Urban wastewater (Fez, Morocco): characterisation and coagulation-flocculation treatment
Bibliographic record
Abstract
In this work, characterisation of urban wastewater from Fez City, Morocco, consisting mainly of a mixture of industrial and urban discharges, and its treatment using the coagulation–flocculation (C-F) process were conducted. Three coagulants were used: lime (Ca(OH) 2 ), ferric chloride (FeCl 3 ) and alum (Al 2 (SO 4 ) 3 ). Ferric chloride achieved the highest reductions in turbidity, chemical oxygen demand (COD) and colour. Then, the Box–Behnken design was applied to optimise the amounts of the coagulant and flocculant and pH. The maximum response values were 78, 98 and 99% for COD, colour and turbidity, respectively, under the following optimal operating conditions: [FeCl 3 ] = 720 mg/l, [flocculant] = 150 mg/l and pH = 7. The operational cost of C-F implemented in this study was estimated at US$0.52/m 3 , proving that it could be a competitive and cost-effective process for the treatment of wastewater. These results will contribute to the existing literature and would be valuable for scaling up the C-F process.
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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 | 0.000 |
| 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 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".