Flame Retardant Exposure in Vehicles Is Influenced by Use in Seat Foam and Temperature
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Flame retardants (FRs) are added to vehicles to meet flammability standards, such as US Federal Motor Vehicle Safety Standard FMVSS 302. However, an understanding of which FRs are being used, sources in the vehicle, and implications for human exposure is lacking. US participants ( n = 101) owning a vehicle of model year 2015 or newer hung a silicone passive sampler on their rearview mirror for 7 days. Fifty-one of 101 participants collected a foam sample from a vehicle seat. Organophosphate esters (OPEs) were the most frequently detected FR class in the passive samplers. Among these, tris(1-chloro-isopropyl) phosphate (TCIPP) had a 99% detection frequency and was measured at levels ranging from 0.2 to 11,600 ng/g of sampler. TCIPP was also the dominant FR detected in the vehicle seat foam. Sampler FR concentrations were significantly correlated with average ambient temperature and were 2–5 times higher in the summer compared to winter. The presence of TCIPP in foam resulted in ∼4 times higher median air sampler concentrations in winter and ∼9 times higher in summer. These results suggest that FRs used in vehicle interiors, such as in seat foam, are a source of OPE exposure, which is increased in warmer temperatures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".