Analysis of sources of bulk conductivity change in saturated silica sand after unbuffered TCE oxidation by permanganate☆
Graphical abstract
Introduction
In situ chemical oxidation (ISCO) using permanganate ion (MnO4−) has become a common method for degrading organic contaminants such as trichloroethene (TCE) in aquifers (Petri et al., 2011, Schnarr et al., 1998, Thomson et al., 2007). As with any chemical remediation technique, ISCO requires physical contact between the injected media and the contaminant. Aquifer heterogeneity can often influence the subsurface movement of MnO4− and other oxidants, making delivery unpredictable and leading to uneven contaminant removal (Smith et al., 2008). Furthermore, monitoring wells on site may be insufficient in number to adequately track oxidant movement (Halihan et al., 2012).
Electrical resistivity tomography (ERT) offers a possible non-intrusive solution for monitoring MnO4− fate and transport with improved resolution over monitoring wells alone. This method uses an array of electrodes emplaced either at the ground surface or in boreholes to collect resistivity measurements at multiple locations and depths over a period of time (see for instance Kowalsky et al., 2011, Revil et al., 2013). Most commonly, four electrodes are used at a given time, with two injecting a current and the other two measuring the difference in electrical potential. An inversion algorithm is then used to produce a model of the bulk resistivity (or conductivity) distribution below the electrodes or between the wells in the case of cross-hole resistivity tomography. Reviews of the methodologies used to perform ERT measurements and to invert these measurements can be found in Daily et al. (2004) and Revil et al. (2012).
Time-lapse ERT involves the use of different strategies to measure changes in electrical resistivity over time. One common technique is to repeat resistivity surveys multiple times and separately invert the different snapshots and map the conductivity changes among each snapshot. Alternately, using permanent electrode installations, resistivity can be monitored continuously over time with more measurements. Then, rather than inverting individual snapshots, newer inversion algorithms process the data as a whole, regularizing both over space and time (Karaoulis et al., 2011, Karaoulis et al., 2013). This type of inversion can reduce noise and improve recovery of conductivity changes that are correlated with time. Time-lapse ERT has been used to monitor the movement of salt plumes and also to provide flow and transport information in heterogeneous aquifers (Jardani et al., 2013, Kemna et al., 2002, Kemna et al., 2006, Vanderborght et al., 2005). Because permanganate-based ISCO involves injecting ions into the aquifer, time-lapse ERT could potentially be used to track the fate and transport of the injected oxidizing solution.
Although investigators have yet to use improved time-lapse inversion methods to monitor ISCO, a few researchers have used multiple ERT snapshots with independent inversions to locate changes in subsurface resistivity that could be attributed to MnO4− injection (Halihan et al., 2012, Harte et al., 2012, Nyquist et al., 1999). While each study was successful in demonstrating changes in aquifer resistivity after MnO4− injection, certain anomalies appeared that were not explained by the investigators. For instance, after injecting MnO4− to oxidize TCE, Nyquist et al. (1999) were unable to explain why increased conductivity values were observed in certain locations where MnO4− could not be detected in groundwater samples. Harte et al. (2012) also observed increased bulk conductivity in areas where MnO4− could not be detected through groundwater sampling during tetrachloroethene (PCE) oxidation. Additionally, they noted the opposite response in certain locations where they expected MnO4− to be located but where conductivity did not increase.
While these initial studies of ERT use during ISCO with MnO4− demonstrated that significant conductivity changes can be observed, additional work is needed before such measurements can be used for more quantitative observations of MnO4− and contaminant fate and transport. While increased electrode coverage, improved electrode placement, or newer inversion methods would improve the resolution of these measurements, this paper focuses on improving the understanding of subsurface conductivity changes that occur as a result of ISCO when MnO4− is the oxidant. Specifically, this study examines the changes in bulk conductivity that occur in saturated sand from the addition of MnO4−, the reaction between MnO4− and TCE, and protonation of the silica sand surface resulting from post-reaction acidity production.
Section snippets
Theoretical background
At circumneutral pH values, the reaction between TCE and MnO4− can be approximated using Eq. (1) (Yan and Schwartz, 2000).
Initially, one molecule of TCE is oxidized by one MnO4− molecule to one of various carboxylic acids through a cyclic hypomanganate ester intermediate. The second order rate constant for the transformation of TCE to carboxylic acid is 0.65 to 0.68 M− 1 s− 1 (Yan and Schwartz, 2000). The carboxylic acid is then oxidized by an additional MnO4−
Sand preparation
Although most aquifers consist of mixes of sands and clays (in addition to silt and gravel), well-sorted clean sand was chosen as the solid material for porous media samples to investigate the effects of one major aquifer component. Unimin industrial quartz with a nominal #70 mesh size was sieved with a Tyler #80 sieve (0.175 mm openings). The sand was then heated to a temperature of 550 °C for 3 h in order to remove organic matter and subsequently rinsed in a 2-liter glass bottle with deionized
Baseline formation factor and surface charge calculation
Fig. 3 shows formation factor and surface charge calculations for saturated sand samples in which no TCE was added or oxidized. The pH for these samples was between 7.6 and 8.1, a typical range for groundwater. Based on the y-intercept of the fit curve, the surface conductivity was only approximately 6 × 10− 4 S/m. This shows that the surface conductivity of the sand is negligible. The formation factor was calculated to be 3.88 ± 0.02 (the margin of error represents the 95% confidence interval).
Manganese dioxide precipitation effects
To
Contributions of processes to conductivity change
The overall effects of MnO4− addition, reaction with TCE, and loss of fluid H+ to silanol protonation are summarized in Fig. 7. The addition of MnO4− causes a measurable increase in both pore fluid and bulk conductivity with the pore fluid to bulk conductivity ratio being the same as the background ratio. The reaction between MnO4− and TCE releases additional ions that increase the pore fluid conductivity despite loss of MnO4−; however protonation of silanol removes protons produced by TCE
Conclusion
Multiple processes can influence bulk conductivity measurements during in situ chemical oxidation of TCE using MnO4−. This research examines how ion addition through MnO4− injection, ion production through TCE oxidation, porosity change from precipitate production, and loss of produced H+ through protonation of silanol all cause changes in conductivity. By accounting for these processes, it was possible to predict within a reasonable margin of error the bulk conductivity measurement that
Acknowledgments
We thank the NSF IGERT Program for partial funding of this research through a fellowship to R.D. Hort from the Colorado School of Mines SmartGeo Program (Project IGERT: Intelligent Geosystems; DGE-0801692).
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Revision 1 of the manuscript originally submitted to the Journal of Contaminant Hydrology on April 7, 2014.