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运用组合受体模型对宝山土壤中潜在有毒元素进行定量源解析

Quantitative Source Apportionment of Potentially Toxic Elements in Baoshan Soils Employing Combined Receptor Models.

作者信息

Dong Chunyu, Zhang Hao, Yang Haichan, Wei Zhaoxia, Zhang Naiming, Bao Li

机构信息

Yunnan Agricultural University, Kunming 650201, China.

Yunnan Laboratory of Improvement of Soil Fertility and Pollution Remediation, Kunming 650201, China.

出版信息

Toxics. 2023 Mar 14;11(3):268. doi: 10.3390/toxics11030268.

DOI:10.3390/toxics11030268
PMID:36977033
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10054906/
Abstract

Arable soils are crucial for national development and food security; therefore, contamination of agricultural soils from potentially toxic elements (PTEs) is a global concern. In this study, we collected 152 soil samples for evaluation. Considering the contamination factors and using the cumulative index and geostatistical methods, we investigated the contamination levels of PTEs in Baoshan City, China. Using principal component analysis, absolute principal component score-multivariate linear regression, positive matrix factorization, and UNMIX, we analyzed the sources and quantitatively estimated their contributions. The average Cd, As, Pb, Cu, and Zn concentrations were 0.28, 31.42, 47.59, 100.46, and 12.36 mg/kg, respectively. The Cd, Cu, and Zn concentrations exceeded the corresponding background values for Yunnan Province. The combined receptor models showed that natural and agricultural sources contributed primarily to Cd and Cu and As and Pb inputs, accounting for 35.23 and 7.67% pollution, respectively. Industrial and traffic sources contributed primarily to Pb and Zn inputs (47.12%). Anthropogenic activities and natural causes accounted for 64.76 and 35.23% of soil pollution, respectively. Industrial and traffic sources contributed 47.12% to pollution from anthropogenic activities. Accordingly, the control of industrial PTE pollution emissions should be strengthened, and awareness should be raised to protect arable land around roads.

摘要

耕地土壤对国家发展和粮食安全至关重要;因此,潜在有毒元素(PTEs)对农业土壤的污染是一个全球关注的问题。在本研究中,我们采集了152个土壤样本进行评估。考虑到污染因素并使用累积指数和地统计学方法,我们调查了中国保山市PTEs的污染水平。使用主成分分析、绝对主成分得分-多元线性回归、正定矩阵因子分解和UNMIX,我们分析了来源并定量估计了它们的贡献。Cd、As、Pb、Cu和Zn的平均浓度分别为0.28、31.42、47.59、100.46和12.36 mg/kg。Cd、Cu和Zn的浓度超过了云南省相应的背景值。综合受体模型表明,自然和农业来源主要导致了Cd和Cu以及As和Pb的输入,分别占污染的35.23%和7.67%。工业和交通来源主要导致了Pb和Zn的输入(47.12%)。人为活动和自然原因分别占土壤污染的64.76%和35.23%。工业和交通来源对人为活动造成的污染贡献了47.12%。因此,应加强对工业PTE污染排放的控制,并提高保护道路周边耕地的意识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/e588ebae42b9/toxics-11-00268-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/46187f53652f/toxics-11-00268-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/658d9efbf3d5/toxics-11-00268-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/f9bf97122c51/toxics-11-00268-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/721d31161e5a/toxics-11-00268-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/62acccec7770/toxics-11-00268-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/748c4b6fe357/toxics-11-00268-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/aea77642f8eb/toxics-11-00268-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/e588ebae42b9/toxics-11-00268-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/46187f53652f/toxics-11-00268-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/aec64184824f/toxics-11-00268-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/658d9efbf3d5/toxics-11-00268-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/f9bf97122c51/toxics-11-00268-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/721d31161e5a/toxics-11-00268-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/62acccec7770/toxics-11-00268-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/748c4b6fe357/toxics-11-00268-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/aea77642f8eb/toxics-11-00268-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b297/10054906/e588ebae42b9/toxics-11-00268-g009.jpg

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