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Drivers and Decoupling Effects of PM 2.5 Emissions in China: An Application of the Generalized Divisia Index

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  • Shangjiu Wang

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China
    School of Mathematics and Statistics, Shaoguan University, Shaoguan 512005, China)

  • Shaohua Zhang

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Liang Cheng

    (School of Political Science and Law, Shaoguan University, Shaoguan 512005, China)

Abstract

Although economic growth brings abundant material wealth, it is also associated with serious PM 2.5 pollution. Decoupling PM 2.5 emissions from economic development is important for China’s long-term sustainable development. In this paper, the generalized Divisia index method (GDIM) is extended by introducing innovation indicators to investigate the main drivers of PM 2.5 pollution in China and its four subregions from 2008 to 2017. Afterwards, a GDIM-based decoupling index is developed to examine the decoupling states between PM 2.5 emissions and economic growth and to identify the main factors leading to decoupling. The obtained results show that: (1) Innovation input scale and GDP are the main drivers for increases in PM 2.5 emissions, while innovation input PM 2.5 intensity, emission intensity, and emission coefficient are the main reasons for reductions in PM 2.5 pollution. (2) China and its four subregions show general upward trends in the decoupling index, and their decoupling states turn from weak decoupling to strong decoupling. (3) Innovation input PM 2.5 intensity, emission intensity, and emission coefficient contribute largely to the decoupling of PM 2.5 emissions. Overall, this paper provides valuable information for mitigating haze pollution.

Suggested Citation

  • Shangjiu Wang & Shaohua Zhang & Liang Cheng, 2023. "Drivers and Decoupling Effects of PM 2.5 Emissions in China: An Application of the Generalized Divisia Index," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:921-:d:1024999
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