Residential space heating produces substantial carbon dioxide emissions, but local climate efforts are often limited by a lack of detailed, location specific data. This study helps fill that gap by introducing an open-source tool that estimates direct, or scope 1, CO₂ emissions from residential space heating across Germany at a 100-meter resolution.
The tool uses a bottom-up method and combines publicly available data on population, average living space per person, building construction periods, heating energy carriers, heating energy consumption rates, and emission factors. With this information, it estimates living space, heating energy use, and direct CO₂ emissions for each grid cell. The Heating Emissions tool in HeiGIT’s Climate Action Navigator makes the results easy to access. Users can pick an area, explore maps and histograms, and download the data as GeoJSON files for further analysis. The interface is built to be user-friendly for both technical and non-technical users.
The analysis shows clear differences between total and per-person emissions. Densely populated urban areas generally have higher total emissions, while rural and peripheral areas often have higher emissions per person. These trends depend on factors like population density, living space, building age, heating sources, and the layout of the area.
Older buildings and the ongoing use of gas, oil, coal, wood, and biomass contribute to higher direct emissions. Electricity, heat pumps, solar and geothermal systems, and district heating are assigned zero direct emissions because the tool only measures emissions released at residential buildings. Emissions produced elsewhere are not included.
The authors compared their estimates with official data for Germany and for the cities of Heidelberg, Mannheim, Cologne, and Frankfurt. After aligning the inventories to the same scope by excluding water heating emissions where necessary, the absolute differences were below 2%. Overall, the study shows that open data, detailed estimates, and interactive maps can help spot emission patterns and support more focused heating decarbonization efforts.
Reference: Kong, G., Ulrich, V., Knoblauch, S., Martin, M., Schott, M., von Elverfeldt, K., Zipf, A., & Block, S. (2027). Residential heating emissions tool in the Climate Action Navigator: High-resolution estimation based on open data. Computers, Environment and Urban Systems, 131, Article 102525. https://doi.org/10.1016/j.compenvurbsys.2026.102525
