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Methane (CH4) is a strong greenhouse gas that has become the focus of climate mitigation policies in recent years. Ethane / methane ratios can be used to identify and partition the difference sources of methane, especially in areas with natural gas mixed with biogenic methane emissions, such as cities. We assessed the precision, accuracy and selectivity of three commercially available laser-based analyzers that have been marketed as measuring instantaneous dry mole fractions of methane and ethane in ambient air. The Aerodyne SuperDUAL instrument performed best of the three instruments but it requires expertise to operate and space for the large footprint. The Aeris Mira Ultra LDS analyzer also performed well for the price point and small footprint but required characterization of the water vapor dependence of reported concentrations and careful setup for use. The Picarro G2210-i precisely measured methane but it did not detect the 10 ppbv increases in ambient ethane detected by the other two instruments when sampling a plume of incompletely combusted natural gas. For long-term tower deployments or those with large mobile laboratories, the Aerodyne SuperDUAL provides the best precision for methane and ethane. For smaller mobile platforms, the Aeris MIRA is a more compact analyzer, and with careful use, can quantify thermogenic methane sources to sufficient precision for short term deployments in urban or oil and gas areas. We weighed the advantages of each instrument, including size, power requirement, ease of use on mobile platforms, and expertise needed to operate the instrument, and we recommend the Aerodyne SuperDUAL or the Aeris MIRA Ultra LDS depending on the situation.

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

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.

Approximately half of the carbon dioxide (CO 2) released annually by the combustion of fossil fuels stays in the atmosphere (Friedlingstein et al., 2022; Keeling et al., 1976; Schimel et al., 2001). The remaining CO 2 is taken up by the terrestrial biosphere and ocean in roughly equal proportions (Keeling & Manning, 2014; Khatiwala et al., 2009; Sabine et al., 2004). The efficiency of the ocean and land sinks varies with both climate and atmospheric CO 2 , representing an important feedback in the climate system (e.g., Ballantyne et al., 2012

This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.

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).

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom 10 s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2 km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation. This paper presents a corrected version of the paper published under the same authors and title (sans “corrected”) as https://doi.org/10.5194/acp-21-13729-2021.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco), net ecosystem CO2 exchange (NEE; Reco − GPP), and terrestrial methane (CH4) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO2-C year−1. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4) were estimated at 35 Tg CH4-C year−1. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Volatile chemical products (VCPs) and other non-combustion-related sources have become important for urban air quality, and bottom-up calculations report emissions of a variety of functionalized compounds that remain understudied and uncertain in emissions estimates. Using a new instrumental configuration, we present online measurements of oxygenated organic compounds in a US megacity over a 10 d wintertime sampling period, when biogenic sources and photochemistry were less active. Measurements were conducted at a rooftop observatory in upper Manhattan, New York City, USA using a Vocus chemical ionization time-of-flight mass spectrometer, with ammonium (NH4+) as the reagent ion operating at 1 Hz. The range of observations spanned volatile, intermediate-volatility, and semi-volatile organic compounds, with targeted analyses of ∼150 ions, whose likely assignments included a range of functionalized compound classes such as 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 wind direction, with enhancements over the highly populated areas of the Bronx, Manhattan, and parts of New Jersey, and included abundant concentrations of acetates, acrylates, ethylene glycol, and other commonly used oxygenated compounds. The results provide top-down constraints on wintertime emissions of these oxygenated and functionalized compounds, with ratios to common anthropogenic marker compounds and comparisons of their relative abundances to two regionally resolved emissions inventories used in urban air quality models.

Recent increases in boreal forest burned area, which have been linked with climate warming, highlight the need to better understand the composition of wildfire emissions and their atmospheric impacts. Here we quantified emission factors for CO and CH 4 from a massive regional fire complex in interior Alaska during the summer of 2015 using continuous high-resolution trace gas observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CRV) tower in Fox, Alaska. Averaged over the 2015 fire season, the mean CO / CO 2 emission ratio was 0.142 ± 0.051, and the mean CO emission factor was 127 ± 40 g kg −1 dry biomass burned. The CO / CO 2 emission ratio was about 39 % higher than the mean of previous estimates derived from aircraft sampling of wildfires from boreal North America. The mean CH 4 / CO 2 emission ratio was 0.010 ± 0.004, and the CH 4 emission factor was 5.3 ± 1.8 g kg −1 dry biomass burned, which are consistent with the mean of previous reports. CO and CH 4 emission ratios varied in synchrony, with higher CH 4 emission factors observed during periods with lower modified combustion efficiency (MCE). By coupling a fire emissions inventory with an atmospheric model, we identified at least 34 individual fires that contributed to trace gas variations measured at the CRV tower, representing a sample size that is nearly the same as the total number of boreal fires measured in all previous field campaigns. The model also indicated that typical mean transit times between trace gas emission within a fire perimeter and tower measurement were 1–3 d, indicating that the time series sampled combustion across day and night burning phases. The high CO emission ratio estimates reported here provide evidence for a prominent role of smoldering combustion and illustrate the importance of continuously sampling fires across time-varying environmental conditions that are representative of a fire season.

Formic acid (HCOOH) is an important component of atmospheric acidity but its budget is poorly understood, with prior observations implying substantial missing sources. Here we combine pole-to-pole airborne observations from the Atmospheric Tomography Mission (ATom) with chemical transport model (GEOS-Chem CTM) and back trajectory analyses to provide the first global in-situ characterization of HCOOH in the remote atmosphere. ATom reveals sub-100 ppt HCOOH concentrations over most of the remote oceans, punctuated by large enhancements associated with continental outflow. Enhancements correlate with known combustion tracers and trajectory-based fire influences. The GEOS-Chem model underpredicts these in-plume HCOOH enhancements, but elsewhere we find no broad indication of a missing HCOOH source in the background free troposphere. We conclude that missing non-fire HCOOH precursors inferred previously are predominantly short-lived. We find indications of a wet scavenging underestimate in the model consistent with a positive HCOOH bias in the tropical upper troposphere. Observations reveal episodic evidence of ocean HCOOH uptake, which is well-captured by GEOS-Chem; however, despite its strong seawater undersaturation HCOOH is not consistently depleted in the remote marine boundary layer. Over fifty fire and mixed plumes were intercepted during ATom with widely varying transit times and source regions. HCOOH:CO normalized excess mixing ratios in these plumes range from 3.4 to >50 ppt/ppb CO and are often over an order of magnitude higher than expected primary emission ratios. HCOOH is thus a major reactive organic carbon reservoir in the aged plumes sampled during ATom, implying important missing pathways for in-plume HCOOH production.

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.

Climate change is causing an intensification in tundra fires across the Arctic, including the unprecedented 2015 fires in the Yukon-Kuskokwim (YK) Delta. The YK Delta contains extensive surface waters (∼33% cover) and significant quantities of organic carbon, much of which is stored in vulnerable permafrost. Inland aquatic ecosystems act as hot-spots for landscape CO2 and CH4 emissions and likely represent a significant component of the Arctic carbon balance, yet aquatic fluxes of CO2 and CH4 are also some of the most uncertain. We measured dissolved CH4 and CO2 concentrations (n = 364), in surface waters from different types of waterbodies during summers from 2016 to 2019. We used Sentinel-2 multispectral imagery to classify landcover types and area burned in contributing watersheds. We develop a model using machine learning to assess how waterbody properties (size, shape, and landscape properties), environmental conditions (O2, temperature), and surface water chemistry (dissolved organic carbon composition, nutrient concentrations) help predict in situ observations of CH4 and CO2 concentrations across deltaic waterbodies. CO2 concentrations were negatively related to waterbody size and positively related to waterbody edge effects. CH4 concentrations were primarily related to organic matter quantity and composition. Waterbodies in burned watersheds appeared to be less carbon limited and had longer soil water residence times than in unburned watersheds. Our results illustrate the importance of small lakes for regional carbon emissions and demonstrate the need for a mechanistic understanding of the drivers of greenhouse gasses in small waterbodies.

Global warming is projected to shift the phenology and increase the productivity of northern ecosystems1–6. Both changes will further feed back to climate through biophysical and biogeochemical processes and are critical for future prediction7,8. However, it remains unclear whether warming and the extended growing season, especially in autumn, would lead to increased net ecosystem carbon uptake9,10. Here we analyse satellite observations, field measurements and model simulations and show a prevalent radiation limitation on carbon uptake in northern ecosystems, especially in autumn. By comparing the start and end of the growing season estimated from vegetation indices and from solar-induced chlorophyll fluorescence (a proxy for gross primary production11,12 (GPP)), we find a greater change in greenness-based start and end of season than that from GPP, mostly caused by the radiation limitation on photosynthesis. This radiation limitation explains the contrasting responses of autumn net carbon exchanges to warming, using both eddy covariance measurements and model simulations from Coupled Model Intercomparison Project Phase 5. Regions with weak radiation limitation benefit more from warming and enhanced vegetation greenness in autumn, where GPP increases can outweigh the warming-induced respiration carbon losses. With continued warming, radiation limitation will increase and exert a strong upper bound on northern ecosystems to act as carbon sinks. Phenological shifts due to warming extend the growing season for plants, with implications for ecosystem productivity. Carbon uptake through photosynthesis is limited by radiation, particularly in autumn, which explains contrasting regional responses of autumn carbon uptake to rising temperatures.

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 CO2 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 CO2 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 CO2 later in the season.

The Southern Ocean plays an important role in determining atmospheric carbon dioxide (CO2), yet estimates of air-sea CO2 flux for the region diverge widely. In this study, we constrained Southern Ocean air-sea CO2 exchange by relating fluxes to horizontal and vertical CO2 gradients in atmospheric transport models and applying atmospheric observations of these gradients to estimate fluxes. Aircraft-based measurements of the vertical atmospheric CO2 gradient provide robust flux constraints. We found an annual mean flux of –0.53 ± 0.23 petagrams of carbon per year (net uptake) south of 45°S during the period 2009–2018. This is consistent with the mean of atmospheric inversion estimates and surface-ocean partial pressure of CO2 (PCO2)–based products, but our data indicate stronger annual mean uptake than suggested by recent interpretations of profiling float observations.

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain (Norton et al. 2019, https://doi.org/10.5194/bg-16-3069-2019). Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012-2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year

Understanding the sources and sinks of 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 total anthropogenic emissions. The largest sources of uncertainty in scaling bottom-up CH4 estimates stem from limited ground-based measurements and the misalignment between drivers of CH4 fluxes and current land use classifications. To understand the CH4 flux potential of natural ecosystems and agricultural lands 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 landcover. To determine the gaps in physical infrastructure for developing this network, we need to understand the representativeness of current measurements. 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, informing the remote sensing and modelling communities and policy decisions, all the way to IPCC reports. Using multidimensional scaling and a cluster analysis, the US was divided into 10 clusters that were distributed across temperature and wetness gradients. We evaluated the distance to the medoid condition within each cluster for research sites with EC tower infrastructure to identify the gaps in existing infrastructure that limit our ability to constrain the contribution of US biogenic CH4 emissions to the global budget. These gaps occurred across all EC flux tower networks and independently managed sites as well as in some environmental clusters. Through our analysis using climate, land cover, and location variables, we have identified priority areas to target for research infrastructure to provide a more complete understanding of the CH4 flux potential of ecosystem types across the US.

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 (https://doi.org/10.3334/ORNLDAAC/1934, Virkkala et al., 2021a).

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state and national level. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop well-targeted emission reductions strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and better inform policy decisions.This presentation builds on previous work estimating methane emissions from New York City and the wider urban area based on measurements taken during nine research flights. We used an ensemble of dispersion model runs in a Bayesian inverse modelling framework to derive posterior emission estimates. Prior emissions were taken from three coarse-resolution inventories based on spatially disaggregated national totals. The most recent version of EDGAR (v5) and the gridded EPA inventory both required upscaling by more than a factor of two to be consistent with our measurements.Here, we construct a high-resolution methane emission prior using a combination of spatial proxies and reported emissions for various sectors. We present preliminary results evaluating the ability of this new prior to represent the magnitude and spatial distribution of emissions, through comparison with both the measured data and results obtained using coarser resolution inventories.

Better constraining the ecosystem gross photosynthetic CO2 uptake (GPP) is necessary to reduce the uncertainties on continental vegetation response to climate change. As GPP cannot be directly measured at the ecosystem scale, different proxies of vegetation CO2 uptake have emerged. These proxies are essential for land surface modelers to estimate GPP at large scale. Carbonyl sulfide (COS) shows many similarities with CO2, following the same diffusional pathways through the leaves. However, unlike CO2 that is also emitted by plants during respiration, COS is essentially only taken up by leaves and not re-emitted back to the atmosphere. Therefore, COS is a promising proxy of photosynthetic activity. In previous studies, fixed values of the leaf relative uptake (LRU) ratio of COS to CO2 fluxes normalized by their respective concentration have typically been used to infer GPP for the different biomes. However, it has been shown that LRU ratio changes with varying Photosynthetically Active Radiation (PAR), which limits its accuracy to constrain photosynthetic activity. Therefore, we redefined the COS-based GPP estimation approach to better capture GPP response to changing environmental conditions, by implementing a mechanistic model of COS exchange by continental vegetation in the ORCHIDEE land surface model. We compared the modelled fluxes against field measurements at two sites and studied the model behavior and environmental drivers. Then, we ran global simulations and computed the annual COS vegetation uptake that was found in the middle range values of previous reported budgets (-490 to -1335 Gg S yr-1), with -756 Gg S yr-1. The simulated fluxes were transported, and COS concentrations were evaluated against measurements from the NOAA atmospheric stations. Our results show that the mechanistic approach is more appropriate when studying photosynthetic activity at high temporal resolution, but similar results in concentrations are obtained between the mechanistic and LRU approaches at the global scale. Accurate evaluation of the continental vegetation COS uptake is necessary as it is the main COS sink. However, COS can also be absorbed or emitted by soils, a flux that complicates the use of eddy covariance COS flux measurements or atmospheric COS measurements to derive information on GPP estimates. Therefore, the soil COS exchange should also be represented in land surface models. We implemented two soil COS exchange models in ORCHIDEE, a mechanistic model (based on Ogée et al. 2016) and a second model based on an empirical relationship with soil respiration (following Berry et al., 2013). We evaluated the two models at several sites against field measurements. We also performed global simulations to evaluate the spatial distribution of soil COS fluxes and their seasonal variations. Finally, we estimated the contributions of the combined impact of soil COS exchange and leaf COS uptake (both from the ORCHIDEE model) to the global COS budget and on the COS atmospheric concentration latitudinal gradient.

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 CO2 flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO2 database, 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−2 d−1) relative to tundra (0.94 ± 0.4 g CO2–C m−2 d−1). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO2–C m−2 d−1; tundra: 0.18 ± 0.16 g CO2–C m−2 d−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 CO2 to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.

Where does the carbon released by burning fossil fuels go? Currently, ocean and land systems remove about half of the CO2 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 CO2 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 CO2, light, and water. OCS provides a spatially and temporally integrated picture of the “front door” of photosynthesis, proportional to CO2 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.

Acetone is one of the most abundant oxygenated volatile organic compounds (VOCs) in the atmosphere. The oceans impose a strong control on atmospheric acetone, yet the oceanic fluxes of acetone remain poorly constrained. In this work, the global budget of acetone is evaluated using two global models: CAM‐chem and GEOS‐Chem. CAM‐chem uses an online air‐sea exchange framework to calculate the bidirectional oceanic acetone fluxes, which is coupled to a data‐oriented machine‐learning approach. The machine‐learning algorithm is trained using a global suite of seawater acetone measurements. GEOS‐Chem uses a fixed surface seawater concentration of acetone to calculate the oceanic fluxes. Both model simulations are compared to airborne observations from a recent global‐scale, multiseasonal campaign, the NASA Atmospheric Tomography Mission (ATom). We find that both CAM‐chem and GEOS‐Chem capture the measured acetone vertical distributions in the remote atmosphere reasonably well. The combined observational and modeling analysis suggests that (i) the ocean strongly regulates the atmospheric budget of acetone. The tropical and subtropical oceans are mostly a net source of acetone, while the high‐latitude oceans are a net sink. (ii) CMIP6 anthropogenic emission inventory may underestimate acetone and/or its precursors in the Northern Hemisphere. (iii) The MEGAN biogenic emissions model may overestimate acetone and/or its precursors, and/or the biogenic oxidation mechanisms may overestimate the acetone yields. (iv) The models consistently overestimate acetone in the upper troposphere‐lower stratosphere over the Southern Ocean in austral winter. (v) Acetone contributes up to 30–40% of hydroxyl radical production in the tropical upper troposphere/lower stratosphere.

We report airborne measurements of acetaldehyde (CH(3)CHO) during the first and second deployments of the National Aeronautics and Space Administration (NASA) Atmospheric Tomography Mission (ATom). The budget of CH(3)CHO is examined using the Community Atmospheric Model with chemistry (CAM-chem), with a newly-developed online air-sea exchange module. The upper limit of the global ocean net emission of CH(3)CHO is estimated to be 34 Tg a(−1) (42 Tg a(−1) if considering bubble-mediated transfer), and the ocean impacts on tropospheric CH(3)CHO are mostly confined to the marine boundary layer. Our analysis suggests that there is an unaccounted CH(3)CHO source in the remote troposphere and that organic aerosols can only provide a fraction of this missing source. We propose that peroxyacetic acid (PAA) is an ideal indicator of the rapid CH(3)CHO production in the remote troposphere. The higher-than-expected CH(3)CHO measurements represent a missing sink of hydroxyl radicals (and halogen radical) in current chemistry-climate models.

A promising tracer for partitioning the global balance of CO2 is carbonyl sulfide (COS or OCS), a trace gas with leaf-level mechanisms shared with carbon dioxide (CO2) and water (H2O). COS is therefore used to derive insights into photosynthesis and transpiration at ecosystem to global scales. However, it remains unclear whether COS reflects photosynthesis or stomatal conductance most strongly, as its leaf biochemical and physical processes are not perfectly analogous to either CO2 or H2O. There is therefore a need to evaluate the models that encapsulate our current understanding of leaf and soil COS fluxes and predictions of carbon and water cycling against independent constraints in tractable experimental systems.In this study, we measured ecosystem, leaf, and soil fluxes of COS in the model Biosphere 2 (B2) Tropical Rainforest across a controlled whole ecosystem drought manipulation. We simultaneously, measured the stable isotopes of CO2, H2O, and their isotopes (13C-CO2, 18O-CO2, 2H-H2O, 18O-H2O) on atmosphere, leaf, and soil measurement streams connected to atmospheric towers, leaf chambers, and soil flux chambers. During the B2 Water, Atmosphere, and Life Dynamics (B2 WALD) campaign, the enclosed ecosystem received no rain for 66 days and was first rewet at depth (2-4 m) at 54 days. Here, we compare COS fluxes to simultaneous and independent measurements of GPP and transpiration from the leaf to ecosystem scales across ecosystem control, drought, and recovery. We further integrate COS measurements with the aforementioned isotopic tracers of carbon and water cycling into the Simple Biosphere Model (SiB3). Our goal is to explore the strengths and limitations of COS as a tracer of ecosystem processes dynamically responding to severe and controlled ecosystem drought.

We have analyzed TROPOspheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data acquired between November 2017 and March 2019 with respect to other satellite (MOPITT, Measurement Of Pollution In The Troposphere) and airborne (ATom, Atmospheric Tomography mission) datasets to better understand TROPOMI's contribution to the global tropospheric CO record (2000 to present). MOPITT and TROPOMI are two of only a few satellite instruments to ever derive CO from solar-reflected radiances. Therefore, it is particularly important to understand how these two datasets compare. Our results indicate that TROPOMI CO retrievals over land show excellent agreement with respect to MOPITT: relative biases and their SD (i.e., accuracy and precision) are on average -3.73%±11.51%, -2.24%±12.38%, and -3.22%±11.13% compared to the MOPITT TIR (thermal infrared), NIR (near infrared), and TIR + NIR (multispectral) products, respectively. TROPOMI and MOPITT data also show good agreement in terms of temporal and spatial patterns. Despite depending on solar-reflected radiances for its measurements, TROPOMI can also retrieve CO over bodies of water if clouds are present by approximating partial columns under cloud tops using scaled, model-based reference CO profiles. We quantify the bias of TROPOMI total column retrievals over bodies of water with respect to colocated in situ ATom CO profiles after smoothing the latter with the TROPOMI column averaging kernels (AKs), which account for signal attenuation under clouds (relative bias and its SD =3.25%±11.46 %). In addition, we quantify enull (the null-space error), which accounts for differences between the shape of the TROPOMI reference profile and that of the ATom true profile (enull=2.16%±2.23 %). For comparisons of TROPOMI and MOPITT retrievals over open water we compare TROPOMI total CO columns to their colocated MOPITT TIR counterparts. Relative bias and its SD are 2.98 %±15.71 % on average. We investigate the impact of discrepancies between the a priori and reference CO profiles (used by MOPITT and TROPOMI, respectively) on CO retrieval biases by applying a null-space adjustment (based on the MOPITT a priori) to the TROPOMI total column values. The effect of this adjustment on MOPITT and TROPOMI biases is minor, typically 1–2 percentage points.

With recent increases in burned area within boreal forests that have been linked to climate warming, there is a need to better understand the composition of emissions and their impact on atmospheric composition. Most previous studies have estimated boreal fire emission factors from daytime samples collected via aircraft near fire plumes or at the surface near actively burning fires. Here we quantified emission factors for CO and CH4 from a massive regional fire complex in interior Alaska during the summer of 2015 using continuous high-resolution trace gas observations from the CRV tower (Fox, AK). Averaged over the 2015 fire season, the CO/CO2 emission ratio was 0.138±0.048 and the CO emission factor was 145±50 g CO per kg of dry biomass consumed. The CO/CO2 emission ratio was about 35 % higher and more variable than most previous aircraft-based estimates for fresh wildfire emissions. The mean CH4/CO2 emission ratio was 0.010±0.003 and the CH4 emission factor was 6.05±2.09 g CH4 per kg of dry biomass consumed, with means similar to previous reports. CO and CH4 emission factors varied in synchrony, with higher CH4 emission factors observed during periods with lower modified combustion efficiency (MCE). By coupling a fire emissions inventory with an atmospheric model, we identified that at least 35 individual fires contributed to trace gas variations measured at the CRV tower, representing a significant increase in sampling compared to the number of boreal fires measured in all previous boreal forest fire work. The model also indicated that typical mean transit times between trace gas emission and tower measurement were 1–3 days, indicating that the time series sampled combustion across day and night burning phases. The high and variable CO emission factor estimates reported here provide evidence for a more prominent role of smoldering combustion, highlighting the importance of continuously sampling of fires across time-varying environmental conditions that are representative of typical burning conditions.

Earth's atmosphere oxidizes the greenhouse gas methane and other gases, thus determining their lifetimes and oxidation products. Much of this oxidation occurs in the remote, relatively clean free troposphere above the planetary boundary layer, where the oxidation chemistry is thought to be much simpler and better understood than it is in urban regions or forests. The NASA airborne Atmospheric Tomography study (ATom) was designed to produce cross sections of the detailed atmospheric composition in the remote atmosphere over the Pacific and Atlantic Oceans during four seasons. As part of the extensive ATom data set, measurements of the atmosphere's primary oxidant, hydroxyl (OH), and hydroperoxyl (HO₂) are compared to a photochemical box model to test the oxidation chemistry. Generally, observed and modeled median OH and HO₂ agree to with combined uncertainties at the 2σ confidence level, which is ~±40%. For some seasons, this agreement is within ~±20% below 6 km altitude. While this test finds no significant differences, OH observations increasingly exceeded modeled values at altitudes above 8 km, becoming ~35% greater, which is near the combined uncertainties. Measurement uncertainty and possible unknown measurement errors complicate tests for unknown chemistry or incorrect reaction rate coefficients that would substantially affect the OH and HO₂ abundances. Future analysis of detailed comparisons may yield additional discrepancies that are masked in the median values.