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广西西江流域农田土壤重金属含量特征及来源解析
引用本文:宋波,张云霞,庞瑞,杨子杰,宾娟,周子阳,陈同斌.广西西江流域农田土壤重金属含量特征及来源解析[J].环境科学,2018,39(9):4317-4326.
作者姓名:宋波  张云霞  庞瑞  杨子杰  宾娟  周子阳  陈同斌
作者单位:桂林理工大学环境科学与工程学院;桂林理工大学岩溶地区水污染控制与用水安全保障协同创新中心;中国科学院地理科学与资源研究所
基金项目:广西自然科学基金项目(2013GXNSFEA053002);广西"八桂学者"建设工程专项;国家自然科学基金项目(41161056,41261082);广西科技重大专项(桂科AA17204047-2)
摘    要:为探明西江流域农田土壤重金属污染分布特征及主要影响因素,采集2 187个农田土壤样品,测试其重金属含量.采用地统计理论与GIS空间插值相结合的方法研究重金属元素的空间结构和分布特征;利用潜在生态风险指数作风险评估;采用相关性分析和主成分分析等多元统计方法解析重金属来源.结果表明,西江流域农田土壤7种重金属元素在土壤中均有一定程度的富集,其中重金属Cd富集情况最为明显,独立样本T检验结果显示,旱地土壤与水田土壤重金属含量存在显著差异(P0.05),水田土壤Cd含量显著高于相应旱地土壤;西江流域农田土壤Cd存在较高的潜在生态风险.相关分析和主成分分析结果显示,土壤中Pb、Zn、As、Cd、Cu的富集是由矿业活动、交通和污水灌溉等人为因素引起的,Ni和Cr则受成土母质等自然因素影响较大.从空间分布上看,流域上游As、Cd、Pb、Zn、Cu高含量区均分布于刁江流域及大环江流域,其中Cd高值分布范围最广,南丹县大厂车河地区高值样点最为密集,说明矿区活动给当地农田土壤造成了一定程度的重金属污染.

关 键 词:西江流域  重金属  污染来源  生态风险  空间分布
收稿时间:2017/12/20 0:00:00
修稿时间:2018/3/12 0:00:00

Analysis of Characteristics and Sources of Heavy Metals in Farmland Soils in the Xijiang River Draining of Guangxi
SONG Bo,ZHANG Yun-xi,PANG Rui,YANG Zi-jie,BIN Juan,ZHOU Zi-yang and CHEN Tong-bin.Analysis of Characteristics and Sources of Heavy Metals in Farmland Soils in the Xijiang River Draining of Guangxi[J].Chinese Journal of Environmental Science,2018,39(9):4317-4326.
Authors:SONG Bo  ZHANG Yun-xi  PANG Rui  YANG Zi-jie  BIN Juan  ZHOU Zi-yang and CHEN Tong-bin
Institution:College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China;Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, Guilin University of Technology, Guilin 541004, China,College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China,College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China,College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China,College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China,College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China and College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Abstract:In order to determine the distribution characteristics of heavy metal pollution in farmland soils and related influencing factors in the Xijiang River Basin, 2187 farmland soil samples were collected and their heavy metal contents were tested. The spatial structure and distribution characteristics of heavy metal elements were studied using a combination of geostatistics theory and GIS spatial interpolation. The potential ecological risk index was employed for risk assessment. Multivariate statistical methods, such as correlation analysis and principal component analysis, were used to analyze heavy metal sources. Results showed that farmland soils in the Basin were enriched with seven kinds of heavy metal to some extent, with Cd accumulation being the most evident. T-test independent samples results showed significant differences in heavy metal content between dry and field paddy soils (P<0.05). Cd content in paddy soils was significantly higher than in corresponding dry land soils. Cd in farmland soils in Xijiang River exhibited higher potential ecological risk. Correlation analysis and principal component analysis showed that enrichment of Pb, Zn, As, Cd, and Cu in soil was due to anthropogenic factors such as mining activities, traffic, and sewage irrigation, while Ni and Cr were influenced by natural factors, such as soil parent material. High-content areas of As, Cd, Pb, Zn, and Cu in the upper reaches of the basin are all distributed in the Diaojiang River basin and the Dahuanjiang River basin. Cd was most widely distributed. The most intensive sampling sites indicated that mining activities have caused some degree of heavy metal pollution in local farmland soils.
Keywords:Xijiang River basin  heavy metal  source analysis  ecological risk  spatial distribution
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