Periodic Reporting for period 2 - ToNoWaste (TOWARDS A NEW ZERO FOOD WASTE MINDSET BASED ON HOLISTIC ASSESSMENT)
Período documentado: 2024-03-01 hasta 2025-08-31
Food waste is a big problem and hard to measure it impacts, there isn’t enough open data neither single method to study it. This makes it difficult for companies to know if their efforts to reduce food waste are truly good for the economy, society, and the environment. Globally, food waste is responsible for 8–10% of greenhouse gas emissions, costs about 1 trillion US dollars per year, and wastes about 30% of farmland. The problem may be even bigger, because up to 70% of food waste is not recorded—for example, food lost during farming or used as animal feed. ToNoWaste is a 54 monthsproject, bringing together 22 institutions from 7 countries. The goal is to propose a sciece based framework to measure sustainability impacts and fight food waste using many perspectives: farming, economics, environment, business, psychology, law, and social innovation. It also looks at issues like gender and social inequality. The project will support businesses and policymakers to make better decisions about food production and consumption. This system will use expert knowledge and past research to understand the root causes of food waste—social, technical, economic, political, ethical, and demographic—and propose comprenhesive sustainability assessment solutions.
ToNoWaste advanced from conceptual design to operational implementation, delivering an integrated, evidence and science-based infrastructure for sustainability assessment of FLWPR actions across fresh food value chains. The period translated prior theoretical frameworks and curated best practices into functioning components: a re‑baselined digital platform, an operational science‑based framework, an implemented KPI system and the first wave of pilots that generate data that supports model validation. These advances have the potential to substantially enhance the project's capacity to generate reproducible, policy-relevant evidence and to inform decision-making at various levels.
The Science Based Framework (SBF) and Key Performance Indicator (KPI) architecture evolved from a conceptual catalogue to an executable measurement system. The framework has been developed to facilitate both ex-ante and ex-post comparison of interventions and is integrated with lifecycle accounting approaches to enable environmental and social foot printing that is consistent with Food 2030 priorities.
QMD advanced through the specification and pilot of risk‑based Hotspots Analysis, a structured review and operationalization of multicriteria and machine‑learning methods, and the deployment of a System Dynamics prototype to visualize temporal effects of interventions. Analytical workflows combine exploratory data analysis, feature selection mapped to KPIs, predictive models for hotspot detection, and scenario/sensitivity analysis to prioritise interventions by expected system‑level benefit and cost‑effectiveness.The platform and data ecosystem evolved from architectural design to interoperable operation.
The progression of behavioural and pilot activities from awareness instruments to demonstrable operational outcomes is indicative of a shift in focus from initial stages to more advanced, tangible outcomes. A multilingual citizen application has been developed to implement configurable surveys and pilot data capture using a capability–opportunity–motivation design. These datasets have informed KPI validation and increased readiness for scale-up.
Project governance, ethics, and exploitation frameworks were reinforced to ensure continuity and replication potential. The following priorities have been identified as being of the utmost importance: the immediate validation of the platform by the end users, the extensive deployment of the interoperability model, the complete integration of data into the quantitative decision-making workflows, and the augmentation of citizen app validation to support scalable, evidence-based policy and operational interventions.
The Science Based Framework (SBF) and Key Performance Indicator (KPI) architecture evolved from a conceptual catalogue to an executable measurement system. The framework has been developed to facilitate both ex-ante and ex-post comparison of interventions and is integrated with lifecycle accounting approaches to enable environmental and social foot printing that is consistent with Food 2030 priorities.
QMD advanced through the specification and pilot of risk‑based Hotspots Analysis, a structured review and operationalization of multicriteria and machine‑learning methods, and the deployment of a System Dynamics prototype to visualize temporal effects of interventions. Analytical workflows combine exploratory data analysis, feature selection mapped to KPIs, predictive models for hotspot detection, and scenario/sensitivity analysis to prioritise interventions by expected system‑level benefit and cost‑effectiveness.The platform and data ecosystem evolved from architectural design to interoperable operation.
The progression of behavioural and pilot activities from awareness instruments to demonstrable operational outcomes is indicative of a shift in focus from initial stages to more advanced, tangible outcomes. A multilingual citizen application has been developed to implement configurable surveys and pilot data capture using a capability–opportunity–motivation design. These datasets have informed KPI validation and increased readiness for scale-up.
Project governance, ethics, and exploitation frameworks were reinforced to ensure continuity and replication potential. The following priorities have been identified as being of the utmost importance: the immediate validation of the platform by the end users, the extensive deployment of the interoperability model, the complete integration of data into the quantitative decision-making workflows, and the augmentation of citizen app validation to support scalable, evidence-based policy and operational interventions.
The ToNoWaste project has achieved 10 Key Exploitable Results in its first 36 months, ranging from science‑based frameworks and taxonomies to ICT tools and consumer engagement apps. These outputs include assessment methods, KPI dashboards, interoperability models, and living labs that connect researchers, policymakers, and citizens.
KER1: Delphi process for Food Loss and Waste (FLW) causes and solutions, fostering dialogue among Research and Technology Organisations
KER2: Science-based Food Loss and Waste Prevention and Reduction (FLWPR) assessment framework, sharing findings via scientific publications:
Article : Domingo-Morcillo, E., Escrig-Olmedo, E., Rivera-Lirio, J. M., & Muñoz-Torres, M. J. (2024). Analyzing the suitability of LCIA methods to foster the most beneficial food loss and waste prevention action in terms of environmental sustainability. Environmental Impact Assessment Review, 107, 107575.
KER3: FLWPR actions database architecture, requiring scientific publications and regulatory support.
KER4: FLWPR solutions co-creation living labs, engaging EU and member state policymakers
KER5: Method for selecting KPIs for FLWPR measurement, depending on scientific publications and regulatory support
KER8: Interoperability data model for FLWPR actions, impacting future platform regulations
KER 10: Key Performance Indicator (KPIs) & Quantitative Decision-Making Methods (QDMM) Dashboard for FWPR decision support
KER11: Ex-ante FLWPR survey method for FWPR interventions that supports the analysis on consumers’ perspectives
KER13:ToNoWaste SocialApp – FWPR Engagement Application for consumer engagement
KER15: Taxonomy of FLWPR actions, aiming for scientific publication inclusion: open dataset from the article Domingo-Morcillo, E., Escrig-Olmedo, E., Rivera-Lirio, J. M., & Muñoz-Torres, M. J. (2024). Analyzing the suitability of LCIA methods to foster the most beneficial food loss and waste prevention action in terms of environmental sustainability. Environmental Impact Assessment Review, 107, 107575 https://doi.org/10.1016/j.eiar.2024.107575(se abrirá en una nueva ventana)
KER1: Delphi process for Food Loss and Waste (FLW) causes and solutions, fostering dialogue among Research and Technology Organisations
KER2: Science-based Food Loss and Waste Prevention and Reduction (FLWPR) assessment framework, sharing findings via scientific publications:
Article : Domingo-Morcillo, E., Escrig-Olmedo, E., Rivera-Lirio, J. M., & Muñoz-Torres, M. J. (2024). Analyzing the suitability of LCIA methods to foster the most beneficial food loss and waste prevention action in terms of environmental sustainability. Environmental Impact Assessment Review, 107, 107575.
KER3: FLWPR actions database architecture, requiring scientific publications and regulatory support.
KER4: FLWPR solutions co-creation living labs, engaging EU and member state policymakers
KER5: Method for selecting KPIs for FLWPR measurement, depending on scientific publications and regulatory support
KER8: Interoperability data model for FLWPR actions, impacting future platform regulations
KER 10: Key Performance Indicator (KPIs) & Quantitative Decision-Making Methods (QDMM) Dashboard for FWPR decision support
KER11: Ex-ante FLWPR survey method for FWPR interventions that supports the analysis on consumers’ perspectives
KER13:ToNoWaste SocialApp – FWPR Engagement Application for consumer engagement
KER15: Taxonomy of FLWPR actions, aiming for scientific publication inclusion: open dataset from the article Domingo-Morcillo, E., Escrig-Olmedo, E., Rivera-Lirio, J. M., & Muñoz-Torres, M. J. (2024). Analyzing the suitability of LCIA methods to foster the most beneficial food loss and waste prevention action in terms of environmental sustainability. Environmental Impact Assessment Review, 107, 107575 https://doi.org/10.1016/j.eiar.2024.107575(se abrirá en una nueva ventana)