4.7 Article

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

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 260, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2020.110092

Keywords

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

Funding

  1. State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control of China [2010DS700124-KF1906]
  2. Key Project of Zhejiang Province [2015CO2011, 2017B70011]

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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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