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dc.contributor.authorWang, Yaxian
dc.contributor.authorBaležentis, Tomas
dc.date.accessioned2023-09-18T20:52:20Z
dc.date.available2023-09-18T20:52:20Z
dc.date.issued2023
dc.identifier.issn0195-9255
dc.identifier.other(crossref_id)152242688
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/153327
dc.description.abstractAs the share of renewable energy increases in the energy-mix, tracking energy intensity (EI) dynamics and determinants thereof is a significant issue of energy economics related to power resilience. Previous decomposition studies have hardly evaluated the effects of absolute factors on the intensity indicator such as EI. The present study proposes a novel generalized Divisia index (GDI) model for intensity factor decomposition and combined it with Tapio index. The case of China's power sector during 2000–2020 is considered. The results suggest that the complexity of EI reduction is increasing from 2006 to 2010 to 2016–2020 though the period of 2000–2020 witnessed the improvement of energy efficiency, and the provincial EI exhibits a distribution trend of “high in the north and low in the south, high in the east and low in the west”. The decomposition results indicate that the energy consumption is the single factor responsible for EI increase, whereas energy structure and technology are the major forces contributing to EI mitigation. The power output and energy consumption exhibit decoupling status from EI in most provinces, but the decoupling situation was not stable and the difficulty of decoupling increases since 2016–2020.eng
dc.formatPDF
dc.format.extentp. 1-13
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyEngineering Index
dc.relation.isreferencedbyElsevier Biobase
dc.source.urihttps://www.sciencedirect.com/science/article/pii/S0195925523002238
dc.titleHow to improve the resilience of power generation from energy intensity perspective? Evidence from the generalized Divisia index approach
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references59
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionBeijing Wuzi University
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Management
dc.subject.researchfieldS 004 - Ekonomika / Economics
dc.subject.studydirectionJ01 - Ekonomika / Economics
dc.subject.vgtuprioritizedfieldsEV02 - Aukštos pridėtinės vertės ekonomika / High Value-Added Economy
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enenergy intensity
dc.subject.enpower sector
dc.subject.enGeneralized Divisia index
dc.subject.enTapio indicator
dcterms.sourcetitleEnvironmental impact assessment review
dc.description.volumevol. 103
dc.publisher.nameElsevier Inc.
dc.publisher.cityNew York
dc.identifier.doi152242688
dc.identifier.doi1-s2.0-S0195925523002238
dc.identifier.doiS0195-9255(23)00223-8
dc.identifier.doi0
dc.identifier.doi001059017400001
dc.identifier.doi10.1016/j.eiar.2023.107257
dc.identifier.elaba174495194


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