Forecasting of GHG (greenhouse gas) Emission using (ARIMA) Data Driven Intelligent Time Series Predicting Approach

Climate change is emerging as one of the major challenges to the existence of life on the Earth. Most scientists believe that if the GHG (greenhouse gas) concentration doubles, temperature would increase by $3^{\circ}\mathrm{C}$ by the end of the century and this would result in economic loss. Countries across the world are showing their concern to reduce GHG emissions in the form of the Paris agreement. Indian participation in the Paris Agreement demonstrated its commitment to reduce GHG emissions by half the amount of GHG produced for every dollar of economic activity by increasing the proportion of non-fossil fuels in power generation capacity up to 40 percent of total capacity, thereby reducing the emissions intensity of the economy by 33 percent to 35 percent. The aim of the present study is to investigate the past and current trends of GHG emissions in India and to forecast the emissions of GHG for future Years. Forecasting GHG emissions over the coming decade will help to know the level of GHG emissions in the forecasted period of the next 10 years. Data-driven intelligent time-series predicting approach, ARIMA (Auto-Regressive Integrated Moving Average) is applied for forecasting GHG emissions. ARIMA (0, 2, 1,) model is used for forecasting, which showed an increasing trend of emissions of GHG. This Projection will help the policymakers to take actions to reduce GHG emissions and achieve the target set in the Paris agreement and minimize the economic loss due to climate change. The forecasted value of GHG emissions over the decade can help the government to plan its future course of action.