Information Content, Complexity, and Uncertainty in Material Flow Analysis

With increased understanding of the effects of human activities on the environment and added awareness of the increasing societal value of natural resources, researchers have begun to focus on the characterization of elemental cycles. Indium has captured significant attention due to the potential for supply shortages and nonexistent recycling at end of life. Such a combination of potentially critical features is magnified for countries that depend on imports of indium, notably many European countries. With the aims of analyzing the dynamics of material flows and of estimating the magnitude of secondary indium sources available for recycling, the anthropogenic indium cycle in Europe has been investigated by material flow analysis. The results showed that the region is a major consumer of finished goods containing indium, and the cumulative addition of indium in urban mines was estimated at about 500 tonnes of indium. We discuss these results from the perspective of closing the metal cycle in the region. Securing access to critical raw materials is a priority for Europe, but the preference for recycling metal urban mines risks to remain only theoretical for indium unless innovations in waste collection and processing unlock the development of technologies that are economically feasible and environmentally sustainable. Keywords:industrial ecology industrial metabolism life cycle assessment (LCA) material flow analysis (MFA) recycling waste electrical and electronic equipment (WEEE)Supporting information is linked to this article on the JIE website

Section: Methodsmentioning

confidence: 99%

Backlighting the European Indium Recycling Potentials

Ciacci

Werner

Vassura

et al. 2018

“…The method involves the quantification of all material and energy inputs, stocks, and outputs required for the functioning of a socioeconomic system (Baccini & Brunner, 2012; Bringezu & Moriguchi, 2018; Fischer‐Kowalski et al., 2011). A practitioner can use it to model, understand, and optimize resource management with the exact choice of method dependent on the study's scope and aim (Müller, Hilty, Widmer, Schluep, & Faulstich, 2014; Schwab & Rechberger, 2018). For example, a dynamic MFA approach explicitly considers the evolution of material stocks and flows through time (e.g., Chen & Graedel, 2012).…”

Section: Stock–flow–service Nexus: Key Conceptsmentioning

confidence: 99%

The use of steel in the United Kingdom's transport sector: A stock–flow–service nexus case study

Carmona

Whiting

Haberl

et al. 2020

Energy and material flows and material stocks are key requirements for the supply of goods and services, which in turn support societal development. However, most resource accounting methods restrict the analysis to resource flows, which fails to acknowledge the increasing role of in‐use stocks in service provision. Using the UK transport sector as a case study, we undertook a material flow analysis through the lens of the stock–flow–service (SFS) nexus. We used the latter to identify how steel consumption and accumulation in vehicles contributed to passenger mobility between 1960 and 2015. Our results show that the efficiency of the steel stock contained in cars and motorcycles decreased from 37.5 to 28.0 passenger‐km (pkm)/kg‐year. The steel service for buses decreased from 63.6 to 32.1 pkm/kg‐year, while that of the national railway increased from 23.8 to 70.3 pkm/kg‐year steel. London Underground steel stock–service efficiency improved from 31.5 to 57.0 pkm/kg‐year steel. The annual fraction of flows that maintained the steel stock varied according to vehicle category and was between 3.4% and 8.2%. In terms of the stock expansion rate, the greatest change (on average, an annual increase of 3%) was that of “cars and motorcycles.” This reflects the demographic transitions and the growing consumer demand for car‐based mobility. We discussed how the SFS nexus contributes to a more comprehensive form of resource accounting and reflect upon some of its limitations and how they might be addressed.

“…To make data inputs more valid or their validity at least testable, scholars have been promoting data transparency (Hertwich et al., 2018). Recent examples of similar efforts include proposals for interactive visualization of data (Font Vivanco et al., 2019); general, method‐independent data model (Pauliuk, Heeren, Hasan, & Müller, 2019); investigation of uncertainty quantification and distribution in LCA (Ross & Cheah, 2019; Weidema, 2018); estimation of uncertainty (Min & Rao, 2018) and aggregation bias (Zhang, Caron, & Winchester, 2019) in using multiregional IO tables; and quantitative evaluation of MFA data quality and uncertainty (Schwab & Rechberger, 2018; Schwab, Laner, & Rechberger, 2017). Along this line, the Journal of Industrial Ecology ( JIE ) has developed data openness badges to acknowledge authors’ efforts in making data transparent and accessible.…”

Section: Toward More Transparent and Reliable Evidence: Advances In Dmentioning

confidence: 99%

Suggested use? On evidence‐based decision‐making in industrial ecology and beyond

Zhu

2020

Industrial ecology (IE) research has well established expertise in accounting for the material stocks, flows, and associated impacts of industrial and consumer activities in a variety of scales and manifestations. As with many other science and social science fields, however, the pathways from IE research findings to policy and business decision-making are often unclear and unsatisfactory. This issue creates a challenge for the application of industrial ecology to sustainable development. By reviewing several strands of literature, this article investigates alternative ways to generate and use research findings to support decision-making and social change. It argues that advances in both the core and the emerging methods in IE complement each other to improve transparency and reliability of research evidence; extension and contextualization of current findings corresponding to different stages in policy-making and organizational decision processes make research evidence more informative; a learning perspective makes research evidence valuable and used in more flexible ways. To better assist decision-making for societal change, more dialogues between researchers of different methodological cultures and between researchers and other stakeholders and a paradigm shift in social systems for which industrial ecologists should be conscious and proactive are required.