应用多属性决策分析法筛选污染场地土壤修复技术

Application of multiple attributes decision analysis to selection of soil remediation technologies for contaminated sites

通过层次分析法计算修复技术评价指标的权重,然后分别采用逼近理想解和灰色综合评价2种模型得到备选修复技术排序。基于该决策方法,开发了修复技术筛选决策支持系统,将该系统应用于某有机污染场地土壤修复技术的筛选。研究结果显示,结合层次分析方法的逼近理想解法和灰色评价均可实现对该场地的备选修复技术较好的排序,排序的结果一致且与场地实际应用情况相符:化学氧化>土壤冲洗>固化/稳定化。逼近理想解法实现简单,但对评分指标的要求比较严格,且需要借助模型的敏感性分析来加以验证,适合于备选修复技术评价结果先汇总后排序。灰色评价法引入了灰色理论用于处理数据的不确定性,适合于评价小组评价者各自评分然后在灰色评价模型中综合。将层次分析法与逼近理想解模型、灰色综合评价模型结合,应用于污染场地修复技术的筛选,既可以减少层次分析法的主观性,又可以削弱逼近理想解模型和灰色综合评价模型在应用过程中对权重的忽视。本研究为选择可行、经济、高效、环境友好的污染场地土壤修复技术提供方法依据和理论参考。

A framework integrating the analytic hierarchy process （AHP） with a technique for order preference by similarity to the ideal solution （TOPSIS） and grey evaluating （GE） for selecting soil remediation technologies was developed and demonstrated. The methodology included two steps： 1 ） the establishment of an evaluation in- dex system and weights calculation, and 2） comparing and sorting preferred remediation technologies. A decision support system was developed based on this framework. The results of applying our system to an organic contami- nated site show that this framework allows ranking of alternative remediation technologies as a consistent result of ranking and matching the practical application： Chemical Oxidation 〉 Soil Washing 〉 Solidification/Stabiliza- tion. The TOPSIS method is easy to use but needs a rigorous evaluation index. Moreover, a sensitivity analysis of aided validation is necessary for TOPSIS, which is suitable for the ranking of remediation technologies after gath- ering all the evaluation scores. By incorporating grey theory for resolving the uncertainty of evaluation scores, GE performs well in the ranking of remediation technologies when all evaluators give their own scores before gather- ing. The application of TOPSIS and GE combined with AHP for the selection of soil remediation technologies can both reduce the subjectivity of AHP and improve TOPSIS and GE by taking the weight of evaluation indexes into account. Our study provides a basic strategy and theoretical reference for the selection of feasible, economical, efficient, and environment-friendly remediation technology for soil contaminated sites.