Road traffic is an important contributor to CO2 emissions. Previous studies lack enough spatiotemporal resolution in emission calculation at the road level and ignore the impact of the built environment on road traffic emissions. Therefore, this study develops a bottom-up methodology based on the traffic trajectory data to analyze the CO2 emission characteristics of road traffic with a high level of spatial-temporal resolution in Shenzhen. Then, the effects of built environment factors on road traffic emissions are investigated using multiscale geographically weighted regression. The results show a highly detailed map of CO2 emissions with high temporal (hour) and space (road) resolutions. The emission characteristics reflect the spatial non-equilibrium in road traffic CO2 emissions. In addition, six factors, including population density, number of workplaces, number of dwellings, density of main road, access to metro stations, and access to bus stops, have a significant effect on road traffic CO2 emissions. Finally, the policy suggestions are proposed for the reduction of road traffic CO2 emissions. Display omitted •A vehicle trajectory-based CO2 emission model is proposed.•The proposed approach can estimate CO2 emissions with high spatial-temporal resolution.•The emission characteristics reflect the spatial non-equilibrium in road traffic CO2 emissions.•Multiscale geographically weighted regression is applied to analyze key driving factors.•The effects of the driving factors on road traffic CO2 emissions are diverse in different areas.