Prediction of Methane Emission using ARIMA Model

Scientists hypothesized that the primary catalyst for global climate change is an increase in the concentration of greenhouse gas emissions, particularly methane, in the atmosphere. The compelling reasons to priorities attention to methane are its high global warming potential and long atmospheric half-life. The atmospheric gas profiles are significantly impacted by human activities on a daily basis. The immediate mitigation of global warming could be achieved by directly implementing actions to reduce methane emissions. In light of the aforementioned points, it can be asserted that monitoring future methane levels by analyzing past data is crucial for understanding the trajectory of climate change in the coming decades. To achieve this objective, we suggest employing a technique that makes use of cutting-edge ARIMA models, which have exhibited exceptional efficacy in predicting time-series data. The primary objectives of this study are to determine the most suitable ARIMAmodel (pdq) and to predict methane emissions for a 12-year duration till 2035.