Abstract
Abstract. Ammonia (NH3) plays a central role in the chemistry of inorganic secondary aerosols in the atmosphere. The largest emission sector for NH3 is agriculture, where NH3 is volatilized from livestock wastes and fertilized soils. Although the NH3 volatilization from soils is driven by the soil temperature and moisture, many atmospheric chemistry models prescribe the emission using yearly emission inventories and climatological seasonal variations. Here we evaluate an alternative approach where the NH3 emissions from agriculture are simulated interactively using the process model FANv2 (Flow of Agricultural Nitrogen, version 2) coupled to the Community Atmospheric Model with Chemistry (CAM-chem). We run a set of 6-year global simulations using the NH3 emission from FANv2 and three global emission inventories (EDGAR, CEDS and HTAP) and evaluate the model performance using a global set of multi-component (atmospheric NH3 and NH4+, and NH4+ wet deposition) in situ observations. Over East Asia, Europe and North America, the simulations with different emissions perform similarly when compared with the observed geographical patterns. The seasonal distributions of NH3 emissions differ between the inventories, and the comparison to observations suggests that both FANv2 and the inventories would benefit from more realistic timing of fertilizer applications. The largest differences between the simulations occur over data-scarce regions. In Africa, the emissions simulated by FANv2 are 200 %–300 % higher than in the inventories, and the available in situ observations from western and central Africa, as well as NH3 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument, are consistent with the higher NH3 emissions as simulated by FANv2. Overall, in simulating ammonia and ammonium concentrations over regions with detailed regional emission inventories, the inventories based on these details (HTAP, CEDS) capture the atmospheric concentrations and their seasonal variability the best. However these inventories cannot capture the impact of meteorological variability on the emissions, nor can these inventories couple the emissions to the biogeochemical cycles and their changes with climate drivers. Finally, we show with sensitivity experiments that the simulated time-averaged nitrate concentration in air is sensitive to the temporal resolution of the NH3 emissions. Over the CASTNET monitoring network covering the US, resolving the NH3 emissions hourly instead monthly reduced the positive model bias from approximately 80 % to 60 % of the observed yearly mean nitrate concentration. This suggests that some of the commonly reported overestimation of aerosol nitrate over the US may be related to unresolved temporal variability in the NH3 emissions.
Highlights
Volatilization of ammonia (NH3) from fertilizers and livestock wastes constitutes the largest source of atmospheric NH3
Comparison with observations shows that the spatial patterns of particulate ammonium and the NH+4 wet deposition are generally well captured in FAN and the other simulations
The smaller correlation for NH3 is in part explained by the shorter atmospheric lifetime of NH3, which results in spatial gradients that cannot be reproduced at the 2◦ resolution
Summary
Volatilization of ammonia (NH3) from fertilizers and livestock wastes constitutes the largest source of atmospheric NH3. In Vira et al (2020b), we introduced an updated version (FANv2) of the process model FAN (Flow of Agricultural Nitrogen), which simulates the physical mechanisms of ammonia volatilization interactively within an Earth system model. Incorporated into the Community Land Model (CLM), the land component of the Community Earth System Model (CESM), FANv2 evaluates NH3 emissions arising from fertilizer use, grazing livestock and manure management. We couple FANv2 and CLM with the Community Atmosphere Model (CAM-chem; Lamarque et al, 2012; Tilmes et al, 2015) to evaluate how interactive NH3 emissions affect the simulation of atmospheric composition and nitrogen deposition. Distinct from the earlier efforts (Bash et al, 2013; Zhu et al, 2015; Shen et al, 2020) to interactively simulate the NH3 emissions in atmospheric chemistry models, we include the NH3 emissions from both fertilizer applications and livestock manure. Including manure as an NH3 emission source increases the fraction of emissions resolved by the process model considerably, since globally about 60 %–80 % of the total agricultural NH3 emissions are estimated to originate from manure (Beusen et al, 2008; Paulot et al, 2014; Vira et al, 2020b)
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