A Micrometeorological Technique to Monitor Total Hydrocarbon Emissions from Landfarms to the Atmosphere
Bibliographic record
Abstract
Landfarming is used to treat petroleum hydrocarbon-contaminated soils and a variety of waste streams from industrial operations. Wastes are applied to a soil surface and indigenous soil microorganisms utilize the hydrocarbons in the applied waste as a carbon source for metabolism, thereby biodegrading the applied material. Concerns have been expressed that abiotic losses, such as volatilization, play a significant role in hydrocarbon reduction within the soil. To assist in better defining atmospheric releases of total hydrocarbons from landfarms treating petroleum hydrocarbons, a flux gradient micrometeorological approach was developed and integrated with a custom-built total hydrocarbon detector, and a novel air sampling system and averaging algorithm. The micrometeorological technique offers unobtrusive spatially averaged real-time continuous measurements, thereby providing a time history of emissions. This provides opportunities to investigate mechanisms controlling emissions and to evaluate landfarm management strategies. The versatility of the technique is illustrated through measurements performed at a remote landfarm used to treat diesel fuel-contaminated soil in northern Ontario and during routine operations at two active refinery landfarms in southwestern Ontario.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".