Impact of the national economy and air pollutant emissions on Chinese energy mix: Evidence from an SBMDEA-TOPSIS model

With Chinese rapid economic growth, fossil energy consumption, greenhouse gas emissions, and air pollution have intensified, posing significant threats to public health and economic sustainability. And improving energy efficiency and optimizing energy structures are essential for sustainable development. Therefore, the paper integrates the Slacks-Based Measure of Efficiency-Data Envelopment Analysis (SBM-DEA) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to comprehensively assess regional energy efficiency. The SBM-DEA accounts for both desirable and undesirable outputs, effectively measuring inefficiencies related to emissions, while the TOPSIS ranks decision-making units (DMUs) by their proximity to the ideal efficiency frontier, enabling precise benchmarking. Then, the proposed SBM-DEA-TOPSIS framework is applied to analyze Chinese energy efficiency in the context of economic growth, greenhouse gas emissions, and air pollution. The results reveal significant regional disparities, with economically developed provinces achieving higher efficiency than resource-dependent areas. Moreover, findings suggest that targeted policy interventions are crucial, including technological innovation, industrial restructuring, and an accelerated transition to clean energy. Finally, provinces with lower efficiency should focus on upgrading energy-intensive industries, optimizing resource allocation, and expanding renewable energy adoption. Additionally, incorporating incentives for green technology and stricter environmental regulations can drive efficiency improvements. Furthermore, the proposed SBM-DEA-TOPSIS model serves as a valuable tool for guiding evidence-based policymaking, supporting Chinese long-term energy transition and environmental objectives.