Using urban Eddy Covariance observations to inform a dynamic high-resolution urban CO2 flux model

High-resolution monitoring systems of urban CO 2 emissions integrating atmospheric observations are needed to assess the accuracy of the self-reported urban emission inventories and provide information useful for planning local climate change mitigation actions. This study presents a new approach for using direct urban CO 2 flux observations derived by Eddy Covariance towers for optimising the estimates of a bottom-up high-resolution flux model in a dynamic data assimilation framework. The methodology is developed and applied in the city centre of Basel, Switzerland, defining a study area of 3 x 3 km which includes two long-term Eddy Covariance towers located 1.6 km apart. The results show that the applied method is most efficient when the areas covered by the Eddy Covariance flux footprints present less complexity in urban structure and CO 2 source/sink mixture, such as street level sources originating from wide open areas. When strong building emissions are mixed with traffic originating by narrow urban canyon structures, then the accurate decomposition of the flux observations becomes more challenging. Additionally, the biogenic fluxes in the city green areas are a confounding factor in our results due to their extremely variable nature across the managed urban landscape. Overall, it is demonstrated that Eddy Covariance is a highly valuable tool for understanding and monitoring local scale source and sink processes within the urban environment and can be efficiently used for evaluating and optimising high-resolution models. Restrictions of the applied methodology, its scalability and complementarity to larger-scale and lower-resolution applications (e.g. atmospheric inversions) are discussed.