Growth and nutrient removal capacity of Chlorella vulgaris microalgae in high ammonia media
Bibliographic record
Abstract
Wastewater treatment is essential to remove toxic particulates before it is discharged to the surrounding environment. Recently, algal-based systems have been widely used for wastewater treatment. However, there is a lack of studies on algal growth’s feasibility in high ammonia media. In this research, the growth of Chlorella Vulgaris microalgae in high ammonia media was investigated. In the first stage, 200, 400, 600, and 800 mg/l of ammonia (NH4) levels were applied. The optimal growth and nutrient removal were achieved with 600 mg/l ammonia. Biomass concentration of 1268 mg/l and ammonia removal of 348 mg/l was obtained. Algae had low growth in a high-ammonia medium (800 mg/l). In the second stage, the buffering system of CO2/ NaHCO3 was applied. Different carbon dioxide concentrations (2, 4, and 6%) and sodium bicarbonate (1, 1.5 and 2 g/l) were investigated. The best results (biomass concentration and ammonia removal of 1740 and 417.33 mg/l, respectively) were obtained with 4% CO2 and 1.5 gr/l NaHCO3. This study shows the feasibility of C. Vulgaris growth in harsh low-pH conditions and its optimal conditions to remove nutrients from wastewater.
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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 | 0.000 | 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 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".