Spatial-temporal differentiation characteristics and driving factors of China's energy eco-efficiency based on geographical detector model

As China is striving to build a modernization in which people and nature live in harmony, evaluating energy eco-efficiency (EEE) is an important part of achieving a balanced development of socio-economic construction and ecological civilization. From the perspective of the "energy-economy-ecology-society" system, this study included social welfare elements and PM2.5 into the EEE evaluation index, and the EEE of 30 provinces in China from 2000 to 2019 were examined more comprehensively. The distribution differences and sources of EEE were measured by Trend analysis and the Dagum Gini coefficient. A unique analytical method that reveals the drivers of spatial heterogeneity, the Geographical Detector model (Geodetector), was used to better account for the explanatory power of the drivers and their interactions. The results show that China's EEE has a weak "N"-shaped trend in time series, with significant spatial heterogeneity, and the contribution of this imbalance is ranked as inter-regional (39.83%) > hypervariable density (31.95%) > inter-regional (28.22%). The core factors that dominate the spatial-temporal differentiation in the East, Center and West are energy consumption structure (0.688), environmental regulation (0.414), and the level of urbanization (0.548), respectively. The factor interactions are all greater than the explanatory power of factor independent effects on EEE divergence, and the strongest interaction is between Environmental Regulation and Level of educational development in 2010(0.91). The interactions have regional characteristics, and targeted EEE enhancement paths should be selected for different regions.