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Bayesian material flow analysis of the construction aggregate cycle in England

Mason, AR; Bide, T; Wang, J; Morley, J; Arora, M; Yayla, A; Stegemann, JA; (2025) Bayesian material flow analysis of the construction aggregate cycle in England. Resources, Conservation and Recycling , 215 , Article 108135. 10.1016/j.resconrec.2025.108135. Green open access

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Abstract

Quantitative analysis of material over their life cycles provides crucial insight into the movement of materials within economies, informing economic and environmental impact assessment, and governmental and industrial interventions. Material Flow Analysis (MFA) for whole material cycles is often hindered by data gaps, limiting its practical value. We apply Bayesian Material Flow Analysis (BaMFA) to quantify England's 2019 construction aggregates (sand, gravel, crushed rock) system, reducing the labour-intensive manual data reconciliation requirement of conventional MFA approaches. Despite industry-reported data describing only 20 % of the system, BaMFA fully quantifies the system, provides novel insights into its supply-demand balance, and highlights opportunities for enhanced resource efficiency and waste minimisation. This includes improved quantification of primary aggregate consumption (142 Mt, 68 % from indigenous sources) and landfilling (20 Mt, 96 % demolition waste). This research demonstrates the potential of BaMFA for quantitative analysis of material systems and evidence-based action for more sustainable and resilient futures.

Type: Article
Title: Bayesian material flow analysis of the construction aggregate cycle in England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.resconrec.2025.108135
Publisher version: https://doi.org/10.1016/j.resconrec.2025.108135
Language: English
Additional information: © 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Construction aggregates, Bayesian inference, Bayes theorem, Material flow analysis, England
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10204257
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