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For a better environment and sustainable development of China, it is indispensable to unravel how urban forms (UF) affect the fine particulate matter (PM 2.5 ) concentration. However, research in this area have not been updated consider multiscale and spatial heterogeneities, thus providing insufficient or incomplete results and analyses. In this study, UF at different scales were extracted and calculated from remote sensing land-use/cover data, and panel data models were then applied to analyze the connections between UF and PM 2.5  concentration at the city and provincial scales. Our comparison and evaluation results showed that the PM 2.5  concentration could be affected by the UF designations, with the largest patch index (LPI) and landscape shape index (LSI) the most influential at the provincial and city scales, respectively. The number of patches (NP) has a strong negative influence (−0.033) on the PM 2.5  concentration at the provincial scale, but it was not statistically significant at the city scale. No significant impact of urban compactness on the PM 2.5  concentration was found at the city scale. In terms of the eastern and central provinces, LPI imposed a weighty positive influence on PM 2.5  concentration, but it did not exert a significant effect in the western provinces. In the western cities, if the urban layout were either irregular or scattered, exposure to high PM 2.5  pollution levels would increase. This study reveals distinct ties of the different UF and PM 2.5  concentration at the various scales and helps to determine the reasonable UF in different locations, aimed at reducing the PM 2.5  concentration.

The Effects of Urban Forms on the PM2.5 Concentration in China: A Hierarchical Multiscale Analysis