Assessing Occupational Exposure to Flame Retardants and Plasticizers using Silicone Passive Samplers and other Measurement Methods
Bibliographic record
Abstract
Occupational exposure to the complex mixtures of semi-volatile organic compounds (SVOCs), including flame retardants (FRs) and plasticizers, used in personal care products and electronic and electrical equipment is a serious concern. This thesis documents occupational exposure to FRs and plasticizers in e-waste facilities and nail salons using silicone passive samplers and other measurement methods, including dust collection and active air sampling. The thesis advances the understanding of the use of silicone passive samplers for measuring SVOC exposure in personal exposure monitoring and assessment. Three silicone passive sampler configurations (brooches, wristbands and armbands) accumulated detectable amounts of FRs and plasticizers within a relatively short deployment time (~8 hours) in both e-waste and nail salon environments. Among these samplers, silicone brooches showed the strongest correlations with active air samplers for most compounds. The correlations between brooches and active air samplers were stronger in e-waste facilities than in nail salons. This thesis found that silicone brooches and wristbands can be useful for indicating internal exposure to SVOCs with relatively long biological half-lives, like decabromodiphenyl ether (BDE-209), but their uses for compounds with relatively short half-lives, like organophosphate esters (OPEs), is unclear. Overall, results suggest that silicone brooches and wristbands are valuable screening tools for qualitative exposure studies, but are not reliable for quantitative exposure measurement. The thesis contains the first reports of FR and plasticizer exposure at elevated levels in Canadian e-waste recycling facilities and nail salons. Higher exposures via air and dust to FRs were found in formal e-waste facilities in Ontario and Quebec compared to previous studies in formal and informal facilities across the globe. E-waste workers in an Ontario facility were exposed to FRs in respirable particles, raising concerns for worker health in e-waste environment. Exposure to some OPEs in nail salons at relatively high levels was an unexpected finding as these chemicals are known to be FRs and have not been reported to be used in personal care products. Results presented here call attention to FRs and plasticizers exposure among workers in e-waste facilities and nail salons where these chemicals are, largely, not addressed by current occupational exposure limits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".