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Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of NH3 through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of NH3, focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. NH3 hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase NH3 over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where NH3 ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global NH3 quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.
Nair et al. (Tue,) studied this question.