Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: a simulation.
Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: a simulation.
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DOI：
10.1186/1476-072x-7-39
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发表时间：
2008-07-18
影响因子：
4.9
通讯作者：
Hystad PW
中科院分区：
文献类型：
--
作者：
Setton EM;Keller CP;Cloutier-Fisher D;Hystad PW
长期暴露于与交通有关的空气污染与成年人的各种健康影响有关，最近的研究表明，暴露程度在空间上各不相同，社区中的一些居民比其他人暴露更多。空间暴露模拟模型（SESM），其中包括6个微环境（室内家庭，室内工作，其他室内，室外，在车内工作和在车内其他）的描述和用于探索的空间变异性估计暴露于交通相关的二氧化氮（不包括室内源）的工作人员。该研究对加拿大不列颠哥伦比亚省大温哥华地区382个人口普查区在人口普查区水平上汇总的估计暴露量的空间变异性进行了建模。通过绘图直观地比较与估计暴露分布有关的汇总统计。观察到的变化，探讨通过分析模型的输入。暴露于交通相关的二氧化氮的空间变异性的两个来源被确定。研究区域不同人口普查区工人的总暴露量中位数为8 μg/m3至35 μg/m3。在环境污染程度最高的地方，接触估计值最高。这反映了研究区域污染的区域梯度以及在家中花费的时间比例相对较高。然而，对于同一人口普查区域内的工人，观察到与居住人口普查区域以外的时间相关的部分暴露估计值存在差异。模拟模型表明，一些工人的暴露可能比居住在同一人口普查区的其他工人高1.3倍，因为他们远离居住人口普查区的时间，而在工作人口普查区的时间对暴露差异的贡献最大。与乘车上下班活动相关的接触估计数可以忽略不计，因为与其他地点相比，在这一微环境中花费的时间相对较短。我们认识到，对于NO2以外的污染物，情况可能并非如此。这些结果是第一次空间分解的变化暴露于交通相关的空气污染在一个社区内已估计和报告。结果表明，虽然花费在家庭室内微环境的时间贡献最大的年度平均暴露于交通相关的NO2的估计之间的人口普查区的变化，花费在工作室内微环境的时间贡献最大的人口普查区内的变化，和时间花费在交通工具的贡献可以忽略不计。SESM有潜力作为一个政策评估工具，输入数据，反映由于交通需求管理和土地利用开发政策的污染水平或工作流模式的变化。
Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy.