A Comparative Analysis Of Carbon Emissions From Countries Of Varying Fossil Fuel Dependence

While aggregate global policy exists, there is less understanding about individual countries’ pathways to reduce emissions. This study utilizes data analytics techniques to understand unique emissions trends for and what drives those trends for all types of countries. Drivers of emissions are analyzed using the Kaya Identity and a decomposition analysis using all countries with available data. A cluster analysis is performed on all countries with sufficient data to identify how these Kaya factors (population, wealth, energy intensity, and carbon intensity) could be used to identify similar groups of emitters. The best performing clustering occurs when three clusters are selected; one large cluster of 146 countries, an intermediate cluster of 23 countries mainly driven by growth in wealth (per capita gross domestic product), and four countries mainly driven by decreasing energy intensity (total energy supply per unit of GDP) and growing wealth. While the heavy emitters have followed certain pathways to where their emissions are now, this research shows that other countries also have unique drivers and will follow individual emissions pathways that will be critical to understand for achieving global climate targets.