Inversion of the global NH3 emissions (2019-2022) based on IASI NH3 observations and the LMDZ-INCA chemistry-transport model

Atmospheric ammonia (NH₃) has significant environmental impacts, contributing to biodiversity loss and air quality deterioration, with potential negative effects on ecosystems and human health. The global and regional NH₃ emissions have been on continuous rise in the recent years, due to the extensive use of fertilizers in agricultural activities and to livestock production. However, the current bottom-up NH₃ emission inventories exhibit large uncertainties at all the spatiotemporal scales. Top-down estimates of the global and regional NH₃ emissions from the atmospheric inversion approach based on satellite observations with global coverage can provide valuable insights on the spatiotemporal variability of ammonia emissions. In this study, we provide top-down atmospheric inversion estimates of the worldwide anthropogenic NH3 emissions using the new version 4 of the IASI ANNI NH₃ observations for a period of four years from 2019 to 2022 at 1.27°×2.5° (latitude × longitude) horizontal resolution and at daily (as a 10-day running average) temporal scale. We use a global chemistry transport model LMDZ-INCA for the NH₃ concentrations simulations and a finite difference mass balance approach for the inversions of the NH₃ emissions. We take advantage of the vertical averaging kernels provided in version 4 of the IASI NH₃ data product by applying them consistently to the LMDZ-INCA NH₃ simulations when evaluating these simulations. We perform the global inversions to estimate the anthropogenic NH3 emissions, using the IASI NH3 total columns observations and LMDZ-INCA NH₃ total columns convolved with the vertical averaging kernel. The global annual anthropogenic NH3 emissions averaged over the four years period (2019-2022) are estimated as ~90 (88-92) Tg yr^-1. These global estimates are ~70% higher than the prior CEDS inventory NH₃ emissions used in the inversions and significantly higher (more than by a factor for two) when compared to two other global bottom-up inventories, CAMS and CAMEO. The regional NH₃ emissions estimates derived from our global inversion are also assessed through comparisons with other inventories and recent top-down estimates based on the satellites NH₃ observations. Our estimates of the NH₃ emissions at both the global and regional scales are mostly consistent with other top-down inversion estimates.