The presence of plasticizers, bisphenols, and flame retardants in potable water and their removal through conventional drinking water treatment
Notice bibliographique
Résumé
Humans are regularly exposed to a wide array of chemicals everyday through consumer products. Certain bisphenols, plasticizers, and flame retardants are receiving growing attention as they have recently been classified as proven or potential endocrine disrupting chemicals (EDCs). Governments around the world have implemented regulations regarding the production and importation of certain EDCs, such as bisphenol A (BPA), and this has led to the development of replacement chemicals. Unfortunately, these replacement chemicals are not always thoroughly tested for low-dose or long-term toxicity. Contaminated potable water, which can be caused by contaminated water sources, insufficient water treatment technologies, or contaminated piping and packaging, is one route of human exposure to flame retardants, bisphenols, and plasticizers. The present Master’s thesis quantified 39 contaminants including flame retardants, bisphenols, and plasticizers in potable water from Montreal and South Africa, and assessed the removal of these contaminants through a conventional drinking water treatment plant (DWTP). Human exposure to contaminants through potable water was assessed, which included five bottled water (BW) brands and three DWTPs in Montreal, and water from one urban DWTP located in Pretoria, and one rural DWTP located in Vhembe, along with water from the same DWTP which had been stored in small and large plastic containers in a rural area. A combination of legacy compounds, typically with proven toxic effects, and replacement compounds were investigated. Lower brominated PBDEs were detected more frequently than higher brominated PBDEs, always at low concentrations < 2 ng/L, and total PBDE levels were statistically higher in South Africa than in Montreal. Replacement flame retardants, organophosphate esters (OPEs), were detected at statistically higher concentrations in Montreal’s BW (68.6 ng/L), drinking water (DW) (421.5 ng/L) and in Vhembe (198.3 ng/L) than legacy PBDEs. Total OPE concentrations did not demonstrate any geographical trend; however levels were statistically higher in Montreal’s DW than Montreal’s BW. Plasticizers were frequently detected in all samples, with legacy compounds DEHP, DBP, and replacement DINCH being detected in 100% of samples with average concentrations ranging from 6.8 ng/L for DEHP in Pretoria to 175 ng/L for DINCH in Montreal’s DW. Total plasticizer concentrations were higher in Montreal than in South Africa. The replacement plasticizers (DINCH, DINP, DIDA, and DEHA) were detected at similar frequencies and concentrations as legacy plasticizers (DEHP, DEP, DBP) and known toxic metabolite (MEHP). The removal of these contaminants through conventional drinking water treatment was assessed in a DWTP in Montreal. The DWTP chosen utilized filtration, ultraviolet (UV) treatment, and chlorination, and 24h-composite daily sampling was performed between each treatment step over a three-day period. PBDEs, considered legacy flame retardants, were infrequently detected or at concentrations < 1 ng/L. Removal efficiencies for ∑_7▒PBDEs was 48.5 and 94.1% on days 2 and 3, respectively, with BDE-183 and BDE-154 only detected in raw water. OPEs, considered replacement flame retardants, were frequently detected in all water samples. The total average concentration of ∑_15▒OPEs was 500 ng/L in raw water and 159 ng/L in drinking water, with an average removal efficiency of 65.8%. The majority of OPE removal was attributed to filtration, which had significant removal of TCIPP (75.9%), TDCIPP (83.6%), and TPHP (94.5%). OPEs proved to be more persistent through drinking water treatment than legacy PBDEs as they were detected at higher frequencies and concentrations throughout the DWTP. While conventional drinking water treatment methods have demonstrated some removal of flame retardants, contributing to mitigating exposure to these contaminants, flame retardants are still present at concentrations in the ng/L range
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».