Soil 14CO2 Source Apportionment for Biodegradation in Contaminated Soils in Permafrost Climates: A Novel Technique for Rapid Sample Collection by Barium Carbonate Precipitation
Bibliographic record
Abstract
The rate of biodegradation of hydrocarbon contaminated soils can be studied using the radiocarbon (14C) content of CO2 efflux from the ground surface over an impacted area.14C is used as a tracer to distinguish modern 14C CO2 from natural respiration processes and 14C depleted CO2 derived from petroleum degradation. Studies have shown that this analysis provides reliable, quantifiable data and an effective means of correcting for background CO2 which may present some natural depletion from older subsurface organics. The study area for this project is a remote community in Northern Yukon where organic rich sediments overlying continuous permafrost are contaminated by diesel oil. An objective of this study was to evaluate the use of 14C to quantify background CO2 in permafrost soils with abundant, older labile organics. A second objective was to test a new sampling technique to facilitate sample shipment from remote sites, which traps soil CO2 in small sealed exetainers as a solid barium carbonate. Data obtained from established radiocarbon sampling procedures and this new novel approach were shown to be comparable and reproducible. This technique facilitated both sample collection and shipment as well as analysis by accelerator mass spectrometry (AMS), allowing for rapid, efficient sampling techniques to be deployed in remote areas. Results of this study show the carbonate method to be an economical and effective sampling method, and used at the Old Crow site, demonstrated that under current climate conditions, older organics in the subsurface do not confound the use of 14CO2 for source zone biodegradation assessment at this hydrocarbon impacted permafrost 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 | 0.001 | 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".