Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach

By P. González, Manuel Landajo, M. J. Presno. 2014

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Aggregate CO2 emitted to the atmosphere from a given region could be determined by monitoring several distinctive components. In this paper we propose five decomposition factors: population, production per capita, fuel mix, carbonization and energy intensity. The latter is commonly used as a proxy for energy efficiency. The problem arises when defining this concept, as there is little consensus among authors on how to measure energy intensity (using either physical or monetary activity indicators). In this paper we analyse several measurement possibilities, presenting and developing a number of approaches based on the LMDI (logarithmic-mean Divisia index) methodology, to decompose changes in aggregate CO2 emissions. The resulting methodologies are so-called MB (monetary based), IR (intensity refactorization) and AR (activity revaluation) approaches. Then, we apply these methodologies to analyse changes in carbon dioxide emissions in the EU (European Union) power sector, both as a whole and at country level. Our findings show the strong impact of changes in the energy mix factor on aggregate CO2 emission levels, although a number of differences among countries are detected which lead to specific environmental recommendations.

Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/1cb17e97a99c0f3c682f621d33221f360966414b

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Citations in the corpus

Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis (2015, background): “Growing environmental awareness, development of clean renewable energy, use of more efficient technologies, and environmental taxation, made that possible (Fernández González et al ., 2014b).”
Empirical analysis on the factors influencing national and regional carbon intensity in China (2016, background): “Based on index decomposition, studies of the factors influencing carbon intensity generally broke it down into energy intensity, industrial structure, and energy structure, on both national and regional levels [47,48].”