Vapor Migration Assessment for Chlorinated Sites via Induced Flux Measurement
Bibliographic record
Abstract
In recent years, the topic of human respiratory exposures from gases and vapors coming from contaminated sites has gained interest. The atmosphere in the unsaturated zone gets contaminated by volatile organic compounds when petroleum or chlorinated liquids are released into the soil. As the liquid is introduced, most of compounds enter into different phases and establish a chemical equilibrium. This equilibrium is affected by varying factors, such as moisture content, barometric pressure, temperature and microbial activity. For this reason, gas and vapor concentrations in the vadose zone vary constantly. To achieve accurate soil atmosphere sampling, many basic concepts must be considered. Among these, the collection of soil atmosphere samples at the lowest flowrate possible and the analysis of gases and vapors at each sampling location are of primary importance. Nevertheless even if active sampling is performed in the best conditions, the dynamic nature of the soil atmosphere will always remain a challenge for the assessment of long term conditions. This paper describes the induced flux method, an innovative sampling technique which uses clean nitrogen to flush the subsurface during a short period of time. This flush alters the “soil-liquid-gas” system equilibrium and causes free liquid, sorbed and dissolved compounds of concern to transfer to the gas phase. When the equilibrium is clearly unbalanced, the rate at which the gas or vapor are transferred to the soil atmosphere is evaluated and induced flux data are calculated. This data may be collected on site with direct reading instruments within 20 minutes per sampling location. Concentrations coupled with induced flux data provide details on potential atmospheric intrusion and on migration of soil gas and vapor around the sampling location. The author suggests different approaches to assess long term conditions of the soil atmosphere when both types of data are available at a 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".