Modeling Nations’ Decarbonisation Potential

Abstract

Global industrialization and excessive consumption of fossil fuels have led to an increase in greenhouse gas emissions and, as a result, rising global temperatures and environmental problems. Growing challenges are setting the world community on the path to reducing carbon emissions as much as possible. Adopted in 2015, the Paris Agreement placed an obligation on the signatory countries to change their development trajectory in order to limit global warming. Responding to this need, the aim of this research is to explore the possibility of applying artificial intelligence techniques in economic decisions to model and analyze decarbonisation capabilities of nations effectively and efficiently. We proposed and validated 11 indicators to define clusters among of 39 countries with similar decarbonisation capabilities over ten-year period. As a result, eight distinct clusters were obtained. The cluster analysis has been conducted in dynamics and identified leader and other clusters, the countries of which should follow leaders by changing their indicators’ values in order to improve their decarbonisation positions in the map. These changes will be associated with transformations of carbon-intensive to zero-carbon economies. We believe that clustering countries by their decarbonisation capabilities have implications for designing zero-carbon policies towards shifting an economy’s sectors to renewable energy consumption or/and supply.