As release under the microbial sulfate reduction during redox oscillations in the upper Mekong delta aquifers, Vietnam: A mechanistic study
Bibliographic record
Abstract
The impact of seasonal fluctuations linked to monsoon and irrigation generates redox oscillations in the subsurface, influencing the release of arsenic (As) in aquifers. Here, the biogeochemical control on As mobility was investigated in batch experiments using redox cycling bioreactors and As- and SO42−-amended sediment. Redox potential (Eh) oscillations between anoxic (−300–0 mV) and oxic condition (0–500 mV) were implemented by automatically modulating an admixture of N2/CO2 or compressed air. A carbon source (cellobiose, a monomer of cellulose) was added at the beginning of each reducing cycle to stimulate the metabolism of the native microbial community. Results show that successive redox cycles can decrease arsenic mobility by up to 92% during reducing conditions. Anoxic conditions drive mainly the conversion of soluble As(V) to As(III) in contrast to oxic conditions. Phylogenetic analyses of 16S rRNA amplified from the sediments revealed the presence of sulfate and iron – reducing bacteria, confirming that sulfate and iron reduction are key factors for As immobilization from the aqueous phase. As and S K-edge X-ray absorption spectroscopy suggested the association of Fe-(oxyhydr)oxides and the importance of pyrite (FeS2(s)), rather than poorly ordered mackinawite (FeS(s)), for As sequestration under oxidizing and reducing conditions, respectively. Finally, these findings suggest a role for elemental sulfur in mediating aqueous thioarsenates formation in As-contaminated groundwater of the Mekong delta.
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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) | 0.001 | 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".