Pilot capacity iron electrocoagulation scale-up for natural organic matter removal for drinking water treatment
Notice bibliographique
Résumé
Canadian remote communities are most often those who are affected by poor water quality and boil water advisories. A major issue is the applicability of traditional water treatment technologies to unconventional applications (small-scale and inaccessible communities). Their inaccessibility presents difficulties for supplying needed chemicals involved in traditional treatment processes such as coagulations and flocculation. Electrocoagulation (EC), an electrochemical process producing coagulant chemicals on-site and on-demand, may be an alternative technology to traditional coagulation suitable for small and remote communities. The following work investigated a continuous iron EC process for natural organic matter (NOM) removal. EC experiments were undertaken in the laboratory at 1.35 and 5 LPM, using synthetic surface water, monitoring the effect of flocculation, metal loading (ML), current density and inter-electrode gap. At both flow rates, flocculation was found to have no effect on the reduction of DOC or UV-abs-254. ML was found to have the greatest effect on both DOC and UV-abs-254 reductions, where the highest ML tested yielded reductions >90% and >60%, respectively. Increases in UV-abs-254 at low ML were found to be due to dissolved residual iron. It was determined that humic acid and chloride functioned as ligands and increased the solubility of iron. Operations were scaled-up to 10 LPM and integrated into a water treatment plant in the community of Van Anda, using raw surface water. Average DOC and UV-abs-254 reductions at the greatest ML were 37.2±4.2% and 54.7±0.9%, respectively. EC was found to have low energy requirements at a pilot-scale, whereby 0.480-0.621 kWh per cubic meter of water treated was required to operate at the conditions that yielded the greatest NOM reductions. Finally, an investigation to determine the current density distribution was undertaken. Current distribution results yielded increased current uniformity with the increase of the inter-electrode gap. This increased uniformity can be attributed to the water velocity profiles in the reactor. Through computational fluid dynamic (CFD) models, it was demonstrated that fluid flow uniformity also increased with an increasing inter-electrode gap. Regions of the electrode that were observed to be occupied by high fluid velocity were also areas yielding greater current density.
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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».