To understand the status of heavy metals in soils of typical industrial and mining towns and quantitatively analyze the potential sources, the contents of seven heavy metals (Cd, As, Pb, Cr, Cu, Ni, and Zn) in 150 surface soils in Xuanhua District, Zhangjiakou City, Hebei Province were collected and examined. The geoaccumulation index and potential ecological risk index methods were used to evaluate the heavy metal pollution status and potential ecological risk. Principal component analysis (PCA) and the positive matrix factorization (PMF) model were used to comprehensively analyze the pollution sources of seven heavy metals, and geostatistics was used to identify the high contribution areas of potential sources. The results revealed that:① the average values of heavy metals in the study area ranged from 0.23-103.34 mg·kg-1, among which the average contents of Cd, Pb, Cu, and Zn were higher than the soil background value of Hebei Province. ② The results of the geoaccumulation and potential ecological risk indices demonstrated that the degree of pollution of the seven heavy metals was in the following order:Cd>Pb>Cu>Zn>Ni>As>Cr, the content of Cd in 16% sites was above a moderate pollution level, and the potential ecological risk of heavy metals in more than 95% sites was at a light risk level. ③ The main sources of accumulation of the seven heavy metals in the study area were combined sources of industry and traffic, natural sources, and agricultural sources, with their contribution rates of 33.1%, 48.7%, and 18.2%, respectively. Among them, Cd, Pb, Cu, and Zn were primarily affected by the combined sources of industry and transportation; Cr, Ni, and As were mainly affected by natural sources, whereas Cd and some As were affected by agricultural sources. The organic combination of PCA, PMF model, and geostatistical methods confirmed the results of each analysis, which increased the reliability of the analytical results of heavy metal sources.
Keywords: heavy metals; positive matrix factorization (PMF); potential ecological risk; source apportionment; spatial distribution.