Study of spatial patterns and spatial effects of energy eco-efficiency in China

Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy–environment–economy system. Using the slacks-based measure (SBM) model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects: scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn: (1) The overall energy eco-efficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are representative regions with low efficiency. Thus, the pattern of evolution of China’s overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found: increasing, fluctuating, mutating, and leveling. (2) At the provincial level, China’s energy eco-efficiency features significant spatial agglomeration both globally and locally. High–high agglomeration occurs mainly in the eastern and southern coastal regions and low–low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high–low and low–high agglomeration, with the most remarkable change taking place in the Beijing–Tianjin–Hebei region. (3) There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region, spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency.