Mathematical modelling and projecting  CO<sub>2</sub> by Autoregressive integrated moving average (ARIMA) and Simple exponential smoothing (SES) model for Bangladesh,Bhutan,Nepal and Pakistan

The impact of climate change has been a vital problem where CO2 emission is one of the greatest contributors to global warming, and it has a negative effect on the environment.The core objective of this study was to understand, analyse and forecast the future CO2 emission in Bangladesh, Bhutan, Nepal, and Pakistan using the Autoregressive Integrated Moving Average (ARIMA) and Simple Exponential Smoothing (SES) models. Annual CO2 emission data produced from various carbon fuels and industries from 1946 to 2021 for Bangladesh, 1970 to 2021 for Bhutan, 1950 to 2021 for Nepal and from 1946 to 2021 for Pakistan were collected from the World Data Bank database and other sources. The study used this data to predict the CO2 emission for the next 27 years, from 2024 to 2050. The ARIMA and SES models with the highest accuracy for Bangladesh, Bhutan, Nepal and Pakistan were determined by possessing the lowest value of Akaike’s Information Criterion (AIC) with a graphical representation of ACF and PACF plots. Based on this method, ARIMA (0,1,1), ARIMA (0,1,0), ARIMA (1,1,1), ARIMA (0,1,0) were assumed to be the most perfect technique for predicting the CO2 emission in Bangladesh, Bhutan, Nepal, and Pakistan. These models were used to draw numerical pictures of future CO2 emission. Projected carbon dioxide emission values in Bangladesh, Bhutan, Nepal and Pakistan will increase, indicating major climate change and global warming. Different policies and strategies should be developed to tackle this situation.