IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i17p7873-d1739684.html

Analyzing Integrated Carbon Emissions from Regional Transport and Land Use in the Context of National Spatial Planning

Author

Listed:
  • Weiwei Liu

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

  • Xiuhong Zhang

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

  • Yangyang Zhu

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

  • Xiaomei Li

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

  • Liang Jin

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

  • Sijie Hu

    (Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China)

Abstract

Against the backdrop of intensified governance of territorial spatial planning, investigating carbon emissions from the perspective of territorial spatial planning for transport-land use integration holds significant academic and practical value. Taking Cangnan County as the case study, this research first dissects the reciprocal feedback mechanism between regional transport and land use at the territorial spatial planning level, while exploring transport-influencing factors. Subsequently, it constructs an integrated reciprocal feedback system for regional transport and land use by integrating accessibility drivers, cost matrices, and neighborhood weights through land use simulation–prediction models and the four-stage transport model. Finally, based on critical land use factors, diverse development scenarios under this integrated system are formulated; carbon emissions from transport and land use under each scenario are quantified; and their interrelationships are analyzed across multiple dimensions to explore the nexus of carbon emissions in transport–land use integration. Results indicate the following: (1) Integrated feedback enhances model accuracy (Kappa: 0.795→0.893; overall accuracy: 0.893→0.915), facilitating more precise land use simulation. (2) The county’s core construction area demonstrates the highest carbon emissions across all scenarios, meriting prioritized attention. (3) As deduced from the analysis of territorial spatial land use patterns, the significantly higher transport carbon emissions under the ecological protection priority scenario, compared to other scenarios, originate from over-concentrated construction land and imbalanced planning of carbon source land. These findings offer insights for regional planning; policy recommendations for Cangnan County include expanding carbon sink land, scientifically planning carbon source land, optimizing transport structures, and promoting new energy vehicles to advance carbon emission reduction and sustainable development.

Suggested Citation

  • Weiwei Liu & Xiuhong Zhang & Yangyang Zhu & Xiaomei Li & Liang Jin & Sijie Hu, 2025. "Analyzing Integrated Carbon Emissions from Regional Transport and Land Use in the Context of National Spatial Planning," Sustainability, MDPI, vol. 17(17), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:7873-:d:1739684
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/17/7873/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/17/7873/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhe Gao & Jianming Ye & Xianwei Zhu & Miaomiao Li & Haijiang Wang & Mengmeng Zhu, 2024. "Characteristics of Spatial Correlation Network Structure and Carbon Balance Zoning of Land Use Carbon Emission in the Tarim River Basin," Land, MDPI, vol. 13(11), pages 1-19, November.
    2. Su, Hailong & Wu, Jia Hao & Tan, Yinghui & Bao, Yuanqiu & Song, Bing & He, Xinghua, 2014. "A land use and transportation integration method for land use allocation and transportation strategies in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 329-353.
    3. Lu Han & Yanbo Qu & Shufeng Liang & Luyan Shi & Min Zhang & Haiyan Jia, 2024. "Spatiotemporal Differentiation of Land Ecological Security and Optimization Based on GeoSOS-FLUS Model: A Case Study of the Yellow River Delta in China Toward Sustainability," Land, MDPI, vol. 13(11), pages 1-21, November.
    4. Qiu, Ai-Ya & Yue, Heng & You, Ze & An, Hao, 2025. "Forecasting of factors influencing carbon emission from land-use in Liaoning Province, China, under the “double carbon” target," Ecological Modelling, Elsevier, vol. 509(C).
    5. Sarri, Paraskevi & Kaparias, Ioannis & Preston, John & Simmonds, David, 2023. "Using Land Use and Transportation Interaction (LUTI) models to determine land use effects from new vehicle transportation technologies; a regional scale of analysis," Transport Policy, Elsevier, vol. 135(C), pages 91-111.
    6. Ivan Muñiz & Andrés Dominguez, 2020. "The Impact of Urban Form and Spatial Structure on per Capita Carbon Footprint in U.S. Larger Metropolitan Areas," Sustainability, MDPI, vol. 12(1), pages 1-19, January.
    7. Feng, Kuishuang & Hubacek, Klaus & Guan, Dabo, 2009. "Lifestyles, technology and CO2 emissions in China: A regional comparative analysis," Ecological Economics, Elsevier, vol. 69(1), pages 145-154, November.
    8. Ying, Jiang Qian, 2024. "Optimization of regulation and fiscal policies for urban residential land use and traffic network management," Regional Science and Urban Economics, Elsevier, vol. 105(C).
    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. Daví-Arderius, Daniel & Sanin, María-Eugenia & Trujillo-Baute, Elisa, 2017. "CO2 content of electricity losses," Energy Policy, Elsevier, vol. 104(C), pages 439-445.
    2. Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    3. Ling Yang & Michael L. Lahr, 2019. "The Drivers of China’s Regional Carbon Emission Change—A Structural Decomposition Analysis from 1997 to 2007," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    4. Ge, Zewen & Geng, Yong & Wei, Wendong & Jiang, Mingkun & Chen, Bin & Li, Jiashuo, 2023. "Embodied carbon emissions induced by the construction of hydropower infrastructure in China," Energy Policy, Elsevier, vol. 173(C).
    5. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    6. Meng, Bo & Wang, Jianguo & Andrew, Robbie & Xiao, Hao & Xue, Jinjun & Peters, Glen P., 2017. "Spatial spillover effects in determining China's regional CO2 emissions growth: 2007–2010," Energy Economics, Elsevier, vol. 63(C), pages 161-173.
    7. Yanbin Li & Zhen Li & Min Wu & Feng Zhang & Gejirifu De, 2018. "Regional-Level Allocation of CO 2 Emission Permits in China: Evidence from the Boltzmann Distribution Method," Sustainability, MDPI, vol. 10(8), pages 1-16, July.
    8. Karlsson, Rasmus, 2012. "Carbon lock-in, rebound effects and China at the limits of statism," Energy Policy, Elsevier, vol. 51(C), pages 939-945.
    9. Lindner, Soeren & Liu, Zhu & Guan, Dabo & Geng, Yong & Li, Xin, 2013. "CO2 emissions from China’s power sector at the provincial level: Consumption versus production perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 164-172.
    10. Huaide Wen & Jun Dai, 2021. "The Change of Sources of Growth and Sustainable Development in China: Based on the Extended EKC Explanation," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    11. Li, Zheng & Zeng, Jingjing & Hensher, David A. & Wu, Chenyang, 2025. "Travel time reliability, psychological choice mechanisms, sustainable transport decisions and smart urban development," Transportation Research Part A: Policy and Practice, Elsevier, vol. 200(C).
    12. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    13. Xiaoxia Shi & Haiyun Liu & Joshua Sunday Riti, 2019. "The role of energy mix and financial development in greenhouse gas (GHG) emissions’ reduction: evidence from ten leading CO2 emitting countries," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 36(3), pages 695-729, October.
    14. Shao, Shuai & Yang, Lili & Yu, Mingbo & Yu, Mingliang, 2011. "Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009," Energy Policy, Elsevier, vol. 39(10), pages 6476-6494, October.
    15. Huijie Yan & Mateo Cordier & Takuro Uehara, 2024. "Future Projections of Global Plastic Pollution: Scenario Analyses and Policy Implications," Sustainability, MDPI, vol. 16(2), pages 1-18, January.
    16. Yuling Sun & Junsong Jia & Min Ju & Chundi Chen, 2022. "Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression," Land, MDPI, vol. 11(7), pages 1-26, July.
    17. Xinshuo Hou, 2022. "Can Public–Private Partnership Wastewater Treatment Projects Help Reduce Urban Sewage Disposal? Empirical Evidence from 267 Cities in China," IJERPH, MDPI, vol. 19(12), pages 1-24, June.
    18. Shigetomi, Yosuke & Matsumoto, Ken'ichi & Ogawa, Yuki & Shiraki, Hiroto & Yamamoto, Yuki & Ochi, Yuki & Ehara, Tomoki, 2018. "Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan," Applied Energy, Elsevier, vol. 228(C), pages 2321-2332.
    19. Safdar, Muhammad & Zhong, Ming & Ren, Zhi & Li, Linfeng & Raza, Asif & Hunt, John Douglas, 2026. "An integrated spatial economic modeling framework for forecasting inland waterway freight demand," Transport Policy, Elsevier, vol. 176(C).
    20. Shao, Shuai & Huang, Tao & Yang, Lili, 2014. "Using latent variable approach to estimate China׳s economy-wide energy rebound effect over 1954–2010," Energy Policy, Elsevier, vol. 72(C), pages 235-248.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:17:y:2025:i:17:p:7873-:d:1739684. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.