Projects per year
Abstract
The built environment contributes around 37% of global energy and process-related greenhouse gas emissions and requires significant decarbonisation to reach global net-zero targets. This means that the existing markets for construction products need to change drastically. Life cycle assessment (LCA) is critical in calculating the environmental impacts of construction products, element designs (such as facades) and buildings. The initial stages of a project create the best opportunity to minimise the final design's environmental impact.
A wealth of ¬environmental product declaration (EPD) data is now available. However, EPDs are often too specific for the early stages of projects where specifications are unknown. Building designers, therefore, need better representative data for early-stage LCA, where there is currently a lack of generic data for construction materials and newly emerging novel products.
Weighted averages from individual datasets weighted by market share (production volume), can help to bridge this data gap. Our new framework for creating weighted average datasets, incorporating uncertaintyfor an example material – steel. For the first time, these weighted averages consider uncertainty in both production volume (market) and LCI datasets. The ability to aggregate individual datasets into weighted averages could empower designers to make more confident early-stage decisions despite incomplete LCA data. And the data categorisation and filtering criteria, the weighted values can be uniquely defined, with the option to increase the specificity of the average value as assessments become more certain,
Finally, if production volumes and uncertainty information were included in EPDs, the method given in this paper could unlock the potential in the rapidly growing library of construction material EPDs to support early-stage LCA.
A wealth of ¬environmental product declaration (EPD) data is now available. However, EPDs are often too specific for the early stages of projects where specifications are unknown. Building designers, therefore, need better representative data for early-stage LCA, where there is currently a lack of generic data for construction materials and newly emerging novel products.
Weighted averages from individual datasets weighted by market share (production volume), can help to bridge this data gap. Our new framework for creating weighted average datasets, incorporating uncertaintyfor an example material – steel. For the first time, these weighted averages consider uncertainty in both production volume (market) and LCI datasets. The ability to aggregate individual datasets into weighted averages could empower designers to make more confident early-stage decisions despite incomplete LCA data. And the data categorisation and filtering criteria, the weighted values can be uniquely defined, with the option to increase the specificity of the average value as assessments become more certain,
Finally, if production volumes and uncertainty information were included in EPDs, the method given in this paper could unlock the potential in the rapidly growing library of construction material EPDs to support early-stage LCA.
Original language | English |
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Journal | Journal of Cleaner Production |
Publication status | Acceptance date - 12 Dec 2024 |
Funding
Funders | Funder number |
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EPSRC - EU |
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InNovative Bio&geo-soUrced, re-used & recycled products coupled with BIM-based dIgitaL platform for very low carbon consTruction, circular economy, energy and resource efficiency - Horizon Europe Guarantee Extension
Allen, S. (PI), Cascione, V. (CoI), Maskell, D. (CoI), Shea, A. (CoI), Walker, P. (CoI), Holcroft, N. (Researcher) & Marsh, E. (Researcher)
Innovate UK, Innovate UK Business Connect
1/12/23 → 31/05/27
Project: EU Commission
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Towards net-zero carbon buildings: tackling UNcertainty when predicting the CARbon footprint of construction products and Buildings (UNCARB)
Allen, S. (PI), Kyprianou, A. (CoI), Hattam, L. (Researcher) & Marsh, E. (Researcher)
Engineering and Physical Sciences Research Council
16/08/21 → 19/07/24
Project: Research council