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首页> 外文会议>Annual conference of the International Society of Exposure Science >Blue Skies Bluer? Puzzling implications of a possible supra-linear relationship between PM exposure and mortality
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Blue Skies Bluer? Puzzling implications of a possible supra-linear relationship between PM exposure and mortality

机译：蓝天更蓝吗？ PM暴露与死亡率之间可能存在超线性关系的令人困惑的含义

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Background and Aims: Recent studies raise the possibility that some health endpoints follow supra-linear concentration-response functions (CRFs). Here, we examine implications of supra-linearity for the design of economically efficient policies to reduce health effects associated with PM2.5 exposures. Methods: We compare two classes of recently published CRFs for cardiopulmonary mortality associated with PM-2.5: (1) a conventional log-linear model, and (2) a supra-linear log-log model. Each CRF is used to model the concentration dependence of the marginal health benefit associated with a fixed 1 μg m-3 reduction in ambient PM-2.5. Results: For a log-linear CRF, the marginal health benefit of a 1 μg m-3 reduction in ambient concentrations has weak dependence on the initial level. In contrast, for the supra-linear (log-log) CRF, the marginal health benefit of a 1 μg m-3 improvement is greatest at low concentrations and drops sharply for more polluted conditions. Surprisingly, for a supra-linear CRF, an efficiency-oriented solution might prioritize marginal pollutant improvements in locales with low annual-average concentrations. This unexpected feature of supra-linear CRFs goes against a key assumption in environmental economics that the marginal benefit of pollution control declines with increasing abatement. Conclusions: Several new challenges would arise for science and policy if supra-linear CRFs were demonstrated to exist for PM2.5. To achieve a given level of population health, more stringent controls on ambient PM2.5- levels may be required than previously assumed. Furthermore, individual policies cannot be understood in isolation; reducing emissions at two sources may have a greater benefit than the addition of the benefits of cleaning either source individually. An economically "optimal" pollution abatement strategy might de-emphasize control in the most polluted communities, raising important concerns for environmental justice.
机译：背景与目的：最近的研究提出了一些健康终点遵循超线性浓度反应功能（CRF）的可能性。在这里，我们研究了超线性对设计经济有效的政策以减少与PM2.5暴露相关的健康影响的含义。方法：我们比较了两类最近发布的与PM-2.5相关的心肺死亡率的CRF：（1）传统对数线性模型，和（2）超线性对数对数模型。每个CRF用于模拟与环境PM-2.5固定降低1μgm-3有关的边际健康益处的浓度依赖性。结果：对于对数线性CRF，环境浓度每降低1μgm-3对健康的边际收益对初始水平的依赖性就很小。相反，对于超线性（对数-对数）CRF，在低浓度下改善1μgm-3对健康的边际效益最大，而在污染更严重的情况下，下降幅度则急剧下降。出乎意料的是，对于超线性CRF，以效率为导向的解决方案可能会优先考虑在年平均浓度较低的地区改善边际污染物。超线性CRF的这一出乎意料的特征与环境经济学中的一个关键假设背道而驰，即污染控制的边际收益随着减排的增加而下降。结论：如果证明PM2.5存在超线性CRF，科学和政策将面临一些新的挑战。为了达到给定的人口健康水平，可能需要比以前设想的更严格的PM2.5水平控制措施。此外，不能孤立地理解个别政策。与单独清洁任一污染源相比，减少两个污染源的排放可能会带来更大的收益。一种经济上“最佳”的污染消除策略可能会在污染最严重的社区中不再强调控制，这引起了对环境正义的重要关注。

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