Methodology for the sustainability assessment of food loss and waste prevention actions
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2024-11-28
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Universidad de Deusto
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Food Loss and Waste (FLW) pose a significant global challenge, with approximately one-third of all food produced for human consumption lost or wasted annually, amounting to about 1.3 billion tons. This immense loss has profound environmental, economic, and social implications, contributing to environmental issues, economic inefficiencies, and food insecurity. In the European Union alone, an estimated 88 million tons of food are wasted annually, costing approximately €143 billion. For these reasons such a problem is embodied in Sustainable Development Goal (SDG) 12.3 aims to halve per capita global food waste by 2030, underscoring the urgency to understand FLW across the entire Food Supply Chain (FSC) and develop effective mitigation strategies.
In order to measure the effectiveness of FLW prevention actions, Key Performance Indicators (KPIs) are pivotal tools widely used in the literature, particularly those quantifying FLW generated and avoided. But despite a growing recognition of the FLW problem, current literature reveals fragmented methodologies for quantifying FLW and assessing the sustainability impacts of FLW prevention actions, resulting in inconsistencies and limited comparability. This includes FLW quantification, where while the European Union's standardised FLW quantification guidelines (Commission Delegated Decision 2019/1597) provide a foundational framework, variations persist in definitions, causes, and destinations across studies. On the other hand, Life Cycle Assessment (LCA) offers a standardised approach for assessing FLW's environmental impact, although its application to FLW prevention remains underexplored. Moreover, integrating sustainability KPIs with Information and Communication Technologies (ICT) shows promise in enhancing the standardisation of these assessments by advancing data reliability and transparency. Especially as regards LCA, a resource-intensive methodology that enormously benefits from this synergy.
To address these gaps, this dissertation develops a standardised methodology for evaluating the environmental, social, and economic impacts of FLW prevention actions across FSCs. With a holistic life cycle approach, the methodology aims to enable efficient and rigorous comparisons between different FSCs, considering the upstream and downstream consequences of FLW prevention efforts. Specific objectives include defining a taxonomy for FLW, establishing KPIs for sustainability impacts, refining FLW quantification and LCA methodologies, and leveraging digitisation for enhanced data reliability and transparency. Validation of this methodology involves analysing five circular economy scenarios in a real case study, encompassing various types of FLW prevention actions.
The research focuses on an entire FSC of prepared salads in Spain, adopting a cradle-to-grave approach to have a comprehensive vision of the case study. The data collected for this case study encompasses different temporal periods between 2021 and 2023. Through extensive literature review, and consultation to experts and stakeholders from 3 different FSCs, a robust set of 69 KPIs was defined, culminating in the creation of the FOODRUS index. This index integrates economic, environmental, and social dimensions, providing a comprehensive framework for evaluating FSC's preparedness to implement FLW prevention actions. The methodology adheres to Delegated Decision 2019/1597 guidelines to quantify FLW and expands its scope, refining definitions and methodologies to include preharvest losses and diverse waste fractions. It enhances FLW quantification by incorporating food characteristics, root causes, destinations, and standardised classifications using NACE codes for FSC stages, UNSPSC codes for food products, and EWC codes for FLW flows. This approach strengthens methodological reliability and exhaustiveness, crucial for monitoring progress towards SDG 12.3. LCA methodology was employed to evaluate the environmental impacts on climate change and water use of FLW prevention actions using the PEF v3.0 as impact assessment method. Digitisation was integrated in the methodology at different steps including the definition, calculation, and visualisation of KPIs. Validation through circular economy scenarios demonstrates the methodology's robustness, assessing a range of FLW prevention actions categorised by the Joint Research Centre (JRC). These scenarios integrate social actions and technological solutions aimed at reducing FLW, each evaluated based on identified causes and potential impacts. A decision tree aids in identifying optimal FLW prevention measures, particularly in Scenario 4.
Results include a standardised set of 69 KPIs to measure the sustainability impact of FLW prevention actions validated through expert knowledge and stakeholder consultations. The index, evaluated across five organisations within the case study, effectively measures readiness, coherent with subsequent KPI measurements. Detailed calculations for each KPI demonstrate considerable performance of the case study at the baseline, highlighting robust FLW prevention efforts such as food donations and animal feeding, notably from Processing and manufacturing (P&M) and Retail and other distribution of food (RDF) stages. FLW prevention action scenarios showcase diverse impacts within the FSC. Supply chain efficiency in Scenario 1 delivers significant economic benefits and reduces FLW to landfills. Redistribution efforts in Scenario 2 achieve moderate economic impact and FLW reduction. Consumer behaviour-focused Scenario 3 generates substantial social benefits despite targeting only the Household (HH) stage. Scenario 4, which incorporates FLW prevention governance, yields significant economic gains and nutritional value saved. Integrating all actions in Scenario 5 shows mixed economic performance but excels in social and technical KPIs, such as nutritional value saved. These scenarios underscore trade-offs and benefits of different FLW prevention actions across the FSC. As concerns FLW prevention, Scenario 5 showcases the best performance, followed closely by Scenario 4. Environmental assessments via LCA highlight significant impacts from Primary Production (PP), primarily contributing to carbon and water footprints. Even if this FSC stage is not where most FLW is generated, this result is due to the additional food production needed to fulfil the functional unit when FLW generation acts. Among FLW prevention actions, Scenario 4 demonstrates the best performance, significantly reducing carbon and water footprints through effective governance. Digitisation enhanced KPI visualisation, promoting transparency and aiding decision-making. Digital tools and data models supported rigorous sustainability assessments by standardising data and enhancing transparency and reliability.
In conclusion, this dissertation establishes a robust framework for assessing and enhancing sustainability within FSCs through 69 KPIs. Spanning economic, environmental, and social dimensions, these KPIs provide a comprehensive toolkit for measuring FLW prevention action impacts. The methodology integrates expert insights, stakeholder inputs, and regulatory guidelines, culminating in the FOODRUS index, a demonstrated useful tool to assess the readiness of FSCs to implement FLW prevention actions validated across 5 FSC stakeholders. The methodology provides a representative measure crucial for achieving SDG 12.3, enriched by food characteristics, root causes, destinations, and standardised classifications. LCA identifies effective solutions and underscores trade-offs, with governance actions showing the highest potential for environmental impact mitigation. Additionally, it is concluded that optimisation of FLW prevention actions' efficiency requires tailored approaches for each specific context. As regards digitisation, it streamlines the deployment of the methodology mainly by enhancing the KPI measurement practicality. Finally, prioritising critical KPIs results to be crucial for optimising FLW prevention actions combinations.
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Materias
Ciencias Tecnológicas
Ingeniería y tecnología del medio ambiente
Eliminación de residuos
Ingeniería y tecnología del medio ambiente
Eliminación de residuos