Articles | Volume 17, issue 20
https://doi.org/10.5194/amt-17-6163-2024
https://doi.org/10.5194/amt-17-6163-2024
Research article
 | 
23 Oct 2024
Research article |  | 23 Oct 2024

Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS

Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim

Related authors

Investigation of meteorological conditions and BrO during ozone depletion events in Ny-Ålesund between 2010 and 2021
Bianca Zilker, Andreas Richter, Anne-Marlene Blechschmidt, Peter von der Gathen, Ilias Bougoudis, Sora Seo, Tim Bösch, and John Philip Burrows
Atmos. Chem. Phys., 23, 9787–9814, https://doi.org/10.5194/acp-23-9787-2023,https://doi.org/10.5194/acp-23-9787-2023, 2023
Short summary
Spatial distribution of enhanced BrO and its relation to meteorological parameters in Arctic and Antarctic sea ice regions
Sora Seo, Andreas Richter, Anne-Marlene Blechschmidt, Ilias Bougoudis, and John Philip Burrows
Atmos. Chem. Phys., 20, 12285–12312, https://doi.org/10.5194/acp-20-12285-2020,https://doi.org/10.5194/acp-20-12285-2020, 2020
Short summary
Long-term time series of Arctic tropospheric BrO derived from UV–VIS satellite remote sensing and its relation to first-year sea ice
Ilias Bougoudis, Anne-Marlene Blechschmidt, Andreas Richter, Sora Seo, John Philip Burrows, Nicolas Theys, and Annette Rinke
Atmos. Chem. Phys., 20, 11869–11892, https://doi.org/10.5194/acp-20-11869-2020,https://doi.org/10.5194/acp-20-11869-2020, 2020
Short summary
First high-resolution BrO column retrievals from TROPOMI
Sora Seo, Andreas Richter, Anne-Marlene Blechschmidt, Ilias Bougoudis, and John Philip Burrows
Atmos. Meas. Tech., 12, 2913–2932, https://doi.org/10.5194/amt-12-2913-2019,https://doi.org/10.5194/amt-12-2913-2019, 2019
Short summary
An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks
Brent N. Holben, Jhoon Kim, Itaru Sano, Sonoyo Mukai, Thomas F. Eck, David M. Giles, Joel S. Schafer, Aliaksandr Sinyuk, Ilya Slutsker, Alexander Smirnov, Mikhail Sorokin, Bruce E. Anderson, Huizheng Che, Myungje Choi, James H. Crawford, Richard A. Ferrare, Michael J. Garay, Ukkyo Jeong, Mijin Kim, Woogyung Kim, Nichola Knox, Zhengqiang Li, Hwee S. Lim, Yang Liu, Hal Maring, Makiko Nakata, Kenneth E. Pickering, Stuart Piketh, Jens Redemann, Jeffrey S. Reid, Santo Salinas, Sora Seo, Fuyi Tan, Sachchida N. Tripathi, Owen B. Toon, and Qingyang Xiao
Atmos. Chem. Phys., 18, 655–671, https://doi.org/10.5194/acp-18-655-2018,https://doi.org/10.5194/acp-18-655-2018, 2018
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
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
Atmos. Meas. Tech., 17, 6485–6516, https://doi.org/10.5194/amt-17-6485-2024,https://doi.org/10.5194/amt-17-6485-2024, 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

Cited articles

An, J., Shi, Y., Wang, J., and Zhu, B.: Temporal Variations of O3 and NOx in the Urban Background Atmosphere of Nanjing, East China, Arch. Environ. Cont. Tox., 71, 224–234, https://doi.org/10.1007/s00244-016-0290-8, 2016. 
Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys., 3, 2225–2232, https://doi.org/10.5194/acp-3-2225-2003, 2003. 
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity emissions and lifetimes of nitrogen oxides probed from space, Science, 333, 1737–1739, 2011. 
Beirle, S., Hörmann, C., Jöckel, P., Liu, S., Penning de Vries, M., Pozzer, A., Sihler, H., Valks, P., and Wagner, T.: The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution, Atmos. Meas. Tech., 9, 2753–2779, https://doi.org/10.5194/amt-9-2753-2016, 2016. 
Belmonte Rivas, M., Veefkind, P., Boersma, F., Levelt, P., Eskes, H., and Gille, J.: Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations, Atmos. Meas. Tech., 7, 2203–2225, https://doi.org/10.5194/amt-7-2203-2014, 2014. 
Download
Short summary
In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.