Spatial and Temporal Trends of Dissolved Polybrominated Diphenyl Ethers and Non-BDE Flame Retardants in the Aquatic Environment across Countries
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Measuring dissolved concentrations of polybrominated diphenyl ethers (PBDEs) and non-BDE flame retardants on a global scale provides critical insights into the effectiveness of the Stockholm Convention. In the present study, we deployed passive sampling devices at 43 seawater and freshwater sites covering 21 countries from 2016 to 2020. The detection frequencies were 20–94% for BDE congeners and 33–42% for dechlorane plus, higher than those (0–20%) for other target compounds. The median concentrations of dissolved Σ 9 PBDE (sum of BDE-28, -47, -66, -85, -99, -100, -153, -154, and -183) were 0.28 and 0.64 pg L –1 in seawater and freshwater, respectively. The concentrations of dissolved Σ 9 PBDE, along with published data, slightly increased before 2016 and remained steady from 2016 to 2018, indicating delayed effects of the global phaseout of technical Penta- and Octa-BDEs. The log-transformed concentrations of individual BDE congeners were better correlated with regional gross domestic product than with population density. The potential ecological risk of BDE-47 was low, and there was a lack of key risk indicators for other compounds. The present study documented the delayed response of the aquatic environment to the regulatory actions on reducing PBDE emissions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".