Optimizing bike sharing systems from the life cycle greenhouse gas emissions perspective. (August 2020)

• Record Type: Journal Article
• Authors: Luo, Hao; Zhao, Fu; Chen, Wei-Qiang; Cai, Hua
• Is Part Of: Transportation research. Volume 117(2020)
• Publication Date: 2020-08
• Subjects: Bike sharing -- Fleet size -- Rebalancing -- Life cycle greenhouse gas emissions -- Sharing economy; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2020.102705
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Proposed a modeling framework to optimize bike sharing system's fleet size and rebalancing. Less frequent rebalancing can reduce dock-less BSS life cycle GHG emission rate. The current dock-less BSS in Xiamen, China is significantly oversupplied with bikes. Rebalancing vehicle fleet can be optimized to reduce rebalancing GHG emissions. Having multiple rebalancing depots can help reduce system's GHG emissions. Abstract: Bike sharing systems (BSSs), being viewed as providing green transportation modes, are growing rapidly in recent years. While BSS operators try to improve the system performance through bike rebalancing and launching more bikes, the current BSSs are facing several sustainability challenges. Bike oversupply could bring intensive greenhouse gas (GHG) emissions due to manufacturing excessive bikes, while frequent bike rebalancing could significantly increase fuel consumption of rebalancing vehicles. Existing studies only optimized given BSS from the system operational perspective (i.e. rebalancing), with predetermined bike fleet size and rebalancing frequencies. However, the bike fleet size and rebalancing should also be optimized from the life cycle's perspective. This study proposes a framework to obtain the optimal bike fleet size and rebalancing strategy to minimize the system's life cycle GHG emissions, integrating a simulation model for fleet size estimation, an optimization model for bike rebalancing, and a life cycle assessment (LCA) model to quantify the system's GHG emission rate. The framework is applied to a dock-less BSS in Xiamen, China as a case study to evaluate the tradeoff between having more bikes (requiring less rebalancing) and more frequent rebalancing (requiring fewer bikes). Our results show that (1) the current BSS in Xiamen is significantly oversupplied, with only 15% of current bikes needed to serve the same demands; (2) decreasing bike fleet size through more frequent rebalancing will increase the system's life cycle GHG emissions; and (3) choosing appropriate rebalancing fleet size, loading capacity, and setting multiple depots can reduce a BSS' rebalancing GHG emissions.