Geophysical Monitoring of Hydrological and Biogeochemical Transformations Associated with Cr(VI) Bioremediation

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• 作者：Susan S. Hubbard ; Ken Williams ; Mark E. Conrad ; Boris Faybishenko ; John Peterson ; Jinsong Chen ; Phil Long ; Terry Hazen
• 刊名：Environmental Science & Technology
• 出版年：2008
• 出版时间：May 15, 2008
• 年：2008
• 卷：42
• 期：10
• 页码：3757 - 3765
• 全文大小：3870K
• 年卷期：v.42,no.10(May 15, 2008)
• ISSN：1520-5851

文摘

Understanding how hydrological and biogeochemical properties change over space and time in response to remedial treatments is hindered by our ability to monitor these processes with sufficient resolution and over field relevant scales. Here, we explored the use of geophysical approaches for monitoring the spatiotemporal distribution of hydrological and biogeochemical transformations associated with a Cr(VI) bioremediation experiment performed at Hanford, WA. We first integrated hydrological wellbore and geophysical tomographic data sets to estimate hydrological zonation at the study site. Using results from laboratory biogeophysical experiments and constraints provided by field geochemical data sets, we then interpreted time-lapse seismic and radar tomographic data sets, collected during thirteen acquisition campaigns over a three year experimental period, in terms of hydrological and biogeochemical transformations. The geophysical monitoring data sets were used to infer: the spatial distribution of injected electron donor; the evolution of gas bubbles; variations in total dissolved solids (nitrate and sulfate) as a function of pumping activity; the formation of precipitates and dissolution of calcites; and concomitant changes in porosity. Although qualitative in nature, the integrated interpretation illustrates how geophysical techniques have the potential to provide a wealth of information about coupled hydrobiogeochemical responses to remedial treatments in high spatial resolution and in a minimally invasive manner. Particularly novel aspects of our study include the use of multiple lines of evidence to constrain the interpretation of a long-term, field-scale geophysical monitoring data set and the interpretation of the transformations as a function of hydrological heterogeneity and pumping activity.