The effect of salinity concentration on algal biomass production and nutrient removal from municipal wastewater by <i>Dunaliella salina</i>
Bibliographic record
Abstract
Extensive amounts of organic and inorganic substances are discharged into the environment, and they have been ascribed to a number of anthropogenic activities including agriculture, industry, and domestic processes. Microalgae, as a promising alternative feedstock for bioenergy production, have advantages in the uptake of nutrients from wastewater for biomass production. This study assessed the feasibility of mass cultivation of microalgae in controlled environment tertiary treated municipal wastewater. Dunaliella salina (D salina) was selected for its high beta carotene generation capacity and being a halophilic species to protect our freshwater resources further in wastewater remediation. Nutrient analyses indicated that D salina can significantly remove nitrate, ammonia, and phosphorus from municipal wastewater in the range of 45% to 88%. Among all combinations studied, the optimal algal growth was observed at 30 ppt salinity level, with a 75% wastewater concentration (3:1 ratio of wastewater and saline water mixture—the growth medium). The findings concluded that D salina has great capacity for nutrient uptake while providing high-value bioproducts. It can therefore be recommended as a potential candidate species that could be used in wastewater treatment systems coupled with high-value bioproducts production.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".