Articles | Volume 13, issue 11
https://doi.org/10.5194/amt-13-6175-2020
https://doi.org/10.5194/amt-13-6175-2020
Research article
 | 
19 Nov 2020
Research article |  | 19 Nov 2020

Version 2 Ozone Monitoring Instrument SO2 product (OMSO2 V2): new anthropogenic SO2 vertical column density dataset

Can Li, Nickolay A. Krotkov, Peter J. T. Leonard, Simon Carn, Joanna Joiner, Robert J. D. Spurr, and Alexander Vasilkov

Related authors

Version 1 NOAA-20/OMPS Nadir Mapper total column SO2 product: continuation of NASA long-term global data record
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024,https://doi.org/10.5194/essd-16-4291-2024, 2024
Short summary
Opinion: Beyond Global Means: Novel Space-Based Approaches to Indirectly Constrain the Concentrations, Trends, and Variations of Tropospheric Hydroxyl Radical (OH)
Bryan Duncan, Daniel Anderson, Arlene Fiore, Joanna Joiner, Nickolay Krotkov, Can Li, Dylan Millet, Julie Nicely, Luke Oman, Jason St. Clair, Joshua Shutter, Amir Souri, Sarah Strode, Brad Weir, Glenn Wolfe, Helen Worden, and Qindan Zhu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2331,https://doi.org/10.5194/egusphere-2024-2331, 2024
Short summary
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023,https://doi.org/10.5194/amt-16-5575-2023, 2023
Short summary
Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023,https://doi.org/10.5194/amt-16-481-2023, 2023
Short summary
Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023,https://doi.org/10.5194/acp-23-1511-2023, 2023
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
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
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024,https://doi.org/10.5194/amt-17-6163-2024, 2024
Short summary

Cited articles

Ahmad, Z., P. K. Bhartia, P. K., and Krotkov, N.: Spectral properties of backscattered UV radiation in cloudy atmospheres, J. Geophys. Res., 109, D01201, https://doi.org/10.1029/2003JD003395, 2004. 
Bhartia, P. K.: OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/Aura/OMI/DATA2024, 2005. 
Can, L., Krotkov, N. A., Leonard, P., and Joiner, J.: OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13×24 km V003, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/Aura/OMI/DATA2022, 2020. 
Carn, S. A., Fioletov, V. E., McLinden, C. A., Li, C., and Krotkov, N. A.: A decade of global volcanic SO2 emissions measured from space, Sci. Rep., 7, 44095; https://doi.org/10.1038/srep44095, 2017. 
Download
Short summary
Sulfur dioxide (SO2) is an important pollutant that causes haze and acid rain. The Ozone Monitoring Instrument (OMI) has been providing global observation of SO2 from space for over 15 years. In this paper, we introduce a new OMI SO2 dataset for global pollution monitoring. The dataset better accounts for the influences of different factors such as location and sun and satellite angles, leading to improved data quality. The new OMI SO2 dataset is publicly available through NASA's data center.