Atmospheric Chemistry and Physics (Jan 2018)

Estimating regional-scale methane flux and budgets using CARVE aircraft measurements over Alaska

  • S. Hartery,
  • R. Commane,
  • J. Lindaas,
  • C. Sweeney,
  • C. Sweeney,
  • J. Henderson,
  • M. Mountain,
  • N. Steiner,
  • K. McDonald,
  • S. J. Dinardo,
  • C. E. Miller,
  • S. C. Wofsy,
  • R. Y.-W. Chang,
  • R. Y.-W. Chang

DOI
https://doi.org/10.5194/acp-18-185-2018
Journal volume & issue
Vol. 18
pp. 185 – 202

Abstract

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Methane (CH4) is the second most important greenhouse gas but its emissions from northern regions are still poorly constrained. In this study, we analyze a subset of in situ CH4 aircraft observations made over Alaska during the growing seasons of 2012–2014 as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Net surface CH4 fluxes are estimated using a Lagrangian particle dispersion model which quantitatively links surface emissions from Alaska and the western Yukon with observations of enhanced CH4 in the mixed layer. We estimate that between May and September, net CH4 emissions from the region of interest were 2.2 ± 0.5 Tg, 1.9 ± 0.4 Tg, and 2.3 ± 0.6 Tg of CH4 for 2012, 2013, and 2014, respectively. If emissions are only attributed to two biogenic eco-regions within our domain, then tundra regions were the predominant source, accounting for over half of the overall budget despite only representing 18 % of the total surface area. Boreal regions, which cover a large part of the study region, accounted for the remainder of the emissions. Simple multiple linear regression analysis revealed that, overall, CH4 fluxes were largely driven by soil temperature and elevation. In regions specifically dominated by wetlands, soil temperature and moisture at 10 cm depth were important explanatory variables while in regions that were not wetlands, soil temperature and moisture at 40 cm depth were more important, suggesting deeper methanogenesis in drier soils. Although similar environmental drivers have been found in the past to control CH4 emissions at local scales, this study shows that they can be used to generate a statistical model to estimate the regional-scale net CH4 budget.