Temporal Variability and Spatial Distribution of CO2 Fluxes in a Danish Suburban Environment: Insights from Tall Tower Eddy Covariance

To quantitatively assess the impact of climate mitigation actions and support sustainable urban planning, the eddy covariance (EC) method serves as a potentially powerful tool for independent monitoring, reporting, and verification. However, interpreting EC fluxes in urban environments is challenging due to the spatial-temporal heterogeneity of urban surfaces and human activities, coupled with the complex coexistence of anthropogenic and biogenic fluxes. Furthermore, the EC footprint varies significantly with meteorological conditions, which can lead to biased flux estimates if the spatial representativeness is not properly accounted for.

This study presents a framework to resolve the monthly spatial distribution of CO₂ sources and sinks at 10-meters resolution by integrating tall tower EC measurements (at heights up to 112 m) with bottom-up modelling and satellite imagery. The study site is a suburban area in Gladsaxe Municipality, northwest of Copenhagen, Denmark. A 12-months dataset collected throughout 2025 was analysed. Five major activities were considered: transportation, residential heating, human respiration, industrial emissions, and vegetation exchange. By coupling a footprint model with land-use and activity data, we performed a source apportionment to optimize spatially unbiased emission estimates.

Preliminary results indicate that transportation is a major contributor to the net CO₂ emission at this suburban site, while residential heating shows an apparent elevation during the winter months. Notably, the CO₂ exchange from vegetated areas displays an identifiable seasonal pattern, shifting between a potential weak source in winter and an appreciable sink during the peak growing season. These findings highlight the utility of tall tower EC in partitioning sectoral emissions, providing critical observation-based constraints for local CO₂ inventories and urban climate action plans.

We acknowledge the financial support from the Independent Research Fund Denmark (DFF, Grant No. 1127-00308B) and the sponsorship provided by CIBICOM A/S (Ballerup, Denmark).