Identifying spatiotemporal characteristics and driving factors for road traffic CO2 emissions

Road traffic is an important contributor to CO 2 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 CO 2 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 CO 2 emissions with high temporal (hour) and space (road) resolutions. The emission characteristics reflect the spatial non-equilibrium in road traffic CO 2 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 CO 2 emissions. Finally, the policy suggestions are proposed for the reduction of road traffic CO 2 emissions. • A vehicle trajectory-based CO 2 emission model is proposed. • The proposed approach can estimate CO 2 emissions with high spatial-temporal resolution. • The emission characteristics reflect the spatial non-equilibrium in road traffic CO 2 emissions. • Multiscale geographically weighted regression is applied to analyze key driving factors. • The effects of the driving factors on road traffic CO 2 emissions are diverse in different areas.