The gridded emissions dataset has been prepared in the Horizon Europe project AVENGERS (https://avengers-project.eu/). It combines official gridded national GHG emissions inventories from Sweden, Germany, the Netherlands, Switzerland and Italy with the TNO gridded GHGco inventory for the other countries in the European domain (30°W-60°E, 30°N-72°N) at a resolution of 0.05°x0.1° (lat-lon). The TNO GHGco inventory is an updated version of the TNO CAMS-REG inventory (Kuenen et al., 2022, https://doi.org/10.5194/essd-14-491-2022) with point sources at exact location. The country gridded emission inventory data have been provided by: * Sweden: The gridded data for Sweden originates from the national emission database (https://nationellaemissionsdatabasen.smhi.se). The years 2011-2014 were prepared by combining reported emissions with the spatial distribution of the nearest year. * Germany: UBA Germany (national inventory submission 2024), gridded with GRETA tool, partially based on GNFR stratified NUTS-3 data provided by Thünen Institute (https://www.eminv-agriculture.de) * the Netherlands: RIVM, the Netherlands, prepared the gridded national emission inventory of the Netherlands for 2010, 2015, 2019, 2020 and 2021. Intermediate years were prepared by combining reported emissions with the spatial distribution of the nearest year. * Switzerland: The Swiss national inventory is based on officially reported data of the Federal Office for the Environment (FOEN). Spatial mapping of sectorial emissions was based on high-resolution grids kindly made available by the company Meteotest, Switzerland. * Italy: The Italian Inventory Agency ISPRA produced distributed emissions at province level for 2010, 2015 and 2019. Intermediate years were prepared by combining reported emissions with the spatial distribution of the nearest year.

A detailed description of the dataset and the methodology is provided in Dröge et al (2024), AVENGERS deliverable D2.2 Anthropogenic emission inventories and natural flux data (in press). This dataset supports Thanwerdas et al. (2026), Exploring atmospheric CH4 monitoring network expansion in Italy using inverse modelling, https://doi.org/10.5194/egusphere-2025-5804 , Atmospheric Chemistry and Physics, in press.