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Metals source apportionment in farmland soil and the prediction of metal transfer in the soil-rice-human chain

文献类型： 外文期刊

作者： Deng, Meihua 1 ; Zhu, Youwei 2 ; Shao, Kan 3 ; Zhang, Qi 1 ; Ye, Guohua 4 ; Shen, Jing 4 ;

作者机构： 1.Zhejiang Acad Agr Sci, Inst Qual & Stand Agroprod, State Key Lab Breeding Base Zhejiang Sustainable, Hangzhou 310021, Zhejiang, Peoples R China

2.Zhejiang Agr & Rural Bur, Hangzhou 310000, Peoples R China

3.Indiana Univ, Dept Environm & Occupat Hlth, Sch Publ Hlth, Bloomington, IN 47405 USA

4.Shaoxing Agr & Rural Bur, Shaoxing 312000, Peoples R China

关键词： Heavy metals; Source identification; Modeling; Metal transfer; Soil-rice-human chain

期刊名称：JOURNAL OF ENVIRONMENTAL MANAGEMENT （ 影响因子：6.789； 五年影响因子：6.914 ）

ISSN： 0301-4797

年卷期： 2020 年 260 卷

页码：

收录情况： SCI

摘要： China is facing serious heavy metal pollution in farmland soil, which is a major pressing concern for food safety and human health. This research delivers an integrated methodology for pollution source apportionment and a soil-rice-human model to predict heavy metal transfer in the farmland soil, rice grain and human blood chain. The source identification integrated positive matrix factorization (PMF), cluster analysis (CA) and the life cycle assessment (LCA) survey of agricultural and industrial production and consumption. Based on the case analysis of Shaoxing, this method showed very good performance through the illustration of the source contributions by PMF and LCA at county level and the identification of the pollution sources using CA and LCA at field scale. According to the overall evaluation, the integrated method was superior for the farmland metals pollution source identification comparing to existing source apportionment methods. To predict metal transformation in soil-rice-human chain, a set of models of metals (As, Pb, Cd, Hg, Cr) accumulation ability in rice grain and human blood has been established by literature review and monitoring data. The models showed adequate predictability for the metal content of rice grains at both the field and regional scale, and plausible simulation of the metal concentration in human blood throughout the whole study region. Therefore, this study provides valuable tools for farmland soil heavy metal pollution source identification and for the prediction of heavy metal transformation in soil-rice-human chain; and it can highlight the need to take mitigating action to reduce farmland metal pollution risks in specific regions.

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