Accurate estimation of greenhouse gas (GHG) is essential to meet carbon neutrality targets, particularly through the calculation of direct CO2 emissions from electricity generation. This work reviews and compares emission factor-based methods for accounting direct carbon emissions from electricity generation. The emission factor approach is commonly worldwide used. Empirical comparisons are based on emission factors computed using data from the Italian electricity market. The analyses reveal significant differences in the CO2 estimates according to different methods. This, in turn, highlights the need to select an appropriate method for reliable emissions, which could support effective regulatory compliance and informed policy-making. As concerns, in particular, the market zones of the Italian electricity market, the results underscore the importance of tailoring emission factors to accurately capture regional fuel variations.

Assessing CO2 emissions from electricity generation: a methodological review and comparative analysis

Marina Bertolini
;
Pierdomenico Duttilo;Francesco Lisi
2025

Abstract

Accurate estimation of greenhouse gas (GHG) is essential to meet carbon neutrality targets, particularly through the calculation of direct CO2 emissions from electricity generation. This work reviews and compares emission factor-based methods for accounting direct carbon emissions from electricity generation. The emission factor approach is commonly worldwide used. Empirical comparisons are based on emission factors computed using data from the Italian electricity market. The analyses reveal significant differences in the CO2 estimates according to different methods. This, in turn, highlights the need to select an appropriate method for reliable emissions, which could support effective regulatory compliance and informed policy-making. As concerns, in particular, the market zones of the Italian electricity market, the results underscore the importance of tailoring emission factors to accurately capture regional fuel variations.
2025
IES 2025 - Statistical Methods for Evaluation and Quality
Innovation & Society: Statistics and Data Science for Evaluation and Quality - IES 2025
9788854958494
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3566928
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