Publications of Leon Kuhn

Bae, K., Song, C.-K., Van Roozendael, M., Richter, A., Wagner, T., Merlaud, A., Pinardi, G., Friedrich, M. M., Fayt, C., Dimitropoulou, E., Lange, K., Bosch, T., Zilker, B., Latsch, M., Behrens, L. K., Ziegler, S., Ripperger-Lukosiunaite, S., Kuhn, L., Lauster, B., Reischmann, L., Uhlmannsiek, K., Cede, A., Tiefengraber, M., Gebetsberger , M., Park, R. J., Lee, H., Hong, H., Chang, L.-S. and Jeon, K.: Validation of GEMS operational v2.0 total column NO₂ and HCHO during the GMAP/SIJAQ campaign., Science of the Total Environment, 974, doi:10.1016/j.scitotenv.2025.179190, 2025.

Lange, K., Richter, A., Boesch, T., Zilker, B., Latsch, M., Behrens, L. K., Okafor, C. M., Boesch, H., Burrows, J. P., Merlaud, A., Pinardi, G., Fayt, C., Friedrich, M. M., Dimitropoulou, E., Van Roozendael, M., Ziegler, S., Ripperger-Lukosiunaite, S., Kuhn, L., Lauster, B., Wagner, T., Hong, H., Kim, D., Chang, L.-S., Bae, K., Song, C.-K., Park, J.-U. and Lee, H.: Validation of GEMS tropospheric NO₂ columns and their diurnal variation with ground-based DOAS measurements, Atmospheric Measurement Techniques, 17(21), 6315–6344, doi:10.5194/amt-17-6315-2024, 2024.

Donner, S., Lauster, B., Ziegler, S., Artaxo, P., Beirle, S., Edtbauer, A., Kuhn, L., Machado, L., Pozzer, A., Ringsdorf, A., Williams, J. and Wagner, T.: Linking MAX-DOAS measurements of formaldehyde and glyoxal to precursor substances at the canopy-atmosphere-interface at ATTO, in EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU., 2026.

Klingmüller, K., Butler, T., Gromov, S., Jorba, O., Kuhn, L., Mas Magre, I., Melli, A., Mouchel-Vallon, C., Petetin, H., Sander, R., Schaap, M., Thürkow, M., Lelieveld, J. and Pozzer, A.: Modelling complex atmospheric chemistry with artificial intelligence: data, constraints, and scalability, in EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU., 2026.

Kuhn, L., Wagner, T. and Beirle, S.: Estimating street-scale NO₂ surface concentrations from TROPOMI observations and high-resolution geographic data, in EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU., 2026.

Kuhn, L., Beirle, S. and Wagner, T.: NitroNet – A new deep-learning model for the prediction of NO₂ profiles based on TROPOMI satellite observations, in EGU General Assembly 2024, Vienna, Austria & Online., 2024.

Klingmüller, K., Butler, T. M., Gromov, S., Jorba, O., Kuhn, L., Magre, I. M., Mouchel-Vallon, C., Petetin, H., Sander, R., Schaap, M., Thürkow, M., Lelieveld, J. and Pozzer, A.: The EACH project: Artificial Intelligence Emulating Atmospheric Chemistry, AGU Annual Meeting 2025 [online] Available from: http://hdl.handle.net/21.11116/0000-0013-566A-4, 2025.

Kuhn, L., Beirle, S., Osipov, S., Pozzer, A. and Wagner, T.: NitroNet – A deep-learning NO₂ profile retrieval prototype for the TROPOMI satellite instrument, EGUsphere, doi:10.5194/egusphere-2024-1196, 2024.