IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9588-d880299.html
   My bibliography  Save this article

Carbon Emission Measurement of Urban Green Passenger Transport: A Case Study of Qingdao

Author

Listed:
  • Xinguang Li

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266500, China)

  • Tong Lv

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266500, China)

  • Jun Zhan

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266500, China)

  • Shen Wang

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266500, China)

  • Fuquan Pan

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266500, China)

Abstract

Urban passenger transport is one of the most significant sources of fossil energy consumption and greenhouse gas emission, especially in developing countries. The rapid growth of urban transport makes it a critical target for carbon reduction. This paper establishes a method for calculating carbon emission from urban passenger transport including ground buses, private cars, cruising taxis, online-hailing taxis, and rail transit. The scope of the study is determined according to the transportation mode and energy type, and the carbon emission factor of each energy source is also determined according to the local energy structure, etc. Taking into consideration the development trend of new energy vehicles, a combination of “top-down” and “bottom-up” approaches is used to estimate the carbon dioxide emission of each transportation mode. The results reveal that carbon emission from Qingdao’s passenger transport in 2020 was 8.15 million tons, of which 84.31% came from private cars, while the share of private cars of total travel was only 45.66%. Ground buses are the most efficient mode of transport. Fossil fuels emit more greenhouse gases than other clean energy sources. The emission intensity of hydrogen fuel cell buses is better than that of other fuel type vehicles. Battery electric buses have the largest sensitivity coefficient, therefore the carbon emission reduction potentially achieved by developing battery electric buses is most significant.

Suggested Citation

  • Xinguang Li & Tong Lv & Jun Zhan & Shen Wang & Fuquan Pan, 2022. "Carbon Emission Measurement of Urban Green Passenger Transport: A Case Study of Qingdao," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9588-:d:880299
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9588/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/15/9588/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Geoffrey Udoka Nnadiri & Anthony S. F. Chiu & Jose Bienvenido Manuel Biona & Neil Stephen Lopez, 2021. "Comparison of Driving Forces to Increasing Traffic Flow and Transport Emissions in Philippine Regions: A Spatial Decomposition Study," Sustainability, MDPI, vol. 13(11), pages 1-17, June.
    2. Mine Isik & Rebecca Dodder & P. Ozge Kaplan, 2021. "Transportation emissions scenarios for New York City under different carbon intensities of electricity and electric vehicle adoption rates," Nature Energy, Nature, vol. 6(1), pages 92-104, January.
    3. Solaymani, Saeed, 2019. "CO2 emissions patterns in 7 top carbon emitter economies: The case of transport sector," Energy, Elsevier, vol. 168(C), pages 989-1001.
    4. Hasan, M.A. & Chapman, R. & Frame, D.J., 2020. "Acceptability of transport emissions reduction policies: A multi-criteria analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Carmen Córdova & Ana Zorio-Grima & Paloma Merello, 2018. "Carbon Emissions by South American Companies: Driving Factors for Reporting Decisions and Emissions Reduction," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    6. Nur Fatma Fadilah Yaacob & Muhamad Razuhanafi Mat Yazid & Khairul Nizam Abdul Maulud & Noor Ezlin Ahmad Basri, 2020. "A Review of the Measurement Method, Analysis and Implementation Policy of Carbon Dioxide Emission from Transportation," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    7. Wang, Shaojian & Liu, Xiaoping & Zhou, Chunshan & Hu, Jincan & Ou, Jinpei, 2017. "Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities," Applied Energy, Elsevier, vol. 185(P1), pages 189-200.
    8. Sergio Maria Patella & Flavio Scrucca & Francesco Asdrubali & Stefano Carrese, 2019. "Traffic Simulation-Based Approach for A Cradle-to-Grave Greenhouse Gases Emission Model," Sustainability, MDPI, vol. 11(16), pages 1-14, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rongbin Wang & Weifeng Zhang & Wenlong Deng & Ruihao Zhang & Xiaohui Zhang, 2022. "Study on Prediction of Energy Conservation and Carbon Reduction in Universities Based on Exponential Smoothing," Sustainability, MDPI, vol. 14(19), pages 1-11, September.
    2. Hongxia Chen & Jeongsoo Yu & Xiaoyue Liu, 2022. "Development Strategies and Policy Trends of the Next-Generation Vehicles Battery: Focusing on the International Comparison of China, Japan and South Korea," Sustainability, MDPI, vol. 14(19), pages 1-12, September.

    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. Jasmina Ćetković & Slobodan Lakić & Angelina Živković & Miloš Žarković & Radoje Vujadinović, 2021. "Economic Analysis of Measures for GHG Emission Reduction," Sustainability, MDPI, vol. 13(4), pages 1-25, February.
    2. Merello, Paloma & Barberá, Antonio & la Poza, Elena De, 2022. "Is the sustainability profile of FinTech companies a key driver of their value?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Kaize Zhang & Juqin Shen & Ran He & Bihang Fan & Han Han, 2019. "Dynamic Analysis of the Coupling Coordination Relationship between Urbanization and Water Resource Security and Its Obstacle Factor," IJERPH, MDPI, vol. 16(23), pages 1-16, November.
    4. Hasan Huseyin Coban & Wojciech Lewicki & Ewelina Sendek-Matysiak & Zbigniew Łosiewicz & Wojciech Drożdż & Radosław Miśkiewicz, 2022. "Electric Vehicles and Vehicle–Grid Interaction in the Turkish Electricity System," Energies, MDPI, vol. 15(21), pages 1-19, November.
    5. Alfredo Alvarez-Diazcomas & Adyr A. Estévez-Bén & Juvenal Rodríguez-Reséndiz & Miguel-Angel Martínez-Prado & Roberto V. Carrillo-Serrano & Suresh Thenozhi, 2020. "A Review of Battery Equalizer Circuits for Electric Vehicle Applications," Energies, MDPI, vol. 13(21), pages 1-29, October.
    6. Zhou, Xi-Yin & Xu, Zhicheng & Zheng, Jialin & Zhou, Ya & Lei, Kun & Fu, Jiafeng & Khu, Soon-Thiam & Yang, Junfeng, 2023. "Internal spillover effect of carbon emission between transportation sectors and electricity generation sectors," Renewable Energy, Elsevier, vol. 208(C), pages 356-366.
    7. Lin, Boqiang & Ma, Ruiyang, 2022. "Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    8. Huiling Wang & Jiaxin Luo & Mengtian Zhang & Yue Ling, 2022. "The Impact of Transportation Restructuring on the Intensity of Greenhouse Gas Emissions: Empirical Data from China," IJERPH, MDPI, vol. 19(19), pages 1-16, October.
    9. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    10. Sheng Xu & Jingxue Chen & Demei Wen, 2023. "Research on the Impact of Carbon Trading Policy on the Structural Upgrading of Marine Industry," Sustainability, MDPI, vol. 15(9), pages 1-17, April.
    11. Wang, Hanjie & Yu, Xiaohua, 2023. "Carbon dioxide emission typology and policy implications: Evidence from machine learning," China Economic Review, Elsevier, vol. 78(C).
    12. Khan Rabnawaz & Kong YuSheng, 2020. "Effects of Energy Consumption on GDP: New Evidence of 24 Countries on Their Natural Resources and Production of Electricity," Ekonomika (Economics), Sciendo, vol. 99(1), pages 26-49, June.
    13. Zhang, Junjie & Jia, Rongwen & Yang, Hangjun & Dong, Kangyin, 2022. "Does electric vehicle promotion in the public sector contribute to urban transport carbon emissions reduction?," Transport Policy, Elsevier, vol. 125(C), pages 151-163.
    14. Liu, Yiming & Hao, Yu & Gao, Yixuan, 2017. "The environmental consequences of domestic and foreign investment: Evidence from China," Energy Policy, Elsevier, vol. 108(C), pages 271-280.
    15. Abdul Hayy Haziq Mohamad & Muhamad Rias K. V. Zainuddin & Rossazana Ab-Rahim, 2023. "Does Renewable Energy Transition in the USA and China Overcome Environmental Degradation?," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 234-243, November.
    16. Yanming Sun & Shixian Liu & Lei Li, 2022. "Grey Correlation Analysis of Transportation Carbon Emissions under the Background of Carbon Peak and Carbon Neutrality," Energies, MDPI, vol. 15(9), pages 1-24, April.
    17. Ze Liang & Yueyao Wang & Jiao Huang & Feili Wei & Shuyao Wu & Jiashu Shen & Fuyue Sun & Shuangcheng Li, 2020. "Seasonal and Diurnal Variations in the Relationships between Urban Form and the Urban Heat Island Effect," Energies, MDPI, vol. 13(22), pages 1-19, November.
    18. Olja Čokorilo & Ivan Ivković & Snežana Kaplanović, 2019. "Prediction of Exhaust Emission Costs in Air and Road Transportation," Sustainability, MDPI, vol. 11(17), pages 1-18, August.
    19. Xiao, Huijuan & Duan, Zhiyuan & Zhou, Ya & Zhang, Ning & Shan, Yuli & Lin, Xiyan & Liu, Guosheng, 2019. "CO2 emission patterns in shrinking and growing cities: A case study of Northeast China and the Yangtze River Delta," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    20. Cai, Bofeng & Lu, Jun & Wang, Jinnan & Dong, Huijuan & Liu, Xiaoman & Chen, Yang & Chen, Zhanming & Cong, Jianhui & Cui, Zhipeng & Dai, Chunyan & Fang, Kai & Feng, Tong & Guo, Jie & Li, Fen & Meng, Fa, 2019. "A benchmark city-level carbon dioxide emission inventory for China in 2005," Applied Energy, Elsevier, vol. 233, pages 659-673.

    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:gam:jsusta:v:14:y:2022:i:15:p:9588-:d:880299. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.