Urban rail transit, as an efficient and eco-friendly mode of transportation, plays a pivotal role in mitigating traffic congestion and lowering urban carbon emissions. Despite the significant contributions by scholars in this area, debates surrounding the quantification of carbon emissions during the operational phase of urban rail transit persist, particularly in assessing its impact on reducing ground traffic congestion. This study examines the passenger flow during Beijing's morning and evening peak hours, assuming that all passengers initially using urban rail transit switch to buses and taxis during these periods. A traffic congestion prediction model is developed based on the analysis of actual traffic operation data under this assumption. Through this model, the study calculates the potential congestion times across various scenarios, employing a bottom-up approach to carbon emission estimation to analyze the impact on carbon emissions. Results spanning 2015 to 2021 suggest that substituting urban rail transit with buses could increase congestion by 37-92 min and 46-59 min during morning and evening peaks, respectively, leading to a 24-82% and 27-56% surge in carbon emissions. The conversion of all these vehicles to taxis would result in a direct paralysis of Beijing's road transport network, with a corresponding increase in carbon emissions of between 289% and 556% and 333% and 614%, respectively.These outcomes emphasize the substantial efficacy of urban rail transit in curbing traffic congestion and carbon emissions.
© 2025. The Author(s).