Evaluation of soil pollution sources using multivariate analysis combined with geostatistical methods in Zanjan Basin, Iran

Abstract

The increase of heavy metals concentration in soils is potentially threatening the environment and human health. In this paper, multivariate analysis methods such as Positive Matrix Factorization (PMF), Principal Component Analysis (PCA) and Cluster Analysis (CA) combined with geostatistical method were employed to identify the potential sources of soil pollution. A collection of 103 samples were obtained from surface soils of different types of lithology and landuse in Zanjan Basin, Iran. The concentration of As, Bi, Cd, Co, Cr, Cu, Pb, Fe, Mo, Ni, Zn, Se and Hg beside of physical and chemical properties were measured. The results showed a strong effect of anthropogenic sources on the enrichment of heavy metals especially, Zn, Pb, Cd, As and Cu in soils. From the results of PMF and PCA, the four-factor model showed the optimized solution for this study. One of the factors is related to the background concentration, another one is associated with agricultural activities and the other two are associated with industrial activities and industrial waste. The PMF method in comparison with the other common methods in multivariate analysis presents physically acceptable and more reasonable results because of non-negative condition for factors and weighting of the variables.