ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Toxicology, Pollution and the Environment
This article is part of the Research TopicModeling for Environmental Pollution and Change, Volume IIView all 6 articles
GIS-PMF-Monte Carlo Integrated Framework for Source-Risk Linkage of Priority Heavy Metals and Metalloid in Retired Coking Site Soils
Provisionally accepted
- 1Shandong University, Jinan, China
- 2Jiaying University, Meizhou, China
- 3Key Laboratory of Guangdong Higher Education Institutions of Northeast Guangdong New Functional Materials, School of Chemistry and Environment, Jiaying University, Guangdong Meizhou, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Abstract Introduction: To 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 (Jinxzhong, China) planned for residential redevelopment. Methods: Twenty-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. Results: Four 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. Conclusions: This 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.
Keywords: Ecological and health risk, Heavy metals and metalloid, PMF modeling, Probabilistic assessment, SOURCE APPORTIONMENT
Received: 29 Nov 2025; Accepted: 12 Dec 2025.
Copyright: © 2025 Liang, Liu, Wang and Wei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Fenghua Wei
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.