Review of kinetics of chemical and photocatalytical oxidation of Arsenic(III) as influenced by pH
Bibliographic record
Abstract
The kinetics and stoichiometry of As(III) oxidation by chemical oxidants is presented. The reactions are first-order with respect to each reactant. The second-order rate constants vary with pH and have a range in magnitude of 10(4)-10(7) M-1 s-1 for free available chlorine (FAC), O3, and FeO4(2-) in a pH range of 6.0-9.0. In this pH range, the reactions of As(III) with chloroamine (NH2Cl) and H2O2 are quite slow with rate constants of 2.9-4.3x10(-1) M-1 s-1 and 2.6x10(-2)-4.5x10(1) M-1 s-1 for chloroamine and H2O2, respectively. The pH dependence of the oxidation reactions can be described using acid-base equilibria of both As(III) species and the oxidant. FAC, O3, and FeO(4)2- oxidize As(III) instantaneously at pH 7.0 with half-lives of milliseconds if 2 mg/L excess dose of oxidant is applied. One major advantage of FeO4(2-) ions over the other oxidants is its ability to remove arsenic in water by two mechanisms; it oxidizes As(III) and also subsequently coagulates As(V) through Fe(III) hydroxide produced from Fe(VI) reduction. Photocatalytic oxidation of As(III) to As(V) follows zero-order kinetics and the oxidation is completed in minutes with no significant pH dependence. The removal of dissolved arsenic to values below the World Health Organization drinking water limit of 10 microg/L can be achieved through photocatalytic oxidation of As(III) to As(V) in acidic solution followed by adsorption of As(V) onto TiO2 surfaces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".