Combined Electrocoagulation and Chemical Coagulation in Treating Brewery Wastewater
Bibliographic record
Abstract
Significant over-strength discharge fees are often imposed on breweries for the disposal of high-strength effluent to sanitary sewers. In this research work, the removal performances of electrocoagulation (EC) compared with operating electrocoagulation and chemical coagulation in sequence (EC-CC) or vice-versa (CC-EC) was examined to determine the capability of treatment in reducing the strength of the wastewater. Optimal operating parameters regarding electrolysis time, initial pH, and applied power were determined in conjunction with nutrient removal performance, electrode consumption and energy usage. Combined EC-CC treatment has been demonstrated to be economically feasible for brewery wastewater applications from an energy consumption perspective due to the efficiency of nutrient removal and the reduction of sewer discharge costs. Treatment by EC-CC at 5 W for 20 min using aluminum electrodes resulted in enhanced and consistent removal efficiencies of 26%, 74%, 76%, and 85% for chemical oxygen demand (COD), reactive phosphorous (RP), total phosphorous (TP) and total suspended solids (TSS), respectively. Energy consumption was the main contributor to operating cost. By considering potential recovered over-strength discharge fees (ODF), EC-CC treatment is economically feasible and beneficial in a brewery wastewater application. The results demonstrated the effectiveness of the CC-EC process to remove phosphorous, organics and solids from brewery wastewater at lower power supply, so that the recovered ODF cost for CC-EC at 5 W-EC is 23% higher than at 10 W-EC.
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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".