Center for Atmospheric Particle Studies , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States.
Department of Civil, Architectural and Environmental Engineering , University of Texas , Austin , Texas 78712 , United States.
Environ Sci Technol. 2018 Oct 16;52(20):11545-11554. doi: 10.1021/acs.est.8b03833. Epub 2018 Oct 8.
Localized primary emissions of carbonaceous aerosol are the major drivers of intracity variability of submicron particulate matter (PM) concentrations. We investigated spatial variations in PM composition with mobile sampling in Pittsburgh, Pennsylvania, United States and performed source-apportionment analysis to attribute primary organic aerosol (OA) to traffic (HOA) and cooking OA (COA). In high-source-impact locations, the PM concentration is, on average, 2 μg m (40%) higher than urban background locations. Traffic emissions are the largest source contributing to population-weighted exposures to primary PM. Vehicle-miles traveled (VMT) can be used to reliably predict the concentration of HOA and localized black carbon (BC) in air pollutant spatial models. Restaurant count is a useful but imperfect predictor for COA concentration, likely due to highly variable emissions from individual restaurants. Near-road cooking emissions can be falsely attributed to traffic sources in the absence of PM source apportionment. In Pittsburgh, 28% and 9% of the total population are exposed to >1 μg m of traffic- and cooking-related primary emissions, with some populations impacted by both sources. The source mix in many U.S. cities is similar; thus, we expect similar PM spatial patterns and increased exposure in high-source areas in other cities.
本地化的碳质气溶胶一次排放是造成城市内亚微米颗粒物（PM）浓度空间变化的主要因素。我们在美国宾夕法尼亚州匹兹堡市进行了移动采样，研究了 PM 成分的空间变化，并进行了源解析分析，将一次有机气溶胶（OA）归因于交通源（HOA）和烹饪源 OA（COA）。在高源影响的地点，PM 浓度平均比城市背景地点高 2μg/m（40%）。交通排放是对人群加权暴露于一次 PM 影响最大的源。车辆行驶里程（VMT）可用于可靠地预测污染物空间模型中 HOA 和本地化黑碳（BC）的浓度。餐馆数量是 COA 浓度的一个有用但不完美的预测因子，可能是由于个别餐馆的排放高度可变。在缺乏 PM 源解析的情况下，路边烹饪排放可能被错误地归因于交通源。在匹兹堡，28%和 9%的总人口暴露于 >1μg/m 的交通和烹饪相关的一次排放中，一些人群受到这两种来源的影响。美国许多城市的污染源组合相似；因此，我们预计在其他城市的高源地区也会出现类似的 PM 空间模式和暴露增加。
