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Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in-situ aircraft and satellite measurements from the CalNex2010 campaign
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2017
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Source: Atmospheric Environment, 163, 65-76
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Journal Title:Atmospheric Environment
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Description:Atmospheric ammonia (NH3) is not only a major precursor gas for fine particulate matter (PM2.5), but it also negatively impacts the environment through eutrophication and acidification. As the need for agriculture, the largest contributing source of NH3, increases, NH3 emissions will also increase. Therefore, it is crucial to accurately predict ammonia concentrations. The objective of this study is to determine how well the U.S. National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC) system predicts ammonia concentrations using their Community Multiscale Air Quality (CMAQ) model (v4.6). Model predictions of atmospheric ammonia are compared against measurements taken during the NOAA California Nexus (CalNex) field campaign that took place between May and July of 2010. Additionally, the model predictions were also compared against ammonia measurements obtained from the Tropospheric Emission Spectrometer (TES) on the Aura satellite. The results of this study showed that the CMAQ model tended to under predict concentrations of NH3. When comparing the CMAQ model with the CalNex measurements, the model under predicted NH3 by a factor of 2.4 (NMB = −58%). However, the ratio of the median measured NH3 concentration to the median of the modeled NH3 concentration was 0.8. When compared with the TES measurements, the model under predicted concentrations of NH3 by a factor of 4.5 (NMB = −77%), with a ratio of the median retrieved NH3 concentration to the median of the modeled NH3 concentration of 3.1. Because the model was the least accurate over agricultural regions, it is likely that the major source of error lies within the agricultural emissions in the National Emissions Inventory. In addition to this, the lack of the use of bidirectional exchange of NH3 in the model could also contribute to the observed bias.
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Content Notes:We acknowledge the generous help and guidance of Dr. Andy Neuman (NOAA), Dr. Ann Middlebrook (NOAA) and Dr. Roya Bahreini (UCR), the NCSU Air Quality Research Group, the NOAA National Air Quality Forecast Program, and the CalNex2010 field campaign.
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Source:Atmospheric Environment, 163, 65-76
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ISSN:1352-2310
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Rights Information:Accepted Manuscript
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Compliance:Library
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