Combined biological and advanced oxidation processes for the treatment of an actual slaughterhouse wastewater
Bibliographic record
Abstract
Environmental protection initiatives and increasing market demand for green practices are driving the meat processing industry to consider sustainable methods for wastewater treatment of slaughterhouse wastewater. On- site treatment is the preferred option to treat the slaughterhouse effluents for water reuse and potential energy recovery due to the conversion of organics into biogas. A thorough review of advancements in slaughterhouse wastewater characteristics, treatment, and management in the meat processing industry, environmental impacts, health effects, and regulatory frameworks relevant to the slaughterhouse wastewater management is presented in this study. Significant progress in high-rate anaerobic treatment, nutrient removal, advanced oxidation processes, and combined processes for an actual slaughterhouse wastewater treatment are highlighted. The optimization of individual and combined processes was performed in this study using quadratic modeling, degradation mechanisms, and response surface methodology to maximize CH4 yield and the removal of TOC and TN while minimizing TSS and H2O2 residuals. The effects of the flow rate, pH, influent TOC concentration, H2O2 dosage, and their interaction on the overall treatment efficiency and CH4 yield were studied. In the final part of this study, an optimized combined anaerobic–aerobic and UV/H2O2 system with recycle was evaluated using a cost- effectiveness analysis by minimizing treatment time, electrical energy consumption, and the overall incurred treatment costs. The agreement between model predictions and experimental values indicated that the proposed models could describe the performance of individual and combined systems for actual SWW treatment. The maximum TOC and TN removals of 91.29 and 86.05%, CH4 yield of 55.72%, and minimum H2O2 residual of 1.45% were found at optimum conditions of influent TOC concentration of 626 mg/L, feed flow rate of 45 mL/min, H2O2 dosage of 350 mg/L, and pH of 6.59. The minimum total retention time was determined to be 10 h with individual residence times of 6.82 h, 2.40 h, and 47 min in the ABR, AS bioreactor, and UV/H2O2 photoreactor, respectively. A minimum electrical power consumption of 0.0194 kWh for an overall treatment cost of 0.12 $/m3 were obtained based on the cost-effectiveness analysis. Results show that the application of combined biological and advanced oxidation processes is useful for on-site slaughterhouse wastewater treatment. Keywords: Slaughterhouse wastewater, anaerobic digestion, activated sludge, advanced oxidation processes, process optimization, cost-effectiveness analysis.
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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".