Key strategies for decarbonizing the residential building stock: Results from a spatiotemporal model for Leiden, the Netherlands

Decarbonizing the building stock plays an important role in realizing climate change mitigation targets. To compare the decarbonization potential of different strategies, this study presents a spatiotemporal bottom-up dynamic building stock model that integrates material flow analysis, building energy modeling, and life cycle assessment. It can simulate future building stock evolution at the component level and track the associated material flows, energy demand and generation, and GHG emissions with the consideration of both endogenous factors (e.g. building energy efficiency upgrade) and exogenous factors (e.g. policies, occupant behavior, and climate scenarios). The model is applied in the residential building stock of Leiden, a municipality in the Netherlands. Results show that annual GHG emissions are reduced by about 40% under the reference scenario while annual GHG emissions can be reduced by about 90% under the ambitious scenario where all the decarbonization strategies are simultaneously implemented. Natural-gas-free heat transition and renewable electricity supply are the most effective strategies, respectively reducing the annual GHG emissions in 2050 by an additional 21% and 19% more than the reference scenario. Rooftop PV, green lifestyle, and wood construction have similar decarbonization potential (about 10%). Surplus electricity can be generated if rooftop PV systems are installed as much as possible. The decarbonization potential of demolition waste recycling is much smaller than other strategies. The model can support policymakers in assessing the decarbonization potential of different policy scenarios and prioritizing decarbonization strategies in advance.

Automated summary

Decarbonizing the building stock is crucial for mitigating climate change. This study presents a comprehensive model that compares the decarbonization potential of different strategies for the building stock. The model can simulate the future evolution of the building stock and track the associated material flows, energy demand, and greenhouse gas emissions.