Investigation and optimization analysis on deployment of China coal chemical industry under carbon emission constraints

The coal chemical industry plays a critical role in the economic growth and energy security of China. In this study, a constrained nonlinear programming is proposed to optimize deployment technologies and processes of the coal chemical industry to reduce CO2 emissions, and thus obtain the minimum CO2 emissions per unit output of the coal chemical sector, while satisfying economic growth and energy security. Deployment of new technologies and processes in the coal chemical industry, over short-term (2020), mid-term (2030) and long-term (2050) periods, with the objective to reduce CO2 emissions, are investigated based on this model. Dynamic sensitivity or uncertainty analysis of impacts of technical factors such as technology upgrading, carbon capture and storage & carbon capture, utilization, and storage and other technologies to deployed coal chemical sectors on CO2 emissions reduction and economic growth, are performed. Different technologies were simulated, with the output providing three scenarios: 100% (positive), 50% (moderate) and 25% (conservative) of the predicted target reduction in CO2 emissions. The reduction in CO2 emissions was analyzed at different time periods, with respect to carbon tax values and crude oil prices. Correspondingly, a development roadmap (2020-2030-2050) of the coal chemical industry, with respect to reducing carbon emissions is drawn.