Developing an urban geographic archetype dataset to support energy retrofit strategy on residential buildings in Düsseldorf, Germany

Cities play an important role in climate change mitigation, with building energy use often accounting for the largest share of urban CO₂ emissions. This study introduces an urban geographic archetype dataset integrated with the Urban Building Energy Model (UBEM) tool, CitySim, to assess the long-term impact of refurbishment strategies in residential areas. While the case study focuses on Düsseldorf, Germany, the methodology uses different building archetypes provided by the European TABULA project and climate data under RCP8.5 scenario for the years 2020, 2050, and 2100 to offer broader insights applicable to other European cities. Unlike many existing UBEM applications that neglect boundary conditions, our framework accounts for buildings surrounding the study area, improving simulation accuracy. Our results identify high-energy-demand building types, especially historic and older multi-family residential buildings built before 1957, which occupy over 60 % of the housing stock, accounted for 70 % of the total heating energy demand. Tailored renovation strategies in these buildings can significantly reduce annual CO₂ emissions by 42–46 % and decrease heating energy demand by approximately 70 % by 2050. Such strategy also can bring significant cost savings, with annual energy costs decreasing from 16.6 to 18.2 €/m² to 9.6–9.9 €/m². This work contributes to urban sustainability planning by prioritizing retrofit strategies based on building archetypes, climate projections, and spatial context, thus aligning with EU decarbonization targets.