Phosphorus and Carbon Capture from Synthetic Municipal Wastewater by Carbonate Apatite Precipitation
Bibliographic record
Abstract
The world’s 7 billion inhabitants depend on chemical fertilizers to meet the growing demand for food. The phosphorus used in fertilizer is sourced from ancient sedimentary deposits of Phosphate Rock (PR), largely in the form of carbonate calcium phosphate, called carbonate apatite, which resembles bone. PR is non-renewable and Canada’s reserves are extremely limited; currently, all 1,400,000 tonnes of phosphorus products used annually are imported. This project investigates a novel method to recycle phosphorus from municipal wastewater in a form that will enable its reuse as a fertilizer, through a reaction with CaCO3 from limestone and waste CO2 (g). This will contribute to the nascent circular nutrient economy within Canada. A review of the current state of phosphorus and nutrient recycling is presented, including a plan for establishing the Canadian Nutrient Platform. A series of inorganic phosphate (PO4-, or Pi) solutions was prepared to simulate the concentrations found in Ottawa’s municipal wastewater, between 2.5-30 mM Pi. These solutions were mixed with CaCO3 solutions that were highly supersaturated through a carbon capture technique. Batch tests successfully reduced the [Pi] and [Ca2+], as measured by colorimetry, and precipitate formed. These results were subsequently repeated in a continuous stirred lab-scale reactor. These precipitation products were characterized using Scanning Electron Microscopy, Raman Spectroscopy, X-Ray Diffraction, and carbon coulometry to measure carbonate content. This analysis confirmed the presence of both Pi and CO3 in a bone-like, carbonate apatite. Although other technologies are being explored to recycle phosphorus from wastewater streams, this is the first indication that it may be possible to precipitate a carbonate apatite by mixing two waste streams, municipal waste water and CO2 (g), with cost-effective CaCO3.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".