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Journal article
High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model
Atmospheric chemistry and physics, v 21(3), pp 2067-2082
11 Feb 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Ammonia (NH3) emissions have large impacts on air quality and nitrogen deposition, influencing human health and the well-being of sensitive ecosystems. Large uncertainties exist in the "bottom-up" NH3 emission inventories due to limited source information and a historical lack of measurements, hindering the assessment of NH3-related environmental impacts. The increasing capability of satellites to measure NH3 abundance and the development of modeling tools enable us to better constrain NH3 emission estimates at high spatial resolution. In this study, we constrain the NH3 emission estimates from the widely used 2011 National Emissions Inventory (2011 NEI) in the US using Infrared Atmospheric Sounding Interferometer NH3 column density measurements (IASI-NH3) gridded at a 36 km by 36 km horizontal resolution. With a hybrid inverse modeling approach, we use the Community Multiscale Air Quality Modeling System (CMAQ) and its multiphase adjoint model to optimize NH3 emission estimates in April, July, and October. Our optimized emission estimates suggest that the total NH3 emissions are biased low by 26 % in 2011 NEI in April with overestimation in the Midwest and underestimation in the Southern States. In July and October, the estimates from NEI agree well with the optimized emission estimates, despite a low bias in hotspot regions. Evaluation of the inversion performance using independent observations shows reduced underestimation in simulated ambient NH3 concentra- tion in all 3 months and reduced underestimation in NH4 wet deposition in April. Implementing the optimized NH3 emission estimates improves the model performance in simulating PM2.5 concentration in the Midwest in April. The model results suggest that the estimated contribution of ammonium nitrate would be biased high in a priori NEI-based assessments. The higher emission estimates in this study also imply a higher ecological impact of nitrogen deposition originating from NH3 emissions.
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Details
- Title
- High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model
- Creators
- Yilin Chen - Georgia Institute of TechnologyHuizhong Shen - Georgia Institute of TechnologyJennifer Kaiser - Georgia Institute of TechnologyYongtao Hu - Georgia Institute of TechnologyShannon L. Capps - Drexel UniversityShunliu Zhao - Carleton UniversityAmir Hakami - Carleton UniversityJhih-Shyang Shih - Resources For The FutureGertrude K. Pavur - Georgia Institute of TechnologyMatthew D. Turner - Stennis Space CenterDaven K. Henze - University of Colorado BoulderJaroslav Resler - Czech Academy of SciencesAthanasios Nenes - Foundation for Research and Technology HellasSergey L. Napelenok - Research Triangle Park FoundationJesse O. Bash - Research Triangle Park FoundationKathleen M. Fahey - Research Triangle Park FoundationGregory R. Carmichael - University of IowaTianfeng Chai - NOAA Air Resources Laboratory (ARL), Cooperative Institute for Satellites Earth System Studies (CISESS), University of Maryland, College Park, MD 20740, USALieven Clarisse - Université Libre de BruxellesPierre-Francois Coheur - Université Libre de BruxellesMartin Van Damme - Université Libre de BruxellesArmistead G. Russell - Georgia Institute of Technology
- Publication Details
- Atmospheric chemistry and physics, v 21(3), pp 2067-2082
- Publisher
- Copernicus Gesellschaft Mbh
- Number of pages
- 16
- Grant note
- NNX16AQ29G / National Aeronautics and Space Administration; National Aeronautics & Space Administration (NASA) R83588001 / United States Environmental Protection Agency 201606010393 / China Scholarship Council
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000619642200002
- Scopus ID
- 2-s2.0-85101006171
- Other Identifier
- 991019167789804721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Environmental Sciences
- Meteorology & Atmospheric Sciences