Phenol degradation by combined photochemical-biological wastewater treatment system : kinetic modeling and optimization
Bibliographic record
Abstract
A dynamic kinetic model, for the oxidation of phenol in water by UV/H₂O₂ system is developed. The model is based on elementary chemical and photochemical reactions, initiated by the photolysis of hydrogen peroxide into hydroxyl radical. Numerical values of chemical reaction rate constants and photochemical parameters are taken from literature. The model is validated with data on the oxidation of phenol in the simulated and the actual UV/H₂O₂ system. Using experimental data from literature, kinetic rate constants for the reactions involving phenol oxidation intermediates, catechol and hydroquinone, are estimated. The rate constants for the reactions, where phenol oxidized to catechol and hyroquinone by hydrogen peroxide are 9x10⁸ and 2x10⁸ s⁻¹ M⁻¹, respectively. The reaction rate constants for oxidations of catechol and hydroquinone by hydrogen peroxide are found to be 9x10⁸ and 8x10⁷ s⁻¹ M⁻¹, respectively. Phenol biodegradation is best represented by a two-step Haldane model. Both photochemical and biological models are coupled together to give one single chemical-biological system. The photochemical-biological process is optimized for the retention time, electrical energy consumption, and cost. The optimization approach is solved using the Successive Quadratic Programming (SQP) method. The least retention time for this system is determined to be 99h and the optimal electrical energy consumption occurs at a photochemical retention time of 15h and a biological retention time of 92h. Calculations on the total cost for different retention times show that the incurred cost by the photochemical unit is considerably higher than that by the biological unit. However, the minimum total cost is evaluated to occur at 15.5h of photochemical retention time and 90h of biological retention time.
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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".