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基于APCS-MLR和PMF受体模型的煤矿矸石山周边农田土壤重金属污染特征及源解析

[Pollution Characteristics and Source Apportionment of Heavy Metals in Farmland Soils Around the Gangue Heap of Coal Mine Based on APCS-MLR and PMF Receptor Model].

作者信息

Ma Jie, Shen Zhi-Jie, Zhang Ping-Ping, Liu Ping, Liu Jin-Zhao, Sun Jing, Wang Ling-Ling

机构信息

Chongqing Ecological and Environmental Monitoring Center, Chongqing 401147, China.

Rural Ecology and Soil Monitoring Technology Research Center, Chongqing 401147, China.

出版信息

Huan Jing Ke Xue. 2023 Apr 8;44(4):2192-2203. doi: 10.13227/j.hjkx.202206045.

Abstract

To analyze the pollution characteristics and source apportionment of heavy metal pollution in soil of farmland surrounding the Gangue Heap of Coal Mine in Nanchuan, Chongqing, the Nemerow pollution index and Muller index were used. Meanwhile, to investigate the sources and contribution rate of heavy metals in the soil, absolute principal component score-multiple linear regression receptor modeling (APCS-MLR) and positive matrix factorization (PMF) were employed. The results showed higher amounts of Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn in the downstream area than those in the upstream area, and only Cu, Ni, and Zn showed significantly higher amounts in the downstream area than those in upstream area (<0.05). The comprehensive Nemerow pollution index was as follows:downstream area (1.22)>upstream area (0.95), and the degree of heavy metal pollution was:Cd>Cu>Hg, As, Pb, Cr, Ni, and Zn. The Muller pollution index showed:Cd>As>Cu=Hg>Ni>Zn=Cr>Pb. The pollution source analysis showed that Cu, Ni, and Zn were mainly affected by mining activities such as long-term accumulation of the gangue heap of coal mine, with the contribution rates of APCS-MLR being 49.8%, 94.5%, and 73.2%, respectively. Additionally, PMF contribution rates were 62.8%, 62.2%, and 63.1%, respectively. Cd, Hg, and As were mainly affected by agricultural activities and transportation activities, with APCS-MLR contribution rates of 49.8%, 94.5%, and 73.2% and PMF contribution rates of 62.8%, 62.2%, and 63.1%, respectively. Further, Pb and Cr were mainly affected by natural factors, with APCS-MLR contribution rates of 66.4% and 94.7% and PMF contribution rates of 42.7% and 47.7%, respectively. The results of source analysis were basically consistent between the APCS-MLR and PMF receptor models.

摘要

为分析重庆南川煤矿矸石山周边农田土壤重金属污染特征及来源,采用了内梅罗污染指数和缪勒指数。同时,为探究土壤中重金属的来源及贡献率,运用了绝对主成分得分-多元线性回归受体模型(APCS-MLR)和正定矩阵因子分解法(PMF)。结果表明,下游区域Cd、Hg、As、Pb、Cr、Cu、Ni和Zn的含量高于上游区域,仅Cu、Ni和Zn在下游区域的含量显著高于上游区域(<0.05)。综合内梅罗污染指数如下:下游区域(1.22)>上游区域(0.95),重金属污染程度为:Cd>Cu>Hg、As、Pb、Cr、Ni和Zn。缪勒污染指数显示:Cd>As>Cu=Hg>Ni>Zn=Cr>Pb。污染源分析表明,Cu、Ni和Zn主要受煤矿矸石山长期堆积等采矿活动影响,APCS-MLR的贡献率分别为49.8%、94.5%和73.2%。此外,PMF的贡献率分别为62.8%、62.2%和63.1%。Cd、Hg和As主要受农业活动和交通活动影响,APCS-MLR的贡献率分别为49.8%、94.5%和73.2%,PMF的贡献率分别为62.8%、62.2%和63.1%。此外,Pb和Cr主要受自然因素影响,APCS-MLR的贡献率分别为66.4%和94.7%,PMF的贡献率分别为42.7%和47.7%。APCS-MLR和PMF受体模型的源分析结果基本一致。

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