dc.contributor.author | Utkucan Şahin | |
dc.contributor.author | Yan,Chen | |
dc.date.accessioned | 2023-10-25T07:55:08Z | |
dc.date.available | 2023-10-25T07:55:08Z | |
dc.date.issued | 2023 | en_US |
dc.identifier.citation | Şahin, 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.issn | 2211467X | |
dc.identifier.uri | https://doi.org/10.1016/j.esr.2023.101234 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12809/11036 | |
dc.description.abstract | Accurate 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.iso | eng | en_US |
dc.publisher | Elsevier Ltd | en_US |
dc.relation.isversionof | https://doi.org/10.1016/j.esr.2023.101234 | en_US |
dc.item-rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Covid-19 | en_US |
dc.subject | Forecasting | en_US |
dc.subject | CO2 emission | en_US |
dc.subject | Seasonal grey model | en_US |
dc.subject | Fractional order | en_US |
dc.subject | Optimisation | en_US |
dc.title | Assessing the current and future effects of Covid-19 on energy related-CO2 emissions in the United States using seasonal fractional grey model | en_US |
dc.item-type | article | en_US |
dc.contributor.department | MÜ, Teknoloji Fakültesi, Enerji Sistemleri Mühendisliği Bölümü | en_US |
dc.contributor.authorID | 0000-0002-5869-8451 | en_US |
dc.contributor.institutionauthor | Utkucan Şahin | |
dc.identifier.volume | 50 | en_US |
dc.relation.journal | Energy Strategy Reviews | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |