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• W2981021328 endingPage "118889" @default.
• W2981021328 startingPage "118889" @default.
• W2981021328 abstract "Under the premise of ensuring economic growth, how to achieve the maximum reduction of PM2.5 has become one of the important tasks in China. In this study, we investigated the influencing factors of PM2.5 by employing the Logarithmic Mean Divisia Index (LMDI). The sensitivity of PM2.5 to various emission reduction factors was also explored. Then, by constructing an indicator of PM2.5 decoupling efforts (PDE), PDE of different regions and the degree of efforts caused by various factors were explored. Finally, the spatiotemporal heterogeneity of internal and external factors influencing PDE was explored using the Geographically and Temporally Weighted Regression Model (GTWR). The main results are as follows. (1) The emission coefficient was the main negative driving factor of changes in PM2.5, and per capita GDP was the main positive driving factor. (2) The sensitivity of PM2.5 to emission reduction factors in most regions followed the ranking: emission coefficient > energy intensity > population. In the analysis of the sensitivity of PM2.5 to various emission reduction factors throughout the country, the sensitivity of the emission coefficient was highest in Shandong province. (3) From 2000 to 2014, all provinces made decoupling efforts (PDE>0), among which PDE in Guizhou province were the largest. According to various indicators of decoupling efforts, the contribution of decoupling effort of emission coefficient was the largest. (4) All influencing factors exhibited spatiotemporal heterogeneity. In most regions, the interaction between environmental regulation and industrial structure had a positive impact on PDE, which verifies the existence of the “Porter Hypothesis”. However, in some central and western regions, this interaction exhibited a dynamic change from negative to positive." @default.
• W2981021328 created "2019-10-25" @default.
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• W2981021328 date "2020-02-01" @default.
• W2981021328 modified "2023-10-07" @default.
• W2981021328 title "Causal chain of haze decoupling efforts and its action mechanism: Evidence from 30 provinces in China" @default.
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• W2981021328 doi "https://doi.org/10.1016/j.jclepro.2019.118889" @default.
• W2981021328 hasPublicationYear "2020" @default.
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