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.

The sustainable development of the mining industry is essential for economic growth. However, this practice necessitates environmental protection and social sustainability. This study uses the super-efficient epsilon-based measure (EBM) model to measure mining energy efficiency (MEE) based on panel data for 30 provinces from 2007 to 2021 in China. We empirically examined the effects of technological innovation (TEC) on MEE and the mediating and threshold effects of industrial structure upgrading (IS) between the two through the fixed, mediating, and threshold effects models. The study findings show that TEC is conducive to enhancing MEE and that this role is relatively robust regarding the mechanism of action. TEC enhances the MEE industry through the IS. We observed the impact of TEC on MEE in the threshold effect of IS—as the level of IS rises, the role of TEC on MEE shows an increasing marginal effect. Therefore, the government should encourage the construction and innovation of technology to optimise the industrial structure and layout and improve energy efficiency in the regional mining industry. This study is a useful supplement to the study of MEE and provides new perspectives and methods for understanding and improving MEE. Meanwhile, the study results provide an important reference for the government to formulate long-term planning and policies for mining development, which is of great significance for optimising the structure of mining resources and improving MEE in the region.