[Source and Influencing Factor Analysis of Soil Heavy Metals Based on PMF Model and GeoDetector].

Q2 Environmental Science
Si-Jing Sun, Chun-Yu Dong, Hao Zhang, Hai-Chan Yang, Zu-Zhi Huang, Yu Han, Nai-Ming Zhang, Li Bao
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Abstract

In Lijiang City, as a typical example, 93 soil samples were collected from the study area, and soil pH; organic matter; and heavy metals arsenic (As), mercury (Hg), copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd), and chromium (Cr) were determined. We explored the sources of heavy metals in the study area by means of Positive Definite Matrix Factorization (PMF) modeling and analyzed the impact of influencing factors by combining seven heavy metals with 13 influencing factors in a GeoDetector. The results showed that the mean values of soil heavy metals ω(As), ω(Hg), ω(Cu), ω(Zn), ω(Pb), ω(Cd), and ω(Cr) in the study area were 17.55, 0.19, 86.75, 164.84, 28.95, 0.39, and 167.87 mg·kg-1, respectively, which were greater than the background values of soils in Yunnan Province (except for As and Pb). Regarding spatial distribution, the high values of Cu and Cr content were mainly concentrated in Yulong Naxi Autonomous County; the high value areas of As, Hg, Pb, and Cd were mainly concentrated in Ninglang Yi Autonomous County; and the high value of Zn content was mainly concentrated in Huaping County. Correlation analysis and PMF modeling revealed that the main sources of heavy metals As and Hg in the study area were industrial sources, Zn was from transportation pollution sources, Cr and Cu were from natural sources, and Cd and Pb were from agricultural sources. Further, the factor detector of the GeoDetector found that soil pH and organic matter (OC) had strong explanatory power for the content of seven heavy metals, and the interaction detector found that the results following the interaction of different influencing factors were nonlinear enhancement or two-factor enhancement, in which the interaction of OC and pH was the dominant factor for the spatial differentiation of heavy metals. This provides an important scientific basis for the protection of the soil environmental health and sustainable development in Lijiang City.

[基于 PMF 模型和 GeoDetector 的土壤重金属来源和影响因素分析]。
以丽江市为例,在研究区域采集了93个土壤样品,对土壤pH值、有机质、重金属砷(As)汞(Hg)、铜(Cu)、锌(Zn)、铅(Pb)、镉(Cd)和铬(Cr)。进行了测定。我们通过正定矩阵因式分解(PMF)模型探索了研究区域的重金属来源,并分析了影响重金属来源的因素。建模,并将 7 种重金属与 13 种影响因素结合在一个 GeoDetector 中,分析了影响因素的影响。结果表明,研究区土壤重金属ω(As)、ω(Hg)、ω(Cu)、ω(Zn)、ω(Pb)、ω(Cd)和ω(Cr)的平均值分别为 17.55%、17.55%和 17.55%。分别为17.55、0.19、86.75、164.84、28.95、0.39和167.87 mg-kg-1,均大于云南省土壤背景值(砷和铅除外)。在空间分布上,铜和铬的高值区主要集中在玉龙纳西族自治县,砷、汞、铅和镉的高值区主要集中在宁蒗彝族自治县,锌的高值区主要集中在华坪县。相关分析和 PMF 模型显示,研究区重金属砷和汞的主要来源是工业污染源,锌的主要来源是交通污染源,铬和铜的主要来源是自然污染源,镉和铅的主要来源是农业污染源。此外,GeoDetector 的因子检测器发现,土壤 pH 值和有机质(OC)交互作用检测器发现,不同影响因素交互作用后的结果呈非线性增强或双因素增强,其中有机质和 pH 的交互作用是重金属空间分异的主导因素。这为保护丽江市土壤环境健康和可持续发展提供了重要的科学依据。
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来源期刊
Huanjing Kexue/Environmental Science
Huanjing Kexue/Environmental Science Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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