Measuring and predicting the fate of contaminants of emerging concern during wastewater treatment
Notice bibliographique
Résumé
The presence of contaminants of emerging concern (CECs) in the aquatic environment and the associated proven toxic impacts have increasingly alarmed researchers. The discharge of wastewater into surface water was identified as the major source for the release of CECs into the environment. Despite the available data on the removal of CECs in wastewater treatment plants (WWTPs) in the literature, previous studies had several shortcomings, resulting in an inaccurate prediction of the CEC fate. This PhD project aimed at monitoring the fate of CECs in different treatment steps with special consideration to the hydrodynamics of the treatment units and adsorption to sludge. The project also aimed at developing and calibrating a model to predict the fate of target CECs in the most widespread secondary treatment technology: the activated sludge process. Among the various classes of CECs, this thesis focused on the widely consumed pharmaceuticals, personal care products, drugs of abuse, hormones, stimulants and artificial sweeteners based on evidences of their presence in treated wastewater implying their inefficient removal during treatment. Recently, the hydraulic characteristics of WWTPs were demonstrated to bias the calculations of CEC removal if not accounted for. To address this issue, the fractionated approach that integrates hydraulic modelling and improved sampling strategies was recently proposed. In order to verify the capability of the fractionated approach at capturing the hydraulic differences, the temperature and electric conductivity of wastewater were used as tracers to model the hydraulics of two full-scale WWTPs. Results demonstrated that a distinctive model was necessary to describe the hydraulics in each WWTP, requiring different number of days for sampling, as well as different CEC removal calculations.In order to explore the contribution of the different fate pathways to the removal of CEC during wastewater treatment, a sampling campaign was performed in a WWTP using an optimized sampling strategy based on the fractionated approach to collect and chemically analyze both wastewater and sludge samples. This allowed performing a mass balance on the incoming load of CECs, which was carried out for the first time with consideration to the hydraulic characteristics. Results indicated that for 21 out of 24 investigated CECs, degradation was the major removal process, with sorption accounting for <10% of the input CEC load fate in the primary clarifier and <5% in the activated sludge process. Most target CECs (22 out of 25) were relatively persistent in rotating biological contactors and sand filtration compared to activated sludge treatment. In order to predict the fate of CECs, a fate model based on the widespread Activated Sludge Model No. 2d (ASM2d) was further modified to better describe the CEC fate processes in aeration tanks. The state-of-the-art Bürger-Diehl secondary clarifier model was extended to include the CEC fate processes for the first time. The resulting secondary treatment model was calibrated to predict the fate of four target CECs that belong to different classes and undergo different fate processes. Results from global sensitivity analysis indicated that depending on the contaminant's properties, a different set of parameters deserved more attention. Further, dynamic sensitivity analysis should be taken into consideration in future sampling campaigns for model calibration.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».