Evaluation of the new 4D-variational inverse modeling system, CIF-CHIMERE: Inversion of NOx emissions over China using OMI NO2 observations

Nitrogen oxides (NOx = NO2 + NO) are primary pollutants that are mainly produced by anthropogenic activities. They play a key role in oxidation processes in the troposphere. They control the photochemical production of Ozone (O3) and affect the concentration of the hydroxyl radical (OH), thus causing air quality degradation. Industrialized countries with high air quality degradation such as China, are implementing mitigation strategies with the aim of improving air quality. The evaluation of these strategies requires having precise and rapidly updated emission inventories. Inverse modeling approaches based on satellite observations are useful tools as they can provide independent inventories to complement the traditional bottom-up inventories. In this study, we propose to evaluate the potential of the new 4D-Var inverse modeling system, CIF (Community Inversion Framework), coupled with the CHIMERE chemistry-transport model to inverse NOx emissions. We focus on the case study of NOx emissions over China for the year 2015 and use OMI satellite NO2 observations as constraints. The HTAP NOx emissions from 2010 are used to prescribe prior emissions and the inversion is performed at 0.5° resolution. The posterior NOx emissions are validated against surface NO2 concentration measurements and compared to the recent MEIC bottom-up inventory from the year 2015.