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

• A multi-objective optimization framework to optimize travel mode splits of ODs. • The framework can both enhance travel efficiency and reduce carbon emissions. • Three policy scenarios are set up to consider the trade-off between two goals. • The optimization range is 11 %–43 %, saving up to 6 mins and 384.1 tCO 2 per trip. • The algorithm is robust under different distance intervals and emission factors. 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 tCO 2 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.