Chlorinated disinfection by-products in drinking water according to source, treatment, season, and distribution location
Bibliographic record
Abstract
The occurrence of the most prevalent chlorinated disinfection by-products (DBPs) was investigated in three Quebec City distribution systems that deliver drinking water subjected to different treatment strategies. Trihalomethanes (THMs), haloacetic acids (HAAs), and other complementary parameters were monitored in several locations representing variable water residence times over 16 months. The occurrence of chlorinated DBPs levels was considerably lower in the system where raw water is subjected to pre-ozonation instead of pre-chlorination (as pre-treatment) or direct chlorination. Seasonal analysis of the data showed that according to the system and to the group of chlorinated DBPs, the average DBP concentrations in winter were two to four times lower than the average DBP levels of the entire period under study. Considerable variations of both DBP groups were observed according to the water residence time in the distribution system, but the behavior was not the same for THMs as for HAAs. In fact, correlations between THM and HAA levels were good only for cold water and low residence time conditions. Seasonal and spatial variations of DBPs documented in this study have important implications on regulatory issues and from an epidemiological point of view. Key words: trihalomethanes, haloacetic acids, drinking water, distribution system, water treatment, source, season, location.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".