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Record W4322209267 · doi:10.5194/egusphere-egu23-14191

Development and First Deployment of an Innovative Airborne δ13C(CH4) In Situ Measurement Setup

2023· preprint· en· W4322209267 on OpenAlexaboutno aff
Paul Waldmann, Michael Lichtenstern, Friedemann Reum, Helmut Ziereis, Alina Fiehn, Michał Gałkowski, Christoph Gerbig, Andreas Fix, Anke Roiger

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMethaneEnvironmental scienceδ13CGreenhouse gasSampling (signal processing)Atmospheric methaneIsotopes of carbonCarbon cycleNatural gasStable isotope ratioRemote sensingChemistryEnvironmental chemistryGeologyTotal organic carbonPhysicsOptics

Abstract

fetched live from OpenAlex

Recent atmospheric methane concentrations show an accelerated increase, but the contributions of the underlying emitters are poorly understood. Recording the stable carbon isotope ratio of methane (δ13C(CH4)) is a powerful tool for CH4 source attribution and the understanding of the global methane budget. The airborne measurement of δ13C(CH4) provides the advantages of reaching remote areas and covering large-scale regions, but is challenging regarding sufficient precision while maintaining high spatial measurement density. The state of the art technique is to collect airborne gas samples for subsequent laboratory analysis by isotope ratio mass spectrometry, with high δ13C(CH4) precision of 0.05 ‰. Here we present an innovative in situ airborne system for the measurement of δ13C(CH4), called MIRACLE. MIRACLE consists of a conventional Picarro cavity ring down greenhouse gas analyzer (G2210-i) for the measurement of CH4 and δ13C(CH4), and a sampler unit. The sampler enables the collection of six gas samples in 2 l stainless steel tanks, in a short time (20 s each) via a metal bellows pump, which allows for the specific sampling of small-scale features, such as point source emissions. The sampling is followed by an extended period of subsequent analysis (up to 10 min). Using this setup, we achieve sufficient δ13C(CH4) precision (1σ uncertainty of 0.34 ‰) and an average of five samples per flight hour, allowing for a large number of samples for long flights. Due to the resulting dense coverage with sufficient precision, this novel approach allows for airborne δ13C(CH4) characterization of small-scale methane emitters and large-scale gradients. We employed MIRACLE aboard the research aircraft HALO during the CoMet 2.0 Arctic campaign in summer 2022, which focused on characterizing natural and anthropogenic methane sources in Canada. In this presentation, a proof of concept for the instrument is elaborated, including the investigation of sample purity and measurement comparisons with other instruments. Additionally, we show δ13C(CH4) signatures revealed by the method of Keeling analysis of measurements obtained during CoMet 2.0 and compare them to previous studies. The airborne operation of the MIRACLE instrument combines the advantages of increased precision δ13C(CH4) measurements, typically only possible under stable laboratory conditions, with the in situ, near real time data analysis and the large-scale sampling of secluded areas. MIRACLE will be deployed during the DLR GHGMon campaign (June 2023) to investigate the δ13C(CH4) ratio of agricultural sources of methane in the Netherlands.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.033
GPT teacher head0.228
Teacher spread0.195 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2023
Admission routes1
Has abstractyes

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