GIS-PMF-Monte Carlo integrated framework for source-risk linkage of priority heavy metals and metalloid in retired coking site soils - Liang, Yuhan; Liu, Jieyu; Wang, Pingping; Wei, Fenghua (Frontiers in Environmental Science, 2025)
IntroductionTo address the limitation of being unable to quantitatively link soil heavy metal and metalloid pollution sources to risk contributions in industrial regions, this study investigated contamination characteristics, sources, and ecological/health risks of six target elements (five heavy metals: Cd, Cu, Pb, Hg, Ni; one metalloid: As) in a decommissioned coking site (Jinzhong, China) planned for residential redevelopment.MethodsTwenty-six soil samples were collected from shallow (0–2.4 m) and deep (2.4–10 m) layers. An integrated framework was applied: Inverse Distance Weighting (IDW) interpolation (using QGIS) for spatial mapping of heavy metals and metalloid; Positive Matrix Factorization (PMF) model for source apportionment of heavy metals and metalloid; and Monte Carlo simulation for risk quantification.ResultsFour sources were identified with distinct contribution rates: traffic emissions (24.5%), agricultural activities (27.6%), coking industry (16.5%), and other industries (31.4%). Ecological risk was dominated by Hg from the coking industry, while health risk, significantly higher in children, was driven by Cd (heavy metal) and As (metalloid) from agricultural activities, surpassing insights from conventional concentration-oriented assessments.ConclusionThis framework realizes quantitative source-risk linkage, identifying coking-derived Hg and agricultural-derived Cd/As as priority pollutants. It provides a scientific basis for targeted pollution control and cost-effective soil remediation in coking areas undergoing urban renewal.