MétaCan
Menu
Retour à la cohorte
Enregistrement W3093275191

Removal of Arsenic and Metals from Mine-impacted Groundwater Using Organic Carbon and Zero-valent Iron in Passive Remediation Systems

2020· dissertation· en· W3093275191 sur OpenAlexaboutno aff
Joanne U. Angai

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2020
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueArsenic contamination and mitigation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésZerovalent ironEnvironmental remediationArsenicGroundwaterEnvironmental chemistryEnvironmental scienceTotal organic carbonContaminated groundwaterGroundwater remediationWaste managementEnvironmental engineeringMining engineeringChemistryContaminationMetallurgyGeologyMaterials scienceEngineeringAdsorptionGeotechnical engineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Arsenic (As) is a wide-spread contaminant, often encountered in drainage associated with Au mining. The oxidation state controls the mobility and toxicity of As in water. Passive remediation is a potential management approach for removing As and other contaminants from mine waters. Permeable reactive barriers (PRBs) are a passive management technology that utilizes reactive material to target the contaminant of interest through chemical interactions, including precipitation, reduction, and adsorption. The Long Lake field site is an abandoned Au mine located near Sudbury, ON, characterized by acidic conditions and high concentrations of As, Fe, SO42-, and metals in the tailings porewater. This project aims to evaluate the potential for passive remediation to remove As and other contaminants from mine drainage at the Long Lake field site. \nA series of laboratory column experiments were conducted to determine the potential of a reactive mixture, containing organic carbon substrates (OC), granular zero-valent iron (ZVI), limestone, and silica sand, to remove As and increase the pH of the water. Groundwater was collected directly from the Long Lake site and used as the influent solution for the column experiments. Results indicated an increase in pH and removal of As within the first 3 cm of reactive material. Removal of As in the three treatment columns represented 99.9% of the total As in the water. A decrease in Eh, the production of H2S, a decline in SO42- concentrations, an enrichment in δ34S, and the presence of microbial communities, indicated the presence of bacterially-mediated SO42- reduction. The percentage of total reads that were sulfate-reducing bacteria (SRB) ranged from 2.4 – 10.0%. Sulfate reduction rates ranged from 0.18 to 0.20 mg L-1 d-1 g-1 dry wt. % OC for the three treatment columns. Synchrotron-radiation bulk S X-ray absorption near-edge structure (XANES) indicated that accumulation of reduced S phases including pyrite and elemental S occurred in the solid material during the experiments. Geochemical modelling results further indicate that precipitation of sulfides including mackinawite, greigite, pyrite, sphalerite, and chalcopyrite, was favoured. Removal of metals, including Cu, Ni, and Zn, is attributed to the precipitation of low-solubility metal sulfides following SO42- reduction. Synchrotron As µXANES indicated that As was present in secondary precipitates in both the reduced phase, as realgar, orpiment, and arsenopyrite, and in the oxidized phase, as As(V) sorbed onto ferrihydrite. The addition of OC contributed to the development of sulfate-reducing conditions and resulted in bacterially-mediated SO42- reduction. The presence of ZVI led to the formation of ferrous iron and ZVI corrosion products, providing additional surface sites for As adsorption. \nTwo separate field-reaction cell (30 cm inner diameter by 99 cm length) trials, were conducted at the Long Lake mine site, one in the summer (mean air temperature of 19 ℃) and one in the autumn (mean air temperature of -1 ℃), to evaluate the effect of temperature on As removal. A reactive mixture containing ZVI, OC, limestone, and pea gravel (at similar proportions to the column experiments) was utilized. The results from the summer field cell were similar to those observed in the laboratory column experiments. A decrease in As, metals, SO42-, and acidity, were observed within the first 9 cm of reactive media. Reactions contributing to metal and As removal include precipitation of low-solubility metal sulfides and adsorption on ZVI corrosion products. The results from the autumn field cell indicated that the development of bacterially-mediated SO42- reduction was limited, with lower percentages of SRB observed in the autumn cell compared to the summer cell and laboratory column experiments. Removal of As, metals, and an increase in pH was observed in the autumn cell, however, aqueous chemistry results did not show a decline in SO42- concentrations or an enrichment in δ34S. Optical microscopy indicated the presence of pyrite and pyrrhotite in the autumn cell material, but abundance was lower in the autumn cell than in the other two experiments. The results from bulk S XANES indicated the accumulation of sulfides in the solid material was also limited. The difference in results between the summer cell and autumn cell may be attributed to colder outside temperatures during the field trial or the shorter duration of the experiment. \nThe results from all three experiments indicate that the addition of OC to the reactive mixture was important for the development of sulfate-reducing conditions and the growth and activity of SRB. The addition of ZVI further enhanced the removal of As, metals, and Fe from the water through the formation of corrosion products and metal sulfide precipitation. Removal of As and metals and an increase in pH was observed in all three experiments despite varying flow rates and fluctuating temperatures. These results indicate that a mixture of OC and ZVI will likely be effective at removing As and metals from mine drainage waters under a range of flow rates and temperature conditions.

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 enseignants0,005
Score d'incertitude au seuil0,010

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 savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,009
Tête enseignante GPT0,189
Écart entre enseignants0,179 · 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

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueUWSpace (University of Waterloo)Même sujetArsenic contamination and mitigationTravaux en français237 207