Research Advances in Dynamic Multi-pollutant Risk Assessment Models for Groundwater in Chemical Industrial Parks

Chemical industrial parks (CIPs) often exhibit groundwater plumes that are characterized by high concentrations, multicomponent mixtures, and pronounced temporal variability owing to intensive raw-material handling, complex production emissions, and accidental releases. These composite plumes pose cumulative risks to both ecosystem integrity and public health. Over the past two decades, groundwater-risk assessment has undergone three paradigm shifts-from static concentration-based thresholds, through multi-pollutant weighted scoring, to dynamic prediction frameworks that fuse process models with data-driven methods. This review systematically dissects the source-migration-exposure-effect chain of multi-contaminant groundwater in CIPs, summarizes recent advances in cross-scale simulation of coupled hydrological, geochemical, and pollutant migration-transformation as well as ecotoxicological processes, and highlights emerging risk-governance paradigms empowered by machine learning and digital-twin technology. Finally, future directions are proposed for regulatory implementation, data sharing, and interdisciplinary integration, providing a comprehensive reference for dynamic multi-pollutant risk assessment and precision management.