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Record W2952532607 · doi:10.1155/2019/6487162

Towards a Better Knowledge of Natural Methane Releases in the French Alps: A Field Approach

2019· article· en· W2952532607 on OpenAlexfundno aff
Frédérick Gal, E. Proust, Wolfram Kloppmann

Bibliographic record

VenueGeofluids · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsMethaneFlux (metallurgy)HydrocarbonOutcropDilutionGeologyMineralogyEnvironmental chemistryChemistryGeomorphologyPhysics

Abstract

fetched live from OpenAlex

We report investigations performed at some hydrocarbon gas seeps located in the French Subalpine Chains in zones of outcropping Jurassic black shales, increasing the reported number of such occurrences in this part of the Alps. We present the characteristics of each of the seeps, based on soil flux measurements and soil gas measurements. Gases emitted are CH4-rich (87–94%) with the exception of one site (78.5% CH4 + 8.2% CO2) where an active landslide may induce dilution by atmospheric air. CO2 is generally measured at low levels (<1.6%). Concentrations in C2H6 are more variable, from less than 1% to more than 2.3%. Gas is emitted over areas of various sizes. The smallest gas emission area measures only 60×20 cm , characterized by a strong hydrocarbon flux (release of about 100 kg of CH4 per year). At a second site, hydrocarbon emissions are measured over a surface of 12 m2. For this site, methane emission is evaluated at 235 kg per year and CO2 emission is 600 kg per year, 210 kg being related to gas seepage. At the third site, hydrocarbons are released over a 60 m2 area but strong gas venting is restricted to localized seeps. Methane emission is evaluated at 5.1 tons per year and CO2 emission at 1.58 tons per year, out of which 0.53 tons are attributed to gas seepage. Several historical locations remain uninvestigated at present, and numerous others may still be unknown. We outline strategies to search for such unrecorded sites. Considering the topography of the potential alpine and perialpine emission areas, the possibilities to detect gas emissions appear of the size recorded so far seem to be restricted to ground-based methods or to methods offering the possibility to point orthogonally to the soil towards the seep maximum. If such sites are to be investigated in the future in the frame of Environmental Baseline Assessment (EBA), even establishing appropriate monitoring protocols will be challenging.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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