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Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation

机译:通行调整后的不确定性量化的机载微粒短期健康影响评估通过蒙特卡洛模拟

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摘要

Background: Exposure to air pollution is associated with a short-term increase in mortality, and this field has begun to focus on health impact assessment.Objectives: Our aim was to estimate the impact of PM10 on mortality within 2 days from the exposure in the Italian region of Lombardy for the year 2007, at the municipality level, examining exposure entailed by daily intermunicipality commuting and accounting for uncertainty propagation.Methods: We combined data from different sources to derive probabilistic distributions for all input quantities used to calculate attributable deaths (mortality rates, PM10 concentrations, estimated PM10 effects, and commuting flows) and applied a Monte Carlo procedure to propagate uncertainty and sample the distribution of attributable deaths for each municipality.Results: We estimated that annual average PM10 concentrations above the World Health Organization-recommended threshold of 20 μg/m3 were responsible for 865 short-term deaths (80% credibility interval: 475, 1,401), 26% of which were attributable to PM10 above the European Union limit of 40 μg/m3. Reducing annual average PM10 concentrations > 20 μg/m3 by 20% would have reduced the number of attributable deaths by 36%. The largest estimated impacts were along the basin of the Po River and in the largest cities. Commuting contributed to the spatial distribution of the estimated impact.Conclusions: Our estimates, which incorporated uncertainty quantification, indicate that the short-term impact of PM10 on mortality in Lombardy in 2007 was notable, and that reduction in air pollution would have had a substantial beneficial effect on population health. Using commuting data helped to identify critical areas for prioritizing intervention.Citation: Baccini M, Grisotto L, Catelan D, Consonni D, Bertazzi PA, Biggeri A. 2015. Commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via Monte Carlo simulation. Environ Health Perspect 123:27–33; 
机译:背景:暴露于空气污染与死亡率的短期升高相关,并且该领域已开始侧重于健康影响评估。目的:我们的目的是评估从暴露于空气中的两天内PM10对死亡率的影响。方法:我们将来自不同来源的数据合并,得出用于计算可归因死亡人数(死亡率)的所有输入量的概率分布,以市政当局的水平评估了2007年意大利伦巴第地区的暴露程度。率,PM10浓度,估计的PM10效果和通勤流量),并应用蒙特卡罗程序传播不确定性并抽样每个城市的可归因死亡人数。结果:我们估计,每年的平均PM10浓度高于世界卫生组织建议的阈值20μg/ m 3 导致865例短期死亡(80可信区间百分比:475、1,401),其中26%归因于超出欧盟限值40μg/ m 3 的PM10。将PM10的年平均浓度> 20μg/ m 3 降低20%,可将应归因的死亡人数减少36%。估计影响最大的地区是波河沿岸地区和最大的城市。结论:我们的估计包括不确定性量化,表明2007年PM10对伦巴第的死亡率具有短期影响,而减少空气污染本来可以对人口健康的有益影响。使用通勤数据有助于确定需要优先干预的关键区域。引文:Baccini M,Grisotto L,Catelan D,Consonni D,Bertazzi PA,Biggeri A. 2015年。通勤调整后的不确定性量化空气传播微粒的短期健康影响评估。通过蒙特卡洛模拟。环境健康透视123:27–33;

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