A novel grey forecasting of greenhouse gas emissions from four industries of China and India

The increased greenhouse gas concentration in the atmosphere causes climate change. China and India are among the most significant contributors to global greenhouse gas emissions. The current study forecasts the emissions from the countries' four sectors - Transportation, Building, Waste, and Manufacturing/Construction. By extending the classical discrete grey forecasting model DGM (1, 1), a new data-driven time-series forecasting technique, called DGM (1, 1, alpha), is proposed and applied to forecast the emissions in these sectors till 2028 with an accuracy of over 95%. The results show that the emissions are generally increasing. However, China continues to show a decline in the emissions from the manufacturing and construction industries. Also, the Posterior-Variance Test is introduced to test whether a given forecasting model is qualified or unqualified for a given problem. The comparative analyses with three forecasting models - DGM (1,1), Even GM (1,1), and Grey Verhulst models -revealed the proposed model's feasibility, flexibility, and accuracy. The study concludes with important recommendations for the policy-makers to develop better emission mitigation policies. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

The study forecasts emissions from four sectors in China and India and introduces a new time-series forecasting technique. Results show an overall increase in emissions, but a decline in manufacturing and construction emissions in China. The study also introduces the Posterior-Variance Test to test the suitability of forecasting models.