Determining the feasibility of phosphorus recovery as struvite from filter press centrate in a secondary wastewater treatment plant
Bibliographic record
Abstract
In this study, the workability of a pilot-scale, fluidized reactor was examined to determine effectiveness in removing, and recovering, phosphorus as struvite, from centrate at Lulu Island Wastewater Treatment Plant (LIWWTP), Richmond, British Columbia. The crystallization process was run continuously over a period of 5 months in two runs (Run 1 for 4 months and Run 2 for a month). In addition to efficient recovery of phosphorus as struvite, the study also investigated factors that affect the growth of struvite. Chemical analyses were conducted on the harvested struvite to determine its purity. Results showed that the reactor was capable of removing over 90% of phosphate and 4% of ammonia-nitrogen, with greater than 85% of the phosphate removed being recovered as harvestable struvite crystals. It was possible to achieve over 90% P-removal at a pH of 7.5; this is contrary to the information found in literature, which recommends that a higher pH (8.2-9.0) is required. Factors that affected phosphate removal were the operating pH, the reactor supersaturation ratio (SSR), the N:P and Mg:P molar ratios. Analysis of the harvested product showed that the crystals were composed of nearly pure struvite (96% by weight), with small amounts of calcium and traces of other metals. High resolution SEM pictures were taken of the inside of the crystals to determine the influence of Mg:P molar ratio on the compactness of the crystals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".