Source Apportionment of Agricultural Soil Heavy Metals Based on PMF Model and Multivariate Statistical Analysis

The safety of human health and agricultural production depends on quality of farmland soil. Multivariate statistical analysis and positive matrix factorization (PMF) have revealed source apportionment of six heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) in a farmland soil of Wenzhou, Zhejiang. The results showed significantly enriched Cd, Pb, Zn, and Cu in this area. The results from Pearson's correlation coefficient and principal component analysis (PCA) methods have identified both natural sources (Cr and Ni) and anthropogenic sources (Cd, Cu, Pb, and Zn). The PMF model in combination with spatial distribution of six heavy metals, have confirmed that Cd and Zn were predominantly from agricultural sources; Cr and Ni were attributed to natural sources; Pb and Zn were originated from mixed sources of transportation and industry. The Cu was derived from atmospheric deposition. The Multivariate statistical method has qualitatively identified pollution sources, and then combined with quantitative calculation of PMF model. The two methods have verified each other, which has improved feasibility of source apportionment results. This study could provide a reference in preventing and controlling soil pollution effectively from source for local authorities.