Investigating the impact of CO2 emissions on the COVID-19 pandemic by generalized linear mixed model approach with inverse Gaussian and gamma distributions

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dc.contributor.authorIyit, Neslihan
dc.contributor.authorSevim, Ferhat
dc.contributor.authorKahraman, Umran Munire
dc.date.accessioned2024-02-23T14:31:50Z
dc.date.available2024-02-23T14:31:50Z
dc.date.issued2023
dc.departmentNEÜen_US
dc.description.abstractCarbon dioxide (CO2) rate within the atmosphere has been rising for decades due to human activities especially due to usage of fuel types such as coal, cement, flaring, gas, oil, etc. Especially in 2020, COVID-19 pandemic caused major economic, production, and energy crises all around the world. As a result of this situation, there was a sharp decrease in the global CO2 emissions depending on the fuel types used during this pandemic. The aim of this study was to explore the effects of CO2 emissions due to the fuel types on percentage of deaths in total cases attributed to the COVID-19 pandemic using generalized linear model and generalized linear mixed model (GLMM) approaches with inverse Gaussian and gamma distributions, and also to obtain global statistical inferences about 169 World Health Organization member countries that will disclose the impact of the CO2 emissions due to the fuel types during this pandemic. The response variable is taken as percentage of deaths in total cases attributed to the COVID-19 pandemic calculated as (total deaths/total confirmed cases attributed to the COVID-19 pandemic until December 31, 2020)*100. The explanatory variables are taken as production-based emissions of CO2 from different fuel types, measured in tonnes per person, which are coal, cement, flaring, gas, and oil. As a result of this study, according to the goodness-of-fit test statistics, GLMM approach with gamma distribution called gamma mixed regression model is determined as the most appropriate statistical model for investigating the impact of CO2 emissions on the COVID-19 pandemic. As the main findings of this study, 1 t CO2 emissions belonging to the fuel types cement, coal, flaring, gas, and oil per person cause increase in deaths in total cases attributed to the COVID-19 pandemic by 2.8919, 2.6151, 2.5116, 2.5774, and 2.5640%, respectively.en_US
dc.description.sponsorshipSelcuk University [22401002]en_US
dc.description.sponsorshipThis study is supported by Selcuk University Scientific Research Projects (BAP) Coordinators with Research Project Number 22401002.en_US
dc.identifier.doi10.1515/chem-2022-0301
dc.identifier.issn2391-5420
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85152552671en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1515/chem-2022-0301
dc.identifier.urihttps://hdl.handle.net/20.500.12452/15352
dc.identifier.volume21en_US
dc.identifier.wosWOS:000964400700001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherDe Gruyter Poland Sp Z O Oen_US
dc.relation.ispartofOpen Chemistryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCo2 Emissionen_US
dc.subjectCovid-19 Pandemicen_US
dc.subjectGeneralized Linear Modelen_US
dc.subjectGeneralized Linear Mixed Modelen_US
dc.subjectInverse Gaussian Distributionen_US
dc.subjectGamma Distributionen_US
dc.titleInvestigating the impact of CO2 emissions on the COVID-19 pandemic by generalized linear mixed model approach with inverse Gaussian and gamma distributionsen_US
dc.typeArticleen_US

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