文献类型： 外文期刊

第一作者： Xiaoni, Huo

作者： Xiaoni, Huo;Danfeng, Sun;Baoguo, Li;Xiaoni, Huo;Hong, Li;Liandi, Zhou

作者机构：

关键词： Multi-scale; Spatial structure; Heavy metals; Beijing; Agricultural soils

期刊名称：ENVIRONMENTAL MONITORING AND ASSESSMENT （ 影响因子：2.513； 五年影响因子：2.871 ）

ISSN： 0167-6369

年卷期： 2010 年 164 卷 1-4 期

页码：

收录情况： SCI

摘要： To effectively investigate the spatial variability of heavy metals in soil, produce a higher quality spatial distribution map, and identify the potential pollution sources of heavy metals, geostatistics was employed to evaluate the effect of scale on spatial variability of heavy metals in Beijing agricultural soils. The results revealed that spatial variability of Cr, Ni, Zn, and Hg was dependent on scale. Validation of the optimality of theoretical semivariance and comparative analysis of the estimation accuracy demonstrated that the multi-scale nested model can reveal the spatial structure of heavy metals effectively and improve the estimation accuracy better than the single-scale method, thereby enabling production a higher quality spatial interpolation map. Thus, the multi-scale kriging nested model is a useful tool for revealing spatial variability of heavy metals in soils, while the spatial distribution maps allow the identification of hot spots with high concentrations of heavy metals.

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