Abstract

The properties and sources of soil heavy metals (Pb, Zn, Cu, Cd, As, Hg, Cr, and Ni) need to be comprehensively analyzed to take effective steps to control and reduce soil pollutants. In this research, 416 soil samples were collected on a large scale in China. Two receptor models (PCA/MLR and PMF) were utilized to identify pollutant sources and quantify the contributions. The means of soil heavy metals (Zn, Cu, As, Hg, Cr, and Ni) were lower than the corresponding screening values and intervention values. Cd was greater than the intervention value, while Pb was between the screening value and the intervention value. Source apportionments suggested that mine sources were the most polluted (64.28%), followed by traffic sources (38.98%), natural sources (11.41-39.58%), industrial sources (9.8-18.65%), and agricultural sources (2.79-14.51%). Compared to the PCA/MLR model, the PMF model had a better effect in evaluating soil heavy metal pollution. It gave corresponding weights according to the data concentration and its uncertainty, which made the result reasonable. The ecological risk assessment indicated that Cd posed a significant risk, while Hg caused a mild risk and the other six heavy metals posed a low risk. The spatial distribution of ecological risk suggested that severe risk points were mainly distributed in the central area, while high-risk points were distributed in the southern region. The SRI method was developed to link pollution sources and their potential ecological risks and indicated better applicability to the PMF model. The study findings could provide guidelines for monitoring the main sources and reducing the pollution of soil heavy metals.

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