Abstract
We present a multidisciplinary approach for characterization of a crude oil-contaminated site (Trecate, Italy), integrating geophysical data, such as subsoil electrical potential (in millivolts) and electrical resistivity (in ohm meters) distribution, with hydrogeological and bio-chemical data. Self-potential measurements have been evaluated together with active geoelectrical measurements and hydrological information, to provide spatial and temporal information about the self-potential sources and their possible correlations with the contamination state of the subsoil. Three self-potential surveys (March 2010, October 2010, and March 2011) were conducted at the site, both in the contaminated and uncontaminated regions. The obtained self-potential maps show large time-lapse differences in correspondence of the contaminated area, with positive electrical potential values (up to 50 mV) in spring surveys and an electrical potential dipolar distribution in October (2010) survey (amplitude from −15 to 25 mV). To understand the origin of the measured self-potential signals, a model using vertical dipolar electrical sources was built, taking into account the electrical resistivity distribution deduced from electrical resistivity tomography. The self-potential source identification allows the Trecate contamination state to be better delineated. In particular, two self-potential contributions are superimposed: the electrokinetic mechanism is predominant in spring, while the redox mechanism represents the most important contribution in autumn.
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Acknowledgments
The work is a part of the research project ModelPROBE (Model-Driven soil probing, site assessment and evaluation, Grant No. 213161 in the framework of the EC-FP7 funded). The authors thank Matthias Kastner and Giorgio Cassiani for their efforts in the project coordination. The authors also thank the two anonymous reviewers for their constructive comments.
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Giampaolo, V., Rizzo, E., Titov, K. et al. Self-potential monitoring of a crude oil-contaminated site (Trecate, Italy). Environ Sci Pollut Res 21, 8932–8947 (2014). https://doi.org/10.1007/s11356-013-2159-y
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DOI: https://doi.org/10.1007/s11356-013-2159-y