{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T22:31:34Z","timestamp":1771885894731,"version":"3.50.1"},"reference-count":42,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2017,11,6]],"date-time":"2017-11-06T00:00:00Z","timestamp":1509926400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2017,11,6]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>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 (CO<jats:sub>2<\/jats:sub>) is the most important one and is responsible for more than the two-third of the greenhouse effect. Currently, greenhouse gas emissions and CO<jats:sub>2<\/jats:sub> emissions \u2013 the root cause of the global warming \u2013 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 CO<jats:sub>2<\/jats:sub> emissions through using different discrete grey models (DGMs) in Turkey and total Europe and Eurasia region.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The proposed DGMs will be applied to predict CO<jats:sub>2<\/jats:sub> 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>In the first stage, estimated values show that non-homogeneous DGM is the best method to predict Turkey\u2019s energy-related CO<jats:sub>2<\/jats:sub> emissions whereas DGM is the best method to predict the energy-related CO<jats:sub>2<\/jats:sub> emissions for total Europe and Eurasia region. According to the results in the second stage, NDGM with RM (<jats:italic>k<\/jats:italic>=26) is the best method for Turkey while optimised DGM with RM (<jats:italic>k<\/jats:italic>=4) delivers most reliable estimates for total Europe and Eurasia region.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study illustrates the effect of different DGM approaches on the estimation performance for the Turkish energy-related CO<jats:sub>2<\/jats:sub> emission data.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-08-2017-0031","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T07:21:45Z","timestamp":1507879305000},"page":"436-452","source":"Crossref","is-referenced-by-count":28,"title":["Energy-related CO<sub>2<\/sub> emission forecast for Turkey and Europe and Eurasia"],"prefix":"10.1108","volume":"7","author":[{"given":"Berk","family":"Ayvaz","sequence":"first","affiliation":[]},{"given":"Ali Osman","family":"Kusakci","sequence":"additional","affiliation":[]},{"given":"G\u00fcl T.","family":"Temur","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"2013","key":"key2020120423121053100_ref001","first-page":"1702","article-title":"CO2 greenhouse emissions in Oman over the last forty-two years: review","volume":"52","year":"2015","journal-title":"Renewable & Sustainable Energy Reviews"},{"key":"key2020120423121053100_ref002","unstructured":"Acar, S., Kitson, L. and Bridle, R. 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