Prediction of Fossil Fuels consumption of Asian countries through ARIMA models

Fossil fuels continue to be a critical component of the global energy landscape in the 21st century, meeting a large portion of the world's energy needs. Despite the growing awareness of their environmental impacts, fossil fuels—namely coal, gas, and oil—are still widely used due to their availability and efficiency. These fuels are essential for powering industries, transportation, and supporting modern lifestyles. However, the significant carbon dioxide (CO2) emissions from fossil fuel combustion present a serious environmental challenge, contributing to global climate change. Understanding the ongoing importance of fossil fuels emphasizes the urgent need to innovate and transition to sustainable energy solutions. Such a shift is crucial for reducing CO2 emissions and ensuring a more environmentally responsible and resilient future. This study examines the consumption patterns of fossil fuels—specifically coal, gas, and oil—in Bangladesh, India, and Pakistan. To predict future demand for these non-renewable resources, the study utilized Autoregressive Integrated Moving Average (ARIMA) models with different (p, d, q) parameters. By using Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots, the study identified suitable ARIMA models for each fuel type, selecting the best models based on the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values. The study successfully forecasted the demand for coal, gas, and oil over the next decade in the three countries. These insights are crucial for planning the production of renewable energy, reducing fossil fuel consumption, and promoting a sustainable environment for future generations.