Toxic cyanobacteria in water supply systems: data analysis to map global challenges and demonstrate the benefits of multi-barrier treatment approaches
Notice bibliographique
Résumé
Abstract The occurrence of toxic cyanobacteria in surface waters and their impact on drinking water treatment plants (WTPs) is a growing, global concern. The main objective of this paper was to assess the presence of cyanobacteria in surface water sources and associated cell removal efficiency in full-scale WTPs across the world. Previously unpublished data was collected from WTPs experiencing cyanobacterial blooms in either their managed surface waters or recreational waters. In total, data were collected from 31 surface water sources and 21 WTPs in North and South America, Europe, Asia, and Australia. The most commonly detected species were identified in both the surface waters, including Microcystis, Anabaena, Nostoc, Oscillatoria, and Planktolyngbya, and water treatment plant intakes, including Microcystis, Cylindrospermopsis, Anabaena, Pseudanabaena, and Aphanizomenon. In the intakes, cyanotoxins and taste and odor (T&O) compounds frequently co-occurred (80%) as did multiple cyanotoxins (39%). Conventional treatment saw a wide range of removal depending on the density of cells, species, and metabolites. Although more than 28% of sampling events displayed negligible or even negative removals of metabolites or cells due to accumulation within the clarifier, filtration, or water recycling, the presence of multiple treatment barriers, particularly advanced treatments like granular activated carbon and nanofiltration, allowed for the cells and their metabolites of concern to be removed to below guideline values. During treatment, total microcystins were often removed without releasing their intracellular fraction, whereas cylindrospermopsin, geosmin, and 2-MIB were commonly detected as entirely extracellular at the plant's intake. The maximum tolerable cell (MTC) counts for cyanotoxin- or T&O-producing cells were calculated using guideline values, average removal efficiency, and the average cell quota derived from data. The 21 WTPs in this work were found to be able to tolerate approximately 74,000 cells/mL for microcystins, 8,000 cells/mL for cylindrospermopsin, and 1,200 cells/mL for geosmin and 2-MIB before exceeding guideline values. These levels provide guidance for water treatment plant operators to assess the potential risk associated with cells capable of producing cyanotoxins or T&O compounds.
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 | 0,000 | 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 ».