IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i2p137-d490726.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/2/137/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/10/2/137/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. Li, Xi & Yu, Biying, 2019. "Peaking CO2 emissions for China's urban passenger transport sector," Energy Policy, Elsevier, vol. 133(C).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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.
    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. 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).
    2. Kajosaari, Anna & Hasanzadeh, Kamyar & Kyttä, Marketta, 2019. "Residential dissonance and walking for transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 134-144.
    3. David Hensher & Tu Ton, 2002. "TRESIS: A transportation, land use and environmental strategy impact simulator for urban areas," Transportation, Springer, vol. 29(4), pages 439-457, November.
    4. Phani Kumar, P. & Ravi Sekhar, Ch. & Parida, Manoranjan, 2018. "Residential dissonance in TOD neighborhoods," Journal of Transport Geography, Elsevier, vol. 72(C), pages 166-177.
    5. Cui, Yin & Li, Zhiyong & Sun, Yu & Sun, Weizheng, 2023. "Environmental performance of an urban passenger transport system and influencing factors: A case study of Tianjin, China," Utilities Policy, Elsevier, vol. 80(C).
    6. 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.
    7. 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.
    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. Rodier, Caroline J, 2000. "Uncertainty in Travel and Emissions Models: A Case Study in the Sacramento Region," University of California Transportation Center, Working Papers qt7cg7f9dd, University of California Transportation Center.
    10. Blanco, Hilda & Wikstrom, Alexander, 2018. "Transit-Oriented Development Opportunities Among Failing Malls," Institute of Transportation Studies, Working Paper Series qt3h62q04h, Institute of Transportation Studies, UC Davis.
    11. Áróra Árnadóttir & Michał Czepkiewicz & Jukka Heinonen, 2019. "The Geographical Distribution and Correlates of Pro-Environmental Attitudes and Behaviors in an Urban Region," Energies, MDPI, vol. 12(8), pages 1-29, April.
    12. Ji, Shujuan & Wang, Xin & Lyu, Tao & Liu, Xiaojie & Wang, Yuanqing & Heinen, Eva & Sun, Zhenwei, 2022. "Understanding cycling distance according to the prediction of the XGBoost and the interpretation of SHAP: A non-linear and interaction effect analysis," Journal of Transport Geography, Elsevier, vol. 103(C).
    13. Merlin, Louis A. & Levine, Jonathan & Grengs, Joe, 2018. "Accessibility analysis for transportation projects and plans," Transport Policy, Elsevier, vol. 69(C), pages 35-48.
    14. Michał Czepkiewicz & Áróra Árnadóttir & Jukka Heinonen, 2019. "Flights Dominate Travel Emissions of Young Urbanites," Sustainability, MDPI, vol. 11(22), pages 1-35, November.
    15. Jing Li & Kevin Lo & Meng Guo, 2018. "Do Socio-Economic Characteristics Affect Travel Behavior? A Comparative Study of Low-Carbon and Non-Low-Carbon Shopping Travel in Shenyang City, China," IJERPH, MDPI, vol. 15(7), pages 1-11, June.
    16. Petter Næss & Harpa Stefansdottir & Sebastian Peters & Michał Czepkiewicz & Jukka Heinonen, 2021. "Residential Location and Travel in the Reykjavik Capital Region," Sustainability, MDPI, vol. 13(12), pages 1-31, June.
    17. Timothy Welch & Sabyasachee Mishra, 2014. "Envisioning an emission diet: application of travel demand mechanisms to facilitate policy decision making," Transportation, Springer, vol. 41(3), pages 611-631, May.
    18. Rao, Fujie & Pafka, Elek, 2021. "Shopping morphologies of urban transit station areas: A comparative study of central city station catchments in Toronto, San Francisco, and Melbourne," Journal of Transport Geography, Elsevier, vol. 96(C).
    19. Nina Schwarz & Dagmar Haase & Ralf Seppelt, 2010. "Omnipresent Sprawl? A Review of Urban Simulation Models with Respect to Urban Shrinkage," Environment and Planning B, , vol. 37(2), pages 265-283, April.
    20. Bin Zhou & Kara Kockelman, 2008. "Neighborhood impacts on land use change: a multinomial logit model of spatial relationships," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 321-340, June.

    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:jlands:v:10:y:2021:i:2:p:137-:d:490726. 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.