Regional Disparities in China’s Total Factor Efficiency Under Renewable Energy Inputs: Spatiotemporal Evolution and Nonlinear Influencing Factors

Regional disparity in total factor efficiency under renewable energy inputs (TFREE) constrains balanced green development amid the global energy transition. This study covers 256 prefecture-level cities in China (2005–2024). TFREE is measured using a meta-frontier dynamic SBM model. Disparity sources are decomposed along four spatial dimensions with the Dagum Gini coefficient. Predictive contributions are analyzed through an XGBoost–SHAP framework within a First Nature–Second Nature perspective. Results show: (1) TFREE disparity shifted from convergence to sustained divergence at the 2011 turning point, forming a persistent “hot South, cold North” pattern. (2) The share of net between-group disparity rose under all dimensions; under the North–South dimension, between-group disparity has exceeded within-group disparity since 2020, becoming the primary source. (3) Second Nature factors make larger predictive contributions than First Nature factors, but this difference narrows over time; annual mean temperature shows the largest increase in contribution. (4) All factors display nonlinear associations with TFREE: GDP shows an overall upward trend; human capital turns persistently negative beyond its transition point; annual mean temperature presents a sign-switching point around 10–15 °C. These findings suggest that differentiated policies may need to consider economic gaps between regional groups, local natural conditions, and nonlinear factor characteristics.