Forecasting Nitrous Oxide emissions based on grey system models

Accurate forecasting is required to measure future national energy performance levels in order to establish clear policies for both monitoring and reducing Nitrous Oxide and other harmful emissions. Using the well-established and accepted measures, we predict the Nitrous Oxide emissions for the year 2030 based on actual data from the years 2000 to 2016 for six countries responsible for 61% of global emissions (China, Indonesia, India, Japan, Russia and the USA). Three advanced mathematical grey predictions models were employed, namely the Even Grey Model (1, 1), the Discrete Grey Model (1, 1) and the Non-homogeneous Discrete Grey Model, which is capable of working with poor or limited data. Results showed that the Non-homogeneous Discrete Grey Model was a better fit and proved more effective in forecasting Nitrous Oxide emissions because it produced the lowest mean absolute percentage error for all countries when compared to the Even Grey Model (1, 1) and the Discrete Grey Model (1, 1). The mean absolute percentage error of the Even Grey Model (1, 1) was 2.4%, that of the Discrete Grey Model (1, 1) was 2.16%, and that of the Non-homogeneous Discrete Grey Model was 1.9%. Furthermore, the results show that China has the highest Nitrous Oxide emissions during the years studied (China 20,578,144, Russia 1,705,110, India 7,806,137, Indonesia 3,405,389, USA 8,891,219 and Japan 780,118). This study also suggests some implications for both academicians and practitioners in respect of reducing Nitrous Oxide emission levels.