Vacuum evaporation coupled with anaerobic digestion for process intensification and ammonia recovery: Model development, validation and scenario analysis
Bibliographic record
Abstract
A mathematical model for vacuum evaporation process was developed, which was experimentally validated at different initial pHs and temperatures for ammonia removal from anaerobically digested sludge. Six scenarios were evaluated by combining vacuum evaporation process with anaerobic digestion using anaerobic digestion model 1. These scenarios included a control, a pretreatment by vacuum evaporation, a post-treatment by vacuum evaporation at pH 9, a post-treatment by conventional evaporation (100 °C), an intensification with vacuum-concentrated recycled digestate back to the digester, and a second intensification at pH 9. Results indicated that using the evaporator as post-treatment at pH 9 or for intensification at pH 9 were the most favorable options, recovering more than 76 % of the nitrogen present in influent sludge with no negative effect on methane production. An economic analysis showed that the intensification at pH 9 was cost-neutral, significantly higher than the net present value of the control scenario (-22 M$).
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 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".