Artefacts in semivolatile organic compound sampling with polyurethane foam substrates in high volume cascade impactors
Bibliographic record
Abstract
Polyurethane foam (PUF) is known to sorb gas-phase semivolatile organic compounds (SVOCs) from ambient air and is used routinely in conventional high volume filter-sorbent sampling of such pollutants. PUF rings have also been employed as impaction substrates in a high volume cascade impactor (HVCI) used as a sampler for the evaluation of particle toxicity. Though nonvolatile particles (e.g., trace metals, inorganic ions) have been the primary focus, the sampler has also been used to measure particulate SVOC concentrations in ambient air. The aim of this work is to investigate the validity of the latter approach. The results of three sets of experiments conducted in Canada and Denmark are reported herein. Model compounds included native and deuterated polycyclic aromatic hydrocarbons (PAHs). The experiments demonstrated that HVCI PUF substrates sorb gas-phase PAH compounds and that the sorbed mass is subject to mobilization through and out of the sampler. Particulate concentrations of low molecular weight and volatile PAHs are therefore prone to overestimation in samples that have been analyzed after extraction of whole PUF substrates. Sonication of collected particles in water before solvent extraction is effective at dislodging them from the PUF but also acts to redistribute their originally particulate PAH mass back to the PUF and to the sonication water. As a result, the PAH content of particles measured after sonication and subsequent filtration does not accurately represent their true values. These artefacts affect not only measured PAH concentrations but also the results of toxicological assays that are conducted to test the characteristics of particles collected using HVCI PUF samplers.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".