Decoupling between economic growth and carbon emission is a global hot topic. This paper studies China’s economic-carbon decoupling and its driving factors. By using the panel data of 30 Chinese provinces from 2000 to 2016, the decoupling index of each province is calculated with the Tapio model. It is found that many provinces have progressed from no decoupling to weak decoupling and then strong decoupling. Then, the econometric models are used to explore the driving factors. Results show that energy structure is the most important factor, followed by GDP per capita and energy intensity, which all increase CO₂ emission significantly. The results are robust when tested with GMM, PCSE and FGLS estimation and LMDI decomposition. Further, we conduct a comparative analysis regarding the temporal and spatial characteristics of the above three driving factors to identify their relationship with decoupling, four groups of regions that represent different economic features are selected for the analysis. Heterogeneity effects of the factors among the regions has been observed, based on this we provide targeted strategies for different regions.

C₂₁H₂₂N₂O₃, orthorhombic, Pbcn (no. 60), a = 15.093(2) Å, b = 13.896(2) Å, c = 17.501(2) Å, V = 3670.5(8) ų, Z = 8, R _gt(F) = 0.0446, wR _ref(F ²) = 0.1208, T = 293(2) K.