Arctic Regional Methane Fluxes by Ecotope As Derived

Atmos. Chem. Phys., 17, 8619–8633, 2017 https://doi.org/10.5194/acp-17-8619-2017 © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License. Arctic regional methane fluxes by ecotope as derived using eddy covariance from a low-flying aircraft David S. Sayres1, Ronald Dobosy2,3, Claire Healy4, Edward Dumas2,3, John Kochendorfer2, Jason Munster1, Jordan Wilkerson5, Bruce Baker2, and James G. Anderson1,4,5 1Paulson School of Engineering and Applied Sciences, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA 2Atmospheric Turbulence and Diffusion Division, NOAA/ARL, Oak Ridge, TN 37830, USA 3Oak Ridge Associated Universities (ORAU), Oak Ridge, TN 37830, USA 4Department of Earth and Planetary Sciences, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA 5Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA Correspondence to: David Sayres ([email protected]) Received: 27 September 2016 – Discussion started: 30 September 2016 Revised: 19 May 2017 – Accepted: 7 June 2017 – Published: 14 July 2017 Abstract. The Arctic terrestrial and sub-sea permafrost re- measurements of surface flux can play an important role in gion contains approximately 30 % of the global carbon stock, bridging the gap between ground-based measurements and and therefore understanding Arctic methane emissions and regional measurements from remote sensing instruments and how they might change with a changing climate is important models. for quantifying the global methane budget and understanding its growth in the atmosphere. Here we present measurements from a new in situ flux observation system designed for use on a small, low-flying aircraft that was deployed over 1 Introduction the North Slope of Alaska during August 2013. The system combines a small methane instrument based on integrated Methane is the third most important greenhouse gas after cavity output spectroscopy (ICOS) with an air turbulence water vapor and carbon dioxide, and its concentration in probe to calculate methane fluxes based on eddy covariance. the atmosphere has increased from a pre-industrial value of We group surface fluxes by land class using a map based 0.7 parts per million by volume (ppmv) to its current value of on LandSat Thematic Mapper (TM) data with 30 m reso- approximately 1.85 ppmv. Methane sources are varied, with lution. We find that wet sedge areas dominate the methane major contributors being anthropogenic (including fossil and fluxes with a mean flux of 2.1 µgm−2 s−1 during the first agricultural) as well as natural. Often multiple sources occur part of August. Methane emissions from the Sagavanirktok in the same vicinity, for example emissions from gas wells River have the second highest at almost 1 µgm−2 s−1. Dur- collocated with agricultural fields or with pasture for grazing ing the second half of August, after soil temperatures had livestock. cooled by 7 ◦C, methane emissions fell to between 0 and In the past few years there have been increased efforts 0.5 µgm−2 s−1 for all areas measured. We compare the air- to understand how methane emissions, as well as carbon craft measurements with an eddy covariance flux tower lo- dioxide, might change from the Arctic region in response to cated in a wet sedge area and show that the two measure- warmer temperatures (Yvon-Durocher et al., 2014; Sturte- ments agree quantitatively when the footprints of both over- vant et al., 2012; Sturtevant and Oechel, 2013; Walter et al., lap. However, fluxes from sedge vary at times by a factor of 2007b, and references therein). For example, temperatures in ◦ 2 or more even within a few kilometers of the tower demon- the Alaskan North Slope have increased 0.6 C per decade for strating the importance of making regional measurements to the last 30 years. Likewise, in that same time period the mini- map out methane emissions spatial heterogeneity. Aircraft mum extent of Arctic sea ice at the end of the summer has de- creased from 8 to 5 million km2. Until this past century late- Published by Copernicus Publications on behalf of the European Geosciences Union. 8620 D. S. Sayres et al.: Arctic methane fluxes from a low-flying aircraft summer sea ice extent was 10 million ± 1 million km2 over gap. Flux measurements from low-flying aircraft coordinated the past 1500 years (Kinnard et al., 2011). Global methane with surface measurements promote extension of the detailed concentrations have also varied during this time period, with surface-flux measurements to the larger regional scale by atmospheric increases slowing down in the 1990s, leveling mapping the heterogeneity in the fluxes over these larger ar- off in the early part of the 21st century and have been increas- eas. ing again since 2007 with concentrations reaching 1.8 ppmv Eddy covariance is a direct way to determine in situ the ex- in 2010 based on several surface-based observation networks change (flux) of mass, momentum, and energy between the (Kirschke et al., 2013). It has been postulated that the in- atmosphere and the surface. Turbulent winds and concentra- crease could be from Arctic wetlands (Koven et al., 2011; tions are measured at a high sample rate, and their covari- Walter et al., 2007b). ance yields the flux. With stationary instruments the wind A brief look at the carbon stock in the Arctic reveals why and concentration measurements can be routinely obtained, it has garnered so much attention. The Arctic permafrost re- and eddy covariance from fixed sites is widely represented gion contains between 1330 and 1580 Pg of carbon in the in the literature as a way of obtaining the flux of a quan- tundra surface layer (0–3 m depth), yedoma deposits, and tity between the surface and atmosphere. Obtaining eddy co- rivers. An additional quantity is contained in deeper deposits variance measurements from a moving aircraft presents some and sub-sea permafrost (Tarnocai et al., 2009). Arctic car- unique challenges including accurately measuring turbulent bon stock represents about a third of the total global surface wind velocity relative to the ground and measuring concen- carbon pool and increases to 50 % when accounting for the trations at a sufficiently high data rate. Furthermore, if the deeper soils (Schuur et al., 2015). As the climate continues flux from the aircraft is to be a good proxy for a measure- to warm, this carbon is vulnerable to thaw and decomposi- ment taken at the surface, it needs to be sampled close to the tion by microbes, potentially leading to large increases in ground. The appropriate distance varies depending on bound- methane and carbon dioxide emissions. Methane from anaer- ary layer height, turbulence, and the footprint size of interest. obic reduction of organic carbon stocks in permafrost is par- Several groups have successfully measured carbon dioxide ticularly important, having a warming potential more than and heat flux from low-flying aircraft in the Arctic (Zulueta twenty times that of carbon dioxide on a 100-year timescale et al., 2011; Oechel et al., 2000, 1998; Gioli et al., 2004), Eu- and greater yet over shorter time periods (Boucher et al., rope (Bange et al., 2007; Vellinga et al., 2010; Hutjes et al., 2009). The correlation between a warming Arctic and the re- 2010; Gioli et al., 2006), Asia (Metzger et al., 2013), and lease of methane and carbon dioxide from northern wetlands continental USA (Kirby et al., 2008; LeMone et al., 2003; and ocean clathrates is strongly evident in the paleoclimate Avissar et al., 2009). record (Zachos et al., 2008; Whiticar and Schaefer, 2007). Here we present methane fluxes taken during the summer This relationship is also seen (1) in current observations of of 2013 in the North Slope of Alaska and use the data to ex- methane release from thermokarst lakes formed from melt- plore several questions. For example, how representative are ing Arctic permafrost each spring and summer (Sepulveda- towers’ footprints of other instances of the remotely deter- Jauregui et al., 2015; Walter et al., 2007b; Bastviken et al., mined land-cover class in which they were placed? In princi- 2004; Casper et al., 2000), (2) in ebullition from deep sea ple a stationary site can measure all manner of properties and sediments (Shakhova et al., 2014; Reagan et al., 2011; Damm state variables in the soil, the vegetation, and the air, within et al., 2010), and (3) from airborne campaigns (Wofsy, 2011; and above the canopy. Much can be learned about the bacte- Chang et al., 2014). ria, soil chemistry, canopy storage, and other quantities rel- The North Slope of Alaska is covered by several differ- evant to the exchange of mass, momentum, and energy with ent land classes though dominated by permafrost. Access the surface. But all of this is known only at a particular site. to the interior normally requires aircraft, except along the How representative is that site of other locations that to re- Dalton Highway (Rt. 11) from Fairbanks to Prudhoe Bay. mote sensors appear similar? Are there land-cover classes The lack of infrastructure, especially roads, makes continu- that are particularly indicative of emissions of a given trace ous ground-based measurements difficult except near major gas? Can the land class so identified be used as a quantita- settlements. This sparsity of data increases the uncertainty tive predictor of a particular type of soil chemistry? This is in regional bottom-up estimates of carbon flux. At the same relevant in assessing the regional methane emissions from time top-down estimates based on inversion modeling from remote sensing. Methane in particular has a fairly complex measured concentration profiles rely on knowledge of flux chemistry in the soil involving state quantities such as the sources on the ground to determine which sources are dom- (sub-canopy) soil temperature and the height of the water inating the emissions in areas like the North Slope, with its table.

Load more