This paper presents the High-Elective Resolution Modelling Emission System delta version (HERMES_Δ), an open-source, parallel and flexible emission processing tool to bridge the gap between official inventories and model-ready emissions for air quality and greenhouse gas (GHG) modelling applications. HERMES_Δ processes and combines the inventories reported to the Convention on Long-Range Transboundary Air Pollution, the EU National Emission Ceilings Directive and the UN Framework Convention on Climate Change with a large collection of detailed spatio-temporal proxies and speciation profiles to create gridded, hourly and speciated emissions for input into a variety of mesoscale modelling systems, including CHIMERE, CMAQ, MOCAGE, MONARCH and WRF-CHEM. Official emissions at sectoral and industrial facility-level of NO<sub>x</sub>, SO<sub>x</sub>, CO, NH<sub>3</sub>, non-methane volatile organic compounds (NMVOC), PM<sub>10</sub>, PM<sub>2.5</sub>, black carbon (BC), CO<sub>2</sub> and CH<sub>4</sub> are combined, whereafter a detailed horizontal, vertical, temporal and speciation treatment is applied to produce ready-to-use modelling emissions compatible with multiple user-defined grids and chemical mechanisms. As a results, HERMES_Δ provides self-consistent air pollutants and GHG high resolution emissions, thus enhancing the integrated analysis of emissions affecting both air pollution and climate change. The paper exemplifies the use of HERMES_Δ by processing the Spanish official inventories and describing the methods and sources of information considered to construct the required input information, which can be used as a guidance for potential applications in other countries. Illustrations of HERMES_Δ emission outputs and of its computational performance are provided to show its capabilities. The model is designed following a flexible and transparent framework, so that it can be applicable to any European country where the required input data are available. The HERMES_Δ code is distributed through a Zenodo repository (<a href="https://doi.org/10.5281/zenodo.21393948" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.21393948</a>, last access: 10/07/2026).