Greenhouse gas emission reduction from residential building renovations in Rotterdam, The Netherlands

Within the research project DE-CIST (“Developing Energy Communities with Intelligent and Sustainable Technologies”) a novel, AI-based Energy Demand Simulator has been developed by our project partners. The Energy Demand Simulator determines the energy efficiency and energy saving potential of the residential building stock in Rotterdam (The Netherlands). By adding socio-economic features to the Energy Demand Simulator, the tool will guide policy makers in developing building renovation strategies on different scales, allowing to design household-level renovation packages which consider social, financial, and physical requirements.  

From such building renovation scenarios, we calculated greenhouse gas emissions and the emission reduction potential of the renovation actions. This insight will allow policymakers to optimize the renovation strategies also for climate change mitigation. We conducted a series of high-resolution (100 m²) simulations of CO₂ emissions using the Dutch Large Eddy Simulation (DALES) model for the city of Rotterdam. DALES is particularly advantageous due to its explicit simulation of boundary-layer turbulence, enhancing the accuracy of atmospheric transport and dispersion of chemical species in the urban environment. The emission inputs for DALES were refined from the Dutch national emission inventory by incorporating statistical data on household gas consumption specific to Rotterdam. This involves adjusting the emission estimates to reflect high-resolution local consumption patterns and spatial distribution, which improves the spatial accuracy of the modeled emissions. This approach will be extended to reactive gases to gain insights into the exposure of citizens to air pollution in combination with other socio-economic conditions.