Editing IPCC:AR6/WGI/Chapter-6 (section)

==== 6.3.3.4 Ammonia (NH <sub>3</sub> ) ====

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Ammonia is the most abundant alkaline gas in the atmosphere. Its present-day source is dominated by livestock and crop production (Section 6.2). Ammonia reacts with nitric acid and sulphuric acid to produce ammonium sulphate and ammonium nitrate, which contribute to the aerosol burden (Section 6.3.5.2), promotes aerosol nucleation by stabilizing sulphuric acid clusters ( [[#Kirkby--2011|Kirkby et al., 2011]] ), and contributes to nitrogen deposition (Section 6.4.4; [[#Sheppard--2011|Sheppard et al., 2011]] ; [[#Flechard--2020|Flechard et al., 2020]] ). Trends in NH <sub>3</sub> were not assessed in AR5.

Considerable expansion of satellite (Clarisse et al. , 2009; [[#Shephard--2015|Shephard and Cady-Pereira, 2015]] ; Warner et al. , 2016) and ground-based observations (Miller et al. , 2014; Y. Li et al. , 2016; Pan et al. , 2018) has improved our understanding of the spatial distribution and seasonal to interannual variability of ammonia, and advanced its representations in models (e.g., [[#Zhu--2015|Zhu et al., 2015]] ). Regionally, peak NH <sub>3</sub> concentrations are observed over large agricultural (e.g., northern India, the USA Midwest and Central Valley) and biomass-burning regions, in good qualitative agreement with emissions inventories (Van Damme et al. , 2015, 2018) . However, several large agricultural and industrial hotspots have been found to be missing or greatly underestimated in emissions inventories (Van Damme et al. , 2018) . NH <sub>3</sub> exhibits a strong vertical gradient, with a maximum in the boundary layer ( [[#Schiferl--2016|Schiferl et al., 2016]] ), and can be transported into the upper troposphere and lower stratosphere (UTLS), particularly in the Asian Monsoon region, as indicated by observations ( [[#Froyd--2009|Froyd et al., 2009]] ; [[#Höpfner--2016|Höpfner et al., 2016]] , 2019) and theoretical considerations (Ge et al. , 2018) . There is a large range in the present-day NH <sub>34</sub> burden (from 0.04–0.7 TgN) simulated by CCMs, highlighting deficiencies in the process-level representation of NH <sub>3</sub> in current global models ( [[#Bian--2017|Bian et al., 2017]] ). The underestimate of surface NH <sub>3</sub> concentrations ( [[#Bian--2017|Bian et al., 2017]] ) further highlights such deficiencies and the limitations in comparing site-specific observations with relatively coarse-resolution models.

Observations show that NH <sub>3</sub> concentration has been increasing in recent decades in the USA (Butler et al. , 2016; Warner et al. , 2016; Yu et al. , 2018) , Western Europe (van Zanten et al. , 2017; Warner et al. , 2017; Wichink Kruit et al. , 2017; Tang et al. , 2018) , and China ( [[#Warner--2017|Warner et al., 2017]] ; M. [[#Liu--2018|]] [[#Liu--2018|Liu et al., 2018]] ). This trend has been attributed to a combination of increasing ammonia emissions ( [[#Sutton--2013|Sutton et al., 2013]] ; [[#Fowler--2015|Fowler et al., 2015]] ) and decreases in the chemical reaction of NH <sub>3</sub> with nitric and sulphuric acids associated with reductions in SO <sub>2</sub> and NO <sub>x</sub> emissions whose rate depends on the region ( [[#Warner--2017|Warner et al., 2017]] ; [[#Yao--2019|Yao and Zhang, 2019]] ). Over longer time scales, CCMs simulate an increase of the NH <sub>34</sub> burden by a factor of two to seven since pre-industrial conditions ( [[#Xu--2012|Xu and Penner, 2012]] ; [[#Hauglustaine--2014|Hauglustaine et al., 2014]] ).

In summary, progress has been made in the understanding of the spatio-temporal distribution of ammonia, though representation of NH <sub>3</sub> remains rather unsatisfactory due to process-level uncertainties. Evidence from observations and models suggests that ammonia concentrations have been increasing over recent decades due to emissions and chemistry. There is ''high confidence'' that the global NH <sub>34</sub> burden has increased considerably from the pre-industrial period to the present day, although the magnitude of the increase remains uncertain.

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