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Modeling and Forecasting Carbon Dioxide Emission from Fossil Fuel Combustion in Pakistan using Arima Model: Implications for Climate Change | ||
| Pollution | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 10 اردیبهشت 1404 | ||
| نوع مقاله: Original Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/poll.2025.388580.2780 | ||
| نویسندگان | ||
| Dr. Romana Khan* ؛ Yasir Malik؛ Romana Jamshed؛ Asim Yaqub؛ Maria Siddique | ||
| COMSATS University Islamabad, Abbottabad Campus | ||
| چکیده | ||
| Greenhouse gases emissions, notably CO2, into atmosphere have driven profound climate change and amplified global warming. This phenomenon not only compromises environmental integrity but also poses a threat to sustainable development, giving rise to a multitude of environmental challenges. Despite the pressing need to mitigate climate change, there is a lack of comprehensive forecasting models specifically tailored to predict CO2 emissions from fossil fuel combustion in Pakistan. Therefore, emissions data of 1990-2020 was obtained from IEA to forecast future increase in CO2. Autoregressive Integrated Moving Average (ARIMA) model for forecasting CO2 and assess the implications of forecasted CO2 emissions on climate change. ARIMA model emphasis on autocorrelations in time series higher accuracy compared to other methods. Exact order for “p” and “q” was determined using autocorrelation function (ACF) and partial autocorrelation function (PACF) to specify the MA (q) and AR (p) order in ARIMA forecasting. ARIMA (2,1,2), ARIMA (6,1,2) and ARIMA (10,1,10) were finalized to analyze the data. Among these ARIMA (6,1,2) was found suitable to forecast CO2 emissions. Analysis of the data from 2021-2030 confirmed 220.117 Mt CO2 rise by 2030. This represents a 9.188% increase in CO2 emissions over the forecast period, highlighting a significant growth rate compared to the initial increase observed in 2021. This study will help the policy makers and other stakeholders to take proactive actions and sustainable practices to balance economic development and environmental ministration. | ||
| کلیدواژه‌ها | ||
| CO2 emissions؛ ARIMA model؛ Climate change؛ Forecast؛ Global warming | ||
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آمار تعداد مشاهده مقاله: 152 |
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