An integrated life cycle assessment framework for bike share systems incorporating battery swapping and data-driven rebalancing modeling

Bike share systems are widely promoted as sustainable transportation solutions, yet existing life cycle assessment (LCA) studies often underestimate operational emissions. This study develops an integrated LCA framework that explicitly incorporates station energy use, battery swapping trips, and data-driven rebalancing modeling. Battery swapping routes are optimized using a Vehicle Routing Problem with Time Windows (VRPTW) model, while rebalancing trips are estimated through empirical activity identification and routing. Using Chicago’s Divvy system as a case study, results show that battery swapping is a major operational impact source, accounting for 9–12 % of total system emissions. Integrating battery swapping with rebalancing reduces operational travel and lowers system-level greenhouse gas (GHG) emission intensity by approximately 4 %. Overall, the life cycle GHG emission intensity of the station-based Divvy system is 103–107 g CO₂-eq per bike-km. The proposed framework improves the completeness and accuracy of environmental assessments for bike share systems.