Microbial consortia in full-scale pre-ozonated biologically active filters treating a high-DOC water: Effects of seasonal and operational variations
Bibliographic record
Abstract
This study investigated the microbial dynamics in full-scale biologically active anthracite/silica sand (BAS) and granular activated carbon (BAC) filters used to treat high-DOC coagulated softened water. By analyzing these filter types across two seasons (winter and summer), we examined the impact of operational conditions-including temperature (1 °C vs. 25 °C), backwashing cycle (72 h vs. two weeks), and empty bed contact time (10 vs. 24 min in BAC and 4 vs. 10 min in BAS)-on organic matter removal, biological activity, and bacterial taxonomy and functionality. The highest DOC (19.1 %) and BDOC (34.8 %) removal rates were observed in BAC during summer and post-backwashing, whereas BAS in both seasons and BAC in the winter showed minimal effects on the organic matter concentration. No direct correlation was found between ATP levels, bacterial 16S rRNA bacterial gene copy numbers, and DOC/BDOC removal in BAC. However, an optimal condition of 13 × 10⁻⁶ ATP per bacterial gene copy number in BAC during summer post-backwashing coincided with the highest DOC and BDOC removal. Bacterial taxa with established associations to DOC degradation accounted for over 60 % of the total bacterial orders identified in both BAS and BAC across seasons. The BAC environment appeared to selectively enrich consortia capable of transforming complex DOC fractions, likely facilitated by its greater surface area, extended EBCT, and less frequent backwashing. These conditions supported the persistence and activity of specific bacterial orders, including Actinomycetales, Myxococcales, Planctomycetales, and Rhizobiales. Subsystem-level metagenomic analysis indicated a significant enrichment of genes associated with metabolic functions linked to enzymes such as decarboxylase, N-methylhydantoinase A, cyclic beta-1,2-glucan synthase, carbon monoxide dehydrogenase, cell division protein FtsH, N-methylhydantoinase B, and UDP-glucose 4-epimerase in BAC samples. This study deepens our understanding of the BAF microbiome's role in natural organic matter removal and its relationship with operational parameters, addressing critical gaps in drinking water biological treatment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".