Environmental impacts of shared mobility : potential, factors, and assessments
Series: IIIEE dissertation ; 2023:1Publication details: Lund : Lund University. IIIEE, 2023Description: 107 sISBN:- 9789187357886
Diss. (sammanfattning) Lund : Lunds universitet, 2023
Environmental impacts from passenger transportation continue to increase globally due to a rise in kilometers traveled and a shift to emission-intensive Environmental impacts from passenger transportation continue to increase globally due to a rise in kilometers traveled and a shift to emission-intensive transportation modes (from public transportation and active modes such as walking and cycling to motorcycle and car ridership). The electrification of the passenger fleet, coupled with low-carbon energy sources, is expected to decrease some of the environmental impacts associated with passenger transportation, including local air pollution, greenhouse gas emissions and fuel depletion. However, different environmental impacts might increase due to this shift, including rare metal depletion and increased pressure on the already-overloaded electrical grid in some parts of the world. Moreover, this shift does not address the increase in transportation activity and the shift to more emission-intensive transportation modes. Shared mobility is a demand-side mechanism that has the potential to change travel behavior and vehicle ownership rates among users. This dissertation aims to understand the potential of shared mobility to decrease the environmental impacts of passenger transportation and to understand the factors that might affect this potential. Here I focus on car sharing, with additional attention to ridesharing, bikesharing, and scooter and moped sharing. In this research I design and apply assessments using life-cycle analysis and multiregional input and output analysis to evaluate the environmental potential of shared mobility. My findings add to our knowledge and understanding of the potential of shared mobility. This study also adds to environmental assessments methods by applying multiregional input and output analysis in a novel way.