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Scenario prediction and decoupling analysis of carbon emission in Jiangsu Province, China

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  • Dong, Jia
  • Li, Cunbin

Abstract

As a major energy consumption province in China, Jiangsu Province is a key area for carbon emission reduction in China. Grasping the future trends of carbon emission in Jiangsu Province will help to find effective ways to reduce carbon emission. This paper proposes the STIRPAT-IGWO-SVR model, including screening the carbon emission influencing factors based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, optimizing the parameters of the support vector regression (SVR) model using the gray wolf optimization (GWO) algorithm improved by the differential evolution (DE) algorithm, and sets five scenarios to predict and compare the carbon emissions of Jiangsu Province under different scenarios. In addition, the Tapio decoupling model is used to analyze the decoupling relationship of carbon emission and economic growth in each scenario. The results show that the STIRPAT-IGWO-SVR model proposed in this paper shows good performance compared with other models. For Jiangsu Province, improving the energy structure has the strongest inhibitory effect on carbon emission, stronger than reducing energy intensity, and far stronger than optimizing the industrial structure. Compared with a single plan, even if the measures are slightly weakened, the implementation of combined planning measures can more effectively control carbon emission.

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  • Dong, Jia & Li, Cunbin, 2022. "Scenario prediction and decoupling analysis of carbon emission in Jiangsu Province, China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    • Handle: RePEc:eee:tefoso:v:185:y:2022:i:c:s0040162522005959
    DOI: 10.1016/j.techfore.2022.122074
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    1. Zhai, Mengyu & Huang, Guohe & Liu, Lirong & Guo, Zhengquan & Su, Shuai, 2021. "Segmented carbon tax may significantly affect the regional and national economy and environment-a CGE-based analysis for Guangdong Province," Energy, Elsevier, vol. 231(C).
    2. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    3. Ma, Haoran, 2022. "Prediction of industrial power consumption in Jiangsu Province by regression model of time variable," Energy, Elsevier, vol. 239(PB).
    4. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    5. Li, Dezhi & Huang, Guanying & Zhu, Shiyao & Chen, Long & Wang, Jiangbo, 2021. "How to peak carbon emissions of provincial construction industry? Scenario analysis of Jiangsu Province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    6. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
    7. Wang, Changjian & Wang, Fei & Zhang, Xinlin & Yang, Yu & Su, Yongxian & Ye, Yuyao & Zhang, Hongou, 2017. "Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 51-61.
    8. Wu, Rong & Wang, Jieyu & Wang, Shaojian & Feng, Kuishuang, 2021. "The drivers of declining CO2 emissions trends in developed nations using an extended STIRPAT model: A historical and prospective analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    9. Tapio, Petri, 2005. "Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001," Transport Policy, Elsevier, vol. 12(2), pages 137-151, March.
    10. Liu, Bingquan & Shi, Junxue & Wang, Hui & Su, Xuelin & Zhou, Peng, 2019. "Driving factors of carbon emissions in China: A joint decomposition approach based on meta-frontier," Applied Energy, Elsevier, vol. 256(C).
    11. Pan, Xiongfeng & Guo, Shucen & Xu, Haitao & Tian, Mengyuan & Pan, Xianyou & Chu, Junhui, 2022. "China's carbon intensity factor decomposition and carbon emission decoupling analysis," Energy, Elsevier, vol. 239(PC).
    12. Xu, Haitao & Pan, Xiongfeng & Guo, Shucen & Lu, Yuduo, 2021. "Forecasting Chinese CO2 emission using a non-linear multi-agent intertemporal optimization model and scenario analysis," Energy, Elsevier, vol. 228(C).
    13. Liu, Hui & Mi, Xiwei & Li, Yanfei & Duan, Zhu & Xu, Yinan, 2019. "Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression," Renewable Energy, Elsevier, vol. 143(C), pages 842-854.
    14. Huo, Tengfei & Xu, Linbo & Feng, Wei & Cai, Weiguang & Liu, Bingsheng, 2021. "Dynamic scenario simulations of carbon emission peak in China's city-scale urban residential building sector through 2050," Energy Policy, Elsevier, vol. 159(C).
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    4. Yang, Yi & Qin, Huan, 2024. "The uncertainties of the carbon peak and the temporal and regional heterogeneity of its driving factors in China," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

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