Temporal and spatial variations in the levels of prominent airborne disinfection by-products at four indoor swimming pools
Bibliographic record
Abstract
Exposure to airborne disinfection by-products, especially trichloramine and trichloromethane, may cause various adverse health effects for the workers and users of indoor swimming pools. This study aims to evaluate the spatial and temporal variations in trichloramine and trichloromethane concentrations within and between swimming pools. Workplace measurements were carried out at four indoor swimming pools in Quebec (Canada) during the cold season. To fully represent daily operating conditions, sampling started 2 hr before the swimming pool opened and continued until 2 hr after closing. To quantify trichloramine and trichloromethane concentrations, 304 air samples have been collected. Temperature, humidity, and CO2 were measured—simultaneously every 2 hr. The results showed that both trichloramine and trichloromethane concentrations varied significantly in time. The observed daily variations in trichloramine and trichloromethane concentrations suggest that the common practice of collecting a single 2-hr air sample does not represent daily pool trichloramine and trichloromethane contamination levels and, consequently, does not represent the true exposure and health risks for workers that are present for a full 8-hr shift. This study recommends a new 8-hr sampling strategy or a full-shift strategy using a cassette with three impregnated filters as a valid and cost-effective solution for comparing time-weighted average (TWA) concentrations to permissible trichloramine 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".