The improvement pathway for industrial energy efficiency under sustainability perspective

Improving industrial energy efficiency (IEE) has become an urgent need in most countries. The factor adjustment aimed at improving IEE is restricted by exogenous conditions, which affects the improvement pathway formulation. This paper develops a data envelopment analysis method that incorporates the value judgment from experts on these constraints and determines an improvement pathway for IEE at the micro level. Moreover, the macro policy design to improve IEE usually needs to make trade-offs in different policy directions. Regression analysis is conducted to explore the drivers that promote IEE and provide reference for improvement pathway at the macro level. A case study with China's industries is applied to illustrate the efficacy of this integrated method. The main results show that: (1) The average IEE score is 0.646, 33% of provinces have a score less than 0.5. (2) In the eastern area, reductions in waste water and waste gas are the largest contributors, with an average reduction rate of 30% and 26%. As for energy input and output, the adjustment proportion in the western area is the highest. (3) Energy structure, marketization degree, industrial concentration and technological development have significant impacts on IEE, which are directions for formulating a macro improvement pathway.

Automated summary

This paper develops a data envelopment analysis method to improve industrial energy efficiency (IEE) at the micro level, taking into account expert judgment on constraints. Regression analysis is also used to explore the drivers of IEE at the macro level, providing reference for improvement pathway formulation. The efficacy of this integrated method is illustrated through a case study of China's industries.