Analysis of Spatial Disparities and Driving Factors of Energy Consumption Change in China Based on Spatial Statistics

The changes of spatial pattern in energy consumption have an impact on global climate change. Based on the spatial autocorrelation analysis and the auto-regression model of spatial statistics, this study has explored the spatial disparities and driving forces in energy consumption changes in China. The results show that the global spatial autocorrelation of energy consumption change in China is significant during the period 1990–2010, and the trend of spatial clustering of energy consumption change is weakened. The regions with higher energy consumption change are significantly distributed in the developed coastal areas in China, while those with lower energy consumption change are significantly distributed in the less developed western regions in China. Energy consumption change in China is mainly caused by transportation industry and non-labor intensive industry. Rapid economic development and higher industrialization rate are the main causes for faster changes in energy consumption in China. The results also indicate that spatial autoregressive model can reveal more influencing factors of energy consumption changes in China, in contrast with standard linear model. At last, this study has put forward the corresponding measures or policies for dealing with the growing trend of energy consumption in China