Influence of backwash regime on biofilter performance in drinking water treatment
Bibliographic record
Abstract
Abstract BACKGROUND Drinking water biofiltration has the advantages of reducing the dissolved organic load in a drinking water treatment plant at a downstream process, such as membrane filtration and disinfection, as well as contributing to the continuity of water distribution. This study examines a series of backwash operational steps, including extended terminal subfluidization ( ETSW ) on dissolved organic carbon ( DOC ) and particulate removal, and additionally examines water with a low C:N:P ratio (considered non‐ideal for carbon removal), and water with an ideal C:N:P ratio for improved carbon removal. RESULTS Results showed that under nutrient limited conditions, collapse pulsing improved DOC removal by approximately 10% compared with a water‐only backwash condition. Bed expansions of 20% and 30% under improved nutrient conditions led to DOC removals of about 35% but further bed expansion to 40% decreased DOC removals (24%). The biofilter biomass concentrations, as measured by phospholipids and adenosine tri‐phosphate ( ATP ) showed no correlation with DOC removal. However, dissolved oxygen ( DO ) uptake showed a direct correlation with DOC removals. The addition of the ETSW had no impact on % DOC removals and successfully eliminated the filter ripening sequence. CONCLUSION The backwash method employed had an observable influence on biofiltration organic carbon removal. While air scour improved DOC removal, too high a bed expansion decreased removal levels. Thus an optimal level of backwashing exists in biofiltration that appears more stringent than requirements for conventional filtration alone. © 2016 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".