Treatment of an Aerobic Digester Sidestream in a Microbial Fuel Cell: Nitrate Removal and Electricity Generation
Bibliographic record
Abstract
Aerobic digestion of waste activated sludge is a common practice at water reclamation facilities. Dewatering of digester effluent produces a liquid stream, commonly referred to as a sidestream, that is rich in nitrogen and phosphorus. Removal of nitrogen from the sidestream improves mainstream treatment, but usually requires input of energy and/or chemicals. The purpose of this study was to evaluate the microbial fuel cell (MFC) as a candidate technology to remove nitrogen from the sidestream of aerobic digestion while simultaneously producing electricity, without requiring input of energy or chemicals. Toward this goal, a bench-scale MFC was constructed and operated for a period of 125 days to remove nitrogen (nitrate) from an aerobic digester sidestream from a treatment facility in Hillsborough County, Florida. The average removal rate of nitrogen was 14 mg/(L·day), the average power production was 0.38 mW/m2 of electrode surface area, and the apparent efficiency of electron transfer from anode to cathode was 41%. The nitrogen removal rate and apparent electron transfer efficiency are similar to those observed in previous MFC studies treating other nitrate-containing streams via cathodic denitrification. The low power generation may be due partly to the two-chamber configuration of the MFC employed, which was appropriate for the goals of this study but is not the most advanced MFC configuration. Therefore, we conclude that the MFC remains a promising candidate for nitrate removal from aerobic digester sidestreams, but that MFC configurations more advanced than the one employed here will be required for the technology to be viable at a larger scale.
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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".