Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-2067-2021
© Author(s) 2021. 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-21-2067-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Feb 2021
Research article |
| 11 Feb 2021
| 11 Feb 2021
High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model
Yilin Chen
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
Huizhong Shen
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
Jennifer Kaiser
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA 30332, United States
Yongtao Hu
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
Shannon L. Capps
Department of Civil, Architectural, and Environmental Engineering,
Drexel University, Philadelphia, PA 19104, United States
Shunliu Zhao
Department of Civil and Environmental Engineering, Carleton
University, Ottawa, Ontario K1S5B6, Canada
Amir Hakami
Department of Civil and Environmental Engineering, Carleton
University, Ottawa, Ontario K1S5B6, Canada
Jhih-Shyang Shih
Resources for the Future, Washington, D.C. 20036, USA
Gertrude K. Pavur
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
Matthew D. Turner
SAIC, Stennis Space Center, MS 39529, USA
Daven K. Henze
Mechanical Engineering Department, University of Colorado, Boulder, CO
80309, USA
Jaroslav Resler
Institute of Computer Science of the Czech Academy of Sciences,
Prague, 182 07, Czech Republic
Athanasios Nenes
Institute for Chemical Engineering Sciences, Foundation for Research
and Technology Hellas, Patras, 26504, Greece
School of Architecture, Civil & Environmental Engineering, Ecole
polytechnique fédérale de Lausanne, 1015, Lausanne, Switzerland
Sergey L. Napelenok
Atmospheric & Environmental Systems Modeling Division, U.S. EPA,
Research Triangle Park, NC 27711, USA
Jesse O. Bash
Atmospheric & Environmental Systems Modeling Division, U.S. EPA,
Research Triangle Park, NC 27711, USA
Kathleen M. Fahey
Atmospheric & Environmental Systems Modeling Division, U.S. EPA,
Research Triangle Park, NC 27711, USA
Gregory R. Carmichael
Department of Chemical and Biochemical Engineering, University of
Iowa, Iowa City, IA 52242, USA
Tianfeng Chai
NOAA Air Resources Laboratory (ARL), Cooperative Institute for
Satellites Earth System Studies (CISESS), University of Maryland, College
Park, MD 20740, USA
Lieven Clarisse
Université libre de Bruxelles (ULB), Spectroscopy, Quantum
Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
Pierre-François Coheur
Université libre de Bruxelles (ULB), Spectroscopy, Quantum
Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
Martin Van Damme
Université libre de Bruxelles (ULB), Spectroscopy, Quantum
Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
School of Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA 30332, United States
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Cited
34 citations as recorded by crossref.
- Reactive Nitrogen from Agriculture: A Review of Emissions, Air Quality, and Climate Impacts L. Luo et al. 10.1007/s40726-025-00360-y
- ISORROPIA‐MCX: Enabling Sensitivity Analysis With Multicomplex Variables in the Aerosol Thermodynamic Model, ISORROPIA B. Berman et al. 10.1029/2022EA002729
- Atmospheric reduced nitrogen: Sources, transformations, effects, and management C. Driscoll et al. 10.1080/10962247.2024.2342765
- Integrating Machine Learning with Causal Inference to Improve Prediction of Ammonium Wet Deposition in the Pearl River Delta R. Lin et al. 10.3390/su17051970
- Vertical Profile Corrections Explain Satellite–Inventory Ammonia Discrepancies and Reveal Concentrated Agricultural Sources in China Q. Liu et al. 10.1021/acs.est.5c08278
- Substantial differences in source contributions to carbon emissions and health damage necessitate balanced synergistic control plans in China Y. Chen et al. 10.1038/s41467-024-50327-8
- Constraining East Asia ammonia emissions through satellite observations and iterative Finite Difference Mass Balance (iFDMB) and investigating its impact on inorganic fine particulate matter M. Momeni et al. 10.1016/j.envint.2024.108473
- Trends in anthropogenic ammonia emissions in China since 1980: A review of approaches and estimations J. Chen et al. 10.3389/fenvs.2023.1133753
- UK Ammonia Emissions Estimated With Satellite Observations and GEOS‐Chem E. Marais et al. 10.1029/2021JD035237
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- Evaluation and Diagnosis of Regional Ammonia Emission Inventory in the Pearl River Delta Using Multisite NH3 Observations and Model Simulations L. Sheng et al. 10.1021/acs.est.5c01380
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- The Diel Cycle of NH3 Observed From the FY‐4A Geostationary Interferometric Infrared Sounder (GIIRS) L. Clarisse et al. 10.1029/2021GL093010
- Using multi-satellite observations to constrain ammonia emissions and unlock their potential over open water M. Momeni et al. 10.1038/s41598-025-09933-9
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- Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea J. Mun et al. 10.1016/j.atmosenv.2022.119429
- A high-resolution inventory of ammonia emissions from agricultural fertilizer application and crop residue in Taiwan C. Hsu et al. 10.1016/j.atmosenv.2023.119920
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- A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use J. Jiang et al. 10.5194/gmd-17-8181-2024
- Global, regional and national trends of atmospheric ammonia derived from a decadal (2008–2018) satellite record M. Van Damme et al. 10.1088/1748-9326/abd5e0
33 citations as recorded by crossref.
- Reactive Nitrogen from Agriculture: A Review of Emissions, Air Quality, and Climate Impacts L. Luo et al. 10.1007/s40726-025-00360-y
- ISORROPIA‐MCX: Enabling Sensitivity Analysis With Multicomplex Variables in the Aerosol Thermodynamic Model, ISORROPIA B. Berman et al. 10.1029/2022EA002729
- Atmospheric reduced nitrogen: Sources, transformations, effects, and management C. Driscoll et al. 10.1080/10962247.2024.2342765
- Integrating Machine Learning with Causal Inference to Improve Prediction of Ammonium Wet Deposition in the Pearl River Delta R. Lin et al. 10.3390/su17051970
- Vertical Profile Corrections Explain Satellite–Inventory Ammonia Discrepancies and Reveal Concentrated Agricultural Sources in China Q. Liu et al. 10.1021/acs.est.5c08278
- Substantial differences in source contributions to carbon emissions and health damage necessitate balanced synergistic control plans in China Y. Chen et al. 10.1038/s41467-024-50327-8
- Constraining East Asia ammonia emissions through satellite observations and iterative Finite Difference Mass Balance (iFDMB) and investigating its impact on inorganic fine particulate matter M. Momeni et al. 10.1016/j.envint.2024.108473
- Trends in anthropogenic ammonia emissions in China since 1980: A review of approaches and estimations J. Chen et al. 10.3389/fenvs.2023.1133753
- UK Ammonia Emissions Estimated With Satellite Observations and GEOS‐Chem E. Marais et al. 10.1029/2021JD035237
- Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model J. Moon et al. 10.1016/j.atmosenv.2024.120490
- Evaluation and Diagnosis of Regional Ammonia Emission Inventory in the Pearl River Delta Using Multisite NH3 Observations and Model Simulations L. Sheng et al. 10.1021/acs.est.5c01380
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- The Diel Cycle of NH3 Observed From the FY‐4A Geostationary Interferometric Infrared Sounder (GIIRS) L. Clarisse et al. 10.1029/2021GL093010
- Using multi-satellite observations to constrain ammonia emissions and unlock their potential over open water M. Momeni et al. 10.1038/s41598-025-09933-9
- 4D‐Var Inversion of European NH3 Emissions Using CrIS NH3 Measurements and GEOS‐Chem Adjoint With Bi‐Directional and Uni‐Directional Flux Schemes H. Cao et al. 10.1029/2021JD035687
- 4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals J. Jin et al. 10.1088/1748-9326/acb835
- Bridging the spatial gaps of the Ammonia Monitoring Network using satellite ammonia measurements R. Wang et al. 10.5194/acp-23-13217-2023
- Global atmospheric inversion of the anthropogenic NH3 emissions over 2019–2022 using the LMDZ-INCA chemistry transport model and the IASI NH3 observations P. Kumar et al. 10.5194/acp-25-12379-2025
- Estimating global ammonia (NH3) emissions based on IASI observations from 2008 to 2018 Z. Luo et al. 10.5194/acp-22-10375-2022
- South Asia anthropogenic ammonia emission inversion through assimilating IASI observations J. Xia et al. 10.5194/acp-25-7071-2025
- Monthly Patterns of Ammonia Over the Contiguous United States at 2‐km Resolution R. Wang et al. 10.1029/2020GL090579
- Evaluation of interactive and prescribed agricultural ammonia emissions for simulating atmospheric composition in CAM-chem J. Vira et al. 10.5194/acp-22-1883-2022
- Diagnosing the Sensitivity of Particulate Nitrate to Precursor Emissions Using Satellite Observations of Ammonia and Nitrogen Dioxide R. Dang et al. 10.1029/2023GL105761
- How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35) X. Yu et al. 10.5194/gmd-14-7775-2021
- Impact of interannual weather variation on ammonia emissions and concentrations in Germany X. Ge et al. 10.1016/j.agrformet.2023.109432
- Satellite Support to Estimate Livestock Ammonia Emissions: A Case Study in Hebei, China P. Liu et al. 10.3390/atmos13101552
- Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea J. Mun et al. 10.1016/j.atmosenv.2022.119429
- A high-resolution inventory of ammonia emissions from agricultural fertilizer application and crop residue in Taiwan C. Hsu et al. 10.1016/j.atmosenv.2023.119920
- The influence of ammonia emission inventories on size-resolved global atmospheric aerosol composition and acidity X. Wang et al. 10.5194/acp-25-10559-2025
- Constraining industrial ammonia emissions using hyperspectral infrared imaging L. Noppen et al. 10.1016/j.rse.2023.113559
- Data Gap: Air Quality Networks Miss Air Pollution from Concentrated Animal Feeding Operations A. Burns et al. 10.1021/acs.est.3c06947
- Ammonia emission estimates using CrIS satellite observations over Europe J. Ding et al. 10.5194/acp-24-10583-2024
- A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use J. Jiang et al. 10.5194/gmd-17-8181-2024
Latest update: 31 Oct 2025
Short summary
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3...
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