Air pollution and health risks due to vehicle traffic.
Air pollution and health risks due to vehicle traffic.
复制标题
DOI：
10.1016/j.scitotenv.2013.01.074
复制
发表时间：
2013-04-15
期刊：
影响因子：
--
通讯作者：
Batterman S
中科院分区：
文献类型：
--
作者：
Zhang K;Batterman S
交通拥堵增加了车辆排放，降低了环境空气质量，最近的研究表明，驾驶员、通勤者和居住在主要道路附近的个人的发病率和死亡率过高。目前，我们对道路挤塞所造成的空气污染影响的了解非常有限。这项研究展示了一种方法来描述交通风险的道路上和附近的人口。模拟建模被用来估计上和近的道路NO2浓度和健康风险的高速公路和动脉的情况下，可归因于不同的交通量在高峰时段的交通。建模使用了两个不同模型的排放因子（综合模态排放模型和机动车排放因子模型版本6.2）、经验交通速度-体积关系、加州线源扩散模型、经验NO2-NOx关系、拥堵期间估计的行驶时间变化以及来自文献的浓度-响应关系，其给出了急诊医生就诊，住院率和死亡率归因于NO2暴露。一项增量分析表明，交通量小幅增加对健康风险的影响是非线性的。对于一条高速公路，“U”形趋势的增量风险预测的道路上的人口，和增量风险是平坦的低交通量附近的道路人口。对于主干道，随着交通量的增加，道路上和附近人口的增量风险急剧增加。这些模式的结果，在排放因子的变化，NO2-NOx的关系，在路上的人口的行程延迟，和近路人口的高峰时间的持续时间延长。这项研究表明，拥堵带来的健康风险可能很大，额外的交通流量会显著增加风险，具体取决于道路类型和其他因素。此外，与拥堵相关的风险评估必须考虑旅行时间，高峰时间的持续时间，特定的排放估计和不确定性。
Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed–volume relationship, the California Line Source Dispersion Model, an empirical NO2–NOx relationship, estimated travel time changes during congestion, and concentration–response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, “U” shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2–NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties.
登录
查看更多内容
影响因子：
6
作者：
Levy, Jonathan I.;Buonocore, Jonathan J.;von Stackelberg, Katherine
通讯作者：
von Stackelberg, Katherine
影响因子：
11.4
作者：
Greco, Susan L.;Wilson, Andrew M.;Levy, Jonathan I.
通讯作者：
Levy, Jonathan I.
DOI：
10.1016/j.tra.2008.09.007
发表时间：
2009-03-01
影响因子：
6.4
作者：
Eliasson, Jonas;Hultkrantz, Lars;Rosqvist, Lena Smidfelt
通讯作者：
Rosqvist, Lena Smidfelt
在亚洲移民人口中，本地人和外国作为儿科哮喘的预测因素：横断面调查。
影响因子：
6
作者：
Brugge, Doug;Lee, Angela C;Woodin, Mark;Rioux, Christine
通讯作者：
Rioux, Christine
影响因子：
5
作者：
Zhang, Kai;Batterman, Stuart;Dion, Francois
通讯作者：
Dion, Francois