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Exploring the macro-scale CO2 mitigation potential of photovoltaics and wind energy in Europe's energy transition

Authors: Usubiaga, A; Acosta-Fernández, J; McDowall, W; Li, F;

Exploring the macro-scale CO2 mitigation potential of photovoltaics and wind energy in Europe's energy transition

Abstract

Replacing traditional technologies by renewables can lead to an increase of emissions during early diffusion stages if the emissions avoided during the use phase are exceeded by those associated with the deployment of new units. Based on historical developments and on counterfactual scenarios in which we assume that selected renewable technologies did not diffuse, we conclude that onshore and offshore wind energy have had a positive contribution to climate change mitigation since the beginning of their diffusion in EU27. In contrast, photovoltaic panels did not pay off from an environmental standpoint until very recently, since the benefits expected at the individual plant level were offset until 2013 by the CO2 emissions related to the construction and deployment of the next generation of panels. Considering the varied energy mixes and penetration rates of renewable energies in different areas, several countries can experience similar time gaps between the installation of the first renewable power plants and the moment in which the emissions from their infrastructure are offset. The analysis demonstrates that the time-profile of renewable energy emissions can be relevant for target-setting and detailed policy design, particularly when renewable energy strategies are pursued in concert with carbon pricing through cap-and-trade systems.

Countries
United Kingdom, Germany
Keywords

690, Renewable energy, ddc:600, Technological innovation, CO2 emissions, Climate change mitigation, Carbon payback time

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    14
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
hybrid