4D‐Var Inversion of European NH₃ Emissions Using CrIS NH₃ Measurements and GEOS‐Chem Adjoint With Bi‐Directional and Uni‐Directional Flux Schemes

Abstract

We conduct the first 4D-Var inversion of NH 3 accounting for NH 3 bi-directional flux, using CrIS satellite NH 3 observations over Europe in 2016. We find posterior NH 3 emissions peak more in springtime than prior emissions at continental to national scales, and annually they are generally smaller than the prior emissions over central Europe, but larger over most of the rest of Europe. Annual posterior anthropogenic NH 3 emissions for 25 European Union members (EU25) are 25% higher than the prior emissions and very close (<2% difference) to other inventories. Our posterior annual anthropogenic emissions for EU25, the UK, the Netherlands, and Switzerland are generally 10%-20% smaller than when treating NH 3 fluxes as uni-directional emissions, while the monthly regional difference can be up to 34% (Switzerland in July). Compared to monthly mean in-situ observations, our posterior NH 3 emissions from both schemes generally improve the magnitude and seasonality of simulated surface NH 3 and bulk NH x wet deposition throughout most of Europe, whereas evaluation against hourly measurements at a background site shows the bi-directional scheme better captures observed diurnal variability of surface NH 3 . This contrast highlights the need for accurately simulating diurnal variability of NH 3 in assimilation of sun-synchronous observations and also the potential value of future geostationary satellite observations. Overall, our top-down ammonia emissions can help to examine the effectiveness of air pollution control policies to facilitate future air pollution management, as well as helping us understand the uncertainty in top-down NH 3 emissions estimates associated with treatment of NH 3 surface exchange.Plain Language Summary Atmospheric ammonia contributes to air pollutants and excessive deposition of reactive nitrogen that is detrimental to sensitive ecosystems. Ammonia is emitted mainly by agricultural livestock and fertilizer use. While surface measurements of NH 3 are sparse, satellite observations can provide near daily global coverage. Here we calculate monthly NH 3 emissions over Europe, the only region adopting NH 3 control policies, using an air quality model coupled with a process-based bi-directional NH 3 flux scheme and NH 3 measurements observed by the CrIS satellite instrument. Our CrIS-derived annual regional total anthropogenic NH 3 emissions are close (<2% difference) to statistic-based bottom-up estimates and are 10%-20% lower than when treating NH 3 exchange between the atmosphere and biosphere as one-way CAO ET AL.

An improved representation of aerosol acidity in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12

“…The timing in the simulations is strongly governed by the monthly variability and magnitude in the emission inventories, which have been show to have significant difference when compared to satellite derived emission estimates (Cao et al (2022)). For NH 4 + the excessive particle concentrations simulated in CY48R1 and CY49R1_NOE4C during summertime (+200% bias) significantly improves upon the application of EQSAM4Clim.…”

An Observing System Simulation Experiment Analysis of How Well Geostationary Satellite Trace‐Gas Observations Constrain NOx Emissions in the US

“…Satellite nitrogen dioxide (NO 2 ) retrievals are well suited for NO x emissions inversion given their wide geographic coverage and have been extensively used in constraining NO x emissions from local to global scales (e.g., Dix et al., 2022; Duncan et al., 2013; Martin et al., 2003; Müller & Stavrakou, 2005; Qu et al., 2017). Two advanced data assimilation (DA) methods are typically utilized to conduct top‐down emissions estimates: The four‐dimensional variational assimilation (4D‐VAR) optimizes the emissions by minimizing the cost function using the adjoint model (e.g., Cao et al., 2022; Choi et al., 2022; Elbern et al., 2007; Qu et al., 2019; Stavrakou et al., 2013). The ensemble Kalman filter (EnKF) approach utilizes the flow‐dependent error covariance generated by the ensemble of model simulations to relate the observation information to emissions (e.g., Barbu et al., 2009; Huang et al., 2022; Ma et al., 2019; Miyazaki et al., 2012, 2017; Peng et al., 2018; Zhang, Li, Wang, et al., 2021; Zhang, Li, Wei, et al., 2021).…”

“…The four‐dimensional variational assimilation (4D‐VAR) optimizes the emissions by minimizing the cost function using the adjoint model (e.g., Cao et al., 2022; Choi et al., 2022; Elbern et al., 2007; Qu et al., 2019; Stavrakou et al., 2013).…”

4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals

“…Atmospheric ammonia emission inversion has recently attracted considerable attention worldwide. For instance, Cao et al (2020Cao et al ( , 2022 conducted a 4DVarbased inversion using CrIS retrieval data and the GEOS-Chem model to optimize the monthly ammonia emission inventories in Europe and the US. CrIS measurements were also assimilated to constrain the ammonia source inventory over North America in Sitwell et al (2022) and Europe in van der Graaf et al (2022).…”