Develops a preference-guided framework for remediation allocation in contaminated industrial parks, suggesting optimized sustainability outcomes.
Soil and groundwater contamination across multiple plots in industrial parks is an important environmental management challenge. Because plots often differ in contamination characteristics and remediation requirements, remediation decision-making needs to generate sustainability-oriented alternatives that account for explicit management preferences and trade-offs among carbon emissions, remediation duration, and cost. Although technology screening for individual contaminated plots has been widely investigated, how to use plot-level screening results to support the selection of multi-plot remediation alternatives under multiple objectives remains insufficiently addressed. This study developed a preference-guided multi-objective decision framework for selecting remediation alternatives in contaminated industrial parks. The framework first generates cross-plot remediation alternatives by assigning one feasible technology to each plot and removes alternatives that violate technological compatibility or project-level engineering constraints. It then identifies Pareto non-dominated alternatives using NSGA-II, retains preference-consistent alternatives through LO-based filtering, and selects the final recommendation using ideal-point distance comparison. The framework was applied to a five-plot contaminated industrial park in northern China. Compared with the LO and NSGA-II benchmarks, the hybrid NSGA-II–LO model selected less imbalanced alternatives that retained the preferred-objective advantage while improving the balance among the remaining objectives. The results show that management priorities can substantially affect remediation technology allocation across plots and that preference screening can support the adjustment of remediation alternatives when low-carbon targets, remediation schedules, or budget constraints change. This study provides an operational decision framework for translating plot-level technology screening into sustainability-oriented multi-plot remediation decision-making.
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Cai et al. (2026) studied this question.
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