Articles | Volume 17, issue 21
https://doi.org/10.5194/amt-17-6315-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-17-6315-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Oct 2024
Research article |
| 30 Oct 2024
| 30 Oct 2024
Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements
Kezia Lange
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Andreas Richter
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Tim Bösch
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Bianca Zilker
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Miriam Latsch
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Lisa K. Behrens
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Chisom M. Okafor
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Hartmut Bösch
Institute of Environmental Physics, University of Bremen, Bremen, Germany
John P. Burrows
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Alexis Merlaud
BIRA-IASB, Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
Gaia Pinardi
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
Steffen Ziegler
Satellite Remote Sensing Group, Max Planck Institute for Chemistry, Mainz, Germany
Simona Ripperger-Lukosiunaite
Satellite Remote Sensing Group, Max Planck Institute for Chemistry, Mainz, Germany
Leon Kuhn
Satellite Remote Sensing Group, Max Planck Institute for Chemistry, Mainz, Germany
Bianca Lauster
Satellite Remote Sensing Group, Max Planck Institute for Chemistry, Mainz, Germany
Thomas Wagner
Satellite Remote Sensing Group, Max Planck Institute for Chemistry, Mainz, Germany
Hyunkee Hong
Environmental Satellite Center, National Institute of Environmental Research, Incheon, Republic of Korea
Donghee Kim
Environmental Satellite Center, National Institute of Environmental Research, Incheon, Republic of Korea
Lim-Seok Chang
Environmental Satellite Center, National Institute of Environmental Research, Incheon, Republic of Korea
Kangho Bae
Department of Civil, Urban, Earth and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Research & Management Center for Particulate Matters in the Southeast Region of Korea, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Chang-Keun Song
Department of Civil, Urban, Earth and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Research & Management Center for Particulate Matters in the Southeast Region of Korea, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Graduate School of Carbon Neutrality, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Jong-Uk Park
School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
Hanlim Lee
Division of Earth Environmental System Sciences, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
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Cited
21 citations as recorded by crossref.
- Co-evolving emission controls and climate impacts: A multi-decadal machine learning decomposition of urban O3 and NO2 air quality measurements M. Brancher
- An improved Bayesian inversion to estimate daily NOx emissions of Paris from TROPOMI NO2 observations between 2018–2023 A. Mols et al.
- Decoding Urban Traffic Pollution: Insights on Trends, Patterns, and Meteorological Influences for Policy Action in Bucharest, Romania C. Tudor et al.
- Tropospheric NO2 Column over Tibet Plateau According to Geostationary Environment Monitoring Spectrometer: Spatial, Seasonal, and Diurnal Variations X. Zhang et al.
- Intercomparison of MAX-DOAS, FTIR and direct sun HCHO vertical columns at Xianghe, China G. Pinardi et al.
- Surface Ozone Estimation over the Beijing–Tianjin–Hebei Region: A Case Study Using EMI-II Total Ozone Observations and Machine Learning Integration H. Cheng et al.
- Demonstration of a Simplified, Two-Wavelength Optical Approach to Measuring Nitrogen Dioxide in Cities E. Halpin et al.
- Mitigating bias induced by missing data in new-generation geostationary satellite monitoring of ground-level NO2 via machine learning N. Ahmad et al.
- Limitations of Polar-Orbiting Satellite Observations in Capturing the Diurnal Variability of Tropospheric NO2: A Case Study Using TROPOMI, GOME-2C, and Pandora Data Y. Li et al.
- Sentinel Data for Monitoring of Pollutant Emissions by Maritime Transport—A Literature Review T. Batista et al.
- Diurnal NO emission underestimation constrained using overlapping TROPOMI swaths Q. He et al.
- Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: benefit of using time-contiguous input features for machine learning models J. Gödeke et al.
- Machine Learning-Based Estimation of Surface NO2 Concentrations over China: A Comparative Analysis of Geostationary (GEMS) and Polar-Orbiting (TROPOMI) Satellite Data Y. Ma et al.
- Validating tropospheric NO2 column density from GEMS version 3.0 and Tropospheric Chemistry Reanalysis version 2 from background to urban conditions over Japan: with a focus on diurnal variations P. Ha et al.
- Fiducial Reference Measurements for Air Quality Monitoring Using Ground-Based MAX-DOAS Instruments (FRM4DOAS) M. Van Roozendael et al.
- Diurnal variations of NO2 tropospheric vertical column density over the Seoul metropolitan area from the Geostationary Environment Monitoring Spectrometer (GEMS): seasonal differences and the influence of the a priori NO2 profile S. Seo et al.
- Unraveling overestimated exposure risks through hourly ozone retrievals from next-generation geostationary satellites S. Li et al.
- Global analysis of nitrogen dioxide and formaldehyde column densities from the Pandora global network: Variability and implications for satellite validation J. Park et al.
- Tropospheric nitrogen dioxide levels vary diurnally in Asian cities J. Park et al.
- Diagnosing the underperformance of satellite-based surface NO2 estimation using geostationary observations: Insights for improvement from station-type and temporal analyses in South Korea S. Park et al.
- Introduction of Ground-based Remote Sensing and Applications for Air Quality Monitoring S. Park et al.
21 citations as recorded by crossref.
- Co-evolving emission controls and climate impacts: A multi-decadal machine learning decomposition of urban O3 and NO2 air quality measurements M. Brancher
- An improved Bayesian inversion to estimate daily NOx emissions of Paris from TROPOMI NO2 observations between 2018–2023 A. Mols et al.
- Decoding Urban Traffic Pollution: Insights on Trends, Patterns, and Meteorological Influences for Policy Action in Bucharest, Romania C. Tudor et al.
- Tropospheric NO2 Column over Tibet Plateau According to Geostationary Environment Monitoring Spectrometer: Spatial, Seasonal, and Diurnal Variations X. Zhang et al.
- Intercomparison of MAX-DOAS, FTIR and direct sun HCHO vertical columns at Xianghe, China G. Pinardi et al.
- Surface Ozone Estimation over the Beijing–Tianjin–Hebei Region: A Case Study Using EMI-II Total Ozone Observations and Machine Learning Integration H. Cheng et al.
- Demonstration of a Simplified, Two-Wavelength Optical Approach to Measuring Nitrogen Dioxide in Cities E. Halpin et al.
- Mitigating bias induced by missing data in new-generation geostationary satellite monitoring of ground-level NO2 via machine learning N. Ahmad et al.
- Limitations of Polar-Orbiting Satellite Observations in Capturing the Diurnal Variability of Tropospheric NO2: A Case Study Using TROPOMI, GOME-2C, and Pandora Data Y. Li et al.
- Sentinel Data for Monitoring of Pollutant Emissions by Maritime Transport—A Literature Review T. Batista et al.
- Diurnal NO emission underestimation constrained using overlapping TROPOMI swaths Q. He et al.
- Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: benefit of using time-contiguous input features for machine learning models J. Gödeke et al.
- Machine Learning-Based Estimation of Surface NO2 Concentrations over China: A Comparative Analysis of Geostationary (GEMS) and Polar-Orbiting (TROPOMI) Satellite Data Y. Ma et al.
- Validating tropospheric NO2 column density from GEMS version 3.0 and Tropospheric Chemistry Reanalysis version 2 from background to urban conditions over Japan: with a focus on diurnal variations P. Ha et al.
- Fiducial Reference Measurements for Air Quality Monitoring Using Ground-Based MAX-DOAS Instruments (FRM4DOAS) M. Van Roozendael et al.
- Diurnal variations of NO2 tropospheric vertical column density over the Seoul metropolitan area from the Geostationary Environment Monitoring Spectrometer (GEMS): seasonal differences and the influence of the a priori NO2 profile S. Seo et al.
- Unraveling overestimated exposure risks through hourly ozone retrievals from next-generation geostationary satellites S. Li et al.
- Global analysis of nitrogen dioxide and formaldehyde column densities from the Pandora global network: Variability and implications for satellite validation J. Park et al.
- Tropospheric nitrogen dioxide levels vary diurnally in Asian cities J. Park et al.
- Diagnosing the underperformance of satellite-based surface NO2 estimation using geostationary observations: Insights for improvement from station-type and temporal analyses in South Korea S. Park et al.
- Introduction of Ground-based Remote Sensing and Applications for Air Quality Monitoring S. Park et al.
Saved (final revised paper)
Latest update: 30 Apr 2026
Short summary
Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS, launched in February 2020, is the first instrument in geostationary orbit and covers a large part of Asia. Our investigations show the observed diurnal evolution of NO2 at different measurement sites.
Instruments for air quality observations on geostationary satellites provide multiple...
Special issue