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Decomposition and Forecasting of CO 2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model

Author

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  • Herui Cui

    (Department of Economics and Management, North China Electric Power University, Huadian Road No.689, Baoding 071003, China
    Baoding Low Carbon Development Research Institute, Baoding 071003, China)

  • Ruirui Wu

    (Department of Economics and Management, North China Electric Power University, Huadian Road No.689, Baoding 071003, China)

  • Tian Zhao

    (Department of Economics and Management, North China Electric Power University, Huadian Road No.689, Baoding 071003, China)

Abstract

China faces significant challenges related to global warming caused by CO 2 emissions, and the power industry is a large CO 2 emitter. The decomposition and accurate forecasting of CO 2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO 2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) > line loss rate (1.112) > GDP per capita (0.669) > generation structure (0.522) > the urbanization level (0.512) > electricity intensity (0.310) > industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO 2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO 2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

Suggested Citation

  • Herui Cui & Ruirui Wu & Tian Zhao, 2018. "Decomposition and Forecasting of CO 2 Emissions in China’s Power Sector Based on STIRPAT Model with Selected PLS Model and a Novel Hybrid PLS-Grey-Markov Model," Energies, MDPI, vol. 11(11), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:2985-:d:179818
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    Cited by:

    1. Mansi Wang & Noman Arshed & Mubbasher Munir & Samma Faiz Rasool & Weiwen Lin, 2021. "Investigation of the STIRPAT model of environmental quality: a case of nonlinear quantile panel data analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12217-12232, August.
    2. Haider Mahmood & Abdullatif Sulaiman Alrasheed & Maham Furqan, 2018. "Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis," Energies, MDPI, vol. 11(12), pages 1-15, December.

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