Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7297-2021
© Author(s) 2021. 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-14-7297-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An improved TROPOMI tropospheric NO2 research product over Europe
Song Liu
CORRESPONDING AUTHOR
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
now at: School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
Pieter Valks
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
Gaia Pinardi
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
National Space Science Center, Chinese Academy of Sciences, Beijing, China
Ka Lok Chan
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
Athina Argyrouli
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
Technical University of Munich (TUM), Department of Civil, Geo and Environmental Engineering, Chair of Remote Sensing Technology, Munich, Germany
Ronny Lutz
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
Steffen Beirle
Max Planck Institute for Chemistry (MPI-C), Mainz, Germany
Ehsan Khorsandi
Deutsches Zentrum für Luft- und Raumfahrt (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, Germany
Frank Baier
Deutsches Zentrum für Luft- und Raumfahrt (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, Germany
Vincent Huijnen
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Alkiviadis Bais
Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
Sebastian Donner
Max Planck Institute for Chemistry (MPI-C), Mainz, Germany
Steffen Dörner
Max Planck Institute for Chemistry (MPI-C), Mainz, Germany
Myrto Gratsea
Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece
François Hendrick
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Dimitris Karagkiozidis
Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
Kezia Lange
Institute of Environmental Physics (IUP-UB), University of Bremen, Bremen, Germany
Ankie J. M. Piters
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Julia Remmers
Max Planck Institute for Chemistry (MPI-C), Mainz, Germany
Andreas Richter
Institute of Environmental Physics (IUP-UB), University of Bremen, Bremen, Germany
Michel Van Roozendael
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Thomas Wagner
Max Planck Institute for Chemistry (MPI-C), Mainz, Germany
Mark Wenig
Meteorological Institute (MIM), Ludwig-Maximilians-Universität München (LMU), Munich, Germany
Diego G. Loyola
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Methodik der Fernerkundung (IMF), Oberpfaffenhofen, Germany
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22 citations as recorded by crossref.
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- Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems A. Penenko et al. 10.3390/atmos12121697
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- Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS S. Seo et al. 10.5194/amt-17-6163-2024
- Observing network effect of shipping emissions from space: A natural experiment in the world’s busiest port S. Liu et al. 10.1093/pnasnexus/pgad391
- Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 2: Impact on NO2 retrieval and mitigation strategies H. Yu et al. 10.5194/amt-15-5743-2022
- 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
- Quantification of lightning-produced NO<sub><i>x</i></sub> over the Pyrenees and the Ebro Valley by using different TROPOMI-NO<sub>2</sub> and cloud research products F. Pérez-Invernón et al. 10.5194/amt-15-3329-2022
- Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0 L. Fehr et al. 10.5194/gmd-16-7491-2023
- Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble J. Douros et al. 10.5194/gmd-16-509-2023
- A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al. 10.1016/j.rse.2024.114267
- Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2 D. Goldberg et al. 10.1016/j.rse.2023.113917
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- Global Observations of Tropospheric Bromine Monoxide (BrO) Columns From TROPOMI Y. Chen et al. 10.1029/2023JD039091
- Comparison of TROPOMI NO2, CO, HCHO, and SO2 data against ground‐level measurements in close proximity to large anthropogenic emission sources in the example of Ukraine M. Savenets et al. 10.1002/met.2108
- 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 L. Kuhn et al. 10.5194/acp-24-185-2024
- An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI A. Argyrouli et al. 10.5194/amt-17-6345-2024
- Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms C. Emde et al. 10.5194/amt-15-1587-2022
- NO2 Air Pollution Trends and Settlement Growth in Megacities T. Erbertseder et al. 10.1109/JSTARS.2024.3419573
- Lightning‐Produced Nitrogen Oxides Per Flash Length Obtained by Using TROPOMI Observations and the Ebro Lightning Mapping Array F. Pérez‐Invernón et al. 10.1029/2023GL104699
21 citations as recorded by crossref.
- Satellite remote-sensing capability to assess tropospheric-column ratios of formaldehyde and nitrogen dioxide: case study during the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) field campaign M. Johnson et al. 10.5194/amt-16-2431-2023
- Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems A. Penenko et al. 10.3390/atmos12121697
- Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 3: Bias estimate using synthetic and observational data A. Kylling et al. 10.5194/amt-15-3481-2022
- Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS S. Seo et al. 10.5194/amt-17-6163-2024
- Observing network effect of shipping emissions from space: A natural experiment in the world’s busiest port S. Liu et al. 10.1093/pnasnexus/pgad391
- Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 2: Impact on NO2 retrieval and mitigation strategies H. Yu et al. 10.5194/amt-15-5743-2022
- 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
- Quantification of lightning-produced NO<sub><i>x</i></sub> over the Pyrenees and the Ebro Valley by using different TROPOMI-NO<sub>2</sub> and cloud research products F. Pérez-Invernón et al. 10.5194/amt-15-3329-2022
- Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0 L. Fehr et al. 10.5194/gmd-16-7491-2023
- Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble J. Douros et al. 10.5194/gmd-16-509-2023
- A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al. 10.1016/j.rse.2024.114267
- Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2 D. Goldberg et al. 10.1016/j.rse.2023.113917
- Sentinel-5P TROPOMI NO<sub>2</sub> retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data J. van Geffen et al. 10.5194/amt-15-2037-2022
- Analysis of NO2 and O3 Total Columns from DOAS Zenith-Sky Measurements in South Italy P. Pettinari et al. 10.3390/rs14215541
- Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium C. Poraicu et al. 10.5194/gmd-16-479-2023
- Global Observations of Tropospheric Bromine Monoxide (BrO) Columns From TROPOMI Y. Chen et al. 10.1029/2023JD039091
- Comparison of TROPOMI NO2, CO, HCHO, and SO2 data against ground‐level measurements in close proximity to large anthropogenic emission sources in the example of Ukraine M. Savenets et al. 10.1002/met.2108
- 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 L. Kuhn et al. 10.5194/acp-24-185-2024
- An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI A. Argyrouli et al. 10.5194/amt-17-6345-2024
- Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms C. Emde et al. 10.5194/amt-15-1587-2022
- NO2 Air Pollution Trends and Settlement Growth in Megacities T. Erbertseder et al. 10.1109/JSTARS.2024.3419573
Latest update: 20 Nov 2024
Short summary
In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented with correction for the dependency of the stratospheric NO2 on the viewing geometry. The AMF calculation is implemented using improved surface albedo, a priori NO2 profiles, and cloud correction. The improved tropospheric NO2 data show good correlations with ground-based MAX-DOAS measurements.
In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over...