Abstract: The study of the environmental Kuznets curve of carbon emission can not only predict the inflection-point appearance time of carbon emission, but also reveal the dynamic relationship between economic development and carbon emission. According to the IPCC carbon emission calculation method and based on the energy consumption data of Anhui Province, a dynamic measurement was conducted on the carbon emission and its intensity in the Province from 1995 to 2010. By using the simplified EKC model, the EKC models of the total carbon emission, per capita carbon emission, and carbon emission intensity in the Province were established, and, based on the co-integration OLS regression method, the EKC curves of the total carbon emission and carbon emission intensity in the Province were analyzed. The results showed that the total carbon emission in the Province was increased from 44.2058 million tons in 1995 to 119.1332 million tons in 2010, and the per capita carbon emission was increased from 0.74 t in 1995 to 1.74 t in 2010, both of them showing a continuous growth trend. On the contrary, the carbon emission intensity per ten thousand RMB Yuan decreased from 2.44 t in 1995 to 0.97 t in 2010, showing a continuous reduction trend. The EKC curve of the carbon emission in the Province was N-shaped. The scatter diagram with trend lines indicated that the N shaped relationship was very weak, no inflection point existed in EKC curve within a short term, but the inflection point would be appeared in 2027. Also, the EKC curve of the carbon emission intensity in the Province was N shaped, the Nshaped relationship was very weak, and no inflection point  existed in EKC curve within a short term while showing a declining trend. The EKC curve was not supported by the per capita carbon emission in the Province. The above results were conducive to understand the future trend of carbon emission, and provide a basis for developing appropriate emission reduction policies.

Key words: Guiyang City, urban expansion, space simulation, optimal path.