Source Apportionment and Spatial Distribution Simulation of Heavy Metals in a Typical Petrochemical Industrial City

Abstract

Identifying the quantitative source and hazardous areas of heavy metals in soils plays a pivotal role in soil pollution research, and can provide a basis for regional soil risk monitoring and environmental management. For this purpose, a total of 175 samples were collected in topsoils from Linzi, a typical petrochemical industrial city in Shandong Province. Positive matrix factorization (PMF) and factor analysis with non-negative constraints (FA-NNC) receptor models were applied to analyze the sources of the heavy metals. Based on the multivariate statistical simulation methods of min/max autocorrelation factors (MAF) and sequential Gaussian simulation (SGS), the distribution of heavy metal and potential pollution areas were determined. As, Co, Cr, and Mn were mainly affected by natural sources, their concentrations were dominated by the parent materials, and the high-value areas were distributed in the south of the study area. Hg was the most serious pollution element among the 10 heavy metals analyzed in Linzi and originated from atmosphere deposition from industrial emissions and coal combustion, and the highest values were distributed in the northeast of the study area. Cd, Cu, Ni, Pb, and Zn were dominated by natural sources and human activities. The hot-spot areas were mainly concentrated in the middle of the study area. The potentially contaminated areas of Cd and Hg were 580.80 km2 and 666.60 km2, about 85.04% and 97.59% of the total area, and should require more attention. The potential pollution area of most elements was small and scattered across the study area, accounting for less than 1%.