Deliverable

D2.1 | D2.2 | D3.1 | D3.2 | D3.3 | D3.4 | D4.1 | D4.2 | D5.1 | D5.2 | D5.3 | D6.4.1 | D6.4.2

Concise description of application fields for different MFA approaches and indicators

MinFuture is a collaborative project funded by the Horizon 2020 framework, aiming to identify, integrate, and develop expertise for global material flow analysis and scenario modelling. In order for material flow analysis to be comprehensive, integrative and systemic in its approach, MinFuture analyses the material cycles across four dimensions:

  1. life cycle stages, including all processing steps from mining to waste disposal,
  2. trade flows through the global economy,
  3. the interactions or “linkages” that occur during the material cycle, such as compositional change, energy content, and monetary value,
  4. and a time dimension to calibration and future scenario modelling.

To this end, one of the first tasks of MinFuture is to have a comprehensive understanding of existing modelling approaches and indicators of resource accounting to the field of mineral raw materials management.

This deliverable entitled “Concise description of application fields for different MFAa pproaches and indicators” summarizes the results of this task. It describes the various methods of material flow analysis (MFA) applied to raw materials, and analyses existing indicators in terms of a characterization scheme that was developed by the MinFuture partners (chapter 4). Chapter 5 gives various case studies illustrating MFA methods and indicators, and chapter 6 identifies some recommendations.

In addition to the four dimensions (stages, trade, linkages, time), we also identified some additional “transversal” factors that are important to consider when evaluating MFAs.

Some of these transversal factors are data related, such as how is data visualized or how is data uncertainty handled, whereas some other factors to consider are more general or difficult to categorize, such as how the analysis contributes to decision making. Table 10 in Chapter 6 summarizes the assessment of all the MFA methods.

Indicators for efficient and effective raw materials use are used to define problems, to formulate policies, and to implement policies. The aim of the policies informed by raw materials indicators is always to change certain aspects of the socio-economic metabolism. Since the different parts of the socio-economic metabolism are all linked with each other, we can also say that the aim is to transform the socio-economic metabolism in a desired direction. This is a complex task, because

  1. the socio-economic metabolism is highly complex (dynamic, multi-layer, international supply chains);
  2. the socio-economic metabolism is still poorly understood;
  3. indicators are drastic simplifications of the socioeconomic metabolism;
  4. the desired direction is often not clearly defined;
  5. and there are many, often diverging, interests of different stakeholders.

There are three main recommendations in regards to indicators used to measure raw materials in the EU: 1) raw material indicators used in policy should consider the physical quality and criticality of the materials, 2) researchers and analysts should provide complete traceability and repeatability of the data provided in their studies, so as to promote raw material data in a centralized database, 3) indicators should be used to complement consistent monitoring of the socio-economic metabolism by government authorities.

Publishing Date May, 2018
MinFuture Authors Gara Villalba
Marta Iglesias Émbil
Language English
Citation Villalba, G., Iglesias, M., Gabarell, X. (2018). Concise description of application fields for different MFA approaches and indicators. MinFuture deliverable D3.2. Universitat Autònoma de Barcelona - UAB.
Credits Contributors: Helmut Rechberger, TU Wien / Astrid Allesch, TU Wien / Gang Liu, SDU / Zhi Cao, SDU / Jan Kovanda, CUNI / Monika Dittrich, IFEU / Joanna Kulczycka, IGSMIE / Marzena Smol, IGSMIE / Jonathan Cullen, UCAM / Sebastian Brazell, UCAM / Elsa Olivetti, MIT / Xinkai Fu, MIT / Daniel B. Müller, NTNU.
Attachments MinFuture_WP3_Task3.1 _D3.2 (Final incl. Annex) - Revised.pdf