Ozonation for the improvement of wastewater quality in lagoons
Notice bibliographique
Résumé
Concerns over environmental sustainability in Canada have increased in recent years leading to changes to the discharge limits of certain contaminants like biological oxygen demand (25 mg/L), ammonia (1.25 mg NH3-N/L), and total suspended solids (25 mg/L) in effluent from wastewater treatment facilities collecting an average daily influent volume of 100 m3 or more. Contaminants of emerging concern (CECs) like pharmaceuticals, hormones, pesticides, herbicides, and other natural and synthetic compounds found in effluent from wastewater treatment facilities remain unregulated in Canada but may persist in the environment and lead to negative environmental outcomes. Given the number of Canadians who rely upon lagoons for their wastewater treatment in small, rural, and remote communities, there is a need to investigate and develop new, cost-effective strategies to improve the quality of wastewater treated in lagoons. Ozonation has been shown to improve the removal of a variety of wastewater contaminants (including CECs) from real wastewater through direct means (oxidation of compounds) and indirect means (increased dissolved oxygen, enhanced biodegradability) and was investigated in the present thesis as a potential strategy to improve wastewater treatment in lagoons. Two pilot tests were conducted to investigate the effects of ozonation on contaminant removal in lagoons. Samples of wastewater were collected from several locations in each lagoon prior to ozonation, during ozonation, and after ozonation and analyzed to determine the effect of ozonation on the removal of conventional contaminants and CECs. The samples were analyzed for biological oxygen demand (BOD), chemical oxygen demand (COD), total ammonia, unionized ammonia, total dissolved solids (TDS), total suspended solids (TSS), nitrite, nitrate, toxicity to Vibrio fischeri, and for the presence of fifteen CECs. For the first pilot test at New Credit First Nation, there were reductions in the BOD and total ammonia during the ozonation period. There was a decrease in toxicity to Vibrio fischeri and a further decrease in total ammonia during the post-ozonation period. The concentrations of three CECs (carbamazepine, gemfibrozil, and ibuprofen) decreased during the ozonation period, and the gemfibrozil concentration continued to decrease during the post-ozonation period. For the second pilot test at Rainy River First Nation, there were reductions in BOD, total ammonia, and unionized ammonia in the post-ozonation period. There was also a reduction in time from ice-off at the lagoon until compliance with the Wastewater System Effluent Regulations (WSERs) in 2018 compared to 2017 and 2016, but this time was still longer than in 2015 or 2014. Laboratory experiments with synthetic wastewater showed no improvements in removal of contaminants due to ozonation in a subsequent biodegradation process by Bacillus, Pseudomonas, and Rhodococcus species, and an increase in the formation nitrate at one of the dose tested. Direct removal of two indicator compounds (caffeine and sulfamethoxazole) by ozone was observed. The optimal dosing strategy for the removal of caffeine was different than for the removal of sulfamethoxazole. Overall, it is unclear if the pilot tests led to improvements in each lagoon and laboratory experiments with synthetic wastewater did provide evidence of an optimal ozone dosing strategy to improve the removal of contaminants. Monitoring at New Credit First Nation and Rainy River First Nation may provide further insight on the impact of ozonation on contaminant removal processes in lagoons. Further laboratory experiments using a more complex synthetic wastewater or real lagoon wastewater may also help determine the impact of ozonation on contaminant removal and the optimal dosing strategy to minimize costs associated with ozone production.
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 | 0,000 | 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) | 0,001 | 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 ».