Use of Acid Preconditioning for Enhanced Dewatering of Wastewater Treatment Sludges from the Pulp and Paper Industry
Bibliographic record
Abstract
In municipal and industrial practices, wastewater treatment sludges are generally conditioned with organic polymers before dewatering. The dewatering polymers are expensive and contribute significantly to the overall sludge management cost. This paper discusses a preconditioning strategy that holds great promise for enhancing dewatering properties of wastewater treatment sludges, while reducing the cost. In this approach, the waste activated sludge (WAS) is briefly preconditioned with an acid before flocculating with an organic polymer. Experimental results showed that acid preconditioning significantly enhanced dewatering. Separately acidifying WAS and subsequently combining it with primary sludge produced higher presscake solids than acidifying the combined sludge to the same final pH. Acidification exhibited the added benefit of reducing Escherichia coli counts in sludge, thus improving its biological character. This may provide flexibility in choosing a beneficial use application.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".