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Health effects of PM_(2.5) emissions from on-road vehicles during weekdays and weekends in Beijing, China

机译:在北京,工作日和周末,公路车辆PM_(2.5)排放物对健康的影响

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Mobile source emissions have significantly contributed to fine particulate matter (PM2.5) pollution in urban atmospheric environments. Few studies have explored on-road vehicular PM2.5 emissions and the health effects attributed to these emissions under different traffic conditions. Based on driving data obtained from 20000 taxi receipts, a motor vehicle emission simulator (MOVES) model was used to estimate the PM2.5 emission levels of motor vehicles in the urban area within the Sixth Ring Road of Beijing (SRRB) on weekdays and weekends, respectively. Two different PM2.5 exposure scenarios were further simulated using an atmospheric dispersion model. Subsequently, the health effects attributable to traffic-related PM2.5 exposure were quantified by using exposure-response function to calculate the population acute morbidity and premature mortality during different time periods. We found that PM2.5 emission levels of motor vehicles on normal weekdays were overall higher than those on weekends. The median vehicular PM2.5 dispersion concentration in the study area was 2.68 mu g/m(3) on weekdays and 1.82 mu g/m(3) on weekends. Annually, there were 4435 premature deaths attributed to vehicle emissions (95% confidence interval (CI): 3655, 4904) under weekday exposure conditions, and this number sharply decreased to 3462 (95% CI: 3052, 4011) on weekends. Considering the hourly measurements, road traffic emissions have the greatest impact on public health during morning rush hour (8:00 a.m.). Total PM2.5 emissions were closely associated with road traffic conditions and largely determined the magnitude of the health impacts caused by traffic-related PM2.5 exposure. These findings provide information to aid in formulating reasonable public health policies to address vehicular PM2.5 emission-induced health implications.
机译:在城市大气环境中,移动源排放显着导致了细颗粒物(PM2.5)污染。很少有研究探索道路车辆PM2.5排放以及在不同交通状况下归因于这些排放的健康影响。根据从20000张出租车收据获得的驾驶数据,使用机动车排放模拟器(MOVES)模型估算北京六环(SRRB)市区在工作日和周末的PM2.5排放水平, 分别。使用大气弥散模型进一步模拟了两种不同的PM2.5暴露情景。随后,通过使用暴露-响应函数来计算在不同时间段内的人群急性发病率和过早死亡,量化了与交通相关的PM2.5暴露所产生的健康影响。我们发现,正常工作日机动车的PM2.5排放水平总体上高于周末。在研究区域中,车辆中PM2.5的平均分散浓度在工作日为2.68μg / m(3),在周末为1.82μg / m(3)。在工作日暴露条件下,每年有4435例归因于车辆排放的过早死亡(95%置信区间(CI):3655,4904),而在周末,这一数字急剧下降至3462(95%CI:3052,4011)。考虑到每小时的测量值,道路交通排放在早上高峰时间(上午8:00)对公共卫生的影响最大。 PM2.5的总排放量与道路交通状况密切相关,并在很大程度上决定了与交通相关的PM2.5暴露对健康的影响程度。这些发现提供了信息,有助于制定合理的公共卫生政策,以解决车辆PM2.5排放引起的健康问题。

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