VALIDATION OF GOMOS OZONE PROFILES USING NDSC LIDAR : STATISTICAL COMPARISONS

ABSTRACT The lidars deployed in the NDSC framework have been used for the validation of GOMOS onboard ENVISAT. During the commissioning phase around ten coincidences per site have been investigated. No significant bias, larger than ±5 %, has been reported except around 50 km and 20 km where both techniques are known to present some limitations. The estimated errors of both GOMOS and lidar are in good agreement with the standard deviation of the differences between coincidences. At higher latitude, comparisons are not so good because of the measurement conditions of bright limb during this period

Quantifying CO2 emissions of a city with the Copernicus Anthropogenic CO2 Monitoring satellite mission

International audienc

Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission

International audienceHigh-resolution atmospheric transport simulations were used to investigate the potential for detecting carbon dioxide (CO 2) plumes of the city of Berlin and neighboring power stations with the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission, which is a proposed constellation of CO 2 satellites with imaging capabilities. The potential for detecting plumes was studied for satellite images of CO 2 alone or in combination with images of nitrogen dioxide (NO 2) and carbon monoxide (CO) to investigate the added value of measurements of other gases co-emitted with CO 2 that have better signal-to-noise ratios. The additional NO 2 and CO images were either generated for instruments on the same CO2M satellites (2 km× 2 km resolution) or for the Sentinel-5 instrument (7.5 km× 7.5 km) assumed to fly 2 h earlier than CO2M. Realistic CO 2 , CO and NO X (= NO+NO 2) fields were simulated at 1 km× 1 km horizontal resolution with the Consortium for Small-scale Modeling model extended with a module for the simulation of greenhouse gases (COSMO-GHG) for the year 2015, and they were used as input for an orbit simulator to generate synthetic observations of columns of CO 2 , CO and NO 2 for constellations of up to six satellites. A simple plume detection algorithm was applied to detect coherent structures in the images of CO 2 , NO 2 or CO against instrument noise and variability in background levels. Although six satellites with an assumed swath of 250 km were sufficient to overpass Berlin on a daily basis, only about 50 out of 365 plumes per year could be observed in conditions suitable for emission estimation due to frequent cloud cover. With the CO 2 instrument only 6 and 16 of these 50 plumes could be detected assuming a high-noise (σ VEG50 = 1.0 ppm) and low-noise (σ VEG50 = 0.5 ppm) scenario, respectively, because the CO 2 signals were often too weak. A CO instrument with specifications similar to the Sentinel-5 mission performed worse than the CO 2 instrument, while the number of detectable plumes could be significantly increased to about 35 plumes with an NO 2 instrument. CO 2 and NO 2 plumes were found to overlap to a large extent, although NO X had a limited lifetime (assumed to be 4 h) and although CO 2 and NO X were emitted with different NO X : CO 2 emission ratios by different source types with different temporal and vertical emission profiles. Using NO 2 observations from the Sentinel-5 platform instead resulted in a significant spatial mismatch between NO 2 and CO 2 plumes due to the 2 h time difference between Sentinel-5 and CO2M. The plumes of the coal-fired power plant Jänschwalde were easier to detect with the CO 2 instrument (about 40-45 plumes per year), but, again, an NO 2 instrument could detect significantly more plumes (about 70). Auxiliary measurements of NO 2 were thus found to greatly enhance the capability of detecting the location of CO 2 plumes, which will be invaluable for the quantification of CO 2 emissions from large point sources

Using NO2 Satellite Observations to Support Satellite-based CO2 Emission Estimates of Cities and Power Plants

International audienc

Characterization of temporal and spatial variability of aerosols from ground-based climatology: towards evaluation of satellite mission requirements

International audienc

PMIF v1.0: assessing the potential of satellite observations to constrain CO<sub>2</sub> emissions from large cities and point sources over the globe using synthetic data

Abstract. This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during 1 year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 08:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 00:00–08:30 and 11:30–00:00) for each clump and for the 366 d of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e., the relative difference between the prior and posterior uncertainties). Beyond the one city or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC yr−1 can potentially have their emissions between 08:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within 1 year (ignoring the potential to cross or extrapolate information between 08:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 08:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need for systematic assessment of the sources of uncertainty in the spatiotemporally resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty in constraining the total budget of CO2 emissions from all the cities and power plants within a country or over the globe with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements

Assimilation of atmospheric CO2observations from space can support national CO2emission inventories

The Paris Agreement establishes a transparency framework for anthropogenic carbon dioxide (CO2) emissions. It's core component are inventory-based national greenhouse gas emission reports, which are complemented by independent estimates derived from atmospheric CO2 measurements combined with inverse modelling. It is, however, not known whether such a Monitoring and Verification Support (MVS) capacity is capable of constraining estimates of fossil-fuel emissions to an extent that is sufficient to provide valuable additional information. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2), is expected to become a key component of such an MVS capacity. Here we provide a novel assessment of the potential of a comprehensive data assimilation system using simulated XCO2 and other observations to constrain fossil fuel CO2 emission estimates for an exemplary 1-week period in 2008. We find that CO2M enables useful weekly estimates of country-scale fossil fuel emissions independent of national inventories. When extrapolated from the weekly to the annual scale, uncertainties in emissions are comparable to uncertainties in inventories, so that estimates from inventories and from the MVS capacity can be used for mutual verification. We further demonstrate an alternative, synergistic mode of operation, with the purpose of delivering a best fossil fuel emission estimate. In this mode, the assimilation system uses not only XCO2 and the other data streams of the previous (verification) mode, but also the inventory information. Finally, we identify further steps towards an operational MVS capacity

ESA's Atmospheric Chemistry Mission - A Status Report

The challenges in understanding the atmospheric chemistry processes for climate research and to model and forecast the air quality on regional scale are still manifold. Presently, ESA is providing atmospheric chemistry data both from their core missions ERS-2 and Envisat as well as from Third Party Missions (TPM). ESAs core atmospheric chemistry instruments onboard ERS-2 and ENVISAT are GOME, GOMOS, MIPAS and SCIAMACHY. With ERS-2 launched in 1995 and ENVISAT in 2002, these instruments are providing a rich dataset to the scientific community and supporting operational services since more than 14 years. Currently, data from the following missions can be provided through ESA: ACE-FTS and MAESTRO data from the CSA SCISAT mission, OSIRIS and SMR data from the SSC ODIN mission, TANSO-FTS AND -CAI data from the JAXA/NIES/MOE GOSAT mission. It is currently planned that also OMI data from the NASA AURA mission will be accessible through ESA. In addition to the operational data, ESA acknowledges that the science community is developing and providing a number of important, quality products based on ESA missions. The presentation will summarise the status of all the issues addressed above with a focus on ESA instruments, algorithm development and data distribution

The potential of a constellation of low earth orbit satellite imagers to monitor worldwide fossil fuel CO2emissions from large cities and point sources

International audienceBackground: Satellite imagery will offer unparalleled global spatial coverage at high-resolution for long term cost-effective monitoring of CO2 concentration plumes generated by emission hotspots. CO2 emissions can then be estimated from the magnitude of these plumes. In this paper, we assimilate pseudo-observations in a global atmospheric inversion system to assess the performance of a constellation of one to four sun-synchronous low-Earth orbit (LEO) imagers to monitor anthropogenic CO2 emissions. The constellation of imagers follows the specifications from the European Spatial Agency (ESA) for the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) concept for a future operational mission dedicated to the monitoring of anthropogenic CO2 emissions. This study assesses the uncertainties in the inversion estimates of emissions ("posterior uncertainties"). Results: The posterior uncertainties of emissions for individual cities and power plants are estimated for the 3 h before satellite overpasses, and extrapolated at annual scale assuming temporal auto-correlations in the uncertainties in the emission products that are used as a prior knowledge on the emissions by the Bayesian framework of the inversion. The results indicate that (i) the number of satellites has a proportional impact on the number of 3 h time windows for which emissions are constrained to better than 20%, but it has a small impact on the posterior uncertainties in annual emissions; (ii) having one satellite with wide swath would provide full images of the XCO2 plumes, and is more beneficial than having two satellites with half the width of reference swath; and (iii) an increase in the precision of XCO2 retrievals from 0.7 ppm to 0.35 ppm has a marginal impact on the emission monitoring performance. Conclusions: For all constellation configurations, only the cities and power plants with an annual emission higher than 0.5 MtC per year can have at least one 8:30-11:30 time window during one year when the emissions can be constrained to better than 20%. The potential of satellite imagers to constrain annual emissions not only depend on the design of the imagers, but also strongly depend on the temporal error structure in the prior uncertainties, which is needed to be objectively assessed in the bottom-up emission maps