Impact of the Detection and Quantitation Limits on the Analytical Feasibility of Measuring the European Chemicals Agency Risk Assessment Committee’s Recommendations for Occupational Exposure Limit Values for Nickel and Its Compounds in the Workplace
Bibliographic record
Abstract
In March 2018, the European Chemicals Agency, Risk Assessment Committee (RAC) published its final opinion for nickel (Ni) and its compounds. The proposed values were 0.005 mg/m3 for the respirable fraction for both Ni metal and Ni compounds and 0.03 mg/m3 for the inhalable fraction for Ni compounds. Scientific recommendations for occupational exposure limit values (OELVs) are based on the risk to health, not on the analytical capability of the method for workplace air determination. Practically, however, the sampling and analytical sensitivity and accuracy at the proposed OELVs need to be considered. The selection of a suitable measurement procedure depends on the requirements as stated in applicable consensus standards, for example, EN 482. This standard states that every procedure should operate within the range of 0.1–2 times OELV. For workplace Ni determination, 24 methods were identified. Based on the candidate methods’ limit of quantitation (LOQs), only 17% of the methods can measure as low as 10% of the recommended respirable OELV and 90% of the methods can measure as low as 10% of the proposed inhalable OELV. In addition, 19 European laboratories responded to a survey regarding the workplace air methods for Ni. Four laboratories responded with a nonworkplace air reference method, seven laboratories could not determine the respirable OELV, and one laboratory could not determine the inhalable OELV. The results of our study show that there is no consistency in the calculation and use of the LOQ, which makes it difficult for companies to comply with binding OELVs. Standards should clearly state what the LOQ values are for the specific analytes on which they act. Consensus also should be reached on the LOQ derivation and the importance of the specificity of the matrix (e.g., workplace air) in this calculation.
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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 | 0.003 | 0.001 |
| 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".