Building energy renovation mitigates carbon emissions but often increases material demand and financial costs. This work addresses this problem by investigating the carbon, material, and economic footprints of various renovation scenarios in the Dutch residential sector from 2015 to 2050. Results show that, compared to the baseline, façade refurbishment could lower cumulative lifecycle emissions by up to 0.3%, while raising material use by 21–25% and costs by 2–6%. Sensitivity analysis indicates that refurbishing the heating system offers greater potential for reducing carbon emissions. Rebuilding could cut emissions by up to 17% under an ambitious energy transition, though this would triple material use and construction costs. Circularity strategies could offset up to 89% of the material footprint and reduce carbon emissions by up to 23%. Nonetheless, considerable cost increases from renovations remain inevitable, even with advanced material circulation systems, suggesting circular renovation strategies with enhanced incentives as concerted action.

Re-use and recycling in the construction sector is essential to keep resource use in check. Data availability about the material contents of buildings is significant challenge for planning future re-use potentials. Compiling material intensity (MI) data is time and resource intensive. Often studies end up with only a handful of datapoints. In order to adequately cover the diversity of buildings and materials found in cities, and accurately assess material stocks at detailed spatial scopes, many more MI datapoints are needed. In this work, we present a database on the material intensity of the Dutch building stock, containing 61 large-scale demolition projects with a total of 781 datapoints, representing more than 306,000 square meters of built floor space. This dataset is representative of the types of buildings being demolished in the Netherlands. Our data were empirically sourced in collaboration with a demolition company that explicitly focuses on re-using and recycling materials and components. The dataset includes both the structural building materials and component materials, and covers a wide range of building types, sizes, and construction years. Compared to the existing literature, this paper adds significantly more datapoints, and more detail to the different types of materials found in demolition streams. This increase in data volume is a necessary step toward enabling big data methods, such as data mining and machine learning. These methods could be used to uncover previously unrecognized patters in material stocks, or more accurately estimate material stocks in locations that have only sparse data available. This article met the requirements for a Gold-Gold JIE data openness badge described at http://jie.click/badges.