Articles | Volume 20, issue 11
https://doi.org/10.5194/acp-20-6631-2020
© 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/acp-20-6631-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jun 2020
Research article |
| 05 Jun 2020
| 05 Jun 2020
Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis
Yi Wang
CORRESPONDING AUTHOR
Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA 52242, USA
Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA 52242, USA
Department of Chemical and Biochemical Engineering, and Center for
Global and Regional Environmental Research, The University of Iowa, Iowa
City, IA 52242, USA
Xiaoguang Xu
Department of Chemical and Biochemical Engineering, and Center for
Global and Regional Environmental Research, The University of Iowa, Iowa
City, IA 52242, USA
Joint Center for Earth Systems Technology and Department of Physics,
University of Maryland Baltimore County, Baltimore, Maryland, MD 21250, USA
Daven K. Henze
Department of Mechanical Engineering, University of Colorado Boulder,
Boulder, CO 80309, USA
Department of Mechanical Engineering, University of Colorado Boulder,
Boulder, CO 80309, USA
Department of Atmospheric and Oceanic Sciences, University of Maryland,
College Park, MD 20742, USA
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Cited
17 citations as recorded by crossref.
- Application Potential of Satellite Thermal Anomaly Products in Updating Industrial Emission Inventory of China R. Li et al. 10.1029/2021GL092997
- Inverse modeling of SO<sub>2</sub> and NO<sub><i>x</i></sub> emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts Y. Wang et al. 10.5194/acp-20-6651-2020
- 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
- A satellite-data-driven framework to rapidly quantify air-basin-scale NO<sub><i>x</i></sub> emissions and its application to the Po Valley during the COVID-19 pandemic K. Sun et al. 10.5194/acp-21-13311-2021
- Optimization and Evaluation of SO2 Emissions Based on WRF-Chem and 3DVAR Data Assimilation Y. Hu et al. 10.3390/rs14010220
- Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation A. Yarce Botero et al. 10.3390/atmos12121633
- Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method Y. Mao et al. 10.1016/j.scitotenv.2024.171585
- Air quality modeling in the metropolitan area of São Paulo, Brazil: A review M. Gavidia-Calderón et al. 10.1016/j.atmosenv.2023.120301
- An integrated view of correlated emissions of greenhouse gases and air pollutants in China X. Lin et al. 10.1186/s13021-023-00229-x
- Aggravated surface O3 pollution primarily driven by meteorological variations in China during the 2020 COVID-19 pandemic lockdown period Z. Lu et al. 10.5194/acp-24-7793-2024
- Is the efficacy of satellite-based inversion of SO2 emission model dependent? N. Li et al. 10.1088/1748-9326/abe829
- Improved modelling of soil NO x emissions in a high temperature agricultural region: role of background emissions on NO2 trend over the US Y. Wang et al. 10.1088/1748-9326/ac16a3
- Inferring and evaluating satellite-based constraints on NOx emissions estimates in air quality simulations J. East et al. 10.5194/acp-22-15981-2022
- 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
- Multisource Remote Sensing Based Estimation of Soil NOx Emissions From Fertilized Cropland at High‐Resolution: Spatio‐Temporal Patterns and Impacts Y. Shen et al. 10.1029/2022JD036741
- Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
- Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy J. Park et al. 10.5194/amt-16-3039-2023
17 citations as recorded by crossref.
- Application Potential of Satellite Thermal Anomaly Products in Updating Industrial Emission Inventory of China R. Li et al. 10.1029/2021GL092997
- Inverse modeling of SO<sub>2</sub> and NO<sub><i>x</i></sub> emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts Y. Wang et al. 10.5194/acp-20-6651-2020
- 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
- A satellite-data-driven framework to rapidly quantify air-basin-scale NO<sub><i>x</i></sub> emissions and its application to the Po Valley during the COVID-19 pandemic K. Sun et al. 10.5194/acp-21-13311-2021
- Optimization and Evaluation of SO2 Emissions Based on WRF-Chem and 3DVAR Data Assimilation Y. Hu et al. 10.3390/rs14010220
- Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation A. Yarce Botero et al. 10.3390/atmos12121633
- Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method Y. Mao et al. 10.1016/j.scitotenv.2024.171585
- Air quality modeling in the metropolitan area of São Paulo, Brazil: A review M. Gavidia-Calderón et al. 10.1016/j.atmosenv.2023.120301
- An integrated view of correlated emissions of greenhouse gases and air pollutants in China X. Lin et al. 10.1186/s13021-023-00229-x
- Aggravated surface O3 pollution primarily driven by meteorological variations in China during the 2020 COVID-19 pandemic lockdown period Z. Lu et al. 10.5194/acp-24-7793-2024
- Is the efficacy of satellite-based inversion of SO2 emission model dependent? N. Li et al. 10.1088/1748-9326/abe829
- Improved modelling of soil NO x emissions in a high temperature agricultural region: role of background emissions on NO2 trend over the US Y. Wang et al. 10.1088/1748-9326/ac16a3
- Inferring and evaluating satellite-based constraints on NOx emissions estimates in air quality simulations J. East et al. 10.5194/acp-22-15981-2022
- 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
- Multisource Remote Sensing Based Estimation of Soil NOx Emissions From Fertilized Cropland at High‐Resolution: Spatio‐Temporal Patterns and Impacts Y. Shen et al. 10.1029/2022JD036741
- Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
- Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy J. Park et al. 10.5194/amt-16-3039-2023
Latest update: 13 Dec 2024
Short summary
The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO2 and NO2 and the consideration of NH3 uncertainty. Independent validation is performed with OMI SO2 and NO2 data. It is shown that simultaneous inversion of NO2 and SO2 from OMPS provides an effective way to rapidly update emissions.
The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented...
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