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Recent atmospheric methane concentrations show an accelerated increase, but the contributions of the underlying emitters are poorly understood. Recording the stable carbon isotope ratio of methane (δ13C(CH4)) is a powerful tool for CH4 source attribution and the understanding of the global methane budget. The airborne measurement of δ13C(CH4) provides the advantages of reaching remote areas and covering large-scale regions, but is challenging regarding sufficient precision while maintaining high spatial measurement density. The state of the art technique is to collect airborne gas samples for subsequent laboratory analysis by isotope ratio mass spectrometry, with high δ13C(CH4) precision of 0.05 ‰. Here we present an innovative in situ airborne system for the measurement of δ13C(CH4), called MIRACLE. MIRACLE consists of a conventional Picarro cavity ring down greenhouse gas analyzer (G2210-i) for the measurement of CH4 and δ13C(CH4), and a sampler unit. The sampler enables the collection of six gas samples in 2 l stainless steel tanks, in a short time (20 s each) via a metal bellows pump, which allows for the specific sampling of small-scale features, such as point source emissions. The sampling is followed by an extended period of subsequent analysis (up to 10 min). Using this setup, we achieve sufficient δ13C(CH4) precision (1σ uncertainty of 0.34 ‰) and an average of five samples per flight hour, allowing for a large number of samples for long flights. Due to the resulting dense coverage with sufficient precision, this novel approach allows for airborne δ13C(CH4) characterization of small-scale methane emitters and large-scale gradients. We employed MIRACLE aboard the research aircraft HALO during the CoMet 2.0 Arctic campaign in summer 2022, which focused on characterizing natural and anthropogenic methane sources in Canada. In this presentation, a proof of concept for the instrument is elaborated, including the investigation of sample purity and measurement comparisons with other instruments. Additionally, we show δ13C(CH4) signatures revealed by the method of Keeling analysis of measurements obtained during CoMet 2.0 and compare them to previous studies. The airborne operation of the MIRACLE instrument combines the advantages of increased precision δ13C(CH4) measurements, typically only possible under stable laboratory conditions, with the in situ, near real time data analysis and the large-scale sampling of secluded areas. MIRACLE will be deployed during the DLR GHGMon campaign (June 2023) to investigate the δ13C(CH4) ratio of agricultural sources of methane in the Netherlands.

Wetlands in the high northern latitudes are a major, yet poorly known contributor to the global methane (CH4) budget. In wetlands, peat bogs and lakes, CH4 is produced by organic degradation processes. These natural emissions are affected by climate change though, e.g. by changing temperatures and permafrost thaw. A better understanding is essential also for discussing the human role in the budget of this important greenhouse gas and mitigation options.However, the data coverage in the region is still thin: accessibility is limited, satellite sensors struggle with the high solar zenith angle, difficult surface and thermodynamic conditions, or clouds. Corresponding emission inventories and models differ significantly, in the distribution as well as in the amount of emissions. Based in Kiruna/Sweden, the French MAGIC initiative addressed these knowledge gaps by bringing together a multitude of instruments on three research aircraft (Safire ATR-42, BAS Twin Otter, DLR Cessna) and various other platforms for measurements in northern Scandinavia in August 2021.Here we focus on airborne in-situ measurements with the DLR Cessna. The suite of instruments aboard the aircraft included a meteorological sensor package, a Picarro, and an Aerodyne QCLS, providing CH4,CO2, C2H6, 13C(CH4), temperature, H2O, 3d-wind, all along the flight track.The Cessna conducted 12 scientific flights in the region, which mostly targeted and scouted hotspots of CH4 emissions indicated by wetland emission inventories. The flights were coordinated as often as possible with other airborne, ground-based and satellite platforms to allow for intercomparisons and for providing ground truth for remote sensing instruments. Estimating CH4 emission fluxes is another major objective, which is challenging because of spatial and temporal heterogeneity of these area sources. To this end we tried a combination of different methods and flight patterns. We provide an overview of the measurements, discuss the different flight strategies and show first results of the analyses that are ongoing in the frame of the ESA MAGIC4AMPAC project.

The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ-scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results; ii) the evaluation of the mixing prop- erties of five different turbulence models using the well-mixed criterion; and iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitiv- ity study, we analyse the effects of stability class, roughness length, zero-plane displacement factor and source height on the three-dimensional plume extent as well as the distance between source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbu- lence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height except for the default turbulence model of ARTM 3.0.0 with deviations by up to 18 %, respectively. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland measured by the DLR Cessna aircraft during the CoMet campaign in 2018 allow to evaluate the model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are in the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM version 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 % resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows a good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes and the plume width with 30 % deviations in peak CO2 concentration and less than 25 % deviation of the measured CO2 plume width. Uncertainties of the simulations may arise from the different spatial and temporal resolution of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representa- tion of real plumes in very unstable atmospheric conditions by the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Power plants and large industrial facilities contribute more than half of global anthropogenic CO2 emissions. Quantifying the emissions of these point sources is therefore one of the main goals of the planned constellation of anthropogenic CO2 monitoring satellites (CO2M) of the European Copernicus program. Atmospheric transport models may be used to study the capabilities of such satellites through observing system simulation experiments and to quantify emissions in an inverse modeling framework. How realistically the CO2 plumes of power plants can be simulated and how strongly the results may depend on model type and resolution, however, is not well known due to a lack of observations available for benchmarking. Here, we use the unique data set of aircraft in situ and remote sensing observations collected during the CoMet (Carbon Dioxide and Methane Mission) measurement campaign downwind of the coal-fired power plants at Bełchatów in Poland and Jänschwalde in Germany in 2018 to evaluate the simulations of six different atmospheric transport models. The models include three large-eddy simulation (LES) models, two mesoscale numerical weather prediction (NWP) models extended for atmospheric tracer transport, and one Lagrangian particle dispersion model (LPDM) and cover a wide range of model resolutions from 200 m to 2 km horizontal grid spacing. At the time of the aircraft measurements between late morning and early afternoon, the simulated plumes were slightly (at Jänschwalde) to highly (at Bełchatów) turbulent, consistent with the observations, and extended over the whole depth of the atmospheric boundary layer (ABL; up to 1800 m a.s.l. (above sea level) in the case of Bełchatów). The stochastic nature of turbulent plumes puts fundamental limitations on a point-by-point comparison between simulations and observations. Therefore, the evaluation focused on statistical properties such as plume amplitude and width as a function of distance from the source. LES and NWP models showed similar performance and sometimes remarkable agreement with the observations when operated at a comparable resolution. The Lagrangian model, which was the only model driven by winds observed from the aircraft, quite accurately captured the location of the plumes but generally underestimated their width. A resolution of 1 km or better appears to be necessary to realistically capture turbulent plume structures. At a coarser resolution, the plumes disperse too quickly, especially in the near-field range (0–8 km from the source), and turbulent structures are increasingly smoothed out. Total vertical columns are easier to simulate accurately than the vertical distribution of CO2, since the latter is critically affected by profiles of vertical stability, especially near the top of the ABL. Cross-sectional flux and integrated mass enhancement methods applied to synthetic CO2M data generated from the model simulations with a random noise of 0.5–1.0 ppm (parts per million) suggest that emissions from a power plant like Bełchatów can be estimated with an accuracy of about 20 % from single overpasses. Estimates of the effective wind speed are a critical input for these methods. Wind speeds in the middle of the ABL appear to be a good approximation for plumes in a well-mixed ABL, as encountered during CoMet.

Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represent one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April–May 2019 to study CH4 emissions from offshore gas facilities in the Southern North Sea with the aim to derive emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms/platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting/fugitive or flaring/combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and with operator-based reporting for individual Dutch facilities. In this study, we find that all inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all sampled Dutch installations together, we find that our estimated flux of (122.7 ± 9.7) kg h-1 deviates by a factor 0.7 (0.35–12) from reported values (183.1 kg h-1). Comparisons with aircraft observations in two other offshore regions (Norwegian Sea and Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by two orders of magnitude. Therefore, mitigation is warranted equally across geographies.

Methane ( CH4 ) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide ( CO2 ). Because of its short atmospheric lifetime relative to that of CO2 , the reduction of the atmospheric abundance of CH4 is an attractive target for short-term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources. For this reason, the CO2 and Methane (CoMet) campaign in May and June 2018 assessed emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the weighting-function-modified differential optical absorption spectroscopy (WFM-DOAS) method. The column anomalies, combined with wind lidar measurements, are inverted to cross-sectional fluxes using a mass balance approach. With the help of these fluxes, reported emissions of small clusters of coal mine ventilation shafts are then assessed. The MAMAP CH4 column observations enable an accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for four clusters with a total of 23 ventilation shafts, which are responsible for about 40 % of the total CH4 mining emissions in the target area. The observations were made during several overflights on different days. The final average CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 h−1 at the time of the campaign. The fluxes observed at one cluster during different overflights vary by as much as 50 % of the average value. Associated errors (1 σ ) are usually between 15 % and 59 % of the average flux, depending mainly on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement within the uncertainties. If only emissions reported annually are available for comparison with the observations, caution is advised due to possible fluctuations in emissions during a year or even within hours. To measure emissions even more precisely and to break them down further for allocation to individual shafts in a complex source region such as the USCB, imaging remote sensing instruments are recommended.

Column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured by a solar viewing portable Fourier transform spectrometer (FTS, EM27/SUN) have been characterized and validated by comparison using in situ profile measurements made during the transfer flights of two aircraft campaigns: Korea-United States Air Quality Study (KORUS-AQ) and Effect of Megacities on the Transport and Transformation of Pollutants at Regional and Global Scales (EMeRGe). The aircraft flew over two Total Carbon Column Observing Network (TCCON) sites: Rikubetsu, Japan (43.46∘ N, 143.77∘ E), for the KORUS-AQ campaign and Burgos, Philippines (18.53∘ N, 120.65∘ E), for the EMeRGe campaign. The EM27/SUN was deployed at the corresponding TCCON sites during the overflights. The mole fraction profiles obtained by the aircraft over Rikubetsu differed between the ascending and the descending flights above approximately 8 km for both CO2 and CH4. Because the spatial pattern of tropopause heights based on potential vorticity values from the ERA5 reanalysis shows that the tropopause height over the Rikubetsu site was consistent with the descending profile, we used only the descending profile to compare with the EM27/SUN data. Both the XCO2 and XCH4 derived from the descending profiles over Burgos were lower than those from the ascending profiles. Output from the Weather Research and Forecasting Model indicates that higher CO2 for the ascending profile originated in central Luzon, an industrialized and densely populated region about 400 km south of the Burgos TCCON site. Air masses observed with the EM27/SUN overlap better with those from the descending aircraft profiles than those from the ascending aircraft profiles with respect to their properties such as origin and atmospheric residence times. Consequently, the descending aircraft profiles were used for the comparison with the EM27/SUN data. The EM27/SUN XCO2 and XCH4 data were derived by using the GGG2014 software without applying air-mass-independent correction factors (AICFs). The comparison of the EM27/SUN observations with the aircraft data revealed that, on average, the EM27/SUN XCO2 data were biased low by 1.22 % and the EM27/SUN XCH4 data were biased low by 1.71 %. The resulting AICFs of 0.9878 for XCO2 and 0.9829 for XCH4 were obtained for the EM27/SUN. Applying AICFs being utilized for the TCCON data (0.9898 for XCO2 and 0.9765 for XCH4) to the EM27/SUN data induces an underestimate for XCO2 and an overestimate for XCH4.

The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting.

The ACT‐America project is a NASA Earth Venture Suborbital‐2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT‐America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower‐based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. We conducted 121 research flights during five campaigns in four seasons during 2016–2019 over three regions of the US (Mid‐Atlantic, Midwest and South) using two NASA research aircraft (B‐200 and C‐130). We performed three flight patterns (fair weather, frontal crossings, and OCO‐2 underflights) and collected more than 1,140 h of airborne measurements via level‐leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT‐America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT‐America data sets., Key Points Atmospheric Carbon and Transport – America (ACT‐America) provides a unique, weather‐oriented collection of atmospheric CO2, CH4, trace gases, and meteorological properties measurementsACT‐America data are free and open to the public from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)ACT‐America data are uniquely suited to improve the accuracy and precision of regional inverse greenhouse gas (GHG) flux estimates

In the last decade, much work has been done to better understand methane (CH4) emissions from the oil and gas (O&G) industry in the United States. Ethane (C2H6), a gas that is co-emitted with thermogenic sources of CH4, is emitted in the US predominantly by the O&G sector. In this study, we perform an inverse analysis on 200 h of atmospheric boundary layer C2H6 measurements to estimate C2H6 emissions from the US O&G sector. Measurements were collected from 2017 to 2019 as part of the Atmospheric Carbon and Transport (ACT) America aircraft campaign and encompass much of the central and eastern United States. We find that for the fall, winter, and spring campaigns, C2H6 data consistently exceeds values that would be expected based on EPA O&G leak rate estimates by more than 50%. C2H6 observations from the summer 2019 data set show significantly lower C2H6 enhancements in the southcentral region that cannot be reconciled with data from the other three seasons, either due to complex meteorological conditions or a temporal shift in the emissions. Combining the fall, winter, and spring C2H6 posterior emissions estimate to an inventory of O&G CH4 emissions, we estimate that O&G CH4 emissions are larger than EPA inventory values by 48%–76%. Uncertainties in the gas composition data limit the accuracy of using C2H6 as a proxy for O&G CH4 emissions. These limits could be resolved retroactively by increasing the availability of industry-collected gas composition data.

Sulfur dioxide (SO2) is known as a major air pollutant harmful to human health. Furthermore, it is a precursor gas of sulfate aerosol, which exerts a direct negative radiative forcing and thus leads to climate cooling. Anthropogenic SO2 sources are primarily associated with the combustion of sulfur-rich fossil fuels. While the operation of flue gas desulfurization devices has led to large SO2 reductions in western Europe, a hotspot of anthropogenic SO2 sources remains in the Balkan region as recently observed from space by the TROPOMI instrument on the Sentinel-5P satellite. Large coal-fired power plants with no or only incomplete SO2 removal cause these high emissions.Targeting these strong emitters, the DLR Falcon 20 aircraft was equipped with an isotopically on-line calibrated Chemical Ionization Ion Trap Mass Spectrometer (CI-ITMS) to obtain detailed in situ SO2 observations during the METHANE-To-Go-Europe aircraft campaign in autumn 2020. These SO2 measurements were complemented by in situ observations of greenhouse gases (CO2, CH4), aerosol number concentrations, and other short-lived pollutants (CO, NO, NOy). Two flights, on November 2nd and 7th 2020, focused on characterizing the pollution plumes downwind of two coal-fired power plants located in Bosnia-Herzegovina (Tuzla) and Serbia (Nikola Tesla), respectively. These power plants belong to the ten strongest SO2 emitters in Europe, and according to the World Health Organization, both countries are among the most polluted ones in Europe.We present a detailed analysis of the two DLR Falcon flights with strongly enhanced SO2 mixing ratios (exceeding 50 ppb), which were observed at low flight altitude (2 column densities, and both flights were performed during cloud-free conditions. The airborne measurements and satellite data will also be complemented by hourly ground-based SO2 measurements near both power plants. In addition, measurements are combined with state-of-the art model simulations from (i) the regional atmospheric chemistry climate model MECO(n); (ii) the atmospheric transport and dispersion model HYSPLIT; and (iii) the chemistry coupled Weather Research and Forecasting model WRF-Chem to improve the emission quantification of these power plants.

Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial era, making methane the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). Fossil fuel extraction is one of the major anthropogenic methane sources as it is estimated to account for 22 % of global CH4 emissions. However, studies indicate that inventories underestimate emissions arising from the oil and gas industry.In two airborne field campaigns carried out in spring 2018 and 2019 offshore gas facilities in the Southern North Sea were probed. A total of nine research flights were conducted to characterize platform emissions. The Twin Otter research aircraft, operated by the British Antarctic Survey, was equipped with a high-precision 10 Hz analyzer (Picarro) to continuously measure CH4 and CO2. In order to identify fossil fuel emissions ethane (C2H6) was simultaneously measured with a 1 Hz TILDAS instrument (Aerodyne Research, Inc). On offshore oil and gas platforms methane is emitted by leakage, venting or flaring. To catch the methane plume, stacked transects were flown downwind of single platforms or platform complexes.Methane fluxes were calculated for six British and four Dutch facilities using the mass balance method. Correlations with C2H6 and CO2 were found with the latter indicating partly combusted methane from flaring. Uncertainties of fluxes arise mainly due to uncertainty of the wind measurement and the plume height. The calculated fluxes were compared to emissions reported to inventories (UK National Atmospheric Emissions Inventory (NAEI), UK Environmental and Emissions Monitoring System database (EEMS), Scarpelli inventory (2016)) and individually reported emissions from Dutch operators.

Atmospheric methane (CH4) is an extremely potent greenhouse gas, with ever-increasing global emissions expected to have a significant influence on the Earth’s climate. The Oil and Gas sector is considered to be a significant source of CH4 to the atmosphere, estimated to make up approximately 22% of global emissions. Offshore facility emissions are poorly ground-truthed, with their quantification being heavily dependent on “bottom-up” scaling of inventory data. It is therefore important to devise reliable methods for locating these emissions and to pinpoint their sources, as this will aid emission quantification and validation against reported data.As part of the United Nations Climate and Clean Air Coalition (UN CCAC) project, this study aims to characterise CH4 emissions from oil and gas infrastructure in the Norwegian Sea. The campaign comprised surveys of selected operational oil and gas platforms in this region and included targeted observations of CH4. These surveys were conducted by the Facility of Airborne Atmospheric Measurements (FAAM) and Scientific Aviation Mooney research aircrafts in July and August 2019, with a total 14 flights. Fluxes are derived using a mass balance approach and aircraft sampling. The Lagrangian particle dispersion model “FLEXPART” is used to aid the attribution of the observed CH4 emissions to the platform(s). We will present results for derived fluxes and uncertainties for individual facilities in the Norwegian Sea. These fluxes will be compared with emissions estimates from platform operators, as well as a global, gridded emission inventory.

Emissions from fossil fuels are one of the primary sources of atmospheric methane (CH4) growth. However, estimates of anthropogenic CH4 emissions still show large uncertainties on global and regional scales. Differences in CH4 isotopic source signatures δ13C and δD can help to constrain different source contributions (e.g. fossil, thermogenic, or biogenic).The Upper Silesian Coal Basin (USCB) represents one of the largest European CH4 emission source regions, with more than 500 Gg CH4 yr-1 released by more than 50 coal mine ventilation shafts. During the CoMet (Carbon Dioxide and Methane Mission) campaign in June 2018 methane observations were conducted from a variety of platforms including aircraft and cars. Beside the continuous sampling of atmospheric methane concentration, numerous air samples were taken from inside the ventilation shafts, around the ventilation shafts (1‑2 km distance) and aboard the DLR Cessna Caravan aircraft and analyzed in the laboratory for the isotopic composition of CH4.The ground-based samples allowed determining the source signatures of individual ventilation shafts. These signatures displayed a considerable range between different shafts and also varied from day to day. The airborne samples contained a mixture of methane emissions from several mines and thus enabled accurately determining the signature of the entire region. The mean isotopic signature of methane emissions over the USCB derived from the aircraft samples was -51.9 ± 0.5 ‰ for δ13C and -233 ± 6 ‰ for δD. This is in between the range of other microbial and thermogenic coal reservoirs, but more depleted in δD than previous USCB studies reported based on samples taken within the mines. Signatures of methane enhancements sampled upwind of the mines and in the free troposphere clearly showed the presence of methane of biogenic origin (e.g. wetlands, waste, ruminants).Furthermore, we simulated the methane isotopologues using the on-line three-times nested global regional chemistry climate model MECO(n). We implemented a submodel extension, which includes the kinetic fractionation and uses the isotopic source signatures determined by the ground-based observations. We compare the regional simulations to flask samples taken during CoMet.

Methane (CH4) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO2). Because of its short atmospheric lifetime relative to that of CO2, the reduction of the atmospheric abundance of CH4 is an attractive target for short term climate mitigation strategies. However, reducing the atmospheric CH4 concentration requires a reduction of its emissions and, therefore, knowledge of its sources is essential. For this reason, the CO2 and Methane (CoMet) campaign in early summer of 2018 was initiated with the primary goal of assessing emissions of one of the largest CH4 emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this campaign, a variety of instruments (both in situ and remote sensing) and platforms (e.g., ground-based and airborne) were deployed, which were supplemented by modeling activities supporting the flight planning and the interpretation of the observations. Consequently, CH4 emissions originating from ~54 coal mine ventilation shafts distributed over an area of around 60 × 40 km2 could be investigated on different scales, ranging from single shafts over smaller clusters up to the entire basin. In this study, we will focus on CH4 column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) method. The column anomalies are combined with wind lidar measurements and inverted to cross-sectional fluxes for different flight tracks making use of a mass balance approach. These fluxes are subsequently used to assess the reported emissions of small clusters of ventilation shafts. The MAMAP CH4 column observations allow for accurate assignment of observed fluxes to small clusters of ventilation shafts. CH4 fluxes are estimated for 4 clusters comprising 23 ventilation shafts in total, which are responsible for about 40 % of the total CH4 emissions from mining in the target area. The observations used were made during multiple overflights on different days between 28 May and 7 June 2018. The final averaged CH4 fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH4 hr−1 at the time of the campaign. The range of fluxes observed at one cluster during different overflights can vary by as much as 50 % of the respective averaged value. Associated errors (1-σ) are usually between 15 % and 59 % of the averaged flux, mainly depending on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement with the computed fluxes within the uncertainties. In the case that only annually reported emissions are available for comparison with the observations, caution is required due to potential fluctuations of the emissions during one year or even within hours. To measure emissions even more precisely and to further unravel them for allocation to individual shafts in a complex source region as encountered in the USCB, imaging remote sensing instruments are recommended.

Abundant mining and industrial activities located in the Upper Silesian Coal Basin (USCB) lead to large emissions of the potent greenhouse gas (GHG) methane (CH4). The strong localization of CH4 emitters (mostly confined to known coal mine ventilation shafts) and the large emissions of 448 and 720 kt CH4 yr−1 reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) and the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2), respectively, make the USCB a prime research target for validating and improving CH4 flux estimation techniques. High-precision observations of this GHG were made downwind of local (e.g., single facilities) to regional-scale (e.g., agglomerations) sources in the context of the CoMet 1.0 campaign in early summer 2018. A quantum cascade–interband cascade laser (QCL–ICL)-based spectrometer adapted for airborne research was deployed aboard the German Aerospace Center (DLR) Cessna 208B to sample the planetary boundary layer (PBL) in situ. Regional CH4 emission estimates for the USCB are derived using a model approach including assimilated wind soundings from three ground-based Doppler lidars. Although retrieving estimates for individual emitters is difficult using only single flights due to sparse data availability, the combination of two flights allows for exploiting different meteorological conditions (analogous to a sparse tomography algorithm) to establish confidence on facility-level estimates. Emission rates from individual sources not only are needed for unambiguous comparisons between bottom-up and top-down inventories but also become indispensable if (independently verifiable) sanctions are to be imposed on individual companies emitting GHGs. An uncertainty analysis is presented for both the regional-scale and facility-level emission estimates. We find instantaneous coal mine emission estimates of 451/423 ± 77/79 kt CH4 yr−1 for the morning/afternoon flight of 6 June 2018. The derived fuel-exploitation emission rates coincide (±6 %) with annual-average inventorial data from E-PRTR 2017 although they are distinctly lower (−28 %/−32 %) than values reported in EDGAR v4.3.2. Discrepancies in available emission inventories could potentially be narrowed down with sufficient observations using the method described herein to bridge the gap between instantaneous emission estimates and yearly averaged inventories.

The densely farmed U.S. Midwest is a prominent source of nitrous oxide (N2O) but top‐down and bottom‐up N2O emission estimates differ significantly. We quantify Midwest N2O emissions by combining observations from the Atmospheric Carbon and Transport‐America campaign with model simulations to scale the Emissions Database for Global Atmospheric Research (EDGAR). In October 2017, we scaled agricultural EDGAR v4.3.2 and v5.0 emissions by factors of 6.3 and 3.5, respectively, resulting in 0.42 nmol m−2 s−1 Midwest N2O emissions. In June/July 2019, a period when extreme flooding was occurring in the Midwest, agricultural scaling factors were 11.4 (v4.3.2) and 9.9 (v5.0), resulting in 1.06 nmol m−2 s−1 Midwest emissions. Uncertainties are on the order of 50 %. Agricultural emissions estimated with the process‐based model DayCent (Daily version of the CENTURY ecosystem model) were larger than in EDGAR but still substantially smaller than our estimates. The complexity of N2O emissions demands further studies to fully characterize Midwest emissions., Plain Language Summary: Nitrous oxide (N2O) is the third most important anthropogenic greenhouse gas contributing to the warming of the planet and the dominant man‐made ozone‐depleting substance in the stratosphere. Its atmospheric concentrations have been rising since industrialization mainly due to an increase in anthropogenic sources, with agriculture being the dominant source. The densely farmed U.S. Midwest plays an important role in the global N2O budget. However, previous studies that have collected observations of N2O indicate that estimates of surface emissions in the Midwest are substantially underestimating the truth. In this study, we combine unique aircraft‐based N2O measurements and model simulations to quantify Midwest emissions in October 2017 and June/July 2019. Agricultural inventory estimates had to be increased by factors up to 20 to match observations, revealing a large underestimation in current inventories. An extreme flooding event in 2019 when the summer observations occurred may be responsible for some of this discrepancy. Estimations of soil N2O emissions calculated with a state‐of‐the‐art biogeochemical model show less underestimation but are still too low compared to the fluxes derived from the aircraft observational data., Key Points: Within the ACT‐America project, we gathered a unique airborne in‐situ N2O data set over the U.S. Midwest with enhancements up to 9 ppb. N2O emissions in the U.S. Midwest were on average 0.42 ± 0.28 nmol m−2 s−1 in October 2017 and 1.06 ± 0.57 nmol m−2 s−1 in June to July 2019. Bottom‐up estimates from EDGAR and DayCent underestimate U.S. Midwest N2O emissions by factors up to 20.

A severe reduction of greenhouse gas emissions is necessary to reach the objectives of the Paris Agreement. The implementation and continuous evaluation of mitigation measures requires regular independent information on emissions of the two main anthropogenic greenhouse gases, carbon dioxide (CO2) and methane (CH4). Our aim is to employ an observation-based method to determine regional-scale greenhouse gas emission estimates with high accuracy. We use aircraft- and ground-based in situ observations of CH4, CO2, carbon monoxide (CO), and wind speed from two research flights over the Upper Silesian Coal Basin (USCB), Poland, in summer 2018. The flights were performed as a part of the Carbon Dioxide and Methane (CoMet) mission above this European CH4 emission hot spot region. A kriging algorithm interpolates the observed concentrations between the downwind transects of the trace gas plume and then the mass flux through this plane is calculated. Finally, statistic and systematic uncertainties are calculated from measurement uncertainties and through several sensitivity tests, respectively. For the two selected flights, the in situ derived annual CH4 emission estimates are 13.8 ± 3.6 kg/s and 15.1 ± 3.0 kg/s, which is well within the range of emission inventories. The regional emission estimates of CO2, which were determined to be 1.21 ± 0.72 t/s and 1.12 ± 0.37 t/s, are in the lower range of emission inventories. CO mass balance emissions of 10.1 ± 3.2 kg/s and 10.7 ± 2.9 kg/s for the USCB are slightly higher than the emission inventory values. The CH4 emission estimate has a relative error of 21–26 %, the CO2 estimate of 33–60 %, and the CO estimate of 27–32 %. These errors mainly result from the uncertainty of atmospheric background mole fractions and the changing planetary boundary layer height during the morning flight. In the case of CO2, biospheric fluxes also add to the uncertainty and hamper the assessment of emission inventories. These emission estimates characterize the USCB and help to verify emission inventories and develop climate mitigation strategies.

Column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured by a solar viewing portable Fourier transform spectrometer (FTS, EM27/SUN) have been characterized and validated by comparison using in-situ profile measurements made during the transfer flights of two aircraft campaigns: Korea-United States Air Quality Study (KORUS-AQ) and Effect of Megacities on the Transport and Transformation of Pollutants on the Regional and Global Scale (EMeRGe). The aircraft flew over two Total Carbon Column Observing Network (TCCON) sites: Rikubetsu, Japan (43.46° N, 143.77° E) for the KORUS-AQ campaign and Burgos, Philippines (18.53° N, 120.65° E) for the EMeRGe campaign. The EM27/SUN was deployed at the corresponding TCCON sites during the overflights. The mole fraction profiles obtained by the aircraft over Rikubetsu differed between the ascending and the descending flights above approximately 8 km for both CO2 and CH4. Because the spatial pattern of tropopause heights based on potential vorticity values from the ERA5 reanalysis show that the tropopause height over the Rikubetsu site was consistent with the descending profile, we used only the descending profile to compare with the EM27/SUN data. Both the XCO2 and XCH4 derived from the descending profiles over Burgos were lower than those from the ascending profiles. Output from the Weather Research and Forecast Model indicate that higher CO2 for the ascending profile originated in central Luzon, an industrialized and densely populated region about 400 km south of the Burgos TCCON site. Air masses observed with the EM27/SUN overlap better with those from the descending aircraft profiles than those from the ascending aircraft profiles with respect to their properties such as origin and atmospheric residence times. Consequently, the descending aircraft profiles were used for the comparison with the EM27/SUN data. The EM27/SUN XCO2 and XCH4 data were derived by using the GGG2014 software in which air mass independent correction factors utilized for the TCCON data (0.9898 for XCO2 and 0.9765 for XCH4) were not applied. The comparison of the EM27/SUN observations with the aircraft data revealed that on average, the EM27/SUN XCO2 data were biased low by 1.22 % and the EM27/SUN XCH4 data were biased low by 1.67 %. The resulting air mass independent correction factors of 0.9878 for XCO2 and 0.9833 for XCH4 were obtained for the portable FTS.

The Upper Silesian Coal Basin (USCB) represents one of the largest European CH4 emission source regions, with a total sum of 500 Gg CH4/a released by individual coal mine ventilation shafts. During the CoMet (Carbon Dioxide and Methane Mission) campaign in late spring 2018, airborne in-situ measurements were carried out aboard the DLR research aircraft Cessna Caravan. The Cessna was equipped with a cavity ring-down and a quantum cascade laser system to measure CH4 and CO2, as well as related tracers such as CO and C2H6. Additionally, air samples were collected and analyzed for greenhouse and trace gases, including isotopic ratios of CH4 and CO2. Meteorological parameters were measured with a boom mounted sensor package.During nine research flights, CH4 emissions were studied by using an airborne Mass Balance Approach. Depending on the wind situation, different areas of the USCB region were targeted. To account for the lower part of the plume not accessible by the aircraft, a number of vans with mobile in-situ measurement systems conducted ground-based measurements in a coordinated manner. The derived methane emission estimate agrees well with bottom-up inventories like the Emission Database for Global Atmospheric Research (EDGAR) and the European Pollutant Release and Transfer Register (E‑PRTR). The CO2 emission estimate is at the lower end of the inventories. The CO emission estimate is higher than inventory values.From simultaneous methane and ethane measurement the emission ratios of different subregions of the USCB could be determined. The emission ratios range from 19 to 290 CH4/C2H6 and are, thus, quite variable within this coal basin. From the analysis of collected flask air samples the isotopic composition of CH4 emissions was determined. Isotopic signatures of Polish USCB CH4 emissions are between -52.7‰ and -49.4‰ for δ13C and between -241‰ and -178‰ for δD. Samples taken in the Czech part of the USCB had a δD isotopic ratio of around -309‰, hinting at a larger influence of biogenic sources in this region.

Methane is the second most important anthropogenic greenhouse gas. The globally averaged dry mole fraction has increased considerably since pre-industrial times and its growth even accelerated in 2014, with an annual rise of 12.7 ± 6 ppb. Fossil fuel emissions are one of the primary sources. However, the quantification of methane sources and sinks is still under debate and estimates of anthropogenic emissions show large uncertainties on global and regional scales. Comprehensive measurement campaigns, such as CoMet 1.0 (May-June 2018), are therefore important for assessing climate change mitigation options. CoMet aimed to quantify point source emissions in the Upper Silesian Coal Basin (USCB), where roughly 502 kt/yr of methane are emitted due to coal mining. Differences in isotopic methane source signatures δ13C and δD can further help to constrain different source contributions (e.g. thermogenic or biogenic). We simulate methane isotopologues from localized coal mine emissions in the USCB using the on-line three times nested global regional chemistry climate model MECO(n). We use a submodel extension, which includes the kinetic fractionation and make different assumptions on the isotopic source signatures in the USCB. Here we show first results of these simulations and a comparison to flask samples taken during CoMet 1.0.

Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO2) and methane (CH4). The total amount of urban GHG emissions, especially for CH4, however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital city Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC]2 project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20th enhancements of up to 4 ppm CO2 and 21 ppb CH4 were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO2 emission flux of 1.39 ± 0.75 t s-1 is in agreement with current inventories, while the CH4 emission flux of 5.20 ± 1.61 kg s-1 is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the high resolution numerical model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH4, which are treated differently by the emission inventories. Our work highlights the importance of a) strong CH4 sources in the surroundings of Berlin and b) a detailed knowledge of GHG inflow mixing ratios to suitably estimate emission rates.

During May and June 2018, the intensive campaign CoMet (Carbon dioxide and Methane mission) made atmospheric measurements of greenhouse gases over Europe, with the upper Silesian coal basin (USCB) in southern Poland as a specific focus area. CoMet aimed at characterising the distribution of CH4 and CO2 over significant regional sources with the use of a fleet of research aircraft, as well as to validate remote sensing measurements from state-of-the-art instrumentation installed on-board against a set of independent in-situ observations.In order to link atmospheric mixing ratios to source emission rates, high-resolution simulations with WRF-GHG v 3.9.1.1. (10 km x10 km Europe + nested 2 km x 2 km domain over the USCB), driven by short-term meteorological forecasts from the ECMWF IFS model and forecasts from CAMS (Copernicus Atmospheric Monitoring Service) for initial and lateral tracer boundary conditions were performed. Biogenic fluxes of CO2 were calculated online using the VPRM model driven by MODIS indices. Anthropogenic emissions over Europe were taken from the database of TNO, Department of Climate, Air and Sustainability (7 km x 7 km), augmented with an internal emissions database developed within CoMet that uses coal mine ventilation shaft emission measurements in combination with recent updates of the E-PRTR (European Pollutant Release and Transfer Register).Tagged tracers were used to simulate a robust set of over 100 distinct anthropogenic sources of CH4 and CO2 from the study area, and these forward simulations were then used as the transport operator in an analytical Bayesian inversion system. Here we discuss the results of an analysis performed with the use of selected in-situ data measured over the course of the three-week campaign, including results and sensitivity tests.

Halogenated very short-lived substances (VSLSs) are naturally produced in the ocean and emitted to the atmosphere. When transported to the stratosphere, these compounds can have a significant influence on the ozone layer and climate. During a research cruise on RV Sonne in the subtropical and tropical west Indian Ocean in July and August 2014, we measured the VSLSs, methyl iodide (CH3I) and for the first time bromoform (CHBr3) and dibromomethane (CH2Br2), in surface seawater and the marine atmosphere to derive their emission strengths. Using the Lagrangian particle dispersion model FLEXPART with ERA-Interim meteorological fields, we calculated the direct contribution of observed VSLS emissions to the stratospheric halogen burden during the Asian summer monsoon. Furthermore, we compare the in situ calculations with the interannual variability of transport from a larger area of the west Indian Ocean surface to the stratosphere for July 2000–2015. We found that the west Indian Ocean is a strong source for CHBr3 (910 pmol m−2 h−1), very strong source for CH2Br2 (930 pmol m−2 h−1), and an average source for CH3I (460 pmol m−2 h−1). The atmospheric transport from the tropical west Indian Ocean surface to the stratosphere experiences two main pathways. On very short timescales, especially relevant for the shortest-lived compound CH3I (3.5 days lifetime), convection above the Indian Ocean lifts oceanic air masses and VSLSs towards the tropopause. On a longer timescale, the Asian summer monsoon circulation transports oceanic VSLSs towards India and the Bay of Bengal, where they are lifted with the monsoon convection and reach stratospheric levels in the southeastern part of the Asian monsoon anticyclone. This transport pathway is more important for the longer-lived brominated compounds (17 and 150 days lifetime for CHBr3 and CH2Br2). The entrainment of CHBr3 and CH3I from the west Indian Ocean to the stratosphere during the Asian summer monsoon is lower than from previous cruises in the tropical west Pacific Ocean during boreal autumn and early winter but higher than from the tropical Atlantic during boreal summer. In contrast, the projected CH2Br2 entrainment was very high because of the high emissions during the west Indian Ocean cruise. The 16-year July time series shows highest interannual variability for the shortest-lived CH3I and lowest for the longest-lived CH2Br2. During this time period, a small increase in VSLS entrainment from the west Indian Ocean through the Asian monsoon to the stratosphere is found. Overall, this study confirms that the subtropical and tropical west Indian Ocean is an important source region of halogenated VSLSs, especially CH2Br2, to the troposphere and stratosphere during the Asian summer monsoon.

Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic methane sources. However, our knowledge about different sources and sinks of methane is still subject to great uncertainties. Comprehensive measuring campaigns, as well as reliable chemistry climate models, are required to fully understand the global methane budget and to further develop future climate mitigation strategies. The CoMet 1.0 campaign (May to June 2018) combined airborne in-situ, as well as passive and active remote sensing measurements to quantify the emissions from coal mining in the Upper Silesian Coal Basin (USCB, Poland). Roughly 502 kt of methane are emitted from the ventilation shafts per year. In order to help the campaigns flight planning, we performed 6-day forecasts using the on-line coupled, three times nested global and regional chemistry climate model MECO(n). We applied three nested COSMO/MESSy instances going down to a spatial resolution of 2.8 km over the USCB. The nested global/regional model system allows for the separation of local emission contributions from fluctuations in the background methane. Here we introduce the forecast setup and assess the model skill by comparing different observations with the individual forecast simulations. Results show that MECO(3) is able to simulate the observed methane plumes and the large scale patterns (including vertically integrated values) reasonably well. Furthermore we receive reasonable forecast results up to forecast day four.

Halogen- and sulfur-containing compounds are supersaturated in the surface ocean, which results in their emission to the atmosphere. These compounds can be transported to the stratosphere, where they impact ozone, the background aerosol layer, and climate. In this study we calculate the seasonal and interannual variability of transport from the West Indian Ocean (WIO) surface to the stratosphere for 2000–2016 with the Lagrangian transport model FLEXPART using ERA-Interim meteorological fields. We investigate the transport relevant for very short lived substances (VSLS) with tropospheric lifetimes corresponding to dimethylsulfide (1 day), methyl iodide (CH3I, 3.5 days), bromoform (CHBr3, 17 days), and dibromomethane (CH2Br2, 150 days). The stratospheric source gas injection of VSLS tracers from the WIO shows a distinct annual cycle associated with the Asian monsoon. Over the 16-year time series, a slight increase in source gas injection from the WIO to the stratosphere is found for all VSLS tracers and during all seasons. The interannual variability shows a relationship with sea surface temperatures in the WIO as well as the El Niño–Southern Oscillation. During boreal spring of El Niño, enhanced stratospheric injection of VSLS from the tropical WIO is caused by positive sea surface temperature anomalies and enhanced vertical uplift above the WIO. During boreal fall of La Niña, strong injection is related to enhanced atmospheric upward motion over the East Indian Ocean and a prolonged Indian summer monsoon season. Related physical mechanisms and uncertainties are discussed in this study. ©2018. American Geophysical Union. All Rights Reserved.

Oceanic very short-lived substances (VSLSs), such as bromoform (CHBr3), contribute to stratospheric halogen loading and, thus, to ozone depletion. However, the amount, timing, and region of bromine delivery to the stratosphere through one of the main entrance gates, the Indian summer monsoon circulation, are still uncertain. In this study, we created two bromoform emission inventories with monthly resolution for the tropical Indian Ocean and west Pacific based on new in situ bromoform measurements and novel ocean biogeochemistry modeling. The mass transport and atmospheric mixing ratios of bromoform were modeled for the year 2014 with the particle dispersion model FLEXPART driven by ERA-Interim reanalysis. We compare results between two emission scenarios: (1) monthly averaged and (2) annually averaged emissions. Both simulations reproduce the atmospheric distribution of bromoform from ship- and aircraft-based observations in the boundary layer and upper troposphere above the Indian Ocean reasonably well. Using monthly resolved emissions, the main oceanic source regions for the stratosphere include the Arabian Sea and Bay of Bengal in boreal summer and the tropical west Pacific Ocean in boreal winter. The main stratospheric injection in boreal summer occurs over the southern tip of India associated with the high local oceanic sources and strong convection of the summer monsoon. In boreal winter more bromoform is entrained over the west Pacific than over the Indian Ocean. The annually averaged stratospheric injection of bromoform is in the same range whether using monthly averaged or annually averaged emissions in our Lagrangian calculations. However, monthly averaged emissions result in the highest mixing ratios within the Asian monsoon anticyclone in boreal summer and above the central Indian Ocean in boreal winter, while annually averaged emissions display a maximum above the west Indian Ocean in boreal spring. In the Asian summer monsoon anticyclone bromoform atmospheric mixing ratios vary by up to 50 % between using monthly averaged and annually averaged oceanic emissions. Our results underline that the seasonal and regional stratospheric bromine injection from the tropical Indian Ocean and west Pacific critically depend on the seasonality and spatial distribution of the VSLS emissions.

During a cruise of R/V METEOR in December 2012 the oceanic sources and emissions of various halogenated trace gases and their mixing ratios in the marine atmospheric boundary layer (MABL) were investigated above the Peruvian upwelling. This study presents novel observations of the three very short lived substances (VSLSs) – bromoform, dibromomethane and methyl iodide – together with high-resolution meteorological measurements, Lagrangian transport and source–loss calculations. Oceanic emissions of bromoform and dibromomethane were relatively low compared to other upwelling regions, while those for methyl iodide were very high. Radiosonde launches during the cruise revealed a low, stable MABL and a distinct trade inversion above acting as strong barriers for convection and vertical transport of trace gases in this region. Observed atmospheric VSLS abundances, sea surface temperature, relative humidity and MABL height correlated well during the cruise. We used a simple source–loss estimate to quantify the contribution of oceanic emissions along the cruise track to the observed atmospheric concentrations. This analysis showed that averaged, instantaneous emissions could not support the observed atmospheric mixing ratios of VSLSs and that the marine background abundances below the trade inversion were significantly influenced by advection of regional sources. Adding to this background, the observed maximum emissions of halocarbons in the coastal upwelling could explain the high atmospheric VSLS concentrations in combination with their accumulation under the distinct MABL and trade inversions. Stronger emissions along the nearshore coastline likely added to the elevated abundances under the steady atmospheric conditions. This study underscores the importance of oceanic upwelling and trade wind systems on the atmospheric distribution of marine VSLS emissions.