Energy-related CO2 emission forecast for Turkey and Europe and Eurasia A discrete grey model approach
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Emerald Group Publishing Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Purpose - 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.
Açıklama
Anahtar Kelimeler
Climate change, CO2 emissions, Greenhouse gases, Discrete grey models, Grey forecasting
Kaynak
Grey Systems-Theory And Application
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
7
Sayı
3
