ORCID Profile
0000-0002-4843-8453
Current Organisation
Vrije Universiteit Amsterdam
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Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-16139
Abstract: & & The Paris Agreement foresees to establish a transparency framework that builds upon inventory-based national greenhouse gas emission reports, complemented by independent emission estimates derived from atmospheric measurements through inverse modelling. The capability of such a Monitoring and Verification Support (MVS) capacity to constrain fossil fuel emissions to a sufficient extent has not yet been assessed. 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 an MVS capacity.& & & & & Here we present a CCFFDAS that operates at the resolution of the CO2M sensor, i.e. 2km by 2km, over a 200 km by 200 km region around Berlin. It combines models of sectorial fossil fuel CO2 emissions and biospheric fluxes with the Community Multiscale Air Quality model (coupled to a model of the plume rise from large power plants) as observation operator for XCO2 and tropospheric column NO2 measurements. Inflow from the domain boundaries is treated as extra unknown to be solved for by the CCFFDAS, which also includes prior information on the process model parameters. We discuss the sensitivities (Jacobian matrix) of simulated XCO2 and NO2 troposheric columns with respect to a) emissions from power plants, b) emissions from the surface and c) the lateral inflow and quantify the respective contributions to the observed signal. The Jacobian representation of the complete modelling chain allows us to evaluate data sets of simulated random and systematic CO2M errors in terms of posterior uncertainties in sectorial fossil fuel emissions. We provide assessments of XCO2 alone and in combination with NO2 on the posterior uncertainty in sectorial fossil fuel emissions for two 1-day study periods, one in winter and one in summer. We quantify the added value of the observations for emissions at a single point, at the 2km by 2km scale, at the scale of Berlin districts, and for & Berlin and further cities in our domain. This means the assessments include temporal and spatial scales typically not covered by inventories. Further, we quantify the effect of better information of atmospheric aerosol, provided by a multi-angular polarimeter (MAP) onboard CO2M, on the posterior uncertainties.& & & & The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call & #8220 other sector& #8221 . We find that XCO2 measurements alone provide a powerful constraint on emissions from larger power plants and a constraint on emissions from the other sector that increases when aggregated to larger spatial scales. The MAP improves the impact of the CO2M measurements for all power plants and for the other sector on all spatial scales. Over our study domain, the impact of the MAP is particularly high in winter. NO2 measurements provide a powerful additional constraint on the emissions from power plants and from the other sector.& &
Publisher: Frontiers Media SA
Date: 11-05-2022
DOI: 10.3389/FRSEN.2022.887456
Abstract: The European Copernicus programme plans to install a constellation of multiple polar orbiting satellites (Copernicus Anthropogenic CO 2 Monitoring Mission, CO2M mission) for observing atmospheric CO 2 content with the aim to estimate fossil fuel CO 2 emissions. We explore the impact of potential CO2M observations of column-averaged CO 2 (XCO 2 ), nitrogen dioxide (NO 2 ), and aerosols in a 200 × 200 km 2 domain around Berlin. For the quantification of anticipated XCO 2 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 XCO 2 and NO 2 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 CO 2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector.” We find that combined measurements of XCO 2 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 XCO 2 measurements on emissions from all power plants and for the other sector on all spatial scales. NO 2 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 CO 2 column in terms of spatial emission impact. This analysis reveals the complex structure of the footprint of an observed CO 2 column, which indicates the limits of simple mass balances approaches for interpretation of such observations.
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