Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN
Bibliographic record
Abstract
Abstract Anaerobic biodegradation of organic amendments and contaminants in aquifers can trigger secondary water quality impacts that impair groundwater resources. Reactive transport models help elucidate how diverse geochemical reactions control the spatiotemporal evolution of these impacts. Using extensive monitoring data from a crude oil spill site near Bemidji, Minnesota (USA), we implemented a comprehensive model that simulates secondary plumes of depleted dissolved O 2 and elevated concentrations of Mn 2+ , Fe 2+ , CH 4 , and Ca 2+ over a two‐dimensional cross section for 30 years following the spill. The model produces observed changes by representing multiple oil constituents and coupled carbonate and hydroxide chemistry. The model includes reactions with carbonates and Fe and Mn mineral phases, outgassing of CH 4 and CO 2 gas phases, and sorption of Fe, Mn, and H + . Model results demonstrate that most of the carbon loss from the oil (70%) occurs through direct outgassing from the oil source zone, greatly limiting the amount of CH 4 cycled down‐gradient. The vast majority of reduced Fe is strongly attenuated on sediments, with most (91%) in the sorbed form in the model. Ferrous carbonates constitute a small fraction of the reduced Fe in simulations, but may be important for furthering the reduction of ferric oxides. The combined effect of concomitant redox reactions, sorption, and dissolved CO 2 inputs from source‐zone degradation successfully reproduced observed pH. The model demonstrates that secondary water quality impacts may depend strongly on organic carbon properties, and impacts may decrease due to sorption and direct outgassing from the source zone.
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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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".