Inversion and Evaluation of anthropogenic CO2 emissions based on 4Dvar method and the ratio of NOx-to-CO2

Anthropogenic carbon dioxide (CO2)emissions areone of the most importantsource of greenhouse gasesthat driver climate change.However, there are still large uncertainties persist in the anthropogenicCO2emissions and and no global observing system exists to monitor emissions from localized CO2sources with sufficient accuracy.Combined nitrogen oxides (NOx)and CO2observations showedthe potential to constrain the identification of the locations and strength of anthropogenic CO2emissions.In this study, a four-dimensional variational assimilation (4Dvar) system was developed to estimate high-resolution inversion of CO2fluxes based on a regional chemical transport model WRF-Chem combined multiple observations. The ratios of NOx-to-CO2from the TROPOspheric Monitoring Instrument (TROPOMI) and Orbiting Carbon Observatory 2 (OCO-2) satellite observations were applied to distinguish the enhancements of CO2concentration from anthropogenic CO2emissions. The gridded data set of monthly anthropogenicemissions (GCP-GridFED version 2022.2) was considered as the priori emission. The posterior CO2emissionsover China during April and September 2021 were estimated to reduce the influence of terrestrial ecosystem carbon sources and sinks. The posterior CO2anthropogenic emissionsreproduced the daily and hourly variation effectively, demonstrating the ability to fully absorb observations and the potential of applying NOx-to-CO2 ratio to estimate CO2emissions. Two sets of forecast experiments were conducted to evaluate the prior and posterior CO2simulations with independent surface observation data. Ourresults provide the basic data for carbon emissions reduction policies and maybehelpful for accurate estimating carbon sinks, achieving carbon neutrality. The advanceddata assimilation systems are beneficial to better quantify and characterize uncertainty for large carbon sourcesand sinks.