Energy-related CO2 emission forecast for Turkey and Europe and Eurasia A discrete grey model approach

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dc.contributor.authorAyvaz, Berk
dc.contributor.authorKusakci, Ali Osman
dc.contributor.authorTemur, Gul T.
dc.date.accessioned2024-03-13T10:35:38Z
dc.date.available2024-03-13T10:35:38Z
dc.date.issued2017
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractPurpose - The global warming, caused by the anthropogenic greenhouse gases, has been one of the major worldwide issues over the last decades. Among them, carbon dioxide (CO2) is the most important one and is responsible for more than the two-third of the greenhouse effect. Currently, greenhouse gas emissions and CO2 emissions - the root cause of the global warming - in particular are being examined closely in the fields of science and they also have been put on the agenda of the political leaders. The purpose of this paper is to predict the energy-related CO2 emissions through using different discrete grey models (DGMs) in Turkey and total Europe and Eurasia region. Design/methodology/approach - The proposed DGMs will be applied to predict CO2 emissions in Turkey and total Europe and Eurasia region from 2015 to 2030 using data set between 1965 and 2014. In the first stage of the study, DGMs without rolling mechanism (RM) will be used. In the second stage, DGMs with RM are constructed where the length of the rolling horizons of the respected models is optimised. Findings - In the first stage, estimated values show that non-homogeneous DGM is the best method to predict Turkey's energy-related CO2 emissions whereas DGM is the best method to predict the energy-related CO2 emissions for total Europe and Eurasia region. According to the results in the second stage, NDGM with RM (k = 26) is the best method for Turkey while optimised DGM with RM (k = 4) delivers most reliable estimates for total Europe and Eurasia region. Originality/value - This study illustrates the effect of different DGM approaches on the estimation performance for the Turkish energy-related CO2 emission data.en_US
dc.identifier.doi10.1108/GS-08-2017-0031
dc.identifier.endpage454en_US
dc.identifier.issn2043-9377
dc.identifier.issn2043-9385
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85124405527en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage437en_US
dc.identifier.urihttps://doi.org/10.1108/GS-08-2017-0031
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4524
dc.identifier.volume7en_US
dc.identifier.wosWOS:000415629200012en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherEmerald Group Publishing Ltden_US
dc.relation.ispartofGrey Systems-Theory And Applicationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClimate changeen_US
dc.subjectCO2 emissionsen_US
dc.subjectGreenhouse gasesen_US
dc.subjectDiscrete grey modelsen_US
dc.subjectGrey forecastingen_US
dc.titleEnergy-related CO2 emission forecast for Turkey and Europe and Eurasia A discrete grey model approachen_US
dc.typeArticleen_US

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