Haze pollution has become a severe threat to China’s sustainable development. It is crucial to provide a complete explanation for the mechanism behind the changes in PM2.5 pollution and explore how to decouple economic growth from PM2.5 pollution. Compared with the traditional decomposition analysis methods, the Generalized Divisia Index Method (GDIM) integrates multiple influencing factors and provides a fuller understanding of the influence mechanism of PM2.5 pollution. In addition, the decomposition of the monitored PM2.5 concentration in previous studies leads to ambiguous economic meanings of some relative impact indicators. In this paper, GDIM decomposition is applied to study the driving factors of energy-related PM2.5 emissions changes in China. Then, based on the GDIM decomposition results, this paper constructs a novel decoupling indicator to study the decoupling relationship between PM2.5 emissions and economic growth, and the contributions of the technical and non-technical factors to the decoupling indicator are quantified. The main results are summarized as follows. (1) The output scale effect and energy use effect are the main reasons for the increase of PM2.5 emissions, while the emission intensity effect and emission coefficient effect make major contributions to decreasing PM2.5 emissions. The effects of population, per capita emissions, per capita output, and energy intensity are relatively minor. (2) China and its three economic regions move from strong decoupling in 1998–2000 to weak decoupling during 2000–2010, and then into strong decoupling over the period of 2010–2014. (3) Technical effect plays an important role in promoting the decoupling between PM2.5 emissions and economic growth, but its contribution shows a downward trend over time. In contrast, non-technical effect hinders the decoupling process, and its contribution is decreasing from 2000 to 2014. This paper is supportive for formulating emissions reduction policies and improving China’s air quality.
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