Yes / Quantification of stocks and flows of construction materials is a key first stage in assessing the potential for creating higher value at end-of-life decisions compared to destructive demolition. Steel and concrete are amongst the most widely used construction materials primarily in structural components. Such components are highly variable in design, type, and dimensions. In the absence of urban-scale digitised models of structural components or building plans, accurate assessment relies on either onsite inspection or modelling by material intensity (MI) co-efficient which can vary by up to a factor of 100. In this study, we extend previous stock modelling approaches through the development of a method that relies on building archetypes and produces MI coefficients of steel and concrete that are representative of frame types, temporally explicit and disaggregated at product level. This is compared to the common existent method of calculating MI to demonstrate the capabilities of the proposed method. Coupled with a spatiotemporal model of urban buildings, the developed MI of both methods are applied to a case study in the UK. The total in-use stock of steel and concrete within multi-storey buildings is estimated at 81,000 tonnes and 655,000 m3 respectively. The stocks of steel and concrete are disaggregated based on their functions as products, for instance steel beams are distinguished from reinforcement steel. Subsequently, the embodied carbon of the in-use stock is calculated as 350 kt CO2eq. The results show the proposed method enables a more granular assessment of the embodied carbon of the structural material quantities. / This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) research grant ‘REBUILD - REgenerative BUILDings and products for a circular economy’ [Grant reference: EP/ P008917/1]
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18602 |
| Date | 15 September 2021 |
| Creators | Ajayebi, A., Hopkinson, P., Zhou, Kan, Lam, Dennis, Chen, H-M., Wang, Y. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2021 Elsevier B.V. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license., CC-BY-NC-ND |
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