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- W2903001415 abstract "The world has witnessed unparalleled economic development over the past decades, but accompanied by large amount of carbon emissions, which triggered the global warming. It is critical for the global sustainable development by decoupling economic growth from carbon emissions at country level, specifically for the largest emitter, China. This study conducts a decoupling analysis from the perspective of carbon intensity (CI), per capita carbon emissions (PC) and total carbon emissions (TC) with reference to 30 Chinese provinces, covering the period of 2001-2015. Based on the Log Mean Divisa Index (LMDI) method, the effects of energy structure (ES), energy intensity (EI), economic output (EO) and population size (P) on TC at provincial level are investigated. Results show that: (1) a strong decoupling relation between GDP and CI is found in most provinces except Hainan, Qinghai and Xinjiang, while there is large room for China to decouple completely from PC and TC; (2) EO and EI are the dominated inhibiting and promoting factors respectively for carbon emission reduction; (3) ES effect on increasing carbon emission changes between positive and negative, while P has a positive but insignificant effect on the increase of carbon emissions for most provinces. The results help local governments formulate measures to coordinate regional economic development and carbon emission reduction." @default.
- W2903001415 created "2018-12-11" @default.
- W2903001415 creator A5006161546 @default.
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- W2903001415 creator A5029453097 @default.
- W2903001415 creator A5063098485 @default.
- W2903001415 creator A5067698258 @default.
- W2903001415 date "2019-03-01" @default.
- W2903001415 modified "2023-10-12" @default.
- W2903001415 title "Decoupling China's economic growth from carbon emissions: Empirical studies from 30 Chinese provinces (2001–2015)" @default.
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- W2903001415 doi "https://doi.org/10.1016/j.scitotenv.2018.11.384" @default.
- W2903001415 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30529962" @default.
- W2903001415 hasPublicationYear "2019" @default.
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