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.