Exploring the Linkages Between Carbon Markets and Sustainable Innovations in the Energy Sector: Lessons from the EU Emissions Trading Scheme

  • Lisa Knoll
  • Anita Engels
Part of the Sustainability and Innovation book series (SUSTAINABILITY)


The European Emissions Trading Scheme (EU ETS) is a central instrument of European climate policy and the first large-scale multi-national greenhouse gas trading programme in the world. It was referred to as the “grand new policy experiment” (Kruger and Pizer 2004). One of the central promises of emissions trading is to provide a price signal on the basis of which companies can calculate whether any shortage of emission allowances should be met with buying more allowances in the trading scheme or with reducing CO2 emissions. From these micro-rational calculations the most efficient CO2 abatement at the macro-level will ideally emerge, as emissions will be reduced where the costs for reducing them is lowest – “an epoch-making means of cost-effective control which can solve future global environmental problems” (Svendsen 1999: 232). Emissions trading thus has a potential to trigger sustainable innovations in the sense that companies face incentives to improve their CO2 performance (Stankeviciute et al. 2008). Still, the EU ETS has been criticised for many short-comings, among others for not providing triggers of innovation decisions in companies due to weak price signals. In a recent study on German companies in the CO2 market the authors point out that most of the CO2 reduction measures in Phase I of the EU ETS were only an unintended effect of emissions trading (Detken et al. 2009: 6–7). However, while the price of CO2 allowances was high in the first year of the EU ETS, some electricity providers mentioned having an incentive to supply electricity from gas-fired plants rather than from more carbon-intensive coal-fired plants (MacKenzie 2009: 169).


Emission Trading Electricity Market Organisational Innovation Emission Trading Scheme Sustainable Innovation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Physica-Verlag HD 2012

Authors and Affiliations

  • Lisa Knoll
    • 1
  • Anita Engels
    • 1
  1. 1.Centre for Globalization and GovernanceUniversity of HamburgHamburgGermany

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