Articles | Volume 13, issue 11
https://doi.org/10.5194/amt-13-6175-2020
© Author(s) 2020. 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-13-6175-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Nov 2020
Research article |
| 19 Nov 2020
| 19 Nov 2020
Version 2 Ozone Monitoring Instrument SO2 product (OMSO2 V2): new anthropogenic SO2 vertical column density dataset
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Nickolay A. Krotkov
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Peter J. T. Leonard
ADNET Systems, Inc., Lanham, MD 20706, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Simon Carn
Michigan Technological University, Houghton, MI 49931, USA
Joanna Joiner
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Robert J. D. Spurr
RT Solutions Inc., Cambridge, MA 02138, USA
Alexander Vasilkov
Science Systems and Applications Inc., Lanham, MD 20706, USA
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- Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0 C. Keller et al. 10.1029/2020MS002413
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- Understanding the Trend of NO2, SO2 and CO over East Africa from 2005 to 2020 R. Opio et al. 10.3390/atmos12101283
- Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage G. Gamal et al. 10.3390/su15129362
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- NeSNet: A Deep Network for Estimating Near-Surface Pollutant Concentrations P. Dey et al. 10.1109/JSTARS.2023.3244719
- A data-augmentation approach to deriving long-term surface SO2 across Northern China: Implications for interpretable machine learning S. Zhang et al. 10.1016/j.scitotenv.2022.154278
- In-plume and out-of-plume analysis of aerosol–cloud interactions derived from the 2014–2015 Holuhraun volcanic eruption A. Peace et al. 10.5194/acp-24-9533-2024
- A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources N. Theys et al. 10.5194/acp-21-16727-2021
- Remote sensing of eruptions and transport of Taal volcano in January 2020 J. Nee et al. 10.1364/AO.524145
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- Differential response of chlorophyll-a concentrations to explosive volcanism in the western South Pacific J. Yoon et al. 10.3389/fmars.2023.1072610
- An assessment of China's industrial emission characteristics using satellite observations of XCO2, SO2, and NO2 Y. Fu et al. 10.1016/j.apr.2022.101486
26 citations as recorded by crossref.
- Effects of emission control areas on sulfur-oxides concentrations——Evidence from the coastal ports in China L. Xu et al. 10.1016/j.marpolbul.2024.116039
- Impact of SO2 Flux Estimation in the Modeling of the Plume of Mount Etna Christmas 2018 Eruption and Comparison against Multiple Satellite Sensors C. Lamotte et al. 10.3390/rs15030758
- Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0 C. Keller et al. 10.1029/2020MS002413
- Version 1 NOAA-20/OMPS Nadir Mapper total column SO2 product: continuation of NASA long-term global data record C. Li et al. 10.5194/essd-16-4291-2024
- Impact of Short-Term Emission Control Measures on Air Quality in Nanjing During the Jiangsu Development Summit H. Zhang et al. 10.3389/fenvs.2021.693513
- Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases M. Bilal et al. 10.1016/j.rse.2021.112617
- Assessment of air quality in North Korea from satellite observations H. Chong et al. 10.1016/j.envint.2022.107708
- The effectiveness of emission control policies in regulating air pollution over coastal ports of China: Spatiotemporal variations of NO2 and SO2 Y. Zhang et al. 10.1016/j.ocecoaman.2022.106064
- SO2 mitigation in China's coal-fired power plants: A satellite-based assessment on compliance and enforcement X. Yan & Y. Xu 10.1016/j.atmosenv.2021.118396
- Assessment of the Performance of TROPOMI NO2 and SO2 Data Products in the North China Plain: Comparison, Correction and Application C. Wang et al. 10.3390/rs14010214
- Understanding the Trend of NO2, SO2 and CO over East Africa from 2005 to 2020 R. Opio et al. 10.3390/atmos12101283
- Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage G. Gamal et al. 10.3390/su15129362
- GCAP 2.0: a global 3-D chemical-transport model framework for past, present, and future climate scenarios L. Murray et al. 10.5194/gmd-14-5789-2021
- Estimation of the ground-level SO2 concentration in eastern China based on the LightGBM model and Himawari-8 TOAR T. Xu et al. 10.3389/feart.2022.1037719
- A new machine-learning-based analysis for improving satellite-retrieved atmospheric composition data: OMI SO2 as an example C. Li et al. 10.5194/amt-15-5497-2022
- Comprehensive Evaluation of Spatial Distribution and Temporal Trend of NO2, SO2 and AOD Using Satellite Observations over South and East Asia from 2011 to 2021 M. Rahman et al. 10.3390/rs15205069
- Version 2 of the global catalogue of large anthropogenic and volcanic SO2 sources and emissions derived from satellite measurements V. Fioletov et al. 10.5194/essd-15-75-2023
- Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground V. Fioletov et al. 10.5194/amt-16-5575-2023
- NeSNet: A Deep Network for Estimating Near-Surface Pollutant Concentrations P. Dey et al. 10.1109/JSTARS.2023.3244719
- A data-augmentation approach to deriving long-term surface SO2 across Northern China: Implications for interpretable machine learning S. Zhang et al. 10.1016/j.scitotenv.2022.154278
- In-plume and out-of-plume analysis of aerosol–cloud interactions derived from the 2014–2015 Holuhraun volcanic eruption A. Peace et al. 10.5194/acp-24-9533-2024
- A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources N. Theys et al. 10.5194/acp-21-16727-2021
- Remote sensing of eruptions and transport of Taal volcano in January 2020 J. Nee et al. 10.1364/AO.524145
- Raw EPIC Data Calibration A. Cede et al. 10.3389/frsen.2021.702275
- Differential response of chlorophyll-a concentrations to explosive volcanism in the western South Pacific J. Yoon et al. 10.3389/fmars.2023.1072610
- An assessment of China's industrial emission characteristics using satellite observations of XCO2, SO2, and NO2 Y. Fu et al. 10.1016/j.apr.2022.101486
Latest update: 18 Nov 2024
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.
Sulfur dioxide (SO2) is an important pollutant that causes haze and acid rain. The Ozone...
