Literature DB >> 35217010

Assessment of heavy metals should be performed before the development of the selenium-rich soil: A case study in China.

Yonglin Liu1, Shuling Liu1, Wei Zhao2, Chuanbo Xia2, Mei Wu1, Qing Wang2, Zhiming Wang2, Yun Jiang2, Andrew V Zuza3, Xinglei Tian4.   

Abstract

The use of selenium (Se)-rich soils in China is an effective method for rural revitalization, but assessment of heavy metals is essential prior to the development of Se-rich soils. This study was focused on the Jiangjin district, a typical Se-rich area located in Sichuan Basin of China, to investigate contamination, influencing factors, and sources of As, Cr, Cu, Cd, Ni, Pb, Sb, and Zn based on 156 topsoil samples. This study analyzed and compared the enrichment factor (EF), Nemerow index (PN), geographical information system (GIS), and positive matrix factorization (PMF). Results demonstrate that the average values of As, Cu, Cd, Sb, and Zn in topsoil were higher than the soil background values of western Chongqing by approximately 1.75, 1.11, 1.27, 1.71, and 2.58 times, respectively, indicating that some heavy metals have been enriched in the soils. The polluted areas of As, Cu, Cd, and Zn in topsoil were mainly distributed in the northern and central Jiangjin district, whereas high-Sb soils were located in the southeast. The Cr, Cu, Cd, Pb, and Sb were concentrated in Se-rich soils, indicating that heavy metals pollution should be carefully considered for the utilization of Se-rich soils. Four potential sources of heavy metals were found in this study area: 1) the parent materials (Cr, Ni, Cu); 2) industrial activities with high coal consumption (As); 3) mechanical and chemical industrial activities (Zn, Sb); and 4) transportation and agricultural activities (Pb, Cd). These observations provide a scientific basis for the development, utilization, and protection of Se-rich soil resources.
Copyright © 2022 Elsevier Inc. All rights reserved.

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Keywords:  Heavy metals; Positive matrix factorization; Selenium-rich soil; Sichuan basin; Spatial analysis

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Year:  2022        PMID: 35217010     DOI: 10.1016/j.envres.2022.112990

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  1 in total

1.  Prediction models for monitoring selenium and its associated heavy-metal accumulation in four kinds of agro-foods in seleniferous area.

Authors:  Linshu Jiao; Liuquan Zhang; Yongzhu Zhang; Ran Wang; Xianjin Liu; Baiyi Lu
Journal:  Front Nutr       Date:  2022-09-23
  1 in total

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