COD Removal of Edible Oil Content in Wastewater by Advanced Oxidation Process
Bibliographic record
Abstract
Different Advanced Oxidation Processes (Photo Fenton process, Fenton process and H2O2/UV) were studied in order to reduce COD from oily compounds aqueous solution using batch system. To get the optimum condition, different variables were studied for each of these processes; such as pH, time, concentration of H2O2, concentration of oil, concentration of FeSO4·7H2O and temperature as parameters. It was found that the optimal pH value for the three processes was 3 and the optimal temperature was 30oC for Photo-Fenton and UV/H2O2 system and 20oC for Fenton process. Photo-Fenton process gave a maximum COD reduction of 80.59 % (COD from 2684 to 521 mg/l), Fenton gave 53.22 % (COD from 2587-1130) and the combination of UV/H2O2 gave a COD reduction of 22.69 % (COD from 2450 to 1894). The percentage of removal found was after the total reaction time (180 min.). The optimum chemical reagents for Photo-Fenton, Fenton and UV/H2O2 were as the following H2O2 = 800 mg/l, 1500 mg/l and 2000 mg/l, Fe2SO4·7H2O = 60 mg/l, 100 mg/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".