The Biological Performance of a Novel Electrokinetic-Assisted Membrane Photobioreactor (EK-MPBR) for Wastewater Treatment
Bibliographic record
Abstract
Developing an effective phycoremediation system, especially by utilizing microalgae, could provide a valuable approach in wastewater treatment for simultaneous nutrient removal and biomass generation, which would help control environmental pollution. This research aims to study the impact of low-voltage direct current (DC) application on Chlorella vulgaris properties and the removal efficiency of nutrients (N and P) in a novel electrokinetic-assisted membrane photobioreactor (EK-MPBR) in treating synthetic municipal wastewater. Two membrane photobioreactors ran in parallel for 49 days with and without an applied electric field (current density: 0.261 A/m2). Mixed liquid suspended soils (MLSS) concentration, chemical oxygen demand (COD), floc morphology, total phosphorus (TP), and total nitrogen (TN) removals were measured during the experiments. The results showed that EK-MPBR achieved biomass production comparable to the control MPBR. In EK-MPBR, an over 97% reduction in phosphate concentration was achieved compared to 41% removal in the control MPBR. The control MPBR outperformed the nitrogen removal of EK-MPBR (68% compared to 43% removal). Induced DC electric field led to lower pH, lower zeta potential, and smaller particle sizes in the EK-MPBR as compared with MPBR. The results of this novel study investigating the incorporation of Chlorella vulgar is in an electrokinetic-assisted membrane photobioreactor indicate that this is a promising technology for wastewater treatment.
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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) | 0.001 | 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".