- 1Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany (andre.butz@uni-heidelberg.de)
- 2Heidelberg Center for the Environment (HCE), Heidelberg University, Heidelberg, Germany
- 3Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
- 4Kirchhoff-Institute for Physics, Heidelberg University, Heidelberg, Germany
- 5now at Harvard University, Cambridge, MA, USA 02138
Carbon dioxide (CO2) emissions from urban areas constitute the largest share of total anthropogenic emissions. At the same time, cities have positioned themselves as frontrunners in the implementation of emission reduction measures, driven by ambitious goals to achieve carbon neutrality within short timeframes. To design and evaluate such measures, localized CO2 measurement and modelling techniques are under development and demonstration deployments are underway in urban environments to estimate emissions, as well as their temporal evolution and trends, at high spatial and temporal resolution.
In the Rhine–Neckar region, encompassing the cities of Heidelberg and Mannheim in southwest Germany, we have established the UNICORN (UnIversity Network for CO2 in the Rhine–Neckar metropolitan area). The network consists of more than a dozen in-situ mid-cost CO2 sensors, a Fourier Transform Spectrometer (FTS) and a Dual Comb laser Spectrometer (DCS) for horizontal path measurements, a sun-viewing FTS with vertical column sensitivity and a CO2 camera for snapshot images of the local power plant. The in-situ nodes are based on the design developed by the University of California, Berkeley, for the BEACO2N (Berkeley Environmental Air-quality & CO2 Network) and equipped with ancillary air quality sensors measuring carbon monoxide, nitrogen oxides, ozone, and particulate matter. For estimating emission distributions from the observed concentration gradients, we employ the GRAMM–GRAL atmospheric model, which operates at a horizontal resolution of 10 m across the study domain.
Key challenges in establishing the UNICORN include optimal sensor placement, calibration of sensors under resource constraints, combining the various techniques under consideration of their sensitivity characteristics, effective use of ancillary meteorological and air quality data, robust estimation of background concentrations and their variability, and the derivation of emission distributions taking into account atmospheric transport and its uncertainties. Here, we report on our progress in addressing these challenges, showcasing the current UNICORN configuration and discussing lessons learned across the employed measurement and modelling techniques.
How to cite: Butz, A., von Buenau, K., Dermendzhiev, M., Herrenknecht, T., Kleinschek, R., Knapp, M., Leyer, S., Löw, B., Lüken-Winkels, C., Maiwald, R., Sindram, M., Schmitt, T., Voss, T., and Vardag, S. N.: UNICORN – UnIversity Network for CO2 in the Rhine–Neckar metropolitan area: implementation and first insights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10583, https://doi.org/10.5194/egusphere-egu26-10583, 2026.