{"title":"Source apportionment and health risks of heavy metals in agricultural soils near mining areas: APCS-MLR and Monte Carlo approaches.","authors":"Yangfan Zhao, Yinggang Wang, Hao Wu, Hui Wang, Jingpeng Yue, Ziyang Gao, Jinliang Deng, Xiaojun Li","doi":"10.1007/s10653-025-02683-7","DOIUrl":null,"url":null,"abstract":"<p><p>Soil contamination is a significant threat to global food security and public health. Accurate apportionment of pollutant sources is a prerequisite for developing science-driven pollution control protocols. This research was undertaken in Huanren Manchu Autonomous County, located in Northeast China. With a resident population of approximately 216,000, the county boasts abundant natural resources including mineral deposits, biodiversity, and water reserves. Data were preprocessed using Principal Component Analysis (PCA) to enhance interpretability for subsequent modeling. Abbreviated Principal Component Score Multilinear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) were cross-validated to ensure robust source attribution, thereby addressing the limitations of single-method uncertainty. This triangulation approach, combined with probabilistic Monte Carlo Simulation and health risk assessment, enabled a multi-dimensional evaluation of contamination pathways and risks. This aspect has been underexplored in heavy metal (HM) studies of mining-impacted agricultural soils. The average concentrations of eight heavy metals were as follows: Cr (74.0 mg/kg), Ni (32.1 mg/kg), Cu (118.9 mg/kg), Zn (541.7 mg/kg), Cd (2.2 mg/kg), Pb (202.0 mg/kg), Hg (0.3 mg/kg), and As (12.0 mg/kg). Quantitative pollution source analysis revealed three primary contributors to soil HMs: industrial point sources (contributing 46.1%), which is the most significant contributor to pollution; agricultural sources (contributing 22.2%) and natural sources (contributing 31.7%). Industrial sources, as the primary local pollution contributors, will effectively guide relevant government departments in formulating targeted management policies and measures. Probabilistic risk evaluation yielded two crucial findings: (1) Non-carcinogenic hazard indices for adults and children remained below 1, indicating acceptable risks from the presence of HMs in agricultural soils, however, (2) Carcinogenic risks surpassed the 1 × 10⁻<sup>4</sup> cancer risk benchmark for 100% of children and 32.3% of adults. Carcinogenic risks to the human population arising from individual HMs showed the following sequence: Cr > Ni > As > Zn > Cd. This research has not only revealed an alarmingly high risk of cancer in the study region due to HMs accumulation in its agricultural soils but also, by identifying the crucial sources, provided a scientific basis for controlling this harmful pollution.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 9","pages":"364"},"PeriodicalIF":3.8000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Geochemistry and Health","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s10653-025-02683-7","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Soil contamination is a significant threat to global food security and public health. Accurate apportionment of pollutant sources is a prerequisite for developing science-driven pollution control protocols. This research was undertaken in Huanren Manchu Autonomous County, located in Northeast China. With a resident population of approximately 216,000, the county boasts abundant natural resources including mineral deposits, biodiversity, and water reserves. Data were preprocessed using Principal Component Analysis (PCA) to enhance interpretability for subsequent modeling. Abbreviated Principal Component Score Multilinear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) were cross-validated to ensure robust source attribution, thereby addressing the limitations of single-method uncertainty. This triangulation approach, combined with probabilistic Monte Carlo Simulation and health risk assessment, enabled a multi-dimensional evaluation of contamination pathways and risks. This aspect has been underexplored in heavy metal (HM) studies of mining-impacted agricultural soils. The average concentrations of eight heavy metals were as follows: Cr (74.0 mg/kg), Ni (32.1 mg/kg), Cu (118.9 mg/kg), Zn (541.7 mg/kg), Cd (2.2 mg/kg), Pb (202.0 mg/kg), Hg (0.3 mg/kg), and As (12.0 mg/kg). Quantitative pollution source analysis revealed three primary contributors to soil HMs: industrial point sources (contributing 46.1%), which is the most significant contributor to pollution; agricultural sources (contributing 22.2%) and natural sources (contributing 31.7%). Industrial sources, as the primary local pollution contributors, will effectively guide relevant government departments in formulating targeted management policies and measures. Probabilistic risk evaluation yielded two crucial findings: (1) Non-carcinogenic hazard indices for adults and children remained below 1, indicating acceptable risks from the presence of HMs in agricultural soils, however, (2) Carcinogenic risks surpassed the 1 × 10⁻4 cancer risk benchmark for 100% of children and 32.3% of adults. Carcinogenic risks to the human population arising from individual HMs showed the following sequence: Cr > Ni > As > Zn > Cd. This research has not only revealed an alarmingly high risk of cancer in the study region due to HMs accumulation in its agricultural soils but also, by identifying the crucial sources, provided a scientific basis for controlling this harmful pollution.
期刊介绍:
Environmental Geochemistry and Health publishes original research papers and review papers across the broad field of environmental geochemistry. Environmental geochemistry and health establishes and explains links between the natural or disturbed chemical composition of the earth’s surface and the health of plants, animals and people.
Beneficial elements regulate or promote enzymatic and hormonal activity whereas other elements may be toxic. Bedrock geochemistry controls the composition of soil and hence that of water and vegetation. Environmental issues, such as pollution, arising from the extraction and use of mineral resources, are discussed. The effects of contaminants introduced into the earth’s geochemical systems are examined. Geochemical surveys of soil, water and plants show how major and trace elements are distributed geographically. Associated epidemiological studies reveal the possibility of causal links between the natural or disturbed geochemical environment and disease. Experimental research illuminates the nature or consequences of natural or disturbed geochemical processes.
The journal particularly welcomes novel research linking environmental geochemistry and health issues on such topics as: heavy metals (including mercury), persistent organic pollutants (POPs), and mixed chemicals emitted through human activities, such as uncontrolled recycling of electronic-waste; waste recycling; surface-atmospheric interaction processes (natural and anthropogenic emissions, vertical transport, deposition, and physical-chemical interaction) of gases and aerosols; phytoremediation/restoration of contaminated sites; food contamination and safety; environmental effects of medicines; effects and toxicity of mixed pollutants; speciation of heavy metals/metalloids; effects of mining; disturbed geochemistry from human behavior, natural or man-made hazards; particle and nanoparticle toxicology; risk and the vulnerability of populations, etc.