Kaminski, T., M. Scholze, P. Rayner, S. Houweling, M. Voßbeck, J. Silver, S. Lama, M. Buchwitz, M. Reuter, W. Knorr, H. W. Chen, G. Kuhlmann, D. Brunner, S. Dellaert, H. A. C. Denier van der Gon, I. Super, A. Löscher, and Y. Meijer
Frontiers in Remote Sensing
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.
Kaminski, T., M. Scholze, P. Rayner, S. Houweling, M. Voßbeck, J. Silver, S. Lama, M. Buchwitz, M. Reuter, W. Knorr, H. W. Chen, G. Kuhlmann, D. Brunner, S. Dellaert, H. A. C. Denier van der Gon, I. Super, A. Löscher, and Y. Meijer, 2022: Assessing the constraint of atmospheric CO2 and NO2 measurements from space on city-scale fossil fuel CO2 emissions in a data assimilation system. Frontiers in Remote Sensing, 3, 887456, https://doi.org/10.3389/frsen.2022.887456.