Recent developments in aqueous phase bromate (BrO3–) species treatment using adsorption, reduction, and ion-exchange processes
Bibliographic record
Abstract
ABSTRACT Recently, bromate (BrO 3 – ) presence in the drinking water sources and its health-related concerns (e.g., carcinogenic) has initiated a lot of attention both within the regulatory bodies across the globe (such as WHO, US EPA, EU, etc.) and also within the scholarly community that look for efficient bromate removal techniques to meet the desired bromate water quality standards. Bromate species is typically formed during disinfection–ozonation of bromide containing water. Considering its carcinogenic and mutagenic threat toward human health, several recent research studies have investigated different processes for efficient bromate removal from the aqueous phase under a varying set of conditions and also report the optimum process variables. In this review paper, we have presented and summarized findings from the respective recent work on bromate removal techniques and have also discussed the effect of various process variables on bromate removal efficiency. The adsorption process is noted to be the most common and widely studied technique. Some of the adsorbent materials used included activated carbon, both unmodified and modified. The respective adsorbent samples are noted to have varying specific surface area, pore size, and surface morphology. In most studies, the effect of pH, initial bromate concentration, contact time, temperature, adsorbent dose, mixing speed, and coexisting ions was investigated to get optimum bromate removal. The adsorption equilibria and kinetics were mainly predicted by Langmuir/Freundlich isotherms and pseudo-second-order models, respectively. Also, the Donnan dialysis and electrodialysis ion-exchange processes removed bromate ions to acceptable concentrations. Bromate reduction can also be achieved using advanced reduction processes where ultraviolet light has been used as an activating agent and mainly sulfite as the reducing agent. Furthermore, chemical reduction, electrochemical reduction, and bio-reduction-based bromate removal processes are also discussed. The reduction-based processes indicated the formation of different reduced species including bromine. The ferrous-based reduction processes are noted to be very effective and several variations of ferrous-based technologies including adsorption and reduction processes are presented and discussed. In summary, this review work indicates a very positive development in the respective area of study, that is, bromate removal from the concerned aqueous streams, and hopefully will also serve as a focal point for further scientific innovations and endeavour for a better human health.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".