A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing

Yixiao Liu, Zihao Tian, Baoran Pan, Wenbin Zhang, Yunqi Liu and Lixin Tian

Applied Energy, 2022, vol. 315, issue C, No S0306261922003841

Abstract: This research has established a set of methods to use the data of existing docked bike sharing system to pre-estimate the emission reduction effects of docked electric bike sharing system that will be built in the future. It extracted demand through the non-homogeneous Poisson process, and used coarse-grained methods and complex network to estimate total riding distance. Tolerance assumptions were given to accurately estimate the emission reduction effect. Compared with the existing threshold assumption, it can better describe the emission reduction caused by the substitution effect. It is found that the emission reduction caused by the substitution effect after upgrading the docked bike sharing system to the docked electric bike sharing system is 4.19 times of the original. While the reduction in emissions caused by its substitution effect on taxis is three times of the original. This contains a huge emission reduction effect. If 1% of the permanent residents of Nanjing change their commuting vehicles from cars to electric bicycles, the one-way emission reduction will exceed 9.55 tonnes of carbon dioxide. This only requires them to tolerate 5 min in average.

Keywords: Bike sharing; Feature extraction; Tolerance assumption; Substitution effect; Emission reduction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.apenergy.2022.118974

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