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A new LDMI decomposition approach to explain emission development in the EU: individual and set contribution

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Abstract

This study breaks down carbon emissions into six effects within the current 28 European Union (EU) countries group, thereafter, they are divided into two different groups (the first 15 countries (EU-15) and the last 13 entering the EU (EU13)). Country-specific highlights are also examined. It analyses the evolution of the effects using a data span that runs from 1990 to 2014, to determine which of them had more impact on the intensity of emissions, while also breaking down the complete period into two distinct periods (before the Kyoto protocol (1990–2004) and after Kyoto (2005–2014)). In order to add more knowledge to the current literature, both the additive and multiplicative decomposition techniques were used to examine carbon dioxide (CO2) emissions and the selected six components: carbon intensity, fossil fuel consumption, energy intensity, oil imports intensity, oil dependence, and population effect. Results point to different adapting velocities for Kyoto targets and necessary compromises. The different velocities were translated into different positive and negative impacts in the change of behavior of CO2 emissions throughout Europe. A stress in the fluctuations in CO2 variations before and after Kyoto and between the two different groups of EU countries could be noticed. Moreover, energy intensity and per capita dependence of oil products were identified as the major responsible components for the total and negative changes of emissions in recent years. A decrease in total changes of emissions is observed due to the fossil fuel energy consumption effect and total petroleum products effects. It is possible to infer from here that increased renewable capacity is contributing in a positive way to eco-efficiency, and should therefore be accounted for in national policymakers’ decisions in the strongest way possible. Results also seem to indicate that per capita dependence of oil products has decreased, despite oil imports intensity constancy and increased renewable capacity, however, with clear heterogeneous effects, worthy of consideration when defining policies.

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Notes

  1. The Europe 2020 strategy sets the following three objectives for climate and energy policy, to be reached by 2020: (1) reducing GHG emissions by at least 20% compared with 1990 levels, (2) increasing the share of renewable energy in final energy consumption to 20%, and (3) moving towards a 20% increase in energy efficiency. These targets are also known as the “20-20-20” targets. Additionally, the strategy points out that the EU is committed to taking a decision to move to a 30% reduction by 2020 compared to 1990 levels (European Commission, 2014).

  2. The author’s results show that the efficiency improvement in CO2 emissions by European countries (EU 27 during the 2001–2008 period) has been enough to override the joint pressure of population (structural effect) and economic growth (activity effect) of CO2 emissions.

  3. It is important to mention here that these factors are dependent and causally linked to each other given that carbon intensity increases when energy intensity and fossil fuel energy consumption increases. With increasing emissions, the higher the oil imports intensity is. When the oil imports intensity increases, this also means that the economic activity increases. In fact, economic activity could be simultaneously cause and consequence of oil imports intensity. Moreover, high net oil imports may also be dependent on per capita dependence of oil products and on population increases, which lead to higher levels of consumption. More relationships details among the factors considered here are provided in the data section. We will also study the interrelated effects here by using both additive and multiplicative decompositions to explain CO2 emissions.

  4. In contrast to Obadi and Korcek (2015), we investigate the drivers of CO2 emissions and not of energy consumption.

  5. The Protocol’s first commitment period started in 2008 and ended in 2012. A second commitment period was agreed on in 2012. It became known as the Doha Amendment to the protocol, in which 37 countries have binding targets, including EU-28.

  6. Austria (1995), Belgium (1958), Bulgaria (2007), Croatia (2013), Cyprus (2004), Czech Republic (2004), Denmark (1973), Estonia (2004), Finland (1995), France (1958), Germany (1958), Greece (1981), Hungary (2004), Ireland (1973), Italy (1958), Latvia (2004), Lithuania (2004), Luxembourg (1958), Malta (2004), Netherlands (1958), Poland (2004), Portugal (1986), Romania (2007), Slovakia (2004), Slovenia (2004), Spain (1986), Sweden (1995), and the UK (1973). EU 15 refers to those whose entrance was prior to 1995, inclusively, whereas EU 13 refers to those whose entrance was after 1995.

  7. The Kaya Identity is an equation for computing the total carbon dioxide (CO2) emissions caused by humans or a specific country. The formula allows to determine the total CO2 emissions by calculating the product of population, GDP per capita, energy use per unit of GDP, and carbon emissions per unit of energy consumed, in accordance to: carbon dioxide emissions = population × per capita GDP × energy intensity × carbon intensity.

  8. In all the presented formulas when using subscript 0, we mean that when considering decompositions by periods the base years 1990 and 2005 were used, but when initially presenting changes through years the 0 subscript is replaced by the t-1 period with respect to t in order to provide changes from year to year.

  9. Eco-efficiency is measured as the ratio between the value added of what has been produced (e.g., GDP) and the added environment impacts of the product or service (e.g., CO2 emissions). The term was first presented by the World Business Council for Sustainable Development in 1992 (WBCSD 2000).

  10. We thank the anonymous referee for advising this explanatory statement inclusion.

  11. Negative values of CO2 variations (Var CO2) mean a decline or reduction of CO2 emissions. Positive values of CO2 variations mean an increase or growth of CO2 emissions.

  12. See footnote 6.

  13. However, the focus of our current analysis was in identifying the relative contribution of the oil imports intensity, eco-efficiency and energy intensity levels, leading us to consider solely the present six factors.

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Acknowledgements

This work was financially supported by the Research Unit on Governance, Competitiveness and Public Policy (project POCI-01-0145-FEDER-006939), funded by FEDER through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia. We thank the anonymous reviewers and the editor for their careful reading of our manuscript and their many insightful comments and suggestions. The authors are solely responsible for any shortcomings, errors or misconceptions that remain.

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  1. GOVCOPP - Research Unit on Governance, Competitiveness and Public Policy (project POCI-01-0145-FEDER-006939); DEGEIT - Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

    Mara Madaleno & Victor Moutinho

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  1. Mara Madaleno
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Correspondence to Mara Madaleno.

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Madaleno, M., Moutinho, V. A new LDMI decomposition approach to explain emission development in the EU: individual and set contribution. Environ Sci Pollut Res 24, 10234–10257 (2017). https://doi.org/10.1007/s11356-017-8547-y

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