Unlocking energy efficiency: Exploring the dynamic evolution and regional correlations in the Huaihe Eco-economic Belt

Abstract

Energy is the cornerstone of today’s social development, and it is of great significance to comprehensively and objectively reflect the level of energy efficiency (EE) and regional differences. Taking the Huaihe Eco-economic Belt (HEB) as an example, the EE of 28 cities in the HEB from 2008 to 2021 was measured and analyzed by using the super-efficiency SBM model with non-expected outputs; Using Dagum Gini coefficient to explore regional differences in EE levels and their sources; It also explores the dynamic evolutionary pattern and spatial correlation of EE levels using kernel density estimation, Markov transfer probability matrix, and Moran index. The results are as follows: (1) The value of EE in the HEB shows a trend of change that first declines and then rises, with relatively small changes; (2) Regional differences in EE show a fluctuating and increasing trend, with hypervariable density being the most important source of overall regional differences, which are much greater within regions than between regions; (3) The development of EE has been polarized, and the hierarchy of EE levels is relatively stable, with the phenomenon of “club convergence”; (4) There is spatial agglomeration in the level of EE development, with cities in the midwest parts of the country mostly falling in the high-value agglomeration area of the first quadrant, and cities in the northern part of the country mostly falling in the low-value agglomeration area of the third quadrant, with a few cities experiencing spatial and temporal jumps. This paper will be valuable to the government in identifying energy-inefficient cities, formulating targeted policy measures, and promoting the synergistic sustainable development of HEB.