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Ammonia (NH3) in the atmosphere contributes to the formation of airborne fine particulate matter (PM2.5), which is associated with adverse human health effects. The emission, transport, reactions, and deposition of NH3 in the atmosphere are modeled using the Community Multiscale Air Quality (CMAQ) model, within the U.S. National Air Quality Forecast Capability (NAQFC). The purpose of this current work is to evaluate the capability of the NAQFC CMAQ model and to identify potential improvements to NH3 emissions estimates and prediction methods. This study focuses on CMAQ predictions of atmospheric NH3 in North Carolina, including a region with intensive animal production and enhanced NH3 emissions. The CMAQ model is run for July 2011 using a version of the 2011 National Emissions Inventory in which agricultural NH3 emissions were adjusted to reflect the lower end of the range of estimates from the current process‐based emissions model. The NAQFC CMAQ model overpredicted atmospheric NH3 at a continuous monitor in Clinton, NC, within the region of intensive animal production. The average concentration measured by the monitor was 6.6 ppbv, while the average predicted by the model was 10.5 ppbv, a 60% overprediction. Outside of the region of intensive animal production, both measured and modeled NH3 concentrations were low, 1.3 ppbv or less. The model underpredicted wet deposition of NH4+ and dry deposition of NH3. It is believed that the overestimation of NH3 at Clinton is attributable at least in part to the underestimation of wet and dry deposition in North Carolina. Key Points: The National Air Quality Forecast System model overpredicted ammonia at a continuous monitor in a region of intensive animal productionModel predictions for ammonia were improved by using State permit information for locations of animal feeding operationsThe model underpredicted wet deposition of ammonium ion and dry deposition of ammonia in eastern North Carolina [ABSTRACT FROM AUTHOR]

Global ammonia (NH3) emissions to the atmosphere are projected to increase in the coming years with the increased use of synthetic nitrogen fertilizers and cultivation of nitrogen‐fixing crops. A statistical model (NH3_STAT) is developed for characterizing atmospheric NH3 emissions from agricultural soils and compared to the performance of other global and regional NH3 models (e.g., Emission Database for Global Atmospheric Research, Magnitude and Seasonality of Agricultural Emissions, MIX, and U.S. Environmental Protection Agency). The statistical model was developed from a multiple linear regression between NH3 emission and the physicochemical variables. The model was evaluated for 2012 NH3 emissions. The results indicate that, in comparison to other data sets, the model provides a lower global NH3 estimate by 58%, (NH3_STAT: 13.9 Tg N yr−1; Emission Database for Global Atmospheric Research: 33.0 Tg N yr−1). We also performed a region‐based analysis (United States, India, and China) using the NH3_STAT model. For the United States, our model produces an estimate that is a ~1.4 times higher in comparison to the Environmental Protection Agency. Meanwhile, the NH3_STAT estimate for India shows NH3 emissions between 0.8 and 1.4 times lower when compared to other data sets. A lower estimate is also seen for China, where the model estimates NH3 emissions 0.4 to 5 times lower than other data sets. The difference in the global estimates is attributed to the lower estimates in major agricultural countries like China and India. The statistical model captures the spatial distribution of global NH3 emissions by utilizing a simplified approach compared to other readily available data sets. Moreover, the NH3_STAT model provides an opportunity to predict future NH3 emissions in a changing world. Key Points: Estimates global ammonia emissions from agricultural soilsPredict future ammonia emissions from agricultural soils in a changing worldDevelops a statistical model for ammonia emissions from agricultural soil [ABSTRACT FROM AUTHOR]