CO2 Capture, Utilization, and Storage (CCUS) Policy Trends in the European Union (EU) and Major European Countries
Bibliographic record
Abstract
According to the 1st Working Group (WG) report of the 6th Assessment Report (AR 6) of the Intergovernmental Panel on Climate Change (IPCC) published on August 9, 2021, the average global temperature is now higher than before industrialization. It has already risen 1.09〬 C, and the average carbon dioxide concentration in the atmosphere is 410ppm, the highest level in 2 million years. If carbon emissions continue according to the current trend, it is highly likely that the temperature rise limit target according to the Paris Agreement and the threshold of an irreversible climate catastrophe will reach 1.5〬 C within 20 years at the most. With such a prospect, it is not enough to emphasize the importance of technology development to reduce greenhouse gas, which threatens the survival of mankind. Carbon Dioxide Capture, Utilization and Storage (CCUS) technology, which is a representative technology for large-scale reduction of greenhouse gas, which is the main cause of global warming, has recently attracted attention. The national vision of achieving carbon neutrality in 2050 is closely related to the implementation of the Nationally Determined Contribution (NDC) under Articles 3 and 4 of the Paris Agreement. Carbon dioxide capture, utilization and storage (CCUS) technology is a representative technology for large-scale reduction of greenhouse gases closely related to achieving carbon neutrality in 2050. In order to increase the effectiveness of Korean CCUS technology, it is important to consider overseas advanced CCUS policies. Accordingly, in this report, examples of carbon dioxide capture, transport, utilization and storage (CCUS) projects that can be seen as part of the Green New Deal policies of the European Union (EU) and major European countries and carbon dioxide in major European countries such as Germany, Norway and the United Kingdom Recent policy trends on capture, transport, utilization and storage (CCUS) are reviewed. Through this, first, CCUS is an important means to achieve 2050 carbon growth by supplementing the problems of new and renewable energy such as intermittent, inefficiency, and noise pollution. Because it is important, regular and occasional disclosure of information to residents and enhancement of public acceptance through resident meetings and seminars are very important. Third, the United States, Canada and China are CCUS powerhouses as well as major European countries such as Germany, Norway, the United Kingdom and the Netherlands. As above mentioned CCUS powerhouses are spurring CCUS research and development, if Korea neglects research and development on CCUS, it will fall into a technology-dependent country. Through this, implications such as that Korea should achieve the carbon-neutral 2050 target and achieve sustainable development were derived.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".