Assessing the Performance of Biological Filtration As Pretreatment to Low Pressure Membranes for Drinking Water
Bibliographic record
Abstract
Although the use of ultrafiltration membranes in drinking water treatment is increasing, fouling remains a major challenge. The objective of this study was to evaluate rapid biological filtration (without coagulant addition) as a pretreatmentto reduce fouling. Surface water was first passed through a pilot scale roughing filter followed by two parallel anthracite/sand biofilters having different contact times, before being fed to the ultrafiltration membrane. As a chemical-free pretreatment, this novel application of biofiltration removes biopolymers (polysaccharides and proteins) that are the most important component of organic matter for fouling, as well as removing particulate matter. Biopolymer removal was influenced by contact time and temperature. The biofilter with the longer contact time led to greater reductions in both hydraulically reversible and irreversible fouling. The extent of hydraulically reversible fouling was related to the membrane influent biopolymer concentration, but the level of hydraulically irreversible fouling was not, indicating that the composition of the biopolymer fraction may have been important. Biofiltration as a simple and robust pretreatment may be particularly suited for small drinking water systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".