Inversion of monthly ammonia emissions in China by assimilating satellite surface observations

Ammonia (NH₃) plays a crucial role in the formation of PM_2.5 as a primary alkaline gas in the atmosphere. An NH₃ emission inventory is an essential component of numerical chemical transport models for scenario simulations and developing mitigation strategies. The significantly NH₃ hotspots located in China can be seen both in compiled inventories and in satellite observations. However, almost all emission inventories report that NH₃ emissions from China have a large uncertainty. In our research, we conducted a top-down optimization of monthly NH₃ emission over China using IASI-derived surface NH₃ concentration and the CAMx model. First, IASI-derived surface NH₃ concentrations are assessed by comparing against a surface monitoring network (NNDMN) in China during 2020. Second, an optimal estimation method is used to assimilate observations to optimize the NH₃ priori emissions. The posteriori NH₃ emissions are approximately double the priori estimates from the prior MEIC inventory and indicate potential underestimation over hotspot areas, especially during the warm months. Monthly variations in posteriori emissions exhibited significant differences across 6 regions of China, with peak emissions occurring in May and July, and relatively stable levels observed in the southern regions of China. In conclusion, this analysis enhanced the understanding of the spatial-temporal patterns of regional NH₃ emissions in China, which is important for the development of mitigation strategies to address consistently high NH₃ emissions in China.