Balancing efficiency and emissions through travel mode shifts: A multi-objective analysis from Beijing, China
以北京为例，构建多目标优化模型，研究通过调整出行方式分布来平衡旅行效率与碳减排，发现优化可使平均旅行时间减少最多6.3分钟、每次出行碳排放减少最多384.1吨，为政策制定提供依据。
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.