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铅锌尾矿库对周围环境重金属污染风险评价指标的建立及方法

梁雅雅1,易筱筠1,2*,党志1,2,高双全1,王琴1,唐婕1   

  1. 1华南理工大学环境与能源学院, 广州 510006;2工业聚集区污染控制与生态修复教育部重点实验室, 广州 510006)
  • 出版日期:2018-06-10 发布日期:2018-06-10

Methods and indices for risk assessment of heavy metal pollution surrounding Pb-Zn tailing ponds.

LIANG Ya-ya1, YI Xiao-yun1,2*, DANG Zhi1,2, GAO Shuang-quan1, WANG Qin1, TANG Jie1   

  1. (1School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; 2The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, Guangzhou 510006, China).
  • Online:2018-06-10 Published:2018-06-10

摘要: 评价铅锌尾矿库对周围环境的重金属污染风险,是对铅锌尾矿库重金属污染风险分级分类的基础,可为环保部门对铅锌尾矿库有针对性的分类管理提供依据。本文针对当前铅锌尾矿库重金属污染风险评价研究方面存在的不足,探索性地建立了铅锌尾矿库对周围环境的重金属污染风险评价技术方法。该方法在构建指标体系时,主要考虑了大气环境和渗漏水两大指标,同时考虑了各个重金属的毒性,此方法定量计算各个指标,操作性强。通过广东梅州的一个铅锌尾矿库的示范应用,初步验证了该方法的可行性和实用性,为进一步建立铅锌尾矿库对周围环境的重金属污染风险评价的相关技术规范和标准体系奠定了基础,具有较好的实践意义。

关键词: 气候变暖, 蒙古栎, 黄菠萝, 径向生长, 时空变异, 树木年轮

Abstract: Heavy metal risk assessment for the sites surrounding Pb-Zn tailing ponds is the basis for classifying the heavy metal pollution for the Pb-Zn tailing ponds into different levels, which may provide basis for the adaptive management of tailing ponds by environmental protection department. At present, the research in environmental risk assessment of the heavy metal pollution surrounding the Pb-Zn tailing pond sites is not enough. Here, we developed a method for evaluating heavy metal pollution risk of the Pb-Zn tailing ponds. In the construction of the evaluation system, this method mainly takes account of atmospheric environment and leakage water, as well as the toxicity of heavy metals. This method can quantitatively calculate each index and is easy to operate. Furthermore, we tested the feasibility and practicality of the method in a tailing pond site in Meizhou City, Guangdong Province. This study contributes to the establishment and improvement of the criteria and standards in heavy metal risk assessment for the surrounding area of the Pb-Zn tailing ponds.

Key words: tree ring, Quercus mongolica, spatial and temporal variability., climate warming, Phellodendron amurense, radial growth