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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Lele Xin & Junsong Jia & Wenhui Hu & Huiqing Zeng & Chundi Chen & Bo Wu, 2021. "Decomposition and Decoupling Analysis of CO 2 Emissions Based on LMDI and Two-Dimensional Decoupling Model in Gansu Province, China," IJERPH, MDPI, vol. 18(11), pages 1-20, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:6013-:d:568254
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