Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.
Methane (CH 4 ) has a large contribution to the global radiative budget and is responsible for about 0.5°C of present global warming over the period 1850 -1900(IPCC, 2021. Methane has a relatively short perturbation lifetime (12.4 years (Balcombe et al., 2018)) and high global warming potential (28-36 times that of CO 2 over a 100year period (IPCC, 2021)). As such, a decline in CH 4 emissions will rapidly reduce global CH 4 concentrations and mitigate the impact of climate change at decadal time scales (United Nations Environment Programme & Climate & Clean Air Coalition, 2021). However, any efforts to target CH 4 emissions reductions require a thorough understanding of the dominant CH 4 sources and sinks and their temporal and regional distribution and trends.Methane is produced in three ways-pyrogenically, thermogenically, or biogenically-from both anthropogenic and natural processes. Pyrogenic sources of CH 4 include biofuel combustion (e.g., wood burning for heating and cooking) and biomass burning (e.g., wildfires and peat fires). All pyrogenic sources produce CH 4 from the incomplete combustion of organic matter. Thermogenic CH 4 is produced from the breakdown of organic matter buried deep within the Earth's crust at high pressure and temperature. Although geological CH 4 is released naturally into the atmosphere through gas seeps, most is released through activities related to the exploration, mining, and transport of fossil fuels (Hmiel et al., 2020;Janssens-Maenhout et al., 2019;Petrenko et al., 2017). The majority of biogenic CH 4 is produced in anaerobic environments by the microbial mediated breakdown of organic matter. These environments include wetlands, inland waters, marine sediments, ruminants such as cattle, rice paddies, manure management and wastewater and landfill systems. Small quantities of CH4 are also produced from the aerobic bacterial metabolization of methylated compounds (e.g., Florez-Leiva et al., 2013) and even photochemically (Li et al., 2020). Counter-balancing these CH 4 sources are three chemically driven atmospheric sinks of CH 4 . The first two reactions with tropospheric OH radicals and tropospheric atomic chlorine account for ~88% (476 -677 Tg CH 4 yr −1 ) and ~2% (1-35 Tg CH 4 yr −1 ) of the total sink, respectively, with a third stratospheric sink (e.g., reaction with O('D), Cl and OH in the stratosphere) accounting for a further ~5% (12-37 Tg CH 4 yr −1 ) (Saunois et al., 2020). However, due to their highly reactive nature, the key reactants are inherently difficult to quantify, driving a significant level of uncertainty in the spatial and temporal distribution of atmospheric sink estimates (Zhao et al., 2019). Many fundamental aspects of the spatial distribution of OH are currently unresolved, for example, estimates of the interhemispheric gradient can vary from 0.85 to 1.4 (NH/SH) depending on the methodology
Abstract. Airborne and ground-based measurements of methane (CH 4 ), carbon dioxide (CO 2 ) and boundary layer thermodynamics were recorded over the Fennoscandian landscape (67-69.5 • N, 20-28 • E) in July 2012 as part of the MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) field campaign. Employing these airborne measurements and a simple boundary layer box model, net regional-scale (∼ 100 km) fluxes were calculated to be 1.2 ± 0.5 mg CH 4 h −1 m −2 and −350 ± 143 mg CO 2 h −1 m −2 . These airborne fluxes were found to be relatively consistent with seasonally averaged surface chamber (1.3 ± 1.0 mg CH 4 h −1 m −2 ) and eddy covariance (1.3 ± 0.3 mg CH 4 h −1 m −2 and −309 ± 306 mg CO 2 h −1 m −2 ) flux measurements in the local area. The internal consistency of the aircraft-derived fluxes across a wide swath of Fennoscandia coupled with an excellent statistical comparison with local seasonally averaged ground-based measurements demonstrates the potential scalability of such localised measurements to regional-scale representativeness. Comparisons were also made to longerterm regional CH 4 climatologies from the JULES (Joint UK Land Environment Simulator) and HYBRID8 land surface models within the area of the MAMM campaign. The average hourly emission flux output for the summer period Based on these observations both models were found to significantly underestimate the CH 4 emission flux in this region, which was linked to the under-prediction of the wetland extents generated by the models.
Abstract. Spectroscopic measurements of atmospheric N 2 O and CH 4 mole fractions were made on board the FAAM (Facility for Airborne Atmospheric Measurements) large atmospheric research aircraft. We present details of the mid-infrared quantum cascade laser absorption spectrometer (QCLAS, Aerodyne Research Inc., USA) employed, including its configuration for airborne sampling, and evaluate its performance over 17 flights conducted during summer 2014. Two different methods of correcting for the influence of water vapour on the spectroscopic retrievals are compared and evaluated. A new in-flight calibration procedure to account for the observed sensitivity of the instrument to ambient pressure changes is described, and its impact on instrument performance is assessed. Test flight data linking this sensitivity to changes in cabin pressure are presented. Total 1σ uncertainties of 2.47 ppb for CH 4 and 0.54 ppb for N 2 O are derived. We report a mean difference in 1 Hz CH 4 mole fraction of 2.05 ppb (1σ = 5.85 ppb) between in-flight measurements made using the QCLAS and simultaneous measurements using a previously characterised Fast Greenhouse Gas Analyser (FGGA, Los Gatos Research, USA). Finally, a potential case study for the estimation of a regional N 2 O flux using a mass balance technique is identified, and the method for calculating such an estimate is outlined.
A stratified air mass enriched in methane (CH4) was sampled at ~600 m to ~2000 m altitude, between the north coast of Norway and Svalbard as part of the Methane in the Arctic: Measurements and Modelling campaign on board the UK's BAe‐146‐301 Atmospheric Research Aircraft. The approach used here, which combines interpretation of multiple tracers with transport modeling, enables better understanding of the emission sources that contribute to the background mixing ratios of CH4 in the Arctic. Importantly, it allows constraints to be placed on the location and isotopic bulk signature of the emission source(s). Measurements of δ13C in CH4 in whole air samples taken while traversing the air mass identified that the source(s) had a strongly depleted bulk δ13C CH4 isotopic signature of −70 (±2.1)‰. Combined Numerical Atmospheric‐dispersion Modeling Environment and inventory analysis indicates that the air mass was recently in the planetary boundary layer over northwest Russia and the Barents Sea, with the likely dominant source of methane being from wetlands in that region.
How complex is the memory structure that honeybees use to navigate? Recently, an insect-inspired parsimonious spiking neural network model was proposed that enabled simulated ground-moving agents to follow learned routes. We adapted this model to flying insects and evaluate the route following performance in three different worlds with gradually decreasing object density. In addition, we propose an extension to the model to enable the model to associate sensory input with a behavioral context, such as foraging or homing. The spiking neural network model makes use of a sparse stimulus representation in the mushroom body and reward-based synaptic plasticity at its output synapses. In our experiments, simulated bees were able to navigate correctly even when panoramic cues were missing. The context extension we propose enabled agents to successfully discriminate partly overlapping routes. The structure of the visual environment, however, crucially determines the success rate. We find that the model fails more often in visually rich environments due to the overlap of features represented by the Kenyon cell layer. Reducing the landmark density improves the agents route following performance. In very sparse environments, we find that extended landmarks, such as roads or field edges, may help the agent stay on its route, but often act as strong distractors yielding poor route following performance. We conclude that the presented model is valid for simple route following tasks and may represent one component of insect navigation. Additional components might still be necessary for guidance and action selection while navigating along different memorized routes in complex natural environments.
Abstract. This study validates trace gas and thermodynamic retrievals from nadir infrared spectroscopic measurements recorded by the UK Met Office Airborne Research Interferometer Evaluation System (ARIES) -a thermal infrared, Fourier transform spectrometer (TIR-FTS) on the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft.Trace-gas-concentration and thermodynamic profiles have been retrieved and validated for this study throughout the troposphere and planetary boundary layer (PBL) over a range of environmental variability using data from aircraft campaigns over and around London, the US Gulf Coast, and the Arctic Circle during the Clear air for London (ClearfLo), Joint Airborne IASI (Infrared Atmospheric Sounding Interferometer) Validation Experiment (JAIVEx), and Measurements, process studies, and Modelling (MAMM) aircraft campaigns, respectively. Vertically resolved retrievals of temperature and water vapour (H 2 O), and partial-column retrievals of methane (CH 4 ), carbon monoxide (CO), and ozone (O 3 ) (over both land and sea) were compared to corresponding measurements from high-precision in situ analysers and dropsondes operated on the FAAM aircraft. Average degrees of freedom for signal (DOFS) over a 0-9 km column range were found to be 4.97, 3.11, 0.91, 1.10, and 1.62 for temperature, H 2 O, CH 4 , CO, and O 3 , respectively, when retrieved on 10 vertical levels. Partial-column mean biases (and bias standard error) between the surface and ∼ 9 km, when averaged across all flight campaigns, were found to be −0.7(±0.3) K, −479(±56) ppm, −11(±2) ppb, −3.3(±1.0) ppb, and +3.5(±1.0) ppb, respectively, whilst the typical a posteriori (total) uncertainties for individually retrieved profiles were 0.4, 9.5, 5.0, 21.2, and 15.0 %, respectively.Averaging kernels (AKs) derived for progressively lower altitudes show improving sensitivity to lower atmospheric layers when flying at lower altitudes. Temperature and H 2 O display significant vertically resolved sensitivity throughout the column, whilst trace gases are usefully retrieved only as partial-column quantities, with maximal sensitivity for trace gases other than H 2 O within a layer 1 and 2 km below the aircraft. This study demonstrates the valuable atmospheric composition information content that can be obtained by ARIES nadir TIR remote sensing for atmospheric process studies.
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