Urban particulate matter 2.5 (PM2.5) pollution and public health are closely related, and concs regarding PM2.5 are wide-spread. Of the underlying factors, the urban morphology is the most manageable. Therefore, investigations of the impact of urban three-dimensional (3D) morphology on PM2.5 concentration have important scientific significance. In this paper, 39 PM2.5 monitoring sites of Beijing in China were selected with PM2.5 automatic monitoring data that were collected in 2013. This data set was used to ana-lyze the impacts of the meteorological condition and public transportation on PM2.5 concentrations. Based on the elimination of the me-teorological conditions and public transportation factors, the relationships between urban 3D morphology and PM2.5 concentrations are highlighted. Ten urban 3D morphology indices were established to explore the spatial-temporal correlations between the indices and PM2.5 concentrations and analyze the impact of urban 3D morphology on the PM2.5 concentrations. Results demonstrated that road length density (RLD), road area density (RAD), construction area density (CAD), construction height density (CHD), construction vol-ume density (CVD), construction othess (CO), and vegetation area density (VAD) have positive impacts on the PM2.5 concentrations, whereas water area density (WAD), water fragmentation (WF), and vegetation fragmentation (VF) (except for the 500 m buffer) have negative impacts on the PM2.5 concentrations. Moreover, the correlations between the morphology indices and PM2.5 concentrations varied with the buffer scale. The findings could lay a foundation for the high-precision spatial-temporal modelling of PM2.5 concentra-tions and the scientific planning of urban 3D spaces by authorities responsible for controlling PM2.5 concentrations.