Phosphorus Reclamation from Municipal Wastewater Sludge for Fertilizer Production
Bibliographic record
Abstract
The increasing population with its associated rising food demand requires more agricultural fertilizers to maintain the harvest for food security. However, the natural calcium carbonate phosphate mineral (carbonate apatite) used to produce phosphorus (P) fertilizer is a non- renewable ore. Therefore, in this study, the objective is to extract the inorganic polymeric phosphate (polyphosphate: polyP) P-component in waste activated sewage sludge (WAS) from Ottawa’s municipal wastewater plant (ROPEC). Once extracted, the goal was to break down the polyP to inorganic phosphate (Pi) to produce carbonate apatite. PolyP is a P-component in WAS because a group of wastewater microorganisms called polyphosphate-accumulating organisms uptake phosphate and generate intracellular polyP stores during aerobic digestion in municipal wastewater treatment plant processes. The total acidic, oxidative P content of WAS was measured. PolyP was extracted and quantified to estimate the fraction of total P as polyP in WAS. Different polyP extraction methods were undertaken. It was determined that the complicated composition and weight fractions of TWAS, including iron phosphate, complicated polyP extraction and Pi measurement. Lessons learned were applied towards preliminary batch and continuous precipitation of carbonate apatite with the product slurry from the anaerobic digestion process at ROPEC. Limestone was tested as an inexpensive calcium carbonate source for carbonate apatite precipitation. The dissolution of calcium and carbonate from limestone was assessed, and it was determined that further optimization is required. Preliminary work indicated that the calcium- carbonate solution from limestone could precipitate synthetic carbonate apatite from anaerobic digester material. This synthetic carbonate apatite product may lead to mitigating the impending limitations on natural carbonate apatite availability for P-fertilizer production.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".