Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3881
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dc.contributor.authorPunchihewa, C. R.-
dc.contributor.authorGunaratne, T-
dc.contributor.authorBadurdeen, S-
dc.contributor.authorLiyanage, S-
dc.contributor.authorJayathilaka, R-
dc.date.accessioned2025-01-16T08:55:21Z-
dc.date.available2025-01-16T08:55:21Z-
dc.date.issued2024-12-04-
dc.identifier.issn2783-8862-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3881-
dc.description.abstractTh e North African (NA) region has recorded the highest average Carbon Dioxide (CO2) emissions in Africa and endures a growing rate in Mean Surface Temperature (MST) levels. Focusing on six NA countries: Algeria, Egypt, Libya, Morocco, Sudan, and Tunisia, this study examines the period from 1990 to 2020. A mathemati cal identi ty for anthropogenic CO2 emissions was derived using the Kaya identi ty, expressing individual countries through four drivers: populati on, GDP per capita, energy intensity, and carbon intensity. Panel Regression and Simple Linear Regression (SLR) analysis were further conducted to determine the regional and country-specifi c impact of CO2 emissions on MST. The key fi ndings indicate a notable elevati on in the four drivers among countries, resulti ng in over a 50% increase in CO2 emissions by 2020 compared to 1990. Regression results suggest that regional and local CO2 emissions signifi cantly positi vely impact MST variati ons in the NA region. The study proposes customised local policies to address the drivers of CO2 emissions to miti gate the negati ve climati c consequences of rising CO2 levels.en_US
dc.language.isoenen_US
dc.publisherFaculty of Humanities and Sciences, SLIITen_US
dc.relation.ispartofseriesPROCEEDINGS OF THE 5th SLIIT INTERNATIONAL CONFERENCE ON ADVANCEMENTS IN SCIENCES AND HUMANITIES;312p.-318p.-
dc.subjectCarbon dioxide emissionsen_US
dc.subjectMean surface temperatureen_US
dc.subjectKaya identi ty frameworken_US
dc.subjectPanel regressionen_US
dc.titleUnveiling Climate Change in North Africa Through Carbon Dioxide Emissions and Surface Temperature Dynamics: A Panel Regression and Kaya Identi ty Analysisen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.54389/DHIJ9533en_US
Appears in Collections:Proceedings of the SLIIT International Conference on Advancements in Science and Humanities2024 [SICASH]

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