IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i2p291-d1580287.html
   My bibliography  Save this article

Carbon Emission Status and Regional Differences of China: High-Resolution Estimation of Spatially Explicit Carbon Emissions at the Prefecture Level

Author

Listed:
  • Jinwei Guo

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China
    Department of Pharmacy, Changzhi Medical College, Changzhi 046000, China)

  • Yanbing Qi

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China)

  • Jiaqi Luo

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China)

  • Guohong Du

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China)

  • Jingyan Sun

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China)

  • Xin Wei

    (College of Humanities & Social Development, Northwest A&F University, Yangling, Xianyang 712100, China)

  • Mukesh Kumar Soothar

    (College of Natural Resources and Environment, Northwest A&F University, Yangling, Xianyang 712100, China)

Abstract

There are disagreements regarding the accuracy of estimation and spatial distribution of carbon emissions in China. It is of great significance to estimate a more detailed carbon emission inventory for China and analyze the carbon emission characteristics of different regions. This study comprehensively estimated carbon dioxide and methane emissions (and their spatial distributions) across eight carbon-emitting sectors in 360 prefecture-level cities in China in 2020. The results indicated that total carbon emissions in China amounted to 146.00 × 10 8 t, with carbon dioxide and methane accounting for 95.87% and 4.13%, respectively. The industrial sector was the main source of carbon emissions, accounting for 75.42% of the total. The North China Plain, the Northeast Plain, and the Sichuan Basin were identified as the carbon emission hotspot areas with the most intensive carbon emission densities. Among the clustered four carbon emission zones based on carbon emission density and economic carbon intensity, the High Carbon Emission Density and High Economic Carbon Intensity zones accounted for 41.73% of total carbon emissions. To achieve carbon neutrality, it is essential to devise emission reduction strategies for specific areas by thoroughly considering spatially explicit variation at the prefecture level, with a focus on primary carbon-emitting cities and sectors.

Suggested Citation

  • Jinwei Guo & Yanbing Qi & Jiaqi Luo & Guohong Du & Jingyan Sun & Xin Wei & Mukesh Kumar Soothar, 2025. "Carbon Emission Status and Regional Differences of China: High-Resolution Estimation of Spatially Explicit Carbon Emissions at the Prefecture Level," Land, MDPI, vol. 14(2), pages 1-27, January.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:291-:d:1580287
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/2/291/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/14/2/291/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shahbaz, Muhammad & Zakaria, Muhammad & Shahzad, Syed Jawad Hussain & Mahalik, Mantu Kumar, 2018. "The energy consumption and economic growth nexus in top ten energy-consuming countries: Fresh evidence from using the quantile-on-quantile approach," Energy Economics, Elsevier, vol. 71(C), pages 282-301.
    2. Qing Li & Kaili Peng & Peng Cheng, 2021. "Community-Level Urban Green Space Equity Evaluation Based on Spatial Design Network Analysis (sDNA): A Case Study of Central Wuhan, China," IJERPH, MDPI, vol. 18(19), pages 1-18, September.
    3. Cai, Bofeng & Guo, Huanxiu & Ma, Zipeng & Wang, Zhixuan & Dhakal, Shobhakar & Cao, Libin, 2019. "Benchmarking carbon emissions efficiency in Chinese cities: A comparative study based on high-resolution gridded data," Applied Energy, Elsevier, vol. 242(C), pages 994-1009.
    4. Chen, Qianli & Cai, Bofeng & Dhakal, Shobhakar & Pei, Sha & Liu, Chunlan & Shi, Xiaoping & Hu, Fangfang, 2017. "CO2 emission data for Chinese cities," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 198-208.
    5. Cai, Bofeng & Zhang, Lixiao, 2014. "Urban CO2 emissions in China: Spatial boundary and performance comparison," Energy Policy, Elsevier, vol. 66(C), pages 557-567.
    6. Haojia Kong & Lifan Shi & Dan Da & Zhijiang Li & Decai Tang & Wei Xing, 2022. "Simulation of China’s Carbon Emission based on Influencing Factors," Energies, MDPI, vol. 15(9), pages 1-15, April.
    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. Cai, Bofeng & Liu, Helin & Zhang, Xiaoling & Pan, Haozhi & Zhao, Mengxue & Zheng, Tianming & Nie, Jingxin & Du, Mengbing & Dhakal, Shobhakar, 2022. "High-resolution accounting of urban emissions in China," Applied Energy, Elsevier, vol. 325(C).
    2. Li, Xiang & Cheng, Zhonghua, 2022. "Does high-speed rail improve urban carbon emission efficiency in China?," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    3. Hou, Mengyang & Cui, Xuehua & Chu, Liqi & Wang, He & Xi, Zenglei & Deng, Yuanjie, 2024. "Nonlinear effects of environmental regulation on PM2.5 and CO2 in China: Evidence from a quantile-on-quantile approach," Energy, Elsevier, vol. 292(C).
    4. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    5. Cui, Can & Wang, Zhen & Cai, Bofeng & Peng, Sha & Wang, Yang & Xu, Chengdong, 2021. "Evolution-based CO2 emission baseline scenarios of Chinese cities in 2025," Applied Energy, Elsevier, vol. 281(C).
    6. Zhang, Hao & Cai, Guixin & Yang, Dongxiao, 2020. "The impact of oil price shocks on clean energy stocks: Fresh evidence from multi-scale perspective," Energy, Elsevier, vol. 196(C).
    7. Huan Zhou & Shaojian Qu & Qinglu Yuan & Shilei Wang, 2020. "Spatial Effects and Nonlinear Analysis of Energy Consumption, Financial Development, and Economic Growth in China," Energies, MDPI, vol. 13(18), pages 1-18, September.
    8. Dong, Kangyin & Dong, Xiucheng & Jiang, Qingzhe & Zhao, Jun, 2021. "Assessing energy resilience and its greenhouse effect: A global perspective," Energy Economics, Elsevier, vol. 104(C).
    9. Xiu Liu & Zhuo He & Zixin Deng & Sandeep Poddar, 2024. "Analysis of Spatiotemporal Disparities and Spatial Spillover Effect of a Low-Carbon Economy in Chinese Provinces Under Green Technology Innovation," Sustainability, MDPI, vol. 16(21), pages 1-19, October.
    10. Muhammad Umar & Abraham Ayobamiji Awosusi & Oluwatayomi Rereloluwa Adegboye & Opeoluwa Seun Ojekemi, 2024. "Geothermal energy and carbon emissions nexus in leading geothermal-consuming nations: Evidence from nonparametric analysis," Energy & Environment, , vol. 35(5), pages 2726-2752, August.
    11. Wang, Xiuli, 2023. "Exploring the role of resource industry dependence and green finance in green development efficiency in the context of post-Covid-19 period," Resources Policy, Elsevier, vol. 85(PB).
    12. Ghosh, Sourav & Yadav, Sarita & Devi, Ambika & Thomas, Tiju, 2022. "Techno-economic understanding of Indian energy-storage market: A perspective on green materials-based supercapacitor technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    13. Ziheng Niu & Jianliang Xiong & Xuesong Ding & Yao Wu, 2022. "Analysis of China’s Carbon Peak Achievement in 2025," Energies, MDPI, vol. 15(14), pages 1-18, July.
    14. Xiaofeng Lv & Kun Lin & Lingshan Chen & Yongzhong Zhang, 2022. "Does Retirement Affect Household Energy Consumption Structure? Evidence from a Regression Discontinuity Design," Sustainability, MDPI, vol. 14(19), pages 1-14, September.
    15. Assem Urekeshova & Zhibek Rakhmetulina & Igor Dubina & Sergey Evgenievich Barykin & Angela Bahauovna Mottaeva & Shakizada Uteulievna Niyazbekova, 2023. "The Impact of Digital Finance on Clean Energy and Green Bonds through the Dynamics of Spillover," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 441-452, March.
    16. Zhu, Huiming & Chen, Yiwen & Ren, Yinghua & Xing, Zhanming & Hau, Liya, 2022. "Time-frequency causality and dependence structure between crude oil, EPU and Chinese industry stock: Evidence from multiscale quantile perspectives," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    17. Magazzino, Cosimo & Drago, Carlo & Schneider, Nicolas, 2023. "Evidence of supply security and sustainability challenges in Nigeria’s power sector," Utilities Policy, Elsevier, vol. 82(C).
    18. Sheilla Nyasha & Yvonne Gwenhure & Nicholas M Odhiambo, 2018. "Energy consumption and economic growth in Ethiopia: A dynamic causal linkage," Energy & Environment, , vol. 29(8), pages 1393-1412, December.
    19. Haseeb, Muhammad & Haouas, Ilham & Nasih, Mohammad & Mihardjo, Leonardus WW. & Jermsittiparsert, Kittisak, 2020. "Asymmetric impact of textile and clothing manufacturing on carbon-dioxide emissions: Evidence from top Asian economies," Energy, Elsevier, vol. 196(C).
    20. Lijiali Huang & Xueqiong Wang & Yanwen Sheng & Jinli Zhao, 2025. "Impact of Venture Capital on Urban Carbon Emissions: Evidence from the Yangtze River Delta Urban Agglomeration in China," Sustainability, MDPI, vol. 17(2), pages 1-25, January.

    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:14:y:2025:i:2:p:291-:d:1580287. 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.