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Assessing CO 2 Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City

Author

Listed:
  • Xianchun Tan

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    John F. Kennedy School of Government, Harvard University, Cambridge, MA 02138, USA)

  • Tangqi Tu

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Department of City and Regional Planning, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA)

  • Baihe Gu

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China)

  • Yuan Zeng

    (School of Economics and Management, Harbin Institute of Technology, Shenzhen 518055, China
    Department of Urban Planning, Luskin School of Public Affairs, University of California Los Angeles, Los Angeles, CA 90095, USA)

  • Tianhang Huang

    (School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Qianqian Zhang

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
    School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

Assessing transport CO 2 emissions is important in the development of low-carbon strategies, but studies based on mixed land use are rare. This study assessed CO 2 emissions from passenger transport in traffic analysis zones (TAZs) at the community level, based on a combination of the mixed-use development model and the vehicle emission calculation model. Based on mixed land use and transport accessibility, the mixed-use development model was adopted to estimate travel demand, including travel modes and distances. As a leading low-carbon city project of international cooperation in China, Shenzhen International Low-Carbon City Core Area was chosen as a case study. The results clearly illustrate travel demand and CO 2 emissions of different travel modes between communities and show that car trips account for the vast majority of emissions in all types of travel modes in each community. Spatial emission differences are prominently associated with inadequately mixed land use layouts and unbalanced transport accessibility. The findings demonstrate the significance of the mixed land use and associated job-housing balance in reducing passenger CO 2 emissions from passenger transport, especially in per capita emissions. Policy implications are given based on the results to facilitate sophisticated transport emission control at a finer spatial scale. This new framework can be used for assessing the impacts of urban planning on transport emissions to promote sustainable urbanization in developing countries.

Suggested Citation

  • Xianchun Tan & Tangqi Tu & Baihe Gu & Yuan Zeng & Tianhang Huang & Qianqian Zhang, 2021. "Assessing CO 2 Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City," Land, MDPI, vol. 10(2), pages 1-19, February.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:2:p:137-:d:490726
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    References listed on IDEAS

    as
    1. Czepkiewicz, Michał & Ottelin, Juudit & Ala-Mantila, Sanna & Heinonen, Jukka & Hasanzadeh, Kamyar & Kyttä, Marketta, 2018. "Urban structural and socioeconomic effects on local, national and international travel patterns and greenhouse gas emissions of young adults," Journal of Transport Geography, Elsevier, vol. 68(C), pages 130-141.
    2. Stanley, John & Ellison, Richard & Loader, Chris & Hensher, David, 2018. "Reducing Australian motor vehicle greenhouse gas emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 76-88.
    3. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    4. Johnston, Robert A. & de la Barra, Tomas, 2000. "Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 125-136, February.
    5. Wang, Bo & Sun, Yefei & Chen, Qingxiang & Wang, Zhaohua, 2018. "Determinants analysis of carbon dioxide emissions in passenger and freight transportation sectors in China," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 127-132.
    6. Lades, Leonhard K. & Kelly, Andrew & Kelleher, Luke, 2020. "Why is active travel more satisfying than motorized travel? Evidence from Dublin," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 318-333.
    7. Johnston, Robert & de la Barra, Thomas, 2000. "Comprehensive Regional Modeling for Long-Range Planning: Linking Integrated Urban Models and Geographic Information Systems," Institute of Transportation Studies, Working Paper Series qt0f97v7sn, Institute of Transportation Studies, UC Davis.
    8. Xianchun Tan & Yuan Zeng & Baihe Gu & Yi Wang & Baoguang Xu, 2018. "Scenario Analysis of Urban Road Transportation Energy Demand and GHG Emissions in China—A Case Study for Chongqing," Sustainability, MDPI, vol. 10(6), pages 1-32, June.
    9. Espinosa Valderrama, Mónica & Cadena Monroy, Ángela Inés & Behrentz Valencia, Eduardo, 2019. "Challenges in greenhouse gas mitigation in developing countries: A case study of the Colombian transport sector," Energy Policy, Elsevier, vol. 124(C), pages 111-122.
    10. Zheng, Bo & Zhang, Qiang & Borken-Kleefeld, Jens & Huo, Hong & Guan, Dabo & Klimont, Zbigniew & Peters, Glen P. & He, Kebin, 2015. "How will greenhouse gas emissions from motor vehicles be constrained in China around 2030?," Applied Energy, Elsevier, vol. 156(C), pages 230-240.
    11. Zeng, Yuan & Tan, Xianchun & Gu, Baihe & Wang, Yi & Xu, Baoguang, 2016. "Greenhouse gas emissions of motor vehicles in Chinese cities and the implication for China’s mitigation targets," Applied Energy, Elsevier, vol. 184(C), pages 1016-1025.
    12. 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.
    13. Guang Tian & Reid Ewing & Rachel Weinberger & Kevin Shively & Preston Stinger & Shima Hamidi, 2017. "Trip and parking generation at transit-oriented developments: a case study of Redmond TOD, Seattle region," Transportation, Springer, vol. 44(5), pages 1235-1254, September.
    14. Li, Xi & Yu, Biying, 2019. "Peaking CO2 emissions for China's urban passenger transport sector," Energy Policy, Elsevier, vol. 133(C).
    15. Guzman, Luis A. & Peña, Javier & Carrasco, Juan Antonio, 2020. "Assessing the role of the built environment and sociodemographic characteristics on walking travel distances in Bogotá," Journal of Transport Geography, Elsevier, vol. 88(C).
    16. David Simmonds, 2001. "The Objectives and Design of a New Land-use Modelling Package: DELTA," Advances in Spatial Science, in: Graham Clarke & Moss Madden (ed.), Regional Science in Business, chapter 9, pages 159-188, Springer.
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