Guan Qingyu, Wang Feifei, Xu Chuanqi, Pan Ninghui, Lin Jinkuo, Zhao Rui, Yang Yanyan, Luo Haiping
Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
Key Laboratory of Western China's Environmental Systems (Ministry of Education) and Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
Chemosphere. 2018 Feb;193:189-197. doi: 10.1016/j.chemosphere.2017.10.151. Epub 2017 Oct 27.
Hexi Corridor is the most important base of commodity grain and producing area for cash crops. However, the rapid development of agriculture and industry has inevitably led to heavy metal contamination in the soils. Multivariate statistical analysis, GIS-based geostatistical methods and Positive Matrix Factorization (PMF) receptor modeling techniques were used to understand the levels of heavy metals and their source apportionment for agricultural soil in Hexi Corridor. The results showed that the average concentrations of Cr, Cu, Ni, Pb and Zn were lower than the secondary standard of soil environmental quality; however, the concentrations of eight metals (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn) were higher than background values, and their corresponding enrichment factor values were significantly greater than 1. Different degrees of heavy metal pollution occurred in the agricultural soils; specifically, Ni had the most potential for impacting human health. The results from the multivariate statistical analysis and GIS-based geostatistical methods indicated both natural sources (Co and W) and anthropogenic sources (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn). To better identify pollution sources of heavy metals in the agricultural soils, the PMF model was applied. Further source apportionment revealed that enrichments of Pb and Zn were attributed to traffic sources; Cr and Ni were closely related to industrial activities, including mining, smelting, coal combustion, iron and steel production and metal processing; Zn and Cu originated from agricultural activities; and V, Ti and Mn were derived from oil- and coal-related activities.
河西走廊是最重要的商品粮基地和经济作物产区。然而，工农业的快速发展不可避免地导致了土壤中的重金属污染。采用多元统计分析、基于地理信息系统（GIS）的地统计方法和正定矩阵因子分解（PMF）受体模型技术，来了解河西走廊农业土壤中重金属的含量及其来源分配。结果表明，铬（Cr）、铜（Cu）、镍（Ni）、铅（Pb）和锌（Zn）的平均浓度低于土壤环境质量二级标准；然而，8种金属（Cr、Cu、锰（Mn）、Ni、Pb、钛（Ti）、钒（V）和Zn）的浓度高于背景值，其相应的富集因子值显著大于1。农业土壤中出现了不同程度的重金属污染；具体而言，镍对人类健康的影响潜力最大。多元统计分析和基于GIS的地统计方法的结果表明，既有自然来源（钴（Co）和钨（W）），也有人为来源（Cr、Cu、Mn、Ni、Pb、Ti、V和Zn）。为了更好地识别农业土壤中重金属的污染源，应用了PMF模型。进一步的源解析表明，Pb和Zn的富集归因于交通源；Cr和Ni与工业活动密切相关，包括采矿、冶炼、煤炭燃烧、钢铁生产和金属加工；Zn和Cu源于农业活动；V、Ti和Mn来自与石油和煤炭相关的活动。
