INNOVATIVE REGULATORY AND FINANCIAL PARAMETERS FOR ADVANCING CARBON CAPTURE AND STORAGE TECHNOLOGIES
Bibliographic record
Abstract
In the post-industrial age, the realisation of inherent technical innovation potentials requires that stakeholders develop flexible, cooperation-based frameworks if first mover opportunities and advantages are to be realised. In the Paris Agreement5 implementation context, carbon capture and storage technologies have emerged as a complementary adjunct to climate change mitigation and a diversified energy mix. However, developing the technology is not without technical and financial risks. The challenge for key stakeholders, primarily (but not exclusively) government and industry counterparts is to develop mutually reinforcing strategies, regulations and policies for testing and commercialising Carbon Capture and Storage (“CCS”)technologies and networks, as that will be determinative of their fate. In the Paris Agreement implementation period, the UK, for example, has indicated a commitment to bold greenhouse gas reductions(57% by 2030),and investment in CCS, as part of the ambitious emissions reductions targets set forth by the European Union, the deployment of which is meant to count for 20% of the greenhouse gas emissions captured by 2030. This has subsequently resulted in plans for several pilot CCS plants on UK soil. The up-scaling of CCS to the demonstration level, however, is dependent not only on the presence of sufficient interest and funding –an ongoing issue in the UK both pre-and post-Brexit-but also on the existence of appropriate regulatory conditions and options for additional private financing by industrial stakeholders. Furthermore, it is important to note that the up-scaling of projects from pilot to demonstration, and further on to a commercial-scale, is materializing in the context of a global financial crisis and a dip in investment trust in high-risk ventures. The development of CCS projects in individual states, is not only influenced by national regulatory regimes, policy developments, and fluctuations in financial markets, but is also dependent upon the legislative signals given from supra-national bodies and binding international agreements. In Europe, the CCS Directive’s approach to long term environmental and related financial risk has led to the current state of regulatory and financial uncertainty, thereby, giving rise to potentially uninsurable liabilities which dis-incentivise private sector investment in CCS technology. This is in contrast with legislation in competing states including the United States, Norway, Canada and Australia. There is every indication that the paramount issue standing in the way of CCS is uncertainty over regulated financial security requirements for site operators and the nature and attribution of liability arising from leakage. This uncertainty could be addressed by a combination of insurance for storage sites and a robust permitting process, which would minimize the likelihood of leakage to virtually zero. There are, therefore, excellent reasons for national and international law and policymakers to seriously consider a more careful and tailored legislative and policy mix, so that regulatory oversight is in balance with innovative financial, insurance and liability mechanisms. In addition to exploring this subject matter, the article offers a number of recommendations for flexible, stakeholder partner-based advancement of CCS technology potentials in climate change and related environmental regulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".