A technological and economic analysis of vacuum‐assisted fermentation to augment enhanced biological phosphorus removal at full‐scale
Bibliographic record
Abstract
Abstract IntensiCarb® represents a vacuum‐driven intensification technology with applicability in fermentation or anaerobic digestion. Implementation of this technology in fermentation facilitates a 50% reduction in process volume while concurrently enhancing the yield of volatile fatty acids (VFAs) for advantageous utilization such as carbon source for enhanced biological phosphorus removal (EBPR). An analysis was conducted to assess the process performance and life‐cycle costs of IntensiCarb in comparison to chemical addition and conventional fermentation methodologies for Total Phosphorus (TP) removal. Experimental outcomes pertaining to vacuum‐assisted process intensification informed the process performance analysis. Greenhouse gas (GHG) emissions were estimated and compared between alternatives. The findings of the assessment indicate that IntensiCarb is a competitive option among alternatives that reduce effluent TP through EBPR. TP removal via FeCl3 chemical addition was the most economically advantageous alternative based on current economics and estimated life‐cycle cost. Practitioner points Novel vacuum‐assisted fermentation, IntensiCarb®, was evaluated against other alternatives for process and cost comparisons in enhanced biological phosphorus removal facilities. IntensiCarb® has a similar life‐cycle cost with conventional fermentation and MicroC® 2000 alternatives for achieving lower effluent total phosphorus. The evaluation suggests this technology may be economically viable at full‐scale for enhanced biological phosphorus removal facilities. FeCl3 addition and IntensiCarb had the highest greenhouse gas emission estimates relative to conventional fermentation or using MicroC® 2000.
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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 | 0.000 | 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 | 0.001 | 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".