MétaCan
Menu
← Retour à la cohorte
Enregistrement W6926026715 · doi:10.20381/ruor-27366

Ammonia Removal from Mining Wastewater by Ion-Exchange Regenerated by Chlorine Solutions

2022· article· en· W6926026715 sur OpenAlexaboutno aff

Notice bibliographique

RevueuO Research (University of Ottawa) · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiquePatient-Provider Communication in Healthcare
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAmmoniaWastewaterChlorineContaminationAcid mine drainageZeoliteEnvironmental remediation

Résumé

récupéré en direct d'OpenAlex

The mining industry is a significant contributor to the Canadian economy. However, the mining activities can be detrimental to the environment due to the release of pollutants. Ammonia is one of the noxious and toxic contaminants associated with mining, ammonia contamination is created by the oxidizing agent in explosives. The explosives impacted mining wastewater (EIMWW) usually contains ammonia and other metal ions. The ammonia in EIMWW could harm the aquatic environment by the depletion of oxygen and its lethal toxicity to aquatic organisms. Before release to environment, EIMWW needs to be treated with an easy-to-operate method for ammonia removal at the remote mining sites. Ion-exchange (IE) with zeolite is an effective method for ammonia removal that is easy-to-operate, is not significantly impacted by cold temperature or toxicity effects. However, the traditional IE regeneration approach of using high concentration NaCl solutions creates a secondary polluting stream. Chlorine regeneration of ammonia-loaded zeolite appears to be a promising option, an evaluation of this option is the main topic of this thesis. This thesis includes three initiatives. The first is a set of multi-cycle batch loading-regeneration tests to assess the viability of ammonia removal with a commercial zeolite (SIR-600) for the treatment of a synthetic EIMWW (containing total ammonia nitrogen (TAN), K, and Ca) and to examine the performance of different ion-exchange regeneration solutions. The long-term TAN uptake of SIR-600 regenerated using a NaOCl (100 mg free Cl2/L) solution was 0.24 meq/g, which was approximately 20% lower than that after a NaCl regeneration. However, chlorine regeneration is promising because the selectivity of SIR-600 for TAN over Ca and K increased after the chlorine regeneration. To simulate recycling of the NaOCl regenerants, K and Ca were added to the NaOCl solution, it did not substantially affect the subsequent SIR-600’s ion uptake. This initiative represents a significant contribution since the earlier studies into chlorine regeneration did not investigate the impact of competing ions. The second initiative addressed concerns regarding the long-term integrity of SIR-600 arising from its exposure to high chlorine concentrations during the regeneration. The five-week long chlorine batch exposure tests with solutions of up to 1000 mg free Cl2/L showed that chlorine exposure did not significantly affect the SIR-600’s characteristics in terms of particle size distribution, surface area, FTIR spectra and ion uptake. Thus, SIR-600 has the potential for long-term use in field applications. The final initiative evaluated the feasibility of chlorine regeneration for continuous flow IE column systems used for ammonia removal from a synthetic EIMWW. Continuous flow column systems are important because these are the standard IE units used in full-scale applications. Multi-cycle column loading-regeneration tests were performed to compare the zeolite performance using a NaOCl (1000 ppm as free Cl2) solution with that using a 5% NaCl regeneration. The influence of loading duration was also assessed. The use of 6-hr loading cycles were shown to be preferable to 23-hr loading cycles because it had lower effluent concentrations and they could achieve higher overall TAN mass removals per unit time. After three operational cycles, the SIR-600 had similar TAN uptake performances (0.21 meq/g Vs. 0.21 meq/g) after NaOCl regeneration and after salt (NaCl) regeneration. This is in contrast to the lower TAN uptakes for the NaOCl regeneration in the batch tests, this indicates that batch tests are not always representative of full-scale applications. Compared to NaCl regenerated SIR-600, SIR-600 after NaOCl regeneration had a higher preference for TAN over Ca and K, which makes this type of regeneration very promising. Its only apparent limitation is that the NaOCl regeneration required a longer duration. During the NaOCl regeneration, the main mechanism appears to be the oxidation of ammonia to nitrogen gas and hydrogen ions, however the Na in the NaOCl solution also seems to have a role in the 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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,288
Tête enseignante GPT0,395
Écart entre enseignants0,106 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueuO Research (University of Ottawa)→Même sujetPatient-Provider Communication in Healthcare→Travaux en français237 207→