Exploring the value of reused building products in renovation and their impact on decision-making
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Last Updated: 3-2024
While sustainability gains more attention in the field of construction, the practice of reusing
building materials is more frequently discussed. However, it remains unclear what the extent
of its impact on the value of a building can be. Thus, selecting more traditional building
techniques and materialisations is often more straightforward. This study aims to challenge
this inclination by evaluating the exact quantified value of applying reused building products in
renovation projects. Thus, the ReSoRS decision-making tool was developed. Based on an
extensive review of existing decision-making tools in the literature and validated in its outputs
with two case studies, the tool is tailored for renovation projects of apartment buildings. It
allows the user to compare renovation scenarios easily. The user can select building products
from a local database to model an existing building and input three renovation scenarios for
side-by-side comparison. For this study, twenty-four unique renovations were modelled,
varying in materialisation, renovation level, and intensity of product reuse, to understand how
product reuse interacts with each parameter. Comparing these 24 scenarios showed that high
levels of renovation profit more from reuse practices. However, they may be less feasible as
the practice is still in an early innovative stage. Furthermore, the push towards biobased
construction and reuse appear to complement one another, as biobased products are
generally easier to reuse. Finally, reusing building products may not significantly impact
decision-making in its current capacity as the impact on financial value is not very large. Reuse
may become a more fruitful practice, looking forward to the potential implementation of
environmental impact costing. Whilst the study aimed to minimise errors and biases through
validation with financial and environmental data of two apartments, the nature of the study
makes it quite prone to error through invalid assumptions. This risk has been minimised by
validating the tool with experts in the field at multiple points in the development process.
Nevertheless, the most significant area for improvement is the inclusion of empirical data to
reduce the number of assumptions.