Articles | Volume 17, issue 21
https://doi.org/10.5194/amt-17-6485-2024
https://doi.org/10.5194/amt-17-6485-2024
Research article
 | 
13 Nov 2024
Research article |  | 13 Nov 2024

NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations

Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner

Related authors

Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements
Kezia Lange, Andreas Richter, Tim Bösch, Bianca Zilker, Miriam Latsch, Lisa K. Behrens, Chisom M. Okafor, Hartmut Bösch, John P. Burrows, Alexis Merlaud, Gaia Pinardi, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Steffen Ziegler, Simona Ripperger-Lukosiunaite, Leon Kuhn, Bianca Lauster, Thomas Wagner, Hyunkee Hong, Donghee Kim, Lim-Seok Chang, Kangho Bae, Chang-Keun Song, Jong-Uk Park, and Hanlim Lee
Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024,https://doi.org/10.5194/amt-17-6315-2024, 2024
Short summary
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations
Leon Kuhn, Steffen Beirle, Vinod Kumar, Sergey Osipov, Andrea Pozzer, Tim Bösch, Rajesh Kumar, and Thomas Wagner
Atmos. Chem. Phys., 24, 185–217, https://doi.org/10.5194/acp-24-185-2024,https://doi.org/10.5194/acp-24-185-2024, 2024
Short summary
The NO2 camera based on gas correlation spectroscopy
Leon Kuhn, Jonas Kuhn, Thomas Wagner, and Ulrich Platt
Atmos. Meas. Tech., 15, 1395–1414, https://doi.org/10.5194/amt-15-1395-2022,https://doi.org/10.5194/amt-15-1395-2022, 2022
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks
Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 18, 241–264, https://doi.org/10.5194/amt-18-241-2025,https://doi.org/10.5194/amt-18-241-2025, 2025
Short summary
The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024,https://doi.org/10.5194/amt-17-6889-2024, 2024
Short summary
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024,https://doi.org/10.5194/amt-17-6459-2024, 2024
Short summary
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024,https://doi.org/10.5194/amt-17-6385-2024, 2024
Short summary
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024,https://doi.org/10.5194/amt-17-6247-2024, 2024
Short summary