IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p4023-d1078656.html
   My bibliography  Save this article

Spatial Zoning of Carbon Dioxide Emissions at the Intra-City Level: A Case Study of Nanjing, China

Author

Listed:
  • Yuan Yuan

    (School of Public Administration, Hohai University, Nanjing 211100, China)

  • Ping Xu

    (School of Public Administration, Hohai University, Nanjing 211100, China)

  • Hui Zhang

    (Department of Land Planning, China Land Surveying and Planning Institute, Beijing 100035, China)

Abstract

With ever-increasing urbanization and industrialization in developing countries, the challenge posed by carbon dioxide emissions (CDEs) has become a hot topic of concern in the realm of sustainable development from a socioeconomic perspective. However, previous studies have only been conducted at macro and meso scales, including at the global, country, and urban levels, and few researchers have delved into the territorial space of urban areas due to a lack of high-precision data. To address this deficiency, we established a theoretical framework to explore the spatial zoning of CDEs based on the newly emerging China high-resolution emission gridded data (CHRED). This study’s innovativeness lies in its provision of a step-by-step process for spatial matching of CDEs based on CHRED in the framework and the construction of square layers to reveal spatial heterogeneity of CDEs at the intra-city level. Taking Nanjing City as the case study area, our findings indicated that CDEs intensity (CDEI) shows an inverted “U-shaped” trend that first increased and then decreased, and finally stabilized from the center to the periphery of the city. With further urbanization and industrialization, the energy consumption sector was found to be the largest contributor to CDEs in Nanjing, and the expanding carbon source zonings will therefore shrink the existing carbon sink zonings. Collectively, these results can provide a scientific reference point to realize China’s “dual carbon” target from the perspective of spatial layout optimization.

Suggested Citation

  • Yuan Yuan & Ping Xu & Hui Zhang, 2023. "Spatial Zoning of Carbon Dioxide Emissions at the Intra-City Level: A Case Study of Nanjing, China," IJERPH, MDPI, vol. 20(5), pages 1-19, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4023-:d:1078656
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/4023/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/5/4023/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    2. Zhang, Ning & Yu, Keren & Chen, Zhongfei, 2017. "How does urbanization affect carbon dioxide emissions? A cross-country panel data analysis," Energy Policy, Elsevier, vol. 107(C), pages 678-687.
    3. Henderson, J. Vernon & Nigmatulina, Dzhamilya & Kriticos, Sebastian, 2021. "Measuring urban economic density," Journal of Urban Economics, Elsevier, vol. 125(C).
    4. Al-mulali, Usama, 2012. "Factors affecting CO2 emission in the Middle East: A panel data analysis," Energy, Elsevier, vol. 44(1), pages 564-569.
    5. Xu, Bin & Lin, Boqiang, 2015. "How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models," Energy Economics, Elsevier, vol. 48(C), pages 188-202.
    6. Yuan Yuan & Wentao Zhao & Hongqing Li & Han Mu, 2022. "Analyzing the Driving Mechanism of Rural Transition from the Perspective of Rural–Urban Continuum: A Case Study of Suzhou, China," Land, MDPI, vol. 11(8), pages 1-17, July.
    7. Shafiei, Sahar & Salim, Ruhul A., 2014. "Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis," Energy Policy, Elsevier, vol. 66(C), pages 547-556.
    8. Shan, Yuli & Liu, Jianghua & Liu, Zhu & Xu, Xinwanghao & Shao, Shuai & Wang, Peng & Guan, Dabo, 2016. "New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors," Applied Energy, Elsevier, vol. 184(C), pages 742-750.
    9. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    10. Zhicong Zhang & Hao Xie & Jubing Zhang & Xinye Wang & Jiayu Wei & Xibin Quan, 2022. "Prediction and Trend Analysis of Regional Industrial Carbon Emission in China: A Study of Nanjing City," IJERPH, MDPI, vol. 19(12), pages 1-23, June.
    11. Cai, Bofeng & Wang, Jinnan & He, Jie & Geng, Yong, 2016. "Evaluating CO2 emission performance in China’s cement industry: An enterprise perspective," Applied Energy, Elsevier, vol. 166(C), pages 191-200.
    12. Liu, Qianqian & Wang, Shaojian & Zhang, Wenzhong & Li, Jiaming & Kong, Yunlong, 2019. "Examining the effects of income inequality on CO2 emissions: Evidence from non-spatial and spatial perspectives," Applied Energy, Elsevier, vol. 236(C), pages 163-171.
    13. Bi, Jun & Zhang, Rongrong & Wang, Haikun & Liu, Miaomiao & Wu, Yi, 2011. "The benchmarks of carbon emissions and policy implications for China's cities: Case of Nanjing," Energy Policy, Elsevier, vol. 39(9), pages 4785-4794, September.
    14. Qianru Chen & Hualin Xie, 2019. "Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China," Land, MDPI, vol. 8(11), pages 1-17, October.
    15. Kong-Qing Li & Ran Lu & Rui-Wen Chu & Dou-Dou Ma & Li-Qun Zhu, 2018. "Trends and Driving Forces of Carbon Emissions from Energy Consumption: A Case Study of Nanjing, China," Sustainability, MDPI, vol. 10(12), pages 1-13, November.
    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. Yi Xiao & Yuantao Liao & Zhe Li & Zhuojun Li & Shaojian Wang, 2023. "Impacts of Land Urbanization on CO 2 Emissions: Policy Implications Based on Developmental Stages," Land, MDPI, vol. 12(10), pages 1-15, October.
    2. Wang, Wei-Zheng & Liu, Lan-Cui & Liao, Hua & Wei, Yi-Ming, 2021. "Impacts of urbanization on carbon emissions: An empirical analysis from OECD countries," Energy Policy, Elsevier, vol. 151(C).
    3. Bo Yang & Minhaj Ali & Shujahat Haider Hashmi & Mohsin Shabir, 2020. "Income Inequality and CO 2 Emissions in Developing Countries: The Moderating Role of Financial Instability," Sustainability, MDPI, vol. 12(17), pages 1-24, August.
    4. 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.
    5. Niu, Honglei & Lekse, William, 2017. "Carbon emission effect of urbanization at regional level: Empirical evidence from China," Economics Discussion Papers 2017-62, Kiel Institute for the World Economy (IfW Kiel).
    6. Niu, Honglei & Lekse, William, 2018. "Carbon emission effect of urbanization at regional level: Empirical evidence from China," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-31.
    7. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    8. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    9. Wei, Honghong & Lahiri, Radhika, 2022. "Urbanization, energy-use intensity and emissions: A sectoral approach," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 667-684.
    10. Yan, Yu & Huang, Junbing, 2022. "The role of population agglomeration played in China's carbon intensity: A city-level analysis," Energy Economics, Elsevier, vol. 114(C).
    11. Yixi Xue & Jie Ren & Xiaohang Bi, 2019. "Impact of Influencing Factors on CO 2 Emissions in the Yangtze River Delta during Urbanization," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
    12. Shen, Neng & Peng, Hui, 2021. "Can industrial agglomeration achieve the emission-reduction effect?," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    13. Zhibo Zhao & Tian Yuan & Xunpeng Shi & Lingdi Zhao, 2020. "Heterogeneity in the relationship between carbon emission performance and urbanization: evidence from China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1363-1380, October.
    14. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
    15. Lapatinas, Athanasios & Garas, Antonios & Boleti, Eirini & Kyriakou, Alexandra, 2019. "Economic complexity and environmental performance: Evidence from a world sample," MPRA Paper 92833, University Library of Munich, Germany.
    16. Pengyan Zhang & Jianjian He & Xin Hong & Wei Zhang & Chengzhe Qin & Bo Pang & Yanyan Li & Yu Liu, 2017. "Regional-Level Carbon Emissions Modelling and Scenario Analysis: A STIRPAT Case Study in Henan Province, China," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    17. Maxwell Chukwudi Udeagha & Marthinus Christoffel Breitenbach, 2023. "Revisiting the nexus between fiscal decentralization and CO2 emissions in South Africa: fresh policy insights," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-46, December.
    18. Wang, Shaojian & Xie, Zihan & Wu, Rong & Feng, Kuishang, 2022. "How does urbanization affect the carbon intensity of human well-being? A global assessment," Applied Energy, Elsevier, vol. 312(C).
    19. Zhonghua Cheng & Xiaowen Hu, 2023. "The effects of urbanization and urban sprawl on CO2 emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1792-1808, February.
    20. Li, Kunming & Fang, Liting & He, Lerong, 2019. "How population and energy price affect China's environmental pollution?," Energy Policy, Elsevier, vol. 129(C), pages 386-396.

    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:jijerp:v:20:y:2023:i:5:p:4023-:d:1078656. 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.