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Multi-scale spatial structure of heavy metals in agricultural soils in Beijing

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Abstract

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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Authors and Affiliations

  1. College of Natural Resources and Environmental Science, China Agricultural University, Beijing, 100193, China

    Huo Xiaoni, Sun Danfeng & Li Baoguo

  2. Beijing Academy of Agriculture and Forestry, Beijing, 100097, China

    Huo Xiaoni, Li Hong & Zhou Liandi

Authors
  1. Huo Xiaoni
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  2. Li Hong
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  3. Sun Danfeng
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  4. Zhou Liandi
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  5. Li Baoguo
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Correspondence to Huo Xiaoni.

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Xiaoni, H., Hong, L., Danfeng, S. et al. Multi-scale spatial structure of heavy metals in agricultural soils in Beijing. Environ Monit Assess 164, 605–616 (2010). https://doi.org/10.1007/s10661-009-0916-7

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