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作 者:张长波[1] 李志博[1] 姚春霞[1] 尹雪斌[1] 吴龙华[1] 宋静[1] 滕应[1] 骆永明[1]
机构地区:[1]中国科学院南京土壤研究所土壤与环境生物修复研究中心
出 处:《土壤》2006年第5期525-533,共9页Soils
基 金:国家自然科学基金重点项目(40432005);国家重点基础研究发展规划项目(2002CB410810);中国科学院知识创新项目(KZCX3-SW-429;CXTD-Z2005-4)共同资助。
摘 要:在面积约10.9km2的重金属污染场地以网格法采集了174个表层土壤样品,测定了7种重金属含量。采用地统计学软件GS+和地理信息系统相结合的方法,研究了这些重金属含量的空间变异性。通过Kriging内插法对未测点重金属含量进行最优估计,并对这些重金属的来源进行了初步识别。结果发现,在研究区内7种重金属具有相似的空间分布特征,污染场地特殊的污染源分布状况、污染程度和地理条件导致点状污染源增大了重金属的空间结构性,呈现出与非典型污染区不同的特征。冶炼厂高炉粉尘排放对重金属的贡献明显高于母质等内在因素,是研究区重金属的主要来源。A geostatistics method combined with Geographic Information System was applied to analyze the spatial variability of soil heavy metals and to perform source identification. One hundred and seventy four surface soil samples were collected from a contaminated site with an area of 10.9 km^2 and analyzed for concentration of seven kind of Cu, Zn, Pb, Cd, As, Se and Hg. The results of semivariance analysis showed that they have similar spatial distribution characteristics, and concentrations of the metals were correlated in a given spatial range. Due to the special characteristics of the area such as distribution of the point pollution sources, the spatial autocorrelations of the metals increased, which was different from that of other unpolluted or slightly polluted areas. It was believed that compared with parent materials the copper smelters were the most important sources for soil heavy metals in the area.
关 键 词:重金属 地统计学 半方差函数 空间变异 污染源识别 土壤
分 类 号:X53[环境科学与工程—环境工程]
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