Quantitative source apportionment and associated driving factor identification for soil potential toxicity elements via combining receptor models, SOM, and geo-detector method
文献类型:期刊论文
作者 | Guo, Guanghui2; Li, Kai; Zhang, Degang; Lei, Mei |
刊名 | SCIENCE OF THE TOTAL ENVIRONMENT
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出版日期 | 2022-07-15 |
卷号 | 830页码:12 |
关键词 | Potential toxicity elements Soil pollution Source apportionment Driving factor |
ISSN号 | 0048-9697 |
DOI | 10.1016/j.scitotenv.2022.154721 |
通讯作者 | Guo, Guanghui(Guogh@igsnrr.ac.cn) |
英文摘要 | Quantitative source apportionment of soil potential toxicity elements (PTEs) and associated driving factor identifica-tion are critical for prevention and control of soil PTEs. In this study, 421 soil samples from a typical area in southeastern Yunnan Province of China were collected to evaluate the pollution level of soil PTE using pollution factors, pollution load index, and enrichment factors. Positive matrix factorization (PMF), absolute principal component score/multiple line regression (APCS/MLR), edge analysis (UNMIX) and self-organizing map (SOM) were applied for source apportionment of soil PTEs. The geo-detector method (GDM) was used to identify the driving factor to PTE pollution sources, which assisted in source interpretation derived from receptor models. The results showed that the geometric mean of As, Cd, Cu, Cr, Ni, Pb, and Zn were 94.94, 1.02, 108.6, 75.40, 57.14, 160.2, and 200.3 mg/kg, which were significantly higher than their corresponding background values (P < 0.00). Particularly, As and Cd were 8.71 and 12.75 times higher than their corresponding background values, respectively. SOM yielded four clusters of soil PTEs: AsCd, PbZn, CrNi, and Cu. APCS/MLR was regarded as the preferred receptor model for source apportionment of soil PTEs due to its optimal performance. The results of ACPS/MLR revealed that 36.64% of Pb and 38.30% of Zn were related to traffic emissions, Cr (92.64 %) and Ni (82.51%) to natural sources, As (85.83%) and Cd (87.04%) to industrial discharge, and Cu (42.78%) to agricultural activities. Distance to road, lithology, distance to industries, and land utilization were the respective major driving factor influencing these four sources, with the q values of 0.1213, 0.1032, 0.2295 and 0.1137, respectively. Additionally, GDM revealed that nonlinear interactions between anthropogenic and natural factors influencing PTEs sources. Based on these results, comprehensive prevention and control strategies should be considered for pollution prevention and risk controlling. |
WOS关键词 | HEAVY-METALS ; AGRICULTURAL SOILS ; RISK-ASSESSMENT ; TRACE-ELEMENTS ; CHINA ; RICE ; CONTAMINATION ; INVENTORY ; POLLUTION ; PROVINCE |
资助项目 | National Key Research and Development Program of China[2018YFC1800104] |
WOS研究方向 | Environmental Sciences & Ecology |
语种 | 英语 |
WOS记录号 | WOS:000790510400013 |
出版者 | ELSEVIER |
资助机构 | National Key Research and Development Program of China |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/177297] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Guo, Guanghui |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Guo, Guanghui,Li, Kai,Zhang, Degang,et al. Quantitative source apportionment and associated driving factor identification for soil potential toxicity elements via combining receptor models, SOM, and geo-detector method[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2022,830:12. |
APA | Guo, Guanghui,Li, Kai,Zhang, Degang,&Lei, Mei.(2022).Quantitative source apportionment and associated driving factor identification for soil potential toxicity elements via combining receptor models, SOM, and geo-detector method.SCIENCE OF THE TOTAL ENVIRONMENT,830,12. |
MLA | Guo, Guanghui,et al."Quantitative source apportionment and associated driving factor identification for soil potential toxicity elements via combining receptor models, SOM, and geo-detector method".SCIENCE OF THE TOTAL ENVIRONMENT 830(2022):12. |
入库方式: OAI收割
来源:地理科学与资源研究所
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