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Integrated Uncertainty Analysis for Ambient Pollutant Health Risk Assessment: A Case Study of Ozone Mortality Risk

机译：环境污染物健康风险评估的综合不确定性分析：以臭氧死亡率风险为例

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摘要

The U. S. Environmental Protection Agency (EPA) uses health risk assessment to help inform its decisions in setting national ambient air quality standards (NAAQS). EPA's standard approach is to make epidemiologically-based risk estimates based on a single statistical model selected from the scientific literature, called the "core" model. The uncertainty presented for "core" risk estimates reflects only the statistical uncertainty associated with that one model's concentration-response function parameter estimate(s). However, epidemiologically-based risk estimates are also subject to "model uncertainty," which is a lack of knowledge about which of many plausible model specifications and data sets best reflects the true relationship between health and ambient pollutant concentrations. In 2002, a National Academies of Sciences (NAS) committee recommended that model uncertainty be integrated into EPA's standard risk analysis approach. This article discusses how model uncertainty can be taken into account with an integrated uncertainty analysis (IUA) of health risk estimates. It provides an illustrative numerical example based on risk of premature death from respiratory mortality due to long-term exposures to ambient ozone, which is a health risk considered in the 2015 ozone NAAQS decision. This example demonstrates that use of IUA to quantitatively incorporate key model uncertainties into risk estimates produces a substantially altered understanding of the potential public health gain of a NAAQS policy decision, and that IUA can also produce more helpful insights to guide that decision, such as evidence of decreasing incremental health gains from progressive tightening of a NAAQS.
机译：美国环境保护署（EPA）使用健康风险评估来帮助其制定国家环境空气质量标准（NAAQS）的决策。 EPA的标准方法是基于从科学文献中选择的称为“核心”模型的单一统计模型，进行基于流行病学的风险估计。为“核心”风险估计提供的不确定性仅反映与该模型的浓度响应函数参数估计相关的统计不确定性。但是，基于流行病学的风险估计也受到“模型不确定性”的影响，这缺乏对许多合理的模型规范和数据集中哪一项最能反映健康与环境污染物浓度之间真实关系的了解。 2002年，美国国家科学院（NAS）委员会建议将模型不确定性纳入EPA的标准风险分析方法中。本文讨论了如何通过健康风险评估的综合不确定性分析（IUA）考虑模型不确定性。它提供了一个说明性的数值示例，该数据示例基于长期暴露于环境臭氧中而导致呼吸系统死亡的过早死亡风险，这是2015年臭氧NAAQS决定中考虑的健康风险。该示例表明，使用IUA将关键模型不确定性定量地纳入风险估计中，会大大改变对NAAQS政策决策的潜在公共卫生收益的理解，并且IUA还可以提供更多有用的见识来指导该决策，例如证据逐步收紧NAAQS会减少增量健康收益。

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