Effects of nitrate concentrations on As(III) immobilization via new ferric arsenite hydroxynitrate precipitates
Bibliographic record
Abstract
The Fe(III)-As(III)-anion precipitation as layered double hydroxide-like compounds such as tooeleite and ferric arsenite hydroxychloride (FC) has been found in As(III)-contaminated acidic mine soils. However, the question of whether As(III) is immobilized by Fe(III) in aqueous nitrate media, a common constituent in soils and metallurgical wastewater, remains unclear. Herein, we investigated the effects and mechanism of nitrate on As(III) immobilization via Fe(III)-As(III)-nitrate precipitation. Our results indicated that new ferric arsenite hydroxynitrate (FN) with variable Fe(III)/As(III)/nitrate molar ratios crystallized in an initial nitrate content range of 11,160–74,400 mg·L−1 at pH 2.3. This FN precipitation resulted in 60.3–87.9% of As(III) removal and a fall-rise immobilization trend as a function of the initial nitrate concentration. The optimal initial nitrate concentration for As(III) fixation was 44,640 mg·L−1. Although FN shared similar morphology and crystal structure with tooeleite and FC, the substitution of NO3− for SO42− and Cl− in the FeO6-AsO3 interlayers caused a significant local structural distortion due to different ionic radii. The characteristic infrared and Raman bands of the nitrate group in FN occurred at 1,363 cm−1, 1,384 cm−1 and 152 cm−1, 722 cm−1, 1,055 cm−1, respectively. The FN induced significantly enhanced As(III) immobilization relative to its tooeleite and FC counterparts at equimolar concentrations of NO3−, SO42−, and Cl− as the media.
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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".