- 1Centre for Environmental and Climate Science, Lund University, Lund, Sweden (betty.molinier@cec.lu.se)
- 2Environmental Sensors and Monitoring, Technical University of Munich, Munich, Germany
- 3Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
- 4Environmental Meteorology, University of Freiburg, Freiburg im Breisgau, Germany
- 5Netherlands Organisation for Applied Scientific Research, Utrecht, Netherlands
- 6Institute of Meteorology and Climate Research Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- 7Institute for Environmental Physics, Heidelberg University, Heidelberg, Germany
- 8Department of Environmental Science, University of Basel, Basel, Switzerland
Emissions of greenhouse gases (GHGs) are known drivers of climate change and related effects; however, they continue to increase every year despite current reduction efforts. Rising populations worldwide as well as changes in land use and in anthropogenic activities contribute significantly to this observed, unmitigated increase in GHG emissions. Cities are clear hotspots for anthropogenic sources of GHGs, and a regional or national emission reduction plan is not enough to effectively target their complex and unique source compositions or relative contributions. To push local or city-level action plans forward, GHG flux towers in three pilot cities (Zurich, Munich, and Paris) were established for long-term eddy-covariance measurements as part of the H2020 ICOS Cities/PAUL project (https://www.icos-cp.eu/projects/icos-cities). The cities were chosen to offer insight into how city size, topography, and source mixture affect GHG and trace gas emissions.
We present results from emission source attribution of carbon dioxide (CO2), carbon monoxide (CO), and methane (CH4) using a combination of flux measurements, footprint modelling, and local emission inventories. Turbulence measurements observed at or derived from information at each tower were implemented in the Flux Footprint Prediction (FFP) model (Kljun et al., 2015) to develop highly spatially- and temporally-resolved flux footprints for each site. These footprints were subsequently combined with (1) annual emission inventories at high spatial resolution and (2) emission sector-specific hourly temporal profiles for the aforementioned trace gases to estimate the relative contributions of emission sectors to the flux signal at each tower. We also incorporate outputs of the Vegetation Photosynthesis and Respiration Model (VPRM; Mahadevan et al., 2008) to quantify biogenic contributions to the CO2 flux signal. The presented results highlight seasonal and diurnal trends as well as spatial hotspots within the flux footprint of sector-separated CO2, CH4 and CO fluxes in cities with diverse characteristics, all of which is valuable for source attribution and for supporting localized and targeted emission reduction plans.
How to cite: Molinier, B., Kljun, N., Aigner, P., Brunner, D., Chen, J., Christen, A., Constantin, L., Denier van der Gon, H., Hilland, R., Holst, C., Kühbacher, D., Li, J., Maiwald, R., Stagakis, S., Super, I., and Vardag, S.: Identifying Greenhouse Gas Emission Trends and Validating Hotspot Locations via Flux Measurements and Footprints in Three Pilot Cities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2888, https://doi.org/10.5194/egusphere-egu25-2888, 2025.
