Effects of temperatures and extracellular proteins on dewaterability of thermophilically digested biosolids
Bibliographic record
Abstract
Thermophilic processes digest sludge at high temperatures to produce Class A biosolids. Recent research work revealed that digestion temperature is the predominant factor affecting dewaterability of thermophilic biosolids. This paper presents findings of a laboratory study that investigated how various digestion temperatures affect dewaterability of digested biosolids, studied the phase partition of the substances affecting dewaterability in digested biosolids, and tested the role of extracellular proteins in affecting dewaterability. Secondary sludges were digested at 40°C, 50°C, 60°C, 70°C, or 22°C for up to 12 d. Filtrates from thermophilically digested biosolids were treated with protease and boiling. This study found that, during the first few hours of digestion, higher temperatures resulted in more rapid and more significant deterioration in dewaterability than lower digestion temperatures. Continued digestion resulted in either improved (60°C or 70°C), unchanged (40°C or 50°C), or gradually deteriorated dewaterability (22°C). The substances affecting dewaterability were primarily located in the liquid phase of thermophilically digested biosolids. Boiling treatment did not result in significant changes in dewaterability. Protease treatment of the liquid phase of thermophilic biosolids improved dewaterability by 13–19%. Such an improvement confirmed the role of proteins in affecting dewaterability. Key words: dewaterability, thermophilic, mesophilic, digestion, biosolids, protein, protease.
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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 | 0.001 |
| 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".