Techno-economic assessment at full scale of a biogas refinery plant receiving nitrogen rich feedstock and producing renewable energy and biobased fertilisers
Bibliographic record
Abstract
Anaerobic digestion of nitrogen (N) rich substrates might be hindered when ammonia (NH3) formation reaches toxic levels for methanogenic microorganisms. One possible strategy to avoid inhibiting conditions is the removal of NH3 from digestate by stripping and scrubbing technology and by recirculating N depleted digestate back to the digester. This study aimed to i) monitor the performance (mass and energy balances) of a full scale digestate processing cascade that includes an innovative vacuum side stream NH3stripping and scrubbing system, ii) assess the production cost of ammonium sulphate (AS) solution and iii) evaluate its fertiliser quality. The use of gypsum to recover NH3 in the scrubbing unit, instead of the more common sulphuric acid, results in the generation of AS and a fertilising liming substrate. Mass and nutrient balances indicated that 57% and 7.5% of ammonium N contained in digestate was recovered in the form of a 22% AS and liming substrate, respectively. The energy balance showed that about 3.8 kWhel and 59 kWhth were necessary to recover 1 kg of N in the form of AS. Furthermore, the production cost of AS, including both capital and operational costs, resulted to be 5.8 € t−1 of digestate processed. According to the fertiliser quality assessment, this technology allows for the recovery of NH3in the form of salt solutions that can be utilised as a substitute for synthetic mineral nitrogen fertilisers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".