A Spatial-Temporal Decomposition Analysis Of Driving Forces In China’s Regional Carbon Intensity Change

In recent years,with the rapid development of China’s economy,CO₂ emissions have also increased significantly.However,the rapid development of the economy can’t be at the cost of the environment.When the total economic output reaches a certain level,how to achieve the balance between the economic development and environmental protection has become an important part of China’s development strategy in the future.To reduce carbon intensity efficiently,it is important to identify regional differences of China’s carbon intensity considering the decoupling relationship between economic output and carbon emissions.This paper divided China’s 30 provinces into 4 regions based on the relationship between the average annual growth rates of CO₂ emissions and GDP,and explored the driving forces of carbon intensity in 2000 and 2015 for China’s 30provinces and 4 regions using a spatial-temporal logarithmic mean Divisia index（LMDI）method.In the spatial decomposition analysis,this paper uses the weighted average approach to select the reference area.This spatial-temporal decomposition method can provide the rankings and specific drivers of carbon intensity,including energy intensity,industrial structure and energy structure.The results show that during 2000-2015,all provinces’carbon intensity decreased except for Hainan.Ningxia,Shanxi,Guizhou,Qinghai and Xinjiang were five top provincial drivers of the carbon intensity growth in China.Energy intensity was the most important driving factor influencing the change of carbon intensity.Industrial structure and energy structure had small effects on the change of carbon intensity.Moreover,the region III with a high CO₂ emission growth rate and a low GDP growth rate had a poor performance of carbon intensity,due to the large impact of energy intensity.Based on the results of this study,the reduction in carbon intensity could be achieved by further reducing energy intensity,optimizing energy and industrial structure,especially in the provinces with fast CO₂ growth rates and slow GDP growth rates.