Selection Tool

Use Cases -Experimentation

Taxonomy and Choice of Appropriate

Set of Circularity Indicators -

The Circularity Indicators Advisor SAIDANI Michael, YANNOU Bernard, LEROY Yann, CLUZEL François

Laboratoire Genie Industriel, CentraleSupélec Université Paris-Saclay, France Contact: michael.saidani@centralesupelec.fr

ATA EcoSD 2018

Orange Gardens, Châtillon

References Circularity Indicators (CI) Proposed Taxonomy

 The circular economy (CE) seems promising to meet the goals of sustainable development (Schroeder et al. 2018)  Yet, two key challenges have still to be addressed: i. How to support CE practitioners in this transition? ii. How to assess the circularity performance?  Joint agreement on the need to measure the progress towards circularity in order to enhance and monitor the impacts, and benefits of this transition.

Presentation

Goal: To support the users in identifying and selecting the most appropriate circularity indicators in line with their objectives.

Audience: Industrial practitioners (e.g. designers, engineers, managers) decision-makers and policy-makers working in CE projects. Software: Microsoft Excel worksheet based tool with macro enabled.

Database: A pool of more than 50 sets of circularity indicators.

Input Data

In the input interface of the Excel file, one can specify the desired features, by answering 8 multiple-choice questions, e.g. if one is interested in measuring the inherent circularity (i.e. recirculation of resources) or the consequences (i.e. impacts) of such circularity?

Run the Search

Once the query is completed, a click on the round logo at the top starts the search.

Outputs

The tool directs automatically to the results table of recommended indicators. It includes a short description of each selected indicator, its working principle, the data required to be computed, and a summary of its potentially useful usages.  Tutorial video https://youtu.be/nRNbWyHRzic  Industrial application https://youtu.be/kd51SsX0Be4

Explore, Test, & Implement



  Azevedo, S.G., Godina, R. and Matias, J.C.O. 2017. Proposal of a Sustainable Circular Index for Manufacturing Companies. Resources, 6, 63.  Bovea, M.D. and Pérez-Belis, V. 2012. A taxonomy of ecodesign tools for integrating environmental requirements into the product design process. Journal of Cleaner Production.  Cayzer, S., Griffiths, P. and Beghetto, V. 2017. Design of indicators for measuring product performance in the circular economy, International Journal of Sustainable Engineering,  Elia, V. et al. 2017. Measuring circular economy strategies through index methods: A critical analysis. Journal of Cleaner Production. Volume 142, pp. 2741-2751.  Ellen MacArthur Foundation (EMF). 2015. Circularity Indicators -An Approach to Measure Circularity. Methodology & Project Overview; Cowes, UK.  European Commission (EC). 2015. Closing the Loop -An EU Action Plan for the Circular Economy. COM (2015) 614/2; Brussels, Belgium.  Geissdoerfer, M., Savaget, P. and Bocken, N.M. 2017. The Circular Economy -A new sustainability paradigm? Journal of Cleaner Production, Volume 143, pp.757-768.  Geng, Y. et al. 2013. Towards a national circular economy indicator system in China: An evaluation and critical analysis. Journal of Cleaner Production, Volume 23, pp. 216-224.  Pauliuk, S. 2018. A dashboard of quantitative system indicators for its implementation in organizations. Resources, Conservation and Recycling, Volume 129, pp. 81-92.  Rousseaux, P. et al. 2017. "Eco-tool-seeker": A new and unique business guide for choosing ecodesign tools. Journal of Cleaner Production, Volume 151, pp. 546-577.  Saidani, M., Yannou, B., Leroy, Y. and Cluzel, F. 2017. How to Assess Product Performance in the Circular Economy? Recycling 2, no. 1: 6.  Saidani, M., Yannou, B., Leroy, Y. and Cluzel, F. 2017. Hybrid top-down and bottom-up framework to measure products' circularity performance. ICED17.  Saidani, M., Yannou, B., Leroy, Y., Cluzel, F., Kendall, A. 2019. A taxonomy of circular economy indicators. Journal of Cleaner Production, Vol 207, pp. 542-559.  Schroeder, P., Anggraeni, K. and Weber, U. 2018. The Relevance of Circular Economy Practices to the Sustainable Development Goals. Journal of Industrial Ecology.  Urbinati, A. et al. 2017. Towards a new taxonomy of circular economy business models. Journal of Cleaner Production. Volume 168, pp. 487-498.

  (Geng et al. 2013) (EC, 2015) (Cayzer et al. 2017)  Due to an increasing number of CI with many different scopes, purposes and usages, the objective is to provide clarity on these indicators, so as to guide CE practicioners towards the right set of indicators, regarding their needs and requirements. Research approach = Extensive literature review on CE-related indicators. Identification, analysis and classification of over 50 sets of circularity indicators developed and used by academics, businesses, consulting companies, environmental organisations and governmental agencies. In line and in complementarity with existing taxonomies of eco-design tools(Rousseaux et al. 2017) (Bovea and Pérez-Belis, 2012) and of circular economy business models (Urbinati et al. 2017)  Clustering method: Proposition of a need-based taxonomy, driven by the usages of such indicators.  Combinatory aspects: The approximately 200 possible pathways thought criteria combination -among the 50 sets of indicators inventoried -ensure a rapid convergence towards the most suitable circularity indicator(s).

A

  direct internet access link to each of the recommended indicators and their assessment framework is also indicated, to get more details on the indicator, to experiment their associated assessment framework (e.g. formulas to compute, web-based tool, dynamic Excel spreadsheet, etc.) and, if relevant, to start implementing such indicator(s) in diverse circular economy project(s). Focus on the micro level of CE (i.e. company, products, components and materials):  To explore how appropriate CI can help (re-)designing better circular products.  To experience the tool on CI use cases published in literature to test its robustness (e.g. on used starter engines, prototype tidal energy device, and catalytic converter).  Perspectives: to link CI heuristics with tangible impacts; to keep the databank up-to-date.

  Potentially useful applications: circularity and sustainability performance assessment, improvement guidelines, decisionmaking, management, benchmarking, communication, etc.

	Level	Definition	Example
		City,	19% of the UK
	Macro	region,	economy	is
		nation,	circular in 2010
	Meso Micro	Inter-entreprise Company, Products, Materials	EIPs performance Material Circularity Indicator	Categories	Levels (micro, meso, macro)	Loops (maintain, reuse/reman, recycle)	Perspective (actual, potential)	Performance (intrinsic, impacts)	Units (quantitative, qualitative)
					(criteria)	Dimension (single, multiple)	Usages (e.g. improvement, benchmarking, communication)	Sources (academics, companies, agencies)	Transversality (generic, sector-specific)	Format (e.g. web-based tool, Excel, formulas)
		…