Identifying the sources of pollutants and analyzing the nested structure of heavy metals is vital for the prevention and control of soil pollution. However, there is a lack of research on comparison the main sources and the nested structure at different scales. In this study, two spatial extent scales were taken as the research objects, the results showed that, (1) the point exceeding standard rate of As, Cr, Ni, and Pb is higher at the entire city scale; (2) As and Pb, while Cr, Ni, and Zn, have weaker spatial variability at the entire scale and surrounding the pollution sources, respectively; (3) the contribution of the larger structure of Cr and Ni, while Cr, Ni, and Zn, at the entire scale and surrounding the pollution sources, respectively, is bigger to the total variability. The representation of semivariogram is better when the general spatial variability is weaker and the contribution of the smaller structure is lower; (4) various factors with different influencing distance could lead to nested structure even at a small extent spatial scale. The results provide a basis for the determination of remediation and prevention objectives at different spatial scales.
Keywords: Nested semivariogram; Positive matrix factorization; Quantitative analysis; Random forest; Soil pollution.
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