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.