High-resolution risk mapping of heavy metals in soil with an integrated static-dynamic interaction model: A case study in an industrial agglomeration area in China

• Published in: Journal of hazardous materials Vol. 455; p. 131650
• Main Authors: Shiyi, Yi, Xiaonuo, Li, Weiping, Chen
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 05.08.2023
• Subjects: case studies; China; heavy metals; Heavy metals pollution; Mass balance theory; quantitative analysis; risk; risk assessment; Risk prediction; soil; Soil management; soil pollution; Source apportionment; traffic; China; Mass balance theory; Risk prediction; Heavy metals pollution; Source apportionment; Soil management
• ISSN: 0304-3894; 1873-3336; 1873-3336
• DOI: 10.1016/j.jhazmat.2023.131650

Heavy metal pollution of soils in industrial agglomeration areas is an increasing concern worldwide. In this study, we traced the sources of heavy metal emissions using a positive matrix factorization (PMF) model. Accordingly, we proposed a novel static-dynamic risk interaction model incorporating multiple risk-related factors to quantify the spatial interaction of emission sources and the probability of accumulation of heavy metals on a large scale. This model was further classified using the Jenks optimization technique to predict the spatial distribution of high-risk hotspots. Our results determined four primary emission sources of heavy metals: industrial (35.01 %), natural (28.61 %), agricultural (26.07 %), and traffic (10.31 %) sources. Five levels were classified by the integrated risk coefficient (IRC), namely, from extremely high to extremely low risk. The extremely high- and high-risk hotspots constituting 41.52 % of the total area of the Zhenhai District, with IRC values ranging from 0.221 to 0.413, were mainly generated by multiple sources linked to PMF-based factors. This quantitative evaluation framework can generate a high-resolution spatially distributed pollution risk map at the grid scale (1 km), which can provide a relatively precise basis for policymaking for point-to-point soil pollution management. [Display omitted] •A novel static-dynamic risk interaction model is proposed for risk mapping.•Industrial source contributes the most (35 %) to heavy metals than other sources.•Extremely high- and high-risk hotspots account for 41.52 % of the study area.•Uncertainty of risk assessment is measured by Monte Carlo simulation.•Risk-based precise soil management strategies are suggested.