Optimization of heavy metal pollution remediation technologies for agricultural land in mining areas based on improved AHP， EWM， and game theory

In order to solve the problems of complexity and cumbersomeness in the optimization process of heavy metal pollution remediation technologies for agricultural land in mining areas， this study identified the optimization indexes of such technologies， and established a comprehensive optimization index system. Based on the improved analytic hierarchy process （AHP）， entropy weight method （EWM）， game theory， and technique for order preference by similarity to ideal solution （TOPSIS）， an optimization model for heavy metal pollution remediation of mining area agricultural land was constructed. Taking the agricultural land around a smelting slag field in Gejiu City， Yunnan Province as an example， the constructed model was verified. The results showed that the scientificity and accuracy of the optimization indexes were improved by weight distribution optimization through the game theory model. According to the different relative closeness values of the candidate technologies， the priority ranking was determined as follows： phytoremediation was superior to soil leaching remediation， followed by animal-mediated remediation， and microbial remediation was the least effective. This indicated that in the heavy metal pollution remediation of agricultural land around the smelting slag field in Gejiu City， Yunnan Province， phytoremediation achieved the best treatment effect， which was consistent with engineering practice. Compared with the traditional models， the new model overcomes the shortcomings of ambiguous indicators， subjective weighting， and single evaluation method inherent in traditional evaluation systems， and has certain practical application value， which can provide a reference for heavy metal pollution remediation projects of agricultural land in mining areas.