This document reports on progress to date within WP5 ‘Connecting scales and uncertainties’ of the CoCO2: Prototype system for a Copernicus CO2 service project. The aim of WP5 is essentially to evaluate and benchmark improvements in the quantification of fossil fuel CO2 emission estimates focussing on enhanced uncertainty estimates as well as across relevant scales. To this end, this work package involves performing observing system simulation experiments (OSSEs) and quantitative network design (QND) experiments, setting up benchmarking systems around natural terrestrial CO2 flux and atmospheric transport modelling, developing multi-scale inversion framework, assessing uncertainty correlations and biases in the satellite observations as well as performing inverse model intercomparisons. All tasks within this WP have considerably progressed according to their work description in the Grant Agreement and no deviations from this work description have been identified. In Task 5.1, the ensemble data assimilation system has been extended to integrate both 3D atmospheric composition state and emission perturbations in the posterior ensemble. Task 5.2 has developed and consolidated a strategy for assessing and quantifying errors in biogenic CO2 fluxes based on eddy-covariance flux measurements. Task 5.3 has implemented a set of atmospheric tracer transport models into the Community Inversion Framework (CIF), which has been developed in the VERIFY project, while Task 5.4 has so far made available CO2M data including systematic and random retrieval uncertainty with and without the use of a multi-angular polarimeter to account for aerosols. In task 5.5, the impact of various design options for the CO2M MVS have been assessed with respect to posterior emission uncertainties. These options include among others the availability of co-located NO2 observation with varying degrees of random uncertainties. Finally, Task 5.6 has started distributing an intercomparison protocol for CH4 inversions among the inverse modelling community as well as tested the impact of transport model uncertainties on atmospheric CO2 inversions.