Expert judgment assessment of the mortality impact of changes in ambient fine particulate matter in the US
Expert judgment assessment of the mortality impact of changes in ambient fine particulate matter in the US
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DOI：
10.1021/es0713882
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发表时间：
2008-04-01
影响因子：
11.4
通讯作者：
Kinney, Patrick L.
中科院分区：
文献类型：
--
作者：
Roman, Henry A. .;Walker, Katherine D.;Kinney, Patrick L.
本文在分析了现有文献的基础上，我们提出了一项多年专家判断研究的结果，该研究全面描述了与颗粒物减少相关的死亡率降低估计的不确定性。对不确定性的适当描述至关重要，因为与死亡相关的效益占环境保护局（EPA）报告的货币化效益的90%。对拟议的空气法规进行分析。许多流行病学和毒理学研究评估了PM2.5与死亡率的关系，并调查了可能导致浓度-响应（C-R）函数不确定性的问题，例如暴露错误分类和其他污染物暴露的潜在混淆。EPA目前的不确定性分析方法主要依赖于已发表研究中的标准误差。然而，没有一项研究能够捕获量化C-R关系中出现的全套问题。因此，环境保护局应用了最先进的专家判断启发技术来开发概率不确定性分布，以反映C-R关系中更广泛的不确定性。这些分布来自12位世界领先的专家，表明美国长期PM2.5暴露减少的死亡率降低的潜在更大的中心估计值，以及比目前EPA分析更广泛的不确定性分布。
In this paper, we present findings from a multiyear expert judgment study that comprehensively characterizes uncertainty in estimates of mortality reductions associated with decreases in tine particulate matter (PM2.5) in the U.S. Appropriate characterization of uncertainty is critical because mortality-related benefits represent up to 90% of the monetized benefits reported in the Environmental Protection Agency's (EPA's) analyses of proposed air regulations. Numerous epidemiological and toxicological studies have evaluated the PM2.5-mortality association and investigated issues that may contribute to uncertainty in the concentration-response (C-R) function, such as exposure misclassification and potential confounding from other pollutant exposures. EPA's current uncertainty analysis methods rely largely on standard errors in published studies. However, no one study tan capture the full suite of issues that arise in quantifying the C-R relationship. Therefore, EPA has applied state-of-the-art expert judgment elicitation techniques to develop probabilistic uncertainty distributions that reflect the broader array of uncertainties in the C-R relationship. These distributions, elicited from 12 of the world's leading experts on this issue, suggest both potentially larger central estimates of mortality reductions for decreases in long-term PM2.5 exposure in the U.S. and a wider distribution of uncertainty than currently employed in EPA analyses.