Correlation of Phosphorus Adsorption with Chemical Properties of Aluminum-Based Drinking Water Treatment Residuals Collected from Various Parts of the United States
Bibliographic record
Abstract
Over the past several decades, the value of drinking water treatment residuals (WTRs), a byproduct of the coagulation process during water purification, has been recognized in various environmental applications, including sustainable remediation of phosphorus (P)-enriched soils. Aluminum-based WTRs (Al-WTRs) are suitable adsorbent materials for P, which can be obtained and processed inexpensively. However, given their heterogeneous nature, it is essential to identify an easily analyzable chemical property that can predict the capability of Al-WTRs to bind P before soil amendment. To address this issue, thirteen Al-WTRs were collected from various geographical locations around the United States. The non-hazardous nature of the Al-WTRs was ascertained first. Then, their P adsorption capacities were determined, and the chemical properties likely to influence their adsorption capacities were examined. Statistical models were built to identify a single property to best predict the P adsorption capacity of the Al-WTRs. Results show that all investigated Al-WTRs are safe for environmental applications, and oxalate-extractable aluminum is a significant indicator of the P adsorption capacity of Al-WTRs (p-value = 0.0002, R2 = 0.7). This study is the first to report a simple chemical test that can be easily applied to predict the efficacy of Al-WTRs in binding P before their broadscale land application.
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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 | 0.000 | 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 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".