New Methodology Transforms Material Flow Analysis for a Circular Economy

Collection of timber at a building site

An innovative approach for tracking material use delivers sharper data accuracy and smarter policy decisions for a more sustainable future.

A new report from the UKRI National Interdisciplinary Circular Economy Research (CE-HUB) Programme highlights a development in material flow analysis (MFA), a key tool for tracking how materials, such as timber or concrete, move through economies. Led by Dr Rupert J. Myers from Imperial College London and Professor Julia Stegemann from University College London, the report introduces Bayesian Material Flow Analysis (BaMFA), an improved methodology that addresses major data gaps, enhances accuracy, and supports more effective policy decisions.

This report is part of the NICER Insight series, a collection of seven reports exploring key aspects of the circular economy, including human behaviour, business and finance perspectives, and technological innovations.

BaMFA represents a major step forward in material flow analysis Dr Rupert J. Myers Senior Lecturer in the Department of Civil and Environmental Engineering

MFA is widely used to understand the extraction, use, and disposal of materials, however traditional MFA methods often struggle with incomplete data, requiring estimates that can introduce significant uncertainties. The NICER report demonstrates how BaMFA, which applies Bayesian statistical techniques, can overcome these challenges by integrating both quantitative data and expert knowledge to produce more reliable results. This means policymakers can better anticipate material shortages, industries can optimise resource efficiency, and recyclers can identify the most impactful waste recovery strategies, leading to a more resilient and circular economic model.

Solving Data Challenges in Material Flow Analysis

One of the primary obstacles in MFA has been the availability and consistency of data. Information on raw material extraction and consumption is often well-documented, but data on waste generation, recycling, and material stockpiles is frequently incomplete or inconsistent. BaMFA significantly improves upon traditional MFA by using statistical inference to estimate missing data points while also quantifying the uncertainty of these estimates.

This is particularly beneficial for industries and policymakers aiming to transition towards a circular economy, where material reuse and recycling play a crucial role. By providing a clearer picture of material stocks and flows, BaMFA allows decision-makers to identify inefficiencies, improve waste management, and design more effective circular economy strategies.

Advantages of Bayesian Material Flow Analysis

BaMFA offers several key advantages, including enhanced data reliability and adaptability, as well as scaling for large and complex systems, which is useful for national and global studies of material flows.

Dr Rupert J. Myers said: "BaMFA represents a major step forward in material flow analysis. By integrating Bayesian statistics, we can generate more reliable estimates even in the presence of incomplete data, which is essential for informing circular economy policies and resource management strategies."

Real-World Applications

The NICER Programme has already applied BaMFA to critical sectors, including construction materials and global wood flows. In the case of construction aggregates in the UK, BaMFA provided a far more detailed understanding of how materials move through the system than conventional MFA approaches. This has major implications for improving recycling processes and reducing the environmental footprint of the construction industry.

Similarly, an application of BaMFA to global wood cycles has shown its potential to model large-scale material systems accurately. This is particularly important as the world explores sustainable alternatives like timber-based construction to reduce carbon emissions.

A Step Forward for the Circular Economy

As the UK and other nations work towards reducing material waste and increasing resource efficiency, innovative methodologies like BaMFA could play a crucial role in shaping a more sustainable future. The NICER Programme’s insights reinforce the need for data-driven approaches to support the transition to a circular economy, ensuring that materials are used more efficiently and sustainably than ever before.