Identification of the Pollution Mechanisms and Remediation Strategies for Abandoned Wells in the Karst Areas of Northern China

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Abstract
Abandoned well pollution is a critical component of global environmental issues and a historical legacy issue of national development. Despite this, the specific mechanisms by which abandoned wells pollute groundwater remain unclear, particularly in the karst regions of Northern China, where no scientifically effective remediation methods exist. To address this gap, this study focuses on Yangquan City in Shanxi Province and employs field investigations, the analytic hierarchy process, high-definition deep-well logging technology, and qualitative analysis to assess the pollution risk of all abandoned wells in the study area, identifying those with high pollution risk. Through the analysis of extensive image and video data for these high-risk wells, we propose a conceptual model of cross-strata channels in abandoned wells and elucidate the mechanisms by which they pollute groundwater. The results show that, from a single-well perspective, the pollution mechanism is cross-strata pollution. From a regional perspective, the pollution mechanisms are hydraulic connectivity and solute migration and transformation. Based on these findings, we present a scientifically effective remediation strategy tailored to the typical characteristics of abandoned wells in the study area, offering a viable solution to the abandoned well pollution problem in Yangquan City. This research not only augments the theoretical framework in the domain of groundwater pollution but also advances sustainable groundwater security and management strategies. Moreover, the study furnishes theoretical foundations and pragmatic solutions for the remediation of abandoned wells in Yangquan City, which are crucial for the sustainability of the groundwater ecosystem.
Funding Information
  • National Key Research and Development Program of China (2023YFC3710000, 41130637, DD20190593, 22373601D, E2021403001)
  • State Key Program of the National Natural Science of China (2023YFC3710000, 41130637, DD20190593, 22373601D, E2021403001)
  • the China Geological Survey Project of CGS (2023YFC3710000, 41130637, DD20190593, 22373601D, E2021403001)
  • S&T Program of Hebei (2023YFC3710000, 41130637, DD20190593, 22373601D, E2021403001)
  • Natural Science Funds Project in Hebei Province (2023YFC3710000, 41130637, DD20190593, 22373601D, E2021403001)

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