Abstract
Objective and accurate prediction of carbon emissions can provide a basis for the country to achieve carbon emission reduction targets and can also comprehensively and scientifically predict the peak of carbon emissions effectively, providing valuable reference information for the implementation of specific emission reduction policies and measures at each stage. In this paper, a novel fractional-order grey multivariate forecasting model is established to analyze and forecast China’s carbon emissions, reflecting the principle of new information priority. The model adds fractional-order cumulative sequences to the traditional integer-order cumulative sequences, uses the Gamma function to represent the fractional-order sequences and the time-response equation, and uses the particle swarm algorithm to find the optimal order of the cumulative sequence. Finally, the modeling steps of the model are given. Then, the new model is analyzed for its effectiveness from three different perspectives using 21 years of Chinese carbon emission data. The results of the first and second cases show that the newly established particle swarm optimization fractional-order model is superior to the grey multivariate comparison model. The results of the third case show that the new model is superior to the three classical grey prediction comparison models. It has stable characteristics for both simulation and prediction and also shows high accuracy, and all three cases fully illustrate the effectiveness of the new model. Finally, this new model is applied to forecast China’s carbon emissions from 2022–2026, analyze the forecast results, and make relevant recommendations.
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The data used to support the findings of this study are available from the corresponding author upon request.
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Acknowledgements
The authors are grateful to the editors and the reviewers for their insightful comments and suggestions.
Funding
This work is supported by the Basic Research Project of Science and Technology Plan of Guizhou of China under Grants Qian Ke He Foundation ZK [2023] General 022 and the National Natural Science Foundation of China (62241301,72171031).
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The manuscript was reviewed and approved for publication by all authors. Hui Li performed the experiments. Zixuan Wu analyzed the data. Hui Li and Huiming Duan wrote the paper. Shuqu Qian, Hui Li, and Huiming Duan reviewed and revised the paper.
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Li, H., Wu, Z., Qian, S. et al. A novel fractional-order grey prediction model: a case study of Chinese carbon emissions. Environ Sci Pollut Res 30, 110377–110394 (2023). https://doi.org/10.1007/s11356-023-29919-2
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DOI: https://doi.org/10.1007/s11356-023-29919-2