LAUSR

Abstract To deal simultaneously with the environmental problems caused by the current high-intensity exploitation and extensive use of coal resources, it is necessary to perform a scientific prediction of the trend and, especially, the peak of China’s coal demand. Based on the historical data on coal consumption and four primary factors (economic growth, energy structure, investment, and industrial structure) during the period of 1981–2015, this study established a hybrid model for coal demand prediction, using particle swarm optimization and cointegration methods. According to the prediction results combined with the actual statistics, in the business-as-usual scenario, China’s coal demand had peaked in 2014, then a downward trend started with an average annual decline rate of 5.85% for 2016 to 2020. However, future coal demand will keep increasing in the pessimism scenario. And in the optimism scenario, coal demand will decline much faster than the business-as-usual scenario. Sensitive analysis on four influential factors shows that coal demand is more sensitive to changes in investment and industrial structure, and more emphasis should be put on the supply and the demand side of coal industry.