CHE_EDGAR-ECMWF_2015 data (Choulga et al., 2020) consist of 11 grid-maps in NetCDF format and one Excel file with information on anthropogenic CO2 emissions and their uncertainties (all files are zipped together in CHE_EDGAR-ECMWF_2015.zip): • Annual_Upper_Lower_Uncertainties_Percentage_0.1_0.1.nc – file has 2×8 fields with annual upper and lower uncertainty bounds in % per each emission group and for all groups summed together on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. - "Lower" – lower uncertainty bound (2.5th percentile of log-normal distribution) for yearly emissions, in %; - "Upper" – upper uncertainty bound (97.5th percentile of log-normal distribution) for yearly emissions, in %; - "Sector" – emission sector numerical name. "0" represents emission group ENERGY_S (with IPCC (2006) activity 1.A.1.a (subset)) standing for power industry emissions from super emitting power plants; "1" group ENERGY_A (1.A.1.a (rest), 4.C) – power industry emissions from average emitting power plants, & solid waste incineration; "2" group MANUFACTURING (1.A.2, 2.C.1, 2.C.2, 2.C.3, 2.C.4, 2.C.5, 2.C.6, 2.C.7, 2.D.1, 2.D.2, 2.D.4, 2.A.1, 2.A.2, 2.A.3, 2.A.4, 2.B.1, 2.B.2, 2.B.3, 2.B.4, 2.B.5, 2.B.6, 2.B.8) – combustion for manufacturing (including autoproducers), & iron and steel production, & non-ferrous metals production, & non energy use of fuels, & non-metallic minerals production, & chemical processes; "3" group SETTLEMENTS (1.A.4, 1.A.5.a, 1.A.5.b.i, 1.A.5.b.ii) – energy for buildings, residential heating; "4" group AVIATION (1.A.3.a_CRS, 1.A.3.a_CDS, 1.A.3.a_LTO) – aviation cruise, & climbing and descent, & landing and take off; "5" group TRANSPORT (1.A.3.b, 1.A.3.d, 1.A.3.c, 1.A.3.e) – road transportation, & shipping, & railways, pipelines, off-road transport; "6" group OTHER (1.A.1.b, 1.A.1.c, 1.A.5.b.iii, 1.B.1.c, 1.B.2.a.iii.4, 1.B.2.a.iii.6, 1.B.2.b.iii.3, 1.B.2.a.ii, 1.B.2.a.iii.2, 1.B.2.a.iii.3, 1.B.2.b.ii, 1.B.2.b.iii.2, 1.B.2.b.iii.4, 1.B.2.b.iii.5, 1.C, 1.B.1.a, 3.C.2, 3.C.3, 3.C.4, 3.C.7, 2.D.3, 2.B.9, 2.E, 2.F, 2.G) – oil refineries and transformation industry, & fuel exploitation, & coal production, & agricultural soils, & solvents and products use; "7" represents all groups summed together; • Monthly_Upper_Lower_Uncertainties_Percentage_0.1_0.1.nc – file has 2×8×12 fields with monthly upper and lower uncertainty bounds in % per each emission group and for all groups summed together on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Annual_Upper_Lower_Uncertainties_Percentage_0.1_0.1.nc, but per month (1, 2, …, 12 correspond to January, February, …, December); • Annual_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×8 fields with annual emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per each emission group and for all groups summed together on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. - "Sup_lower" – lower uncertainty bound (2.5th percentile of log-normal distribution) for yearly emissions of ENERGY_S group, in kg·m-2·s-1; - "Sup_upper" – upper uncertainty bound (97.5th percentile of log-normal distribution) for yearly emissions of ENERGY_S group, in kg·m-2·s-1; - "Sup_flux" – yearly emissions of ENERGY_S group, in kg·m-2·s-1; - "Ene_lower", "ene_upper", "ene_flux" – same, but for ENERGY_A group, in kg·m-2·s-1; - "Man_lower", "man_upper", "man_flux" – same, but for MANUFACTURING group, in kg·m-2·s-1; - "Set_lower", "set_upper", "set_flux" – same, but for SETTLEMENTS group, in kg·m-2·s-1; - "Avi_lower", "avi_upper", "avi_flux" – same, but for AVIATION group, in kg·m-2·s-1; - "Tra_lower", "tra_upper", "tra_flux" – same, but for TRANSPORT group, in kg·m-2·s-1; - "Oth_lower", "oth_upper", "oth_flux" – same, but for OTHER group, in kg·m-2·s-1; - "All_lower", "all_upper", "all_flux" – same, but for all groups summed together, in kg·m-2·s-1; • Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per ENERGY_S emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. - "Sup_lower" – lower uncertainty bound (2.5th percentile of log-normal distribution) for monthly emissions of ENERGY_S group, in kg·m-2·s-1; - "Sup_upper" – upper uncertainty bound (97.5th percentile of log-normal distribution) for monthly emissions of ENERGY_S group, in kg·m-2·s-1; - "Sup_flux" – monthly emissions of ENERGY_S group, in kg·m-2·s-1; - "Month" – month numerical name, where 1, 2, …, 12 correspond to January, February, …, December; • Monthly_Ene_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per ENERGY_A emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "ene_lower", "ene_upper", "ene_flux" fields; • Monthly_Man_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per MANUFACTURING emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "man_lower", "man_upper", "man_flux" fields; • Monthly_Set_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per SETTLEMENTS emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "set_lower", "set_upper", "set_flux" fields; • Monthly_Avi_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per AVIATION emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "avi_lower", "avi_upper", "avi_flux" fields; • Monthly_Tra_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per TRANSPORT emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "tra_lower", "tra_upper", "tra_flux" fields; • Monthly_Oth_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 per OTHER emission group on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "oth_lower", "oth_upper", "oth_flux" fields; • Monthly_All_Upper_Lower_Uncertainties_0.1_0.1.nc – file has 3×12 fields with monthly emissions, and upper and lower uncertainty bounds in kg·m-2·s-1 for all groups summed together on a regular grid with 1800 pixels along the latitude and 3600 pixels along the longitude, where values represent centre of the grid-cell. File structure is identical to the file Monthly_Sup_Upper_Lower_Uncertainties_0.1_0.1.nc, but with "all_lower", "all_upper", "all_flux" fields; • CHE_EDGAR_2015.xlsx – file has 16 spreadsheets with listed information per country (metadata, emissions, uncertainties, statistical parameters). - "COUNTRY" – ISO Code (3-letter abbreviation of a geographical entity), Geographical name (name of a geographical entity), Type (development level of countries statistical infrastructure, meaning with well-/less well-developed statistical infrastructure), Main country (dependency, which country geographical entity in question belongs to), Full information (full name of a geographical entity, and what territory it occupies on the map of this study); - "GROUP" – № (number of anthropogenic CO2 emission group), ECMWF group (group name), IPCC (2006) activity (IPCC activities that are included in each group), Note (short explanation of the group), Global emission budget 2015, Mton (total global emissions per group), Prior uncertainty bounds, % (initial, calculated purely based on assumptions from IPCC, lower and upper uncertainty bounds for countries with well-/less well-developed statistical infrastructures); - "YEARLY" – ISO Code (3-letter abbreviation of a geographical entity), ECMWF group (group name), Budget, kton (yearly anthropogenic CO2 emission budget per group and total per geographical entity), Uncertainty bounds, % (calculated based on Prior uncertainty bounds and Budgets yearly uncertainties per group and total per geographical entity, uncertainties lower/upper/symmetrical bounds), Contribution to total countries uncertainty, % (share of each group in geographical entities total yearly uncertainty, total contribution is always 100 %), Parameters of log-normal distribution (anthropogenic CO2 emission distribution is assumed to be log-normal, so additionally for modelling purposes log-normal mean, log-normal standard deviation and log-normal variance were calculated); - "MONTHLY_01", "MONTHLY_02", …, "MONTHLY_12" – same explanation as for spreadsheet "YEARLY", but for a month (01, 02, …, 12 correspond to January, February, …, December).

The new CHE_EDGAR-ECMWF_2015 dataset with anthropogenic fossil CO2 emissions and their uncertainties and with a new 7×7 covariance matrix for the atmospheric transport model was compiled and tested. The fossil CO2 emissions include all long-cycle carbon emissions from human activities, such as fossil fuel combustion, industrial processes (e.g. cement) and products use, but excludes emissions from land-use change and forestry. Human CO2 emission inventories were processed into gridded maps to provide an estimate of prior CO2 emissions, aggregated in 7 main emissions groups: 1) energy production super-emitters, 2) energy production standard-emitters, 3) manufacturing, 4) settlements, 5) aviation, 6) other transport at ground level and 7) others, with estimation of their uncertainty and covariance. For the first implementation it is assumed that each emission group is fully correlated with itself and fully uncorrelated with any other group (only diagonal values are non-zero and equal to log-normal variance). The CHE_EDGAR-ECMWF_2015 represents the 2015 global fossil CO2 emissions prior at 0.1º×0.1º resolution that has been for the first time to our knowledge bridging the inventory community and the atmospheric modelling community. In fact, the uncertainty calculations fully respect the detailed error propagation approach recommended by IPCC (2006) guidelines for GHG inventories while these datasets as prior input were processed such that the uncertainty information could be fully taken up by the ECMWF model IFS. Estimation of emission uncertainties is purely based on IPCC (2006) and IPCC-TFI (2019) emission factor and activity data uncertainty values and assumptions – mainly that emissions are fully uncorrelated. Uncertainties related to the spatial distribution (representativeness of the proxy data and their uncertainty) were not assessed in this study, but they can be included by the user on top of the calculated emission uncertainties. All calculations, performed for the year 2015, are documented so that the methodology and algorithms used can be easily adapted for any other year. The dataset can be directly used in inverse modelling, and ensemble data assimilation applications, such as those envisaged within the Copernicus Atmosphere Monitoring Service (CAMS) system. CHE_EDGAR-ECMWF_2015 consists of 11 global NetCDF files with gridded yearly and monthly upper and lower bounds of uncertainties in % and kg·m-2·s-1 per each ECMWF group and their sum, and 1 Excel file with 16 spreadsheets with the same information listed per country (metadata, emissions, uncertainties, statistical parameters). Calculated emissions and uncertainties of fossil CO2 have been compared to other data sets based on the country-specific data reported to UNFCCC and on fuel-specific data reported in the energy statistics of IEA. The global values and their uncertainty at a 2σ range for the CHE_EDGAR-ECMWF_2015 dataset show the lowest value of -4.7/+9.6 % or ±7.1 % range due to the methodology used. At country level the CHE_EDGAR-ECMWF_2015 dataset provides generally larger uncertainty ranges, that are reduced when more detailed information is available to reduce the uncertainties; in summary, using the information that is uniformly available for all countries a coherent uncertainty representation is obtained. The CHE_EDGAR-ECMWF_2015 dataset has been tested to provide the ECMWF Earth system ensemble spread to characterise the CO2 atmospheric concentrations’ uncertainties in the prototype of the Copernicus CO2 Monitoring and Verification Support Capacity. Annual and monthly uncertainties have been evaluated in the ECMWF’s atmospheric transport model IFS ensemble simulations as well as the sensitivity to the spatial distribution of anthropogenic CO2 emissions (McNorton et al., 2020). Results show to be rather sensitive to the spatial distribution proxies, and most updated proxies and prior uncertainties are better adapted for data assimilation applications. This needs to be studied in a future research project, the Prototype system for a Copernicus CO2 service (CoCO2), that follows the current CHE research project. Contribution of representativeness errors to uncertainties and time correlation are neglected in CHE_EDGAR-ECMWF_2015 and will need to be assessed in successive future studies. The estimation of global gridded emissions with their spatially and temporally distributed uncertainties constitute the backbone for atmospheric inversions to estimate anthropogenic emissions from atmospheric concentrations (Pinty et al., 2017). Dedicated satellite missions (e.g. Copernicus anthropogenic CO2 monitoring mission CO2M described in Janssens-Maenhout et al. (2020)) are being planned to monitor anthropogenic emissions from space and substantially reduce emission uncertainties. The developments in the emission uncertainty based on prior knowledge computation presented in this paper is an important preparatory step for an ensemble-based CO2 Monitoring and Verification System prototype, such as the one developed within the CHE project.