Use of dissolved and vapor‐phase gases to investigate methanogenic degradation of petroleum hydrocarbon contamination in the subsurface
Bibliographic record
Abstract
At many sites contaminated with petroleum hydrocarbons, methanogenesis is a significant degradation pathway. Techniques to estimate CH4 production, consumption, and transport processes are needed to understand the geochemical system, provide a complete carbon mass balance, and quantify the hydrocarbon degradation rate. Dissolved and vapor‐phase gas data collected at a petroleum hydrocarbon contaminated site near Bemidji, Minnesota, demonstrate that naturally occurring nonreactive or relatively inert gases such as Ar and N2 can be effectively used to better understand and quantify physical and chemical processes related to methanogenic activity in the subsurface. In the vadose zone, regions of Ar and N2 depletion and enrichment are indicative of methanogenic and methanotrophic zones, and concentration gradients between the regions suggest that reaction‐induced advection can be an important gas transport process. In the saturated zone, dissolved Ar and N2 concentrations are used to quantify degassing driven by methanogenesis and also suggest that attenuation of methane along the flow path, into the downgradient aquifer, is largely controlled by physical processes. Slight but discernable preferential depletion of N2 over Ar, in both the saturated and unsaturated zones near the free‐phase oil, suggests reactivity of N2 and is consistent with other evidence indicating that nitrogen fixation by microbial activity is taking place at this site.
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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".