Forecasting of Pakistan’s CO2 Emission: Using ARIMA Approach
DOI:
https://doi.org/10.55737/trt/WR25.167Keywords:
CO2 Emission, , Box-Jenkins Methodology, ARIMAAbstract
Carbon dioxide (CO2) is a key driver of global warming and acts as a dominant player in the global warming and climate change phenomenon. Pakistan’s economy is heavily dependent on oil, natural gas, and coal and other non renewable energy sources, which together account for nearly 81% of its total primary energy consumption. Pakistan’s CO₂ emissions have risen sharply, reaching 179.80 million tons, making it the second highest emitter in South Asia, despite contributing less than 1% to global emissions. Forecasting CO₂ emissions has become increasingly important in addressing the challenges of climate change, particularly for Pakistan. Accurate forecasting of CO2 emission is therefore essential for Environmental sustainability and climate policy formulation. The primary objective of our this research study, to forecast CO2 emission of Pakistan. Therefore, the data has been collected for the years from 1950 to 2022 from the Global Carbon Budget. The study used the well known Auto Regressive Moving Average (ARIMA) model, and forecast CO2 emission of Pakistan for the next 18 years i.e from 2023-2040. With the Box and Jenkins methodology, the ARIMA(6,1,3) model has been selected for forecasting CO2 emission in Pakistan. The results indicate a continued increase in Pakistan’s CO2 emission, and is projected to reach 0.30 tones per person by 2040. Hence an average annual increase of 27.2% of CO2 has been predicted, over the period 2023–2040. Pakistan urgently needs diversified energy, population management, hydro power expansion, and technology for sustainable environmental future.
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