PDF(Pubmed)
Abstract：
Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 roadside sites within a large, 1200 land km2 (463 mi2) area representative of the cohort. We collected about 29 two-minute measurements at each site during all seasons, days of the week, and most times of the day over a 1-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and monitoring agency sites (R2 = 0.68-0.73). Universal kriging-partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R2 (and root mean square error) values of 0.77 (1177 pt/cm3) for PNC, 0.60 (102 ng/m3) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 μg/m3) for PM2.5, and 0.51 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.
摘要：
越来越多的证据将交通相关的空气污染（TRAP）与不利的健康影响联系起来。我们设计了一个创新和广泛的移动监测活动，以描述成人思想变化（ACT）研究的TRAP暴露水平，一个西雅图的队列。运动测量颗粒数浓度（PNC）以捕获超细颗粒（UFP），黑碳（BC），二氧化氮(NO2),细颗粒物（PM2.5），和二氧化碳(CO2)在309个路边站点内，1200km2陆地(463mi2)面积代表该队列。我们在每个季节收集了大约29个两分钟的测量值，一周的日子，以及一年中的大部分时间。验证显示我们BC之间的协议很好，NO2和PM2.5测量和监测机构站点（R2=0.68-0.73）。年平均污染物浓度的通用克里格偏最小二乘模型对PNC的基于均方误差的R2（和均方根误差）值为0.77（1177pt/cm3），0.60（102纳克/立方米）的BC，NO2为0.77（1.3ppb），PM2.5为0.70（0.3μg/m3），CO2为0.51（4.2ppm）。总的来说,我们发现，这种广泛运动的设计很好地捕获了空间污染物的变化，这些都是由合理的土地利用特征来解释的，包括与交通有关的。
