4.7 Article

Using fuzzy cognitive maps to identify better policy strategies to valorize organic waste flows: An Italian case study

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 319, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.128722

Keywords

Italy; Circular bioeconomy; Organic fraction of municipal solid waste; Policy scenarios; (OFMSW); Policy mixes; Organic fraction of municipal solid waste (OFMSW)

Funding

  1. German Federal Ministry for Education and Research (BMBF) [Forderkennzeichen 031B0781A]

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In Europe, there is a significant amount of municipal waste available for utilization, with the organic fraction representing a valuable part that can be used to produce value-added products. This study focused on Italy's bioeconomy sector and the use of OFMSW as feedstock, identifying barriers to effective adoption of the CBE and suggesting policy strategies to improve outcomes. Results highlighted that excessive bureaucracy, linear logic, and technology-based solutions ignoring waste planning complexities were key factors influencing the implementation of CBE in Italy, with a policy mix combining economic support and waste collection system improvements showing the most positive impact on outcomes.
In Europe, there is a vast amount of municipal waste available. The organic fraction of municipal solid waste (OFMSW) represents a particularly valuable part of this waste, due to its potential to be employed to produce a range of value-added products. While several studies have addressed the utilization of the OFMSW in the Italian context, an overall picture of how the circular bioeconomy (CBE) model is being implemented in Italy is lacking. Accordingly, the present study investigated the status quo of the Italian bioeconomy sector, focusing on the use of the OFMSW as feedstock. The research aimed at increasing our understanding of barriers to the effective adoption of the CBE and identifying effective policy strategies. Specifically, a fuzzy cognitive mapping technique using an artificial neural network model was used to assess the impact of both single policy measures and policy mixes on a sample of selected outcomes, including human health, the environment, profitability and biorefinery approach. The results clearly showed that excessive bureaucracy, linear logic and technology-based solutions ignoring the complex characteristics of waste planning activities were the most important variables influencing the implementation of the CBE in Italy. Moreover, the results suggested that a policy mix combining economic and financial support policies for sustainable activities alongside improvements to waste collection systems could generate the highest positive effect on all considered outcomes.

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