An evaluation of autothermal thermophilic aerobic digestion (ATAD) of municipal sludge in Ireland
Bibliographic record
Abstract
Autothermal thermophilic aerobic digestion (ATAD) is an exothermic process where sludge is subjected to temperatures greater than 55 °C and a hydraulic retention time of 6–15 days. Organic solids are degraded and the heat released during the microbial degradation maintains thermophilic temperatures. Autothermal thermophilic aerobic digestion can produce a biologically stable product while reducing both sludge mass and volume. The full-scale ATAD facility in Killarney, Ireland, is unique because the feed sludge is blended from three different secondary treatments and there are seasonal fluctuations in hydraulic load. An assessment of the on-site operational and solids data showed that the process operation has improved since commissioning. Total solids reduction increased from 13.7% in 2001 to 39.1% in 2004. Also, despite some operational problems the regulatory target of 38% reduction in volatile solids was achieved. The data fluctuated but the percent reduction in volatile solids increased from 35.6% in 2001 to 49.8% in 2004. This paper compares the process data obtained from the Killarney site with other ATAD facilities operated in Europe and North America. It discusses some of the operational changes employed to deal with process control issues and it presents recommendations for enhanced ATAD process improvement.Key words: autothermal, thermophilic, aerobic, digestion, sludge, biosolids.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".