Source apportionment and spatial distribution of potentially toxic elements in soils: A new exploration on receptor and geostatistical models.

Potentially toxic element (PTE) pollution is considered as the main soil environmental problem in the world. Source apportionment and spatial pattern of soil PTEs are essential for soil management. US-EPA positive matrix factorization (EPAPMF) and sequential Gaussian simulation (SGS) are general modeling tools for source apportionment and spatial distribution, respectively. Factor analysis with nonnegative constraints (FA-NNC) and stochastic partial derivative equations (SPDE) provided potential tools for this issue. We compared the performance of FA-NNC with PMF and the performance of SPDE with SGS, based on a dataset containing 9 PTEs in 285 topsoil samples. Three factors were determined by the two receptor models, and the source contributions were similar, suggesting that FA-NNC can validly identify quantitative sources of soil PTEs. The average source contributions were calculated based on the PMF and FA-NNC. Natural sources dominated the contents of As, Co, Cr, Cu, Ni, and Zn and affected 56.0%, 38.7%, and 84.8% of the Cd, Hg, and Pb concentrations, respectively. A total of 59.8% of Hg and 12.0% of Pb were associated with atmospheric deposition from coal combustion, industrial and traffic emissions, respectively. Agricultural and industrial activities contributed 37.2% of Cd concentration. SPDE proved to be an effective geostatistical technique to simulate the spatial patterns of soil PTEs with higher prediction accuracy than SGS. Co, Cr, Cu, and Ni had similar spatial patterns with hotspots randomly distributed across the study area. The common hotspots of As, Cd, Hg, Pb, and Zn in central parts inherited their high geochemical background in mudstone, while intensive human inputs in these areas also contributed to the accumulation of Cd, Hg, and Pb.