Decomposition and Decoupling Analysis of CO2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China

Currently, little attention has been paid to reducing carbon dioxide (CO2) emissions of Gansu, and the two-dimensional decoupling model has been rarely used to study the relationship between the economic development and CO2 emissions, especially in western China (e.g., Gansu). Thus, here, we first used the Logarithmic Mean Divisia Index (LMDI) to decompose the driving factors of Gansu's CO2 emissions between 2000-2017 and then analyzed the decoupling relationship by using the two-dimensional model. Results showed: (1) Gansu's CO2 emissions increased from 7805.70 x 10(4) t in 2000 to 19,896.05 x 10(4) t in 2017. The secondary industry accounted for the largest proportion in Gansu's CO2 emissions, followed by the tertiary industry and the primary industry. (2) The economic output showed the dominant driving effect on Gansu's CO2 emissions growth with the cumulative contribution rate of 201.94%, followed by the effects of industrial structure, population size, and energy structure, and their cumulative contribution rates were 9.68%, 7.81%, and 3.05%, respectively. In contrast, the energy intensity effect presented the most obvious mitigating effect with the cumulative contribution rate of -122.49%. (3) The Environmental Kuznets Curve (EKC) between CO2 emissions and economic growth was demonstrated the inverted U-shape in Gansu. The two-dimensional decoupling status was the low level-weak decoupling (WD-LE) during 2000-2017. Thus, dropping the proportion of the secondary industry, reducing the use of carbon-intensive fuel like coal, introducing advanced technologies, and increasing the investment of new energy might effectively restrain the growth of Gansu's CO2 emissions.