Stability of As- and Mn-sludge after neutral mine water treatment using Fe(VI) vs electrocoagulation
Bibliographic record
Abstract
The electrocoagulation (ECG) and ferrate (Fe(VI))-based processes are increasingly acknowledged as efficient for the simultaneous removal of As and Mn from synthetic and real mine effluents. Prior to design of full-scale applications, more information on the physicochemical, mineralogical, and environmental characterization of the produced sludge is required. The main objective of this study was to characterize and evaluate the leaching potential of problematic elements in As- and Mn-rich sludge produced during ECG or Fe(VI) treatment of circumneutral surrogate mine water. To do so, PHREEQC modelling was carried out on the effluents, before and after ECG or Fe(VI) treatment, to calculate the saturation index of dissolved As, Fe, and Mn species. A physicochemical and mineralogical characterization of the sludge was also performed using powder X-ray diffraction (PXRD) and a scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS). Then, a non-sequential selective extraction procedure (N-SEP) combined with a USGS field leaching test (FLT) were conducted to evaluate the environmental behaviour of the As- and Mn-rich sludge. Geochemical modelling indicated that the Fe(VI) and ECG processes favor the precipitation of Fe-(oxy)hydroxides (lepidocrocite, schwertmannite, ferrihydrite). Chemical characterization showed that the Fe(VI)-sludge contained higher As and Mn concentrations and lower Fe concentrations than the ECG-sludge (3.8% As, 5.3% Mn, and 34% Fe for the Fe(VI)-sludge vs 1.2% As, 0.77% Mn, and 52% Fe for the ECG-sludge). These findings can be explained by the smaller amount of sludge produced during the Fe(VI) treatment and the higher removal efficiency of this method, especially for Mn. The PXRD patterns suggested the formation of poorly crystalline Fe-(oxy)hydroxides (lepidocrocite or βFeO(OH) in the ECG-sludge vs ferrihydrite in the Fe(VI)-sludge); however, no As- or Mn-bearing minerals were identified. Findings from N-SEP tests showed different speciation of As and Mn in the sludge, with a higher proportion of As bound to poorly crystalline Fe-(oxy)hydroxides in the Fe(VI) sludge than the ECG-sludge (97% and 71%, respectively), and higher proportion of Mn associated with the residuals in the Fe(VI)-sludge than the ECG-sludge (57% and 5.7%, respectively). Finally, FLT results indicated that very low concentrations of As (<0.05 mg/L) and Mn (<0.5 mg/L) were leached from the ECG- and Fe(VI)-sludge, with the Fe(VI) treatment resulting in slightly better As and Mn immobilization in the sludge relative to the ECG process. Nevertheless, both treatment processes were satisfactory in terms of efficient removal of As and Mn and their immobilization in the produced sludge.
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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".