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

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