| 1. |
- Kaminski, Thomas, et al.
(författare)
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Assessing the constraint of atmospheric CO2 and NO2 measurements from space on city-scale fossil fuel CO2 emissions in a data assimilation system
- 2022
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Ingår i: Frontiers in Remote Sensing. - : Frontiers Media SA. - 2673-6187. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- The European Copernicus programme plans to install a constellation of multiple polar orbiting satellites (Copernicus Anthropogenic CO2 Monitoring Mission, CO2M mission) for observing atmospheric CO2 content with the aim to estimate fossil fuel CO2 emissions. We explore the impact of potential CO2M observations of column-averaged CO2 (XCO2), nitrogen dioxide (NO2), and aerosols in a 200 × 200 km2 domain around Berlin. For the quantification of anticipated XCO2 random and systematic errors we developed and applied new error parameterisation formulae based on artificial neural networks. For the interpretation of these data, we further established a CCFFDAS modelling chain from parameters of emission models to XCO2 and NO2 observations to simulate the 24 h periods preceeding simulated CO2M overpasses over the study area. For one overpass in winter and one in summer, we present a number of assessments of observation impact in terms of the posterior uncertainty in fossil fuel emissions on scales ranging from 2 to 200 km. This means the assessments include temporal and spatial scales typically not covered by inventories. The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector.” We find that combined measurements of XCO2 and aerosols provide a powerful constraint on emissions from larger power plants; the uncertainty in fossil fuel emissions from the largest three power plants in the domain was reduced by 60%–90% after assimilating the observations. Likewise, these measurements achieve an uncertainty reduction for the other sector that increases when aggregated to larger spatial scales. When aggregated over Berlin the uncertainty reduction for the other sector varies between 28% and 48%. Our assessments show a considerable contribution of aerosol observations onboard CO2M to the constraint of the XCO2 measurements on emissions from all power plants and for the other sector on all spatial scales. NO2 measurements onboard CO2M provide a powerful additional constraint on the emissions from power plants and from the other sector. We further apply a Jacobian representation of the CCFFDAS modelling chain to decompose a simulated CO2 column in terms of spatial emission impact. This analysis reveals the complex structure of the footprint of an observed CO2 column, which indicates the limits of simple mass balances approaches for interpretation of such observations.
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| 2. |
- Kaminski, Thomas, et al.
(författare)
-
Assessing the Impact of Atmospheric CO2 and NO2 Measurements From Space on Estimating City-Scale Fossil Fuel CO2 Emissions in a Data Assimilation System
- 2022
-
Ingår i: Frontiers in Remote Sensing. - : Frontiers Media SA. - 2673-6187. ; 3
-
Tidskriftsartikel (refereegranskat)abstract
- The European Copernicus programme plans to install a constellation of multiple polar orbiting satellites (Copernicus Anthropogenic CO2 Monitoring Mission, CO2M mission) for observing atmospheric CO2 content with the aim to estimate fossil fuel CO2 emissions. We explore the impact of potential CO2M observations of column-averaged CO2 (XCO2), nitrogen dioxide (NO2), and aerosols in a 200 × 200 km2 domain around Berlin. For the quantification of anticipated XCO2 random and systematic errors we developed and applied new error parameterisation formulae based on artificial neural networks. For the interpretation of these data, we further established a CCFFDAS modelling chain from parameters of emission models to XCO2 and NO2 observations to simulate the 24 h periods preceeding simulated CO2M overpasses over the study area. For one overpass in winter and one in summer, we present a number of assessments of observation impact in terms of the posterior uncertainty in fossil fuel emissions on scales ranging from 2 to 200 km. This means the assessments include temporal and spatial scales typically not covered by inventories. The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector.” We find that combined measurements of XCO2 and aerosols provide a powerful constraint on emissions from larger power plants; the uncertainty in fossil fuel emissions from the largest three power plants in the domain was reduced by 60%–90% after assimilating the observations. Likewise, these measurements achieve an uncertainty reduction for the other sector that increases when aggregated to larger spatial scales. When aggregated over Berlin the uncertainty reduction for the other sector varies between 28% and 48%. Our assessments show a considerable contribution of aerosol observations onboard CO2M to the constraint of the XCO2 measurements on emissions from all power plants and for the other sector on all spatial scales. NO2 measurements onboard CO2M provide a powerful additional constraint on the emissions from power plants and from the other sector. We further apply a Jacobian representation of the CCFFDAS modelling chain to decompose a simulated CO2 column in terms of spatial emission impact. This analysis reveals the complex structure of the footprint of an observed CO2 column, which indicates the limits of simple mass balances approaches for interpretation of such observations.
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| 3. |
- Kaminski, Thomas, et al.
(författare)
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Assimilation of atmospheric CO2observations from space can support national CO2emission inventories
- 2022
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9318 .- 1748-9326. ; 17:1
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Scholze, Marko, et al.
(författare)
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Reviews and syntheses : Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems
- 2017
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:14, s. 3401-3429
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Forskningsöversikt (refereegranskat)abstract
- The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.
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