Assessment of a wastewater stabilization pond system for removal of arsenic, iron, and ammonia from reverse osmosis water treatment plant residual wastewater
Bibliographic record
Abstract
Drinking water treatment plants (DWTPs) produce wastewaters with elevated concentrations of heavy metals, metalloids, ammonia, and other contaminants. These wastewaters require treatment via processes including wastewater stabilization ponds (WSPs). This study assessed the arsenic (As), iron (Fe), and ammonia (NH3) concentrations in a Saskatchewan DWTP WSP system of five sequential ponds. Drone imaging combined with flow and depth data was used to estimate retention times which increased from 7–9 to 8–10 days after the DWTP upgrade. Concentration trends showed Fe decreased from Pond 1 to 3 and increased in Ponds 3 and 5, while As decreased from Pond 1 to 5. Average effluent As concentrations of 10.6 µg/L were above the 5.0 µg/L guideline, while concentration guidelines for both Fe and NH3 were easily met post-upgrade in 2020. Several actions are recommended to ensure adequate WSP operation including dredging, aeration, and installing macrophytes capable of As uptake.
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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 | 0.001 | 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 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".