Cross-border cooperation on CO2 transport and sequestration: the case of Germany and Norway
Bibliographic record
Abstract
If two different jurisdictions are involved in the Carbon Capture and Storage (CCS) chain, CO2 handling needs to be harmonized across borders and interface issues should be resolved (e.g. technical and operational standards, certification, transfer of ownership and risk, etc.). Similar to the imbalance which exists between the demand for fossil fuels between importing and exporting countries, suitable geological formations for CO2 storage may not exist in the highest-emitting countries, which calls for a need to export CO2 to countries with more suitable storage sites. It may also be in the interest of fossil fuel exporting countries to help their customers to dispose of CO2 stemming from imported hydrocarbons, as importing countries may have no other option due to the lack of sequestration potential (e.g. Japan). This will involve exporting and importing of CO2 across borders, relying on offshore transport by ships or via pipelines in most cases. Thus far, such examples include the transport of CO2 by onshore pipelines from the Boundary Dam project in Canada to the Weyburn project in the US, and the upcoming Longship project which envisages cross-border transport of CO2 via shipping from the UK and EU countries to Norway. All other projects so far have been within one jurisdiction. However, most recently (August 2022), Northern Lights signed a first-of-its-kind commercial agreement for cross-border CO2 capture and transport, where, from 2025, CO2 will be captured, compressed and liquified in the Netherlands, to be transported and stored in Norway. It is expected that other similar ventures will be established, making the publication of this study all the more timely. This paper appraises a specific case study of cross-border CO2 transport from Germany to Norway. It is argued that the opportunity offered by Norway to sequester large volumes of CO2 under its shelf in the North Sea is one that Germany should use to meet its ambitious net-zero goal for 2045. While the infrastructure needed on both sides requires vast investments, coordination and regulatory and legal efforts, endeavours of comparable scale have been achieved by cooperation between both countries in the past such as the successful development of the Troll gas export project and the infrastructure linked to it both offshore and onshore and the development of its market in less than 20 years. One important conclusion is the need to develop a joint vision on the necessary development in the short time (and the limited size of the CO2 budget) left, and to create procedures and institutions needed for cooperation and coordination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".