A novel discrete conformable fractional grey system model for forecasting carbon dioxide emissions

Peng Zhu (), Han Zhang (), Yunsheng Shi (), Wanli Xie (), Mingyong Pang () and Yuhui Shi ()
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Peng Zhu: Nanjing University of Science and Technology
Han Zhang: Nanjing University of Science and Technology
Yunsheng Shi: China Nuclear Industry Huaxing Construction Co., Ltd.
Wanli Xie: Qufu Normal University
Mingyong Pang: Nanjing Normal University
Yuhui Shi: Southern University of Science and Technology

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 6, No 49, 13609 pages

Abstract: Abstract Providing an accurate forecast of the CO2 emission growth path at the country level can help governments make informed decisions, thereby making their environmental protection policies more effective. A conformable fractional discrete grey system model is raised for carbon emission forecasting in this paper. The proposed model improves the traditional discrete grey-based model by incorporating CFA and CFD, built and tested by using the annual CO2 emissions data from Germany, Japan, and Thailand from 2011 to 2021. As is demonstrated by experimental results, the model is extremely advantageous in comparison with a variety of benchmark grey-based models. Based on the model, an examination of carbon emission trends in the three countries reveals that all of them made progress in reducing air pollution, and Japan achieved the most CO2 emissions reduction during the period.

Keywords: Grey prediction model; CO2 emission forecasting; Fractional calculus; Environmental sustainability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-024-04479-8

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