Exploring the path of carbon emissions reduction in China?s industrial sector through energy efficiency enhancement induced by R&D investment

The energy efficiency enhancement induced by R&D investment is of vital importance to curb the carbon emissions in industrial sector. However, none of the literatures have incorporated R&D investment into the economic growth model to explore the path of energy efficiency enhancement. Therefore, this paper explores the path of energy efficiency improvement to achieve carbon intensity and carbon peak goals from the perspective of R&D investment. We establish a multi-objective optimization model with industrial economic output, total energy consumption and carbon emissions being the objectives, and R&D intensity and physical capital investment being control variables. The genetic algorithm is utilized to find out the optimal path of energy efficiency improvement in China's industrial sector. The results indicate that, under the optimized scenario, the average annual growth rate of R&D intensity and physical capital investment are 11.14% and 10.61%, respectively, which increase 3.06% and 0.02% compared to the baseline scenario; the energy intensity will decrease by 78.4% in 2030 compared to that in 2005. The energy consumption and carbon emissions will be significantly lower than that in the baseline scenario, and will peak at 2672Mtce and 6042 Mt respectively in 2021. Moreover, the paths of energy efficiency enhancement induced by R&D investment in various industrial sub-sectors are worth studying in the further work. (c) 2021 Elsevier Ltd. All rights reserved.