Balancing efficiency and emissions through travel mode shifts: A multi-objective analysis from Beijing, China

The transition towards climate-neutral mobility remains challenging for cities worldwide, particularly in balancing travel efficiency with emission reduction goals. This study develops a policy-oriented framework to optimize travel mode splits, demonstrating how behavioral adaptations can contribute to sustainable urban mobility without extensive infrastructure investments. Using Beijing as a case study, we formulate a multi-objective optimization model to identify optimal travel mode distributions between origin-destination pairs, considering both travel efficiency and carbon emissions. Our results reveal significant potential through strategic mode shifts: the optimization could reduce average travel time by up to 6.3 min while cutting carbon emissions by up to 384.1 tCO2 per trip. The effectiveness varies across urban contexts, with optimization potential ranging from 11 % to 43 %, suggesting targeted policy interventions. Different scenarios, prioritizing either emission reduction or efficiency improvement, help identify high-priority areas for implementing mode shift strategies. Sensitivity analyses demonstrate the framework’s robustness across various contexts, including scenarios of vehicle electrification. These findings provide evidence-based support for policymakers to design targeted interventions that effectively influence travel behavior towards climate-neutral mobility.