Articles | Volume 11, issue 7
https://doi.org/10.5194/amt-11-3955-2018
© Author(s) 2018. 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-11-3955-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Jul 2018
Research article |
| 06 Jul 2018
| 06 Jul 2018
Comparing OMI-based and EPA AQS in situ NO2 trends: towards understanding surface NOx emission changes
Ruixiong Zhang
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Charles Smeltzer
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Hang Qu
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
William Koshak
NASA-Marshall Space Flight Center, National Space Science & Technology Center, 320 Sparkman Drive, Huntsville, Alabama, USA
K. Folkert Boersma
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
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- Using satellite observations of tropospheric NO2 columns to infer long-term trends in US NOx emissions: the importance of accounting for the free tropospheric NO2 background R. Silvern et al. 10.5194/acp-19-8863-2019
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- How Does COVID-19 Lockdown Impact Air Quality in India? Z. Hu et al. 10.3390/rs14081869
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- Remote Sensing Measurements at a Rural Site in China: Implications for Satellite NO2 and HCHO Measurement Uncertainty and Emissions From Fires K. Chong et al. 10.1029/2023JD039310
- Toxicity Impact Assessment of Nitrogen Oxide and Sulfur Dioxide Emissions in China’s Textile Industry With Chemical Footprint Method Y. Guo et al. 10.1177/24723444231161744
- Toward Better and Healthier Air Quality: Global PM2.5 and O3 Pollution Status and Risk Assessment Based on the New WHO Air Quality Guidelines for 2021 J. Liu et al. 10.1002/gch2.202300258
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- Trend reversal from source region to remote tropospheric NO2 columns X. Cai et al. 10.1007/s11356-021-16857-0
- Global-Scale Patterns and Trends in Tropospheric NO2 Concentrations, 2005–2018 S. Jamali et al. 10.3390/rs12213526
- Temporal Analysis of OMI-Observed Tropospheric NO2 Columns over East Asia during 2006–2015 K. Han 10.3390/atmos10110658
- Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019 D. Goldberg et al. 10.1088/1748-9326/ac2c34
- Dependence of Summertime Surface Ozone on NOx and VOC Emissions Over the United States: Peak Time and Value J. Li et al. 10.1029/2018GL081823
- Long-term trends in urban NO2 concentrations and associated paediatric asthma incidence: estimates from global datasets S. Anenberg et al. 10.1016/S2542-5196(21)00255-2
- Isoprene Mixing Ratios Measured at Twenty Sites in China During 2012–2014: Comparison With Model Simulation Y. Zhang et al. 10.1029/2020JD033523
- Disentangling the Impact of the COVID‐19 Lockdowns on Urban NO2 From Natural Variability D. Goldberg et al. 10.1029/2020GL089269
- Impact of COVID-19 restrictions liberalization on air quality: a case study of Chongqing, Southwest China H. Wang et al. 10.1007/s10661-024-13213-w
- Mid-gap states induced by sulfur substitution in ZnO nanoparticle via low solvothermal temperature for enhanced photocatalytic NOx removal under visible light irradiation A. Taufik et al. 10.1016/j.mssp.2025.109299
- Tracking NO2 Pollution Changes Over Texas: Synthesis of In Situ and Satellite Observations M. Gyawali et al. 10.1029/2022JD037473
- Extending Ozone‐Precursor Relationships in China From Peak Concentration to Peak Time H. Qu et al. 10.1029/2020JD033670
- Chemical Production of Oxygenated Volatile Organic Compounds Strongly Enhances Boundary-Layer Oxidation Chemistry and Ozone Production H. Qu et al. 10.1021/acs.est.1c04489
- Tropospheric NO2: Anthropogenic Influence, Global Trends, Satellite Data, and Machine Learning Application V. Ojeda-Castillo et al. 10.3390/rs17010049
- Measuring and Monitoring Urban Impacts on Climate Change from Space C. Milesi & G. Churkina 10.3390/rs12213494
- The 2020 Italian Spring Lockdown: A Multidisciplinary Analysis over the Milan Urban Area M. Migliaccio et al. 10.3390/world2030025
- The Effects of COVID-19 Lockdown on Air Pollutant Concentrations across China: A Google Earth Engine-Based Analysis S. Wang et al. 10.3390/ijerph192417056
- Impact of COVID-19 Lockdown on Air Pollutants in a Coastal Area of the Yangtze River Delta, China, Measured by a Low-Cost Sensor Package L. Chen et al. 10.3390/atmos12030345
- Combing GOME-2B and OMI Satellite Data to Estimate Near-Surface NO2 of Mainland China D. Li et al. 10.1109/JSTARS.2021.3117396
- LNOx Emission Model for Air Quality and Climate Studies Using Satellite Lightning Mapper Observations Y. Wu et al. 10.1029/2022JD037406
- Impacts of reduced deposition of atmospheric nitrogen on coastal marine eco-system during substantial shift in human activities in the twenty-first century F. Mumtaz et al. 10.1080/19475705.2021.1949396
- Evidence of heterogeneous HONO formation from aerosols and the regional photochemical impact of this HONO source X. Lu et al. 10.1088/1748-9326/aae492
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- Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NOx emissions J. Li et al. 10.5194/acp-21-11133-2021
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Latest update: 02 Apr 2025
Short summary
This study focuses on how to improve OMI NO2 retrievals for trend analysis. We retrieve OMI tropospheric NO2 vertical column densities (VCDs) and obtain the NO2 seasonal trends over the United States, which are compared with coincident in situ surface NO2 measurements from the Air Quality System network. We find that three procedures are essential in comparing both datasets, including the ocean trend removal, the albedo update, and the lightning filter.
This study focuses on how to improve OMI NO2 retrievals for trend analysis. We retrieve OMI...
