Kexue Han’s research focuses on the migration, transformation, and retardation mechanisms of light non-aqueous phase liquid (LNAPL) pollutants within the vadose and capillary zones. His work investigates how soil moisture, permeability contrasts, and environmental factors influence pollutant seepage, adsorption, and kinetic behavior. By integrating experimental analysis, hydrological modeling, and machine-learning approaches such as random forest algorithms, he advances quantitative prediction of LNAPL concentrations and pollutant transport pathways. His studies contribute to improved understanding of groundwater contamination processes and support more effective management and remediation strategies for hazardous organic pollutants in complex hydrogeological environments.