Chlorine vs. Sodium Chloride Regeneration of Zeolite Column for Ammonium Removal from an Explosives Impacted Mining Wastewater
Bibliographic record
Abstract
There has only been limited research on ammonium removal by zeolites followed by chlorine regeneration; these studies used batch tests and, in many cases, only dealt with single solute solutions as opposed to multi-component ones. To better simulate full-scale applications, this study used a continuous-flow ion exchange (IE) column system to assess the feasibility of chlorine regeneration of a zeolite IE column used for the removal of ammonium from synthetic explosives impacted mining wastewater (EIMWW). Multi-cycle column loading-regeneration tests were used to evaluate and compare the performance of a NaOCl (1000 ppm as free Cl2) solution with that of a standard salt regeneration solution (5% NaCl). In addition, the impact of two loading cycle durations was evaluated. After three operational cycles with 6 h loading phases, the TAN (total ammonia nitrogen) uptake after NaOCl regeneration was almost the same as that obtained with salt regeneration (0.21 meq/g vs. 0.21 meq/g). The zeolite with NaOCl regeneration showed a higher preference for TAN than with NaCl regeneration (Ca:TAN:K = 2.8:2.3:1 vs. 2.5:1.9:1 for the 6 h loading phase); however, the NaOCl regeneration took longer to complete. It was also found that effluent pH, total chlorine level, and free chlorine level during the chlorine regeneration were positively related, seemingly confirming that the ammonium is oxidized to nitrogen gas and producing hydrogen ions. Regardless of the regeneration solution, if one uses a two-column system, with one column online and the other offline, the shorter loading cycles (6 h) yield a substantially higher daily TAN removal rate.
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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 | 0.001 |
| 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".