Forecasting CO2 emissions using grey system theory

Due to the increase in CO2 emissions as a pollutant, irreversible damages are inflicted on humans and environment. Therefore, policies must be implemented to control and reduce CO2 emissions. Analysis and forecasting of CO2 emission is a crucial subject for determining suitable policies. The aim of this paper is to use grey system theory for predicting the CO2 emissions. The factors oil, gas and coal burning are considered as the inputs that affect the CO2 emissions. The GM(1,4) model is used for predicting CO2 emissions. The effect of each item in the CO2 emissions is investigated. A fitting polynomial function with weighted data is proposed for evaluating CO2 emissions in different situations. This is essential for selecting the most appropriate policy scenario to reduce air pollution. Numerical results show that the method is robust and accurate.