首页> 外文期刊>Environmental Science & Technology >Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures
【24h】

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures

机译:降低实际水混合物水生效果评估不确定性的分层贝叶斯方法

获取原文
获取原文并翻译 | 示例
           

摘要

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceutical demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.
机译:水生环境中的物种对所遇到的各种化学物质的毒理学敏感性不同。在水生风险评估中,这种种间差异通常通过物种敏感性分布来量化。由于可用于表征这些分布的信息通常有限,因此信息的最佳使用对于减少评估所涉及的不确定性至关重要。在本研究中,我们表明,如果遵循经典方法,其中暴露于环境相关地表水浓度下的化学品混合物中,估计潜在受影响物种物种的可信区间可以非常宽泛被认为是孤立的。作为替代方案,我们提出了一种分级贝叶斯方法,其中结合了除所评估化学品以外的有关化学品毒性的知识。包含13种药物的混合物的案例研究表明,由于减少了对数据贫乏化学品的物种敏感度分布的不确定性,这种分层方法可以对可能受影响的部分进行更实际的估计。

著录项

  • 来源
    《Environmental Science & Technology》 |2015年第17期|10457-10465|共9页
  • 作者单位

    Department of Environmental Science, Institute for Wetland and Water Research, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands;

    Department of Applied Stochastics, Institute for Mathematics, Astrophysics and Particle Physics, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands;

    Department of Environmental Science, Institute for Wetland and Water Research, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands,Department of Ecological Risk Assessment, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands;

    Department of Environmental Science, Institute for Wetland and Water Research, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands,Faculty of Management, Science & Technology, Open Universiteit, Valkenburgerweg 177, 6419 AT Heerlen, The Netherlands;

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

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号