湖泊沉积物砷生物有效性评估采样分析技术综述
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X171.5

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国家自然科学基金重点项目(41430751);江苏省普通高校研究生科研创新计划(KYZZ16-0292)


Review of sampling and analysis techniques to assess arsenic bioavailability of lake sediments
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    摘要:

    为了给浅水湖泊砷(As)污染状况的评估和综合治理提供技术支撑,在分析As污染物在湖泊中的赋存形态、各形态之间的转化以及As生物有效性影响因素的基础上,对比分析了传统采样技术和原位采样技术的优劣。结果表明,传统采样技术极易在样品采集和测定过程中对As产生再吸附、再溶解和再分配,无法真实地反映As的污染状况和迁移转化过程,而原位采样技术中Peeper、DET、DGT等可较好地评估湖泊As污染的生物有效性,但这类技术忽视了沉积物和上覆水的交互作用,导致累计的过程中不能对目标元素直接量化,且忽略了微生物的变化对测量的影响,所以测定过程仍需进一步优化;传统的采样技术和新型的原位测定技术各自具有明显的劣势,因此多种采样分析技术的联用可减小As污染浓度误差。

    Abstract:

    In order to provide technical support for the assessment and comprehensive management of the pollution of shallow lakes, the advantages and disadvantages of traditional sampling techniques and in-situ sampling techniques are compared based on the analysis of the presence of As pollutants in lakes, the transformation between forms, and the factors affecting the biological effectiveness of As. The results show that it is easy to reabsorb, dissolve and redistribute arsenic in the process of sample collection and determination for the traditional sampling techniques, which cannot truly reflect arsenic contamination and migration and transformation processes. In in-situ sampling techniques, Peeper, DET, DGT, etc. can better assess the As bioavailability of lake, but such techniques ignore the interaction between sediments and overlying water, resulting in the accumulation process can not directly quantify the target elements. And it ignores the impact of microbial changes on the measurement, so the measurement process still needs to be further optimized. Both traditional sampling techniques and new in-situ measurement techniques have obvious disadvantages. Therefore, the combination of sampling analysis techniques can reduce the error of As pollution concentration.

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姚羽,王沛芳,王超.湖泊沉积物砷生物有效性评估采样分析技术综述[J].水资源保护,2019,35(6):109-114.(YAO Yu, WANG Peifang, WANG Chao. Review of sampling and analysis techniques to assess arsenic bioavailability of lake sediments[J]. Water Resources Protection,2019,35(6):109-114.(in Chinese))

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  • 收稿日期:2019-01-06
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  • 在线发布日期: 2019-11-28
  • 出版日期: 2019-11-20