Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States.
Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712, United States.
Sci Total Environ. 2019 Mar 10;655:473-481. doi: 10.1016/j.scitotenv.2018.11.197. Epub 2018 Nov 14.
To quantify the fine-scale spatial variations and local source impacts of urban ultrafine particle (UFP) concentrations, we conducted 3-6 weeks of continuous measurements of particle number (a proxy for UFP) and other air pollutant (CO, NO, and PM) concentrations at 32 sites in Pittsburgh, Pennsylvania during the winters of 2017 and 2018. Sites were selected to span a range of urban land use attributes, including urban background, near local and arterial roads, traffic intersections, urban street canyon, near-highway, near large industrial source, and restaurant density. The spatial variations in urban particle number concentrations varied by about a factor of three. Particle number concentrations are 2-3 times more spatially heterogeneous than PM mass. The observed order of spatial heterogeneity is UFP > NO > CO > PM. On average, particle number concentrations near local roads with a cluster of restaurants and near arterial roads are roughly two times higher than the urban background. Particle number concentrations in the urban street canyon, downwind of a major highway, and near large industrial sources are 2-4 times higher than background concentrations. While traffic is known as an important contributor to particle number concentrations, restaurants and industrial emissions also contribute significantly to spatial variations in Pittsburgh. Particle size distribution measurements using a mobile laboratory show that the local spatial variations in particle number concentrations are dictated by concentrations of particles smaller than 50 nm. A large fraction of urban residents (e.g., ~50%) in Pittsburgh live near local sources and are therefore exposed to 50%-300% higher particle number concentrations than urban background location. These locally emitted particles may have greater health effects than background particles.
为了量化城市超细颗粒物 (UFP) 浓度的精细空间变化和本地源影响,我们在宾夕法尼亚州匹兹堡进行了 2017 年和 2018 年冬季的 3-6 周连续测量,测量了 32 个地点的颗粒物数(UFP 的代表)和其他空气污染物(CO、NO 和 PM)浓度。选择这些地点以涵盖一系列城市土地利用属性,包括城市背景、靠近当地和动脉道路、交通路口、城市街道峡谷、靠近高速公路、靠近大型工业源和餐馆密度。城市颗粒物数浓度的空间变化幅度约为三倍。颗粒物数浓度的空间异质性比 PM 质量高 2-3 倍。观察到的空间异质性顺序是 UFP>NO>CO>PM。平均而言,靠近有一群餐馆的当地道路和靠近动脉道路的地方的颗粒物数浓度比城市背景高约两倍。在主要高速公路下风处的城市街道峡谷中和靠近大型工业源的地方的颗粒物数浓度比背景浓度高 2-4 倍。虽然交通被认为是颗粒物数浓度的重要贡献者,但餐馆和工业排放也对匹兹堡的空间变化做出了重要贡献。使用移动实验室进行的颗粒物粒径分布测量表明,颗粒物数浓度的本地空间变化受小于 50nm 的颗粒物浓度控制。匹兹堡的很大一部分城市居民(例如,约 50%)居住在当地源附近,因此暴露于比城市背景位置高 50%-300%的颗粒物数浓度。这些本地排放的颗粒物可能比背景颗粒物具有更大的健康影响。