Coupling anaerobic digestion process and electrocoagulation using iron and aluminium electrodes for slaughterhouse wastewater treatment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The performance of a two-stage process combining anaerobic digestion (AD) and electrocoagulation (EC) was studied for the treatment of slaughterhouse wastewater (SWW). Anaerobic digestion was used as primary treatment, whereas electrocoagulation process was used as secondary treatment. After anaerobic digestion, the optimal current density and the treatment time for Chemical Oxygen Demand (COD) and P-PO43− removal by electrocoagulation using Fe and Al electrodes were determined. These optimal conditions were finally used for the secondary treatment of slaughterhouse wastewater by electrocoagulation. The primary treatment by anaerobic digestion removed of 49.93 ± 0.37% COD. However, this led to an increase in residual concentration of P-PO43−. The optimal conditions for COD and P-PO43− removal by electrocoagulation were obtained with a current density of 18.18 mA/cm2 and a treatment time of 40 min for both types of electrodes. The secondary treatment by electrocoagulation respectively resulted from a total removal of 79.73±0.75% and 80.12±0.85% COD, 95.90±0.03% and 95.42±0.11% NO3−, and 92.48±0.20% and 90.66±0.36% of turbidity, respectively, with Fe and Al electrodes. This study reveals the complementarity of anaerobic digestion and electrocoagulation could be the basis of a process able to simultaneously remove organic and inorganic pollutants for various applications (municipal and industrial wastewater treatment, etc.).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it