Field calibration of polyurethane foam disk passive air samplers for PBDEs
Bibliographic record
Abstract
A field study was performed to derive uptake rates of airborne polybrominated diphenyl ethers (PBDEs) to polyurethane foam (PUF) disk passive air samplers (PAS) and to investigate the influence of deployment location and device design. Data are presented on the gas-particle partitioning of PBDEs, since atmospheric phase distribution was considered to be a variable which could affect sampler performance. Uptake rates for these compounds were similar to those derived previously for other classes of persistent organic pollutants (POPs) (approximately 2-6 m(3)/day), with rates higher for the higher brominated species. Whilst other compound classes (e.g. polychlorinated biphenyls) are predominantly present in the air in the gas phase, heavier PBDEs have an association with particulates in the atmosphere at ambient temperatures. In this study, the PUF disk PAS therefore sampled PBDEs present in the gas phase and on fine aerosols with a similar sampling efficiency to those which are predominantly gas phase compounds. Compounds which are exclusively on particles are sampled less efficiently. A comparison of the three most commonly used PUF deployment configurations, used by different research groups, indicated little difference in uptake rates. The ranges of derived air concentrations for BDE-47, -99, and -183 between three sampler designs were 7.5-9.8, 7.4-12.4, and 4.7-6.6 pg/m(3), respectively. This suggests the robustness of this sampler in comparisons between regional and global campaigns where these three designs are employed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".