Use of carbon dioxide stripping for struvite crystallization to save caustic dosage: performance at pilotscale operationPaper submitted to the Journal of Environmental Engineering and Science.
Bibliographic record
Abstract
The feasibility of stripping CO2 from anaerobic digester centrate (generated in a sludge dewatering process) to raise pH, and therefore reduce the cost of caustic chemical(s) dosage for similar operation in a struvite-recovery system, was investigated. A cascade CO2 stripper was installed in a pilot-scale, struvite-recovery reactor system at the Lulu Island Wastewater Treatment Plant, Richmond, British Columbia, Canada, as a replacement of part of (about 1/3) the reactor downpipe. Centrate was used as the process feed. Both the influent and the effluent from the struvite reactor were analyzed for pH, temperature (°C), and concentrations of Mg, NH4-N, and PO4-P. Results indicated that, by adding the CO2 stripper, caustic chemical savings was as much as 46%–65%. Moreover, because of the capability of the stripper in providing a more gradual pH increase, fewer fine solids were produced in the reactor than when caustic solution was used to raise the pH of the reactor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".