IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i21p13786-d951158.html
   My bibliography  Save this article

Characterizing Carbon Emissions and the Associations with Socio-Economic Development in Chinese Cities

Author

Listed:
  • Zijie Shen

    (School of Economics & Management, Fuzhou University, No. 2 Wulongjiangbei Avenue, Minhou Country, Fuzhou 350116, China)

  • Liguo Xin

    (School of Management, Shandong University, 27 Shanda Nanlu, Jinan 250100, China)

Abstract

Reducing carbon emissions in cities is crucial for addressing climate change, while the city-level emissions of different compositions and their relationships with socio-economic features remain largely unknown in China. Here, we explored the city-level emission pattern from the industrial, transportation, and household sectors and the emission intensity, as well as their associations with socio-economic features in China, using the up-to-date (2020) CO 2 emissions based on 0.1° grid (10 × 10 km) emission data. The results show that: (1) CO 2 emissions from the industrial sector were considerably dominant (78%), followed by indirect (10%), transportation (8%), and household (2%) emissions on the national scale; (2) combining total emissions with emission intensity, high emission–high intensity cities, which are the most noteworthy regions, were concentrated in the North, while low emission–low intensity types mainly occurred in the South-West; (3) cities with a higher GDP tend to emit more CO 2 , while higher-income cities tend to emit less CO 2 , especially from the household sector. Cities with a developed economy, as indicated by GDP and income, would have low emissions per GDP, representing a high emission efficiency. Reducing the proportion of the secondary sector of the economy could significantly decrease CO 2 emissions, especially for industrial cities. Therefore, the carbon reduction policy in China should focus on the industrial cities in the North with high emission–high intensity performance. Increasing the income and proportion of the tertiary industry and encouraging compact cities can effectively reduce the total emissions during the economic development and urbanization process.

Suggested Citation

  • Zijie Shen & Liguo Xin, 2022. "Characterizing Carbon Emissions and the Associations with Socio-Economic Development in Chinese Cities," IJERPH, MDPI, vol. 19(21), pages 1-11, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:21:p:13786-:d:951158
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/21/13786/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/21/13786/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Jinying & Li, Sisi, 2020. "Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model," Energy Policy, Elsevier, vol. 140(C).
    2. Kaika, Dimitra & Zervas, Efthimios, 2013. "The Environmental Kuznets Curve (EKC) theory—Part A: Concept, causes and the CO2 emissions case," Energy Policy, Elsevier, vol. 62(C), pages 1392-1402.
    3. Jinfeng Chang & Philippe Ciais & Thomas Gasser & Pete Smith & Mario Herrero & Petr Havlík & Michael Obersteiner & Bertrand Guenet & Daniel S. Goll & Wei Li & Victoria Naipal & Shushi Peng & Chunjing Q, 2021. "Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    4. Yu, Shiwei & Zheng, Shuhong & Li, Xia, 2018. "The achievement of the carbon emissions peak in China: The role of energy consumption structure optimization," Energy Economics, Elsevier, vol. 74(C), pages 693-707.
    5. Wu, Jianxin & Ma, Chunbo & Tang, Kai, 2019. "The static and dynamic heterogeneity and determinants of marginal abatement cost of CO2 emissions in Chinese cities," Energy, Elsevier, vol. 178(C), pages 685-694.
    6. Xueli Wang & Caizhi Sun & Song Wang & Zhixiong Zhang & Wei Zou, 2018. "Going Green or Going Away? A Spatial Empirical Examination of the Relationship between Environmental Regulations, Biased Technological Progress, and Green Total Factor Productivity," IJERPH, MDPI, vol. 15(9), pages 1-23, September.
    7. Xu, Li & Zhang, Qin & Shi, Xunpeng, 2019. "Stakeholders strategies in poverty alleviation and clean energy access: A case study of China's PV poverty alleviation program," Energy Policy, Elsevier, vol. 135(C).
    8. Jin, Gui & Guo, Baishu & Deng, Xiangzheng, 2020. "Is there a decoupling relationship between CO2 emission reduction and poverty alleviation in China?," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    9. Jalil, Abdul & Mahmud, Syed F., 2009. "Environment Kuznets curve for CO2 emissions: A cointegration analysis for China," Energy Policy, Elsevier, vol. 37(12), pages 5167-5172, December.
    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. Qikang Zhong & Zhe Li & Yujing He, 2023. "Coupling Evaluation and Spatial–Temporal Evolution of Land Ecosystem Services and Economic–Social Development in a City Group: The Case Study of the Chengdu–Chongqing City Group," IJERPH, MDPI, vol. 20(6), pages 1-29, March.

    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. Maxwell Kongkuah & Hongxing Yao & Veli Yilanci, 2022. "The relationship between energy consumption, economic growth, and CO2 emissions in China: the role of urbanisation and international trade," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 4684-4708, April.
    2. Shahbaz, Muhammad & Haouas, Ilham & Hoang, Thi Hong Van, 2019. "Economic growth and environmental degradation in Vietnam: Is the environmental Kuznets curve a complete picture?," Emerging Markets Review, Elsevier, vol. 38(C), pages 197-218.
    3. Shokoohi, Zeinab & Dehbidi, Navid Kargar & Tarazkar, Mohammad Hassan, 2022. "Energy intensity, economic growth and environmental quality in populous Middle East countries," Energy, Elsevier, vol. 239(PC).
    4. Barra, Cristian & Zotti, Roberto, 2016. "Investigating the impact of national income on environmental pollution. International evidence," MPRA Paper 74149, University Library of Munich, Germany.
    5. Nghiem, Son & Tran, Bach & Afoakwah, Clifford & Byrnes, Joshua & Scuffham, Paul, 2021. "Wealthy, healthy and green: Are we there yet?," World Development, Elsevier, vol. 147(C).
    6. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2017. "Carbon Dioxide Emissions and Economic Growth: An Assessment Based on Production and Consumption Emission Inventories," Ecological Economics, Elsevier, vol. 135(C), pages 269-279.
    7. Yanli Ji & Jie Xue, 2022. "Decoupling Effect of County Carbon Emissions and Economic Growth in China: Empirical Evidence from Jiangsu Province," IJERPH, MDPI, vol. 19(6), pages 1-22, March.
    8. Ben Lahouel, Béchir & Taleb, Lotfi & Ben Zaied, Younes & Managi, Shunsuke, 2021. "Does ICT change the relationship between total factor productivity and CO2 emissions? Evidence based on a nonlinear model," Energy Economics, Elsevier, vol. 101(C).
    9. Gopinathan Satheedevi, Amrutha & Sharma, Abhibhav & Dhar, Murali, 2022. "How do the anthropogenic factors affect the environment in India? Evidence from the urban provinces," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    10. Sun, Huaping & Samuel, Clottey Attuquaye & Kofi Amissah, Joshua Clifford & Taghizadeh-Hesary, Farhad & Mensah, Isaac Adjei, 2020. "Non-linear nexus between CO2 emissions and economic growth: A comparison of OECD and B&R countries," Energy, Elsevier, vol. 212(C).
    11. Goher-Ur-Rehman Mir & Servaas Storm, 2016. "Carbon Emissions and Economic Growth: Production-based versus Consumption-based Evidence on Decoupling," Working Papers Series 41, Institute for New Economic Thinking.
    12. Yang, Zikun & Zhang, Mingming & Liu, Liyun & Zhou, Dequn, 2022. "Can renewable energy investment reduce carbon dioxide emissions? Evidence from scale and structure," Energy Economics, Elsevier, vol. 112(C).
    13. Shahbaz, Muhammad & Shafiullah, Muhammad & Khalid, Usman & Song, Malin, 2020. "A nonparametric analysis of energy environmental Kuznets Curve in Chinese Provinces," Energy Economics, Elsevier, vol. 89(C).
    14. Liu, Fengqi & Kang, Yuxin & Guo, Kun, 2022. "Is electricity consumption of Chinese counties decoupled from carbon emissions? A study based on Tapio decoupling index," Energy, Elsevier, vol. 251(C).
    15. Zhang, Qianxue & Liao, Hua & Hao, Yu, 2018. "Does one path fit all? An empirical study on the relationship between energy consumption and economic development for individual Chinese provinces," Energy, Elsevier, vol. 150(C), pages 527-543.
    16. Yan, Bin & Wang, Feng & Dong, Mingru & Ren, Jing & Liu, Juan & Shan, Jing, 2022. "How do financial spatial structure and economic agglomeration affect carbon emission intensity? Theory extension and evidence from China," Economic Modelling, Elsevier, vol. 108(C).
    17. Zhao, Jing & Zhao, Ziru & Zhang, Huan, 2021. "The impact of growth, energy and financial development on environmental pollution in China: New evidence from a spatial econometric analysis," Energy Economics, Elsevier, vol. 93(C).
    18. Balado-Naves, Roberto & Baños-Pino, José Francisco & Mayor, Matías, 2018. "Do countries influence neighbouring pollution? A spatial analysis of the EKC for CO2 emissions," Energy Policy, Elsevier, vol. 123(C), pages 266-279.
    19. Bölük, Gülden & Mert, Mehmet, 2015. "The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 587-595.
    20. Ma, Rufei & Deng, Liqian & Ji, Qiang & Zhai, Pengxiang, 2022. "Environmental regulations, clean energy access, and household energy poverty: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    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:19:y:2022:i:21:p:13786-:d:951158. 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.