Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States.
Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States.
Environ Sci Technol. 2020 Aug 4;54(15):9295-9304. doi: 10.1021/acs.est.0c02763. Epub 2020 Jul 14.
The epidemiological evidence for ultrafine particles (UFP; particles with diameter <100 nm) causing chronic health effects independent of fine particulate matter (PM) mass is inconclusive. A prevailing view is that urban UFP and PM mass have different spatial patterns, which should allow epidemiological studies to distinguish their independent, chronic health effects. We investigate intraurban spatial correlation of PM and UFP exposures in Pittsburgh, Pennsylvania. Measurements and predictions of a land-use regression model indicate moderate spatial correlation between particle number concentrations (PNC; a proxy for UFP) and PM ( of 0.38 and 0.41, respectively). High-resolution (1-km) chemical transport model simulations predict stronger spatial correlation ( ≈ 0.8). The finding of moderate to strong spatial correlation was initially surprising because secondary aerosol contributes the vast majority of PM mass. However, intraurban spatial patterns of both PNC and PM are driven by local emissions and both pollutants largely behave as passive tracers at time scales of 1 day or less required for transport across most urban environments. Although previous research has shown little temporal correlation between PNC and PM, our finding of moderate to strong spatial correlation may complicate epidemiological analyses to separate the chronic health effects of PNC from PM mass.
超细颗粒（UFP；直径<100nm 的颗粒）对慢性健康影响的流行病学证据与细颗粒物（PM）质量无关，这一证据尚无定论。目前的观点认为，城市 UFP 和 PM 质量具有不同的空间分布模式，这应该使流行病学研究能够区分它们对慢性健康的独立影响。我们研究了宾夕法尼亚州匹兹堡市 PM 和 UFP 暴露的城市内空间相关性。基于土地利用回归模型的测量和预测表明，颗粒物数浓度（UFP 的一种替代物）与 PM 之间存在中等程度的空间相关性（分别为 0.38 和 0.41）。高分辨率（1 公里）化学输送模型模拟预测出更强的空间相关性（≈0.8）。这一发现表明中等至强的空间相关性最初令人惊讶，因为二次气溶胶贡献了 PM 质量的绝大部分。然而，PNC 和 PM 的城市内空间分布模式均由本地排放驱动，这两种污染物在大多数城市环境中跨越所需的 1 天或更短的时间尺度上，主要表现为被动示踪剂。尽管之前的研究表明 PNC 和 PM 之间几乎没有时间相关性，但我们发现中等至强的空间相关性可能会使流行病学分析复杂化，难以将 PNC 的慢性健康影响与 PM 质量区分开来。
