稳健变异函数在土壤污染物来源识别中的应用：以某重金属污染场地为例

空间特异值可以提供污染源的位置信息.以Genton稳健估计量为基础的变异函数为研究工具,对某重金属冶炼场地土壤中Cu、Zn、Pb、Cd、As、Se和Hg含量进行了空间特异值分析,并根据空间特异值的地理位置及土地利用方式等信息指示污染源.结果表明,7种元素变异函数曲线的理论模型符合球状模型,7种元素都具有较小的块金方差,Cu、Zn和Pb只为0.000.与Matheron估计量相比,该研究得到的变异函数具有更小的块金效应,说明Genton估计量能够消除或减弱特异值对变异函数的影响.7种元素的空间特异值多集中在个别小范围内,以簇状形式存在,与该区域冶炼高炉及尾渣堆放处的位置具有很好的相关性,说明冶炼行为及其相关过程是该区重金属的重要来源.

Application of robust estimator in source identification of soil pollutants: a case study at a heavy metal contaminated site

Spatial outliers can give us useful information on locations of pollution sources. A Genton's estimator based variogram was applied to analyse the concentration of Cu, Zn, Pb, Cd, As, Se and Hg in soils at a contaminated site. Spatial outliers were identified to imply the location of the pollution sources of heavy metals. The results showed that the semivariograms of 7 elements were best described by spherical model, and the nugget variances were very small, especially for Cu, Zn and Pb, which were 0.000. Compared with Matheron's estimator, Genton's estimator can damp the effect of outliers, and so get a smaller nugget effect. The spatial outliers existed in a cluster pattern, whose locations coincided with those of copper smelters in the area. This indicated that the copper smelters were the important sources of soil heavy metals.