Multimethod characterization of a chlorinated solvents contaminated site and geoelectrical monitoring of in-situ bioremediation

Soil contamination is a widespread problem and actions need to be taken in order toprevent damage to the groundwater and the life around the contaminated sites. InSweden more than 80.000 sites are potentially contaminated, therefore there is ademand for accurate and efficient methods for site characterization and soilremediation. In the past, the preferred methodology for soil remediation involvedthe excavation of the contaminated mass which was either deposited in landfills (digand dump) or treated elsewhere (dig and treat). However, these techniques areassociated with significant high risk (secondary exposure) and long-term costs. Onthe other hand, in-situ bioremediation has the potential to address these issuesoffering a safer, more sustainable and cost-efficient alternative for soil remediation.Unfortunately, monitoring the progress of in-situ treatments requires soil/watersampling and laboratory analysis, which, if done frequently, can increase the costdramatically. For this reason, there is a demand for new methodologies that can beused to follow the progress of in-situ bioremediation.The work presented in this thesis involves a former dry-cleaning facility located inAlingsås (Sweden). The site is contaminated with chlorinated solvents and a pilotin-situ bioremediation plan was launched in November 2017. First, we adapted amultimethod approach for site characterization using several methods: DirectCurrent resistivity and time-domain Induced Polarization (DCIP), SeismicRefraction Tomography (SRT) and the Membrane Interface Probe (MIP). The aimwas to build a refined geological conceptual model. Second, we developed anautonomous and fully automated system for geophysical monitoring with the DCIPmethod that aims to follow the daily changes in the subsurface. We present acomplete workflow that includes data acquisition, pre-processing, inversion andvisualization of the daily DCIP monitoring data. The proposed scheme is robust andshows that DCIP monitoring has great potential to record the changes due to thebioremediation; however, it needs to be paired with more information (temperature,geochemistry, contaminant concentrations) to better understand the changes thattake place in the subsurface