Assessment of sediment arsenic and iron occurrence and leaching potential in a potable water treatment plant wastewater stabilization pond system
Bibliographic record
Abstract
Wastewater stabilization ponds (WSPs) are commonly used to reduce wastewater metal(loid) concentrations from drinking water treatment plants (DWTPs) through sedimentation. However, this results in increased sediment concentrations that can be released back into the overlying water. Thus, our goal was to evaluate the WSP metal(loid)s occurrence and leaching potential. Currently, a Saskatchewan based DWTP’s WSP system was investigated given historically elevated effluent As and Fe concentrations. The WSP consists of five ponds that were sampled on six occasions in 2019 and 2020. In addition, sediments were used in laboratory-based experiments to determine their leaching potential. Overall, the sediments were found to contain elevated concentrations of As and Fe of 25 to 400 mg/kg and 10 000 to 45 000 mg/kg, respectively. Leaching experiments indicated that the pond sediments could potentially release As and Fe with log Kd values ranging from 2.21 to 4.31 L/kg, whereas Fe ranged from 3.32 to 5.53 L/kg.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".