Open AccessComprehensiveness of circular economy assessments of regions: a systematic review at the macro-level
Author(s) -
Bart J.A. van Bueren,
Usha IyerRaniga,
Mark A.A.M. Leenders,
Kevin Argus
Publication year - 2021
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/ac209c
Subject(s) - benchmarking , macro , reuse , circular economy , computer science , cluster analysis , resource (disambiguation) , environmental economics , stakeholder , resource efficiency , environmental resource management , data science , business , environmental science , economics , machine learning , ecology , marketing , computer network , management , biology , programming language
The circular economy (CE) is emerging as a solution for a thriving economy within regional and planetary boundaries for environment and social justice. CE is multifaceted with interconnected processes and therefore rather difficult to assess comprehensively. This paper reviewed the corpus of macro-level CE assessments, to find the best practices in CE assessments of regions scaling from neighborhoods to planetary. The extensive content analysis on the corpus of 165 studies used a novel mixed methods of meta-analysis, taxonomy and integrative review. This review investigates the comprehensiveness of CE assessments. Findings include three types of CE performance monitoring, four types of resource clustering, five scales, and a 5-step procedure to evaluate CE. CE can be monitored on: (a) absolute performance, quantifying economic resource-input, stock and waste-output; (b) efficiency performance, monitoring the optimization of CE processes similar to recycling, reuse, or even sharing and virtualizing; (c) policy performance to monitor strategies from regional stakeholders. Resource clustering can create hierarchies by metrics, uses, system-boundaries, or emergy. Identified scales are: XL for the planet; L for continents; M for large provinces, states and smaller countries; S for cities; and, XS for neighborhoods. Scales assist in comparing and benchmarking, but are also required for a proposed policy of localizing CE. This review found the ReSOLVE-framework as relatively comprehensive on CE processes. Also, multiple knowledge gaps were identified among resources, processes and regions. This review aids CE knowledge accumulation across regions and scales, to accelerate implementing the CE.