Assessment of the decarbonization efficiency in the European Union: machine learning approach

Šimić, Goran and Radovanović, Mirjana and Filipović, Sanja (2025) Assessment of the decarbonization efficiency in the European Union: machine learning approach. Energy, Sustainability and Society, 15 (52). ISSN 2192-0567

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Abstract

The European Union has established a strategic objective to attain carbon neutrality across the continent by the year 2050; however, this complex undertaking is shaped by a variety of influencing factors. It is particularly important to monitor the effects of such a long-term strategy, as it will influence all aspects of the European Union’s sustainable energy development as well as the welfare of its citizens. Since no universally accepted methodology exists for tracking the effects of decarbonization, the use of machine learning as a method of artificial intelligence is proposed—not only to generate concrete results but also to evaluate its applicability for this purpose. The main objective of this research is to assess the trends of 13 selected energy indicators that are vital to the decarbonization initiative. The research was conducted on a sample of 27 countries for the period from 2013 to 2030 using a novel predictive model developed in the Python runtime environment.

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