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

Author

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  • 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
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    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.
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