Material intensity database for the Dutch building stock: Towards Big Data in material stock analysis

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 http://jie.click/badges.

Data innovation in industrial ecology

“…datasets in an open manner (Xie et al, 2021), or even earned JIE's Data Openness Badge (Agez et al, 2021;Asensio et al, 2021;Huang & Eckelman, 2020;Kerdlap et al, 2021;Sprecher et al, 2021;Vilaysouk et al, 2021). 1 Similarly, studies in this special issue contributed new open-source code (Agez et al, 2021;Joyce & Björklund, 2021) or extended open-source software from this community (Vunnava et al, 2021).…”

“…The publication, documentation, and analysis of extensive, high-resolution datasets are increasingly often the primary objective of IE research projects. Sprecher et al (2021) worked with demolition projects to empirically sample the material intensity of the Dutch building stock, documenting a range of building types, sizes, and construction years in terms of multiple structural and component materials. Rather than directly focussing on materials (e.g., glass), Arbabi et al (2021) Energy Agency (IEA).…”

“…For some studies, the very insight that they seek hinges on a fine geographical mapping of data points, demonstrating the extent to which geographic information system (GIS) data is pervading IE research. Such GIS-based research ranges from the mapping of waste (Ballatore et al, 2021;Kerdlap et al, 2021) or of infrastructure stocks (Arbabi et al, 2021;Ebrahimi et al, 2021;Sprecher et al, 2021)…”

“…Many publications focus on cities and their urban metabolism, leveraging the increased data richness of these dense environments (Arbabi et al, 2021;Ballatore et al, 2021;Clark et al, 2021;Hastie et al, 2020;Xie et al, 2021). Characterizing material stocks, especially infrastructures, is also increasingly facilitated by novel data acquisition and analysis techniques (Arbabi et al, 2021;Ebrahimi et al, 2021;Sprecher et al, 2021;Vilaysouk et al, 2021;Zhou et al, 2021). In particular, waste management and recirculation strategies are propelling a very diverse set of novel data-driven research (Ballatore et al, 2021;Davis & Aid, 2021;Kerdlap et al, 2021;Zhou et al, 2021).…”

Making it Concrete: Analysing the Role of Concrete Plants’ Locations for Circular City Policy Goals

“…The building material stocks within the case study were calculated based on the methodology by Verhagen et al (2021). The public spatial dataset of the Netherlands, the BAG3D (2020 version), was combined with the material intensity data of Sprecher et al (2021) for the municipal boundaries of the Hague. With the use of the BAG3D dataset, it was possible to identify the following residential buildings types: detached houses, row houses, apartments and high rise.…”