Risk assessment and management frameworks for carbon capture and geological storage: a global perspective
Bibliographic record
Abstract
Carbon capture and storage (CCS) is included in the list of technological processes that could reduce point source carbon dioxide emissions that contribute to climate change. For geological storage projects, global frameworks for environmental and human health risk assessment (RA) and risk management (RM) have been developed within various regional and national jurisdictions as well as by non-government organisations since the 2005 Intergovernmental Panel on Climate Change Special Report on CCS. This article provides an updated compendium of elaborated RA/RM frameworks in leading jurisdictions for CCS in the regulatory and non-regulatory contexts including online resources. Using a 3- or 4-step RA, there is an emphasis on storage site selection and characterisation; an iterative approach is recommended for RM emphasising monitoring and re-assessment; and other risk-based considerations such as communications and transparency are discussed more frequently in non-government guidance. Comprehensive risk estimation is not yet promoted.
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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 | 0.031 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".