Nutrient removal (nitrogen and phosphorous) in secondary effluent from a wastewater treatment plant by microalgae
Bibliographic record
Abstract
Microalgae as a feasible option to remove nutrients (phosphorous and nitrogen) from domestic wastewater treatment plant discharge is demonstrated. Laboratory-scale experiments are described, characterizing nutrient removal of total phosphorous and ammonia by three cultured microalgae strains: Chlorella vulgaris, Spirulina maxima, and mixed cultures of naturally growing algae found in wastewater from the Collingwood Wastewater Treatment Plant in Ontario, Canada containing Synechocystis sp. (dominant), Chlorella sp. (common), and a few cells of Scenedesmus sp. Removal of phosphates strongly positively relates to solution pH. Volatilization of ammonia due to increase in pH is not a dominant contributor to overall removal efficiency. Total phosphorous removal rates reached 95.8% and 90.4% for untreated and autoclaved secondary effluent, respectively. Ammonia removal rates reached 94.6% and 86.2% for untreated and autoclaved secondary effluent, respectively. These results demonstrate that use of microalgae represents a sustainable approach to improve removal efficiencies of nutrients in wastewater treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".