NUREG/CR-6911

Tests of Uranium (VI) Adsorption 

Models in a Field Setting 

U.S. Geological Survey 

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research 

Washington, DC 20555-0001
 

 

 

 NUREG/CR-6911 

 

Tests of Uranium (VI) Adsorption

Models in a Field Setting

Manuscript Completed: August 2006

Date Published: August 2006

Prepared by

G. P. Curtis, J. A. Davis

Water Resources Division

U.S. Geological Survey

Menlo Park, CA 94025

A. L. Schwartzman, NRC Project Manager

Prepared for

Division of Fuel, Engineering, and Radiological Research 

Office of Nuclear Regulatory Research 

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

Job Code Y6462
ii
ABSTRACT 

Field-based techniques were tested for determining Kd values or for validating surface 

complexation model-derived Kd values. The field site used for the study was a uranium mill 

tailings site at Naturita, Colorado. The techniques tested included: 1) the use of downhole in-situ

devices that held a sample of a single mineral or sediment that were deployed in the aquifer 

contaminated with uranium, 2) in-situ push-pull tracer tests conducted within the contaminated 

aquifer, and 3) small-scale U(VI) migration tracer tests conducted within the aquifer. The 

experiments were conducted on scales that ranged from centimeters for the downhole devices to 

several meters for the small-scale tracer tests. 

The tracer test results showed that U(VI) that has been present in the Naturita aquifer for several 

decades could be readily desorbed by perturbing groundwater chemical conditions. The 

experimental observations clearly demonstrated that in aquifers where U(VI) concentrations are 

controlled by adsorption, dissolved U(VI) concentrations can be rapidly impacted by increases or 

decreases in alkalinity. The experimental results in U(VI) migration tests were reasonably well 

described by a reactive transport model that simulated adsorption reactions using a semimechanistic surface complexation modeling approach. The model predicted both increases and 

decreases of U(VI) concentration reasonably well when the transport parameters were calibrated 

to observed Br transport. The results demonstrate the adequacy of the model for simulation of 

transient geochemical effects under the influence of a natural gradient. In contrast, a constant-Kd

model would have predicted neither the observed increases nor decreases in U(VI) concentration 

in tests in which only the alkalinity of the groundwater was perturbed. This indicates that the 

uncertainty of predictions using the SCM approach were much smaller than those that would have 

been obtained if a constant-Kd approach had been used to model U(VI) adsorption. A detailed 

understanding of U(VI) surface and aqueous speciation is required to predict changes in U(VI) 

concentration in the Naturita aquifer, and likely in other aquifers contaminated with U(VI). 

It was concluded that push-pull test results were not useful in the Naturita aquifer for evaluating 

adsorption model parameters. The limitation results from the nearly reversible nature of the 

reactive transport simulations when applied to cases where sorption processes are probed by 

manipulating groundwater alkalinity. Velocity and/or dispersive processes in the aquifer were 

sufficiently large that geochemical effects were dampened by dilution in most of the experiments. 

Push-pull tests may be useful for studying rates of sorption and desorption in aquifers. 

The results with downhole in-situ devices for measuring Kd values suggest that the method needs 

further improvement. Furthermore, the experiments suggest that surface complexation models 

for single minerals need to be calibrated in solutions with high dissolved carbonate concentrations 

in order to be applied to aquifers that contain groundwaters in equilibrium with partial pressures 

of carbon dioxide gas greater than 0.01 atmospheres, such as the Naturita aquifer. 

iii
iv
FOREWORD 

The U.S. Nuclear Regulatory Commission (NRC) is responsible for the regulatory oversight of

remediation and cleanup of sites contaminated with radionuclides. Regulatory decisions 

associated with this responsibility are based, in part, on performance assessment (PA) 

calculations that utilize numerical models to estimate radioactive exposure at selected locations. 

Determining the radioactive exposure risk in PA requires the calculation of total radionuclide 

concentrations present at a specific site. Subsurface transport models used by the NRC and its 

licensees estimate the effects of the anticipated interactions between radionuclides and solids in 

the ground. In practice, however, most reactive transport models summarize the chemical 

complexity of aqueous complexation and sorption processes by utilizing a single constant 

distribution coefficient (i.e., Kd value) approach. This approach defines the distribution 

coefficient as the proportion of radionuclide in the groundwater compared to the radionuclide 

associated with the solids in the ground. Uncertainties in these distribution coefficients for 

various soil types are the result of their sensitivities to water chemistry and mineralogy. 

Distribution coefficients used to characterize the adsorption of radionuclides in soils have been 

identified as potential sources of uncertainty in decommissioning, uranium recovery, and 

radioactive waste disposal cases. 

The NRC has worked with the U.S. Geological Survey (USGS), through interagency agreements, 

to develop more realistic models for site-specific chemical sorption processes. The ultimate goal 

of this work is to create more realistic PA models that can adequately represent the effects of 

natural processes at chemically complex sites on radioactive materials movement through the 

environment. One way the NRC and its licensees assess the potential movement of radioactive 

materials in the subsurface is by modeling the transport of radionuclides on specific sites. 

Therefore, techniques for determining site-specific distribution coefficients are necessary to both 

implement and test the results of models that are sensitive to changes due to mineralogy and 

water quality from point-to-point and over time. This report evaluates field-based techniques for 

determining Kd values or for validating laboratory- or model-derived Kd values. The site used for 

this study was a uranium mill tailings site at Naturita, Colorado. 

This report is one in a series of reports documenting a field demonstration using surface 

complexation models to obtain a more realistic and site-specific estimate of the movement of 

radioactive materials in soil. This report investigates three field-based techniques for determining 

Kd values for a specific field site. Section 1 provides a detailed description of the Naturita field 

site and a general description of the project. Section 2 compares the Kd values determined in the 

field with Kd values predicted using surface complexation models. Section 3 describes two types 

of tracer tests used to evaluate the applicability of semi-mechanistic surface complexation 

modeling (SCM) for describing uranium (VI) adsorption and desorption under field conditions. 

Section 4 provides observations and modeling descriptions associated with the use of push-pull 

tracer tests, and Section 5 focuses on the use of small-scale migration tracer tests to model the 

site.

v

CONTENTS 

ABSTRACT................................................................................................................................... iii 

FOREWORD....................................................................................................................................v 

FIGURES ........................................................................................................................................xi 

TABLES.........................................................................................................................................xv 

1. TESTS OF URANIUM(VI) ADSORPTION MODELS IN A FIELD SETTING: 

INTRODUCTION AND FIELD SITE DESCRIPTION..................................................................1 

1.1 Introduction ..................................................................................................................1 

1.2 The Naturita UMTRA Site ...........................................................................................1 

1.2.1 Site Description ............................................................................................2 

1.2.2 Hydrogeology...............................................................................................2 

1.2.3 Geochemical Characterization......................................................................4 

1.3 Project Approach.........................................................................................................6 

2. COMPARISON OF IN-SITU KD VALUES FOR URANIUM(VI) SORPTION WITH 

VALUES PREDICTED FROM SURFACE COMPLEXATION MODELS .....................9 

2.1 Introduction ..................................................................................................................9 

2.2 Materials and Methods.................................................................................................9 

2.2.1 Preparation, Installation, and Retrieval of Samples .....................................9 

2.2.2 Extraction and Analysis of Samples...........................................................10 

2.3 Laboratory Kinetics....................................................................................................11 

2.4 Groundwater Chemistry .............................................................................................13 

2.5 In-Situ Kaolinite Field Measurements........................................................................14 

2.5.1 Effect of Residence Time in Wells.............................................................14 

2.5.2 Effect of Sample Holder Type....................................................................14 

2.5.3 Carbonate Extraction Kinetics....................................................................14 

2.5.4 Comparison of Carbonate and Nitric Acid Extractions..............................15 

2.5.5 Comparison with Predictions of Kaolinite Surface 

Complexation Model............................................................................................15 

2.6 In-Situ Quartz Field Measurements............................................................................15 

2.6.1 Carbonate Extraction Results.....................................................................15 

2.6.2 Nitric Acid Extraction Results ...................................................................25 

2.6.3 Predictions with Quartz Surface Complexation Model..............................25 

2.7 In-Situ Hematite Field Measurements........................................................................25 

2.7.1 Carbonate Extraction Results.....................................................................25 

2.7.2 Nitric Acid Extraction Results ...................................................................25 

2.7.3 Comparison with Predictions of Hematite Surface Complexation 

Model ...................................................................................................................25 

2.8 In-Situ Clinoptilolite Field Measurements.................................................................30 

2.8.1 Carbonate and Formate Extraction Results................................................30 

2.8.2 Nitric Acid Extraction Results ...................................................................30 

2.9 In-Situ Measurements with Forty-Mile Wash Sediments ..........................................33 

2.9.1 Carbonate Extraction Results.....................................................................33 

2.9.2 Nitric Acid Extraction Results ...................................................................33 

2.10 Conclusions..............................................................................................................37 

vii
3. REACTIVE TRANSPORT MODELING APPROACHES FOR IN SITU 

TRACER TESTS ..............................................................................................................39 

3.1 Introduction ................................................................................................................39 

3.1.1 Background ................................................................................................39 

3.1.2 Uranium(VI) Adsorption............................................................................39 

3.1.3 Push-Pull Tracer Tests................................................................................40 

3.1.4 Objectives...................................................................................................41 

3.2 Reactive Transport Modeling Approaches for Push-Pull Tests .................................41 

3.2.1 Alternative Conceptual Models for Simulation Push-Pull Tests................42 

3.2.1.1 Local Equilibrium ......................................................................42 

3.2.1.2 Kinetically Controlled Adsorption .............................................42 

3.2.1.3 Slow Mobile-Immobile Exchange..............................................43 

3.2.1.4 Instantaneous Injection...............................................................44 

3.3 Model Scenarios.........................................................................................................44

3.4 Push-Pull Reactive Transport Modeling Results........................................................46 

3.4.1 Local Equilibrium Simulations ..................................................................47 

3.4.2 Nonequilibrium Simulations ......................................................................48 

3.4.2.1 Kinetically Controlled Adsorption ............................................53 

3.4.2.2 First Order Mass Transfer Simulation Results ..........................54 

3.4.2.3 Instantaneous Source .................................................................54 

3.5 Conclusions................................................................................................................57 

4. OBSERVATIONS AND MODELING OF U(VI) TRANSPORT IN PUSH-PULL TRACER 

TESTS ...............................................................................................................................63 

4.1 Introduction ................................................................................................................63 

4.2 Methods and Materials...............................................................................................64 

4.2.1 Site Description ..........................................................................................64 

4.2.2 Tracer Test Descriptions ............................................................................64 

4.2.3 Groundwater Sampling and Analysis.........................................................66 

4.3 Results........................................................................................................................66 

4.3.1 Observed Concentration Histories..............................................................66 

4.3.2 Nonreactive Transport Calibration.............................................................70 

4.3.3 Reactive Transport Simulations .................................................................70 

4.4 Conclusions................................................................................................................72 

5. OBSERVATIONS AND MODELING OF U(VI) TRANSPORT IN SMALL-SCALE 

MIGRATION TRACER TESTS.......................................................................................75 

5.1 Introduction ................................................................................................................75 

5.2 Methods and Materials...............................................................................................76 

5.2.1 Site Description ..........................................................................................76 

5.2.2 Sediment Collection ...................................................................................76 

5.2.3 Uranium(VI) Adsorption............................................................................78 

5.2.4 Tracer Test Descriptions ............................................................................78 

5.2.5 Groundwater Sampling and Analysis.........................................................79 

5.3 Results........................................................................................................................79 

5.3.1 Surface Area ...............................................................................................79 

5.3.2 Uranium(VI) Aqueous Speciation..............................................................80 

5.3.3 Observed Breakthrough Behavior..............................................................80 

5.3.4 Quasi One-Dimensional Nonreactive Transport Modeling........................82 

viii
5.3.4.1 Modeling Approach....................................................................87 

5.3.4.2 Nonreactive Transport Modeling ...............................................88 

5.3.4.3 Reactive Transport Modeling.....................................................89 

5.3.4.4 Sensitivity Calculations..............................................................89 

5.3.5 Complex Breakthrough Behavior...............................................................90 

5.4 Conclusions................................................................................................................91 

6. CONCLUSIONS.....................................................................................................................93 

6.1 Downhole In-Situ Devices..........................................................................................93 

6.2 Push-Pull Tracer Tests................................................................................................93 

6.3 Small-Scale U(VI) Migration Tracer Tests................................................................94 

REFERENCES...............................................................................................................................95 

ix
x
FIGURES 

1.1 Locality Map of Naturita, Colorado, U.S.A, showing locations of 

groundwater monitoring wells, sediment sampling locations, groundwater 

flow direction, locations of the former uranium mill yard and tailings pile, 

and U(VI) concentration contours in 1999..........................................................................3 

1.2 Alkalinity, pH, and the concentrations of dissolved U(VI), Ca, Fe, Mn and 

O2 in the Naturita alluvial aquifer in March 2004 and sulfate in 1999................................5 

2.1 The ratio of U(VI) concentrations inside and outside of dialysis bags as a 

function of time in test experiments with quartz, kaolinite, and 40-Mile 

Wash composite sediment.................................................................................................12 

2.2 U(VI) desorbed from kaolinite or the FMW sediment composite by the 

bicarbonate-carbonate solution as a function of time, expressed as a Kd value ................12 

2.3 Comparison of various elemental concentrations measured in replicate 

clinoptilolite and 40-Mile Wash composite dialysis bags compared with 

 bulk groundwater (bulk) in December 2005......................................................................16 

2.4 Comparison of U(VI) concentrations for kaolinite samples deployed in 

Dialysis tubing and placed in wells for 2 days or 1 month. U(VI) 

concentrations in (A) carbonate solution extracts, and (B) nitric acid extracts. ................18 

2.5 Comparison of U(VI) extracted from kaolinite deployed in different sample 

holder types: KDT (dialysis tubing) and KNV (nylon vial), with U(VI) 

extracted by carbonate solution (A) and nitric acid (B). .................................................. 19 

2.6 Comparison of dissolved concentrations of U(VI), Ca, Na, and V in bulk 

groundwater samples and replicate nylon vials without kaolinite.....................................20 

2.7 Concentrations of elements extracted at various times from kaolinite 

after exposure to groundwater for 1 month........................................................................21 

2.8 Comparison of U(VI) concentrations extracted from kaolinite exposed to 

groundwater for 1 month by the carbonate solution and nitric acid..................................22 

2.9 Calculated amounts of U(VI) extracted by carbonate solution from 

quartz samples for various extraction times. Part (A) shows the amount 

of U(VI) extracted without correction for U(VI) in the water entrained 

with the quartz samples. Part (B) illustrates the same data after the 

correction is applied...........................................................................................................23 

2.10 Concentrations of various elements (Ca, Mg, Na, Si, V) in carbonate 

extraction solutions of quartz at various time during the extraction..................................24 

2.11 Comparison of concentrations of U(VI) and V extracted from quartz by 

concentrated nitric acid alone versus total extracted (sum of carbonate 

solution and nitric acid extracts)........................................................................................26 

xi
2.11 Concentrations of various elements at selected times during carbonate 

solution extracts of hematite after exposure to groundwater for 1 month. ........................27 

2.13 Comparison of various elements extracted from hematite by nitric acid alone 

versus total extracted (sum of carbonate solution and nitric acid extracts) 

after exposure to groundwater for 1 month. ......................................................................28 

2.14 Ca and Mg in carbonate solution extractions of clinoptilolite at various times.................31 

2.15 Comparison of various elements extracted from clinoptilolite by the sum of 

the carbonate solution and formate buffer extractions and the nitric acid 

extraction...........................................................................................................................32 

2.16 The concentrations of various elements dissolved in carbonate solution 

extracts of 40-Mile Wash sediments. Part (A) shows U, Part (B) shows 

Ca, Fe, Mg, Na, and V, and Part (C) shows individual replicate samples 

for U and V........................................................................................................................34 

2.17 Comparison of U extracted from 40-Mile Wash sediments by nitric 

acid alone and total U extracted by the sum of the carbonate solution 

and nitric acid extractions..................................................................................................38 

3.1 Kinetic data and model for U(VI) adsorption in laboratory batch experiments ................44 

3.2 Model domain for hypothetical tracer test simulations......................................................45 

3.3 Temporal evolution of bromide, alkalinity, total dissolved U(VI), and total 

 adsorbed U(VI)..................................................................................................................49 

3.4 Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) 

and (d) Kd values for a hydraulic conductivity of 60 m/d..................................................50 

3.5 Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) 

and (d) Kd values for a hydraulic conductivity of 6 m/d ...................................................51 

3.6 Simulated concentration histories for (a) bromide, (b) alkalinity, (c) aqueous 

U(VI) at the push-pull injection-extraction well ...............................................................52 

3.7 Simulated concentration histories for (a) bromide, (b) alkalinity, (c) aqueous 

U(VI) at the push-pull injection-extraction well for the high alkalinity, 

low alkalinity and uncontaminated injection scenarios.....................................................53 

3.8 Temporal evolution of bromide, alkalinity, total dissolved U(VI), and total 

adsorbed U(VI) for kinetically controlled simulations using Model 1 ..............................55 

3.9 Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) 

and (d) Kd values for kinetically controlled adsorption and Model 1................................56 

3.10 Simulated concentration histories for aqueous U(VI) at the push-pull 

injection-extraction well the kinetically controlled simulations using 

xii
model 1, model 2 and model 1 with decreased forward and backward 

 rate constants .....................................................................................................................57 

3.11 Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed 

U(VI) and (d) Kd values for the first order mass transfer model. ......................................58 

3.12 Simulated concentration histories for aqueous U(VI) at the push-pull 

injection-extraction well for mass transfer coefficients equal to 10-3 

 and 10-2 hr..........................................................................................................................59

3.13 Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed 

U(VI) and (d) Kd values for the disequilibrium-equilibrium case .....................................60 

3.14 Simulated concentration histories for aqueous U(VI) at the push-pull 

injection-extraction well for injection waters having high alkalinity, low 

alkalinity, uncontaminated water with a hydraulic conductivity of 60 m/d 

and high alkalinity injection with a hydraulic conductivity of 6 m/d. ...............................61 

4.1 Map of the small-scale tracer test site developed near well NAT25. The 

numbers after the well designations indicate different sampling levels, 

with 1 being the deepest screened interval. .......................................................................65 

4.2 Concentration histories observed in push-pull tracer test 1 (PPT1)...................................67 

4.3 Concentrations of U(VI) and Br tracer in push-pull tracer tests conducted 

with uncontaminated groundwater for various drift periods and injected 

alkalinities: (a) PPT3, (b) PPT2, (c) PPT5, and (d) PPT9. ................................................68 

 

4.4 Concentration histories for U(VI), Br tracer, and alkalinities in PPT4 

and PPT8. Results show U(VI) desorption into contaminated groundwater 

that was treated to: (a) increase the alkalinity or (b) decrease the alkalinity. ....................69 

4.5 Changes in U(VI) concentration resulting from the addition of Br as either: 

(a) KBr or (b) NaBr. ..........................................................................................................70 

4.5 Concentration histories observed in push-pull tracer test 12, which had an 

Injectate with a low dissolved Ca concentration and an increased alkalinity....................71 

4.7 Comparison of observed concentration of Br, U(VI) and alkalinity with model 

simulations for: (a) PPT1, (b) PPT4, (c) PPT8, and (d) PPT12. .......................................73 

5.1 Map of the small-scale tracer test site developed near NAT25. The numbers 

after the well designations indicate different sampling levels with 1 being the 

deepest screened interval...................................................................................................77 

5.2 Variation of specific surface area with depth ....................................................................80 

5.3 Speciation of 4 μM U(VI) in groundwater in equilibrium with calcite at pH 7.1 

and with variable alkalinity ...............................................................................................81 

xiii
5.4 Observed and simulated bromide, U(VI) and alkalinity concentrations 

in migration test MT1 at observation well A1...................................................................81 

5.5 Observed and simulated bromide, U(VI) and alkalinity concentrations 

in migration test MT2 at observations wells (a) A3, (b) M2, (c) N2, 

and (d) O1..........................................................................................................................83 

5.6 Observed and simulated bromide, U(VI) and alkalinity concentrations 

in migration test MT3 at observations wells (a) A3, (b) D1, (c) M2, 

(d) N2, and (e) O1..............................................................................................................85 

5.7 Sensitivity of simulated U(VI) concentration, at well A1 in test MT1 and 

well A3 in tests MT2 and MT3, to equilibrium constants for the predominant 

aqueous and surface species..............................................................................................90 

5.7 Observed and simulated bromide, U(VI) and alkalinity concentrations in 

migration tests MT2 and MT3 at observation well P1 ......................................................92 

xiv
TABLES

2.1 Typical chemical compositions of groundwater in wells used for mineral bag 

deployment. .......................................................................................................................13 

2.2 Iron and manganese concentrations in wells MAU07 and MAU08 at various 

sampling times...................................................................................................................13 

2.3 Comparison of measured and model-predicted U(VI) Kd values for kaolinite 

samples in contact with Naturita groundwater..................................................................15 

2.4 Model parameters of the SCM used to predict U(VI) adsorption on hematite 

deployed in dialysis bags in Naturita groundwater ...........................................................29 

2.5 Comparison of measured and model-predicted U(VI) Kd values for hematite 

samples in contact with Naturita groundwater..................................................................29 

2.6 Alkalinities measured in carbonate solutions after 3 weeks of extraction of 

Clinoptilolite......................................................................................................................30 

2.7 Measured U(VI) Kd values for clinoptilolite samples in contact with Naturita 

groundwater.......................................................................................................................33 

2.8 Alkalinities measured in carbonate solution extractions of replicate 40-Mile Wash 

sediment samples deployed in Naturita wells after 3 weeks of extraction........................37 

2.9 Measured U(VI) Kd values for 40-Mile Wash sediment samples in contact 

with Naturita groundwater.................................................................................................37 

3.1 NABS surface complexation model ..................................................................................40 

3.2 Properties of hypothetical aquifer .....................................................................................46 

3.3 Geochemical composition of the initial groundwater conditions and 

injectate used in the hypothetical simulations...................................................................46 

4.1 Composition of injectate solutions and groundwater in push-pull tests............................66 

4.2 Summary of flow and transport parameters determined by model calibration .................71 

5.1 NABS surface complexation model ..................................................................................78 

5.2 Summary of migration tests at the NAT25 small-scale tracer test site..............................79 

5.3 Summary of nonreactive transport model parameters.......................................................88 

5.4 Summary of nonreactive transport model parameters for bromide 

breakthrough at well NAT25P1.........................................................................................91 

 

xv
xvi
1 TESTS OF URANIUM(VI) ADSORPTION MODELS IN A FIELD 

SETTING: INTRODUCTION AND FIELD SITE DESCRIPTION 

1.1 Introduction

Numerous sites throughout the United States are 

contaminated by radionuclides, especially

uranium (U) and thorium (Th) and their byproducts, due to mining, milling, and other 

industrial processes (Morrison and Cahn, 1991). 

The United States Nuclear Regulatory 

Commission (USNRC) is responsible for the 

regulatory oversight of site remediation and 

clean up, and possible release of sites for public 

or unrestricted use. Licensing decisions are 

made based on performance assessment (PA) 

calculations that utilize numerical models to 

estimate the increase in radioactivity exposure to 

the biosphere at selected locations. 

Contamination is often limited to the soils, 

subsurface sediments, and shallow aquifers at 

these sites. 

Prediction of the fate and transport of 

radionuclides is of paramount importance in 

evaluating remediation schemes and in 

quantifying the risk of contamination to human 

or ecosystem health (Davis et al., 2004a; 

USEPA, 1999). To make a calculation of 

radioactive exposure risk in PA, it is necessary

to calculate the total amount of each 

radionuclide that will be present at selected 

locations as a function of time. A solute 

transport model is typically used to describe the 

physical processes of advection and dispersion 

that may transport radionuclides in groundwater 

from the source location to a site of ingestion. 

In addition to these hydrophysical processes, the 

transport of many radionuclides can be strongly

influenced by reactive chemical processes, 

including aqueous complexation, sorption, 

precipitation and dissolution, and redox

reactions. However, in practice, most reactive 

transport models ignore the chemical complexity

of aqueous complexation and sorption processes 

and utilize the distribution coefficient (constant 

Kd) approach to describe the retardation of 

radionuclide contaminants (Curtis et al., 2006;

Davis and Curtis, 2003; USEPA, 1999). 

Although sorption is only a part of the overall 

PA calculations, retardation of radionuclide 

transport in the far-field geosphere zone may be 

extremely important in reducing the risk of 

biosphere exposure of certain radionuclides to 

levels that are in compliance with regulations. In 

order to be “conservative”, large ranges of Kd

values may need to be estimated by expert 

judgement in order to account for possible 

changes in chemical conditions and for other 

sources of error. The uncertainties in these 

ranges are difficult to assess quantitatively 

without doing large numbers of experiments. 

In this study, field-based techniques were tested 

for determining Kd values or for validating 

laboratory- or model-derived Kd values. The 

field site used for the study was the uranium mill 

tailings site at Naturita, Colorado (Davis and 

Curtis, 2003). The techniques included: 1) the 

use of downhole in-situ devices that held a 

sample of a single mineral or sediment that were 

deployed in the aquifer contaminated with 

uranium, 2) in-situ push-pull tracer tests 

conducted within the contaminated aquifer, and 

3) small-scale U(VI) migration tracer tests 

conducted within the aquifer. The experiments 

were conducted on scales that ranged from

centimeters for the downhole devices to several 

meters for the small-scale tracer tests. 

1.2 The Naturita UMTRA Site 

Uranium (U) ore processing on the Colorado 

Plateau resulted in a number of inactive mill 

tailing sites at which there is contamination of 

groundwater (USDOE, 1996). The groundwater 

at many of these sites is contaminated with U 

and often other species including vanadium (V), 

selenium and molybdenum. The USDOE is 

responsible for clean up of many of these sites as 

dictated by the Uranium Mill Tailings 

Remediation Act (UMTRA). 

Uranium occurs in the environment 

predominantly as U(IV) in reducing systems and 

U(VI) in oxic systems. In reducing waters, 

U(IV) forms insoluble phases and thus is 

1
relatively immobile (Langmuir, 1997). In oxic 

waters, U(VI) forms many soluble hydroxide 

and carbonate complexes which lead to 

increased solubility and mobility. Precipitation 

of U(VI) phases usually occurs only within and 

near uranium ore bodies or near concentrated 

waste sources. Adsorption of U(VI) in oxic 

waters is sensitive to pH and partial pressure of 

carbon dioxide gas (pCO2). Adsorption is 

generally negligible at low pH values where the 

uranyl cation (UO2

+2) is the dominant species 

and increases with increasing pH usually in the 

pH range of 4 to 6. In the alkaline region, U(VI) 

is strongly adsorbed in the absence of dissolved 

CO2 (Hsi and Langmuir, 1985; Prikryl et al., 

2001) but in the presence of dissolved CO2, the 

formation of U(VI)-carbonate complexes 

reduces adsorption (Davis et al., 2004b; Waite et 

al, 1994). At intermediate values of pH and 

CO2, the extent of adsorption is determined by

competition between the formation of aqueous 

U(VI)- carbonate complexes and surface U(VI)-

carbonate complexes (Bargar et al., 1999; 

Bargar et al., 2000; Bostick et al., 2002; Arai et 

al., 2006). The importance of CO2 in the 

formation of both aqueous and surface 

complexes with U(VI) illustrates that adsorption 

and transport of U(VI) can be strongly impacted 

by variable alkalinity.

Dissimilatory Fe(III)-reducing bacteria (DIRB) 

play an important role in the geochemistry of 

many subsurface groundwater and sediment 

environments. Many DIRB are able to reduce 

the highly soluble and mobile U(VI) species to 

highly insoluble U(IV), which precipitates as 

uraninite (Lovely et al., 1991). Microbial Fe(III) 

reduction can also lead to an increase in 

radionuclide mobility if sorbed or coprecipitated U(VI) is released following Fe(III) 

oxide reduction. Sorbed Fe(II) on mineral 

surfaces (Jeon et al., 2005; Liger et al., 1999) 

and mineral phases containing Fe(II) 

(O’Loughlin et al., 2003; Wersin et al., 1994) 

can also reduce U(VI) to U(IV). 

The Naturita UMTRA site is useful for studying 

the influence of the processes mentioned above 

on U fate and transport (Curtis et al., 2006; 

Davis et al., 2006). The site has both variable 

alkalinity and redox conditions, resulting in 

complex U(VI) transport behavior. 

1.2.1 Site Description 

The former U mill tailings site is approximately

3 km northwest of the town of Naturita, CO 

along the San Miguel River in southwestern 

Colorado as shown in Figure 1.1. The San 

Miguel River is the only perennial surface water 

body at the site. The Naturita area is semi-arid; 

the estimated average annual precipitation is 9 

inches (23 centimeters) and grasses and 

sagebrush dominate the vegetation, except near 

the river where cottonwoods are common. 

The ore mill processed U and V ores at the site 

beginning in 1939 almost continuously until the 

mill was shut down in 1958. From 1961 until 

1963, a U ore upgrader was operated at the site. 

Uranium and V were extracted from the ore by

salt roasting followed by carbonate leaching in

percolation tanks. Carbonate leach tails were 

slurried to the western half of the Naturita site to 

an area of the site farthest (200 meters) from the 

San Miguel River and closest to highway 141. 

Carbonate leaching residues were later sent to a 

second stage of sulfuric acid leaching. Acid 

leach tails were deposited closer to the river. 

Between 1977 and 1979, the mill tailings were 

removed from the site, and between 1996 and 

1998 the contaminated surface soils were

excavated and transported offsite. 

1.2.2 Hydrogeology 

Contaminated groundwater at the Naturita site 

occurs in the thin alluvial deposits of the San 

Miguel River floodplain. The aquifer is 

recharged by the river to the southeast of the site 

and discharges into the river north of the site. 

Ground water flows approximately parallel to 

the river. The alluvial aquifer is separated from

an underlying, moderately permeable sandstone 

aquifer (the Salt Wash Member) by a finegrained shale (the Brushy Basin Member), 

which is approximately 30 m thick. The average 

saturated thickness is 1.8 m when the river is at 

low flow conditions. The alluvial aquifer 

consists of sand, gravel and cobbles and the 

mineralogy consists of primarily quartz with 

2
Figure 1.1. Locality Map of Naturita, Colorado, U.S.A, showing locations of groundwater 

monitoring wells, sediment sampling locations, groundwater flow direction, locations of the former 

uranium mill yard and tailings pile, and U(VI) concentration contours in 1999. 

lesser amounts of detrital feldspars, carbonates, 

magnetite, and fine clay-size materials (Davis et 

al., 2004b). 

Figure 1.1 shows a map of the Naturita site that 

illustrates the location of the former mill yard, 

the extent of the former tailings pile, and all of 

the monitoring wells at the site. Between 1986 

and 1997, USDOE installed 12 wells in the 

alluvial aquifer and 2 wells in the Salt Wash 

aquifer. All of these wells except DOE-547 and 

DOE-548, which are in the alluvial aquifer, were 

removed by the end of 1998. In 1998 and 1999, 

the USGS installed wells at 39 new locations 

and some of these new wells were clusters that 

included some multilevel wells. High 

concentrations of U(VI) are found in the ground 

water below and downgradient of the former 

tailings pile. Both water used to process the U 

ore and mill tailings and rain and snow that 

leached U from the deposited tailings could have 

caused the transport of U(VI) to the ground 

water at the site. 

A well that was installed in the Salt Wash 

aquifer in the 1980's and subsequently

abandoned by USDOE had heads that exceeded 

those in the alluvial aquifer indicating the 

potential for vertically upward flow and 

transport. The deep groundwaters had an 

average chloride (Cl) concentration of 20 mM, 

which was 200 times higher than Cl in 

background alluvial wells, indicating minimal 

3
upward flow. The U(VI) concentration in the 

deep groundwaters was 0.16 μM. 

1.2.3 Geochemical Characterization 

Spatial concentration contours for alkalinity, pH, 

and dissolved U(VI), Ca, Fe, Mn, and O2 in the 

Naturita alluvial aquifer in March 2004 are 

shown in Figure 1.2. Elevated concentrations of 

U(VI) and alkalinity were observed below and 

downgradient of the former uranium mill 

tailings, and the concentrations were generally

lower near the San Miguel River and higher near 

the western edge of the aquifer. The average 

U(VI) concentration in the wells upgradient of 

the former mill site was 0.02 μM, and a peak 

concentration of 7 μM was observed at well 

NAT-26. Most of the impacted groundwater had 

U(VI) concentrations between 2 and 6 μM. 

Alkalinity had a similar spatial pattern as the 

U(VI) concentration, but the range in 

concentration was smaller. Alkalinity values 

ranged from approximately 4.7 meq/L 

upgradient to peak values of 10.5 meq/L at well 

NAT-26. Calcite saturation indices generally

range from –0.25 to 0.35 suggesting that the 

groundwaters were in equilibrium with calcite, 

which is present in the sediments (Davis and 

Curtis, 2003). Computed pCO2 values range 

from 0.0024 to 0.14 atm. The distribution of 

sulfate at the site in 1999 was very similar to 

that observed for the alkalinity (Fig. 1.2); sulfate 

concentrations were 1.7 mM at wells DOE-547 

and MAU-03, 7.0 mM at NAT-19, and 10.6 mM

at MAU-07. The highest sulfate concentration 

observed was 15.8 mM at well NAT-26. 

The pH values from wells DM-1, DOE-547, and 

NAT-20, -21, -22, which are upgradient of the 

former mill site are approximately 1 pH unit less 

than that observed in the San Miguel River. 

Upgradient alkalinity values have been nearly

constant over time (average value of 4.7 meq/L), 

whereas the alkalinities in the San Miguel River 

varied seasonally with a range of 1.3 meq/L at 

high river stage to 2.6 meq/L at low river stage 

(Davis and Curtis, 2003). The decrease in the pH 

and the increase in alkalinity within the aquifer 

are consistent with biological activity. This 

activity is assumed to occur in the riverbank and 

possibly in the root zone of cottonwoods and 

willows near the river because water samples 

from well DM-1, which is ~10 m from the river, 

are similar to those from well DOE-547 which is 

~120 m from the river. There were also high V 

concentrations close to highway 141, where 

concentrations approached 100 μM, whereas 

outside of this plume dissolved V was below 

detection limits (Davis and Curtis, 2003).

The groundwaters at the Naturita site are 

generally not in equilibrium with respect to 

redox conditions. This is indicated by the cooccurrence of low, but measurable dissolved O2

and Fe(II) in water pumped from wells (Fig. 

1.2), which is not expected under equilibrium

conditions at near neutral pH values (Langmuir, 

1997). Since 1998, nitrate has only been

consistently detected at well NAT-26, where the 

average concentration was 40 μM, and 

dissolved Mn(II) is present in the range of 20-50 

μM throughout much of the site. Sulfide was 

absent in groundwater from all wells sampled in 

March 2004. The concentration of Fe(II) is 

relatively small (≤10 μM) in the upgradient 

portion of the site, including the area beneath the 

former mill and tailings (Fig. 1.2). The relative 

constancy of the dissolved Fe(II) and O2

concentrations over this portion of the site 

suggest that the extent of microbiological 

activity may be limited, perhaps by carbon 

limitation. However, in the extreme 

downgradient portion of the site, Fe(II) 

concentrations increase to as high as 50 μM. 

This area of the site has a thick stand of 

cottonwood trees, and studies have reported that 

mild reducing conditions and active microbial 

populations occur in the vicinity of tree roots, 

possibly because of microbial degradation of 

root exudates (Lee et al., 2000; Godsy et al., 

2003). Carbonate extractions on freshly

collected sediments from near well NAT-25 

under an inert atmosphere demonstrated that 

U(IV) phases were probably not important at 

that location (Kohler et al., 2004), however, 

reducing conditions in the downgradient portion 

of the aquifer appear to be sufficient for bacteria 

to reduce U(VI), leading to precipitated U(IV) 

(Davis et al., 2006). Historical data (Davis and 

4
Curtis, 2003) clearly indicate that the plumes of dissolved U(VI) and alkalinity are moving 

Figure 1.2. Alkalinity, pH, and the concentrations of dissolved U(VI), Ca, Fe, Mn and O2 in the 

Naturita alluvial aquifer in March 2004 and sulfate in 1999. Locations of the wells MAU-04, MAU07, NAT-18, and NAT-25 are shown. 

5
downgradient, while Fe(II) concentrations in the 

downgradient area with reducing conditions 

have remained relatively stable (Fig. 1.2). 

Determining the relative importance of U(VI) 

adsorption and U(IV) precipitation as processes 

that influence uranium fate and transport under 

suboxic conditions is difficult. Bacterial studies 

demonstrated that known Fe(III)-reducing 

bacteria are present in the downgradient MAU04 and –07 groundwater samples, but not in an 

upgradient NAT-18 groundwater sample (Davis 

et al., 2006). A wide variety of Fe(III)-reducing 

bacteria were isolated from MAU-04 and -07 

enrichment cultures, indicating that there is 

significant diversity among the Fe(III)-reducing 

bacteria in the subsurface in the downgradient 

region of the aquifer. An organism closely 

related to the Fe(III)- and U(VI)-reducing 

bacterium, Geobacter sulfurreducens, (Caccavo 

et al., 1994) was identified in MAU-04

groundwater, where it accounted for about 2% 

of the microbial community (Davis et al., 2006). 

The overall microbial composition is similar to 

the groundwater community structure at another 

UMTRA site at Rifle, Colorado, USA 

(Anderson et al., 2003). At the Naturita site, it 

appears that U(IV) precipitation may occur in 

the downgradient region, where significant 

dissolved Fe(II) is present and Fe(III)-reducing 

bacteria are detected in the microbial 

community. 

Saturation indices (SI) have been computed to 

assess if the solubility of U(VI) minerals might 

be controlling U(VI) transport (Davis and Curtis, 

2003). The computed SI values were found to

be well below saturation for several U(VI) 

phases including uranophane, soddyite, 

schoepite, and rutherfordine. Calculations were 

also performed to evaluate the stability of the 

U(IV) phases, uraninite and U3O8. The 

calculations assumed that the Fe(III)/Fe(II) 

couple was at equilibrium with the U(VI)/U(IV) 

couple and that Fe(III) activity was controlled by 

the solubility of either ferrihydrite or goethite. 

The U(IV) phases were below saturation (SI<-5) 

if equilibrated with ferrihydrite and at or near 

saturation (-2<SI<2) if equilibrated with goethite 

(Davis and Curtis, 2003). 

1.3 Project Approach 

Simulations of reactive transport processes in 

groundwater often require many parameters as 

model inputs. These parameters include 

hydrologic parameters that describe flow and 

transport as well as reaction parameters that 

describe the chemical reaction network. While 

hydrologic parameters are most often 

determined from field tests such as pump tests, 

slug tests, or tracer tests coupled with model 

calibration, there is less agreement on how 

chemical reaction parameters should be 

determined. For chemical reaction processes, 

such as adsorption reactions, parameter values 

could be based on a variety of sources including 

tabulated thermodynamic data, laboratory 

experiments using site-specific materials, or 

field-determined values. 

 

Surface complexation models (SCMs) are a 

useful approach for simulating adsorption in 

reactive transport models, especially in instances 

where geochemical conditions vary spatially and 

temporally (Curtis et al., 2006; Kent et al., 

2000). One approach for developing an SCM for 

use in field-scale reactive transport simulations 

is to use published SCMs for well-characterized 

mineral surfaces coupled with detailed soil 

characterization for the field medium. This 

approach has been termed the component

additivity method, in which SCM for single 

mineral phases are assembled in an additive 

fashion to predict adsorption by a whole 

sediment. Our previous work (Davis et al., 

2004b) identified four significant sources of 

uncertainty in using this approach: (1) 

estimation of surface site types and surface area

abundances, even for well-characterized 

sediments, (2) a lack of fundamental data on the 

effects of competitive adsorption of common 

groundwater solutes, (3) a lack of fundamental 

data on the effects of common groundwater 

solutes on surface charge and potentials, and (4) 

inconsistencies that could result when 

combining SCMs that use different electrical 

double layer formulations. In the current

project, we addressed the second of these 

6
uncertainties by conducting in-situ experiments 

with well-characterized mineral phases: 

kaolinite, quartz, and hematite. 

A second approach for developing an SCM for a 

natural sediment is to calibrate a model to

measured adsorption data. In this approach, 

adsorption is postulated to occur on generic 

surface sites that represent average properties of 

the sediment surfaces rather than specific 

mineral surfaces. Model parameters are

calibrated to adsorption data for postulated 

reaction stoichiometries and different model 

formulations, and are selected based on 

simplicity and goodness of fit. An advantage of 

this approach is that the electrical double layer is 

not considered explicitly; adsorption reaction 

stoichiometry and binding constants are derived 

by fitting the macroscopic dependence of 

adsorption as a function of pH. This is 

important because of the difficulty in 

quantifying electrical field and charge at the 

mineral-water interface in mixtures of mineral 

phases with associated surface coatings. In the 

current work, we refer to this approach as a 

semi-mechanistic approach; in previous work it 

has been called a generalized composite 

approach. For the Naturita field site, laboratory

experiments using site-specific materials 

obtained upgradient of the contaminated zone 

were used to develop a semi-mechanistic SCM 

that described U(VI) reaction stoichiometry and 

apparent stability constants with the sediments 

(Davis et al., 2004b). This SCM did a good job 

of predicting U(VI) Kd values for both 

contaminated sediments that were collected 

during the installation of groundwater 

monitoring wells (Kohler et al., 2004), with the 

exception of two downgradient wells where 

U(VI) reduction may have occurred (Davis et 

al., 2006). In addition, the SCM successfully

predicted Kd values measured on 

uncontaminated sediments suspended in 

groundwater wells that had variable U(VI) 

concentrations and alkalinity values (Curtis et 

al., 2004). 

The suitability of the semi-mechanistic SCM for 

simulating U(VI) migration in a reactive 

transport model was evaluated previously for the 

Naturita site (Curtis et al., 2006; Davis and 

Curtis, 2003). The reactive transport model 

could be fit to the site data, although some 

uncertainties remain regarding the applicability

of the SCM to describe U(VI) transport in the 

field. The most significant uncertainty results 

because the source term was so poorly

understood that the composition of the source 

had to be included in the model calibration. The 

uncertainty related to the source term would 

likely dominate an uncertainty analysis of the 

transport of U(VI). Thus, to achieve the goal of 

reducing uncertainty of the simulated long-term

fate on U(VI) concentration in the aquifer, it is 

important to demonstrate the applicability of the 

SCM to describe U(VI) transport under field 

conditions. To achieve this goal, reactive 

transport experiments were conducted in the 

field at scales of 0.5 to 3 m. Uranium migration 

tests were conducted that considered variable 

U(VI) concentrations and alkalinity, and 

included Br as an inert tracer. The field 

experiments also included several single-well 

push-pull tests that were conducted at increased 

and decreased U(VI) concentrations and 

alkalinity values. The tracer tests demonstrated 

that the sediment readily releases U(VI) even 

after many years of contact with the 

contaminated groundwater, suggesting that 

U(VI) migration is controlled by adsorption 

reactions. Reactive transport simulations used 

the SCM developed with uncontaminated 

Naturita sediments (Davis et al., 2004b).

7
 

8
2 COMPARISON OF IN-SITU KD VALUES FOR URANIUM(VI) 

SORPTION WITH VALUES PREDICTED FROM SURFACE 

COMPLEXATION MODELS 

2.1 Introduction 

In previous experiments, mesh bags constructed 

of 50 micron nylon filter fabric containing a 

composite of uncontaminated Naturita sediment 

(NABS) were suspended in well casings in 

various wells throughout the Naturita field site 

(Curtis et al., 2004). The mesh bags were 

removed periodically and analyzed for U uptake. 

Kd values (or distribution coefficients) observed 

for these samples were compared with modelpredicted Kd values from a surface complexation 

model calibrated with uncontaminated Naturita 

sediments in laboratory experiments (Davis et 

al., 2004b). 

In the experiments described in this section, a 

similar approach was taken using pure reference 

minerals for which surface complexation models 

have been developed that describe U(VI) 

sorption as a function of water chemistry. The 

purpose of these experiments was to determine 

the applicability of laboratory-derived models

for reference minerals (which can be found in 

the literature) to field conditions. This study

was conducted by contacting well-characterized 

mineral phases with Naturita groundwater in 

wells that had variable U(VI) concentrations and 

alkalinity. U(VI) adsorption measured in the 

field could be different from that in laboratory

conditions because laboratory conditions 

typically do not consider competitive adsorption 

of common groundwater solutes, nor do they

consider conditions that could lead to the 

formation of surface coatings containing 

aluminum and silicon. Such coatings may be 

difficult to characterize yet significantly change 

adsorption properties. 

The following materials were chosen for downhole studies: kaolinite, hematite, quartz, 

clinoptilolite, and a sediment composite 

prepared from cores collected in the saturated 

zone of the 40-Mile Wash (FMW) aquifer, Nye 

County, Nevada. 

2.2 Materials and Methods 

2.2.1 Preparation, Installation, and 

Retrieval of Samples 

Because of the small particle sizes of the

reference materials, two new types of sample 

holders were investigated. Previous experiments 

with the Naturita uncontaminated composite 

(NABS) utilized 50 μm filter fabric (Curtis et 

al., 2004). Kaolinite was used to test the effects 

of exposure time in the wells on measurements 

of U(VI) sorption and to test the two new sample 

holders: a) dialysis tubing (KDT) and b) nylon 

vials (KNV). Kaolinite (KGA-1), obtained from

the Source Clays Repository of the Clay

Minerals Society, was prepared as a slurry (200 

g/L) in MilliQ water, which had been purged 

with N2(g) to displace any O2(g) which might 

oxidize and precipitate Fe(II) present in the well 

waters. The slurry (5 mL, corresponding to 1 g 

kaolinite) was then pipetted into either a 5-mL

nylon vial or a short length (~4.5 cm) of dialysis 

tubing (SpectraPor7, 8K Dalton, 7.5 mm 

diameter). The mouths of the nylon vials (1.25 

cm in diameter) were covered with dialysis 

tubing. At the same time, “blank” nylon vials 

containing only water and covered with dialysis 

tubing (BNV) were also prepared. The samples 

were placed into mason jars containing N2-

purged deionized water. The mason jars were 

purged with N2(g) several times over 24 hr in 

order to remove as much O2(g) as possible. 

Duplicates of each sample type were prepared 

for installation into each of 10 wells that had 

variable water chemistry. The samples were 

placed into 35.5 cm lengths of 3.2 cm diameter 

PVC pipe that had been drilled with 1.25 cm

diameter holes and lined with nylon mesh. The 

sample holders were lowered into the wells to 

within about 23 to 30 cm of the well bottom. 

Samples were installed in the following wells on 

March 24, 2004 and retrieved on March 26 (1 

dialysis sample) or April 23-24, 2004 (remaining 

samples): NAT-05, NAT-09, NAT-11, NAT-19, 

9
NAT-20, NAT-24, NAT-25, NAT-26, MAU-07, 

and MAU-08. After the dialysis bags were 

sampled, the bags were opened and the slurry

was transferred to a pre-weighed vial, removing 

as much water as possible. The nylon vials were

simply capped and transported back to the lab. 

Water samples from each well were collected by

low-flow sampling at the elevation where the 

mineral bags were deployed within the borehole. 

Alkalinity and pH were measured in the field. 

Concentrations of U(VI) and other metals were 

determined in the laboratory by kinetic 

phosphorescence analysis (KPA) and 

inductively-coupled plasma spectroscopy (ICPAES), respectively. 

From initial experiments with kaolinite, we 

determined that the dialysis tubing with an

exposure time of 1-month was the best method 

for placing mineral samples in the wells. 

Subsequent experiments with quartz, hematite, 

clinoptilolite and the 40-Mile Wash sediment 

composite (FMW) were performed using a 1-

month exposure time. 

The quartz used was a commercially obtained 

crushed quartz powder, Min-U-Sil 30 

(Pennsylvania Glass & Sand Company). Quartz 

was treated to remove contaminants as described 

by Kohler et al. (1996). Grain sizes were 8-30 

μm and the specific surface area as measured by

5 point BET nitrogen gas adsorption was 0.29 

m2

/g. Dialysis tubing was filled with about 4 g 

quartz and 3 mL of N2-purged deionized water. 

Duplicate quartz bags were installed in the wells 

listed above (except MAU-01 was substituted 

for NAT-25) on 10/9/2004 and retrieved on 

11/10/2004. 

Hematite was synthesized following the method 

of Bargar et al. (1997). The hematite had a 

surface area of 50 m2

/g as measured by 5 point 

BET nitrogen adsorption. Hematite was stored 

as a slurry in MilliQ water containing 171 g/L 

and transferred to dialysis tubing by pipet. 

Duplicate hematite bags were installed in the 

wells listed above for quartz on 3/27 and 

3/28/2005 and retrieved on 4/28 and 4/29/2005. 

Clinoptilolite was obtained courtesy of Paul 

Bertetti of the Southwest Research Institute, San 

Antonio, TX. The material was similar to that 

used in Bertetti et al. (1998), and had been 

cleaned and processed in order to generate Naclinoptilolite as described by Pabalan et al. 

(1998, 1994). The clinoptilolite sample had a 

surface area of 10.1 m2

/g. 

The 40-Mile Wash composite (FMW) was 

prepared from samples collected as part of the 

Nye County (Nevada) Early Warning Drilling 

Program. Core materials were subsampled 

during the drilling of Borehole NC-EWDP 19PB 

at depths from 350-587 feet below ground 

surface on December 2-5, 2003. The water table 

was located at approximately 350 feet below 

ground surface at the location of sampling. The 

core materials were dry sieved to remove 

particles greater than 3 mm in size. The 

composite was prepared by mixing sediments in 

roughly equal weights per unit vertical length. 

Approximately 1 g samples of clinoptilolite or 

FMW composite were placed in dialysis tubing

along with 5 mL of N2-purged deionized water. 

Duplicate samples of each were installed in the 

wells listed above (except NAT-26) on 11/3 and 

11/4/2005 and retrieved on 12/6 and 12/7/2005. 

All samples were stored in N2-purged deionized 

water in mason jars as discussed above prior to 

installation in the wells. During retrieval of 

clinoptilolite and FMW bags, excess water from

inside the bags was retained, transported back to 

the lab and centrifuged at 6876 g for 20 min to 

completely separate the solid and liquid phases. 

These samples were analyzed and compared 

with bulk groundwater samples collected from

each well at the same time.

2.2.2 Extraction and Analysis of Samples 

With the exception of hematite, all mineral bag 

samples were weighed and dried to determine 

the amount of water present in each sample. 

Dried samples were then extracted with 20-mL

of bicarbonate-carbonate solution (20 meq/L 

alkalinity, pH 9.4, hereafter referred to as 

‘carbonate solution’) for 3 weeks (quartz was 

extracted for 4 weeks), followed by an 

extraction with 20 mL of hot, concentrated nitric 

10
acid for 3 days. The hematite samples were not 

dried, but simply extracted as a slurry with 40 

mL of carbonate solution, adjusting the pH to 

9.4. The volume of water associated with each 

hematite sample was determined by weighing 

the samples and calculating volume based on the 

known density of the hematite slurry. The 

carbonate extraction will desorb U(VI) that was 

adsorbed after deploying the samples in the 

wells, while the nitric acid can dissolve any U 

remaining that is more tightly bound (Kohler et 

al., 2004). Clinoptilolite samples were also 

extracted with 0.1 M sodium formate at pH 3.5 

(‘formate solution’) after the carbonate 

extraction, in order to determine the amount of 

adsorbed U(VI), for reasons that will be 

discussed in more detail below. Samples were 

diluted as necessary and analyzed for dissolved 

U(VI) (by KPA or ICP-MS) and selected other 

elements (by ICP-AES). Water samples 

collected for alkalinity were titrated with 

sulfuric acid using the Gran titration. All other 

water samples were acidified with nitric acid to 

0.15 M HNO3 and analyzed by KPA and ICPAES. 

2.3 Laboratory Kinetics

Kinetics experiments investigating the amount 

of time required for U(VI) sorption to reach 

equilibrium have been performed by others for 

the minerals used in these experiments (Pabalan 

et al., 1998; Fox et al., 2006). These studies have 

demonstrated that equilibration times of 48-72 

hr are sufficient in well-mixed batch 

experiments. However, in our studies the 

equilibration time required should be longer 

because the minerals were held within dialysis 

tubing, and additional time is needed for the 

water inside the bag to equilibrate with the water 

composition outside of the bag. We performed 

experiments in the laboratory to determine the 

appropriate equilibration time for samples held 

in the dialysis bags. Mineral bag samples of 

quartz, kaolinite, and FMW composite were 

prepared in the same manner as the field

samples, placed in a 1 L bottle filled with an 

artificial groundwater (AGW) solution 

containing 750 μg/L U(VI), 6.64 mM Ca2+, 1.52

mM Mg2+, 0.064 mM K+

, 2.41 mM Na+, 4.79 

mM SO4

2-, 4.50 mM Cl-

, and an alkalinity of 

4.71 meq/L. The bottle was bubbled 

continuously with a 2% CO2/ 98% N2 gas 

mixture in a glove bag in order to maintain a pH 

of 6.9. Dialysis bag samples were removed 

periodically for up to 30 days, and the solid and 

liquid phases were separated by centrifugation 

(16,270 g for 5 minutes). The supernatant 

samples were then acidified to 0.15 M with 

nitric acid and analyzed for U(VI) concentration 

by KPA, along with a sample of the AGW 

outside of the dialysis bags. Due to some 

evaporation during the experiments, U(VI) 

concentrations in the bulk solution outside of the 

bag changed slightly over time, and therefore, a 

sample of water outside of the dialysis bags was 

collected each time a bag was sampled. In the 

cases of kaolinite and FMW, the solid phase was 

retained and extracted with carbonate solution 

for 3 weeks in order to determine the total U(VI) 

sorbed. 

Figure 2.1 shows the ratio of U(VI) 

concentrations in water inside and outside the 

dialysis bags as a function of time for the quartz, 

kaolinite, and FMW composite experiments. In 

the cases of quartz and FMW, the U(VI) 

concentration inside the bags reaches identical 

concentrations with the water outside the bags 

after only 1 day of exposure. However, 

kaolinite, which adsorbed more U(VI) than 

either quartz or FMW, required 7 days of 

equilibration before reaching identical 

concentrations. 

Kaolinite and FMW sediments removed from

the dialysis bags were extracted with carbonate 

solution in order to desorb U(VI). The amount 

of U(VI) extracted reached a maximum after 14 

days of dialysis bag equilibration in kaolinite 

experiments and 7 days in FMW composite 

experiments (Figure 2.2). In both cases, this is 

slightly longer than the equilibration times 

measured for water equilibration inside and 

outside the bags (Figure 2.1). U(VI) extracted 

with carbonate solution decreased over longer 

exposure times (30 days for kaolinite, and 14-30

days for FMW composite). This may be an 

indication that U(VI) is becoming more tightly

bound over time, with less U(VI) desorbed in the

carbonate extraction. All of the mineral samples 

11
0 5 10 15 20 25 30 35

Exposure Time (days)

0.0

0.2

0.4

0.6

0.8

1.0

U i

n Ba

g/U i

n AG

W

Quartz

Kaolinite

FMW

Figure 2.1. The ratio of U(VI) concentrations inside and outside of dialysis bags as a function of 

time in test experiments with quartz, kaolinite, and 40-Mile Wash composite sediment. 

0 5 10 15 20 25 30 35

Exposure Time (days)

0

1

2

3

4

5

6

7

8

9

Kd (L/

kg)

Kaolinite

FMW

Figure 2.2. U(VI) desorbed from kaolinite or the FMW sediment composite by the bicarbonatecarbonate solution as a function of time, expressed as a Kd value. Error bars for the FMW 

experiment are smaller than the data points. 

12
collected after field exposure were extracted 

with hot concentrated nitric acid in order to fully

recover any U(VI) that was not extracted with 

the carbonate solution. We chose a field 

exposure time of about 30 days based on the 

results of the laboratory experiments. 

2.4 Groundwater Chemistry 

Table 2.1 shows the concentrations of various 

elements measured in groundwater samples at 

the wells studied. Groundwater was sampled at 

each well when each mineral bag deployment 

was sampled. There was very little change in 

the concentrations over the 1-month exposure 

time for each mineral bag. While most 

elemental concentrations remained fairly 

constant over the entire 2-year period of this 

study, Fe and Mn concentrations in wells MAU07 and MAU-08 varied considerably, 

demonstrating changing redox conditions in 

these wells. The values presented in Table 2.1 

represent typical groundwater concentrations. 

Table 2.2 shows the Fe and Mn concentrations 

in MAU-07 and MAU-08 wells over the entire 

study period. Fe and Mn concentrations in 

MAU-08 were particularly variable, and seemed 

to vary seasonally, being lower in the spring and 

higher in the fall. However, the presence of 

dissolved Fe(II) in these wells is an indication 

that in addition to U(VI) sorption, U(IV) 

precipitation might occur in these wells,

increasing the apparent Kd values (Davis et al., 

2006). 

Table 2.1. Typical chemical compositions of groundwater in the wells used for mineral bag 

deployment. The values are from samples collected on 11/10/2004, except for well NAT-25, 

which was sampled on 4/23/2004. 

pH Alk‡ U Ca Fe Mg Mn Na Si V

meq/L μg/L mg/L 

MAU-01 7.10 6.98 608 154 BDL† 43.8 0.72 217 8.39 0.16

MAU-07 7.02 7.57 485 173 2.05 51.7 0.91 171 8.07 0.18

MAU-08 7.16 9.91 923 191 0.90 65.9 1.19 474 8.66 0.23

NAT-05 7.02 7.57 878 168 BDL 59.8 1.07 315 9.85 3.80

NAT-09 7.26 6.66 476 163 BDL 47.9 0.06 189 9.81 1.99

NAT-11 7.09 6.65 639 227 BDL 64.8 1.11 217 9.65 1.94

NAT-19 6.98 5.60 32 215 BDL 53.9 1.44 144 7.53 0.38

NAT-20 7.11 4.33 12 208 BDL 43.4 BDL 65 6.33 0.17

NAT-24 7.08 6.76 629 170 BDL 45.0 0.20 166 8.42 0.17

NAT-25 7.02 9.23 1256 178 1.10 56.8 0.30 450 8.81 0.20

NAT-26 7.21 9.97 1782 133 BDL 60.3 0.10 726 7.01 0.21

†

BDL: Below detection limit 

‡

Alk: Alkalinity 

Table 2.2. Iron and manganese concentrations in wells MAU-07 and MAU-08 at various 

sampling times. 

Mar04 Apr04 Oct04 Nov04 Mar05 Apr05 Nov05 Dec05

Fe Concentrations (mg/L)

MAU-07 2.02 2.02 1.74 2.05 1.87 1.70 1.35 1.68

MAU-08 0.12 BDL† 1.97 0.90 BDL BDL 0.48 0.52

Mn Concentrations (mg/L) 

MAU-07 1.23 1.15 0.74 0.91 1.09 1.02 0.82 1.02

MAU-08 0.35 0.27 1.14 1.19 0.06 0.87 1.10 0.60 †BDL: Below detection limit 

913 
Water collected from inside the clinoptilolite 

and FMW dialysis bags is compared with the 

bulk groundwater collected at the same time 

(December 2005) in Figure 2.3. The 

concentrations of U, K, Mg, and Na inside the 

bags agreed within measurement error with the 

concentrations in bulk groundwater. Calcium

concentrations inside the bags were either the 

same or slightly lower inside the bags in 

comparison to the bulk groundwater. Measured 

values for Fe and Mn were much more variable, 

with no clear trend. 

2.5 In-situ Kaolinite Field 

Measurements 

2.5.1 Effect of Residence Time in Wells 

A comparison of the KDT samples retrieved 

after 2 days and 1 month of exposure time in the 

wells demonstrates that U(VI) concentrations 

did not reach equilibrium after only 2 days in the 

wells (Fig. 2.4). More U(VI) was extracted by

carbonate solution in every well after 1 month 

of exposure time versus 2 days (Fig. 2.4A). 

However, in the case of the nitric acid 

extractions, only two wells with the highest 

overall U(VI) concentrations (NAT-24 and 

NAT-26) showed higher U(VI) extracted after 1 

month of exposure time (Fig. 2.4B). This trend 

is a reflection of the lack of equilibrium between 

the water inside and outside of the dialysis 

tubing. Because there was some water entrained 

with the kaolinite sample before it was dried (up 

to 5 mL/g), a fairly large correction was required 

to the raw carbonate extraction data in order to 

account for dissolved U(VI) present within the 

dialysis bag. This correction was made by

assuming that the U(VI) concentration measured 

in the groundwater from each well was the same 

as that present inside the dialysis bag. Our 

kinetics experiments indicated that 7 days were 

required to reach identical U(VI) concentrations 

in water inside and outside the bags in kaolinite 

experiments, and up to 14 days of equilibration 

were required to achieve steady-state carbonateextractable U(VI) (Figs. 2.1 and 2.2). The data 

in Figure 2.4 supports our kinetic data produced 

in the laboratory, which shows that longer 

exposure times (e.g., 1 month) are necessary to 

achieve equilibrium concentrations of adsorbed 

U(VI) within the dialysis bags. 

2.5.2 Effect of Sample Holder Type

Two sample holder types were tested with 

kaolinite in the field, dialysis tubing and nylon

vials with the tops covered with dialysis 

membrane. U(VI) extracted by carbonate 

solution and nitric acid for the two types of 

sample holder deployments are shown in Figure 

2.5. While it appears that more U(VI) was 

sorbed in the samples placed in the nylon vials 

than in the dialysis tubing, the sorbed U(VI) 

values calculated for the nylon vials have much 

greater error due to the correction for dissolved 

U(VI) present in entrained water (nylon vials 

had about 2.5-5 mL water per g of kaolinite). 

For many samples, this correction was very

large, accounting for over 100% of the carbonate 

extracted U(VI) (e.g. NAT-24, KNV2). It 

appears that water inside the nylon vials was not 

in equilibrium with water outside the nylon vials 

(groundwater). Two nylon vial samples 

containing only water (no kaolinite) were also 

sampled for each well and the U(VI), Ca, Mg 

Na, and V concentrations in each are compared 

in Figure 2.6. As shown in Figures 2.5 and 2.6, 

the concentrations measured in replicate samples 

do not agree very well for these samples,

particularly for U(VI) and Ca, and also do not 

agree with concentrations measured in the bulk 

groundwater. It was concluded that the dialysis 

bags were a much better method for deployment 

in wells, because of better agreement between 

replicate samples and better equilibration 

between the bulk groundwater and water inside 

the dialysis bags. 

2.5.3 Carbonate Extraction Kinetics 

Kaolinite samples were extracted with carbonate 

solution for a period of 3 weeks. The amount of 

U(VI) extracted increased between 24 hr and 2 

weeks, but was not significantly different 

between 2 and 3 weeks. The concentrations of 

elements extracted from kaolinite by the 

carbonate solution data are shown in Figure 2.7. 

Significant amounts of V (well above 

background for the kaolinite used in this study)

were extracted from samples placed in wells 

14
NAT-05, NAT-09, NAT-11, and NAT-19. All 

other samples had low levels of V, equivalent to 

that extracted from kaolinite before deployment 

in dialysis bags in the wells.

2.5.4 Comparison of Carbonate and 

Nitric Acid Extractions

Surprisingly, a significant amount of U(VI) was 

also extracted by nitric acid following the 

carbonate solution extraction. Some of this was 

due to background U(VI) present in the kaolinite 

prior to exposure to groundwater. A comparison 

of the carbonate and nitric acid extracted U(VI) 

is shown in Figure 2.8. The “blanks” show data 

for extractions of kaolinite without exposure to 

groundwater. After the amount of U(VI) present 

in the kaolinite is subtracted out, the nitric acid 

extracted U(VI) is less than that extracted by

carbonate, but in most cases the amount is still 

significant. 

2.5.5 Comparison with Predictions 

of Kaolinite Surface Complexation 

Model 

Adsorbed U(VI) on the kaolinite samples was 

estimated from the amount of U(VI) desorbed in 

the carbonate solution extractions. Kd values for 

U(VI) adsorption by kaolinite were then 

calculated from the estimated adsorbed U(VI) 

concentration divided by the dissolved U(VI) 

concentration in the groundwater sampled at the 

same depth in the well. Model-predicted Kd

values were calculated from the calibrated SCM 

reported for kaolinite by Payne et al. (2004). The 

two sets of Kd values are shown in Table 2.3. 

The measured Kd values ranged from 0.6 mL/g 

to 2.4 mL/g for the kaolinite deployed in the 

wells, with Kd values generally increasing with 

decreasing alkalinity and U(VI) concentration. 

The kaolinite model-predicted Kd values ranged 

from 15 to 45, approximately 20 times larger 

than the measured values. The reason for the 

discrepancy between the measured and modelpredicted values is unknown, but it is suspected 

that the SCM overpredicts U(VI) adsorption 

because of the lack of experimental data at high 

partial pressures of CO2(g) in the study by Payne 

et al. (2004). The partial pressures of CO2(g) in 

groundwater ranged from 2-5% based on the 

measured pH and alkalinity values at the wells at 

which kaolinite was deployed (Table 2.1). 

Another possible reason for the disagreement 

between the model and measurements of Kd

values is that aqueous chemical conditions (e.g., 

pH, alkalinity) were different inside the dialysis 

bags than in the groundwater despite the 30-days

of equilibration, perhaps due to microbial 

fouling. However, microbial fouling was not 

visually observed and the test of U(VI) 

concentrations inside and outside the dialysis 

bags showed little difference. This suggests that 

the difference between the measured and modelpredicted Kd values may be more likely

impacted by the accuracy of the SCM under 

conditions of high partial pressures of CO2(g). 

The measured Kd values for wells MAU-07 and 

MAU-08 did not seem unusually larger than 

other wells, suggesting that U(IV) precipitation 

onto the samples was likely insignificant. 

Table 2.3. Comparison of measured and 

model-predicted U(VI) Kd values for 

kaolinite samples in contact with Naturita 

groundwater 

Well Measured

Kd (mL/g) 

Model-Predicted 

Kd value (mL/g) 

MAU-07 0.86 28

MAU-08 0.65 15

NAT-05 0.93 33

NAT-09 1.0 22

NAT-11 0.79 23

NAT-19 1.6 45

NAT-24 2.4 29

NAT-25 1.1 24

NAT-26 1.0 23

2.6 In-Situ Quartz Field 

Measurements 

2.6.1 Carbonate Extraction Results 

In contrast to the kaolinite samples, U(VI) 

accumulation on quartz was not measurable 

within the errors of the experimental approach. 

15
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

0.0e0

2.0e-6

4.0e-6

0.0e0

3.0e-3

6.0e-3

0.0e0

2.0e-5

4.0e-5

0.0e0

2.0e-4

4.0e-4

C

o

n

centr

atio

n (M)

Uranium

Calcium

Iron

Potassium

C1

C2

F1

F2

Bulk

Figure 2.3. Comparison of various elemental concentrations measured in replicate clinoptilolite 

(C1, C2) and 40-Mile Wash composite (F1, F2) dialysis bags compared with bulk groundwater 

(bulk) in December 2005. Data below the detection limit for Fe (1.8x10-6 M), K (2.0x10-4 M), and 

Mn (2.5x10-7 M) is not plotted.

16
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

0.0e0

1.1e-3

2.2e-3

0.0e0

1.2e-5

2.4e-5

0.0e0

1.0e-2

2.0e-2

0.0e0

5.0e-5

1.0e-4

C

onc

e

ntration (

M)

Magnesium

Manganese

Sodium

Vanadium

C1

C2

F1

F2

Bulk

Figure 2.3 (continued). Comparison of various elemental concentrations measured in replicate 

clinoptilolite (C1, C2) and 40-Mile Wash composite (F1, F2) dialysis bags compared with bulk 

groundwater (bulk) in December 2005. Data below the detection limit for Fe (1.8x10-6 M), K 

(2.0x10-4 M), and Mn (2.5x10-7 M) is not plotted.

17
MAU-07

MAU-08

NAT-05NAT-09

NAT-11NAT-19

NAT-20

NAT-24

NAT-25

NAT-26

Kaolinite

0.0e0

2.0e-9

4.0e-9

6.0e-9

8.0e-9

U C

onc

e

ntr

ation (mol/g)

2 days

1 month

A

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-25

NAT-26

Kaolinite

0.0e0

2.0e-9

4.0e-9

6.0e-9

8.0e-9

U C

onc

e

ntration (mol/g)

2 days

1 month

B

Figure 2.4. Comparison of U(VI) concentrations for kaolinite samples deployed in dialysis tubing 

and placed in wells for 2 days or 1 month. U(VI) concentrations in (A) carbonate solution extracts, 

and (B) nitric acid extracts. Sample labeled ‘Kaolinite’ shows data for extractions without field 

deployment. 

18
MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-25

NAT-26

Kaolinite

-5.0e-9

0.0e0

5.0e-9

1.0e-8

1.5e-8

2.0e-8

2.5e-8

U C

onc

e

ntration (

mol/g)

KDT

KNV1

KNV2

A

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-25

NAT-26

Kaolinite

0.0e0

5.0e-9

1.0e-8

1.5e-8

U Conc

e

ntr

ation (mol/g)

KDT

KNV1

KNV2

B

Figure 2.5. Comparison of U(VI) extracted from kaolinite deployed in different sample holder 

types: KDT (dialysis tubing) and KNV (nylon vial), with U(VI) extracted by carbonate solution (A) 

and nitric acid (B). Sample labeled ‘Kaolinite’ shows data for extractions without field deployment. 

19
MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-25

NAT-26

0.0e0

4.0e-6

8.0e-6

0.0e0

3.0e-3

6.0e-3

0.0e0

2.0e-3

4.0e-3

0.0e0

1.5e-2

3.0e-2

0.0e0

3.0e-5

6.0e-5

C

o

n

c

e

ntrati

o

n (M)

Uranium

Calcium

Magnesium

Sodium

Vanadium

Bulk

BNV1

BNV2

Figure 2.6. Comparison of dissolved concentrations of U(VI), Ca, Na, and V in bulk groundwater 

samples (sampled April 23, 2004) and replicate nylon vials without kaolinite (BNV). 

20
Kaolinite

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-24

NAT-25

NAT-26

0.0e0

4.0e-9

8.0e-9

0.0e0

1.0e-6

2.0e-6

0.0e0

1.1e-6

2.2e-6

0.0e0

5.0e-4

1.0e-3

0.0e0

5.0e-7

1.0e-6

Co

n

c

e

ntratio

n (

m

ol/g)

Uranium

Calcium

Magnesium

Sodium

Vanadium

24 hours

2 weeks

3 weeks

Figure 2.7. Concentrations of elements extracted at various times from kaolinite after exposure to 

groundwater for 1 month. For U(VI) and V, the data are corrected for the amounts of U(VI) and V 

that were present in entrained water when the kaolinite samples were collected. None of the other 

elements were corrected for the amount present in entrained water. Sample labeled ‘Kaolinite’ 

shows data for extractions without field deployment.

21
Kaolinite

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-24

NAT-25

NAT-26

0.0e0

2.0e-9

4.0e-9

6.0e-9

8.0e-9

U C

onc

e

ntr

ation (mol

/

g)

Carbonate

Nitric Acid

Figure 2.8. Comparison of U(VI) concentrations extracted from kaolinite exposed to groundwater 

for 1 month by the carbonate solution and nitric acid. The carbonate data presented is for 3 weeks 

of extraction time and is corrected for U(VI) in entrained water associated with the sample. Sample 

labeled ‘Kaolinite’ shows data for extractions without field deployment. 

A small amount of U(VI) was extracted by the 

carbonate extraction (Fig. 2.9A), however, when 

the amounts of U(VI) present from entrained 

water associated with the quartz samples are 

subtracted out, the net U(VI) extracted drops to 

zero or below, as shown in Figure 2.9B. Quartz 

has a much lower surface area than other 

minerals used in this study (0.29 m2

/g for quartz 

versus 8.4 and 50 m2

/g for kaolinite and 

hematite, respectively). Thus, we would expect 

a much lower amount of U(VI) to adsorb to the 

quartz surface per unit weight. Because the 

amount of adsorbed U(VI) is determined by

subtraction of two numbers that are of similar 

value, the experimental errors in determining 

these two numbers are greater than the actual 

amount of adsorbed U(VI). There is also the 

possibility that the correction factor applied is 

too large if the U(VI) concentrations within the 

entrained water were actually lower than the 

concentrations in groundwater outside the bag. 

However, the kinetics experiments performed in 

the laboratory showed that U(VI) in water inside 

dialysis bags containing quartz reached 

equilibrium in only 3 days. 

Other elements were measured in the carbonate 

extraction solution (Fig. 2.10). These data have 

not been corrected for amounts present in 

entrained water associated with the quartz 

samples, except as indicated in Figure 2.10 for 

V. It is interesting to note that while the 

correction for U(VI) present in entrained water 

was very large compared to extracted U(VI), the 

correction factor was not too large for vanadium. 

Vanadium accumulated on samples deployed in 

wells NAT-05, NAT-09, NAT-11, and NAT-19, 

even when correcting for the amount of V 

present in entrained water. This observation 

suggests that there was likely good contact 

between the quartz and groundwater within the 

dialysis tubing. 

22
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Quartz

0.0e0

5.0e-10

1.0e-9

1.5e-9

2.0e-9

2.5e-9

U Conc

e

ntr

ation (mol/g)

24 hours

2 weeks

3 weeks

4 weeks

A

MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Quartz

-4.0e-10

-2.0e-10

0.0e0

2.0e-10

4.0e-10

6.0e-10

U Conc

e

ntration (mol/g)

24 hours

2 weeks

3 weeks

4 weeks

B

Figure 2.9. Calculated amounts of U(VI) extracted by carbonate solution from quartz samples for 

various extraction times. The data presented represent the average from two dialysis bags 

containing quartz that were deployed in each well. Part (A) shows the amount of U(VI) extracted 

without correction for U(VI) in the water entrained with the quartz samples. Part (B) illustrates the 

same data after the correction is applied. 

23
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Quartz

0.0e0

4.0e-7

8.0e-7

0.0e0

5.0e-7

1.0e-6

0.0e0

1.0e-4

2.0e-4

0.0e0

4.0e-6

8.0e-6

0.0e0

1.0e-7

2.0e-7

C

o

ncentrati

o

n (m

ol/

g)

Calcium

Magnesium

Sodium

Silicon

Vanadium

24 hours

2 weeks

4 weeks

Figure 2.10. Concentrations of various elements (Ca, Mg, Na, Si, V) in carbonate extraction 

solutions of quartz at various time during the extraction. The data are not corrected for the 

amounts present in entrained water, except for V. The data presented represent the average from 

two dialysis bags containing quartz that were deployed in each well. Data below the detection limit 

for V (1x10-8 mol/g) and Mg (5x10-9 mol/g) are not plotted. Sample labeled ‘Quartz’ shows data for 

extractions without field deployment. 

24
2.6.2 Nitric Acid Extraction Results 

Although the amount of U(VI) extracted from

the quartz samples by the carbonate solution was 

not measurable within experimental error, a 

small amount of extracted U(VI) was measured 

in hot, concentrated nitric acid extractions (Fig. 

2.11). Some V was also extracted by nitric acid, 

although the amount extracted by carbonate 

solution accounted for the bulk of the total V 

recovered. 

2.6.3 Predictions with Quartz Surface 

Complexation Model 

As described above, adsorbed U(VI) on the 

quartz samples could not be determined within 

the experimental errors of the method. 

Nonetheless, model-predicted adsorbed U(VI) 

concentrations and Kd values were calculated 

from the calibrated SCM recently reported for 

quartz by Fox et al. (2006). The quartz modelpredicted Kd values ranged from 0.053 to 0.13. 

The predicted quantities of U(VI) adsorbed 

ranged from 4.0E-12 to 3.5E-10 moles U(VI)/g 

quartz for all wells other than NAT-26, and a 

value of 9.8E-10 for well NAT-26. Comparison 

of these values with the estimates of adsorbed 

U(VI) in Figure 2.9B show that the modelpredicted values of U(VI) adsorbed fall within 

the experimental errors of the measurements. 

Thus, the failure to measure adsorbed U(VI) 

with quartz should be interpreted as a limitation 

of the field method rather than a problem with 

the SCM. 

2.7 In-situ Hematite Field 

Measurements 

2.7.1 Carbonate Extraction Results 

Carbonate-extracted U(VI) for the hematite 

samples was much higher than any of the other 

solids investigated in this study (Fig. 2.12). For 

example, for NAT-26, the well with the highest 

U(VI) concentrations measured in groundwater, 

hematite adsorbed 2 orders of magnitude more 

U(VI) than did kaolinite per unit weight. The 

surface area of hematite is 50 m2

/g, much greater 

than that of kaolinite (8.7 m2

/g). Unlike the 

other minerals investigated, no Ca or Mg was 

detected in the carbonate extractions for 

hematite. Some V and Si were detected, but 

only in samples from wells NAT-05 and NAT11 (Fig. 2.12). 

2.7.2 Nitric Acid Extraction Results 

A comparison of the amount of U(VI) extracted 

by the carbonate solution and nitric acid 

extractions is shown in Figure 2.13. Significant 

amounts of U(VI) were recovered in the nitric 

acid extraction after the carbonate extraction, 

indicating that the carbonate extraction did not 

fully recover U(VI) accumulated on hematite 

during exposure in the wells. 

2.7.3 Comparison with Predictions 

of Hematite Surface Complexation 

Model 

Kd values for U(VI) adsorption by hematite were 

then calculated from the estimated adsorbed 

U(VI) concentration divided by the dissolved 

U(VI) concentration in the groundwater sampled 

at the same depth in the well. Model-predicted 

Kd values were calculated from the SCM shown 

in Table 2.4, the model parameters are based on 

preliminary models of unpublished data for 

carbonate adsorption (M. Kohler, unpublished 

data) and U(VI) adsorption (R. Reitmeyer, 

unpublished data) on hematite prepared with the 

same method used here. The two sets of Kd

values are shown in Table 2.5. The measured Kd

values ranged from 90 mL/g to 210 mL/g for the 

hematite deployed in the wells, with Kd values 

generally increasing with decreasing alkalinity

and U(VI) concentration. The hematite modelpredicted Kd values ranged from 550 to 3750, 

approximately 5 to 18 times larger than the 

measured values. As in the case for kaolinite, the 

reason for the discrepancy between the 

measured and model-predicted values is 

unknown, but it is possible that the SCM 

overpredicts U(VI) adsorption because of the 

lack of experimental data at high partial 

pressures of CO2(g) in the data used to calibrate 

the hematite model. Again, as in the case of 

kaolinite, the measured Kd values for wells 

MAU-07 and MAU-08 did not seem unusually

25
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Quartz

0.0e0

2.0e-10

4.0e-10

0.0e0

5.0e-8

1.0e-7

1.5e-7

2.0e-7

C

o

ncentratio

n (

m

ol/g)

Uranium

Vanadium

Nitric Acid

Total

Figure 2.11. Comparison of concentrations of U(VI) and V extracted from quartz by concentrated 

nitric acid alone versus total extracted (sum of carbonate solution and nitric acid extracts). The 

total extracted values have been corrected for U(VI) or V present in entrained water during 

sampling (this caused the total to be lower in some cases than the nitric acid extracted amount). 

The data presented represent the average from two dialysis bags containing quartz that were 

deployed in each well. Sample labeled ‘Quartz’ shows data for extractions without field 

deployment. 

26
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Hematite

0.0e0

5.0e-7

1.0e-6

0.0e0

5.0e-4

1.0e-3

0.0e0

1.1e-6

2.2e-6

C

o

n

centratio

n (

m

ol/g)

Uranium

Sodium

Vanadium

24 hours

2 weeks

3 weeks

Figure 2.12. Concentrations of various elements at selected times during carbonate solution 

extracts of hematite after exposure to groundwater for 1 month. For U(VI) and V, data are 

corrected for the amount of each element present in entrained water when samples were collected. 

The data presented represent the average from two dialysis bags containing hematite that were 

deployed in each well. Data that was below the detection limit, including all Ca and Mg values and 

some V, are not plotted. Sample labeled ‘Hematite’ shows data for extractions without field 

deployment. 

27
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

NAT-26

Hematite

0.0e0

1.0e-6

2.0e-6

0.0e0

4.0e-5

8.0e-5

0.0e0

1.0e-5

2.0e-5

0.0e0

5.0e-6

1.0e-5

C

once

ntration (mol/g)

Uranium

Calcium

Magnesium

Vanadium

Nitric Acid

Total

Figure 2.13. Comparison of various elements extracted from hematite by nitric acid alone versus 

total extracted (sum of carbonate solution and nitric acid extracts) after exposure to groundwater 

for 1 month. For U(VI) and V, data are corrected for the amount of each element present in 

entrained water when samples were collected. The data presented represent the average from two 

dialysis bags containing hematite that were deployed in each well. Data that were below the 

detection limit for V are not plotted. Sample labeled ‘Hematite’ shows data for extractions without 

field deployment. 

28
Table 2.4. Model parameters of the SCM used to predict U(VI) adsorption on hematite 

deployed in dialysis bags in Naturita groundwater 

Exponents in mass law

defining surface species⊥

Model Surface species a b c d e f Log Kf

(I=0) 

SOH2

+ 1 1 1 8.31

SO- 1 -1 -1 -11.3

SOH2

+

NO3

- 1 1 1 -1 9.36

SONa+ 1 -1 -1 1 -10.4

(SOH2

+

)2CO3 2 1 2 -2 10.1

(SOCO3-strongH2

+

)2CO3 2 1 2 -2 12.5

(SOCO3-strong)2CO3 2 1 0.82 -0.82 10.2

(SOH)2UO2CO3 2 -2 1 1 2.34

(SOH)2UO2(CO3)2

2- 2 -4 2 1 0 -2 -7.65

Hematite TLM⊕

0.1M NaNO3 

U(VI): 10-7–10-5M 

pH: 4–9 

pCO2: air

(SOHUO2-strong)2UO2CO3 2 -2 1 1 8.95

⊥ Mass law for formation of the surface species is: [Surface species] = 

Kf[SOH]

a

(H+)

b

(H2CO3)

c

(UO2

2+)d

exp{(-F/RT)(eΨo+fΨβ)}. Coefficients for Na+ and NO3

-

 not shown. 

⊕ Model based on unpublished data of M. Kohler for carbonate adsorption and R. Reitmeyer for U(VI) 

adsorption. TLM = triple layer model; C1 = 0.97 Farads/m2

, C2 = 0.2 Farads/m2, surface area of 

hematite (43 m2

/g in carbonate study; 46.1 m2/g in U(VI) adsorption study; 50 m2/g in dialysis bag 

study; weak site density = 33.8 μmoles/m2

; strong carbonate site density = 2.69 μmoles/m2; strong 

U(VI) site density = 0.0677 μmoles/m2; U(VI) surface species form bidentate bonds that consume two 

surface sites in mass balance and have an exponent of two in the mass law. Acidity and ion-pair 

electrolyte constants assumed to have the same values for all surface site types. 

Table 2.5. Comparison of measured and model-predicted U(VI) Kd

values for hematite samples in contact with Naturita groundwater

Well Measured Kd

(mL/g) 

Model-Predicted Kd

(mL/g) 

MAU-01 152 610

MAU-07 191 920

MAU-08 163 1020

NAT-05 125 1010

NAT-09 90 550

NAT-11 188 1070

NAT-19 210 3750

NAT-20 189 3460

NAT-24 210 3120

NAT-26 128 700

29
larger than other wells, suggesting that U(IV) 

precipitation onto the samples was likely 

insignificant. 

2.8 In-Situ Clinoptilolite Field 

Measurements 

2.8.1 Carbonate and Formate Extraction 

Results 

Clinoptilolite was first extracted with carbonate 

solution in the same manner as the other mineral 

samples. However, clinoptilolite has a very high 

capacity for ion exchange (Pabalan, 1994), and 

the sample adsorbed a large amount of calcium. 

During the carbonate extractions, the pH

dropped repeatedly and was readjusted to 9.4

several times throughout the 3-week extraction 

period. Ca and Mg concentrations were initially

high in the carbonate extraction, and dropped by

an order of magnitude by 3 weeks (Fig. 2.14). 

As shown in Table 2.6, the alkalinity of the 

carbonate extractions measured after 3 weeks 

was significantly lower than the initial alkalinity

of 20 meq/L for all samples. The unexposed 

clinoptilolite is shown for comparison. These 

observations suggest that in the field, 

clinoptilolite adsorbed Ca and Mg, which was 

subsequently released in the carbonate solution 

extraction and precipitated as Ca and Mg 

carbonate phases. Some U(VI) may have coprecipitated with these phases. For this reason, 

the clinoptilolite samples were extracted with 

0.1 M sodium formate at pH 3.5 after the 

carbonate extraction, to dissolve any precipitated 

carbonates. Sodium acetate at pH 5 is often 

used to dissolve carbonates with minimal 

disturbance of other minerals. However, at pH 

5, U(VI) adsorption is strong (Pabalan et al., 

1998), and readsorption onto clinoptilolite 

would have occurred. In contrast, the sodium

formate extraction solution is buffered at pH 3.5 

at which negligible U(VI) sorption occurs. 

The sum of U(VI) dissolved in both the 

carbonate solution and formate buffer 

extractions is presented in Figure 2.15. The total 

amount of U(VI) extracted from clinoptilolite in 

most of the wells is close to or less than that

present in the original clinoptilolite sample prior 

Table 2.6. Alkalinities measured in 

carbonate solutions after 3 weeks of 

extraction of clinoptilolite. Two 

replicate samples (C1 and C2) for 

each well are shown. 

Well Alkalinity (meq/L)

C1 C2

MAU-01 4.48 4.72

MAU-07 4.48 4.66

MAU-08 6.43 7.50

NAT-05 5.89 5.23

NAT-09 5.02 4.60

NAT-11 4.70 4.93

NAT-19 3.30 4.19

NAT-20 2.47 2.49

NAT-24 3.85 3.73

Clinoptilolite 20.47 20.61

to groundwater exposure (Fig. 2.15, sample 

labeled as “Clinoptilolite”). Only samples 

recovered from MAU-07 and MAU-08, and 

perhaps MAU-01, contained more U(VI) than 

was present in the unexposed mineral. 

2.8.2 Nitric Acid Extraction Results 

The nitric acid extractions recovered a greater 

amount of U(VI) from the clinoptilolite samples 

than the sum of carbonate solution and formate 

buffer extractions. However, the amount of 

U(VI) extracted by nitric acid was 

approximately equal to the amount present in the 

unexposed material, as shown in Figure 2.15. In 

fact, there appeared to be slightly more U(VI) 

present in the unexposed clinoptilolite, 

indicating that a small amount of U(VI) may

have been released by the mineral during 

exposure to the groundwater. 

The estimated Kd values for U(VI) sorption on 

clinoptilolite are shown in Table 2.7. 

Experimental measurements of U(VI) sorption 

on clinoptilolite have been made in systems 

equilibrated with air (Pabalan et al., 1998), but 

no surface complexation model has yet been 

published for these data. As in the cases of 

kaolinite and hematite, the measured Kd values 

for wells MAU-07 and MAU-08 did not seem

unusually larger than other wells, suggesting that 

30
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

Clinoptilolite

0.0e0

5.0e-6

1.0e-5

1.5e-5

0.0e0

1.0e-6

2.0e-6

3.0e-6

Concentrati

o

n (mol/

g)

Calcium

Magnesium

24 hours

2 weeks

3 weeks

Figure 2.14. Ca and Mg in carbonate solution extractions of clinoptilolite at various times. Data 

are not corrected for the amount of Ca or Mg present in entrained water during sampling. The 

data presented represent the average from two dialysis bags containing clinoptilolite that were 

deployed in each well. Sample labeled ‘Clinoptilolite’ shows data for extractions without field 

deployment. 

31
MAU-01

MAU-07

MAU-08

NAT-05NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

Clinoptilolite

0.0e0

2.0e-9

4.0e-9

0.0e0

2.0e-4

4.0e-4

0.0e0

5.0e-5

1.0e-4

0.0e0

5.0e-7

Conc

e

ntration (

mol

/g)

Uranium

Calcium

Magnesium

Vanadium

Carbonate + Formate

Nitric Acid

Figure 2.15. Comparison of various elements extracted from clinoptilolite by the sum of the 

carbonate solution and formate buffer extractions and the nitric acid extraction. The nitric acid 

sample for well NAT-19 is missing. The data presented is the average of two replicate clinoptilolite 

dialysis bags sampled from each well. Data below the detection limit is not plotted (i.e. for 

vanadium). Sample labeled ‘Clinoptilolite’ shows data for extractions without field deployment. 

32
U(IV) precipitation onto the samples was likely

insignificant. 

Table 2.7. Measured U(VI) Kd

values for clinoptilolite samples in 

contact with Naturita groundwater

Well Measured Kd

(mL/g) 

MAU-01 1.09

MAU-07 1.11

MAU-08 1.06

NAT-05 1.16

NAT-09 1.06

NAT-11 1.00

NAT-19 1.68

NAT-20 2.70

NAT-24 0.91

2.9 In-Situ Measurements with 

Forty-Mile Wash Sediments 

2.9.1 Carbonate Extraction Results 

U(VI) extracted from 40-Mile Wash sediments 

by the carbonate solution is shown in Figure 

2.16. The most notable thing about these data is 

the large amount of U(VI) accumulated on 

samples placed in well MAU-07. The amount of 

U(VI) present in groundwater was very similar 

at wells MAU-07, MAU-01 and MAU-08. 

However, the total U extracted from the FMW 

solids was much higher for well MAU-07. 

While MAU-07 is consistently one of the wells 

with the largest accumulation of U(VI) for all of 

the solids tested, only with the FMW dialysis 

bags was the extent of accumulation 

significantly higher than the other wells (close to 

ten times higher than any other well). MAU-07 

has the highest concentrations of dissolved Fe of 

any of the wells studied (Tables 2.1 and 2.2), 

indicating that iron-reducing conditions exist in 

the aquifer near this well. It seems likely that 

some U(VI) was reduced to U(IV) in the dialysis 

bag for the FMW sediment in well MAU-07, 

although this did not seem to occur for other 

mineral phases in well MAU-07 (this study) or 

when uncontaminated Naturita sediments were 

suspended in wells MAU-03 and MAU-04 

(Davis et al., 2006; Curtis et al., 2004). Perhaps 

there is something unique about the properties of 

the FMW sediments (e.g., internal porosity) that 

favors a more reducing environment and U(VI) 

reduction. High dissolved Fe(II) concentrations 

were measured consistently above detection 

(1.35-2.05 mg/L) in well MAU-07 during the 

study, but none of the other mineral samples 

exhibited such a large U accumulation, including

clinoptilolite, which was deployed in well 

MAU-07 at the same time as the FMW sample. 

For the FMW sediment, there was a fairly large 

variation in the amount of U(VI) recovered from

replicate samples (e.g., MAU-08 and NAT-05 in 

Fig. 2.16C). For well NAT-05, there was also a 

large variation in the amount of V recovered. 

The FMW solid is a composite sample that is 

much more heterogeneous than any of the single 

mineral samples studied here, and it is likely that 

the 1 g sample sizes used in these experiment 

was not sufficiently large to achieve uniform

samples. Calcium concentrations in the 

carbonate solution extractions dropped over the 

3-week period for all of the FMW samples. 

However, unlike clinoptilolite, the pH was only

readjusted once throughout the extraction 

period. Alkalinities measured at the end of 3 

weeks were 16-18 meq/L as shown in Table 2.8, 

only slightly lower than the starting alkalinity of 

20 meq/L. The alkalinity of unexposed FMW 

material is shown for comparison. It is possible 

that some U(VI) co-precipitated with carbonates 

during this extraction. Any co-precipitated 

U(VI) would be recovered in the nitric acid 

extraction. We chose not to extract these 

samples with 0.1M sodium formate buffer 

because: (1) carbonate precipitation was not 

very extensive, and (2) the FMW sediments 

contains naturally occurring carbonates which 

would be dissolved along with any newly 

precipitated carbonates. 

2.9.2 Nitric Acid Extraction Results 

Some U was extracted by the nitric acid 

extraction (Fig. 2.17), but only exceeded the 

amount of U extracted from the unexposed 

material in a couple of cases (MAU-07, perhaps 

MAU-08). The amount of U extracted by the 

carbonate solution extraction greatly exceeded 

33
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

FMW

0.0e0

4.0e-9

8.0e-9

1.2e-8

2.8e-8

3.1e-8

3.5e-8

3.9e-8

Concentration (

mol

/

g)

24 hours

2 weeks

3 weeks

A

Uranium

Figure 2.16. The concentrations of various elements dissolved in carbonate solution extracts of 40-

Mile Wash sediments. Part (A) shows U, Part (B) shows Ca, Fe, Mg, Na, and V, and Part (C) shows 

individual replicate samples for U and V. Parts (A) and (B) show the average of two replicate 

samples. U and V data are corrected for the amount present in entrained water. Data below the 

detection limit for V are not plotted. Sample labeled ‘FMW’ shows data for extractions of the 40-

Mile Wash sediment composite without field deployment. 

34
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

FMW

0.0e0

1.0e-6

2.0e-6

0.0e0

1.0e-7

2.0e-7

0.0e0

6.0e-7

1.2e-6

0.0e0

2.0e-4

4.0e-4

0.0e0

8.0e-7

1.6e-6

C

onc

e

ntration (

mol/g)

Calcium

Iron

Magnesium

Sodium

Vanadium

B

Figure 2.16 (continued). The concentrations of various elements dissolved in carbonate solution 

extracts of 40-Mile Wash sediments. Part (A) shows U, Part (B) shows Ca, Fe, Mg, Na, and V, and 

Part (C) shows individual replicate samples for U and V. Parts (A) and (B) show the average of two 

replicate samples. U and V data are corrected for the amount present in entrained water. Data 

below the detection limit for V are not plotted. Sample labeled ‘FMW’ shows data for extractions 

of the 40-Mile Wash sediment composite without field deployment. 

35
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

FMW

0.0e0

3.0e-9

6.0e-9

9.0e-9

2.5e-8

2.8e-8

3.1e-8

3.4e-8

3.7e-8

4.0e-8

C

oncentration (

mol/g)

24 hours

2 weeks

3 weeks

C

Uranium

NAT-05 NAT-09 NAT-11 NAT-19

0.0e0

5.0e-7

1.0e-6

1.5e-6

C

oncentration (

m

ol/g)

Vanadium

Figure 2.16 (continued). The concentrations of various elements dissolved in carbonate solution 

extracts of 40-Mile Wash sediments. Part (A) shows U, Part (B) shows Ca, Fe, Mg, Na, and V, and 

Part (C) shows individual replicate samples for U and V. Parts (A) and (B) show the average of two 

replicate samples. U and V data are corrected for the amount present in entrained water. Data 

below the detection limit for V are not plotted. Sample labeled ‘FMW’ shows data for extractions 

of the 40-Mile Wash sediment composite without field deployment. 

36
that extracted by nitric acid for the sample 

collected from well MAU-07. 

Table 2.8. Alkalinities measured in 

carbonate solution extractions of 

replicate (F1 and F2) 40-Mile Wash 

sediment samples deployed in 

Naturita wells after 3 weeks of

extraction 

Well Alkalinity (meq/L)

F1 F2

MAU-01 15.64 16.27

MAU-07 16.10 16.68

MAU-08 17.59 17.09

NAT-05 17.94 17.37

NAT-09 17.13 16.48

NAT-11 16.28 16.28

NAT-19 16.45 16.14

NAT-20 15.72 16.02

NAT-24 16.24 16.03

FMW 15.48 15.62

The estimated Kd values for U(VI) sorption on 

clinoptilolite are shown in Table 2.9. 

A surface complexation model for U(VI) 

sorption on 40-Mile Wash sediments has not yet 

been published, but measurements are currently 

being made in the laboratory and a model will be 

available in a future NUREG report. 

Table 2.9. Measured U(VI) Kd values 

for 40-Mile Wash sediment samples in 

contact with Naturita groundwater 

Well Measured Kd 

value (mL/g) 

MAU-01 0.80

MAU-07 12.0

MAU-08 1.91

NAT-05 0.84

NAT-09 0.22

NAT-11 0.33

NAT-19 4.09

NAT-20 2.57

NAT-24 0.37

2.10 Conclusions

The in-situ adsorption measurements were

conducted as further tests of the method of 

measuring Kd values with dialysis bags 

suspended in boreholes and as a measure of the 

applicability of surface complexation models to 

the field environment. A similar approach was 

successful in a previous application with 

uncontaminated Naturita sediments (Curtis et al., 

2004), although the grain sizes were much 

larger, allowing the use of mesh bags rather than 

dialysis tubing. However, the results presented 

here suggest that either: a) the method or 

experimental approach need improvement, 

and/or b) the surface complexation models for 

kaolinite and hematite did not work well when 

applied to the aqueous chemical conditions in 

the Naturita aquifer. In particular, the ability of 

the kaolinite and hematite surface complexation 

models to predict U(VI) adsorption under 

conditions of high bicarbonate concentration is 

not well known. The quartz surface 

complexation model presented here was 

calibrated with data at high bicarbonate 

concentrations. However, the ability of this 

model to predict U(VI) adsorption could not be 

determined because of several factors, including 

the very low surface area of the quartz sample 

and the experimental error of the dialysis bag 

method related to the entrained water collected 

with the sample. Improvements to the method 

and the deployment of larger sample sizes in the 

well could solve some of these problems. 

Larger samples would allow a sampling of water 

within the dialysis bag for aqueous chemical 

conditions. The use of a centrifuge in the field 

might be required to improve solid/liquid phase 

separation at the time of sampling, which would 

reduce the correction required for entrained 

water in the sample. 

In-situ Kd values for U(VI) adsorption on 

samples of clinoptilolite and a 40-Mile Wash 

sediment composite were also made, but these 

values could not be compared with modelpredicted values because of the lack of published 

models for these samples at present. 

37
MAU-01

MAU-07

MAU-08

NAT-05

NAT-09

NAT-11

NAT-19

NAT-20

NAT-24

FMW

0.0e0

1.0e-8

2.0e-8

3.0e-8

4.0e-8

Concentration (

mol

/

g)

Nitric Acid

Total

Figure 2.17. Comparison of U extracted from 40-Mile Wash sediments by nitric acid alone 

and total U extracted by the sum of the carbonate solution and nitric acid extractions. 

Nitric acid data for a couple of samples are missing (NAT-09 and NAT-19). The data 

presented is the average of two replicate FMW sample dialysis bags sampled from each 

well. Sample labeled ‘FMW’ shows data for extractions of the 40-Mile Wash sediment

composite without field deployment. 

38
3 REACTIVE TRANSPORT MODELING APPROACHES FOR 

IN-SITU TRACER TESTS 

3.1 Introduction 

Previous work (Davis and Curtis, 2003; Curtis et 

al., 2006) demonstrated that the reactive 

transport of U(VI) at the Naturita site could be 

simulated with a model that used a semimechanistic SCM to describe U(VI) adsorption 

to the aquifer sediments. While these results are 

encouraging, the simulations do not provide a 

rigorous test of the SCM because the good 

match between the observed and simulated 

U(VI) concentrations was achieved by model 

calibration. Specifically, the concentrations of 

U(VI) and alkalinity in recharge water that had 

leached through the mill yard and the tailings 

pile were varied to optimize the fit to the

observed data. The composition and spatial and 

temporal distribution of this contaminated 

recharge were not measured and consequently

significant uncertainty must be attributed to the 

U(VI) source and therefore to the transport 

simulation results. The semi-mechanistic model 

gave good predictions of U(VI) Kd values 

measured under variable chemical conditions for 

both contaminated sediments (Kohler et al., 

2004) and for NABS samples that were 

suspended in 17 different monitoring wells 

(Curtis et al., 2004). These studies involved 

equilibration times that ranged from days to 

years and therefore may not be applicable to the 

dynamic conditions present in an aquifer. 

Therefore, small-scale tracer tests are a more

rigorous approach for evaluating the 

applicability of the semi-mechanistic SCM 

developed for Naturita aquifer background 

sediments (NABS). 

 

3.1.1 Background 

Two types of experiments were conducted to 

evaluate the applicability of the semimechanistic SCM to describe U(VI) adsorption 

and desorption under field. Both single well 

push-pull tests (Section 4) and multi-well, smallscale migration tests (Section 5) were conducted 

to evaluate the effect of variable geochemical 

conditions on the reactive transport of U(VI). 

The tracer tests were conducted in the shallow 

alluvial aquifer downgradient from the former 

uranium mill and the tailings disposal area. The 

U(VI) concentration in the groundwater at the 

tracer test site was approximately 4 μM, the 

alkalinity was 7.5 meq/L and the pH was 

approximately 7.1. Previous studies at the site 

demonstrated the U(VI) concentration was most 

sensitive to the alkalinity and least sensitive to 

the pH values relative to the range of measured 

values. Uranium migration tests were conducted 

on a scale of 1-3 m and considered variable 

U(VI) concentration and alkalinity, and included 

Br as an inert tracer. The objectives of these 

tests were to evaluate field methods for 

determining and evaluating adsorption reaction 

constants for use in reactive transport 

simulations. 

 

3.1.2 Uranium(VI) Adsorption 

In the absence of separate U phases, adsorption 

is probably the most significant factor that 

reduces U(VI) mobility in groundwater. Batch 

adsorption experiments were conducted using 

Naturita aquifer background sediments (NABS) 

that were collected from a gravel pit located 

upgradient of well DOE547 (Davis et al., 

2004b). The batch experimental conditions 

encompassed the range of geochemical 

conditions observed in the field and a semimechanistic SCM was fit to the adsorption data 

using the geochemical optimization program

FITEQL (Herbelin and Westall, 1999). The 

SCM consists of 6 reactions and 3 different sitetypes that are listed as Model 1 in Table 3.1. 

The three site-types are described as very strong 

(>SSOH), strong (>SOH), and weak (>WOH) 

sites, corresponding to their relative U(VI) 

binding strength (Table 3.1). Multiple site-types 

are commonly used in formulating SCMs and 

approximating the nonlinear isotherms 

commonly observed for cation adsorption on 

well-characterized metal oxides (Dzombak and 

Morel, 1990). Postulating multiple site-types 

was also important for simulating peak tailing in 

laboratory columns packed with quartz (Kohler 

39
Table 3.1 NABS Surface Complexation Model 1

 

Reaction Symbol2 Log K kf

Model 1: Reactions in terms of the UO2

+2 species

>SSOH + UO2

2+ = >SSOUO2+

 + H+ KSS 6.80 3x1014

>SOH + UO2

2+ = >SOUO2+

 + H+ KS 5.82 4x1013

>WOH + UO2

2+ = >WOUO2+

 + H+ KW 2.57 2x1010

>SSOH + UO2

2+ + H2O = >SSOUO2OH + 2H+ KSSOH -0.67 5x1014

>SOH + UO2

2+ + H2O = >SOUO2OH + 2H+ KSOH -2.08 4x1013

>WOH + UO2

2+ + H2O = >WOUO2OH + 2H+ KWOH -5.32 2x1010

Model 2: Reactions in terms of the Ca2UO2(CO3)3 species 

>SSOH + Ca2UO2(CO3)3 + 2H+

 = >SSOUO2

+

 + 3HCO3

-

 + 2Ca2+ 7.23 1.8x1022

>SOH + Ca2UO2(CO3)3 + 2H+ = >SOUO2

+

 + 3HCO3

-

 + 2Ca2+ 6.25 9.0x1021

>WOH + Ca2UO2(CO3)3 + 2H+ = >WOUO2

+

 + 3HCO3

-

 + 2Ca2+ 3.01 1.8x1018

>SSOH + Ca2UO2(CO3)3 + H+ + H2O = >SSOUO2OH + 3HCO3

-

 +2Ca2+ -0.23 6.0x1014

>SOH + Ca2UO2(CO3)3 + H+ + H2O = >SOUO2OH + 3HCO3

-

 +2Ca

2+ -1.65 4.0x1013

>WOH + Ca2UO2(CO3)3 + H+ + H2O = >WOUO2OH + 3HCO3

-

 +2Ca2+ -4.88 1.8x1009

et al., 1996). Davis et al. (2004b) illustrated that 

observed and modeled KD values at constant pH 

and alkalinity decreased by a factor of 

approximately 3 as U(VI) concentration 

increased from 0.03 μM to 10 μM indicating 

that the adsorption isotherm is moderately

nonlinear. The semi-mechanistic SCM does not 

include an electrical double layer term and 

assumes that the adsorption occurs by U(VI) 

binding to generic sites that represent average 

surface chemical properties of the sediment. 

3.1.3 Push-Pull Tracer Tests 

A push-pull test (also known as a single-well 

injection-withdrawal test) involves the injection 

(“push”) of a test solution into an aquifer

followed by the extraction (“pull”) of the test 

solution/groundwater mixture from the same

location (Hall et al., 1991; Leap and Kaplan, 

1988; Istok et al., 1997). The push and pull 

phases of the test may be separated by a “drift” 

phase where the test solution migrates with the 

native groundwater and provides time to allow 

reactions of interest to occur. The tests may be 

performed in existing monitoring wells or multilevel samplers and therefore could be applicable 

at many sites. The injected test solution usually 

consists of groundwater with a non-reactive 

tracer added to account for dilution, and the test 

solution can contain one or more other solutes of 

interest. During the injection phase, the test 

solution is injected into the aquifer where it 

flows away from the injection well as a roughly 

cylindrical tracer cloud in an ideal case. During 

the extraction phase, flow is reversed and the 

40
concentrations of tracer, reactive solutes, and 

possible reaction products are measured as a 

function of time at the same well. Push-pull 

tests have been conducted to evaluate the 

physical properties of an aquifer including the 

porosity, dispersivity, advection velocity and the 

extent of mass transfer between mobile and 

immobile zones. Push-pull tests have also been 

conducted to evaluate in-situ reactions related to 

a variety of processes including estimating 

biodegradation rates, ion exchange reactions, 

and partitioning of tracers between aqueous and 

non-aqueous phases. 

 

3.1.4 Objectives 

The purpose of this section is to develop a 

strategy for modeling the reactive transport that 

occurs during the in situ push-pull tracer tests. 

These simulations, coupled with sensitivity 

analyses, are critical for discriminating between 

competing processes that affect U(VI) 

concentration such as adsorption, dilution and 

reduction. 

3.2 Reactive Transport Modeling 

Approaches for Push-Pull Tests 

Although push-pull tests have been conducted to 

investigate a wide variety of subsurface 

processes including advection, dispersion, 

degradation and sorption, the application of a 

general reactive transport model to push-pull 

tests has generally lagged behind the 

experimental studies. Part of this difference 

probably results because push-pull tests have 

often been used to investigate physical processes 

such advection and dispersion (Hall et al., 1991; 

Leap and Kaplan, 1988). Most push-pull studies 

involving reactive processes have focused on 

kinetically controlled reactions (Istok et al., 

1997, Reinhard et al, 1997; Haggerty et al., 

1998; Schroth et al, 1998). Push-pull tests have 

also been conducted to evaluate the reductive 

immobilization of U by reducing U(VI) to U(IV) 

(Senko et al., 1998). Only a few push-pull 

studies have considered adsorption (Istok et al., 

1999; Schroth et al, 2001). One previous study

on adsorption of DOWAX, a commercially 

available surfactant, simulated adsorption using 

a Langmuir isotherm and found that the effect of 

adsorption was overpredicted, possibly because 

of rate-limited adsorption (Istok et al., 1999). 

None of the previous studies have used 

multicomponent reactive transport modeling to 

help understand the processes controlling 

adsorption that is sensitive to variable chemical 

conditions. 

Push-pull tests in most field settings require at 

least a two-dimensional (e.g., Schroth et al., 

2001) and perhaps a three-dimensional solution. 

This arises because during the injection and 

withdrawal phases of the experiment, the 

transport occurs radially outward from or toward 

the groundwater well in response to the pumping 

stress. However, during the drift phase of the 

experiment, transport may occur primarily in 

one direction in response to the natural gradient. 

In aquifers where the vertical hydraulic 

conductivity is significantly smaller that the 

longitudinal or transverse hydraulic 

conductivity, it might be possible to approximate 

the aquifer as a single two-dimensional layer. 

Conversely, if the vertical hydraulic 

conductivity is comparable in magnitude to the 

longitudinal or transverse hydraulic 

conductivity, or if there are significant 

heterogeneities in the hydraulic conductivity, 

three-dimensional simulations may be required. 

Although push-pull tests have the advantage that 

the tests are conducted in situ, the tests have the 

disadvantage that the flow system and transport 

velocities are highly perturbed during the both 

the push and pull (but not drift) phases of the 

experiment. Specifically, during both the push 

and pull phases of the test, the flow field is 

dominated by radial transport and consequently

the groundwater velocities with the radial 

distance squared if the flow is predominantly

cylindrical or even with the radial distance 

cubed if the flow is predominantly spherical. 

Moreover, the local equilibrium assumption may

not be valid in radial flow (Valocchi, 1986). 

Consider, for example, a typical study described 

discussed in chapter 4 that involved injection of 

0.04m3

 (40L) into a well with a 1m-screened 

interval at a uniform rate of 0.08 m3

/hr. If it 

assumed that the adsorption reaction can be 

described by a linear isotherm having a half life 

41
of 24 hours, then the dimensionless parameter 3.2.1.1 Local Equilibrium

that can be considered to equal the rate of 

adsorption relative to the rate of advection has a 

value of 400 at a distance of 1m from the well. 

Valocchi (1986) found that for such a value of 

the dimensionless parameter, the local 

equilibrium assumption would probably 

introduce significant errors into a simulation 

result. Although it is difficult to extrapolate 

these results for a linearly sorbing solute 

reacting with an infinite supply of adsorption 

sites to the case of U(VI) adsorption where the 

adsorption is nonlinear and constrained by a 

finite number of sites, the results nevertheless 

raise questions about the validity of the local 

equilibrium approximation for U(VI). 

The local equilibrium approach was used 

previously to simulate U(VI) transport at the 

Naturita site (Curtis et al., 2006). This approach 

assumes that the characteristic times of 

adsorption reactions are fast relative to the 

characteristic times for reaction. This 

assumption makes it possible to ignore the many

possible causes for departure from equilibrium

such as kinetic limitations of sorptiondesorption, diffusion within aggregates or mass 

transfer between zones of different hydraulic 

properties. 

3.2.1.2 Kinetically Controlled Adsorption 

3.2.1 Alternative Conceptual Models For 

Simulating Push-Pull Tests 

An alternative to the local equilibrium approach 

is to assume that the adsorption reactions are 

kinetically controlled. Adsorption of U(VI) by 

the NABS sample in batch adsorption studies 

required approximately 3 days to reach 

equilibrium (Davis et al., 2004b). Transport 

simulations with kinetically controlled 

adsorption reactions were conducted to evaluate 

if this adsorption time scale could produce 

significant deviations from local equilibrium in 

the field scale simulations (Davis and Curtis, 

2003). Although the kinetic effects were found

to be negligible for the plume scale simulations, 

kinetically limited sorption could be important 

in the small-scale push-pull tests where the flow 

field is highly perturbed. 

The primary goal of this project is to evaluate if 

semi-mechanistic SCM models can be used to 

described U(VI) adsorption and desorption 

under variable geochemical conditions. Owing 

to the complexity of the geochemical and 

hydrological systems, this evaluation inevitable 

involves the comparison between observations 

and numerical model simulations. The simple 

approach of assuming local equilibrium

assumption is an obvious starting point for these 

numerical simulations. Other approaches 

considered include a kinetics approach, a mass 

transfer approach and a hybrid approach that 

ignores adsorption-desorption reactions during 

the push and pull phases of the experiments. An empirical approach to simulate the effect of 

slow kinetics is to use 'mass action kinetics'

which relates the rate of the reaction to the 

reaction stoichiometry. For example, the 

adsorption reaction can be written as:

+ + > +

←

→

+ > + WOUOOH 2H

k

k

UO WOH H O

r

f

2

2

2 (3-1) 

where kf and kr are rate constants. The rate of formation of adsorbed U(VI) is: 

42
k ( WOUOOH)(H ) k ( WOH)(UO ) t

( WOUOOH) 2

r 2

2

f

+ + = > − >

∂

∂ > (3-2) 

In order to maintain consistency with the NABS SCM, the rate constants were related to the equilibrium

constant (KEQ) by: 

r

f

EQ k

k

K = (3-3)

Alternatively, the adsorption reaction in terms of the abundant aqueous Ca2UO2(CO3)3 is: 

+ − + > + +

←

→

+ > + + 2

2 3

'

r

'

f

2

0

2 2 3 3(aq) WOUO OH 3HCO 2Ca

k

k

Ca UO (CO ) WOH H H O (3-4)

A complete set of rate expressions using UO2

+2

ion as the reactant in the adsorption reactions is 

referred to as Model 1 and a complete set of rate 

expressions using the Ca2UO2(CO3)3

0

(aq) ion as 

the reactant is referred to as Model 2 and these 

are summarized in Table 3.1. The two 

stoichiometric formulations listed in Table 3.1 

were used because the two kinetic models are 

affected differently by variable chemical

conditions. 

The rate constants in Table 3.1 were estimated 

from batch data collected at pH 7.9 and at 

atmospheric partial pressure of CO2 (Davis et 

al., 2004b). The two calibrated batch adsorption

models are illustrated in Figures 3.1a and 3.1b

for batch data collected at 0.09 and 9.5 μM 

U(VI). For both initial concentrations the model 

simulations reach a stable concentration after 

approximately 50 to 70 hr, in agreement with the 

adsorption data. The simulated U(VI) 

concentrations are slightly smaller than the 

observations for both cases because the NABS 

SCM does not exactly fit the adsorption data for 

the particular experimental conditions of the 

kinetic experiments. 

3.2.1.3 Slow Mobile-Immobile Exchange 

Flow velocities in many aquifers are often 

nonuniform with water flowing rapidly in some

zones of the aquifer, slow and other zones and 

even stagnant in other zones of the aquifer. This 

distribution of velocities can result from the 

heterogeneity in hydraulic conductivity or from

stagnant zones that occur within particle grains. 

When the mass transfer between regions of high 

velocity and regions low velocity or stagnant 

zones is slow compared to the rate of advection, 

the system is in physical nonequilibrium. The 

simplest approach to simulating this 

nonequilibrium is to assume that any slowly

moving water is stagant and that the mass

transfer between the mobile and immobile zones 

is described by a simple first order mass transfer 

process:

 

k (C C ) t

C = La im − m ∂

∂ (3-5) 

where kLa is a first order mass transfer 

coefficient, Cm is the dissolved concentration in 

the mobile phase, and Cim is the dissolved 

concentration in the immobile phase. Equation 

3-5 inherently assumes that no gradients exist in 

either the mobile or immobile zones. Equation 

3-5 is perhaps the simplest approach for 

simulating physical nonequilibrium transport in 

porous medium. More complex approaches treat 

transport in the immobile zone as a diffusive 

process by explicitly simulating spatial 

gradients. Alternatively, the multirate mass 

transfer approach treats the more general case 

represented by equation 3-5, where multiple 

43
Figure 3.1. Kinetic data and model for U(VI) 

adsorption in laboratory batch experiments. 

immobile zones exist and the mass transfer 

coefficient is represented by a distribution rather 

than a single value (Haggerty and Gorelick, 

1995). 

3.2.1.4 Instantaneous Injection 

A hybrid approach for simulating a push-pull 

test is to assume that no adsorption reactions 

occur during the push or pull phases of the 

experiment. In this approach, it is assumed that 

all of the adsorption reactions and mass transfer 

processes are so slow that during the push and 

pull phases of the simulations the adsorption 

reactions can be ignored and U(VI), like all 

other species, is transported conservatively

during the injection and withdrawal phases of 

the experiment. However, during the drift phase 

of the simulation, the adsorption reactions are 

assumed to be equilibrium controlled even if the 

duration of the drift phase is arbitrarily small but 

greater than zero. To implement this approach, 

three separate simulations are conducted for the 

push, drift and pull phases. In the push phase of 

the experiment, the simulation is conducted 

assuming that the concentration of adsorption 

sites is zero. This yields a spatial distribution of 

all dissolved solutes including U(VI) which is in 

effect linearly related to the concentration of a 

nonreactive tracer. With the exception of U(VI), 

these distributions are used as initial conditions 

for the total aqueous concentrations for the drift 

phase. For the case of U(VI), the simulated 

dissolved U(VI) concentration at the end of the 

injection phase is added adsorbed U(VI) 

computed from the NABS SCM and the 

background conditions in the aquifer to define 

the total (aqueous plus adsorbed) U(VI) 

concentration. Consequently, when the drift 

phase of the test is initiated, the simulation 

distributes the total U(VI) between the dissolved 

and adsorbed phases. During the drift phase of 

the experiment, U(VI) transport is controlled by

local equilibrium processes. The simulated 

aqueous concentrations at the end of the drift 

phase are used as the initial conditions for a third 

simulation, which represents the pull phase of 

the tracer test. These last simulations are 

conduced with no adsorption reactions. 

3.3 Model Scenarios 

The behavior of U(VI) was simulated for each of 

the conceptual models described above for 

several geochemical scenarios. Two dimension 

simulations were conducted in a hypothetical 

aquifer that was 8m long and 4m wide as 

depicted in Figure 3.2. No flow boundaries 

were assumed along the long axis of the aquifer 

and constant head boundaries were assumed 

along the short axis of the aquifer. The heads at 

the constant head boundaries were computed 

from the average gradient of 0.001, which is 

typical of the Naturita aquifer near well NAT25, 

where the tracer tests described in Section 4 

were conducted. Other values used in the 

simulations are listed in Table 3.2; each is 

representative of the tracer test site near well 

NAT25. 

44
Most of the simulations were conducted by

assuming that the aquifer could be approximated 

as a 2-dimensional areal aquifer with constant 

thickness. In general, the simulated aquifer was 

constructed to be representative of the general 

conditions near well NAT25. Most of the tests 

described in chapter 4 involved injecting 0.035 

to 0.040 m3

 of groundwater into the test well; 

therefore the injected volume was assumed to 

equal 0.036 m3

 in all simulations. The thickness 

of the aquifer was assumed to equal only 0.3m

even though the saturated thickness near well 

NAT25 is approximately 2m. This thin layer 

was assumed because the tracer tests described 

in Chapter 4 were conducted in wells with a 0.15

screen length. In addition, most of the tracer 

tests described in Section 5 showed distinct 

vertical gradients, suggesting that the vertical 

spreading was small and thus supporting the 2D 

approximation. Moreover, separate simulations 

that used a 3D approach for describing the pushpull test results, witha vertical hydraulic 

conductivity that was 10 percent of the 

horizontal hydraulic conductivity, showed only

small differences when compared to the 2D 

simulations. 

Figure 3.2 illustrates the most significant 

features of the simulated aquifer. The width of 

the aquifer was assumed to be 4m. This width 

was selected because it is approximately 10 

times than the diameter of a cylinder that would 

enclose the 0.04m3

 injection for the assumed 

porosity of 0.3 and aquifer thickness of 0.3m. 

The length of the aquifer was twice the width 

(8m) and the injection well was located 2.6m

from the upgradient boundary. No flow 

boundary conditions were assumed along the 

sides of the aquifer and constant head boundary

conditions were assumed on the upgradient and 

downgradient boundaries. 

One of the challenges in conducting the 

simulations described below was that during the 

push and pull phases of the simulated tests, the 

flow in the aquifer was predominantly radial but 

during the drift phase of the test, the flow was 

predominantly longitudinal. These two different 

flow regimes naturally suggest a radial grid and 

a Cartesian grid respectively but this was not 

feasible for a single simulation. For simplicity,

a uniform Cartesian grid was used in all of the 

simulations. However, the timestep used in the 

simulations was varied to insure that the Courant 

number (Cr=v∆t/∆x) was equal to 0.8 for push, 

drift and pull phases of the simulation. 

The base case properties used in simulations are 

listed in Table 3.2. The simulations, however, 

assumed that the aquifer was confined because 

this assumption made it easier to conduct the 

simulations because it avoided the tendency of 

the simulations to produce dry cells during the 

pull phase of cases involving low hydraulic 

conductivities.

Figure 3.2. Model domain for hypothetical tracer test simulations. 

45
Table 3-2. Properties of Hypothetical Aquifer 

Property Value

Hydraulic 

Conductivity

60 m/d 

Thickness 0.3m

Porosity 0.3 (m3/m3) 

Longitudinal 

Dispersivity

0.05m

Transverse 

Dispersivity

0.01m

Anisotropy Ratio 1.0 

∆x 0.1m

∆y 0.1m

The initial conditions used in the modeling 

scenarios were typical of the groundwater at 

well NAT25 and are listed in Table 3.3. These 

example simulations considered three 

hypothetical geochemical scenarios defined 

primarily by the alkalinity and the U(VI) 

concentration of the injectate. The simulations 

also assumed that the aquifer was in equilibrium

with respect to calcite and that the background 

ionic strength was determined by measured 

values of SO4

-2 and Cl-

 together with the 

assumption that the Na+

 concentration was 

constrained by charge balance considerations. 

The aquifer sediments in the simulations were 

assumed to have a specific surface area of 

4.2m2

/g and the site density was assumed to 

equal 2.31 sites/nm2

. These values, together 

with an assumed porosity of 0.3 gave a total 

adsorption site concentration of 4.75x10-2 sites 

per liter of groundwater. 

The model simulations used a uniform hydraulic 

conductivity and uniform distribution of

adsorption sites in all cases. While there are 

abundant reports that demonstrate the 

heterogeneous nature of hydraulic conductivity,

the simple homogeneous approach was selected 

for these hypothetical simulations because, as is 

demonstrated below, the simulated U(VI) 

transport in some cases is complex just because 

of geochemical considerations. If the 

simulations had included realistic estimates of 

hydraulic conductivity it would have been 

difficult to understand the extent to which the 

U(VI) simulations were controlled by complex 

geochemistry or complex hydrogeology.

3.4 Push-Pull Reactive Transport 

Modeling Results 

Simulations were conducted for each of the four 

conceptual models for reactive transport 

described in Section 3.2 (e.g., the local 

equilibrium approach, the kinetically controlled 

approach, the first order mass transfer approach 

and the instantaneous injection approach). For 

each conceptual model, simulations were 

conducted for the cases where the injectate had 

either high or low alkalinity but otherwise nearly

constant geochemical conditions or for the case 

where the injectate was typical of 

uncontaminated groundwater. Each simulation 

considered an injection volume of 0.036m3

 that 

was injected at a uniform rate of 0.06 m3

/hr, 

consistent with a total injection time of 0.6 hr. 

The plume resulting from the injection was 

allowed to migrate under the influence of a 

natural gradient for 15 hr and then the solution 

was extracted from the aquifer at a rate of 0.06 

m3

/hr. 

Table 3.3. Geochemical Composition of the Initial Groundwater Conditions And Injectate Used in 

the Hypothetical Simulations 

Groundwater Description 

U(VI) 

(μM) 

Alkalinity 

(meq/L) 

pH 

(-) 

SO4

-2

(mM) 

Cl- 

(mM) 

Ca+2†

(mM) 

Na+╕

(mM) 

Initial Conditions 4.0 7.5 7.1 9.0 3.4 0.4 20.6

High Alkalinity 4 22.5 7.1 9.0 3.4 1.3 18.8

Low Alkalinity 4 2.5 7.1 9.0 3.4 3.3 13.8

Uncontaminated 0.01 2.5 7.1 3.7 0.3 3.3 1.1

† Calculated from calcite equilibrium and selected alkalinity and pH 

╕Calculated from charge balance 

46
3.4.1 Local Equilibrium Simulations 

Figure 3.3 shows the simulated Br, alkalinity,

U(VI)AQU and U(VI)ADS spatial distributions at 

five times corresponding to: (1) 0.6 hr, 

corresponding to the end of the injection, (2) 6 

hr after the end of the injection, (3) 15.6 hr, 

corresponding to the end of the drift phase of the 

simulation, (4) 16.2 hr, corresponding to the 

time required to extract one injection volume 

(0.036 m3

) from the aquifer, and (5) 17.4 hr, 

corresponding to the time required to extract two 

injection volumes (0.072 m3

) from the aquifer. 

The Br plumes in Figure 3.3 illustrate that for 

the selected conditions, the idealistic ellipsoidal 

plume migrates downgradient so that at the end 

of the drift phase, the upstream boundary of the 

plume is located at the injection well. During the 

extraction (from 15.6 to 17.4 hr), the center of 

mass of the Br plume is roughly stationary and a 

significant amount of Br remains in the aquifer 

even though 2 injection volumes had been 

extracted during the pull phase of the test. This 

indicates that the water pumped from the well is 

a mixture of injectate and background water 

entering the injection well from upgradient 

locations. The simulated alkalinity behaves 

nearly identically to the simulated Br because 

there are no important reactive processes

affecting transport of HCO3

-

, the major 

constituent of alkalinity for the simulation 

conditions. The simulated U(VI)AQU plume 

exhibits distinctly different simulation results 

when compared the either Br or alkalinity. At 

the end of the injection the concentration at the 

injection well is 4 μM, which equals both the 

initial concentration and the injected 

concentration. However, a halo of high 

dissolved concentration U(VI) develops around 

the injection well because the high alkalinity of 

the injectate leaches adsorbed U(VI) from the 

sediment surfaces. The time between 0.6 and 

15.6 hr corresponds to the drift phase of the 

simulated push-pull test and during this time 

period the Br and alkalinity behave nearly 

identically. Both plumes migrate under the 

influence of the natural gradient such that at the 

end of the drift phase the upgradient extent of 

each plume coincides approximately with the 

location of the injection well. The nearly 

symmetric dissolved U(VI) plume present at the 

end of the injection transforms into an 

asymmetric plume with the highest 

concentrations located downgradient of the 

injection well at the end of the drift period. 

The geochemical changes at the injection well 

are more easily seen from a profile taken 

through the injection well along the mean 

direction of the groundwater flow. Figure 3.4a 

shows five alkalinity profiles at the same times 

shown in Figure 3.3; at the end of the injection, 

approximately midway through the drift phase, 

at the end of the drift phase, and at two times 

during the pull phase of the simulation. After 

0.6 hr, the alkalinity has an approximately 

Gaussian shape that migrates downgradient 

during the drift phase that ends after 15.6 hr, 

such that the peak concentration is 

approximately 0.8 m downgradient of the 

injection well. During the pull phase of the 

simulation, the upgradient portion of the

alkalinity plume is nearly completely extracted 

by 16.2 hr, but a significant portion of the 

alkalinity remains in the groundwater after one 

injection volume has been extracted. This 

remaining alkalinity in the aquifer implies that a 

significant portion of the water pumped during

the first 0.6 hr of the pull phase was derived 

from background water. 

The dissolved U(VI) concentrations shown in 

Figure 3.4b illustrate that the U(VI) 

concentration at the injection well at the end of 

the push phase (0.6 hr) nearly equals equals 4 

μM, which is equivalent to the concentration in 

the injectate. Both upgradient and downgradient 

of the injection well the U(VI) concentration 

reaches peak concentrations of 9.4 μM because 

the high alkalinity of the injectate leaches

adsorbed U(VI) from the sediment as shown in 

Figure 3.4c. During the drift phase of the 

simulation the U(VI) migrates downgradient, but 

the adsorption processes vary spatially and 

temporally as shown in Figure 3.4d. Dissolved 

U(VI) upgradient of the injection well readsorbs 

(Figure 3.4c) to the sediment surfaces because 

the alkalinity plume migrates downgradient 

nearly conservatively, whereas the U(VI) has a 

Kd value ranging between 0.3 to 0.8 mL/g 

(Figure 3.4d), corresponding to retardation 

factors ranging from 1.8 to 5.8. Conversely,

downgradient of the injection well the excess 

47
alkalinity causes further desorption (Figure 

3.4c). Together, the readsorption of U(VI) 

upgradient of the injection well and desorption 

downgradient causes the asymmetric U(VI) 

plume shown in Figures 3.3 and 3.4. 

The simulation results presented in Figure 3.5 

show the alkalinity, uranium, and Kd profile for 

the case where the hydraulic conductivity was 

decreased by a factor of 10 relative to the 

simulations presented in Figure 3.4. In this 

scenario, each of the profiles is nearly

symmetric at each of the simulation times

illustrated because the groundwater velocity is 

only 0.02 m/d. 

In a push-pull test, the most relevant 

experimentally observable values are the

concentrations in the water pumped from the 

aquifer during the pull phases of the experiment. 

These concentrations, which are traditionally 

presented as concentrations versus volume 

extracted normalized to the volume injected, are 

illustrated in Figure 3.6 for the two cases where 

different hydraulic conductivity values of 6 and 

60 m/d were used. The bromide concentrations 

in Figure 3.6a show that tailing was more 

significant in the case where the hydraulic 

conductivity equaled 60 m/d. This tailing is 

caused by the mixing of uncontaminated

upgradient water with contaminated 

downgradient water in the model cell containing 

the well. The bromide in the low hydraulic 

conductivity simulation initially decreases 

rapidly, but nevertheless still has a tail of small 

concentrations that extends to more that 8 

extraction volumes. The simulated alkalinity

values in Figure 3.6b show behavior that is 

nearly identical to that for bromide because, as 

noted above, alkalinity is not significantly 

impacted by reactions. 

The concentration histories for U(VI) at the 

extraction well show significant differences 

depending on the hydraulic conductivity. For 

the case where the hydraulic conductivity was 

only 6 m/d, the U(VI) concentration in the 

extracted groundwater was initially 5.1 μM, 

which slowly declined to 4 μM over the course 

of the 8 extraction volumes. In contrast, for the 

case where the hydraulic conductivity was 60 

m/d, the U(VI) concentration was practically

constant throughout the extraction phase of the 

simulation. This is particularly surprising given 

that the Figures 3.3 and 3.4 show that the peak 

simulated U(VI) concentrations were 2.2 times 

larger than the background concentrations. The 

nearly constant concentrations in this latter case 

are probably the result of multiple interacting 

processes, including U(VI) and alkalinity 

transport and speciation, along with the effects 

of advection and dispersion. 

Figure 3.7 illustrates similar results for push-pull

simulations simulated using the local 

equilibrium assumption and variable alkalinity

values. The simulations for the low alkalinity

case show that the U(VI) concentration was very

nearly constant at the injection well even though 

the U(VI) in parts of the simulation were 

decreased by a factor of 2.2. The U(VI) in the 

simulation where the background water was 

used as the injectate show a gradual increase 

over the first 4 extraction volumes. However, 

almost all of this increase can be attributed to 

simple mixing between the injectate and the 

native groundwater, indicating that the effect of 

reactions on the U(VI) was small. Taken 

together, the simulations shown in Figures 3.6 

and 3.7 suggest that the U(VI) concentration 

measured in the extracted groundwater may be 

relatively insensitive to several model variables 

including the injected alkalinity. This 

insensitivity could result from the inherent 

reversibility of the thermodynamic equilibrium, 

coupled with the reversible nature of the flow 

simulations; the primary irreversible process was 

dispersion, which was chosen to be relatively 

small in the selected simulations. 

3.4.2 Nonequilibrium Simulations 

As described above, the simplified analysis for a 

linearly sorbing solute suggested that the local 

equilibrium assumption may be a poor 

assumption for the push and pull phases of a 

push-pull test. Therefore, simulations were 

conducted using three additional conceptual 

models that include rate-limited sorption. 

Results using these approaches are described 

below. 

48
Figure 3.3. Temporal evolution of bromide, alkalinity, total dissolved U(VI) (U(VI)AQU), and total adsorbed U(VI) (U

49
Figure 3.4. Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) and 

(d) Kd values for a hydraulic conductivity of 60 m/d. 

50
Figure 3.5. Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) and 

(d) Kd values for a hydraulic conductivity of 6 m/d. 

51
Figure 3.6. Simulated concentration histories for (a) bromide, (b) alkalinity, (c) aqueous 

U(VI) at the push-pull injection-extraction well. 

52
Figure 3.7. Simulated concentration histories for (a) bromide, (b) alkalinity, (c) aqueous 

U(VI) at the push-pull injection-extraction well for the high alkalinity, low alkalinity and

uncontaminated injection scenarios. 

3.4.2.1 Kinetically Controlled 

Adsorption 

Simulations using the chemical kinetics 

approach to simulate adsorption previously

showed that at the plume scale, there was no 

significant difference between the kinetic 

simulation and the local equilibrium

simulation (Davis and Curtis, 2003). At 

smaller scales, however, kinetic limitations 

are more likely to be significant. 

Figure 3.8 shows the simulation results 

obtained using kinetic model 1 (see Table 3-

1) for Br, alkalinity, dissolved U(VI) and 

adsorbed U(VI) at five times corresponding

the end of the push phase, during and at the 

end of the drift phase and during the pull 

phase of the simulation. The Br and 

alkalinity are nearly identical to Figure 3.3, 

but the U(VI) species show some 

differences. The halo of high U(V) at the 

end of the push phase (0.6hr) was less

distinct for the kinetically controlled 

simulation as is the peak that forms at the 

53
leading edge of the plume at the end of the 

drift phase (15.6 hr). This is shown in 

additional detail in Figure 3.9, which, when 

compared with the local equilibrium

simulation in Figure 3.4, shows that each of 

the profiles in Figure 3.10 is generally more 

diffuse than the local equilibrium

simulation. Such results are typical of 

kinetically controlled simulations. 

The simulated concentration histories for the 

kinetic model are shown in Figure 3.10 for 

the case where the injectate had a high 

alkalinity of 22.5 meq/L and a U(VI) 

concentration of 4 μM. Simulations are 

illustrated for Model 1, Model 2, and also

Model 1 with each of the rate constants 

decreased by a factor of 10. This adjustment 

to the rate constant was made for both the 

forward and backward rate constants so that 

the adsorption equilibrium would not 

change. The two kinetic simulations for 

Model 1 and Model 2 were generally quite 

close to the simulation results based on the 

local equilibrium assumption. In contrast, 

the kinetic simulation that used Model 1

with each rate constants reduced by a factor 

of 10 showed significantly different results. 

In this case, the dissolved U(VI) increased to 

5 μM and then gradually decreased to 

background conditions. Apparently, this

results because the U(V) desorption remains 

relatively fast, possibly because of the high 

alkalinity, but the rate of readsorption is 

kinetically slow. 

3.4.2.2 First Order Mass Transfer 

Simulation Results 

The simulation using the simple first order 

mass transfer model were conducted using 

mass transfer coefficients ranging from 10-1

and 10-5 hr-1. Values of 10-1 gave simulation 

results that were nearly identical to those for 

the local equilibrium simulation. 

Concentration profiles obtained using a 

mass transfer constant equal to 10-2 hr-1 are

shown in Figure 3.11. The results are quite 

similar to the simulation results obtained 

using the kinetic model. The concentration 

histories for these conditions are shown in 

Figure 3.12. The simulated U(VI) 

concentration is nearly independent of time; 

similar results were also observed for the 

mass transfer coefficient equal to 10-3 hr-1 as 

well as for values of 10-4 hr-1 or 10-5 hr-1

. In 

general, none of the simulations reproduced 

the typical observations described in Section 

4, where significant increases in U(VI) 

concentration were observed in cases where 

the alkalinity of the injectate was increased. 

3.4.2.3 Instantaneous Source 

The instantaneous source approach is the 

third nonequilibrium approach used to 

simulate the push-pull test. In this approach, 

however, no kinetically controlled process is 

explicitly included in the simulation. 

Instead, the approach assumes complete

disequilibrium during the push and pull

phases of the simulation. 

Figure 3.13 shows simulated profiles for the 

case of the injection of the high alkalinity 

water. The simulated alkalinity in Figure 

3.13 is essentially identical to that simulated 

for the local equilibrium case. The simulated 

U(VI) concentration, however, is 

significantly different for the these two 

cases. For the instantaneous source method, 

the U(VI) concentration is nearly linearly 

related to the alkalinity after 0.6hr because 

no adsorption is allowed during the 

injection. Consequently, the halo of high

U(VI) concentration that forms in the local 

equilibrium case did not form when 

adsorption was not included. During the 

drift phase of the simulation, the aqueous 

U(VI) increased and adsorbed U(VI) 

decreased because adsorption reactions were 

allowed to equilibrate. Relative to the local 

equilibrium case, there are higher U(VI) 

concentrations near the injection well for the 

instantaneous source. 

The higher concentrations near the injection 

well yield initially higher concentrations 

during the pull phase of the simulation as 

show in Figure 3.14. Specifically, the 

simulated U(VI) at the extraction well starts

at 8 μM and then decreases to background

54
Figure 3.8. Temporal evolution of bromide, alkalinity, total dissolved U(VI), [shown as U(VI)AQU], and total adsorbe

(U(VI)ADS] for kinetically controlled simulations using Model 1.

55
Figure 3.9. Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) and (d) Kd

values for kinetically controlled adsorption and Model 1. 

56
Figure 3.10. Simulated concentration histories for aqueous U(VI) at the push-pull injectionextraction well the kinetically controlled simulations using model 1, model 2 and model 1 with 

decreased forward and backward rate constants. 

concentrations after approximately 5 injection 

volumes. This simulated behavior is quite 

similar to that simulated for the slow kinetics 

case in Figure 3.10. Figure 3.14 also shows the 

simulated concentration histories for the case 

when the injection water had low alkalinity or 

low alkalinity plus low U(VI) concentration. In 

both cases, the U(VI) concentrations were 

approximately 1μM, and this concentration 

gradually increased to background 

concentrations after approximately 5 injection 

volumes. 

3.5 Conclusions 

Each of the local equilibrium simulations 

showed that calculated U(VI) concentrations at 

the extraction well were relatively constant. 

This result was obtained even though the 

simulations showed that there were significant 

geochemical changes in the aquifer. The 

relatively small changes simulated for the 

equilibrium case show that push-pull tests are 

probably not effective experiments for 

evaluating semi-mechanistic surface 

complexation model parameters. However, 

push-pull tests may be very useful for studying

rates of sorption and desorption in aquifers. 

57
Figure 3.11. Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) and 

(d) Kd values for the first order mass transfer model. 

58
Figure 3.12. Simulated concentration histories for aqueous U(VI) at the push-pull injectionextraction well for mass transfer coefficients equal to 10-3 and 10-2 hr. 

59
Figure 3.13. Simulated profiles of (a) alkalinity, (b) aqueous U(VI), (c) adsorbed U(VI) and 

(d) Kd values for the disequilibrium-equilibrium case. 

60
Figure 3.14. Simulated concentration histories for aqueous U(VI) at the push-pull injectionextraction well for injection waters having high alkalinity, low alkalinity, uncontaminated 

water with a hydraulic conductivity of 60 m/d and high alkalinity injection with a hydraulic 

conductivity of 6 m/d. 

61
62
4 OBSERVATIONS AND MODELING OF U(VI) TRANSPORT 

IN PUSH-PULL TRACER TESTS 

4.1 Introduction 

Simulations of reactive transport processes in 

groundwater often require many parameters as 

model inputs. These parameters include 

hydrologic parameters that describe flow and 

transport as well as reaction parameters that 

describe the chemical reaction network. While 

hydrologic parameters are often determined 

from field tests such as pump tests, slug tests, or 

tracer tests coupled with model calibration, there 

is less agreement on how chemical reaction 

parameters should be determined. For chemical 

reaction processes, parameter values could be 

based on a variety of sources including tabulated 

thermodynamic data, laboratory experiments 

using site-specific materials, or field-determined 

values. 

The appropriate method used to obtain reaction 

parameters may depend on the type of the 

chemical reaction being modeled. For example, 

tabulated equilibrium constants may be adequate 

for simulating aqueous complexation reactions 

and some solubility constraints (Grenthe et al., 

1992, Allison et al., 1991, Smith and Martell, 

1976). For adsorption reactions, laboratory

experiments using site-specific materials have 

been used to develop surface complexation 

models (SCM) that describe the reaction 

stoichiometry and apparent stability constants 

(Davis et al., 2004b; Stollenwerk, 1998; Davis et 

al., 1998; Davis and Curtis, 2003). Although the 

SCM approach has been applied in the 

laboratory, these models have generally not been 

independently tested in the field. This study

compares hexavalent uranium (U(VI)) 

adsorption calculated from an SCM developed 

from laboratory batch experiments (Davis et al., 

2004b) with adsorption measured under in situ 

conditions at a field site. 

In oxic environments, the most stable valence of 

uranium is U(VI), which forms moderately 

soluble solid phases (Guillaumont et al., 2003). 

Thus, at concentrations less than approximately

20 μM, the mobility of U(VI) can be controlled 

by adsorption reactions at circumneutral pH 

values (Davis and Curtis, 2003). Adsorption of 

U(VI) to minerals surfaces in oxic waters is 

sensitive to pH and carbonate activity and 

therefore to the partial pressure of CO2 (PCO2). 

This sensitivity arises primarily because of 

changes in aqueous speciation, and perhaps 

surface speciation. Adsorption is generally

small at low pH values where the dominant 

species is the UO2

2+ cation. Adsorption increases 

with increasing pH usually in the pH range of 4 

to 6 and U(VI) hydrolysis species in solution 

become increasingly dominant (Davis et al., 

2002; Hsi and Langmuir, 1985; Waite et al., 

1994; Pabalan et al., 1998). In the alkaline 

region, U(VI) is strongly adsorbed in the 

absence of dissolved CO2 (Hsi and Langmuir, 

1985; Prikryl et al., 2001), but in the presence of 

dissolved CO2, the formation of aqueous U(VI)-

carbonato and Ca-U(VI)-carbonato complexes 

can cause adsorption to be negligible (Davis et 

al., 2004b; Hsi and Langmuir, 1985; Waite et al., 

1994). 

A semi-mechanistic SCM for U(VI), 

developed for the Naturita aquifer background 

sediments (NABS, Davis et al., 2004b), was 

found to predict U(VI) adsorption within a 

factor of approximately 3 by contaminated 

sediments at the site (Kohler et al, 2004) and 

by NABS samples that were contacted in situ

with contaminated groundwater (Curtis et al., 

2004). The SCM was also successfully used 

in plume scale simulations that were fit to 

historical U(VI) observation at the Naturita

mill site (Curtis et al., 2006). However,

because these simulations were calibrated to the 

observed data, the simulations were not a 

rigorous evaluation of the performance of the 

SCM under conditions of transient reactive 

transport. 

The objective of the research presented in this 

section was to evaluate the semi-mechanistic 

SCM approach in push-pull tests. Push-pull 

tracer experiments were conducted at the 

NAT25 experimental test field. The tests 

63
considered both variable alkalinity and U(VI) 

concentration, as these variables were found to

be most significant in controlling U(VI) 

transport at the Naturita site (Curtis et al., 2006). 

These data are compared with reactive transport 

simulations using the semi-mechanistic SCM 

developed for the Naturita aquifer background 

solids. 

4.2 Methods and Materials 

4.2.1 Site Description 

Infrastructure for small-scale tracer tests was 

developed at the Naturita site at a location that 

was downgradient of the highest U(VI) 

concentrations and in a relatively uniform sandy

portion of the alluvial aquifer near well, NAT25 

(Figure 4.1). The groundwater at this location 

had an average alkalinity of 8.5 meq/L, an 

average U(VI) concentration of 4 μM (950 ppb), 

and the pH was approximately 7.1. The 

groundwater near well NAT25 is nearly

saturated with respect of calcite (-0.3<SI<0.4). 

Eleven wells were installed downgradient of 

NAT25 and these wells were constructed using a 

variety of methods that changed over time. 

Wells 25B, 25C, 25F and 25G were installed as 

stainless steel drive points with a 15 cm

screened interval that was connected to a 1.25 

cm polyethylene tube with a hose barb. All of 

the materials installed below the water table 

were constructed from either stainless steel or 

polyethylene. Wells 25A, 25D and 25E were 

multilevel wells constructed from 0.75 cm

polypropylene tubing housed in a 2.5 cm PVC 

well casing. The end of the tubing protruded 

from the well casing and was covered with a 

stainless steel screen. Wells 25K, 25L 25M, 

25N, 25O, and 25P were multilevel 1.25 cm

PVC wells with a 15 cm slotted interval. These 

wells had custom fabricated permanent packers 

that isolated the two separate screened intervals, 

which were separated vertically by 30cm.

4.2.2 Tracer Test Descriptions 

The push-pull tests were conducted by pumping 

groundwater from the alluvial aquifer at the 

Naturita site into 10 gallon containers, adding 

bromide (as KBr or NaBr) as a conservative 

tracer and then, in some instances, either 

increasing or decreasing the alkalinity of the 

pumped groundwater prior to siphoning the 

groundwater sample back into the aquifer. 

Varying geochemical conditions were used in 

the tracer tests, especially the alkalinity or U(VI) 

concentration, and the conditions for the tests 

are summarized in Table 4.1. The alkalinity in 

the tests varied by approximately a factor of 8, 

while the U(VI) concentration varied by a factor 

of 100. The first two push-pull tests (PPT) were 

conducted in September 2001. PPT3 through 

PPT7 were conducted in July and August 2005,

and the remaining tests were conducted in

October and November 2005. 

Several tests used water that had a low U(VI) 

concentration. In these experiments, water from

well DOE547, which is upgradient of the former 

ore mill, was collected and transported to the 

NAT25 field test site. Other experiments used 

water that was pumped from the same vertical 

level of the well in which the push-pull test was 

conducted. 

In some experiments, the alkalinity of the 

injectate was decreased by adding concentrated 

HCl while purging the containers with N2 gas. 

The N2 gas was used to remove CO2 from

solution in order to increase pH without further 

changing the alkalinity. The HCl was added 

slowly while the containers were continuously

purged with N2, such that the pH of the 

groundwater did not drop below 6. After the 

alkalinity was decreased to approximately 3.9 

meq/L, the pH was adjusted to the final value of 

7.1 by N2 purging. 

The alkalinity of the injectate was increased in 

some experiments by adding NaHCO3 and 

Na2CO3. The pH of the containers was first 

decreased to approximately 6.0 by purging with 

10% CO2 in N2. The NaHCO3/Na2CO3 was then 

added slowly so that the pH remained below 7.3. 

Once the desired amount of NaHCO3/Na2CO3

was added, the pH was decreased to the ambient 

pH by purging the containers with the N2/CO2

gas mixture. This method was used to reduce the 

64
Figure 4.1. Map of the small-scale tracer test site developed near well NAT25. The numbers after 

the well designations indicate the different sampling levels, with 1 being the deepest screened 

interval. 

65
Table 4.1. Composition of Injectate Solutions and Groundwater in Push-Pull Tests 

Injection Water Test Site water 

Injected 

Volume 

(L) 

Drift 

(hr) 

pH U(VI) 

(μM) 

Alkalinity

(meq/L) 

pH U(VI) 

(μM) 

Alkalinity

(meq/L) 

PPT1 36.7 14.7 7.04 0.03 3.85 7.17 3.50 8.43

PPT2 35.6 15.6 7.18 0.03 7.62 7.26 3.69 8.42

PPT3 38.0 0.5 7.08 0.08 10.95 7.05 3.52 8.35

PPT4 36.5 12.8 7.11 3.32 15.17 7.12 3.36 7.69

PPT5 35.1 13.7 7.09 0.08 9.34 7.09 3.43 7.71

PPT6 44.3 13.6 7.10 3.40 3.88 7.07 3.47 7.99

PPT7 34.8 13.4 7.17 0.08 3.20 7.13 3.47 7.84

PPT8 36.6 15.4 7.11 4.65 6.04 7.07 4.57 8.40

PPT9 35.3 0.4 7.05 4.58 24.00 7.07 4.57 8.30

PPT10 30.3 2.1 7.03 4.81 8.30 7.03 4.74 8.30

PPT11 30.0 2.5 7.14 4.76 8.30 7.08 4.94 8.30

PPT12 37.4 15.4 7.11 4.62 21.80 7.05 4.92 7.93

chances of co-precipitating U(VI) in carbonate 

phases, which might have been significant if 

NaHCO3/Na2CO3 was added rapidly to the 

containers. Finally, an experiment was 

conducted with a reduced Ca concentration. For

test PPT12, Ca was precipitated by adding 28.7 

grams of Na2CO3 to approximately 53 liters of 

groundwater. The precipitated calcite was 

allowed to settle overnight and then the 

supernatant was filtered with a high capacity

0.45 μm filter and placed in a second container. 

The alkalinity of the filtrate was increased by

adding 31.9 grams of NaHCO3 and the pH (8.1 

after filtration) was adjusted to 7.1 by bubbling 

CO2 gas into the water as described above. 

4.2.3 Groundwater Sampling and 

Analysis 

Groundwater was collected using a peristaltic 

pump and filtered with a 0.45 μm Millex HV 

filter (Millipore). Samples were diluted as 

necessary and analyzed for dissolved U(VI) (by

kinetic phosphorescence analysis) and for 

selected other elements by ICP-AES. Water 

samples collected for alkalinity were titrated 

with sulfuric acid using the Gran titration 

method. Bromide samples were analyzed using a 

Lachat flow-injection analyzer. The surface 

area was measured on triplicate samples using 

the BET-N2 gas adsorption method with a 

Micrometrics Flowsorb 2000 instrument.

4.3 Results 

4.3.1 Observed Concentration Histories 

Figure 4.2 shows the results for PPT1, which 

was conducted by injecting 36.7 liters of 

background water that had a low alkalinity and 

low U(VI) concentration into well 25F, after 

21.1 g of KBr was added to the water. After a 

drift phase that lasted 14.7 hr, the groundwater 

was pumped from the injection well with a 

peristaltic pump at a constant rate of 49.9 L/hr. 

The first Br sample had a concentration that was 

only 62 percent of the injected concentration. 

Thereafter, the Br concentrations decreased 

slowly as a result of mixing in the aquifer. Even 

though only 36.7 liters of water were injected 

into the aquifer, Br concentration was still 

significant after 160 L had been pumped from

the injection well. At the end of the experiment, 

88.5 percent of the injected Br had been

extracted from the sampling well. The alkalinity

of the first sample taken was 5.7 meq/L, which 

was between the alkalinity of the injectate (3.85 

meq/L) and that of the initial groundwater (8.43 

meq/L). If the sample alkalinity was a result of 

simple linear mixing of the injectate and 

groundwater, the expected alkalinity value 

would be 6.6 meq/L, which is relatively close to 

the observed value of 5.7 meq/L. The U(VI) 

concentration of the groundwater slowly 

increased from approximately 2.2 to 3.6 μM, 

66
Figure 4.2. Concentration histories observed in push-pull tracer test 1 (PPT1). 

and this generally followed a trend that was 

opposite that of the Br tracer. Figure 4.2 also 

shows the results expected for U(VI) 

concentration computed from a simple mixing 

calculation using the Br concentration 

observations. The observed U(VI) 

concentrations were larger than the 

concentration calculated from mixing in the first 

70 liters of water pumped from the well, 

suggesting that there was a small amount of 

U(VI) desorption that contributed to the 

observed values. 

The extent of U(VI) desorption into

uncontaminated groundwater was further 

investigated in four additional experiments that 

had different drift times and different alkalinity

values in the injectate. Figure 4.3a illustrates the 

results for PPT3, which had a drift period of 

only 0.5 hr. In this experiment, the Br 

concentration remained at a constant value of 

4.6 mM for the first 30 L of groundwater 

extraction, which was equal to the injected Br 

concentration, suggesting that there was 

negligible mixing between the injectate and the 

groundwater. The U(VI) concentration in the 

first sample taken 0.5 hr after the injection was 

approximately 2.2 μM, which must be attributed 

to U(VI) desorption given the negligible mixing 

indicated by the Br observations (see dashed 

line). The U(VI) concentration gradually 

increased in the groundwater after 25 L of 

pumpage, and this increase can be attributed to 

mixing between native groundwater and the 

groundwater that had 2.2 μM resulting from

U(VI) desorption during the first 0.5 hr.

Figures 4.3b and 4.3c illustrate the results for 

U(VI) desorption into uncontaminated 

groundwater that had alkalinity values of 7.62

and 9.34 meq/L, respectively. The U(VI) 

concentrations versus volume pumped in Figure 

4.3b was similar to that in Figure 4.3a. Since 

PPT2 and PPT3 had drift times of 15.6 hr and 

0.5 hr, respectively, the results suggest that

U(VI) desorption did not continue significantly

67
Figure 4.3. Concentrations of U(VI) and Br 

tracer in push-pull tracer tests conducted 

with uncontaminated groundwater for 

various drift periods and injected alkalinities: 

(a) PPT3, (b) PPT2, (c) PPT5, and (d) PPT9. 

The dashed line represents U(VI) 

concentrations expected from the mixing of 

injected and native groundwater, based on 

the concentrations of Br tracer. 

with increasing drift time. In PPT5, which had a 

slightly elevated alkalinity in the injectate, the 

U(VI) concentration was nearly constant for the 

duration of the experiment (Fig. 4.3c). 

Figure 4.3d illustrates the desorption of U(VI) in 

an experiment that had a drift time of only 0.4

hr, with an increased alkalinity of 24 meq/L. 

Unlike the previous test results shown in Figure 

4-3, the injectate had a U(VI) concentration of 

4.6 μM, which equaled that of the ambient 

groundwater. The U(VI) concentration of the 

groundwater that was pumped from the injection 

well (after a drift time of 0.4 hr) increased as the 

first 35 L of water was pumped from the well. 

After 35 L were pumped, the Br and U(VI) 

concentrations decreased sharply, as nearly all of 

the injectate was recovered. The Br decreased to 

background concentrations, whereas the U(VI) 

decreased to approximately 90 percent of the 

initial and background U(VI) concentrations of 

4.6 μM. The U(VI) concentration remained 

nearly constant at this slightly depressed 

concentration for the duration of the experiment. 

As discussed in detail in Section 5, this decrease 

in U(VI) concentration is probably caused by

U(VI) adsorption that occurs as native 

groundwater encounters sediments that had been 

leached with the high alkalinity injected water. 

The effect of alkalinity was examined further in 

experiments with contaminated groundwater that 

was treated to either increase the alkalinity to 

15.2 meq/L or decrease the alkalinity to 6.0 

meq/L (Fig. 4.4). When the alkalinity was 

increased by a factor of two in the injectate, the 

U(VI) concentration in the first sample pumped 

from the well had also increased by a factor of 2 

(compared to the injectate concentration). After 

the first sample, the alkalinity and Br and U(VI) 

concentrations gradually decreased to the initial 

values in the aquifer. 

When the alkalinity was decreased by 50%, the 

U(VI) concentration increased slightly in the 

first 10 liters pumped from the well, after which 

the concentration was nearly constant. The 

increase in U(VI) concentration was also

observed in a duplicate experiment (results not 

shown). The reasons for the observed increase in 

U(VI) concentrations in these tests are not

68
Figure 4.4. Concentration histories for U(VI), Br tracer, and alkalinities in PPT4 and PPT8. 

Results show U(VI) desorption into contaminated groundwater that was treated to (a) increase the 

alkalinity or (b) decrease the alkalinity. 

known. The decrease in alkalinity was expected 

to cause some U(VI) present in the injectate to 

be adsorbed in a region close to the well, leading 

to a decrease in local U(VI) concentrations. 

Figure 4.5 shows the U(VI) and Ca 

concentrations observed in two experiments that 

compared the effects of adding Br as either 

NaBr or KBr. The U(VI) concentration and 

alkalinity values were identical in the injectate 

and the groundwater in both experiments. For 

the KBr experiment, the U(VI) concentration 

increased 4.3 to 5.5 μM and, at the same time, 

the Ca concentration increased slightly from 4.3 

to 4.8 mM. In contrast, the U(VI) and the Ca 

concentrations were essentially constant in the 

case with NaBr added to the injectate. These 

results suggest that the addition of K causes ion 

exchange with Ca on clay surfaces, and that the 

liberated Ca increases the formation of dissolved 

Ca-U(VI)-CO3 complexes. The Na has only a 

small effect on Ca concentration, probably

69
Figure 4.5. Changes in U(VI) concentration 

resulting from the addition of Br as either (a) 

KBr or (b) NaBr. 

because the background Na concentration is not

changed significantly by the injection 

(approximately 20 mM in native groundwater 

and 24 mM in the injectate). In contrast, the K 

concentration is 0.3 mM in the native 

groundwater and 4.3 mM in the injectate. 

The effect of Ca on U(VI) partitioning in the 

groundwater was further investigated in PPT12, 

in which dissolved Ca was removed from the 

injectate by precipitating calcite (as described in 

methods). The results show that the U(VI) 

concentration initially was 90 percent of the 

ambient value, even though the alkalinity had 

been increased to 22 meq/L (Fig. 4.6). For 

comparison, the U(VI) concentration in PPT4 

increased by a factor of 2.1 when the alkalinity

was increased to only 15.2 meq/L. Thus, U(VI) 

adsorption is apparently affected by both the 

dissolved Ca concentration and alkalinity in 

these experiments. Fox et al. (2006) found that 

dissolved Ca concentrations impact U(VI)

adsorption on quartz by changing aqueous U(VI) 

speciation.

4.3.2 Nonreactive Transport Calibration 

The Br concentrations observed in the push-pull 

tests were fit to a two-dimensional nonreactive 

flow and transport model. The model domain 

and discretization were described in Section 3. 

The purpose of the calibration was to account 

for the observed behavior of Br tracer, so that 

the reactive transport of U(VI) could be 

predicted using the semi-mechanistic SCM 

(Table 3.1, Model 1). The observed Br 

concentrations were calibrated by varying the 

hydraulic conductivity and the longitudinal 

dispersivity within the aquifer. Mobile-immobile 

zones were not considered because the mass

transfer parameter could not be calibrated from

the observed data Br data when the longitudinal 

dispersivity was also used a calibration 

parameter. The final calibrated model 

simulations for four selected cases are shown in 

Figure 4.7 and the model parameters are 

summarized in Table 4.2. 

4.3.3 Reactive Transport Simulations 

The applicability of the semi-mechanistic SCM 

(Table 3.1, Model 1) was assessed by comparing 

reactive transport simulations with the observed 

data. The groundwater velocity, dispersivity and

mass transfer coefficient for exchange between 

the mobile and immobile porosity and the 

duration of the hypothetical injection were 

obtained by calibrating a one-dimensional 

nonreactive transport model to the observed Br 

breakthrough curves. The reactive transport of 

U(VI) was then predicted using the calibrated 

nonreactive transport model parameters together 

with the semi-mechanistic SCM. The 

concentration of adsorption sites used in the 

model was 1.92⋅10-6 sites/m2

 (Davis et al., 

2004b) and was calculated from the measured 

surface area (4.0 m2

/g) of a core sample 

collected near well NAT25 (see Section 5.3.1). 

The total porosity of the aquifer was assumed to 

equal 0.4. The model simulations were 

conducted using the model RATEQ (Curtis, 

2005). Simulations were conducted using the 

70
Figure 4.6. Concentration histories observed in push-pull tracer test 12, which had an injectate with 

a low dissolved Ca concentration and an increased alkalinity. 

Table 4.2 Summary of Flow and Transport 

 Parameters Determined by Model Calibration 

Drift 

(hr) 

Well Hydraulic

Conductivity

(m/hr) 

Longitudinal

Dispersivity 

(m) 

PPT1 14.7 25F 0.98 0.047

PPT4 12.8 25O1 1.00 0.073

PPT8 15.4 25O1 2.26 0.004

PPT12 2.5 25K1 0.71 0.30

local equilibrium approach, the kinetics 

approach and the instantaneous source approach 

as described in Section 3. 

Each of the three approaches gave simulated 

alkalinity values that were nearly identical, and 

therefore, only the results obtained using the 

local equilibrium approach are shown in Figure 

4.7. In each of the four cases considered, the 

simulations gave good predictions of the 

observed alkalinity. However, the alkalinity in 

these experiments was behaving nearly as a 

nonreactive solute, which was determined by

comparing the normalized concentrations of 

alkalinity and Br tracer (results not shown). The 

three modeling approaches also gave nearly the 

same U(VI) simulation results, although the 

models did not predict the observed changes in 

several cases. A fair prediction for U(VI) 

concentration history was achieved for PPT1 

(Fig. 4.7a), but most of the change in U(VI) 

concentration can be attributed to mixing of the 

injectate and the groundwater, and not to

reactive processes. In the remaining three cases 

(Figs. 4.7b-4.7d), all of the predictions for U(VI) 

concentrations underpredicted the observed data. 

71
4.4 Conclusions 

The experimental observations illustrate that 

increases in alkalinity can desorb U(VI) that has 

been present in the Naturita aquifer for several 

decades. In addition, U(VI) desorption was 

relatively fast; push-pull tracer tests that had 

contact times of as little as 0.5 hr had U(VI) 

concentrations that increased from an initial 

concentration of 0.05 μM in the injected water to 

2 μM in sampled groundwater. Higher 

concentrations, up to 17 μM, were observed in 

some experiments where the alkalinity was 

increased. However, in one experiment where 

the alkalinity was increased and the Ca 

concentration was decreased, the U(VI) 

concentration was nearly constant. 

The push-pull test results were not useful for 

evaluating adsorption model parameters for the 

purpose of reactive transport. This limitation 

results from the nearly reversible nature of the 

reactive transport simulations when applied to 

cases where sorption processes are probed by

manipulating the groundwater alkalinity. In 

addition, the velocity and or dispersive processes 

at this site were sufficiently large that the 

geochemical effects were dampened by dilution 

in many of the experiments. It is possible that 

push-pull tests would be more successful in 

environments where the groundwater velocity is 

small. 

72
 

Figure 4.7. Comparison of observed concentration of Br, U(VI) and alkalinity with model 

simulations for: (a) PPT1 and (b) PPT4. 

73
Figure 4.7 (cont). Comparison of observed concentrations of Br, U(VI) and alkalinity with 

model simulations for (c) PPT8 and (d) PPT12.

74
5 OBSERVATIONS AND MODELING OF U(VI) TRANSPORT 

IN SMALL-SCALE MIGRATION TRACER TESTS 

5.1 Introduction 

Uranium (U) contamination of soils and 

groundwaters occurs at mining and mill sites and 

is also an important contaminant at many U.S. 

Department of Energy sites resulting from the 

storage, disposal, and processing of nuclear 

materials (Riley et al., 1992; Crowley and 

Ahearne, 2002). Under oxidizing conditions, 

uranium is predominantly present as U(VI), 

which can be quite mobile in aquifers (Davis 

and Curtis, 2003; Curtis et al., 2006). The 

mobility of U in water-rock systems is controlled both by precipitation reactions and by

sorption reactions with mineral surfaces. 

Furthermore, the extent of U(VI) adsorption and 

mobility in aquifers with circumneutral to 

alkaline pH values is controlled by the formation 

of both uranium-carbonato species (e.g., 

UO2(CO3)2

-2 and UO2(CO3)3-4) and, in calcium

rich environments, by aqueous ternary calciumuranium-carbonato species (e.g., CaUO2(CO3)3

2-

and Ca2UO2(CO3)3

0

 ). Even in environments 

where U precipitates are present, adsorption 

processes can be important controls on the 

small, but significant, concentrations that linger 

after a precipitate dissolves. Thus, a detailed 

understanding of aqueous speciation and 

sorption is necessary for accurate risk 

assessments to be performed at uraniumcontaminated sites. 

Numerous investigations of U(VI) sorption by

natural soils and sediments have been described 

in the literature (Duff and Amrhein, 1996; 

Turner et al., 1996; Barnett et al., 2000, 2002;

Zheng et al., 2003; Davis et al., 2004b, Dong et 

al., 2005, Lui et al., 2005, Qafoku et al, 2005, 

Wang et al, 2005a, Wang et al, 2005b). In some

cases, U(VI) adsorption was well described by

surface complexation models (Davis et al., 

2004b), but only a few studies have evaluated

the SCM performance under field conditions. 

A semi-mechanistic U(VI) SCM developed for 

the Naturita aquifer background sediments 

(Davis et al., 2004b) was found to predict 

U(VI) adsorption within a factor of 

approximately 3 by contaminated sediments at

the site (Kohler et al, 2004) and by NABS 

samples that were contacted in-situ with

contaminated groundwater (Curtis et al., 

2004). The SCM was also successfully used 

in plume scale simulations that were fit to 

historical U(VI) observation at the Naturita

mill site (Curtis et al., 2006). However,

because these latter results were calibrated to the 

observed data, the simulations were not a 

rigorous evaluation of the performance of the 

SCM under conditions of transient reactive 

transport. 

Small-scale natural gradient migration tests are 

directly applicable approaches for evaluating the 

semi-mechanistic SCM approach for modeling 

adsorption reactions in reactive transport 

simulations of subsurface geochemical behavior. 

In this approach, a known volume of water is 

injected into an aquifer and the aquifer is 

sampled at downgradient wells to obtain a 

description of the geochemical changes in the 

aquifer. The sampling can be conducted either 

at a single location over a period of time to 

provide a temporal description (e.g., a 

breakthrough curve) of the reactive transport 

processes, or the sampling can be conducted 

over a dense sampling network to obtain a 

spatial description of the geochemical conditions 

at a single time. The temporal approach 

(breakthrough curves) has the advantage that a 

dense observation network is not required. 

Small-scale migration tests have several

advantages when compared with the push-pull 

tests described in Chapter 4. First, after the 

relatively short injection period, the reactive 

transport processes occur under the influence of 

the natural hydraulic gradient. Therefore, the 

tests are conducted at groundwater flow 

velocities representative of the aquifer of 

interest. In addition, the natural gradient tests 

usually sample a larger volume of the aquifer, 

and therefore are less likely to be influenced by 

very small-scale heterogeneities. Like the pushpull tests, small-scale migration tests are in-situ

75
tests and are influenced by the natural 

distribution of hydraulic conductivity, 

abundance of sorption sites, and geochemical 

conditions, such as the redox environment, all of 

which can be difficult to reproduce in the 

laboratory. Small-scale migration tests, 

however, do have a number of limitations. First, 

in many aquifers it can be difficult to accurately

assess the direction of groundwater flow at the 

small-scale because of heterogeneities in 

hydraulic conductivity. This creates a 

significant probability that an injected tracer will 

not be detected unless a dense monitoring 

network is used. Second, small migrations tests 

can require a significant effort to monitor the 

spatial and temporal changes that may occur 

over several months, in order to fully resolve the 

complex geochemical response to an injected 

plume. 

 

The objectives of the work described in this 

section were to evaluate the semi-mechanistic 

SCM approach in small-scale migration tests. In 

the work described below, breakthrough curves 

were recorded at several wells that were located 

between 1.8 and 2.3 m downgradient of the 

injection wells at the NAT25 experimental tracer 

test site. The tests considered both variable 

alkalinity values and U(VI) concentration, as 

these variables were found to be most significant 

in controlling U(VI) transport at the Naturita site 

(Curtis et al., 2006). These data are compared 

with reactive transport simulations using the 

semi-mechanistic SCM developed for the 

Naturita aquifer background solids (NABS). 

5.2 Methods and Materials 

5.2.1 Site Description 

Infrastructure for small-scale tracer tests was 

developed at the Naturita site at a location 

downgradient of the highest U(VI) 

concentrations and in a relatively uniform sandy

portion of the alluvial aquifer near NAT25

(Figure 5.1). The groundwater has an average 

alkalinity equal to 8.5 meq/L, an average U(VI) 

concentration of 4 μM (950 ppb), and the pH 

was approximately 7.1. The groundwater 

sampled from well NAT25 is nearly saturated 

with respect to calcite (-0.3<SI<0.4). 

Eleven wells were installed downgradient of 

well NAT25, and these wells were constructed 

using a variety of methods that changed over 

time. Wells 25B, 25C, 25F and 25G are 

stainless steel drive points with a 15 cm

screened interval that are connected to a 1.25cm

polyethylene tube with a hose barb. All of the 

materials installed below the water table are 

constructed from either stainless steel or 

polyethylene. Wells 25A, 25D and 25E are 

multilevel wells constructed from 0.75cm

polypropylene tubing housed in a 2.5 cm PVC 

well casing. The end of the tubing protrudes 

from the well casing and is covered with a 

stainless steel screen. Wells 25M, 25N, 25O and 

25P are multi-level 1.25cm PVC wells with a 15 

cm slotted interval. These wells have customfabricated permanent packers that isolate the two 

separate screened intervals, which are separated 

vertically by 30 cm. Finally, wells 25K and 25L 

are identical to 25M-P except that these wells 

were used as injection wells. 

5.2.2 Sediment Collection 

A core was collected approximately 0.5 m west 

of well NAT25P1 in August 2005. The core 

was collected by hand augering 3.9 m to the 

water table, and then driving a 1.5” PVC pipe 

fitted with a ‘core catcher’ into the saturated 

zone of the aquifer. The core could only be 

driven to a total depth of 4.6 m, which was 

approximately 8 cm above the center of the 

lower screened interval at well NAT25P. The 

core was removed from the auger hole, and cut 

into 8 cm segments. The top 0.3 m of the core 

was missing, probably because some to the 

sediments fell out of the core when it was 

removed from the auger hole, given the 

streaking observed on the inside of the core 

liner. 

The sediments collected from the core were 

primarily Fe and Al oxyhydroxide coated quartz 

(90-95%), with minor amounts of K-feldspar 

and ferromagnetic minerals. Carbonate minerals 

were present in the sediments. 

76
Figure 5.1. Map of the small-scale tracer test site developed near NAT25. The numbers after the 

well designations indicate the different sampling levels with 1 being the deepest screened interval. 

77
5.2.3 Uranium(VI) Adsorption 

The purpose of the small-scale migration tests 

described in this section was to compare field 

observations of transient U(VI) transport with 

reactive transport simulations that used the 

equilibrium surface complexation model 

previously developed in the laboratory to

simulate adsorption reactions. Batch adsorption 

experiments were conducted using 

uncontaminated Naturita aquifer background

sediments (NABS) that were collected from a 

gravel pit located upgradient of well DOE547 

(Davis et al., 2004b). The batch experimental 

conditions encompassed the range of 

geochemical conditions observed in the U(VI) 

plume at the Naturita site, with alkalinities that 

ranged from 4 to 12 meq/L (Davis and Curtis, 

2003). However, the alkalinities in the field 

experiments described below were as high as 24 

meq/L, and consequently, use of the NABS 

SCM for the migration tests requires a modest 

extrapolation. A semi-mechanistic SCM was fit 

to the adsorption data using the geochemical 

optimization program FITEQL (Herbelin and 

Westall, 1999). The SCM consists of 6 

reactions (2 reactions each with 3 different sitetypes) that are listed as Model 1 in Table 5.1. 

The three site-types are described as very strong 

(>SSOH), strong (>SOH), and weak (>WOH) 

sites, corresponding to their relative U(VI)-

binding strength (Table 5.1). Multiple site types 

are commonly used in formulating SCMs and 

approximate the nonlinear isotherms commonly

observed for cation adsorption on wellcharacterized metal oxides (Dzombak and 

Morel, 1990). Postulating multiple site types 

was also important for simulating peak tailing in 

laboratory columns packed with quartz (Kohler 

et al., 1996). Davis et al. (2004b) illustrated that 

observed and modeled Kd values at constant pH 

and alkalinity decreased by a factor of 

approximately 3 as U(VI) concentration 

increased from 0.03 μM to 10 μM, indicating 

that the adsorption isotherm is moderately

nonlinear. The semi-mechanistic SCM does not 

include an electrical double layer term and 

assumes that the adsorption occurs by U(VI) 

binding to generic sites that represent average 

surface chemical properties of the sediment. 

5.2.4 Tracer Test Descriptions 

The small-scale migration tests were conducted 

by pumping groundwater from the alluvial 

aquifer at the Naturita site into 30 gallon 

containers, adding bromide (as KBr) as a 

conservative tracer and then, in some instances, 

either increasing or decreasing the alkalinity of 

the pumped groundwater prior to siphoning it 

into the aquifer. Three different geochemical 

conditions were used in the tests, which are 

summarized in Table 5.2. Alkalinity in the tests 

was varied by approximately a factor of 12, 

while the U(VI) concentration was varied by a 

factor of 100.

The first migration test (MT1) was conducted 

when only wells 25A-25E were installed in the 

Table 5.1 NABS Surface Complexation Model [Davis et al., 2004b] 1

Reaction Log K

Model 1: Reactions in terms of the UO2

+2 species

>SSOH + UO2

2+ = >SSOUO2+

 + H+ 6.80 

>SOH + UO2

2+ = >SOUO2+

 + H+ 5.82 

>WOH + UO2

2+ = >WOUO2+

 + H+ 2.57 

>SSOH + UO2

2+ + H2O = >SSOUO2OH + 2H+ -0.67 

>SOH + UO2

2+ + H2O = >SOUO2OH + 2H+ -2.08 

>WOH + UO2

2+ + H2O = >WOUO2OH + 2H+ -5.32 

1

 The total site concentration was 1.92⋅10-6 sites/g. The fraction of weak sites (>WOH) was 0.9989, the 

fraction of strong sites (>SOH) was 0.001 and the fraction of very strong sites (>SSOH) was 0.0001. 

78
Table 5.2. Summary of Migration Tests at the NAT25 Small-Scale Tracer Test Site 

Test 

Number

Source 

Water 

Injection 

Well 

Observation 

Wells 

Gallons 

injected 

Br-

(mM)

U(VI) 

(μM) 

Alkalinity 

(meq/L) 

MT1 DOE547 NAT25 NAT25A1 90 6.6 0.04 4.0

MT2 NAT25 NAT25,

25K, 25L 

NAT25A3, 

M1, N1, O1, 

P1 

150 6.7 4.6 2.0

MT3 NAT25 NAT25,

25K, 25L 

NAT25A3, 

D1, M1, N1, 

O1, P1 

150 6.6 4.6 24

aquifer. In this test, water from well DOE547, 

which is upgradient of the former ore mill 

location, was collected and transported to the 

NAT25 site. After the KBr tracer was added to 

the water, the water was siphoned into the 

aquifer without any further changes in 

geochemical conditions. 

In test MT2, alkalinity was decreased by adding 

concentrated HCl while purging the containers 

holding the groundwater with N2 gas. The N2

gas was used to remove CO2 from solution in 

order to increase pH without further changing 

the alkalinity. The HCl was added sufficiently 

slowly while the containers were continuously

purged with N2 gas such that the pH did not drop

below 6. After sufficient acid was added to 

decrease the alkalinity to 2.0 meq/L, the pH was 

re-adjusted to the final value of 7.1 by N2

purging. 

In test MT3, the alkalinity of the pumped 

groundwater was increased by adding NaHCO3

and Na2CO3. The pH of the containers was first 

decreased to approximately 6.0 by purging with 

10% CO2 in N2. The NaHCO3/Na2CO3 was then 

slowly added so that the pH remained below 7.3. 

Once all of the NaHCO3/Na2CO3 was added, the 

pH was decreased to the ambient pH by purging 

the containers with the N2/CO2 gas mixture. This 

method was used to reduce the chances of coprecipitating U(VI) in carbonate mineral phases, 

which may have been significant if NaHCO3

was rapidly added to the containers. 

5.2.5 Groundwater Sampling and 

Analysis 

Groundwater was collected using a peristaltic 

pump and filtered with a 0.45μm Millex HV 

filter (Millipore). Samples were diluted as 

necessary and analyzed for dissolved U(VI) 

concentration by kinetic phosphorescence 

analysis and selected other elements (by ICPAES). Water samples collected for alkalinity

were titrated with sulfuric acid using the Gran 

titration method. Bromide samples were 

analyzed using a Lachat flow-injection 

spectrophotometer. The surface area was 

measured on triplicate samples using the BETN2 adsorption method with a Micrometrics 

Flowsorb 2000 instrument. 

5.3 Results 

5.3.1 Surface Area 

The sediments that were recovered from the core 

sample were air-dried, and analyzed to 

determine specific surface area. The results, 

shown in Figure 5.2, illustrate that the surface 

area decreased with increasing depth. The depth 

shown in Figure 5.2 equals the total depth driven 

into the ground corrected for the 0.3 m of 

missing core. The measured surface areas

suggest that the surface area approaches a nearly

constant value near a depth of 4 m, although this 

trend needs to be verified with samples collected 

at greater depth. A single sample collected at 

NAT25B had a specific surface area equal to 5.4 

m2

/g (Kohler et al., 2004), although the depth 

from which this sample was collected is

79
Figure 5.2. Variation of specific surface area 

with depth. 

uncertain because the auger hole collapsed 

during sampling. For comparison, the surface 

area of the NABS sample (< 3 mm) was 5.15 

m2

/g, and the average surface area of sediments 

collected in 1998 from auger flights (during 

monitoring wells installation) was 12.4 m2

/g 

(Davis et al., 2004b). All of the sediments 

collected near well NAT25 consisted of fine 

sand, and it is estimated that only a few percent 

by weight of these samples were particles

greater than 3 mm in diameter. This contrasts 

markedly with the uncontaminated sediments 

from which the NABS sample was derived, 

which had approximately 85 percent of the 

material exceeding 3 mm in diameter. It is 

possible, however, that larger materials were 

excluded from the 3.7 cm core barrel during the 

sampling of the NAT25 samples. 

 

5.3.2 Uranium(VI) Aqueous Speciation 

The groundwater near the NAT25 tracer test site 

has a U(VI) concentration of approximately 4 

μM, an alkalinity of 7.5 meq/L, and a very stable 

pH value of 7.1. Alkalinity of the groundwater 

was varied from 2 meq/L to 24 meq/L in the 

migration tests. Figure 5.3 illustrates that at pH 

7.1, the predominant species in groundwater 

changes with alkalinity under conditions of 

variable alkalinity and equilibrium with calcite. 

At low alkalinity values, Ca2UO2(CO3)2 is 

predicted to be the predominant species, 

accounting for greater than 84 percent of 

dissolved U(VI). Most of the remaining aqueous 

U(VI) is predicted to be present as CaUO2(CO3)2

-2. Conversely, at an alkalinity of 24 

meq/L, three species are important: UO2(CO3)2

-4, 

CaUO2(CO3)2

-2 and Ca2UO2(CO3)2, accounting 

for 37 percent, 31 percent and 23 percent, 

respectively, of the dissolved U(VI). The 

primary cause for this change in speciation is 

that the predicted calcium concentration 

decreases with increasing alkalinity, due to the 

imposed requirement that calcite remain in 

equilibrium with the aqueous phase. 

5.3.3 Observed Breakthrough Behavior 

Figure 5.4 illustrates Br, U(VI), and alkalinity

concentrations observed at well A1 as a result of 

the injection of uncontaminated groundwater 

into well NAT25 (Tracer Test MT1). The 

observed Br concentration reached a maximum

concentration of 7.0 mM at approximately 86 hr, 

which is within the range of the Br 

concentrations measured in the three injection 

containers. These observations correspond to an 

approximate velocity of 10 cm/hr (2.4 m/d). 

The Br concentration also exhibits significant 

tailing, suggesting that nonreactive transport is 

impacted by zones with varying velocities. The 

observation that the Br concentration in well A1 

reached the injected concentration implies that if 

no U(VI) desorption occurred, the observed 

U(VI) concentration would have been equal to 

that in the injectate (0.04 μM). In contrast, the 

U(VI) concentration observed at 86 hr was 1.4 

μM, indicating that a significant amount of 

U(VI) desorption had occurred even though the 

sediments had been in contact with elevated 

U(VI) concentrations for several decades (Davis 

and Curtis, 2003). 

Figure 5.5 illustrates the Br, U(VI), and 

alkalinity concentrations observed in test MT2. 

80
Figure 5.3. Speciation of 4 μM U(VI) in groundwater in equilibrium with calcite at pH 7.1 and with 

variable alkalinity. 

Figure 5.4. Observed and simulated bromide, U(VI) and alkalinity concentrations in migration test 

MT1 at observation well A1. 

81
In this test, groundwater pumped from well 

NAT25 was treated to decrease the alkalinity to 

2 meq/L as described above and then the sample 

was re-injected into the aquifer. The U(VI) 

concentration in NAT25 groundwater at the time 

of the experiment was 4.71 μM and the average 

U(VI) concentration of the injectate was 4.63 

μM, demonstrating that loss of U(VI) to the 

container walls was insignificant (even with the 

decreased alkalinity). The observed Br 

concentration in observation wells A3, M2 and 

N2 reached maximum concentrations ranging 

from 4.7 to 5.5 mM, which corresponds to 71 to

83 percent of the injected concentration, and the 

peak concentrations were observed at between 

66 and 91 hr. The peak Br concentration in well 

O1 was 5.3 mM, observed at 122 hr. The four 

Br breakthrough curves for test MT2 had 

varying amounts of tailing. The breakthrough at 

well A3 showed a modest amount of tailing, 

whereas the breakthrough at O1 was nearly 

symmetrical. The breakthrough observed in 

wells M2 and N2 both had a small increase in Br 

concentration between 200 and 300 hr, and then 

gradual decreases to background concentrations 

by 500 hr. These secondary peaks probably

resulted from flowpaths that encountered zones 

of low hydraulic conductivity, but nevertheless 

were still captured by the sampling wells. 

The U(VI) concentrations in each of the 

observation wells decreased from the initial 

concentration of 4.6 μM to minimum values that 

ranged from 1.2 to 1.9 μM. Moreover, the 

decreases in U(VI) concentrations coincided 

with the decrease in alkalinity and increase in Br 

concentration. Taken together, these data 

suggest that the alkalinity perturbation migrated 

nearly conservatively and that the U(VI)

concentrations decreased in samples with

decreased alkalinity because of increased

adsorption. The observed U(VI) concentrations 

in each of the breakthrough curves (Figure 5.5) 

increased after the Br concentration had 

decreased to values near the background

concentrations. Note that these results contrast 

markedly with results that would be predicted 

from a simple constant Kd model to describe 

U(VI) adsorption. The constant Kd would 

predict a constant U(VI) concentration during 

the breakthrough curve, because the U(VI) 

concentrations in the aquifer and in the injectate 

were nearly identical. 

Br, U(VI), and alkalinity concentrations 

observed in test MT3 are shown in Figure 5.6. 

The observed Br in each of the 5 observation 

wells was similar to Br observed in test MT2. 

The alkalinity in each of the breakthrough 

curves increased and the location of the peaks 

coincided with the observed Br peak, again 

suggesting reactive processes did not 

significantly affect alkalinity. U(VI) 

concentrations increased in each of the 

experiments and the increase coincided with the 

Br and alkalinity peaks. After the Br 

concentrations had decreased to near 

background concentrations, the U(VI) 

concentrations decreased below the original 

ambient concentration of 4.7 μM to values 

ranging from 3 to 4 μM in each of the 5 

breakthrough curves. 

5.3.4 Quasi One-Dimensional 

Nonreactive Transport Modeling 

In each of the cases discussed above, Br 

breakthrough curves were dominated by a single 

peak, although there was some tailing in many

cases. Consequently, a quasi one-dimensional 

approach was used to simulate Br concentrations 

in the nonreactive and reactive transport 

simulations described below. In this quasi onedimensional approach, it was assumed that the 

domain between the injection well and each 

individual observation well could be treated as a 

separate one-dimensional column, and that a 

pulse of high Br solution was introduced into the 

column over a finite period of time. The 

simulated injection period can be significantly

longer than the actual injection time to 

compensate for high velocities that occurred 

during the actual injection. This approach is 

significantly simpler and more computationally

efficient than the two-dimensional approach 

described in Sections 3 and 4 that attempted to 

simulation the injection, drift and extraction of 

the tracers in the push-pull simulations. 

 

82
Figure 5.5. Observed and simulated bromide, U(VI) and alkalinity concentrations in migration test 

MT2 at observations wells (a) A3, and (b) M2. 

83
Figure 5.5 (cont). Observed and simulated bromide, U(VI) and alkalinity concentrations in 

migration test MT2 at observations wells (c) N2, and (d) O1. 

 

84
Figure 5.6. Observed and simulated bromide, U(VI) and alkalinity concentrations in migration test 

MT3 at observations wells (a) A3, and (b) D1. 

85
Figure 5-6 (cont). Observed and simulated bromide, U(VI) and alkalinity concentrations in 

migration test MT3 at observations wells (c) M2, and (d) N2. 

 

86
Figure 5-6 (cont). Observed and simulated bromide, U(VI) and alkalinity concentrations in 

migration test MT1 at observation well O1. 

5.3.4.1 Modeling Approach 

It was assumed that the one-dimensional domain could be approximated a simple mobile-immobile zone 

model. In this approach, transport of a nonreactive solute in the mobile zone is described by: 

m m

m

m L

m m im im C

x

v

x

C

v

t

( C )

t

( C )

∂

∂ − θ

∂

∂ = θ α

∂

∂ θ

+

∂

∂ θ

2

2

 (5-1) 

where Cm is the concentration in the mobile zone, Cim is the concentration in the immobile zone, θm is the 

porosity of the mobile zone, θim is the porosity of the immobile zone, αL is the longitudinal dispersivity, v 

is the groundwater velocity, t is time and x is distance. The concentration in the immobile zone is 

governed by: 

k (C C ) t

C

La m im

im

im = − ∂

∂ θ (5-2)

where kLa is a first order mass transfer coefficient. 

87
The applicability of the semi-mechanistic SCM 

was assessed by comparing reactive transport 

simulations using the NABS SCM with the 

observed data. The groundwater velocity, 

dispersivity and mass transfer coefficient for 

exchange between the mobile and immobile 

porosity and the duration of the hypothetical 

injection were obtained by calibrating a onedimensional nonreactive transport model to the 

observed Br breakthrough curves. The reactive 

transport of U(VI) was then predicted using the 

calibrated nonreactive transport model 

parameters together with the semi-mechanistic 

SCM described in Table 5.1. The concentration 

of adsorption sites was calculated from the 

measured surface area of the core sample of 4.0 

m2

/g and the site density of 1.92⋅10-6 sites/g 

(Davis et al., 2004b). The total porosity of the 

aquifer was assumed to equal 0.4, and it was 

further assumed that this porosity consisted of a 

mobile porosity of 0.3 and an immobile porosity

of 0.1. The model simulations were conducted 

using the model RATEQ (Curtis, 2005) and the 

calibrations to the observed Br data were 

obtained using the optimization toolbox in 

Matlab. 

5.3.4.2 Nonreactive Transport Modeling 

The observed Br concentrations illustrated in 

Figures 5.4, 5.5, and 5.6 were fit to the mobileimmobile zone model. The final calibrated 

model simulations are shown on the figures and 

the model parameters are summarized in Table 

5.3. In each case, it was possible to obtain a 

good fit to the observed data. The calibrated 

velocity values ranged by a factor of 2.5 from

0.00754 m/hr at well O1 in MT3 to 0.0189 m/hr 

at well D1 in MT2. In contrast, the dispersivity 

and kLa values ranged more widely: the 

dispersivity values ranged from 0.00066 to 

0.064 m (a factor of 100) and the kLa values 

ranged from 0.00035 to 0.107 hr-1 (a factor of 

300). Separate calculations showed that 

simulations with kLa values less than 0.002 hr-1

gave concentration breakthrough curves that 

were nearly identical to simulations that did not 

consider mass transfer (results not shown). The 

results in Table 5.3 also suggest a weak inverse 

relation between the dispersivity and the kLa

values. Given that increases in both values 

increases peak spreading, it is possible that the 

parameter combinations in Table 5.3 are not 

unique values. However, for the purposes of 

this work, the primary objective was to account 

Table 5.3. Summary of Nonreactive Transport Model Parameters 

Tracer Test Observation 

Well 

Velocity 

(m/hr) 

Dispersivity 

(m) 

kLa

(hr-1) 

Pulse 

Length 

(hr) 

MT1 A1 0.0112 0.000664 0.00263 57.7

MT2 A3 0.0127 0.00309 0.00461 37.3

MT2 M2 0.0102 0.0318 0.00287 48.5

MT2 N2 0.0118 0.0645 0.00194 48.3

MT2 O1 0.00928 0.000325 0.0144 34.3

MT3 A3 0.00965 0.0229 0.107 46.0

MT3 D1 0.0189 0.000749 0.00545 47.9

MT3 M2 0.00787 0.0169 0.00397 59.0

MT3 N2 0.00816 0.0637 0.000350 92.9

MT3 O1 0.00754 0.00118 0.0107 58.8

88
for the observed Br concentration breakthrough,

even if only empirically, in each of the 

breakthrough curves.

5.3.4.3 Reactive Transport Modeling

Simulated U(VI) concentrations and alkalinity

for test MT1 are illustrated as the solid lines in 

Figure 5.4. The model simulations agree very 

well with observed decrease in U(VI) 

concentrations up to 110 hr. This is particularly

encouraging because, as described above, the 

observed changes in U(VI) concentration result 

from the opposing effects of dilution, which 

decreases the U(VI) concentration, and 

desorption, which increases the U(VI) 

concentration. After 110 hr, the predicted U(VI) 

concentrations do not agree as well with the 

observed data; the observed U(VI) concentration 

increased above the background concentration of 

3.9 μM to 5 μM, whereas the simulated 

concentrations did not increase above 

background. 

For test MT2, the decrease in alkalinity caused 

U(VI) adsorption to increase, which in turn 

caused the aqueous U(VI) concentration to 

decrease. The decrease in concentration is 

predicted very well in each of the four 

breakthrough curves shown in Figure 5.5. The 

model simulations also predicted the decrease in 

alkalinity very well, which occurred 

simultaneously with the appearance of Br tracer. 

After the Br and alkalinity concentrations 

returned to the initial values at approximately

200 hr, the U(VI) concentrations increased 

above the initial concentration. The increase can 

be attributed to desorption and retardation of the 

U(VI) that adsorbed when the alkalinity values 

were small. This trend is predicted in each of 

the breakthrough curves, although there are 

some discrepancies between the data and the 

model in each case. In observation well A3 

(Fig. 5.5a), the model over-predicted the peak in 

U(VI) concentration that appeared at 120 hr by

approximately 25 percent. In contrast, the 

predictions for U(VI) concentrations were closer 

to the observed data at wells M2 and N2, 

although concentrations were under-predicted 

after 250 hr. The alkalinity values observed in 

M2 and N2 after 200 hr were also slightly underpredicted. The small Br peaks between 200 and

500 hr in Figures 5.5b and 5.5c suggest that 

there was a minor, slow flowpath sampled by

these wells, and this may have also increased the 

alkalinity and U(VI) slightly at longer times. In 

Figure 5.5d, the simulated U(VI) concentration 

reproduced the decrease in observed values in 

the first 120 hr. At longer times, the simulated 

peak in U(VI) concentration that occurred at 260 

hr matches the shape of the observed U(VI) 

concentrations, but the observed peak is centered 

at 210 hr. The observed alkalinity after 210 hr 

was larger than the initial alkalinity, and the 

increased alkalinity is consistent with the 

observed earlier arrival of the U(VI), but the 

cause for these observations is unknown.

The model predictions were also good for test 

MT3 in which the alkalinity was increased. The 

model simulations demonstrate that the increase 

in alkalinity caused U(VI) to desorb, and 

therefore increase the aqueous U(VI) 

concentration. After the alkalinity peak passed 

through the aquifer, native groundwater that 

flows into the test site from upgradient 

encounters sediments with less adsorbed U(VI) 

than was present initially. Some of the dissolved 

U(VI) adsorbs to re-establish equilibrium, which 

causes the U(VI) concentration to temporally

decrease. All of the simulated U(VI) 

breakthrough curves match the shape of the 

observations. However, all of the simulations 

under-predict the observed U(VI) 

concentrations. 

5.3.4.4 Sensitivity Calculations 

First-order sensitivity analyses were calculated 

for the simulated U(VI) concentrations. The 

scaled sensitivities (Poeter and Hill, 1998) were 

defined by: 

i

i

i b

b

Y SS

∂

∂ = (5-3) 

where SSi is the scaled sensitivity, Y is the 

simulated quantity, and bi is the i'th parameter 

value. The scaling normalizes the sensitivity by 

the parameter values so that sensitivities with 

respect to widely varying parameter values can 

be compared. Equation 5-3 was approximated 

by finite differences, and the parameters were 

89
perturbed by 0.1 log units. The parameters 

included in this simple sensitivity analysis were: 

1) the formation constants for the aqueous 

species UO2(CO3)2

-2, UO2(CO3)3-4, Ca2UO2(CO3)2 and CaUO2(CO3)2

-2 and, 2) the 

equilibrium constants for the U(VI) surface 

reactions. 

The sum of the absolute values of the scaled 

sensitivity values is illustrated in Figure 5.7 for 

the simulated U(VI) breakthrough curve at well 

A1 in test MT1 and at wells A3 in tests MT2 

and MT3. The simulated U(VI) concentration is 

most sensitive to the formation constant for 

aqueous Ca2UO2(CO3)2 in each of the three 

cases. This is the predominant species in

background water at the test site and is also the 

predominant species in the injectate for tests 

MT1 and MT2, as illustrated in Figure 5.3. The 

simulated U(VI) concentrations are also 

sensitive to the equilibrium constants for the 

reactions resulting in formation of both 

>WOUO2

+

 and >SOUO2

+

. These species were 

the predominant adsorbed species in Naturita 

plume scale simulations (Curtis et al., 2006) and 

are also the predominant species in the migration 

test simulations. The simulated U(VI) 

concentration is approximately equally sensitive 

to the constants for each of the two surface 

species. Overall, Figure 5.7 suggests that the 

model was more sensitive in the simulations for 

test MT3, but this is because the U(VI) 

concentrations increased to relatively high 

values (~12 μM), but the sensitivity calculations 

were not normalized by U(VI) concentration. 

5.3.5 Complex Breakthrough Behavior 

Breakthrough curves at well 25P1 were 

collected for tests MT2 and MT3 and the results 

are shown in Figure 5.8. In both cases, the 

breakthrough curves for each of the solutes were

quite complex. In both tests, the breakthrough 

observed for Br had two distinct peaks that were 

observed at approximately 120 and 200-300 hr. 

These observations suggest that transport 

occurred along at least two unique flow paths, 

each of which was captured to some extent by

the sampled well. The velocities along these 

flowpaths differed by only a factor of 3 or less, 

which is relatively small compared to other 

heterogeneous aquifers (Zinn and Harvey, 

2003). 

Figure 5.7 Sensitivity of simulated U(VI) concentration, at well A1 in test MT1 and well A3 in tests 

MT2 and MT3, to equilibrium constants for the predominant aqueous and surface species. 

90
It was not possible to simulate this complex 

behavior with the quasi one-dimensional 

approach, which can only yield a single Br peak 

for a single injection (although the peak can be 

broad). However, it was possible to reproduce 

each of the two Br peaks observed in test MT2 

by calibrating one quasi one-dimensional model 

to the first peak, using Br concentrations 

observed during the first 190 hr of the 

breakthrough, and then calibrating a second 

quasi one-dimensional model to the remaining 

data. Using this approach, a good fit to the 

observed Br data in test MT2 was obtained 

(Figure 5.8a) using the parameters listed in 

Table 5.4. Similarly, a good fit to the Br data 

was obtained for the MT3 test results as shown 

in Figure 5.8b. In both tests, the reactive 

transport models gave an excellent prediction of 

U(VI) concentrations, except for the U(VI) data 

collected after 200 hr in test MT2. In this latter 

case, the predictions show the observed temporal 

trends, but the U(VI) concentrations predictions 

are smaller than the observed data by

approximately 1 μM. It is not clear why the 

U(VI) predictions were successful in test MT3 

but apparently biased in MT2. 

5.4 Conclusions 

U(VI) that has been present in the Naturita 

aquifer for several decades can be readily 

desorbed by variable chemical conditions. In 

experiments where the alkalinity was increased 

from 8.8 to 24 meq/L (factor of 2.8), the U(VI) 

concentration increased from 4.3 to 14.7 μM 

(factor of 3.4). The cause of this increase in 

U(VI) concentration is the formation of aqueous 

Ca-UO2-CO3 complexes in the groundwater. 

The results clearly demonstrate that in 

environments where U(VI) concentrations are 

controlled by adsorption, dissolved U(VI) 

concentrations can be impacted by increases in 

alkalinity. Interestingly, increases in U(VI) 

concentration were also observed in experiments 

where the alkalinity was decreased. In 

experiments where the alkalinity was decreased 

from 8.8 to 2 meq/L (factor of 4.4), the U(VI) 

concentration initially decreased from 4.8 to 1.8 

μM. Adsorption to the aquifer sediments causes 

this decrease in U(VI) concentration. However, 

when the alkalinity relaxed to its initial value, 

the additional adsorbed U(VI) desorbed, causing 

peak groundwater concentrations as high as 7 

μM. Thus, a detailed understanding of U(VI) 

surface and aqueous speciation is required to 

predict changes in U(VI) concentration in the 

Naturita aquifer, and likely in other aquifers 

contaminated with U(VI). 

The observed temporal changes in U(VI) 

concentration were reasonably well described by

a reactive transport model that simulated 

adsorption reactions using the SCM approach. 

Although this model was previously shown to 

simulate U(VI) adsorption in long term, near 

steady-state experiments (Kohler et al., 2004;

Curtis et al., 2004), the current results 

demonstrate the adequacy of the model for 

simulation of transient effects under the 

influence of a natural gradient. The model 

predicted both increases and decreases of U(VI) 

concentration reasonably well when the 

transport parameters were calibrated to observed 

Br transport. In contrast, a constant-Kd model 

would have predicted neither the observed 

increases nor decreases in U(VI) concentration

Table 5.4. Summary Of Nonreactive Transport Model Parameters 

for Bromide Breakthrough at Well NAT25P1 

Tracer Test Calibration 

Time(hr) 

Velocity 

(m/hr) 

Dispersivity 

(m) 

kLa

(hr-1) 

Pulse 

Length (hr) 

MT2 0-200 0.00658 0.0216 0.00135 29.5

MT2 200-500 0.00326 0.0510 0.00186 51.8

MT3 0-210 0.00576 0.00006 0.00198 34.0

MT3 210-500 0.00251 0.0389 0.00094 44.7

91
in tests MT2 and MT3, because the U(VI) 

concentration in the injectate was equal to that in 

the groundwater. This indicates that the 

uncertainty of predictions using the SCM 

approach were smaller than those that would 

have been obtained using a constant-Kd

approach to model U(VI) sorption.

Figure 5.8. Observed and simulated bromide, U(VI) and alkalinity concentrations in 

migration tests MT2 and MT3 at observation well P1. 

92
6 CONCLUSIONS 

Simulations of reactive transport processes in 

groundwater often require many parameters as 

model inputs. These parameters include 

hydrologic parameters that describe flow and 

transport as well as reaction parameters that 

describe the chemical reaction network. While 

hydrologic parameters are most often 

determined from field tests such as pump tests, 

slug tests, or tracer tests coupled with model 

calibration, there is less agreement on how 

geochemical reaction parameters should be 

determined. For geochemical reaction processes, 

such as adsorption reactions, parameter values 

could be based on a variety of sources including 

tabulated thermodynamic data, laboratory 

experiments using site-specific materials, or 

field-determined values. 

In this study, field-based techniques were tested 

for determining Kd values or for validating 

laboratory- or model-derived Kd values. The 

field site used for the study was the uranium mill 

tailings site at Naturita, Colorado (Davis and 

Curtis, 2003). The techniques included: 1) the 

use of downhole in-situ devices that held a 

sample of a single mineral or sediment that were 

deployed in the aquifer contaminated with 

uranium, 2) in-situ push-pull tracer tests 

conducted within the contaminated aquifer, and 

3) small-scale U(VI) migration tracer tests 

conducted within the aquifer. The experiments 

were conducted on scales that ranged from

centimeters for the downhole devices to several 

meters for the small-scale tracer tests.

6.1 Downhole In-Situ Devices 

The use of downhole in-situ devices appeared to 

be quite successful in a previous application 

with mesh bags and uncontaminated Naturita 

sediments (Curtis et al., 2004). The experiments 

completed in this study were conducted as 

further tests of this method of measuring Kd

values and as a measure of the applicability of 

surface complexation models to the field 

environment. The results suggest that either: a) 

the method or experimental approach needs 

further improvement, and/or b) current surface 

complexation models for kaolinite and hematite 

in the literature did not work well when applied 

to the aqueous chemical conditions in the 

Naturita aquifer. In particular, the ability of the 

kaolinite and hematite surface complexation 

models to predict U(VI) adsorption under 

conditions of high bicarbonate concentration is 

not well known. The quartz surface 

complexation model presented here was 

calibrated with data at high bicarbonate 

concentrations. However, the ability of this 

model to predict U(VI) adsorption could not be 

determined because of several factors, including 

the very low surface area of the quartz sample 

and the experimental error of the dialysis bag 

method related to entrained water collected with 

the sample. Improvements to the method and 

the deployment of larger quartz sample sizes in 

the well may solve some of these problems. 

In-situ Kd values for U(VI) adsorption on 

samples of clinoptilolite and a 40-Mile Wash 

sediment composite were also made, but these 

values could not be compared with modelpredicted values because of the lack of published 

models for these samples at present. 

6.2 Push-Pull Tracer Tests 

The experimental results illustrated that 

increases in groundwater alkalinity could 

quickly desorb U(VI) that had been present in 

the Naturita aquifer for several decades. Pushpull tracer tests that had contact times as little as 

0.5 hr resulted in U(VI) concentrations that 

increased from an initial concentration of 0.05 

μM in injected water to 2 μM in sampled 

groundwater. Higher concentrations, up to 17 

μM, were observed in some experiments in 

which the alkalinity was increased. 

It was concluded that push-pull test results were 

not useful in the Naturita aquifer for evaluating 

adsorption model parameters. This limitation 

results from the nearly reversible nature of the 

reactive transport simulations when applied to 

cases where sorption processes are probed by

manipulating groundwater alkalinity. In

93
addition, the velocity and/or dispersive 

processes in this aquifer were sufficiently large 

that geochemical effects were dampened by

dilution in most of the experiments. It is possible 

that push-pull tests would be more successful in 

environments where the groundwater velocity is 

small. In addition, push-pull tests may be useful 

for studying rates of sorption and desorption in

aquifers.

6.3 Small-Scale U(VI) Migration 

Tracer Tests 

U(VI) that has been present in the Naturita 

aquifer for several decades was readily desorbed 

by perturbing groundwater chemical conditions. 

In experiments where the alkalinity was 

increased from 8.8 to 24 meq/L (factor of 2.8), 

the dissolved U(VI) concentration increased 

from 4.3 to 14.7 μM (factor of 3.4). The cause 

of this increase in U(VI) concentration is the 

formation of aqueous Ca-UO2-CO3 complexes in 

the groundwater. The results clearly

demonstrated that in environments where U(VI) 

concentrations are controlled by adsorption, 

dissolved U(VI) concentrations can be rapidly

impacted by increases in alkalinity. 

Interestingly, increases in U(VI) concentration 

were also observed in experiments where the 

alkalinity was decreased. In experiments where 

the alkalinity was decreased from 8.8 to 2 meq/L 

(factor of 4.4), the U(VI) concentration initially

decreased from 4.8 to 1.8 μM. Adsorption to the 

aquifer sediments causes this decrease in U(VI) 

concentration. However, when the alkalinity

relaxed to its initial value, the additional 

adsorbed U(VI) desorbed, causing peak 

groundwater concentrations as high as 7 μM. 

Thus, a detailed understanding of U(VI) surface 

and aqueous speciation is required to predict 

changes in U(VI) concentration in the Naturita 

aquifer, and likely in other aquifers 

contaminated with U(VI). 

The experimental observations in the U(VI) 

migration tests were reasonably well described 

by a reactive transport model that simulated 

adsorption reactions using the SCM approach. 

Although this model was previously shown to 

simulate U(VI) adsorption in long term, near 

steady-state experiments (Kohler et al., 2004;

Curtis et al., 2004), the current results 

demonstrate the adequacy of the model for 

simulation of transient effects under the 

influence of a natural gradient. The model 

predicted both increases and decreases of U(VI) 

concentration reasonably well when the 

transport parameters were calibrated to observed 

Br transport. In contrast, a constant-Kd model 

would have predicted neither the observed 

increases nor decreases in U(VI) concentration 

in some of the tracer tests, because the U(VI) 

concentration in the injectate was equal to that in 

the groundwater. This indicates that the 

uncertainty of predictions using the SCM 

approach were much smaller than those that 

would have been obtained if a constant-Kd

approach had been used to model U(VI) 

adsorption. 

94
REFERENCES 

Allison, J. D., Brown, D. S., and Novo-Gradac, K. J., “MINTEQA2/PRODEFA2, A Geochemical 

Assessment Model for Environmental Systems,” Version 3.0 User's ManualEPA/600/3-91/021, 

1991. 

Anderson R. T. et al., “Stimulating the In-Situ Activity of Geobacter species to remove uranium

from the groundwater of a uranium-contaminated aquifer,” Appl. Environ. Microbiol., Vol. 69, 

5884-5891, 2003. 

Arai, Y. et al., “Uranyl Adsorption and Surface speciation at the Imogolite-water Interface: SelfConsistent Spectroscopic and Surface Complexation Models,” Geochimica et Cosmochimica 

Acta, Vol. 70, 2492-2509, 2006. 

Bargar, J. R., Reitmeyer, R., and Davis, J. A., “Spectroscopic Confirmation of 

Uranium(VI)-Carbonato Adsorption Complexes on Hematite,” Environmental Science and 

Technology, Vol. 33, No. 14, 2481-2484, 1999. 

Barger, J.R. et al., “Characterization of U(VI)-Carbonato Cernary Complexes on Hematite: 

EXAFS and Electrophoretic Mobility Measurements,” Geochimica et Cosmochimica Acta, Vol. 

64, No. 16, 2737-2749, 2000. 

Barnett, M.O. et al., “U(VI) Adsorption to Heterogeneous Subsurface Media: Application of 

Surface Complexation Model”, Environ. Sci. Technol, Vol. 36, 937–942, 2002. 

Barnett, M.O. et al., “Adsorption and Transport of Uranium(VI) in Subsurface Media,” Soil Sci. 

Soc. Am. J, Vol. 64, 908–917, 2000. 

Bernhard, G. et al., “Speciation of Uranium in Seepage Waters of a Mine Tailing Pile Studied by

Time Resolved Laser-induced Fluorescence Spectroscopy (TRLFS),” Radiochim. Acta, Vol. 74,

87–91, 1996.

Bernhard, G. et al., “Uranyl(VI) Carbonate Complex Formation: Validation of the 

Ca2UO2(CO3)3(aq.) Species,” Radiochim. Acta, Vol. 89, 511–518, 2001. 

Bostick, B.C. et al., “Uranyl Surface Complexes Formed on Subsurface Media from DOE 

Facilities,” Soil Science Society of America Journal, Vol. 66, No. 1, 99-108, 2002. 

Brooks, S.C. et al., “Inhibition of Bacterial U(VI) Reduction by Calcium. Environ,” Sci. Technol,

Vol. 37, 1850–1858, 2003.

Caccavo Jr F. et al., “Geobacter Sulfurreducens Sp. Nov., a Hydrogen and Acetate-Oxidizing 

Dissimilatory Metal Reducing Microorganism,” Appl. Environ. Microbiol., Vol. 60, 3752-3759, 

1994. 

Crowley, K.D., and Ahearne, J.F., “Managing the Environmental Legacy of U.S. Nuclear 

Weapons Production,” Am. Sci, Vol. 90, 514–523, 2002. 

95
Curtis, G.P., Fox, P., Kohler, M., and Davis, J.A., “Comparison of In Situ Uranium KD Values 

with a Laboratory Determined Surface Complexation Model,” Appl. Geochem, Vol. 19, 1643–

1653, 2004. 

Curtis, G.P., “Documentation and Applications of the Reactive Geochemical Transport Model 

RATEQ,” Report NUREG CR-6871, U. S. Nuclear Regulatory Commission, Rockville, MD, 98, 

2005. 

Curtis, G. P., Davis, J.A., and Naftz, D.L., “Simulation of Reactive Transport of Uranium(VI) in 

Groundwater with Variable Chemical Conditions,” Water Resour. Res., Vol. 42, W04404, 

doi:10.1029/2005WR003979, 2006. 

Davis, J.A., and Kent, D.B., “Surface Complexation Modeling in Aqueous Geochemistry: 

Mineral-water Interface Geochemistry,” Rev. Mineral, Vol. 23, 177–260, 1990. 

Davis, J. A. et al., “Application of the Surface Complexation Concept to Complex Mineral 

Assemblages,” Environ. Sci. Technol., Vol. 32, 2820-2828, 1998. 

Davis, J.A. and Curtis, G.P., “Application of Surface Complexation Modeling to Describe 

Uranium(VI) Adsorption and Retardation at the Uranium Mill Tailings Site at Naturita, 

Colorado,” Report NUREG CR-6820, U. S. Nuclear Regulatory Commission, Rockville, MD, 

223, 2003 Available at: 

http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6820/cr6820.pdf, 

Davis, J.A. et al., “Assessing Conceptual Models for Subsurface Reactive Transport of Inorganic 

Contaminants,” EOS, Vol. 85, 449-455, 2004a. 

Davis, J.A. et al., “Approaches to Surface Complexation Modeling of Uranium(VI) Adsorption 

on Aquifer Sediments,” Geochim. Cosmochim. Acta, Vol. 68, 3621-3641, 2004b. 

Davis, J.A. et al., “Processes Affecting Transport of Uranium in a Suboxic Aquifer,” Physics and 

Chemistry of the Earth, Parts A/B/C, Vol. 31(10-14), 548-555, 2006. 

Dong W. et al., "Influence of Calcite and Dissolved Calcium on Uranium(VI) Sorption to a 

Hanford Subsurface Sediment,” Environmental Science and Technology, Vol. 39(20), 7949-

7955, 2005. 

Drever, J.I. and McKee, C.R., “The Push-Pull Test A Method of Evaluating Formation 

Adsorption Parameters for Predicting the Environmental Effects on In-Situ Coal Gasification and 

Uranium Recovery,” In Situ, Vol. 4(3), 181-206, 1980. 

Duff, M.C., and Amrhein, C., “Uranium(VI) Adsorption on Goethite and Soil in Carbonate 

Solutions,” Soil Sci. Soc. Am. J, Vol. 60, 1393– 140, 1996. 

Dzombak, D.A. and Morel, F.M.M., “Surface Complexation Modeling: Hydrous Ferric Oxide,”

John Wiley & Sons, New York, NY, 1990. 

Fox, P.M., Davis, J.A., and Zachara, J.M, “The Effect of Calcium on Aqueous Uranium (VI)

Speciation and Adsorption to Ferrihydrite and Quartz,” Geochimica et Cosmochimica Acta, Vol. 

70, 1379-1387, 2006. 

96
Godsy, E.M., Warren, E., and Paganelli, V.V., “The Role of Microbial Reductive Dechlorination 

of TCE at a Phytoremediation Site,” International Journal of Phytoremediation, Vol., 5, 73-88, 

2003. 

Grenthe, I. et al., Chemical Thermodynamics of Uranium, Amsterdam, North Holland, 715, 1992. 

Guillaumont, R. et al., “Update on the Chemical Thermodynamics of Uranium, Neptunium, 

Plutonium, Americium, and Technetium,” Elsevier, Amsterdam, 2003. 

Haggerty, R. and Gorelick, S.M, “Multiple-Rate Mass Transfer for Modeling Diffusion and 

Surface Reactions in Media with Pore-Scale Heterogeneity,” Water Resources Research, Vol. 

31(10), 2382-2400, 1995. 

Haggerty, R., Schroth, M.H. and Istok, J.D., “Simplified Method of "Push-Pull Test Data 

Analysis for Determining In Situ Reaction Rate Coefficients,” Ground Water, Vol. 36, No. 2, 

March-April, 1998. 

Hall, S.H., Luttrell, S.P., and Cronin, W.E., “A Method for Estimating Effective Porosity and

Ground-Water Velocity,” Ground Water, Vol. 29, No. 2, March-April, 1991. 

Herbelin, A. L., and Westall, J. C., “FITEQL: A Computer Program for the Determination of 

Chemical Equilibrium Constants from Experimental Data,” Chemistry Department Oregon State 

University, Corvallis, Oregon, Version 4.0, report 99-01, 1999. 

Hsi, C.D. and Langmuir, D., “Adsorption of Uranyl onto Ferric Oxyhydroxides; Application of

the Surface Complexation Site-binding Model,” Geochim. Cosmochim. Acta, Vol. 49, No. 9, 

1931-1941, 1985. 

Istok, J.D. et al., “Laboratory and Field Investigation of Surfactant Sorption Using Single-Well, 

"Push-Pull" Tests,” Ground Water, Vol. 37, No. 4, July-August 1999. 

Istok, J.D. et al., “Single Well, ‘Push-Pull' Test for In Situ Determination of Microbial 

Activities,” Ground Water, Vol. 35, No. 4, July-August 1997. 

Jeon, B-H. et al., “Chemical Reduction of U(VI) by Fe(II) at the Solid/Water Interface Using 

Natural and Synthetic Fe(III) Oxides,” Environ. Sci. Tech., Vol. 39, 5642-5649, 2005. 

Kent, D.B. et al., “Modeling the Influence of Variable pH on the Transport of Zinc in a 

Contaminated Aquifer Using Semi-Empirical Surface Complexation Models,” Water Resources 

Research, Vol. 36, 3411-3425, 2000. 

Kohler, M. et al., “Experimental Investigation and Modeling of Uranium(VI) Transport Under 

Variable Chemical Conditions,” Water Resources Research, Vol. 32, No. 12, 3539-3551, 1996. 

Kohler, M. et al., “Methods for Estimating Adsorbed Uranium(VI) and Distribution Coefficients 

in Contaminated Sediments,” Environmental Science and Technology, Vol. 38, 240-247, 2004. 

Langmuir, D., Aqueous Environmental Chemistry, Prentice-Hall, Upper Saddle River, NJ, 1997 

97
Leap, D. I. and Kaplan, P. G., “A Single-Well Tracing Method for Estimating Regional 

Advective Velocity in a Confined Aquifer: Theory and Preliminary Laboratory Verification,” 

Water Resources Research, Vol. 24, No. 7, July 1988.

Lee, R.W. et al., “Phreatophyte Influence on Reductive Dechlorination in a Shallow Aquifer 

Contaminated with Trichloroethene (TCE),” International Journal of Phytoremediation, Vol. 2,

193-211, 2000. 

Liger, E., Charlet, L., van Cappellan, P., “Surface Catalysis of Uranium(VI) Reduction by

Iron(II),” Geochim. Cosmochim. Acta, Vol. 63, 2939-2955, 1999. 

Liu C et al., "Influence of Sediment Bioreduction and Reoxidation on Uranium Sorption." 

Environmental Science and Technology, Vol. 39(11), 4125-4133, 2005. 

Lovley D. R. et al., “Microbial Reduction of Uranium,” Nature, Vol. 350, 413-416, 1991. 

Morrison, S.J. and Cahn, L.S., “Mineralogical Residence of Alpha-emitting Contamination and 

Implications for Mobilization from Uranium Mill Tailings,” J. Contam. Hydrol., Vol. 8, 1-21, 

1991. 

O'Loughlin, E.J. et al., “Reduction of Uranium(VI) by Mixed Iron(II)/Iron(III) Hydroxide (Green 

Rust): Formation of UO2 Nanoparticles,” Environ. Sci. Tech., Vol. 37, 721-727, 2003. 

Pabalan, R.T., “Thermodynamics of Ion Exchange Between Clinoptilolite and Aqueous Solutions 

of Na+K and Na/Ca,” Geochim. Cosmochim. Acta, Vol. 58, 4573-4590, 1994. 

Pabalan, R.T. et al., “Uranium(VI) Sorption onto Selected Mineral Surfaces: Key Geochemical 

Parameters,” Adsorption of Metals by Geomedia, Academic Press, 99-130, 1998. 

Poeter, E. P. and Hill, M.C., “UCODE, a Computer Code for Universal Inverse Modeling,” 

U.S.Geological Survey, Water-Resources Investigations, Rept. 98-4080, 1998. 

Prikryl, J.D. et al., “Uranium(VI) Sorption Behavior on Silicate Mineral Mixtures,” J. Contam. 

Hydrol., Vol. 47, 241-253, 2001. 

Qafoku N. et al., "Kinetic Desorption and Sorption of U(VI) During Reactive Transport in a 

Contaminated Hanford Sediment,” Environmental Science and Technology, Vol. 39(9), 3157-

3165, 2005. 

Reinhard, M. et al., “In Situ BTEX Biotransformation under Enhanced Nitrate- and SulfateReducing Conditions,” Environ. Sci. Technol., Vol. 31, 28-36, 1997. 

Schroth, M.H., Istok, J.D. and Haggerty, R., “In Situ Evaluation of Solute Retardation Using 

Single-Well Push-Pull Tests,” Advances in Water Resources, Vol. 24, 105-117, 2001. 

Schroth, M.H. et al., “Spatial Variability in In-Situ Aerobic Respiration and Denitrification Rates 

in a Petroleum-Contaminated Aquifer,” Ground Water, Vol. 36, No. 6, November-December 

1998. 

98
Senko, J.M. et al., “In-Situ Evidence for Uranium Immobilization and Remobilization,” Environ. 

Sci. Technol., Vol. 35, 1491-1496, 2002

Smith, R. M., and Martell, A. E., Critical Stability Constants, Volume 4, Inorganic Complexes, 

Plenum Press, New York, 1976. 

Stollenwerk, K. G., “Molybdate Transport in a Chemically Complex Aquifer; Field 

Measurements Compared with Solute-transport Model Predictions,” Water Resour. Res., 

Vol. 34, 2727-2740, 1998. 

Turner, G.D. et al., “Surface Charge Properties and UO22+ Adsorption of a Subsurface 

Smectite,” Geochim. Cosmochim. Acta, Vol. 60, 3399–3414, 1996.

USEPA, “Understanding Variation in Partition Coefficient, Kd, Values,” Vol. 1, EPA 402-R-99-

0044A, Washington, DC, 1999. 

USDOE, “Programmatic Environmental Impact Statement for the Uranium Mill Tailings 

Remedial Action Ground Water Project,” U.S. Department of Energy, Grand Junction Office, 

Vol. I, No. DOE/EIS-0198, 314, 1996. 

Valocchi, A.J., “Effect of Radial Flow on Deviations from Local Equilibrium During Sorbing 

Solute Transport Through Homogeneous soils,” Water Resources Research, Vol. 22, 1693-1701, 

1986. 

Waite, T.D. et al., “Uranium(VI) Adsorption to Ferrihydrite: Application of a Surface 

Complexation Model,” Geochimica et Cosmochimica Acta, Vol. 58, No. 24, 5465-5478, 1994. 

Wang Z. et al., "Cryogenic Laser Induced U(VI) Fluorescence Studies of a U(VI) Substituted 

Natural Calcite: Implications to U(VI) Speciation in Contaminated Hanford Sediments,” 

Environmental Science and Technology, Vol. 39, 2651-2659, 2005a. 

Wang Z. et al., "Fluorescence Spectroscopy of U(VI)-Silicates and U(VI)-Contaminated Hanford 

Sediment,” Geochimica et Cosmochimica Acta, Vol. 69(6), 1391-1403, 2005b. 

Wersin, P. et al., “Interaction Between Aqueous Uuranium(VI) and Sulfide Minerals: 

Spectroscopic Evidence for Sorption and Reduction,” Geochim. Cosmochim. Acta, Vol. 58, 2829-

2843, 1994. 

Zheng, Z., Tokunaga, T.K., and Wan, J., “Influence of Calcium Carbonate on U(VI) Sorption to

Soils,” Environ. Sci. Technol, Vol. 37, 5603–5608, 2003. 

Zinn, B., and Harvey, C. F., "When Good Statistical Models Of Aquifer Heterogeneity Go Bad: 

A Comparison of Flow, Dispersion and Mass Transfer in Multigaussian and Connected 

Conductivity Fields,” Water Resources Research, Vol. 39(3), 1051, 2003. 

99