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Hydrogen is considered one of the most promising solutions in future energy systems. Previous work on hydrogen energy systems predominantly analysed hydrogen models on a national level or only parts of the mobility sector. This indicates a research gap for geospatial models that include multiple sectors in which hydrogen can be used. These models can be used to support decision-making processes around the hydrogen economy in cities. This study presents a holistic model addressing the geospatial modelling of hydrogen demand in urban areas. It proposes a method that integrates a variety of open source data, including geodata, earth observation data and energy data to estimate hydrogen demand top down for the industrial feedstock (steel, ammonia, organic chemistry), process heating, and mobility (buses, trucks, trains, airplanes, ships) sectors. The proposed method can also be extended to different sectors. The method is validated by modelling the hydrogen demand in all German cities and benchmarking it with national studies. This study\u2019s results are within the same range as the results of national studies. For this paper, the method is applied for two case studies in Freiburg im Breisgau and Frankfurt am Main. Applying this method in urban areas shows potential hydrogen demand hotspots in these areas. The model\u2019s results help policymakers and industry stakeholders make informed decisions about the development of hydrogen infrastructure and facilitate the adoption of hydrogen as a low-carbon energy carrier. Future research could explore the temporal aspects of hydrogen demand and the spatial influence of hydrogen demand on future hydrogen production facilities such as electrolysers.<\/jats:p>","DOI":"10.1186\/s42162-023-00291-2","type":"journal-article","created":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T14:02:13Z","timestamp":1697724133000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A methodological framework for geospatial modelling of hydrogen demand in cities"],"prefix":"10.1186","volume":"6","author":[{"given":"Stefan","family":"Beck","sequence":"first","affiliation":[]},{"given":"David","family":"Fischer","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,19]]},"reference":[{"key":"291_CR39","unstructured":"Air BP Ltd. 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