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Environmental benefits of bike sharing: A big data-based analysis


  • Zhang, Yongping
  • Mi, Zhifu


Bike sharing is a new form of transport and is becoming increasingly popular in cities around the world. This study aims to quantitatively estimate the environmental benefits of bike sharing. Using big data techniques, we estimate the impacts of bike sharing on energy use and carbon dioxide (CO2) and nitrogen oxide (NOX) emissions in Shanghai from a spatiotemporal perspective. In 2016, bike sharing in Shanghai saved 8358 tonnes of petrol and decreased CO2 and NOX emissions by 25,240 and 64 tonnes, respectively. From a spatial perspective, environmental benefits are much higher in more developed districts in Shanghai where population density is usually higher. From a temporal perspective, there are obvious morning and evening peaks of the environmental benefits of bike sharing, and evening peaks are higher than morning peaks. Bike sharing has great potential to reduce energy consumption and emissions based on its rapid development.

Suggested Citation

  • Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
  • Handle: RePEc:eee:appene:v:220:y:2018:i:c:p:296-301
    DOI: 10.1016/j.apenergy.2018.03.101

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    References listed on IDEAS

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    Cited by:

    1. Tianjian Yang & Ye Li & Simin Zhou & Yu Zhang, 2019. "Dynamic Feedback Analysis of Influencing Factors and Challenges of Dockless Bike-Sharing Sustainability in China," Sustainability, MDPI, Open Access Journal, vol. 11(17), pages 1-17, August.
    2. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.
    3. Chengming Li & Zhaoxin Dai & Weixiang Peng & Jianming Shen, 2019. "Green Travel Mode: Trajectory Data Cleansing Method for Shared Electric Bicycles," Sustainability, MDPI, Open Access Journal, vol. 11(5), pages 1-14, March.
    4. Alexandros Nikitas, 2019. "How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers," Sustainability, MDPI, Open Access Journal, vol. 11(11), pages 1-17, June.
    5. Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.
    6. Peiyu Yi & Feihu Huang & Jian Peng, 2019. "A Rebalancing Strategy for the Imbalance Problem in Bike-Sharing Systems," Energies, MDPI, Open Access Journal, vol. 12(13), pages 1-18, July.
    7. Tianjian Yang & Ye Li & Simin Zhou, 2019. "System Dynamics Modeling of Dockless Bike-Sharing Program Operations: A Case Study of Mobike in Beijing, China," Sustainability, MDPI, Open Access Journal, vol. 11(6), pages 1-20, March.
    8. Ruijing Wu & Shaoxuan Liu & Zhenyang Shi, 2019. "Customer Incentive Rebalancing Plan in Free-Float Bike-Sharing System with Limited Information," Sustainability, MDPI, Open Access Journal, vol. 11(11), pages 1-24, May.
    9. Zhang, Haoran & Song, Xuan & Long, Yin & Xia, Tianqi & Fang, Kai & Zheng, Jianqin & Huang, Dou & Shibasaki, Ryosuke & Liang, Yongtu, 2019. "Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis," Applied Energy, Elsevier, vol. 242(C), pages 138-147.


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