Decomposition and Decoupling Analysis of CO 2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China

Lele Xin, Junsong Jia, Wenhui Hu, Huiqing Zeng, Chundi Chen and Bo Wu
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Lele Xin: Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
Junsong Jia: Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
Wenhui Hu: Centre de Recherche Sur Madagascar, Foreign Languages College, Jiangxi Normal University, Jiangxi Normal University, Nanchang 330022, China
Huiqing Zeng: School of Resources Environmental and Chemical Engineering, Nanchang University, Nanchang 330031, China
Chundi Chen: School of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Bo Wu: Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education/School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China

IJERPH, 2021, vol. 18, issue 11, 1-20

Abstract: Currently, little attention has been paid to reducing carbon dioxide (CO 2 ) emissions of Gansu, and the two-dimensional decoupling model has been rarely used to study the relationship between the economic development and CO 2 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 CO 2 emissions between 2000–2017 and then analyzed the decoupling relationship by using the two-dimensional model. Results showed: (1) Gansu’s CO 2 emissions increased from 7805.70 × 10 4 t in 2000 to 19,896.05 × 10 4 t in 2017. The secondary industry accounted for the largest proportion in Gansu’s CO 2 emissions, followed by the tertiary industry and the primary industry. (2) The economic output showed the dominant driving effect on Gansu’s CO 2 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 CO 2 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 CO 2 emissions.

Keywords: CO 2 emissions; LMDI; two-dimensional decoupling model; energy consumption; Gansu province (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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