| Title | Material intensity database for the Dutch building stock: Towards Big Data in material stock analysis |
|---|---|
| ID_Doc | 26074 |
| Authors | Sprecher, B; Verhagen, TJ; Sauer, ML; Baars, M; Heintz, J; Fishman, T |
| Title | Material intensity database for the Dutch building stock: Towards Big Data in material stock analysis |
| Year | 2022 |
| Published | Journal Of Industrial Ecology, 26, 1 |
| Abstract | 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 . |
| https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jiec.13143 |
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