Assessing neighborhood air pollution exposure and its relationship with the urban form. (15th May 2019) - Gao, Ya; Wang, Zhanyong; Liu, Chao; Peng, Zhong-Ren
Abstract: Previous studies on air pollution exposure have mostly focused on the urban, regional, national and global scales, but the outcomes cannot well support risk assessments in urban communities. To determine how the urban form and meteorology influence the air pollution distribution at a neighborhood scale (2 km*2 km), we performed a fine-scale investigation of a typical air pollutant (i.e., PM2.5 ) by mobile measurements in two communities in the inner and outer cities of Shanghai, China. The PM2.5 mass concentrations and potential impacting factors, such as PM2.5 background levels, road networks, traffic volumes, meteorological parameters, building heights and land use types, were collected at a 10 m spatial resolution, and their relationships were analyzed using both a generalized additive model (GAM) and land use regression (LUR). The modeling results showed that the GAM outperformed LUR in both study areas, with a higher adjusted R 2 and a lower RMSE. The PM2.5 was found to have drastic variations at the neighborhood scale, which was primarily driven by spatial patterns of the PM2.5 background levels and traffic volumes. The GAM-based PM2.5 concentration surface clearly disclosed the heterogeneous variation of the PM2.5 mass concentrations in each community, and demonstrated the prominent influence from the nearby highway, especially in the central urban area. This study provides the first empirical evidence of the exposure heterogeneity of the air pollution on a neighborhood scale, which can assist planners and policymakers in evaluating planning strategies with a full consideration of reducing local air pollution. Highlights: Mobile measurements of PM2.5 concentrations are performed in two neighborhoods of Shanghai. Generalized additive models outperform land use regressions for assessing PM2.5 variations. PM2.5 of high values are mainly distributed alongside highways up to 100–300 m. Building height with wind speed primarily determines PM2.5 variations in the central urban area. PM2.5 variations in the suburban area are mainly impacted by regional emission sources.