Kinetics of the Chemistry and Photochemistry across Different Reaction Stages of UV/chlorine and UV/H2O2 in Water Treatment and Water Reuse
Notice bibliographique
Résumé
This thesis addressed four distinct (photo)chemical phenomena that are related by their importance to the design of UV-based advanced oxidation processes (AOPs) for water treatment. The first phenomenon was the impact of breakpoint chlorination chemistry on UV/chlorine AOPs in the context of potable reuse. In reverse osmosis-based treatment, chloramines are often applied to control fouling of the reverse osmosis (RO) membrane. Chloramine rejection by the RO is incomplete, so when free chlorine is applied for the UV/chlorine AOP, chlorine-chloramine breakpoint reactions will occur. These rapid reactions can affect the oxidant speciation and concentrations entering the UV reactor, and hence, the UV/chlorine performance. A model validated in this study showed the impracticality of eliminating the residual chloramines in RO permeate by dosing chlorine beyond the breakpoint Cl/N ratio. Operating parameters that limit monochloramine and favour dichloramine may slightly improve UV/chlorine performance, such as by increasing the water travel time prior to the UV reactor or increasing the applied Cl/N ratio. The second factor explored was related to radical scavenging capacity (Sc), which is a water quality parameter that directly affects the radical concentration and therefore the target pollutant decay kinetics in UV/AOP. To date, there have been very few studies of the variability of Sc within a water source, or across treatment trains. In this work, Sc was tracked at 5 surface and 1 ground drinking water treatment plants in Ontario over approximately one year. The variation in Sc was observed to range within 15–30%. The impact of this variation on pollutant removal efficiency in a UV/AOP was estimated to be comparatively smaller (±10% in pollutant removal rate) since pollutant removal is a function of the scavenging of not only the background water matrix (Sc), but also the oxidant (H2O2 or chlorine). Sc was not strongly correlated with total organic carbon, UV absorbance at 254 nm, or fluorescence excitation-emission matrix components. The third phenomenon examined relates to the design of UV/AOPs, and specifically how UV/chlorine is compared to UV/H2O2 in terms of predicted performance. Past studies have made such comparisons based on UV collimated beam testing or testing using small (pilot)-scale UV reactors. In this research, however, it was demonstrated that such small-scale tests are biased against UV/chlorine since UV/chlorine efficiency increases with longer UV path lengths (i.e., when using more powerful lamps that are spaced further apart, such as at full-scale). Modelling and experiments were conducted to examine mono- and polychromatic UV/H2O2 and UV/chlorine performance at 2–30 cm path lengths. For monochromatic (254 nm) UV light, the path length effect was not significant, but for medium pressure (polychromatic) lamps, the difference in such lamp spacing makes the pollutant removal efficiency of UV/chlorine relative to UV/H2O2 increase by 40%. The effects of natural water matrix absorbance, oxidant dose, and water pH were also discussed. The fourth phenomenon examined was a detailed study of H2O2 quenching kinetics using thiosulfate, bisulfite, and chlorine. When applying UV/H2O2 advanced oxidation, the majority of the H2O2 survives and need to be quenched since H2O2 exerts a significant downstream chlorine demand. It was determined that over the normal pH range of drinking water (7–8.5), chlorine is the most rapid quenching agent. The form of chlorine (hypochlorite vs. Cl2 gas) can impact H2O2 quenching rate, with gaseous chlorine slowing the reaction and hypochlorite having the opposite effect. These impacts diminish when water alkalinity increases to 80 mg/L as CaCO3.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».