Evaluation of control strategies for reducing occupational exposure to trichloramine in indoor swimming pools
Bibliographic record
Abstract
Studies have shown that swimming pool workers often exhibit symptoms linked to exposure to disinfection by-products (DBPs), particularly trichloramine (TCA). However, current studies on occupational exposure to DBPs, including TCA, lack standardized sampling methods. Improving exposure assessment requires harmonizing sampling strategies and considering variations within and between pools, as well as spatial, temporal, personal, and environmental factors. This thesis aims to characterize occupational exposures to TCA in indoor swimming pools, assess the associated health outcomes and investigate strategies to reduce these exposures. The specific objectives were: (1) to evaluate TCA sampling methods, comparing collection strategies to evaluate airborne TCA levels and investigate temporal and spatial variations in indoor pools; (2) to model TCA exposure, using comprehensive sampling and empirical modeling of DBPs in water and air, and estimate occupational exposure to airborne TCA using the well-mixed model (WMM); (3) to assess the health outcomes of TCA exposure on pool workers and compare results from stationary and personal sampling. For the first objective, both laboratory experiments and field samplings were conducted, including measurements in multiple pools. TCA was generated in a dedicated laboratory setup, with air samplings adapted from the Hery method. In swimming pools, 2h-air samples were made in diverse locations and using various sampling trains. Besides 2h samples, 4h-, 6h- and 8h samples were collected using an innovative sampling cassette assembly composed of three filters and a separable pre-filter. For the second objective, a database of air and water measurements from four pools was created, and statistical analyses were performed to assess the association between DBPs and explanatory variables. In addition, the WMM, a model used within the IH MOD tool, was applied to estimate TCA concentrations. In the third objective, environmental and personal samplings were collected to explore the relationship between TCA exposure and respiratory health effects in pool workers. Data from six indoor pools and personal measurements from 60 workers were analyzed. Respiratory outcomes were assessed through questionnaires and respiratory tests, including FENO assessments, conducted before and after shifts. Laboratory studies showed that TCA concentrations exceeding 1 mg/m3 resulted in significant deposition on the second filter, indicating potential material loss. Using a separable cassette assembly prevented overestimation of TCA levels, supporting its use in exposure assessments. Field studies identified significant daily variations in TCA concentrations, challenging the adequacy of 2-hour samples in estimating occupational exposure. A full-shift sampling strategy with three filters was proposed as a more accurate method for time-weighted average TCA exposure assessments. Findings from four chlorinated pools revealed a significant impact of bather attendance on air DBPs levels, with increases in TCA concentrations. Models for airborne DBPs, using parameters like CO2 and relative humidity, showed strong predictive capacity for day-to-day monitoring. The WMM, updated to include swimmer numbers, proved useful tool for anticipating TCA levels. The research highlighted significant health concerns associated with high TCA levels in indoor pools, exceeding previously reported levels. The study emphasized the prevalence of work-related symptoms among pool workers, particularly eye irritation, underscoring the need for preventive measures to protect their health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".