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dc.contributor.authorUtkucan Şahin
dc.contributor.authorYan,Chen
dc.date.accessioned2023-10-25T07:55:08Z
dc.date.available2023-10-25T07:55:08Z
dc.date.issued2023en_US
dc.identifier.citationŞahin, U., & Chen, Y. (2023). Assessing the current and future effects of Covid-19 on energy related-CO2 emissions in the United States using seasonal fractional grey model. Energy Strategy Reviews, 50, 101234.en_US
dc.identifier.issn2211467X
dc.identifier.urihttps://doi.org/10.1016/j.esr.2023.101234
dc.identifier.urihttps://hdl.handle.net/20.500.12809/11036
dc.description.abstractAccurate CO2 forecasting plays an important role in energy planning. However, in the annual forecasting studies on CO2 emissions, the seasonal effects cannot be predicted. To overcome this problem, this study proposed a novel prediction model based on the seasonally optimised fractional nonlinear grey Bernoulli model (SOFANGBM(1,1)), combining the seasonal fluctuation technique with optimisation of the background, power index, and fractional order values. The proposed novel model offers two important improvements in prediction performance: (1) This model combined optimised fractional nonlinear grey Bernoulli model (OFANGBM(1,1)) with the seasonal fluctuation technique to enable monthly and quarterly predictions (2) The seasonally optimised fractional nonlinear grey Bernoulli model (SFANGBM(1,1)) was improved by optimising the background value. CO2 emissions had the largest share in global GHG emissions, and the United States was the second largest CO2 emission emitter worldwide after China in 2019. However, cases and deaths from Covid-19 continue in the United States, and important questions arise: How has Covid-19 affected CO2 emissions by fossil fuel type in the past, and how will it reshape them in the future? This study aimed to analyse how Covid-19 affects CO2 emissions from fossil fuels in the U.S., how it will reshape its future, and also contribute to Sustainable Development Goals (SDGs). Quarterly CO2 emissions from coal, natural gas, petroleum, and total CO2 emissions in the U.S. were forecasted using a novel grey prediction model under pandemic and pandemic-free scenarios. The pandemic-free scenario determined the CO2 emissions gap due to Covid-19, and the pandemic scenario presented forecasted results of quarterly and annual CO2 emissions by 2025. The prediction performance was tested from 2022-Q1 to 2022-Q4 by simulated from 2015-Q1 to 2021-Q4. Using the SOFANGBM(1,1), Covid-19 caused 2 %, 2 %, 16 %, and 12 % reductions in CO2 emissions from coal, natural gas, petroleum, and total CO2 emissions, respectively, in 2020. SOFANGBM(1,1) also forecasts that total CO2 emissions will reach 4520.6 Mt by 2025.en_US
dc.item-language.isoengen_US
dc.publisherElsevier Ltden_US
dc.relation.isversionofhttps://doi.org/10.1016/j.esr.2023.101234en_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCovid-19en_US
dc.subjectForecastingen_US
dc.subjectCO2 emissionen_US
dc.subjectSeasonal grey modelen_US
dc.subjectFractional orderen_US
dc.subjectOptimisationen_US
dc.titleAssessing the current and future effects of Covid-19 on energy related-CO2 emissions in the United States using seasonal fractional grey modelen_US
dc.item-typearticleen_US
dc.contributor.departmentMÜ, Teknoloji Fakültesi, Enerji Sistemleri Mühendisliği Bölümüen_US
dc.contributor.authorID0000-0002-5869-8451en_US
dc.contributor.institutionauthorUtkucan Şahin
dc.identifier.volume50en_US
dc.relation.journalEnergy Strategy Reviewsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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