Forecasting Methane Emissions in Kuwait by 2030: A Time Series Approach Using ARIMA

Global methane emissions present a major challenge for climate change mitigation, with industrial and agricultural activities contributing significantly to greenhouse gas concentrations. This research applies the ARIMA (Autoregressive Integrated Moving Average) model to forecast Kuwait's annual methane emissions, projecting an annual growth rate of 3.70% between 2023 and 2030. By analyzing historical emissions data from 1850 to 2022, the research provides essential information for environmental policymaking. The model's validation via the autocorrelation function (ACF) and the partial autocorrelation function (PACF) highlights the strengths and limitations of the method. The forecasts emphasize the urgent necessity for targeted emission reduction policies with potential improvements, including the incorporation of explanatory variables, aggregate methods, and regional structural factors.