Improving Black Carbon Emission Estimates at Global Scale Using GEOS-Chem model and 4D-Var assimilation of TROPOMI/GRASP data

Radiative forcing by light-absorbing aerosols, particularly black carbon (BC), a major climate forcing agent alongside CO₂ and CH₄, remains poorly constrained due to insufficient characterisation of their optical properties and highly variable spatio-temporal distributions. Here we aim to refine BC’s spatio-temporal variability using the GEOS-Chem 3D Eulerian chemistry-transport model, which incorporates BC’s well-defined physical and chemical properties. The model includes aerosol-phase chemistry relevant to urban atmospheres, such as desert dust, BC, organic carbon, sea salts, SiO₂, metal oxides, SO₄²⁻, NO₃^-, NH₄⁺, Na⁺, and Ca²⁺, at a global resolution (2°×2.5°) with primary aerosols only. Our primary objective is to precisely map BC’s spatial and temporal distributions, which is critical for evaluating the long-term impact of absorbing aerosols on net radiative forcing.

Using the 4D-Var assimilation method with TROPOMI/GRASP aerosol optical depth (AOD) and aerosol absorption optical depth (AAOD) data, we adjust global-scale emissions at an hourly resolution from March 2019 to November 2020. From a satellite remote sensing perspective, this characterization of aerosols via a single-viewing spectrometer is unprecedented. The GRASP open-source algorithm has generated this novel dataset. The GEOS-Chem model is driven by 3-hourly meteorological fields obtained from GEOS-FP reanalysis data. Our study includes the extreme events of the Australian bushfire season and Canadian forest fire events, where we identify emission sources absent from the GFED3 inventories (1996–2012) used in the forward run. Assimilation of TROPOMI/GRASP AOD and AAOD data into the model allows to reproduce carbonaceous aerosol emissions. These results are validated using MODIS and VIIRS RGB imagery. Ground-level BC concentrations are further validated against in situ measurements from France in the frame of the ANR BLACKNET project and from AERONET. 

This framework will enable creating a global particulate matter (PM) database with high temporal resolution, spanning several years. Satellite data alone cannot achieve this level of detail. High-resolution BC distribution via inverse modelling will benefit from future spaceborne multi-angular polarimetric sensors, such as 3MI, CO2M MAP, and PACE. Additionally, aerosol vertical distributions will be studied to assess their influence on temperature profiles and atmospheric stability. This work will aid in validating and comparing suborbital measurements. The inverse modelling approach aligns closely with LiDAR-based observations from the EarthCARE mission.