Biofiltration for Manganese Removal from Groundwater: Mechanistic Insights and Operational Strategies
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".