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Location-specific co-benefits of carbon emissions reduction from coal-fired power plants in China

Author

Listed:
  • Pu Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Cheng-Kuan Lin

    (Harvard T.H. Chan School of Public Health
    Massachusetts College of Pharmacy and Health Sciences)

  • Yi Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dachuan Liu

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dunjiang Song

    (Chinese Academy of Sciences)

  • Tong Wu

    (Chinese Academy of Sciences)

Abstract

Climate policies that achieve air quality co-benefits can better align developing countries’ national interests with global climate mitigation. Since the effects of air pollutants are highly dependent on source locations, spatially nuanced policies are crucial to maximizing the achievement of co-benefits. Using the coal power industry as a case study, this study presents an interdisciplinary approach to assessing facility level co-benefits at every specific source location in China. We find that co-benefits range from US$51-$278 per ton CO2 reduction nationwide and are highly heterogeneous spatially, with “hotspot” regions that should be the priority of emissions reduction policies, and that provinces should use different techno-economic strategies to reduce emissions. The location-specific co-benefit value plus a carbon price serves as a unified environmental indicator that enables policy makers to more accurately understand the social costs of electricity generation from coal burning and provides a scientific framework for geographically nuanced policymaking.

Suggested Citation

  • Pu Wang & Cheng-Kuan Lin & Yi Wang & Dachuan Liu & Dunjiang Song & Tong Wu, 2021. "Location-specific co-benefits of carbon emissions reduction from coal-fired power plants in China," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27252-1
    DOI: 10.1038/s41467-021-27252-1
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    4. Wang, Linhui & Chen, Qi & Dong, Zhiqing & Cheng, Lu, 2024. "The role of industrial intelligence in peaking carbon emissions in China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    5. Zhang, Boling & Wang, Qian & Wang, Sixia & Tong, Ruipeng, 2023. "Coal power demand and paths to peak carbon emissions in China: A provincial scenario analysis oriented by CO2-related health co-benefits," Energy, Elsevier, vol. 282(C).
    6. Yaolin Wang & Zilin Yuan & Jun Yan & Haixu Zhang & Qinge Guan & Sheng Rao & Chunlai Jiang & Zhiguo Duan, 2024. "Analysis of Synergistic Drivers of CO 2 and NO X Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020," Sustainability, MDPI, vol. 16(17), pages 1-17, August.
    7. Quanxi Wang & Ni Wang & Haodong Wang & Yuan Xiu, 2022. "Study on Influencing Factors and Simulation of Watershed Ecological Compensation Based on Evolutionary Game," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    8. Wan, Panbing & Zhang, ZhongXiang & Chen, Lin, 2024. "Environmental co-benefits of climate mitigation: Evidence from clean development mechanism projects in China," China Economic Review, Elsevier, vol. 85(C).
    9. Liu, Dachuan & Wang, Pu & Sun, Yan & Zhang, Huawei & Xu, Shanqing, 2024. "Co-abatement of carbon and air pollutants emissions in China’s iron and steel industry under carbon neutrality scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    10. Wang, Longze & Zhang, Yan & Li, Zhehan & Huang, Qiyu & Xiao, Yuxin & Yi, Xinxing & Ma, Yiyi & Li, Meicheng, 2023. "P2P trading mode for real-time coupled electricity and carbon markets based on a new indicator green energy," Energy, Elsevier, vol. 285(C).

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