Ammonia (NH₃) is a key precursor of PM_2.5, contributing to the formation of secondary inorganic aerosols and playing a crucial role in haze events. However, current bottom-up emission inventories in China often underestimate NH₃ emissions, particularly with significant uncertainties in urban areas. This study developed a “top-down” iterative algorithm that integrates the IASI satellite observations with the WRF-Chem model to optimize bottom-up NH₃ emissions, and further quantified the impacts of source-specific emission reductions on PM_2.5 pollution. The result reveals that the updated NH₃ emissions in Eastern China for 2016 amounted to 4.2 Tg yr⁻¹, 27.3% higher than prior estimations. The optimized NH₃ emissions peak in summer at 463.1 Gg month⁻¹, with agricultural sources accounting for 85%, while winter emissions drop to 217 Gg month⁻¹ when the contribution from non-agricultural sources (e.g., industry, vehicle) significantly increases. The optimized NH₃ emission significantly improved the simulation of both total column and surface NH₃ concentrations, with improvements in magnitude (31%–42%) and variations (17%–55%). Sensitivity simulations show that a 30%–60% reduction in NH₃ emission led to decreases of 1.5–8.8 µgm⁻³ in city level PM_2.5 concentrations and the potential effect of reducing non-agricultural emissions is comparable with that from agricultural sources. Furthermore, the NH₃ reduction positively impacts public health, resulting in a 6.5%–10.3% decrease in premature deaths attributed to PM_2.5 exposure. Our study evaluated NH₃ emissions from various sources in Eastern China, emphasizing the impact of reducing non-agricultural ammonia emissions on air quality and public health benefits.
 

NH3,排放,数值模型,空气质量