Carbon emission reduction benefits of ride-hailing vehicle electrification considering energy structure
Journal article, 2024

Ride-hailing services provided by companies like Uber, Lyft, and Didi have rapidly grown, leading to increased traffic congestion and greenhouse gas emissions. The transition of ride-hailing fleets to Electric vehicles (EVs) presents a considerable opportunity to reduce emissions in the transportation sector. Despite this potential, the carbon emission benefits of electrifying ride-hailing vehicles remain inadequately quantified. This study introduces a framework designed to assess carbon emission reductions resulting from EVs, specifically accounting for emissions transferred from electricity during the operational phase of ride-hailing vehicles. The study employs field data from Chengdu and Xi'an, China for case studies using the proposed framework. Our findings indicate that emission reductions are markedly influenced by the grid electricity emission factors specific to each city. The daily reduction in emissions due to electrification of ride-hailing vehicles is equivalent to eliminating approximately 133,307 and 63,162 trips of gasoline vehicle in the ride-hailing services of Chengdu and Xi'an, respectively. More importantly, this study identifies equilibrium points that establish the necessary grid electricity emission factors for achieving emission reductions across all ride-hailing trips when transitioning from gasoline to EVs through sensitivity analysis. For Chengdu and Xi'an, the thresholds of grid electricity emission factors are 156.25 g/kWh and 131.09 g/kWh, respectively. This study offers an applicable analytical framework to evaluate emission reductions of ride-hailing electrification across various urban contexts, thereby aiding in the determination of conditions conducive to effective integration of EVs into ride-hailing services.

Grid emission factor

Carbon emission

Electric vehicle

Ride-hailing

Author

Zhe Zhang

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

State Key Laboratory of Ocean Engineering

Qing Yu

Beijing University of Technology

Kun Gao

Geology and Geotechnics

Hong Di He

State Key Laboratory of Ocean Engineering

Yang Liu

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Haichao Huang

State Key Laboratory of Ocean Engineering

Applied Energy

0306-2619 (ISSN) 18729118 (eISSN)

124548

Subject Categories

Transport Systems and Logistics

Other Engineering and Technologies not elsewhere specified

Computer Systems

DOI

10.1016/j.apenergy.2024.124548

More information

Latest update

10/15/2024