Removal of effluent organic matter by purolite fluidised bed and submerged membrane hybrid system
Bibliographic record
Abstract
In this study, Purolite®A500PS was used to remove effluent organic matter in a fluidised bed and submerged membrane hybrid system (SMHS). It was found that the fluidised bed purolite column can effectively remove 73% of dissolved organic compound (DOC) from synthetic biologically treated sewage effluent (BTSE). DOC removal can be reduced further, by up to 95% when the fluidised bed purolite column was combined with a treatment by granular activated carbon column. Purolite®A500PS was also used as an adsorbent in the SMHS. The results showed that critical flux of the SMHS depend on the purolite size. Critical fluxes of SMHS were 30 and 35 L/m2.h where 0.1 g/L of purolite of sizes below 150 µm and 150–300 µm were used respectively. The removal efficiency of natural organic matter from synthetic BTSE by SMHS was a function of purolite dose. The removal efficiency increased from less than 60% to more than 70% when the purolite dose increased from 0.05g/L to 0.1g/L.
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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) | 0.000 | 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 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".