A novel grey Verhulst model with four parameters and its application to forecast the carbon dioxide emissions in China

Abstract

In the context of dual carbon targets, a reliable prediction of China's carbon dioxide emissions is of great significance to the design and formulation of emission reduction policies by Chinese government. To this end, a novel grey Verhulst model with four parameters is proposed in this paper according to the evolution law and the data characteristics of China's carbon dioxide emissions. The new model solves the defect of poor structural adaptability of the traditional grey Verhulst model by introducing a nonlinear correction term. Besides, the range of values for the order of the grey generation operator of the new model is expanded from a positive real number to any real number (r ∈ R⁺ → r ∈ R) by expanding the value range of the Gamma function. The new model is used to simulate China's carbon dioxide emissions, and its comprehensive mean relative percentage error is only 0.65 %, which is better than that of the other three grey models (2.39 %, 2.34 %, 2.35 % respectively). It shows that the proposed new model has better modeling ability. Finally, the new model is applied to predict China's carbon dioxide emissions, and the results show that it will still increase year by year, reaching 13,687 million tons by 2028 (only 11,420 million tons in 2021). Therefore, some countermeasures and suggestions are proposed to control China's carbon dioxide emissions in this paper.

Keywords: Carbon dioxide emissions prediction; Four-parameter grey Verhulst model; Model structure expansion; Parameter optimization; Result analysis and suggestions.