Biofiltration for Manganese Removal from Groundwater: Mechanistic Insights and Operational Strategies
Notice bibliographique
Résumé
Groundwater is an essential source of drinking water worldwide. Among various contaminants that are present in groundwater, manganese (Mn) is one of them. Manganese in drinking water can cause aesthetic and operational problems and has been associated with cognitive and neurobehavioral effects in children. In response, Health Canada has established as guidelines a maximum acceptable concentration (MAC) of 120 µg/L and an aesthetic objective (AO) of 20 µg/L for Mn in drinking water. \nBiofiltration provides an environmentally friendly and effective method for removing Mn from water, as it does not require chemicals and does not produce harmful by-products. However, limitations include a prolonged start-up period with virgin media and diminished efficacy at lower water temperatures (< 15°C) due to reduced microbial activity, particularly when iron (Fe) is present as a co-contaminant in groundwater. Additionally, while biofilters are typically operated continuously (24 h/d), intermittent operation (6-12 h/d) in small-scale or remote communities, depending on local demand, may affect the performance of biofilters. Despite research on Mn removal mechanisms by biofiltration, the evolution of these processes as biofilters mature requires further investigation. Consequently, this research aims to deepen the understanding of Mn removal mechanisms in biofilters from startup to maturity and to investigate the influence of filter media characteristics and operational modes (intermittent vs. continuous) on the performance of biofilters for Mn and Fe removal. \n \nThe research was conducted in three phases, utilizing a combination of pilot-scale biofilters and bench-scale batch experiments. Pilot-scale biofilters were designed and constructed at a drinking water facility in Southern Ontario, Canada and were operated under various configurations for approximately 400 days with raw groundwater containing Mn and Fe. Concurrent bench-scale batch experiments with and without inhibitors were conducted to elucidate different Mn removal mechanisms. This study employed multiple analytical techniques such as scanning electron microscopy (SEM), energy dispersive X-ray (EDX), Raman spectroscopy, adenosine triphosphate (ATP) measurements, extracellular polymeric substance (EPS) analysis, cultural plating techniques, and 16S rRNA gene sequencing. \n \nPhase one evaluated the impact of different filter media, including granular activated carbon (GAC), sand, and anthracite, on startup, Mn removal mechanisms, and microbial community dynamics. Findings indicated that filter media characteristics influence the startup period of Mn removal; GAC biofilters primarily initiated Mn removal through adsorption, transitioning to biological and physicochemical processes, while sand and anthracite predominantly engaged in biological processes. The batch tests confirmed these findings, with sand and anthracite media showing biological dominance at the top layer and GAC media exhibiting physicochemical dominance throughout. The presence of manganese-oxidizing bacteria (MnOB) genera varied across biofilter media types and depths, highlighting the complex interplay between biofilter media and microbial colonization patterns. \nPhase two focused on the evolution of Mn removal mechanisms in a sand biofilter from startup to maturity, utilizing a combination of pilot-scale biofilter and bench-scale batch experiments. The study revealed an initial dominance of biologically generated manganese oxides (Bio-MnOx), which gradually transitioned to physicochemical forms of MnOx. This shift is likely due to the competitive dynamics between MnOx and MnOB, with the influence of MnOB diminishing over time. Other contributing factors include changes in the nutrient consumption patterns of MnOB and shifts in microbial community composition. Several MnOB genera, including Sphingopyxis, Sphingomonas, Hyphomicrobium, Hydrogenophaga, and Variovorax, were present in the biofilter from startup to maturity. Genes associated with direct and indirect biological Mn oxidation pathways were also predicted, highlighting the complex, multi-pathway nature of biological Mn oxidation. \n \nPhase three evaluated the performance of intermittently (6 h/d, 12 h/d) and continuously operated biofilters (24 h/d), in addition to the effects of a 10-day shutdown. The findings demonstrated that intermittently operated biofilters maintain Mn and Fe removal efficiency comparable to continuously operated biofilters, although continuous biofilters exhibited higher ATP and EPS levels. Biofilters quickly recovered after a 10-day shutdown, highlighting their robustness. The overall microbial community composition was not significantly different between continuously and intermittently operated biofilters. \nOverall, the study successfully demonstrated that pilot-scale biofilters could reduce Mn levels below the Health Canada recommended AO of 20 μg/L, achieving over 90% removal efficiency in the presence of Fe at low water temperatures (15°C). The findings highlight the potential of GAC media to shorten start-up times and the feasibility of operating biofilters intermittently without compromising Mn and Fe removal efficiency.
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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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».