Effect of coagulation and flocculation conditions on water quality in an immersed ultrafiltration process
Why this work is in the frame
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Bibliographic record
Abstract
The removal of natural organic matter under variable coagulation and flocculation pretreatment conditions was evaluated for three surface waters in an immersed ultrafiltration (UF) process. Coagulation with alum, flocculation and UF treatment were conducted in a bench-scale test apparatus designed to simulate pilot- and full-scale water treatment systems. Variable coagulation and flocculation operating conditions were investigated, including coagulant dose, hydraulic retention time (HRT) and mixing intensity (e.g. velocity gradient). Treatment performance was evaluated by measuring specific water quality parameters in the permeate stream, including dissolved organic carbon (DOC), UV254 and true colour. Coagulant dose was found to be the most important variable for treatment performance with regard to permeate water quality, with significantly lower alum dosages required to achieve enhanced coagulation water quality targets than conventional filtration systems. Experiments conducted to evaluate variable flocculation stage HRT and applied velocity gradient demonstrated that traditional set points for these operating variables, applied in conventional filtration systems, may not be required in UF systems. In particular, optimized UF permeate water quality was found with reduced flocculation retention times (e.g. <10 minutes) and mixing intensities (e.g. < 100 s(-1)). The impact of intermittent air scour, or air sparging, operations in the UF process tank during operation was also evaluated. The use of air scour, tested as an intermittent operation at an applied velocity gradient of 50 s(-1) was found to significantly reduce DOC concentrations and UV254 measurements in the UF permeate stream when compared with UF operations without air scour.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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 it