IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v352y2023ics0306261923012230.html
   My bibliography  Save this article

Spatio-temporal analysis of carbon footprints for urban public transport systems based on smart card data

Author

Listed:
  • Shang, Wen-Long
  • Chen, Yishui
  • Yu, Qing
  • Song, Xuewang
  • Chen, Yanyan
  • Ma, Xiaolei
  • Chen, Xiqun
  • Tan, Zhijia
  • Huang, Jianling
  • Ochieng, Washington

Abstract

The increasing severity of global climate change has made reductions in carbon emissions an urgent global issue. The relative lack of carbon footprint analyses of urban public transportation systems (UPTS) is therefore surprising, given that UPTS is an important component of urban transportation and one that may play a crucial role in carbon emission reduction. This study conducts a spatio-temporal analysis of carbon footprints for UPTS during the COVID-19 pandemic based on smart card data in Beijing. Since the core of carbon footprint calculation is to estimate travellers' trip trajectories and the ridership of urban rail transit (URT) and buses, we construct a novel multi-layer urban rail network model to calculate passenger volume and travellers' trajectories through a traffic assignment model. Furthermore, we utilize the Generalized Additive Model (GAM) to analyse the correlation relationship between the carbon footprints of buses and URT. Additionally, we conduct statistical analysis of the carbon footprint of UPTS. The results of the spatio-temporal analysis of carbon footprints for UPTS show significantly lower carbon emissions during holidays compared to those on working days, and emissions during peak hours contribute approximately half of the total daily UPTS emissions, while there are notable variations in the distribution of the carbon footprint among different districts. Moreover, our analysis reveals a positive correlation between the carbon footprints of buses and URT. The statistical analysis reflects different patterns of carbon footprint distribution on different dates during the pandemic, but the carbon footprint distributions on selected dates all follow a power-law distribution. This study may facilitate the understanding to the impacts of UPTS on the environment during the COVID-19 pandemic, and also provide important guidance and reference for the development of carbon emission reduction strategies.

Suggested Citation

  • Shang, Wen-Long & Chen, Yishui & Yu, Qing & Song, Xuewang & Chen, Yanyan & Ma, Xiaolei & Chen, Xiqun & Tan, Zhijia & Huang, Jianling & Ochieng, Washington, 2023. "Spatio-temporal analysis of carbon footprints for urban public transport systems based on smart card data," Applied Energy, Elsevier, vol. 352(C).
    • Handle: RePEc:eee:appene:v:352:y:2023:i:c:s0306261923012230
    DOI: 10.1016/j.apenergy.2023.121859
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923012230
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.121859?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jia, Yingnan & Fu, Hua, 2019. "Association between innovative dockless bicycle sharing programs and adopting cycling in commuting and non-commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 12-21.
    2. Sui, Yi & Zhang, Haoran & Shang, Wenlong & Sun, Rencheng & Wang, Changying & Ji, Jun & Song, Xuan & Shao, Fengjing, 2020. "Mining urban sustainable performance: Spatio-temporal emission potential changes of urban transit buses in post-COVID-19 future," Applied Energy, Elsevier, vol. 280(C).
    3. Brand, Christian & Goodman, Anna & Ogilvie, David, 2014. "Evaluating the impacts of new walking and cycling infrastructure on carbon dioxide emissions from motorized travel: A controlled longitudinal study," Applied Energy, Elsevier, vol. 128(C), pages 284-295.
    4. He, Xiaoping & Jiang, Shuo, 2021. "Effects of vehicle purchase restrictions on urban air quality: Empirical study on cities in China," Energy Policy, Elsevier, vol. 148(PB).
    5. Valery Vodovozov & Zoja Raud & Eduard Petlenkov, 2022. "Review of Energy Challenges and Horizons of Hydrogen City Buses," Energies, MDPI, vol. 15(19), pages 1-27, September.
    6. Paul Wolfram & Stephanie Weber & Kenneth Gillingham & Edgar G. Hertwich, 2021. "Pricing indirect emissions accelerates low—carbon transition of US light vehicle sector," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    7. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
    8. Wen-Long Shang & Yanyan Chen & Huibo Bi & Haoran Zhang & Changxi Ma & Washington Y. Ochieng, 2020. "Statistical Characteristics and Community Analysis of Urban Road Networks," Complexity, Hindawi, vol. 2020, pages 1-21, September.
    9. Liu, Zheng & Huang, Yu-Qing & Shang, Wen-Long & Zhao, Yuan-Jun & Yang, Zao-Li & Zhao, Zhao, 2022. "Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game," Applied Energy, Elsevier, vol. 326(C).
    10. Li, Peilin & Zhao, Pengjun & Brand, Christian, 2018. "Future energy use and CO2 emissions of urban passenger transport in China: A travel behavior and urban form based approach," Applied Energy, Elsevier, vol. 211(C), pages 820-842.
    11. Ching-Chih Chang & Po-Chien Huang, 2022. "Carbon footprint of different fuels used in public transportation in Taiwan: a life cycle assessment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5811-5825, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Yixiao & Tian, Zihao & Pan, Baoran & Zhang, Wenbin & Liu, Yunqi & Tian, Lixin, 2022. "A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing," Applied Energy, Elsevier, vol. 315(C).
    2. M. A. Hannan & M. S. Abd Rahman & Ali Q. Al-Shetwi & R. A. Begum & Pin Jern Ker & M. Mansor & M. S. Mia & M. J. Hossain & Z. Y. Dong & T. M. I. Mahlia, 2022. "Impact Assessment of COVID-19 Severity on Environment, Economy and Society towards Affecting Sustainable Development Goals," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    3. Schulte-Fischedick, Marta & Shan, Yuli & Hubacek, Klaus, 2021. "Implications of COVID-19 lockdowns on surface passenger mobility and related CO2 emission changes in Europe," Applied Energy, Elsevier, vol. 300(C).
    4. Yu, Qing & Li, Weifeng & Zhang, Haoran & Chen, Jinyu, 2022. "GPS data in taxi-sharing system: Analysis of potential demand and assessment of fuel consumption based on routing probability model," Applied Energy, Elsevier, vol. 314(C).
    5. Zhou, Junfeng & Zhang, Yanhui & Zhang, Yubo & Shang, Wen-Long & Yang, Zhile & Feng, Wei, 2022. "Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning," Applied Energy, Elsevier, vol. 314(C).
    6. Indre Siksnelyte-Butkiene, 2021. "Impact of the COVID-19 Pandemic to the Sustainability of the Energy Sector," Sustainability, MDPI, vol. 13(23), pages 1-19, November.
    7. Dai, Rongjian & Ding, Chuan & Gao, Jian & Wu, Xinkai & Yu, Bin, 2022. "Optimization and evaluation for autonomous taxi ride-sharing schedule and depot location from the perspective of energy consumption," Applied Energy, Elsevier, vol. 308(C).
    8. Qiu, Dawei & Wang, Yi & Sun, Mingyang & Strbac, Goran, 2022. "Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 313(C).
    9. Rong, Peijun & Kwan, Mei-Po & Qin, Yaochen & Zheng, Zhicheng, 2022. "A review of research on low-carbon school trips and their implications for human-environment relationship," Journal of Transport Geography, Elsevier, vol. 99(C).
    10. Wenjing Wang & Yanyan Chen & Haodong Sun & Yusen Chen, 2021. "Multiple Binary Classification Model of Trip Chain Based on the Fusion of Internet Location Data and Transport Data," Sustainability, MDPI, vol. 13(21), pages 1-15, November.
    11. Chen, Haoqian & Sui, Yi & Shang, Wen-long & Sun, Rencheng & Chen, Zhiheng & Wang, Changying & Han, Chunjia & Zhang, Yuqian & Zhang, Haoran, 2022. "Towards renewable public transport: Mining the performance of electric buses using solar-radiation as an auxiliary power source," Applied Energy, Elsevier, vol. 325(C).
    12. Li, Xi & Yu, Biying, 2019. "Peaking CO2 emissions for China's urban passenger transport sector," Energy Policy, Elsevier, vol. 133(C).
    13. Vladimír Konečný & Jozef Gnap & Tomáš Settey & František Petro & Tomáš Skrúcaný & Tomasz Figlus, 2020. "Environmental Sustainability of the Vehicle Fleet Change in Public City Transport of Selected City in Central Europe," Energies, MDPI, vol. 13(15), pages 1-23, July.
    14. Hua Pan & Huimin Zhu & Minmin Teng, 2023. "Low-Carbon Transformation Strategy for Blockchain-Based Power Supply Chain," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
    15. Liu, Xingjian & Wang, Mingshu & Qiang, Wei & Wu, Kang & Wang, Xiaomi, 2020. "Urban form, shrinking cities, and residential carbon emissions: Evidence from Chinese city-regions," Applied Energy, Elsevier, vol. 261(C).
    16. Wen, Yifan & Zhang, Shaojun & Zhang, Jingran & Bao, Shuanghui & Wu, Xiaomeng & Yang, Daoyuan & Wu, Ye, 2020. "Mapping dynamic road emissions for a megacity by using open-access traffic congestion index data," Applied Energy, Elsevier, vol. 260(C).
    17. Zhang, Haoran & Chen, Jinyu & Li, Wenjing & Song, Xuan & Shibasaki, Ryosuke, 2020. "Mobile phone GPS data in urban ride-sharing: An assessment method for emission reduction potential," Applied Energy, Elsevier, vol. 269(C).
    18. 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.
    19. Pye, Steve & Daly, Hannah, 2015. "Modelling sustainable urban travel in a whole systems energy model," Applied Energy, Elsevier, vol. 159(C), pages 97-107.
    20. Pan, Shuai & Yu, Wendi & Fulton, Lewis M. & Jung, Jia & Choi, Yunsoo & Gao, H. Oliver, 2023. "Impacts of the large-scale use of passenger electric vehicles on public health in 30 US. metropolitan areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:352:y:2023:i:c:s0306261923012230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.