Removal of phosphate from greenhouse wastewater using hydrated lime
Bibliographic record
Abstract
Phosphate (P) contamination in nutrient-laden wastewater is currently a major topic of discussion in the North American greenhouse industry. Precipitation of P as calcium phosphate minerals using hydrated lime could provide a simple, inexpensive method for retrieval. A combination of batch experiments and chemical equilibrium modelling was used to confirm the viability of this P removal method and determine lime addition rates and pH requirements for greenhouse wastewater of varying nutrient compositions. Lime: P ratio (molar ratio of CaMg(OH)₄: PO₄‒P) provided a consistent parameter for estimating lime addition requirements regardless of initial P concentration, with a ratio of 1.5 providing around 99% removal of dissolved P. Optimal P removal occurred when lime addition increased the pH from 8.6 to 9.0, suggesting that pH monitoring during the P removal process could provide a simple method for ensuring consistent adherence to P removal standards. A Visual MINTEQ model, validated using experimental data, provided a means of predicting lime addition and pH requirements as influenced by changes in other parameters of the lime-wastewater system (e.g. calcium concentration, temperature, and initial wastewater pH). Hydrated lime addition did not contribute to the removal of macronutrient elements such as nitrate and ammonium, but did decrease the concentration of some micronutrients. This study provides basic guidance for greenhouse operators to use hydrated lime for phosphate removal from greenhouse wastewater.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".