CO₂ Monitoring Challenges Notebook Package

Notebook package from the CMC-CITYMAP framework, provided alongside a complementary mapbooks (https://doi.org/10.18160/Z66D-05JT), serve as supplementary material for the forthcoming publication "Monitoring CO₂ in Diverse European Cities: Highlighting Needs and Challenges Through Characterization" (Storm et al., 2025, in preparation).

Paper abstract: For the development of a joint European capacity for monitoring CO2 emissions, we created the framework “CO2 Monitoring Challenges City Mapbooks v1.0” (acronym CMC-CITYMAP). It includes a Jupyter notebook tool (Storm et al., 2025) which we use to characterize and cluster cities based on aspects relevant for different CO2 monitoring challenges, including (a) determining background levels of CO2 inflow into a city (“background challenge”), (b) separating the anthropogenic emissions from the influence of the biosphere (“biogenic challenge”), (c) representing spatially and temporally non-uniform emissions in models (“modelling challenge”), and (d) implementing observation strategies not covered by the other challenges (“application-specific observational challenge”). We provide and discuss the challenges city-by-city basis, but our primary focus is on the relationships between cities: best practices and lessons learned from monitoring CO2 emissions in one city can be transferred to other cities with similar characteristics. Additionally, we identify cities with characteristics that strongly contrast with those of cities with existing urban monitoring systems.

While the tool includes 308 cities, this paper focuses on the results for 96 cities with more than 200,000 inhabitants, with a particular emphasis on Paris, Munich, and Zurich. These cities are pilot cities for the Horizon 2020-funded project Pilot Application in Urban Landscapes (“ICOS Cities”), where a range of urban CO2 monitoring methods are being implemented and assessed. According to our analyses, Zurich — and Munich especially — should be less challenging to monitor than Paris. Examining the challenges individually reveals that the most significant relative challenge is the “modelling challenge” (c) for Zurich and Paris. Complex urban topography adds to the challenge for both cities, and in Zurich, the natural topography further amplifies the challenge. Munich has low scores across all challenges, but with the greatest challenge anticipated from the “application-specific observational challenge” (d). Overall, Bratislava (Slovakia) and Copenhagen (Denmark) are among the most distant from Paris, Munich, and Zurich in our dendrogram resulting from numerical cluster-analysis. This makes them strong candidates for inclusion in the ICOS Cities network, as they would potentially provide the most information on how to monitor emissions in cities that face different challenges.

How to run the tool: This package contains scripts and data, in addition to the notebook, and the whole package is needed for the tool to run. There is a requirements.txt file that specifies all Python packages that needs to be installed. An alternative to downloading the notebook package is to use the up-to-date version of the tool available on exploredata in the folder "project_jupyter_notebooks". Here is the direct link: https://exploredata.icos-cp.eu/hub/user-redirect/lab/tree/project_jupyter_notebooks/city-characterization-tool/city_characteristic_analysis.ipynb.

You can request a password for this service here: https://www.icos-cp.eu/data-services/tools/jupyter-notebook/exploredata-password. Observe that once you log out from exploredata, any changes will automatically be dropped once you log out.