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Spatiotemporal modeling of soil heavy metals and early warnings from scenarios-based prediction

机译:土壤重金属的时空建模与基于场景的地区预测

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摘要

Prediction of soil heavy metal concentrations based on continuous site specific investigation can provide reference for soil metal contamination prevention and early warning of soil environmental quality. In this study, the spatiotemporal variations of soil heavy metals (Cd, Ni, Zn, Pb and Cu) in Wenling were analyzed with 132 and 169 soil samples gathered in 2011 and 2016. In addition, we adopted a scenario-simulation model to predict future dynamic concentrations of soil heavy metals under optimistic (the pollution inputs are zero under strict environmental policy) and default (the pollution status maintain constant) conditions. Results indicated that the paddy soil was contaminated mainly by Cd and Cu. Spatiotemporal maps revealed distinct patterns in the joint area, where soil Cd, Ni, Zn, Pb and Cu all increased in northwest. Soil heavy metal concentrations as well as the associated ecological risks would decline gradually under optimistic scenario, while sharply increase when no control acts are taken over long term in default condition. The percentages of soil Cd and Cu that exceeding their corresponding risk screening value (RSV) under the default condition would be 1.6 and 1.3 times higher than those under optimistic scenario 10 years later. The probability of high potential ecological risk in default condition would be twice higher than that under optimistic scenario in 2026. Overall, strengthening the control of pollution sources and strict environmental policy are very important for soil heavy metals contamination prevention and control. (C) 2020 Elsevier Ltd. All rights reserved.
机译:基于连续场地特异性研究的土壤重金属浓度预测可为土壤污染防治预防和土壤环境质量预警提供参考。在这项研究中,用2011年和2016年聚集的132和169种土壤样品分析了温岭中土壤重金属(Cd,Ni,Zn,Pb,Pb和Cu)的时空变化。此外,我们采用了一种情况模拟模型来预测未来的土壤重金属在乐观态度(严格环境政策下的污染投入为零)和违约(污染状况保持不变)条件。结果表明,水稻土主要由CD和Cu污染。时空地图在西北部揭示了联合面积中的明显图案,其中土壤Cd,Ni,Zn,Pb和Cu都增加了西北部。土壤重金属浓度以及相关的生态风险将在乐观情景下逐步下降,而在默认条件下没有控制行为无控制行为急剧增加。在违约条件下超过其相应风险筛查价值(RSV)的土壤CD和Cu的百分比将比10年后的乐观情景下的1.6%,1.3倍。默认情况下,高潜在的生态风险概率将比2026年的乐观情景下的两倍。总体而言,加强对污染源的控制和严格的环境政策对土壤重金属污染防治非常重要。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Chemosphere》 |2020年第9期|126908.1-126908.9|共9页
  • 作者单位

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

    Zhejiang Univ Coll Environm & Nat Resource Sci Zhejiang Prov Key Lab Agr Resources & Environm Hangzhou 310058 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Soil heavy metal; Spatiotemporal variation; Source identification; Scenario simulation; Early warning;

    机译:土壤重金属;时尚变异;源识别;情景仿真;预警;

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