ICOS Atmospheric Stations: Spatial Characterization of CO2 Footprint Areas and Evaluating the Uncertainties of Modelled CO2 Concentrations

Abstract: The main purpose of this thesis is to present and analyze spatial characteristics of 31 different European atmospheric measurement stations in the ICOS (Integrated Carbon Observation System) station network. The characterization includes quantification of where air arriving at the stations can be expected to have come from, as well as a breakdown of what these areas cover with regards to land cover, point source emissions and population. A dataset regarding emissions of radiocarbon at nuclear power plants has also been processed because possible transports of radiocarbon from these facilities to the stations need to be accounted for when quantifying fossil fuel emissions based on measured ratio between 14C and 12C. “Where the air arriving can be expected to have come from” for a specific date and time is synonymous with a station’s footprint. For a general characterization based on annual values, an average footprint based on all three-hourly footprints in the year is used. Each individual footprint has already been combined with data on anthropogenic emissions and a model that quantifies the biospheric component to estimate the CO2 concentration at the stations. The known sources that make up the total CO2 signal also allows for a breakdown into different categories of contribution. Averages of these are also part of the characterization. The annual averages for the different characterizations vary greatly between the stations: station Pallas’ anthropogenic contribution is only 2.2% of the estimated contribution at the station with the highest value, Heidelberg. Furthermore, there are large variabilities between the footprints at the individual stations that are used to generate annual averages. Individual footprints values are used in closer analysis exemplified for selected stations. However, years 2016 and 2017 show similar annual values for the different stations which indicate stability of the annual characterizations. Dominant land cover classes in the model domain, including ocean, cropland, pastures and different types of forests, are found within the annual footprints of all stations. This is no surprise because of the large spatial extent of most footprints: on average 48% of the sensitivity is to the area within 300 km of the station, again with large differences between stations and between individual footprints of the stations. The large footprint extent is also why the spatial characterization is extra important: it is not possible to know what is within the footprint areas without it. Knowing what is in the area in close proximity to the stations is not enough.