Relationship between Air Pollution and Urban Forms: Evidence from Prefecture-Level Cities of the Yangtze River Basin.

Urban forms, such as size, shape, density, compactness, and fragmentation, are associated with local air pollution concentrations. However, empirical analyses on how urban form improves or degrades urban air quality are still limited and inconclusive, especially for those rapidly expanding cities in developing countries. In this study, by using the improved STIRPAT (stochastic impacts by regression on population, affluence, and technology) model, the quantitative impact of urban form on near-surface PM2.5 and NO2 concentrations was identified in the 10 prefecture-level cities of the Yangtze River Basin (YRB) from 2000 to 2013. Trend analyses showed a significant increasing trend in both PM2.5 (9.69 × 10-4 µg·m-3·year-1) and NO2 (1.73 × 10-4 ppb·year-1) for the whole study period. Notably, a turning point of PM2.5 from increasing to decreasing trends occurred around 2007. In addition, both pollutants showed a spatial agglomeration. The STIRPAT model demonstrated that socioeconomic, transportation and urban form factors played an important role in alleviating the increase of PM2.5 and NO2. In particular, a 1% decrease in urban extent density (UED) significantly increased NO2 by 0.203%, but reduced PM2.5 by 0.033%. The proximity index (PI) measured as a city's compactness was significantly negatively correlated with PM2.5 and NO2. Conversely, a significant positive relationship of PM2.5 and NO2 concentrations against the openness index (OI) was observed, an important variable for measuring a city's fragmentation. In addition, the environmental Kuznets curve (EKC) hypothesis between per capita GDP and PM2.5 concentration was confirmed but failed in NO2. Overall, this study encouraged a less fragmented and more compact urban form, which helped alleviate local air pollution concentrations by enhancing urban connectivity, reducing vehicle dependence, and facilitating the use of bicycles and walking.

Pubmed ID: 31533359