Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4247-2020
© 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-13-4247-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Aug 2020
Research article |
| 13 Aug 2020
| 13 Aug 2020
A new TROPOMI product for tropospheric NO2 columns over East Asia with explicit aerosol corrections
Mengyao Liu
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
now at: R&D Satellite Observations Department, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
Hao Kong
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
K. Folkert Boersma
R&D Satellite Observations Department, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Meteorology and Air Quality department, Wageningen University,
Wageningen, the Netherlands
Henk Eskes
R&D Satellite Observations Department, Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Yugo Kanaya
Research Institute for Global Change, Japan Agency for Marine-Earth
Science and Technology (JAMSTEC), Yokohama 2360001, Japan
School of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China
Institutes of Physical Science and Information Technology, Anhui
University, Hefei, 230601, China
Key Laboratory of Environmental Optics and Technology, Anhui
Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei,
230031, China
School of Environment and Geoinformatics, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China
Pinhua Xie
Institutes of Physical Science and Information Technology, Anhui
University, Hefei, 230601, China
Key Laboratory of Environmental Optics and Technology, Anhui
Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei,
230031, China
CAS Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Robert Spurr
RT Solutions Inc., Cambridge, Massachusetts 02138, USA
Ruijing Ni
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
Yingying Yan
Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan, China
Hongjian Weng
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
Jingxu Wang
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing, China
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41 citations as recorded by crossref.
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- Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals Z. Zhao et al. 10.1016/j.scitotenv.2023.166693
- Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons J. Park et al. 10.1080/15481603.2022.2026640
- Evaluation of TROPOMI and OMI Tropospheric NO2 Products Using Measurements from MAX-DOAS and State-Controlled Stations in the Jiangsu Province of China K. Cai et al. 10.3390/atmos13060886
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- Using a New Top‐Down Constrained Emissions Inventory to Attribute the Previously Unknown Source of Extreme Aerosol Loadings Observed Annually in the Monsoon Asia Free Troposphere S. Wang et al. 10.1029/2021EF002167
- Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements V. Kumar et al. 10.5194/amt-14-5241-2021
- Tracking SO <sub>2</sub> Plumes From the Tonga Volcano Eruption With Multi-Satellite Observations C. Xia et al. 10.2139/ssrn.4193122
- Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements Q. He et al. 10.1088/1748-9326/abc7df
- Evaluating Sentinel-5P TROPOMI tropospheric NO<sub>2</sub> column densities with airborne and Pandora spectrometers near New York City and Long Island Sound L. Judd et al. 10.5194/amt-13-6113-2020
- First Chinese ultraviolet–visible hyperspectral satellite instrument implicating global air quality during the COVID-19 pandemic in early 2020 C. Liu et al. 10.1038/s41377-022-00722-x
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- Tracking SO2 plumes from the Tonga volcano eruption with multi-satellite observations C. Xia et al. 10.1016/j.isci.2024.109446
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- Combing GOME-2B and OMI Satellite Data to Estimate Near-Surface NO2 of Mainland China D. Li et al. 10.1109/JSTARS.2021.3117396
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
- An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe S. Liu et al. 10.5194/amt-14-7297-2021
- High natural nitric oxide emissions from lakes on Tibetan Plateau under rapid warming H. Kong et al. 10.1038/s41561-023-01200-8
- Improving machine-learned surface NO2 concentration mapping models with domain knowledge from data science perspective M. Hu et al. 10.1016/j.atmosenv.2024.120372
- 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
- Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires R. Dang et al. 10.5194/acp-23-6271-2023
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- A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification J. Fu et al. 10.1016/j.atmosenv.2023.119756
- Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation D. Griffin et al. 10.5194/amt-14-7929-2021
- Satellite-based estimates of decline and rebound in China’s CO 2 emissions during COVID-19 pandemic B. Zheng et al. 10.1126/sciadv.abd4998
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- Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2 Q. Zhang et al. 10.5194/acp-23-551-2023
- Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic C. Xia et al. 10.1021/acs.est.1c01970
- Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence J. Wei et al. 10.1021/acs.est.2c03834
- Examining the status of improved air quality in world cities due to COVID-19 led temporary reduction in anthropogenic emissions S. Sannigrahi et al. 10.1016/j.envres.2021.110927
- The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia J. Jung et al. 10.1029/2021JD035251
- NOx Emission Reduction and Recovery during COVID-19 in East China R. Zhang et al. 10.3390/atmos11040433
40 citations as recorded by crossref.
- Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble J. Douros et al. 10.5194/gmd-16-509-2023
- Stereoscopic hyperspectral remote sensing of the atmospheric environment: Innovation and prospects C. Liu et al. 10.1016/j.earscirev.2022.103958
- Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals Z. Zhao et al. 10.1016/j.scitotenv.2023.166693
- Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons J. Park et al. 10.1080/15481603.2022.2026640
- Evaluation of TROPOMI and OMI Tropospheric NO2 Products Using Measurements from MAX-DOAS and State-Controlled Stations in the Jiangsu Province of China K. Cai et al. 10.3390/atmos13060886
- High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models X. Man et al. 10.1016/j.envres.2024.118609
- Using a New Top‐Down Constrained Emissions Inventory to Attribute the Previously Unknown Source of Extreme Aerosol Loadings Observed Annually in the Monsoon Asia Free Troposphere S. Wang et al. 10.1029/2021EF002167
- Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements V. Kumar et al. 10.5194/amt-14-5241-2021
- Tracking SO <sub>2</sub> Plumes From the Tonga Volcano Eruption With Multi-Satellite Observations C. Xia et al. 10.2139/ssrn.4193122
- Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements Q. He et al. 10.1088/1748-9326/abc7df
- Evaluating Sentinel-5P TROPOMI tropospheric NO<sub>2</sub> column densities with airborne and Pandora spectrometers near New York City and Long Island Sound L. Judd et al. 10.5194/amt-13-6113-2020
- First Chinese ultraviolet–visible hyperspectral satellite instrument implicating global air quality during the COVID-19 pandemic in early 2020 C. Liu et al. 10.1038/s41377-022-00722-x
- Cropland nitrogen dioxide emissions and effects on the ozone pollution in the North China plain R. Wang et al. 10.1016/j.envpol.2021.118617
- Tracking SO2 plumes from the Tonga volcano eruption with multi-satellite observations C. Xia et al. 10.1016/j.isci.2024.109446
- Model-free daily inversion of NOx emissions using TROPOMI (MCMFE-NOx) and its uncertainty: Declining regulated emissions and growth of new sources K. Qin et al. 10.1016/j.rse.2023.113720
- A Novel Hyperspectral Remote Sensing Technique with Hour-Hectometer Level Horizontal Distribution of Trace Gases: To Accurately Identify Emission Sources C. Lu et al. 10.34133/remotesensing.0098
- Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001–2018) S. Liu et al. 10.1021/acs.est.3c02111
- Observation on the aerosol and ozone precursors in suburban areas of Shenzhen and analysis of potential source based on MAX-DOAS H. Zhang et al. 10.1016/j.jes.2022.08.030
- Combing GOME-2B and OMI Satellite Data to Estimate Near-Surface NO2 of Mainland China D. Li et al. 10.1109/JSTARS.2021.3117396
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
- An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe S. Liu et al. 10.5194/amt-14-7297-2021
- High natural nitric oxide emissions from lakes on Tibetan Plateau under rapid warming H. Kong et al. 10.1038/s41561-023-01200-8
- Improving machine-learned surface NO2 concentration mapping models with domain knowledge from data science perspective M. Hu et al. 10.1016/j.atmosenv.2024.120372
- 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
- Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires R. Dang et al. 10.5194/acp-23-6271-2023
- Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models X. Li et al. 10.1016/j.envint.2023.107967
- COVID‐19 Induced Fingerprints of a New Normal Urban Air Quality in the United States S. Kondragunta et al. 10.1029/2021JD034797
- A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification J. Fu et al. 10.1016/j.atmosenv.2023.119756
- Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation D. Griffin et al. 10.5194/amt-14-7929-2021
- Satellite-based estimates of decline and rebound in China’s CO 2 emissions during COVID-19 pandemic B. Zheng et al. 10.1126/sciadv.abd4998
- Sentinel-5P TROPOMI NO<sub>2</sub> retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data J. van Geffen et al. 10.5194/amt-15-2037-2022
- Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks T. Verhoelst et al. 10.5194/amt-14-481-2021
- A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al. 10.1029/2021GL094151
- Assessment of surface ozone production in Qinghai, China with satellite-constrained VOCs and NOx emissions W. Li et al. 10.1016/j.scitotenv.2023.166602
- Estimating city NOX emissions from TROPOMI high spatial resolution observations – A case study on Yangtze River Delta, China R. Xue et al. 10.1016/j.uclim.2022.101150
- Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2 Q. Zhang et al. 10.5194/acp-23-551-2023
- Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic C. Xia et al. 10.1021/acs.est.1c01970
- Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence J. Wei et al. 10.1021/acs.est.2c03834
- Examining the status of improved air quality in world cities due to COVID-19 led temporary reduction in anthropogenic emissions S. Sannigrahi et al. 10.1016/j.envres.2021.110927
- The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia J. Jung et al. 10.1029/2021JD035251
1 citations as recorded by crossref.
Discussed (final revised paper)
Latest update: 25 Apr 2024
Short summary
Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play crucial roles in the formation of ozone and particulate matter. The recently launched TROPOspheric Monitoring Instrument (TROPOMI) provides an opportunity to retrieve tropospheric concentrations of nitrogen dioxide (NO2) at an unprecedented high horizontal resolution. This work presents a new NO2 retrieval product over East Asia and further quantifies key factors affecting the retrieval, including aerosol.
Nitrogen oxides (NOx = NO + NO2) are important air pollutants in the troposphere and play...
