超细粒子
微粒
环境科学
气溶胶
大气科学
粒子数
相关性
空间相关性
空间生态学
质量浓度(化学)
粒子(生态学)
环境卫生
气象学
地理
统计
化学
材料科学
物理
医学
地质学
数学
体积热力学
纳米技术
物理化学
几何学
海洋学
生物
有机化学
量子力学
生态学
作者
Provat K. Saha,Shayak Sengupta,P. J. Adams,Allen L. Robinson,Albert A. Presto
标识
DOI:10.1021/acs.est.0c02763
摘要
The epidemiological evidence for ultrafine particles (UFP; particles with diameter <100 nm) causing chronic health effects independent of fine particulate matter (PM2.5) mass is inconclusive. A prevailing view is that urban UFP and PM2.5 mass have different spatial patterns, which should allow epidemiological studies to distinguish their independent, chronic health effects. We investigate intraurban spatial correlation of PM2.5 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 PM2.5 (R2 of 0.38 and 0.41, respectively). High-resolution (1-km) chemical transport model simulations predict stronger spatial correlation (R2 ≈ 0.8). The finding of moderate to strong spatial correlation was initially surprising because secondary aerosol contributes the vast majority of PM2.5 mass. However, intraurban spatial patterns of both PNC and PM2.5 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 PM2.5, our finding of moderate to strong spatial correlation may complicate epidemiological analyses to separate the chronic health effects of PNC from PM2.5 mass.
科研通智能强力驱动
Strongly Powered by AbleSci AI