Deposition of Brominated Flame Retardants to the Devon Ice Cap, Nunavut, Canada
Bibliographic record
Abstract
Brominated flame retardants (BFRs) can be transported to Arctic regions via atmospheric long-range transport, however, relatively little is known about their deposition to terrestrial environments. Snow cores from the Devon Ice Cap in Nunavut, Canada served to determine the recent depositional trends of BFRs. Snow pits were dug in 2005, 2006, and 2008. Dating using annual snow accumulation data, ion chemistry, and density measurements established that the pits covered the period from approximately 1993 to spring 2008. Samples were extracted under clean room conditions, and analyzed using GC-negative ion MS for 26 tri- to decabromodiphenyl ethers (BDEs), as well as other BFRs, nonbrominated flame retardants, and industrial chemicals. Decabromodiphenyl ether (BDE-209) was the major congener present in all samples followed by nona-BDEs (BDE-207, BDE-206, and BDE-208), both accounting for 89% and 7% of total BDE, respectively. BDE-209 concentrations were in most cases significantly correlated (P < 0.05) to tri- to nona-BDE homologues, and the strength of the correlations increased with increasing degree of bromination. Prior to or after deposition BDE-209 may be subject to debromination to lighter congeners. Deposition fluxes of BDE-209 show no clear temporal trend and range between 90 and 2000 pg·cm(-2)·year(-1). Back trajectory origin in densely populated areas of northeastern North America is significantly correlated (P < 0.005) with the BDE-209 deposition flux. Several other high production volume and/or alternative BFRs such as hexabromocyclododecane (HBCD), 1,2-bis(2,4,6-dibromophenoxy)ethane (BTBPE), pentabromo ethyl benzene (PBEBz), and pentabromobenzene (PBBz), as well as the industrial chemical 1,3,5-tribromobenzene (135-TBBz) were found consistently in the snow pits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".