Integrating Anaerobic Digestion With Struvite Production for Enhanced Nutrient Recovery, Pathogen Reduction, and Circularity in Manure Management
Bibliographic record
Abstract
ABSTRACT Introduction Anaerobic digestion (AD) is essential for manure management, generating biogas and nutrient‐rich digestate for organic fertilizer. However, improper digestate use can pose environmental risks. Recovering struvite, a magnesium ammonium phosphate (MAP) compound, from digestate provides a sustainable, controlled‐release fertilizer, supporting a circular economy in agriculture. Materials and Methods The study employed a two‐stage (liquid–solid) AD process using poultry, dairy, and swine manures, along with wasted corn silage. Digestates were sampled for physicochemical and biogas quality analyses, with feedstocks categorized into D1 and D2, and a composite (D3) formed for struvite characterization. Microbial populations were enumerated on selective media, and struvite mineral content was analysed via argon plasma emission spectrometry. Results The digesters processing feedstock mixtures D1 and D2 achieved specific methane yields of 1.26 L/g CODs fed and 1.49 L/g CODs fed, with cumulative biogas production of 374 and 369 L, respectively, over four 77‐day cycles. The two‐stage AD process significantly reduced antibiotic‐resistant, Enterobacteriaceae and Enterococcus spp. Total ammoniacal nitrogen (TAN) recovery rates were high at 98%–99%, with a consistent struvite crystal mass of 0.67 g/10 mL, indicating the efficiency of this integrated process. The agronomic value of struvite was determined, indicating its potential utility as a fertilizer, and scanning electron microscopy analysis revealed diverse crystal structures, warranting further investigation into their implications for usage and storage. Conclusion The results suggests that the two‐stage AD process efficiently transforms organic waste into high‐quality biogas, reduces antibiotic‐resistant bacteria, and facilitates nutrient recovery through struvite precipitation. This approach supports co‐digestion of multi‐substrates and promotes circular economy principles, with potassium or sodium phosphate enhancing struvite recovery for sustainable agriculture.
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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) | 0.001 | 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) | 0.000 | 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".