Pilot-scale, on-site investigation of crushed recycled glass as tertiary filter media for municipal lagoon wastewater treatment
Bibliographic record
Abstract
Glass recycling is a process that faces many obstacles, especially in the closed-loop context. Waste glass separation and transportation can become quite expensive, turning glass collection for remanufacture unfeasible. For this reason, it is important that alternative markets for waste glass are sought. This study evaluated crushed recycled glass as tertiary media in subsurface pilot-scale filters for on-site municipal wastewater treatment, using control sand media filters. Filters were operated over 128 days at a 24-h hydraulic retention time, treating secondary lagoon effluent from the rural municipality of Dunnottar, Manitoba, Canada. Crushed recycled glass filters removed 92%, 90% and 45% of the total suspended solids (TSS), ammonium nitrogen (NH4 +–N) and chemical oxygen demand (COD), respectively. Total suspended solids were removed equally well in sand and crushed recycled glass filters (α = 0.05), whereas NH4 +–N and COD reductions were 10% and 21% greater in sand media, respectively. Both sand and crushed recycled glass filters failed to achieve phosphorus (P) discharge guidelines. This study shows that there is potential for crushed recycled glass in wastewater filtration, especially to achieve TSS, COD and NH4 +–N removal. Small communities served by waste stabilization ponds could benefit from glass media filters, as waste glass could be diverted from curbside collection and utilized locally to polish municipal lagoon effluent.
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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 | 0.001 | 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".