Quantitative Assessment of the Environmental Impact of Urban Rail Transits through Carbon Emission Reduction—A Case Study of Beijing Municipality

Abstract

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 focuses on the passenger flows in Beijing during peak morning and evening hours, postulating a shift from urban rail transit to alternative modes, such as buses and taxis. A model predicting traffic congestion states based on passenger flow and other relevant parameters was developed. 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 76–169 minutes and 101–162 minutes during morning and evening peaks, respectively, leading to a 27%-51% and 31%-55% surge in carbon emissions. Conversely, a shift to taxis could result in a 271–291 minutes and 252–312 minutes increment in congestion times, with carbon emissions spiking by 130%-222% and 142%-236%, respectively. These outcomes emphasize the substantial efficacy of urban rail transit in curbing traffic congestion and carbon emissions.