High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model
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Published:2021-02-11
Issue:3
Volume:21
Page:2067-2082
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Chen Yilin, Shen HuizhongORCID, Kaiser Jennifer, Hu Yongtao, Capps Shannon L.ORCID, Zhao Shunliu, Hakami AmirORCID, Shih Jhih-ShyangORCID, Pavur Gertrude K., Turner Matthew D., Henze Daven K., Resler JaroslavORCID, Nenes AthanasiosORCID, Napelenok Sergey L., Bash Jesse O.ORCID, Fahey Kathleen M., Carmichael Gregory R., Chai TianfengORCID, Clarisse LievenORCID, Coheur Pierre-François, Van Damme MartinORCID, Russell Armistead G.ORCID
Abstract
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 concentration 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.
Funder
National Aeronautics and Space Administration China Scholarship Council
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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