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Record W7027978757

Disproportional contribution of geological sources to Mackenzie Delta methane emissions revealed from airborne eddy-covariance measurements

2016· article· en· W7027978757 on OpenAlexaboutno aff

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostDeltaArcticRiver deltaMethaneWetlandActive layerThermokarst
DOInot available

Abstract

fetched live from OpenAlex

Arctic wetlands associated with permafrost as well as thawing permafrost emit the greenhouse gas methane (CH4). Two important contributors are recent microbial activity in the active layer or taliks (biogenic CH4), and deeper fossil sources where pathways through the permafrost exist (geologic CH4). Current emission estimates vary strongly between different models. Moreover, there is still disagreement between bottom-up estimates from local field studies, and topdown estimates from atmospheric measurements. Here, we quantify permafrost CH4 emissions directly on the regional scale, based on the Airborne Measurements of Methane Fluxes Campaigns (AIRMETH) in the Mackenzie River Delta region, Canada, in July 2012 and 2013 [Kohnert et al., 2014]. The Mackenzie Delta is the second largest Arctic delta (13,000 km2). Our measurements covered an area extending 320 km from west to east (140°58’W to 133°22’W) and of 240 km from north to south (69°33’N to 67°26’N). The study area comprises the delta itself, the adjacent Yukon coastal plain, and Richards Island north east of the delta. The area surrounding the delta is described as continuous permafrost zone where the permafrost reaches a thickness of 300 m along the coastal plain and 500 m on Richards Island. In the delta itself the discontinuous permafrost reaches a maximum thickness of 100 m. The northern part of the study area is crossed by geological faults and underlain by oil and natural gas deposits. We analyse the regional pattern of CH4 fluxes and estimate the contribution of geologic emissions to the total CH4 budget of the delta. CH4 fluxes were calculated with a time-frequency resolved version of the eddy-covariance technique [Metzger et al., 2013], followed by the calculation of flux topographies [Mauder et al., 2008]. The result is a 100 m resolved gridded flux map within the footprints of the flight tracks. The results provide the first regional estimate of CH4 release from the Mackenzie Delta and the adjacent coastal plain. We distinguish geological gas seeps from biogenic sources by their strength, and show that geologic sources contribute strongly to the annual CH4 budget of the study area: One percent of the covered area contains the strongest geological seeps which contribute disproportionately to an annual emission estimate. The contribution of geological sources to CH4 emission warrants further attention, in particular in areas where permafrost is vulnerable to increased geologic gas migration due to thawing and opening of new pathways. The presented map can be used as a baseline for future CH4 flux studies in the Mackenzie Delta. References Kohnert, K.; Serafimovich, A.; Hartmann, J. and Sachs, T. [2014]: Airborne measurements of methane fluxes in alaskan and canadian tundra with the research aircraft “polar 5”. In Reports on Polar and Marine Research, volume 673. Alfred Wegener Institue Bremerhaven, pp. 81. Mauder, M.; Desjardins, R.L. and MacPherson, I. [2008]: Creating surface flux maps from airborne measurements: Application to the Mackenzie area GEWEX study MAGS 1999. Boundary-Layer Meteorology, 129:431–450, 2008. Metzger, S.; Junkermann, W.; Mauder, M.; Butterbach-Bahl, K.; Trancón y Widemann, B.; Neidl, F.; Schäfer, K.; Wieneke, S.; Zheng, X. H.; Schmid, H. P. and Foken, T. [2013]: Spatially explicit regionalization of airborne flux measurements using environmental response functions. Biogeosciences, 10(4):2193–2217, 2013. doi:10.5194/bg-10-2193-2013.

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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 score0.785
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.116
GPT teacher head0.357
Teacher spread0.241 · 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
Published2016
Admission routes1
Has abstractyes

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