1 

Groundwater Chemistry Changes as a Result of CO2 Injection 

at the ZERT Field Site in Bozeman, Montana 

Project Report 

Contributors in Alphabetical Order: 

Lawrence Berkeley National Laboratory: 

John A. Apps, Jens T. Birkholzer, Nicolas Spycher, Liange Zheng 

U.S. Geological Survey: 

Gil Ambats, William N. Herkelrath, Yousif, K. Kharaka, James J. Thordsen, 

Evangelos Kakouros, Sarah Beers 

Montana State University: 

Kadie S. Gullickson, Lee H. Spangler 
2 

TABLE OF CONTENTS 

1. INTRODUCTION.......................................................................................................... 6

1.1. Understanding the Problem..................................................................................................6 

1.2. Scope and Objective.............................................................................................................7 

2. DESCRIPTION OF THE ZERT FIELD SITE ................................................................ 7

2.1. Regional and local setting ....................................................................................................8 

2.2. Geology ................................................................................................................................9 

2.3. Test Configuration and Groundwater Flow .........................................................................9 

2.4. Water Sampling and Analysis ............................................................................................11 

3. WATER SAMPLING RESULTS ................................................................................ 12

3.1. Dissolved Inorganic Chemicals..........................................................................................13 

3.2. Dissolved Organic Chemicals ............................................................................................20 

4. MINERALOGICAL DATA.......................................................................................... 21

4.1. Core Analysis and Methods ...............................................................................................21 

4.2. Mineralogical Results.........................................................................................................22 

5. HYDROGEOLOGICAL AND GEOCHEMICAL INTERPRETATION ......................... 25

5.1. Transport of CO2 in Gas and Aqueous Phases...................................................................26 

5.2. Geochemical Response to CO2 Release and Interpretation ...............................................27 

5.3 Geochemical Modeling ......................................................................................................55 

6. SUMMARY AND CONCLUDING REMARKS............................................................ 69

7. ACKNOWLEDGMENTS and Disclaimer.................................................................. 72

8. REFERENCES........................................................................................................... 72

APPENDIX A .................................................................................................................... 79

APPENDIX B .................................................................................................................... 82

APPENDIX C .................................................................................................................... 83

APPENDIX D .................................................................................................................... 85
3 

List of Figures 

Figure 2.1 Packer system installed in horizontal well (from Spangler et al., 2009)......................8 

Figure 2.2 Location of water monitoring wells in relation to the surface trace of the slotted 

horizontal CO2 injection pipe in zone 6 of the ZERT site. The gridpoints in the figure 

show refer to a grid with 10 m spacing that was established to provide a common 

reference system for researchers. ...............................................................................11 

Figure 3.1 Cumulative precipitation and groundwater levels in selected ZERT wells during the 

sampling period in 2008.............................................................................................13 

Figure 3.2 Modified Stiff diagrams showing concentrations (equivalent units normalized to 

100%) of major cations and anions, together with salinity and pH of groundwater 

from well 2B before and during CO2 injection. .........................................................14 

Figure 3.3 Field- measured groundwater pH values (a), alkalinities (b), and electrical 

conductance (c), obtained from selected ZERT wells as a function of time of 

sampling. Note the systematic decrease in pH values from ~7.0 before CO2 injection 

to values as low as 5.6 during injection, and subsequent pH increases after CO2

injection ended. Alkalinities increased from about 400 mg/L before CO2 injection to 

values close to 1200 mg/L as HCO3, and electrical conductance also increased from 

about 600 μS/cm before CO2 injection to values higher than 1,600 μS/cm during 

injection......................................................................................................................15 

Figure 3.4 Concentrations of major cations in groundwater from the ZERT wells plotted as a 

function of water alkalinities. Note the relatively constant concentrations of Na and 

K, but the general increases in the concentrations of divalent cations with water 

alkalinities, possibly indicating dissolution of carbonate minerals............................16 

Figure 3.5 Ca/Mg weight ratios plotted as a function of time of sampling. Note that the ratios 

are higher than the value expected from dissolution of dolomite (1.6), and are 

relatively constant for well 4B, but continue to increase for well 2B until CO2

injection was terminated, possibly indicating dissolution of calcite..........................17 

Figure 3.6 Concentrations of Fe (a) and Mn (b) in groundwater from selected ZERT wells 

plotted as a function of time of sampling. Note the low Fe and Mn concentrations 

during July 20 to July 26, which we are attributing to the oxidizing conditions 

possibly caused by percolating oxygenated water from rainfall events (see Figure 

3.1)..............................................................................................................................18 

Figure 3.7 Trace metal concentrations in groundwater from selected ZERT wells plotted as a 

function of water alkalinities. Some of the scatter shown probably results because the 

reported values in some cases are close to the detection limits..................................19 

Figure 3.8 Concentrations of BTEX compounds detected in groundwater from selected ZERT 

wells plotted as a function of time of sampling. The BTEX concentrations are all 

significantly below the maximum contaminant levels (MCLs) (e.g., 5 ppb for 

benzene). ....................................................................................................................20 

Figure 4.1 Grain size fractions for different zones in Well W6. .................................................22 

Figure 4.2 Grain size fractions for 15 gravel samples analyzed from Wells 6, 7, and 8.............23 

Figure 5.1 Schematic representation of CO2 transport in ZERT field site. The cross-section 

shown is along the axis of well pairs 1A/B, 2A/B, 3A/B, and 4A/B. ........................27 
4 

Figure 5.2 Correlation plots showing relationships between various species in solution ...........33 

Figure 5.3 Normalized saturation indices of magnetite, goethite, siderite, green rust (fougeriteCO3) and Fe(OH)3 (ferrihydrite) plotted as a function of pe......................................49 

Figure 5.4 Normalized saturation indices of pyrolusite, bixbyite, manganite, hausmannite and 

rhodochrosite, plotted as a function of pe. ................................................................50 

Figure 5.5 Saturation index of calcite as a function of log P(CO2) calculated for groundwater 

samples taken between July 7 and July 17, 2008 at the ZERT site. For an 

explanation of the trend lines, please refer to the text................................................54 

Figure 5.6 Calculated pH with different combination of chemical reactions..............................62 

Figure 5.7 Calculated calcium concentration vs pH with different calcite dissolution rate. .......63 

Figure 5.8 Calculated sodium concentration vs pH.....................................................................63 

Figure 5.9 Calculated potassium concentration vs pH. ...............................................................64 

Figure 5.10 Calculated magnesium concentration vs pH. .............................................................64 

Figure 5.11 Calculated lead concentration vs pH..........................................................................64 

Figure 5.12 Calculated cadmium concentration vs pH..................................................................65 

Figure 5.13 Calculated copper concentration vs pH......................................................................65 

Figure 5.14 Calculated zinc concentration vs pH..........................................................................65 

Figure 5.15 Calculated iron concentration vs pH in the base model, in which only cation 

exchange is considered and a sensitivity run in which both cation exchange and 

siderite dissolution are considered .............................................................................66 

Figure 5.16 Calculated bicarbonate concentration vs pH..............................................................67 

Figure 5.17 Calculated arsenic concentration vs pH .....................................................................67 

Figure 5.18 Calculated selenium concentration vs pH ..................................................................68 

Figure 5.19 Calculated phosphate concentration vs pH ................................................................68 

Figure D.1 Normalized saturation indices of chromite, magnesiochromite, and the chromium 

spinels of Cd, Co, Cu and Zn, Eskolaite and Cr-ferrihydrite, plotted as a function of 

pe. ...............................................................................................................................85 

Figure D.2 Normalized saturation indices of copper, bornite, covellite, chalcocite, cuprite and 

tenorite, plotted as a function of pe. ..........................................................................86 

Figure D.3 Normalized saturation indices of selenium, molybdenum selenide, cadmoselite and 

clausthalite, plotted as a function of pe. .....................................................................87 
5 

List of Tables 

Table 5.1 Correlation matrix of the log molar concentrations of all species analyzed in MSUZERT groundwaters for the period July 8 to July 17, 2008.......................................31 

Table 5.2 Principal components derived from an analysis of groundwater chemical 

compositions for the period July 7 to July 17, 2008 ..................................................36 

Table 5.3 Correlation of aqueous species with principal components for the period July 7 to 

July 17, 2008 in relation to short-term chemical processes .......................................39 

Table 5.4 Assumed initial composition of the groundwater at the ZERT site prior to CO2

injection......................................................................................................................43 

Table 5.5 Saturation indices of redox-insensitive primary and secondary minerals with respect 

to groundwater at the ZERT site ................................................................................46 

Table 5.6 Variation in principal aqueous species of selected redox-sensitive species as a 

function of pe at circum-neutral pH (pH = 6.9). ........................................................48 

Table 5.7 Distribution of the predominant Cr, Fe and Se species in solution at pH = 6.82 and pe 

= +9 ............................................................................................................................51 

Table 5.8 Calculated calcite saturation index and CO2 partial pressure for groundwaters taken 

at the ZERT site between July 7 and July 17, 2008 ...................................................53 

Table 5.9 Primary species and their initial concentration ..........................................................57 

Table 5.10 Minerals considered in the model. .............................................................................57 

Table 5.11 Aqueous complexes and their dissociation constants ................................................58 

Table 5.12 Cation exchange reactions and selectivity coefficients..............................................59 

Table 5.13 Surface complexation reactions and surface complexation constants (logK) on HFO

....................................................................................................................................59 

Table 5.14 Equilibrium constants for minerals1...........................................................................61 

Table 5.15 Initial volume fraction and kinetic parameters for minerals considered in the model1

....................................................................................................................................62 

Table 5.16 Initial (Ci

) and final (Cf) adsorbed concentration and their difference Cf –Ci...........67 

Table A1 Chemical composition of water samples from ZERT monitoring wells....................79 

Table B1 Well log for well 6 .....................................................................................................82 
6 

1. INTRODUCTION 

1.1. Understanding the Problem 

Combustion of fossil fuels produces CO2, a common greenhouse gas linked to global climate 

change. Separation of CO2 from emissions produced by large industrial point sources like power 

plants, cement kilns and refineries, and injection deep underground into geologic formations is one 

method of preventing CO2 releases into the atmosphere. This process is referred to as Carbon 

Capture and Storage (CCS). CCS is one of several solutions being considered to mitigate global 

climate change. Other solutions include increased energy efficiency, renewables, nuclear power, 

advanced coal, and plug-in hybrid electric vehicles. 

Injection of CO2 into deep geologic reservoirs is one solution, but this method of sequestering 

carbon is not without its own unique set of environmental risks, summarized by the United States 

Environmental Protection Agency (US EPA) in its draft rules governing underground injection of 

CO2 (US EPA, 2008). The US EPA designates potable groundwater aquifers as those underground 

sources of drinking water (USDW) worthy of protection under the Safe Drinking Water Act (US 

EPA, 2004). Many municipalities, businesses, and private individuals across the United States rely 

on these USDW as their primary source of drinking water, or for process water used in 

manufacturing, power production, etc. 

Compressed CO2 (as a free phase liquid or supercritical fluid) is less dense than water under most 

conditions, causing it to float (like oil on water) and move upward if unconstrained by fine-grained, 

low permeability rocks or sediments (such as shale, mudstone, clay or salt). Therefore, if not 

properly capped (analogous to a soda bottle), CO2 has the potential to leak from the storage 

formation where it was injected and move as a buoyant fluid into overlying USDW. Once CO2

enters a USDW, it readily dissolves in the groundwater, forming a weak acid (i.e., carbonic acid), 

which lowers the pH of the groundwater and increases its dissolved carbonate content, according to 

the following overall reaction: 

CO2(g) + H2O ==> H+

 + HCO3– (1-1) 

The magnitude and extent of acidification and alkalinity increase is expected to depend on the 

degree of buffering by aquifer materials (such as carbonate minerals found in many aquifers) and 

could result in the release of trace metals by dissolution and/or desorption and ion exchange 

reactions. Both of these processes could mobilize heavy metals including lead (Pb), cadmium (Cd) 

and arsenic (As) into groundwater (e.g., Wang and Jaffe, 2004; Kharaka et al., 2006; Birkholzer et 

al., 2008; Kharaka et al., 2009b). The solvent properties exhibited by supercritical CO2 may also 

leach organic compounds including benzene, toluene, ethylbenzene and xylenes (BTEX), phenols, 

polynuclear aromatic hydrocarbons (PAHs) and other compounds, from organic matter present in 

the aquifer. The release of these constituents at levels exceeding US EPA maximum contaminant 

levels (MCL) could become a potential health hazard. Therefore, even though the risk of CO2

migration from the storage reservoir is considered to be small with proper site selection and a 

regulatory framework designed to oversee, monitor and control risk (IPCC, 2007), the potential 

impact the CO2 can have on potable groundwater resources warrants further study. 
7 

1.2. Scope and Objective 

In this report, we describe the geochemical and hydrological results of a shallow CO2-injection test 

performed during July and August 2008 at a field site created by the Zero Emission Research and 

Technology Center (ZERT), located on Montana State University (MSU) property near Bozeman, 

Montana. From July 9 to August 7, 2008, approximately 300 kg/day of food-grade CO2 was 

injected through a perforated pipe placed approximately 1.1–2.5 m below ground surface, and about 

0.5–1 m below the water table. The objective of this study was to investigate, using a small-scale 

field experiment, whether sequestered CO2 released from a hypothetical geologic storage reservoir 

would have an adverse impact on USDW. The objective was accomplished by collecting 

approximately 80 shallow groundwater samples before, during, and after CO2 gas injection and 

analyzing these samples for their concentrations of major, minor, and trace inorganic and organic 

compounds. The scope of the study was limited to the potential impact of gaseous CO2 on potable 

groundwater and did not consider or evaluate the impact of displaced saline groundwater on shallow 

freshwater aquifers. The study was undertaken as a collaborative project between the Earth Sciences 

Division at Lawrence Berkeley National Laboratory (LBNL) and the U.S. Geological Survey 

(USGS), in part funded by the Electronic Power Research Institute (EPRI). 

2. DESCRIPTION OF THE ZERT FIELD SITE 

ZERT was initially created as a collaboration involving two universities and six DOE national 

laboratories. ZERT started in 2006 to develop a field test site where controlled, shallow subsurface 

release of CO2 would be possible over a significant spatial extent. The primary purpose of the 

ZERT field site, located on MSU property near Bozeman, Montana, was to allow controlled studies 

of near-surface CO2 transport and detection technologies. A slotted horizontal well of about 70 m 

length divided into six zones was installed into the shallow subsurface (Figure 2.1). The average 

depth of the slotted section of the horizontal well is on average about 1.8 m below ground surface, 

varying from up to 2.5 m at the southwestern end (Zone V and VI) to 1.1 m at the northwestern end 

(Zone I). On average, the horizontal well is about 0.5–1 m below the water table (also see Section 

5.1). The scale and CO2 release rates were chosen to be representative of possible leakage rates 

from large-scale CO2 storage projects. Controlled releases of CO2 were performed in the summers 

of 2007 and 2008. A wide variety of detection techniques were deployed by various collaborators to 

determine the efficacy of monitoring strategies, and to better understand transport from the 

saturated zone to the vadose zone and ultimately to the atmosphere (Spangler et al., 2009). This 

report focuses primarily on the geochemical and hydrological results of shallow CO2 injection into 

the groundwater at the ZERT site, based on the groundwater samples and other relevant data 

obtained in the 2008 release experiment (Kharaka et al., 2009a). Details on other aspects of the 

project can be found in Spangler et al. (2009). 
8 

Figure 2.1. Packer system installed in horizontal well (from Spangler et al., 2009). 

2.1. Regional and local setting 

The ZERT field site is located on a relatively flat 12 hectare agricultural plot at the western edge of 

the MSU-Bozeman campus in Bozeman, Montana, USA (see Spangler et al., 2009, for description 

of regional setting, and the various investigations completed or currently ongoing at this site). Plant 

coverage is about 70% grasses with the remainder being alfalfa, clover, dandelion, and thistle. 

The ZERT site is located at an elevation of 1,495 m near the southeastern boundary of the Gallatin 

Valley, which is a north-south-trending intermontane basin of about 1,350 km2

 in area (Kendy and 

Tresch, 1996). Structurally, the Gallatin Valley is an eastward tilted graben, a broad alluvial plain 

filled with up to 1,800 m of poorly consolidated Cenozoic sandy gravel deposits. At the ZERT site, 

about a meter of silts and clays with a top soil layer of variable thickness overlie the sandy gravel. 

Test pits and cores collected from several locations on the field consistently revealed two distinct 

soil zones. The topsoil of organic silt and clay with some sand ranges in thickness from 0.2 to 1.2 

m. A caliche layer, high in calcite and clay, is observed at depths of ~50–80 cm, but only small 

traces of carbonate are observed in fines above 2.5 m and in megascopic detrital carbonate. Beneath 

the topsoil layer is a cohesionless deposit of sandy gravel extending to 5 m, the maximum depth 

investigated (Spangler et al., 2009). More information on core analysis and local mineralogy is 

given in Section 4. 
9 

2.2. Geology 

The Gallatin Valley basement and surrounding mountains consist of complexly folded and faulted 

Tertiary through Archean bedrock.The eastern boundary of this valley is a series of steep normal 

faults along the fronts of the Bridger and Gallatin Ranges. The Gallatin Range, which borders the 

south margin and crests above 3,000 m elevation, provides source material to the basin-fill deposits 

in the portion of the Gallatin Valley which includes the ZERT field site. 

The basin-fill deposits are subdivided by Kendy (2001) into three hydrogeologic units: Quaternary 

alluvium (Qal), Quaternary and Tertiary undifferentiated deposits (QTd), and Tertiary Bozeman 

group (Tb). The Tertiary Bozeman Group is considered to underlie the entire Gallatin Valley; it 

outcrops as pediments on the Madison Plateau and benches east of Bozeman, but it is mostly 

covered by a veneer of Quaternary and/or Tertiary alluvium. Quaternary and Tertiary 

undifferentiated deposits consists of unconsolidated Quaternary alluvial-fan deposits overlying 

Tertiary sedimentary pediments. Alluvial fan deposits extend into the Gallatin Valley from the 

Bridger and Gallatin Range fronts and consist of a heterogeneous mixture of unconsolidated poorly 

sorted rock fragments in a sand, silt and clay matrix with some carbonate cement (Kendy and 

Tresch, 1996; Lonn and English, 2002). The largest of these alluvial fans, extends northwards from 

the Gallatin Range front into the alluvial plain between Hyalite and Bozeman Creeks. The city of 

Bozeman and much of the surrounding land, including the ZERT field site, is located on this 

alluvial fan and is mapped, in Kendy (2001) as Quaternary and Tertiary undifferentiated deposit 

(Qtd). 

The Gallatin Range provides the source material for the alluvial fan deposits in and around the 

ZERT site. The bedrock geology for the Gallatin Range is grouped by Kendy (2001) into four 

hydrogeologic units: (1) Tertiary (Eocene) volcanic rocks (Tv), which include andesite and basalt 

flows, breccia, agglomerate, and tuff of the Gallatin-Absaroka Volcanics; (2) Tertiary through 

Middle Proterozoic sedimentary bedrock (Tysaq), which include a number of sandstone and 

limestone formations, and the Middle Proterozoic Belt Supergroup. Sandstone, conglomerate, and 

limestone predominate the lithologies; (3) Cretaceous through Cambrian sedimentary bedrock 

(KCscu), in which fine-grained sandstone, shale, mudstone, siltstone, and chert predominate the 

lithologies; (4) Archean metamorphic rocks (Am), which consists of crystalline rocks, mainly 

biotite gneiss, with some schist, quartzite, and marble. Tertiary volcanic rocks (Tv) and Archean 

metamorphic rocks (Am) predominate in the Gallatin Range and appear to be the major rock 

lithologies in poorly to moderately sorted sand and gravel at the ZERT field site. 

2.3. Test Configuration and Groundwater Flow 

Five pairs of polyvinyl chloride (PVC) groundwater monitoring wells, 5 cm in diameter and 

extending to depths of about 1.5 m (B-wells) and about 3.0 m (A-wells) below ground surface, were 

installed in the summer of 2007. These were emplaced at the southwestern end of the slotted section 

of the horizontal CO2 injection pipe (zone 6) to measure changes in the chemical composition of 

shallow groundwater and head-space gas, following CO2 injection (Figure 2.2). The wells are 

screened at the bottom 0.76 cm, and are located at distances ranging from 1 to 6 m from the 

horizontal CO2 injection well. Comparison of the elevation of the horizontal injection well in zone 6 

with the screening depth of the groundwater wells reveals that the CO2 injection occurs 
10 

approximately 0.26 to 0.33 m above the top of the screening interval in the deep A-wells, and about 

0.50 to 0.60 m below the bottom of the screening interval in the shallow B-wells (see schematic in 

Figure 5.1). 

The groundwater hydraulic gradient and flow direction were estimated to be 17 degrees west of 

north (Figure 2.2). Four of the monitoring well pairs were installed north of the horizontal injection 

well (2A/B, 3A/B, 4A/B, and 5A/B) in the downgradient groundwater flow direction; one pair 

(1A/B) was installed south or hydraulically upgradient (Figure 2.2) from the horizontal well. In 

December 2008, three additional monitoring wells were installed (W6, W7, and W8), primarily to 

obtain core for mineral characterization and laboratory experiments. Well W6 is 2.6 m deep with 

the bottom 0.76 m screened. Wells W7 and W8 are 3 m deep with the bottom 1.5 m screened. Four 

additional water wells in the area have been used to estimate groundwater flow gradients and 

direction (MW1 through MW4); however, these wells are too far away from the injection well to be 

affected by CO2 injection. 

The depth of the water table at the ZERT field site is close to the ground surface, but varies 

seasonally. Spangler et al. (2009) report a variation of about 1 m in the depth of the water table over 

the last two and a half years. In the summers of 2007 and 2008, the depth of the water table 

measured in the water monitoring wells in zone 6 ranged from approximately 1.35 m to slightly 

more than 1.5 below ground surface, indicating that the shallow wells were just deep enough to 

collect water samples. Percolation tests made in 2006 yielded hydraulic conductivity values 

approximately 0.76 and 1.4 m/day in the upper soil (sandy silt) layer and in the sand-gravel aquifer, 

respectively. Results of tracer tests conducted in 2009 showed the lateral groundwater flow is high 

at about 2 m/day, and higher than previously estimated (Spangler et al., 2009). Calculated rates of 

CO2 diffusion and advection in the unsaturated zone are at least an order of magnitude higher than 

the groundwater flow rate (Lewicki et al., 2007; Lewicki et al., 2009). Also, analyses of gas samples 

obtained from the head space of the wells yielded P(CO2) values as high as 0.95 bar relatively 

rapidly (Strazisar, 2009; Strazisar et al., 2009). These data indicate that the rapid and systematic 

changes observed in the chemical composition of groundwater are likely driven by both fast 

spreading of gaseous CO2 in the sand-gravel unsaturated zone under the upper soil layer, 

accompanied by re-dissolution into the groundwater, as well as by the transport of dissolved CO2 in 

the groundwater (see also Section 5.1). 
11 

5B 10m

5A

W6

W7

W8

1A

2A

3A

4A 4B

3B

2B

1B

(-3,1)

groundwater

gradient

(-3,0)

17°

N

(-4,0)

Horizontal 

well

(-4,-1)

Monitoring Wells

Depth = 3 m

Depth = 1.5 m

Installed 2008 

Depth ~ 3 m

Gridpoints (10m)

5B 10m

5A

W6

W7

W8

1A

2A

3A

4A 4B

3B

2B

1B

(-3,1)

groundwater

gradient

(-3,0)

17°

N

(-4,0)

Horizontal 

well

(-4,-1)

Monitoring Wells

Depth = 3 m

Depth = 1.5 m

Installed 2008 

Depth ~ 3 m

Gridpoints (10m)

Monitoring Wells

Depth = 3 m

Depth = 1.5 m

Installed 2008 

Depth ~ 3 m

Gridpoints (10m)

Monitoring Wells

Depth = 3 m

Depth = 1.5 m

Installed 2008 

Depth ~ 3 m

Gridpoints (10m)

Figure 2.2. Location of water monitoring wells in relation to the surface trace of the slotted horizontal CO2

injection pipe in zone 6 of the ZERT site. The gridpoints in the figure refer to a grid with 10 m spacing 

that was established to provide a common reference system for researchers. 

2.4. Water Sampling and Analysis 

Most of the water samples for this study were obtained from the shallow groundwater wells (1.5 m 

deep). The water from the deeper wells was not significantly impacted by the injected CO2, likely 

because these are screened between 0.26 and 0.33 m below the level of the injection pipe. Sample 

collection, preservation, and field and laboratory chemical analyses of water and some relevant 

isotopes were carried out by methods described in Kharaka and Hanor (2007). Groundwater 

samples were collected using a peristaltic pump after purging the well by collecting 0.5–1 L aliquot 

that was used for rinsing the sampling containers. On-site chemical analyses of groundwater 

samples, carried out in a USGS mobile laboratory, included measurements of pH, Eh, conductivity, 

alkalinity, dissolved oxygen (DO) and temperature. Sample filtration, acidification, and 

preservation were also carried out in the USGS field laboratory. Groundwater samples for metal 

analysis were filtered using a 0.1 micron filter, then acidified using ultrex HNO3 and kept in a 

refrigerator and shipped on ice to the USGS laboratory in Menlo Park, California. 

Laboratory analyses for cations and metals were evaluated by comprehensive inductively coupled 

plasma mass spectrometry (ICP-MS), with focus on concentrations of various trace elements, 

including As, B, Cd, Cr, Cu, Fe, Hg, Mn, Pb, Se, U, and Zn. Sophisticated ICP-MS equipment was 

necessary because these elements of interest have very low background concentrations in the site 

groundwater, often close to the detection limits. Major and minor anions were determined in USGS 

laboratory by ion chromatography (IC). Benzene, toluene, ethyl-benzene, m-, p- and o-xylene 

(BTEX) were analyzed using an SRI-8610C gas chromatograph as described in EPA Method 
12 

5030C, a purge-and-trap procedure for the analysis of low levels of volatile organic compounds 

(VOCs) in aqueous samples and water miscible liquid samples. The gas chromatographic 

determinative steps are found in EPA methods 8015 and 8021 (US EPA, 2003). 

3. WATER SAMPLING RESULTS 

Detailed chemical analyses of over 60 groundwater samples collected from the ZERT wells in July–

August 2008 have been completed. Most of the samples analyzed are from four of the five shallow 

1.5 m deep “B” wells; results from Well 3B are incomplete because we were unable to obtain 

adequate volumes of water for our analytical requirements, as water recovery in this well was 

generally slow. The chemical data obtained for the samples are listed in Appendix A. The chemical 

composition of water obtained from the 3 m-deep “A” wells are similar to those listed for sample Z109 (Table A1), collected prior to CO2 injection in Well 2B, and remained relatively unchanged 

following CO2 injection primarily because their perforations are located below the CO2 injection 

pipe. 

The major cations and anions listed in Appendix A and plotted in the included figures carry 

analytical uncertainties of approximately ±3%. The uncertainties are ±5% for trace metals, and 

these may be more than ±10% for trace metals that are close to their detection limits. For sample 

collection, preservation, analysis, and uncertainties applicable to these results, see Kharaka and 

Hanor (2007) and references therein. 

Sample collection started in July 7, 2008, before the CO2 injection, which began at 15:45 on July 9, 

2008. Injection was continuous, except for a few short intervals when it was interrupted for various 

reasons. CO2 injection ended on August 7, 2008, but water sample-collection continued through 

August 14, 2008. During the sampling period, there were several relatively large rainfall events that 

impacted the chemical composition of the groundwater and raised the groundwater levels in the 

wells (Figure 3.1). On the other hand, groundwater levels fell as a result of either drainage or evapotranspiration and water sampling (Figure 3.1). 
13 

1493.94

1493.98

1494.02

1494.06

1494.10

1494.14

1494.18

1494.22

1494.26

1494.30

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Water level (m above mean sea level)

0

1

2

3

4

5

6

7

8

9

Cumulative precipitation (cm)

 1B

 2B

 4B

 5B

0.3 cm

2.4 cm

0.26 cm

2.8 cm

0.26 cm 0.56 cm

1.6 cm

CO2 start

(7/9 15:45)

CO2 stop

(8/7 10:00)

1493.94

1493.98

1494.02

1494.06

1494.10

1494.14

1494.18

1494.22

1494.26

1494.30

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Water level (m above mean sea level)

0

1

2

3

4

5

6

7

8

9

Cumulative precipitation (cm)

 1B

 2B

 4B

 5B

0.3 cm

2.4 cm

0.26 cm

2.8 cm

0.26 cm 0.56 cm

1.6 cm

1493.94

1493.98

1494.02

1494.06

1494.10

1494.14

1494.18

1494.22

1494.26

1494.30

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Water level (m above mean sea level)

0

1

2

3

4

5

6

7

8

9

Cumulative precipitation (cm)

 1B

 2B

 4B

 5B

0.3 cm

2.4 cm

0.26 cm

2.8 cm

0.26 cm 0.56 cm

1.6 cm

1493.94

1493.98

1494.02

1494.06

1494.10

1494.14

1494.18

1494.22

1494.26

1494.30

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Water level (m above mean sea level)

0

1

2

3

4

5

6

7

8

9

Cumulative precipitation (cm)

 1B

 2B

 4B

 5B

0.3 cm

2.4 cm

0.26 cm

2.8 cm

0.26 cm 0.56 cm

1.6 cm

CO2 start

(7/9 15:45)

CO2 stop

(8/7 10:00)

Figure 3.1. Cumulative precipitation and groundwater levels in selected ZERT wells during the sampling period in 

2008. 

3.1. Dissolved Inorganic Chemicals 

The chemical data obtained for samples from shallow and deep wells prior to CO2 injection show 

that the groundwater in the area is a Ca-Mg-Na-HCO3 type water, with a fresh water salinity of 

about 600 mg/L TDS (Figure 3.2; Sample Z- 109 in Table A1). The groundwater has a pH of 

approximately 7, and HCO3 is the dominant anion. The concentrations of Cl and SO4 are relatively 

low. The initial concentrations of Fe, Mn, Zn, Pb, and other trace metals are at ppb levels, which is 

typical of shallow groundwaters in regions of moderate precipitation. 

Following CO2 injection, the pH of groundwater decreased systematically to values around 6.0 at 

wells 1B, 2B, and 5B, all in close proximity to the injection pipe, strongly responding within one 

day. The strongest early response occurred in Well 2B, only 1 m from the injection pipe and in the 

direction of groundwater flow, decreasing to a pH of 5.7 (Figure 3.3a). The pH of water for samples 

from Well 4B (6 m from pipe) started decreasing only after three days following CO2 injection, but 

pH values remained above pH 6.0 (Figure 3.3a). The pH in all wells started increasing towards 6.5 

after CO2 injection was terminated on August 7, 2008. The measured pH values of groundwater 

were controlled primarily by P(CO2), which was measured by Strazisar et al. (2009) in capped 

wells, and was computed with SOLMINEQ (Kharaka et al., 1988) using the measured temperature, 

pH, alkalinity, and other chemical parameters. The P(CO2) values measured and computed for the 

ZERT samples were 0.035 bar before CO2 injection; they increased to values close to 1.0 bar 

following CO2 injection. It is evident from these results that pH is an excellent early indicator for 

detection of CO2 intrusion into groundwater. 
14 

100 75 50 25 0 25 50 75 100

Well 2B [08-109]

(pre-injection)

100 75 50 25 0 25 50 75 100

pH = 5.96; TDS = 1514 mg/L

pH = 7.04; TDS = 614 mg/L

Cl

Cl

SO4

HCO3

HCO3

SO4

Mg

Mg

Ca

Na

Ca

Na

Well 2B [08-146]

(post-injection; T = 339hr)

Figure 3.2. Modified Stiff diagrams showing concentrations (equivalent units normalized to 100%) of major cations 

and anions, together with salinity and pH of groundwater from well 2B before and during CO2 injection. 

The alkalinity of groundwater increased from about 400 mg/L as HCO3 to values higher than 1,300 

mg/L, following CO2 injection (Figure 3.3b). Alkalinity values for different wells, as with the pH 

values, show variable trends reflecting distance from the CO2 injection pipe, impacts from 

precipitation events, and possibly local variations in the mineral composition of soils and sediments. 

Given the reasonable assumption that the initial groundwater composition for Well 5B was similar 

to the average background composition at the site, the alkalinity values for this well and Well 2B 

increase first and show the highest alkalinities (up to 1330 mg/L). The alkalinity values in Well 4B, 

which is furthest away from the injection well, increase more slowly and only to about 700 mg/L. 

The alkalinities in all wells decrease to values approaching 400 mg/L after termination of CO2

injection (Figure 3.3b). 

Values for the electrical conductance, also measured at the site, show similar trends to alkalinity, 

increasing from ~600 μS/cm before CO2 injection to approximately 1800 μS/cm following CO2

injection (Figure 3.3c). Assuming that the electrical conductivity of the groundwater in Well 5B 

was initially similar to the average background value at the site, the conductance values for wells 

1B, 2B, and 5B increase first and show the highest conductance. Conductance values for Well 4B 

increase more slowly and only to about 1,100 μS/cm. All conductance measurements decrease to 

values approaching 600 μS/cm after termination of CO2 injection on August 7, 2008 (Figure 3.3c). 
15 

5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

pH

1B

2B

4B

5B

CO2 start CO2 stop

200

400

600

800

1000

1200

1400

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Alkalinity, as HCO3 ( mg/L )

1B

2B

4B

5B

CO2 start CO2 stop

400

600

800

1000

1200

1400

1600

1800

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Electrical conductance ( S/cm )

1B

2B

4B

5B

CO CO2 stop 2 start

(c)

(b)

(a) 5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

pH

1B

2B

4B

5B

CO2 start CO2 stop

200

400

600

800

1000

1200

1400

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Alkalinity, as HCO3 ( mg/L )

1B

2B

4B

5B

CO2 start CO2 stop

400

600

800

1000

1200

1400

1600

1800

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Electrical conductance ( S/cm )

1B

2B

4B

5B

CO CO2 stop 2 start

5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

pH

1B

2B

4B

5B

CO2 start CO2 stop

5.4

5.6

5.8

6.0

6.2

6.4

6.6

6.8

7.0

7.2

7.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

pH

1B

2B

4B

5B

CO2 start CO2 stop

200

400

600

800

1000

1200

1400

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Alkalinity, as HCO3 ( mg/L )

1B

2B

4B

5B

CO2 start CO2 stop

200

400

600

800

1000

1200

1400

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Alkalinity, as HCO3 ( mg/L )

1B

2B

4B

5B

CO2 start CO2 stop

400

600

800

1000

1200

1400

1600

1800

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Electrical conductance ( S/cm )

1B

2B

4B

5B

CO CO2 stop 2 start

400

600

800

1000

1200

1400

1600

1800

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Electrical conductance ( S/cm )

1B

2B

4B

5B

CO CO2 stop 2 start

(c)

(b)

(a)

Figure 3.3. Field- measured groundwater pH values (a), alkalinities (b), and electrical conductance (c), obtained 

from selected ZERT wells as a function of time of sampling. Note the systematic decrease in pH values 

from ~7.0 before CO2 injection to values as low as 5.6 during injection, and subsequent pH increases 

after CO2 injection ended. Alkalinities increased from about 400 mg/L before CO2 injection to values 

close to 1200 mg/L as HCO3, and electrical conductance also increased from about 600 μS/cm before 

CO2 injection to values higher than 1,600 μS/cm during injection. 

The alkalinity increases following CO2 injection are balanced primarily by increases in the 

concentrations of Ca and Mg, whereas the concentrations of Na (10 ±2 mg/L) are relatively constant 

(Figure 3.4). The molar and atomic concentrations of Ca increase the most, with atomic values for 

Ca increasing from about 80 mg/L to up to 240 mg/L, and those for Mg increasing from about 25 

mg/L to up to 70 mg/L (Figure 3.4). In Section 4.2, we report the presence of calcite throughout the 

sampled sediment column, as well as a small fraction of detrital limestone and dolomite. The 

presence of these carbonate minerals could explain increases of Ca and Mg upon dissolution. 

However, atomic Ca/Mg ratios obtained initially and following CO2 injection (Figure 3.5) cannot be 
16 

explained by dissolution of dolomite alone; the values, increasing from 3.2 to 6.1 for Well 2B, 

indicate that dissolution of calcite is dominant, but that dissolution of both calcite and dolomite (or 

Mg-rich calcite) are required to explain the changes in alkalinity and concentrations of Ca and Mg 

(Figure 3.5, Table A1). Dissolution of calcite (reaction 3-1) and dolomite (reaction 3-2) can be 

represented by the following reactions: 

CO2(g) + H2O + CaCO3(s) = Ca2+ + 2HCO3

-

 (3-1) 

2H+ + CaMg(CO3)2(s) = Ca2+ + Mg2+ + 2HCO3

-

 (3-2) 

These conclusions are supported by the initial characterization of minerals in core samples that 

show that calcite is abundant in a caliche layer observed at depths of ~50-80 cm. Small amounts of 

carbonates (~2% detrital limestone and calcite coatings on grains) were also observed in gravels 

below the caliche layer (Section 4.2). Results of geochemical modeling with an updated 

SOLMINEQ (Kharaka et al., 1988) support dissolution of calcite and disordered dolomite as 

possible reactions at all pH values; also, groundwater is undersaturated with respect to dolomite at 

the lowered pH values obtained following CO2 injection, allowing for its dissolution. Desorptionion exchange reactions on clay minerals with H+

 are also suggested as an alternative and/or 

additional mechanism leading to increases in the concentrations of Ca, Mg, and other dissolved 

species, as discussed further in Sections 5.2 and 5.3 

0

50

100

150

200

250

300 400 500 600 700 800 900 1000 1100 1200

Alkalinity, as HCO3 (mg/L)

Ca, Mg, Na, K Concentration (mg/L)

0.0

0.2

0.4

0.6

0.8

1.0

Sr, Ba Concentration (mg/L)

 Ca

 Mg

 Na

 K

 Sr

 Ba

Figure 3.4 Concentrations of major cations in groundwater from the ZERT wells plotted as a function of water 

alkalinities. Note the relatively constant concentrations of Na and K, but the general increases in the 

concentrations of divalent cations with water alkalinities, possibly indicating dissolution of carbonate 

minerals. 
17 

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Ca/Mg (weight ratio)

1B

2B

4B

5B

A wells

CO2 start CO2 stop 2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Ca/Mg (weight ratio)

1B

2B

4B

5B

A wells

CO2 start CO2 stop

Figure 3.5 Ca/Mg weight ratios plotted as a function of time of sampling. Note that the ratios are higher than the 

value expected from dissolution of dolomite (1.6), and are relatively constant for well 4B, but continue 

to increase for well 2B until CO2 injection was terminated, possibly indicating dissolution of calcite. 

The concentrations of Fe and Mn, the two most abundant trace metals in groundwater, also increase 

following CO2 injection (Figure 3.6). The concentrations of Fe in groundwater could increase from 

dissolution of Fe(II) and Fe(III) minerals. These potentially include Fe (hydr)oxides such as 

ferrihydite and green rust (see Section 5.2), which are likely to be present from the oxidation of 

primary phases such as magnetite and biotite, observed in the sediments (Section 4.2). Dissolution 

of siderite would also result in increased Fe concentrations. However, thermodynamic evaluations 

(Section 5.2) indicate the groundwater to be quite undersaturated with respect to this mineral, 

suggesting it is not likely to be present, except potentially as a detrital phase. Example dissolution 

reactions include: 

Fe(OH)3(s) + 3H+

 = Fe3+ + 3H2O (3-3) 

4FeOOH(s) + 8H+

 = 4Fe2+ + 6H2O +O2 (3-4) 

4Fe(OH)3 + CH2O + 8H+ ==> H2CO3 + 4Fe+2 + 10H2O (3-5) 

Fe(CO3)(s) + H+

 = Fe2+ + HCO3

-

 , (3-6) 

where CH2O is a generic representation of dissolved (and particulate) organic matter. The 

concentrations of Fe in groundwater are a strong function of Eh, which could only be measured in 

water from the deep wells that were not impacted by CO2 injection, because shallow wells did not 

yield enough water volume. The Eh values obtained (150 to 200 mV; pe ~ 2.5–3.5) indicate suboxic 

conditions that account for the low concentration of dissolved Fe; much higher Fe values are 

possible under more reducing conditions because of the higher solubility of Fe(II) minerals (Hem, 

1985). Note that Eh measurements may be of limited use, as discussed in Section 5.2. The Fe 

concentrations (Figure 3.6a) increase from 5 to 1200 ppb, but show very low values during July 20 

to July 26 following significant rainfall events (Figure 3.1) even when pH values were low. Dilution 

alone cannot explain the low Fe concentrations during July 20 to July 26, but the low values could 

be attributed to more oxic conditions, possibly caused by increased dissolved O2 content in 
18 

groundwater transported with percolating water from rainfall events. Ion exchange reactions on 

clays with H+

 and major dissolved cations, such as Ca, Mg, and Na, are other possible controls on 

Fe concentrations, as discussed in Sections 5.2 and 5.3. 

The concentrations of Mn show similar trends to those of Fe, increasing from 5 to 1400 ppb 

following CO2 injection, but also show low values during July 20 to July 26 (Figure 3.6b). 

Dissolution and redox reactions can be written for Mn as for Fe above. It should be noted that Mn 

concentrations are higher for Well 4B than for 2B and 5B, and this may be controlled by local 

mineral compositions. 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Concentration (mg/L)

1B

2B

4B

5B

A wells

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Concentration (mg/L)

(a) Fe

(b) Mn

CO2 start

CO2 stop

CO2 start

CO2 stop

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Concentration (mg/L)

1B

2B

4B

5B

A wells

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

Concentration (mg/L)

(a) Fe

(b) Mn

CO2 start

CO2 stop

CO2 start

CO2 stop

CO2 start

CO2 stop

CO2 start

CO2 stop

Figure 3.6 Concentrations of Fe (a) and Mn (b) in groundwater from selected ZERT wells plotted as a function of 

time of sampling. Note the low Fe and Mn concentrations during July 20 to July 26, which we are 

attributing to the oxidizing conditions possibly caused by percolating oxygenated water from rainfall 

events (see Figure 3.1). 

The concentrations of Pb, As, Zn, and other trace metals (Table A1 and Figure 3.7) generally show 

an increase with increasing alkalinity (lower pH value) following CO2 injection. The values 

reported, however, carry high uncertainties (10–50% analytical error) as they are, in some cases, 

close to the analytical detection limits, especially with the required dilutions (up to 5 fold) prior to 

analyses. The concentration increases are likely caused by desorption-ion exchange reactions with 

H+

, Ca, and Mg resulting from lowered pH values (see Section 5). Because measured H2S values 

were below our detection limit (0.2 mg/L), we are unable to use geochemical modeling to check for 

solubility of sulfide minerals as controls on metal concentrations. The concentrations, it should be 

noted, are all significantly below the maximum contaminant levels (MCLs) for the respective trace 

metals (e.g., 15 ppb for Pb, 6 ppb for As). The initial values and the increases in concentrations of 

these trace metals, although small, are readily measured by the sampling and analytical methods 
19 

used in this study. These results highlight the role of geochemical tools for early detection of CO2

leakage into groundwater. 

0.01

0.10

1.00

10.00

300 400 500 600 700 800 900 1000 1100 1200

Alkalinity, as HCO3 (mg/L)

Concentration ( g/L )

As Cu Zn Cd Pb Al Se

Figure 3.7 Trace metal concentrations in groundwater from selected ZERT wells plotted as a function of water 

alkalinities. Some of the scatter shown probably results because the reported values in some cases are 

close to the detection limits. 

The chemical changes observed in the ZERT groundwater are similar in trends, though much lower 

in concentrations, to the changes observed in the Frio Brine Pilot test, near Houston, where 1600 t 

of CO2 were injected at 1500 m depth into a 24 m thick “C” sandstone unit of the Frio Formation 

(Freifeld et al., 2005; Hovorka et al., 2006; Kharaka et al., 2006). Following CO2 breakthrough, 51 

hours after injection, Frio samples showed sharp drops in pH (6.5 to 5.5 measured at ground 

surface), pronounced increases in alkalinity (100 to 3000 mg/L as HCO3) and in Fe (30 to 1100 

mg/L), a slug of very high DOC values, and significant shifts in the isotopic compositions of H2O, 

DIC, and CH4. These data, coupled with geochemical modeling, indicated rapid dissolution of 

minerals, especially calcite and iron oxyhydroxides, both caused by lowered pH (initially ~3.0 at 

subsurface conditions) of the brine in contact with supercritical CO2 (Kharaka et al., 2009b). The 

differences between results from Frio and ZERT tests are related to several geochemical 

parameters, but the most important reason relates to the difference in subsurface P(CO2) value, 

which was approximately 150 bar at Frio (Kharaka et al., 2009b), while P(CO2) values at ZERT 

measured (Strazisar, 2009; Strazisar et al., 2009) and computed with SOLMINEQ (Kharaka et al., 

1988) ranged from 0.035 to ~1 bar. The amount of CO2 dissolved in water is a function of fluid 

pressure, temperature and salinity. The CO2 solubility increases at higher pressures, but decreases 

at higher (moderate) temperatures and salinities. In the present case, the large difference in pressure 

between the ZERT and Frio sites has a stronger effect than differences in temperature and salinity 

between the two sites. Thus, in a shallow aquifer such as that at the ZERT site, much less CO2 can 

dissolve in the groundwater compared to the amount that can dissolve in deep pressurized formation 

waters such as at the Frio site. Therefore, the CO2-induced decrease in groundwater pH will be less 

pronounced, and thus the corresponding change in dissolved groundwater constituents will also be 

less. Consequently, trace metal mobilization from solids is expected to be less pronounced at 

shallow sites such as ZERT. 
20 

3.2. Dissolved Organic Chemicals 

Dissolved organic carbon (DOC) values obtained in this study are generally about 4 mg/L, with a 

variation range from 2.6 to 6.9 mg/L, and these variations do not seem related to CO2 injection. 

Concentrations of benzene, toluene, ethyl-benzene, m-, p- and o-xylene (BTEX) were determined in 

a relatively large number of samples collected when it became clear that the injection of CO2 was 

likely responsible for very small but systematic increases in the concentrations of dissolved BTEX 

compounds (up to ~1.6 μg/L for m-, p-xylene), as depicted in Figure 3.8. It should be noted that the 

concentrations are all below the maximum contaminant levels (MCLs) for the respective BTEX 

compounds (5 ppb for benzene). There is some scatter in the results, but the concentrations are 

about 0.2 μg/L before CO2 injection, increasing to values greater than 1.0 μg/L for m-, p-xylene and 

o-xylene, and to about 1.0 and 0.8 μg/L for toluene and benzene, respectively. The measured values 

are higher in water from Wells 1B (Figure 3.8a) and 2B (Figure 3.8b) relative to Well 4B, which is 

farther away from the injection pipe (Figure 3.8c). All the measured BTEX values decrease to a 

value approaching pre-injection (~0.2 μg/L) after termination of CO2 injection on August 7, 2008 

(Figure 3.8d). 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

(c) well 4B (d) all wells

(a) well 1B (b) well 2B

Concentration ( g/L )

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

 benzene

 toluene

 ethyl-benzene

 m-p-xylene

 o-xylene

Concentration ( g/L )

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

CO2 start CO2 stop CO2 start CO2 stop

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

(c) well 4B (d) all wells

(a) well 1B (b) well 2B

Concentration ( g/L )

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

 benzene

 toluene

 ethyl-benzene

 m-p-xylene

 o-xylene

Concentration ( g/L )

7/7 7/10 7/13 7/16 7/19 7/22 7/25 7/28 7/31 8/3 8/6 8/9 8/12 8/15

CO2 start CO2 stop CO2 start CO2 stop

Figure 3.8 Concentrations of BTEX compounds detected in groundwater from selected ZERT wells plotted as a 

function of time of sampling. The BTEX concentrations are all significantly below the maximum 

contaminant levels (MCLs) (e.g., 5 ppb for benzene). 

The origin of the low amounts of BTEX compounds detected in groundwater following CO2

injection was investigated during 2008, and more recently in 2009. Three main possible sources 

were examined: (1) A natural source from deep organic matter or a petroleum source; (2) 
21 

contamination from a surface source or when installing the injection pipe and groundwater wells; or 

(3) contamination with trace amounts of BTEX in the injected CO2, although the gas used was foodgrade quality. Our initial results obtained in 2008 were inconclusive with regard to the injected CO2

being the source of the observed BTEX. We analyzed core samples obtained from wells drilled in 

December 2008 for BTEX. Though progress was slow because results obtained were close to the 

detection limits of available analytical methods, results showed that BTEX concentrations were 

below detection limits. Thus, natural sources were eliminated as a possibility for the observed 

concentration increases. Purge-and-trap analysis of CO2 samples collected from the injection source 

tank in 2009 showed conclusively that the injected CO2 (though food-grade) contained a very small 

amount of organic chemicals and thus was identified as the source of the trace concentrations of 

detected BTEX (Kharaka et al., 2009b). Our results indicate that BTEX compounds can be detected 

in groundwater at extremely low concentrations, below MCL levels. 

4. MINERALOGICAL DATA 

4.1. Core Analysis and Methods 

Three wells were installed in December 2008 to obtain core for mineral characterization and 

laboratory experiments. Well W6 is 2.6 m deep with the bottom 0.76 m screened. Wells W7 and 

W8 are 3 m deep with the bottom 1.5 m of the wells screened (Figure 2.2). Cores from these wells 

have been logged and sampled at different intervals for detailed mineralogical analysis. 

Approximately 20 samples have been collected from the cores for rock, mineral, and grain-size 

analysis, and 17 samples of these have been dry-sieved to 3 size fractions with grain-size diameters 

of (1) >9.5 mm (medium gravel +); (2) 9.5–2.0 mm (fine to very fine gravel), and (3) < 2 mm 

(coarse sand to clay/colloid). X-ray diffraction (XRD) work was completed with the primary goal of 

identifying carbonates and clays. Short exploratory sessions were conducted with a scanning 

electronic microscope (SEM), including some semi-quantitative chemical analysis using the 

Energy-Dispersive X-Ray (EDX) system on the SEM. The short summary given below focuses on 

ZERT Well W6, which is located in the main well field (Figure 2.2). A log for well W6 is given in 

Table B.1 in Appendix B. The grain size fraction for different zones in Well W6 is shown in Figure 

4.1. 

It should be noted that the cores were obtained by a “direct-push” geoprobe, using a 3-inch 

geoprobe system. The direct-push methodology creates a bias in the true grain-size distribution 

because the larger cobbles, which are abundant throughout the cored interval (even the top “A” soil 

horizon), are simply pushed out of the way. Large well-rounded cobbles exceeding 10 cm diameter 

exist in abundance throughout the cored interval. 
22 

ZERT - Well 6 (W6) grain-size distribution

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

123 4567

% of size fraction (normalized to 100%

< 2mm

2-9.5 mm

> 9.5 mm

“A” soil

20-25 cm “caliche”

50-55 cm

gravel

251-261 cm

gravel

177-184 cm gravel

245-251 cm

gravel

61-64 cm

gravel

107-118 cm

ZERT - Well 6 (W6) grain-size distribution

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

123 4567

% of size fraction (normalized to 100%

< 2mm

2-9.5 mm

> 9.5 mm

“A” soil

20-25 cm “caliche”

50-55 cm

gravel

251-261 cm

gravel

177-184 cm gravel

245-251 cm

gravel

61-64 cm

gravel

107-118 cm

Figure 4.1 Grain size fractions for different zones in Well W6. 

4.2. Mineralogical Results 

The cores have an organic-rich dark soil zone at the top (0 to ~40 cm), which grades into a light to 

medium gray “caliche” zone. The caliche zone is high in carbonate and clay, with lesser fine sand to 

fine silt (predominantly quartz, feldspar and white mica, and very minor volcanic rock fragments). 

Clay extracts from the caliche zone of W6 appear to be smectite. The carbonate mineral is calcite; 

however, the XRD pattern shows it is poorly crystallized, with a peak shift towards Mg-rich calcite. 

“A” soil horizon

The top 30-40 cm of each core consists of clay and organic-rich soil. The soil is generally brown, 

plastic, and matrix supported with some fine sand. The topsoil zone grades into a caliche layer that 

is ~20-40 cm thick. The mineralogy has not been studied in detail. XRD analysis performed on the 

clays from earlier auger core samples indicated chlorite; however, our study indicates the caliche 

clay is dominantly smectite. Some well-rounded pebbles, possibly volcanic andesite, are found in 

the top soil. 

Caliche or high carbonate zone

The caliche zone begins at ~40 cm, graded gently in color from dark brown topsoil to medium and 

light gray. The caliche zone is very fine-grained, with most material passing easily through 2 mm 

sieve (Figure 4.1). Unlike the caliche from a hand-augered core taken previously from other nearby 

wells (located at gridpoint -5,-3 on the reference grid), which was predominantly carbonate with 

lesser amounts of clay and fine sand, the caliche zone at Well 6 appears to be more clay and quartzdominated fine sand and silt, and less carbonate. The XRD scan of a bulk powder sample shows 

quartz and clay (smectite), with significant calcite and plagioclase, and minor but measureable 

kaolinite and mica. XRD results suggest that the main clay mineral is smectite (main 001 peak ~14 
23 

angstroms, with a shift to ~17 angstroms upon glycolation, and a slightly higher peak shift using 

glycerol). More work would be needed to describe the clays in more detail. An SEM stub was 

prepared with the caliche material; however, the carbonate and clay was so fine-grained and comingled that it was not possible to resolve the morphology of the crystals or to isolate grains for 

elemental analysis. Mica is readily identified in sieved samples from the caliche; it is predominantly 

white (muscovite) and lesser green mica. Mafic rock fragments are a very minor constituent of the 

caliche zone. 

Gravel zone

Below the caliche zone, the core changes rapidly to coarse gravel, with large pebbles up to the full 

diameter of the core (~6 cm), and gravel (> 2 mm) representing ~75% or more of the core. The 

gravel continues to the bottom of each 10 ft deep well. Megascopically, there are no obvious 

distinct zones. A total of 15 samples, ranging from ~150 to 400 grams, were collected from the 

gravel zones of the three wells (5 samples from W6; 4 samples from W7; 6 samples from W8). 

Because the gravel was so coarse, the entire diameter of the core was collected for each sample, 

from core intervals of ~5 to 10 cm. The grain size fractions for all 15 gravel samples analyzed from 

wells 6, 7, and 8 are plotted in Figure 4.2. 

ZERT - W6, W7, W8 "gravel zones" - grain-size distribution

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

% of size fraction (normalized to 100%)

< 2mm

2-9.5 mm

> 9.5 mm

Figure 4.2 Grain size fractions for 15 gravel samples analyzed from wells 6, 7, and 8. 

Overall, the gravel material can best be described as “extremely heterogeneous,” and it would be a 

significant task to identify all the rock types and minerals in this gravel. An approximate 

distribution of rock types in the gravel is presented below, with results from W6: 

 Approximately 60%–70% mafic/basic volcanic rocks, likely andesite (mostly aphantic, 

some small plagioclase laths). Usually subangular to subrounded habit, often with broken 

edges. Some volcanic fragments have a pale blue “oxidized” exterior, but when broken are 

fresh. XRD shows dominant mineral is Ca-Na plagioclase (albite to anorthite). Semi-
24 

quantitative SEM/EDX “spot scans” of several feldspars showed a wide range of Na to Ca. 

Include basalt and diabase in this group. Olivine was identified in some rocks using 

SEM/EDX. 

 ~20-30% quartz –biotite-+/-amphibole gneiss. Habit angular to subangular. 

 ~10% misc crystalline rocks, such as red granite/gneiss (with dark red potassium feldspar). 

Sub-angular. Likely rhyolite (pink-orange, subrounded), quartz-mica schist (angular). 

 ~2% limestone—described below. 

In general, the darker, denser aphanitic volcanic rocks dominate in the larger size fractions, often as 

well-rounded pebbles (up to 30 grams weight). A wide range plethora of rock types exist in the 

smaller size fractions (large sand to fine gravel size)—diabase, schists, granites, vesicular volcanics, 

rhyolite, and many exotic crystalline rocks, ranging from highly altered/weathered to fresh—that 

will take considerable some effort to identify. 

Most of the mafic volcanic rocks are highly magnetic, so that even rock fragments > 2 mm are 

easily separated with a 1-ounce horseshoe magnet. The XRD pattern of a separate of fine-grained 

magnetic material was determined to be magnetite. SEM/EDX spectra of several “Fe-rich” minerals 

in andesite showed iron and titanium (up to 7 atomic %). 

Limestone (in gravel)

Detrital limestone (not found in the core-catcher samples) is present in the gravel zone of Well 6, as 

a very small fraction of the total gravel. Of 97 hand-checked pebbles (~1 cm+ diameter) from the 

five W6 gravel samples, only 3 pebbles are limestone. Considered by weight, the 3 limestone 

pebbles total only 10.2 grams, from a total weight of 573 grams of is this size fraction. The 

limestone has a resemblance in color and texture to the Madison limestone; however, it appears 

even more fine-grained than the hand specimen we have of Madison Limestone. The conchoidal 

fracture and XRD pattern shows it to be well-crystallized calcite. Limestone is also present in the 2–

9.5 mm size-fraction, again in very small amounts (~2%). 

Carbonate

Calcite, primarily as a coating, is a common minor constituent throughout the gravel zone. Calcite 

also commonly occurs as crusts of secondary calcite on rounded rock surfaces, from small to 

medium pebbles. An XRD pattern of such a carbonate crust was determined to be well-crystallized 

calcite. All 94 noncarbonate pebbles from the > 9.5 mm size fraction had a carbonate coating and/or 

crust and reacted slightly-to-vigorously to dilute HCl. Likewise, all of the matrix samples (sieved 

and unsaved) reacted to HCl. Calcite also occurs throughout the matrix as very fine rounded grains, 

which dissolve in a few seconds in dilute HCl. We find no dolomite in the coarse fractions, although 

the 2–9.5 mm fraction would need further study. The finer size fractions likely contain some 

dolomite, identified as small rounded grains that fizz very slowly in 10% HCl (as opposed to 

calcite, which fizzes rapidly. Because the dolomite fractions are too small to appear in bulk XRD 

powders (generally ~5% by weight is needed), SEM or hand-picked grains would be necessary for 

positive identification. 
25 

Matrix minerals

In the progressively finer size fractions, minerals predominate over rock fragments and lighter 

minerals predominate over darker minerals. For minerals, quartz is dominant, followed by feldspar. 

Micas are abundant in all the size fractions, with muscovite more abundant in the finer sizes 

compared to biotite. Green and brown mica are also present (possibly chlorite, phlogopite). For the 

darker minerals, amphibole appears most abundant; pyroxene is not easily spotted in matrix, 

although common in some rock fragments. Magnetite is abundant. Carbonate, as a coating, and 

calcite as very small rounded grains are found throughout the gravel zone. Fe-oxides, as yet 

unidentified, are present in the matrix, both as fine coatings on other minerals (often quartz) and as 

small rounded and powdery grains. Some pistachio green epidote was observed on a pebble surface. 

Sulfides

No sulfide minerals have been identified in the matrix. Pyrite is rare in some rock fragments, 

typically on fresh surfaces. The SEM backscatter system was used on many rock grains to recognize 

sulfide minerals, but none were found in our samples. High Fe targets were usually found to be 

oxides, magnetite, or titaniferous magnetite. 

5. HYDROGEOLOGICAL AND GEOCHEMICAL INTERPRETATION 

 

The groundwater data collected to study the effect of CO2 injection on groundwater quality at the 

ZERT site was presented in Section 3. Here, the groundwater data collected during this study are 

evaluated in a more quantitative manner, in light of the site hydrogeology, its mineralogical 

characterization, and the various geochemical processes likely to result from CO2 dissolution in 

water. 

It should be remembered that this study was conducted in a shallow water-table aquifer, only a 

couple of meters below ground surface, at essentially atmospheric pressure, and thus under 

conditions that are not representative of deeper USDW. In addition, because of the thin vadose 

zone, recharge from rainfall events during the test (Figure 3.1) had a rapid and noticeable effect on 

groundwater composition trends, complicating data interpretation. Nevertheless, geochemical data 

collected during this study are quite useful to test some hypotheses regarding the effect of CO2

dissolution in groundwater, namely that the pH decrease and alkalinity increase accompanying CO2

dissolution in water are likely to drive dissolution and desorption/exchange reactions that could 

impact groundwater quality. These reactions would be expected to take place in any aquifer, 

although to a lesser extent in a shallow site such as ZERT compared to a deep USDW. This is 

because, as mentioned earlier, less CO2 can dissolve in water at low pressure than at high pressure, 

thus limiting the pH decrease and alkalinity increase (e.g., reaction 1-1) accompanying CO2

injection. Obviously, the geochemical response of an aquifer to CO2 dissolution also highly depends 

on the aquifer mineralogy, salinity, redox conditions, and initial (background) pH. Because these 

data are site-specific, results of analyses presented in this section should not be directly applied to 

other sites, except for illustrating the general type of reactions (and not their specific effect or 

magnitude) that could take place at other locations. 
26 

Section 5.1 summarizes what is known about CO2 transport in the subsurface at the ZERT site, to 

provide context for evaluating the water quality response to CO2 injection. In Section 5.2, statistical 

and thermodynamic analyses are presented to determine correlations between the concentrations of 

various species, and formulate hypotheses on the types of mechanisms likely responsible for 

observed concentration trends and groupings of certain species. Based in part on this information, 

geochemical modeling analyses are then presented in Section 5.3. The modeling incorporates 

processes (i.e., dissolution, sorption/desorption, and ion exchange) that are most likely to affect 

groundwater quality upon CO2 injection. Besides providing possible explanations for observed 

water quality changes at the ZERT site, the modeling also illustrates the types of coupled geochemical mechanisms that could affect groundwater quality in deeper USDW. 

 

5.1. Transport of CO2 in Gas and Aqueous Phases 

The transport of CO2 in the subsurface at the ZERT site (e.g., as gas phase in the vadose zone and 

dissolved in groundwater) is assessed in other parallel studies (Lewicki et al., 2007; Strazisar et al., 

2009; Oldenburg et al., 2009). As discussed in Section 2.3, groundwater flow velocities at the site 

may be up to 2 m/d, which is very high, and rates of CO2 transport in the unsaturated zone are 

estimated to be at least an order of magnitude higher. Therefore, the rapid and systematic changes 

observed in the chemical composition of groundwater at ZERT are likely driven by both the fast 

spreading of CO2 as gas phase in the sand-gravel unsaturated zone under the upper soil layer, 

followed by re-dissolution into the groundwater, as well as by transport of groundwater with 

dissolved CO2 (see schematic in Figure 5.1). Notice that in both transport scenarios, the deeper 

A-wells are not significantly affected by the injected CO2. Redissolution of gaseous CO2 is limited 

to a small layer at the soil-groundwater interface, while the flow of CO2-charged water from the 

injection well bypasses the A-wells, because the screening interval is too deep. 

The fast transport in the gas phase is directly supported by gas samples obtained from the head 

space of the groundwater wells. CO2 concentrations in wells 1B, 2B, and 5B increased up to about 

90% (by volume) only two days after injection started (Strazisar, 2009). These wells are all less 

than 2 m away from the injection pipe, with 5B actually located upstream (Strazisar et al., 2009). 

Well 3B about 3 m downstream arrives at 50% CO2 after about 5 days; Well 4B about 6 m 

downstream starts to respond after the same time period. Model results from Oldenburg et al. (2009) 

also indicate that gaseous CO2 spreads out fast through the vadose zone under the soil layer. It is 

thus quite certain that dissolution of CO2 from the vadose zone back into groundwater is a 

prominent process triggering the chemical changes measured in the groundwater samples. However, 

because the groundwater flow velocity is very high (up to 2 m/day), the transport of dissolved CO2

in groundwater cannot be ruled out as an additional main source of CO2 responsible for the 

groundwater quality changes, at least in the shallower wells located downstream from the injection 

pipe. Because uncertainties remain regarding gas and groundwater flow rates, recharge effects, and 

subsurface heterogeneity, no attempts were made, here, at modeling the reactive transport of CO2 in 

the subsurface. We focus instead solely on geochemical modeling of reactive processes, such that 

the transport specifics responsible for increased CO2 levels at monitored locations are not needed. 
27 

Figure 5.1 Schematic representation of CO2 transport in ZERT field site. The cross-section shown is along the axis 

of well pairs 1A/B, 2A/B, 3A/B, and 4A/B. 

5.2. Geochemical Response to CO2 Release and Interpretation 

The characterization of the geochemical response of groundwaters in the shallow phreatic zone at 

the ZERT site was undertaken in response to the opportunity afforded by an independent field 

program to evaluate phenomena associated with the atmospheric leakage of CO2 from underground 

storage sites. Both time and funding constraints limited the scope of the study, which was 

recognized at the outset as being exploratory in nature, and aimed at defining the relevant 

geochemical processes relating to CO2 contamination of subsurface potable water sources, rather 

than their quantification. This section discusses several steps undertaken to interpret chemical 

analyses of groundwaters from the ZERT site, in an effort to provide a framework for the 

geochemical modeling conducted in Section 5.3. 

The large number of species analyzed in groundwaters from the ZERT site, and their temporal 

variation, provides a basis for understanding the transient chemical processes operating in the 

phreatic zone near the water table and the overlying vadose zone. These processes include the 

following: 

 Dissolution of CO2 in the groundwater 

 Evaporative concentration 

 Infiltration of rainfall 

 Bacterial mineralization of organic matter with generation of CO2

 Oxidation/reduction 

 Ion exchange 
28 

 Adsorption 

 Mineral precipitation/dissolution 

The depression of pH due to CO2 uptake in the groundwater can induce dissolution of a number of 

primary and secondary minerals, and drive sorption/desorption and ion exchange reactions. The 

bicarbonate ion generated during CO2 dissolution can also compete with other species, such as the 

arsenate anion for adsorption. Fluctuations in the concentrations of oxidants and reductants, and the 

potential inhibition of bacterial activity by increasing concentrations of CO2, can likewise affect 

precipitation, ion exchange, and adsorption of those species that are subject to changes in oxidation 

state. The evaporation induced by the bubbling of CO2 through the groundwater, with concomitant 

removal of dissolved redox-sensitive gaseous species (e.g., O2, N2, CH4, and H2S), may disturb the 

oxidation state and also lead to evaporative concentration of nonvolatile species. Random periods of 

rainfall are likely to flush residual capillary waters from the overlying soil horizons of the vadose 

zone, which have been subject to evapotranspiration and modification by pedogenic processes. 

These vadose zone soil waters also contain the concentrated residues of dissolved species from 

earlier rainfall events. Bacterial oxidation of organic matter transported from the overlying soil zone 

in the dissolved or particulate state modifies the concentration of dissolved concentration of 

carbonate species in the groundwater and leads to elevated partial pressures of CO2 in the gaseous 

phase in the overlying vadose zone. Such bacterial activity also modifies the concentrations of 

nutrients in the groundwater and generates reductants that can likewise induce the reductive 

dissolution or precipitation of minerals in the saturated zone. Ion exchange can take place in more 

than one mineral. Adsorption characteristics also vary, depending on the nature of the mineral 

substrates, of which there may be several. 

The information available to help identify transient chemical processes in the saturated zone 

consists of some 60 comprehensive chemical analyses of groundwaters taken at intervals throughout 

the test, the temperature and electrical conductivity of the groundwaters samples, information on 

rainfall events, the height of the water table, and mineralogical analyses of core samples taken from 

a number of shallow boreholes (see Sections 2 to 4). In addition, data on the chemical composition 

of rainwater collected at two sites in Montana were downloaded from US EPA’s National Pollutant 

Discharge Elimination System (NPDES) web site to estimate contributions of dissolved species to 

the groundwater from that source. These data are evaluated below using Principal Component 

Analyses (PCA) to determine whether certain species correlate with each other, potentially 

indicating similar or coupled geochemical behavior, and to shed light on possible geochemical 

mechanisms at play upon CO2 injection. Because the geochemical behavior of many metal species 

in groundwater is tied to oxidation state, and because uncertainties remain concerning the 

controlling redox processes within the saturated zone at the ZERT site, thermodynamic analyses are 

also presented to help constrain the identity of potential phases exercising thermodynamic control 

over the redox potential at this site. 

5.2.1 Principal Component Analysis 

Principal Component Analysis (PCA) is a statistical tool for the interpretation of datasets consisting 

of multiple observations in each of many samples, and where it is desired to determine linear 

relations between the observations in the dataset. The aim is to reduce the observed relations among 

the variables to simpler relations between fewer variables, called principal components. These 
29 

principal components are linear combinations of the variables, which are not correlated, but which 

explain the total variance of the data. 

In evaluating the groundwater analyses from the ZERT site, PCA does not identify what each 

principal component relates to in terms of the chemical processes taking place in the field. 

However, it does identify which chemical species are strongly correlated with a given principal 

component, and this in itself provides a basis for hypothesizing the relationship of each principal 

component to a chemical process that is likely to be operative. Unequivocal assignment of any 

specified chemical process to each of the derived principal components is plausible only in 

conjunction with an independent evaluation of the mineralogy, interpretation of measured soil 

chemical and physical properties, and independent thermodynamic and kinetic analyses. The 

interpretation can be further strengthened through an independent comparison of modeled 

predictions of groundwater composition with field observations, as is illustrated in a subsequent 

section of this report. 

Shlens (2009) points out that certain assumptions are implicit in PCA for it to be effective: 

1. Relations between the variables should be linear, although nonlinear regimes have been 

explored. 

2. It is assumed that large variances have important structure. In other words, the data have a 

high signal-to-noise ratio, and the principal components with larger associated variances 

represent interesting structure. 

3. The principal components are orthogonal. This assumption makes PCA solvable using linear 

algebra decomposition techniques. 

Treatment of the data

The underlying relations between the various analyzed chemical species in the groundwaters are 

likely to obey thermodynamic or kinetic mass action relationships, which are defined in terms of the 

logarithms of the activities of the independent components. For a truly rigorous analysis, these 

activities would have to be calculated using a distribution of species code such as EQ3/6 (Wolery, 

1993) or PHREEQC (Parkhurst and Appelo, 1999), taking into account species complexation and 

species activity coefficients. However, the supporting thermodynamic databases of such codes are 

typically incomplete, especially regarding complexation by trace elements, which are of particular 

interest to this study. Furthermore, since it is unlikely that the sampled groundwaters were in 

homogeneous equilibrium with respect to redox state, as is discussed further in Section 5.2.2, it is 

not possible to ascertain with any degree of confidence the likely oxidation state of several of the 

trace elements or their complexing agents. For these reasons, calculation of the thermodynamic 

activities of the aqueous basic species was not warranted. For the purpose of PCA, the measured 

species concentrations were therefore transformed to the logarithmic molar concentrations as 

proxies for the corresponding activities. The loss of accuracy introduced by this approximation is 

mitigated somewhat by the sampled groundwaters being very dilute (total dissolved solids (TDS) 

 1,500 mg/L). Furthermore, since the activity coefficients of all charged species vary 

systematically within the limited range of ionic strength at the ZERT site, the ratio of the activity 

coefficients of any two species is approximately constant. 

A preliminary study of the behaviors of individual chemical constituents indicated that the sampling 

period should be subdivided into discrete time intervals for evaluation and interpretation, because 
30 

different chemical processes became pre-eminent over time, as atmospheric influences changed. 

Here, we restrict our analysis to a data set consisting of the period utilized to establish the baseline 

ambient chemistry of the groundwater (July 7–8, 2008), and the initial period following the start of 

CO2 injection up to the time when a significant rainfall event perturbed the water table elevation 

(July 8–17, 2008). This time period allows evaluation of the short-term response of groundwater 

chemistry to increasing partial pressure of CO2, P(CO2). Because of the broad similarities in the 

chemical responses of the groundwaters to CO2 injection during this period, regardless of location 

of the sampled wells, analyses from all wells were combined for the purpose of PCA. 

The individual datasets were evaluated using the StatisticXLTM package, which is designed for use 

with the Microsoft ExcelTM spreadsheet software under the Windows operating system. The number 

of principal components was not constrained, as prior knowledge of the geochemistry of the system 

suggested that many geochemical processes could be operative, and that independent processes 

affecting different mineral substrates might condition the initial response of the system to CO2

uptake. 

Results

Table 5.1 displays the correlation matrix of the log molar concentrations of all analyzed species. 

The correlation coefficients are color-coded in ranges 0.9, 0.8, 0.7, 0.6, 0.5 and 0.4. Very strong 

correlations exist between the alkali earth metals, Mg, Ca, Sr, Ba, HCO3, Al, and to a slightly lesser 

extent with SiO2. Li, Cd, Pb, Al, Cr, SiO2 and B are also strongly correlated. Fe and Co are strongly, 

but inversely correlated with PO4. Se is strongly correlated with Cr, whereas Mn is fairly strongly 

correlated with Co and moderately with Fe. Several species show notably weak correlations with 

other constituents, notably Zn, U, Cl, Br, and NO3. H (-pH) is most strongly correlated with K 

(0.856), but is otherwise only moderately correlated with most other constituents. Although some of 

the observed correlations could be fortuitous, many probably reflect underlying thermodynamic, 

kinetic, stoichiometric, or mixing relations. These may involve complexing, exchange, or 

adsorption or, with negative correlations, precipitation. Figure 5.2 illustrates some examples of 

relevant correlations between various species in solution, which are intended to show that these 

results might ultimately be used to initiate broader lines of inquiry regarding the behavior of trace 

metals in response to system perturbations caused by CO2 injection.
Table 5.1 Correlation matrix of the log molar concentrations of all species analyzed in MSU-ZERT groundwaters for the period J

 H Li Na K Mg Ca Sr Ba Mn Fe Co Cu Zn 

H 1.000 

Li 0.677 1.000 

Na 0.645 0.822 1.000 

K 0.856 0.580 0.524 1.000 

Mg 0.793 0.850 0.902 0.736 1.000 

Ca 0.850 0.813 0.851 0.846 0.974 1.000 

Sr 0.823 0.828 0.893 0.790 0.992 0.992 1.000 

Ba 0.830 0.762 0.799 0.835 0.959 0.974 0.972 1.000 

Mn 0.160 0.438 0.333 0.188 0.329 0.257 0.290 0.327 1.000 

Fe 0.554 0.729 0.723 0.529 0.814 0.767 0.794 0.829 0.645 1.000 

Co 0.411 0.665 0.595 0.348 0.620 0.539 0.584 0.619 0.889 0.877 1.000 Cu 0.543 0.872 0.833 0.542 0.786 0.769 0.781 0.690 0.254 0.637 0.465 1.000 

Zn 0.067 0.347 0.289 0.099 0.262 0.216 0.243 0.219 0.118 0.143 0.225 0.284 1.0

Cd 0.728 0.951 0.705 0.643 0.770 0.761 0.760 0.722 0.500 0.689 0.681 0.803 0.2

Pb 0.612 0.927 0.676 0.571 0.704 0.685 0.690 0.627 0.476 0.620 0.624 0.828 0.2

Al 0.775 0.953 0.843 0.705 0.931 0.916 0.920 0.883 0.346 0.779 0.615 0.878 0.2Cr 0.665 0.944 0.657 0.576 0.698 0.687 0.684 0.647 0.409 0.606 0.596 0.802 0.3

As 0.099 0.474 0.461 -0.015 0.320 0.241 0.282 0.180 -0.116 0.097 0.060 0.449 0.3

Se 0.525 0.918 0.720 0.413 0.695 0.634 0.659 0.596 0.336 0.558 0.544 0.789 0.3

Mo 0.225 0.633 0.594 0.214 0.478 0.396 0.444 0.356 0.388 0.443 0.470 0.693 -0.0

U 0.398 0.430 0.652 0.288 0.592 0.563 0.609 0.542 0.002 0.449 0.293 0.501 0.0

F -0.491 -0.039 -0.070 -0.559 -0.332 -0.432 -0.375 -0.490 0.043 -0.381 -0.122 0.011 0.3

Cl 0.217 0.253 0.099 0.367 0.306 0.246 0.254 0.329 0.458 0.364 0.375 0.262 -0.0

Br -0.058 0.310 0.260 -0.018 0.214 0.149 0.169 0.082 0.103 0.098 0.067 0.518 0.1

NO3 -0.325 -0.415 -0.406 -0.096 -0.345 -0.232 -0.293 -0.316 -0.636 -0.473 -0.670 -0.229 -0.1

PO4 -0.479 -0.697 -0.668 -0.431 -0.722 -0.665 -0.696 -0.740 -0.758 -0.950 -0.912 -0.569 -0.1SO4 0.448 0.492 0.409 0.451 0.649 0.552 0.586 0.621 0.351 0.587 0.490 0.389 0.0

HCO3 0.806 0.828 0.887 0.763 0.990 0.983 0.993 0.965 0.291 0.804 0.594 0.772 0.2

SiO2 0.753 0.963 0.860 0.661 0.909 0.879 0.893 0.847 0.346 0.753 0.625 0.868 0.3

B 0.727 0.911 0.693 0.616 0.791 0.747 0.758 0.726 0.471 0.662 0.642 0.751 0.2

LEGEND

> 0.9> 0.8> 0.7> 0.6> 0.5

> 0.4 
 Al 27 Cr 52 As 75 Se 82 Mo 98 U 238 F Cl Br NO3 PO4 SO4 HCO

Al 1.000 Cr 0.885 1.000 As 0.347 0.414 1.000 Se 0.821 0.910 0.727 1.000 Mo 0.573 0.634 0.321 0.629 1.000 U 0.462 0.242 0.234 0.302 0.411 1.000 F -0.204 0.009 0.293 0.127 0.322 -0.152 1.000 Cl 0.299 0.282 -0.120 0.228 0.387 -0.077 -0.114 1.000 Br 0.265 0.239 0.261 0.307 0.272 0.150 0.200 0.313 1.000 NO3 -0.338 -0.427 -0.126 -0.463 -0.378 -0.059 -0.149 -0.419 -0.004 1.000 PO4 -0.715 -0.603 -0.086 -0.567 -0.417 -0.318 0.264 -0.367 -0.141 0.615 1.000 SO4 0.573 0.412 0.100 0.424 0.463 0.238 -0.217 0.795 0.168 -0.426 -0.506 1.000 HCO3 0.919 0.681 0.275 0.653 0.446 0.603 -0.362 0.260 0.179 -0.296 -0.698 0.608 1.0SiO2 0.967 0.902 0.515 0.899 0.595 0.449 -0.134 0.285 0.239 -0.404 -0.692 0.556 0.8B 0.906 0.916 0.307 0.837 0.617 0.233 -0.032 0.459 0.219 -0.536 -0.654 0.656 0.7

LEGEND 

> 0.9> 0.8> 0.7> 0.6> 0.5> 0.4 
33 

y = 1.0102x - 0.7914

R2

 = 0.9795

-3.2

-3.1

-3.0

-2.9

-2.8

-2.7

-2.6

-2.5

-2.4

-2.4 -2.2 -2.0 -1.8 -1.6

Log (HCO3-) (mol/L)

Log (Mg) (mol/L)

y = 0.8888x - 0.7204

R2

 = 0.9656

-2.8

-2.7

-2.6

-2.5

-2.4

-2.3

-2.2

-2.4 -2.2 -2.0 -1.8 -1.6

Log (HCO3-) (mol/L)

Log (Ca) (mol/L)

 (a) (b) 

y = 0.9334x - 3.4564

R2

 = 0.9855

-5.6

-5.5

-5.4

-5.3

-5.2

-5.1

-5.0

-2.4 -2.2 -2.0 -1.8 -1.6

Log (HCO3-) (mol/L)

Log (Sr) (mol/L)

y = 0.9381x - 4.0444

R2

 = 0.9311

-6.2

-6.1

-6.0

-5.9

-5.8

-5.7

-5.6

-2.4 -2.2 -2.0 -1.8 -1.6

Log (HCO3-) (mol/L)

Log (Ba) (mol/L)

 (c) (d) 

y = -1.5063x - 15.425

R2

 = 0.903

-7.0

-6.5

-6.0

-5.5

-5.0

-4.5

-7.0 -6.8 -6.6 -6.4 -6.2 -6.0 -5.8 -5.6

Log (PO4) (mol/L)

Log (Fe) (mol/L)

y = -0.7856x - 12.793

R2

 = 0.8318

-8.6

-8.4

-8.2

-8.0

-7.8

-7.6

-7.4

-7.2

-7.0 -6.8 -6.6 -6.4 -6.2 -6.0 -5.8 -5.6

Log (PO4) (mol/L)

Log (Co) (mol/L)

 (e) (f) 

Figure 5.2. Correlation plots showing relationships between various species in solution 
34 

Figures 5.2a–d represent plots of the concentrations of the alkali earth metals with respect to 

alkalinity (reported as HCO3

-

), which shows a much stronger correlation than with H+. Minimal 

scatter characterizes all four plots, even for Ba, which is present in micro-molar concentrations, and 

all regressions show linear correlations with slopes near unity. The trendlines of all alkali earth 

metal concentrations with respect to each other and with respect to alkalinity are also linear and 

extrapolate through the origin, suggesting a common source for all four metals. The correlations 

exhibited in Figures 5.2a–d cannot be attributed to complexing of the respective alkali earths by 

HCO3

-

, because an independent thermodynamic analysis demonstrates that the MHCO3

-

 complex 

(M = Mg, Ca, Sr, Ba) is present only as a minor species, the predominant species being M+2. 

Equilibration with respect to a carbonate mineral according to the reaction 

MCO3 + CO2(aq) + H2O  M+2 + 2HCO3

-

 (5-1) 

also cannot explain the unit slope positive correlation of log M with log HCO3

-

. Furthermore, the 

linear correlation between Mg and Ca yields a molar ratio, Mg/Ca of approximately 0.45, which, 

even for the most magnesian rich calcite, seems to be excessive (maximum observed values are 

approximately 0.25), and would imply that the observed secondary calcite precipitates at the MSUZERT site are proto-dolomites (Busenberg and Plummer, 1989). The perturbation of carbonate 

solubility according to the reaction 

MCO3 + H+  M+2 + HCO3

-

 (5-2) 

is also not supported by the data, because correlations between all log M and pH are poor and nonstoichiometric. This is in part explained by the buffering effect that dissolved CO2 has on pH 

according to the reaction: 

CO2(aq) + H2O  HCO3

-

 + H+; pK ≈ 6.5 @ 10C (5-3) 

Finally, a comparison with Figure 5.5 (see Section 5.2.3 below) shows that significant resaturation 

of calcite started taking place only after the partial pressure of dissolved CO2 exceeded 0.2 bar, 

which implies that calcite may not have been actively dissolving until that partial pressure had been 

exceeded. The linear trend observed between log (Ca+2) and log (HCO3

-

) in Figure 5.2b suggests 

that Ca+2 was initially released from some source other than calcite, and that only later in the time 

period under investigation did calcite dissolution contribute significantly to the total dissolved Ca+2

in solution. This hypothesis is consistent with the argument that the increased acidity resulting from 

the dissociation of CO2(aq) would depress the chemical potential of the CaO component in solution 

(defined in terms of log [Ca+2]/[H+

]

2

), and that this would have induced the release of Ca+2, most 

probably from cation exchange sites, and concurrently through the dissolution of calcite. 

The short-term and immediate response of the system to changes in alkalinity as demonstrated by 

these correlation plots can be best explained by ion exchange on the basis of the following 

arguments: (a) the strong correlation observed in Figures 5.2a–d and the inferred rapid response of 

the system to increasing alkalinity; (b) the linear relations between the log concentrations of the 

alkali earths and other divalent cations, suggesting a common source for all divalent cations, and 

even monovalent and trivalent cations; (c) the inferences drawn from the principal component 

analysis described below; (d) the close correlation of the geochemical modeling described in 
35 

Section 5.3 in which an ion exchange model, using independently derived ion exchange parameters, 

closely matches field measurements of pH against analytical data for the alkali earth metal and other 

divalent cation concentrations in solution; and (e) the mineralogical evidence for the presence of 

smectite in both vadose and phreatic zone sediments. We are led to the tentative conclusion that a 

shifting state of ion exchange equilibrium with respect to interlayer site occupancies on smectite 

may be responsible for the observed response of the groundwater composition to CO2 uptake, 

although not necessarily driven exclusively by Ca+2 released by the dissolution of calcite. This 

process can be represented by the following equation, where X represents a negatively charged (-2) 

ion exchange site: 

X-M(II) + 2H2CO3(aq) = X-H2 + (M+2•2HCO3

-

) (5-4) 

Alkalinity (reported as HCO3

-

) is represented approximately by the concentration of HCO3

-

 in this 

particular system (where minor complexation by HCO3

-

 and the contribution due to CO3

-2 can be 

ignored). Therefore, 

log (HCO3

-

)  1⁄2-log(M+2) (5-5) 

The trendlines in Figures 5.2a–d give slopes that approximate unity rather than 0.5, as would be 

expected from the above relationship. The observed correlation between alkalinity and the alkali 

earth metals is therefore not readily interpreted. Synthetic geochemical modeling of the response of 

a groundwater composition in equilibrium with a cation exchanger to changes in P(CO2) should be 

conducted to further elucidate the many complex system interactions that might explain the 

observed relationships. 

Figures 5.2e and f show the negative correlations between phosphate (log PO4), and log Fe and log 

Co, with trendline slopes of ~1.5 and 0.75, respectively. The correlation between log Fe and log 

PO4 is strongly suggestive of an equilibrium state between these species and some ferrous 

phosphate mineral such as vivianite: 

Fe3(PO4)2.8H2O = 3Fe+2 + 2PO4

-3; log [PO4-3] = K ́ + 3/2 log[Fe+2] (5-6)

Calculations show, however, that prior to CO2 injection, the MSU-ZERT groundwaters were 

unsaturated with respect to both vivianite and strengite (FePO4.2H2O) prior to CO2 injection. The 

slope coefficient of the trendline for cobalt could be explained by achievement of solution 

equilibrium with respect to the cobalt analogue of, for example, gormanite 

(FeII

3Al4(PO4)4(OH)6•2(H2O)), mclausanite (HFeII3Al2(PO4)4F•18(H2O)) or keckite 

Ca(Mn,Zn)2FeIII

3(PO4)4(OH)3•2(H2O), where: 

log [PO4

-3] = K ́ + 3/4 log[Co+2] + ..., or log [PO4-3] = K ́ + 3/4 log[Co+3] + ... (5-7) 

These examples are illustrative of the potential complexity associated with the mineralogy of 

shallow sedimentary systems. In reality, Co(II) is likely to substitute for Fe(II) in solid solution in 

Fe(II) hydroxides, such as green rust, but the presence of trace nanophases exercising solubility 

control over trace elements cannot be discounted, and insoluble phosphates might under some 

circumstance be potential candidates. 
36 

We now return to the correlation of the chemical species with a restricted set of principal 

components. Information on the first ten principal components is presented in Table 5.2. The first 

four principal components explain over 80% of the variance, whereas principal components No. 5 

(PC5) and No. 6 (PC6) explain another 10%. As with Table 5.1, the correlation coefficients are 

similarly color coded in ranges 0.9, 0.8, 0.7, 0.6, 0.5 and also 0.4. 

Table 5.2. Principal components derived from an analysis of groundwater chemical compositions for the period 

July 7 to July 17, 2008 

Explained Variance (Eigenvalues) 

Value PC 1 PC 2 PC 3 PC 4 PC 5 PC 6 PC 7 PC 8 PC 9 PC 10 

Eigenvalue 17.353 3.073 2.668 1.480 1.345 1.071 0.892 0.644 0.466 0.289 

% of Var. 57.844 10.242 8.894 4.934 4.484 3.569 2.975 2.145 1.553 0.962 

Cum. % 57.844 68.086 76.980 81.914 86.398 89.967 92.942 95.087 96.641 97.603 

Component Loadings (correlations between initial variables and principal components) 

Variable PC 1 PC 2 PC 3 PC 4 PC 5 PC 6 PC 7 PC 8 PC 9 PC 10 

H 0.774 -0.419 0.114 0.090 -0.289 -0.079 -0.111 0.051 0.279 0.018 

Li 0.951 0.202 0.120 -0.010 -0.093 -0.063 0.071 -0.056 -0.026 0.086 

Na 0.874 0.023 0.216 -0.246 0.223 -0.015 -0.064 0.062 0.113 -0.169 

K 0.711 -0.500 0.071 0.245 -0.252 0.031 0.076 0.136 -0.005 -0.226 

Mg 0.946 -0.215 0.111 -0.044 0.117 0.115 -0.059 0.029 -0.002 -0.002 

Ca 0.914 -0.339 0.175 -0.014 0.018 0.062 0.023 0.051 -0.006 -0.070 

Sr 0.931 -0.282 0.154 -0.060 0.084 0.077 -0.028 0.061 0.004 -0.044 

Ba 0.902 -0.385 0.030 -0.053 0.025 0.127 -0.035 0.028 -0.032 -0.034 

Mn 0.484 0.229 -0.735 -0.236 -0.001 -0.029 0.199 0.025 -0.033 -0.127 

Fe 0.841 -0.169 -0.316 -0.257 0.156 0.019 0.088 -0.118 -0.164 0.044 

Co 0.734 0.100 -0.537 -0.351 0.032 -0.015 0.077 -0.022 -0.070 0.045 

Cu 0.857 0.201 0.275 0.113 0.176 -0.060 0.211 0.018 0.000 -0.116 

Zn 0.282 0.372 0.221 -0.287 -0.268 0.663 0.076 0.317 -0.098 0.051 

Cd 0.914 0.156 -0.013 0.080 -0.234 -0.173 0.163 0.030 0.044 0.119 

Pb 0.872 0.287 0.007 0.155 -0.184 -0.233 0.109 0.089 -0.060 0.060 

Al 0.972 -0.021 0.131 0.055 -0.054 -0.019 0.066 -0.004 -0.043 0.065 

Cr 0.872 0.276 0.070 0.116 -0.298 -0.164 0.079 -0.061 -0.007 0.068 

As 0.352 0.482 0.529 -0.105 0.044 0.174 -0.330 -0.410 -0.073 -0.109 

Se 0.832 0.417 0.189 0.013 -0.142 0.001 -0.115 -0.228 -0.020 0.005 

Mo 0.620 0.441 -0.058 0.196 0.313 -0.411 -0.150 0.166 -0.145 -0.143 

U 0.497 -0.203 0.325 -0.258 0.562 -0.203 -0.126 0.194 0.086 0.208 

F -0.201 0.870 0.095 -0.056 0.047 0.006 -0.108 0.368 0.004 -0.045 

Cl 0.385 0.035 -0.573 0.615 0.168 0.257 -0.102 0.029 -0.021 -0.081 

Br 0.252 0.387 0.148 0.340 0.464 0.286 0.497 -0.140 0.275 0.046 

NO3 -0.477 -0.303 0.547 0.195 0.083 -0.056 0.352 0.005 -0.431 0.026 

PO4 -0.791 0.034 0.434 0.310 -0.094 -0.030 -0.125 0.165 0.027 0.012 

SO4 0.631 -0.104 -0.347 0.406 0.217 0.245 -0.359 0.014 -0.153 0.179 

HCO3 0.928 -0.271 0.141 -0.061 0.099 0.097 -0.032 0.065 -0.014 -0.007 

SiO2 0.967 0.079 0.165 0.002 -0.079 0.028 -0.056 -0.076 -0.043 -0.009 

B 0.910 0.172 -0.084 0.202 -0.223 -0.045 -0.061 0.031 0.038 0.107 

LEGEND 

> 0.9

> 0.8

> 0.7

> 0.6

> 0.5

> 0.4 

With respect to principal component No. 1 (PC1), nine of the chemical species show correlations of 

0.9 and above, and another six show correlations between 0.8 and 0.9. With the exception of HCO3, 
37 

Li and Na, all of the remainder are probably present as divalent cations or divalent hydroxy-cations 

of trivalent species, i.e., B, Al, Cr, and Mn. Principal component No. 2 (PC2) correlates strongly 

only with F, and relatively weakly with As, Se and Mo, all potential oxy-anionic species, and 

inversely, but weakly with H and K. Principal component No. 3 (PC3) inversely correlates with Mn, 

Co and Cl, and directly with As, NO3 and PO4. Principal component No. 4 (PC4) correlates with Cl 

and SO4. Correlations of chemical species with the remaining six components are for the most part 

weak and are of questionable significance. 

Interpretation

Each of the primary principal components most probably relates to a chemical process that takes 

place rapidly, given the short interval over which the analyses were taken, and considering the fact 

that a close logarithmic relationship is observed with respect to HCO3

-

 in the first principal 

component. The most likely short term processes are, in order of reaction rate: adsorption/desorption, ion exchange (both cationic and anionic), dissolution of carbonates and metastable Fe 

hydroxides and green rusts, some homogeneous redox reactions in the aqueous phase, and pore 

water infiltration from the vadose zone. Other unidentified processes may also be involved, which 

future investigations might reveal. 

Table 5.3 lists the correlated variable for each of the first six principal components, and identifies 

the likely processes in which the dominant aqueous species might participate. Note that over the 

possible range of redox states in the shallow phreatic zone at the ZERT site, several aqueous species 

might transform to other species with different oxidation states, notably Fe(III)/Fe(II), Cu(II)/Cu(I), 

Cr(VI)/Cr(III), N(VII)/N(0), U(VI)/U(IV), Se(VI)/Se(IV)/Se(-II). It is also possible, although less 

likely, that extremely reducing conditions might arise through the progressive decomposition of 

organic matter, leading to transformations with respect to As(III)/As(-I), S(VI)/S(-II), 

Mo(VI/Mo(II), C(IV)/C(0)/C(-IV), and N(0)/N(-III). It should also be noted that many trace 

elements could be present in solid solution in minerals that are known to dissolve rapidly in 

response to changing pH, such as calcite and/or hydroxide minerals including green rust. These 

have not been checked in Table 5.3 under “Precipitation/dissolution,” because the extent of such 

solid solutions is unknown. 

Table 5.3 suggests that PC1 may be related to ion exchange or desorption processes because the 

alkali earth metals and other divalent cations correlate very strongly with this component. Several 

monovalent cations (H+

, Li+, Na+, K+) are also moderately to strongly correlated. These correlations 

suggest cation exchange on smectite interlayer sites. Trivalent species such as B, Al, Fe and Cr, and 

tetravalent Si (as SiO2(aq)) are also moderately to strongly correlated, and are known to sorb onto 

clays. However, the strong positive correlation with HCO3

-

 is not readily explained in relation to 

sorption or ion exchange on smectite. Other oxy-anionic species, such as SO4

-2, Mo (as MoO4-2), Se 

(as SeO4

-2 or SeO3-2) are also positively correlated. It is tempting to assume that these species likely 

occupy the interlayer sites of anionic clays such as fougerite, a Mg-rich form of green rust, 

especially when it is recognized that such occupancy in green rust has been confirmed in the 

laboratory for all but MO4

-2. However, the oxy-anions, PO4 an NO3, are negatively correlated, 

implying a different association with PC-1, which is not readily explained without further study. 

PC2 appears to be dominated by anionic species (F, As (probably as HAsO4

-2), Se (as SeO4-2

 or 

SeO3

-2) and Mo (as MoO4-2), which are positively correlated, and by H and K, which are negatively 

correlated, and suggest adsorption on hydrous ferric oxide (HFO), which could be ferrihydrite, 
38 

lepidocrocite, or goethite. PC3 shows a negative correlation with respect to Mn, Co and Cl, and a 

positive correlation with respect to As (probably as HAsO4

-2), NO3 and PO4. This correlation is 

suggestive of saturation control by some transition metal phosphate with substitution of AsO4

-3 for 

PO4

-3. PC4 may be related to infiltration of pore water from the overlying vadose zone. U is 

correlated with PC5 and Zn appears to show the strongest correlation by far with PC-6. No 

explanation for these correlations is apparent. The behavior of Zn appears to be unique, and is 

unexpected. 

Because smectite has been identified as a mineral that is present in the sediments in the saturated 

zone, it is reasonable to assume as a working hypothesis that ion exchange on smectite is operative, 

and is responsible for the species correlations observed with respect to PC1. It is not entirely clear, 

though, what specific ion exchange mechanism is taking place. Increasing H+ caused by the 

dissolution of CO2 might be responsible. However, the correlation between H+

 and the first 

principal component is only moderate, and as noted in preceding discussions, does not explain the 

strong positive correlation with HCO3

-

. Another possibility is that increased P(CO2) leads to 

calcium carbonate dissolution, which in turn induces ion exchange with other divalent cations 

observed to increase in concentration in the groundwater. This mechanism would therefore be 

controlled by the rate of calcite dissolution. As a working hypothesis, we will assume that the 

primary response to increasing concentrations of dissolved CO2 is cation exchange and desorption 

induced by Ca+2 due to calcite dissolution, and anion exchange induced by increasing HCO3

-

 in 

solution. We will also assume that an adsorbent is present whose surface behaves analogously to 

HFO such as ferrihydrite, or other ferric oxy-hydroxides and other metastable phases (e.g., 

schwertmannite and green rust) commonly resulting from the transformation of HFO (see further 

discussion in Section 5.2.2). The presence of these minerals can also provide anionic exchange 

sites as suggested by the correlation between PC1 and PC2 with respect to aqueous anionic species. 

The modeling of this system is presented subsequently in Section 5.3 of this report. 
39 

Table 5.3. Correlation of aqueous species with principal components for the period July 7 to July 17, 2008 in 

relation to short-term chemical processes 

Component Variable Correlation Dominant 

Aqueous 

Species 

Cation 

Exchange 

Anion 

Exchange 

Adsorption Precipitation/ 

dissolution 

Redox 

Reactions 

Infiltration 

1 H 0.774 H+ √ √ 

 Li 0.951 Li+ √ √ 

 Na 0.874 Na+ √ √ 

 K 0.711 K+ √ √ 

 Mg 0.946 Mg+2 √ √ √ 

 Ca 0.914 Ca+2 √ √ √ 

 Sr 0.931 Sr+2 √ √ 

 Ba 0.902 Ba+2 √ √ 

 Mn 0.484 Mn+2 √ √ √

 Fe 0.841 Fe+2 √ √ √ √

 Co 0.734 Co+2 √ √ √ 

 Cu 0.857 Cu+2/Cu+ √ √ √ 

 Cd 0.914 Cd+2/CdSe √ √ 

 Pb 0.872 PbCO3/PbSe √ √ 

 Al 0.972 Al(OH)3- 

H3SiO4- 

? ? √ √ 

 Cr 0.872 CrO4

-2/CrO+ ? √ √ √ 

 Se 0.832 SeO4

-2 √ √ √ 

 Mo 0.620 MoO4

-2 √ 

 U 0.497 UO2(CO3)2

-

2

/UO2 

 √ √

 NO3 -0.477 NO3

-

 √ √ √ √

 PO4 -0.791 H2PO4- √ √ 

 SO4 0.631 SO4

-

2 √ √ √ √

 HCO3 0.928 HCO3

-

 √ √ √ ? 

 SiO2 0.967 Si(OH)4 √ √ 

 B 0.910 B(OH)3 √ 

2 H -0.419 H+ √ √ 

 K -0.500 K+ √ √ 

 As 0.482 AsO3F--2 √ √ ? 

 Se 0.417 SeO4

-2/HseO3- √ √ √ 

 Mo 0.441 MoO4

-2 √ ? 

 U -0.203 UO2(CO3)2

-

2

/UO2 

 √ √ 

 F 0.870 F- √ 

3 Mn -0.735 Mn+2 √ √ √ 

 Co -0.537 CO2(OH)3

+ √ √ 

 As 0.529 AsO3F-2 √ ? 

 Cl -0.573 Cl- √ √

 NO3 0.547 NO3

-

 √ √

 PO4 0.434 H2PO4

-

 √ √ 

4 Cl 0.615 Cl- √

 SO4 0.406 SO4

-2 √

5 U 0.562 UO2(CO3)2

-

2

/UO2 

 √ √ 

 Br 0.464 Br- √

6 Zn 0.663 Zn+2 √ √ 

 Mo -0.411 MoO4

-2 √ √ ? 
40 

5.2.2 Thermodynamic Evaluation of Baseline Groundwater Composition and Redox 

State 

One of the more difficult problems associated with interpreting the geochemistry of the 

groundwaters in the saturated zone at the ZERT Site is the determination of the redox state. In 

addition, as discussed further below, it has been clearly established that complete redox equilibrium 

in shallow groundwater systems is rarely, if ever, achieved (e.g., Lindberg and Runnels, 1984; 

Washington et al., 2004; Stefansson et al., 2005). Furthermore, many of the trace elements and 

some of the major constituents can undergo reduction or oxidation in response to periodic 

infiltration of rainfall, which transports not only dissolved constituents already present in the rain 

(Na+

, Mg+2, Ca+2, NH4

+

, HCO3

-

, NO3

-

, SO4

-2, Cl-, Br-

), which have been subject to evapotranspiration, but also dissolved inorganic constituents and organic matter from the overlying soil 

zone. The transported organic matter is present both in the form of dissolved organic acids and 

associated complexes with inorganic cations, but also is probably present in colloidal form. Both 

during transport and after reaching the water table, the organic matter in the pore waters undergoes 

oxidative mineralization through the agency of bacteria and fungal matter, depleting all dissolved 

and gaseous phase oxygen in the vadose and phreatic zones, and then reducing both dissolved and 

solid-phase electron donors. These include N(V) as NO3

-

, N(III) as NO2

-

, N(0) as N2, S(VI) as 

SO4

-2, and dissolved minor elements and trace metals involving species and complexes and 

associated solid phases in the following oxidation states; C(IV)/C(0)/C(-IV), Fe(III)/Fe(II), 

Mn(IV)/Mn(III)/Mn(II), As(V)/As(III)/As(-I)/As(-III), Se(VI)/Se(IV)/Se(0)/Se(-II), Cr(VI)/Cr(III), 

Co(III)/Co(II), Cu(II)/Cu(I), Mo(VI)/Mo(II) and U(VI)/U(IV). 

The traditional approach taken in trying to characterize the redox state of groundwaters is through 

the use of a platinum (Pt) electrode and associated reference electrode, e.g., calomel or Ag/AgCl, 

which measures the redox potential of the groundwater when in thermodynamic equilibrium. 

However, as noted above, shallow groundwaters are rarely if ever at thermodynamic equilibrium, 

and therefore the measured mixed potential cannot be utilized as a meaningful representation of the 

redox potential. Furthermore, a Pt electrode can locally catalyze redox reactions on its surface, 

leading to precipitation of PtO, which, in combination with the Pt substrate, results in it responding 

to pH rather than Eh (see Baas Becking, 1960). The Pt electrode can also be poisoned. Thus, unless 

great precaution is taken, the measured potential may have more to do with the electrode sensor 

than the solution in which it is immersed. 

The problems associated with direct in situ measurement of redox potential using a Pt electrode 

have been known for many years (Baas Becking, 1960). Following Lindberg and Runnels (1984), 

therefore, attempts have been made to chemically analyze dissolved redox pairs in groundwaters 

(e.g., Washington et al., 2004; Stefansson et al., 2005), and then calculate the apparent redox 

potential for each pair. As expected, the analyzed redox pairs yield disparate redox “potentials.” 

indicating a nonattainment of homogeneous equilibrium. Washington et al. (2004) made a 

significant contribution, when they showed that the potentials associated with the analyzed redox 

pairs are not random, but behave in a systematic manner, and that “...redox couples composed of 

concentrated reactants achieve nearly thermodynamic equilibrium concomitantly, and those with 

dilute reactants deviate from equilibrium by an amount roughly inverse to their concentrations.” In 

typical groundwaters, an upper group of redox couples is essentially controlled by the presence of 

NO3, which is involved in the oxidation of species such as, for example, Fe(II), thus: 

NO3

-

 + 2Fe+2 + 5H2O  NO2

-

 + 2Fe(OH)3(ppt) + 4H+ (5-8) 
41 

and a lower group controlled by the presence of dissolved organic matter, which can be represented 

by equations of the type: 

3CH2O + 2H+

 + SO4

-2  H2S(aq) + 2CO2(aq) + 2H2O , (5-9) 

where CH2O is a generic representation of dissolved (and particulate) organic matter. According to 

Washington et al. (2004), the upper cluster of redox pairs is centered on pe ≈ +10, whereas the 

lower cluster is centered on pe ≈ -2. Over time, or with increasing depth below the water table, all 

NO3 in solution is progressively consumed, and the redox pairs, initially in local partial equilibrium 

with respect to NO3, drift to lower redox states, where control of the redox state is assumed by the 

reservoir of organic matter and microbial activity, which is usually the dominant reducing agent in 

shallow unconfined aquifers underlying soil zones with active vegetative cover. This scenario is 

particularly pertinent to the redox state of the ZERT site, as is described further below. 

While the direct characterization of redox pairs represents the most rigorous means of 

characterizing the redox state in a groundwater, such an approach is rarely implemented in practice, 

because it requires elaborate sampling procedures to avoid inadvertent contamination by 

atmospheric oxygen, and time-consuming and expensive analytical procedures. A more typical 

scenario is represented by the current characterization of the ZERT site and elsewhere—e.g., see 

Bourrie et al. (1999) and Feder et al. (2005)—where collected groundwaters are subjected to 

standard field and laboratory analytical procedures, and where only the total concentrations of 

elements in solution are determined rather than their speciation, including the distribution of species 

between oxidation states. 

An alternative means of indirectly characterizing the oxidation state of a groundwater is through a 

thermodynamic analysis of the groundwater composition using a distribution of species code such 

as PHREEQC (Parkhurst and Appelo, 1999) or EQ3/6 Wolery, 1992, 1993) and calculating the 

saturation states of minerals that might control the redox state of the system by varying the redox 

potential over a specified range and examining at what pe (or Eh) potential redox controlling 

minerals equilibrate with the redox affected aqueous species in solution. Ideally, the redox state can 

be established where one or more redox sensitive phases containing the same redox pair coexist in a 

state of saturation at a particular value of pe. Such an analysis is in some respects more 

fundamental, in that solid phases participating in redox reactions are likely to exert a substantial 

buffering capacity on the system as a whole, and are more likely to define a temporally averaged 

redox state, rather than a momentary, but not necessarily representative oxidation state 

characterized by the analysis of an isolated groundwater sample. Such utilization of redox sensitive 

minerals to help define the oxidation state of an aqueous system is subject to several limitations and 

caveats: 

1. The redox sensitive phases must be reactive, i.e., they must be able to respond by dissolving 

or precipitating sufficiently rapidly, so that they reasonably approach thermodynamic 

equilibrium under ambient conditions. Such phases are most likely to be metastable and 

either finely crystalline or amorphous. 

2. The redox sensitive phases must be clearly identified, and their thermodynamic properties 

reasonably well characterized. 

3. Ideally, several redox sensitive components should be considered in the analysis in order to 

provide independent corroboration. 
42 

4. The participating aqueous species must be present at sufficiently high concentrations to be 

detectable and quantifiable in solution. 

5. Groundwater sampling procedures exclude contamination, and custodial integrity can be 

assumed (i.e., samples have not re-equilibrated under post-sampling redox conditions). 

6. The thermodynamic properties of the aqueous species must be known and their 

complexation with other species in solution must be known and quantified. 

7. Suitable corrections to the thermodynamic data used in the analysis should be made to 

account for ambient field temperatures of 10oC rather than the standard reference 

temperature of 25oC used in most thermodynamic calculations concerning groundwaters. 

8. Validation of the thermodynamic analysis should be made through an independent 

mineralogical study of the abundance and distribution of redox sensitive phases in the 

soil/sediment profile through the vadose and phreatic zones where the groundwaters were 

sampled. 

In the following analysis, a modified EQ3/6 thermodynamic database was used as described in 

Birkholzer et al. (2008). The database is a substantial revision of an earlier database, Data0. 

ymp.R4, which was developed and qualified for use by the Yucca Mountain Project on behalf of the 

U.S. Department of Energy. A very important requirement for conducting a successful 

thermodynamic evaluation of the ZERT site is the incorporation of the solubility products of 

metastable redox sensitive minerals that might exercise partial or complete secular control over the 

redox state of the system. Among these is a class of minerals referred to as “green rusts” of which 

fougerite is the most important naturally occurring representative. Because this mineral is unstable 

under oxic conditions, its recovery and preservation during coring for soil and sediment samples is 

questionable unless appropriate precautions are taken to avoid contamination with atmospheric 

oxygen. Despite the fact that such precautions were not anticipated or implemented, circumstantial 

evidence suggests that it may be present at the ZERT site, and some geochemical similarities 

between the ZERT site and the type locality for fougerite in Brittany mandate that it be taken into 

consideration in the following thermodynamic evaluation. (By “type locality”, we refer to the 

original site from which the fougerite was initially obtained, characterized mineralogically, and 

reported in the scientific literature.) Appendix C presents a summary description regarding the 

known thermodynamic properties of fougerite and its compositional variation, as cited in the recent 

literature, and describes the procedure adopted for calculating its solubility product in a form 

appropriate for inclusion in Data0.ymp.R4. 

Baseline Groundwater Composition

The groundwater composition selected for evaluation of the redox state is based on the average of 

seven comprehensive chemical analyses of groundwaters taken on July 7 and 8, 2008, immediately 

prior to CO2 injection. With the exception of sample 08ZERT-104, all samples were taken from the 

deeper A-wells and from two monitoring wells drilled further away from the injection well (MW1 

and MW2). It is possible that a redox gradient exists between the water table and deeper horizons 

within the phreatic zone, and that sample 08ZERT-104 may reflect more oxidizing conditions. 

However, the chemical analysis does not support this interpretation, and even suggests a lower 

redox potential induced by exogenic contamination, as is noted further below. These analyses and 

the average values are given in Table 5.4. 
43 

Table 5.4 Initial composition of the groundwater at the ZERT site prior to CO2 injection 

SAMPLE T pH Li Na K Mg Ca Sr Ba Mn Fe 

 °C mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L 

08ZERT-102 10 6.8 0.003 7.5 6.2 24 85 0.27 0.13 0.002 <0.01

08ZERT-103 10 6.8 0.003 9.2 5.5 24 95 0.31 0.12 0.001 <0.01

08ZERT-104 15 6.9 0.006 9.7 5.6 27 90 0.30 0.10 0.11 0.05

08ZERT-105 8 6.9 0.003 7.8 5.6 23 84 0.27 0.11 0.001 <0.01

08ZERT-106 8 6.9 0.004 8.1 5.6 25 86 0.28 0.10 0.31 <0.01

08ZERT-107 8 6.7 0.005 7.5 5.3 24 84 0.26 0.11 0.001 <0.01

08ZERT-109 12 7.0 0.007 9.1 5.4 28 92 0.30 0.10 0.028 <0.01

Average 10.286 6.871 0.004 8.414 5.583 24.992 87.988 0.285 0.110 0.065 0.015

SAMPLE Co Cu Zn Cd Pb Al Cr As Se Mo U 

 ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L 

08ZERT-102 <0.2 1.4 3.4 0.07 <0.02 2 <0.4 0.8 <2 0.4 4.3 

08ZERT-103 0.3 1.5 4.0 0.09 <0.02 2 0.4 1.0 <2 0.3 4.9 

08ZERT-104 0.8 2.4 2.4 0.26 0.08 3 10 1.0 <4 1.3 4.5 

08ZERT-105 <0.2 1.2 2.8 0.08 0.02 2 <0.4 0.9 <2 0.4 4.0 

08ZERT-106 0.6 1.1 3.2 0.10 0.02 2 <0.4 0.8 <2 0.3 4.0 

08ZERT-107 0.2 1.6 3.1 0.23 0.05 3 12 1.0 <4 0.4 4.1 

08ZERT-109 0.4 2.5 3.8 0.29 0.06 3 12 1.3 5 0.7 4.3 

Average 0.376 1.668 3.245 0.162 0.038 2.383 5.010 0.976 3.003 0.545 4.291 

SAMPLE F Cl Br NO3 PO4 SO4 HCO3 SiO2 B 11 

 mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L 

08ZERT-102 0.09 6.5 0.051 0.12 0.20 8.3 396 27 0.012 

08ZERT-103 0.10 3.7 0.042 0.79 0.17 5.8 432 27 0.009 

08ZERT-104 0.17 5.3 0.046 0.10 0.09 7.3 431 33 0.017 

08ZERT-105 0.10 4.7 0.040 0.55 0.17 7.5 386 26 0.012 

08ZERT-106 0.11 5.1 0.044 0.19 0.13 7.4 398 26 0.013 

08ZERT-107 0.12 4.8 0.042 0.60 0.18 7.4 387 32 0.018 

08ZERT-109 0.17 5.4 0.099 0.26 0.10 7.2 434 32 0.017 

Average 0.123 5.071 0.052 0.373 0.149 7.270 409.129 28.9

31 0.014 

In general, most of the major chemical constituents and trace elements show relatively consistent 

values, giving one confidence that the analyses truly reflect the actual concentrations present in the 

groundwater. However, several species of critical interest in defining the oxidation state of the 

groundwater and the saturation state of redox sensitive phases are at or close to their detection 

limits. These include Mn, Fe, Cr and Se. Furthermore, sample 08ZERT-104 shows anomalously 

high concentrations of Fe, Cu, Cd, Cr and Mo, suggesting contamination by steel. The averaged 

concentrations should therefore be considered as maximum values in interpreting the subsequent 

results. However, it should also be noted that these same species show variations in concentrations 

subsequent to CO2 injection that place them well within the range of detectability for the analytical 

methods used. 
44 

Thermodynamic Analysis of Baseline Groundwater

The average concentrations of the chemical species given in Table 5.4 were entered into the input 

file of EQ3/6, and an initial run was made to calculate the extent of complexation by HCO3

-

 at 25oC. 

The analytical value for HCO3

-

 was adjusted to account for cation complexation, and the revised 

value inserted as a “free” concentration. In this manner, the total equilibrium concentration of all 

carbonate species, including CO2(aq), can be accounted for in solution, and P(CO2) determined. 

EQ3/6 was then re-run, setting the temperature to the average ambient value of 10.28oC. The 

resulting charge imbalance was calculated to be –0.50% of the mean charge of all charged species, 

which is excellent, and therefore no attempt was made to ensure electrical neutrality by balancing 

on any selected species. 

The calculated saturation indices (SI) for several primary and secondary minerals of interest, but 

which are not sensitive to the redox state of the system, are listed in Table 5.5. The saturation 

indices of aluminosilicate minerals have been normalized to both Al and Si to afford a better 

respective comparison with the gibbsite (Al(OH)3) and silica (opal-CT or quartz) chemical 

components. These results are typical of what would be expected in a soil zone of this type, where 

primary rock-forming minerals associated with detrital igneous, metamorphic, and sedimentary rock 

fragments observed in the shallow subsurface environment at the ZERT site are weathering in the 

presence of neutral to weakly acid groundwaters containing dissolved organic matter from the 

overlying soil zone. The aluminum concentration is elevated and actually supersaturated with 

respect to gibbsite, which is consistent with field observations elsewhere (Dobrzynski, 2007), and is 

caused by the formation of metastable amorphous or poorly crystalline hydroxy-aluminum silicates 

(HAS) such as imogolite or allophane as weathering products of detrital minerals of igneous or 

metamorphic provenance. These HAS minerals are also closely associated with secondary opal-CT, 

which forms concurrently in systems with excess silica. Recent work has shown that HAS minerals 

form as metastable precursors to secondary minerals actually observed in the fine fractions of 

sediments recovered from the site, i.e., smectite, illite, and kaolinite. The transformation from HAS 

to these secondary clays is exceedingly slow, and therefore the former, together with opal-CT, 

controls the activity of Al(OH)3 and SiO2 components in the aqueous phase. As a result, the 

weathering minerals can approach thermodynamic equilibrium, and indeed, secondary epitaxial 

overgrowths of K-feldspar on detrital feldspar grains have sometimes been observed. 

The groundwater at the ZERT site does not appear to be saturated with respect to either HAS or to 

opal-CT. Calcite also appears to be undersaturated, with SI(calcite) = -0.283. Given the fact that 

secondary calcite precipitates are ubiquitous both below and above the water table at the ZERT site 

(Section 4), it is perhaps surprising that it is not closer to saturation. Furthermore, mineralogical 

studies of secondary calcite suggest that it may be magnesium rich. Such calcites are less stable than 

the pure form (Busenberg and Plummer, 1989), which would imply even greater degrees of 

undersaturation. However, undersaturation with respect to HAS, opal-CT and calcite can be 

explained by transient dilution of the groundwater due to rainfall prior to the start of the test. Table 

5.5 shows that all of the listed potential secondary phyllosilicates except celadonite, including those 

actually observed to be present in sediments at the ZERT site, are supersaturated, as expected. The 

supersaturation of K-feldspar is consistent with some observations elsewhere (Zhu et al., 2006), but 

may be related to potassium retention by vegetation in the presence of illite, rather than any 

thermodynamic or kinetic control by this mineral, especially when it is recognized that the pH is ≤7. 

The observed undersaturation with respect to low albite is expected. 
45 

Table 5.5 also lists the saturation indices of some other minerals of passing interest. Dolomite is 

strongly undersaturated, as is characteristic of shallow groundwaters (Edmunds et al., 1982; Back et 

al., 1983; Hopkins and Putnam, 2000; James et al., 1993; Pacheco and Szocs, 2006), and therefore 

dolomite, if present, would tend to dissolve. As mentioned in Section 4, individual grains of detrital 

dolomite and occasional fragments of dolomitic limestone were identified in the coarse fractions of 

sediments from the ZERT site. This material shows evidence of corrosion, which is consistent with 

the findings of the thermodynamic analysis. Earlier work (Birkholzer et al., 2008) involving the 

thermodynamic evaluation of 38,000 potable groundwaters showed that the concentration of Ba was 

controlled primarily with respect to barite (BaSO4). Table 5.5 shows that barite is significantly 

undersaturated with respect to both barite and to alstonite, the barium analogue of dolomite. This 

finding is also suggestive of dilution by rainfall, preventing the accumulation of the products of 

weathering to saturate, except possibly after prolonged dry spells. Finally, the saturation indices of 

hydroxy-apatite, fluor-apatite and crandallite are compared. Hydroxy-apatite is strongly undersaturated, whereas fluor-apatite is strongly supersaturated. Many of the detrital lithic fragments at 

the ZERT site consist of amphibolites or extrusive mafic rocks including andesitic volcanics. These 

rocks typically contain apatite, commonly with significant F- substitution for OH-. Therefore, it is 

possible that the shallow groundwaters may be saturated with respect to hydroxy-fluor apatite. It is 

more likely, however, that apatite is unstable with respect to secondary crandallite, which is close to 

saturation. Other alkali-earth metals such as Sr and Ba, and also Pb and Cd are known to substitute 

for Ca, and AsO4

-3, VO4-3, CO3-2, MoO4-2, SO4-2, SeO4-2 and even CrO4-2 can substitute for PO4-3 in 

the crandallite crystal structure. Fe+3 and Cr+3 can also substitute for Al+3 in crandallite—see 

Schwartz, et al. (2000). Therefore, this mineral or an isostructural mixed phosphate-sulfate, 

woodhouseite (CaAl3(PO4)(SO4)(OH)6), could exercise partial thermodynamic control over the 

activities of a number of trace elements in the groundwater. 
46 

Table 5.5. Saturation indices of redox-insensitive primary and secondary minerals with respect to groundwater at 

the ZERT site 

Name Formula SI SI(n. Al) SI(n. Si) 

Quartz SiO2 +0.633 - +0.633 

Opal-CT SiO2 -0.267 - -0.267 

Gibbsite Al(OH)3 +0.402 +0.402 - 

Hydroxy Aluminum and Magnesium Silicates

Imogolite Al2SiO5.xH2O -0.897 -0.448 -0.897 

Hydroxy 

aluminium silicate 

Al2Si2O5(OH)4

-2.310 -1.155 -1.155 

Kaolinite Al2Si2O5(OH)4 +2.440 +1.220 +1.220 

Talc Mg3Si4O10(OH)2 -5.540 - -1.385 

Clinochlore Mg5Al2Si3O10(OH)8 +2.332 +1.166 +0.777 

Pyrophyllite Al2Si4O10(OH)2 +1.919 +0.959 +0.480 

Smectites

Beidellite-Ca Ca0.165Al2.33Si3.67O10(OH)2 +2.206 +0.947 +0.601 

Smectite-Ca Ca0.145Mg0.26Al1.77Si3.97O10(OH)2 +4.639 +2.621 +1.169 

Montmorillonite-Ca Ca0.165Mg0.33Al1.67Si4O10(OH)2 +2.175 +1.302 +0.544 

Phengites

Celadonite KMgAlSi4O10(OH)2 -0.355 -0.355 -0.089 

Illite K0.6Mg0.25Al1.8Al0.5Si3.5O10(OH)2 +1.647 +0.716 +0.544 

Feldspars

K-feldspar KAlSi3O8 +1.009 +1.009 +0.336 

Albite-low NaAlSi3O8 -1.887 -1.887 -0.629 

Carbonates

Calcite CaCO3 -0.283 - - 

Dolomite CaMg(CO3)2 -3.196* - - 

Alstonite BaCa(CO3)2 -2.435 - - 

Phosphates

Hydroxy-apatite Ca5(OH)(PO4)3 -4.992 - - 

Fluor-apatite Ca5(F)(PO4)3 +5.721 - - 

Crandallite CaAl3(PO4)(OH)5.H2O -0.230 -0.077 - 

Sulfates 

Barite BaSO4 -0.440 - - 

* Solubility product is based on data reported by Rock et al. (2001) 

To evaluate redox sensitivities, EQ3/6 was re-run specifying the redox state at successive 

increments ranging from –2 to +14 in units of pe (-log[e-]) (mol/kg H2O) at 2-unit pe intervals. The 
47 

principal aqueous species of Fe, Mn and selected trace elements are displayed for each pe increment 

in Table 5.6. Note that Mn, Co, Cd, Pb and Zn remain in the (II) state throughout the range of pe’s 

investigated. However, solid Mn and Fe phases coexisting with aqueous Mn and Fe do show 

changes in oxidation state. The dominant speciation for Pb and Zn also changes under strongly 

reducing conditions. Changes in aqueous speciation associated with changes in oxidation state are 

observed for Fe, Cu, Cr, Se, U, and NO3, but changes are not observed with respect to As, which 

remains in the As(V) state, and S (as SO4), which remains in the S(VI) state, although reducing 

conditions are likely to stabilize As(O), As(-I), As(-II), S(-I), and S(-II), respectively. 

The candidate elements that show the most potential for identifying redox controls over the 

expected range of values at the ZERT site appear to be Mn, Fe, Cr, Cu and Se. In the following 

evaluation, only Fe and Mn are addressed. The behavior of Cr, Cu, and Se are addressed in 

Appendix D. In this evaluation, the concentrations of all species in solution are held constant, in 

conformity with the average composition given in Table 5.4, regardless of the oxidation state 

specified by the pe. The calculations assume complete homogeneous equilibrium with respect to the 

groundwater, and the saturation index (SI) for each redox-sensitive solid phase is calculated. If the 

trend of calculated SI’s of a given redox-sensitive phase as a function of pe intersects the zero axis, 

i.e., SI = 0, then that phase is in equilibrium with the groundwater at the pe where SI = 0, regardless 

of the number of essential redox-sensitive components constituting that phase. For example, 

consider the mineral bornite (Cu5FeS4) (Appendix D, Figure D.2). In this mineral, all three elements 

can take up different equilibrium oxidation states in solution, depending on pe, as is illustrated in 

Table 5.6, i.e., Cu(II)/Cu(I), Fe(III)/Fe(II) an S(VI)/S(-II). The translation equation defining the 

solubility product of bornite in Data0.ymp.R4 of EQ3/6 is given by: 

Cu5FeS4 + 4H+ = Cu+ + Cu+2 + Fe+2 +4HS- (5-10) 

Each redox-sensitive species is also related to the primary basis redox-sensitive species by other 

translation equations defining the appropriate dissociation constants relating redox pairs, thus: 

Cu+

 + H+ +1/4O2(g) = Cu+2 +1/2H2O (5-11) 

Fe+3 + 1/2H2O =1/4O2(g) + Fe+2 + H+

 (5-12) 

HS- + 2O2(g) = SO4

-2 + H+

 (5-13) 

where 

O2(g) +4H+

 + 4e- = 2H2O; (5-14) 

pe  logK  log   O2  g 1

2 H  

  H2O 1

2

 (5-15) 

When EQ3/6 calculates the distribution of species in the aqueous phase, it ensures that all aqueous 

redox pairs are in a state of homogeneous equilibrium at the specified pe, defined in relation to 

O2(g) in the above-cited equation. Therefore, when SI(bornite) is calculated, it does so in relation to 

all equilibrated redox-sensitive species at the specified pe. In the following figures, and those given 
48 

in Appendix D, the SIs of redox-sensitive minerals for a given redox-sensitive component can be 

compared, regardless of the presence of any other redox-sensitive essential components in any 

given phase. 

In the following evaluation, the purpose is to identify coexisting pairs of redox-sensitive minerals 

that buffer the pe (Eh) of the system at equilibrium, i.e., where the stability fields of each intersect 

each other at equilibrium with the coexisting groundwater, which can be recognized by the 

intersection of their respective SIs, where both SIs = 0. In reality, the intersection may occur 

incrementally above or below SI = 0, because of uncertainties in the thermochemical data used in 

the analyses, analytical errors (which are accentuated near the detection limits for elements in 

solution), and other factors, such as temperature, ionic strength, and accountability of all aqueous 

complexes of the participating species. 

The saturation indices of relevant iron and manganese phases as a function of pe were tabulated and 

the data graphed as shown in Figures 5.3 and 5.4, respectively. To make meaningful comparisons 

between the saturation indices of different minerals of a given element, each saturation index was 

normalized to represent the stoichiometry of a mineral containing one mole of the referenced 

element, e.g., in the iron system, SI(magnetite (Fe3O4)) is divided by 3 to yield SI(FeO1.333). 

Table 5.6. Variation in principal aqueous species of selected redox-sensitive species as a function of pe at circumneutral pH (pH = 6.9). 

Aqueous Dominant Aqueous Species at Specified pe 

Species 14 12 10 8 6 4 2 0 -2 

Mn Mn+2 Mn+2 Mn+2 Mn+2 Mn+2 Mn+2 Mn+2 Mn+2 Mn+2

Fe FeO+ FeO+ FeO+ FeO+ Fe+2 Fe+2 Fe+2 Fe+2 Fe+2

Co Co+2 Co+2 Co+2 Co+2 Co+2 Co+2 Co+2 Co+2 Co+2

Cu Cu+2 Cu+2 Cu+2 Cu+2 Cu+2 Cu+ Cu+ Cu+ Cu+

Cd Cd+2 Cd+2 Cd+2 Cd+2 Cd+2 Cd+2 Cd+2 Cd+2 Cd+2

Pb PbCO3 PbCO3 PbCO3 PbCO3 PbCO3 PbCO3 PbSe PbSe PbSe 

Cr CrO4

-2 CrO4-2 CrO4-2 CrO+ CrO+ CrO+ CrO+ CrO+ CrO+ 

As FeAsO4(aq) FeAsO4(aq) FeAsO4(aq) FeAsO4(aq) FeAsO4(aq) FeAsO4(aq) FeAsO4(aq) AsSe(OH)(SeH)- AsSe(OH)(SeH)-

Se SeO4

-2 SeO4-2 SeO4-2 HSeO3-

 HSeO3

-

 HSeO3

-

 ZnSe FeSe FeSe 

Mo MoO4

-2 MoO4-2 MoO4-2 MoO4-2 MoO4-2 MoO4-2 MoO4-2 MoO4-2 MoO4-2

U UO2(CO3)2

-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2(CO3)2-2 UO2

Zn Zn+2 Zn+2 Zn+2 Zn+2 Zn+2 Zn+2 Zn+2 Zn(SCN)4

-2 Zn(SCN)4-2

NO3 NO3

-

 N2 N2 N2 N2 N2 N2 N2 N2

PO4 H2PO4- H2PO4- H2PO4- H2PO4- H2PO4- H2PO4- H2PO4- H2PO4- H2PO4- 

SO4 SO4

-2 SO4-2 SO4-2 SO4-2 SO4-2 SO4-2 SO4-2 SO4-2 SO4-2

HCO3 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 HCO3

-

 
49 

Figure 5.3. Normalized saturation indices of magnetite, goethite, siderite, green rust (fougerite-CO3) and Fe(OH)3

(ferrihydrite) plotted as a function of pe. 

Inspection of Figure 5.3 indicates that the phase boundary between fougerite-CO3 and Fe(OH)3

(ferrihydrite is located where SI(fougerite-CO2) –SI(Fe(OH)3) ≈ 0 at pH =6.82 and pe ≈ +9 (Eh ≈

+0.51 V). This oxidation potential is somewhat higher than that calculated for the boundary 

between green rust sulfate where pe ≈ +6 at the same pH, as calculated by Majzlan et al. (2004). 

However, these investigators used the thermodynamic properties for green rust sulfate estimated by 

Bourrie et al. (1999), which ignored the presence of Mg(II) substitution for Fe(II) in the trioctahedral sheets. This substitution considerably expands the stability field of naturally occurring 

fougerite in pe-pH space (Bourrie et al., 2004). 

Given the reactive nature of both fougerite-CO3 and ferrihydrite, and the potentially rapid 

transformation between one mineral and the other, we assert that the redox potential is most likely 

to be buffered through the coexistence of these two minerals. Note that detrital magnetite is also 

observed in the ZERT sediments (Section 4), and both fougerite and ferrihydrite could be 

reductively transformed to magnetite within the pe range between +2.5 and +13. However, the 

reaction is likely to be inhibited kinetically. The groundwater would also be supersaturated with 

respect to goethite at any pe ≥ 1. However, it is well recognized that the presence of SiO2(aq) 

inhibits the transformation of green rust and ferrihydrite to more stable oxy-hydroxides (Kwon et 

al., 2007). Finally, it should be noted that siderite remains unsaturated, i.e., SI(siderite) ≈ -2, even 

under reducing conditions where all dissolved Fe(T) is transformed to Fe(II), i.e., pe ≤ +4. In this 

context, it should be mentioned that at greater unsampled depths below the water table, reducing 

conditions could be such that all Fe(III) in metastable iron oxides, i.e., ferrihydrite and green rust, 

and presumed to be prevalent near the interface with the vadose zone, could be reduced to Fe(II) 

and transformed to siderite under ambient P(CO2). 
50 

Figure 5.4. Normalized saturation indices of pyrolusite, bixbyite, manganite, hausmannite and rhodochrosite, 

plotted as a function of pe. 

Examination of Figure 5.4, which displays the calculated normalized saturation indices of various 

manganese oxides, shows that pyrolusite (MnO2) would saturate at pe ≈ +11.5, bixbyite (Mn2O3) 

and manganite (MnOOH) at pe ≈ +12, and hausmannite (Mn3O4) at pe ≈ +14.5. Rhodochrosite 

remains undersaturated, that is, SI(rhodochrosite) ≈ -1.8, throughout the examined range of pe 

values (-2 < pe < +14). Thus, if any of the minerals pyrolusite, bixbyite, manganite, or hausmannite 

were present as pure substances, and in equilibrium with the groundwater, the pe would, at a 

minimum be ≈ +11 (for pyrolusite). However, given that the average crustal abundance of Mn is 

about 1.7% that of Fe, it is likely that most, if not all Mn is present in solid solution in reactive Fe 

oxy-hydroxides such as ferrihydrite or goethite, e.g., see Sileo et al. (2001). Thus, assuming an 

ideal solid solution in ferrihydrite, Mn+2 ions would be in equilibrium with a solid solution at pe ≈

12 – 1.8 = 10.2, which is about 1 pe unit higher that the pe estimated from the pe buffering 

equilibrium between fougerite-CO3 and Fe(OH)3 (ferrihydrite). Note that in the presence of 

significant concentrations of Mn in sediments, Fe(II) can reduce pyrolusite with concomitant 

precipitation of the manganese spinel, jacobsite (MnFe2O4), e.g., see Villinski et al. (2000). 

In summary, the foregoing analysis of the saturation indices of redox-sensitive minerals indicates 

that the redox potential of the system is to a large extent controlled by the metastable redox 

buffering equilibrium between fougerite-CO3 and ferrihydrite at a pe circa +9 (Eh ≈ +0.51 V). The 

observed initial concentration of Mn in solution is consistent with saturation with manganese oxide 

minerals at an oxidation state pe ≤ +11.5, but because the average crustal abundance of Mn is less 

than that of iron, it is likely that the system pe with respect to Mn is determined by a solid solution 

of Mn(II) in ferrihydrite, and therefore the pe would be << +11.5. Equilibrium between potential Cr 

oxide minerals suggests a pe-buffering phase equilibrium between Cr-ferrihydrite and chromite at 

pe ≈ +8.7, although both the thermodynamic data used in the interpretation and the potential 

involvement of solid solution substitution in Fe(III) bearing phases such as ferrihydrite discounts 
51 

the significance of this observation. Nevertheless, the behavior of the Cr system is consistent with 

those of Fe and Mn. 

The preponderance of the evidence from the foregoing analysis is that the pe of the system is 

probably buffered at approximately +9 ±1 (see also Appendix D regarding Cr minerals). This value 

is close to the pe value of +10 of the local partial equilibrium cluster of redox pairs controlled by 

nitrate observed in shallow Georgia groundwaters by Washington et al. (2004). However, 

examination of the behavior of Cu and Se minerals as a function of pe (see Appendix D) suggests 

that organic matter might also be playing a role with respect to the establishment of a lower pe 

cluster of redox pairs at pe ≈ +1. This compares with an average value of pe ≈ -2 determined by 

Washington et al. (2004) 

Note the distribution of Cr, Fe and Se species in solution at pe = +9, as shown in the following 

Table 5.7. With respect to Cr, Cr(VI) and Cr(III) species are present in sub-equal concentrations, 

i.e., 82 mol.% versus 18 mol.%. A similar situation obtains with respect to Se(VI) versus Se(IV) 

species with respective concentrations of 85.1 and 15 mol.%. With respect to Fe, however, Fe(III) 

dominates Fe(II) by about 103

. It is possible that all three species are impacted by NO3

-

/NO2

-

 in 

solution, although unfortunately, the concentration of NO2

-

 was not measured in groundwater 

samples from the ZERT site. 

Table 5.7. Distribution of the predominant Cr, Fe and Se species in solution at pH = 6.82 and pe = +9 

Species Molality Percentage 

Chromium Species 

CrO4

-2 1.99E-08 43.4 

CaCrO4(aq) 1.11E-08 24.2 

HCrO4

-

 6.55E-09 14.31 

CrO+ 6.43E-09 14.04 

CrOH+2 1.80E-09 3.92 

HCrO2(aq) 4.58E-11 1.00E-01 

Cr+3 8.91E-12 1.95E-02 

Iron Species

FeO+ 1.28E-07 41.83 

HFeO2(aq) 1.05E-07 34.49 

Fe(OH)2F(aq) 5.44E-08 17.83 

Fe(OH)3H3SiO4

-

 1.73E-08 5.68 

FeOH+2 1.49E-10 4.89E-02 

Fe+2 1.33E-10 4.36E-02 

Selenium Species

SeO4

-2 2.59E-08 85.1 

HSeO3

-

 3.16E-09 10.38 

SeO3

-2 1.37E-09 4.51 
52 

5.2.3 Evolution of Calcite Saturation Indices During Injection 

Examination of core material from the ZERT site shows that coatings of secondary calcite are 

ubiquitous throughout the section, including that section below the water table from which 

groundwater samples were drawn for analysis. It would therefore not be surprising if a 

thermodynamic analysis showed that initial groundwater samples taken prior to injection of carbon 

dioxide were saturated with respect to calcite. However, it must be recognized that the equilibrium 

state of the shallow subsurface environment at that ZERT site is subject to perturbations due to 

seasonal and long-term variations in the following parameters: 

 Fluctuations in temperature 

 Groundwater recharge, leading to fluctuations in the height of the water table. 

 Infiltration of rainwater 

 Evapotranspiration from the vadose zone 

 Capillary transport 

 Bio-metabolism 

That some or all of these processes are operative is evident from the detection of a caliche horizon 

within the vadose zone approximately one meter below the surface. An extensive body of literature 

exists which describes the listed processes in relation to the formation of caliche zones under 

various climatic conditions, and which could aid in interpreting how these processes might impact 

groundwater composition and trace element distributions at the ZERT site. However, time 

limitations permit only a cursory examination of changes in calcite saturation in response to CO2

injection during the test. 

Table 5.8 shows the calculated saturation indices of calcite and calculated P(CO2) for each 

groundwater sample based on a thermodynamic analysis using the code EQ3/6 (Wolery, 1992, 

1993). The groundwater samples are those taken between the start of the sampling program and the 

first significant rainfall, i.e., between July 7 and July 17, 2008. The calculations incorporate an 

adjustment to the analytical value of HCO3 to account for bicarbonate complexation, and entry of 

the corrected HCO3

-

 as a “free” concentration to force the code to calculate the concentration of 

dissolved CO2 in equilibrium with the “free” bicarbonate concentration. Each calculation was 

conducted at the measured temperature for each groundwater (≈ 10oC). Also included in Table 5.8 

is the calculated charge imbalance, as a percentage of total charge for each groundwater chemical 

analysis. The charge imbalances are, with the exception of samples 124 and 128, within the 

acceptable limits of ±5%, and might generally be considered as excellent. 

Figure 5.5 is a graphical representation of the same data. It is clear that the increase in ambient 

P(CO2) leads to undersaturation of the groundwater with respect to calcite and the rate of 

dissolution of the calcite is insufficient to maintain equilibrium. The trend is irregular and shows 

considerable scatter, which would be expected of a system where samples are taken from different 

wells at different depths in a soil system that is vertically heterogeneous, and probably also laterally 

heterogeneous. Also plotted on Figure 5.5 are three trend lines. Trend Line A assumes the 

approximate path taken with respect to calcite resaturation as P(CO2) increases. This path would 

vary depending on the rate of CO2 saturation of the groundwater, the kinetics of calcite dissolution, 

calcite surface area and abundance, and groundwater flow rates. Path A is constrained by the other 

two trend lines. Trend Line B is the path taken under static conditions where resaturation of calcite 

occurs after instantaneous saturation of the groundwater with CO2 at a pressure of 1 bar, the 
53 

approximate limit of saturation expected at the ZERT site. Trendline C assumes that no dissolution 

of calcite takes place upon uptake of CO2. It is evident that about half of the water samples taken 

between July 7 and July 17, 2008 reflect this state of affairs (close to trendline C), and that only 

after log P(CO2) exceeded ≈ -0.7, equivalent to 0.2 bar, did significant dissolution of calcite occur. 

From the start of the test until the first significant rainfall, the water table fell progressively, which 

suggests that the water table was still responding to some rainfall event preceding the start of the 

test, due either to drainage, or to evapotranspiration. Dilution by rainfall could explain the initial 

degree of undersaturation of calcite, and this observation is indirectly corroborated by the observed 

undersaturation with respect to opal-CT and amorphous hydroxy-aluminosilicates (HAS). For this 

reason, it is less likely that the initial undersaturation might be due to transient elevation of P(CO2) 

due to aggressive mineralization of carbonaceous material by bacteria. 

Table 5.8. Calculated calcite saturation index and CO2 partial pressure for groundwaters taken at the ZERT site 

between July 7 and July 17, 2008 

ZERT 

Sample 

No. 

Charge 

Imbalance. 

% 

SI(Calcite) 

(-) 

Log P(CO2) 

(bars) 

102 -1.20 -0.377 -1.3113 

103 -4.10 -0.342 -1.2739 

104 -0.30 -0.156 -1.3567 

105 -1.73 +0.691 -0.951 

106 0.15 -0.301 -1.4203 

107 0.65 -0.524 -1.2369 

109 0.96 -0.090 -1.4708 

112 0.74 -0.566 -0.9664 

116 -2.00 -0.369 -0.3542 

117 2.94 -1.237 -0.0961 

118 0.78 -0.415 -0.7166 

119 0.08 -0.178 -1.5106 

124 -7.69 -0.492 -0.0881 

126 0.63 -0.781 -0.7594 

127 0.09 -0.856 -0.1881 

128 8.11 -0.715 -0.1458 

129 -2.95 -0.588 -0.1579 

130 -1.20 -0.759 -0.7421 

131 -1.30 -0.827 -0.1648 

132 -2.39 -0.692 -0.09 
54 

 

Figure 5.5. Saturation index of calcite as a function of log P(CO2) calculated for groundwater samples taken 

between July 7 and July 17, 2008 at the ZERT site. For an explanation of the trend lines, please refer to 

the text. 

5.2.4 Findings from Geochemical Evaluations 

This section summarizes the principal findings of the foregoing geochemical evaluations. These 

findings have been useful in setting up the geochemical model described in Section 5.3 below. 

 Principal Component Analysis of the initial perturbation (first 10 days of the test) in 

groundwater quality due to CO2 uptake shows strong positive linear correlations between the 

transformed logarithmic concentrations of many of the measured species. The first principal 

component, PC1, correlates strongly with monovalent, divalent and trivalent cations, 

suggesting that ion exchange on smectite might be the mechanism responsible for their 

release. The positive correlation between various anionic species: HCO3, SO4, Mo (as MO4) 

and Se (as SeO3 or SeO4) and PC1 also suggest a common mechanism involving either ion 

exchange or adsorption. However, NO3 and PO4 are negatively correlated. The second 

principal component, PC2, correlates strongly with F, and relatively weakly with As, Se and 

Mo, and inversely, but weakly with H and K, suggesting some anionic exchange or 

adsorption process. The third principal component, PC3, correlates inversely with Mn, Co 

and Cl, and directly with As, NO3 and PO4, suggesting precipitation control by a transition 

metal phosphate. PC4 correlates with Cl and SO4, which may be related to earlier infiltration 

of rain water from the overlying vadose zone. Not all correlation trendlines between the 

various species are readily explained, highlighting the need for more in-depth study of the 

geochemistry of shallow groundwater systems (Section 5.2.1). 

 Thermodynamic evaluation of the groundwater chemistry before CO2 injection reveals a 

species distribution that reflects rapid weathering and the formation of metastable hydroxy-
55 

aluminum silicates. The initial groundwater is slightly undersaturated with respect to calcite, 

opal-CT and barite, suggesting dilution of the groundwater by rainwater prior to the test. 

Supersaturation with respect to smectites, illite and kaolinite and gibbsite is indicative of 

saturation by persistent metastable hydroxy-aluminum silicates (Section 5.2.2). 

 Examination of the degree of supersaturation of redox sensitive minerals as a function of pe 

(or Eh) suggests that the redox potential is most likely buffered by the coexistence of 

fougerite-CO3 and Fe(OH)3 (ferrihydrite) at a pe ≈ +9. However, there are also indications 

that the concentrations of some trace elements, e.g., Cd, Cu, Pb, may be controlled by 

precipitation of reduced species such as CdSe, Cu2O and PbSe. This suggests that decaying 

organic matter might be exercising reductive control over these, and possibly other species, 

which implies that the system redox state is not in equilibrium, and may also be spatially 

inhomogeneous. The distribution of species, therefore, may be kinetically controlled 

(Section 5.2.2). 

 Examination of the perturbation in calcite saturation following injection of CO2 shows that 

calcite immediately became significantly undersaturated, but recovery of the saturation 

states was slow and incomplete during the first ten days of the test (Section 5.2.3). 

5.3 Geochemical Modeling 

Geochemical simulations were run to test some of the observations discussed earlier, namely that 

ion exchange and sorption processes, together with dissolution of carbonates, could explain the 

water chemistry trends observed during the test (Zheng et al., 2009a). Additional modeling work 

incorporating transport processes was not warranted because of the relatively limited set of field 

data, as well as uncertainties regarding groundwater flow and CO2 transport (e.g., Section 5.1), 

subsurface heterogeneity, and rainfall effects. It should be noted that geochemical changes in 

groundwater after the release of CO2 were fairly rapid and even, occurring almost simultaneously in 

wells 1B, 2B and 5B (Section 3). Furthermore, PCA analyses (Section 5.2) reveal similar 

groundwater chemistry responses to CO2 injection at the different monitored locations. This 

suggests that “batch” simulations, focused solely on reactive processes induced by increasing levels 

of CO2, are a good modeling approach in this case, with little more to gain from more sophisticated 

simulations including transport. The simulations were performed using, TOUGHREACT (Xu et al., 

2006), which was enhanced through incorporation of surface complexation and ion exchange 

models to compute the distribution of adsorbed chemical species on mineral surfaces (Zheng et al., 

2009b). 

Rainfall was shown to significantly affect groundwater chemistry during the test (Section 3). 

Because of the limited amount of rainfall-related data (including composition, recharge rates, and 

oxidation/mixing effects in the subsurface), and because PCA analyses (Section 5.2.1) focused on 

the groundwater chemistry data before the first rainfall, the geochemical simulations discussed 

below were based solely on groundwater data collected before the first rainfall. 

 

5.3.1 Model setup 

A “batch” (single-gridblock) geochemical model was developed, with initial conditions 

representative of field conditions prior to CO2 injection (Table 5.9). CO2 was then (numerically) 
56 

injected into the modeled system, and model results were examined as a function of pH. As 

discussed previously, the CO2 volume fractions measured in the head space of groundwater 

monitoring wells increased rapidly (within a day to a few days) to levels up to 0.9 (90% by 

volume), corresponding to P(CO2) values near 1 bar at the water table soon after injection. CO2 was 

injected into the model gridblock until the computed pH value fell from an initial value ~7.1 to a 

value near 5.8, consistent with the field measurements. At this point, the calculated maximum 

P(CO2) was around 1.5 bar. Instantaneous equilibration of gaseous CO2 with the aqueous phase was 

assumed. Other elements of the model are described below. Simulations were carried out assuming 

an initial temperature of 10°C and an initial pressure close to atmospheric values. 

Initial conditions

Seven groundwater samples were taken before the release of CO2. The initial chemical composition 

for the model (Table 5.9) was taken from one of these samples (i.e., 08ZERT-107), with initial pH 

adjusted slightly from 6.7 to 7.1 so that our calculation covers the pH range of all samples 

considered in this study. An initial aqueous speciation was conducted with EQ3 (Wolery, 1993) to 

verify charge balance and evaluate the water saturation with respect to several minerals. The initial 

partial pressure of CO2 in the groundwater was calculated to be 2.5×10-2 bars. Furthermore, calcite 

was close to saturation, i.e., SI(calcite) ≈ –0.1 (–0.3 at pH 6.7). 

As pointed out in Section 5.2, redox is not likely to have reached equilibrium in this shallow, lowtemperature system. This complicates the use of geochemical models such as the one applied here, 

because these models rely on the assumption of redox equilibrium to calculate the distribution of 

redox-sensitive species. Here, the initial redox state of the groundwater is calculated from the 

Fe(II)/Fe(III) equilibrium using the measured (total) Fe concentration in water and assuming 

equilibrium with goethite, yielding a pe ~ 1.7. Assuming equilibrium with ferrihydrite and fougerite 

(green rust) would result in a significantly higher value (pe ~9) (Section 5.2.2). This range of pe 

values suggests suboxic (but not strongly reducing) conditions prevail at the site. Note that 

measured Eh values (150–200 mV, Section 3) correspond to pe ~ 2.5–3.5. However, as discussed in 

Section 5.2.2, measured potentials represent mixed potentials that are not representative of a 

specific redox couple and that may be biased by the redox sensor. Given these uncertainties, and the 

fact that redox equilibrium is assumed in the simulations, model results regarding redox species 

should be viewed as qualitative rather than quantitative. Obviously, the choice of pe affects model 

results for redox-sensitive species. However, in this modeling case, the amount of solid Fe for 

sorption is unknown and adjusted to match observed groundwater compositions. Therefore, 

assuming a higher pe would likely be compensated by this calibration such that, qualitatively, 

model results would not be expected to change significantly if a different pe was used. 
57 

Table 5.9. Primary species and their initial concentration 

Species Concentration 

(mol/L) Species Concentration (mol/L) 

pH 7.1 Ba+2 7.9E-07 

Ca+2 1.9E-03 Cd+2 2.0E-09 

Mg+2 9.8E-04 Co+2 4.2E-09 

Na+

 3.3E-04 Cu+2 2.4E-08 

K+

 1.4E-04 H2AsO4

-

 1.3E-08 

Fe+2 1.8E-09 Mn+2 1.8E-08 

AlO2

-

 1.2E-07 Sr+2 3.0E-06 

SiO2(aq) 5.3E-04 Zn+2 4.6E-08 

Cl-

 1.3E-04 HSeO3

-

 4.9E-08 

HCO3

-

 6.3E-03 MO4

-2 4.6E-09 

SO4

-2 7.7E-05 UO2+2 1.7E-08 

NO3

-

 9.6E-06 Cr(OH)2

+

 2.2E-07 

O2(aq)1

 1.2E-51 HPO4

-2 1.8E-06 

Pb+2 2.4E-10 Li+

 7.7E-07 1

Corresponds to pe ~ 1.7, Eh ~ 100 mV (see text) 

Mineralogy 

Section 4.2 describes the mineralogical analyses of cored sections to a depth of approximately 3 m. 

Sediments in the saturated zone are composed predominantly of a matrix of cobble-sized rounded 

fragments, consisting primarily of andesitic volcanic rocks with predominant plagioclase, quartzbiotite-amphibole gneiss, and red granite/gneiss. The mafic volcanic rock fragments are very high in 

magnetic iron. Minor limestone and occasional dolomite fragments are also observed in the matrix. 

Unspecified Fe oxides appear in a <0.25 mm fraction as “powdery orange blebs.” Secondary 

carbonate coatings are found throughout the core, and a caliche zone is present in the overlying 

unsaturated zone. Small quantities of clay (~1 wt%), believed to consist of smectite and minor 

kaolinite are also found in the saturated zone. The list of minerals considered in the geochemical 

model (Table 5.10) was based on these observations, as well as on the discussions in Section 5.2. 

Arbitrary volume fractions are assigned to each mineral, which are roughly consistent with the 

mineralogy analyses. It should be noted that in the time frame of the simulation described in this 

report, most of the listed rock-forming minerals are essentially inert, i.e., they are mostly unreactive 

during the short injection period, as discussed later. 

Table 5.10. Minerals considered in the model. 

Primary Mineral Volume fraction Primary Mineral Volume fraction 

Quartz 0.45 Ferrihydrite 0.01 

K-feldspar 0.1 Magnetite 0.02 

Oligoclase 0.34 Goethite 0.001 

Smectite 0.01 Siderite 0.001 

Dolomite 0.02 Calcite 0.05 

Chemical reactions and equilibrium/kinetic constraints

Chemical reactions considered in the model include aqueous complexation, cation exchange, 

adsorption/desorption, and mineral dissolution/precipitation. Of these, cation exchange and 
58 

adsorption/desorption reactions are believed to predominate (see Section 5.2.1). Table 5.11 lists 

aqueous complexes included in the simulation and their dissociation constants which are from 

database data0.ymp.R4 (Wolery and Jareck, 2003; Wolery and Jove-Colon, 2007). Table 5.12 lists 

the cation exchange reactions and their selectivity coefficients. The Gaines-Thomas convention is 

used here. The selectivity coefficient for exchangeable H+

 is taken from Charlet and Tournassat 

(2005), and those for the remainder of the exchangeable cations are taken from Appelo and Postma 

(1994). The cation exchange capacity (CEC) is the key parameter for the calculation of cation 

exchange. Because the measured CEC for the sediments at ZERT site is not currently available, we 

used a CEC value of around 12 meq/100g measured for Hanford sediments (Steefel et al., 2003), 

which has similar composition to the sediments at the ZERT site. A nonelectrostatic surface 

complexation model calculates adsorption/desorption, which involves most anions and H+

. Table 

5.13 lists the surface complexation reactions. Surface complexation constants are taken from 

Dzombak and Morel (1990). Hydrous ferric iron oxide (HFO) is assumed to be the only adsorbent. 

The site density for the strong site is assumed to be 1.76×10-6 mol/m2

, and that for weak sites is 

assumed to be 3.22×10-6 mol/m2 (Muller and Sigg, 1991). The specific surface area is assumed to be 

14.7 m2

/g (Muller and Sigg, 1991). The amount of HFO for sorption was (loosely) calibrated to 

metal concentrations in groundwater using these data. 

Table 5.11. Aqueous complexes and their dissociation constants 

Species Logk (25o

C) Species Logk (25oC) Species Logk (25oC) Species Logk (25oC)

OH- 13.991 Al(OH)2

+

 -12.78 Cu(CO3)2

-2 10.476 SrOH+

 13.292 

CaHCO3

+

 -1.043 AlOH+2 -17.868 NaHCO3(aq) -0.17 UO2(CO3)2

-2 3.747 

FeHCO3

+

 -2.044 Al13O4(OH)24+7 -198.749 NaSO4

-

 -0.811 UO2(CO3)3

-4 9.43 

FeCO3(aq) 4.879 CdCl+

 -1.966 NaCl(aq) 0.782 UO2(CO3) (aq) 0.663 

CO2(aq) -6.342 HCOO2

-

 21.243 PbCl+ -1.456 UO2(OH)2(aq) 10.315 

CO3

-2 10.325 HAsO4-2 6.754 PbCl2(aq) -2.016 Cr(OH)3(aq) 8.3 

MgHCO3

+

 -1.033 MnCO3(aq) 5.809 SrSO4(aq) -2.271 Cr(OH)+2 -5.7 

MgSO4(aq) -2.382 MnHCO3

+

 -0.882 SrCO3(aq) 7.47 CaHPO4(aq) -2.69 

CaSO4(aq) -2.1 BaCO3(aq) 7.691 SrCl+

 0.253 MgHPO4(aq) -2.91 

HAlO2(aq) -6.448 CuOH+

 7.287 SrNO3

+

 -0.796 
59 

Table 5.12. Cation exchange reactions and selectivity coefficients. 

Cation exchange reaction KNa/M

Na+ + X-H = X-Na + H+ 1 

Na+

 + X-K = X-Na + K+ 0.2 

Na+

 + 0.5X-Ca = X-Na + 0.5Ca+2 0.4 

Na+

 + 0.5X-Mg = X-Na + 0.5Mg+2 0.45 

Na+

 + 0.5X-Pb = X-Na + 0.5Pb+2 0.4 

Na+

 + 0.5X-Ba = X-Na + 0.5Ba+2 0.35 

Na+

 + 0.5X-Cd = X-Na + 0.5Cd+2 0.4 

Na+

 + 0.5X-Co = X-Na + 0.5Co+2 0.6 

Na+

 + 0.5X-Cu = X-Na + 0.5Cu+2 0.5 

Na+

 + 0.5X-Mn = X-Na + 0.5Mn+2 0.55 

Na++0.5X-Sr = X-Na + 0.5Sr+2 0.35 

Na++0.5X-Zn = X-Na + 0.5Zn+2 0.4 

Na++0.5X-Fe = X-Na + 0.5Fe+2 0.6 

Table 5.13. Surface complexation reactions and surface complexation constants (logK) on HFO 

Surface complexation logK 

HFO_sOH2

+

 = HFO_sOH + H+ -7.29 

HFO_wOH2

+

 = HFO_wOH + H+ -7.29 

HFO_sO- + H+ = HFO_sOH 8.93 

HFO_wO- + H+ = HFO_wOH 8.93 

HFO_sOHSO4

-2 = HFO_sOH + SO4-2 -0.79 

HFO_wOHSO4

-2 = HFO_wOH + SO4-2 -0.79 

HFO_sSO4

-

 + H2O = HFO_sOH + SO4

-2 + H+ -7.78 

HFO_wSO4

-

 + H2O = HFO_sOH + SO4

-2 + H+ -7.78 

HFO_sSeO3

-

 + H2O = HFO_sOH +HSeO3

- -4.29 

HFO_wSeO3

-

 + H2O = HFO_wOH +HSeO3

- -4.29 

HFO_sMoO4

-

 + H2O = HFO_sOH + MoO4

-

 + H+ -9.5 

HFO_wMoO4

-

 + H2O = HFO_wOH + MoO4

-

 + H+ -9.5 

HFO_sOHMoO4

-2 = HFO_sOH + MoO4-2 -2.4 

HFO_wOHMoO4

-2 = HFO_wOH + MoO4-2 -2.4 

HFO_sH2AsO4 + H2O = HFO_sOH + H2AsO4

-

 + H+ -10.17 

HFO_wH2AsO4 + H2O = HFO_wOH + H2AsO4

-

 + H+ -10.17 

HFO_sHAsO4

- + H2O = HFO_sOH + H2AsO4- 0.35 

HFO_wHAsO4

- + H2O = HFO_wOH + H2AsO4- 0.35 

HFO_sH2PO4 + H2O = HFO_sOH + HPO4

-2 + 2H+ -18.9 

HFO_w H2PO4 + H2O = HFO_wOH + HPO4

-2 + 2H+ -18.9 

HFO_sPO4

-2 + H2O = HFO_sOH + HPO4-2 -5.4 

HFO_wPO4

-2 + H2O = HFO_wOH + HPO4-2 -5.4 

HFO_wCO2

- + H2O = HFO_sOH + HCO3- -2.45 

HFO_wCO2H + H2O = HFO_sOH + HCO3

-

 + H+ -2.45 
60 

All minerals are set to react under kinetic constraints. Currently, TOUGHREACT (Xu et al., 2006) 

uses a general form of kinetic rate law based on the transition state theory (TST) (Lasaga et al., 

1994; Steefel and Lasaga, 1994): 

r kA Q K 1 /             (5-16) 

where r is the kinetic rate (positive values indicate dissolution, negative values precipitation), k is 

the rate constant (moles per unit mineral surface area and unit time), which is temperature 

dependent, A is the specific reactive surface area per kg H2O, K is the equilibrium constant for the 

mineral–water reaction, and Q is the reaction quotient. Here, the parameters θ and η are assumed 

equal to unity, and surface areas are estimated based on Xu et al. (2006). For further details 

concerning the kinetics of mineral dissolution/precipitation, the reader is referred to Xu et al. 

(2006). 

Tables 5.14 and 5.15 list the equilibrium constants (as log(K)) and rate constants (k), respectively, 

for minerals included in the simulations. Except for siderite, equilibrium constants are from 

database data0.dat.ymp.R4 (Wolery and Jareck, 2003; Wolery and Jove-Colon, 2007). The 

equilibrium constant for siderite was calculated from more recent data from Preis and Gamsjager 

(2002), and differs slightly from that adopted in data0.ymp.R4. The value of Q/K in Equation 5-16 

dictates whether dissolution or precipitation occurs. In the present case, all minerals dissolve. 

However, except for calcite and siderite, the calculated dissolution rates are very small (relative to 

the length of the test) and do not affect model results. 

The dissolution rate of calcite is critical, because the increase of Ca+2 resulting from calcite 

dissolution affects cation exchange, which may be responsible for the increases in major cations and 

most trace metals except for Fe and possibly Mn and Co (Section 5.3.2). Depending on the level of 

undersaturation, according to Kaufmann and Dreybrodt (2007), the dissolution of calcite can be 

described by a fast and a slow rate law. The fast and slow rate laws are discriminated by the ratio of 

calcium concentration in the solution to the calcium concentration in equilibrium with calcite 

(C/Ceq) at a given CO2 partial pressure. Kaufmann and Dreybrodt (2007) reported that when the 

ratio (C/Ceq) is <0.3, the fast rate law applies, whereas when C/Ceq > 0.3, the slow rate law applies. 

In the current simulations, C/Ceq is about 0.4–0.5, and thus the slow rate law of Kaufmann and 

Dreybrodt (2007) is adopted, with the rate constant k (Equation 5-16) equal to 1.6×10-6 mol/m2

/s. 

Svensson and Dreybrodt (1992) investigated the dissolution kinetics of calcite in CO2-water 

systems approaching calcite equilibrium and gave a rate constant k of 1.6×10-6 – 2.2×10-6 mol/m2

/s, 

although they indicated that C/Ceq should be around 0.6–0.8. Gledhill and Morse (2006) reported 

that the dissolution rate depends on brine composition, P(CO2) (0.1–1 bar), and temperature and the 

rate constant (k) can be estimated from a multiple regression model. Applying their regression 

model to our simulation conditions, the rate constant is from 1.6×10-6 to 2.2×10-5 mol/m2

/s. Jordan 

and Rammensee (1998) gave a dissolution rate of 1.6×10-6 mol/m2

/s on the calcite surface obtained 

by scanning force microscopy, which corresponds well to the rates obtained from batch experiments. Pokrovsky et al. (2005) measured the dissolution rate of calcite at high pressure, which is 

more relevant to deep CO2 geological storage than CO2 releases at the ZERT site. Therefore, these 

various published dissolution rates for calcite at lower levels of undersaturation are all quite 

consistent with the value selected for this study. 
61 

The baseline model considers only cation exchange for iron. However, sensitivity analyses were 

conducted to consider the dissolution of green rust (fougerite) and siderite. Note that siderite is 

initially undersaturated (SI ≈ -1.5) and thus unlikely to be present, except possibly as a detrital 

phase. For siderite, the kinetic rate reported by Duckworth and Martin (2004) is adopted. These 

investigators studied the dissolution of siderite under both oxic and anoxic conditions at 298 K, and 

fitted their measured data to a mechanistic kinetic equation similar to that employed in 

TOUGHREACT. The rate constant is given for both neutral and acid dissolution mechanisms: 

+

2 [H O] [H ] n H kk k   (5-17) 

with kn = 10-8.65 mol/m2

/s and kH = 10-4.6 mol/m2/s, respectively. The dissolution rate is dominated 

by the neutral mechanism when pH > 5.5, whereas the acid mechanism becomes important when 

pH < 5.5. Testemale et al. (2009) confirmed that the dissolution rate constant of siderite at acid 

condition (pH < 4) can be expressed as: 

 + [H ] H k k  (5-18) 

with kH = 10-9.3 mol/cm2

/s (kH = 10-5.3 mol/m2/s) which is close to the kH given by Duckworth and 

Martin (2004). Testemale et al. (2009) compared their findings with other data (Braun, 1991; 

Golubev et al., in press) and concluded that published kinetic rates for siderite dissolution are 

generally in good agreement. Duckworth and Martin (2004) also mentioned that the dissolution of 

siderite is retarded under oxic conditions, due to armoring by Fe (hydr)oxides. At the ZERT site, the 

proximity of the water table to ground surface and presence of secondary ferric oxy-hydroxides 

suggest oxic to suboxic conditions may prevail, at least during rainfall events. Therefore, the 

siderite dissolution rate adopted for the model could be underestimated. 

The initial water is supersaturated with respect to green rust (SI ≈ 0.3, normalized to 1 Fe), although 

this mineral readily dissolves upon pH decrease. Its dissolution rate is taken from Williams and 

Scherer (2001) with kn = 10-8.82 mol/m2

/s and kH = 10-2.6 mol/m2/s (Equation 5-16). 

Table 5.14. Equilibrium constants for minerals1

 

Primary 

Mineral 

log(K) Primary Mineral log(K) 

Quartz -3.75 Ferrihydrite -63.24 

K-feldspar -22.91 Magnetite -6.505 

Oligoclase -97.78 Goethite -8.12 

Smectite -39.51 Siderite -0.251 

Dolomite 2.524 Calcite 1.85 

Fougerite 24.24 

1

 For dissolution in terms of species shown in Table 5.9 
62 

Table 5.15. Initial volume fraction and kinetic parameters for minerals considered in the model1

Parameters for Kinetic Rate Law 

Mineral Volume Neutral Mechanism Acid Mechanism Base Mechanism 

fraction 

A 

(cm2/g) k25

(mol/m2/s) 

k25 

(mol/m2/s)

 n(H+

) k25 

(mol/m2/s)

 n(H+

) 

Quartz 0.45 9.8 1.02310-14 – – – – 

K-feldspar 0.1 9.8 3.8910-13 8.7110-11 0.5 6.3110-12 -0.823 

Oligoclase 0.338 9.8 1.4410-12 2.1310-10 0.457 – – 

Smectite 0.01 151.6 1.6610-13 1.0510-11 0.34 3.0210-17 -0.4 

Dolomite 0.02 9.8 2.9510-8 6.4610-4 0.5 – – 

Ferrihydrite 0.01 12.9 2.3410-7 1 – – 

Magnetite 0.02 9.8 4.5710-10 4.1710-7 1 – – 

Goethite 0.001 12.9 2.5210-12 – – – – 

Siderite 0.001 22.3 2.2410-9 2.510-5 0.75 – –

Calcite 0.05 3.05 1.610-6 – – – –

1 Kinetic data from Xu et al. (2006), except for calcite (Kaufmann and Dreybrodt 2007) and siderite (Duckworth and Martin, 2004), see text. 

5.3.2 Results and Discussion 

Earlier generic studies of CO2 leakage into potable groundwater aquifers (Birkholzer et al., 2008; 

Wang and Jaffe, 2004; Zheng et al., 2009b) indicated that the dissolution of carbonate minerals 

(mainly calcite) can significantly buffer the pH decrease accompanying the dissolution of CO2 in 

water (from the dissociation of carbonic acid). Clay ion exchangers, when present in significant 

amounts in an aquifer host rock or sediment, can also strongly buffer pH through exchange of H+

with the groundwater (Bradbury and Baeyens, 1997; Samper et al., 2008; Zheng and Samper, 2009; 

Zheng et al., 2009c). In the present model, the dissolution of calcite, dolomite and siderite, and H+

buffering through cation exchange and surface complexation could all contribute to buffering pH. 

Figure 5.6 shows the calculated pH by different combinations of these chemical equilibria. A 

simulation without carbonate minerals leads to a lower pH than the base case where the presence of 

carbonates is assumed, but is only marginally higher than the simulation without any buffering. This 

suggests that at the ZERT site, dissolution of carbonate minerals is the principal pH buffering 

process, whereas the H+

 exchange by clays does not affect pH significantly, because the shallow 

saturated zone at the ZERT site soil does not contain large amounts of clay minerals, and the pH 

decrease is only moderate. 

5

5.5

6

6.5

7

7.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Fugacity of CO2 (bar)

pH

base case

no carbonate minerals

no carbonate mineral + no protonation

Figure 5.6. Calculated pH with different combination of chemical reactions 
63 

The groundwater at the ZERT site responds promptly to the release of CO2. The pH falls within 1 or 

2 days from the start of injection, and a significant increase in major cations and trace metals is 

observed before the first rainfall occurs, about 10 days later. In such a short-duration test, only the 

dissolution kinetic rates for rapidly dissolving minerals such as calcite are important. As noted 

earlier, the dissolution rate of calcite is critical, because the resulting increase of Ca+2 induces cation 

exchange, which may be responsible for the increases in major cations and most trace metals except 

for Fe and possibly Mn and Co. The value adopted in this study falls within the lower range of 

published values (Section 5.3.1) and yields results consistent with measured changes in calcium 

concentration observed in the field (Figure 5.7). If a higher calcite dissolution rate is used, such as 

that given by Gledhill and Morse (2006), i.e., 2.2×10-5 mol/m2

/s, the computed calcium 

concentration overestimates the measured data (Figure 5.7). 

As pH decreases, calcite dissolves and releases Ca+2 into the aqueous phase. Aqueous Ca+2 in turn 

exchanges with the exchangeable cations on the cation exchanger, tentatively assumed to be 

smectite. As a result, the concentrations of all the major cations increase in solution. Figures 5.8–

5.10 show the calculated sodium, potassium, and magnesium concentration versus pH. The close 

agreement between calculated and measured concentrations supports the hypothesis that cation 

exchange may indeed dominate the evolution of major cations in response to the CO2 injection at 

the ZERT site. 

0E+00

1E-03

2E-03

3E-03

4E-03

5E-03

6E-03

7E-03

8E-03

9E-03

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Ca (mol/L)

measured data

base model k-calcite = 1.6e-6

sensitivity run k-calcite = 2.2e-5

Figure 5.7. Calculated calcium concentration vs pH with different calcite dissolution rate. 

0.E+00

1.E-04

2.E-04

3.E-04

4.E-04

5.E-04

6.E-04

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Na (mol/L)

measured data

model results

Figure 5.8. Calculated sodium concentration vs pH. 
64 

0.E+00

5.E-05

1.E-04

2.E-04

2.E-04

3.E-04

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

K (mol/L)

measured data

model results

Figure 5.9. Calculated potassium concentration vs pH. 

0.E+00

5.E-04

1.E-03

2.E-03

2.E-03

3.E-03

3.E-03

4.E-03

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Mg (mol/L)

measured data

model results

Figure 5.10. Calculated magnesium concentration vs pH. 

Figures 5.11-5.14 show the calculated trace metal concentrations for lead, cadmium, copper, and 

zinc. With the exception of Zn, which PCA shows to behave anomalously, reasonable matches 

between calculated and measured concentrations again suggest that the calcium-driven cation 

exchange could explain the observed trace metal response to CO2 injection. 

0.E+00

1.E-10

2.E-10

3.E-10

4.E-10

5.E-10

6.E-10

7.E-10

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Pb (mol/L)

measured data

model results

Figure 5.11. Calculated lead concentration vs pH 
65 

0.E+00

1.E-09

2.E-09

3.E-09

4.E-09

5.E-09

6.E-09

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Cd (mol/L)

measured data

model results

Figure 5.12. Calculated cadmium concentration vs pH 

0.0E+00

5.0E-09

1.0E-08

1.5E-08

2.0E-08

2.5E-08

3.0E-08

3.5E-08

4.0E-08

4.5E-08

5.0E-08

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Cu (mol/L)

measured data

model results

Figure 5.13. Calculated copper concentration vs pH 

0.0E+00

2.0E-08

4.0E-08

6.0E-08

8.0E-08

1.0E-07

1.2E-07

1.4E-07

1.6E-07

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Zn (mol/L)

measured data

model results

Figure 5.14. Calculated zinc concentration vs pH 

The baseline model, which considers only cation exchange for iron, leads to a significant 

underestimation of measured iron concentrations (see Figure 5.15). This finding is consistent with 

the PCA, which indicates that its behavior is not identified with the component associated with ion 

exchange. If siderite dissolution is assumed to contribute to the increase in aqueous iron 

concentration, a better fit is obtained, although the predicted iron concentrations are still lower than 
66 

those actually measured. Note that the calculated iron concentration is highly sensitive to the rate of 

siderite dissolution. 

Another hypothesis that has been tested to explain the behavior of iron is the dissolution of 

Fougerite (green rust, Fe6.7Mg5.3O34H26.7C3) (see Section 5.2.2). The dissolution of green rust leads 

to a better match between computed and measured iron concentration, although this process is 

highly redox dependent, and it must be remembered that a large uncertainty exists regarding the 

iron data and redox conditions at the site. Further determinations of the redox condition of 

groundwater at the ZERT site would be useful to validate the hypothesis that dissolution green rust 

controls the evolution of iron. 

It should be noted that the desorption of Fe+2 sorbed onto HFO (which is known to take place under 

suboxic but not necessarily strongly reducing conditions, e.g., Hiemstra and van Riemsdijk, 2007) 

could also contribute to increasing Fe concentrations in groundwater. Preliminary simulations 

including this process showed a larger than observed Fe concentration increase in groundwater upon 

pH decrease. Given the limited amount of field data and uncertainties regarding redox conditions at 

the site, further modeling work including this process was not attempted. 

0.E+00

1.E-06

2.E-06

3.E-06

4.E-06

5.E-06

6.E-06

7.E-06

8.E-06

9.E-06

1.E-05

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

Fe (mol/L)

measured data

base model: cation exchange only

sensitivity run: cation exchange + siderite dissolution

sensitivity run: cation exchange + green rust dissolution

Figure 5.15. Calculated iron concentration vs pH in the base model, in which only cation exchange is considered and 

a sensitivity run in which both cation exchange and siderite dissolution are considered 

Another effect from the dissolution of CO2 in groundwater is the increase of aqueous bicarbonate 

(HCO3

-

) concentration (Figure 5.16). This increase modifies the distribution of adsorbed anionic 

species on HFO. Table 5.16 lists the adsorbed concentrations associated with those ions considered 

in the surface complexation reactions on HFO. Desorption and adsorption constitutes the net effects 

of decreasing and increasing the concentrations for all relevant surface complexes. For example, the 

desorption/adsorption of As(V) can be represented by all relevant surface complexes including 

HFO_sH2AsO4, HFO_wH2AsO4, HFO_sHAsO4

-

 and HFO_wHAsO4

-

 (see Table 5.13). The total 

adsorbed concentration (represented as s_ H2AsO4

-

 in Table 5.16) is the summation of the 

concentrations for all four complexes. Table 5.16 shows the initial (Ci

) and final (Cf) adsorbed 

concentrations and their difference Cf

 –Ci. Negative values of Cf–Ci indicate desorption, while 

positive values indicate adsorption. Initially, adsorbed carbonate occupies a large portion of the 

sorption sites (about 55%). The increase in HCO3

-

 due to the dissolution of CO2 leads to increased 

adsorption of carbonate on the HFO surface. As a result, some anionic species are displaced into the 

aqueous phase. 
67 

Table 5.16. Initial (Ci) and final (Cf) adsorbed concentration and their difference Cf –Ci

Adsorbed species Ci

 Cf Cf - Ci

s_H+ 1.7E-03 2.0E-03 3.0E-04 

s_ SO4

-2 5.2E-07 2.1E-07 -3.1E-07

s_HSeO3

-

 9.4E-07 5.2E-07 -4.2E-07

s_MoO4

-2 1.7E-09 1.0E-09 -7.1E-10

S_HCO3

-

 2.3E-03 3.0E-03 7.2E-04 

s_ H2AsO4

-

 8.5E-08 6.7E-08 -1.9E-08

s_ HPO4

-

 2.3E-04 2.3E-04 7.4E-07 

0.0E+00

5.0E-03

1.0E-02

1.5E-02

2.0E-02

2.5E-02

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

HCO3 (mol/L)

measured data

model results

Figure 5.16. Calculated bicarbonate concentration vs pH 

Figure 5.17 shows the aqueous concentration of arsenic. Even though scatter in the As data is large, 

the similarities between computed and measured As concentrations suggests carbonate-initiated 

desorption could be a controlling process for As, as observed in other systems (e.g., Appelo et al., 

2002; Frau et al., 2008). It should be noted, however, that our model has ignored adsorption of 

As(III) species. This could affect model results. However, because As(III) does not sorb as much as 

As(V) and because significant As(III) is not expected in suboxic to oxic conditions at the site, it is 

unlikely that inclusion of As(III) in the system would significantly affect model results. 

0.0E+00

5.0E-09

1.0E-08

1.5E-08

2.0E-08

2.5E-08

3.0E-08

3.5E-08

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

H2AsO4-2 (mol/L)

measured data

model results

Figure 5.17 Calculated arsenic concentration vs pH 
68 

The computed aqueous concentrations of selenium overestimate the measured concentrations 

(Figure 5.18), possibly attributable either to uncertainties in the selenite surface-complexation 

constant, or to the omission of adsorbed selenate or selenide species. Preliminary EQ3 distribution 

of species modeling suggests that oligomeric neutral selenide complexes of Fe and Zn may 

predominate in solution, although such a distribution is highly dependent on a correct estimate of 

the redox state of the groundwater, and the unlikely assumption that homogeneous equilibrium with 

respect participating redox species has been attained. The concentration of aqueous phosphate 

(Figure 5.19) decreases with the decrease in pH, because anionic adsorption occurs. Although the 

concentrations of adsorbed HFO_sPO4

-2 and HFO_wPO4-2 tend to decrease as carbonate species 

adsorb, the concentrations of HFO_sH2PO4 and HFO_wH2PO4 increase as the pH falls. This 

increase is greater than the decrease in HFO_sPO4

-2 and HFO_wPO4-2, thus the concentration of 

phosphate in the groundwater falls. 

0E+00

1E-07

2E-07

3E-07

4E-07

5E-07

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

HSeO3

- (mol/L)

measured data

model results

Figure 5.18 Calculated selenium concentration vs pH 

0.0E+00

5.0E-07

1.0E-06

1.5E-06

2.0E-06

2.5E-06

7.2 7.0 6.8 6.6 6.4 6.2 6.0 5.8

pH

HPO4-2 (mol/L)

measured data

model results

Figure 5.19 Calculated phosphate concentration vs pH 

In summary, the concentration increase of major and trace elements in the groundwater at the MSUZERT field test has been interpreted with a batch geochemical model in which hypothesized 

reactive processes were tested, including the dissolution of calcite and Fe minerals, ion exchange, 

and sorption/desorption. These processes were presumed to take place on the basis of observed 

groundwater quality trends (Section 3) as well as statistical and thermodynamic evaluations 
69 

(Section 5.2). Only data before the first rainfall (after the start of the test) were used for comparing 

model results with observed trends, to avoid complexities resulting from the mixing of infiltrating 

rainwater with groundwater. Reasonable agreement between measured data and model results 

suggest that (1) calcite dissolution could be the primary process buffering pH, (2) the increase in the 

concentrations of major cations and trace metals except Fe could be explained by Ca+2-driven 

exchange reactions, (3) the release of anions from adsorption sites due to competing adsorption of 

bicarbonate could explain the concentration trends of most anions and (4) the dissolution of reactive 

Fe minerals could explain the increase in total Fe concentration. 

6. SUMMARY AND CONCLUDING REMARKS 

The primary purpose of the MSU ZERT CO2 release test conducted in summer 2008 was to allow 

controlled studies of near-surface CO2 transport and detection technologies. However, this test also 

provided a unique opportunity to evaluate the effects of CO2 release on the chemistry of groundwater at this site, which is the focus of this study. 

When CO2 dissolves in water, carbonic acid is produced, decreasing the pH and increasing the 

dissolved carbonate content of the water reacting with CO2. These processes and their effects were 

monitored at the ZERT site, through geochemical investigations conducted prior to, during, and 

after the 2008 injection test. During this test, CO2 was injected for 30 days into a shallow horizontal 

pipe installed at a depth near 1.8 m below ground surface, and about 0.5 m to 1 m below the water 

table. Groundwater chemistry was monitored from five locations, one upgradient and four 

downgradient of the injection pipe. Over 60 groundwater samples were collected. Most of these 

samples were obtained from shallow wells screened at depths close the soil-groundwater interface. 

The samples showed a fast response to the CO2 release, as early as a day after start of injection in 

nearby wells. The response was marked primarily by a pH decrease from ambient values ~ 7 to 

minimum values ~5.8 at wells closest to the injection well (within 1–2 m from it), and a significant 

increase in alkalinity and electrical conductivity. The concentrations of many dissolved species, 

including trace metals, also increased. Volatile organics were also detected in groundwater as the 

result of CO2 injection, but were found to be linked to the CO2 source and not to CO2-sediment 

interactions. Concentrations of constituents listed on the EPA priority pollutant risks (US EPA, 

2004), however, did not rise above their established maximum contaminant levels (MCL). Several 

samples were also collected from deeper wells screened at levels below the level of the injection 

pipe. These samples, however, have not been affected by the CO2 release. Several rainfall events 

occurred during the test. Because of the thin vadose zone, water levels and water chemistry were 

quick to respond to rainfall (within a day or more). In particular, the concentrations of Fe and Mn 

in groundwater were observed to drop at the onset of rainfall, presumably as the result of 

groundwater mixing with more oxic recharge water. For these reasons, the interpretation of 

geochemical system response to CO2 injection concentrated on the first week of CO2 injection, 

during which time the test was not affected by rainfall. 

Standard geochemical evaluations, statistical analyses, and geochemical modeling suggest that: 

 CO2 dissolution in the groundwater causes calcite to dissolve. Calculations of the calcite 

saturation index indicate increasing undersaturation with increasing CO2 uptake, with slow 

calcite dissolution and incomplete resaturation during the first ten days of the test. 
70 

 Observed increases in the concentration of dissolved trace metals result likely from Ca+2-

driven ion exchange with clays (smectites) and sorption/desorption reactions likely 

involving Fe (hydr)oxides. 

 Bicarbonate from CO2 dissolution appears to compete for sorption with anionic species such 

as HAsO4

-2, potentially increasing dissolved As levels in groundwater. 

In particular, principal component analyses (PCA) for the first 10 days of the test, using the 

collected groundwater quality data show that: 

 A strong correlation exists between alkali metals (Li, Na, K), alkali earths (Mg, Ca, Sr, Ba), 

B, Al, Cr, SiO2(aq), Cd and Pb, and an inverse relationship to pH, suggesting ion exchange 

as a release mechanism for these cationic species. 

 F, As, Se, and Mo are correlated, suggesting possible adsorption of these anionic species on 

secondary iron (hydr)oxides or anionic clays. 

 PO4 is negatively correlated with Mn, Fe, and Co, suggesting some precipitation/dissolution 

mechanism may be operative. 

 Cl and SO4

-2 are correlated and suggest perturbation by earlier rainfall events, prior to 

monitoring. 

Thermodynamic analyses indicate that: 

 The initial groundwater is slightly undersaturated with respect to calcite, opal-CT and barite, 

suggesting dilution of the groundwater by rainwater prior to the test. 

 The calculated redox potential is at pe ≈ +9 assuming fougerite-CO3 and Fe(OH)3

(ferrihydrite) as the controlling phases, and pe ≈ 2 if assuming goethite. There are 

indications that the system redox state may not be in equilibrium or spatially homogeneous. 

Geochemical simulations were run to test whether ion exchange and sorption processes, together 

with dissolution of carbonates, could explain the water chemistry trends observed during the test. 

Results show reasonable agreement with field data, suggesting these processes were triggered by 

the CO2 release. Because of the lack of site-specific data for key model parameters such as the 

cation exchange capacity, smectite and iron oxyhydroxide content, sorption data, mineral surface 

areas, and redox state, the simulations relied on assumed and/or typical but not site-specific values 

for these critical parameters. In addition, no unique solution may exist for a system as complex as at 

the ZERT site, for which multiple combinations of input parameters and modeled processes could 

yield similar results. Consequently, the modeling effort should be regarded as providing more 

qualitative than quantitative results. 

It is evident that further detailed characterization of sediments and groundwater samples, including 

redox-sensitive sampling and analysis, would be required to test some of the hypotheses made in 

this study, and to provide a full understanding of metal behavior and speciation in this complex 

system. Such detailed analysis, however, is not within the scope of this study. Ongoing 

investigations, including the analyses of metals in sequential extractions of sediment samples, may 

prove quite useful to determine the association of metals with solid phases in the sediment. Such 

associations are critical as they are expected to dictate the magnitude and type (dissolution, 

desorption, exchange) of groundwater quality response to CO2 injection. 
71 

It should be noted that this study was conducted in a shallow water-table aquifer under conditions 

that are not representative of deeper USDW. However, the collected geochemical data during this 

study were useful to evaluate key processes (dissolution, exchange, and sorption/desorption 

reactions) that would be expected to take place in any aquifer impacted by CO2. It is anticipated that 

higher pressures in deep USDW would result in increased CO2 dissolution in groundwater, relative 

to observations at the ZERT site, and thus could result in a more pronounced pH decrease and 

possibly a more significant release of contaminants. Such stronger response has indeed been 

observed during CO2 injection tests in reservoirs at much greater depths, such at the Frio test site 

(Kharaka et al., 2009b). Furthermore, the controlled-release period of about four weeks may have 

been too short to test the importance of slower release mechanisms for trace metals, such as the 

dissolution minerals containing trace amounts of metals. We recommend conducting further 

controlled-release experiments to improve our understanding of possible groundwater contamination from CO2 intrusion, ideally in deeper aquifers more representative of the majority of our 

groundwater resources, and with longer injection period to monitor contaminant release from shortterm and long-term geochemical processes. 

The possible impact of increased CO2 dissolution in groundwaters at greater depth could be partly 

mitigated when impacted waters migrate upward from deeper formations, releasing CO2 as the 

hydrostatic pressure decreases. It has long been known, for example, that the exsolution of CO2

from naturally CO2-rich and metal-rich thermal waters upon ascension to shallow depths is 

accompanied by a pH increase that causes the precipitation of calcite and other metal-bearing 

phases (e.g., Drummond and Ohmoto, 1985; Spycher and Reed, 1989). The effect of CO2

exsolution along smaller temperature gradients but higher pressure gradients in the case of CCS 

(relative to thermal waters) has not been evaluated, but it would be anticipated to at least partly 

reverse the trends predicted in this study. Therefore, the full assessment of CCS impacts on the 

quality of a USDW may require assessing geochemical processes not only at the source of a CO2

leak, but also along the path of impacted (carbonated) waters as they migrate towards potential 

receptors. 
72 

7. ACKNOWLEDGMENTS and Disclaimer 

This work was conducted as part of the ZERT project, supported by the Assistant Secretary for 

Fossil Energy, Office of Sequestration, Hydrogen, and Clean Coal Fuels, through the National 

Energy Technology Laboratory, U.S. Department of Energy, under Contract No. DE-AC02-

05CH11231. This research was conducted at the ZERT field facility directed by Lee Spangler and 

managed by Laura Dobeck, MSU, Bozeman, MT. http://www.montana.edu/zert. We thank the 

entire ZERT team and participating organizations for creating a supportive and exciting research 

environment, and gratefully acknowledge. This research was funded primarily by the Electric 

Power Research Institute, EPRI; additional funds were also obtained from EPA, DOE, LBNL, and 

USGS. 

The USGS contributions to this report have not undergone formal internal review and approval for 

publication by the USGS; therefore, these contributions are subject to change and alternative 

interpretation. 

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APPENDIX A Table A1 Chemical composition of water samples from ZERT monitoring wells MW1

Major Solutes (mg/L) T

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-103 7/7/08 17:00 6.8 10 432 9.2 5.5 24 95 0.31 0.12 0.001 <0.01 0.10 3.7 0.042 0.79 0.17 5.8 27 37 2 1.0 0.009 0.09 0.3 

MW2

Major Solutes (mg/L) Tra

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-102 7/7/08 15:30 6.8 10 396 7.5 6.2 24 85 0.27 0.13 0.002 <0.01 0.09 6.5 0.051 0.12 0.20 8.3 27 42 2 0.8 0.012 0.07 <0.2 

1A

Major Solutes (mg/L) Tr

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-105 7/8/08 9:15 588 6.9 8 386 7.8 5.6 23 84 0.27 0.11 0.001 <0.01 0.10 4.7 0.040 0.55 0.17 7.5 26 39 2 0.9 0.012 0.08 <0.2 

1B

Major Solutes (mg/L) T

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-112 7/10/08 15:15 650 6.5 13 438 8.4 6.0 26 94 0.29 0.11 0.003 <0.01 0.14 4.9 0.049 0.33 0.16 7.1 34 46 3 1.2 0.018 0.28 0.3 08ZERT-117 7/12/08 9:15 847 5.7 9 551 9.4 6.8 34 124 0.39 0.15 0.003 <0.01 0.09 5.0 0.046 <0.01 0.14 7.3 37 49 4 1.2 0.022 0.38 0.3 08ZERT-127 7/15/08 10:00 1015 5.9 9 724 9.8 7.6 43 155 0.49 0.19 0.005 <0.013 0.11 5.2 0.046 0.31 0.17 7.7 41 54 5 1.3 0.021 0.43 0.4 08ZERT-131 7/17/08 10:30 1041 5.9 9 735 9.7 7.7 44 159 0.51 0.20 0.006 0.014 0.11 5.3 0.048 0.28 0.18 7.9 35 48 4 0.9 0.023 0.40 0.4 08ZERT-135 7/19/08 10:15 1124 6.1 10 821 9.9 8.1 46 174 0.55 0.22 0.017 0.017 0.12 5.5 0.055 0.26 0.19 8.1 37 51 4 1.2 0.017 0.21 0.5 08ZERT-139 7/21/08 9:50 1181 6.0 21 1000 9.4 7.7 44 173 0.53 0.21 0.021 <0.025 0.15 5.6 0.046 0.23 0.18 8.4 36 50 5 1.1 0.016 0.33 <0.25 08ZERT-144 7/23/08 11:45 908 6.0 15 861 8.7 7.7 40 158 0.49 0.19 0.012 <0.013 0.12 5.6 0.052 0.23 0.17 8.4 34 49 3 1.0 0.013 0.20 0.4 08ZERT-147 7/26/08 9:30 667 5.9 13 565 7.6 6.2 26 109 0.33 0.12 0.005 <0.01 0.13 5.6 0.046 0.23 0.17 7.7 28 41 2 1.0 0.011 0.11 0.2 08ZERT-151 7/29/08 9:00 646 5.7 15 480 8.2 6.1 25 99 0.31 0.11 0.008 0.014 0.15 5.6 0.047 0.26 0.19 7.6 27 41 2 0.9 0.011 0.11 0.2 08ZERT-160 8/4/08 11:15 961 5.9 15 693 9.3 7.5 38 147 0.46 0.18 0.006 0.018 0.13 5.6 0.050 0.38 0.19 8.0 33 47 4 0.9 0.021 0.33 0.3 08ZERT-163 8/7/08 9:00 984 5.9 15 702 9.2 7.7 38 149 0.47 0.19 0.006 0.04 0.10 5.6 0.056 0.48 0.20 8.1 38 52 3 1.1 0.017 0.15 0.3 08ZERT-167 8/8/08 9:00 954 5.8 13 668 9.0 7.7 36 147 0.46 0.18 0.006 0.030 0.11 5.6 0.059 0.50 0.20 8.0 38 52 4 1.0 0.019 0.20 0.3 08ZERT-171 8/11/08 9:40 705 6.0 13 529 7.9 6.8 29 118 0.36 0.14 0.004 <0.01 0.11 5.8 0.062 0.51 0.18 8.0 34 48 3 0.8 0.016 0.19 0.3 08ZERT-176 8/13/08 11:20 625 6.4 26 402 7.4 6.1 21 91 0.28 0.11 0.002 <0.006 0.12 5.9 0.062 0.68 0.20 7.8 30 45 3 1.0 0.016 0.19 0.2 

2A

Major Solutes (mg/L) 

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-107 7/8/08 11:45 585 6.7 8 387 7.5 5.3 24 84 0.26 0.11 0.001 <0.01 0.12 4.8 0.042 0.60 0.18 7.4 32 45 3 1.0 0.018 0.23 0.2 
2B

Major Solutes (mg/L) Tra

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-109 7/9/08 9:00 651 7.0 12 434 9.1 5.4 28 92 0.30 0.10 0.028 <0.01 0.17 5.4 0.099 0.26 0.10 7.2 32 45 3 1.3 0.017 0.29 0.4 08ZERT-118 7/12/08 10:00 952 6.4 9 664 9.7 7.1 41 142 0.45 0.19 0.19 0.08 0.14 5.3 0.048 0.12 0.05 7.4 40 53 5 1.0 0.022 0.45 1.2 08ZERT-128 7/15/08 11:00 1270 5.9 9 816 10.1 8.3 54 204 0.63 0.27 0.13 0.39 0.07 5.5 0.049 0.20 0.02 7.7 44 57 7 1.3 0.024 0.61 1.2 08ZERT-132 7/17/08 11:15 1193 5.9 9 924 9.5 8.0 49 191 0.57 0.26 0.14 0.53 0.06 5.6 0.049 0.20 <0.015 7.8 37 51 6 0.4 0.020 0.43 1.2 08ZERT-136 7/19/08 11:15 1342 6.0 10 1115 9.9 7.4 55 223 0.69 0.23 0.011 <0.025 0.05 5.5 0.056 0.25 0.24 8.4 38 52 6 0.9 0.017 0.22 0.5 08ZERT-140 7/21/08 10:10 1335 6.0 16 1127 9.6 6.9 51 227 0.67 0.21 0.008 <0.025 0.09 5.5 0.047 0.30 0.26 8.4 37 51 8 1.1 0.021 0.40 <0.25 08ZERT-146 7/23/08 13:15 1424 6.0 15 1147 10.2 7.4 55 239 0.73 0.24 0.014 <0.025 0.13 5.6 0.051 0.35 0.26 8.6 39 54 8 1.6 0.018 0.22 0.6 08ZERT-150 7/26/08 11:35 1339 5.9 13 1054 9.6 7.1 47 241 0.68 0.22 0.015 <0.025 <0.05 5.6 0.047 0.41 0.02 8.5 30 45 7 1.5 <0.015 0.19 <0.5 08ZERT-154 7/29/08 13:45 1235 5.8 21 967 8.8 7.6 40 216 0.58 0.25 0.13 0.78 0.06 5.7 0.055 0.46 <0.015 8.0 29 44 5 1.2 <0.015 0.18 1.2 08ZERT-161 8/4/08 12:15 1195 5.8 19 916 8.5 7.7 36 219 0.52 0.27 0.19 1.1 0.10 5.8 0.052 0.64 <0.015 7.8 38 53 10 0.4 0.020 0.32 1.3 08ZERT-165 8/7/08 10:45 1201 5.7 22 884 8.8 7.7 35 212 0.50 0.26 0.21 1.19 0.07 6.1 0.062 0.77 <0.015 8.0 38 53 8 0.5 0.016 0.23 1.5 08ZERT-169 8/8/08 11:25 732 6.0 21 511 7.1 5.9 20 125 0.29 0.15 0.13 0.87 0.18 6.3 0.065 1.0 <0.015 8.0 31 46 4 0.4 0.018 0.19 0.8 08ZERT-172 8/11/08 10:20 615 5.8 14 451 7.2 5.4 17 106 0.25 0.12 0.090 0.35 0.24 6.5 0.070 1.1 0.023 7.9 29 45 3 0.5 0.014 0.14 0.6 08ZERT-177 8/13/08 12:30 606 6.4 25 389 7.8 5.2 16 94 0.23 0.10 0.052 0.15 0.27 6.9 0.073 1.4 0.06 7.8 29 46 2 0.7 0.017 0.15 0.5 

3B

Major Solutes (mg/L) 

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd 08ZERT-174 8/11/08 11:30 1430 6.2 16 1069 11.3 9.1 63 224 0.75 0.31 0.21 <0.025 <0.05 6.3 0.063 0.72 0.07 9.9 43 60 6 1.4 0.024 0.61 

4A

Major Solutes (mg/L) T

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-106 7/8/08 10:00 609 6.9 8 398 8.1 5.6 25 86 0.28 0.10 0.31 <0.01 0.11 5.1 0.044 0.19 0.13 7.4 26 39 2 0.8 0.013 0.10 0.6 

4B

Major Solutes (mg/L) 

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd C08ZERT-104 7/7/08 17:40 644 6.9 15 431 9.7 5.6 27 90 0.30 0.10 0.11 0.05 0.17 5.3 0.046 0.10 0.09 7.3 33 46 3 1.0 0.017 0.26 0.08ZERT-119 7/12/08 11:00 624 7.0 9 410 8.2 5.8 25 87 0.28 0.12 1.02 0.05 0.14 5.4 0.044 <0.01 0.03 7.6 31 44 3 0.9 0.019 0.32 1.08ZERT-126 7/15/08 9:15 706 6.3 9 468 8.7 6.0 29 99 0.33 0.14 1.2 0.08 0.13 5.4 0.045 <0.01 0.02 7.4 34 47 3 0.9 0.019 0.37 2.08ZERT-130 7/17/08 9:30 720 6.3 9 475 9.1 6.1 30 101 0.33 0.15 1.2 0.08 0.11 5.4 0.045 <0.01 0.024 7.5 32 45 3 0.6 0.021 0.30 2.08ZERT-134 7/19/08 9:00 848 6.5 10 533 10.3 6.7 35 123 0.41 0.16 0.51 0.030 0.13 5.4 0.050 0.07 0.05 7.7 34 48 3 0.6 0.019 0.18 1.08ZERT-141 7/21/08 11:30 882 6.6 15 589 10.3 6.6 37 130 0.42 0.16 0.37 <0.013 0.13 5.5 0.046 0.10 0.05 7.9 33 47 4 0.6 0.022 0.35 0.08ZERT-143 7/23/08 11:00 997 6.2 16 708 11.6 7.0 42 143 0.49 0.17 0.28 0.034 0.12 5.4 0.054 0.14 0.05 8.2 37 51 3 0.6 0.018 0.19 0.08ZERT-148 7/26/08 10:15 1085 6.4 14 742 12.1 7.6 47 163 0.55 0.19 0.34 0.020 0.11 5.5 0.049 0.20 0.04 8.5 30 45 3 0.7 0.014 0.18 0.08ZERT-152 7/29/08 9:50 941 6.4 14 641 10.7 7.4 41 141 0.48 0.19 1.00 0.11 0.11 5.6 0.054 0.13 0.02 8.2 32 46 2 0.8 0.013 0.19 1.08ZERT-159 8/4/08 10:00 807 6.1 14 528 9.1 7.0 33 115 0.38 0.18 1.44 0.21 0.09 6.1 0.060 0.13 <0.015 8.0 35 49 4 0.7 0.022 0.44 2.08ZERT-166 8/7/08 12:15 786 6.2 16 542 9.1 7.0 33 111 0.38 0.17 1.4 0.14 0.09 6.3 0.066 0.21 <0.015 8.0 36 51 3 0.6 0.015 0.23 2.08ZERT-168 8/8/08 9:45 794 6.3 15 546 9.1 7.0 33 113 0.38 0.18 1.41 0.18 0.09 6.4 0.068 0.24 <0.015 8.0 35 50 3 0.5 0.019 0.27 2.08ZERT-173 8/11/08 11:05 702 6.3 16 581 9.5 7.0 35 122 0.41 0.17 0.65 0.068 0.11 6.7 0.074 0.66 0.016 8.3 35 51 3 0.5 0.020 0.26 1.08ZERT-178 8/13/08 13:50 727 6.5 24 484 8.5 6.6 29 100 0.35 0.14 0.77 0.089 0.13 7.0 0.076 0.87 0.020 8.2 33 49 3 0.7 0.016 0.22 1.
5B

Major Solutes (mg/L) Tra

SAMPLE DATE time EC pH T HCO3 Na K Mg Ca Sr Ba Mn Fe F Cl Br NO3 PO4 SO4 SiO2 TDS Al As B Cd Co 08ZERT-116 7/11/08 14:45 1257 6.2 9 994 12.7 6.5 66 190 0.67 0.25 0.046 0.19 0.15 5.3 0.051 <0.01 <0.015 8.1 46 60 8 <2 0.026 0.41 1.0 08ZERT-124 7/14/08 13:15 1287 6.0 9 1174 11.7 6.8 68 201 0.71 0.27 0.14 0.63 0.14 5.4 0.054 0.018 <0.015 8.5 50 64 8 <2 0.028 0.59 2.5 08ZERT-129 7/15/08 12:30 1264 6.0 10 982 11.3 6.8 64 181 0.63 0.26 0.17 0.93 0.06 5.4 0.053 0.049 <0.015 8.3 47 61 7 <2 0.024 0.56 3.1 08ZERT-133 7/17/08 12:00 1321 5.9 9 1060 11.2 6.8 70 199 0.71 0.27 0.19 0.72 0.09 5.5 0.052 0.028 <0.015 8.7 41 55 7 0.6 0.025 0.58 2.4 08ZERT-137 7/19/08 13:00 1434 6.0 10 1152 10.9 6.8 70 227 0.83 0.29 0.15 0.06 0.06 5.5 0.056 0.05 0.07 9.1 42 57 5 0.6 0.019 0.31 1.0 08ZERT-142 7/21/08 11:50 1415 6.0 23 1081 10.5 6.6 66 228 0.80 0.28 0.10 <0.025 0.05 5.6 0.051 0.14 0.07 9.5 39 55 7 0.6 0.026 0.55 0.8 08ZERT-145 7/23/08 12:40 1495 5.9 15 1136 11.4 6.9 68 233 0.83 0.29 0.11 0.026 0.10 5.6 0.055 0.32 0.09 10.2 42 58 5 1.1 0.016 0.32 1.1 08ZERT-149 7/26/08 11:00 1285 6.0 15 1023 9.9 6.4 55 213 0.74 0.25 0.058 <0.025 <0.05 5.6 0.048 0.55 0.08 9.4 29 44 4 1.1 <0.015 0.21 <0.5 <08ZERT-153 7/29/08 11:15 1111 6.0 17 881 9.2 6.0 46 185 0.62 0.22 0.083 0.10 0.16 5.6 0.052 0.34 0.03 8.5 29 44 3 0.8 <0.012 0.20 0.8 <08ZERT-162 8/4/08 13:00 1113 5.9 17 843 9.5 6.5 48 187 0.63 0.24 0.14 0.31 0.13 5.9 0.056 0.50 <0.015 8.5 38 53 5 0.5 0.021 0.54 1.4 08ZERT-164 8/7/08 10:00 6.0 761 9.4 6.5 44 160 0.55 0.21 0.20 0.85 0.15 6.2 0.068 0.68 <0.015 8.5 39 55 4 0.6 0.017 0.27 2.1 08ZERT-170 8/8/08 12:30 1130 6.1 20 832 9.5 6.8 47 176 0.62 0.24 0.23 0.77 0.15 6.4 0.069 0.54 <0.015 8.7 37 53 5 <0.5 0.021 0.41 2.3 08ZERT-175 8/11/08 12:45 1037 6.1 16 727 8.4 6.0 38 167 0.55 0.21 0.072 0.055 0.11 6.7 0.075 1.5 0.019 9.2 34 52 4 <0.5 0.017 0.35 0.7 08ZERT-179 8/13/08 15:04 759 6.2 20 506 7.0 5.2 25 114 0.38 0.14 0.033 0.071 0.16 7.0 0.082 1.9 0.018 8.9 29 46 3 0.8 0.013 0.22 0.5 
82 

APPENDIX B 

Table B1 Well log for well 6 

Core (ft) (cm) % re covery Depth (cm) Notes BTEX Description

0-5cm grass and air

dark brown, clay rich, plastic soil with roots througout. 

Slightly fizzes with HCl

11-15cm large rock m ost likely broken by geoprobe

30-39cm plastic clay grading from dk brown to lt brown indicating a 

gradation into caliche

39-57cm 46-48.5cm

10YR 5/4. Caliche zone. Highly reactive with HCl, very fine 

grained and plastic with some roots. Few larger, rounded 

grains between 1-3cm.

57-64cm Sandy gravels (with som e caliche smearing on kevlar sleeve).

0-15cm

11-15cm

Slough? with a large grain cored through by the geoprobe at 

11-15cm.

15-76cm 30cm 54-58cm

10YR 3/3 dark brown. Coarse sandy gravel, possibly higher 

percentage of gravels than other cores. Grains as large as 

4cm. Gravels appear to have been rounded then broken, 

possible geoprobe damage? Saturated below 30cm. Lightly 

fizzes with acid throug

8-10' 61.0 67% 0-41cm 33-37cm

10YR 3/3 dark brown. Coarse sandy gravel, few fines. 

Grains up to 4cm, possibly damaged by geoprobe. Some 

plastic from a broken core catcher is present. Few orange 

clay streaks near 37cm.

3.5-8'

Well 6

Log Date 4/29/09 - 4/30/09

0-3.5'

5-30cm

107

137

60%

55%
83 

APPENDIX C 

Estimation of the Solubility Product of Fougerite 

Over the past twenty years, considerable study has been devoted to the characterization of 

metastable minerals that form in soil zones at or near the water table, and where the redox state is 

affected by decomposition of organic matter derived from vegetative cover. In particular, much 

attention has been paid to the formation of so called ”green rusts”, which consist of stacked 

positively charged tri-octahedral sheets of ferrous hydroxide in which some of the Fe(II) has been 

oxidized to Fe(III). The octahedral sheets are separated by interlayers containing water and chargebalancing anions (see Genin et al., 2006, and references cited therein). At the time of their initial 

characterization (Bernal et al., 1959; Dasgupta and Mackay, 1959), it was found that green rusts 

could be characterized by two distinct structures; (1) a rhombohedral form designated as GR-I, 

which contained simple charge-balancing anions such as OH- or Cl-, or planar oxy-anionic charge 

balancing species such as HCO3

-

 and/or CO3

-2, (2) a hexagonal form containing large oxy-anionic 

species such as SO4

-2 and SeO4-2. 

Earlier work concluded that green rusts occupy a stability field in Eh-pH space defined by neutral to 

weakly acid pH and moderately reducing (anoxic) conditions (Refait and Genin, 1993; Drissi et al., 

1995; Genin et al., 1996, 1998; Ruby et al., 2006). Other minerals that might also be associated with 

green rusts, depending on the concentration of Fe(T) and SO4

-2 in the system, and fluctuations in 

oxidations state include hydroxy-magnetite or magnetite (Olowe and Genin, 1991), schwertmannite 

and ferrihydrite (Majzlan et al., 2004), these latter phases principally occupying stability fields at 

higher Eh, and where the phase boundary between schwertmannite and ferrihydrite falls within a pH 

range close to 7.0. Ruby et al. (2006) also noted that the initial oxidation of green rust causes a 

characteristic color change from blue-green to orange-yellow while preserving the original trioctahedral structure. It is noteworthy that some of the recovered fine material from cores taken at 

the ZERT site also contained unspecified iron oxides characterized as “powdery orange blebs” 

(Thordsen, 2009), lending credence to the belief that green rust may actually form in shallow 

groundwater at the ZERT site. Green rust decomposes exceedingly rapidly upon exposure to air, 

and therefore it would not be expected to survive coring and recovery at the ZERT site unless 

extreme precautions had been taken. Elsewhere (Schwertmann and Fechter, 1994) has observed that 

green rust eventually transforms to lepidocrocite under oxidizing conditions. However, whether or 

not green rust transforms to ferrihydrite as an intermediate step before recrystallization to 

lepidocrocite is not clear from the literature, although the following thermodynamic analysis 

suggests that this could be the case at the ZERT site. 

Characterization of green rusts in a gleysol horizon at Fougeres in Normandy, France (Trolard et al., 

1996; Abdelmoula et al., 1998) lead to its recognition as a mineral species; fougerite, and 

furthermore revealed that the tri-octahedral sheets are in fact a mixture of Fe(II), Fe(III) and Mg(II). 

Bourrie et al. (2004) created a solid solution model of the hydroxide form of fougerite in which 

Fe(II)-Mg(II) substitution was treated as an ideal solution, whereas Fe(II)-Fe(III) substitution was 

treated as a regular solution with the constraint that adjacent Fe(III) sites are prohibited. Information 

on the thermodynamic properties of the end member binary solid solutions in the three-component 

system was obtained from prior solubility and calorimetric studies reported in the literature. This 

model was subsequently expanded by Feder et al. (2005) to consider anion occupancies by (HCO3

-

+ CO3

-2), Cl-

 and SO4

-2 in place of OH-

- in the interlayer positions, without, however, taking into 
84 

account interlayer ion exchange. Recently, Christiansen et al. (2009) found that at least some green 

rusts also contain interlayer cations in addition to anions. Therefore, a complete characterization of 

green rust thermodynamic properties must await further study. Feder et al. (2005) also examined the 

possibility that these forms of fougerite might achieve thermodynamic equilibrium in the saturated 

soil zone at Fougeres. They found that saturation was achieved with respect to certain carbonate and 

sulfate fougerite compositions, but that chloride forms would always be undersaturated, whereas the 

hydroxide forms would always be grossly supersaturated. 

A preliminary comparison of groundwater compositions at Fougeres (Feder et al., 2005) with those 

at the ZERT site indicated that although temperature and pH were comparable, Mg+2, Fe(T), Cl-

 and 

SO4

-2 concentrations were lower, and the alkalinity (as HCO3-

) was higher. These observations 

suggest that a carbonate form of fougerite might be stable at the ZERT site. 

The solubility products of all forms of fougerite were calculated assuming the stoichiometry to be 

([2/9FeII(OH)2.1/3FeIII(OH)2.4/9Mg(OH)2

]+1/3[1/3A]-1/3), where A = OH-, Cl-, (2/3HCO3-

.1/6CO3

-2), 

or 1/2SO4

-2. The solubility products were determined by direct comparison with the reported field 

saturation states at Fougeres, rather than by calculating the solubility products from the reported 

thermodynamic data given by Bourrie et al. (2003) and Feder et al. (2005), as the reference states 

used in their derivations differed from those we currently use in EQ3/6. Incorporation of the 

solubility products of the fougerite forms in the EQ3/6 thermodynamic database and testing using 

the baseline groundwater composition before CO2 injection indicated that the carbonate form of 

fougerite could be stable at the ZERT site, depending on the oxidation state of the system. 
85 

APPENDIX D 

The Saturation State of Redox-Sensitive Chromium, Copper, and Selenium Minerals as 

Function of pe. 

In this appendix, we pick up on Section 5.2.2, which considers potential solid phase redox buffers 

that might influence the redox state, or be influenced by the redox state, in the coexisting groundwater in a shallow unconfined aquifer such as that represented by the ZERT site. We start with a 

discussion of the stabilities of a suite of chromium oxide minerals, most of which are spinels. 

Figure D.1. Normalized saturation indices of chromite, magnesiochromite, and the chromium spinels of Cd, Co, Cu 

and Zn, Eskolaite and Cr-ferrihydrite, plotted as a function of pe. 

The phase behavior of these chromium oxide minerals as a function of pe is displayed in Figure 

D.1. The saturation indices of chromium spinels, MCr2O4, where M = Mg(II), Fe(II), Cu(II), Co(II) 

and Zn(II), and eskolaite (Cr2O3) varies systematically with pe, and at intermediate pe values, i.e., 

pe +2 - +8, are, with the exception of the Zn spinel, closely correlated. The phase boundary 

between Cr-ferrihydrite (Fe4(CrO4)(OH)10), and chromite (FeCr2O4) occurs at pe ≈ +8.7 at SI ≈ +2, 

where the pe value is similar to that between fougerite-CO3 and Fe(OH)3. The significance of this 

correlation is not clear. It is probable that Cr(III) substitutes as a minor component in these phases 

at the ZERT site. However, this substitution is constrained at higher redox potentials by the 

oxidation of Cr(III) to Cr(VI) in solution with concomitant destabilization of chromium spinels, as 

is evident in the figure. The close correlation between the saturation indices of the chromium 

spinels between pe +2 - +8, invites speculation that the concentrations of Mg(II), Fe(II), Cu(II), and 

Co(II) in solution might be determined by solid solution equilibrium with respect to some common 

iron, or Fe(II)/Mg(II) oxide mineral in the system at the ZERT site. However, the principal 

component analysis is equivocal on this point. Further study of the behavior of Cr in shallow 
86 

groundwater systems is certainly merited, and the thermodynamic properties of the participating 

minerals should be verified. 

Figure D.2. Normalized saturation indices of copper, bornite, covellite, chalcocite, cuprite and tenorite, plotted as a 

function of pe. 

The normalized saturation indices of various copper minerals as a function of pe are plotted in 

Figure D.2. The redox behavior of copper is of interest because phase relations between tenorite 

(CuO) and cuprite (Cu2O) marks the redox transition between the Cu(II) and Cu(I) oxidation states, 

which occurs under moderately reducing conditions. The concentration of Cu in solution at the 

ZERT site is insufficient to cause saturation with respect to tenorite. However, both native copper 

and cuprite would achieve saturation at pe ≈ +1.5, whereas the chalcocite and cuprite phase 

boundary is intersected at pe ≈ -0.5. 

It is interesting to note that at pe ≤ +2, cuprite remains close to saturation, i.e., SI ≈ 0. A possible 

explanation is that the redox pair Cu+2/Cu+

 forms one of the cluster of redox pairs in local partial 

equilibrium with respect to organic matter, as observed by Washington et al. (2004). However, the 

average crustal abundance of Cu is such that this redox pair is unlikely to exert any redox control 

over the system. Similar control by organic matter on the SO4

-2/HS-

 redox pair might be responsible 

for saturation with respect to chalcocite. 
87 

Figure D.3. Normalized saturation indices of selenium, molybdenum selenide, cadmoselite and clausthalite, plotted 

as a function of pe. 

Figure D.3 illustrates the behavior of the saturation indices of selenium minerals with variation in 

pe. Saturation is achieved with respect to native selenium at pe ≈ +2.7, and with respect to 

cadmoselite and clausthalite at about +2.4. MoSe2, a phase that has not been identified in nature, 

would saturate at pe ≈ 0. Given that the participating trace elements Cd, Mo, Pb and Se are all 

present in exceedingly low concentrations, none of the saturating phases are likely to exert a 

significant redox buffering capacity on the system. However, as noted with respect to the potential 

saturation of cuprite and chalcocite in the copper system, the concentrations of Cd and Pb could be 

controlled by saturation with respect to their selenides or sulfides as a result of reduction of Se(IV) 

to Se(0) and Se(-II), and S(VI) to S(-II) by organic matter. 

Both Cu and Se are trace element with very low natural crustal abundance, and it is therefore 

unlikely that either play a significant role in controlling the oxidation state of the system. However, 

the impact of organic matter in exercising local partial equilibrium control over some redox pairs 

cannot be discounted, especially in relation to Se, S and possibly U. This would imply that, 

although the redox state of MSU-ZERT groundwaters are controlled primarily by iron minerals and 

their interaction with infiltrating nitrate, organic matter could also be playing a role with respect to 

some species. In other words, the MSU-ZERT groundwaters are behaving in a manner similar to 

shallow groundwaters investigated by Washington et al. (2004) with formation of two redox cluster 

in local partial equilibrium, one dominated by nitrate and the other dominated by organic matter. 

An intriguing possibility, which merits further study, is that a redox potential gradient exists at the 

site, with more reducing conditions at greater depth, where transient ingress of infiltrating oxidizing 

groundwater is less likely to have an impact. The more reducing conditions induce local saturation 

with respect to Cu(I) mineral such as cuprite or chalcocite, and control the activity of copper in 
88 

solution, which is established in the overlying oxidizing horizons through diffusive transport. 

Similar behavior is observed with respect to the selenides cadmoselite (CdSe) and clausthalite 

(PbSe) with respect to selenium minerals. The foregoing statement is highly speculative and 

requires further study before it can be advanced as a serious hypothesis.