Arcabouço institucional brasileiro para captura e armazenamento de carbono (CCS): o novo mercado de carbono em economia de transição energética.
Bibliographic record
Abstract
This thesis proposes an institutional model for the development of Carbon Capture and Storage (CCS) under the legal and regulatory frameworks in Brazil. This model allows agents using best practices and take advantages of the Brazilian potential in the carbon markets, national and international, based on the CCS technology and under the long-term perspectives. Through a comparative study, the CCS best practices and the implementing policies have been analysed, especially those in the USA, Canada, Norway, the United Kingdom, the Netherlands, the UAE, Saudi Arabia and China. For them, the instruments pursued tried to solve market failures linked to climate change and political specificities, and to incentivize the CCS deployment. The study analysed also how to incentivize the CCS technology through fiscal, regulatory and public policy instruments, considering the premise of reduced impact of costs for consumers (and citizens), the need of dealing with political uncertainties, the long-term responsibilities, and the market failures that inertially work in favour of rent seeking behaviour, inter- and intra-sectorial oligopolies in which, in a broad sense, would tend to verticalize business and reduce the engagement of other than the oil industry and bioenergy agents. In Brazil, the current incentives for the CCS adjacent sectors indicate a potential deployment to the CCS clusters using the production of biofuels, electricity, and particularly for hydrocarbon exploitation under the CO2-EOR. The institutional perception allows us to conclude that the legal, regulatory, normative and framework for the CCS business should be built considering the empowerment of a few regulatory and political authorities (RCA and PCA, respectively), the existing institutions, promoting changes incrementally to maintain the current engagement of prior sectors with high CO2-GHG emissions according to business as usual. In addition, issues related to the complexity of costs transfer to final consumers should be considered, under the risk of compromising public perception and political veto. The model to be implemented in the Brazilian legal framework will need to present solutions to virtually reduce political and long-term risks, cross-chains risks horizontally and vertically.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".