Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest | |
Xiaohang Xu; Zhidong Xu; Longchao Liang; Jialiang Han; Gaoen Wu; Qinhui Lu; Lin Liu; Pan Li; Qiao Han; Le Wang; Sensen Zhang; Yanhai Hu; Yuping Jiang; Jialin Yang; Guangle Qiu; Pan Wu | |
2024 | |
Source Publication | Science of The Total Environment
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Volume | 954 |
Abstract | Heavy metal(loid)s (HMs) in agricultural soils not only affect soil function and crop security, but also pose health risks to residents. However, previous concerns have typically focused on only one aspect, neglecting the other. This lack of a comprehensive approach challenges the identification of hotspots and the prioritization of factors for effective management. To address this gap, a novel method incorporating spatial bivariate analysis with random forest was proposed to identify high-risk hotspots and the key influencing factors. A large-scale dataset containing 2995 soil samples and soil HMs (As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, and Zn) was obtained from across Henan province, central China. Spatial bivariate analysis of both health risk and ecological risks revealed risk hotspots. Positive matrix factorization model was initially used to investigate potential sources. Twenty-two environmental variables were selected and input into random forest to further identify the key influencing factors impacting soil accumulation. Results of local Moran's I index indicated high-high HM clusters at the western and northern margins of the province. Hotspots of high ecological and health risk were primarily observed in Xuchang and Nanyang due to the widespread township enterprises with outdated pollution control measures. As concentration and exposure frequency dominated the non-carcinogenic and carcinogenic risks. Anthropogenic activities, particularly vehicular traffic (contributing ∼37.8 % of the total heavy metals accumulation), were the dominant sources of HMs in agricultural soils. Random forest modeling indicated that soil type and PM2.5 concentrations were the most influencing natural and anthropogenic variables, respectively. Based on the above findings, control measures on traffic source should be formulated and implemented provincially; in Xuchang and Nanyang, scattered township enterprises with outdated pollution control measures should be integrated and upgraded to avoid further pollution from these sources.
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DOI | 10.1016/j.scitotenv.2024.176359 |
URL | 查看原文 |
Indexed By | SCI |
Language | 英语 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.gyig.ac.cn/handle/42920512-1/15630 |
Collection | 环境地球化学国家重点实验室 |
Affiliation | 1.Key Laboratory of Karst Georesources and Environment, Ministry of Education, College of Resources and Environmental Engineering, Guizhou University, Guiyang 550025, China 2.State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China 3.School of Chemistry and Materials Science, Guizhou Normal University, Guiyang 550001, China 4.The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Provincial Engineering Research Center of Ecological Food Innovation, School of Public Health, Guizhou Medical University, Guiyang 550025, China 5.Henan Academy of Geology, Zhengzhou 450016, China 6.No.6 Geological Unit Team, Henan Provincial Non-ferrous Metals Geological and Mineral Resources Bureau, Luoyang 471002, China |
Recommended Citation GB/T 7714 | Xiaohang Xu,Zhidong Xu,Longchao Liang,et al. Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest[J]. Science of The Total Environment,2024,954. |
APA | Xiaohang Xu.,Zhidong Xu.,Longchao Liang.,Jialiang Han.,Gaoen Wu.,...&Pan Wu.(2024).Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest.Science of The Total Environment,954. |
MLA | Xiaohang Xu,et al."Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest".Science of The Total Environment 954(2024). |
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