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模拟单个机场排放造成的空气污染相关健康损害的变异性。

Modeling variability in air pollution-related health damages from individual airport emissions.

作者信息

Penn Stefani L, Boone Scott T, Harvey Brian C, Heiger-Bernays Wendy, Tripodis Yorghos, Arunachalam Sarav, Levy Jonathan I

机构信息

Boston University School of Public Health, Department of Environmental Health, 715 Albany St 4W Boston, MA 02118, United States.

University of North Carolina at Chapel Hill, UNC Institute for the Environment, 100 Europa Dr., Chapel Hill, NC 27517, United States.

出版信息

Environ Res. 2017 Jul;156:791-800. doi: 10.1016/j.envres.2017.04.031. Epub 2017 May 11.

DOI:10.1016/j.envres.2017.04.031
PMID:28501677
Abstract

In this study, we modeled concentrations of fine particulate matter (PM) and ozone (O) attributable to precursor emissions from individual airports in the United States, developing airport-specific health damage functions (deaths per 1000t of precursor emissions) and physically-interpretable regression models to explain variability in these functions. We applied the Community Multiscale Air Quality model using the Decoupled Direct Method to isolate PM- or O-related contributions from precursor pollutants emitted by 66 individual airports. We linked airport- and pollutant-specific concentrations with population data and literature-based concentration-response functions to create health damage functions. Deaths per 1000t of primary PM emissions ranged from 3 to 160 across airports, with variability explained by population patterns within 500km of the airport. Deaths per 1000t of precursors for secondary PM varied across airports from 0.1 to 2.7 for NOx, 0.06 to 2.9 for SO, and 0.06 to 11 for VOCs, with variability explained by population patterns and ambient concentrations influencing particle formation. Deaths per 1000t of O precursors ranged from -0.004 to 1.0 for NOx and 0.03 to 1.5 for VOCs, with strong seasonality and influence of ambient concentrations. Our findings reinforce the importance of location- and source-specific health damage functions in design of health-maximizing emissions control policies.

摘要

在本研究中,我们对美国各机场前体排放所导致的细颗粒物(PM)和臭氧(O)浓度进行了建模,开发了特定机场的健康损害函数(每1000吨前体排放导致的死亡人数)以及可进行物理解释的回归模型,以解释这些函数的变异性。我们使用解耦直接法应用社区多尺度空气质量模型,以分离66个单个机场排放的前体污染物中与PM或O相关的贡献。我们将特定机场和污染物的浓度与人口数据以及基于文献的浓度-反应函数相联系,以创建健康损害函数。各机场每1000吨一次PM排放导致的死亡人数在3至160之间,其变异性可由机场500公里范围内的人口模式来解释。各机场二次PM前体每1000吨的死亡人数,对于氮氧化物(NOx)在0.1至2.7之间,对于硫氧化物(SO)在0.06至2.9之间,对于挥发性有机化合物(VOCs)在0.06至11之间,其变异性可由影响颗粒物形成的人口模式和环境浓度来解释。每1000吨O前体导致的死亡人数,对于NOx在-0.004至1.0之间,对于VOCs在0.03至1.5之间,具有很强的季节性且受环境浓度影响。我们的研究结果强化了特定地点和来源的健康损害函数在设计最大化健康的排放控制政策中的重要性。

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