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• W3100451829 endingPage "112017" @default.
• W3100451829 startingPage "112017" @default.
• W3100451829 abstract "Haze pollution has been a serious environmental issue in China, however, little research has focused on the industrial sector which accounts for a large part of total PM 2.5 emissions. This paper aims to disclose the driving mechanism and decoupling effect of industrial PM 2.5 emissions. First, this study reveals the spatial-temporal drivers of industrial PM 2.5 emissions in China spanning 2000–2014 through geographical detector and logarithmic mean Divisia index decomposition, respectively. Then, the decoupling causal chain of industrial economic growth and PM 2.5 emissions is investigated by a refined Laspeyres index method. The empirical results illustrate that: (1) Population distribution is the dominating factor for the spatial heterogeneity of industrial PM 2.5 emissions. Different influencing factors show significant synergistic effects. (2) Industrial development effect is the main reason for the increase of industrial PM 2.5 emissions, while the reduction in industrial PM 2.5 emissions is primarily due to energy intensity effect, followed by coal pollution intensity and energy mix effects. (3) During the study period, the PM 2.5 -economic growth decoupling undergoes two states, and shows the tendency towards strong decoupling. (4) The PM 2.5 -coal consumption effect and energy consumption-economic growth effect are important factors influencing the changes of PM 2.5 -economic growth decoupling indicator, while the impact of the coal consumption-energy consumption effect is quite small. This paper provides important implications for reducing industrial PM 2.5 emissions. • Reveal the spatial heterogeneity of industrial PM 2.5 emissions by geographical detector. • Study the temporal variation of industrial PM 2.5 emissions using LMDI decomposition. • The decoupling causal chain is decomposed by a refined Laspeyres index method. • Population distribution is the main factor explaining the spatial differentiation. • The reduction in industrial PM 2.5 emissions is primarily due to energy intensity effect." @default.
• W3100451829 created "2020-11-23" @default.
• W3100451829 creator A5001248258 @default.
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• W3100451829 date "2021-02-01" @default.
• W3100451829 modified "2023-10-17" @default.
• W3100451829 title "Driving mechanism and decoupling effect of PM2.5 emissions: Empirical evidence from China’s industrial sector" @default.
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• W3100451829 doi "https://doi.org/10.1016/j.enpol.2020.112017" @default.
• W3100451829 hasPublicationYear "2021" @default.
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