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

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  • 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
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    References listed on IDEAS

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    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 & Zhang, Lixiao, 2014. "Urban CO2 emissions in China: Spatial boundary and performance comparison," Energy Policy, Elsevier, vol. 66(C), pages 557-567.
    4. 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.
    5. 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.
    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.
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