Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1357-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-1357-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Mar 2023
Research article |
| 14 Mar 2023
| 14 Mar 2023
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Kezia Lange
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Andreas Richter
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Anja Schönhardt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Andreas C. Meier
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Tim Bösch
Institute of Environmental Physics, University of Bremen, Bremen, Germany
André Seyler
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Kai Krause
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Lisa K. Behrens
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Folkard Wittrock
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Alexis Merlaud
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Frederik Tack
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Caroline Fayt
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Martina M. Friedrich
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Ermioni Dimitropoulou
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Michel Van Roozendael
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Vinod Kumar
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Sebastian Donner
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Steffen Dörner
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Bianca Lauster
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Maria Razi
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Christian Borger
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Katharina Uhlmannsiek
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Thomas Wagner
Satellite Remote Sensing, Max Planck Institute for Chemistry, Mainz, Germany
Thomas Ruhtz
Institute for Space Science, FU Berlin, Berlin, Germany
Henk Eskes
KNMI, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Birger Bohn
Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany
Daniel Santana Diaz
LuftBlick, Innsbruck, Austria
Nader Abuhassan
Joint Center for Earth Systems Technology, University of Maryland, Baltimore County (UMBC), Baltimore, Maryland, USA
Dirk Schüttemeyer
European Space Agency, ESA-ESTEC, Noordwijk, the Netherlands
John P. Burrows
Institute of Environmental Physics, University of Bremen, Bremen, Germany
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Cited
11 citations as recorded by crossref.
- Machine learning-based global air quality index development using remote sensing and ground-based stations T. Anggraini et al. 10.1016/j.envadv.2023.100456
- Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements K. Lange et al. 10.5194/amt-17-6315-2024
- Can TROPOMI NO2satellite data be used to track the drop in and resurgence of NOxemissions in Germany between 2019–2021 using the multi-source plume method (MSPM)? E. Dammers et al. 10.5194/gmd-17-4983-2024
- NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations L. Kuhn et al. 10.5194/amt-17-6485-2024
- Fiducial Reference Measurements for Air Quality Monitoring Using Ground-Based MAX-DOAS Instruments (FRM4DOAS) M. Van Roozendael et al. 10.3390/rs16234523
- Technical note: Evaluation of the Copernicus Atmosphere Monitoring Service Cy48R1 upgrade of June 2023 H. Eskes et al. 10.5194/acp-24-9475-2024
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Sensitivity analysis of NO2 differential slant column density according to spatial resolution using GCAS data from the SIJAQ 2022 campaign S. Lee et al. 10.1016/j.atmosenv.2024.120723
- Informing Near-Airport Satellite NO2 Retrievals Using Pandora Sky-Scanning Observations A. Mouat et al. 10.1021/acsestair.4c00158
- A new method for estimating megacity NOx emissions and lifetimes from satellite observations S. Beirle & T. Wagner 10.5194/amt-17-3439-2024
- Trends and drivers of anthropogenic NO emissions in China since 2020 H. Li et al. 10.1016/j.ese.2024.100425
11 citations as recorded by crossref.
- Machine learning-based global air quality index development using remote sensing and ground-based stations T. Anggraini et al. 10.1016/j.envadv.2023.100456
- Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements K. Lange et al. 10.5194/amt-17-6315-2024
- Can TROPOMI NO2satellite data be used to track the drop in and resurgence of NOxemissions in Germany between 2019–2021 using the multi-source plume method (MSPM)? E. Dammers et al. 10.5194/gmd-17-4983-2024
- NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations L. Kuhn et al. 10.5194/amt-17-6485-2024
- Fiducial Reference Measurements for Air Quality Monitoring Using Ground-Based MAX-DOAS Instruments (FRM4DOAS) M. Van Roozendael et al. 10.3390/rs16234523
- Technical note: Evaluation of the Copernicus Atmosphere Monitoring Service Cy48R1 upgrade of June 2023 H. Eskes et al. 10.5194/acp-24-9475-2024
- TROPOMI NO2 Shows a Fast Recovery of China’s Economy in the First Quarter of 2023 H. Li & B. Zheng 10.1021/acs.estlett.3c00386
- Sensitivity analysis of NO2 differential slant column density according to spatial resolution using GCAS data from the SIJAQ 2022 campaign S. Lee et al. 10.1016/j.atmosenv.2024.120723
- Informing Near-Airport Satellite NO2 Retrievals Using Pandora Sky-Scanning Observations A. Mouat et al. 10.1021/acsestair.4c00158
- A new method for estimating megacity NOx emissions and lifetimes from satellite observations S. Beirle & T. Wagner 10.5194/amt-17-3439-2024
- Trends and drivers of anthropogenic NO emissions in China since 2020 H. Li et al. 10.1016/j.ese.2024.100425
Latest update: 30 Dec 2024
Short summary
We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted...
