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重庆市煤矸山周边农用地土壤重金属污染评价和定量溯源解析
引用本文:马杰,刘萍,刘今朝,郭春会,张秀,王玲灵.重庆市煤矸山周边农用地土壤重金属污染评价和定量溯源解析[J].环境科学,2022,43(12):5698-5709.
作者姓名:马杰  刘萍  刘今朝  郭春会  张秀  王玲灵
作者单位:重庆市生态环境监测中心, 重庆 401147;农村生态与土壤监测技术研究中心, 重庆 401147;重庆市国土整治中心, 重庆 400020;西南大学资源环境学院, 重庆 400715
基金项目:重庆市生态环境局项目(21C00344);重庆市科技局科研机构绩效激励引导专项(cstc2021jxjl2002)
摘    要:以重庆市南川区某煤矸山周边农用地土壤为研究对象,运用内梅罗指数法、地累积指数法和GIS地统计分析土壤重金属污染水平和分布特征,并采用相关性分析、主成分分析(PCA)和绝对因子得分-多元线性回归分析(APCS-MLR),探析研究区土壤重金属来源及其贡献率.结果表明,煤矸山周边旱地土壤中8项重金属含量均显著高于水田(P<0.05),Cd、Hg、As、Pb和Cr含量显著高于园地(P<0.05);园地土壤中Cu、Ni和Zn含量显著高于水田(P<0.05).内梅罗综合污染指数表现为旱地(2.77)>园地(1.04)>水田(0.59),重金属污染程度由大到小表现为:Cd>Cu>Ni>Zn>Hg、As、Cr和Pb.污染累积程度由大到小表现为:Cd>Hg>Cu>Ni>Zn>As>Cr>Pb.污染源解析表明,Cd和Hg存在显著正相关关系(r=0.756,P<0.01),主要受到煤矸山长期堆存等矿业活动影响,贡献率分别为51.6%和52.9%.Cu、Ni和Zn之间存在显著正相关关系(r为0.755~0.955,P<0.01),主要受到施肥等农业活动影响,贡献率分别为72.3%、63.3%和59.2%.As和Pb主要受到土壤母质等自然因素影响,贡献率分别为60.8%和86.9%.Cr主要受到施肥等农业活动和土壤母质等自然因素共同影响,贡献率分别为38.9%和40.9%.应重点加强对Cd的来源管控和污染防治.

关 键 词:煤矸山  土壤  重金属  农用地  APCS-MLR受体模型  来源解析
收稿时间:2022/2/18 0:00:00
修稿时间:2022/4/11 0:00:00

Pollution Evaluation and Quantitative Traceability Analysis of Heavy Metals in Farmland Soils Around the Gangue Heap of a Coal Mine in Chongqing
MA Jie,LIU Ping,LIU Jin-zhao,GUO Chun-hui,ZHANG Xiu,WANG Ling-ling.Pollution Evaluation and Quantitative Traceability Analysis of Heavy Metals in Farmland Soils Around the Gangue Heap of a Coal Mine in Chongqing[J].Chinese Journal of Environmental Science,2022,43(12):5698-5709.
Authors:MA Jie  LIU Ping  LIU Jin-zhao  GUO Chun-hui  ZHANG Xiu  WANG Ling-ling
Institution:Chongqing Ecological and Environmental Monitoring Center, Chongqing 401147, China;Rural Ecology and Soil Monitoring Technology Research Center, Chongqing 401147, China;Chongqing Land Consolidation and Rehabilitation Center, Chongqing 400020, China;College of Resources and Environment, Southwest University, Chongqing 400715, China
Abstract:To analyze the level and distribution characteristics of heavy metal pollution in the soil of farmland surrounding the gangue heap of a coal mine in Nanchuan, Chongqing, the Nemerow pollution index, Muller index, and ArcGIS Geostatistical methods were used. Additionally, to investigate the sources and contribution rate of heavy metals in the soil, correlation analysis, principal component analysis (PCA), and absolute principal component score-multiple linear regression receptor modeling (APCS-MLR) were employed. The results showed that it contained significantly higher amounts of Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn in dry land than that in the paddy field (P<0.05) and higher amounts of Cd, Hg, As, Pb, and Cr than that in the orchard (P<0.05). However, there was only significant amounts of Cu, Ni, and Zn in the orchard than that in the paddy field (P<0.05). The comprehensive Nemerow pollution index was:dry land (2.77)>garden land (1.04)>paddy field (0.59); the degree of heavy metal pollution was:Cd>Cu>Ni>Zn>Hg, As, Cr, and Pb; and the accumulation degree of heavy metals in the soil was:Cd>Hg>Cu>Ni>Zn>As>Cr>Pb. The analysis of pollution sources showed that Cd and Hg had a significant positive correlation (r=0.756, P<0.01), which was mainly affected by mining activities such as long-term accumulation of the gangue heap of the coal mine with a contribution rate of 51.6% and 52.9%, respectively. In addition, there was a significant positive correlation between Cu, Ni, and Zn (r 0.755-0.955, P<0.01), which was mainly affected by agricultural activities such as fertilization with contribution rates of 72.3%, 63.3%, and 59.2%, respectively. Furthermore, the amount of As and Pb was affected by natural factors with contribution rates of 60.8% and 86.9%, respectively, and Cr was affected by agricultural factors and natural factors with contribution rates of 38.9% and 40.9%, respectively. Therefore, it is necessary to strengthen the source control of Cd, as well as pollution prevention.
Keywords:gangue heap  soil  heavy metal  farmland  APCS-MLR receptor model  source apportionment
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