DRC-2024-007804

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Revised Final Groundwater Geochemical Modeling at
the White Mesa Uranium Mill Report
Contract No. 68HERC20D0029
Task Order No. 68HERC22F0178

Prepared for:
U.S. Environmental Protection Agency
Region 8 and
Office of Research and Development
Center for Environmental Solutions and Emergency Response
Land Remediation & Technology Division

Prepared by:
1701 Pearl Street
Suite 200
Boulder, CO 80302
Under subcontract from:
505 King Avenue
Columbus, OH 43201

November 22, 2024
Disclaimer: This document is a work prepared for the United States Government by Integral Consulting
Inc. under subcontract from Battelle. In no event shall the United States Government, Battelle, or Integral
have any responsibility or liability for any consequences of any use, misuse, inability to use, or reliance on
any product, information, designs, or other data contained herein, nor does either warrant or otherwise
represent in any way the utility, safety, accuracy, adequacy, efficacy, or applicability of the contents hereof.

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CONTENTS
LIST OF FIGURES .................................................................................................................................. iii
LIST OF TABLES ..................................................................................................................................... iv
ACRONYMS AND ABBREVIATIONS................................................................................................ v
1 Background ....................................................................................................................................... 1-1
2 Report Review .................................................................................................................................. 2-1
2.1 HYDRO GEO CHEM (2012) .............................................................................................. 2-1
2.2 INTERA (2012) ..................................................................................................................... 2-3
3 Geochemical Modeling .................................................................................................................. 3-1
3.1 CONCEPTUAL MODEL .................................................................................................... 3-1
3.2 QUALITY ASSURANCE .................................................................................................... 3-1
3.3 MODELING PLATFORM .................................................................................................. 3-2
3.4 MODEL INPUTS ................................................................................................................. 3-3
3.4.1 Wells Modeled ........................................................................................................ 3-3
3.4.2 Water Chemistry ..................................................................................................... 3-3
3.4.3 Equilibrium Phases ................................................................................................ 3-4
3.5 BASELINE RESULTS .......................................................................................................... 3-5
3.6 POST-BASELINE RESULTS ............................................................................................... 3-7
3.7 MIXING RESULTS .............................................................................................................. 3-8
4 Conclusions ...................................................................................................................................... 4-1
5 REFERENCES ................................................................................................................................... 5-1
Appendix A. Water Quality Time-Series Plots and Summary Statistics
Appendix B. Baseline Model Runs
Appendix C. Post-Baseline Model Runs
Appendix D. Mixing Model Runs
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LIST OF FIGURES
Figure 1. Site and key well locations
Figure 2. Observed changes in pH at the Mill (Intera, 2012)
Figure 3. Conceptual model
Figure 4. Model data flow schematic
Figure 5. Carbon dioxide saturation in modeled wells, baseline and post-baseline
conditions
Figure 6. Baseline model run dashboard plot, MW-11, pyrite 0.8%, calcite 0%
Figure 7. Baseline model run dashboard plot, MW-11, pyrite 0.8%, calcite 1.5%
Figure 8. Post-baseline model run dashboard plot, MW-24, pyrite 0.8%, calcite 0%
Figure 9. Post-baseline model run dashboard plot, MW-24, pyrite 0.8%, calcite 1.5%
Figure 10. Post-baseline model run dashboard plot, MW-22, pyrite 0.1%, calcite 0%
Figure 11. Post-baseline model run dashboard plot, MW-22, pyrite 0.8%, calcite 1.5%
Figure 12. Mixing model run dashboard plot, MW-24, pyrite 0.45%, calcite 0%, leachate
fraction 0.5%
Figure 13. Mixing model run dashboard plot, MW-24, pyrite 0.45%, calcite 0%, leachate
fraction 1 %
Figure 14. Mixing model run dashboard plot, MW-24, pyrite 0.45%, calcite 1.5%, leachate
fraction 1%

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LIST OF TABLES
Table 1. Summary of selected monitoring wells for geochemical modeling
Table 2. Baseline and post-baseline water quality at modeled wells
Table 3. Representative containment cell 1 leachate water quality
Table 4. Summary of available calcite content data
Table 5. Summary of baseline model run conditions
Table 6. Summary of post-baseline model run conditions
Table 7. Summary of leachate mixing model run conditions
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ACRONYMS AND ABBREVIATIONS
CaCO3 calcite
CO2 carbon dioxide
EPA United States Environmental Protection Agency
GWCL groundwater compliance levels
H2SO4 sulfuric acid
LLNL Lawrence Livermore National Laboratory
NH3 ammonia
NO3 nitrate
O2 oxygen gas
ORP oxidation-reduction potential
QAPP quality assurance project plan
SOW statement of work
UDEQ Utah Department of Environmental Quality
UMUT Ute Mountain Ute Tribe
USGS United States Geological Survey
XRD X-ray diffraction

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1 BACKGROUND
The White Mesa Uranium Mill (Mill) is located in southeast Utah, just south of the town of
Blanding, Utah (Figure 1). The Mill was constructed in 1979 and was permitted and began
operation in 1980 (United States Geological Survey [USGS], 2011; Utah Department of
Environmental Quality [UDEQ], 2023). The ore beneficiation process at the Mill is used for the
production of uranium and vanadium concentrates (Energy Fuels, 2023; Hurst and Solomon,
2008). This process utilizes sulfuric acid (H2SO4) and ammonia, among other chemicals, as
processing aids (USGS, 2011; Intera, 2009). Tailings and solutions from ore processing are, or
have been, disposed of in five containment cells at the site (Figure 1). Samples of solutions from
one of these cells (specifically, the cell 2 slimes drain) were reported as having a pH of 3, high
metals concentrations (e.g., arsenic up to 26.9 mg/L or iron up to 2,900 mg/L), and elevated
concentrations of sulfate (up to 74,000 mg/L), nitrate (up to 100 mg/L), and ammonia (up to
4,000 mg/L) (MWH, 2010).
Trends of decreasing pH and increasing concentrations of metals have been observed in
groundwater monitoring wells in the Dakota and Burro Canyon formations at the Mill (Intera,
2012). These changing conditions have been observed in wells hydraulically up-gradient of the
Ute Mountain Ute Tribe’s (UMUT) White Mesa community. Members of the UMUT are
concerned that contaminant releases from the Mill have the potential to impact local springs
and possibly their public water supply. Springs fed by shallow groundwater from the Dakota
and Burro Canyon formations provide water for livestock and wildlife. The public water
supply for the White Mesa community is sourced from the deeper Navajo Sandstone aquifer.
The UMUT community is concerned that the observed changes in groundwater quality may be
associated with a Mill-related contaminant plume. However, the Mill attributes the changes in
groundwater quality to oxidation of naturally-occurring pyrite (Hydro Geo Chem, 2012).
This report presents the results of geochemical modeling performed to provide insight into the
observed changes in groundwater quality at the Mill and the geochemical processes that affect
these changes. A technical review and analysis of past geochemical modeling at the Mill is
presented in Section 2 below. The data analysis, input preparation, and development of the
geochemical model are described in Section 3 below. That section also presents, and discusses,
the results of the modeling. The geochemical modeling and associated analyses were
performed following the project quality assurance project plan (QAPP, Battelle 2023).
Three separate tasks, and the results of each, are described in greater detail in the following
sections. The tasks are briefly summarized below:
• Task 1 Report review: This task was a technical review of reports prepared
by Hydro Geo Chem (2012) and Intera (2012). Those reports include data
analysis and geochemical modeling focused on evaluating the observed
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changes in groundwater quality, with a focus on changes in pH. This
review identified key assumptions and limitations.
• Task 2 Pyrite oxidation modeling: The purpose of this task was to simulate
groundwater chemistry and associated dissolution, precipitation, and
oxidation reactions that are likely to occur in the subsurface. Groundwater
conditions at the site were divided into two temporal periods. The baseline
period (1980–2005) is associated with anoxic groundwater conditions. The
post-baseline (2005–present) is associated with the presence of electron
acceptors (i.e., oxygen and/or nitrate) that have the ability to facilitate the
oxidation of pyrite that naturally occurs in the aquifer matrix.
• Task 3 Mixing modeling: The purpose of this task was to geochemically
model the mixing of containment cell-associated water with different types
and amounts of native groundwater and aquifer materials present at the
Mill.
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2 REPORT REVIEW
2.1 HYDRO GEO CHEM (2012)
Hydro Geo Chem (2012) concludes that the changes in groundwater quality at the Mill are
driven by the oxidation of pyrite in the subsurface. This oxidation is explained as being driven
by the introduction of oxygen to the subsurface as a byproduct of the pumping of groundwater
monitoring wells. A field sampling program and a geochemical modeling effort were
completed and the resulting data were interpreted by Hydro Geo Chem (2012) as supporting
this mechanism.
The field sampling program was focused on the mineralogical analysis of drill cuttings and core
samples. This review found the Hydro Geo Chem (2012) report and sampling effort to be
biased regarding the presence of pyrite, as demonstrated by three observations.
First, the sample selection process was focused on analyzing only those samples that were
found to, or believed to, contain pyrite—”samples were from depth intervals noted to have
pyrite in the lithologic logs or from intervals likely to have pyrite” (p. 18). The consequence of
this sampling methodology is that the samples are not representative of the overall
characteristics of the aquifer formation; rather they represent pyrite-rich portions of the aquifer
formation. Given the sampling bias, these data do not represent the pyrite occurrence across
the geologic formation and should be used with caution. This sampling program likely
overestimates the pyrite content of the subsurface.
Second, the report also attempts to infer the presence of pyrite in samples where none is
detected.
“Although pyrite was not directly detected by XRD [X-ray Diffraction] in
samples from MW-23, MW-25, or MW-29, the detected iron and sulfur in these
samples is consistent with the presence of pyrite. While at least a portion of the
detected sulfur may result from the gypsum or anhydrite detected in some of
these samples, iron not in the form of pyrite would be expected to exist primarily
in the form of iron oxides or perhaps iron carbonates. The absence of detected
iron oxides or carbonates in samples from these borings suggests iron in the form
of pyrite.” (pg. 20)
This analysis concludes that one compound (pyrite) must be present even though it is not
detected. Yet, Hydro Geo Chem reverses this logic by concluding that two other compounds
(gypsum and iron oxides) must be absent since they are not detected.
Third, the absence of pyrite is explained by such mechanisms as “oxidation of pyrite within the
samples during storage will reduce detected pyrite concentrations, and possibly lead to non-
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detections in samples that originally contained small amounts of pyrite” (p 15). If oxidation of
samples during storage was of concern, minimizing this sample alteration would have been a
suggested portion of the sampling and analysis plan.
The geochemical modeling performed by Hydro Geo Chem had two conclusions. The first
conclusion was that, in the absence of oxygen, pyrite was stable and did not react. The second
conclusion was that, in the presence of oxygen, pyrite was oxidized and resulted in decreasing
pH and increasing sulfate concentrations. These conclusions are consistent with an
understanding of pyrite oxidation mechanisms. However, there were several limitations of the
modeling inputs and outputs identified during review of these results.
First, it was found that the model input files for all scenarios fixed the pH. As such, the pH
input to each model run was identical to the final pH. The report notes that the final pH of the
oxygen-containing model runs was lower than the final pH of the oxygen-free model runs. As
the pH were fixed these lower pHs are the result of model inputs and not a result of the
oxidation of pyrite. Hydro Geo Chem noted that higher sulfate was observed in oxygen-
containing model runs. However, the initial model input sulfate for the runs with oxygen was
higher than the input sulfate for the runs without oxygen. As with pH, the differences noted for
sulfate between model runs are the result of model inputs and not geochemical processes.
Second, none of the model input files included the presence of acid-neutralizing minerals such
as calcite or dolomite. These minerals have the ability to buffer acidity generated by pyrite
oxidation. The sampling presented in the Hydro Geo Chem report (2012) found calcite at
concentrations from 0 to 14% and dolomite concentrations at 0 to 4.1%. These concentrations
are consistent with more general geological descriptions of the Burro Canyon that found up to
6% calcite cement (Craig, 1982). Further, this is consistent with other mineralogical
characterization at the Mill that found calcite present at concentrations from 0 to 18.2% (MWH,
2010). The Hydro Geo Chem report states that the presence of calcite is “accounted for in the
simulations (pg. 31)”, yet review of the model input files did not indicate the inclusion of calcite.
It should also be noted that the modeling assumed that all of the pyrite was available for
immediate reaction. This is generally a reasonable assumption, however, it should be noted
that real-world reactions are often limited by the rate of reaction and the physical availability of
pyrite for reaction. For example, in some cases pyrite may be coated by reaction-limiting
mineral films or located entirely within a second mineral as an inclusion.
Third, the geochemical modeling by Hydro Geo Chem assumes that there is no groundwater
flow and all generated acidity and sulfate would be retained in the same location. In fact, flow
of groundwater in the subsurface would dilute and disperse any generated acidity and sulfate.
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2.2 INTERA (2012)
The Intera report provides a statistical and geochemical analysis of the trends of pH in wells at
the Mill site. That report concludes that, in all cases, decreases in pH at the site are explained as
the “the result of natural influences and/or the improperly set GWCLs [groundwater
compliance limits]”. That report utilizes Hydro Geo Chem (2012) as a buttress for many of its
conclusions.
Intera (2012) provides a map of pH trends at the Mill that demonstrate that the majority of wells
with stable or increasing pH are located upgradient of the Mill, and the majority of wells with
decreasing pH are located within or downgradient of the Mill (Figure 2). This observation
suggests that conditions within and downgradient of the Mill are different than those observed
upgradient.
A primary support of Intera’s conclusions is an analysis of nitrate in groundwater. For
example, at MW-27 Intera calculates that it would take approximately 11% tailings solution
mixing with the groundwater to drive the observed change in nitrate concentrations. This is
based upon a tailings nitrate concentration of 290 mg/L. However, nowhere in this analysis are
the elevated concentrations of ammonia in tailings leachate discussed. Based upon EPA-
provided data 1, the Cell 1 average ammonia and nitrate concentrations are 7,490 mg/L and 166
mg/L, respectively, which indicates approximately 45 times more ammonia than nitrate. The
potential for nitrification of ammonia (conversion of ammonia to nitrite and then to nitrate) is
ignored in the analysis—and this conversion would result in much smaller mixing ratios.
Intera’s analysis is primarily based upon the analysis of chloride and, to a lesser extent, nitrate
and fluoride. However, in many wells there is divergence in the trends for individual
constituents. Consideration of the complexity of the subsurface, and the multiple potential
mechanisms affecting fate and transport, indicates the need for an analysis of contaminant fate
and transport utilizing a wider range of constituents to better elucidate patterns and trends.

1 The data provided by EPA is a compilation of publicly available data from the Mill. Data acquired from previous
sampling events have been evaluated as part of those specific projects and their associated data quality objectives.
These data have been compiled and provided by EPA. Work performed for this project did not include the
evaluation of compiled data in a context of data usability or quality review.
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3 GEOCHEMICAL MODELING
This section of the report provides a summary of the two geochemical modeling tasks
completed for this project. It begins with a discussion of model setup and inputs and follows
with a presentation and discussion of key results.
3.1 CONCEPTUAL MODEL
A geochemical conceptual model is used to help develop a site understanding and identify key
factors that control and affect the reactions and processes occurring at a site. These identified
reactions and processes can then be included in modeling. Following the review of site
documents, two key factors were identified. The first factor was the delineation of the model
period into two phases—one phase, the ‘baseline’ phase where oxygen is not present and a
second phase, the ‘post-baseline’ phase where oxygen is present. The second factor is that the
groundwater at the Mill is flowing and not static. Past investigations at the Mill have
demonstrated the presence of groundwater plumes of chloroform and nitrate that extend away
from the Mill operations area (Hydro Geo Chem, 2014). These plumes are direct evidence of
transport. Hydro Geo Chem (2014) also estimates that flow velocities at the facility range from
0.26 to 76 ft/year, which corroborate the observed transport.
The geochemical conceptual model described in Figure 3 identifies transport as an important
aspect of modeling the system. In this model, the system is divided into five cells (Figure 3).
Upgradient water flows into model Cell 1, where water is equilibrated with the atmosphere in
the vicinity of a borehole. This water is then subsequently transported downgradient through
Cells 2 through 5. Once transported downgradient and past Cell 1, this water is no longer in
equilibrium with the atmosphere; however, mineral phases (calcite and pyrite) are available for
geochemical reactions. Conceptually, the key factor in this geochemical conceptual model is
recognizing that beyond the immediate vicinity of a borehole, transport of oxygen into the
subsurface is done through advective (flow-based) transport.
3.2 QUALITY ASSURANCE
The data analysis and modeling were performed following the project quality assurance project
plan (QAPP, Battelle 2023). The management, handling, and reporting of data were subject to
Integral’s Quality Management Program (Integral 2022). Per this guidance, model inputs and
outputs were subject to a technical review.
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3.3 MODELING PLATFORM
PHREEQC software version 3.0 was used for all geochemical modeling runs (USGS, 2013)2.
After project discussions with the EPA, the Lawrence Livermore National Laboratory (LLNL)
thermodynamic database (one of the databases provided with PHREEQC) was selected as the
database to be used for all modeling runs. That database provides a well-vetted set of
thermodynamic data governing the formation and reaction of a wide-range of elements and
minerals.
Utilization of the PHREEQC model requires the selection of how to implement mixing,
reactions, input water chemistry, and input equilibrium phases. Consistent with the
geochemical conceptual model, PHREEQC allows transport of solutions. For this process the
‘advection’ functionality was used for all runs. The ‘advection’ functionality simulates one-
dimensional flow and allows for the implementation of all chemical processes modeled in
PHREEQC. For the modeling described here, the advection functionality was defined to have
five modeled cells and 100 shifts. During each shift, the following transport and reactions
occur:
• In Cell 1 upgradient water enters and reacts and equilibrates with the equilibrium
phases present in that cell,
• In Cell 2, water transported from Cell 1 enters and reacts and equilibrates with the
equilibrium phases present in that cell,
• The processes in Cells 3 through 5 are analogous to those in Cell 2,
• Equilibrium phases, that is mineral and gas phases, are not transported and remain for
reaction and equilibrium at the cell for which they are defined.
Per the PHREEQC utilized methodology, this is the equivalent of transporting 20 pore volumes
through the model. The ‘advection’ function does not account for dispersion or diffusion.
Increasing grid density and larger numbers of shifts may be appropriate for detailed simulation
of in-situ conditions. However, the relatively simple set-up used is sufficient for the evaluation
of the key factors identified in the conceptual model—specifically the impact of pyrite, calcite,
and oxygen transport in the vicinity of the wells on geochemical conditions.

2 PHREEQC version 3.7.3.15968 was the specific model version. The most-up-to-date version was downloaded aft the
USGS website: https://www.usgs.gov/software/phreeqc-version-3
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3.4 MODEL INPUTS
This section provides a description of the development of model inputs. The overall flow of
data through the model and the primary questions at each step are presented in Figure 4.
3.4.1 Wells Modeled
Consistent with the statement of work (SOW) a total of five monitoring wells were included for
baseline and post-baseline model runs. These wells are (in upgradient to downgradient order):
MW-27, -24, -11, -3A, -22 (Figure 1, Table 1). For leachate mixing runs, consistent with the SOW,
three wells (MW-27, MW-24, and MW-11) were included in the model. Those wells are located
at or immediately downgradient of the Mill containment cells and would be the most likely to
directly receive leachate.
3.4.2 Water Chemistry
Water chemistry datasets were provided by EPA3. In a PHREEQC model, input water quality
represents the initial conditions of the water phase in the model. This modeling effort focused
on modeling primary water quality parameters and did not attempt to address a wider range of
metals. These data were used to develop two characteristic water quality profiles for each
modeled well—a baseline and post-baseline condition..
The constituents included in the model were: calcium (Ca), magnesium (Mg), potassium (K),
sodium (Na), iron (Fe), chloride (Cl), fluoride (F), alkalinity, ammonia (NH3), nitrate (NO3), pH,
and oxidation/reduction potential (ORP). Representative values were calculated as arithmetic
means, with the exception of pH, which was calculated as the geometric mean of proton
concentration ([H+]). The use of means as representative values can introduce uncertainty as
these calculated values are not perfectly representative of conditions in any one sample. The
form of this uncertainty may be shifts in charge balance or saturation indices. However, these
representative values are useful in condensing large amounts of data to identify overall
geochemical conditions at each well. This simplification is consistent with the conceptual
model and intention of the model.
Post-baseline ORP values were based upon field-measured ORP, and electron activity (pe) was
calculated from the field ORP data using the Nernst equation. In the absence of measured ORP
values pe values for baseline runs were set to –3. This assumption is consistent with the
conceptual model of baseline conditions having both no oxygen and the presence of pyrite.

3 The data provided by EPA is a compilation of publicly available data from the Mill. Data acquired from previous
sampling events have been evaluated as part of those specific projects and their associated data quality objectives.
These data have been compiled and provided by EPA. Work performed for this project did not include the
evaluation of compiled data in a context of data usability or quality review.
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Two profiles were developed for each well: baseline and post-baseline conditions. Baseline
conditions are representative of groundwater conditions from the 1980-2005 period,
characterized by the absence of oxygen and/or nitrate. Baseline conditions provide the initial
water quality for all runs (baseline, post-baseline, and mixing; Figure 4).
Post-baseline conditions are representative of conditions from the 2006-present period,
characterized by the presence of oxygen and nitrate. Post-baseline conditions provide
benchmarks for the evaluation of model results. Some well/constituent combinations did not
have data prior to 2006; in this case, the first full year of available data was used to characterize
the baseline period water quality. Representative water quality for each modeled well is
presented in Table 2. Time-series plots of water chemistry for modeled wells are included in
Appendix A.
For mixing runs, leachate water quality data were provided by EPA. 4 These data were used to
develop a water quality profile associated with Cell 1 leachate. Cell 1 leachate was selected as a
representative leachate water quality for evaluating the interaction of leachate with different
aquifer conditions and water-qualities. Utilization of the same leachate water-quality for all
runs provided a basis for simple comparison. Additionally, a comparison of leachate water
quality found that leachate from Cell 3 (which is located closest to MW-11) is generally
comparable to the leachate in Cell 1. Based on this comparison, it is unlikely that additional
runs with multiple leachate profiles would impact the results of the modeling. Representative
values were calculated from all available data as arithmetic means with the exception of pH,
which was calculated as the geometric mean of proton concentration ([H+]). Leachate water
quality is presented in Table 3. Leachate was represented at mixing fractions of 0.1, 0.3, 0.5, 1, 3,
5, and 10%.
3.4.3 Equilibrium Phases
In a PHREEQC model, equilibrium phases represent the gas or mineral phases that are available
for reactions. The modeling presented here included both mineral and gas phases.
Two mineral phases were utilized for reactions in this geochemical modeling5. Pyrite (FeS2) was
modeled at concentrations of 0, 0.1, 0.4 and 0.8%. Those concentrations were set in the SOW.
The range of pyrite concentrations from the SOW are consistent with those observed at the Mill
(Hydro Geo Chem, 2012). The second mineral phase included in the model was calcite (CaCO3).
Calcite was modeled at concentrations of 0, 1.5, and 5%. The range of calcite concentrations was

4 The data provided by EPA is a compilation of publicly available data from the Mill. Data acquired from previous
sampling events have been evaluated as part of those specific projects and their associated data quality objectives.
These data have been compiled and provided by EPA. Work performed for this project did not include the
evaluation of compiled data in a context of data usability or quality review.
5 For the purposes of determining the amount of equilibrium mineral phases present, a porosity of 18.2 and a density
of 2.47 g/cc were assumed. These values were based on data in MWH (2010) and UMETCO (1993).
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based on data reported in Hydro Geo Chem (2012) and MWH (2010, Table 3). For model runs,
the saturation index control for pyrite was set to 0. The saturation index limit for calcite was set
to 0.5; this was estimated based upon the calcite over-saturation observed in the modeled wells.
It was assumed that both mineral phases were completely available for reaction. This
assumption is consistent with the assumptions used by Hydro Geo Chem (2012, see Section 2.1).
This is generally a reasonable assumption, however, it should be noted that real-world reactions
are often limited by the rate of reaction and the physical availability of mineral phases for
reaction. For example, availability of a mineral phase for reaction may be limited due to coating
of a mineral or its occurrence as an inclusion in a larger mineral phase.
Two gas phases were utilized for reactions in this geochemical modeling. In those model runs
that were oxic (i.e., post-baseline runs), oxygen gas (O2) was included at a partial pressure of 0.2
atm (logarithm of O2 partial pressure {pO2} of -0.67). Both baseline and post-baseline runs
utilized carbon dioxide (CO2) as an equilibrium phase. The partial pressure for the baseline and
post-baseline conditions was based on the input water quality (Table 2). The input water
quality was speciated in PHREEQC to determine the partial pressure at each well under each
condition. Under baseline conditions, the PHREEQC-calculated logarithm of CO2 partial
pressure (pCO2) in the five modeled wells varied from -1.84 to -2.52 with an average of -2.1
(Figure 5). Under post-baseline conditions, the PHREEQC-calculated pCO2varied from -1.27
to -2.05 with an average of -1.62. Based upon these analyses, baseline runs utilized a pCO2 of -
2.1 and post-baseline runs an index of -1.6. These analyses demonstrate that under both
baseline and post-baseline conditions, the groundwater at the Mill is over-saturated with
respect to atmospheric CO2 (typical historical pCO2 at sea level is -3.5).
For leachate model runs, mid-range pyrite (0.4%) and calcite at 0 and 1.5% concentrations were
chosen to represent likely subsurface conditions. For these leachate runs, oxygen was not
included.
3.5 BASELINE RESULTS
The baseline runs are based upon an anoxic condition that assumes the presence and stability of
pyrite. Conceptually, this condition is intended to represent an earlier period of Mill
operations, defined in the SOW as 2005 and before, when little or no oxygen was available to
the subsurface.
Water quality for the five modeled wells was developed as described in Section 3.3.2. A total of
12 runs were completed for each well, with each run defined by a combination of calcite and
pyrite concentrations as described in Section 3.3.3 (Table 5). Input, output files, and plots of
model results are presented in Appendix B.
Under some runs, minimal amounts of calcite may dissolve or precipitate to reach equilibrium.
However, this does not substantially affect the resulting water quality. An example of this is for
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MW-11 where no change is seen in pyrite (Figure 6).6 In some cases, small amounts of calcite
may dissolve or precipitate to reach equilibrium between these phases and the surrounding
system; however, these subtle shifts do not drive reductions in pH (as an example, see Figure 7
for MW-11).
Key species that can indicate reactions and changes in geochemical conditions in this
geochemical system include sulfate, fluoride, nitrate, and ammonia. The concentrations of
sulfate are unchanged during these runs as no pyrite is oxidized. Further, most wells (with the
except of MW-22) are undersaturated with respect to gypsum and so this is unlikely to be a
solubility control. Fluorite is over-saturated in MW-22 and may be a likely concentration-
controlling phase for fluoride; however, for the other wells, fluorite is undersaturated. Under
baseline conditions, all the wells were observed to have concentrations of both nitrate and
ammonia (Table 2). Under the reducing conditions that characterize the baseline runs, the
modeled equilibrium results in the conversion of any nitrate to ammonia. This result is in
contrast to the observed conditions (under both baseline and past-baseline conditions)—where
the presence of both nitrate and ammonia in groundwater indicates a redox disequilibrium in
this system. This observed disequilibrium is likely the result of biologically mediated reactions
(or lack thereof) and are unlikely to be well represented by geochemical modeling of this type.
These findings are consistent with those of Hydro Geo Chem (2012), which also found that
pyrite was stable under anoxic conditions. In the absence of oxygen, there is no acidity or
sulfate generated by the oxidation of pyrite and water quality is unchanged over the course of
the simulation (Figures 6 and 7). Variations in the amounts of pyrite or calcite do not affect the
results.
These results indicate that in the absence of oxygen, pyrite is stable in the subsurface at the Mill.
That is consistent with the fact that pyrite does, in fact, occur in the subsurface as documented
by Hydro Geo Chem (2012). Further, it is observed that the water quality at wells MW-27, MW-
24, MW-11, and MW-3A are over saturated with respect to calcium carbonate. This is consistent
with the observations of calcite in some wells and the occurrence of calcite as a cementitious
phase in the Burro Canyon formation (Craig, 1982).

6 These ‘dashboard’ plots show six individual sub-figures. Each sub-figure presents model results for each of the five
model cells over the first 50 advection steps. The top two figures are pH and sulfate concentrations. For post-
baseline and leachate mixing runs lines are included that represent average conditions in these wells for the post-
baseline period as a model results benchmark. The middle two figures represent the change in calcite or pyrite at
each model step. These changes are presented as millimoles; positive values represent precipitation (increases in
mineral mass) and negative values represent dissolution (decreases in mineral mass). The bottom two plots present
saturation indices for gypsum and fluorite. These two minerals represent likely primary solubility controls for
sulfate and fluoride. Values of the saturation index greater than zero indicate over-saturation; values less than zero
indicate under-saturation.
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3.6 POST-BASELINE RESULTS
The post-baseline runs are based upon oxic conditions. Conceptually, this condition is intended
to represent a more recent period, defined in the SOW as after 2005, when oxygen was available
in the subsurface. In these runs, Cell 1 of the model is equilibrated with the atmosphere; Cells 2
through 5 are equilibrated with pyrite and/or calcite.
Water quality for the five modeled wells was developed as described in Section 3.3.2. A total of
12 runs were completed for each well, with each run defined by a combination of calcite and
pyrite concentrations as described in Section 3.3.3 (Table 6). Input, output files, and plots of
model results are presented in Appendix C.
The key findings from the post-baseline runs are:
• Pyrite oxidizes to an extent concomitant to the provision of oxygen.
• The downgradient transport of dissolved oxygen in water provides only limited oxygen
transport and subsequently, only limited pyrite oxidation.
• Pyrite oxidation from the transport of dissolved oxygen in water is unable to lower the
pH due to alkalinity and/or the presence of calcite.
• Pyrite concentrations are not the controlling factor and variation has limited impact on
the results.
• Upgradient inflow provides a continual source of high-alkalinity water that buffers
pyrite-oxidation related pH decreases.
The results of the individual wells are generally consistent. The groundwater at the Mill is
associated with sufficient alkalinity to buffer any acidity generated by pyrite oxidation (Figure
8). The addition of calcite provides further buffering of pH (Figure 9). Most of the wells have
relatively high alkalinity (more than 300 mg/L; Table 2). MW-22, in contrast to the other wells,
has lower alkalinity (19 mg/L; Table 2). In the absence of calcite, the oxidation of pyrite is able
to lower pH (Figure 10) at that well. However, the addition of calcite to the system at MW-22
stabilizes the pH (Figure 11).
Key species that can indicate reactions and changes in geochemical conditions in this
geochemical system include sulfate, fluoride, and nitrate/ammonia. The concentrations of
sulfate in the baseline runs increase as a result of pyrite oxidation. This increase is directly
proportional to the amount of pyrite oxidized. Given the high baseline sulfate concentrations
(ranging from 365 mg/L in MW-27 to 6,400 mg/L in MW-22) the modeled increases in sulfate
concentration are proportionately small. Fluorite is over-saturated in MW-22 and may be a
likely concentration-controlling phase for fluoride; however, for the other wells, fluorite is
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undersaturated. The modeled changes in pH are small and do not notably affect fluorite
saturation of the system for any wells. Under baseline conditions, all the wells show
concentrations of nitrate and ammonia (Table 2). Nitrogen reactions, such as nitrification and
denitrification, are most commonly and rapidly mediated biologically. Under the modeled
post-baseline conditions, pyrite controls the oxidation-reduction potential of the modeled
solutions. As a result, the post-baseline runs are consistent with the baseline runs with respect
to nitrogen speciation—with nitrate converted to ammonia. Under conditions where all the
pyrite is consumed, such as if the model was allowed to run for very many steps or additional
oxygen is provided to the system, ammonia is then oxidized to nitrate. However, it should be
noted that observed conditions in site groundwater are in dis-equilibrium with respect to
nitrogen species.
Hydro Geo Chem (2012) also found that when oxygen was provided to the geochemical system,
pyrite was oxidized and generated acidity. In those runs, from 1 to 10 L of air was provided as
an equilibrium phase for reaction. As a result, substantially more pyrite was oxidized and this
oxidation continued until the oxygen was completely consumed. However, once water travels
away from the aerated environment in the vicinity of a monitoring well, the ability to transport
oxygen is driven solely by the flow of water.
Based upon this modeling, the reduction of pH driven by pyrite oxidation is possible under
only very limited conditions. Specifically, multiple conditions must be satisfied: alkalinity must
be low, no calcite can be present, reactions are not kinetically inhibited; wells are equilibrated
with the atmosphere; and pyrite is present within the aquifer at the depth of the well screens
(where the oxygen would be present if from wells).
3.7 MIXING RESULTS
The mixing runs are based upon the mixing of baseline period water with leachate from the
tailings ponds. The purpose of these model runs was to better understand the geochemical
conditions and water quality results from the mixing of leachate water into the aquifer at the
Mill. These mixing runs were performed using conditions consistent with those of the baseline
runs.
Water quality for the three modeled wells was developed as described in Section 3.3.2. A total
of 14 runs were completed for each well, with each run defined by a combination of calcite
concentration, pyrite concentration, and leachate mixing ratio (Table 7). Input, output files, and
plots of model results are presented in Appendix D.
The key findings from the mixing runs are:
• Decreases in pH from mixing at low mixing ratios are generally consistent with those
observed.
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• Increases in sulfate from mixing are larger than observed.
An example of these results can be seen in Figure 12 for MW-11. In the absence of calcite, small
amounts of additional leachate can rapidly consume alkalinity and drive pH very low. For
MW-11 at 1% leachate the system drops to near pH 3 (Figure 13) versus near pH 6.5 at 0.5%
leachate (Figure 12). The effective buffering capacity of calcite is seen in Figure 14, which
includes calcite at the same mixing conditions. However, at higher leachate concentrations the
calcite can be entirely consumed, resulting in rapid pH drops.
In all results, gypsum and fluorite are over-saturated. Further, it can be observed that sulfate
concentrations increase much more rapidly than observed in the monitoring wells. These lines
of evidence suggest that additional reactions and alteration of the leachate occur in the
subsurface beyond those modeled in these runs. Such reactions are likely to include the
formation of iron and aluminum hydroxy-sulfate minerals (Nicholson et al., 2003) as an
important process. While the modeling handles the direct mixing of the leachate with the
subsurface, in the actual subsurface leachate would interact with substantial amounts of
vadose-zone material before reaching the aquifer—which is likely to substantially alter the
released leachate. Further understanding of the leachate alteration is needed to further
elucidate the likelihood of the leachate release hypothesis.

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4 CONCLUSIONS
Groundwater at the White Mesa Mill has been observed to be undergoing shifts in water
quality. These changes generally include lowering of pH, increases in sulfate, and increases in
the concentrations of some metals. In past reports, these changes in groundwater geochemistry
have been hypothesized to be the result of the oxidation of pyrite in the subsurface.
Geochemical modeling described in this report found that pyrite is stable in the subsurface at
baseline, or anoxic, conditions. When oxygen is provided to the geochemical system, pyrite
dissolves in an amount proportional to the amount of oxygen added to the system. Past
geochemical modeling indicated that this pyrite oxidation is a potential driver of the observed
changes in subsurface water quality. However, that modeling ignored the presence of acid-
buffering minerals such as calcite. Further, that modeling did not account for transport in the
subsurface and the associated dilution and transport of reaction products. The modeling
described in this report found that the amount of oxygen that is likely transported in the
subsurface is insufficient to result in substantial changes to groundwater quality. This is
explained by the presence of buffering phases and the in-flux of upgradient water to dilute and
disperse reaction products. Past studies over-estimated the likely influence of pyrite oxidation
in the subsurface by over-emphasizing the presence of acid generating pyrite and ignoring the
presence of buffering phases.
Additional modeling investigated the potential for leachate water from the tailings cells to
impact groundwater quality. Leachate water quality is characterized by low pH, high sulfate,
high nitrate and ammonia, and high metals concentrations. Mixing of low percentages of
leachate, on the order of 1% or less, was found to lower pH and increase sulfate concentrations.
However, the increases in sulfate were larger than those observed at the Mill. The scope of this
modeling effort did not take into account the alteration of leachate solutions by the soils and
rock of the vadose zone. It is likely that reactions between the leachate and the materials of the
vadose zone and aquifer would further reduce sulfate concentrations.
Groundwater quality is the result of the interaction of multiple processes in a complex
subsurface. The existence of chloroform and nitrate plumes at the Mill are direct evidence that
transport from the surface to the subsurface has occurred over the period of operation of the
Mill. The geochemical modeling presented here suggests that oxygen transport in the
subsurface is unlikely to drive substantial pyrite oxidation in the subsurface outside of areas
immediately influenced by monitoring wells. The decreases in pH and increases in sulfate and
metals observed in some wells are generally consistent with the mixing of leachate water.
However, the limited scope of the modeling effort presented herein was insufficient to fully
elucidate the mechanisms driving changes in the groundwater quality at the Mill. The materials
reviewed and the result of geochemical modeling has identified a number of additional steps
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that would help better detail the processes impacting and driving changes in water quality at
the Mill.
These additional steps include:
• Inverse geochemical modeling of leachate to better understand the alteration of leachate
that would occur due to interactions with the aquifer matrix.
• Geochemical forensics analyses investigating trends and patterns in a range of Mill-
specific parameters to better identify and differentiate the processes affecting individual
wells.
• Hydrologic modeling to quantify flow paths and flow rates to better understand the
physical transport of solutes and water at the Mill.
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5 REFERENCES
Battelle 2023. Quality assurance project plan, groundwater geochemical modeling at the White
Mesa Uranium mill. February 9.
Craig L.C. 1982. Uranium potential of the Burro Canyon formation in Western Colorado. USGS
Open-File Report 82-222, United States Department of the Interior, Geological Survey, 1982.
Energy Fuels 2023. https://www.energyfuels.com/white-mesa-mill. Accessed 3/16/2023.
Hurst and Solomon 2008. Summary of work completed, data results, interpretations and
recommendations for the July 2007 sampling event at the Denison Mines, USA, White Mesa
Uranium Mill. May 2008.
Hydro Geo Chem 2012. Investigation of pyrite in the perched zone, White Mesa Uranium Mill
site. December 7.
Hydro Geo Chem 2014. Hydrogeology of the White Mesa uranium mill. June 6.
Intera 2009. Nitrate contamination investigation report. December 30.
Intera 2012. pH report, White Mesa uranium mill, Blanding, Utah. November 9.
MWH 2010. Revised infiltration and contaminant transport modeling report, White Mesa Mill
Site, Blanding, Utah. March.
Nicholson, A., A. Davis, and S. Helgen. 2003. Elements influencing cost apportionment in the
Pinal Creek Aquifer, Arizona USA. Part II: Identification of Geochemical Controls on
Remediation Time. Environ. Forensics 4:271–286.
United States Geological Survey (USGS) 2011. Assessment of potential migration of
radionuclides and trace elements from the White Mesa uranium mill to the Ute Mountain Ute
Reservation and surrounding areas, Southeastern Utah. SIR 2011-5231
USGS 2013. Description of input and examples for PHREEQC Version 3—A computer Program
for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations.
TM6-A42.
UMETCO 1993. Groundwater study White Mesa facility, Blanding UT. January.
Utah Department of Environmental Quality (UDEQ). 2023. https://deq.utah.gov/waste-
management-and-radiation-control/energy-fuels-resources-usa-inc. Accessed 3/16/2023.

Figures

¯0 1,000 2,000 3,000
Feet
Aerial Source: Esri, Maxar (2018)
Figure 1.
Site and key well locations
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Key Well Locations
Disposal Cell Locations
Site Boundary
Las Vegas
Great Basin
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Salt Lake City
MW-27
MW-11
MW-24
MW-3A
MW-22
Cell 1
Cell 2
Cell 3
Cell 4B
Cell 4A
Site Location
Figure 2.Observed changes in pH at the Mill (Intera 2012)
Figure 3.
Conceptual model
1 2 534
O2CO2
PyriteCalcite
PyriteCalcite PyriteCalcite PyriteCalcite
Phases
MW Downgradientcell Downgradientcell Downgradientcell DowngradientcellUpgradient inflow
Conceptual
Select MWwater quality
Select MWwater quality Select MWwater quality Select MWwater quality
Select MWwater quality Select MWwater quality
Initial WQ
Figure 4.
Model data flow schematic
Baseline Water
Quality
Input Data Model Runs
Post-Baseline
Runs
Baseline
Runs
Leachate
Mixing
Benchmark
Data
Post-
Baseline
Water
Quality
Post-
Baseline
Water
Quality
Model Test
Stability of Pyrite under anoxic
conditions
Evaluation of
effects of oxygen on groundwater
quality and pyrite stability
Evaluation of leachate mixing with site
groundwater
Figure 5.
Carbon dioxide saturation in modeled wells, baseline and
post-baseline conditions
Figure 6.
Baseline model run dashboard plot
MW-11, pyrite 0.8%, calcite 0%
Figure 7.
Baseline model run dashboard plot
MW-11, pyrite 0.8%, calcite 1.5%
Figure 8.
Post-baseline model run dashboard plot
MW-24, pyrite 0.8%, calcite 0%
Figure 9.
Post-baseline model run dashboard plot
MW-24, pyrite 0.8%, calcite 1.5%
Figure 10.
Post-baseline model run dashboard plot
MW-22, pyrite 0.8%, calcite 0%
Figure 11.
Post-baseline model run dashboard plot
MW-22, pyrite 0.8%, calcite 1.5%
Figure 12.
Mixing model run dashboard plot
MW-11, pyrite 0.45%, calcite 0%, leachate fraction 0.5%
Figure 13.
Mixing model run dashboard plot
MW-11, pyrite 0.45%, calcite 0%, leachate fraction 1%
Figure 14.
Mixing model run dashboard plot
MW-24, pyrite 0.45%, calcite 1.5%, leachate fraction 1%

Tables

Revised Final
White Mesa Geochemical Modeling
10/26/2024
Table 1. Summary of selected monitoring wells for geochemical modeling
Generalized Location Well Description
Upgradient MW-27 At processing area, immediately upgradient of tailings cell 1
MW-24 Southwest (downgradient) corner of tailings cell 1
MW-11 Northern edge of tailings cell 4A
MW-3A Approximately 600 m south of tailings cell 4/4A
Downgradient MW-22 Approximately 1,600 m south of tailings cell 4A
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Table 2. Baseline and post-baseline water quality at modeled wells
NH3 Alkalinity Ca Cl F Fe Mg NO3-K Na SO4-2
mg/L
mg/L as
CaCO3 mg/L mg/L mg/L ug/L mg/L mg/L mg/L mg/L mg/L
MW-27 0.06 330a 158 34.4 0.68a 30.0 69.6 28.0a 4.3 75.7 365a -3 7.65
MW-24 18.5 483 492 50.4 0.30 2176 176 0.62 20.2 438 2660 -3 7.36
MW-11 0.80 372 72.7 33.8 0.60 30.6 24.4 0.44 7.0 515 1043 -3 7.73
MW-3A 0.08a 347a 463 61.6 0.10 126 297 0.44 27.3 709 3420a -3 7.36
MW-22 1.1a 19.2a 489 62.0 12.7a 38.0 1035 11.2a 25.4 260 6423a -3 6.47
MW-27 0.1 330.1 152.6 39.8 0.68 36.9 66.1 28.0 4.3 73.8 365 7.1 7.16
MW-24 0.4 85.3 489.6 44.7 0.46 732 182 2.77 13.4 481 2778 7.2 5.82
MW-11 0.9 317.1 74.9 37.7 0.43 75.9 23.6 9.18 7.1 589 1173 5.4 7.41
MW-3A 0.1 346.9 469.7 59.4 0.92 30.3 297 4.08 28.4 797 3420 7.2 6.56
MW-22 1.1 19.2 432.0 57.1 12.7 76.6 1093 11.2 22.5 274 6423 8.4 5.03
Notes
a due to data availability limitations post-baseline data used for baseline period.
Baseline
Post-
baseline
pe pHPeriodWell
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Table 3. Representative containment cell 1 leachate water quality
NH3 Alkalinity Ca Cl F Fe Mg NO3-K Na SO4-2
mg/L
mg/L as
CaCO3 mg/L mg/L mg/L ug/L mg/L mg/L mg/L mg/L mg/L
Cell 1 7494 0 565 27161 3357 5912 11568 166 4128 32979 184604 1.46
Description pH
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Table 4. Summary of available calcite content data
Report Min.Max.Mean
Hydro Geo Chem (2012)a 0.05b 14.0 1.68
MWH (2010)c 0.05b 18.2 1.38
1.5
Notes:
a Based upon data presented in Table 4, for all wells
b 0.05 represents non-detect values
c Based on data presented in Table C4, for all wells.
Calcite Content (%)
average
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Table 5. Summary of baseline model run conditions
Well
Calcite
(%)
Pyrite
(%)
CO2
(partial pressure)
O2
(partial pressure)
00-2.1 0
00.1-2.1 0
00.4-2.1 0
00.8-2.1 0
1.5 0 -2.1 0
1.5 0.1 -2.1 0
1.5 0.4 -2.1 0
1.5 0.8 -2.1 0
50-2.10
5 0.1 -2.1 0
5 0.4 -2.1 0
5 0.8 -2.1 0
00-2.10
0 0.1 -2.1 0
0 0.4 -2.1 0
0 0.8 -2.1 0
1.5 0 -2.1 0
1.5 0.1 -2.1 0
1.5 0.4 -2.1 0
1.5 0.8 -2.1 0
50-2.10
5 0.1 -2.1 0
5 0.4 -2.1 0
5 0.8 -2.1 0
00-2.10
0 0.1 -2.1 0
0 0.4 -2.1 0
0 0.8 -2.1 0
1.5 0 -2.1 0
1.5 0.1 -2.1 0
1.5 0.4 -2.1 0
1.5 0.8 -2.1 0
50-2.10
5 0.1 -2.1 0
5 0.4 -2.1 0
5 0.8 -2.1 0
00-2.10
0 0.1 -2.1 0
0 0.4 -2.1 0
0 0.8 -2.1 0
1.5 0 -2.1 0
1.5 0.1 -2.1 0
1.5 0.4 -2.1 0
1.5 0.8 -2.1 0
50-2.10
5 0.1 -2.1 0
5 0.4 -2.1 0
5 0.8 -2.1 0
00-2.10
0 0.1 -2.1 0
0 0.4 -2.1 0
0 0.8 -2.1 0
1.5 0 -2.1 0
1.5 0.1 -2.1 0
1.5 0.4 -2.1 0
1.5 0.8 -2.1 0
50-2.10
5 0.1 -2.1 0
5 0.4 -2.1 0
5 0.8 -2.1 0
MW-27
MW-24
MW-11
MW-3A
MW-22
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Table 6. Summary of post-baseline model run conditions
Well
Calcite
(%)
Pyrite
(%)
CO2
(partial pressure)
O2
(partial pressure)
00-1.6 -0.67
0 0.1 -1.6 -0.67
0 0.4 -1.6 -0.67
0 0.8 -1.6 -0.67
1.5 0 -1.6 -0.67
1.5 0.1 -1.6 -0.67
1.5 0.4 -1.6 -0.67
1.5 0.8 -1.6 -0.67
5 0 -1.6 -0.67
5 0.1 -1.6 -0.67
5 0.4 -1.6 -0.67
5 0.8 -1.6 -0.67
0 0 -1.6 -0.67
0 0.1 -1.6 -0.67
0 0.4 -1.6 -0.67
0 0.8 -1.6 -0.67
1.5 0 -1.6 -0.67
1.5 0.1 -1.6 -0.67
1.5 0.4 -1.6 -0.67
1.5 0.8 -1.6 -0.67
5 0 -1.6 -0.67
5 0.1 -1.6 -0.67
5 0.4 -1.6 -0.67
5 0.8 -1.6 -0.67
0 0 -1.6 -0.67
0 0.1 -1.6 -0.67
0 0.4 -1.6 -0.67
0 0.8 -1.6 -0.67
1.5 0 -1.6 -0.67
1.5 0.1 -1.6 -0.67
1.5 0.4 -1.6 -0.67
1.5 0.8 -1.6 -0.67
5 0 -1.6 -0.67
5 0.1 -1.6 -0.67
5 0.4 -1.6 -0.67
5 0.8 -1.6 -0.67
0 0 -1.6 -0.67
0 0.1 -1.6 -0.67
0 0.4 -1.6 -0.67
0 0.8 -1.6 -0.67
1.5 0 -1.6 -0.67
1.5 0.1 -1.6 -0.67
1.5 0.4 -1.6 -0.67
1.5 0.8 -1.6 -0.67
5 0 -1.6 -0.67
5 0.1 -1.6 -0.67
5 0.4 -1.6 -0.67
5 0.8 -1.6 -0.67
0 0 -1.6 -0.67
0 0.1 -1.6 -0.67
0 0.4 -1.6 -0.67
0 0.8 -1.6 -0.67
1.5 0 -1.6 -0.67
1.5 0.1 -1.6 -0.67
1.5 0.4 -1.6 -0.67
1.5 0.8 -1.6 -0.67
5 0 -1.6 -0.67
5 0.1 -1.6 -0.67
5 0.4 -1.6 -0.67
5 0.8 -1.6 -0.67
MW-27
MW-24
MW-11
MW-3A
MW-22
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Table 7. Summary of leachate mixing model run conditions
Well
Calcite
(%)
Pyrite
(%)
CO2
(partial pressure)
O2
(partial pressure)
Leachate Mixing
Fraction (%)
0 0.4 -1.6 0 0.1
0 0.4 -1.6 0 0.3
0 0.4 -1.6 0 0.5
0 0.4 -1.6 0 1
0 0.4 -1.6 0 3
0 0.4 -1.6 0 5
0 0.4 -1.6 0 10
1.5 0.4 -1.6 0 0.1
1.5 0.4 -1.6 0 0.3
1.5 0.4 -1.6 0 0.5
1.5 0.4 -1.6 0 1
1.5 0.4 -1.6 0 3
1.5 0.4 -1.6 0 5
1.5 0.4 -1.6 0 10
0 0.4 -1.6 0 0.1
0 0.4 -1.6 0 0.3
0 0.4 -1.6 0 0.5
0 0.4 -1.6 0 1
0 0.4 -1.6 0 3
0 0.4 -1.6 0 5
0 0.4 -1.6 0 10
1.5 0.4 -1.6 0 0.1
1.5 0.4 -1.6 0 0.3
1.5 0.4 -1.6 0 0.5
1.5 0.4 -1.6 0 1
1.5 0.4 -1.6 0 3
1.5 0.4 -1.6 0 5
1.5 0.4 -1.6 0 10
0 0.4 -1.6 0 0.1
0 0.4 -1.6 0 0.3
0 0.4 -1.6 0 0.5
0 0.4 -1.6 0 1
0 0.4 -1.6 0 3
0 0.4 -1.6 0 5
0 0.4 -1.6 0 10
1.5 0.4 -1.6 0 0.1
1.5 0.4 -1.6 0 0.3
1.5 0.4 -1.6 0 0.5
1.5 0.4 -1.6 0 1
1.5 0.4 -1.6 0 3
1.5 0.4 -1.6 0 5
1.5 0.4 -1.6 0 10
MW-27
MW-24
MW-11
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