Accurate prediction of leachate from industrial solid waste landfills is a key prerequisite for mitigating the risks of soil and groundwater contamination. Analyzing existing leachate prediction methods can provide valuable scientific support for environmental risk management in industrial waste landfills. This article begins by examining the fundamental differences in formation mechanisms and pollutant characteristics between leachate from industrial solid waste and that from municipal solid waste. It subsequently reviews three mainstream prediction methods for industrial solid waste leachate: water balance, empirical formulas, and numerical simulation. These methods encounter challenges, including the absence of a dedicated parameter system for industrial solid waste, as well as the oversimplification of chemical processes and heterogeneous media. Addressing these issues, future research priorities should focus on a “database construction-AI optimization-multi-process coupling” framework, wherein the deep integration of AI algorithms and mechanistic models will be pivotal in enhancing the prediction accuracy of industrial solid waste leachate.
CHEN et al. (Thu,) studied this question.