On-site comparison of the OSHA 47, Asset EZ4-NCO, Iso-Chek, DAN, and CIP10 methods for measuring methylene diphenyl diisocyanate (MDI) at an oriented-strand board (OSB) factory
Bibliographic record
Abstract
Diisocyanates are occupational contaminants and known sensitizers causing irritation (skin and respiratory tract) as well as occupational asthma. Because of their physicochemical properties (semi-volatile and high reactivity) and low occupational limits, diisocyanate exposure evaluation is still a challenge nowadays for industrial hygienists and laboratories. The objective of this study was to compare the methylene diphenyl diisocyanate (MDI) concentrations measured by five methods using different collection or derivatization approaches in an oriented-strand board (OSB) factory. The methods used were: OSHA 47 (filter, 1-(2-pyridyl)piperazine) (OSHA), Asset EZ4-NCO (denuder and filter, dibutylamine) (Asset), Iso-Chek (double-filter, 9-(N-methylaminomethyl) anthracene and 1,2-methoxyphenylpiperazine), DAN (filter, 1,8-diaminonaphthalene), and CIP10 (centrifugation, 1,2-methoxyphenylpiperazine). Real-time monitoring of particle concentration and size distribution was performed to explain the potential bias between methods. The comparison study was performed over 3 consecutive days, generating at least 18 replicates for each of the 5 methods. The results of each methods were compared using linear mixed effect modeling. Compared to Asset, which yielded the highest concentrations overall, the OSHA method provided the smallest bias with -18% (95% CI [-61;24]) (not significant) for MDI monomer and the DAN method provided the smallest bias with -30 (95% CI [-70;9]) (not significant) for Total Reactive Isocyanate Group (TRIG). The CIP10 and Iso-Chek methods provided the largest biases for MDI monomer (-83% (95% CI [-115;-51]) and -78% (95% CI [-110;-46]), respectively) as well as for TRIG (-87% (95% CI [-120;-55]) and -75% (95% CI [-107;-44]), respectively). The underestimations of the CIP10 and Iso-Chek were explained by its inefficient sampling principle for fines particles and the use of a non-impregnated filter to collect aerosol MDI, respectively. This study confirms that impregnated filter, including denuding device such as the Asset EZ4-NCO sampler, collects the MDI-coated wood particles and MDI vapor with similar efficiency. It also demonstrates for the first time in this type of MDI emission a significant agreement for TRIG concentration between the DAN method in the impregnated filter configuration and an international standard one such as Asset.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".