Articles | Volume 23, issue 4
https://doi.org/10.5194/acp-23-2465-2023
© 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/acp-23-2465-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Feb 2023
Research article |
| 22 Feb 2023
| 22 Feb 2023
Tropospheric NO2 vertical profiles over South Korea and their relation to oxidant chemistry: implications for geostationary satellite retrievals and the observation of NO2 diurnal variation from space
Laura Hyesung Yang
CORRESPONDING AUTHOR
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Daniel J. Jacob
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA 01238, USA
Nadia K. Colombi
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA 01238, USA
Shixian Zhai
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Kelvin H. Bates
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Department of Environmental
Toxicology, University of California Davis, Davis, CA 95616, USA
Viral Shah
Global Modeling and Assimilation Office, NASA Goddard Space Flight
Center, Greenbelt, MD 20771, USA
Science Systems and Applications,
Inc., Lanham, MD 20706, USA
Ellie Beaudry
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Robert M. Yantosca
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Haipeng Lin
John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138, USA
Jared F. Brewer
Department of Soil, Water and Climate, University of Minnesota, St.
Paul, MN 55108, USA
Heesung Chong
Harvard-Smithsonian Center for Astrophysics, Cambridge,
MA 02138, USA
Katherine R. Travis
NASA Langley Research Center, Hampton, VA 23666, USA
James H. Crawford
NASA Langley Research Center, Hampton, VA 23666, USA
Lok N. Lamsal
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland Baltimore County, Baltimore, MD 21250, USA
Ja-Ho Koo
Department of Atmospheric Sciences, Yonsei University, Seoul 03722, South Korea
Jhoon Kim
Department of Atmospheric Sciences, Yonsei University, Seoul 03722, South Korea
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20 citations as recorded by crossref.
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- Anthropogenic NO x emissions of China, the U.S. and Europe from 2019 to 2022 inferred from TROPOMI observations Y. Mao et al. 10.1088/1748-9326/ad3cf9
- Quantifying the diurnal variation in atmospheric NO2 from Geostationary Environment Monitoring Spectrometer (GEMS) observations D. Edwards et al. 10.5194/acp-24-8943-2024
- TROPOMI NO2 Sentinel-5P data in the Community of Madrid: A detailed consistency analysis with in situ surface observations C. Morillas et al. 10.1016/j.rsase.2023.101083
- A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm Y. Zhang et al. 10.5194/amt-16-4643-2023
- Interpreting Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite observations of the diurnal variation in nitrogen dioxide (NO2) over East Asia L. Yang et al. 10.5194/acp-24-7027-2024
- Interpreting summertime hourly variation of NO2 columns with implications for geostationary satellite applications D. Chatterjee et al. 10.5194/acp-24-12687-2024
- 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
- Why is ozone in South Korea and the Seoul metropolitan area so high and increasing? N. Colombi et al. 10.5194/acp-23-4031-2023
- Intercomparison of GEOS-Chem and CAM-chem tropospheric oxidant chemistry within the Community Earth System Model version 2 (CESM2) H. Lin et al. 10.5194/acp-24-8607-2024
- Impact of improved representation of volatile organic compound emissions and production of NOx reservoirs on modeled urban ozone production K. Travis et al. 10.5194/acp-24-9555-2024
- Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations M. Ghahremanloo et al. 10.1016/j.envint.2024.108818
- Informing Near-Airport Satellite NO2 Retrievals Using Pandora Sky-Scanning Observations A. Mouat et al. 10.1021/acsestair.4c00158
- Observational Evidence of Unknown NOx Source and Its Perturbation of Oxidative Capacity in Bermuda's Marine Boundary Layer Y. Wang et al. 10.1029/2023JD039582
- Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning N. Ahmad et al. 10.1016/j.chemosphere.2023.140615
- Changes in Domestic Emissions Impact on Provincial PM2.5 and NO2 Concentrations during the 1st to 4th Seasonal PM Management Periods J. Seo et al. 10.5572/KOSAE.2024.40.2.242
- A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument Y. Oak et al. 10.5194/amt-17-5147-2024
- Long-term variations and trends of tropospheric and ground-level NO2 over typical coastal areas X. Tian et al. 10.1016/j.ecolind.2024.112163
- Estimation of ground-level NO2 and its spatiotemporal variations in China using GEMS measurements and a nested machine learning model N. Ahmad et al. 10.5194/acp-24-9645-2024
- A Scheme for Representing Aromatic Secondary Organic Aerosols in Chemical Transport Models: Application to Source Attribution of Organic Aerosols Over South Korea During the KORUS‐AQ Campaign J. Brewer et al. 10.1029/2022JD037257
19 citations as recorded by crossref.
- First evaluation of the GEMS formaldehyde product against TROPOMI and ground-based column measurements during the in-orbit test period G. Lee et al. 10.5194/acp-24-4733-2024
- Anthropogenic NO x emissions of China, the U.S. and Europe from 2019 to 2022 inferred from TROPOMI observations Y. Mao et al. 10.1088/1748-9326/ad3cf9
- Quantifying the diurnal variation in atmospheric NO2 from Geostationary Environment Monitoring Spectrometer (GEMS) observations D. Edwards et al. 10.5194/acp-24-8943-2024
- TROPOMI NO2 Sentinel-5P data in the Community of Madrid: A detailed consistency analysis with in situ surface observations C. Morillas et al. 10.1016/j.rsase.2023.101083
- A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm Y. Zhang et al. 10.5194/amt-16-4643-2023
- Interpreting Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite observations of the diurnal variation in nitrogen dioxide (NO2) over East Asia L. Yang et al. 10.5194/acp-24-7027-2024
- Interpreting summertime hourly variation of NO2 columns with implications for geostationary satellite applications D. Chatterjee et al. 10.5194/acp-24-12687-2024
- 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
- Why is ozone in South Korea and the Seoul metropolitan area so high and increasing? N. Colombi et al. 10.5194/acp-23-4031-2023
- Intercomparison of GEOS-Chem and CAM-chem tropospheric oxidant chemistry within the Community Earth System Model version 2 (CESM2) H. Lin et al. 10.5194/acp-24-8607-2024
- Impact of improved representation of volatile organic compound emissions and production of NOx reservoirs on modeled urban ozone production K. Travis et al. 10.5194/acp-24-9555-2024
- Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations M. Ghahremanloo et al. 10.1016/j.envint.2024.108818
- Informing Near-Airport Satellite NO2 Retrievals Using Pandora Sky-Scanning Observations A. Mouat et al. 10.1021/acsestair.4c00158
- Observational Evidence of Unknown NOx Source and Its Perturbation of Oxidative Capacity in Bermuda's Marine Boundary Layer Y. Wang et al. 10.1029/2023JD039582
- Effects of meteorological conditions on the mixing height of Nitrogen dioxide in China using new-generation geostationary satellite measurements and machine learning N. Ahmad et al. 10.1016/j.chemosphere.2023.140615
- Changes in Domestic Emissions Impact on Provincial PM2.5 and NO2 Concentrations during the 1st to 4th Seasonal PM Management Periods J. Seo et al. 10.5572/KOSAE.2024.40.2.242
- A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument Y. Oak et al. 10.5194/amt-17-5147-2024
- Long-term variations and trends of tropospheric and ground-level NO2 over typical coastal areas X. Tian et al. 10.1016/j.ecolind.2024.112163
- Estimation of ground-level NO2 and its spatiotemporal variations in China using GEMS measurements and a nested machine learning model N. Ahmad et al. 10.5194/acp-24-9645-2024
Latest update: 23 Nov 2024
Short summary
A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2...
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