Pollution reduction at wastewater treatment facilities through thermophilic sludge digestion
Bibliographic record
Abstract
Wastewater treatment facilities produce large amounts of sludge, which is a pollutant to the environment if not properly managed. Among the three most common methods (landfills, land application, incineration) of sludge disposal, thermophilic digestion to produce Class-A biosolids for land application is recognized as the most cost-effective, environmentally sustainable option. Full-scale experience revealed that thermophilically digested biosolids consumed a higher dosage of chemicals for conditioning and dewatering than conventionally (mesophilically) digested biosolids. This paper presents findings of a recent study to investigate how major operational parameters affect dewatering properties of thermophilically digested biosolids, and to search for the inter-relationship between digestion, characteristics of digested biosolids, and dewatering properties of thermophilic biosolids. Experimental work was carried out using bench-scale aerobic digesters. This study found that feed sludge composition has a significant effect on dewaterability. A higher content of secondary sludge resulted in poorer dewaterability in undigested and digested sludge. Dewatering properties are sensitive to a temperature effect. Such an effect is physical-chemical in nature. Excessive high shear results in significant deterioration in dewaterability. Thermophilic digestion resulted in a substantial increase in ammonia and phosphate concentrations, but these two factors seem to not have much impact on dewaterability. Instead, cellular biopolymers have a significant role in affecting dewatering properties of thermophilically digested biosolids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".