Rates of As and Trace-Element Mobilization Caused by Fe Reduction in Mixed BTEX–Ethanol Experimental Plumes
Bibliographic record
Abstract
Biodegradation of organic matter, including petroleum-based fuels and biofuels, can create undesired secondary water-quality effects. Trace elements, especially arsenic (As), have strong adsorption affinities for Fe(III) (oxyhydr)-oxides and can be released to groundwater during Fe-reducing biodegradation. We investigated the mobilization of naturally occurring As, cobalt (Co), chromium (Cr), and nickel (Ni) from wetland sediments caused by the introduction of benzene, toluene, ethylbenzene, and xylenes (BTEX) and ethanol mixtures under iron- and nitrate-reducing conditions, using in situ push-pull tests. When BTEX alone was added, results showed simultaneous onset and similar rates of Fe reduction and As mobilization. In the presence of ethanol, the maximum rates of As release and Fe reduction were higher, the time to onset of reaction was decreased, and the rates occurred in multiple stages that reflected additional processes. The concentration of As increased from <1 μg/L to a maximum of 99 μg/L, exceeding the 10 μg/L limit for drinking water. Mobilization of Co, Cr, and Ni was observed in association with ethanol biodegradation but not with BTEX. These results demonstrate the potential for trace-element contamination of drinking water during biodegradation and highlight the importance of monitoring trace elements at natural and enhanced attenuation sites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 teacher head, 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".