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dc.contributor.authorŞahin, Utkucan
dc.date.accessioned2020-11-20T14:40:33Z
dc.date.available2020-11-20T14:40:33Z
dc.date.issued2019
dc.identifier.issn0959-6526
dc.identifier.issn1879-1786
dc.identifier.urihttps://doi.org/10.1016/j.jclepro.2019.118079
dc.identifier.urihttps://hdl.handle.net/20.500.12809/767
dc.description0000-0002-5869-8451en_US
dc.descriptionWOS: 000487237100076en_US
dc.description.abstractThis study aims to contribute to the development of energy policies for Turkey's greenhouse gas (GHG) emissions in the future. For this purpose, linear and nonlinear metabolic grey models are combined with the optimization technique to obtain more accurate forecasting results. Optimization technique provides estimation of the parameters in metabolic grey model (MGM(1,1)) and nonlinear metabolic grey model (NMGM(1,1)). In this study, MGM(1,1), NMGM(1,1), optimized metabolic grey model OMGM(1,1), and optimized nonlinear metabolic grey model (ONMGM(1,1)) are applied for prediction of Turkey's GHG emissions including the Land Use, Land Use Change and Forestry (LULUCF), excluding LULUCF and from the energy sector. The ONMGM(1,1) gives more accurate results than the others from 1995 to 2016. The MAPE values of the ONMGM(1,1) are 4.80%, 4.14% and 5.19% for Turkey's GHG emissions with LULUCF, without LULUCF and from the energy sector, respectively. On the other hand, results of the ONMGM(1,1) show that the annual growth rates are forecasted as 0.56%, 0.66% and 0.49% for Turkey's GHG emissions with LULUCF, without LULUCF and from the energy sector, respectively, from 2017 to 2025. Furthermore, Turkey's highest GHG emissions with LULUCF, without LULUCF and from the energy sector are estimated by MGM(1,1) as 606.9 Mt of CO2 equivalent, 726.4 Mt of CO2 equivalent and 585.2 Mt of CO2 equivalent in 2025, respectively. According to Turkey's Intended Nationally Determined Contribution (INDC), target of its GHG emissions including LULUCF is estimated as 934 Mt of CO2 equivalent in a Business-As-Usual scenario and 790 Mt of CO2 equivalent in a Mitigation scenario for the year 2025. Therefore, this study presents lower values of Turkey's GHG emissions with LULUCF than the values of Turkey's INDC for the year 2025. Additionally, results of this study present that energy sector has the largest share of Turkey's GHG emissions from 2017 to 2025. Therefore, Turkish Government should develop policies to use energy more efficiently and to increase the capacity of renewable energy sources in electricity generation. Especially, Turkey's ambition to increase the share of renewable energy in total is very assertive. This can be seen from the Turkey's 11th Development Plan. According to the Plan, the share of total renewable energy and natural gas in total electricity generation is going to be increased from 32.5% in 2018 to 38.8% in 2023 and to be decreased from 29.85% in 2018 to 20.7% in 2023, respectively. (C) 2019 Elsevier Ltd. All rights reserved.en_US
dc.item-language.isoengen_US
dc.publisherElsevier Sci Ltden_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectForecastingen_US
dc.subjectTurkeyen_US
dc.subjectGreenhouse Gas Emissionsen_US
dc.subjectMetabolic Grey Modelen_US
dc.subjectNonlinear Metabolic Grey Modelen_US
dc.subjectOptimizationen_US
dc.titleForecasting of Turkey's greenhouse gas emissions using linear and nonlinear rolling metabolic grey model based on optimizationen_US
dc.item-typearticleen_US
dc.contributor.departmentMÜ, Teknoloji Fakültesi, Enerji Sistemleri Mühendisliği Bölümüen_US
dc.identifier.doi10.1016/j.jclepro.2019.118079
dc.identifier.volume239en_US
dc.relation.journalJournal of Cleaner Productionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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