Ultrasound induced destruction of emerging contaminants
Notice bibliographique
Résumé
There are many reports indicating the presence of emerging contaminants such as: estrogen hormones, 1,4-dioxane and perfluoro-octanoic acids in the natural environment. Estrogen hormones are considered important emerging class of contaminants due to their endocrine disrupting effects. These compounds are invariably found in the environment originating mostly from natural sources. Trace concentrations of estrogen hormones (low µg/L concentrations) have been detected in municipal wastewater treatment plants and observed in receiving water bodies. 1,4-Dioxane (C4H8O2) is used as an organic solvent and solvent stabilizer numerous in chemical processes. The United States Environmental Protection Agency (US-EPA) has recognized 1,4-dioxane as a toxic chemical and a possible human carcinogen. 1,4-dioxane has been detected as a contaminant in the natural environment, drinking water supplies, superfund sites, public groundwater sources in the United States, Canada and Japan at concentrations greater than the permissible standards. Perfluorinated chemicals such as perfluoro-octanoic acid (PFOA) and perfluorooctane-sulfonate (PFOS) have been manufactured for use in a variety of industrial and consumer applications. Due to their environmental persistence, PFOAs have been detected in surface waters at a number of locations at concentrations ranging from pg/L to ng/L. Elevated concentrations of PFOAs have been measured in surface and ground waters near specific point sources. Through this project, successful attempts have been made for the destruction of emerging contaminants using ultrasound. This study deals with the optimization of various process parameters for the destruction of estrogen hormones. The influence of process parameters such as power density, reactor geometry, power intensity, ultrasound amplitude, and external mixing was investigated. Artificial neural network (ANN) approach was used to describe the interactions between optimized parameters. The important findings obtained in the present work for the optimized estrogen degradation can help tackle the challenges of scale up such as operational optimization and energy consumption. The effect of process conditions such as pH and presence of oxidizing agents on the ultrasonic destruction of 1,4-dioxane and PFOA was studied. Acidic conditions favored the destruction of both the compounds. The presence of activated sulfate radicals enhanced the reaction rate kinetics. An innovative technology using electric potential and ultrasound for the removal organic contaminants was developed. The existence of organic contaminants in ionic form under certain process conditions has led to the development of this technology. Applying a low electric potential across the probe enhances the mass transfer of the contaminants into effective reaction zone, thereby enhancing the total destruction. A two-fold increase in the reaction rates was observed. This study shows ultrasound as an efficient and effective treatment technology for the destruction of emerging contaminants.
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 | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».