Three-dimensional building morphology impacts on PM2.5 distribution in urban landscape settings in Zhejiang, China

Abstract

Three-dimensional (3D) urban landscape patterns and building morphology are crucial for urban planning and essential for urban landscape functions. In this study, fixed and mobile monitoring sites were used to determine the spatial distribution of PM2.5 concentrations in Hangzhou. Six 3D metrics were selected to analyze the response of PM2.5 pollution to landscape patterns and building morphology, while their two-dimensional (2D) counterparts' metrics were also analyzed to contrast the differences. A variance partitioning analysis (VPA) was performed to measure the combined and relative contribution of 3D and 2D metrics to the changes in PM2.5 concentrations. The results showed that: (1) on the 3D scale, forming a building pattern with a combination of different building heights can eliminate the accumulation of PM2.5; (2) on the 2D scale, fragmentation and decentralization of landscapes and building patches alleviate PM2.5 pollution; and (3) 3D building morphology indicators have the highest explanatory power (40.94%) for the changes of PM2.5 concentrations. It turns out that the explanatory power of 3D metrics for PM2.5 concentrations changes is much greater than that of 2D metrics. In addition, when compared to building morphology indicators from a single dimension, the combination of 2D and 3D metrics is better able to reflect urban PM2.5 pollution. The results of this study expand our understanding of how PM2.5 pollution responds to 2D and 3D metrics and provide useful information for urban planning.