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Sustainable synergy via clean energy technologies and efficiency dynamics

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dc.citedby11
dc.contributor.authorYu Z.en_US
dc.contributor.authorKamran H.W.en_US
dc.contributor.authorAmin A.en_US
dc.contributor.authorAhmed B.en_US
dc.contributor.authorPeng S.en_US
dc.contributor.authorid58040949100en_US
dc.contributor.authorid57201870704en_US
dc.contributor.authorid57217247080en_US
dc.contributor.authorid57220201686en_US
dc.contributor.authorid55553916400en_US
dc.date.accessioned2024-10-14T03:17:30Z
dc.date.available2024-10-14T03:17:30Z
dc.date.issued2023
dc.description.abstractThe sustainability paradigm has gained global attention, and the same has been expected from the economies having increasing levels of environmental footprints over the past couple of decades. This research aims to investigate the nexus between clean energy technologies and climate change mitigation among the top ecologically pollutant (TEP) economies during 1996�2020. The research incorporated other drivers of climate change, including energy efficiency, industrialization, and sustainable policies through environmental regulations. The methodological context covers the necessary preliminary tests and the Method of Moment Quantile Regression (MMQR). The preliminary results indicate that TEP economies are interdependent with the heterogenous slope coefficients, stationarity data trends, and cointegrated relationships. The findings from the MMQR unveiled that clean energy technologies tend to mitigate climate change from 0.10th to 0.70th quantiles. Relatedly, energy efficiency reduces the environmental burden across all the quantiles except for the 0.10th one. Conversely, industrialization and economic growth cause an upward shift in climate change among TEP economies across all the quantiles, suggesting a need to shift production-based economies to more service-intensive ones. However, the study found no significant evidence for the nexus between sustainable environmental policies and climate change. The robustness checks also validate the MMQR estimationsen_US
dc.description.abstracthowever, their parameters' magnitude substantially varied. These outcomes encourage policymakers to implement holistic strategies supporting energy innovation, technologies, and efficiency improvements while controlling the adverse effects of industrialization and traditional growth models. � 2023 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.ArtNo113744
dc.identifier.doi10.1016/j.rser.2023.113744
dc.identifier.scopus2-s2.0-85171353355
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85171353355&doi=10.1016%2fj.rser.2023.113744&partnerID=40&md5=5341bb3201e4c71023134fa5eb29b0eb
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/33953
dc.identifier.volume187
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleRenewable and Sustainable Energy Reviews
dc.subjectClean energy technologies
dc.subjectClimate change
dc.subjectEcological footprints
dc.subjectEnergy efficiency
dc.subjectMMQR
dc.subjectSustainable policies
dc.subjectClimate change
dc.subjectEconomics
dc.subjectEnvironmental regulations
dc.subjectMethod of moments
dc.subjectSustainable development
dc.subjectClean energy technology
dc.subjectClimate change mitigation
dc.subjectEcological footprint
dc.subjectEnergy efficiency policies
dc.subjectEnvironmental footprints
dc.subjectIndustrialisation
dc.subjectIndustrialization policy
dc.subjectMoment quantile regression
dc.subjectQuantile regression
dc.subjectSustainable policies
dc.subjectEnergy efficiency
dc.titleSustainable synergy via clean energy technologies and efficiency dynamicsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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