Disproportional contribution of geological sources to Mackenzie Delta methane emissions revealed from \nairborne eddy-covariance measurements
Bibliographic record
Abstract
Arctic wetlands associated with permafrost as well \nas thawing permafrost emit the greenhouse gas methane \n(CH4). Two important contributors are recent \nmicrobial activity in the active layer or taliks (biogenic \nCH4), and deeper fossil sources where pathways \nthrough the permafrost exist (geologic CH4). Current \nemission estimates vary strongly between different \nmodels. Moreover, there is still disagreement between \nbottom-up estimates from local field studies, and topdown \nestimates from atmospheric measurements. \nHere, we quantify permafrost CH4 emissions directly \non the regional scale, based on the Airborne \nMeasurements of Methane Fluxes Campaigns (AIRMETH) \nin the Mackenzie River Delta region, Canada, \nin July 2012 and 2013 [Kohnert et al., 2014]. The \nMackenzie Delta is the second largest Arctic delta \n(13,000 km2). Our measurements covered an area \nextending 320 km from west to east (140°58’W to \n133°22’W) and of 240 km from north to south (69°33’N \nto 67°26’N). The study area comprises the delta itself, \nthe adjacent Yukon coastal plain, and Richards \nIsland north east of the delta. The area surrounding \nthe delta is described as continuous permafrost zone \nwhere the permafrost reaches a thickness of 300 m \nalong the coastal plain and 500 m on Richards Island. \nIn the delta itself the discontinuous permafrost \nreaches a maximum thickness of 100 m. The northern \npart of the study area is crossed by geological faults \nand underlain by oil and natural gas deposits. \nWe analyse the regional pattern of CH4 fluxes and \nestimate the contribution of geologic emissions to the \ntotal CH4 budget of the delta. CH4 fluxes were calculated \nwith a time-frequency resolved version of the \neddy-covariance technique [Metzger et al., 2013], followed \nby the calculation of flux topographies [Mauder \net al., 2008]. The result is a 100 m resolved gridded \nflux map within the footprints of the flight tracks. \nThe results provide the first regional estimate of CH4 \nrelease from the Mackenzie Delta and the adjacent \ncoastal plain. We distinguish geological gas seeps from \nbiogenic sources by their strength, and show that geologic \nsources contribute strongly to the annual CH4 \nbudget of the study area: One percent of the covered \narea contains the strongest geological seeps which \ncontribute disproportionately to an annual emission \nestimate. The contribution of geological sources to \nCH4 emission warrants further attention, in particular \nin areas where permafrost is vulnerable to increased \ngeologic gas migration due to thawing and opening of \nnew pathways. The presented map can be used as a \nbaseline for future CH4 flux studies in the Mackenzie \nDelta. \nReferences \nKohnert, K.; Serafimovich, A.; Hartmann, J. and \nSachs, T. [2014]: Airborne measurements of methane \nfluxes in alaskan and canadian tundra with the \nresearch aircraft “polar 5”. In Reports on Polar \nand Marine Research, volume 673. Alfred Wegener \nInstitue Bremerhaven, pp. 81. \nMauder, M.; Desjardins, R.L. and MacPherson, I. \n[2008]: Creating surface flux maps from airborne \nmeasurements: Application to the Mackenzie area \nGEWEX study MAGS 1999. Boundary-Layer Meteorology, \n129:431–450, 2008. \nMetzger, S.; Junkermann, W.; Mauder, M.; \nButterbach-Bahl, K.; Trancón y Widemann, B.; \nNeidl, F.; Schäfer, K.; Wieneke, S.; Zheng, \nX. H.; Schmid, H. P. and Foken, T. [2013]: \nSpatially explicit regionalization of airborne flux \nmeasurements using environmental response functions. \nBiogeosciences, 10(4):2193–2217, 2013. \ndoi:10.5194/bg-10-2193-2013.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".