Polycentric and dispersed population distribution increases PM2.5 concentrations: Evidence from 286 Chinese cities, 2001–2016

While many studies find that air pollution has been generally related with natural factors and anthropogenic activities, relatively little attention has been paid to exploring the impact of urban spatial structure on air pollution. This paper investigates the relationship between urban spatial structure and PM2.5 concentrations by drawing upon a panel dataset covering 286 Chinese cities during the 2001–2016 period. We measure two dimensions of urban spatial structure by using the LandScan High Resolution Global Population Dataset. The polycentricity-monocentricity dimension reflects to what extent population is distributed in a single center or across a number of subcenters. The concentration-dispersion dimension represents to what extent population is clustered in urban centers. By controlling for per capita GDP, population density, and the employment share of the secondary industry, our empirical results based on two-way fixed panel regression models find positive relationships between polycentricity, dispersion, and PM2.5 concentrations of Chinese cities. Other things being equal, an increase in the degrees of polycentricity and dispersion by 0.1 would lead to a rise in PM2.5 concentration by 0.1996 μg/m3 and 0.4063 μg/m3 respectively. Moreover, we find that the impact of polycentricity on PM2.5 concentrations is heterogeneous across cities. For cities with higher per capita GDP (>5200 US$) or a higher employment share of the secondary industry (>55.37%), a polycentric distribution of population is also expected to reduce PM2.5 concentrations. The results suggest that the planning of polycentric urban structure pursued by many Chinese local governments should be cautiously rethought.