Phosphorus removal from aqueous solutions by sorption on two volcanic soils
Bibliographic record
Abstract
The use of low-cost materials for P removal is of interest for developing cost-effective techniques for preventing P pollution. This paper reports a study on phosphate removal from aqueous solutions by sorption on two volcanic soils. The raw and HCl-treated soils were characterized with respect to oxalate-extractable and dithionite-extractable Al and Fe contents, surface area, and P sorption capacities. The phosphate sorption isotherms, kinetics, pH effects, and desorbability were evaluated in batch tests. The measured isotherm data were well fitted by the Freundlich and Temkin models. Phosphate sorption on these soils was relatively fast and the kinetics could be satisfactorily described by the simple Elovich and power function equations. The two soils had maximum phosphate sorption capacities of approximately 0.85 and 1.35 mg g-1 gram of soil at pH 6.0–6.5. The pH had different effects on phosphate sorption on these soils, likely due to either calcium phosphate precipitation or surface repulsion of the negatively charged phosphate species at a higher pH. Column flow-through tests using both synthetic phosphate solution and liquid swine manure confirmed the phosphate removal ability of the volcanic soils. It was concluded that volcanic soils could be potential low-cost materials for controlling P pollution from agricultural sources. Key words: Phosphate removal, volcanic soil, sorption, isotherm, kinetics, desorption
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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".