Co-Processing of Organic Fraction of Municipal Solid Waste and Primary Sludge – Stabilization and Disinfection
Bibliographic record
Abstract
Batch mesophilic digesters were fed a mixture of the organic fraction of municipal solid waste (OF-MSW) and primary sludge (PS), and operated under non-mixing condition at a 30-day influent mass retention time. The reactors were started in a slurry mode and brought to the target level of 26-30% total solids in about 3 months from start. Two feed characteristics, the level of PS solids in the feed, and the particle size of the OF-MSW, were the variables used to determine their effect on methane production during digester operation. Higher biodegradable volatile solid reductions and methane yields matched increased fractions of primary sludge in the feed (5%, 10%, and 15% as dry solids). Incomplete digestion, limited to fermentation, took place in reactors that did not receive primary sludge. The particle size did not have any effect on specific weight of the feed but the amount of primary sludge did. Addition of vitamins and micronutrients to the inhibited reactors did not stimulate methane production, which narrowed the range of possible causes to the lack of available macronutrients, namely nitrogen. On the other hand, possible un-ionized ammonia (NH3) inhibition of reactors fed with the highest primary sludge-amended feed hindered organic conversion rates. Elimination of pathogenic microorganisms from the high-solids residue via long-term storage, followed by low-dose lime disinfection, was also investigated. Storage alone reduced fecal coliform and Salmonella sp. bacteria to below detection, but bacterial spores of anaerobic Clostridium perfringens survived. Subsequent liming of the residue caused irreversible inactivation of the spores because of high pH and, possibly, free ammonia (NH3) inherent to sludge.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".