Abstract

Groundwater contamination is a threat to drinking water resources and ecosystems. Remediation by injection of chemical reagents into the aquifer may be preferred to excavation to reduce cost and environmental footprint. Yet, successful remediation requires complete contact between contamination and reagents. Subsurface heterogeneities are often responsible for diffusion into low-permeable zones, which may inhibit this contact. Monitoring the spatial distribution of injected reagents over time is crucial to achieve complete interaction. Source zone contamination at megasites is particularly challenging to remediate and monitor due to the massive scale and mixture of contaminants. Source zone remediation at Kærgård Plantation megasite (Denmark) is monitored here, with a new methodology, using high-resolution cross-borehole electrical resistivity tomography (XB-ERT) imaging calibrated by chemical analyses on groundwater samples. At this site, high levels of toxic non-aqueous phase liquids (NAPL) are targeted by in-situ chemical oxidation using activated persulfate. It may take numerous injection points with extensive injection campaigns to distribute reagents, which requires an understanding of how reagent may transport within the aquifer. A geophysical (XB-ERT) monitoring network of unprecedented size was installed to identify untreated zones and help manage the remediation strategy. The combination of spatially continuous geophysical information with discrete but precise chemical information, allowed detailed monitoring of sulfate distribution, produced during persulfate activation. Untreated zones identified in the first remediation campaign were resolved in the second campaign. The monitoring allowed adjusting the number of injection screens and the injection strategy from one campaign to the next, which resulted in better persulfate distribution and contaminant degradation in the second campaign. Furthermore, geophysical transects repeated over the timespan of a remediation campaign allowed high-resolution time-lapse imaging of reagent transport, which could in the future improve the predictability of transport models, compared to only using on a-priori assumptions of the hydraulic conductivity field.

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