Displays

Anthropogenic CO₂ and NO₂ emissions from combustion processes usually have the same sources but different emission ratios. Because of their similar sources, combustion emissions of CO₂ and NO₂ are correlated in space and time. Or in other words: combustion emissions of NO₂ will generally be accompanied by CO₂ emissions, and vice versa.

This concept can be used for converting satellite-based emissions of NO₂ into CO₂ emissions by multiplying known emission ratios of CO₂ over NO₂ from established emission databases with satellite-derived NO₂ emissions.

As part of the H2020 CHE project (“CO₂ Human Emissions”) we have applied this method to TROPOMI/S5P NO₂ emission data and “bottom-up” emission databases from Dutch TNO. TROPOMI/S5P emissions using the inversion algorithm DECSO were derived for the Iberian Peninsula in Europe and an area over South America.

We find that, after accounting for naturally occurring soil NO_x emissions, the spatial distribution of DECSO-TROPOMI based CO₂ emissions over the Iberian Peninsula and the South America region overall are very realistic, and within uncertainties CO₂ emissions budgets from both methods are not dissimilar.

We will also present and discuss some additional aspects and uncertainties of this ratio-method, including the influence of uncertainties in the TNO bottom-up emission database, like inter-country differences, and the relevance of applying emission ratios representative for the same time period as the TROPOMI/S5P measurements. We will also provide some recommendations for further improving this method.

Overall, at minimum this method appears to provide a “sanity check” for bottom-up (reported) CO₂ emissions, but potentially more than that, also evidenced by several new satellite mission proposals to combine direct measurements of CO₂ with direct measurements of NO₂ from the same satellite platform.

How to cite: de Laat, J. and van der A, R.: Deriving anthropogenic CO2 emissions for combustion by application of the emission-ratio method to TROPOMI/S5P NO2 emission data., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5535, https://doi.org/10.5194/egusphere-egu2020-5535, 2020.

Semi-arid ecosystems have been recognized as an important driver of interannual variability (IAV) in the growth rate of atmospheric CO2. However, the importance of these ecosystems for IAV in gross primary productivity (GPP) and net ecosystem exchange (NEE) over North America is not well characterized. In this study, we examine IAV over temperate North America using NEE constrained by surface-based and space-based atmospheric CO2 measurements over 2010–2015 and upscaled GPP from FluxSat over 2001–2017. We show that the arid west of North America provides a larger contribution to IAV in GPP and NEE than the more productive eastern half of North America. This occurs because flux anomalies in western North America are temporally coherent across the growing season leading to an amplification of GPP and NEE for wet years. In contrast, IAV in eastern North America shows seasonal compensation effects, wherein positive anomalies during April–June are compensated for by negative anomalies during July–September.

How to cite: Byrne, B., Liu, J., Bloom, A. A., Bowman, K., Butterfield, Z., Joiner, J., Keppel-Aleks, G., Parazoo, N., and Yin, Y.: Interannual variability in North American ecosystems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5966, https://doi.org/10.5194/egusphere-egu2020-5966, 2020.

The Orbiting Carbon Observatory 3 (OCO-3) was installed on the International Space Station (ISS) in May 2019 and will continue the observation of global CO₂ and solar-induced chlorophyll fluorescence (SIF) observations using the flight spare instrument from OCO-2. This talk will focus on the science data products, early operations, abd a few highlights from early mission data.

The low-inclination ISS orbit lets OCO-3 sample the tropics and sub-tropics across the full range of daylight hours with dense observations at northern and southern mid-latitudes (+/- 52º). The combination of these dense CO₂ and SIF measurements provides continuity of data for global flux estimates as well as a unique opportunity to address key deficiencies in our understanding of the global carbon cycle. The instrument utilizes an agile, 2-axis pointing mechanism (PMA), providing the capability to look towards the bright reflection from the ocean and validation targets. The PMA also allows for the collection of dense datasets over 80km by 80km areas called snapshot area maps (SAMs).

The in-orbit check out of the instrument was conducted through July 2019. In this phase the engineering team verified the performance of all systems, the calibration team began collecting the needed calibration data, and the mission operations team verified the performance of all measurement modes and the mission operations planning tools. Since August 2019, OCO-3 has been collecting routine nadir, glint, target, and SAM data.

Target mode observations over surface-based Total Carbon Column Observing Network (TCCON) sites help to identify and minimize potential instrument biases in the OCO-3 data. Other validation activities include direct comparisons to XCO₂ estimates from OCO-2 and comparisons to predictions from near-real-time models. These comparisons will be discussed and early results will be presented. In addition, several hundred SAMs have been collected over (mega-)cities, powerplants, volcanos, and other terrestrial carbon focus areas.  The steadily growing number of SAM observations provides a unique dataset for scientific studies on local scales. We discuss the potential of these observations, alone and in conjunction with simultaneous observations from other space-based sensors, to yield greater insights into carbon cycle science.

How to cite: Eldering, A., O’Dell, C., Somkuti, P., Taylor, T., Kiel, M., Nelson, R., Spiers, G., Fisher, B., Pavlick, R., Kurosu, T., Osterman, G., Laughner, J., Rosenberg, R., Keller-Rodrigues, G., Yu, S., Marchetti, Y., Crisp, D., and Wennberg, P.: An Overview of the First Year of the OCO-3 Mission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6225, https://doi.org/10.5194/egusphere-egu2020-6225, 2020.

Precise and accurate observations of anthropogenic greenhouse gases (GHGs), especially carbon dioxide (CO₂) and methane (CH₄), are of utmost importance for the estimation of their emission strengths, flux changes and long-term monitoring. Furthermore, these measurements can be directly used for the verification of climate mitigation actions as demanded by the Paris COP21 agreement. Satellite observations are well suited for this task as they provide global coverage. However, like all measurements these need to be validated, particularly to avoid potential biases. The Total Carbon Column Observing Network (TCCON) performs ground-based observations of GHGs with reference precision using high-resolution Fourier Transform infrared (FTIR) spectrometers. TCCON data are of high accuracy as TCCON uses species dependent scaling factors derived from in-situ reference measurements to be calibrated to the World Meteorological Organization (WMO) reference scale. For several satellites measuring GHGs TCCON data are the main validation source.

Recently, in an effort to further improve the global coverage of ground-based FTIR spectrometers and complement TCCON in remote areas, the COllaborative Carbon Column Observing Network (COCCON) was established. This network utilizes the EM27/SUN FTIR spectrometer, a compact solar-viewing low-resolution instrument. Even though a COCCON spectrometer has recently been used in combination with two TCCON instruments to validate the Orbiting Carbon Observatory-2 (OCO-2) satellite, until now the main focus of COCCON was on the quality control of EM27/SUN spectrometers and dedicated campaigns to estimate emission strengths of CO₂ and CH₄ from local and regional sources, e.g. from cities, fracking areas, volcanoes or mining sites.

Here we present long-term observations with a spectrometer from the COCCON network. In 2015 the instrument was installed at the Gobabeb Namib Research Center in Namibia. Gobabeb is located at the center of the hyperarid Namib desert. Moreover, Gobabeb is situated next to the Kuiseb river, which marks the sharp transition zone between the gravel plains to the north and the sand desert to the south of the station. This high albedo site is especially interesting for satellite validation, as ground-based FTIR data with these characteristics are sparse. Furthermore, it is the first ground-based FTIR instrument measuring CO₂ and CH₄ on the African mainland.

We show long-term COCCON observations from Gobabeb and compare them to results obtained from the TCCON instrument at Reunion Island. Finally, we present a comparison with target mode observations from the Greenhouse Gases Observation Satellite GOSAT.

How to cite: Frey, M., Blumenstock, T., Dubravica, D., Hase, F., Goettsche, F., Gross, J., Olesen, F., Amadhila, P., Handjaba, M., Maggs-Koelling, G., Marais, E., Mushi, R., Morino, I., Shiomi, K., de Maziere, M., and Sha, M. K.: Long-term column-averaged greenhouse gas observations using a COCCON spectrometer at a high surface albedo site in Namibia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6477, https://doi.org/10.5194/egusphere-egu2020-6477, 2020.

Validation opportunities for model data and satellite observations in the short-wave infra-red spectral range are still sparse above the oceans. To provide such opportunities, we qualify a Fourier-transform spectrometer (FTS) for the regular use on ships. We use the EM27/SUN FTS [1] in direct-sunlight measurement geometry to retrieve total column densities of carbon dioxide (CO₂), methane (CH₄), and carbon monoxide (CO) [2] with solar absorption spectroscopy.
Performing direct-sunlight measurements from a moving platform poses significant challenges to the solar tracking. We use a solar tracker that compensates the vessel's movements in real time, keeping the pointing of the instrument relative to the center of the sun better than 0.05° for more than 99 % of the time [3]. The solar tracker is part of a newly developed enclosure that allows automated measurements and withstands environmental factors such as rain, humidity, and sea spray.
The instrument was deployed on board the German research vessel RV Sonne during the MORE-2 (Measuring Oceanic REferences 2) campaign on a longitudinal transect from Vancouver (Canada) to Singapore in June 2019. During the campaign we recorded 33800 direct sunlight spectra from which column-averaged dry-air mole fractions of CO₂, CH₄, and CO are retrieved. Our results are calibrated against World Meteorological Organization standards and the columns achieve a relative precision of 0.06 %, 0.06 %, and 1.02 % for CO₂, CH₄, and CO, respectively.
We compare our records to coincident observations of the Greenhouse gases Observing SATellite (GOSAT), the Orbiting Carbon Observatory-2 (OCO-2), and the TROPOspheric Monitoring Instrument (TROPOMI). Our CO₂ records show a mean offset of -3.2 ± 1.1 ppm to OCO-2 and -1.4 ± 1.7 ppm to GOSAT observations. Furthermore, we find a mean CH₄ offset of 17 ± 6 ppb to GOSAT and a mean CO offset of 3.5 ± 2.6 ppb to TROPOMI. The Copernicus Atmosphere Monitoring Service (CAMS) provided us with model data of CH₄ and CO. We could show that the CO data agree well with our measurements, showing an offset of 3.5 ± 3.6 ppb.

[1] Gisi, M. et al.: XCO2-measurements with a tabletop FTS using solar absorption spectroscopy, Atmos. Meas. Tech., 5, 2969-2980, 2012
[2] Hase, F. et al.: Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements, Atmos. Meas. Tech., 9, 2303-2313, 2016
[3] Klappenbach, F. et al.: Accurate mobile remote sensing of XCO2 and XCH4 latitudinal transects from aboard a research vessel, Atmos. Meas. Tech., 8, 5023–5038, 2015

How to cite: Knapp, M., Kleinschek, R., Hemmer, B., Pfeifer, R., Hase, F., Agustí-Panareda, A., Inness, A., Barre, J., Kinne, S., and Butz, A.: Mobile ground-based remote sensing of atmospheric CO2, CH4, and CO column densities above the Pacific Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7345, https://doi.org/10.5194/egusphere-egu2020-7345, 2020.

Production of oil and natural gas in North America is at an all-time high due to the development and use of horizontal drilling and hydraulic fracturing. Methane emissions associated with this industrial activity are a concern because of the contribution to climate radiative forcing. We present new measurements from the space-based TROPOspheric Monitoring Instrument (TROPOMI) launched in 2017 that show methane enhancements over production regions in the United States. Using methane and NO₂ column measurements from the new TROPOMI instrument, we show that emissions from oil and gas production in the Uintah and Permian Basins can be observed in the data from individual overpasses. This is a vast improvement over measurements from previous satellite instruments, which typically needed to be averaged over a year or more to quantify trends and regional enhancements in methane emissions. In the Uintah Basin in Utah, TROPOMI methane columns correlated with in-situ measurements, and the highest columns were observed over the deepest parts of the basin, consistent with the accumulation of emissions underneath inversions. In the Permian Basin in Texas and New Mexico, methane columns showed maxima over regions with the highest natural gas production and were correlated with nitrogen-dioxide columns at a ratio that is consistent with results from in-situ airborne measurements. The improved detail provided by TROPOMI will likely enable the timely monitoring from space of methane and NO2 emissions associated with regular oil and natural gas production.

How to cite: Levelt, P., Veefkind, P., Roosenbrand, E., Lin, J., Landgraf, J., Dix, B., and de Gouw, J.: Daily Satellite Observations of Methane from Oil and Gas Production Regions in the United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11404, https://doi.org/10.5194/egusphere-egu2020-11404, 2020.

California has made reducing methane (CH₄) from its dairy industry, which accounts for nearly 50% of its inventoried CH₄ emissions, a key part of its climate change mitigation plan. However, in situ atmospheric measurement-based estimates suggest that the state-wide dairy source may be underestimated by up to a factor of 2.  Furthermore, emissions at the local scales important to mitigation policy (10’s km) are very uncertain. Ground based measurements of atmospheric column averaged methane concentrations (XCH₄) can provide useful constraints on local to regional methane fluxes. Additionally, the high spatial and temporal resolution XCH₄ observations by the space-based TROPOMI and GOSAT instruments provide an excellent opportunity to measure CH₄ fluxes at these scales. We report field measurements of XCH₄ gradients across the dairy intensive region (500 dairies, 330 Gg/yr CH4 emissions inventory) in the San Joaquin Valley (SJV) using two EM27/SUN solar spectrometers. With our EM27’s we observed several days of sustained downwind-upwind XCH₄ enhancements of over 40 ppb, placing these signals well above TROPOMI and GOSAT’s precision level and among the highest reported XCH₄ enhancements. We compare TROPOMI and GOSAT spatial XCH₄ enhancements to our EM27 data to validate it in an area of high signal and to demonstrate its utility for observing localized sources. We also use GOSAT and TROPOMI’s data to characterize the wider SJV’s CH₄ sources and to fill in temporal gaps between our field campaigns. Finally, we perform inverse optimizations using WRF-STILT simulations demonstrating that top-down observationally constrained dairy emissions are a factor of 2 larger than reported inventories.  This work illustrates how ground and space-based measurements can complement each other to improve our understanding of CH₄ sources at scales relevant to mitigation policy.

How to cite: Dubey, M. K., Heerah, S., Frausto-Vicencio, I., Jeong, S., Fischer, M., and Hopkins, F.: Observations of Methane Emissions from California Dairies from Ground and Space: New Top-Down Constraints at Regional Scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11747, https://doi.org/10.5194/egusphere-egu2020-11747, 2020.

In accordance with the Global stocktake under Article 14 of Paris Agreement, each county estimates its own greenhouse gas (GHG) emissions based on standardised bottom-up management methods. However, the accuracy of these methods along with the standards differs from country to country, resulting in large uncertainties that make it difficult to implement effective climate change mitigation strategies. India plays an important role in global methane emission scenario, necessitating the accurate quantification of its sources at the regional and the local levels. However, the country lacks sufficient long term, continuous and accurate observations of the atmospheric methane which are required to quantify its source, to understand changes in the carbon cycle and the climate system. Recent technological advancements in the use of satellite remote-sensing dedicated to the greenhouse gases enforce international standards for the observation methods; hence enabling those high-resolution-high-density observations to be utilised for this quantification purpose. This study focuses on exploring the use of such dedicated observations of the column-averaged dry-air mixing ratio of methane (XCH₄) retrieved from TROPOMI onboard Sentinel-5 Precursor to quantify the major CH₄ anthropogenic and natural emission fluxes over India.

Our inverse modelling approach at the mesoscale includes a high-resolution atmospheric modelling framework consisting of the Weather Research and Forecasting model with greenhouse gas module (WRF-GHG) and a set of prior emission inventory model data. We use TROPOMI retrievals derived using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm. WRF-GHG simulations are performed in hourly time intervals at a horizontal resolution of 10 km ×10 km for a month. In order to compare our CH₄ simulations with the satellite column data, we have also taken into account the different vertical sensitivities of the instrument by applying the averaging kernel to the model simulations. To demonstrate the model performance, our simulations are also compared with the CAMS reanalysis product based on ECMWF (European Centre for Medium-Range Weather Forecasts) numerical weather prediction reanalysis data available at a horizontal resolution of 0.25^o × 0.25^o. Our comparison of these modelling results against unique satellite dataset indicates high potential of using TROPOMI retrievals in distinguishing the major CH₄ anthropogenic and natural sources over India via inverse modelling. The results will help to objectively investigate the claims of emission reductions and the efficiency of reduction countermeasures, as well as the establishment of standards and advancement of technology. The details about our approach and preliminary results based on our analysis using above satellite measurements and WRF-GHG simulations over India will be presented.  

How to cite: Pillai, D., Deshpande, M., Marshall, J., Gerbig, C., Schneising, O., and Buchwitz, M.: Satellite-derived Indian methane emission sources with TROPOMI retrievals and a high-resolution modelling framework: Initial comparison with WRF-GHG model results, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12559, https://doi.org/10.5194/egusphere-egu2020-12559, 2020.

We use satellite observations of methane (CH₄) from the Japanese Greenhouse gases Observing SATellite (GOSAT) to study the temporal and spatial changes in Chinese CH₄ emissions from 2010 to 2017. We use v12.5.0 of the GEOS-Chem model of atmospheric chemistry and transport, driven by prior emission inventories, to describe observed variations of atmospheric CH₄. To infer fluxes from North, central, South, East, northeast, northwest and southwest China we use an established ensemble Kalman filter method in conjunction with the GEOS-Chem model. We find that annual nationwide CH₄ emissions decreased from 53 Tg in 2010 to 49 Tg in 2012, but then increased to 54 Tg in 2017. Emissions from eastern China represent the largest regional contribution to the nationwide total, accounting for 22%, while southern and northeast China each represent the smallest regional contributions of 7%. We find that emission trends of various regions are very different. Generally, regional CH₄ emissions are smallest during January and peak in July. We report a downward trend during Spring over southwest and southern regions but find no significant trend in northern and northwest China.  By analyzing the seasonal maximum and minimum values over each region, we find that annual mean trends are driven by changes in seasonal peak values, with no obvious trend in the seasonal minimum. We will discuss how changes in coal mine emissions may have impacted nationwide trends after 2013.

How to cite: Zhu, S., Feng, L., Palmer, P., and Liu, Y.: The distribution and trends in Chinese methane emissions, 2010-2017, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17662, https://doi.org/10.5194/egusphere-egu2020-17662, 2020.

The community has been measuring greenhouse gases from space for two decades, starting with SCIAMACHY and proceeding through GOSAT, OCO-2, TROPOMI, GOSAT-2, OCO-3, with many more to come in the future. The GeoCarb mission was selected in 2016 under the Earth Venture Mission program by NASA.  GeoCarb will measure CO2, CH4, and CO from geostationary orbit aboard a commercial communications satellite as a hosted payload starting in 2023.  In this presentation, we will discuss mission technical progress and program updates, including the recent passage into Phase C on Jan 1, 2020 and plans moving forward with integration and test and eventual launch.    Additionally, we will discuss plans for how best to proceed in this brave new world of a true constellation of greenhouse gas sensors, including cross-calibration and use of the data for flux determination.

How to cite: Crowell, S. and Moore, B.: The GeoCarb Mission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20213, https://doi.org/10.5194/egusphere-egu2020-20213, 2020.

Independent verification of reported carbon dioxide (CO2) emissions is a corner stone for advancing towards emission accounting and reduction measures agreed upon in the Paris agreement. Here, we present the concept and first performance assessment of a compact space-borne imaging spectrometer that could support the task of "monitoring, verification, reporting'' (MVR) of CO2 emissions worldwide. With a ground resolution of 50m x 50m, the goal is to estimate the CO2 emissions from localized sources down to a source strength of approx. 1 MtCO2/yr, hence complementing other planned CO2 monitoring missions, like the European Carbon Constellation (CO2M).

Such fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, a fleet of satellites, each carrying such an instrument is envisioned, requiring a relatively low-cost and simple design, e.g. by restricting the spectrometer to a single spectral window. To demonstrate that column-averaged dry-air mole-fractions of CO2 (XCO2) can be reliably retrieved with a single spectral window and at the required coarse spectral resolution, we use degraded GOSAT short-wave infrared spectra of the CO2 bands near 1.6 and 2.0 µm, respectively.

Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is further shown that an instrument noise error of 1.1 ppm (1sigma) can be achieved for the XCO2 retrieval. Despite the limited amount of information from a single spectral window and a relatively coarse spectral resolution, scattering by atmospheric aerosol and cirrus can be partly accounted for, with deviations of at most 4.0 ppm from the true abundance for 68 % of the scenes in the global trial ensemble.

Finally we simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban environment using high-resolution CO2 emission and surface albedo data for the city of Indianapolis. Given the preliminary instrument design and the corresponding instrument noise error, emission plumes from point sources with an emission rate down to the order of 0.3 MtCO2/yr can be resolved, i.e. well below the target source strength of 1 MtCO2/yr. Hence, some margin for additional error sources like scattering particles and complex meteorology exists.

How to cite: Strandgren, J., Wilzewski, J., Krutz, D., Paproth, C., Sebastian, I., Gurney, K., Liang, J., Roiger, A., and Butz, A.: Towards space-borne monitoring of localized CO2 emissions: an instrument concept and first performance assessment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19044, https://doi.org/10.5194/egusphere-egu2020-19044, 2020.

Scattering due to aerosols and cirrus has long been identified as one of main sources of uncertainties in retrieving XCO₂ from solar backscattered radiation. In this work, we investigate the added value of multi-angle polarimeter (MAP) measurements in the context of Copernicus candidate mission for anthropogenic CO₂ monitoring (CO2M). To this end, we compare aerosol-induced XCO₂ errors from standard retrievals using spectrometer only (without MAP) with those from retrievals using both MAP and spectrometer. MAP measures radiance and degree of linear polarization (DLP) simultaneously at multiple wavelengths and at multiple viewing angles; these observations are expected to provide information about aerosols that is useful for improving XCO₂ accuracy. Using an ensemble of 500 synthetic scenes over land, we show that the standard XCO₂ retrieval approach that makes no use of MAP observations returns XCO₂ errors with an overall bias of 1.04 ppm, and a spread (equivalent to standard deviation for a normal distribution) of 2.07 ppm. The latter is far higher than the required XCO₂ accuracy (0.5 ppm) and precision (0.7 ppm) of the CO2M mission. Moreover, these XCO₂ errors exhibit a significantly larger bias and scatter at high aerosol optical depth, high aerosol altitude, and low solar zenith angle, which suggest a worse performance in retrieving XCO₂ from polluted areas where CO₂ and aerosols are co-emitted. Given the CO2M mission requirements, we proceed to derive MAP instrument specifications in terms of measurement uncertainties, number of viewing angles, and the wavelength range. Two different MAP instrument concepts are considered in this requirement analysis. We find that for either concept, MAP measurement uncertainties on radiance and degree of linear polarization should be no more than 3% and 0.003, respectively. Adopting the derived MAP requirements, a retrieval exercise on the 500 synthetic scenes using both MAP and spectrometer measurements delivers XCO₂ errors with an overall bias of -0.09 ppm and a spread of 0.57 ppm, indicating compliance with the CO2M mission requirements. For the test ensemble, we find effectively no dependence of the XCO₂ errors on aerosol optical depth, altitude of the aerosol layer, and solar zenith angle. These results represent a significant improvement in the retrieved XCO₂ accuracy compared to the standard retrieval approach, which may lead to a higher data yield, better global coverage, and a more comprehensive determination of CO₂ sinks and sources. As such, this outcome underscores the contribution of, and therefore the need for, a MAP instrument onboard the CO2M mission.

How to cite: Rusli, S. P., Hasekamp, O., aan de Brugh, J., Fu, G., Meijer, Y., and Landgraf, J.: Anthropogenic CO2 monitoring satellite mission: the need for multi-angle polarimetric observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20532, https://doi.org/10.5194/egusphere-egu2020-20532, 2020.

Emissions of carbon dioxide (CO₂) will have to be drastically reduced in the coming decades to reach the goal of the Paris Agreement to limit the global temperature increase to no more than 2°C. To support this process, Europe is planning to establish a CO₂ anthropogenic emission monitoring system, which will assist countries, cities and facility operators in monitoring their emissions and evaluating the progress towards their reduction targets. The system will combine measurements from ground-based networks with observations from a new constellation of CO₂ satellites, which will provide high-resolution images of total column CO₂ allowing tracking the plumes of large emission sources. A suite of atmospheric transport modelling systems will assimilate these observations and inversely estimate emissions from the continental to the country scale and down to the scale of individual cities and power plants.

In the European project "CO₂ Human Emissions" (CHE), the components of such a modelling framework are explored, which includes the generation of a library of realistic atmospheric CO₂ simulations. These "nature runs" are obtained by running global and regional atmospheric transport models at the highest possible resolution affordable today and using state-of-the-art inputs of anthropogenic emissions and natural CO₂ fluxes. The library includes global simulations at 9 km x 9 km resolution with the CAMS-IFS model, European simulations at 5 km x 5 km resolution with WRF-GHG, COSMO-GHG and LOTOS-EUROS, and high-resolution simulations at 1 km x 1 km over the city of Berlin and several power plants with COSMO-GHG and LOTOS-EUROS.

Here we analyse and compare the model simulations to address the following questions: How realistically are atmospheric gradients in CO₂ caused by spatial and temporal variations in biospheric and anthropogenic fluxes and by atmospheric dynamics represented at the different model resolutions? What resolution is required to resolve the plumes of individual cities and power plants? How large are the differences in near surface and total column CO₂ due to uncertainties in atmospheric transport including uncertainties in vertical mixing? Information on transport uncertainties is derived from an ensemble of CAMS-IFS simulations and from the spread between the individual models.

Answering these questions is critical for the design of a future operational capacity to monitor anthropogenic CO₂ emissions, which should optimally support decision makers at facility, city, and country scale as well as the global stocktake process of the Paris Agreement.

How to cite: Brunner, D., Haussaire, J.-M., Marshall, J., Segers, A., Denier van der Gon, H., McNorton, J., and Agusti-Panareda, A.: Impact of model resolution and transport uncertainties on the representation of CO2 emission plumes by global and regional atmospheric transport models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10787, https://doi.org/10.5194/egusphere-egu2020-10787, 2020.

Pledges from nations and cities to reduce their carbon footprints have reinforced the needs for accurate and transparent reporting of fossil fuel emissions at various scales, with the ultimate goal of the establishments of carbon stocktake as defined by the Paris Agreement. But the assessment of anthropogenic emissions results primarily in collecting socio-economic indicators and emission factors, hence difficult to evaluate, track, or compare without a more standardized and robust methodology. Atmospheric measurements of greenhouse gases are of particular interests by offering an independent and global source of information thanks to satellite platforms observing continuously the atmospheric content of the major gases responsible for human-induced climate change.

Based on lessons learned from the NASA Orbiting Carbon Observatory (OCO)-2 mission, we present the potential of satellite-based approaches to monitor greenhouse gas emissions from large metropolitan areas across the world (Riyadh, Lahore, Los Angeles). After exploring the technical aspects and challenges of the approach, potential aerosol contamination (CALIPSO), and model requirements, we introduce the upcoming capabilities from the follow-up mission, OCO-3, dedicated in part to urban emissions with the Snapshot Area Mapping mode, the first imagery of atmospheric CO2 concentrations for hundreds of targeted cities and power plants. Early snapshots are examined with high-resolution simulations over a handful of cities. The ongoing development of assimilation systems to inform policy makers about current trends and inter-annual variations is presented and discussed. We finally examine the potential roles and objectives of satellite missions by exploring recent trends in fossil fuel emissions along with proxies of air quality (MODIS) as a unique opportunity to track not only greenhouse gas emissions but more generally the evolution of urban environments.

How to cite: Lauvaux, T., Feng, S., Lei, R., Oda, T., Danjou, A., Broquet, G., Schuh, A., Pavlick, R., and Elderling, A.: Urban fossil fuel CO2 emissions from space: lessons learned from the OCO missions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22158, https://doi.org/10.5194/egusphere-egu2020-22158, 2020.

Single-frequency solid-state lasers have important applications in laser remote sensing, such as Doppler lidar, differential absorption lidar (DIAL), gravitational wave detection and so on. In recent ten years, highly stable and narrow spectrum single-frequency Q-switched 1.6 μm lasers are widely applied in coherent Doppler wind detection liar and CH₄ DIAL. For applications in space-based wind lidar and DIAL, high output energy of the lasers is essential. In order to obtain a single-frequency laser with high energy, a common method is to inject a stable single-frequency seed laser into a high-energy Q-switched slave laser. Energy upconversion is the main factor which affects the energy enhancement of Er:YAG laser at 1.6μm. We report a Er:YAG ceramic single-frequency pulsed laser at 1645nm dual-end-pumped by two diode lasers with different wavelengths. Compared to a laser pumped by the two same wavelength diode lasers, the laser has higher slope efficiency because the energy upconversion is weakened. Otherwise, ceramic materials have many advantages compared with single crystals, such as ease of fabrication large-size ceramic material, short fabrication time, low cost and good thermo-mechanical properties. Uniform dopant can be realized in ceramic materials, which are much tougher and stronger than single crystals. All the advantages of ceramic materials mentioned above contribute to scalability to high energy laser. In this letter, we report a single frequency pulse ceramic laser with output energy of more than 10 mJ and pulse-width of more than 150 ns at a repetition rate of 500 Hz, which is pumped by two diode lasers with the wavelengths of 1470 nm and 1532 nm, respectively. This single-frequency pulse laser is a potential candidate as a seed laser for a slab laser amplifier system, which is an ideal source for space-based DIAL and Doppler wind lidar.

How to cite: Wang, L., Mao, Y., Lin, M., and Zhang, F.: Two diode lasers with different wavelengths resonantly pumped Er:YAG ceramic single-frequency laser, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21289, https://doi.org/10.5194/egusphere-egu2020-21289, 2020.

In this study, we apply the nonlinear least squares four-dimensional variational (NLS-4DVar) method to the retrieval of the column-averaged dry air mole fraction of carbon dioxide (X_CO2 ) from the Orbiting Carbon Observatory-2 (OCO-2) satellite observations. The NLS-4DVar method avoids the computation of the tangent linear and adjoint models of the forward model, which reduces the computational and implementation complexity greatly. We use the forward model from the Atmospheric CO₂ Observations from Space (ACOS) X_CO2 retrieval algorithm. The inverse model is constructed of two parts, generating samples and minimizing the cost function. For the CO₂ profile, we apply an improved sampling algorithm based on ensemble singular value decomposition (SVD). For the other elements in the state vector, we apply a sampling algorithm based on normal distributions, and values of standard deviations of normal distributions are vital to the accuracy of retrieval. To minimize the cost function, the NLS-4Dvar method rewrite it into a nonlinear least squares problem, and solve it by a Gauss-Newton iterative method. We have tested our method in summer and winter at four sites through observing system simulation experiments, which are Lamont, Bremen, Wollongong and an ocean site in the North Pacific respectively. All the four sites show an improved X_CO2 and CO₂ profile after the retrieval.

How to cite: Jin, Z. and Tian, X.: Carbon dioxide retrieval from OCO-2 satellite observations using the nonlinear least squares four-dimensional variational method: observing system simulation experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4109, https://doi.org/10.5194/egusphere-egu2020-4109, 2020.

TanSat is the 1^st Chinese carbon dioxide measurement satellite, launched in 2016. Preliminary TanSat XCO₂ retrievals have been introduced in previous studies based on the 1.6 m weak CO₂ band. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO₂ retrievals. We develop a spectrum correction method to reduce the retrieval errors by an online fitting of an 8^th order Fourier series. The model and a priori is developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O₂ A band retrieval. Accordingly, we extend the previous TanSat single CO₂ weak band retrieval to a combined O₂ A and CO₂ weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared. The same quality control parameters have been used in the bias correction due to the stronger correlation with the XCO₂ retrieval error. A footprint independent multiple linear regression is applied to determine the sounding XCO₂ retrieval error and bias correction. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach of the TanSat XCO₂ retrieval. We show that our new approach produces a significant improvement of the XCO₂ retrieval accuracy and precision when compared with TCCON with an average bias and RMSE of -0.08 and 1.47 ppm respectively. The methods used in this study, such as continuum correction, can help to improve the XCO₂ retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO₂ processing.

How to cite: Boesch, H., Yang, D., Liu, Y., and Somkuti, P.: Toward high precision XCO2 retrievals from TanSat observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17522, https://doi.org/10.5194/egusphere-egu2020-17522, 2020.

The Japanese Greenhouse gases Observing SATellite (GOSAT), in orbit since January 2009, and its successor GOSAT-2, in orbit since October 2018, are dedicated to enhancing our knowledge of the carbon cycle. We use our RemoTeC full-physics algorithm to infer atmospheric concentrations and auxiliary parameters from the measured solar SWIR radiances backscattered at the earth´s atmosphere and surface. Accuracy requirements are a major challenge for these space-based measurements of column-averaged dry-air mole fractions of carbon dioxide and methane (XCO₂ and XCH₄).

Here we present 1) a consolidated ten years GOSAT XCO₂ and XCH₄ dataset and 2) first results for GOSAT-2 XCO₂ and XCH₄ retrievals. For GOSAT, 4.8 % of all measurements pass our cloud filter, based on the O₂ A-band signal and several quality filters. For validation and bias-correction, we use collocated measurements from ground-based stations of the Total Carbon Column Observing Network (TCCON). The dataset shows a scatter of well below 1 %. For GOSAT-2, we are able to reliably process measurements in land nadir and ocean glint geometry. In addition to the retrieval windows implemented for GOSAT, we use the spectral ranges at 4290 - 4328 cm^-1 and 4354 - 4441 cm^-1 to retrieve carbon monoxide and nitrous oxide concentrations. We evaluate instrument performance and precision by comparing XCO₂ and XCH₄ retrievals to both collocated GOSAT and ground-based TCCON measurements.

How to cite: Haun, M., Suto, H., and Butz, A.: Carbon dioxide and methane RemoTeC retrievals from GOSAT (2009-2019) and GOSAT-2 (2019), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4612, https://doi.org/10.5194/egusphere-egu2020-4612, 2020.

Precise knowledge of sources and sinks in the carbon cycle is desired to understand
its sensitivity to climate change and to account and verify man-made emissions. An
important role herein play extended sources like urban areas. While in-situ measure-
ments of carbon dioxide (CO₂) and methane (CH₄) are highly accurate but localized,
satellites measure column-integrated concentrations over an extended footprint. Our
innovative measurement technique aims at determining CO₂ and CH₄ concentrations
near to the ground on the scale of a few kilometers and therefore fills the sensitivity
gap between in-situ and satellite measurements.
Using a modified EM27/SUN Fourier transform spectrometer we are able to record
spectra of surface scattered sunlight in the range of 4000 − 11000 cm⁻¹ . To accurately
retrieve CO₂ and CH₄ concentrations an advanced retrieval method is required that
includes the simultaneous estimation of atmospheric scattering properties.
Based on our radiative transfer and retrieval software RemoTeC, we built a simulation
environment that includes atmospheric scattering processes. With this tool we can
generate and retrieve synthetic scattered light observations. Here we present our
simulation environment, first results and ongoing developments.

How to cite: Proß, C., Hemmer, B., Wellmann, C., Kostinek, J., and Butz, A.: Toward CO2 and CH4 measurements by ground based observations of surface-scattered sunlight: Radiative transfer modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3576, https://doi.org/10.5194/egusphere-egu2020-3576, 2020.

How to cite: Wellmann, C., Proß, C., Bigge, K., and Butz, A.: A model setup for simulations of ground-based scattered sunlight measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5342, https://doi.org/10.5194/egusphere-egu2020-5342, 2020.

How to cite: Hemmer, B., Holzbeck, P., Kleinschek, R., Knapp, M., Kostinek, J., Müller, R., Proß, C., Hase, F., and Butz, A.: Toward CO2 and CH4 measurements by ground-based observations of surface-scattered sunlight: Instrumentation and experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7479, https://doi.org/10.5194/egusphere-egu2020-7479, 2020.

Quantifying sources and sinks, as well as photochemical activity of trace gases in the lower troposphere, requires accurate measurements of the concentrations of the species of interest. While there exist in-situ measurement techniques, which are highly accurate, point-like measurements tend to suffer from insufficient representativeness, especially true for high-gradient environments, e.g., an urban setting. Hence, measuring those concentrations averaged on the length scales of a few kilometers is desirable. Further, quantifying emissions requires combining the concentration measurements with regional transport models, which cover a comparable spatial resolution.

Here, we present a long open-path setup that aims at delivering concentration averages on these scales in the urban boundary layer. Our setup is based on an IFS 125 HR Fourier transform spectrometer, which is a commercially available, high precision spectrometer for the IR to near UV regime. We use an artificial light source, which is modulated within the interferometer of the instrument. The modulated beam is then sent towards an array of retro-reflectors 1.5 km away. Sending of the initial beam and collecting of the reflected light is accomplished by a single telescope, which is coupled to the instrument via an optical fiber. The collected light is measured using an InGaS detector. In a first feasibility study, we aim at measuring CO₂ and CH₄ above Heidelberg to quantify the achievable precision and accuracy. Here we present our setup, first measurements, and ongoing developments.

How to cite: Schmitt, T., Kleinschek, R., Batzler, D., Schmitt, S., Hase, F., Griffith, D. W. T., and Butz, A.: Towards long open-path FTIR spectrometry of CO2 and CH4 in an urban environment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7547, https://doi.org/10.5194/egusphere-egu2020-7547, 2020.

The Orbiting Carbon Observatory-3 (OCO-3) was successfully launched on May 4, 2019 from Kennedy Space Center via a Space-X Falcon 9. One week later, the instrument was installed as an external payload on the International Space Station (ISS). OCO-3 extends NASA’s study of carbon and measures the dry-air mole fraction of column carbon dioxide (XCO2) in the Earth’s atmosphere from space.

These space-based measurements are compared to ground-based observations from the Total Carbon Column Observing Network (TCCON). TCCON is a global network of high-resolution ground-based Fourier Transform Spectrometers that records spectra of the sun in the near-infrared spectral region. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2 are retrieved. TCCON data are tied to the WMO scale and serve as the link between calibrated surface in situ measurements and OCO-3 measurements.

OCO-3’s agile 2-D pointing mirror assembly (PMA) allows the instrument to stare at a TCCON station as it passes overhead - providing information about the quality, biases, and errors in the OCO-3 data. Here, we show early comparisons between the OCO-3 XCO2 dataset collected during target mode observations and coincident TCCON measurements and discuss site-dependent biases and its potential origins.

How to cite: Kiel, M., Laughner, J., Eldering, A., Fisher, B., Kurosu, T., Pavlick, R., Osterman, G., Nelson, R., O'Dell, C., Somkuti, P., Taylor, T., and Roehl, C.: Early Comparison of OCO-3 XCO2 Measurements with TCCON , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9844, https://doi.org/10.5194/egusphere-egu2020-9844, 2020.

During 2016 and again during 2019 through 2020 an EM27/SUN portable near infrared solar absorption Fourier Transform Spectrometer of the Karlsruhe Institute of Technology was transported first to Lauder, New Zealand (45.034S, 169.68E, alt. 370 m) and then to the Arrival Heights laboratory, Ross Island Antarctica (77.82S, 166.65E, 200 m). On the first occasion the EM27/SUN made the first ever near infrared solar absorption retrievals of carbon dioxide and methane in Antarctica over a period of two weeks. The second deployment had the aim of making retrievals in Antarctica throughout the 2019-2020 Austral summer.

We report on the comparison of retrievals of carbon dioxide and methane from the EM27 spectra with those made by the Total Carbon Column Observing Network (TCCON) stations at both Karlsruhe and Lauder and compare with similar comparisons made throughout the Collaborative Carbon Column Observing Network (COCCON), as well as the latitudinal extension of these measurements to Antarctica.

Further comparisons with observations from TROPOMI instrument on the Sentinel 5 precursor satellite will be discussed.

How to cite: Pollard, D. F., Smale, D., Tran, H., McGaw, J., Hase, F., and Blumenstock, T.: Travels with an EM27, measurements of CO2 and CH4 below 45 degrees south., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12628, https://doi.org/10.5194/egusphere-egu2020-12628, 2020.

Carbon dioxide and methane column measurement at the Finnish Meteorological Institute’s Sodankylä facility in northern Finland started in early 2009. The measurements have been taken by a Fourier Transform Spectrometer (FTS) in the near-infrared spectral region. From the spectra column-averaged abundances of CO₂, CH₄ and other gases are derived. The instrument participates in the Total Carbon Column Observing Network (TCCON).  Here we present long-term ground based FTS measurements of carbon dioxide and methane and comparisons with satellite borne observations. We find that CO₂ column amounts have increased by 2.2 ± 0.1 ppm/year since the start of the measurements in 2009 and CH₄ column amounts have increased by 7 ± 0.4 ppb/year. The measurements are in good agreement with multi-year measurements by the Greenhouse Gases Observing Satellite (GOSAT): the relative difference in XCH₄ has been -0.07 ± 0.02 % and the relative difference in XCO₂ has been 0.04 ± 0.02 %. Finally we use balloon borne AirCore observations at the Sodankylä site to provide comparisons between FTS and in situ observations during all seasons.

How to cite: Kivi, R., Chen, H., Hatakka, J., Heikkinen, P., Laurila, T., and Lindqvist, H.: Atmospheric Carbon Dioxide and Methane measurements at Sodankylä, Finland , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13106, https://doi.org/10.5194/egusphere-egu2020-13106, 2020.

Atmospheric CO₂ growth rate is the primary driver of the global warming and a valuable indicator of the interannual changes in carbon cycle. We broaden the knowledge about temporal and spatial variations of annual CO₂ growth (AGR) by using CO₂ observations from the Total Column Observing Network (TCCON), CO₂ simulations from Carbon Tracker (CT) and Copernicus Atmospheric Monitoring System (CAMS) models together with the global-scale AGR references from Global Carbon Budget (GCB) and satellite data (SAT) for 2004-2019 years. TCCON and the CO₂ models reveal temporal AGR variations (AGR_TCCON = 1.71 – 3.35 ppm, AGR_CT = 1.59 – 3.30 ppm, AGR_CAMS = 1.66 – 3.13 ppm) of the similar magnitude to the global-scale CO₂ growth references (AGR_GCB = 1.59 – 3.23 ppm, AGR_SAT = 1.55 – 2.92 ppm). However, TCCON estimates of global AGR agree well with the referenced AGR growth only during the 2010s since the network has considerably improved its spatial coverage after 2009. Moreover, TCCON-based AGRs reasonably agree (r = 0.67) with strength of El Nino Southern Oscillations (ENSO) in the 2010s. The highest atmospheric CO₂ growth (2015-2016) driven by the very strong El-Nino event is accurately reproduced by TCCON that provided AGR of 2015-2016 years (3.29 ± 0.98 ppm) in very close agreement to the SAT reference (3.23 ± 0.50 ppm). We validate CAMS and CT simulations of AGR versus the newly-acquired TCCON-based AGR (as the point-location reference) for an every single TCCON site and low agreement (r < 0.50) is evidenced only at 3 out of 20 stations. This minor caveat has not affected the accuracy of simulated global AGR since it exhibits high agreement with SAT, GCB (r = 0.74 – 0.78) and TCCON (r > 0.65) references at global scales. Moreover, the correlation of AGR simulations across all grid cells (3 x 2 degree) between CAMS and CT is nearly perfect (r = 0.95) for the modeling period (2004-2016). Similarly, land-wise AGR intercomparison between CAMS and CT yields in perfect correlation (r ≧ 0.90) for 15 out of 20 MODIS land classes where the least vegetated areas exhibit the highest agreement. From spatial perspective, the highest AGR estimates (> 20% from the median value) are observed in the regions with intense combustion (East Asia) or with frequent biomass burning (Amazon, Central Africa). The slight disagreement of AGR spatial variability simulated by CT and CAMS is likely driven by the latter two regions of SH where drier conditions during El-Nino events allegedly increase the probability for divergence between the models. In overall, the current estimates of global AGR are consistent across a wide range of the data sources and strengthening of CO₂ observational infrastructure should further improve the accuracy of AGR estimates on global and fine spatial scales.

How to cite: Labzovskii, L., Takele Kenea, S., Kim, J., Byun, Y.-H., Goo, T.-Y., Lee, H., Li, S., and Oh, Y.-S.: Temporal and Spatial Variations of Atmospheric CO2 Growth reproduced by Ground-Based Remote Sensing and CO2 Inverse Modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6398, https://doi.org/10.5194/egusphere-egu2020-6398, 2020.

Methane (CH4) is the most important anthropogenic greenhouse gas after carbon dioxide, and it keeps increasing globally since 2007 after a period of relative stability, which is well-documented by surface measurements and satellites. Although satellites provide long-term global observations of CH4, the interpretation of column-averaged mixing ratios (xCH4) is difficult due to the influence of elevated terrains (i.e. mountain areas) and less abundant methane in the stratosphere. The lack of data over the ocean further limits global insights. Here we build a long-term global CH4 data set at a resolution of 0.25° × 0.25°  from SCIAMACHY, including the areas over the ocean, with the help of FRESCO cloud data. We dynamically consider the influence of elevations and contributions from the stratosphere through converting xCH4 to tropospheric xCH4 (trop_xCH4) by applying the daily ratios of tropospheric to stratospheric xCH4 in GEOS-Chem model.

The large increases occur in Trop_xCH4 over the source regions and mountain areas. The trend of SCIAMACHY Trop_xCH4 over the global ocean is comparable to the trend of NOAA globally averaged marine monthly mean data, showing the capability of SCIAMACHY in monitoring the ocean. After removing the latitudinally independent background concentration based on SCIAMACHY data over the ocean, we quantify the regional sources. A significant trend in Trop_ xCH4 relating to the background in Eastern China, India, tropical Africa, and tropical South America is further found from 2003 to 2011. 

How to cite: Liu, M., Van der A, R., Tan, H., Frankenberg, C., Aben, I., Kong, H., Sun, J., Ding, J., and Zhang, L.: Quantify the regional methane emissions based on a new SCIAMACHY data set, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5341, https://doi.org/10.5194/egusphere-egu2020-5341, 2020.

Atmospheric CO₂ measurement has proven its appositeness for different applications in carbon cycle science. Many satellites are currently measuring the atmospheric CO₂ concentration worldwide, for example, NASA’s Orbiting Carbon Observatory-2 (OCO-2), Exploratory Satellite for Atmospheric CO₂ (TanSat), Japanese Greenhouse gases Observing SATellite (GOSAT), and Environmental Satellite (ENVISAT). The OCO-2 measures the column-averaged CO₂ dry air mole fractions (XCO₂) in the atmosphere as contiguous parallelogram footprints, each having area up to about 3 km². The problem associated with this measurement is its narrow swath of approximately 10.6 km width which results in limited spatial coverage.

A number of research works have been reported to spatially map the available XCO₂ samples on a regional scale or globally in different temporal scale and spatial resolution. Kriging, a family of geostatistical interpolation method, has been a popular choice for this mapping. In our recent research, we have shown that the univariate kriging methods are not able to produce a pragmatic surface of XCO₂ and require the incorporation of more covariates. We have studied the OCO-2’s XCO₂ observations and mapped them on a regional scale including multiple covariates, such as Open-source Data Inventory for Anthropogenic CO2 (ODIAC) and the Emissions Database for Global Atmospheric Research (EDGAR) emission estimates and land use and land cover (LULC) information. It is observed that the inclusion of these covariates is able to produce more accurate mapping compared to their baseline alternatives.

However, the CO₂ concentration is usually highly influenced by the transportation of the emission particles through the wind. A larger temporal measurement window may ignore its effect by assuming that the wind direction is constantly changing. However, for regional mapping of space-borne XCO₂ in a time instance, it is essential to model. This work has developed a novel multivariate kriging-based framework to map OCO-2’s XCO₂ measurements including Stochastic Time-Inverted Lagrangian Transport-(STILT)-based atmospheric transport modeling. This model could be coupled with the biospheric flux models and emission estimates to map their local scale distributions.

In this framework, every unmeasured location that is required to be estimated is considered as the receptor point in the STILT simulation. The emission particles are tracked backward in time from each of these receptor points to simulate possible routes from their upstream locations. A footprint map is then generated which is regarded as the influence of other points to the receptor point in the whole study region. The footprint map, being combined with the emission estimates, will produce a prior CO₂ concentration map. This STILT-generated prior concentration map is inserted into the multivariate kriging framework. The output map, i.e., the interpolated XCO₂ surface is more pragmatic to include the influence of atmospheric transport for the prediction of XCO₂. The accuracy of the framework is proven by comparing the estimated data with ground-based measurements. This work is one of the initial attempts to generate a Level-3 XCO₂ surface on a local scale by combining STILT with a multivariate kriging method.

How to cite: Bhattacharjee, S., Chen, J., Jindun, L., and Zhao, X.: Kriging-based Mapping of Space-borne CO2 Measurements by Combining Emission Inventory and Atmospheric Transport Modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10076, https://doi.org/10.5194/egusphere-egu2020-10076, 2020.

International agreements to reduce CO2 emissions call for an independent mechanism for evaluating the compliance with emission reduction targets. Atmospheric measurements can provide important information in support of this goal. However, to do this globally requires a drastic expansion of the existing monitoring network, using a combination of surface measurements and satellites. CO2 sensing satellites can deliver the required spatial coverage, filling in the gaps that are difficult to cover on ground. However, to reach the accuracy that is required for monitoring CO2 from space is a challenge, and even more so for anthropogenic CO2.

The European space agency is preparing for the launch of a constellation of satellites for monitoring anthropogenic CO2 within the Copernicus program, starting in 2025. Scientific support studies have been carried out to define this mission in terms of payload and observational requirements. We report on the AeroCarb study, which investigated the impact retrieval errors due to aerosols in CO2 plumes downwind of large cities, and the potential benefit of an onboard aerosol sensor to help mitigate such errors. In this study, CO2 and aerosol plumes have been simulated at high-resolution for the cities of Berlin and Beijing. The impact of aerosol scattering on spaceborne CO2 measurements has been assessed using a combined CO2-aerosol retrieval scheme, with and without the use of an onboard multi-angular spectropolarimeter (MAP) for measuring aerosols. The results have been used to quantify the accuracy at which the CO2 emissions of Berlin and Beijing can be quantified using inverse modelling and the impact of aerosols depending on the chosen satellite payload. 

In this presentation we summarize the outcome of this study, and discuss the implications for the space borne monitoring of anthropogenic CO2 emissions from large cities.

How to cite: Houweling, S., Landgraf, J., Reum, F., van Heck, H., Tao, W., Cheng, Y., Vlemmix, T., and Stammes, P.: Spaceborne monitoring of CO2 emissions from large cities and the impact of aerosols, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20599, https://doi.org/10.5194/egusphere-egu2020-20599, 2020.

The TROPOspheric Monitoring Instrument (TROPOMI) is the satellite instrument on board the Copernicus Sentinel-5 Precursor satellite launched on 13 October 2017.  Data products include column estimates of ozone, nitrogen dioxide, methane, carbon monoxide, among others, and feature unprecedent high spatial resolution. These new data products provide opportunities to gain detailed insights into emissions and their sources on scales previously not feasible. We present results from five student teams investigating TROPOMI observations in a semester-long statistical and machine learning analysis practicum under the joint guidance of an atmospheric scientist and statistician. The analysis follows agile practices, where initial results inform the next analysis step. The focus is on the United States, specifically the investigation of methane emissions from natural gas production in key geological basins.

How to cite: Hammerling, D., Blake, L., Daniels, W., Dykstal, A., and Crowell, S.: Student-led investigation of TROPOMI data for the US, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22133, https://doi.org/10.5194/egusphere-egu2020-22133, 2020.

We examine CH₄ variability over different regions of India and the surrounding oceanic regions using thermal infrared (TIR) band observations by the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observation SATellite (GOSAT) and simulated by the updated MIROC4.0-based Atmospheric Chemistry Tracer Model (ACTM) for the period 2009-2014. GOSAT TIR provides data coverage and density captures detailed features of CH₄ distributions at height levels from the top of the boundary layer to the upper troposphere even in the cloudy conditions, which is very common for the region with a monsoon climate. Analysis of transport and emission contributions to CH4 variabilities suggests that the CH₄ seasonal cycle over India is controlled by the heterogeneous distribution of surface emissions under the influence of the monsoonal divergent wind circulations. Distinct seasonal variations of CH₄ are observed over northern and southern regions of India corresponding to the southwestern monsoon (July–September) and early autumn (October–December) seasons. In summer, three principal circulations pumping CH₄ upward over South Asia: the lateral (the cross-equatorial circulation) and transverse (flows between the arid regions of North Africa and the Near East and South Asia) monsoons, and the Walker Circulation extends across the Pacific Ocean. GOSAT TIR derives CH₄ profiles due to retrieval of signal from 22 vertical levels. In general, the mean ACTM (no averaging kernel incorporated)-GOSAT misfit is within 50 ppb, excepting the level of 150 hPa and upward, where the GOSAT TIR sensitivity becomes too low. Due to the use of MIROC4.0 AGCM performance of ACTM in the upper troposphere and lower stratosphere has been improved. The GOSAT-ACTM misfit above the level of 150 hPa is likely to arise from a priori model for TIR retrievals. Convolution of the modeled profiles with retrieval a priori and averaging kernels reduces the misfit to below uncertainty. However, the weight of the a priori profiles becomes too large with such smoothing. Overall, the ACTM simulations of CH₄ in the Indian regions compare favorably with the GOSAT TIR samplings, in terms of seasonality and regional variability. However, the GOSAT-ACTM inconsistencies indicate opportunities for further flux optimization and emission uncertainty reduction by inverse modeling methods.

How to cite: Belikov, D., Saitoh, N., K. Patra, P., and Chandra, N.: CH4 variability over India derived from the GOSAT/TANSO-FTS TIR observations and simulated by MIROC4-ACTM model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11936, https://doi.org/10.5194/egusphere-egu2020-11936, 2020.

Tropical wetlands have been proposed as a potential driver for the recent rise in global atmospheric methane. However, direct access and quantification of emissions is difficult. In March 2019, a pilot study was given permission to overfly the Bolivian Llanos de Moxos wetlands to measure atmospheric mixing ratios of methane and collect spot samples for isotopic analysis. Combined with this was a short ground campaign to collect isotopic samples directly above the wetland edge to compare with the integrated atmospheric signature.

Atmospheric mixing ratios of methane reached a maximum of 2400 ppb (500 ppb above baseline concentrations) in the well mixed boundary layer flying at 400m above the wetland. Upwind and downwind transects were a maximum of 300 km, and methane mixing ratios increased roughly linearly with distance downwind. The isotopic data from the airborne surveys and ground surveys give a bulk isotopic signature for δ¹³C_CH4 of ~-59 ‰ ± 4, which is less negative than Amazon floodplain work focusing on emission of methane through trees, but match well with bulk isotopic values from the Amazon Basin. Ground based wetland samples taken concurrently near Trinidad, Bolivia, gave a source signature of -56 ‰ ± 4 re-enforcing the likelihood that the atmospheric enhancements measured are related to the wetland emissions. For comparison, tropical wetlands measured at ground level during a recent Ugandan and Zambian campaign gave heavier δ¹³C_CH4 isotopic source signatures of -50 to -54 ‰. Based on this snap shot study, flux estimations suggest that the Bolivian wetlands could be emitting ~10mg CH₄ m^-2 h^-1. The observed mole fractions will be compared to model simulations to determine how well the Bolivian wetland methane fluxes are represented.

How to cite: France, J. L., Jones, A., Lachlan-Cope, T., Weiss, A., Andrade, M., Moreno, I., Fisher, R., Lowry, D., Lanoiselle, M., Nisbet, E., and Lunt, M.: Significant fluxes of methane over tropical wetlands and their associated δ13C isotopic source signatures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9660, https://doi.org/10.5194/egusphere-egu2020-9660, 2020.