Literature DB >> 29164465

Assessment of pollutions and identification of sources of heavy metals in sediments from west coast of Shenzhen, China.

Fengwen Huang1, Yang Xu1,2, Zhenhao Tan1, Zhibing Wu1, Hong Xu3, Liangliang Shen1, Xu Xu1, Qingguo Han1, Hai Guo4, Zhangli Hu5.   

Abstract

The sediment samples were collected from eight sites located in the Pearl River Estuary and the Shenzhen Bay of the west coast of Shenzhen. The distributions of the seven elements Zn, Cr, Hg, Cu, Cd, Pb and As have been analyzed, and their pollution degrees, corresponding potential ecological risks and source identifications have been studied using geo-accumulation index, potential ecological risk index and integrated multivariate statistical methods, respectively. Based on the calculated geo-accumulation indices, the contamination levels of all elements in the Pearl River Estuary are similar to those in the Shenzhen Bay, reflecting that these elements in the study areas have similar sources because of the adequate seawater exchange. The calculated potential ecological risk indices suggest that Cd and Hg are at considerable and moderate risk, respectively. Multivariate statistical analyses further reveal that Zn, Hg, Cd and Pb originated from industrial wastewater, while Cr and Cu are mainly from both industrial wastewater and agricultural sources, and As is mainly from natural source. These research results provide baseline information for both the coastal environment management and the worldwide heavy metal distribution and assessment.

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Keywords:  Heavy metal; Pollution; Sediment; Source identification; Statistical analysis

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Year:  2017        PMID: 29164465     DOI: 10.1007/s11356-017-0362-y

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  1 in total

1.  Spatial distribution and source identification for heavy metals in surface sediments of East Dongting Lake, China.

Authors:  Yi Yuan; Baolin Liu; Hao Liu
Journal:  Sci Rep       Date:  2022-05-13       Impact factor: 4.996

  1 in total

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