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Analysis and prediction of CO2 emissions from commercial energy consumption and emission reduction potential of renewable energy in China

Author

Listed:
  • Xinxin Zhang

    (Beijing University of Technology
    Beijing University of Technology)

  • Kaili Xu

    (Beijing University of Technology
    Beijing University of Technology)

Abstract

Based on the relevant data from 2001 to 2019, an internationally agreed methodology for calculating CO2 emissions developed by Intergovernmental Panel on Climate Change is used in this paper to calculate CO2 emissions generated by commercial energy consumption in China. On this basis, the regional heterogeneity of commercial energy consumption and CO2 emissions is compared and analyzed on a provincial scale. Moreover, the CO2 emissions reduction potential of renewable energy power generation is analyzed. The consumption of commercial energy and its related carbon emissions, the power generation from renewable energy and its resulting carbon emission reduction from 2020 to 2030 are also predicted by using SPSS (Statistical Product and Service Solutions). The prediction show that the consumption of coal, natural gas and electricity is expected to be 5592.0699 million tons, 625.099 billion cubic meters, and 10996.462 billion kWh, respectively by 2030, when the carbon emissions reach the peak, and CO2 emissions generated by the consumption of coal and natural gas will reach 9.40 × 1012 and 1.37 × 1012 kg, respectively. Wind, hydropower, solar and biomass power generation are expected to be 847753.3 kWh, 1933147.57, 498087.78 and 149955.00 GWh, respectively, which can reduce CO2 emissions by about 2.45 × 1011, 5.59 × 1011, 1.44 × 1011 and 4.34 × 1010 kg, respectively.

Suggested Citation

  • Xinxin Zhang & Kaili Xu, 2025. "Analysis and prediction of CO2 emissions from commercial energy consumption and emission reduction potential of renewable energy in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 10835-10856, May.
    • Handle: RePEc:spr:endesu:v:27:y:2025:i:5:d:10.1007_s10668-023-04334-2
    DOI: 10.1007/s10668-023-04334-2
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