To further explore the characteristics of heavy metal pollution and the ecological risk of typical industries in reclaimed soil, based on data from 315 different depth profiles of soil samples collected from 49 plots in Jiading District, Shanghai, the geo-accumulation index and potential ecological risk index were used to evaluate the contents and potential ecological risk of seven heavy metals, namely Cd, Pb, Cu, Zn, Ni, Hg, and As. The APCS-MLR receptor model and PMF positive matrix factorization model were employed to analyze the pollution sources. The results showed that:① except for As, the contents of other heavy metals in the soil of the study area exceeded the Shanghai soil background values to varying degrees. The contents of Cd, Pb, Cu, Zn, Ni, and Hg in the surface soil were 3.54, 2.34, 2.91, 1.20, 3.75, and 4.40 times the background values, respectively. The contents of heavy metals in the soil decreased with the increase in depth, and heavy metals were enriched to a certain extent in the surface soil, indicating that human activities had an impact on the distribution of heavy metals in the soil. ② The APCS-MLR and PMF receptor models identified four main sources of soil heavy metals in the study area. Source 1 (Cu, Zn, and Pb) was a mixture of metal products and automobile manufacturing, source 2 (Ni and Cd) was electroplating enterprises, source 3 (Hg) was mainly from chemical enterprises, and source 4 (As) was natural. The combined use of the two receptor models further improved the accuracy and credibility of source identification. ③ The geo-accumulation index in descending order was Hg(1.54)>Ni(1.32)>Cd(1.21)>Cu(0.96)>Pb(0.64)>Zn(-0.33)>As(-1.02). The potential ecological risk index showed that the comprehensive potential ecological risk index RI value in the study area ranged from 32.50 to 4 910.97, with a mean of 321.40, indicating a strong potential ecological risk. The pollution values of heavy metals Hg, Ni, and Cd in industrial site soil deserve further attention for re-development and utilization purposes.
Keywords: absolute factor analysis-multiple linear regression(APCS-MLR); heavy metals; index of geo-accumulation; positive matrix factorization(PMF); potential ecological risk; soil.