Abstract The Chinese economy has been experiencing rapid growth since the implementation of the reform and opening-up policy. However, at the same time, it faces issues regarding resource savings and environmental protection, which are important aspects of the new industrialization. Therefore, this study conducts data envelopment analysis (DEA) to evaluate the environmental efficiency of Chinese regions. Certain existing DEA models account for undesirable outputs and do not elucidate the weak disposable relationship between undesirable and desirable outputs. Thus, polar theory is introduced among the DEA modeling in this study. First, drawing on stochastic frontier analysis, Ray stochastic frontier analysis, and DEA, we propose a Ray slack-based model (RSBM) to evaluate provincial environmental efficiencies in China from 2004 to 2012. Subsequently, an RSBM-Malmquist–Luenberger (total factor productivity) index is structured. Finally, economic growth, environmental efficiency, and energy consumption are analyzed using spatial panel econometrics. As this study treats industrial waste as undesirable outputs, the RSBM results show that the environmental efficiencies in the east are the highest, while those in the central regions are the lowest. The spatial econometric analysis reveals that the ratios of direct to total elasticity and those of direct to total effect for capital, labor, and energy input variables are fixed. Furthermore, the study provides policy implications and suggestions for future research.