The role of data resolution in analyzing urban form and PM2.5 concentration

Abstract

Despite the global concern about the chronic toxic effects of fine particulate matter (PM2.5) on human health, particularly in urban areas, the impact of urban form on PM2.5 pollution remains incompletely understood. This study established panel regression models for two resolutions (1 km and 30 m), covering 320 cities in China from 2000 to 2015, using landscape metrics and natural and socioeconomic variables to explore the urban form-PM2.5 relationship. The findings suggest that while the effects of fragmentation and agglomeration are opposite, the impact of urban scale on PM2.5 remains consistent across different resolutions. To unveil its mechanism, we compared authentic urban land use data under varying resolutions in detail and discovered that the coarse-resolution data lacked certain small patches, in addition to exhibiting edge deformation. As a result, we conducted counterfactual experiments on high-resolution land use data (30 m), simulating changes to urban patches, including removing small urban patches, dilating urban patch edges, and eroding urban patch edges. The implication of the findings is that the loss of information on small patches is more common in coarse resolution data than the deformation of patch edges, which in turn ultimately alters the results. Therefore, one of the major contributions of this study is exploring the mechanism of how spatial resolution impacts the relationship between urban form and PM2.5 concentration. The results can provide recommendations for sustainable urban development, emphasizing the significance of the scale effect in studies. This recommends urban planners to adopt a satellite urban development approach in which large cities are evenly distributed and minor ones are clustered together, with the aim of reducing PM2.5 pollution and human exposure.