Fractional Cumulative Grey Model And Its Application In Carbon Dioxide Emission Forecast

Energy combustion releases a large amount of carbon dioxide,which is the main cause of the greenhouse effect,so there is an inevitable connection between these two factors.Predicting carbon dioxide emissions can play a better monitoring role,which is the key to reducing carbon dioxide emissions.New data can better characterize future development trends,so the grey system theory that prioritizes new information is used to study carbon dioxide emissions.Based on the grey system theory and carbon dioxide emissions as the research object,through the construction of grey forecasting models,the issue of international and domestic carbon dioxide emissions is studied.Based on the relevant research results of univariate model,multivariate model and carbon dioxide emissions,and through relevant theoretical proofs,a new cumulative grey prediction model is constructed.According to the established non-equidistant new cumulative grey GM(1,1)model,the carbon dioxide emissions of 53 countries and regions around the world are predicted.The results of the study show that 22 countries and regions have experienced a decline in carbon dioxide emissions,30 countries’ carbon dioxide emissions have shown an upward trend,and one country’s forecast results have fluctuated.Converted from an international perspective to a domestic perspective,based on the division of economic zones,the carbon dioxide emissions predictions are made for 24 regions in China.The carbon emissions of Anhui Province and Xinjiang Uygur Autonomous Region should be paid more attention to by studying the carbon emissions of different regions in China from the perspectives of regional longitudinal and inter-regional horizontal.Finally,considering that carbon dioxide emissions are affected by many factors including energy consumption,a new cumulative grey multivariate model is proposed based on the grey univariate model.Based on the matrix perturbation theory,the properties of the new cumulative grey multivariate model are studied.Use case analysis to prove the effectiveness of the model.The impact of three variables including energy consumption,population,and gross regional product(GDP)on carbon dioxide emissions is considered,so univariate models with relatively large errors can be corrected.The research results show that the new multivariate grey model can reduce the error of the univariate model.Finally,based on the prediction results of the grey model,emission reduction measures are proposed for areas with high carbon dioxide emissions,which provide a reference for realizing the common goal of “carbon neutrality”.