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Understanding the sources and sinks of methane (CH4) is critical to both predicting and mitigating future climate change. There are large uncertainties in the global budget of atmospheric CH4, but natural emissions are estimated to be of a similar magnitude to anthropogenic emissions. To understand CH4 flux from biogenic sources in the United States (US) of America, a multi-scale CH4 observation network focused on CH4 flux rates, processes, and scaling methods is required. This can be achieved with a network of ground-based observations that are distributed based on climatic regions and land cover. To determine the gaps in physical infrastructure for developing this network, we need to understand the landscape representativeness of the current infrastructure. We focus here on eddy covariance (EC) flux towers because they are essential for a bottom-up framework that bridges the gap between point-based chamber measurements and airborne or satellite platforms that inform policy decisions and global climate agreements. Using dissimilarity, multidimensional scaling, and cluster analysis, the US was divided into 10 clusters distributed across temperature and precipitation gradients. We evaluated dissimilarity within each cluster for research sites with active CH4 EC towers to identify gaps in existing infrastructure that limit our ability to constrain the contribution of US biogenic CH4 emissions to the global budget. Through our analysis using climate, land cover, and location variables, we identified priority areas for research infrastructure to provide a more complete understanding of the CH4 flux potential of ecosystem types across the US. Clusters corresponding to Alaska and the Rocky Mountains, which are inherently difficult to capture, are the most poorly represented, and all clusters require a greater representation of vegetation types.

Methane (CH4) emissions from the boreal and arctic region are globally significant and highly sensitive to climate change. There is currently a wide range in estimates of high-latitude annual CH4 fluxes, where estimates based on land cover inventories and empirical CH4 flux data or process models (bottom-up approaches) generally are greater than atmospheric inversions (top-down approaches). A limitation of bottom-up approaches has been the lack of harmonization between inventories of site-level CH4 flux data and the land cover classes present in high-latitude spatial datasets. Here we present a comprehensive dataset of small-scale, surface CH4 flux data from 540 terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakes and ponds), compiled from 189 studies. The Boreal–Arctic Wetland and Lake Methane Dataset (BAWLD-CH4) was constructed in parallel with a compatible land cover dataset, sharing the same land cover classes to enable refined bottom-up assessments. BAWLD-CH4 includes information on site-level CH4 fluxes but also on study design (measurement method, timing, and frequency) and site characteristics (vegetation, climate, hydrology, soil, and sediment types, permafrost conditions, lake size and depth, and our determination of land cover class). The different land cover classes had distinct CH4 fluxes, resulting from definitions that were either based on or co-varied with key environmental controls. Fluxes of CH4 from terrestrial ecosystems were primarily influenced by water table position, soil temperature, and vegetation composition, while CH4 fluxes from aquatic ecosystems were primarily influenced by water temperature, lake size, and lake genesis. Models could explain more of the between-site variability in CH4 fluxes for terrestrial than aquatic ecosystems, likely due to both less precise assessments of lake CH4 fluxes and fewer consistently reported lake site characteristics. Analysis of BAWLD-CH4 identified both land cover classes and regions within the boreal and arctic domain, where future studies should be focused, alongside methodological approaches. Overall, BAWLD-CH4 provides a comprehensive dataset of CH4 emissions from high-latitude ecosystems that are useful for identifying research opportunities, for comparison against new field data, and model parameterization or validation. BAWLD-CH4 can be downloaded from https://doi.org/10.18739/A2DN3ZX1R (Kuhn et al., 2021).

Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small ( km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).

Aquatic ecosystems are major sources of greenhouse gases (GHGs). Robust measurements of natural GHG emissions are vital for evaluating regional to global carbon budgets and for assessing climate feedbacks of natural emissions to improve climate models. Diffusive and ebullitive (bubble) transport are two major pathways of gas release from surface waters. To capture the high temporal variability of these fluxes in a well-defined footprint, we designed and built an inexpensive device that includes an easily mobile diffusive flux chamber and a bubble counter all in one. In addition to automatically collecting gas samples for subsequent various analyses in the laboratory, this device also utilized a low-cost carbon dioxide (CO2) sensor (SenseAir, Sweden) and methane (CH4) sensor (Figaro, Japan) to measure GHG fluxes. Each of the devices was equipped with an XBee module to enable local radio communication (DigiMesh network) for time synchronization and data readout at a server controller station on the lakeshore. The software of this server controller was operated on a low-cost computer (Raspberry Pi), which has a 3G connection for remote control and monitor functions from anywhere in the world. This study shows the potential of a low-cost automatic sensor network system for studying GHG fluxes on lakes in remote locations.

Abstract The Arctic faces multiple pressures including climate change, shifting demographics, human health risks, social justice imbalances, governance issues, and expanding resource extraction. A convergence of academic disciplines—such as natural and social sciences, engineering and technology, health and medicine—and international perspectives is required to meaningfully contribute to solving the challenges of Arctic peoples and ecosystems. However, successfully carrying out convergent, international research and education remains a challenge. Here, lessons from the planning phase of a convergence research project concerned with the health of Arctic waters developed by the Arctic Science IntegrAtion Quest (ASIAQ) are discussed. We discuss our perspective on the challenges, as well as strategies for success, in convergence research as gained from the ASIAQ project which assembled an international consortium of researchers from disparate disciplines representing six universities from four countries (Sweden, Japan, Russia, and the United States) during 2018–2020.

Vegetation, soil and ecosystem level carbonyl sulfide (COS) exchange was observed at Duke Forest, a temperate loblolly pine forest, grown under ambient (Ring 1, R1) and elevated (Ring 2, R2) CO2. During calm meteorological conditions, ambient COS mixing ratios at the top of the forest canopy followed a distinct diurnal pattern in both CO2 growth regimes, with maximum COS mixing ratios during the day (R1=380±4 pptv and R2=373±3 pptv, daytime mean ± standard error) and minimums at night (R1=340±6 pptv and R2=346±5 pptv, nighttime mean ± standard error) reflecting a significant nighttime sink. Nocturnal vegetative uptake (−11 to −21 pmol m−2s−1, negative values indicate uptake from the atmosphere) dominated nighttime net ecosystem COS flux estimates (−10 to −30 pmol m−2s−1) in both CO2 regimes. In comparison, soil uptake (−0.8 to −1.7 pmol m−2 s−1) was a minor component of net ecosystem COS flux. In both CO2 regimes, loblolly pine trees exhibited substantial COS consumption overnight (50% of daytime rates) that was independent of CO2 assimilation. This suggests current estimates of the global vegetative COS sink, which assume that COS and CO2 are consumed simultaneously, may need to be reevaluated. Ambient COS mixing ratios, species specific diurnal patterns of stomatal conductance, temperature and canopy position were the major factors influencing the vegetative COS flux at the branch level. While variability in branch level vegetative COS consumption measurements in ambient and enhanced CO2 environments could not be attributed to CO2 enrichment effects, estimates of net ecosystem COS flux based on ambient canopy mixing ratio measurements suggest less nighttime uptake of COS in R2, the CO2 enriched environment.

Summertime atmospheric toluene enhancements at Thompson Farm in the rural northeastern United States were unexpected and resulted in a toluene/benzene seasonal pattern that was distinctly different from that of other anthropogenic volatile organic compounds. Consequently, three hydrocarbon sources were investigated for potential contributions to the enhancements during 2004–2006. These included: (1) increased warm season fuel evaporation coupled with changes in reformulated gasoline (RFG) content to meet US EPA summertime volatility standards, (2) local industrial emissions and (3) local vegetative emissions. The contribution of fuel evaporation emission to summer toluene mixing ratios was estimated to range from 16 to 30 pptv d−1, and did not fully account for the observed enhancements (20–50 pptv) in 2004–2006. Static chamber measurements of alfalfa, a crop at Thompson Farm, and dynamic branch enclosure measurements of loblolly pine trees in North Carolina suggested vegetative emissions of 5 and 12 pptv d−1 for crops and coniferous trees, respectively. Toluene emission rates from alfalfa are potentially much larger as these plants were only sampled at the end of the growing season. Measured biogenic fluxes were on the same order of magnitude as the influence from gasoline evaporation and industrial sources (regional industrial emissions estimated at 7 pptv d−1 and indicated that local vegetative emissions make a significant contribution to summertime toluene enhancements. Additional studies are needed to characterize the variability and factors controlling toluene emissions from alfalfa and other vegetation types throughout the growing season.

No abstract available.