Impact of blending reuse and lake water on treated water quality
Bibliographic record
Abstract
The impact of supplementing a raw drinking water source with reuse water was examined. Reuse water produced from municipal wastewater by a membrane bioreactor and reverse osmosis (MBR-RO) system was blended with untreated Lake Ontario water, then subjected to conventional water treatment processes, and evaluated in terms of disinfection by-products (DBPs), nitrate, and coliforms. The addition of reuse water to the lake water improved water quality in terms of total organic carbon (TOC) and bromide, which resulted in reduced trihalomethane (THM) formation. This appeared to be entirely due to dilution with no specific impact from the conventional treatment process. Nitrate levels in the reuse water (1.4 mg/L) were higher than the lake water (0.4 mg/L) and, therefore, an increase in the reuse water : lake water blend ratio resulted in a linear increase in nitrate levels. The conventionally treated blend water was shown to meet typical drinking water regulations for THMs, haloacetic acids (HAAs), total coliform, and nitrate. Key words: water reuse, drinking water supplement, reverse osmosis, membrane bioreactor, conventional water treatment, disinfection by-products, nitrate.
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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 | 0.000 | 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 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".