Towards Net Zero Emissions - Creating Incentives for BECCS and DACCS

In the paper published in the European Liberal Forum by Lars Zetterberg and Kenneth Mollersten, the authors study the incentives and funding structures that are necessary for the deployment of CDR methods. In particular, they focus on bioenergy with carbon capture and storage (BECCS) and direct air capture and carbon storage (DACS). In doing so, they first highlight the need for CDR and the pace at which technologies whose deployment are necessary for the utilization of CDR should be scaled gradually. Then, they provide an overview regarding the current state of play with respect to BESCCS and DACS. They use this analysis to compare the BECCS and DACCS with other CDR methods and highlight the main areas of risks and difficulties. In addition, they study the existing EU policies and new projects that have been developed in EU countries. To tackle the inadequacy of the current incentives that act as drivers for the deployment of BECCS and DACCS, they propose the introduction of five models, namely ‘state support programs, quota obligations, emissions trading, trade between states and voluntary markets.’ Lastly, they discuss the benefits that can be driven by and the barriers against the implementation of these models with a focus on the role that the EU and EU member states can play in ensuring their implementation.

The key takeaways with respect to the utilization of each model:

  • Model 1 - State support programs: The purchase of CDR outcomes via targeted programs by states as part of this model can drive the creation of first facilities that capture carbon. However, states’ engagement in such transactions can prove to be risky due to the utilization of taxpayers’ money for the purchases.

  • Model 2 - Quota Obligations: Under this model, states impose a quota obligation requiring the undertakings operating in sectors that pose challenges for emission abatement such as agriculture, transport and waste burning to buy credits to remove carbon via BECCS or DACCS in proportions that match their emission levels. While this model expands the scope of the stakeholders that can finance CDR to include not only states but also private entities, it can create a financial burden for consumers who may have to bear the costs.

  • Model 3 - Emission Trading: This model allows the use of CDR-credits by those that trade emissions as part of the EU ETS as an alternative for emission abatement, decreasing the costs beared by the participants of the EU ETS. However, the adoption of this model can deter stakeholders from reducing emissions, leading them to purchase CDR instead of taking mitigation action. In order to prevent carbon removals from being subjected to excessive use, a mechanism should be established that monitors and limits the credits that enter the EU ETS market.

  • Model 4 - Trade between States: This model creates room for states to cooperate under Article 6 of the Paris Agreement to reach their Nationally Determined Contributions in order to increase the level of general ambition and drive greater emission reductions compared to the abatement outcomes that would emerge in the absence of cooperation.

  • Model 5 - Voluntary Markets: This model allows private persons and entities to buy credits to be used for carbon removal activities so as to compensate for their adverse impact upon climate. However, cases of double claiming may arise in situations where a given carbon removal activity is counted as progress towards reaching climate goals by both private persons or entities and states. This risk can be eliminated through the changes that can be made to emission reporting, which necessitates the amendment of current reporting rules.

Model 1 can be significant during initial phases for the acquisition of experience regarding financing. Other models, particularly models 2 and 3, are necessary for expanding the sources of finance and their volume.

Read the full paper here: Towards Net Zero Emissions - Creating Incentives for BECCS and DACCS Policy Paper

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