Evaluating surface fluxes of CH4 using total column data requires models to accurately account for the transport and chemistry of methane in the free-troposphere and stratosphere, thus reducing sensitivity to the underlying fluxes. Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Atmospheric Infrared Sounder (AIRS) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite Thermal And Near Infrared for Carbon Observations (GOSAT TANSO, herein GOSAT for brevity). These retrievals, currently provided on a 5x4 (lon/lat) grid, have an uncertainty that ranges from 15 to 35 ppb but with peak sensitivity at 908 hPa and little sensitivity to the upper troposphere and stratosphere. These lower-tropospheric estimates can be compared to the surface network, and these comparisons show a similar error structure as the calculated uncertainties. The accuracy degrades with latitude such that we only use the initial version of these data for evaluating tropical methane fluxes. Using an analytical (Bayesian-based) flux estimation approach, We find these lower-tropospheric retrievals are almost directly sensitive to methane fluxes in S. America, Africa, and Asia, with degrees-of-freedom-for signal (DOFS) of these methane fluxes ranging from 0.7 to 0.9. Theoretical error reduction ranges from 30 to 70% for tropical wetland fluxes.

Sentinel-5P was successfully launched in October 2017 with on board its single payload instrument TROPOMI. TROPOMI is a push-broom spectrometer measuring various trace gases including methane (CH4). CH4 is the second most important anthropogenic greenhouse gas after CO2, but on a per molecule basis methane is a much more potent green house gas compared to CO2. In addition, because of its much shorter lifetime in the atmosphere, reduction of its emissions would provide quick short term benefit against climate change. This makes it an interesting target for climate change mitigation action which has been recognized by many policy makers. Moreover, in the oil and gas sector these emissions are effectively economic losses for industry and reducing CH4 ‘leaks’ thus also has a clear direct economic benefit for the industries involved.

The potential of detecting local sources of CH4 and quantifying its emissions from space has been demonstrated by studies using SCIAMACHY and GOSAT data. SCIAMACHY was the first to detect anomalous atmospheric CH4 levels from space related to leakages from the fossil fuel industry in the US, thereby showing these emissions were largely underestimated. With TROPOMI we aim to make a next step in this field as TROPOMI CH4 measurements have unprecedented high spatial resolution (7 x 7 km2) combined with daily global coverage and low measurement noise. In this presentation we will show a few CH4 local sources observed with TROPOMI including preliminary estimates of their emissions. These local sources include emissions from wetlands, emissions from Oil and Gas basins, and a major accidental well blowout at a Gas & Oil facility. The latter leakage, which lasted almost 3 weeks, was to - our knowledge - not ‘observed’ through any other atmospheric measurement thereby highlighting the importance of the space based observations by TROPOMI to detect such accidental leakages.

In order to improve our knowledge on emissions of the second most important anthropogenic greenhouse gas Methane (CH4) and to collect data for satellite data validation on local to regional scales, a coordinated measurement campaign in the Upper Silesian Coal Basin (USCB) in Poland, one of Europe’s anthropogenic CH4 hot spots, was executed. The 4 weeks campaign in May/June 2018 was carried out by a team of scientists deploying in-situ and remote sensing instruments on four aircraft as well as on ground. Two Cessna aircraft – one equipped with in-situ sensors for CH4 and related gases, another equipped with the CH4 remote sensing instrument MAMAP - concentrated on characterizing the CH4 distribution in the USCB with high horizontal and vertical detail. The German research aircraft HALO - equipped with the CH4 and CO2 detecting lidar CHARM-F, as well as with in-situ sensors – provided the larger scale picture about atmospheric CH4 distributions. In addition, a DO228 aircraft equipped with a HySpex hyperspectral sensor joined the campaign for a few days in order to try to detect CH4 anomalies over coal mine ventilation shafts. These aircraft based measurements were complemented by ground based observations: several ground-based FTIR instruments as well as wind lidars were deployed. In addition, in-situ measurements from mobile vans and small drones provide near-surface information of CH4. GOSAT and Sentinel-5P CH4 products will be compared with the ground-based and airborne data. In order to assess regional and local scale fluxes using the data set collected, a hierarchy of modelling approaches (mass balance/Gaussian plume modelling, regional inverse modelling, chemistry-climate modelling with regional refinement) will be used. The paper will present initial findings from the CoMet campaign with a focus on CH4 and steps towards the exploitation of the observations. The latter will include attempts to contribute to S5P validation.

Anthropogenic CO2 emissions from fossil fuel combustion have large impacts on climate. In order to monitor the increasing CO2 concentrations in the atmosphere, accurate spaceborne observations, as available from NASA’s carbon dioxide mission Orbiting Carbon Observatory-2 (OCO-2), are needed. Recently, direct methods, i.e. the methods that do not involve atmospheric inverse modeling, have been developed to study anthropogenic CO2 emissions using space-based observations. In this work, we present the XCO2 anomalies (Hakkarainen et al., 2016, 2018) calculated from OCO-2 observations, available since September 2014.

We show that the global XCO2 anomaly patterns are robust and consistent from year-to-year, and we compare these anomalies to model-simulated local concentration enhancements. We find that, despite the simplicity of the method, the anomalies describe the spatio-temporal variability of XCO2 consistently with more complex model-based approaches. We see, for example, that positive anomalies correspond to fossil fuel combustion over the major industrial areas (e.g., China, eastern USA, central Europe, India, and the Highveld region in South Africa), shown as large positive XCO2 enhancements in the FLEXPART model simulations. We also analyze model-simulated enhancements and OCO-2 anomalies together in several local “case studies.”

One large obstacle limiting the quantification of anthropogenic CO2 flux from space is the limited mapping capability of current satellite missions. For example OCO-2 provides measurements with eight 2.25 km long footprints along a narrow (less than 10 km) swath. In order to facilitate the detection of CO2 plumes, we also use data from the TROPOspheric Monitoring Instrument (TROPOMI), launched on October 13th 2017 on board of the Copernicus Sentinel-5 Precursor satellite. TROPOMI provides daily global coverage with a spatial resolution of 3.5 km × 7 km in nadir direction, and observes NO2, SO2 and CO, among other atmospheric parameters. We collocate TROPOMI and OCO-2 observations to detect anthropogenic CO2 sources and plumes. We calculate the local CO2 enhancements, and we analyze the NO2-to-CO2 ratio from individual plumes.

References
Hakkarainen, J., I. Ialongo, and J. Tamminen (2016), Direct space-based observations of anthropogenic CO2 emission areas from OCO-2, Geophys. Res. Lett., 43, 11,400–11,406, doi:10.1002/2016GL070885.

Hakkarainen, J., Ialongo, I., Maksyutov, S., and Crisp, D.: Global XCO2 anomalies as seen by Orbiting Carbon Observatory-2, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2018-649, in review, 2018.

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas and monitoring its emissions from space has become an important objective of (potential) future satellite missions such as the planned European Copernicus anthropogenic CO2 monitoring mission (CO2M) or NASA’s OCO-3 or GeoCarb mission.

CO2 is long lived and well mixed in the atmosphere. Globally, its natural gross fluxes are much larger than anthropogenic emissions. This makes it challenging to detect and analyze plumes of individual point sources in satellite measurements of the CO2 column-average dry-air mole fraction (XCO2).

In populated and industrialized areas, the largest part of tropospheric Nitrogen dioxide (NO2) originates from the co-emission with CO2 during the combustion of fossil fuels, e.g., by power plants, traffic, and domestic heating. NO2 has a short lifetime in the order of hours, so that its vertical column densities often exceed background levels by orders of magnitude near sources. This makes it a suitable tracer of recently emitted anthropogenic CO2, i.e. close to the source before the CO2 plumes blend into background concentrations.

In this presentation we use NO2 measurements made by the S5P (Sentinel-5 Precursor) satellite to help to locate the anthropogenic CO2 plumes in co-located XCO2 measurements of the OCO-2 (Orbiting Carbon Observatory 2) satellite, close to sources. Due to OCO-2’s narrow swath, it usually measures only a cross section of the plume. We estimate the cross sectional CO2 flux utilizing ECMWF ERA5 wind information and discuss the results and potential source attributions by taking into account the extended NO2 plume structures observable in S5P’s wide swath.

Strictly speaking, the plume cross sectional flux equals the source emission only under steady state conditions. Changes in wind speed, wind direction, or atmospheric stability in the time span between emission and satellite overpass may result in large deviations. Much better estimates of the source emissions will be possible with potential future satellite missions such as CO2M. This will allow imaging of larger plume structures with simultaneous NO2 observations from the same platform.

Specifically, we will present and discuss results for plumes emitted by, e.g., Moscow, South African power plants, Australian wildfires, and Nanjing. The main goal of our cross-sectional flux estimates are not highly accurate source emissions but to demonstrate the advantages of simultaneous NO2 and XCO2 observations, especially, as outlook to CO2M.

Carbon Dioxide (CO2) is a main anthropogenic greenhouse gas whose concentration increase leads to heating of the troposphere and subsequently to global warming. The well-developed ground-based networks either using remote sensing or in-situ technology provide highly accurate reference measurement but their coverage is too coarse to inform reliable on regional carbon fluxes. Satellite measurement of the total column CO2 from shortwave infrared hyperspectral measurement can provide highly accurate and precision measurements from space with sufficient coverage and resolution to improve the situation and help to advance out understanding of CO2 and carbon fluxes.
Following the European Space Agency (ESA) SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the ENVIronmental SATellite (ENVISAT), which is the first space-based instrument to provide SWIR CO2 band hyperspectral detection, the next generation satellites GOSAT and OCO-2 launched in 2009 and 2014, respectively. The Chinese carbon dioxide observation satellite (TanSat), which is the first Chinese greenhouse gas monitoring satellite and a ESA third party mission and has been supported by the Ministry of Science and Technology of China, the Chinese Academy of Sciences, and the China Meteorological Administration, was launched on 22 Dec 2016. A hyperspectral grating spectrometer onboard the TanSat is monitoring the column-averaged CO2 dry-air mixing ratio (XCO2) over the globe. In-orbit calibration tests were completed in the summer of 2017, and the performance of the instrument has since been evaluated in test sessions. Subsequent to on-board testing and calibration, TanSat has been operationally measuring backscattered sunlight in its scientific earth observation mode and produces XCO2 data for more than one year now.
The TanSat XCO2 retrieval algorithm is the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS), which has also been used for GOSAT (ATANGO) and OCO-2 retrieval studies. The University of Leicester (UoL) algorithm has been used for GOSAT retrieval and provide XCO2 product to the ESA Climate Change Initiative (CCI) and the Copernicus Climate Change Service. The retrieval accuracy and precision of both, the IAPCAS and UoL algorithm, has been well investigated by verifying them against TCCON measurement. In this presentation, we will introduce the application of the IAPCAS and UoL algorithms to TanSat XCO2 retrievals. The fitting residual has been analyzed, and PCA based analysis method show an improvement on residual. The approaches for aerosol and cirrus treatment have been inter compared and indicate that the methods adopted by both algorithms are reasonable to deal with the particle scattering. Validation against TCCON measurement show a well agreement on both algorithms.