Assessing neighborhood air pollution exposure and its relationship with the urban form

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.