Unveiling Climate Change in North Africa Through Carbon Dioxide Emissions and Surface Temperature Dynamics: A Panel Regression and Kaya Identity Analysis

The 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 mathematical identity for anthropogenic CO2 emissions was derived using the Kaya identity, expressing individual countries through four drivers: population, 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-specific impact of CO2 emissions on MST. The key findings indicate a notable elevation in the four drivers among countries, resulting in over a 50% increase in CO2 emissions by 2020 compared to 1990. Regression results suggest that regional and local CO2 emissions significantly positively impact MST variations in the NA region. The study proposes customised local policies to address the drivers of CO2 emissions to mitigate the negative climatic consequences of rising CO2 levels. Keywords: Carbon dioxide emissions; Mean surface temperature; Kaya identity framework; Panel regression