Assessing sustainability impacts of shared e-scooters

This study proposes a framework to implement standardized micromobility data, such as Mobility Data Specification (MDS), to evaluate the energy and emission impacts of the shared e-scooters related to system operations and modal shift. The proposed methodology complements the existing studies evaluating the emission of shared e-scooter systems by estimating the usage and operational parameter of the Life Cycle Assessment (LCA) using Big Data. Along with improving the accuracy of the LCA analysis, such an approach also allows the evaluation of the temporal aspect of emission and energy use profile (such as time-of-the-day, day-of-the-week, and month-of-the-year). The findings of the proposed analysis are expected to help city governments to understand the overall environmental impact of shared e-scooters and develop data-driven strategies to manage their transportation-related sustainability impacts. This project is funded by the Oak Ridge National Laboratory’s (ORNL) Graduate Advancement, Training, and Education (GATE) program.