Integrative assessment of sediment quality in acidification scenarios associated with carbon capture and storage operations
Bibliographic record
Abstract
Efforts to stem global change include the application of new technological developments that aim to reduce atmospheric carbon dioxide (CO 2 ) through the carbon capture and storage (CCS) of this greenhouse gas in stable geological structures. In this paper, we assess the potential risks related to the application of CCS technology and the acidification of aquatic ecosystems through CO 2 enrichment. We use the multiple lines of evidence approach (LOEs) to characterize the effects of the acidification with contamination in aquatic sediments. We highlight and discuss the effects of acidification on the LOEs including contamination and mobility of contaminants in sediments, toxicity, macrobenthic community structure, in situ effects, and bioaccumulation–biomagnification processes. We further assess the results of acidification on the toxicity of organic contaminants such as antibiotics or illicit drugs like the freebase form of cocaine (crack). The main goal of using the LOE approach is to distinguish between adverse effects that are associated with contaminants and those related to acidification by enrichment of CO 2 as a result of CCS technology. Previous assessments were not designed or conducted to incorporate an integrative point of view, nor did they employ a weight of evidence approach (WOE) in risk characterization and management of CCS operations and other situations related to acidification by enrichment of CO 2 in the aquatic ecosystem. Based on the findings of this review, the WOE can identify the effects of the acidification on the different LOEs used for sediment quality: contaminant mobility, the adverse effects in organism under laboratory and field conditions, and the bioaccumulation–biomagnification of contaminants. The main strength in using the WOE is the ability of this method to discriminate between LOE responses associated with contamination by different organic and inorganic substances from those related to CO 2 acidification itself. The WOE will significantly improve the risk assessment in areas affected by potential leakages of CO 2 during CCS operations.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".