionuclide transport processes. This is 
also supported by field observation that mineral coatings exist in many cavities (BSC 2002 
[160247], Section 6.10). The coating is a signature for liquid-water flow paths. Although the 
cavity openings are larger than fracture apertures, the roughness of cavity walls could result in 
film flow (along cavity walls) from fractures to the cavities (Tokunaga and Wan 1997 [139195]). 
The effects of cavities are also not considered in the site-scale model for the Yucca Mountain 
UZ. This omission would result in further underestimating the performance of the proposed 
repository. 

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Table 7.4-1. Uncalibrated Rock Properties 
tsw33 tsw34 Rock property Fault 
Fracture Matrix Fracture Matrix 
Permeability (m2) 4.34E-11 5.5E-13 3.08E-17 0.35E-13 
4.07E-18 
Porosity 1.00 6.6E-3 0.154 1.E-2 0.11 
Fracture frequency 
(1/m) 
1.03 1.5 
Fracture aperture 
(m) 
1.12E-3 1.49E-3 1.14E-3 
Active fracture model 
parameter . 
0.0 0.41 0.41 
van Genuchten a 
(Pa-1) 
1.0E-3 1.46E-3 
2.13E-5 5.16E-4 
3.86E-6 
van Genuchten m 0.608 0.608 
0.298 0.608 
0.291 
DTNs: LB997141233129.001 [104055], LB980901233124.101 [136593], LB990861233129.001 [110226] and 
LB990501233129.001 [106787] (Also see Wang 2003 [164021], SN-LBNL-SCI-215-V1, pp. 114-115) 
Table 7.4-2. Rock Properties Calibrated from Seepage Rate Data (Run #1) 
Rock property Fault tsw33 tsw34 
Fracture 
Permeability (m2) 
6.67E-11 8.93E-13 3.16E-14 
Fracture van 
Genuchten a (Pa-1) 
1.15E-3 1.67E-3 4.59E-4 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
NOTE: All other rock properties are the same as those in Table 
7.4-1. 

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Table 7.4-3. Rock Properties Calibrated from both Seepage Rate and Water Travel Velocity Data 
(Run #2) 
Rock property Fault tsw33 tsw34 
Fracture Permeability (m2) 1.12E-10 1.23E-12 5.01E-13 
Fracture Porosity 0.066 
Fracture aperture (m) 0.03 
Fracture van Genuchten a (Pa-1) 1.24E-3 2.19E-3 1.09E-3 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
NOTE: All other rock properties are the same as those in Table 7.4-1. 

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0 100 200 300 400 
Time (d) 
0 
50 
100 
150 
200 
250 
300 
350 
400 
450 
Infiltration Rate (L/d) 
DTNs: GS020508312242.001 [162129] and GS020908312242.001 [162141] 
Figure 7.4-1. Infiltration Rate as a Function of Time 
0 100 200 300 
Time (day) 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Seepage rate (L/day) 
DTN: LB0303A8N3LIQR.001 [162570] 
Figure 7.4-2. Total Seepage Rate as a Function of Time. Data for 3/6/2001 through 1/28/2002. 

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0 1 2 3 4 5 6 
Distance from Collar (m) 
0 
0.25 
0.5 
0.75
1 
1.25 
1.5 
1.75
2 
Velocity of Wetting Front (m/d) 
DTN: LB0303A8N3LIQR.001 [162570] 
Figure 7.4-3. Water Travel Velocity Data at two boreholes (9 and 10) 
0 50 100 150 
Time (day) 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
Relative Concentration 
Br 
PFBA 
DTN: LB0303A8N3LIQR.001 [162570] (Also see Wang 2003 [164021], SN-LBNL-SCI-215-V1, p.108-109) 
Figure 7.4-4. Observed Flux-Average Breakthrough Curve 

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0 10 20 30 
x (m) 
-20 
-15 
-10 
-5
0 
z (m) 
small plot 
Niche 3 
Alcove 8 
TSw33 
TSw34 
For illustration purposes only. 
Figure 7.4-5. A Cross Section View of 3-D Numerical Grid 
0 100 200 300 
Time (day) 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Seepage rate (L/d) 
data 
simulation 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
Figure 7.4-6. A Comparison between Simulated Seepage Rates as a Function of Time (Run #1) and 
Field Observations 

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0 1 2 3 4 5 6 
Distance from Collar (m) 
0 
0.25 
0.5 
0.75
1 
1.25 
1.5 
1.75
2 
Velocity of Wetting Front (m/d) 
Data 
Run #1 
Run #2 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
Figure 7.4-7. A Comparison among Calculated Water Travel Velocities from Two Calibration Runs and 
the Velocity Data Observed from the Fault Test 
0 100 200 300 
Time (day) 
0 
10 
20 
30 
40 
50 
60 
70 
80 
90 
100 
Seepage rate (L/d) 
data 
simulation 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
Figure 7.4-8. A Comparison between Simulated Seepage Rates as a Function of Time (Run #2) and 
Field Observations 

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0 25 50 75 100 
Time (day) 
0 
0.05 
0.1 
0.15 
0.2 
0.25 
0.3 
0.35 
0.4 
0.45 
0.5 
0.55 
0.6 
0.65 
0.7 
0.75 
Relative Concentration 
data (Br) 
Data (PFBA) 
Original interface area (Br) 
Original interface area (PFBA) 
Increased interface area (Br) 
Increased interface area (PFBA) 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
Figure 7.4-9. Comparisons between Simulated Breakthrough Curves at the Niche for Two Different 
Fault-Matrix Interface Areas and the Observed Data. 
0 25 50 75 100 
Time (day) 
0 
0.05 
0.1 
0.15 
0.2 
0.25 
0.3 
0.35 
0.4 
0.45 
0.5 
0.55 
0.6 
0.65 
0.7 
0.75 
Relative Concentration 
data (Br) 
Data (PFBA) 
Simulation (Br) 
Simulation (PFBA) 
Source: DTN: LB0303A8N3MDLG.001 [162773] 
Figure 7.4-10. Comparisons between Simulated Breakthrough Curves (Considering Dispersion) at the 
Niche for the Increased Fault-Matrix Interface Areas and the Observed Data. 

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7.5 VALIDATION OF THE SORPTION MODEL 
The validation approach and criteria are discussed in the TWP (BSC 2002 [160819], Section I-2- 
1-3), which stipulates that: 
The sorption model is linear equilibrium, defined by Kd values, between sorbed and aqueous species in 
the UZ.  Kd values will be provided by comparison with laboratory data from the TDMS. This 
comparison constitutes validation of the sorption model by Method 1, corroboration with experimental 
data. 
 Kd values will be justified by comparison with laboratory data from the TDMS. This comparison 
constitutes validation of the sorption model by Method 1, corroboration with experimental data. The 
criterion for validation is that Kd values calculated from experimental data be within a factor of 3 of the Kd 
values used in the model. The model will also be corroborated by comparison with published data. 
The acceptance criterion, as stated in the TWP (BSC 2002 [160819]), is inadequate in this case 
because it presupposes estimation of a single Kd from the analysis of the experimental data. A 
far more rigorous approach is used in the Kd analysis of this Model Report (discussed in 
Attachments I and II), which aims to (a) identify the type and develop the parameters that 
describe the statistical distribution of Kd based on data from a number of samples belonging to 
the same general hydrogeologic unit, and (b) provide representative Kd estimates from these 
statistical distributions. 
Validation is provided by (a) confirmation that the analysis of the laboratory data (described in 
Attachments I and II) supports the linear equilibrium sorption model (onto which the Kd concept 
is based) for a given radionuclide and rock, and (b) using Kd values that are within the range 
determined from these laboratory experiments and correspond to the expected values (as 
estimated from the statistical distributions). 
Confirmation of the validity of the linear equilibrium sorption model is provided in Attachments 
I and II. Table 6.5-1 presents the Kd range and the types of the Kd probability distributions of the 
various radionuclides in the UZ rocks. The Kd values used in the model (indicated by boldface 
numbers) are also listed in this table, and are shown to be within the measured range and to 
coincide with the median Kd value from the statistical distributions. Thus, the sorption model is 
validated. 

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7.6 VALIDATION OF THE COLLOID TRANSPORT MODEL 
The validation approach and criteria are discussed in the TWP (BSC 2002 [160819], Section I-2- 
1-4), which indicates that: 
The Colloid Transport Model was judged in the Model Validation Status Report (BSC 2001 [156257], p. 
28) to have been validated satisfactorily for its purposes in CRWMS M&O (2000 [122799]). Therefore, no 
further validation of the Colloid Transport Model is planned. 
However, some additional validation was performed in the Model Report. This additional 
validation of the colloid transport model is included in the validation of the RTM, and is 
discussed in Sections 7.2.1.5 (Method 2) and 7.2.2 (Method 3) of this Model Report. 

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7.7 VALIDATION OF THE ACTIVE FRACTURE MODEL WITH MATRIX 
DIFFUSION 
Validation of the Active Fracture Model (AFM) with matrix diffusion for transport was planned 
in Section I-2-1-5 of the TWP (BSC 2002 [160819]). The TWP outlines the required level of 
confidence, validation approaches, and validation criteria. 
The validation for the AFM with Matrix Diffusion combines two parts: 
.. The AFM, already validated for its intended use to represent site-scale flow, in a separate 
Model Report (BSC 2001 [158726]). 
.. The Matrix Diffusion model, already validated for saturated or nearly-saturated conditions in 
Section 7.4 of this report. 
The resulting model for AFM with Matrix Diffusion is intended to represent transport of 
radionuclides in the UZ for in situ saturation conditions (high saturation in the rock matrix, and 
low saturation in the fractures). 
The processes represented by the AFM and Matrix Diffusion are intertwined and it is impossible 
to discriminate their separate effects (and the efficacy of the matrix diffusion part) from 
presently available UZ testing data. Instead the validation strategy presented in this report draws 
from (1) separate validation of the AFM description of flow behavior, and (2) limited available 
evidence of matrix diffusion behavior from field testing in the UZ at Yucca Mountain. 
Section 7.7 includes two subsections. Section 7.7.1. addresses the issue of confidence building 
during the development of the AFM with matrix diffusion (based on sensitivity analysis of the 
AFM for transport, aiming to ensure that the incorporation of UZ transport into the TSPA is 
conservative for fracture-release cases), while Section 7.7.2 focuses on post-development 
validation of the model. 
7.7.1 Confidence Building during Model Development 
In the AFM conceptualization (Liu et al. 1998 [105729], pp. 26382641) only a portion of 
fracture networks are active (hydraulically conductive) under unsaturated conditions. The active 
portion is defined as a function of water saturation S to the power of the active fracture 
parameter . (0=.=1) (Liu et al. 1998 [105729], pp. 26382641). When .=0 or S=1 
(corresponding to a saturated condition) all fractures are active, while .=1 indicates the smallest 
active fracture portion for a given saturation. 
Using carbon-14 data (and incorporating the uncertainty involved in these data), the active 
fracture parameter . for tsw32tsw38 were estimated to be in the 0.20.4 range (BSC 2003 
[161773], pp. 7882). There is a discrepancy between these estimates and the 0.57  0.6 values 
obtained through inverse modeling in the calibrated flow model (DTN: 
LB0208UZDSCPMI.002 [161243]). Note that the calibrated values of . (approximately 0.6) 
were used in all 3-D site-scale simulations in this Model Report. 

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The impact of uncertainties in . on 3-D site-scale flow and transport through the UZ was 
investigated in BSC 2003 [163045], Section 6.8. The results of this sensitivity analysis indicated 
that (a) the percolation flux through the repository layers, and (b) the saturation and water 
potential distributions were not sensitive to large variations in the value ., i.e., reductions by 
50% (Figure 7.7-1). 
However, the sensitivity studies indicated that transport is more sensitive to uncertainty in the 
value of . than flow. Additionally, the effect is more pronounced at earlier times because 
diffusive fluxes become progressively smaller as the concentrations in the matrix and fractures 
approach equilibrium. The sensitivity of transport to . is demonstrated in Figure 7.7-2, which 
shows a substantial retardation in the arrival of a conservative tracer (with the diffusion 
coefficient of 99Tc) at the water table when . is reduced by 50% from its original calibrated value 
of approximately 0.6. In this case (which involved tracer release directly into the repository 
fractures), t10 increased by over an order of magnitude (from 40 to 650 years), while t50 doubled 
(from 3500 years to 7000 years). 
This study demonstrates that the calibrated . value of approximately 0.6 for the 
hydrostratigraphic units underneath the repository horizon provided conservative estimates of 
transport times through the UZ (BSC 2003 [163045] Section 6.8.2) when the tracers were 
released directly into the repository fractures. Note, however, that this value of . leads to an 
optimistic breakthrough estimate if the tracers are released into the matrix of the repository 
gridblocks (BSC 2003 [164889] Section 6.3.3). 
7.7.2 Post-Development Validation 
The post-development validation for the AFM with Matrix Diffusion combines the two parts 
described in the beginning of Section 7.7, i.e., the AFM flow model and the Matrix Diffusion 
model. 
Evidence of matrix diffusion from the Alcove 8/Niche 3 Phase 1 Line-Release (Fault) test is 
somewhat limited because the fracture saturation conditions along the transport pathway (i.e., at 
or near the fault) are believed to have been highly saturated (inferred from the 2 cm positive 
pressure head applied at the infiltration plot, see Section 7.4.1). Further testing in Yucca 
Mountain tuffs, under unsaturated conditions with multiple tracers, could significantly strengthen 
the validation arguments presented in this report. Two such tests are planned: the Alcove 
8/Niche 3 Phase 2 large-plot test, and the cubic-meter-block laboratory test. Relevant 
unsaturated transport data are currently unavailable from either of these tests, a possibility that 
was foreseen in the TWP. The TWP covering this Model Report selected independent technical 
review as a second method for post-development model validation. However, the independent 
technical review was not utilized in this case. The independent technical review was not 
considered necessary for adequate validation given the independent validations conducted for the 
AFM (BSC 2003 [161773], Section 7.2) and matrix diffusion models (see Section 7.4). Future 
confirmation testing of the UZ transport model is addressed in the Performance Confirmation 
Plan (Snell et al. 2003 [166219], Section 4.1.1.2). 

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The validation approach for the AFM with Matrix Diffusion is based on the validation of the 
AFM flow model and the Matrix Diffusion model separately. It combines the AFM, which is 
validated in a separate Model Report (BSC 2001 [158726], with the Matrix Diffusion model, 
validated in Section 7.4 of this report. The validity of the AFM with Matrix Diffusion for 
Transport Model, for its intended use, is inferred from that of the two separate component 
models. Additional validation is not necessary because both the active fracture model validation 
and the matrix diffusion model validation have both active fracture (unsaturated flow through 
fractures) and matrix diffusion (diffusive exchange between fracture and matrix) processes 
represented in the validation data. 

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(a) 
Saturation 
Elevation (m) 
0 0.25 0.5 0.75 1 
700 
800 
900 
1000 
1100 
1200 
1300 
1400 
Calibrated AFP 
Smaller AFP for under repository 
Model unit interface 
TCw 
PTn 
TSw 
CHn 
(b) 
Saturation 
Elevation (m 
0 0.25 0.5 0.75 1 
700 
800 
900 
1000 
1100 
Smaller AFP for under repository 
Model unit interface 
TSw 
CHn 
Water potential (bar) 
Elevation (m) 0 2 4 6 8 10 
700 
800 
900 
1000 
1100 
1200 
1300 
1400 
Calibrated AFP 
Smaller AFP for under repository 
Model unit interface 
TSw 
CHn 
PTn 
TCw 
Model ResultsDTN LB0304RDTRNSNS.001 [165992] 
Figure 7.7-1. Comparison of (a) Simulated Matrix Liquid Saturation and (b) Water Potentials Using 
Calibrated Hydraulic Properties (Solid Line) with That Obtained Using a Smaller (Half) 
Value of . in the Units of Under Repository (Dashed Line) for Borehole USW SD-6  From 
BSC 2003 [163045], Section 6.8, Figure 6.8-2. 

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1.00E+0 
1.00E+1 
1.00E+2 
1.00E+3 
1.00E+4 
1.00E+5 
1.00E+6
Time (year) 
0.00 
0.20 
0.40 
0.60 
0.80 
1.00 
Fractional Mass Breakthrough 
Calibrated gamma (base case) 
Changed gamma of TSw units 
Changed gamma of units below the repository 
Model ResultsDTN: LB0304RDTRNSNS.001 [165992] 
Figure 7.7-2. Comparison of a Simulated Breakthrough Curve of Relative Tracer Mass at the 
Groundwater Table Obtained for the Base Case (Using Calibrated Rock Hydraulic 
Properties, Red Solid Line), a Case Using a Smaller (Half) Value of . of the TSw Units 
(Blue Dash Line), and Another Case Using a Smaller (Half) Value of . of All Units below 
the Repository (Green Solid Line)  From BSC 2003 [163045], Section 6.8, Figure 6.8-3. 

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8. CONCLUSIONS 
Section 8 is composed of three subsections. In Section 8.1 we present a summary of the 
modeling activity in the present Model Report. The main conclusions from the individual 
studies discussed in Section 6 are presented in Section 8.2, which includes conclusions from the 
2-D studies, the 3-D site-scale studies for instantaneous and continuous release of solutes and 
colloids, and corresponding sensitivity analyses. Section 8.3 focuses on the model output, 
uncertainties, and limitations. 
8.1 SUMMARY OF MODELING ACTIVITY 
Modeling in Sections 6.8-6.14 involved the application of T2R3D V1.4 (LBNL 1999 [146654]; 
Wu et al. 1996 [100649]) to study the transport of important radionuclides (99Tc, 237Np, 239Pu, 
233U, 235U, 241Am, 135Cs, 90Sr, 226Ra, 229Th, and 221Pa) in the entire Yucca Mountain system, 
using large-scale 3-D grids and assuming an instantaneous (single event) release scenario. 
Modeling in Section 6.15 involved the application of TOUGH2 V1.4 Module EOS9 V1.4 
(LBNL 2000 [146496]) study the transport of 99Tc, 237Np, and 239Pu in the entire Yucca 
Mountain system, using large-scale 3-D grids and assuming a continuous release scenario. In 
Section 6.16 and 6.17, TOUGH2 V1.4 Module EOS9 V1.4 (LBNL 2000 [146496]) was used to 
study the 3-D site scale transport of the 239Pu 235U 231Pa chain and of the 241Am 237Np 
233U 229Th chain, respectively, under a continuous release scenario. 
The modeling activity in Section 6.18 involved the application of EOS9nT to study the transport 
of four true colloids of different sizes and properties in the entire Yucca Mountain system, using 
large-scale 3-D grids. Modeling using the T2R3D (LBNL 1999 [146654]) and EOS9nT codes in 
Section 6.19 aimed at evaluating the Yucca Mountain UZ system performance under (a) an 
alternative conceptual model of representing the fracture-matrix system, and (b) an alternative 
modeling approach involving particle tracking. T2R3D and EOS9nT simulations in Section 6.20 
evaluated the impact of the standard radionuclide release model (in which radionuclides are 
released simultaneously throughout the entire repository) by limiting releases to locations that 
are not in the immediate vicinity of permeable faults. 
8.2. MODEL REPORT CONCLUSIONS 
The following conclusions can be drawn from this study: 
8.2.1 General Conclusions From the 3-D Studies 
1. Three dimensional site-scale simulations using EOS9nT indicate that, under the #1 perchedwater 
model, radionuclide transport from the bottom of the proposed repository to the water 
table is both dominated and controlled by the faults. These provide fast pathways for downward 
migration to the water table, but also limit lateral transport across the fault walls into the 
formation. 

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2. The 3-D site-scale EOS9nT simulations for both an instantaneous and a continuous release 
regime indicate that radioactive solutes from the repository move faster and reach the water table 
earlier and over a larger area in the northern part of the repository. This appears to be consistent 
with the geologic model of the UZ, which is characterized by the presence of highly fractured 
zeolitic CHz layers in that area. The fractures in these layers are several orders of magnitude 
more conductive than the corresponding matrices. Thus, flow is fracture-dominated, and results 
in the transport pattern observed in this study. 
3. The transport patterns follow the infiltration and percolation distributions. A review of the 
infiltration pattern at the surface, the percolation flux at the repository level and the percolation 
flux at the groundwater level indicates that they closely reflect the transport patterns discussed in 
Conclusion (2) above. Thus, the water flow pattern dictates the advective transport pattern. 
4. For both an instantaneous and a continuous release regime, the highly conductive Drillhole 
Wash fault and Pagany Wash fault are the main pathways of transport (and related to the 
percolation patterns) for the dominance of the northern part of the repository. Radionuclides 
released directly into these faults or reaching them from adjacent areas move rapidly downward 
to reach the water table at an earlier time. Additionally, the Sundance fault, the Solitario fault, 
and the Sever Wash fault are transport-facilitating geological features, but their effect becomes 
significant at later times. 
5. Fractures are the main pathways of radionuclide transport. Diffusion from the fractures into 
the matrix is one of the main retardation processes in radionuclide transport. When 
radionuclides sorb onto the matrix into which they diffuse, their migration is further retarded. 
Sorption also leads to retardation in the fractures by resulting in larger concentration gradients 
(thus enhanced diffusion) between the liquid phases in the fractures and in the matrix. 
6. Caution should be exercised in the analysis and interpretation of the 3-D simulation results 
because the underlying approach is extremely conservative, involves successive (and 
multiplicative) levels of worst-case scenarios, and is improbable (if not outright impossible). 
Thus, in this Model Report (a) all the waste packages are assumed to rupture at the same time 
throughout the repository, (b) water is allowed to seep into the repository by overcoming the 
capillary pressure barrier, to enter uninhibited the breached canisters, and to carry radionuclides 
directly into the fractures, (c) drip shields are not considered, (d) the retardation effects of the 
invert and of the shadow zone are ignored, (e) the vertical fractures are assumed to be open and 
continuous throughout the UZ from the repository to the water table, (f) the horizontal fractures 
are assumed to be interconnected, and are also connected (directly or indirectly) to the vertical 
fractures, and (g) the radioactive tracers (solutes or colloids) are stable, unaffected by the near 
field conditions (thermal, geochemical, physical), and are not subject to chemical immobilization 
(e.g., through irreversible sorption or precipitation) anywhere in the UZ. 
7. Note that the importance of faults and perched-water bodies in transport is directly 
dependent on the underlying geologic and perched-water conceptual models. It is reasonable to 
expect that changing geologic and perched-water models may lead to substantially different 
results, given the sensitivity of transport to these geologic features. This realization underlines 
the importance of representative conceptual models. 

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8.2.2 Conclusions From the 3-D Studies of Instantaneously-Released Radioactive Solutes 
8. For present-day climatic conditions (Table 6.7-1) and instantaneously-released 
radionuclides, the t10 (see definition in Section 6.8) of the nonsorbing 99Tc for low, mean, and 
high infiltration is 13,900, 83, and 6 years, and the t50 (see definition in Section 6.8) is over 
1,000,000, 6,640, and 230 years, respectively (Table 6.20-1). Under the same conditions, the 
t10 of the moderately sorbing 237Np for low, mean, and high infiltration is 33,800, 410, and 4 
years, and the corresponding t50 is over 1,000,000, 25,400, and 1,600 years, respectively. The 
strongly sorbing 239Pu did not exhibit a sufficiently high breakthrough level at the water table for 
t10 or t50 to become meaningful in most cases (the only exception was a t10 = 1,530 year for a high 
present-day infiltration. 
9. For present-day climatic conditions (Table 6.7-1) and instantaneously-released 
radionuclides, the t10 (see definition in Section 6.8) of the moderately sorbing 233U for low, 
mean, and high infiltration is 65,200, 433, and 12 years, and the t50 (see definition in Section 6.8) 
is over 1,000,000, 29,100, and 1,120 years, respectively (Table 6.20-1). The t10 and t50 for 235U 
are very close. These results indicate that the 233U and 235U behavior is similar to that of 237Np. 
Under the same conditions, the t10 of the variably sorbing 135Cs (very different sorption affinity 
for different rocks, see Table 6.5-1) for low, mean, and high infiltration is 1,000,000, 52,500, and 
2,170 years, and the corresponding t50 is over 1,000,000, over 1,000,000, and 71,200 years, 
respectively. 
10. For present-day climatic conditions (Table 6.7-1) and instantaneously-released 
radionuclides, the cumulative breakthrough curves of 241Am, 231Pa, 229Th, 226Ra, 90Sr indicate 
very limited (if any) radionuclide arrivals at the water table (Table 6.20-1) because of very 
strong sorption (all) and short half lives (241Am and 90Sr). 
11. The results discussed in (8)-(10) lead to the conclusion that transport to the water table is 
strongly dependent on the sorption affinity of the radionuclide to the geohydrologic units it 
encounters in the UZ. Generally speaking, lower Kd values (quantifying weaker sorption) lead to 
faster radionuclide transport to the water table. 
12. The 3-D site-scale simulations indicate that a change in the future climatic conditions can 
have a significant effect on transport. Increasing infiltration (as the climatic regime changes 
from present-day to monsoon and glacial conditions and its level changes from low to mean to 
high) leads to faster radionuclide transport to the water table. The acceleration in transport 
increases with decreasing sorption. 
13. Matrix diffusion (as quantified by the molecular diffusion coefficient D0) has a significant 
impact on breakthrough predictions, resulting in faster arrival times for lower D0 values. The 
relative effect of D0 on breakthrough predictions appears to be mitigated by sorption, i.e., the 
importance of D0 in transport decreases with an increasing Kd. 
8.2.3 Conclusions From the 3-D Studies of Continuously-Released Radioactive Solutes 
14. For mean present-day climatic conditions (Table 6.7-1) and continuously-released 
radionuclides from a decaying source, the t10 (see definition in Section 6.15) of 99Tc and 237Np is 

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74 and 781 years, and the t50 (see definition in Section 6.15) is 3,901 and 22,940 years, 
respectively (Table 6.20-2). In the case of the strongly sorbing 239Pu, RF did not reach the 0.1 
level in the 1,000,000 years of simulation. 
15. In the simulation of 3-D transport of 239Pu, the members of the decay chain may have to be 
considered (i.e., 239Pu, 235U, and 231Pa) if the 239Pu release rate at the repository is significant 
(Table 6.20-2). Although the t10 for 239Pu transport is always larger than 1,000,000 years, 235U 
becomes the main contributor in the radionuclide release at the water table after 10,000 years (at 
most) because of its weaker sorption onto the matrix and its longer half-life. The contributions 
of 231Pa are not important. Under mean present-day climatic conditions, the t10 and the t50 of the 
sum of the members of the 239Pu chain are computed from the 3-D simulations as 6,419 and 
33,660 years, respectively. 
16. The analysis of 3-D transport of the members of the 241Am chain indicates that only the 
237Np daughter is significant in the 1,000,000 time frame of this study. The strong sorption 
affinity and the short T1/2 (432.2 years) of 241Am precludes a significant role in the radionuclide 
stream arriving at the water table, while the long half life of 237Np prevents its daughters from 
dominating the releases at the water table. Note that the t10 and t50 of the sum of the 241Am chain 
members (1,027 and 23,450, respectively) are roughly the sum of t10 and t50 of the transport of 
pure 237Np (see Conclusion 17 and Table 6.20-2) and the T1/2 (432.2 years) of 241Am. 
8.2.4 Conclusions From the 3-D Studies of Continuously-Released Radioactive Colloids 
17. For continuous colloid release under a mean present-day infiltration regime and for a given 
kinetic clogging (forward filtration) coefficient .+, the transport of radioactive true colloids is 
not appreciably influenced by the kinetic declogging (reverse filtration) coefficient .- in larger 
colloids. This is caused by (a) the inability of the colloids to reach the matrix because of 
straining and a low D0 (a result of their large size) and (b) the corresponding very limited 
filtration in the matrix. 
18. The colloid size has a significant effect on transport. Large colloids reach the water table 
faster. Because fractures are the main transport conduit at Yucca Mountain, the inability of larger 
colloids to diffuse into the matrix because of smaller D0 values and size exclusion (straining) 
result in faster transport to the groundwater. Smaller colloidal particles can diffuse more easily 
into the matrix, and their transport is thus retarded. 
19. When there is no filtration in the fractures (Cases 1 to 3), the results of the simulations of 
transport of PuO2 colloids of four different sizes (450 nm, 200 nm, 100 nm, and 6 nm) indicate 
that there is very limited retardation of the larger colloids, all of which have a very similar t10 
(Table 6.20-3). Note that t10 increases with a decreasing size, but the change is very small (from 
4.35 to 4.53 years when the colloid diameter decreases from 450 nm to 100 nm). Although RF 
does not reach the 0.5 level (thus t50 cannot be defined), it rises rapidly and reaches 0.4 in about 
20 years. Conversely, the retardation of the smallest colloid (6 nm) is very significant, and RF is 
well below the 0.1 level. 
20. When limited filtration in the fractures is considered (Case 4), the results of the simulations 
of transport of PuO2 colloids of four different sizes (450 nm, 200 nm, 100 nm, and 6 nm) are 

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similar to those for no filtration in the fractures. However, although t10 is still low, it is 
significantly larger than that for no fracture filtration, and decreases from 32.4 to 27.6 years 
when the colloid diameter decreases from 450 nm to 100 nm (Table 6.20-3). In this case RF rises 
rapidly and reaches 0.4 in about 100-150 years. As in the case for no fracture filtration, the 
retardation of the smallest colloid (6 nm) is very significant, and RF remains well below 0.1 
during the simulation period. 
21. Size exclusion (straining) at the interfaces of different hydrogeologic layers leads to colloid 
concentrations immediately above the interface that can be higher than that in the water released 
from the proposed repository. This phenomenon is more pronounced in larger colloids. 
8.2.5 Conclusions From the Study of Alternative Conceptual Models 
22. When the alternative conceptual model of multiple interactive continua (to describe the 
fracture-matrix system) is employed, transport is delayed due to enhanced fracture-matrix 
interaction. 
8.2.6 Conclusions From the Barrier Evaluation 
23. Even under the improbably conservative approach involved in the 3-D site-scale studies 
(Section 6.7.8 and Conclusion 9), the UZ of Yucca Mountain appears to be an effective barrier to 
the transport of the strongly sorbing radionuclides (90Sr, 226Ra, 229Th, 241Am, 221Pa and 239Pu) to 
the water table. 
24. The variably sorbing 135Cs (strongly on zeolites, much less on other rocks), the mildly 
sorbing 233U, 235U, 237Np, and the nonsorbing 99Tc arrive at the water table at times that are 
fractions of their respective half-lives. However, this is not necessarily an indication of a 
breached or ineffective UZ barrier, but can be a direct consequence of the conceptual model of 
UZ flow and of the improbably conservative (if not practically impossible) approach described 
in Section 6.7.8. A more definitive evaluation of the barrier can be provided by using a more 
realistic scenario accounting for the successive retardation effects of the processes discussed in 
Section 6.7.8. 
25. Eliminating potential sources from the vicisnity of the fault fractures appears to have only a 
small effect on transport and arrivals at the water table. For instantaneous release (when a finite 
radionuclide mass is involved), the RM breakthrough curves in Figures 6.20-1 and 6.20-2 show a 
small increase in t10 (in line with expectations because there is no release into the fast-conducting 
fault fractures), but t50 is practically unchanged. The RF breakthrough curves in Figures 6.20-3 
and 6.20-4 for continuous release show practically no discernible difference from those that 
account for release into the faults (Section 6.15). 
8.3. MODEL OUTPUT, UNCERTAINTIES, AND LIMITATIONS 
8.3.1 Model Output 
As indicated in TWP (BSC 2002 [160819], p. 54), the output/product of this Model Report is a 
set of breakthrough curves for use as benchmarks for the particle-tracking calculations 

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performed for TSPA (BSC 2003 [163933]). All the breakthrough curves presented and 
discussed in this Model Report are included in DTN: LB0307MR0060R1.007, which 
incorporates both the graphical representations and the model output used for their development. 
All output DTNs from this Model Report are summarized in Table 8.1 
8.3.2 Model Uncertainties 
As indicated in Section 6, the predictions of transport are subject to three general types of 
uncertainties. 
8.3.2.1 Uncertainties in the Flow Conceptual Model and the Corresponding Parameters 
The impact of uncertainties in the flow conceptual model and the corresponding hydraulic 
parameters is in the estimation of the magnitude and relative sizes of flows and saturations in the 
fractures and in the matrices of the UZ, which affect directly both advective transport (and, 
consequently, travel times to the water table following a radionuclide release) and diffusive 
fluxes (see Equations 1821). Although the importance of these uncertainties is readily 
recognized, addressing them is beyond the scope of this study, but rather the subject of the 
Model Report on the UZ Flow Model (BSC 2003 [163045], Section 6). Because the 
radionuclide transport study is intertwined with the UZ flow uncertainties (from which it derives 
its flow fields), it suffers from the same flow-related limitations and uncertainties. 
8.3.2.2 Climatic Uncertainties 
The impact of these uncertainties is assessed by estimating transport under all possible nine 
climatic scenarios of Table 6.7-1, thus bounding the possible solution. From these simulations, 
the universal conclusion is that the travel time to the water table decreases, and overall transport 
increases, with an increasing infiltration. 
8.3.2.3 Uncertainties in Matrix Diffusion 
Uncertainties in matrix diffusion are reflected in the values of the diffusion coefficient D0. To 
address this issue, we investigated the sensitivity of transport through the UZ for the D0 values 
shown in Table 6.5-2, which cover the possible D0 range for all three possible types of 
radionuclides (strongly sorbing, mildly sorbing, and nonsorbing). The results of these studies 
indicated that the D0 value has a significant impact on breakthrough predictions, resulting in 
faster arrival times for lower D0 values. The impact increases as the sorption affinity of the 
radionuclides decreases. 
8.3.2.4 Uncertainties in Sorption 
Such uncertainties in sorption are reflected in the values of the distribution coefficient Kd and are 
important only in the case of mildly sorbing radionuclides. (We did not investigate the effects 
for strongly sorbing radionuclides, because the studies presented in the Model Report covered 
the whole range of possibilities and showed minimal effects). To address this issue, we 
investigated the sensitivity of 237Np transport through the UZ for the Kd values shown on Figure 
6.9-5. These cover the range between zero (no sorption, in which case behavior similar to that of 
99Tc was expected) to the maximum values reported in Table 6.5-2. 

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As expected, Kd has a significant impact on breakthrough predictions, resulting in faster arrival 
times for lower Kd values. Note that the relative effect of Kd uncertainty in the prediction of 
transport of the sorbing 237Np appears to be much more pronounced than that for the 
D0 uncertainty for the range tested here. 
8.3.2.5 Uncertainties in Filtration 
The impact of these uncertainties is assessed by estimating (a) transport for a very wide range of 
the kinetic filtration parameters (clogging and declogging coefficients), and (b) the impact of 
filtration in the fractures (by considering minor fracture fillup), thus bounding the possible 
solutions. The simulations indicate that the transport is not significantly affected by significantly 
varying the filtration parameters, travel time to the water table decreases with the colloid size, 
larger colloids show little retardation while very small ones are retarded significantly, and 
fracture filtration can have a substantial impact on transport. 
8.3.3 Limitations of Applicability 
The results reported in this Model Report should be viewed as representative of the upper bound 
of possible solutions when the approach discussed in Section 6.1.5 is employed. When viewed 
under this light, these results are applicable without limitations. 
Generally speaking, the results and observations in the Model Report are not applicable to 
conditions that are not adequately described by the Model Report approach and underlying 
assumptions. This scenario could include a different conceptual model of UZ flow and/or 
considerations of the mitigating processes discussed in Sections 6.7.8 and 6.20.3 which are likely 
to lead to greater delay of radionuclide transport. Therefore, the model is appropriate for 
comparison with other transport models supporting TSPA to ensure that radionuclide transport is 
not underestimated. 

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Table 8-1. Output Data and Data Tracking Numbers 
Location in this report 
DTN 
Text Figure Table 
Remarks 
LA0302AM831341.002 6.1.1 
6.4.2 
6.5-1 
6.5-2 
6.5-3 
Unsaturated Zone Distribution 
Coefficients (KD) For U, Np, Pu, 
Am, Pa, Cs, Sr, Ra, and Th. 
LA0311AM831341.001 Attachment 
II 
II-2 Correlation Matrix for Sampling 
of Sorption Coefficient 
Probability Distributions. 
Submittal date: 11/06/2003. 
LB0307MR0060R1.001 6.9.1 
6.9.2 
6.10.1 
6.11 
6.12 
6.13 
6.14 
6.7-2 
Ambient Radionuclide Transport 
- Uniform Instantaneous 
Release: Simulations 
(Input/output files). 
LB0307MR0060R1.002 6.8.1.3 
6.9.1 
6.9.1.3 
6.9.2 
6.10.1 
6.10.1.2 
6.11 
6.8-2 through 6.8-21 
6.7-2 Ambient Radionuclide Transport 
 Uniform Instantaneous 
Release: Summaries 
LB0307MR0060R1.003 6.7.2 
6.15.1 
6.16 
6.17 
6.18.1 
6.7-2 Ambient Radionuclide Transport 
 Uniform Continuous Release: 
Simulations (Input/output files) 
LB0307MR0060R1.004 6.15.4 
6.7-2 
Ambient Radionuclide Transport 
 Uniform Continuous Release: 
Summaries. 
LB0307MR0060R1.005 6.20.2 
6.7-2 
Ambient Radionuclide Transport 
 No radionuclide releases in 
the vicinity of major faults, 
Instantaneous and Continuous 
Release: Simulations 
(Input/output files). 
LB0307MR0060R1.006 6.20.2 6.7-2 
Ambient Radionuclide Transport 
- No radionuclide releases in the 
vicinity of major faults, 
Instantaneous and Continuous 
Release: Summaries. 

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Table 8-1. Output Data and Data Tracking Numbers (Continued) 
Location in this report DTN 
Text Figure Table 
Remarks 
LB0307MR0060R1.007 8.3.1 6.8-1 
6.8-26 
6.8-27 
6.8-28 
6.9-1 
6.9-2 
6.9-3 
6.9-4 
6.9-5 
6.10-1 
6.10-2 
6.10-4 
6.11-1 
6.11-2 
6.12-1 
6.12-2 
6.13-1 
6.14-1 
6.14-2 
6.14-3 
6.15-1 
6.16-1 
6.16-2 
6.17-1 
6.17-2 
6.18-1 
6.18-2 
6.20-1 
6.20-2 
6.20-3 
6.20-4 
6.7-2 
6.20-1 
6.20-2 
6.20-3 
Ambient Radionuclide Transport 
 TSPA Deliverable Extractions. 
LB0308MR0060R1.008 7.2.1.2 
7.2.1.3 
7.2.1.4 
7.2.1.5 
7.3.3.2 
7.3.4.2 
7.3.5.2 
7.2-1 
7.2-2 
7.2-3 
7.2-4 
7.2-5 
7.3-3 
7.3-5 
Ambient Radionuclide Transport 
 Model Validation: Simulations 
(Input/output files). 
LB0308MR0060R1.009 7.2-2 
7.2-3 
7.2-4 
7.2-5 
7.2-6 
7.3-2 
7.3-3 
7.3-4 
7.3-5 
7.3-6 
7.3-7 
7.2-6 
7.3-8 
Ambient Radionuclide Transport 
 Model Validation: Data 
Summaries. 
LB0310MR0060R1.010 6.19.2.1 
6.19.2.2 
6.9-2 
6.10-3 
6.18-3 
6.7-2 Supplemental Radionuclide 
Transport Simulations: 
Simulations (Input/output files). 
LB0310MR0060R1.011 6.19.2.1 
6.19.2.2 
6.7-2 Supplemental Radionuclide 
Transport Simulations: Data 
Summaries. 

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INTENTIONALLY LEFT BLANK 

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9. INPUTS AND REFERENCES 
The following is a list of the references cited in this document. Column 1 represents the unique 
six digit numerical identifier (the Document Input Reference System [DIRS] number), which is 
placed in the text following the reference callout (e.g., BSC 2002 [160819]). The purpose of 
these numbers is to assist the reader in locating a specific reference. Within the reference list, 
multiple sources by the same author (e.g., BSC 2002) are sorted alphabetically by title. 
9.1 CITED DOCUMENTS 
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158463 BSC (Bechtel SAIC Company) 2001. In Situ Field Testing of Processes. ANL-NBSHS-
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Transport Properties (U0100). ANL-NBS-HS-000019 REV 00 ICN 02. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: MOL.20020311.0017. 
158726 BSC (Bechtel SAIC Company) 2001. UZ Flow Models and Submodels. MDL-NBSHS-
000006 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
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160247 BSC (Bechtel SAIC Company) 2002. Analysis of Geochemical Data for the 
Unsaturated Zone. ANL-NBS-HS-000017 REV 00 ICN 02. Las Vegas, Nevada: 
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159124 BSC (Bechtel SAIC Company) 2002. Geologic Framework Model (GFM2000). 
MDL-NBS-GS-000002 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20020530.0078. 
160059 BSC (Bechtel SAIC Company) 2002. Radionuclide Screening. ANL-WIS-MD- 
000006 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
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160146 BSC (Bechtel SAIC Company) 2002. Total System Performance Assessment-License 
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Nevada: Bechtel SAIC Company. ACC: MOL.20020923.0175. 

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MDL-NBS-HS-000008 REV 01 276 November 2003 
161773 BSC (Bechtel SAIC Company) 2003. Analysis of Hydrologic Properties Data. 
MDL-NBS-HS-000014 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
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000003 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
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and Transport Modeling. ANL-NBS-HS-000015 REV 01. Las Vegas, Nevada: 
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163152 BSC (Bechtel SAIC Company) 2003. Dissolved Concentration Limits of Radioactive 
Elements. ANL-WIS-MD-000010 REV 02. Las Vegas, Nevada: Bechtel SAIC 
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162050 BSC (Bechtel SAIC Company) 2003. Drift-Scale Coupled Processes (DST and THC 
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164889 BSC (Bechtel SAIC Company) 2003. Drift-Scale Radionuclide Transport. MDLNBS-
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163933 BSC (Bechtel SAIC Company) 2003. Particle Tracking Model and Abstraction of 
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162267 BSC (Bechtel SAIC Company) 2003. Seepage Calibration Model and Seepage 
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163226 BSC (Bechtel SAIC Company) 2003. Seepage Model for PA Including Drift 
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134571 Tachi, Y.; Shibutani, T.; Sato, H.; and Yui, M. 1998. Sorption and Diffusion 
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101023 Triay, I.R.; Cotter, C.R.; Huddleston, M.H.; Leonard, D.E.; Weaver, S.C.; Chipera, 
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100649 Wu, Y.S.; Ahlers, C.F.; Fraser, P.; Simmons, A.; and Pruess, K. 1996. Software 
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Transport in Unsaturated Fractured Rock: Effects of Multiscale Heterogeneity of 
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New York, New York: Elsevier. TIC: 253978. 
Software Cited 
155323 BSC (Bechtel SAIC Company) 2001. Software Code: PHREEQC. V2.3. PC. 
10068-2.3-00. 
139918 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: iTOUGH2. 
V4.0. SUN, DEC. 10003-4.0-00. 
146654 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: T2R3D. 
V1.4. FORTRAN 77, SUN, DEC / ALPHA. 10006-1.4-00. 
113943 LBNL (Lawrence Berkeley National Laboratory) 1999. Software Code: TOUGH2. 
V1.11 MEOS9nTV1.0. MAC, SUN, DEC/Alpha, PC. 10065-1.11MEOS9NTV1.0- 
00. 
132448 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Code: DCPT. 
V1.0. PC. 10078-1.0-00. 
146496 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Code: TOUGH2. 
V1.4. Sun Workstation and DEC/ALPHA. 10007-1.4-01. 
162143 LBNL (Lawrence Berkeley National Laboratory) 2002. Software Code: Bkread.f. 
V1.0. SunOS 5.5.1. 10894-1.0-00. 
154342 LBNL (Lawrence Berkeley National Laboratory) 2002. Software Code: DCPT. 
V2.0. PC, Windows. 10078-2.0-00. 
162142 LBNL (Lawrence Berkeley National Laboratory) 2002. Software Code: Smesh.f. 
V1.0. SunOS 5.5.1. 10896-1.0-00. 
160242 LBNL (Lawrence Berkeley National Laboratory) 2002. Software Code: TOUGH2. 
V1.6. PC/MS-DOS under Windows 98, Sun UltraSparc OS 5.5.1, DEC-Alpha OSF1 
V4.0. 10007-1.6-00. 
161491 LBNL (Lawrence Berkeley National Laboratory) 2003. Software Code: TOUGH2. 
V1.6. PC/MS-DOS under Windows 98, Sun UltraSparc OS 5.5.1, DEC-Alpha OSF1 
V4.0. 10007-1.6-01. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 289 November 2003 
162786 LBNL (Lawrence Berkeley National Laboratory) 2003. Software Code: XtractG.f90. 
V1.0. MAC, OS 9.2; DEC Alpha, OSF1 V4.0 and OSF1 V5.1. 10930-1.0-00. 
9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
156605 10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. Readily available. 
AP-2.22Q, Rev. 1, ICN 0. Classification Criteria and Maintenance of the Monitored Geologic 
Repository Q-List. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: DOC.20030807.0002. 
AP-SI.1Q, Rev. 05, ICN 2. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20030902.0003. 
9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
147613 GS000308311221.005. Net Infiltration Modeling Results for 3 Climate Scenarios for 
FY99. Submittal date: 03/01/2000. 
153407 GS000608312271.001. Pore-Water Hydrochemistry and Isotopic Data for Boreholes 
USW NRG-6, USW NRG-7A, USW SD-7, USW SD-9, USW SD-12, USW UZ-14 
and UE-25 UZ#16 from 10/1/96 to 1/31/97. Submittal date: 06/23/2000. 
165860 GS010608312272.001. Chemical Analysis of Pore Water from Boreholes USW UZ- 
7A, USW WT-24, USW SD-6, USW SD-7 and USW SD-12 During FY 1997 and FY 
1998. Submittal date: 07/09/2001. 
156375 GS010708312272.002. Chemical Data for Pore Water from Tuff Cores of USW 
NRG-6, USW NRG-7/7A, USW UZ-14, USW UZ-N55 and UE-25 UZ#16. 
Submittal date: 09/05/2001. 
165859 GS011008312272.004. Analysis for Chemical Composition of Pore Water from 
Boreholes USW WT-24 and USW SD-6 During FY98 and FY99. Submittal date: 
12/20/2001. 
160899 GS020408312272.003. Collection and Analysis of Pore Water Samples for the 
Period from April 2001 to February 2002. Submittal date: 04/24/2002. 
162129 GS020508312242.001. Trench Fault Infiltration in Alcove 8 Using Permeameters 
from March 5, 2001 to June 1, 2001. Submittal date: 05/22/2002. 
162141 GS020908312242.002. Trenched Fault Infiltration in Alcove 8 Using Permeameters 
from June 1, 2001 to March 26, 2002. Submittal date: 09/17/2002. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 290 November 2003 
162131 GS030108314224.001. Geotechnical Data for Alcove 8 (ECRB) and Niche 3 (ESF): 
Full Periphery Geologic Map (Drawing OA-46-356). Submittal date: 02/05/2003. 
144662 GS950608312231.008. Moisture Retention Data from Boreholes USW UZ-N27 and 
UE-25 UZ#16. Submittal date: 06/06/1995. 
165858 GS951208312272.004. Analysis for Chemical Composition of Perched-Water from 
Boreholes USW UZ-14, USW NRG-7A, USW SD-9, USW SD-7 and Groundwater 
from Boreholes UE-25 ONC#1 and USW G-2 from 8/18/89 to 3/21/95. Submittal 
date: 09/12/2001. 
145272 GS980908312242.039. Unsaturated Water Retention Data for Lexan-Sealed Samples 
from USW SD-6 Measured Using a Centrifuge. Submittal date: 09/22/1998. 
146134 GS990208312272.001. Analysis for Chemical Composition of Pore Water from 
Borehole USW UZ-14 and UE-25 UZ#16 and Groundwater from UE-25 UZ#16. 
Submittal date: 02/23/1999. 
107185 GS990308312242.007. Laboratory and Centrifuge Measurements of Physical and 
Hydraulic Properties of Core Samples from Busted Butte Boreholes UZTT-BB-INJ- 
1, UZTT-BB-INJ-3, UZTT-BB-INJ-4, UZTT-BB-INJ-6, UZTT-BB-COL-5 and 
UZTT-BB-COL-8. Submittal date: 03/22/1999. 
109822 GS990708312242.008. Physical and Hydraulic Properties of Core Samples from 
Busted Butte Boreholes. Submittal date: 07/01/1999. 
148603 LA000000000034.002. Diffusion of Sorbing and Non-Sorbing Radionuclides. 
Submittal date: 06/22/1993. 
156582 LA0008WS831372.001. Calculated Daily Injection Rates for the Busted Butte 
Unsaturated Zone Transport Tests. Submittal date: 08/23/2000. 
157100 LA0112WS831372.001. Busted Butte UZ Transport Test: Phase II Collection Pad 
Tracer Loading. Submittal date: 12/06/2001. 
157115 LA0112WS831372.002. Busted Butte UZ Transport Test: Phase II Collection Pad 
Tracer Concentrations. Submittal date: 12/06/2001. 
157106 LA0112WS831372.003. Busted Butte UZ Transport Test: Phase II Normalized 
Collection Pad Tracer Concentrations. Submittal date: 12/06/2001. 
164721 LA0201WS831372.007. Busted Butte UZ Transport Test: Phase II Normalized 
Collection Pad Metal Tracer Concentrations. Submittal date: 01/22/2002. 
162766 LA0201WS831372.008. Busted Butte UZ Transport Test: Phase I Collection Pad 
Normalized Tracer Concentrations. Submittal date: 01/22/2002. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 291 November 2003 
161526 LA0203WS831372.002. Freundlich and Linear Isotherm Parameters for 
Radionuclides and Sorbing Tracers Used in the Busted Butte UZ Transport Test. 
Submittal date: 03/20/2002. 
160051 LA0206AM831234.001. Eh-pH Field Measurements on Nye County EWDP Wells. 
Submittal date: 06/21/2002. 
163852 LA0206AM831234.002. Geochemical Field Measurements on Nye County EWDP 
Wells. Submittal date: 06/21/2002. 
162763 LA0211WS831372.001. Busted Butte Rock Extractions: Measured and Normalized 
Anion and FBA Tracer Concentrations. Submittal date: 11/19/2002. 
162765 LA0302WS831372.001. Fluorescein Plume Images from the Phase 1A Mineback at 
Busted Butte. Submittal date: 02/26/2003. 
163789 LA0305AM831341.001. 1977 to 1987 Sorption Measurements of AM, BA, CS, NP, 
PU, PA, SR, TH, and U with Yucca Mountain Tuff Samples. Submittal date: 
05/21/2003. 
164949 LA0306AM831343.001. Modeling Calculations of Radionuclide Sorption via 
Surface-Complexation Reactions. Submittal date: 06/09/2003. 
165523 LA0309AM831341.002. Batch Sorption Coefficient Data for Barium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165524 LA0309AM831341.003. Batch Sorption Coefficient Data for Cesium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165525 LA0309AM831341.004. Batch Sorption Coefficient Data for Neptunium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165526 LA0309AM831341.005. Batch Sorption Coefficient Data for Plutonium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165527 LA0309AM831341.006. Batch Sorption Coefficient Data for Strontium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165528 LA0309AM831341.007. Batch Sorption Coefficient Data for Uranium on Yucca 
Mountain Tuffs in Representative Water Compositions. Submittal date: 09/25/2003. 
165865 LA0310AM831341.001. Sorption/Desorption Measurements of Cesium on Yucca 
Mountain Tuff. Submittal date: 10/21/2003. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 292 November 2003 
147156 LA9910WS831372.008. Busted Butte UZ Transport Test: Gravimetric Moisture 
Content and Bromide Concentration in Selected Phase 1A Rock Samples. Submittal 
date: 11/03/1999. 
156586 LA9912WS831372.001. Sorption of Fluorinated Benzoic Acids and Lithium on 
Rock Samples Form Busted Butte, NV. Submittal date: 02/22/2000. 
159525 LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed from 
Field Data. Submittal date: 05/14/2002. 
159672 LB0207REVUZPRP.002. Matrix Properties for UZ Model Layers Developed from 
Field and Laboratory Data. Submittal date: 07/15/2002. 
161243 LB0208UZDSCPMI.002. Drift-Scale Calibrated Property Sets: Mean Infiltration 
Data Summary. Submittal date: 08/26/2002. 
160799 LB0210THRMLPRP.001. Thermal Properties of UZ Model Layers: Data Summary. 
Submittal date: 10/25/2002. 
162379 LB03013DSSCP3I.001. 3-D Site Scale Calibrated Properties: Data Summaries. 
Submittal date: 01/27/2003. 
162130 LB0301N3SURDAT.001. Niche 3107 Measurements and Elevations Used for Grid 
Generation. Submittal date: 01/29/2003. 
163044 LB03023DSSCP9I.001. 3-D Site Scale UZ Flow Field Simulations for 9 Infiltration 
Scenarios. Submittal date: 02/28/2003. 
162570 LB0303A8N3LIQR.001. Alcove 8 - Niche 3 Seepage Data Compilation. Submittal 
date: 03/19/2003. 
162773 LB0303A8N3MDLG.001. Alcove 8 - Niche 3 Seepage Modeling: Simulations. 
Submittal date: 03/31/2003. 
165992 LB0304RDTRNSNS.001. Supporting Files of 3D Flow and Transport Sensitivity 
Analyses. Submittal date: 04/29/2003. 
165172 LB0308AMRU0185.001. Section 6.3.2 Matrix Block Discretization and its Effects 
on UZ Flow and Transport Simulations. Submittal date: 08/29/2003. 
166225 LB03093RADTRNS.001. Three Way Transport Model Comparison: Input/Output 
Files. Submittal date: 09/24/2003. 
166071 LB03093RADTRNS.002. Three Way Transport Model Comparison: Data 
Summaries. Submittal date: 09/24/2003. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 293 November 2003 
136593 LB980901233124.101. Pneumatic Pressure and Air Permeability Data from Niche 
3107 and Niche 4788 in the ESF from Chapter 2 of Report SP33PBM4: Fracture 
Flow and Seepage Testing in the ESF, FY98. Submittal date: 11/23/1999. 
106787 LB990501233129.001. Fracture Properties for the UZ Model Grids and Uncalibrated 
Fracture and Matrix Properties for the UZ Model Layers for AMR U0090, Analysis 
of Hydrologic Properties Data. Submittal date: 08/25/1999. 
106785 LB990701233129.001. 3-D UZ Model Grids for Calculation of Flow Fields for PA 
for AMR U0000, Development of Numerical Grids for UZ Flow and Transport 
Modeling. Submittal date: 09/24/1999. 
110226 LB990861233129.001. Drift Scale Calibrated 1-D Property Set, FY99. Submittal 
date: 08/06/1999. 
164858 LB991220140160.010. Model Prediction of Busted Butte Using T2R3D Input and 
Output Files. AMR U0060, Radionuclide Transport Models Under Ambient 
Conditions.. Submittal date: 03/14/2000. 
104055 LB997141233129.001. Calibrated Basecase Infiltration 1-D Parameter Set for the 
UZ Flow and Transport Model, FY99. Submittal date: 07/21/1999. 
151523 MO0007MAJIONPH.010. Major Ion Content of Groundwater from Borehole UE-25 
P #1 Extracted from ANL-NBS-HS-000021, Geochemical and Isotopic Constraints 
on Groundwater Flow Directions, Mixing and Recharge at Yucca Mountain, Nevada. 
Submittal date: 07/27/2000. 
151530 MO0007MAJIONPH.013. Major Ion Content of Groundwater from Selected YMP 
and Other Boreholes Extracted from ANL-NBS-HS-000021, Geochemical and 
Isotopic Constraints on Groundwater Flow Directions, Mixing and Recharge at 
Yucca Mountain, Nevada. Submittal date: 07/27/2000. 
164527 MO0307SEPFEPS4.000. LA FEP List. Submittal date: 07/31/2003. 
119199 MO9910MWDISMMM.003. ISM3.1 Mineralogic Models. Submittal date: 
10/01/1999. 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LA0302AM831341.002. Unsaturated Zone Distribution Coefficients (KDS) For U, NP, PU, 
AM, PA, CS, SR, RA, AND TH. Submittal date: 02/04/2003. 
LA0311AM831341.001. Correlation Matrix for Sampling of Sorption Coefficient Probability 
Distributions. Submittal date: 11/06/2003. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 294 November 2003 
LB0307MR0060R1.001. Ambient Radionuclide Transport  Uniform Instantaneous Release. 
Submittal date: 07/19/2003. 
LB0307MR0060R1.002. Ambient Radionuclide Transport  Uniform Instantaneous Release. 
Submittal date: 07/19/2003. 
LB0307MR0060R1.003. Ambient Radionuclide Transport  Uniform Continuous Release. 
Submittal date: 07/19/2003. 
LB0307MR0060R1.004. Ambient Radionuclide Transport  Uniform Continuous Release. 
Submittal date: 07/19/2003. 
LB0307MR0060R1.005. Ambient Radionuclide Transport - Unfaulted Domain, Instantaneous 
and Continuous Release. Submittal date: 07/19/2003. 
LB0307MR0060R1.006. Ambient Radionuclide Transport - Unfaulted Domain, Instantaneous 
and Continuous Release. Submittal date: 07/19/2003. 
LB0307MR0060R1.007. Ambient Radionuclide Transport  TSPA Deliverable Extractions. 
Submittal date: 07/19/2003. 
LB0308MR0060R1.008. Ambient Radionuclide Transport  Model Validation: Simulations. 
Submittal date: 08/29/2003. 
LB0308MR0060R1.009. Ambient Radionuclide Transport  Model Validation: Data 
Summaries. Submittal date: 08/29/2003. 
LB0310MR0060R1.010. Supplemental Radionuclide Transport Simulations: Input/Output files. 
Submittal date: 10/23/2003. 
LB0310MR0060R1.011. Supplemental Radionuclide Transport Simulations: Data Summaries. 
Submittal date: 10/23/2003. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-1 November 2003 
ATTACHMENT I 
TECHNICAL BASIS FOR Kd PROBABILITY DISTRIBUTION FUNCTIONS 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-3 November 2003 
FIGURES 
Page 
I-1. Americium Sorption Coefficients on Devitrified Tuff versus Calculated Final Cesium 
Concentration in Solution ............................................................................................I-18 
I-2. Americium Sorption Coefficients for Devitrified Tuff as a Function of Experiment 
Duration .......................................................................................................................I-19 
I-3. Americium Sorption Coefficients on Devitrified Tuff Versus pH of J-13 Water...............I-20 
I-4a. Americium Sorption Coefficients on Quartz from Beall et al. (1986 [162983]) and 
Model Fit......................................................................................................................I-21 
I-4b. Americium Sorption Coefficients on Zeolitic Tuff versus Calculated Final 
Americium Concentration in Solution .........................................................................I-22 
I-5. Americium Sorption Coefficients for Zeolitic Tuff as Function of Duration of 
Sorption and Desorption Experiments .........................................................................I-23 
I-6. Americium Sorption Coefficient Data and Modeling Results for Zeolitic Tuff as a 
Function of pH .............................................................................................................I-24 
I-7. Americium Sorption Coefficients on Vitric Tuff versus Calculated Final Americium 
Concentration in Solution ............................................................................................I-25 
I-8. Americium Sorption Coefficient Data and Modeling Results for Vitric Tuff as a 
Function of pH .............................................................................................................I-25 
I-9. Cesium Sorption Coefficients on Devitrified Tuff versus Calculated Final Cesium 
Concentration in Solution ............................................................................................I-27 
I-10. Freundlich Isotherm Fit to Sorption Coefficient Data for Cesium on Devitrified Tuff 
Sample G1-2840 in J-13 Water....................................................................................I-28 
I-11. Cesium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-28 
I-12. Cesium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Cesium 
Concentration in Solution ............................................................................................I-29 
I-13. Freundlich Isotherm Fit to Sorption Coefficient Data for Sample YM-38 in J-13 
Water...........................................................................................................................I-29 
I-14. Cesium Sorption Coefficients on Zeolitic Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-30 
I-15. Cesium Sorption Coefficients on Vitric Tuff versus Calculated Final Cesium 
Concentration in Solution ............................................................................................I-31 
I-16. Cesium Sorption Coefficients on Vitric Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-31 
I-17. Neptunium Sorption Coefficients on Devitrified Tuff versus Calculated Final 
Neptunium Concentration in Solution .........................................................................I-33 
I-18. Neptunium Sorption Coefficients on Devitrified Tuff versus Calculated Final 
Neptunium Concentration in Solution. Experiments oversaturated with Np2O5 
have been omitted. .......................................................................................................I-34 
I-19. Neptunium Sorption Coefficient on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments. Experiments 
oversaturated with Np2O5 have been omitted. .............................................................I-34 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-4 November 2003 
FIGURES 
Page 
I-20. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 
versus Solution pH in Sorption (Forward) and Desorption (Backward) 
Experiments. PHREEQC model results for J-13 and p#1 waters also plotted ............I-35 
I-21. Neptunium Sorption Coefficients on Zeolitic Tuff versus Calculated Final 
Neptunium Concentration in Solution .........................................................................I-36 
I-22. Neptunium Sorption Coefficients on Zeolitic Tuff versus Calculated Final 
Neptunium Concentration in Solution. Oversaturated experiments have been 
removed........................................................................................................................I-36 
I-23. Neptunium Sorption Coefficient on Zeolitic Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments. Oversaturated 
experiments have been omitted....................................................................................I-37 
I-24. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 
versus Solution pH in Sorption (Forward) and Desorption (Backward) 
Experiments. Oversaturated experiments have been omitted. ....................................I-38 
I-25. Neptunium Sorption Coefficients on Vitric Tuff versus Calculated Final Neptunium 
Concentration in Solution. Oversaturated experiments have been omitted................I-39 
I-26. Neptunium Sorption Coefficient on Vitric Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments. Oversaturated 
experiments have been omitted....................................................................................I-39 
I-27. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 
versus Solution pH in Sorption (Forward) and Desorption (Backward) 
Experiments. Oversaturated experiments have been omitted. ....................................I-40 
I-28. Plutonium Sorption Coefficients on Devitrified Tuff versus Calculated Final 
Plutonium Concentration in Solution...........................................................................I-41 
I-29. Plutonium Sorption Coefficient versus Calculated Final Plutonium Solution 
Concentration in Moles/Liter for Experiments with Samples YM-22 and G4-272.....I-42 
I-30. Plutonium Sorption Coefficient on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-43 
I-31. Plutonium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus 
Solution pH in Sorption (Forward) and Desorption (Backward) Experiments. 
Experiments lasting 40 days or more are plotted separately from experiments 
lasting less than 40 days...............................................................................................I-43 
I-32. Plutonium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus 
Solution pH in Sorption (Forward) and Desorption (Backward) Experiments with 
Durations Greater than 40 Days...................................................................................I-44 
I-33. Plutonium Sorption Coefficients versus Eh as Predicted by PHREEQC V2.3 Model. 
Separate curves are shown for different pH values. ....................................................I-45 
I-34. Plutonium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Plutonium 
Concentration in Solution ............................................................................................I-47 
I-35. Plutonium Sorption Coefficient on Zeolitic Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-48 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-5 November 2003 
FIGURES 
Page 
I-36. Plutonium Sorption Coefficient on Zeolitic Tuff in J-13 and Synthetic p#1 versus 
Solution pH in Sorption (Forward) and Desorption (Backward) Experiments with 
Durations Greater than 40 Days...................................................................................I-48 
I-37. Plutonium Sorption Coefficients on Vitric Tuff versus Calculated Final Plutonium 
Concentration in Solution ............................................................................................I-49 
I-38. Plutonium Sorption Coefficient on Vitric Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-50 
I-39. Plutonium Sorption Coefficient on Vitric Tuff in J-13 and Synthetic p#1 versus 
Solution pH in Sorption (Forward) and Desorption (Backward) Experiments with 
Durations Greater than 40 Days...................................................................................I-51 
I-40. Protactinium Sorption Coefficients vs. pH .......................................................................I-52 
I-41. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Calculated 
Final Barium or Radium Concentrations in Solution ..................................................I-54 
I-42. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Experiment 
Duration for Sorption (Forward) and Desorption (Backward) Experiments ...............I-55 
I-43. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Experiment 
Duration for Sorption (Forward) and Desorption (Backward) Experiments ...............I-56 
I-44. Barium and Radium Sorption Coefficients on Zeolitic Tuff versus Calculated Final 
Barium or Radium Concentrations in Solution............................................................I-57 
I-45. Isotherm Diagram for Ba Sorption on Zeolitic Tuff YM-38 in J-13 Water......................I-57 
I-46. Barium and Radium Sorption Coefficient on Zeolitic Tuff in J-13 versus Experiment 
Duration for Sorption (Forward) and Desorption (Backward) Experiments ...............I-58 
I-47. Barium and Radium Sorption Coefficients on Vitric Tuff versus Calculated Final 
Barium or Radium Concentrations in Solution............................................................I-59 
I-48. Barium and Radium Sorption Coefficient on Vitric Tuff versus Experiment Duration 
for Sorption (Forward) and Desorption (Backward) Experiments ..............................I-59 
I-49. Strontium Sorption Coefficients on Devitrified Tuff versus Calculated Final 
Strontium Concentration in Solution ...........................................................................I-61 
I-50. Strontium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments. Data points 
include experiments in which fines were not removed from sample...........................I-62 
I-51. Strontium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments. Fines fraction 
removed from all experiments. ....................................................................................I-63 
I-52. Strontium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Strontium 
Concentration in Solution ............................................................................................I-64 
I-53. Strontium Sorption Coefficients versus Calculated Final Solution Concentration in 
M/L for Sample YM-38 in J-13 Water ........................................................................I-65 
I-54. Strontium Sorption Coefficients on Zeolitic Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-65 
I-55. Strontium Sorption Coefficients on Zeolitic Tuff with Fine Fraction Removed versus 
Experiment Duration for Sorption (Forward) and Desorption (Backward) 
Experiments .................................................................................................................I-66 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-6 November 2003 
FIGURES 
Page 
I-56. Strontium Sorption Coefficients on Vitric Tuff versus Calculated Final Strontium 
Concentration in Solution ............................................................................................I-67 
I-57. Strontium Sorption Coefficients on Vitric Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-67 
I-58. Thorium Sorption Coefficients on Tuff versus Calculated Final Thorium 
Concentration in Solution ............................................................................................I-69 
I-59. Thorium Sorption Coefficients on Tuff Versus pH ..........................................................I-70 
I-60. Uranium Sorption Coefficients on Devitrified Tuff Versus Calculated Final 
Uranium Concentration in Solution .............................................................................I-71 
I-61. Uranium Sorption Coefficients on Devitrified Tuff Versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments....................................I-72 
I-62. Uranium Sorption Coefficients on Devitrified Tuff versus pH. Model curves are 
from the PHREEQC Surface Complexation Model. ...................................................I-73 
I-63. Uranium Sorption Coefficients on Devitrified Tuff in p#1 Water versus pH. Model 
curve is from the PHREEQC Surface Complexation Model.......................................I-73 
I-64. Uranium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Uranium 
Concentration in Solution ............................................................................................I-74 
I-65. Uranium Sorption Coefficients on Zeolitic Tuff as a Function of Experiment 
Duration .......................................................................................................................I-75 
I-66. Uranium Sorption Coefficients for Zeolitic Tuff in J-13 Plotted as a Function of pH. 
Model curves derived with PHREEQC surface complexation modeling are also 
shown. ..........................................................................................................................I-76 
I-67. Uranium Sorption Coefficients for Zeolitic Tuff in Synthetic p#1 Plotted as a 
Function of pH. Model curves derived with PHREEQC surface complexation 
modeling are also shown..............................................................................................I-76 
I-68. Uranium Sorption Coefficients on Vitric Tuff versus Calculated Final Uranium 
Concentration in Solution ............................................................................................I-77 
I-69. Uranium Sorption Coefficients on Vitric Tuff as a Function of Experiment Duration ....I-78 
I-70. Uranium Sorption Coefficients for Vitric Tuff in J-13 Plotted as a Function of pH. 
Model curves derived with PHREEQC surface complexation modeling are also 
shown. ..........................................................................................................................I-79 
I-71. Uranium Sorption Coefficients for Vitric Tuff in Synthetic p#1 Plotted as a Function 
of pH. Model curves derived with PHREEQC surface complexation modeling 
are also shown..............................................................................................................I-79 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-7 November 2003 
TABLES 
Page 
I-1. Surface Areas1 in m2/g for Yucca Mountain Tuffs .................................................................11 
I-2. Composition of Yucca Mountain UZ Waters ........................................................................12 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-8 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-9 November 2003 
I.1. INTRODUCTION 
This attachment provides the bases for the derivation of sorption coefficient probability 
distributions used in the unsaturated zone (UZ) transport calculations. The sorption 
coefficient data on which the distributions are based were obtained in laboratory 
experiments in which crushed rock samples from the Yucca Mountain site were contacted 
with groundwaters (or simulated groundwaters) representative of the site, spiked with one 
or more of the elements of interest. Sorption experiments have been carried out as a 
function of time, element concentration, atmospheric composition, particle size, and 
temperature. In some cases, the solids remaining from sorption experiments were contacted 
with unspiked groundwater in desorption experiments. The sorption and desorption 
experiments together provide information on the equilibration rates of the forward and 
backward sorption reactions. For elements that sorb primarily through surface 
complexation reactions, the experimental data are augmented with the results of modeling 
calculations using PHREEQC V2.3 (BSC 2001 [155323]). The inputs for the modeling 
calculations include groundwater compositions, surface areas, binding constants for the 
elements of interest, and thermodynamic data for solution species. These modeling 
calculations provide a basis for interpolation and extrapolation of the experimentally 
derived sorption coefficient dataset. 
The primary controls on sorption behavior of the elements of interest in the UZ flow 
system include the detailed characteristics of mineral surfaces in the rock units through 
which water flows from the repository to the saturated zone. They also include the detailed 
chemistry of pore waters and perched waters in the UZ along this flow path, the sorption 
behavior of each element, and the concentrations of the various radionuclides in the 
groundwaters. These parameters will be discussed in the following sections. 
This Attachment provides probability distributions for the sorption coefficient of each 
element of interest, on the three major rock types (devitrified, zeolitic, and vitric) found in 
the UZ. The influence of expected variations in water chemistry, radionuclide 
concentrations, and variations in rock surface properties within one of the major rock types 
are incorporated into these probability distributions. 
I.2. AQUIFER MATRIX COMPOSITIONS ALONG MOST PROBABLE TRANSPORT 
PATHWAYS 
Data on rock mineralogic compositions in the UZ are provided in DTN: 
MO9910MWDISMMM.003 [119199]. These data have been incorporated into a site 
mineralogic model. There are three dominant rock types in the part of the UZ along 
potential flow paths from the repository to the saturated zone: devitrified tuff, zeolitic tuff, 
and vitric tuff. Devitrified tuff is composed primarily of silica (quartz and cristobalite) and 
alkali feldspar. It may also contain trace amounts of mica, hematite, calcite, tridymite, 
kaolinite, and hornblende, as well as minor amounts (<25%) of smectite and/or zeolite. For 
the purposes of this analysis, sorption coefficient distributions for devitrified tuff are based 
on data obtained on samples that are composed primarily of silica phases and feldspar with 
only trace amounts of other phases. Although devitrified tuff samples that contain 
significant amounts (> 5%) of clays or zeolites generally have higher sorption coefficients 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-10 November 2003 
than samples that do not, the distribution of these types of altered rocks along the flowpath 
is not well enough established to reliably incorporate these rock types into the sorption 
coefficient probability distributions. 
Sorption coefficient distributions for zeolitic tuff exclusively use samples that contain more 
than 50% zeolite, with the balance made up of clay, silica phases, alkali feldspar, and/or 
glass. For vitric tuffs, sorption coefficient distributions are based on samples that contain 
more than 50% glass, with the remainder made up predominantly of feldspar, silica phases, 
zeolites, and clay. 
The total number of samples for each rock type used in the analysis in this section included 
38 devitrified tuffs, 34 zeolitic tuffs, and 7 vitric tuffs. Not all of these samples were 
obtained from the UZ. Nonetheless, these samples as a whole are taken to be 
representative of devitrified, zeolitic, and vitric tuffs in the Yucca Mountain UZ. 
As explained below, surface areas for the tuffs are inputs to PHREEQC V2.3 (BSC 2001 
[155323]) calculations. Triay et al. (1996 [101023], p. 62) presented surface-area analyses 
for 23 tuff samples. A table of the analyses with averages (omitting these outlying 
samples) is presented in Table I-1. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-11 November 2003 
Table I-1. Surface Areas1 in m2/g for Yucca Mountain Tuffs 
Not Ground Dry-sieved2 Wet sieved2 
With J-13 water 
trial #1 
Wet sieved2 
With J-13 water 
trial #2 
Wet sieved2 
With UE-25 p#1 
water 
USW G1-732 Devitrified 2.1 2.7 2.6 2.5 3.3 
USW G1-1936 Devitrified 4.5 4.9 3.6 3.9 3.7 
USW G4-270 Devitrified 2.0 6.4 5.1 5.0 
USW G4-275 Devitrified 2.9 4.5 
USW G4-2570 Devitrified 2.8 3.6 2.9 2.9 2.8 
USW GU3-747 Devitrified 2.2 2.9 2.8 2.4 2.8 
USW GU3-2325 Devitrified 1.8 2.5 2.2 1.8 2.5 
Average 2.6 3.9 3.2 2.7 3.4 
USW G1-1405 Zeolitic 32 28 26 31 
USW G2-1813 Zeolitic 34 
USW G2-1951 Zeolitic 66 
USW GU3-1992 Zeolitic 32 
USW G4-1506 Zeolitic 22 30 27 25 
USW G4-1529 Zeolitic 37 21 22 31 
USW G4-1530 Zeolitic 40 41 
USW G4-1625 Zeolitic 28 27 28 33 
USW G4-1772 Zeolitic 23 22 23 23 23 
USW G4-2077 Zeolitic 19 18 
Average 28.7 26.7 32.3 23 28.6 
USW G2-767 Vitric 0.89 1.1 0.62 0.71 0.87 
USW GU3-1249 Vitric 0.52 0.92 0.99 0.87 
USW GU3-1407 Vitric 1.7 3.3 3.0 3.2 
Average 1.0 1.8 1.5 0.71 1.6 
Source: Triay et al. (1996 [101023], pp. 5, 6, 8, 62, and Appendix C) 
NOTE: 1 BET method 
2 75-500 m fraction 
I.3. RADIONUCLIDES OF INTEREST AND THEIR POTENTIAL 
CONCENTRATION RANGES IN TRANSPORT SYSTEM 
The list of radionuclides for which sorption coefficient data are required was derived in 
Radionuclide Screening (BSC 2002 [160059], Table 10). The list includes isotopes of Am, 
Cs, Np, Pa, Pu, Ra, Sr, Th, and U. Because different isotopes of a given (heavy) element 
behave the same in chemical reactions, this discussion will focus on this list of elements. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-12 November 2003 
Sorption coefficients for the radionuclides of interest can be a function of the 
concentrations of the radionuclides present in solution. Thus, experiments have been 
carried out as a function of radionuclide concentrations for most of the elements of interest. 
In most cases, experiments were carried out over a range of concentrations up to a 
solubility limit. Above the solubility limit, a solid phase incorporating the element of 
interest is precipitated out of solution. Therefore, the concentration of an element in 
solution cannot rise much higher than the solubility limit. Experiments in which the final 
solution concentrations for a given element of interest exceeded the solubility limit are not 
useful in this analysis and will be rejected. 
Because experiments have been carried out at concentrations up to the solubility limit for 
most elements of interest, the experimental results and the probability distributions derived 
from them include this dependency. The only element for which the experimental 
concentrations did not approach a solubility limit was Cs. The solubility of cesium 
compounds is very high in Yucca Mountain waters (BSC 2001 [163152], Section 6.17). 
Thus, the sorption coefficient probability distributions for cesium must be calibrated to the 
Cs concentrations expected in the UZ. 
I.4. WATER COMPOSITIONAL RANGES ALONG TRANSPORT PATHWAYS 
The chemistry of pore waters and perched waters in the UZ along potenial flowpaths to the 
accessible environment is discussed in the Analysis of Geochemical Data for the 
Unsaturated Zone (BSC 2002 [160247]). In the UZ, two rather distinct water types exist in 
the ambient system. One is perched water and the other is pore water. Perched water is 
generally more dilute than pore water. 
Table I-2. Composition of Yucca Mountain UZ Waters 
Element Units J-13b Range of 
concentrations in 
perched watersc 
Range of concentrations 
in pore waters within 
and below repository 
horizond 
UE 25 p#1 
Carbonate 
aquifera 
Synthetic 
p#1 
Ca mg/L 12 2.945 0.391.8 100 
Mg mg/L 2.1 04.1 024.6 39 
Na mg/L 42 3498 3207 150 261 
K mg/L 5 3.65.8 1.4148.7 12 
SiO2 mg/L 57 7.764 5352 41 
Cl mg/L 7.1 4.116 6130 28 
SO4 mg/L 17 4223 6101.1 160 
HCO3 mg/L 124 112197 8384 694 691 
pH 7.2 7.68.7 6.79.7 6.6 
SOURCE: aDTN: MO0007MAJIONPH.010 [151523] 
bDTN: MO0007MAJIONPH.013 [151530] 
cDTN: GS951208312272.004 [165858] 
dDTN: GS010708312272.002 [156375]; GS011008312272.004 [165859]; 
GS990208312272.001 [146134]; GS010608312272.001 [165860]; 
GS000608312271.001 [153407] 

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MDL-NBS-HS-000008 REV 01 Attachment I-13 November 2003 
The J-13 and UE p#1 waters were used in sorption experiments as end-member 
compositions intended to bracket the impact of water composition on sorption coefficients. 
Because water from the UE p#1 well was not available to the experimental program at all 
times, a synthetic p#1 water was developed. This water (Table I-2) was primarily intended 
to have a bicarbonate concentration similar to that found in UE p#1. It was used primarily 
in experiments with uranium, neptunium, and plutonium because the solution and sorption 
behavior of these elements is sensitive to the bicarbonate and carbonate concentrations in 
solution. 
I.5. EXPERIMENTAL TECHNIQUES 
Most of the experimental data upon which the conclusions of this section are based were 
obtained at Los Alamos National Laboratories over a period of 25 years. Over this time 
period, there were minor changes in the experimental techniques used to obtain sorption 
coefficient data. However, the main technique was developed early on and was maintained 
through most of the 25-year time frame. 
It is the intent of this section to provide an overview of the experimental techniques used to 
obtain sorption coefficients. The details of the various techniques used (e.g., radioactivity 
counting techniques) are provided in the quality assurance procedures developed for this 
purpose. These procedures can be obtained from the YMP. 
The basic technique for the laboratory determination of sorption coefficients involved the 
contact of a groundwater sample, spiked with the radionuclide of interest, with a crushed 
sample of tuff or alluvium. The rock sample was generally obtained as a core sample. The 
rock and water samples were not sterilized and therefore contain representative microbial 
biota from the UZ. The rock was crushed in a jaw crusher and subsequently sieved to a 
selected grain-size fraction. The sieving process was usually carried out under water. 
Initially, several different grain-size fractions were used in the experiments. With 
experience, it was concluded that the 75500 m fraction was the most appropriate for use 
in these types of experiments. Results for samples which included all sizes below a certain 
grain size (e.g., <35 m) tended to produce higher sorption coefficient values than the 75 
500 m fraction. This was thought to result from increased surface area, the creation of 
active surface sites, or mineral fractionation. Because the tuffs are very fine grained (i.e., 
crystal sizes on the order of 1020 m), crushing would not produce significant increases 
in mineral surface area. The idea that active sites were created by crushing the rock 
samples was negated by analysis of sorption coefficients over a range of grain sizes from a 
single rock sample. This analysis (Rogers and Meijer 1993 [123127], pp. 15111512) 
showed that different size fractions do not necessarily produce different sorption coefficient 
values. This was thought to reflect the very fine-grained nature of the tuffs. Mineral 
fractionation is the process by which certain minerals such as clays become enriched in a 
very fine-grain-size fraction. This is the most likely explanation for the higher sorption 
coefficients obtained in experiments that included fines. 
One gram of crushed rock material was added to a test tube with 20 mL groundwater 
spiked with the radionuclide(s) of interest. The test tube was put on a shaker table for a 
pre-determined period to allow reaction to occur. After the predetermined time had passed, 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-14 November 2003 
the solution was separated from the solid phase by either centrifugation or filtration. 
Centrifugation was preferred for those elements thought to have an affinity for the filter 
medium. The separations were not always perfect, due to various experimental constraints. 
In some cases, the solid fraction was separately counted. A sorption coefficient was 
usually calculated from the difference between the initial and final solution concentrations. 
Corrections were generally made for sorption onto the surface of the test tube during the 
equilibration (shaking) period. 
Some potential sources of errors and experimental artifacts that may pertain to the sorption 
coefficients obtained at Los Alamos include weighing errors, counting errors, errors 
resulting from solutions being oversaturated with the element of interest, errors from 
imperfect solid/liquid separations, errors from inaccurate correction for sorption onto 
container walls, recording errors, transcription errors, inadvertent laboratory errors, and 
calculation errors. These errors cannot be quantitatively assessed. However, their 
existence will become apparent in the scatter of the data on diagrams presented in a later 
section. 
I.6. APPROACH TO THE DERIVATION OF Kd RANGES FOR MAJOR ROCK 
TYPES IN THE YUCCA MOUNTAIN FLOW SYSTEM. 
The derivation of sorption coefficient probability distributions for the elements of interest 
on the major rock types in Yucca Mountain involves both an evaluation of available 
experimental data and sorption modeling. Experimental data will be used to evaluate the 
impact of variations in rock sorption properties within each of the rock types, radionuclide 
concentrations, sorption kinetics, and water chemistry on sorption coefficients for the 
elements of interest. 
The radionuclides of interest are divided into three groups of radioelements. For the first 
group, including Am, Np, Pa, Pu, Th and U, experimental data is used to evaluate the 
impact of radionuclide concentrations, sorption kinetics, and variations in water chemistry 
on sorption coefficients. Surface complexation modeling is used to further evaluate the 
impact of variations in water chemistry and surface area on sorption coefficients. The 
surface complexation models used in this analysis are based on the code PHREEQC V2.3 
(BSC 2001 [155323]). The binding constants required for surface complexation modeling 
are either obtained from the literature or derived from experimental data involving sorption 
of the radioelement on quartz (see discussion in Section I.7). 
In the second group of elements, including Cs, Pa, Ra, and Sr, the ranges of sorption 
coefficient values for the major rock types are derived directly from the available 
experimental data and the ranges for environmental variables expected in the transport 
system. Although it would be preferable to have a theoretical model to evaluate /the 
impact of variations in water chemistry and rock chemistry on sorption coefficients for 
these radionuclides, sufficient data are not available to properly constrain such a model. 
For the third group, including carbon, iodine, and technetium, the sorption coefficient is set 
to zero in volcanic rocks and in alluvium. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-15 November 2003 
I.7. SURFACE COMPLEXATION MODELING 
The PHREEQC surface complexation model used in this analysis is a nonelectrostatic 
model (Parkhurst 1995 [142177], p. 1011). Inputs required for modeling include 
deprotonation constants, binding constants for elements of interest, total site concentration, 
water chemistry, and a thermodynamic database for solution species and solids. Because 
the tuffs contain up to 80 weight percent silica (Broxton et al. 1986 [100023], p. 39), a 
silica surface was used to represent the mineral surfaces in the tuffs. The surface 
complexation models included the effects of competition from common constituents in the 
rock such as Ca, Mg, Na, K, and Al. Deprotonation constants for silica were obtained from 
Dixit and Van Cappellen (2002 [162985], p. 2565). Binding constants were obtained from 
Dixit and Van Cappellen (2002 [162985], p. 2565) for aluminum on silica, from Triay et al. 
(1996 [100422], Table 22) for potassium and calcium on silica, and from Marmier et al. 
(1999 [162986], p. 228) for sodium on silica (the same value was used for potassium). The 
total site concentrations were obtained from surface areas reported in Triay et al. (1996 
[101023], p. 62) and a site density of 2.3 sites/nm2 as recommended by Pabalan et al. (1998 
[162987], p. 124). The thermodynamic database used for the modeling was the 
LLNL.DAT database supplied with the baselined YMP version (V2.3; STN: 10068-2.3-00 
[155323]) of the PHREEQC code. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-16 November 2003 
I.8. DISCUSSION AND ANALYSIS OF EXPERIMENTAL SORPTION COEFFICIENT 
DATA AND SURFACE COMPLEXATION MODELING 
The data and modeling results for each element are discussed in separate sections. The 
sections are arranged in alphabetical order as follows: 
A. AMERICIUM 
B. CESIUM 
C. NEPTUNIUM 
D. PLUTONIUM 
E. PROTACTINIUM 
F. RADIUM 
G. STRONTIUM 
H. THORIUM 
I. URANIUM 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-17 November 2003 
I.8.A. AMERICIUM 
According to Nitsche et al. (1993 [155218], p. 78, 86), the solubility of americium in J-13 water 
is controlled by Am(OH)CO3. At pH = 8.5, the solubility is 2.4 (+/-1.9)  10-9 moles/Liter at 
25C. At pH = 7.0, the solubility is 1.2 (+/-0.3)  10-9 moles/Liter at 25C. 
Devitrified Tuff 
Sorption coefficients measured on devitrified tuffs are plotted versus calculated final solution 
concentrations in Figure I-1. The points identified by the term sorption refer to experiments in 
which J-13 water spiked with americium was contacted with devitrified tuff. The points 
identified by the term desorption refer to experiments in which the solid remaining after the 
sorption step was contacted with unspiked J-13. The steep negative slopes evident at the higher 
concentrations for individual samples reflect a mass-balance constraint. That is, the final 
solution concentration is calculated using the starting solution concentration and the measured 
sorption coefficient. This forces a linear dependence of the sorption coefficient on the final 
solution concentration. The offset between the points for the various samples primarily reflects 
different starting concentrations. 
The position of a sample along a slope reflects the degree of equilibration among various 
experiments on the same sample with the same starting concentration. When the sorption 
experiments are initiated, these trends start on the abscissa at the initial concentration. As 
experiment duration is increased, americium is sorbed to the solid phase, the solution 
concentration decreases correspondingly, and the Kd increases. At equilibrium, the solution 
concentration remains constant with time, and the Kd is at a maximum value. For desorption 
experiments, the trend is reversed. As the duration of a desorption experiment increases, the 
solution concentrations increase as americium is released from the solid, and the Kd decreases. 
At equilibrium, the Kd obtained from a desorption experiment should approach the Kd value 
obtained from the associated sorption experiment, unless the isotherm is quite nonlinear (in 
which case the trends could be offset). The offset would be caused by a different total 
americium concentration in the sorption and desorption experiments. The Kd value on which the 
two trends converge is considered the equilibrium value. 
As shown in Figure I-1, the calculated final solution concentrations were higher than the 
solubility of Am(OH)CO3 in numerous experiments with samples JA-32 and YM-54. Thus, the 
results for these experiments must be discounted. For the remaining experiments, the sorption 
coefficients range from 1,000 to more than 10,000 mL/g. In one sample (GU3-688), americium 
concentrations were analyzed by isotope dilution mass spectrometry (Triay et al. 1991 [104129], 
p. 144). This technique has higher sensitivity than the (radioactivity) counting techniques 
normally used, thereby allowing the use of lower americium concentrations. The result obtained 
for this sample is in the range of the results obtained for the other samples. 
The sorption coefficients derived from desorption experiments are generally larger than those 
derived from the sorption experiments on a given sample (Figure I-1). This could result from 
slow desorption kinetics or a nonlinear isotherm. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-18 November 2003 
Americium sorption coefficients are plotted versus duration of the sorption and desorption 
experiments in Figure I-2. The trend in the data (ignoring data from samples JA-32 and YM-54) 
suggests americium sorption coefficient values are not very sensitive to the duration of the 
experiments except in those experiments with very short durations. Thus, the kinetics of the 
americium sorption reactions appear to be relatively fast. 
Americium on Devit. Tuff in J-13 
10 
100 
1000 
10000 
100000 
1.00E-15 1.00E-12 1.00E-09 1.00E-06 
Final Am Concentration (mol/L) 
Am Kd (mL/g) 
Sorption G1-1883 
Desorption G1-1883 
Sorption GU3-0433 
Desorption GU3-0433 
Sorption JA-32 
Desorption JA-32 
Sorption YM-22 
Desorption YM-22 
Sorption YM-54 
Desorption YM-54 
GU3-688 
DTN: LA0305AM831341.001 [163789] 
Figure I-1. Americium Sorption Coefficients on Devitrified Tuff versus Calculated Final Cesium 
Concentration in Solution 

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MDL-NBS-HS-000008 REV 01 Attachment I-19 November 2003 
Americium on Devit. Tuff in J-13 
10 
100 
1000 
10000 
100000 
0 50 100 
Experiment Duration (Days) 
Am Kd (mL/g) 
Sorption G1-1883 
Desorption G1-1883 
Sorption GU3-0433 
Desorption GU3-0433 
Sorption JA-32 
Desorption JA-32 
Sorption YM-22 
Desorption YM-22 
Sorption YM-54 
Desorption YM-54 
GU3-688 
DTN: LA0305AM831341.001 [163789] 
Figure I-2. Americium Sorption Coefficients for Devitrified Tuff as a Function of Experiment Duration 
The effects of variations in water chemistry on americium sorption coefficients have been not 
been tested experimentally except for variations in final solution pH. All the americium sorption 
and desorption experiments carried out with Yucca Mountain samples used J-13 water. 
Americium sorption and desorption coefficients in J-13 water are plotted versus pH in Figure I-3. 
It is evident that there is no clear trend among the data points plotted. The variations in sorption 
coefficients observed in multiple experiments with the same rock sample could reflect 
(radioactivity) counting statistics, long-term stability of the counting equipment, sorption 
kinetics, imperfect separation of the solid and liquid phases, and/or the consistency of adsorption 
of americium to the walls of the experimental containers. Counting statistics are generally a 
small percentage of the error in the measured sorption coefficient. Sorption kinetics may explain 
some of the scatter but not all of it. The other factors are likely significant, but they cannot be 
quantified with the available data. 

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MDL-NBS-HS-000008 REV 01 Attachment I-20 November 2003 
Americium on Devit. Tuff in J-13 
10 
100 
1000 
10000 
100000
6 7 8 9 10 
pH 
Am Kd (mL/g) 
Sorption G1-1883 
Desorption G1-1883 
Sorption GU3-0433 
Desorption GU3-0433 
Sorption JA-32 
Desorption JA-32 
Sorption YM-22 
Desorption YM-22 
Sorption YM-54 
Desorption YM-54 
GU3-688 
Model J-13 (2.8m2/g) 
Model p#1-v (2.8 m2/g) 
DTNs: LA0306AM831343.001 [164949]; LA0305AM831341.001 [163789] 
Figure I-3. Americium Sorption Coefficients on Devitrified Tuff Versus pH of J-13 Water 
To gauge the potential impact of variations in water chemistry on americium sorption 
coefficients, surface complexation modeling was carried out with PHREEQC. In the modeling, 
it was assumed all surface sites on devitrified tuff were equivalent to surface sites on silica. 
Binding constants for americium species on silica were derived by fitting data presented by Beall 
et al. (1986 [162983], p. 502) for the sorption of americium onto quartz (2.8 m2/g; Allard et al. 
1980 [104410], p. 478) in Oak Ridge National Laboratory (ORNL) Standard Water. This water 
is similar in composition to J-13. As shown in Figure I-4a, the sorption coefficients for 
americium on quartz (Beall et al. 1986 [162983], p. 502) as a function of pH could be fit very 
well using two surface reactions involving an americium sulfate complex and an americium 
carbonate complex. These reactions are listed in Table I-3. 
Table I-3. Surface Complexation Reactions for Americium 
SiOH + Am3+ + SO4
2- . SiOAmSO4 + H+ Log K = 5.5 
SiOH + Am3+ + CO3
2- . SiOAmCO3 + H+ Log K = 6.5 

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MDL-NBS-HS-000008 REV 01 Attachment I-21 November 2003 
Americium on Qtz in ORNL Water 
(Beall et al., 1986) 
1 
10 
100 
1000 
10000
3 5 7 9 
pH 
Kd (mL/g) 
Data 
Model 
DTN: LA0306AM831343.001 [164949]; LA0305AM831341.001 [163789] 
Figure I-4a. Americium Sorption Coefficients on Quartz from Beall et al. (1986 [162983]) and Model Fit 
Using a surface area of 2.8 m2/g, americium sorption coefficients were calculated for devitrified 
tuff in J-13 as a function of pH. The model curves are shown in Figure I-3. The fact that the 
model sorption coefficient for J-13 at pH = 8.5 lies in the middle of the range of experimental 
values provides confidence that the model is reasonable. The model curves move up or down 
linearly with surface area. Thus, at least part of the range of experimental values could reflect 
variations in devitrified tuff surface areas. 
The model curve shown in Figure I-3 indicates that sorption coefficients for americium will 
increase with decreasing pH in the pH range from 7.0 to 9.0. Thus, in terms of pH, the 
experimentally derived sorption coefficients are at the low end of the range of coefficients to be 
expected in the saturated zone. The effect of variation in major ion chemistry of groundwater is 
shown by the curve calculated for p#1-v groundwater. Americium sorption coefficients 
calculated using p#1-v water are similar to those calculated using J-13 water. Thus, variations in 
water chemistry are not expected to have a major impact on americium sorption coefficients. 
On the basis of the experimental data and model curves plotted in Figure I-3, the range of 
americium sorption coefficients expected for devitrified tuffs in the saturated volcanic section at 
Yucca Mountain is selected as 1,00010,000 mL/g. The probability distribution type selected is 
a truncated normal distribution. The data for JA- 32 and YM-54 were discounted in derivation of 
the distribution because the final solutions in the experiments with these samples were 
oversaturated with Am(OH)CO3. 
Zeolitic Tuff 
The measured sorption coefficients for zeolitic tuff are plotted versus calculated final solution 
concentrations in Figure I-4b. The calculated final solution concentrations were higher than the 
solubility of Am(OH)CO3 in essentially all the experiments with sample JA-18. Therefore, the 
sorption coefficients obtained for this sample are discounted in the derivation of the sorption 
coefficient probability distribution for americium on zeolitic tuff. Sorption experiments with 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-22 November 2003 
sample G4-1952 were close to saturation with Am(OH)CO3. The sorption coefficients obtained 
for this sample will be used in the derivation of the distribution. 
Am on Zeolitic Tuff 
10 
100 
1000 
10000 
100000 
1.00E-11 1.00E-10 1.00E-09 1.00E-08 1.00E-07 1.00E-06 
Final Am Concentration (mol/L) 
Am Kd (mL/g)
Sorption G2-1952 
Desorption G4-1952 
Sorption G4-1502 
Sorption YM-38 
Desorption YM-38 
Sorption YM-49 
Desorption YM-49 
Sorption JA-18 
Desorption JA-18 
DTN: LA0305AM831341.001 [163789] 
Figure I-4b. Americium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Americium 
Concentration in Solution 
Americium sorption coefficients for zeolitic tuff are plotted versus duration of the sorption and 
desorption experiments in Figure I-5. As with the devitrified tuffs, the trend in the data 
(excluding sample JA-18) suggests americium sorption coefficient values obtained in 
experiments with solutions undersaturated with Am(OH)CO3 are not very sensitive (<10X) to 
the duration of the experiments, except in those experiments with short durations (e.g., sample 
G4-1502). Thus, the kinetics of the americium sorption reactions on zeolitic tuff appear to be 
relatively fast. 
The surface complexation model developed for zeolitic tuff is similar to the model developed for 
devitrified tuff, except that a surface area of 28 m2/g was used. The model sorption coefficient at 
pH = 8.5 lies at the high end of the range of experimental values (Figure I-6). It might be 
expected that the sorption coefficients for zeolitic tuffs would be on the order of 10 times larger 
than those for devitrified tuffs to reflect the factor of 10 increase in surface area. The fact that 
the americium sorption coefficients obtained for zeolitic tuffs are not, on average, a factor of 10 
larger than those measured in devitrified tuffs suggests not all the surface area in the zeolitic tuffs 
may be accessible to americium. Alternatively, the binding sites in the interior of zeolite crystals 
may not have a high affinity for americium species. 

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MDL-NBS-HS-000008 REV 01 Attachment I-23 November 2003 
Americium on Zeolitic Tuff in J-13 
10 
100 
1000 
10000 
100000 
0 50 100 
Experiment Duration (Days) 
Am Kd (mL/g)
Sorption G4-1502 
Sorption G2-1952 
Desorption G2-1952 
Sorption JA=18 
Desorption JA-18 
Sorption YM-38 
Desorption YM-38 
Sorption YM-49 
Desorption YM-49 
DTN: LA0305AM831341.001 [163789] 
Figure I-5. Americium Sorption Coefficients for Zeolitic Tuff as Function of Duration of Sorption and 
Desorption Experiments 
As with devitrified tuff, the model curves for zeolitic tuffs shown in Figure I-6 indicate that 
sorption coefficients for americium will increase with decreasing pH in the pH range from 7.0 to 
9.0. Thus, in terms of pH, the experimentally derived sorption coefficients are at the low end of 
the range of coefficients to be expected in the unsaturated zone. The effect of variation in the 
major ion chemistry of groundwater is shown by the curve calculated for p#1 groundwater. 
Americium sorption coefficients calculated using p#1 water are similar to the coefficients 
calculated using J-13 water. 
On the basis of the experimental data and model curves plotted in Figure I-6, the range of 
americium sorption coefficients selected for zeolitic tuffs in the saturated volcanic section at 
Yucca Mountain is 1,00010,000 mL/g. The probability distribution type selected is a truncated 
normal distribution. The upper end of this distribution could have been set at 100,000 mL/g 
instead of 10,000 mL/g based on the available data and modeling results. However, the 10,000 
mL/g value is large enough to effectively keep americium from being transported over the 
regulatory time frame. In addition, by using an upper limit of 10,000 mL/g, the same distribution 
can be used for devitrified and zeolitic tuffs. The data for JA-18 were discounted in derivation of 
the distribution because the final solutions in the experiments with this sample were 
oversaturated with Am(OH)CO3. 

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MDL-NBS-HS-000008 REV 01 Attachment I-24 November 2003 
Americium on Zeolitic Tuff in J-13 
10 
100 
1000 
10000 
100000 
1000000
6.00 7.00 8.00 9.00 10.00 
pH 
Am Kd (mL/g) 
Sorption G4-1502 
Sorption G2-1952 
Desorption G2-1952 
Sorption JA=18 
Desorption JA-18 
Sorption YM-38 
Desorption YM-38 
Sorption YM-49 
Desorption YM-49 
Model J-13 (28 m2/g) 
Model p#1-v (28 m2/g) 
DTNs: LA0305AM831341.001 [163789]; LA0306AM831343.001 [164949] 
Figure I-6. Americium Sorption Coefficient Data and Modeling Results for Zeolitic Tuff as a Function of 
pH 
Vitric Tuff 
The measured sorption coefficients for vitric tuff are plotted versus calculated final solution 
concentrations in Figure I-7. The calculated final solution concentrations were close to 
Am(OH)CO3 solubility in essentially all the experiments with samples GU3-1203 and GU3- 
1301. Therefore, the sorption coefficients obtained for these samples are minimum values. 
Americium sorption experiments on vitric tuffs were all carried out for a duration of 42 days. 
Thus, there is no information available on the kinetics of the americium sorption reactions on 
vitric tuff. 
The dependence of Am sorption coefficients on water chemistry in vitric tuff will be very similar 
to the dependence calculated in devitrified tuff (Figure I-3). Thus, americium sorption 
coefficients will decrease with increasing pH. Since the sorption experiments with vitric tuffs 
were carried out at the high end of the pH range expected in the natural system, sorption 
coefficients in the natural system are expected to be larger than those experimentally observed. 

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MDL-NBS-HS-000008 REV 01 Attachment I-25 November 2003 
Am on Vitric Tuff in J-13 
100 
1000 
10000 
100000 
1000000 
1.0E-13 1.0E-12 1.0E-11 1.0E-10 1.0E-09 1.0E-08 
Calculated Final Am Concentration (mol/L) 
Am Kd (mL/g) 
Sorption G2-547 
Desorption G2-547 
Sorption G2-723 
Desorption G2-723 
Sorption GU3-1203 
Desorption GU3-1203 
Sorption GU3-1301 
Desorption GU3-1301 
DTN: LA0305AM831341.001 [163789] 
Figure I-7. Americium Sorption Coefficients on Vitric Tuff versus Calculated Final Americium 
Concentration in Solution 
Am Kd on Vitric Tuff in J-13 
100 
1000 
10000 
100000 
1000000
6.0 7.0 8.0 9.0 
pH 
Am Kd (mL/g) 
Sorption G2-547 
Desorption G2-547 
Sorption G2-723 
Sorption GU3-1203 
Desorption GU3-1203 
Sorption GU3-1301 
Desorption GU3-1301 
DTN: LA0305AM831341.001 [163789] 
Figure I-8. Americium Sorption Coefficient Data and Modeling Results for Vitric Tuff as a Function of pH 
On the basis of the experimental data plotted in Figure I-8 and the inferred pH dependence from 
Figure I-3, the americium sorption-coefficient probability distribution selected for vitric tuff is a 
cumulative distribution with a value of 100 mL/g at 0.0, 400 mL/g at 0.5, and 1,000 mL/g at 1.0. 

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MDL-NBS-HS-000008 REV 01 Attachment I-26 November 2003 
The range of values in this distribution could have been set at between 1,000 mL/g and 
1,000,000 mL/g based on the available data and modeling results. However, the lower values 
were selected to acknowledge the potential for vitric units to have smaller surface areas than 
those reported for vitric tuff in Table I-1. Surface areas of true vitrophyres are likely to be 
substantially lower than the surface areas listed in Table I-1 for vitric tuffs. The data for GU3- 
1203 and GU3-1301 were rejected in derivation of the distribution because the final solutions in 
the experiments with this sample were oversaturated with Am(OH)CO3. 

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MDL-NBS-HS-000008 REV 01 Attachment I-27 November 2003 
I.8.B CESIUM 
The solubility of cesium in J-13 water at 25C is very high. In fact, cesium concentrations in 
Yucca Mountain groundwaters will not have a solubility limitation (BSC 2001 [155455], p. 43). 
Devitrified Tuff 
Experimentally derived sorption coefficients for cesium on devitrified tuff are plotted against the 
calculated final cesium concentrations of the experiments in Figure I-9. The data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water type, and whether the sorption coefficient was determined from a 
sorption or a desorption experiment. There are also data for sorption isotherms on samples YM- 
22 and G1-2840. 
Cs on Devitrified Tuff 
1 
10 
100 
1000 
10000 
1.0E-12 1.0E-10 1.0E-08 1.0E-06 1.0E-04 1.0E-02 
Calculated Final Cs Conc. (mol/L) 
Cs Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
Old p#1 
YM-22 
Old J-13 
G1-2840 
Old J-13 
DTNs: LA0309AM831341.003 [165524]; LA0305AM831341.001 [163789] 
Figure I-9. Cesium Sorption Coefficients on Devitrified Tuff versus Calculated Final Cesium 
Concentration in Solution 
Sorption coefficients obtained in new experiments lie within the range defined by the old 
experiments at similar cesium concentrations. Although most of the sorption experiments 
resulted in Kd values greater than 100 mL/g, these experiments were carried out at cesium 
concentrations below 1.0  10-6 mol/L. At higher cesium concentrations, the Kd values obtained 
were between 10 and 100 mL/g. Nonlinear sorption isotherms were obtained for samples YM- 
22 and G1-2840 in J-13 water. The data for sample G1-2840 were fit using a Freundlich 
equation as shown in Figure I-10. Sorption coefficients obtained in experiments with p#1 water 
fall in the middle of the cluster of points in Figure I-9 near 1  10-10 mol/L. Thus, there is little 
or no impact caused by water-chemistry variations on cesium sorption coefficients in devitrified 
tuff. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-28 November 2003 
Cs on Devitrified Tuff G1-2840 in J-13 
y = 0.0024x0.7212 
1.0E-12 
1.0E-10 
1.0E-08 
1.0E-06 
1.0E-04 
1.0E-12 1.0E-10 1.0E-08 1.0E-06 1.0E-04 1.0E-02 
Calculated Final Cs Conc (mol/L) 
Cs on Solid (mol/g) 
DTN: LA0305AM831341.001 [163789] 
Figure I-10. Freundlich Isotherm Fit to Sorption Coefficient Data for Cesium on Devitrified Tuff Sample 
G1-2840 in J-13 Water 
The effects of experiment duration on the cesium sorption coefficients for devitrified tuff are 
shown in Figure I-11. The large range in sorption coefficients obtained at a given duration (e.g., 
21 days) mainly reflects variations in solution cesium concentrations, although variations in ion 
exchange capacities may also contribute to the range. The range of sorption coefficient values is 
fairly consistent with duration when the results for samples YM-22 and G1-2840 are excluded. 
This range extends from just above 100 mL/g to above 1,000 mL/g. The consistency indicates 
cesium sorption reactions are fast. 
Cs on Devitrified Tuff 
1 
10 
100 
1000 
10000
0 20 40 60 80 100 
Experiment Duration (days) 
Cs Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
Old p#1 
YM-22 
Old J-13 
G1-2840 
Old J-13 
DTNs: LA0309AM831341.003 [165524]; LA0305AM831341.001 [163789] 
Figure I-11. Cesium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The cesium sorption-coefficient probability distribution derived for devitrified tuff in the UZ is a 
uniform distribution with a range of 115 mL/g. This distribution was chosen to acknowledge 
the potential for high cesium concentrations (e.g., >10-3 mol/L) to be transported in the UZ. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-29 November 2003 
Zeolitic Tuff 
Experimentally derived sorption coefficients for cesium on zeolitic tuff are plotted against the 
calculated final cesium concentrations of the experiments in Figure I-12. The data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water type, and on whether the sorption coefficient was determined 
from a sorption or a desorption experiment. There are also data for a sorption isotherm on 
sample YM-38. 
Cs on Zeolitic Tuff in J-13 
1000 
10000 
100000 
1.00E-13 1.00E-10 1.00E-07 1.00E-04 
Calculated Final Cs Conc. (mol/L) 
Cs Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0310AM831341.001[165865] 
Figure I-12. Cesium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Cesium Concentration 
in Solution 
The range of measured cesium sorption coefficients for zeolitic tuffs is 3,500-72,000 mL/g. A 
sorption isotherm was obtained for sample YM-38 in J-13 water. As shown in Figure I-13, the 
isotherm is nearly linear. Sorption coefficients obtained in experiments with p#1 water fall at the 
lower end of the range of values obtained for experiments with J-13 water (Figure I-12). Thus, 
there is some impact from variations in water chemistry on cesium sorption coefficients in 
zeolitic tuff, although this impact is minor. 
Cs on Zeolitic Tuff YM-38 in J-13 
y = 1.8197x0.9397 
1.0E-12 
1.0E-10 
1.0E-08 
1.0E-06 
1.0E-04 
1.0E-12 1.0E-10 1.0E-08 1.0E-06 1.0E-04 
Calculated Final Cs Conc (mol/L) 
Cs on Solid (mol/g) 
DTN: LA0310AM831341.001 [165865] 
Figure I-13. Freundlich Isotherm Fit to Sorption Coefficient Data for Sample YM-38 in J-13 Water 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-30 November 2003 
The effects of experiment duration on cesium Kd for zeolitic tuff are shown in Figure I-14. The 
large range in sorption coefficients obtained at a given duration mainly reflects variations in 
cesium solution concentrations, although there must also be some contribution from variations in 
ion exchange capacities of the zeolitic tuff samples used in the experiments. The range of 
sorption coefficient values is fairly consistent with duration. For example, the range of sorption 
coefficient values for 3.6-day experiments is similar to the range for the 42-day experiments. 
This indicates the sorption reaction kinetics are fast. 
Cs on Zeolitic Tuff in J-13 
1000 
10000 
100000
0 20 40 60 80 100 
Calculated Final Cs Conc. (mol/L) 
Cs Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
Old p#1 
Desorption 
Old p#1 
YM-38 
Old J-13 
DTNs: LA0309AM831341.003 [165524]; LA0305AM831341.001 [163789] 
Figure I-14. Cesium Sorption Coefficients on Zeolitic Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The cesium sorption-coefficient probability distribution selected for zeolitic tuff in the UZ is a 
cumulative distribution, starting with a value of 425 mL/g at 0.0, 5,000 mL/g at 0.5, and 20,000 
mL/g at 1.0. The low end of this distribution was selected to acknowledge the potential for high 
cesium concentrations and lower-than-average ion exchange capacities during transport in the 
UZ. The middle value of the distribution was selected as a more representative value for cesium 
concentrations below 10-4 mol/L. The upper end of the range was selected as a minimum upper 
limit, given the potential impact of lower cesium solution concentrations and higher-thanaverage 
ion exchange capacities. 
Vitric Tuff 
Experimentally derived sorption coefficients for cesium on vitric tuff are plotted against the 
calculated final cesium concentrations of the experiments in Figure I-15. The data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water type, and on whether the sorption coefficient was determined 
from a sorption or a desorption experiment. 
Experiment Duration (Days) 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-31 November 2003 
Cs on Vitric Tuff 
10 
100 
1000 
10000
1.0E-11 1.0E-10 1.0E-09 1.0E-08 
Calculated Final Cs Conc. (mol/L) 
Cs Kd (mL/g) 
Sorption 
J-13 (New ) 
Sorption 
J-13 (Old) 
Desorption 
J-13 (Old) 
Sorption 
p#1 (Old) 
Desorption 
p#1 (Old) 
DTNs: LA0309AM831341.003 [165524]; LA0310AM831341.001[165865] 
Figure I-15. Cesium Sorption Coefficients on Vitric Tuff versus Calculated Final Cesium Concentration in 
Solution 
The range of measured cesium sorption coefficients for zeolitic tuffs is 501,000 mL/g. Sorption 
coefficients obtained in experiments with p#1 water fall at the lower end of the range of values 
obtained for experiments with J-13 water (Figure I-15). However, the p#1 experiments were 
performed with higher initial cesium solution concentrations than all the experiments performed 
with J-13 water. Thus, it is unclear to what extent water chemistry caused the sorption 
coefficients to be lower in p#1 water compared to J-13. 
The effects of experiment duration on the cesium Kd for vitric tuff are shown in Figure I-16. 
That the sorption coefficient values obtained in short-term experiments exceed those obtained in 
longer-term experiments indicates that cesium sorption reactions on vitric tuff are fast. 
Cs on Vitric Tuff in J-13 
10 
100 
1000 
10000
0 10 20 30 40 50 
Calculated Final Cs Conc. (mol/L) 
Cs Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.003 [165524]; LA0305AM831341.001 [163789] 
Figure I-16. Cesium Sorption Coefficients on Vitric Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
Experiment Duration Days 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-32 November 2003 
The cesium-sorption-coefficient probability distribution selected for vitric tuff in the UZ is a 
cumulative distribution, starting with a value of 0.0 mL/g at 0.0, rising to a value of 2.0 mL/g at 
0.5, and ending at a value of 100 mL/g at 1.0. The low-end value was selected based on the 
possibility that cesium concentrations could be high in the UZ (i.e., higher than those plotted in 
Figure I-15) and the possibility that surface areas in vitrophyric zones could be lower than those 
listed in Table I-1. The middle value was selected to represent more representative surface areas, 
high cesium concentrations, and water chemistries like p#1. The upper end of the distribution 
was chosen as a minimum upper limit, given the potential impact of lower cesium solution 
concentrations (Figure I-15), higher surface areas in ash layers, and more dilute water chemistry 
(e.g., like J-13). 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-33 November 2003 
I.8.C. NEPTUNIUM 
According to CRWMS M&O (2001 [154629], p. 19), the solubility of neptunium in J-13 water at 
25C, pH = 8.4, is 7.0  0.8  10-6 mol/L and the solubility controlling solid is Np2O5 under 
oxidizing conditions (Eh >180 mv). At pH = 7.0, the solubility is higher at 6.9  0.8  10-5 
mol/L under oxidizing conditions (Eh >250 mv). The solubility of neptunium in p#1 water at 
25C, pH = 8.5, is 2.5  0.1  10-5 mol/L, and 7.3  0.4  10-5 mol/L at 25C, pH = 7.0 according 
to CRWMS M&O (2001 [154629], p.19). Thus, the solubility of neptunium in J-13 is somewhat 
lower than it is in p#1. 
Devitrified Tuff 
The results of sorption experiments with devitrified tuff are shown in Figure I-17. Some of the 
experiments with J-13 water had final neptunium concentrations above 7.0  10-6 mol/L. Thus, 
the results for these experiments should be discounted because the experiments could have been 
oversaturated with Np2O5. All but four of the experiments with synthetic p#1 water had final 
neptunium solution concentrations of less than 2.5  10-5 mol/L. The results for the four 
experiments with over-saturated final solutions will be discounted. The remaining data points, 
plotted in Figure I-17, suggest a dependence of the sorption coefficient on the final neptunium 
solution concentration. 
Np on Devitrified Tuff 
0.01 
0.1
1 
10 
100
1E-12 1E-10 1E-08 1E-06 1E-04 
Calculated Final Np Conc. (M/l) 
Np Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
Calculated Final Np Conc. (mol/L) 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-17. Neptunium Sorption Coefficients on Devitrified Tuff versus Calculated Final Neptunium 
Concentration in Solution 
Neptunium sorption experiments carried out as a function of experiment duration are shown in 
Figure I-18. A significant difference appears between the results for old and new 
experiments, with the old results generally having higher values than the new results. The 
most straightforward explanation is that the difference is caused by the old results representing 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-34 November 2003 
experiments with longer durations than the new results. Within the old data points, the 
sorption coefficient values appear to reach a steady-state level after 42 days. 
Np on Devitrified Tuff 
0.01 
0.1
1 
10 
100
1E-12 1E-10 1E-08 1E-06 1E-04 
Np Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
Calculated Final Np Conc. (mol/L) 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-18. Neptunium Sorption Coefficients on Devitrified Tuff versus Calculated Final Neptunium 
Concentration in Solution. Experiments oversaturated with Np2O5 have been omitted. 
Np on Devitrified Tuff 
0.01 
0.1
1 
10 
100
0.1 10 1000 
Experiment Duration (days) 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-19. Neptunium Sorption Coefficient on Devitrified Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. Experiments oversaturated with Np2O5 
have been omitted. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-35 November 2003 
The impact of variations in pH on neptunium coefficients on devitrified tuffs is shown in Figure 
I-20. There is a lot of scatter in the new data, and there do not appear to be clear positive or 
negative trends among these data points. Nor does there appear to be much difference between 
the J-13 and synthetic p#1 results. The old data points are more consistent and show that the 
neptunium sorption coefficient depends very little on pH, except at pH values less than 7.0. 
PHREEQC surface complexation model curves for devitrified tuff in J-13 and in p#1 are also 
plotted. Neptunium binding constants on silica were obtained from Turner et al. (1998 [162989], 
p. 264). The J-13 curve lies between the old sorption and desorption points. This placement 
suggests that the curve may reflect the equilibrium values of neptunium sorption coefficients on 
devitrified tuff better than the experimental data. In this interpretation, the sorption data points 
reflect experiments that have not reached an equilibrium state. 
Np on Devitrified Tuff 
0.01 
0.1
1 
10 
100
6 7 8 9 10 
pH 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Model 2.8 
m2/g J-13 
Model 2.8 
m2/g p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789]; LA0306AM831343.001 [164949] 
Figure I-20. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus Solution 
pH in Sorption (Forward) and Desorption (Backward) Experiments. PHREEQC model results 
for J-13 and p#1 waters also plotted 
The neptunium sorption-coefficient probability distribution selected for devitrified tuff in the UZ 
is a cumulative distribution, starting with a value of 0.0 mL/g at 0.0, increasing to a value of 0.5 
mL/g at 0.5, and to a value of 6.0 mL/g at 1.0. The low end of the chosen range is selected based 
on the minimum value obtained in short-term experiments (up to 21 days). The upper end of the 
distribution was chosen as a minimum upper limit for a neptunium concentration near the 
solubility limit (Figure I-18), with emphasis on results from experiments with p#1 water at pH 
near 7.0. It is acknowledged that a higher limit could be selected for the upper end of the 
distribution, based on the available data and modeling results. 
Zeolitic Tuff 
Sorption coefficients on zeolitic tuff are shown as a function of calculated final solution 
concentration in Figure I-21. Many of the experiments with J-13 water had final neptunium 
concentrations above 7.0  10-6 mol/L. Thus, the results for these experiments should be 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-36 November 2003 
discounted because the experiments could have been oversaturated with Np2O5. Many of the 
experiments with synthetic p#1 water had final neptunium solution concentrations close to or 
greater than 2.5  10-5 M/L. Results for these experiments must also be discounted. 
Np on Zeolitic Tuff 
0.1
1 
10 
100 
1.E-12 1.E-10 1.E-08 1.E-06 1.E-04 1.E-02 
Calculated Final Np Conc. (M/l) 
Np Kd (ml/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
Old Sorption 
p#1 >40 Days 
Old Desorption 
p#1 >40 Days 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-21. Neptunium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Neptunium 
Concentration in Solution 
Removal of the oversaturated experiments from the dataset results in Figure I-22. With the 
oversaturated data points removed, the sorption coefficient has virtually no dependence on the 
calculated final solution concentration for J-13 experiments. However, there is clearly a 
dependence of sorption coefficient on water chemistry in the short-term experiments. If the 
solubility of neptunium in synthetic p#1 is less than the solubility in p#1, this dependence on 
water chemistry may not be real. 
Np on Zeolitic Tuff 
0.1
1 
10 
100 
1.E-12 1.E-10 1.E-08 1.E-06 1.E-04 
Calculated Final Np Conc. (mol/L) 
Np Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
Old Sorption 
p#1 >40 Days 
Old Desorption 
p#1 >40 Days 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-22. Neptunium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Neptunium 
Concentration in Solution. Oversaturated experiments have been removed. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment I-37 November 2003 
Neptunium sorption experiments carried out as a function of experiment duration are shown in 
Figure I-23. There is a significant difference between the results for old and new 
experiments, with the old results generally having higher values than the new results. The 
most straightforward explanation is that the difference is caused by the old results representing 
experiments with longer durations than the new results. Within the old data points, the 
sorption coefficient values appear to reach a steady-state level after 42 days. 
Np on Zeolitic Tuff 
0.1
1 
10 
100
0.1 10 1000 
Experiment Duration (days) 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-23. Neptunium Sorption Coefficient on Zeolitic Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. Oversaturated experiments have been 
omitted. 
The impact of variations in pH on neptunium coefficients for devitrified tuffs is shown in Figure 
I-24. There is a lot of scatter in the new data, and there do not appear to be clear positive or 
negative trends among these data points. Nor does there appear to be much difference between 
the J-13 and synthetic p#1 results. The old data points are more consistent and show that the 
neptunium sorption coefficient has very little dependence on pH, except at pH values less than 
7.0. 

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MDL-NBS-HS-000008 REV 01 Attachment I-38 November 2003 
Np on Zeolitic Tuff 
0.01 
0.1
1 
10 
100
6 7 8 9 10 
pH 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-24. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus Solution 
pH in Sorption (Forward) and Desorption (Backward) Experiments. Oversaturated 
experiments have been omitted. 
The neptunium sorption-coefficient probability distribution selected for zeolitic tuff in the UZ is 
a cumulative distribution, starting at 0.0 mL/g at 0.0, increasing to a value of 0.5 mL/g at 0.5, 
and ending at a value of 6 mL/g at 1.0. The low end of the chosen range is selected based on the 
minimum value obtained in short-term experiments (up to 21 days). The upper end of the 
distribution was chosen as a minimum upper limit for a neptunium concentration near the 
solubility limit (Figure I-21), with emphasis on results from experiments with p#1 water at pH 
near 7.0. It is acknowledged that a higher limit could be selected for the upper end of the 
distribution, based on the available data. 
Vitric Tuff 
Sorption coefficients on vitric tuff are shown as a function of calculated final solution 
concentration in Figure I-25. Many of the experiments with J-13 water had final neptunium 
concentrations above 7.0  10-6 mol/L. Thus, the results for these experiments were omitted 
from the diagram because the experiments could have been oversaturated with Np2O5. Several 
of the experiments with synthetic p#1 water had final neptunium solution concentrations close to 
or greater than 2.5  10-5 mol/L. Results for these experiments were also omitted. The 
remaining data points show a clear dependence on final neptunium solution concentration. 

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MDL-NBS-HS-000008 REV 01 Attachment I-39 November 2003 
Np on Vitric Tuff 
0.01 
0.1
1 
10 
100 
1.E-12 1.E-10 1.E-08 1.E-06 1.E-04 
Calculated Final Np Conc. (mol/L) 
Np Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
Old Sorption 
p#1 >40 Days 
Old Desorption 
p#1 >40 Days 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-25. Neptunium Sorption Coefficients on Vitric Tuff versus Calculated Final Neptunium 
Concentration in Solution. Oversaturated experiments have been omitted. 
Neptunium sorption experiments carried out as a function of experiment duration are shown in 
Figure I-26. There is a trend of increasing sorption coefficient with increasing duration. 
Np on Vitric Tuff 
0.01 
0.1
1 
10 
100
1.0 10.0 100.0 1000.0 
Experiment Duration (days) 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-26. Neptunium Sorption Coefficient on Vitric Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. Oversaturated experiments have been 
omitted. 
The impact of variations in pH on neptunium coefficients on vitric tuffs is shown in Figure I-27. 
There is a lot of scatter in the new data and there do not appear to be clear positive or negative 
trends among these data points. Nor does there appear to be much difference between the J-13 
and synthetic p#1 results. 

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MDL-NBS-HS-000008 REV 01 Attachment I-40 November 2003 
Np on Vitric Tuff 
0.01 
0.1
1 
10 
100
6.0 7.0 8.0 9.0 10.0 
pH 
Np Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.004 [165525]; LA0305AM831341.001 [163789] 
Figure I-27. Neptunium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus Solution 
pH in Sorption (Forward) and Desorption (Backward) Experiments. Oversaturated 
experiments have been omitted. 
The neptunium sorption-coefficient probability distribution selected for vitric tuff in the UZ is a 
cumulative distribution starting at 0.0 mL/g at 0.0, increasing to a value of 1.0 mL/g at 0.5, and 
ending with a value of 3.0 mL/g at 1.0. The low end of the chosen range is selected based on the 
minimum value obtained in short-term experiments (up to 21 days). The upper end of the 
distribution was chosen as a minimum upper limit for a neptunium concentration near the 
solubility limit (Figure I-25), with emphasis on results from experiments with p#1 water at pH 
near 7.0. It is acknowledged that a higher limit could be selected for the upper end of the 
distribution, based on the available data. 

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MDL-NBS-HS-000008 REV 01 Attachment I-41 November 2003 
I.8.D PLUTONIUM 
According to Nitsche et al. (1993 [155218], p. 54), the solubility of plutonium in J-13 water at 
25C, pH = 8.4, is 2.9  0.8  10-7 mol/L and is not very sensitive to pH over the range from 7.0 
to 8.4. The solubility of plutonium in p#1 water at 25C, pH = 8.5, is 1.0  0.1  10-6 mol/L, and 
4.5  0.4  10-7 mol/L at 25C, pH = 7.0 according to Nitsche et al. (1994 [155218], p. 39). 
Thus, the solubility of plutonium in J-13 is somewhat lower than it is in p#1. 
Devitrified Tuff 
The experimentally derived sorption coefficients for plutonium on devitrified tuff are plotted 
against the calculated final plutonium concentrations of the experiments in Figure I-28. The data 
points are separated into groups on the basis of when the experiments were carried out (pre-1990 
= old and post-1990 = new), water chemistry, experiment duration, and whether the sorption 
coefficient was determined from a sorption or a desorption experiment. The plotted data indicate 
that the new and old data show similar ranges of Kd values, that the longer-term experiments 
generally yield higher sorption coefficient values than the shorter term experiments, and that 
desorption experiments yield higher sorption coefficient values than sorption experiments. 
These points are discussed in greater detail below. 
Pu on Devitrified Tuff in J-13 
1 
10 
100 
1000 
10000 
1.0E-15 1.0E-13 1.0E-11 1.0E-09 1.0E-07 
Calculated Final Pu Conc. (mol/L) 
Pu Kd (mL/g) 
New Sorption 
J-13 <40 Days 
New Sorption 
J-13 >40 Days 
New Desorption 
J-13 <40 Days 
Old Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 <40 days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
New Desorption 
p#1 <40 Days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-28. Plutonium Sorption Coefficients on Devitrified Tuff versus Calculated Final Plutonium 
Concentration in Solution 
The maximum calculated final plutonium concentration plotted in Figure I-28 is slightly less 
than the solubility determined by Nitsche et al. (1993 [155218], p. 54) for plutonium in J-13. 
Thus, the plutonium sorption coefficients plotted in Figure I-28 reflect solutions that were 
undersaturated with respect to the solid plutonium phase precipitated in the experiments reported 
by Nitsche et al. (1993 [155218], p. 54). 

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MDL-NBS-HS-000008 REV 01 Attachment I-42 November 2003 
The effect of the solution plutonium concentration on the sorption coefficient value obtained is 
shown more clearly in Figure I-29. Data are plotted for two devitrified tuff samples that contain 
only trace amounts of secondary phases (e.g., clays, zeolites). In addition, plotted data are 
restricted to 21-day experiment durations and pH between 7.2 and 9.2. As is evident in the 
figure, within the errors of the analyses, the measured plutonium sorption coefficients are nearly 
independent of the final plutonium solution concentration. 
Pu on Devitrified Tuff in J-13 
(pH = 8.4; 21 Days) 
1 
10 
100 
1000 
10000 
1.0E-14 1.0E-12 1.0E-10 1.0E-08 
Calculated Final Solution Pu Conc. (M/l) 
Pu Kd (ml/g) 
Sorption 
YM-22 
Desorption 
YM-22 
Sorption 
G4-272 
Desorption 
G4-272 
(pH = 7.2-9.2; 21 Days) 
mol/L) 
mL/g) 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-29. Plutonium Sorption Coefficient versus Calculated Final Plutonium Solution Concentration in 
Moles/Liter for Experiments with Samples YM-22 and G4-272. 
The effect of experiment duration on the plutonium Kd is shown in Figure I-31. As expected, the 
Kd values for sorption experiments increase with increasing duration and the Kd values for 
desorption experiments decrease with increasing duration. However, the increase in the sorption 
values is much greater than the decrease in the desorption values over the time-frame of the 
experiments. This may reflect the reduction of plutonium +5 and/or +6 to plutonium +4 on the 
mineral surfaces present in devitrified tuff as discussed in greater detail below. The trends in the 
sorption and desorption data points suggest they would converge to values somewhere between 
100 and 1,000 mL/g. Based on the data plotted, such convergence would require more than 100 
days. Note that the old sorption data points exceeding 1,000 mL/g are for samples that contain 
significant amounts of clay or zeolite. For this reason, these data are discounted in the derivation 
of the sorption coefficient probability distribution. 

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MDL-NBS-HS-000008 REV 01 Attachment I-43 November 2003 
Pu on Devitrified Tuff in J-13 
1 
10 
100 
1000 
10000 
0 20 40 60 80 100 
Experiment Duration (days) 
Pu Kd (mL/g) 
Sorption 
New J-13 
Desorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Desorption 
p#1 New 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-30. Plutonium Sorption Coefficient on Devitrified Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The impact of variations in pH for plutonium sorption coefficients on devitrified tuffs is shown 
in Figure I-31. There is a lot of scatter in the data, and there do not appear to be clear positive or 
negative trends in any of the data groupings. 
Pu on Devitrified Tuff 
1 
10 
100 
1000 
10000
6 7 8 9 10 
pH 
Pu Kd (mL/g) 
Sorption-New 
J-13 <40 Days 
Sorption-New 
J-13 >40 Days 
Desorption-New 
J-13 
Sorption-Old 
J-13 <40 Days 
Sorption-Old 
J-13 >40 Days 
Desorption-Old 
J-13 
Sorption-New 
p#1 <40 days 
Sorption-New 
p#1 >40 days 
Desorption-New 
p#1 <40 days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-31. Plutonium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus Solution 
pH in Sorption (Forward) and Desorption (Backward) Experiments. Experiments lasting 40 
days or more are plotted separately from experiments lasting less than 40 days. 
The lack of clear trends is also evident when the results of short-term experiments (<40 days) are 
removed from the dataset. This is shown in Figure I-32, in which only the longer-term data are 
plotted. 

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Pu on Devitrified Tuff 
10 
100 
1000 
10000
6 7 8 9 10 
pH 
Pu Kd (mL/g) 
Sorption-New 
J-13 >40 Days 
Sorption-Old 
J-13 >40 Days 
Desorption-Old 
J-13 
Sorption-New 
p#1 >40 days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-32. Plutonium Sorption Coefficient on Devitrified Tuff in J-13 and Synthetic p#1 versus Solution 
pH in Sorption (Forward) and Desorption (Backward) Experiments with Durations Greater 
than 40 Days 
The impact of variations in the major ion composition of groundwaters are also shown in Figures 
I-30 through I-32. Although there is a limited set of experiments with synthetic p#1 water, the 
results are within the range of the results obtained in experiments with J-13 water. Thus, there is 
no clear evidence of the impact of water chemistry variations on plutonium sorption coefficients 
in devitrified tuff. 
A major factor not explicitly accounted for in the experimental program is the impact of 
variations in the Eh (oxidation/reduction potential normalized to the Standard Hydrogen 
Electrode) of Yucca Mountain groundwaters on plutonium sorption coefficients. The laboratory 
experiments upon which the data discussed in this section are based were invariably conducted 
under oxidizing conditions, because the waters used in the experiments contained dissolved 
oxygen and were in contact with the atmosphere. Nitsche et al. (1993 [155218], pp. 6061) 
found that plutonium dissolved in J-13 water is present predominantly in the +5 and +6 oxidation 
states. If plutonium in the +5 and +6 oxidation states behaves similarly to neptunium +5 and 
uranium +6, respectively, as has been suggested by many investigators (e.g., Keeney-Kennicutt 
and Morse 1985 [106313], pp. 25772578), then small values (<10 mL/g) would be expected for 
plutonium sorption coefficients under oxidizing conditions (see Neptunium and Uranium 
attachment sections). The fact that plutonium sorption coefficients measured under oxidizing 
conditions are up to 23 orders of magnitude larger than expected (Figure I-28) suggests that 
either plutonium +5 and +6 do not behave like neptunium +5 and uranium +6 in sorption 
reactions, or plutonium is reduced to the +4 oxidation state on rock/mineral surfaces. Data 
presented by Keeney-Kennicutt and Morse (1985 [106313], p. 2577) support the latter 
alternative. 
To further pursue the latter alternative, a PHREEQC model was developed to calculate 
plutonium sorption coefficients as a function of Eh. To develop this model, binding constants 
for neptunium +5 and uranium +6 species were used for plutonium +5 and plutonium +6 species, 

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MDL-NBS-HS-000008 REV 01 Attachment I-45 November 2003 
respectively. For plutonium +4, binding constants were derived by fitting experimental data for 
plutonium sorption on quartz in Oak Ridge Reference Water published by Allard (1982 
[104512], p. 61). This water composition has somewhat reducing characteristics, so that 
plutonium +4 would be expected to be sorbed onto the solid phase. The sorption coefficients 
calculated with this model using J-13 water are plotted as a function of Eh in Figure I-33. The 
curves plotted in Figure I-33 suggest that at Eh values less than 500 mv, plutonium is 
predominantly in the +4 oxidation state in the solution and on the solid phase. This Eh value is 
higher than the highest value measured in Yucca Mountain groundwater (Ogard and Kerrisk 
1984 [100783], pp. 10, 15; DTNs: LA0206AM831234.001 [160051]; LA0206AM831234.002 
[163852]). This implies that plutonium +4 will be the dominant oxidation state sorbed in most 
Yucca Mountain groundwaters. At higher Eh values, plutonium in solution will become 
progressively oxidized to plutonium +5 and eventually to plutonium +6. The end points of the 
curves (high Eh) plotted in Figure I-33 represent the Eh values expected when the water is in 
contact with the atmosphere. In the p#1 water composition, the lower ends of the curves are 
shifted downward somewhat to lower Kd values at a given Eh value (not shown). 
Pu on Devitrified Tuff (2.8 m2/g) in J-13 
0.1
1 
10 
100 
1000 
10000 
0 200 400 600 800 1000 
Eh (mv) 
Pu Kd (mL/g) 
pH 7.0 
pH 7.5 
pH 8.5 
DTN: LA0306AM831343.001 [164949] 
Figure I-33. Plutonium Sorption Coefficients versus Eh as Predicted by PHREEQC V2.3 Model. Separate 
curves are shown for different pH values. 
The large range in plutonium sorption coefficients measured in devitrified tuffs (e.g., Figure I- 
28) could be explained if plutonium is present in more than one oxidation state on the 
rock/mineral surfaces in the devitrified tuffs. However, in the absence of definitive data for the 

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MDL-NBS-HS-000008 REV 01 Attachment I-46 November 2003 
oxidation state of plutonium on rock/mineral surfaces, the experimentally determined sorption 
coefficient values will be used to derive the probability distributions. 
The plutonium sorption-coefficient probability distribution derived for devitrified tuff in the UZ 
is a cumulative distribution starting at 10 mL/g at 0.0, increasing to a value of 70 mL/g at 0.5, 
and ending at a value of 200 at 1.0. A cumulative distribution was chosen for the sake of 
simplicity given the limited data set for p#1 water. The low end of the chosen range is selected 
to allow for the possibility of relatively fast flow in the UZ. It also captures the potential impact 
of variations in surface areas among samples used in the experiments, variations in water 
chemistry, and variations in plutonium concentrations up to the solubility limit. The upper end 
of the distribution was chosen as a minimum upper limit given the potential impacts of sorption 
kinetics during potentially fast flow in the UZ. 
Zeolitic Tuff 
The experimentally derived sorption coefficients for plutonium on zeolitic tuff are plotted against 
the calculated final plutonium concentrations in Figure I-34. As before, the data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water chemistry, experiment duration, and whether the sorption 
coefficient was determined from a sorption or a desorption experiment. The plotted data indicate 
that there is no clear trend of plutonium Kd with solution concentration. Most of the data from 
sorption experiments plot between sorption coefficient values of 100 and 1,000 mL/g. A series 
of old experiments at concentrations between 10-7 and 10-9 M/L yielded sorption coefficient 
values less than 100 mL/g. However, the same rock type when used in newexperiments 
yielded a series of sorption coefficient values >100 mL/g. Why there is a difference of almost a 
factor of ten between these two sets of data is not known with certainty. Part of the answer lies 
in the fact that, on average, the Old data points represent shorter duration experiments than the 
new data points. However, other factors are likely involved. For example, the oxidation state 
of plutonium in the starting solution may play a part. 
As with devitrified tuffs, the plutonium sorption coefficients for zeolitic tuff plotted in Figure I- 
34 reflect solutions that were undersaturated with the plutonium phase precipitated in the Nitsche 
et al. (1993 [155218], p. 54; 1994 [144515], p. 39) experiments. 

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MDL-NBS-HS-000008 REV 01 Attachment I-47 November 2003 
Pu on Zeolitic Tuff 
1 
10 
100 
1000 
10000 
1.0E-15 1.0E-13 1.0E-11 1.0E-09 1.0E-07 
Calculated Final Pu Conc. (mol/L) 
Pu Kd (mL/g) 
New Sorption 
J-13 <40 Days 
New Sorption 
J-13 >40 Days 
New Desorption 
J-13 <40 Days 
Old Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 <40 days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
New Desorption 
p#1 <40 Days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-34. Plutonium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Plutonium 
Concentration in Solution 
The effects of experiment duration on the plutonium Kd for zeolitic tuff are shown in Figure I-35. 
As expected, the Kd values for sorption experiments increase with increasing duration and the Kd 
values for desorption experiments decrease with increasing duration, at least in short-term 
experiments. Interestingly, the decrease in longer-term desorption experiments is not very 
pronounced. The trends in the sorption and desorption data points suggest they would converge 
to values somewhere between the values of 100 and 1,000 mL/g. This is similar to the range of 
values predicted for devitrified tuffs. Thus, the higher surface areas of zeolitic tuffs compared to 
devitrified tuffs (approximately 10) do not appear to result in higher sorption values. This 
effect was also observed by Pabalan et al. (1998 [162987], p. 113) in experiments with uranium 
sorption on zeolite. The cause for the large range of values obtained at a given value for 
experiment duration is not known, but may largely result from variations in the oxidation state of 
plutonium in the starting solutions. However, variations in surface areas and surface chemistry 
among the samples used in the experiments must also contribute to the range observed. 

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Pu on Zeolitic Tuff 
1 
10 
100 
1000 
10000
0 20 40 60 80 100 
Experiment Duration (days) 
Pu Kd (mL/g) 
Sorption 
J-13 New 
Desorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
Sorption 
p#1 New 
Desorption 
p#1 New 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-35. Plutonium Sorption Coefficient on Zeolitic Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The impact of variations in pH on plutonium sorption coefficients on devitrified tuffs is shown in 
Figure I-36. Although there is a lot of scatter in the data, there do not appear to be clear positive 
or negative trends among any of the data groupings. 
Pu on Zeolitic Tuff 
1 
10 
100 
1000 
10000
6 7 8 9 10 
pH 
Pu Kd (mL/g) 
New Sorption 
<40 Days 
New Sorption 
>40 Days 
New Desorption 
<40 Days 
Old Sorption 
<40 Days 
Old Sorption 
>40 Days 
Old Desorption 
<40 days 
Old Desorption 
>40 days 
New Sorption 
P#1 <40 Days 
New Desorption 
p#1 <40 Days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-36. Plutonium Sorption Coefficient on Zeolitic Tuff in J-13 and Synthetic p#1 versus Solution pH 
in Sorption (Forward) and Desorption (Backward) Experiments with Durations Greater than 
40 Days 
The impact of variations in the major ion composition of groundwaters is also shown in Figure I- 
36. Although there are a limited set of experiments with synthetic p#1 water, the results are 
largely within the range of the results obtained in experiments with J-13 water. Thus, there is no 

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MDL-NBS-HS-000008 REV 01 Attachment I-49 November 2003 
clear evidence that water chemistry variations have an impact on plutonium sorption coefficients 
in devitrified tuff. 
The plutonium sorption-coefficient probability distribution derived for zeolitic tuff in the UZ is a 
cumulative distribution, starting at 10 mL/g with a value of 100 mL/g at 0.5 and 200 mL/g at 1.0. 
The value at 0.5 was increased from 70 mL/g for devitrified tuff to 100 mL/g for zeolitic tuff to 
reflect the higher sorption coefficient values obtained with zeolitic tuff at lower pH values (7 
7.5). 
Vitric Tuff 
The experimentally derived sorption coefficients for plutonium on vitric tuff are plotted against 
the calculated final plutonium concentrations in Figure I-37. As before, the data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water chemistry, experiment duration, and on whether the sorption 
coefficient was determined from a sorption or a desorption experiment. The plotted data indicate 
that there is no clear trend of plutonium Kd with final solution concentration. As with devitrified 
tuffs, the plutonium sorption coefficients for vitric tuff plotted in Figure I-37 reflect solutions 
that were undersaturated with respect to the plutonium phase precipitated in the Nitsche et al. 
(1993 [155218], p.54; 1994 [144515], p. 39) experiments. 
Pu on Vitric Tuff 
10 
100 
1000 
10000 
1.0E-15 1.0E-13 1.0E-11 1.0E-09 1.0E-07 
Calculated Final Pu Conc. (mol/L) 
Pu Kd (mL/g) 
New Sorption 
J-13 <40 Days 
New Sorption 
J-13 >40 Days 
New Desorption 
J-13 <40 Days 
Old Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 <40 days 
Old Desorption 
J-13 >40 days 
New Sorption 
p#1 <40 Days 
New Sorption 
p#1 >40 Days 
New Desorption 
p#1 <40 Days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-37. Plutonium Sorption Coefficients on Vitric Tuff versus Calculated Final Plutonium 
Concentration in Solution 
The data in Figure I-37 for experiments with synthetic p#1 water plot in the middle of the data 
for experiments with J-13 water. Thus, there does not appear to be a significant impact of 
variations in water composition. 
The effects of experiment duration on the plutonium Kd for vitric tuff are shown in Figure I-38. 
As expected, the Kd values for sorption experiments generally increase with increasing duration. 

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MDL-NBS-HS-000008 REV 01 Attachment I-50 November 2003 
The Kd values for the new and old desorption experiments also increase with increasing 
duration, unlike the results for devitrified and zeolitic tuffs. However, as a group, the desorption 
results decrease with increasing duration. The trends in the sorption and desorption data points 
suggest they would converge to values somewhere between 100 and 1,000 mL/g. This is similar 
to the range of values predicted for devitrified and zeolitic tuffs. The cause for the large range of 
values obtained at a given value for experiment duration is not known, but may largely result 
from variations in the oxidation state of plutonium in the starting solutions in addition to 
analytical errors. Variations in surface areas and surface chemistry among the samples used in 
the experiments must also contribute to the range observed. 
Pu on Vitric Tuff 
10 
100 
1000 
10000
0 20 40 60 80 100 
Experiment Duration (days) 
Pu Kd (mL/g) 
Sorption 
New J-13 
Desorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New p#1 
Desorption 
New p#1 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-38. Plutonium Sorption Coefficient on Vitric Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The impact that variations in pH have on plutonium sorption coefficients in vitric tuffs is shown 
in Figure I-39. Although there is a lot of scatter in the data, there are no obvious trends among 
any of the data groupings. 

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Pu on Vitric Tuff 
10 
100 
1000 
10000
6 7 8 9 10 
pH 
Pu Kd (mL/g) 
Sorption J-13 
New <40 Days 
Sorption J-13 
New >40 Days 
Desorption J-13 
New <40 Days 
Sorption J-13 
Old <40 Days 
Sorption J-13 
Old >40 Days 
Desorption J-13 
Old <40 days 
Desorption J-13 
Old >42 Days 
Sorption p#1 
New <40 Days 
Desorption p#1 
New <40 Days 
DTNs: LA0309AM831341.005 [165526]; LA0305AM831341.001 [163789] 
Figure I-39. Plutonium Sorption Coefficient on Vitric Tuff in J-13 and Synthetic p#1 versus Solution pH in 
Sorption (Forward) and Desorption (Backward) Experiments with Durations Greater than 40 
Days 
The impact of variations in the major ion composition of groundwaters is also represented in 
Figures I-38 and I-39. The limited set of experiments with synthetic p#1 water are within the 
range of the results obtained in experiments with J-13 water, although they tend to be at the 
lower end of this range. 
The plutonium sorption-coefficient probability distribution selected for vitric tuff in the UZ is a 
cumulative distribution starting with a value of 10 mL/g at 0.0, increasing to a value of 100 mL/g 
at 0.5 and ending with a value of 200 mL/g at 1.0. The 10 mL/g value is selected to compensate 
for the potential for fast transport through the UZ. The value of 100 mL/g at 0.5 is intended to 
emphasize the median value among the sorption coefficients obtained in experiments with 
synthetic p#1 water. The upper limit of 200 mL/g was selected also to emphasize the p#1 water 
chemistry. 

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I.8.E PROTACTINIUM 
Protactinium is very insoluble in waters of the type found at Yucca Mountain. The best 
estimates of protactinium solubility in these waters range from 10-15 to 10-13 mol/L (Berry et al. 
1989 [144728], p. 346). 
Devitrified Tuff 
The oxidation state of protactinium is +5 in groundwaters of the type found at Yucca Mountain 
(Cotton and Wilkinson 1988 [105732], p. 1002). No sorption coefficient data have been 
obtained for protactinium on devitrified tuffs from Yucca Mountain. Allard et al. (1983 
[162982], p. 12) have reported protactinium sorption coefficient data for experiments with a 
silica sample having a surface area similar to that measured for devitrified tuffs. The solution 
composition used in the experiments was 0.01 M NaClO4. The initial protactinium 
concentration used in all experiments was 4.0  10-12 mol/L. Allard's data indicate that 
protactinium sorption coefficients vary substantially (approximately 2 orders of magnitude) as a 
function of pH (as shown in Figure I-40). The cause for this variation in sorption coefficients 
with pH is unknown. Over the pH range expected in saturated zone waters at Yucca Mountain 
(78.5), the sorption coefficients reported by Allard et al. (1983 [162982], p. 12) range from 
approximately 7,500 to 20,000 mL/g. The results for 6-hour experiments were similar to the 
results for experiments lasting up to 6 weeks. Thus, sorption kinetics for protactinium sorption 
reactions appear to be fast. Allard et al. (1983 [162982], p. 12) reported results for alumina that 
were very similar to the results they reported for silica. 
Protactinium 
1 
10 
100 
1000 
10000 
100000
0 5 10 
pH 
Pa Kd (mL/g) 
Allard-SiO2 
YMP-Zeol 
DTN: LA0305AM831341.001 [163789] 
Figure I-40. Protactinium Sorption Coefficients vs. pH 
Hydrolysis reactions appear to dominate the solution chemistry of protactinium. The hydrolysis 
reactions of pentavalent protactinium in water are very complex even in relatively acidic 
solutions (Cotton and Wilkinson 1988 [105732], p. 1002). In near-neutral solutions, the 

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hydrolysis behavior of protactinium is essentially unknown. However, because hydrolysis 
reactions appear to dominate the solution behavior of protactinium, changes in the major ion 
chemistry of groundwaters are not expected to impact the sorption behavior of protactinium. 
Unfortunately, insufficient thermodynamic data are available to model protactinium sorption 
behavior using a surface complexation model. 
The sorption coefficient range for americium (1,000 to 10,000 mL/g) was used as a default for 
protactinium. This range is well within the range reported by Allard et al. (1983 [162982], p. 12) 
for silica and alumina. As with americium sorption coefficients, a truncated normal distribution 
was selected. Corroboration of this range of sorption coefficient values is provided by 
protactinium sorption experiments performed by Berry et al. (1989 [144728], p. 347). These 
authors report a range of 1,000 to 1,000,000 mL/g in protactinium sorption coefficients for rock 
samples including sandstone, shale, granite, and clay in contact with natural groundwaters. 
Zeolitic Tuff 
Sorption coefficients for protactinium on zeolitic tuffs from Yucca Mountain in J-13 water were 
reported by Rundberg et al. (1985 [101355], p. 63). The reported sorption coefficients ranged 
from 3.3 to 10.1 mL/g (Figure I-40). The initial solution concentrations in the experiments 
ranged from 1  10-11 to 5  10-14 molar. The initial solution concentration used by Allard et al. 
(1983 [162982], p. 6) was in the low end of this range. Thus, initial solution concentration does 
not appear to explain the difference between the Allard et al. (1983 [162982], p. 12) results and 
the results on Yucca Mountain samples. It is possible that the results on Yucca Mountain 
samples reflect oversaturation due to co-precipitation of protactinium with some other easily 
hydrolyzed species. 
The pH values of the final solutions in the experiments on Yucca Mountain samples were in the 
range 6.36.7. These pH values are below the range expected in saturated zone waters at Yucca 
Mountain. Thus, the reported sorption coefficients do not directly apply to conditions in the 
Yucca Mountain UZ. As shown in Figure I-40, there appears to be an adsorption edge at a pH 
close to 6.8, and sorption coefficients increase by approximately 2 orders of magnitude at 
pH>6.8. The cause for this increase is not known, but is likely related to hydrolysis reactions. 
Because zeolitic tuffs have greater surface area than devitrified tuffs, the sorption coefficient 
distribution for devitrified tuff is used as a default for zeolitic tuff. This will lead to conservative 
predictions of protactinium transport rates. 
Vitric Tuff 
No sorption coefficient data is available for vitric tuffs. Because vitric tuffs have surface areas 
similar to the surface areas of devitrified tuffs, the sorption coefficient probability distribution for 
devitrified tuffs is used for vitric tuffs. 

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MDL-NBS-HS-000008 REV 01 Attachment I-54 November 2003 
I.8.F RADIUM 
The chemistry of radium is very similar to that of barium (Cotton and Wilkinson 1988 [105732], 
p. 144). Because barium has a radioactive isotope more readily measured by gamma counting 
than the radium isotopes, barium was used to measure sorption coefficients for radium. A 
limited number of experiments were performed with radium to confirm its sorption behavior 
relative to barium. 
Barite is the solubility-controlling solid for barium in Yucca Mountain groundwaters. The 
solubility of barite (barium sulfate) in J-13 water at 25C is 9.0  10-7 mol/L (DTN: 
LA0306AM831343.001 [164949]). The solubility of barite in p#1 water at 25C is 2.0  10-7 
mol/L. At 25C, the solubility of radium sulfate is 3.2  10-7 mol/L in J-13 water. 
Devitrified Tuff 
The experimentally derived sorption coefficients for barium on devitrified tuff are plotted against 
the calculated final barium concentrations of the experiments in Figure I-41. The data points are 
separated into groups on the basis of when the experiments were carried out (pre-1990 = old 
and post-1990 = new), water chemistry, experiment duration, and whether the sorption 
coefficient was determined from a sorption or a desorption experiment. 
Ba and Ra on Devitrified Tuff 
100 
1000 
10000 
100000 
1.0E-13 1.0E-11 1.0E-09 1.0E-07 1.0E-05 
Calculated Final Ba Conc. (mol/L) 
Ba Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 <40 Days 
Old Desorption 
J-13 >40 Days 
Radium 
J-13 >40 Days 
Old Sorption 
p#1 >40 Days 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-41. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Calculated Final Barium 
or Radium Concentrations in Solution 
The calculated final concentration of barium in the experiments with J-13 was below saturation 
with barite in all but one experiment (Figure I-41). The results for this one experiment will be 
omitted from further consideration. The calculated final barium concentrations in experiments 
with p#1 are all lower than the barite-saturation value of 2.0  10-7 mol/L. Thus, oversaturation 
was not an issue in the barium sorption experiments with p#1 water. Similarly, the radium 
solution concentrations were all lower than the radium sulfate saturation value in J-13. Thus, 
these experiments were undersaturated with radium sulfate. 

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The data plotted in Figure I-41 show a general increase in sorption coefficient with decreasing 
concentration. This suggests that the isotherms for barium sorption onto devitrified tuff are 
nonlinear. The impact of this nonlinearity must be included in the sorption coefficient 
probability distribution. 
The effects of experiment duration on the barium Kd for devitrified tuff are shown in Figure I-42. 
The large range in sorption coefficients obtained at a given duration reflects variations in grain 
size of the crushed tuff samples used in the experiments, variations in solution concentrations, 
variations in surface chemistry, and analytical errors and artifacts. Experiments with crushed 
tuff samples that include the fines (e.g., <30 m) often have sorption coefficients larger than 
samples from which the fines have been removed (e.g., 75500 m). This is partly due to the 
higher surface area of samples with fines and partly due to mineral fractionation. Mineral 
fractionation can occur during the sieving process and cause the preferential concentration of 
very fine grained minerals (e.g., clays) in the fine fraction. 
Ba and Ra on Devitrified Tuff 
100 
1000 
10000 
100000
0 20 40 60 80 100 
Experiment Duration (Days) 
Ba Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
Desorption 
J-13 Old 
Sorption 
p#1 Old 
Desorption 
p#1 Old 
Radium 
J-13 Old 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-42. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments 
Figure I-43 shows the effects of experiment duration on sorption coefficients for samples with 
the fines removed. The few sorption coefficients with values near 10,000 mL/g represent 
experiments with very low solution concentrations (Figure I-41). For the remaining experiments, 
the total range of sorption coefficient values is substantially reduced. Further, it appears likely 
the range would converge to a range between 100 and 1,000 mL/g with increasing duration. The 
horizontal trend among data points at durations other than 21 and 42 days suggests that barium 
and radium sorption reactions are relatively fast. 

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MDL-NBS-HS-000008 REV 01 Attachment I-56 November 2003 
Ba and Ra on Devitrified Tuff 
100 
1000 
10000 
100000
0 20 40 60 80 100 
Experiment Duration (Days) 
Ba Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
Sorption 
p#1 Old 
Desorption 
p#1 Old 
Radium 
J-13 Old 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-43. Barium and Radium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments 
The impact of variations in the major ion composition of groundwaters is also shown in Figures 
I-42 and I-43. Although there is a limited set of experiments with p#1 water, the sorption 
coefficients obtained (at 42 days) fall at the low end of the range of results for J-13 water. Thus, 
there is some water-chemistry impact, although it is substantially less than an order of 
magnitude. 
The radium sorption-coefficient probability distribution derived for devitrified tuff in the UZ is a 
uniform distribution with a range of 1001,000 mL/g. The low end of the chosen range was 
selected based on the minimum value observed in long-term experiments (>40 days) and the 
potential impact of variations in water chemistry and surface areas among devitrified tuffs at 
Yucca Mountain. Because there are experiments within the dataset that have solution 
concentrations close to saturation with a barium/radium sulfate, the effect of nonlinear isotherms 
is incorporated into the distribution. The upper end of the distribution was chosen as a minimum 
upper limit, given the potential impact of sorption kinetics, radium solution concentrations, and 
variation in surface areas. 
Zeolitic Tuff 
The experimentally derived sorption coefficients for barium and radium on zeolitic tuff are 
plotted against the calculated final barium or radium concentrations in Figure I-44. As before, 
the data points are separated into groups on the basis of when the experiments were carried out 
(pre-1990 = old and post-1990 = new), experiment duration, and whether the sorption 
coefficient was determined from a sorption or a desorption experiment. The plotted data indicate 
that there is no clear trend of barium Kd with solution concentration. Essentially all the sorption 
coefficients exceed a value of 10,000 mL/g and some desorption experiments approach values of 
1,000,000 mL/g. The radium results are in the range of the results for barium, confirming the 
similar sorption behavior of these two elements. As with devitrified tuffs, the barium and radium 
sorption coefficients for zeolitic tuff plotted in Figure I-44 reflect solutions that were 
undersaturated with barium and radium sulfate. The sorption coefficients obtained with p#1 

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MDL-NBS-HS-000008 REV 01 Attachment I-57 November 2003 
water are well within the range defined by the experiments with J-13 water. Thus, varying 
groundwater chemistry does not appear to have a clear impact. 
Ba and Ra on Zeolitic Tuff 
1000 
10000 
100000 
1000000 
1.0E-14 1.0E-12 1.0E-10 1.0E-08 
Calculated Final Conc. (mol/L) 
Ba Kd (mL/g) 
New Sorption 
J-13 <40 Days 
Old Sorption 
J-13 <40 Days 
Old Sorption 
J-13 >40 Days 
Old Desorption 
J-13 <40 Days 
Old Desorption 
J-13 >40 Days 
Radium 
J-13 >40 Days 
Old Sorption 
p#1 >40 Days 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-44. Barium and Radium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Barium or 
Radium Concentrations in Solution 
Data plotted in Figure I-44 also indicate that there is no clear trend of barium Kd with solution 
concentration. Data were obtained for a sorption isotherm on sample YM-38 (Figure I-45). As 
indicated by the exponent in the equation on the diagram, the calculated isotherm is essentially 
linear. 
Ba on Zeolitic Tuff YM-38 in J-13 
y = 23.23x0.9499 
1.0E-09 
1.0E-08 
1.0E-07 
1.0E-06 
1.0E-05 
1.0E-11 1.0E-10 1.0E-09 1.0E-08 1.0E-07 
Calculated Final Ba Conc (mol/L) 
Ba on Solid (mol/g) 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-45. Isotherm Diagram for Ba Sorption on Zeolitic Tuff YM-38 in J-13 Water 

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MDL-NBS-HS-000008 REV 01 Attachment I-58 November 2003 
The effects of experiment duration on the barium Kd for zeolitic tuff are shown in Figure I-46. 
The barium and radium sorption reactions are quite fast, as indicated by the range of values 
obtained in 6-day experiments (Figure I-46) being similar to the range of values obtained in 84 
day experiments. 
Ba and Ra on Zeolitic Tuff 
1000 
10000 
100000 
1000000 
0 20 40 60 80 100 
Experiment Duration (Days) 
Ba Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
Sorption 
p#1 Old 
Desorption 
p#1 Old 
Radium 
J-13 Old 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-46. Barium and Radium Sorption Coefficient on Zeolitic Tuff in J-13 versus Experiment Duration 
for Sorption (Forward) and Desorption (Backward) Experiments 
The impact of variations in the major ion composition of ground waters is also shown in Figure 
I-46. Although there is a limited set of experiments with synthetic p#1 water, the results are 
largely within the range of the results obtained in experiments with J-13 water. Thus, there is no 
clear evidence of water-chemistry variations having an impact on barium/radium sorption 
coefficients in zeolitic tuff. 
The radium sorption-coefficient probability distribution derived for zeolitic tuff in the 
unsaturated zone is a uniform distribution with a range of 1,0005,000 mL/g. The low end of the 
chosen range was selected based on the possibility that at concentrations near the solubility limit, 
sorption coefficients may be lower than the minimum value observed in long-term experiments 
(i.e., isotherms may be nonlinear) and that rock chemistry (Ca+Mg/Na+K in zeolites) may show 
greater variation than that represented among the samples used in the experiments. The upper 
end of the distribution was chosen as a minimum upper limit given the potential impacts of 
radium solution concentrations and variation in rock chemistry. 
Vitric Tuff 
The experimentally derived sorption coefficients for barium and radium on vitric tuff are plotted 
against the calculated final barium or radium concentrations in Figure I-47. As before, the data 
points are separated into groups on the basis of when the experiments were carried out (pre-1990 
= old and post-1990 = new), experiment duration, and on whether the sorption coefficient 
was determined from a sorption or a desorption experiment. Although there are a limited 
number of datapoints, the data plotted in Figure I-47 show a general increase in sorption 
coefficient with decreasing concentration. This suggests that the isotherms for barium sorption 
onto vitric tuff are nonlinear. The impact of this nonlinearity must be included in the sorption 
coefficient probability distribution. 

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MDL-NBS-HS-000008 REV 01 Attachment I-59 November 2003 
The radium sorption coefficient values obtained are larger than the barium coefficients obtained 
at similar solution concentrations. This indicates that barium sorption coefficients provide a 
conservative estimate of radium sorption coefficients on vitric tuff. As with devitrified tuffs, the 
barium and radium sorption coefficients for vitric tuff plotted in Figure I-47 reflect solutions that 
were undersaturated with barium and radium sulfate. The sorption coefficients obtained with 
p#1 water have values that are lower than those obtained in experiments with J-13 water. This 
indicates there is a groundwater composition effect for barium/radium sorption onto vitric tuff. 
Ba and Ra on Vitric Tuff 
10 
100 
1000 
10000 
1.0E-12 1.0E-10 1.0E-08 1.0E-06 
Calculated Final Ba Conc. (mol/L) 
Ba Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Radium 
Old J-13 
Sorption 
Old p#1 
Desorption 
Old p#1 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-47. Barium and Radium Sorption Coefficients on Vitric Tuff versus Calculated Final Barium or 
Radium Concentrations in Solution 
The effects of experiment duration on the barium Kd for vitric tuff are shown in Figure I-48. The 
fact that the short-term experiments show higher sorption coefficient values than the longer-term 
experiments indicates that barium and radium sorption reactions on vitric tuff are fast. 
Ba and Ra on Vitric Tuff 
10 
100 
1000 
10000 
100000
0 10 20 30 40 50 
Experiment Duration (days) 
Ba Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
Radium 
J-13 Old 
Sorption 
p#1 Old 
Desorption 
p#1 Old 
DTNs: LA0309AM831341.002 [165523]; LA0305AM831341.001 [163789] 
Figure I-48. Barium and Radium Sorption Coefficient on Vitric Tuff versus Experiment Duration for 
Sorption (Forward) and Desorption (Backward) Experiments 

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MDL-NBS-HS-000008 REV 01 Attachment I-60 November 2003 
The impact of variations in the major ion composition of groundwaters are also shown in Figure 
I-48. Although there is a limited set of experiments with synthetic p#1 water, the sorption 
coefficient values obtained are clearly below the range of the values obtained in experiments 
with J-13 water. Thus, there is evidence that water chemistry variations have an impact on 
barium sorption coefficients in devitrified tuff. 
The radium sorption-coefficient probability distribution derived for vitric tuff in the UZ is a 
uniform distribution with a range from 50600 mL/g. The value of 50 mL/g was derived based 
on experiments with p#1 water at final solution concentrations near saturation with barite. The 
value of 600 mL/g was derived based on the potential impact of more dilute water chemistry (J- 
13-like) combined with the potential for radium concentrations near the solubility limit. 

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I.8.G STRONTIUM 
The solubility of strontium in J-13 water at 25C ranges from 2.7  10-5 mol/L at pH = 7.1 to 1.4 
 10-6 mol/L at pH = 8.5 and the solubility-controlling phase is strontianite (strontium 
carbonate). The solubility of strontianite in p#1 water at 25C ranges from 2.4  10-5 mol/L at 
pH = 6.9 to 9.9  10-7 mol/L at pH = 8.6 (see DTN: LA0306AM831343.001 [164949]). 
Devitrified Tuff 
The experimentally derived sorption coefficients for strontium on devitrified tuff are plotted 
against the calculated final strontium concentrations of the experiments in Figure I-49. The data 
points are separated into groups on the basis of when the experiments were carried out (pre-1990 
= old and post-1990 = new), water type, and whether the sorption coefficient was 
determined from a sorption or a desorption experiment. There is also data for a sorption 
isotherm on sample G1-2840. 
Sr on Devitrified Tuff 
1 
10 
100 
1000 
10000 
1.00E-12 1.00E-09 1.00E-06 1.00E-03 
Calculated Final Sr Conc. (mol/L) 
Sr Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
G1-2840 
J-13 Old 
p#1 Old 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-49. Strontium Sorption Coefficients on Devitrified Tuff versus Calculated Final Strontium 
Concentration in Solution 
Most of the calculated final solution concentrations for the sorption experiments are nearly all 
below saturation with strontianite in J-13. The data points with concentrations greater than 1.0  
10-6 mol/L reflect experiments that were oversaturated with strontianite. Thus, the sorption 
coefficients obtained in these five experiments will not be used in the derivation of the strontium 
sorption coefficient probability distribution. The calculated final strontium concentrations used 
in experiments with p#1 are all lower than the saturation value. Thus, oversaturation was not an 
issue in the strontium sorption experiments with p#1 water. 
A sorption isotherm was obtained for sample G1-2840 in J-13 water. The isotherm is linear at 
concentrations below approximately 5  10-5 mol/L as shown in Figure I-49. Further, the Kd 
value in the linear portion of the isotherm is at the low end of the range of strontium sorption 
coefficients obtained with J-13 and p#1 waters. Thus, the isotherms for the bulk of the samples 
would lie at higher Kd values compared to the isotherm for G1-2840. The sorption coefficients 

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MDL-NBS-HS-000008 REV 01 Attachment I-62 November 2003 
obtained in experiments with p#1 water fall in the middle of the range of values obtained for 
experiments with J-13 water. Thus, there is little or no impact of variations in water chemistry 
on strontium sorption coefficients on devitrified tuff. 
The effects of experiment duration on the strontium Kd for devitrified tuff are shown in Figure I- 
50. The large range in sorption coefficients obtained at a given duration reflects variations in 
grain size of the crushed tuff samples used in the experiments, variations in solution strontium 
concentrations, variations in surface chemistry, and analytical error and artifacts. Experiments 
with crushed tuff samples that include the fines (e.g., particle size <30 m) usually have sorption 
coefficients that are larger than samples from which the fines have been removed (e.g., particle 
sizes 75500 m). This is partly caused by the higher surface area of samples with fines and 
partly by mineral fractionation. Mineral fractionation can occur during the sieving process and 
cause the preferential concentration of very fine grained minerals (e.g., clays) in the fine fraction. 
Sr on Devitrified Tuff 
1 
10 
100 
1000 
10000
0 20 40 60 80 100 
Experiment Duration (days) 
Sr Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
G1-2840 
J-13 Old 
p#1 Old 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-50. Strontium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. Data points include experiments in 
which fines were not removed from sample. 
Figure I-51 shows the effects of duration on sorption coefficients for crushed tuff samples with 
the fines removed. The total range of sorption coefficient values is reduced compared to Figure 
I-50. Further, it appears likely this range would converge to a range between 50 and 500 mL/g 
with increasing duration. The horizontal trend among data points at durations other than 21 and 
42 days suggests strontium sorption reactions are relatively fast. 

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MDL-NBS-HS-000008 REV 01 Attachment I-63 November 2003 
Sr on Devitrified Tuff 
1 
10 
100 
1000 
0 20 40 60 80 100 
Experiment Duration (days) 
Sr Kd (mL/g) 
Sorption 
J-13 New 
Sorption 
J-13 Old 
Desorption 
J-13 Old 
G1-2840 
J-13 Old 
p#1 Old 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-51. Strontium Sorption Coefficients on Devitrified Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. Fines fraction removed from all 
experiments. 
The strontium sorption coefficient probability distribution derived for devitrified tuff in the 
unsaturated zone is a uniform distribution with a range of 1070 mL/g. The low end of the 
chosen range was selected based on the minimum value observed in isotherm experiments. 
Because the minimum value observed in isotherm experiments corresponds to solution 
concentrations close to saturation with a strontium carbonate, the effect of nonlinear isotherms is 
incorporated into the distribution. The upper end of the distribution was chosen as a minimum 
upper limit, given the potential impact of natural strontium in pore waters. Natural strontium 
concentrations measured in pore waters can be as high as 4.7  10-5 mol/L but the average is 
closer to 1.1  10-5 mol/L (DTN: GS020408312272.003 [160899]). The isotherm shown in 
Figure I-51 would indicate a sorption coefficient of 5070 mL/g at this concentration. The high 
end of this range was chosen for the upper limit of the distribution. A uniform distribution was 
chosen to equally weight the sorption coefficient values in the selected range. 
Zeolitic Tuff 
The experimentally derived sorption coefficients for strontium on zeolitic tuff are plotted against 
the calculated final strontium concentrations of the experiments in Figure I-52. The data points 
are separated into groups on the basis of water type, whether or not the solid phase included 
fines, and whether the sorption coefficient was determined from a sorption or a desorption 
experiment. 

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MDL-NBS-HS-000008 REV 01 Attachment I-64 November 2003 
Sr on Zeolitic Tuff 
1000 
10000 
100000 
1000000 
1.0E-13 1.0E-10 1.0E-07 1.0E-04 
Calculated Final Sr Conc. (M/l) 
Sr Kd (ml/g) 
Sorption-Old 
J-13 w / fines 
Sorption-Old 
J-13 no fines 
Desorption-Old 
J-13 w / fines 
Desorption-Old 
J-13 no fines 
Sorption-Old 
p#1 no fines 
Desorption-Old 
p#1 no fines 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-52. Strontium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Strontium 
Concentration in Solution 
All except two of the calculated final solution concentrations were below the saturation level 
with strontianite. The calculated final strontium concentrations used in experiments with p#1 are 
all lower then the saturation value. Thus, oversaturation was not an issue in the strontium 
sorption experiments. 
The few sorption coefficients obtained with p#1 water tend to lie at the low end of the range of 
values shown in Figure I-52. This suggests variations in water composition will have an impact 
on the strontium sorption coefficient for zeolitic tuff. 
Sorption experiments were carried out at a number of different starting concentrations to obtain 
an isotherm for sample YM-38. As shown in Figure I-53, the sorption coefficients obtained in 
these experiments are not consistent with a simple relationship between strontium concentration 
and sorption coefficient. Nonetheless, the sorption coefficients plotted in Figure I-52 were 
obtained over a range of strontium concentrations. Thus, the concentration dependence of the 
sorption coefficient is included in the dataset. 

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Sr on Zeolitic Tuff YM-38 
1000 
10000 
100000 
1.0E-11 1.0E-09 1.0E-07 1.0E-05 1.0E-03 
Calculated Final Sr Conc. (mol/L) 
Sr Kd (mL/g) 
Sorption-Old 
J-13 no fines 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-53. Strontium Sorption Coefficients versus Calculated Final Solution Concentration in M/L for 
Sample YM-38 in J-13 Water 
The effects of experiment duration on the strontium Kd for zeolitic tuff are shown in Figure I-54. 
The large range in sorption coefficients obtained at a given duration reflects variations in the 
grain size of the crushed tuff samples used in the experiments, variations in solution strontium 
concentrations, variations in surface chemistry, and analytical errors and artifacts. Experiments 
with crushed tuff samples that include the fines (e.g., particle size <30 m) usually have sorption 
coefficients larger than samples from which the fines have been removed (e.g., particle sizes 75 
500 m). This is partly a result of the higher surface area of samples with fines and partly due to 
mineral fractionation. Mineral fractionation can occur during the sieving process and cause the 
preferential concentration of very fine grained minerals (e.g., clays) in the fine fraction. 
Sr on Zeolitic Tuff 
1000 
10000 
100000 
1000000 
0 20 40 60 80 100 
Experiment Duration (days) Sr Kd (mL/g) 
Sorption-New 
J-13 no fines 
Sorption-Old 
J-13 w / fines 
Sorption-Old 
J-13 no fines 
Desorption-Old 
J-13 w / fines 
Desorption-Old 
J-13 no fines 
Sorption-Old 
p#1 no fines 
Desorption-Old 
p#1 no fines 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-54. Strontium Sorption Coefficients on Zeolitic Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments. 
Figure I-55 shows the effects of duration on sorption coefficients for crushed tuff samples with 
the fines removed. The total range of sorption coefficient values is reduced slightly compared to 

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MDL-NBS-HS-000008 REV 01 Attachment I-66 November 2003 
Figure I-54. The rather limited range of values at 84 days is likely caused by the limited number 
of experiments carried at this duration. There is no clear trend of sorption coefficient value with 
duration. This likely reflects fast sorption kinetics. 
Sr on Zeolitic Tuff 
1000 
10000 
100000 
1000000
0 20 40 60 80 100 
Experiment Duration (days) 
Sr Kd (mL/g) 
Sorption-New 
J-13 no fines 
Sorption-Old 
J-13 no fines 
Desorption-Old 
J-13 no fines 
Sorption-Old 
p#1 no fines 
Desorption-Old 
p#1 no fines 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-55. Strontium Sorption Coefficients on Zeolitic Tuff with Fine Fraction Removed versus 
Experiment Duration for Sorption (Forward) and Desorption (Backward) Experiments 
The strontium sorption coefficient probability distribution derived for devitrified tuff in the UZ is 
a uniform distribution with a range of 502000 mL/g. The low end of the chosen range was 
selected based on the minimum value observed in isotherm experiments and the trend of lower 
sorption coefficients with increasing strontium concentration. When the trend is extended to the 
solubility limit for p#1 water, the value obtained is well below 1,000 mL/g. A value of 50 mL/g 
was chosen as a conservative value. The upper end of the distribution was chosen as a minimum 
upper limit, given the potential impact of natural strontium in pore waters. Natural strontium 
concentrations measured in pore waters can be as high as 4.7  10-5 mol/L but the average is 
closer to 1.1  10-5 mol/L (DTN: GS020408312272.003 [160899]). The data shown in Figure I- 
52 would indicate a sorption coefficient of approximately 2,000 mL/g at this concentration. A 
uniform distribution was chosen to equally weight the sorption coefficient values in the selected 
range. 
Vitric Tuff 
The experimentally derived sorption coefficients for strontium on vitric tuff are plotted against 
the calculated final strontium concentrations of the experiments in Figure I-56. The data points 
are separated into groups on the basis of when the experiments were carried out (pre-1990 = 
old and post-1990 = new), water type, and whether the sorption coefficient was determined 
from a sorption or a desorption experiment. 

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MDL-NBS-HS-000008 REV 01 Attachment I-67 November 2003 
Sr on Vitric Tuff 
1 
10 
100 
1000
1.E-10 1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 
Calculated Final Sr Conc. (mol/L) 
Sr Kd (mL/g) 
Sorption 
J-13 (New ) 
Sorption 
J-13 (Old) 
Desorption 
J-13 (Old) 
Sorption 
p#1 (Old) 
Desorption 
p#1 (Old) 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-56. Strontium Sorption Coefficients on Vitric Tuff versus Calculated Final Strontium 
Concentration in Solution 
The calculated final solution concentrations for the sorption experiments are all below saturation 
with strontianite. Thus, oversaturation was not an issue in the strontium sorption experiments. 
Sorption coefficients obtained in experiments with p#1 water fall in the middle of the range of 
values obtained for experiments with J-13 water. Thus, variations in water chemistry have little 
or no impact on strontium sorption coefficients in devitrified tuff. 
The effects of experiment duration on the strontium Kd for devitrified tuff are shown in Figure I- 
57. Because the short-term experiments have higher sorption coefficient values than the longerterm 
experiments, strontium sorption kinetics must be relatively fast. 
Sr on Vitric Tuff 
1 
10 
100 
1000 
0 20 40 60 80 100 
Experiment Duration (days) 
Sr Kd (mL/g) 
Sorption-New 
J-13 no fines 
Sorption-Old 
J-13 no fines 
Desorption-Old 
J-13 no fines 
Sorption-Old 
p#1 no fines 
Desorption-Old 
p#1 no fines 
DTNs: LA0309AM831341.006 [165527]; LA0305AM831341.001 [163789] 
Figure I-57. Strontium Sorption Coefficients on Vitric Tuff versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 

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MDL-NBS-HS-000008 REV 01 Attachment I-68 November 2003 
The strontium sorption coefficient probability distribution derived for vitric tuff in the 
unsaturated zone is a uniform distribution with a range of 050 mL/g. The low end of the chosen 
range was selected based on the minimum value observed in experiments with p#1 water and 
acknowledgment that the solution concentrations could get close to the saturation concentration 
(8  10-4 mol/L) with the addition of natural strontium to the radioactive fraction released from 
the repository (1.14.7  10-5 mol/L; DTN: GS020408312272.003 [160899]). The upper end of 
the distribution was chosen as a minimum upper limit in J-13 water with natural strontium. A 
uniform distribution was chosen to equally weight the sorption coefficient values in the selected 
range. 

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MDL-NBS-HS-000008 REV 01 Attachment I-69 November 2003 
I.8.H THORIUM 
The solubility of thorium dioxide in waters such as the UZ waters is estimated at 3.2  10-9 
mol/L at pH > 6.0 (Hummel et al. 2002 [161904], p. 377). 
Devitrified Tuff 
Experiments with Yucca Mountain tuffs were carried out with initial concentrations in the 
1.0  10-7 to 6  10-8 mol/L range. Thus, the experiments were initially oversaturated with 
thorium dioxide. The calculated final thorium concentrations shown in Figure I-58 indicate that 
Th sorption onto the rock sample brought the final solution concentrations below saturation with 
thorium dioxidein some cases but not all. The results of experiments oversaturated with 
thorium dioxide are of questionable value. For the remaining experiments, the sorption 
coefficients range from 1,213 to 23,800 mL/g. There are no data available for the effect of 
experimental duration on sorption coefficient values for Yucca Mountain samples. However, 
Allard et al. (1983 [162982], p. 10) reported that over experiment durations of 6 hours to 6 
weeks, time had little influence on the measured sorption coefficients for Th on silica in 0.01 M 
NaClO4. Note that the starting concentrations reported by Allard et al. (1983 [162982], p. 6) 
were below the saturation level for thorium dioxide. 
Th Sorption Coefficients in J-13 
100 
1000 
10000 
100000
1.E-11 1.E-10 1.E-09 1.E-08 1.E-07 
Calculated Final Th Conc. 
Th Kd (mL/g) 
Devitrified Tuff 
Zeolitic Tuff 
Vitric Tuff 
DTN: LA0305AM831341.001 [163789] 
Figure I-58. Thorium Sorption Coefficients on Tuff versus Calculated Final Thorium Concentration in 
Solution 
There are no data available to evaluate the impact of variations in water chemistry on Th sorption 
coefficients. However, thorium forms primarily hydroxide complexes at near neutral pH 
(Langmuir and Herman 1980 [147527], p. 1753). Therefore, water chemistry is expected to have 
very little influence on Th sorption coefficient values in Yucca Mountain groundwaters. 
However, water chemistry (i.e., pH) does impact the solubility of thorium dioxide. This is the 
reason some of the experiments in Figure I-58 were oversaturated with thorium dioxide. As 
shown in Figure I-59, the lowest sorption coefficients were obtained at near-neutral pH values 
where J-13 water was oversaturated with thorium dioxide. 

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Th Sorption Coefficients in J-13 
100 
1000 
10000 
100000
4 5 6 7 8 9 
pH 
Th Kd (mL/g) 
Devitrified Tuff 
Zeolitic Tuff 
Vitric Tuff 
DTN: LA0305AM831341.001 [163789] 
Figure I-59. Thorium Sorption Coefficients on Tuff Versus pH 
On the basis of the experimental data in Figures I-58 and I-59, the range of thorium sorption 
coefficients expected for devitrified tuffs in the saturated volcanic section at Yucca Mountain is 
1,000-10,000 mL/g. This range is intended to reflect the range in surface areas found in 
devitrified tuffs in the saturated zone and the range in thorium concentrations expected during 
saturated zone transport. The lower end of the range reflects sorption coefficients at thorium 
concentrations near the solubility limit. Given the sparseness of the available data, the 
probability distribution type selected is a uniform distribution. 
Zeolitic Tuff 
Sorption coefficient data for zeolitic tuff are plotted in Figures I-58 and I-59. Based on the 
available data, zeolitic tuffs have sorption coefficients for thorium that are similar to those 
obtained for devitrified tuffs. 
On the basis of the data plotted in Figures I-58 and I-59, the range of thorium sorption 
coefficients selected for zeolitic tuffs in the saturated volcanic section at Yucca Mountain is 
1,00030,000 mL/g. The upper end of this range was selected to reflect the higher surface areas 
of zeolitic tuffs relative to devitrified tuffs. A uniform distribution is selected for zeolitic tuffs. 
Vitric Tuff 
Sorption coefficient data for vitric tuff are plotted in Figures I-58 and I-59. Based on the 
available data, vitric tuffs have sorption coefficients for thorium in the range of those obtained 
for the other tuffs in those experiments that were undersaturated in thorium dioxide. 
On the basis of the data plotted in Figures I-58 and I-59, the range of thorium sorption 
coefficients selected for vitric tuffs in the saturated volcanic section at Yucca Mountain is 
1,000-10,000 mL/g. A uniform distribution is selected for vitric tuffs. 

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MDL-NBS-HS-000008 REV 01 Attachment I-71 November 2003 
I.8.I URANIUM 
The solubility of uranium in J-13 water under oxidizing conditions ranges from 1.8  10-4 at 
pH = 7.1 to 2.0  10-4 mol/L at pH = 8.5 (DTN: LA0306AM831343.001 [164949]). The 
solubility of uranium in synthetic p#1 water under oxidizing conditions ranges from 6.7  10-4 at 
pH = 6.9 to 9.0  10-4 mol/L at pH = 8.6 (DTN: LA0306AM831343.001 [164949]). The 
solubility-controlling solid in both waters is schoepite. 
Devitrified Tuff 
As shown in Figure I-60, the calculated final uranium concentrations in the sorption experiments 
were generally below saturation with schoepite. The sorption coefficients obtained in sorption 
experiments with devitrified tuffs do not show a correlation with the calculated final uranium 
solution concentrations. 
U on Devitrified Tuff 
-10 
-5
0 5 
10 
15 
20 
1.E-08 1.E-06 1.E-04 
Calculated Final U Conc. 
U Kd (mL/g) 
Sorption 
Old J-13 
Sorption 
New J-13 
Sorption 
New p#1 
Desorption 
Old J-13 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-60. Uranium Sorption Coefficients on Devitrified Tuff Versus Calculated Final Uranium 
Concentration in Solution 
Sorption experiments carried out as a function of time are shown in Figure I-61. Beyond 
approximately 3 days, there is no clear correlation between the sorption coefficients obtained and 
the duration of the experiments. The data imply that uranium sorption reactions on devitrified 
tuffs must be relatively fast (i.e., they reach steady state in a few days). 

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U on Devitrified Tuff 
-10 
-5
0 5 
10 
15 
20
0 20 40 60 
Experiment Duration (days) 
U Kd (mL/g) 
Sorption 
Old J-13 
Sorption 
New J-13 
Sorption 
New p#1 
Desorption 
Old J-13 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-61. Uranium Sorption Coefficients on Devitrified Tuff Versus Experiment Duration for Sorption 
(Forward) and Desorption (Backward) Experiments 
The dependence of the uranium sorption coefficient on water chemistry was tested with 
experiments using two water compositions (J-13 and synthetic p#1). The J-13 experimental data 
are shown as a function of pH in Figure I-62. The old data were obtained in the 1980s and the 
new data were obtained in the 1990s. The difference between them is not statistically 
significant. The range of values obtained at a given pH (e.g., 8.4) reflects experimental errors 
and natural variations in rock properties (e.g., surface area and mineral chemistry). It is not 
possible to discriminate between these possible causes with the available data. On the basis of 
the experimental data points, there does not appear to be a correlation between Kd and pH. 
However, surface complexation modeling with PHREEQC, using binding constants derived by 
Pabalan et al. (1998 [162987], p. 124) for uranium on silica, points to a clear pH dependence as 
shown in Figure I-62. The two model curves reflect two different surface areas (2.8 and 5.6 
m2/g). The 2.8 m2/g surface area is approximately an average value for devitrified tuffs at Yucca 
Mountain. 
The sorption coefficients obtained in experiments with synthetic p#1 water are shown in 
Figure I-63. The data plotted have substantial experimental errors associated with them, as 
indicated by the magnitude of some of the negative Kd values. These experimental errors result 
from counting statistics, the stability of counters over time, corrections made for adsorption to 
container walls, and the pH of the tracer solution added to the experiment. Taken at face value, 
the experimental data suggest a trend of increasing Kd with increasing pH. However, the surface 
complexation modeling predicts a decrease in Kd with increasing pH, although the absolute Kd 
values are rather small. 

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Uranium on Devit Tuff in J-13 
-4 
-2
0
2
4
6
8 
10
6 7 8 9 
pH 
Uranium Kd (mL/g) 
Model 5.6 m2/g 
Model 2.8 m2/g 
Old Data 
New Data 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528]; LA0306AM831343.001 [164949] 
Figure I-62. Uranium Sorption Coefficients on Devitrified Tuff versus pH. Model curves are from the 
PHREEQC Surface Complexation Model. 
Uranium on Devit Tuff in p#1 
-6 
-4 
-2
0
2
4
6
6 7 8 9 10 
pH 
Uranium Kd (mL/g) 
YMP Data 
Model 2.8 m2/g 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528]; LA0306AM831343.001 [164949] 
Figure I-63. Uranium Sorption Coefficients on Devitrified Tuff in p#1 Water versus pH. Model curve is 
from the PHREEQC Surface Complexation Model. 
On the basis of the experimental data and model curves plotted in Figures I-62 and I-63, a 
cumulative probability distribution type was selected for the sorption coefficient probability 
distribution for devitrified tuff, with a value of 0.0 mL/g at 0.0, 0.2 mL/g at 0.5, and 4.0 mL/g at 
1.0. 

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Zeolitic Tuff 
As shown in Figure I-64, the sorption coefficients obtained in sorption experiments with zeolitic 
tuffs do not show a clear correlation with the calculated final uranium solution concentrations. 
The high end of the concentrations plotted is below saturation with a solid uranium phase. 
U Kd on Zeolitic Tuff 
-10
0 
10 
20 
30 
40 
1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 
Calculated Final U Concentration (mol/L) 
U Kd (mL/g) 
J-13 "New" 
J-13 "Old" 
Synthetic p#1 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-64. Uranium Sorption Coefficients on Zeolitic Tuff versus Calculated Final Uranium 
Concentration in Solution 
Uranium sorption experiments on zeolitic tuffs carried out as a function of time are shown in 
Figure I-65. Beyond a period of approximately 3 days, there is no clear correlation between the 
sorption coefficients obtained and the duration of the experiments. These data imply that 
uranium sorption reactions on zeolitic tuffs are relatively fast (i.e., they reach steady state in a 
few days). 

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Uranium on Zeolitic Tuff 
-10
0 
10 
20 
30 
40
0 20 40 
Experiment Duration (days) 
U Kd (mL/g) 
J-13 "Old" 
J-13 "New" 
Synthetic p#1 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-65. Uranium Sorption Coefficients on Zeolitic Tuff as a Function of Experiment Duration 
The dependence of the uranium sorption coefficient on water chemistry was tested with 
experiments using two water compositions (J-13 and synthetic p#1). The J-13 data are shown as 
a function of pH in Figure I-66. The old data were obtained in the 1980s and the new data 
were obtained in the 1990s. The difference between them is not statistically significant. The 
range of values observed at a given pH (e.g., 8.4) reflects variations in rock properties and 
experimental errors. The experimental errors result from such things as counting statistics, the 
stability of counters over time, the accuracy of corrections for adsorption to container walls, and 
other experimental artifacts. In some cases, the pH of the tracer solution added to the experiment 
seems to have an effect. Some of these errors are random (e.g., counting errors) and others (e.g., 
adsorption to container walls) may have a nonrandom bias. It is not possible to separately 
evaluate these errors with the information available. Note that the distribution of data points in 
Figure I-66 does not indicate a strong correlation between Kd and pH. 
Surface complexation modeling was carried out with PHREEQC to provide a framework in 
which to interpret the experimental data. Binding constants for uranium on silica derived by 
Pabalan et al. (1998 [162987], p. 124) were used in the modeling. The modeling results show a 
clear pH dependence (Figure I-66). The two model curves reflect two different surface areas. A 
surface area of 28 m2/g was used because it approximates an average value for zeolitic tuffs and 
because it is an order of magnitude larger than the average value used for modeling devitrified 
tuffs. A surface area of 14 m2/g was also used to show the impact of a factor of 2 change in 
surface area. 
The sorption coefficients obtained in experiments with synthetic p#1 water are shown in 
Figure I-67. The magnitudes of the negative Kd values plotted are similar to the magnitudes of 
the positive values plotted. Thus, the net values may be very close to zero. Taken at face value, 
the experimental data suggest a trend of increasing Kd with increasing pH. However, the surface 
Experiment Duration 

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MDL-NBS-HS-000008 REV 01 Attachment I-76 November 2003 
complexation modeling predicts an increase in Kd with decreasing pH, although the absolute Kd 
values are rather small, in agreement with the net values obtained from the experimental data. 
Uranium on Zeolitic Tuff in J-13 
-25
0 
25 
50
6 7 8 9 
pH 
Uranium Kd (mL/g) 
Model 
(28 m2/g) 
Model 
(14 m2/g) 
YMP "Old 
Data" 
YMP "New 
Data" 
DTNs: LA0305AM831341.001 [163789]; 
LA0309AM831341.007 [165528]; LA0306AM831343.001 [164949] 
Figure I-66. Uranium Sorption Coefficients for Zeolitic Tuff in J-13 Plotted as a Function of pH. Model 
curves derived with PHREEQC surface complexation modeling are also shown. 
Uranium on Zeolitic Tuff in Synthetic p#1 
-8 
-6 
-4 
-2
0
2
4
6
8
6.000 7.000 8.000 9.000 10.000 
pH Uranium Kd (mL/g) 
Model 
(14 m2/g) 
YMP Data 
DTNs: LA0305AM831341.001 [163789]; 
LA0309AM831341.007 [165528]; LA0306AM831343.001 [164949] 
Figure I-67. Uranium Sorption Coefficients for Zeolitic Tuff in Synthetic p#1 Plotted as a Function of pH. 
Model curves derived with PHREEQC surface complexation modeling are also shown 

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MDL-NBS-HS-000008 REV 01 Attachment I-77 November 2003 
On the basis of the experimental data and model curves plotted in Figures I-66 and I-67, a 
cumulative probability distribution type was selected for the sorption coefficient probability 
distribution for zeolitic tuff with a value of 0.0 mL/g at 0.0, 0.2 mL/g at 0.5 and 30.0 mL/g at 1.0. 
UraniumVitric Tuff 
As shown in Figure I-68, the high end of the concentration range plotted is below saturation with 
schoepite. Thus, oversaturation was not a problem in sorption experiments with vitric tuffs. 
Uranium on Vitric Tuffs 
-5
0
5 
10 
15
1.E-09 1.E-07 1.E-05 1.E-03 
Final Uranium Conc. (mol/L) 
Uranium Kd (mL/g) 
Sorption 
New J-13 
Sorption 
New s-p#1 
Sorption 
Old J-13 
Desorption 
Old J-13 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-68. Uranium Sorption Coefficients on Vitric Tuff versus Calculated Final Uranium Concentration 
in Solution 
Uranium sorption experiments on vitric tuffs carried out as a function of time are shown in 
Figure I-69. Beyond a period of approximately 3 days, there is no clear correlation between the 
sorption coefficients obtained and the duration of the experiments. These data imply that 
uranium sorption reactions on vitric tuffs are relatively fast (i.e., they reach steady state in a few 
days). Sorption coefficients obtained from desorption experiments are larger, on average, than 
sorption coefficients obtained from sorption experiments. The desorption experiments were 
performed on a sample that contained 15% zeolite. Perhaps the presence of zeolite in this 
sample caused it to have a higher affinity for uranium. The point with the largest sorption 
coefficient value from sorption experiments (12 mL/g) was also obtained on this particular 
sample. 

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Uranium on Vitric Tuff 
-5
0
5 
10 
15 
0 10 20 30 40 50 
Experiment Duration (days) 
Uranium Kd (mL/g) 
Sorption 
New J-13 
Sorption 
Old J-13 
Desorption 
Old J-13 
Sorption 
New s-p#1 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-69. Uranium Sorption Coefficients on Vitric Tuff as a Function of Experiment Duration 
The dependence of the uranium sorption coefficient on water chemistry was tested with 
experiments using two water compositions (J-13 and synthetic p#1). The J-13 data are shown as 
a function of pH in Figure I-70. The coefficients obtained in sorption experiments are smaller 
than the coefficients obtained in desorption experiments, as noted above. As before, the range of 
values observed at a given pH (e.g., 8.4) reflects variations in rock properties and experimental 
errors. The experimental errors result from such things as counting statistics, the stability of 
counters over time, the accuracy of corrections for adsorption to container walls, and other 
experimental artifacts. In some cases, the pH of the tracer solution added to the experiment 
seems to have an effect. Some of these errors are random (e.g., counting errors), and others (e.g., 
adsorption to container walls) may have a nonrandom bias. It is not possible to separately 
evaluate these errors with the information available. However, the magnitude of the negative 
values suggest error values of up to 100%. A model using 1.5 m2/g surface area to represent the 
average vitric tuff is shown on the Figure I-70. This model predicts sorption coefficient values 
in the pH range 8.5 to 7.0 between 0.2 and 1.5 mL/g, respectively. 
Uranium sorption coefficients obtained with synthetic p#1 water are plotted in Figure I-71. The 
average of the points plotted is close to zero. The results of a model calculation using a 1.5 m2/g 
surface area and the p#1 water composition as inputs are shown in Figure I-71. This model 
predicts sorption coefficient values of 0.004 and 0.12 mL/g for pH values of 8.5 and 7.0, 
respectively. Thus, the predicted uranium sorption coefficient for vitric tuff in p#1-v water is 
close to zero, consistent with the experimental data. 

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Uranium on Vitric Tuff in J-13 
-5
0
5 
10 
15
6 7 8 9 10 
pH 
Uranium Kd (mL/g) 
Sorption 
Desorption 
Model J-13 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-70. Uranium Sorption Coefficients for Vitric Tuff in J-13 Plotted as a Function of pH. Model curves 
derived with PHREEQC surface complexation modeling are also shown. 
Uranium on Vitric Tuff in Synthetic p#1 
-5
0
5 
10
6 7 8 9 10 
pH 
Uranium Kd (mL/g) 
Sorption 
New s-p#1 
Model 
p#1-v 
DTNs: LA0305AM831341.001 [163789]; LA0309AM831341.007 [165528] 
Figure I-71. Uranium Sorption Coefficients for Vitric Tuff in Synthetic p#1 Plotted as a Function of pH. 
Model curves derived with PHREEQC surface complexation modeling are also shown. 
On the basis of the experimental data and model curves plotted in Figures I-70 and I-71, a 
cumulative probability distribution type was selected for the sorption coefficient probability 
distribution for vitric tuff, with a value of 0.0 mL/g at 0.0, 0.2 mL/g at 0.5 and 3.0 mL/g at 1.0. 

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I.9. SUMMARY 
Sorption-coefficient probability distribution functions were derived for radionuclides of 
interest to be used in transport calculations. Experimental and modeling results were used 
to constrain the distributions. In general, the approach used in derivation of the 
distributions tended to underestimate the range and median or expected value. This was 
done to provide some conservatism in the derivation, given potential scaling uncertainties 
in the application of these distributions to transport calculations at the Yucca Mountain site. 

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ATTACHMENT II 
CORRELATIONS FOR SAMPLING OF SORPTION COEFFICIENT PROBABILITY 
DISTRIBUTIONS 

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TABLES 
Page 
II-1. Ratings of Controls on Sorption Behavior..............................................................................6 
II-2. Correlations For Sampling Sorption Coefficient Probability Distributions ...........................7 

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In the TSPA, UZ transport calculations are carried out separately for each radionuclide. The 
sorption-coefficient probability distribution for each radionuclide could be sampled 
independently in each transport calculation. However, such independent sampling could 
potentially lead to dose dilution. That is, independent sampling of the distributions could cause 
radionuclides to travel at independent rates, such that the calculated dose at the accessible 
environment would not be representative of maximum possible doses. Similarities in the 
chemical dependencies of sorption coefficients for the various radionuclides suggest transport 
rates in the UZ are likely to be correlated for some radionuclides. 
Correlations for sampling sorption coefficient probability distributions have been derived for the 
elements Am, Cs, Np, Pa, Pu, Ra, Sr, Th, and U. To derive the correlations, a rating system was 
first developed to rate the impact of six different variables on the sorption coefficient for a given 
element in each of the three major rocks types. The matrix containing the ratings is shown in 
Table II-2. The six variables are pH, Eh, water chemistry, rock composition, rock surface area, 
and radionuclide concentration. Most of these parameters are self explanatory. Water chemistry 
refers to the major ion concentrations and silica. Rock composition refers to both the 
mineralogic composition of the rocks and the chemical composition of the minerals (e.g., zeolite 
compositions). 
The ratings are based on the sorption data and modeling presented in Section I.5 of Attachment I, 
combined with professional judgement. 
The rating system presented in Table II-1 was used to develop correlations between the sorption 
coefficient probability distributions for the elements of interest. Identical parameter ratings 
resulted in a correlation of 100%. If the two highest rating were in the same parameters in the 
same order, a correlation of 75% was assigned. If the two highest ratings were in the same 
parameters but not in the same order, a correlation of 50% was assigned. If the three highest 
ratings were in the same parameters but not in the same order, a correlation of 25% was 
assigned. If the four highest ratings were in the same parameters but not in the same order, a 
correlation of 10% was assigned. If the three highest ratings were not in the same parameters, a 
correlation of 0% was assigned. 

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Table II-1. Ratings of Controls on Sorption Behavior 
Element pH Eh Water 
Chemistry 
Rock 
Comp. 
Surface 
Area 
RN Conc. 
Am (Devit.) 2 No 3 4 1 N/D 
Am (Zeol.) 2 No 3 4 1 N/D 
Am (Vitric) 2 No 3 4 1 N/D 
Cs (Devit.) No No 3 4 2 1 
Cs (Zeol.) No No 2 1 3 4 
Cs (Vitric) No No 3 4 2 1 
Np (Devit.) 3 No 1 4 2 5 
Np (Zeol.) 3 No 1 4 2 5 
Np (Vitric) 3 No 1 4 2 5 
Pa (Devit.) 2 No N/D N/D 1 N/D 
Pa (Zeol.) 2 No N/D N/D 1 N/D 
Pa (Vitric) 2 No N/D N/D 1 N/D 
Pu (Devit.) 4 (No) 2 1 3 5 
Pu (Zeol.) 4 (No) 2 1 3 5 
Pu (Vitric) 4 (No) 2 1 3 5 
Ra (Devit.) No No 3 4 2 1 
Ra (Zeol.) No No 1 2 3 4 
Ra (Vitric) No No 3 4 2 1 
Sr (Devit.) No No 2 4 1 3 
Sr (Zeol.) No No 1 2 3 4 
Sr (Vitric) No No 2 4 1 3 
Th (Devit.) No No 2 N/D 1 N/D 
Th (Zeol.) No No 2 N/D 1 N/D 
Th (Devit.) No No 2 N/D 1 N/D 
U (Devit.) 2 (No) 1 No 4 3 
U (Zeol.) 2 (No) 1 No 4 3 
U (Vitric) 2 (No) 1 No 4 3 
DTN: LA0311AM831341.001 [Output] 
NOTE: 1 = High impact, 5 = Low impact. 
(No) = No impact under oxidizing conditions. Note, however, that rock composition may provide 
locally reducing environments for plutonium to sorb as plutonium IV. For example, ferrous ironbearing 
minerals may provide such local microenvironments. 
N/D = No data available. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment II-7 November 2003 
Table II-2. Correlations For Sampling Sorption Coefficient Probability Distributions 
Element Am 
(Devit.) 
Am 
(Zeol.) 
Am 
(Vitric) 
Cs 
(Devit.) 
Cs 
(Zeol.) 
Cs 
(Vitric) 
Np 
(Devit.) 
Np 
(Zeol.) 
Np 
(Vitric) 
Pa 
(Devit.) 
Pa 
(Zeol.) 
Pa 
(Vitric) 
Pu 
(Devit.) 
Pu 
(Zeol.) 
Pu 
(Vitric) 
Ra 
(Devit.) 
Ra 
(Zeol.) 
Ra 
(Vitric) 
Sr 
(Devit.) 
Sr 
(Zeol.) 
Sr 
(Vitric) 
Th 
(Devit.) 
Th 
(Zeol.) 
Th 
(Vitric) 
U 
(Devit.) 
U 
(Zeol.) 
U 
(Vitric) 
Am 
(Devit.) 
100 
Am 
(Zeol.) 
100 100 
Am 
(Vitric) 
100 100 100 
Cs 
(Devit.) 
0 0 0 100 
Cs 
(Zeol.) 
0 0 0 10 100 
Cs 
(Vitric) 
0 0 0 100 10 100 
Np (Devit.) 25 25 25 0 0 0 100 
Np 
(Zeol.) 
25 25 25 0 0 0 100 100 
Np 
(Vitric) 
25 25 25 0 0 0 100 100 100 
Pa 
(Devit.) 
75 75 75 0 0 0 0 0 0 100 
Pa 
(Zeol.) 
75 75 75 0 0 0 0 0 0 100 100 
Pa 
(Vitric) 
75 75 75 0 0 0 0 0 0 100 100 100 
Pu 
(Devit.) 
10 10 10 0 75 0 10 10 10 0 0 0 100 
Pu 
(Zeol.) 
10 10 10 0 75 0 10 10 10 0 0 0 100 100 
Pu 
(Vitric) 
10 10 10 0 75 0 10 10 10 0 0 0 100 100 100 
Ra 
(Devit.) 
0 0 0 100 10 100 0 0 0 0 0 0 0 0 0 100 
Ra 
(Zeol.) 
0 0 0 10 50 10 0 0 0 0 0 0 50 50 50 10 100 
Ra 
(Vitric) 
0 0 0 100 10 100 0 0 0 0 0 0 0 0 0 100 10 100 
Sr 
(Devit.) 
0 0 0 25 10 25 50 50 50 0 0 0 0 0 0 25 10 25 100 
Sr 
(Zeol.) 
0 0 0 10 50 10 0 0 0 0 0 0 50 50 50 10 100 10 10 100 
Sr 
(Vitric) 
0 0 0 25 10 25 50 50 50 0 0 0 0 0 0 25 10 25 100 10 100 
Th 
(Devit.) 
0 0 0 0 0 0 50 50 50 0 0 0 0 0 0 0 0 0 75 0 75 100 
Th 
(Zeol.) 
0 0 0 0 0 0 50 50 50 0 0 0 0 0 0 0 0 0 75 0 75 100 100 
Th 
(Vitric) 
0 0 0 0 0 0 50 50 50 0 0 0 0 0 0 0 0 0 75 0 75 100 100 100 
U 
(Devit.) 
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 
U 
(Zeol.) 
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 100 
U 
(Vitric) 
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 100 100 
DTN: LA0311AM831341.001 [Output] 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01J Attachment II-8 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment II-9 November 2003 
II.1 CORRELATION OF SAMPLING OF SORPTION-COEFFICIENT PROBABILITY 
DISTRIBUTIONS BETWEEN THE UNSATURATED ZONE AND SATURATED 
ZONE 
The sampling of sorption coefficient probability distributions for the UZ should not be correlated 
with sampling of sorption coefficient probability distributions for the saturated zone (SZ) except 
possibly for the elements radium and cesium in devitrified tuffs. This conclusion is based on an 
analysis of variations in the parameters that have the greatest impact on the sorption behavior of 
the radionuclides of interest (i.e., pH, Eh, water chemistry, rock composition, radionuclide 
concentration). This analysis is discussed in the following. 
 Parameter: pH 
Beneath the repository footprint, variation in pH in SZ groundwater is limited (7.07.2). 
This is likely to be the case in any climate scenario, because the primary control on pH 
is elevated 2 CO P (log = -2.0) maintained from below (i.e., Paleozoic aquifer). Outside 
the repository footprint, pH shows somewhat greater variation (7.07.5). In the UZ, the 
pH of pore water is more variable, particularly in zeolitic units. There is no evidence that 
the pH of SZ groundwaters are correlated with the pH of UZ pore waters or perched 
waters. Therefore, there is no reason to correlate the sorption-coefficient probability 
distributions on the basis of pH. 
 Parameter: Eh 
In the UZ, Eh will always be oxidizing. In the SZ, Eh can be reducing or oxidizing. 
Therefore, there is no reason to correlate the sorption-coefficient probability 
distributions on the basis of Eh. 
 Parameter: Water Chemistry (i.e., ionic strength, alkalinity) 
SZ appears to have groundwater chemistry of glacial times. UZ pore water has 
chemistry of an arid climate. Further, UZ water chemistry appears to be layered, with 
variations mainly in the vertical direction. There is no evidence that UZ pore-water 
chemistry is areally correlated with SZ groundwater chemistry. Therefore, there is no 
reason to correlate the sorption-coefficient probability distributions on the basis of water 
chemistry. 
 Parameter: Rock Composition 
Rock composition (e.g., zeolite compositions) is known to be variable horizontally and 
vertically in both the UZ and SZ. There is no evidence that rock compositions in the UZ 
are areally correlated with rock compositions in the SZ within the repository footprint. 
In fact, rock compositions tend to be layered, with variations primarily in the vertical 
direction. Therefore, there is no reason to correlate the sorption coefficient probability 
distributions on the basis of rock composition. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment II-10 November 2003 
 Parameter: Surface Area 
Rock surface area (see Table I-1 of Attachment I, this Model Report) will not change 
significantly over the regulatory time frame. There is no evidence that rock surface area 
in the UZ is correlated areally with rock surface area in the SZ. This also reflects the 
horizontal layering of rock compositions. Therefore, there is no reason to correlate the 
sorption coefficient probability distributions on the basis of rock surface area. 
 Parameter: Radionuclide Concentration 
If the concentration of a radionuclide in the UZ is on the high end of the range, the 
concentration of the radionuclide in the SZ will also be on the high end of the range. 
Thus, there is a reason to correlate the sorption-coefficient probability distributions. 
However, radionuclide concentrations are the dominant control on radionuclide sorption 
behavior only for radium and cesium on devitrified and vitric tuffs (Table II-1). Thus, it 
would seem appropriate to correlate the sampling of sorption-coefficient distributions 
for these two elements in these two rock types. However, vitric tuffs are not a 
component of the saturated zone. Thus, only sorption-coefficient probability 
distributions for cesium and radium on devitrified tuff in the UZ and the saturated zone 
might need to be correlated. 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-1 November 2003 
ATTACHMENT III 
SUPPORTING GEOLOGICAL DATA FOR THE CONCEPTUAL MODEL 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-3 November 2003 
TABLES 
Page 
III-1. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW SD-6 Borehole............................................................................... III-4 
III-2. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW SD-12 Borehole............................................................................. III-5 
III-3. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW UZ-14 Borehole............................................................................. III-6 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-4 November 2003 
Table III-1. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW SD-6 Borehole. 
Hydrogeologic 
unit 
Thickness (m) Elevation (m) 
tswF6 30.70 1090.00 
tswF7 15.34 1059.30 
tswF8 14.33 1043.96 
tswFv 5.19 1029.63 
ch1Fv 12.50 1024.44 
ch2Fv 7.85 1011.94 
ch3Fv 7.85 1004.09 
ch4Fv 7.85 996.23 
ch5Fv 7.85 988.38 
ch6Fv 15.54 980.53 
pp4Fz 7.59 964.98 
pp3Fd 40.25 957.39 
pp2Fd 11.00 917.14 
pp1Fz 65.34 906.14 
bf3Fd 96.57 840.80 
Source: DTN LB03013DSSCP3I.001 [162379] 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-5 November 2003 
Table III-2. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW SD-12 Borehole. 
Hydrogeologic 
unit 
Thickness (m) Elevation (m) 
tswF5 83.70 1075.30 
tswF6 43.15 991.60 
tswF7 21.57 948.45 
pcF38 9.10 926.88 
pcF39 9.01 917.78 
pcF1z 4.50 908.77 
ch1Fv 18.02 904.26 
ch2Fv 14.33 886.25 
ch3Fv 14.33 871.91 
ch4Fz 14.33 857.58 
ch5Fv 14.33 843.24 
ch6Fz 14.96 828.91 
pp4Fz 8.65 813.95 
pp3Fd 33.54 805.30 
pp2Fd 23.76 771.75 
bf3Fd 96.57 840.80 
Source: DTN LB03013DSSCP3I.001 [162379] 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment III-6 November 2003 
Table III-3. Thickness and Elevation of Hydrogeologic Units in the Vertical Column on the 
Location of USW UZ-14 Borehole. 
Hydrogeologic 
unit 
Thickness (m) Elevation (m) 
tswF6 29.10 1088.40 
tswF7 15.34 1059.30 
tswF8 14.33 1043.96 
tswFv 5.19 1029.63 
ch1Fv 12.50 1024.44 
ch2Fv 7.85 1011.94 
ch3Fv 7.85 1004.09 
ch4Fv 7.85 996.23 
ch5Fv 7.85 988.38 
ch6Fv 15.54 980.53 
pp4Fz 7.59 964.98 
pp3Fd 40.25 957.39 
pp2Fd 11.00 917.14 
pp1Fz 65.34 906.14 
bf3Fd 96.57 840.80 
Source: DTN LB03013DSSCP3I.001 [162379] 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-1 November 2003 
ATTACHMENT IV 
FIGURES FROM THE 237Np 3-D TRANSPORT STUDIES 
(INSTANTANEOUS RELEASE, MEAN PRESENT-DAY INFILTRATION) 
OUTPUT-DTN: LB0307MR0060R1.002 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-3 November 2003 
FIGURES 
Page 
IV.1. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 Layer at t = 10 Years for Mean Present-Day Infiltration and Instantaneous 
Release ..............................................................................................................................5 
IV.2. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 layer at t = 10 Years for Mean Present-Day Infiltration and Instantaneous 
Release ..............................................................................................................................5 
IV.3. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 Layer at t = 100 years for Mean Present-Day Infiltration and Instantaneous 
Release ..............................................................................................................................6 
IV.4. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 Layer at t = 100 years for Mean Present-Day Infiltration and Instantaneous 
Release ..............................................................................................................................6 
IV.5. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 layer at t = 1,000 years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................7 
IV.6. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 Layer at t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................7 
IV.7. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................8 
IV.8. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................8 
IV.9. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 Layer at t = 100,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................9 
IV.10. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 Layer at t = 100,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .......................................................................................................9 
IV.11. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures of the 
tsw39 Layer at t = 1,000,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .....................................................................................................10 
IV.12. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix of the 
tsw39 Layer at t = 1,000,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release .....................................................................................................10 
IV.13. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater Table at t = 10 Years for Mean Present- 
Day Infiltration and Instantaneous Release ....................................................................11 
IV.14. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 10 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................11 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-4 November 2003 
FIGURES (Continued) 
Page 
IV.15. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater at t = 100 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................12 
IV.16. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 100 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................12 
IV.17. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater at t = 1,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................13 
IV.18. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 1,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................13 
IV.19. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater at t = 10,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................14 
IV.20. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 10,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................14 
IV.21. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater at t = 100,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................15 
IV.22. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 100,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release ............................................................................15 
IV.23. Distribution of the Relative Mass Fraction XR of 237Np in the Fractures 
Immediately Above the Groundwater at t = 1,000,000 Years for Mean Present- 
Day Infiltration and Instantaneous Release ....................................................................16 
IV.24. Distribution of the Relative Mass Fraction XR of 237Np in the Matrix 
Immediately Above the Groundwater at t = 1,000,000 Years for Mean Present- 
Day Infiltration and Instantaneous Release ....................................................................16 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-5 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Np-PM-TSw-FL-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.1. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 Layer at t = 10 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Np-TSw-ML-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.2. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 layer at t = 10 Years for Mean 
Present-Day Infiltration and Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-6 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Np-TSw-FL-100 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.3. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 Layer at t = 100 years for 
Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Relative Mass Fraction 
Np-TSw-ML-100 Output-DTN: LB0307MR0060R1.002 
Figure IV.4. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 Layer at t = 100 years for Mean 
Present-Day Infiltration and Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-7 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-PM-TSw-FL-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.5. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 layer at t = 1,000 years for 
Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Np-TSw-ML-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.6. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 Layer at t = 1,000 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-8 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-TSw-FL-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.7. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 Layer at t = 10,000 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-TSw-ML-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.8. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 Layer at t = 10,000 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-9 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Np-TSw-FL-100,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.9. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 Layer at t = 100,000 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-TSw-ML-100,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.10. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 Layer at t = 100,000 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-10 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-07 
9.50E-08 
9.00E-08 
8.50E-08 
8.00E-08 
7.50E-08 
7.00E-08 
6.50E-08 
6.00E-08 
5.50E-08 
5.00E-08 
4.50E-08 
4.00E-08 
3.50E-08 
3.00E-08 
2.50E-08 
2.00E-08 
1.50E-08 
1.00E-08 
5.00E-09 
0.00E+00 
Np-TSw-FL-1,000,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.11. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures of the tsw39 Layer at t = 1,000,000 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Np-TSw-ML-1,000,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.12. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix of the tsw39 Layer at t = 1,000,000 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-11 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Np-WT-FL-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.13. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater 
Table at t = 10 Years for Mean Present-Day Infiltration 
and Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Np-WT-ML-10 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.14. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at t = 
10 Years for Mean Present-Day Infiltration and 
Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-12 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Np-WT-FL-100 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.15. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater at 
t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-ML-100 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.16. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at 
t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-13 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Np-WT-FL-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.17. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater at 
t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-ML-1000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.18. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at 
t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-14 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-FL-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.19. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater at 
t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-ML-10,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.20. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at 
t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-15 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-FL-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.21. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater at 
t = 100,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Np-WT-ML-100,000 Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.22. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at 
t = 100,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment IV-16 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-07 
9.50E-08 
9.00E-08 
8.50E-08 
8.00E-08 
7.50E-08 
7.00E-08 
6.50E-08 
6.00E-08 
5.50E-08 
5.00E-08 
4.50E-08 
4.00E-08 
3.50E-08 
3.00E-08 
2.50E-08 
2.00E-08 
1.50E-08 
1.00E-08 
5.00E-09 
0.00E+00 
Np-WT-FL-1,000,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.23. Distribution of the Relative Mass Fraction XR of 237Np in 
the Fractures Immediately Above the Groundwater at 
t = 1,000,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Np-WT-ML-1,000,000 
Relative Mass Fraction 
Output-DTN: LB0307MR0060R1.002 
Figure IV.24. Distribution of the Relative Mass Fraction XR of 237Np in 
the Matrix Immediately Above the Groundwater at 
t = 1,000,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-1 November 2003 
ATTACHMENT V 
FIGURES FROM THE 99Tc 3-D TRANSPORT STUDIES 
(CONTINUOUS RELEASE, MEAN PRESENT-DAY INFILTRATION) 
Output-DTN: LB0307MR0060R1.004 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-3 November 2003 
FIGURES 
Page 
V.1. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
tsw39 Layer at t = 10 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................5 
V.2. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration and Continuous Release ..........5 
V.3. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
tsw39 Layer at t = 100 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................6 
V.4. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 
Layer at t = 100 Years for Mean Present-Day Infiltration and Continuous Release ........6 
V.5. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
tsw39 Layer at t = 1,000 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................7 
V.6. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................7 
V.7. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
tsw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................8 
V.8. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................8 
V.9. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
tsw39 Layer at t = 100,000 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................9 
V.10. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day Infiltration and Continuous Release ................9 
V.11. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
Immediately Above the Groundwater Table at t = 10 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................10 
V.12. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix 
Immediately Above the Groundwater at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................10 
V.13. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
Immediately Above the Groundwater at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................11 
V.14. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately 
Above the groundwater at t = 100 Years for Mean Present-Day Infiltration and 
Continuous Release.........................................................................................................11 
V.15. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
Immediately Above the Groundwater at T = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................12 
V.16. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately 
Above the Groundwater at t = 1,000 Years for Mean Present-Day Infiltration and 
Continuous Release.........................................................................................................12 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-4 November 2003 
FIGURES 
Page 
V.17. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
Immediately Above the Groundwater at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................13 
V.18. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately 
Above the Groundwater at t = 10,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................13 
V.19. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
Immediately Above the Groundwater at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................14 
V.20. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix Immediately 
Above the Groundwater at t = 100,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................14 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-5 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Tc at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.1. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the tsw39 Layer at t = 10 Years for 
Mean Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Tc at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.2. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix of the tsw39 Layer at t = 
10 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-6 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Tc at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.3. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures of the tsw39 Layer at t 
= 100 Years for Mean Present-Day Infiltration 
and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Tc at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.4. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix of the tsw39 Layer at t = 
100 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-7 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Tc at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.5. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures of the tsw39 Layer at t 
= 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Tc at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.6. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix of the tsw39 Layer at 
t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-8 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Tc at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.7. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures of the tsw39 Layer at t 
= 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Tc at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.8. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix of the tsw39 Layer at t = 
10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-9 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Tc at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.9. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures of the tsw39 Layer at t 
= 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Tc at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.10. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix of the tsw39 Layer at 
t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-10 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(for Tc at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.11. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures Immediately Above 
the Groundwater Table at t = 10 Years for 
Mean Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+0 
Matrix Mass Fraction at Water Table 
(for Tc at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.12. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix Immediately Above the Groundwater at t 
= 10 Years for Mean Present-Day Infiltration and 
Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-11 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(for Tc at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.13. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures Immediately Above 
the Groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.100 
0.095 
0.090 
0.085 
0.080 
0.075 
0.070 
0.065 
0.060 
0.055 
0.050 
0.045 
0.040 
0.035 
0.030 
0.025 
0.020 
0.015 
0.010 
0.005 
0.000 
Matrix Mass Fraction at Water Table 
(for Tc at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.14. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix Immediately Above the 
groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-12 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction atWater Table 
(for Tc at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.15. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures Immediately Above 
the Groundwater at T = 1,000 Years for Mean 
Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Water Table 
(for Tc at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.16. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix Immediately Above the 
Groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-13 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction atWater Table 
(for Tc at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.17. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures Immediately Above 
the Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Water Table 
(for Tc at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.18. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix Immediately Above the 
Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment V-14 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction atWater Table 
(for Tc at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.19. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Fractures Immediately Above 
the Groundwater at t = 100,000 Years for 
Mean Present-Day Infiltration and Continuous 
Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Water Table 
(for Tc at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure V.20. Distribution of the Relative Mass Fraction XR 
of 99Tc in the Matrix Immediately Above the 
Groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous 
Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-1 November 2003 
ATTACHMENT VI 
FIGURES FROM THE 3-D TRANSPORT STUDIES OF THE 
6 nm 239PuO2 COLLOID IN CASE 2 
(CONTINOUS RELEASE, MEAN PRESENT-DAY INFILTRATION) 
Output-DTN: LB0307MR0060R1.004 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-3 November 2003 
FIGURES 
Page 
VI.1. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures of the tsw39 Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release....................................................................................................7 
VI.2. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................7 
VI.3. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................8 
VI.4. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures of the tsw39 Layer at t = 100 Years for Mean Present-Day Infiltration 
and Continuous Release....................................................................................................8 
VI.5. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix of the tsw39 Layer at t = 100 Years for Mean Present-Day Infiltration and 
Continuous Release...........................................................................................................9 
VI.6. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................9 
VI.7. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures of the tsw39 Layer at t = 1,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................10 
VI.8. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix of the tsw39 Layer at t = 1,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................10 
VI.9. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................11 
VI.10. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures of the tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................11 
VI.11. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix of the tsw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................12 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-4 November 2003 
FIGURES 
Page 
VI.12. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................12 
VI.13. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures of the tsw39 Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................13 
VI.14. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix of the tsw39 Layer at t = 100,000 Years for Mean Present-Day Infiltration 
and Continuous Release..................................................................................................13 
VI.15. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................14 
VI.16. Distribution of the Relative Mass Fraction XR of the 6 nm239PuO2 Colloid in the 
Fractures immediately above the groundwater table at t = 10 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................14 
VI.17. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix immediately above the groundwater at t = 10 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................15 
VI.18. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................15 
VI.19. Distribution of the Relative Mass Fraction XR of the 6 nm239PuO2 Colloid in the 
Fractures immediately above the groundwater at t = 100 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................16 
VI.20. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix immediately above the groundwater at t = 100 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................16 
VI.21. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................17 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-5 November 2003 
FIGURES 
Page 
VI.22. Distribution of the Relative Mass Fraction XR of the 6 nm239PuO2 Colloid in the 
Fractures immediately above the groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................17 
VI.23. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix immediately above the groundwater at t = 1,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................18 
VI.24. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................18 
VI.25. Distribution of the Relative Mass Fraction XR of the 6 nm239PuO2 Colloid in the 
Fractures immediately above the groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................19 
VI.26. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix immediately above the groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................19 
VI.27. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................20 
VI.28. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Fractures immediately above the groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................20 
VI.29. Distribution of the Relative Mass Fraction XR of the 6 nm 239PuO2 Colloid in the 
Matrix immediately above the groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................21 
VI.30. Distribution of the Relative filtered concentration FR of the 6 nm 239PuO2 Colloid 
in the Matrix of the tsw39 Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................21 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-6 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-7 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co006 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.1. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release 
Nevada Coordinate E-W (m) Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 2.00E-0 
1.90E-0 
1.80E-0 
1.70E-0 
1.60E-0 
1.50E-0 
1.40E-0 
1.30E-0 
1.20E-0 
1.10E-0 
1.00E-0 
9.00E-0 
8.00E-0 
7.00E-0 
6.00E-0 
5.00E-0 
4.00E-0 
3.00E-0 
2.00E-0 
1.00E-0 
0.00E+ 
Matrix Mass Fraction at Bottom of TSw 
(for Co006 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.2. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix of the tsw39 Layer at 
t = 10 Years for Mean Present-Day Infiltration and 
Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-8 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co006 at 10 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.3. Distribution of the Relative filtered concentration XR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co006 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.4. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 100 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-9 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 2.00E-02 
1.90E-02 
1.80E-02 
1.70E-02 
1.60E-02 
1.50E-02 
1.40E-02 
1.30E-02 
1.20E-02 
1.10E-02 
1.00E-02 
9.00E-03 
8.00E-03 
7.00E-03 
6.00E-03 
5.00E-03 
4.00E-03 
3.00E-03 
2.00E-03 
1.00E-03 
0.00E+00 
Matrix Mass Fraction at Bottom of TSw 
(for Co006 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.5. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix of the tsw39 Layer at 
t = 100 Years for Mean Present-Day Infiltration and 
Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co006 at 100 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.6. Distribution of the Relative filtered concentration XR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-10 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co006 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.7. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 2.00E-01 
1.90E-01 
1.80E-01 
1.70E-01 
1.60E-01 
1.50E-01 
1.40E-01 
1.30E-01 
1.20E-01 
1.10E-01 
1.00E-01 
9.00E-02 
8.00E-02 
7.00E-02 
6.00E-02 
5.00E-02 
4.00E-02 
3.00E-02 
2.00E-02 
1.00E-02 
0.00E+00 
Matrix Mass Fraction at Bottom of TSw 
(for Co006 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.8. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix of the tsw39 Layer at 
t = 1,000 Years for Mean Present-Day Infiltration and 
Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-11 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co006 at 1000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.9. Distribution of the Relative filtered concentration XR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co006 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.10. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-12 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Co006 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.11. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix of the tsw39 Layer at 
t = 10,000 Years for Mean Present-Day Infiltration and 
Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co006 at 10000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.12. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-13 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.100 
0.095 
0.090 
0.085 
0.080 
0.075 
0.070 
0.065 
0.060 
0.055 
0.050 
0.045 
0.040 
0.035 
0.030 
0.025 
0.020 
0.015 
0.010 
0.005 
0.000 
Fracture Mass Fraction at Bottom of TSw 
(for Co006 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.13. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.100 
0.095 
0.090 
0.085 
0.080 
0.075 
0.070 
0.065 
0.060 
0.055 
0.050 
0.045 
0.040 
0.035 
0.030 
0.025 
0.020 
0.015 
0.010 
0.005 
0.000 
Matrix Mass Fraction at Bottom of TSw 
(for Co006 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.14. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix of the tsw39 Layer at 
t = 100,000 Years for Mean Present-Day Infiltration and 
Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-14 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co006 at 100000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.15. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(forCo006 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.16. Distribution of the Relative Mass Fraction XR of the 
6 nm239PuO2 Colloid in the Fractures immediately 
above the groundwater table at t = 10 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-15 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-07 
9.50E-08 
9.00E-08 
8.50E-08 
8.00E-08 
7.50E-08 
7.00E-08 
6.50E-08 
6.00E-08 
5.50E-08 
5.00E-08 
4.50E-08 
4.00E-08 
3.50E-08 
3.00E-08 
2.50E-08 
2.00E-08 
1.50E-08 
1.00E-08 
5.00E-09 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co006 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.17. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix immediately above 
the groundwater at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co006 at 10 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.18. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-16 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(for Co006 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.19. Distribution of the Relative Mass Fraction XR of the 
6 nm239PuO2 Colloid in the Fractures immediately 
above the groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co006 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.20. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix immediately above 
the groundwater at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-17 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co006 at 100 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.21. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100 Years for Mean Present-Day Infiltration 
and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(forCo006 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.22. Distribution of the Relative Mass Fraction XR of the 
6 nm239PuO2 Colloid in the Fractures immediately 
above the groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-18 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co006 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.23. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix immediately above 
the groundwater at t = 1,000 Years for Mean Present- 
Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co006 at 1000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.24. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-19 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.50 
0.48 
0.45 
0.43 
0.40 
0.38 
0.35 
0.33 
0.30 
0.28 
0.25 
0.23 
0.20 
0.18 
0.15 
0.13 
0.10 
0.08 
0.05 
0.03 
0.00 
Fracture Mass Fraction atWater Table 
(for Co006 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.25. Distribution of the Relative Mass Fraction XR of the 
6 nm239PuO2 Colloid in the Fractures immediately 
above the groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co006 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.26. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix immediately above 
the groundwater at t = 10,000 Years for Mean Present- 
Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-20 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co006 at 10000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.27. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.100 
0.095 
0.090 
0.085 
0.080 
0.075 
0.070 
0.065 
0.060 
0.055 
0.050 
0.045 
0.040 
0.035 
0.030 
0.025 
0.020 
0.015 
0.010 
0.005 
0.000 
Fracture Mass Fraction atWater Table 
(for Co006 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.28. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Fractures immediately 
above the groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-21 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
3.21E-02 
3.06E-02 
2.91E-02 
2.75E-02 
2.60E-02 
2.45E-02 
2.29E-02 
2.14E-02 
1.99E-02 
1.84E-02 
1.68E-02 
1.53E-02 
1.38E-02 
1.22E-02 
1.07E-02 
9.18E-03 
7.65E-03 
6.12E-03 
4.59E-03 
3.06E-03 
1.53E-03 
Matrix Mass Fraction at Water Table 
(for Co006 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VI.29. Distribution of the Relative Mass Fraction XR of the 
6 nm 239PuO2 Colloid in the Matrix immediately above 
the groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co006 at 100000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VI.30. Distribution of the Relative filtered concentration FR of 
the 6 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VI-22 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-1 November 2003 
ATTACHMENT VII 
FIGURES FROM THE 3-D TRANSPORT STUDIES OF 
THE 450 nm 239PuO2 COLLOID IN CASE 2 
(CONTINOUS RELEASE, MEAN PRESENT-DAY INFILTRATION) 
Output-DTN: LB0307MR0060R1.004 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-3 November 2003 
FIGURES 
Page 
VII.1. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures of the tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................7 
VII.2. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release....................................................................................................7 
VII.3. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................8 
VII.4. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures of the tsw39 Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................8 
VII.5. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix of the tsw39 Layer at t = 100 Years for Mean Present-Day Infiltration 
and Continuous Release....................................................................................................9 
VII.6. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release..................................................................................9 
VII.7. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures of the tsw39 Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................10 
VII.8. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix of the tsw39 Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................10 
VII.9. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 1,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................11 
VII.10. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures of the tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................11 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-4 November 2003 
FIGURES 
Page 
VII.11. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix of the tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................12 
VII.12. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 10,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................12 
VII.13. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures of the tsw39 Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................13 
VII.14. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix of the tsw39 Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................13 
VII.15. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 100,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................14 
VII.16. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures Immediately Above the Groundwater Table at t = 10 Years for 
Mean Present-Day Infiltration and Continuous Release.................................................14 
VII.17. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix Immediately Above the Groundwater at t = 10 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................15 
VII.18. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................15 
VII.19. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures Immediately Above the Groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................16 
VII.20. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix Immediately Above the Groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................16 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-5 November 2003 
FIGURES 
Page 
VII.21. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................17 
VII.22. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures Immediately Above the Groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................17 
VII.23. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix Immediately Above the Groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................18 
VII.24. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release................................................................................18 
VII.25. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures Immediately Above the Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................19 
VII.26. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix Immediately Above the Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................19 
VII.27. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 layer at t = 10,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................20 
VII.28. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Fractures Immediately Above the Groundwater at t = 100,000 Years for 
Mean Present-Day Infiltration and Continuous Release.................................................20 
VII.29. Distribution of the Relative Mass Fraction XR of the 450 nm 239PuO2 Colloid in 
the Matrix Immediately Above the Groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release...........................................................21 
VII.30. Distribution of the Relative Filtered Concentration XR of the 450 nm 239PuO2 
Colloid in the Matrix of the tsw39 layer at t = 100,000 Years for Mean Present- 
Day Infiltration and Continuous Release........................................................................21 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-6 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-7 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co450 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.1. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Matrix Mass Fraction at Bottom of TSw 
(for Co450 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.2. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10 Years for Mean Present-Day Infiltration 
and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-8 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+02 
7.08E+01 
5.01E+01 
3.55E+01 
2.51E+01 
1.78E+01 
1.26E+01 
8.91E+00 
6.31E+00 
4.47E+00 
3.16E+00 
2.24E+00 
1.58E+00 
1.12E+00 
7.94E-01 
5.62E-01 
3.98E-01 
2.82E-01 
2.00E-01 
1.41E-01 
1.00E-01 
Matrix Filtered Concentration at Bottom of TSw 
(for Co450 at 10 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.3. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co450 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.4. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-9 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.020 
0.019 
0.018 
0.017 
0.016 
0.015 
0.014 
0.013 
0.012 
0.011 
0.010 
0.009 
0.008 
0.007 
0.006 
0.005 
0.004 
0.003 
0.002 
0.001 
0.000 
Matrix Mass Fraction at Bottom of TSw 
(for Co450 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.5. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co450 at 100 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.6. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-10 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co450 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.7. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.20 
0.19 
0.18 
0.17 
0.16 
0.15 
0.14 
0.13 
0.12 
0.11 
0.10 
0.09 
0.08 
0.07 
0.06 
0.05 
0.04 
0.03 
0.02 
0.01 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Co450 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.8. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-11 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co450 at 1000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.9. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Fracture Mass Fraction at Bottom of TSw 
(for Co450 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.10. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-12 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.00 
0.95 
0.90 
0.85 
0.80 
0.75 
0.70 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Co450 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.11. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co450 at 10000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.12. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-13 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.100 
0.095 
0.090 
0.085 
0.080 
0.075 
0.070 
0.065 
0.060 
0.055 
0.050 
0.045 
0.040 
0.035 
0.030 
0.025 
0.020 
0.015 
0.010 
0.005 
0.000 
Fracture Mass Fraction at Bottom of TSw 
(for Co450 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.13. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.20 
0.19 
0.18 
0.17 
0.16 
0.15 
0.14 
0.13 
0.12 
0.11 
0.10 
0.09 
0.08 
0.07 
0.06 
0.05 
0.04 
0.03 
0.02 
0.01 
0.00 
Matrix Mass Fraction at Bottom of TSw 
(for Co450 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.14. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix of the tsw39 
Layer at t = 100,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-14 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Bottom of TSw 
(for Co450 at 100000 years) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.15. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 100,000 Years for Mean Present- 
Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.50 
1.43 
1.35 
1.27 
1.20 
1.13 
1.05 
0.97 
0.90 
0.82 
0.75 
0.67 
0.60 
0.53 
0.45 
0.38 
0.30 
0.22 
0.15 
0.07 
0.00 
Fracture Mass Fraction atWater Table 
(forCo450 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.16. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures Immediately 
Above the Groundwater Table at t = 10 Years for 
Mean Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-15 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co450 at 10 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.17. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix Immediately 
Above the Groundwater at t = 10 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co450 at 10 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.18. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 Layer at t = 10 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-16 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.50 
1.43 
1.35 
1.27 
1.20 
1.13 
1.05 
0.97 
0.90 
0.82 
0.75 
0.67 
0.60 
0.53 
0.45 
0.38 
0.30 
0.22 
0.15 
0.07 
0.00 
Fracture Mass Fraction atWater Table 
(for Co450 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.19. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures Immediately 
Above the Groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co450 at 100 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.20. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix Immediately 
Above the Groundwater at t = 100 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-17 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co450 at 100 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.21. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 layer at t = 100 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.50 
1.43 
1.35 
1.27 
1.20 
1.13 
1.05 
0.97 
0.90 
0.82 
0.75 
0.67 
0.60 
0.53 
0.45 
0.38 
0.30 
0.22 
0.15 
0.07 
0.00 
Fracture Mass Fraction atWater Table 
(forCo450 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.22. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures Immediately 
Above the Groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-18 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Matrix Mass Fraction at Water Table 
(for Co450 at 1000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.23. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix Immediately 
Above the Groundwater at t = 1,000 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co450 at 1000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.24. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 layer at t = 1,000 Years for Mean Present-Day 
Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-19 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 1.50 
1.43 
1.35 
1.27 
1.20 
1.13 
1.05 
0.97 
0.90 
0.82 
0.75 
0.67 
0.60 
0.53 
0.45 
0.38 
0.30 
0.22 
0.15 
0.07 
0.00 
Fracture Mass Fraction atWater Table 
(for Co450 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.25. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures Immediately 
Above the Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
0.20 
0.19 
0.18 
0.17 
0.16 
0.15 
0.14 
0.13 
0.12 
0.11 
0.10 
0.09 
0.08 
0.07 
0.06 
0.05 
0.04 
0.03 
0.02 
0.01 
0.00 
Matrix Mass Fraction at Water Table 
(for Co450 at 10000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.26. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix Immediately 
Above the Groundwater at t = 10,000 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-20 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co450 at 10000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.27. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 layer at t = 10,000 Years for Mean Present-Day 
Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 0.30 
0.28 
0.27 
0.26 
0.24 
0.22 
0.21 
0.20 
0.18 
0.16 
0.15 
0.14 
0.12 
0.11 
0.09 
0.07 
0.06 
0.04 
0.03 
0.01 
0.00 
Fracture Mass Fraction atWater Table 
(for Co450 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.28. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Fractures Immediately 
Above the Groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-21 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
0.030 
0.029 
0.027 
0.026 
0.024 
0.022 
0.021 
0.020 
0.018 
0.017 
0.015 
0.014 
0.012 
0.011 
0.009 
0.007 
0.006 
0.005 
0.003 
0.002 
0.000 
Matrix Mass Fraction at Water Table 
(for Co450 at 100000 years) 
Output-DTN: LB0307MR0060R1.004 
Figure VII.29. Distribution of the Relative Mass Fraction XR of the 
450 nm 239PuO2 Colloid in the Matrix Immediately 
Above the Groundwater at t = 100,000 Years for Mean 
Present-Day Infiltration and Continuous Release 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E+04 
3.98E+03 
1.58E+03 
6.31E+02 
2.51E+02 
1.00E+02 
3.98E+01 
1.58E+01 
6.31E+00 
2.51E+00 
1.00E+00 
3.98E-01 
1.58E-01 
6.31E-02 
2.51E-02 
1.00E-02 
3.98E-03 
1.58E-03 
6.31E-04 
2.51E-04 
1.00E-04 
Matrix Filtered Concentration at Water Table 
( for Co450 at 100000 years ) 
kg/m3 
Output-DTN: LB0307MR0060R1.004 
Figure VII.30. Distribution of the Relative Filtered Concentration XR 
of the 450 nm 239PuO2 Colloid in the Matrix of the 
tsw39 layer at t = 100,000 Years for Mean Present- 
Day Infiltration and Continuous Release 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VII-22 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-1 November 2003 
ATTACHMENT VIII 
FIGURES FROM THE 99Tc 3-D TRANSPORT STUDIES 
(INSTANTANEOUS RELEASE ONLY FROM NON-FAULTED DOMAIN, MEAN 
PRESENT-DAY INFILTRATION) 
Output-DTN: LB0307MR0060R1.002 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-2 November 2003 
INTENTIONALLY LEFT BLANK 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-3 November 2003 
FIGURES 
Page 
VIII.1. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
TSw39 Layer at t = 10 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................5 
VIII.2. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the TSw39 
Layer at t = 10 Years for Mean Present-Day Infiltration and Instantaneous 
Release only from Non-Faulted Domain. .........................................................................5 
VIII.3. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
TSw39 Layer at t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................6 
VIII.4. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the TSw39 
Layer at t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................6 
VIII.5. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
TSw39 Layer at t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................7 
VIII.6. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the TSw39 
Layer at t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................7 
VIII.7. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
TSw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................8 
VIII.8. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the 
TSw39 Layer at t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................8 
VIII.9. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures of the 
TSw39 Layer at t = 100,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release only from Non-Faulted Domain. ...........................................9 
VIII.10. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix of the TSw39 
Layer at t = 100,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ..................................................9 
VIII.11. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
immediately above the groundwater table at t = 10 Years for Mean Present-Day 
Infiltration and Instantaneous Release only from Non-Faulted Domain. .......................10 
VIII.12. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix immediately 
above the groundwater at t = 10 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ................................................10 
VIII.13. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
immediately above the groundwater at t = 100 Years for Mean Present-Day 
Infiltration and Instantaneous Release only from Non-Faulted Domain. .......................11 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-4 November 2003 
FIGURES 
Page 
VIII.14. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix immediately 
above the groundwater at t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ................................................11 
VIII.15. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
immediately above the groundwater at t = 1,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release only from Non-Faulted Domain. .......................12 
VIII.16. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix immediately 
above the groundwater at t = 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ................................................12 
VIII.17. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
immediately above the groundwater at t = 10,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release only from Non-Faulted Domain. .......................13 
VIII.18. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix immediately 
above the groundwater at t = 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release only from Non-Faulted Domain. ................................................13 
VIII.19. Distribution of the Relative Mass Fraction XR of 99Tc in the Fractures 
immediately above the groundwater at t = 100,000 Years for Mean Present-Day 
Infiltration and Instantaneous Release only from Non-Faulted Domain. .......................14 
VIII.20. Distribution of the Relative Mass Fraction XR of 99Tc in the Matrix immediately 
above the groundwater at t = 100,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release only from Non-Faulted Domain. .........................................14 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-5 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-NF-FL-10 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.1. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the TSw39 Layer at t = 10 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-02 
9.50E-03 
9.00E-03 
8.50E-03 
8.00E-03 
7.50E-03 
7.00E-03 
6.50E-03 
6.00E-03 
5.50E-03 
5.00E-03 
4.50E-03 
4.00E-03 
3.50E-03 
3.00E-03 
2.50E-03 
2.00E-03 
1.50E-03 
1.00E-03 
5.00E-04 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-NF-ML-10 Output-DTN: LB0307MR0060R1.002 
Figure VIII.2. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix of the TSw39 Layer at t = 10 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-6 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Fraction 
Tc-TSw-NF-FL-100 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.3. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the TSw39 Layer at t = 100 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Fraction 
Tc-TSw-NF-ML-100 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.4. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix of the TSw39 Layer at t = 100 Years for 
Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-7 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Fraction 
Tc-TSw-NF-FL-1000 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.5. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the TSw39 Layer at t = 1,000 
Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-NF-ML-1000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.6. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix of the TSw39 Layer at t = 1,000 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-8 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-NF-FL-10,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.7. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the TSw39 Layer at t = 10,000 
Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Fraction 
Tc-TSw-NF-ML-10,000 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.8. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix of the TSw39 Layer at t = 10,000 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-9 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-07 
9.50E-08 
9.00E-08 
8.50E-08 
8.00E-08 
7.50E-08 
7.00E-08 
6.50E-08 
6.00E-08 
5.50E-08 
5.00E-08 
4.50E-08 
4.00E-08 
3.50E-08 
3.00E-08 
2.50E-08 
2.00E-08 
1.50E-08 
1.00E-08 
5.00E-09 
0.00E+00 
Fraction 
Tc-TSw-NF-FL-100,000 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.9. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures of the TSw39 Layer at t = 100,000 
Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Relative Mass Fraction 
Tc-TSw-NF-ML-100,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.10. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix of the TSw39 Layer at t = 100,000 Years 
for Mean Present-Day Infiltration and Instantaneous 
Release Only from Non-Faulted Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-10 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-03 
9.50E-04 
9.00E-04 
8.50E-04 
8.00E-04 
7.50E-04 
7.00E-04 
6.50E-04 
6.00E-04 
5.50E-04 
5.00E-04 
4.50E-04 
4.00E-04 
3.50E-04 
3.00E-04 
2.50E-04 
2.00E-04 
1.50E-04 
1.00E-04 
5.00E-05 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-FL-10 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.11. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures immediately above the groundwater 
table at t = 10 Years for Mean Present-Day Infiltration 
and Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-ML-10 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.12. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix immediately above the groundwater at t 
= 10 Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-11 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-04 
9.50E-05 
9.00E-05 
8.50E-05 
8.00E-05 
7.50E-05 
7.00E-05 
6.50E-05 
6.00E-05 
5.50E-05 
5.00E-05 
4.50E-05 
4.00E-05 
3.50E-05 
3.00E-05 
2.50E-05 
2.00E-05 
1.50E-05 
1.00E-05 
5.00E-06 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-FL-100 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.13. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures immediately above the groundwater 
at t = 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-ML-100 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.14. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix immediately above the groundwater at t 
= 100 Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-12 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Fraction 
Tc-WT-NF-FL-1,000 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.15. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures immediately above the groundwater 
at t = 1,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-ML-1,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.16. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix immediately above the groundwater at t 
= 1,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-13 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-FL-10,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.17. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures immediately above the groundwater 
at t = 10,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-ML-10,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.18. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix immediately above the groundwater at t 
= 10,000 Years for Mean Present-Day Infiltration and 
Instantaneous Release Only from Non-Faulted 
Domain 

Radionuclide Transport Models Under Ambient Conditions U0060 
MDL-NBS-HS-000008 REV 01 Attachment VIII-14 November 2003 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-06 
9.50E-07 
9.00E-07 
8.50E-07 
8.00E-07 
7.50E-07 
7.00E-07 
6.50E-07 
6.00E-07 
5.50E-07 
5.00E-07 
4.50E-07 
4.00E-07 
3.50E-07 
3.00E-07 
2.50E-07 
2.00E-07 
1.50E-07 
1.00E-07 
5.00E-08 
0.00E+00 
Fraction 
Tc-WT-NF-FL-100,000 
Relative Mass Output-DTN: LB0307MR0060R1.002 
Figure VIII.19. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Fractures immediately above the groundwater 
at t = 100,000 Years for Mean Present-Day Infiltration 
and Instantaneous Release Only from Non-Faulted 
Domain 
Nevada Coordinate E-W (m) 
Nevada Coordinate N-S (m) 
168000 170000 172000 174000 
230000 
232000 
234000 
236000 
238000 
1.00E-05 
9.50E-06 
9.00E-06 
8.50E-06 
8.00E-06 
7.50E-06 
7.00E-06 
6.50E-06 
6.00E-06 
5.50E-06 
5.00E-06 
4.50E-06 
4.00E-06 
3.50E-06 
3.00E-06 
2.50E-06 
2.00E-06 
1.50E-06 
1.00E-06 
5.00E-07 
0.00E+00 
Relative Mass Fraction 
Tc-WT-NF-ML-100,000 
Output-DTN: LB0307MR0060R1.002 
Figure VIII.20. Distribution of the Relative Mass Fraction XR of 99Tc 
in the Matrix immediately above the groundwater at t = 100,000 
Years for Mean Present-Day Infiltration and Instantaneous Release 
Only from Non-Faulted Domain