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Record W2551250436

EFFECTS OF BUBBLE-FACILITATED VOC TRANSPORT FROM LNAPL SMEAR ZONES ON VAPOR INTRUSION

2016· dissertation· en· W2551250436 on OpenAlexfundno aff
N. C. Soucy

Bibliographic record

VenueQSpace (Queen's University Library) · 2016
Typedissertation
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaQueen's University
KeywordsIntrusionEnvironmental sciencePetroleum engineeringBubbleEnvironmental chemistryAtmospheric sciencesChemistryGeologyMechanicsGeochemistryPhysics
DOInot available

Abstract

fetched live from OpenAlex

Light non-aqueous phase liquid (LNAPL) sources can pose a significant threat to indoor air through vapour intrusion (VI). Most conceptual and numerical models of VI assume that the transport of volatile organic compounds (VOCs) is a diffusion-limited process. Recently, alternate conditions have been identified that could lead to faster transport, including the presence of preferential pathways and methanogenic gas production. In this study, an additional mechanism that could lead to faster transport was investigated: bubble-facilitated VOC transport from LNAPL smear zones. A laboratory investigation was preformed using pentane in one-dimensional laboratory columns and two-dimensional visualization experiments. 
\nResults of the column experiments showed that average VOC mass fluxes in the bubble-facilitated columns were over two orders of magnitude greater than in the diffusion-limited columns. In addition, the flux signal was intermittent, consistent with expectations of bubble-facilitated transport as bubbles expand, mobilize and are released to the vadose zone at various times during the test. The results from the visualization experiments showed gas fingers growing and mobilizing over time, which supports the findings of the column experiments. In conclusion, these results demonstrate the potential for bubble-facilitated VOC transport to affect mass transfer in LNAPL smear zones, and lead to increased indoor air concentrations by VI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.165
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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