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In the Arctic waterbodies are abundant and rapid thaw of permafrost is destabilizing the carbon cycle and changing hydrology. It is particularly important to quantify and accurately scale aquatic carbon emissions in arctic ecosystems. Recently available high-resolution remote sensing datasets capture the physical characteristics of arctic landscapes at unprecedented spatial resolution. We demonstrate how machine learning models can capitalize on these spatial datasets to greatly improve accuracy when scaling waterbody CO₂and CH₄fluxes across the YK Delta of south-west AK. We found that waterbody size and contour were strong predictors for aquatic CO₂emissions, attributing greater than two-thirds of the influence to the scaling model. Small ponds (<0.001 km²) were hotspots of emissions, contributing fluxes several times their relative area, but were less than 5% of the total carbon budget. Small to medium lakes (0.001–0.1 km²) contributed the majority of carbon emissions from waterbodies. Waterbody CH₄emissions were predicted by a combination of wetland landcover and related drivers, as well as watershed hydrology, and waterbody surface reflectance related to chromophoric dissolved organic matter. When compared to our machine learning approach, traditional scaling methods that did not account for relevant landscape characteristics overestimated waterbody CO₂and CH₄emissions by 26%–79% and 8%–53% respectively. This study demonstrates the importance of an integrated terrestrial-aquatic approach to improving estimates and uncertainty when scaling C emissions in the arctic.

 

Volatile chemical products (VCPs) and other non-combustion-related sourceshave become important for urban air quality, and bottom-up calculationsreport emissions of a variety of functionalized compounds that remainunderstudied and uncertain in emissions estimates. Using a new instrumentalconfiguration, we present online measurements of oxygenated organiccompounds in a US megacity over a 10 d wintertime sampling period, whenbiogenic sources and photochemistry were less active. Measurements wereconducted at a rooftop observatory in upper Manhattan, New York City, USAusing a Vocus chemical ionization time-of-flight mass spectrometer, withammonium (NH4+) as the reagent ion operating at 1 Hz. The range ofobservations spanned volatile, intermediate-volatility, and semi-volatileorganic compounds, with targeted analyses of ∼150 ions, whoselikely assignments included a range of functionalized compound classes suchas glycols, glycol ethers, acetates, acids, alcohols, acrylates, esters,ethanolamines, and ketones that are found in various consumer, commercial,and industrial products. Their concentrations varied as a function of winddirection, with enhancements over the highly populated areas of the Bronx,Manhattan, and parts of New Jersey, and included abundant concentrations ofacetates, acrylates, ethylene glycol, and other commonly used oxygenatedcompounds. The results provide top-down constraints on wintertime emissionsof these oxygenated and functionalized compounds, with ratios to commonanthropogenic marker compounds and comparisons of their relative abundancesto two regionally resolved emissions inventories used in urban air qualitymodels.

 

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate. 

Abstract. Understanding the sources and sinks of methane (CH4)is critical to both predicting and mitigating future climate change. Thereare large uncertainties in the global budget of atmospheric CH4, butnatural emissions are estimated to be of a similar magnitude toanthropogenic emissions. To understand CH4 flux from biogenic sourcesin the United States (US) of America, a multi-scale CH4 observationnetwork focused on CH4 flux rates, processes, and scaling methods isrequired. This can be achieved with a network of ground-based observationsthat are distributed based on climatic regions and land cover. To determinethe gaps in physical infrastructure for developing this network, we need tounderstand the landscape representativeness of the current infrastructure.We focus here on eddy covariance (EC) flux towers because they are essentialfor a bottom-up framework that bridges the gap between point-based chambermeasurements and airborne or satellite platforms that inform policydecisions and global climate agreements. Using dissimilarity,multidimensional scaling, and cluster analysis, the US was divided into 10clusters distributed across temperature and precipitation gradients. Weevaluated dissimilarity within each cluster for research sites with activeCH4 EC towers to identify gaps in existing infrastructure that limitour ability to constrain the contribution of US biogenic CH4 emissionsto the global budget. Through our analysis using climate, land cover, andlocation variables, we identified priority areas for research infrastructureto provide a more complete understanding of the CH4 flux potential ofecosystem types across the US. Clusters corresponding to Alaska and theRocky Mountains, which are inherently difficult to capture, are the mostpoorly represented, and all clusters require a greater representation ofvegetation types. 

Abstract Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO 2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO 2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO 2 later in the season. 

Abstract Where does the carbon released by burning fossil fuels go? Currently, ocean and land systems remove about half of the CO 2 emitted by human activities; the remainder stays in the atmosphere. These removal processes are sensitive to feedbacks in the energy, carbon, and water cycles that will change in the future. Observing how much carbon is taken up on land through photosynthesis is complicated because carbon is simultaneously respired by plants, animals, and microbes. Global observations from satellites and air samples suggest that natural ecosystems take up about as much CO 2 as they emit. To match the data, our land models generate imaginary Earths where carbon uptake and respiration are roughly balanced, but the absolute quantities of carbon being exchanged vary widely. Getting the magnitude of the flux is essential to make sure our models are capturing the right pattern for the right reasons. Combining two cutting-edge tools, carbonyl sulfide (OCS) and solar-induced fluorescence (SIF), will help develop an independent answer of how much carbon is being taken up by global ecosystems. Photosynthesis requires CO 2 , light, and water. OCS provides a spatially and temporally integrated picture of the “front door” of photosynthesis, proportional to CO 2 uptake and water loss through plant stomata. SIF provides a high-resolution snapshot of the “side door,” scaling with the light captured by leaves. These two independent pieces of information help us understand plant water and carbon exchange. A coordinated effort to generate SIF and OCS data through satellite, airborne, and ground observations will improve our process-based models to predict how these cycles will change in the future. 

Abstract. The uptake of carbonyl sulfide (COS) by terrestrial plants is linked tophotosynthetic uptake of CO2 as these gases partly share the sameuptake pathway. Applying COS as a photosynthesis tracer in models requires anaccurate representation of biosphere COS fluxes, but these models have notbeen extensively evaluated against field observations of COS fluxes. In thispaper, the COS flux as simulated by the Simple Biosphere Model, version 4(SiB4), is updated with the latest mechanistic insights and evaluated with siteobservations from different biomes: one evergreen needleleaf forest, twodeciduous broadleaf forests, three grasslands, and two crop fields spread overEurope and North America. We improved SiB4 in several ways to improve itsrepresentation of COS. To account for the effect of atmospheric COS molefractions on COS biosphere uptake, we replaced the fixed atmospheric COS molefraction boundary condition originally used in SiB4 with spatially andtemporally varying COS mole fraction fields. Seasonal amplitudes of COS molefractions are ∼50–200 ppt at the investigated sites with aminimum mole fraction in the late growing season. Incorporating seasonalvariability into the model reduces COS uptake rates in the late growingseason, allowing better agreement with observations. We also replaced theempirical soil COS uptake model in SiB4 with a mechanistic model thatrepresents both uptake and production of COS in soils, which improves thematch with observations over agricultural fields and fertilized grasslandsoils. The improved version of SiB4 was capable of simulating the diurnal andseasonal variation in COS fluxes in the boreal, temperate, and Mediterraneanregion. Nonetheless, the daytime vegetation COS flux is underestimated onaverage by 8±27 %, albeit with large variability across sites. On aglobal scale, our model modifications decreased the modeled COS terrestrialbiosphere sink from 922 Gg S yr−1 in the original SiB4 to753 Gg S yr−1 in the updated version. The largest decrease influxes was driven by lower atmospheric COS mole fractions over regions withhigh productivity, which highlights the importance of accounting forvariations in atmospheric COS mole fractions. The change to a different soilmodel, on the other hand, had a relatively small effect on the globalbiosphere COS sink. The secondary role of the modeled soil component in theglobal COS budget supports the use of COS as a global photosynthesis tracer. Amore accurate representation of COS uptake in SiB4 should allow for improvedapplication of atmospheric COS as a tracer of local- to global-scaleterrestrial photosynthesis. 

Soil respiration (i.e. from soils and roots) provides one of the largest global fluxes of carbon dioxide (CO₂) to the atmosphere and is likely to increase with warming, yet the magnitude of soil respiration from rapidly thawing Arctic-boreal regions is not well understood. To address this knowledge gap, we first compiled a new CO₂flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO₂database, multi-sensor satellite imagery, and random forest models to assess the regional magnitude of soil respiration. The flux database includes a new Soil Respiration Station network of chamber-based fluxes, and fluxes from eddy covariance towers. Our site-level data, spanning September 2016 to August 2017, revealed that the largest soil respiration emissions occurred during the summer (June–August) and that summer fluxes were higher in boreal sites (1.87 ± 0.67 g CO₂–C m⁻²d⁻¹) relative to tundra (0.94 ± 0.4 g CO₂–C m⁻²d⁻¹). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO₂–C m⁻²d⁻¹; tundra: 0.18 ± 0.16 g CO₂–C m⁻²d⁻¹) from soils during the winter (November–March) despite frozen surface conditions. Our model estimates indicated an annual region-wide loss from soil respiration of 591 ± 120 Tg CO₂–C during the 2016–2017 period. Summer months contributed to 58% of the regional soil respiration, winter months contributed to 15%, and the shoulder months contributed to 27%. In total, soil respiration offset 54% of annual gross primary productivity (GPP) across the study domain. We also found that in tundra environments, transitional tundra/boreal ecotones, and in landscapes recently affected by fire, soil respiration often exceeded GPP, resulting in a net annual source of CO₂to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.

 

Abstract. Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).