Earth Science Frontiers ›› 2023, Vol. 30 ›› Issue (4): 470-484.DOI: 10.13745/j.esf.sf.2023.2.46

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Spatial distribution, sources and health risks of heavy metals in soil in Qingcheng District, Qingyuan City: Comparison of PCA and PMF model results

NING Wenjing1(), XIE Xianming2, YAN Liping1,*()   

  1. 1. Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University,Wuhan 430100, China
    2. Guangdong Hydrogeology Battalion, Guangzhou 510510, China
  • Received:2022-07-12 Revised:2023-02-07 Online:2023-07-25 Published:2023-07-07

Abstract:

In this study we collected 122 soil samples from a typical, rapidly transforming industrial urban area in southeastern China to evaluate pollution characteristics of 9 heavy metals (As, Co, Cr, Cu, Hg, Ni, Pb, Ti, and Zn) in soil using enrichment factor (EF), geological accumulation index (Igeo), Spearman correlation analysis, potential ecological risk comprehensive index (RI), and human health risk model (HHR); combined with principal component analysis (PCA), positive matrix factorization (PMF) model and geostatistical analysis, the source of heavy metals was investigated. The results showed that As, Cu, Hg, Pb, and Zn were obviously enriched in soil, but the study area as a whole is clean from heavy metal pollution. Hierarchical clustering and grouping results of heavy metals by PCA and PMF models identified 2 and 3 source areas respectively, which helped to improve the accuracy of source analysis. According to ecological risk assessment the study area as a whole is at slight ecological risk, and Hg poses the highest ecological risk among all elements. By human health risk assessment neither adults nor children in the study area are at health risks from heavy metal pollution, including non-carcinogenic and carcinogenic risks, but we found that heavy metal pollution poses greater health risks to children and should be taken seriously.

Key words: soil heavy metals, source analysis, principal component analysis (PCA), positive matrix factorization model (PMF), health assessment

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