CAMS-REG-UNC-v8.1: a detailed uncertainty product for the gridded CAMS-REG-v8.1 emission inventory

Abstract. Independent verification of greenhouse gas emission reductions and trends in air pollution levels is receiving increasing attention. Atmospheric observations can provide such a constraint on emission estimates through inverse modelling, which requires a detailed quantification of uncertainties in prior emission inventories, observations and chemical transport models. This paper describes a detailed methodology to quantify uncertainties in a state-of-the-art European emission inventory: CAMS-REG. Uncertainties are estimated for all input data used to create the emission inventory and propagated to the final product. This results in separate uncertainty estimates for country-level emissions per sector and uncertainties in the spatial allocation of those emissions. Ideally, the gridded emission uncertainties should add up to the country-level emission uncertainties and for this purpose an optimization procedure was developed (only for countries with detailed emission reporting). This results in (scaled) gridded emission uncertainties and spatial error correlation lengths, which are included in the final dataset. The gridded uncertainty maps show large differences between pollutants and countries, representing the variability in input data and their reliability. CO2 shows the smallest gridded (optimized) uncertainties, with a median relative standard deviation of 15 % (interquartile range: 9 %–25 %). The largest gridded (optimized) uncertainties are found for NMVOC: 45 % (38 %–58 %). This work follows up from previous efforts and details the first comprehensive emission uncertainty dataset for Europe. The data are available from Zenodo: https://doi.org/10.5281/zenodo.18400810 (Super et al., 2026).