Chemical disinfection of secondary municipal wastewater effluents: Optimizing CT dose and tailing effects through high‐intensity mixing
Notice bibliographique
Résumé
Abstract This paper investigates the impact of average velocity gradient and mixing effects on secondary wastewater coliform inactivation kinetics using an innovative in‐line treatment technology based on sodium hypochlorite as disinfecting agent. Experiments included both laboratory batch kinetic studies (as reference) as well as bench‐scale pilot tests. The laboratory studies were carried out using a magnetically stirred vessel to simulate low‐mixing conditions (Ḡ ≈ 1000 s −1 at 1 atm), while the bench‐scale pilot tests employed a flow‐through system consisting of two centrifugal pumps in series to simulate high average velocity gradients and intense mixing conditions (Ḡ ≈ 10,000 s −1 at 1.5 atm). In both cases, disinfectant demand and decay models for sodium hypochlorite were fitted against observed data using various expressions corresponding to different kinetic orders and subsequently incorporated into fecal inactivation kinetics via their integral CT expression. Experimental results showed a very remarkable and significant influence of high velocity gradient and mixing intensity on disinfection efficiency. While conventional batch kinetics indicated a 3‐log reduction in fecal coliforms at concentration‐time integral product (CT) of 16 (mg·min·L −1 ), less than 1/10th of the CT dose (under comparable process conditions) were needed in the case of advanced disinfection with high average velocity gradient and mixing intensity. Using the experimental data collected in this study, a novel inactivation model was developed that uniquely incorporates the average velocity gradient Ḡ as explicitly kinetic parameter, enabling precise prediction of CT required for various mixing conditions to meet specific microbial treatment targets. To achieve an effluent total coliform concentration of 10 CFU per 100 mL, a CT of 48.5 mg·min·L −1 was required at a mixing intensity of Ḡ = 762 s −1 , while only 0.82 mg·min·L −1 was needed at Ḡ = 18,158 s −1 . Inactivation tailing was drastically reduced under high‐mixing conditions by enhancing disinfectant penetration in the flocs shielding particle‐associated coliforms. Furthermore, disinfection by‐product (DBP) screening tests confirmed that enhanced inactivation under high‐mixing conditions was achieved while also maintaining regulated DBP levels across all CT values. This integration of mixing effects in microbial inactivation kinetics marks a significant advancement over traditional disinfection design frameworks allowing the disinfection community to access a more refined approach for sizing and validation purposes. PRACTITIONER POINTS Particle‐associated coliforms are inactivated by hypochlorite under high mixing. A 3‐log reduction of coliforms observed at more than 30 times lower CT under high mixing. High mixing and mild pressure can reduce chlorine dose and contact time significantly. Tailing effects are well mitigated by high mixing combined with sodium hypochlorite. An inactivation model for coliform bacteria accounting for mixing intensity is proposed.
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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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».