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Sustainability appraisal of desired contaminated groundwater remediation strategies: an information-entropy-based stochastic multi-criteria preference model

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Abstract

This study proposes an information-entropy-based stochastic multi-criteria preference model (SMCPM) to assess the sustainability of groundwater remediation strategies. The model was applied to a real-world site, which includes the following steps: (1) selecting fifty remediation alternatives with four criteria, including total pumping rate, remediation cost, average contaminant concentration and general cancer risk in light of uncertainty parameter (e.g., slope factor); (2) evaluating the health risks associated with the strategies under three confidence levels (i.e., 68.3%, 95.4% and 99.7%); (3) computing the weight by information entropy; and (4) determining the ranking of remedial alternatives by establishing a random evaluation matrix. Results from the case study indicate that: (1) the most desirable actions are action A39 (i.e., the pumping rates at six wells are 3.499, 2.722, 2.624, 1.458, 7.776 and 2.527 m3/h, respectively) for the 5-year; (2) action A25 (i.e., the six pumping rates at injecting and extracting wells are 2.819, 2.722, 0, 3.791, 0.972 and 1.166 m3/h, respectively) for the 10-year; (3) action A24 (i.e., the pumping rates of wells P1–P6 are 1.944, 1.555, 1.166, 3.110, 7.193 and 0.583 m3/h, respectively) for the 15-year; (4) action A37 (i.e., the optimal pumping rates of P1 to P6 become 2.138, 2.722, 3.694, 2.722, 3.694 and 7.582 m3/h, respectively) for the 20-year remediation, respectively. Compared to the traditional MCPM, the proposed SMCPM would be more acceptable and reasonable since various uncertainties be addressed.

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Acknowledgements

This research was supported by the National Key R&D Program of China (2018YFC0407201), Science Fund for Creative Research Groups of the National Natural Science Foundation of China (51621092), and College-level Research Fund Project of Shanxi Institute of Energy (ZB-2018007).

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Authors and Affiliations

  1. State Key Laboratory of Hydraulic Engineering Simulation and Safety and School of Civil Engineering, Tianjin University, Tianjin, 300072, China

    Li He

  2. School of Renewable Energy, North China Electric Power University, Beijing, 102206, China

    Li He & Feng Shao

  3. Shanxi Institute of Energy, Jinzhong, 030600, Shanxi, China

    Lixia Ren

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  1. Li He
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  2. Feng Shao
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Correspondence to Li He.

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He, L., Shao, F. & Ren, L. Sustainability appraisal of desired contaminated groundwater remediation strategies: an information-entropy-based stochastic multi-criteria preference model. Environ Dev Sustain 23, 1759–1779 (2021). https://doi.org/10.1007/s10668-020-00650-z

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