Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons.

Planned urban form has become an important strategy to improve air quality in urban agglomerations (UAs), especially pollution due to PM2.5, but the influencing mechanisms are not yet clear. This study explores the relationship between four metrics of urban form (size, fragmentation, shape, and dispersion) as determined by analysis of remotely sensed images at 30-m resolution and PM2.5 concentrations in 19 Chinese UAs. The influence of level of urban development and season is examined. Five control variables, including population density, temperature, precipitation, wind speed, and the normalized difference vegetation index (NDVI) are selected for use in multiple linear regression models. Size, fragmentation, and shape of urban form, but not dispersion, were found to have significant effects on PM2.5 concentrations of different urbanization-level UAs. Urban size and fragmentation have stronger impacts on PM2.5 concentrations in UAs with lower urbanization levels while urban shape has a greater impact in higher-level UAs. In terms of seasonal variation in all UAs, urban form is more pronouncedly associated with PM2.5 concentrations during spring and autumn than summer and winter. Urban size and fragmentation are positively associated with PM2.5 concentrations whereas urban shape and dispersion are on the contrary. The relationships between urban form and PM2.5 uncovered here underscore the importance of urban planning as a tool to minimize PM2.5 pollution. Specifically, local government should encourage polycentric urban form with lower fragmentation in urban agglomerations. UAs with lower urbanization levels should control the disordered expansion of construction land and higher-level UAs should promote the mix of green land and construction land. Moreover, measures to control air pollution from anthropogenic activities in spring, autumn and winter are likely to be more effective in decreasing PM2.5 concentrations in UAs.