Nonlinear Redox Transformations of Chromium in Soil during Wildfire Heating: The Critical Role of Iron Mineralogy
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Fire activity, including wildfires and urban fires, is increasing in frequency and severity, significantly impacting soil-borne metals such as chromium (Cr), which can be transformed from benign Cr(III) to toxic Cr(VI) during heating. However, the reaction pathway of Cr(VI) formation during wildfires remains unclear. We investigated the impacts of Fe-bearing minerals on the fire-induced formation of Cr(VI). Magnetite (Fe 3 O 4 ) synthesized and doped with Cr(III), and Fe and Cr rich soils were heated up to 800 °C to investigate temperature-dependent transformations. For the synthetic system, Cr(III) oxyhydroxide (CrOOH) was oxidized to metastable Cr(VI) trioxide (CrO 3 ) up to 600 °C, which spontaneously converted to Cr(III) oxide (Cr 2 O 3 ) with increasing temperature to 800 °C. In the soil samples, Fe-bearing minerals reacted with Cr(III) hydroxide [Cr(OH) 3 ] and chromite [FeCr 2 O 4; Cr(III)] to form Cr(VI) and magnetite up to 600 °C, which react with each other with increasing temperature and reduce Cr(VI) to form chromite and hematite (α-Fe 2 O 3 ). These findings highlight the role of Fe-bearing minerals in controlling the Cr(VI) formation and reduction pathway during fires. Our results have implications for understanding how wildfires contribute to the formation of toxic metals in soils, providing valuable insights for predicting the risks posed by wildfires.
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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 | 0.004 |
| 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".