Reduction of leachability of sewage sludge by alum treatment
Bibliographic record
Abstract
The sustainable disposal practices of waste materials have drawn much attention in the last two decades. One of the growing disposal practices is the use of land-based application (e.g. fertiliser). However, the application poses concerns of contamination from heavy metals and nutrients. Therefore, there appeared to be a growing necessity for finding appropriate technology to address the concerns related to leaching from sewage sludge. The objective of this paper is to assess the applicability of alum treatment of biologically treated sewage sludge for reduction of leachability. Alum and lime were used for the treatment of sewage sludge. Laboratory-based batch and column tests were conducted to assess the effect of alum treatment on leachability. Batch experimental results indicated that alum treatment was capable of reducing phosphorus and other heavy metal leaching. However, some of the aluminium appeared to have leached into the water. Column experimental results indicated that alum treatment was capable of reducing phosphorus, copper and ammonia leaching from sewage sludge, but indicated an increase in aluminium and chromium leaching. However, the leaching of chromium and copper was at low concentrations, indicating the necessity of further exploration onto sewage sludge from different wastewater treatment plants.
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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 | 0.001 | 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".