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Record W4322002725 · doi:10.5194/egusphere-egu23-12327

First measurement of methane emissions from Canadian glaciers in the Yukon

2023· article· en· W4322002725 on OpenAlexaboutno aff
Sarah Elise Sapper, Christian Juncher Jørgensen, Moritz Schroll, Frank Keppler, Jesper Riis Christiansen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsGlacierMethaneMethane emissionsEnvironmental sciencePhysical geographyEarth scienceGeologyGeographyChemistry

Abstract

fetched live from OpenAlex

Land-terminating glaciers in Greenland and Iceland are sources of methane (CH4) to the atmosphere1,2,3. CH4 is produced through microbial methanogenesis underneath the ice, transported dissolved in subglacial meltwater to the margin where the gas is emitted to the atmosphere via degassing4. However, sparse empirical data exist about the spatial distribution of subglacial CH4 production and emission in other glaciated regions of the world, limiting our understanding of its regional and global importance in atmospheric carbon budgets and its possible role in the climate system.In August 2022, we conducted fieldwork at three outlet glaciers - Dusty, Kluane and Donjek glaciers - of the St. Elias Icefields in Yukon, Canada, to investigate if these alpine glaciers are also sources of CH4 emissions to the atmosphere. The glaciers were chosen due to the absence of proglacial lakes and the presence of meltwater upwellings at the glacier termini, which were accessed via helicopter.In-situ extracted dissolved CH4 and CO2 concentrations were measured in the field with a portable greenhouse gas analyzer. Additionally, extracted gas was collected in exetainers for concentration measurements via gas chromatography and in Tedlar gas bags for stable carbon and hydrogen isotope analyses of CH4 to decipher its origin. Further, water samples were collected for geochemical analyses. At Dusty glacier, we performed a high-intensity sampling campaign over 10 hours and continuous measurements of dissolved CH4 concentrations with a custom-made low-cost and low-power dissolved CH4 sensor5 to study changes in dissolved gas concentrations, stable isotopic signatures and water chemistry during the rising limb of the diurnal discharge curve.In-situ measured CH4 and CO2 concentrations yielded significantly elevated CH4 and depleted CO2 levels in the meltwater of all three glaciers. Discrete gas samples confirmed dissolved CH4 concentrations 45x, 135x and 250x above the atmospheric equilibrium concentration (3.6 nmol L-1) in the meltwater of Dusty, Kluane and Donjek glaciers, respectively. First measurements of stable carbon and hydrogen isotope values of CH4 showed enrichment in 13C, while 2H was depleted compared to atmospheric CH4, at all sites, likely originating from a thermogenic source or caused by bacterial CH4 oxidation. Water analyses showed an alkaline environment enriched in carbonates and DOC, in contrast to more acidic waters from glaciers in Greenland and Iceland.These first measurements demonstrate that the subglacial meltwaters from glaciers in the St. Elias Icefields are net sources of CH4 and net sinks of CO2 to the atmosphere. Our findings indicate that CH4 emissions from subglacial environments under alpine glaciers may be a more common phenomenon than previously thought, and a potential cause for remotely sensed CH4 concentrations anomalies over glaciated regions. However, more alpine glaciers and outlets from the Greenland Ice Sheet need to be studied to evaluate this link and provide the needed ground truthing for satellite sensors in high latitudes. 1. Christiansen & Jørgensen (2018) DOI 10.1038/s41598-018-35054-72. Lamarche-Gagnon et al. (2019) DOI 10.1038/s41586-018-0800-03. Burns et al. (2018) DOI 10.1038/s41598-018-35253-24. Christiansen et al. (2021) DOI 10.1029/2021JG0063085. Sapper et al. (2022) DOI:10.5194/egusphere-egu22-9972

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)0.000
metaresearch head score (Gemma)0.000
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 score0.032
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.225
Teacher spread0.168 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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