Bibliographic record
Abstract
The study examined the individual and combined effects of potassium ferrate(VI) additions and freeze-thaw conditioning for the stabilisation and dewatering of wastewater sludges.The purpose of the research was to develop a simple and effective sludge management approach for remote communities in cold climates.Freeze-thaw sludge dewatering with gravity meltwater drainage reduced the sludge volume by up to 88%, and resulted in approximately 2.4-log inactivation of fecal coliform.For many of the test samples, increasing the time frozen from 1 to 15 days increased the level of inactivation of fecal coliform.However, some samples demonstrated >3-log inactivation of fecal coliform after only 1 day frozen, which suggests that fecal coliform inactivation occurs primarily as a result of the freezing process.Similarly, the freezing temperature did not have a significant effect on the level of inactivation, and increasing the duration of time spent frozen from 1 to 15 days did not improve sludge drainability during thaw, which indicates that particle consolidation, leading to improved sludge dewaterability, occurs during the freezing process.Potassium ferrate(VI) additions followed by a 15-minute reaction period oxidised sludge constituents, which inactivated fecal coliform, reduced the concentrations of odour causing compounds (ammonia and sulphide), and solubilised sludge solids, resulting in an increase in soluble chemical oxygen demand (sCOD), soluble proteins and soluble carbohydrates.Potassium ferrate(VI) additions as low as 1.0 g/L also reduced the concentrations of hormones in sludge.iii Co-treatment of anaerobically digested sludge using 5.0 g/L of potassium ferrate(VI) followed by freeze-thaw with gravity meltwater drainage reduced fecal coliform to <100 colony forming units (CFU)/g dry solids (DS), and dewatered the sludge to >12% total solids (TS), representing an 85% reduction in sludge mass following a 12-hour thawing period.The sludge cake remaining was suitable for land application in terms of fecal coliform under the level 1 criteria for pathogens (CP1) (Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA), 2013).Additionally, raw primary sludge was treated and dewatered to below CP2 limits using 5.1 g/L potassium ferrate(VI) followed by freeze-thaw with gravity meltwater drainage, and to below CP1 limits using <15 g/L pretreatment followed by freeze-thaw.
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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 | 0.000 | 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".