journal article·2022-03-09Open access

Fingerprinting Organochlorine Groundwater Plumes Based on Non-Invasive ERT Technology at a Chemical Plant

Zihan Yan, Xiaoming Song, Yuhui Wu, Cuiping Gao, Yunlong Wang, Yuesuo Yang

Applied Sciences· Volume 12· Issue 6

Abstract

The refined characterization of groundwater pollution is an important prerequisite for efficient and effective remediation. A high-resolution survey of a contaminated site in a chemical pesticide factory was carried out using non-invasive geophysical sensing technology. Modern electrical resistivity tomography (ERT) technology can rapidly identify and characterize the groundwater pollution plumes of organochlorine pesticides, which was demonstrated in this study by the significantly abnormal resistivity sensing in stratums and aquifers under the raw material tanks, production, and loading areas. The results were found to be highly consistent with the ERT sensing results achieved via incorporating borehole sampling and hydrochemical analysis. With high abnormal resistivity, the range of contamination within the profile was characterized on the meter level. We also unexpectedly found new pollution and explained its source. This study confirmed that the modern refined ERT method has a high feasibility and accuracy in characterizing the spatial distribution of organochlorine pesticide plumes in groundwater.
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Research context

OpenAlex topics: Geophysical and Geoelectrical Methods · Geophysical Methods and Applications · Mineral Processing and Grinding

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Groundwater Resources and Environment, Jilin University, Ministry of Education, Changchun 130021, China

Jilin Provincial Key Laboratory of Water Resources and Environment, Jilin University, Changchun 130021, China

Key Lab of Eco-Restoration of Regional Contaminated Environment, Shenyang University, Ministry of Education, Shenyang 110044, China

Funding

National Major R&D Program of China · Major R&D Project of Liaoning Province · 111 Project (B16020) of Jilin University, China

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