Wanyue Li¹, Xuehua Zhang^1,

Energy conservation and carbon emission reduction are the same root and homology issues. A comprehensive accounting of CO₂ emissions of the research objects can objectively evaluate their green and low-carbon levels at the current stage, tap their energy conservation and emission reduction potential, and lay a solid foundation for formulating energy conservation and emission reduction policies according to local conditions. Therefore, this paper firstly takes the “traditional carbon” accounting based on the carbon emissions of energy consumption as the accounting basis, adds the accounting of potential carbon emissions of waste discharge, implicit carbon emissions of net electricity input and forest carbon sequestration, and constructs a new “Full Carbon” accounting system. Then, the carbon emission intensity of China's provinces under the “Full Carbon” accounting system during the 13th Five-Year Plan period is calculated to characterize the low-carbon level of each province. Finally, the spatial correlations of China's provincial low-carbon levels under the two accounting systems are analyzed by using Moran's I index method, and the two results are compared. The results show that there are some differences in the spatial correlations of provincial low-carbon levels under the “traditional carbon” and the “Full Carbon” accounting systems, which are as follows: (1) On the whole, the low-carbon levels of the “traditional carbon” accounting system showed more significant spatial correlations in provinces than in the “Full Carbon” accounting system, but the regional spatial spillover effect of spatial agglomeration formed by the “Full Carbon” accounting system was more obvious; (2) From a local perspective, under the “traditional carbon” accounting system, the “Low-Low” agglomeration regions formed by southeast and south-central China showed positive spatial spillover effect. Under the “Full Carbon” accounting system, the “Low-Low” agglomeration area formed by Sichuan and Yunnan in southwest China showed a positive spatial spillover effect, while the “High-High” agglomeration area located in Nei Mongolia showed a negative spatial spillover effect.

“Full Carbon” accounting, 13th Five-Year Plan period, low-carbon level, Moran’s I index, spatial correlation analysis