Governing the circular economy: how urban policymakers can accelerate the agenda
Notice bibliographique
Résumé
We believe the climate crisis will be resolved in cities. Today, while cities occupy only 2% of the Earth's surface, 57% of the world's population lives in cities, and by 2050, it will jump to 68% (UN, 2018). Currently, cities consume over 75% of natural resources, accumulate 50% of the global waste and emit up to 80% of greenhouse gases (Ellen MacArthur Foundation, 2017). Cities generate 70% of the global gross domestic product and are significant drivers of economic growth (UN-Habitat III, 2016). At the same time, cities sit on the frontline of natural disasters such as floods, storms and droughts (De Sherbinin et al., 2007; Major et al., 2011; Rockström et al., 2021). One of the sustainability pathways to reduce the environmental consequences of the current extract-make-dispose model (or the "linear economy") is a circular economy (CE) model. A CE is defined as "an economic system that is based on business models which replace the 'end-of-life' concept with reducing, alternatively reusing, recycling and recovering materials in production/distribution and consumption processes" (Kirchherr et al., 2017, p. 224). By redesigning production processes and thereby extending the lifespan of goods and materials, researchers suggest that CE approaches reduce waste and increase employment and resource security while sustaining business competitiveness (Korhonen et al., 2018; Niskanen et al., 2020; Stahel, 2012; Winans et al., 2017). Organizations such as the Ellen MacArthur Foundation and Circle Economy help steer businesses toward CE strategies. The CE is also a political priority in countries and municipalities globally. For instance, the CE Action Plan, launched by the European Commission in 2015 and reconfirmed in 2020, is a central pillar of the European Green Deal (European Commission, 2015, 2020). Additionally, more governments are implementing national CE strategies in China (Ellen MacArthur Foundation, 2018), Colombia (Government of the Republic of Colombia, 2019), Finland (Sitra, 2016), Sweden (Government Offices of Sweden, 2020) and the US (Metabolic, 2018, 2019), to name a few. Meanwhile, more cities worldwide are adopting CE models to achieve more resource-efficient urban management systems, thereby advancing their environmental ambitions (Petit-Boix & Leipold, 2018; Turcu & Gillie, 2020; Vanhuyse, Haddaway, et al., 2021). Cities with CE ambitions include, Amsterdam, Barcelona, Paris, Toronto, Peterborough (England) and Umeå (Sweden) (OECD, 2020a). In Europe, over 60 cities signed the European Circular Cities Declaration (2020) to harmonize the transition towards a CE in the region. In this policy brief, we provide insights into common challenges local governments face in implementing their CE plans and suggest recommendations for overcoming these. It aims to answer the question: How can the CE agenda be governed in cities? It is based on the results of the Urban Circularity Assessment Framework (UCAF) project, building on findings from 25 interviews, focus group discussions and workshops held with different stakeholder groups in Umeå, as well as research on Stockholm's urban circularity potential, including findings from 11 expert interviews (Rezaie, 2021). Our findings were complemented by the Circular Economy Lab project (Rezaie et al., 2022) and experiences from working with municipal governments in Sweden, Belgium, France and the UK, on CE and environmental and social sustainability.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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