Présence et devenir d'absorbants ultraviolets et d'antioxydants industriels dans le fleuve Saint-Laurent
Bibliographic record
Abstract
RÉSUMÉ : Les absorbants ultraviolets (UVAs) et les antioxydants industriels (IAs) sont des contaminants émergents préoccupants. Dans cette étude, la distribution et la répartition, des UVAs et des IAs dans les eaux de surface, les sédiments et les différents tissus de deux espèces de poisson, soit l'esturgeon jaune (Acipenser fulvescens) - un omnivore benthique - et le grand brochet (Esox lucius) - un piscivore pélagique - du fleuve Saint-Laurent (SLR), Québec, Canada ont été étudiées. Les résultats indiquent que le 2,6-di-tert-butyl-1,4-benzoquinone (BHTQ), un produit de transformation des antioxydants phénoliques synthétiques, est le contaminant dominant dans les eaux de surface, avec des concentrations médianes de 43, 15 et 123 ng/L pour les trois sites d'échantillonnages. Les comparaisons spatiales ont été réalisées et des niveaux plus élevés de différents UVAs, BHTQ et diphénylamine dans les eaux de surface recueillies en aval de Longueuil et de Montréal par rapport au site en amont, suggérant l'influence des activités urbaines sur la contamination de ces contaminants émergents dans le SLR. Les coefficients de partage sédiment-eau normalisés par rapport au carbone organique sur le terrain (log Koc) des composés cibles détectables sont généralement plus élevés (4,4-6,2) que les résultats de modélisation (2,8-5,4) du programme d'estimation du devenir environnemental (EPI) (Estimation Programs Interface). Ce résultat indique que la modélisation actuelle du devenir environnemental de ces produits chimiques peut sous-estimer leur distribution dans les sédiments. Des profils de contamination différents ont été trouvés chez l'esturgeon jaune et le grand brochet, ce qui suggère une différence entre les voies d'absorptions et d'élimination deux espèces. Les facteurs de bioaccumulation (BAF) sur le terrain pour les contaminants fréquemment détectés (log BAF 1.5-4.2) sont généralement comparables ou inférieurs aux résultats de la modélisation de l'EPI (1.4-5.0), ce qui indique que certains de ces contaminants peuvent être moins bioaccumulables que prévu. -- Mot(s) clé(s) en français : absorbants UVs, antioxydants industriels, fleuve Saint-Laurent, distribution, devenir, bioaccumulation. -- \nABSTRACT : UV absorbents (UVAs) and industrial antioxidants (IAs) are contaminants of emerging concern. However, the occurrence and fate of these contaminants, which are key factors affecting their toxicities, are poorly understood. In this study, we investigated the distribution and partitioning of UVAs and IAs in surface water, sediment, and various tissues of two fish species, the lake sturgeon (Acipenser fulvescens) a benthic omnivore and the northern pike (Esox lucius) a pelagic piscivore, from the St. Lawrence River (SLR), Quebec, Canada. Results indicated that, 2,6-di-tert-butyl-1,4-benzoquinone (BHTQ), a transformation product of synthetic phenolic antioxidants, was the dominant contaminant in surface water, with median concentrations of 43, 15, and 123 ng/L for three sampling sites, respectively. Spatial comparisons were characterized by higher levels of various UVAs, BHTQ and diphenylamine in surface water collected downstream of a major city compared to the upstream site, suggesting the in?uence of the urban activities on the contamination of these emerging contaminants in the SLR. The SLR field-based organic carbon normalized sediment-water partition coefficients (log Koc) of detectable target compounds were generally greater (4.4-6.2) than the modeling results (2.8-5.4) from Estimation Programs Interface (EPI) Suite, indicating that the current modeling of the environmental fate of these chemicals may underestimate their distribution in the sediment. Different contamination profiles were found in lake sturgeon and northern pike, implying the differences in the uptake and elimination of these contaminants between two species. The field-based bioaccumulation factors (BAF) for those frequently detected contaminants (log BAF 1.5-4.2) were generally comparable or lower than the EPI modeling results (1.4-5.0), indicating that some of these contaminants may be less bioaccumulative than previously expected. -- Mot(s) clé(s) en anglais : UV absorbents, industrial antioxidants, St. Lawrence River, distribution, partitioning, bioaccumulation.
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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 | 0.001 |
| 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) | 0.002 | 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".