ANION EXCHANGE RESIN TECHNOLOGY FOR NATURAL ORGANIC MATTER REMOVAL FROM SURFACE WATER
Notice bibliographique
Résumé
Natural organic matter (NOM) is present in all surface waters as a result of decaying vegetation, biological activity, and organic soil. Alternative NOM removal processes such as anion exchange resins (AERs) have shown NOM removals typically ranging between 50 to 90%, with up to 99% removal achieved in some cases. \nThe first portion of this study evaluated the performance of two AERs; a conventional Type 1 AER and magnetic ion exchange resin (i.e. MIEX®) for NOM removal from surface water quantified by UV254, dissolved organic carbon (DOC), and specific UV absorbance (SUVA). Samples were also characterized for chloride, sulphate, and chloride-to-sulphate mass ratio (CSMR) to provide additional information on water quality characteristics of AER treated waters. Overall, the results showed that both AERS were effective for removing NOM. However, the MIEX® resin provided greater removal of NOM with shorter contact times compared to the conventional resin investigated. Water treated with MIEX® resin showed significantly higher chloride and lower sulphate concentrations than the conventional AER. Higher CSMR values were found with MIEX® treated water compared to conventional AER system, although both resins showed CSMR much greater than 0.5, which can increase galvanic corrosion effects with lead.\nBench-scale jar tests were conducted to investigate the impact of temperature on the efficacy of three NOM removal treatment technologies; enhanced coagulation with alum, MIEX® and a combined MIEX® treatment followed by coagulation with a low dose of alum. Higher settled water turbidity was observed during cold water operating conditions for all three processes. At cold-water operating conditions, DOC removal was reduced with combined MIEX® -Alum treatment, and UV254 removal was impacted for both MIEX® and MIEX® -Alum processes. The combined MIEX®-Alum process was found to provide the lowest THMFP and HAAFP at both temperatures to concentrations lower than current regulatory maximum acceptable concentration (MAC) guidelines in Canada. \nSurface charge analysis experiments were performed at bench-scale using synthetic water containing humic acid to determine the relationship between NOM and the charge of AER-treated waters. Further bench and pilot-scale studies were performed to investigate the use of surface charge measurements to monitor and optimize NOM removal during treatment with AER systems. Strong correlations were observed between UV254 and respective charge measurements (i.e. ZP, SC) of AER-treated synthetic and raw waters. The results of this research has shown that it is possible to use charge to optimize the MIEX® process for NOM removal. Additionally, it was found that SC measurements could be used as an operational tool for AER processes, where deviations in SC from optimum treatment would indicate the requirement for fresh resin addition or resin regeneration.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».