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首页> 外文期刊>Journal of the air & waste management association >Air Pollution And Survival Within The Washington University-epri Veterans Cohort: Risks Based On Modeled Estimates Of Ambient Levels Of Hazardous And Criteria Air Pollutants
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Air Pollution And Survival Within The Washington University-epri Veterans Cohort: Risks Based On Modeled Estimates Of Ambient Levels Of Hazardous And Criteria Air Pollutants

机译：华盛顿大学埃普雷退伍军人队列中的空气污染和生存：基于危害性和标准空气污染物的环境水平建模估算的风险

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For this paper, we considered relationships between mortality, vehicular traffic density, and ambient levels of 12 hazardous air pollutants, elemental carbon (EC), oxides of nitrogen (NO_x), sulfur dioxide (SO_2) and sulfate (SO_4~(2-)) These pollutant species were selected as markers for specific types of emission sources, including vehicular traffic, coal combustion, smelters, and metal-working industries. Pollutant exposures were estimated using emissions inventories and atmospheric dispersion models. We analyzed associations between county ambient levels of these pollutants and survival patterns among approximately 70,000 U.S. male veterans by mortality period (1976-2001 and subsets), type of exposure model, and traffic density level. We found significant associations between all-cause mortality and traffic-related air quality indicators and with traffic density per se, with stronger associations for benzene, formaldehyde, diesel particulate, NO_X, and EC. The maximum effect on mortality for all cohort subjects during the 26-yr follow-up period is approximately 10%, but most of the pollution-related deaths in this cohort occurred in the higher-traffic counties, where excess risks approach 20%. However, mortality associations with diesel particulates are similar in high- andrnlow-traffic counties. Sensitivity analyses show risks decreasing slightly over time and minor differences between linear and logarithmic exposure models. Two-pollutant models show stronger risks associated with specific traffic-related pollutants than with traffic density per se, although traffic density retains statistical significance in most cases. We conclude that tailpipe emissions of both gases and particles are among the most significant and robust predictors of mortality in this cohort and that most of those associations have weakened over time. However, we have not evaluated possible contributions from road dust or traffic noise. Stratification by traffic density level suggests the presence of response thresholds, especially for gaseous pollutants. Because of their wider distributions of estimated exposures, risk estimates based on emissions and atmospheric dispersion models tend to be more precise than those based on local ambient measurements.
机译：在本文中，我们考虑了死亡率，车辆交通密度与12种有害空气污染物，元素碳（EC），氮氧化物（NO_x），二氧化硫（SO_2）和硫酸盐（SO_4〜（2-） ）选择了这些污染物种类作为特定类型排放源的标记，包括车辆交通，煤炭燃烧，冶炼厂和金属加工行业。使用排放清单和大气扩散模型估算污染物暴露量。我们按死亡率（1976-2001年及其子集），接触模型的类型和交通密度水平分析了郡县这些污染物的环境水平与大约70,000名美国退伍军人的生存模式之间的关联。我们发现，全因死亡率与交通相关的空气质量指标之间以及与交通密度本身之间存在显着关联，而苯，甲醛，柴油颗粒，NO_X和EC的关联则更强。在26年的随访期内，所有队列对象对死亡率的最大影响约为10％，但该队列中大多数与污染有关的死亡发生在交通繁忙的县，那里的过度风险接近20％。然而，在高流量和低流量的县，死亡率与柴油机颗粒的关联相似。敏感性分析显示，风险会随着时间的推移而略有降低，线性和对数暴露模型之间的差异也很小。尽管在大多数情况下交通密度仍然具有统计学意义，但两种污染物模型显示与交通相关的特定污染物相关的风险要大于交通密度本身。我们得出的结论是，在该队列中，气体和颗粒物的尾气排放都是最重要和最可靠的死亡率预测指标之一，并且随着时间的推移，大多数关联已减弱。但是，我们尚未评估道路尘埃或交通噪音可能造成的影响。按交通密度水平进行分层表明存在响应阈值，尤其是对于气态污染物。由于估计暴露的分布范围更广，因此基于排放和大气扩散模型的风险估计往往比基于局部环境测量的风险估计更为精确。

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