A Fuzzy-based Methodology for an Aggregative Environmental Risk Assessment of Restored Soil

Environmental risks pertaining to contaminated soils have been well studied, while little attention has been paid to the risks of the soils after remediation. In this study, a concept model developed based on fuzzy set theory was applied to evaluate the uncertainties of three risk indicators, namely, plant growth, groundwater safety and human health, of a restored site that had been previously polluted by heavy metals. The concept model classified the grade and importance of risk factors by an 11-level ranking system and was able to yield a comprehensive risk result rather than multi-risk results for complex risk indicators. Modeling results showed that the risks to the three indicators were effectively reduced after the remediation. Moreover, great sensitivity of the risks was found related to the weight distribution among the three risk indicators. In general, the risks of both polluted and restored soils to the environment were in the order of groundwater safety > plant growth > human health. The model was proved to solve the problems of multi-risk results due to complex risk indicators that previously encountered by other researchers, which made it helpful in decision-making and management of restored soils.