Probing the debromination of the flame retardant decabromodiphenyl ether in sediments of a boreal lake
Bibliographic record
Abstract
After decades of use of polybrominated diphenyl ethers (PBDEs) as flame retardants, a large reservoir of these toxins has accumulated in ecosystems worldwide. The present study used an innovative approach to examine whether the fully brominated PBDE decabromodiphenyl ether (decaBDE) degrades to more toxic congeners in aquatic environments. The authors incubated intact sediment microcosms with high-purity [(13)C]decaBDE in a remote boreal lake to assess its debromination under ambient conditions. Although the addition of [(13)C]decaBDE increased total PBDE concentrations in sediment more than 10-fold, the relative amount of [(13)C]decaBDE in sediment did not change significantly over a 1-mo incubation. However, observation of small quantities of lower-brominated [(13)C]BDEs lent support to the hypothesis that decaBDE is slowly debrominated. The authors observed a significant increase in octaBDEs and nonaBDEs in profundal, but not littoral, sediment over 30 d. A second experiment in which sediment was incubated under different light and oxygen regimes yielded a surprising result-oxygen significantly stimulated the formation of octaBDEs and nonaBDEs. The authors also conducted a large-scale in situ enclosure experiment in which they followed the fate of experimentally added decaBDE in sediment over 26 mo, but that study yielded little evidence of decaBDE debromination. Overall, the authors suggest that the debromination of decaBDE occurs very slowly, if at all, in natural sediment of boreal lakes, in contrast to the rapid degradation kinetics reported by most laboratory-based studies, which are usually conducted by dissolving decaBDE in organic solvents. The findings reinforce the need for field studies on contaminant fate to inform environmental policy decisions.
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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 | 0.000 | 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 | 0.001 | 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 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".