DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR COMPANIES IN THE ENERGY FROM BIOMASS AREA, APPLYING CIRCULAR ECONOMY PRINCIPLES WITH A LIFE CYCLE THINKING APPROACH

The biomass supply chain (BSC) for energy production has emerged as a promising alternative to traditional fossil fuels, playing a crucial role in mitigating climate change and promoting sustainable development. Biomass utilisation offers numerous environmental, economic, and social benefits, including reduced greenhouse gas (GHG) emissions, enhanced energy security, and job creation in rural areas, which are known as important aspects of sustainable development. Moreover, the use of waste, by-products, and residue in BSC is essential to improving the circular economy (CE) in agriculture, wood, and paper processing industries, as well as waste treatment and management. Therefore, to further harness the potential of biomass energy production in sustainability and transition to the CE context, it is significant for companies in the BSC to apply circular business models (CBM).While the role of biomass in the CE has been confirmed, the gap still exists in evaluating the application of CE to the BSC. Up to the authors’ knowledge, currently, there is no set of circularity and sustainability indicators as standard for the company in the BSC. The variety of CE approaches and indicators makes it difficult to convert linear business models into circular ones. In addition, the variety of biomass materials, differences in biomass processing technology and multiple end-products lead to transformation into a CE model in many alternatives with many stages and different technology processes. Furthermore, some indicators assessing aspects of sustainability and circularity of different alternatives are subject to conflict and trade-offs. A more sustainable solution might not necessarily be better in terms of circularity and similar trade-offs exist within the pillars of sustainability. Given the trade-offs between sustainability and circularity, decision support systems (DSS) based on life cycle thinking with a standard set of indicators are promising tools for evaluating and selecting the best alternative of sustainability and circularity BSC.For what is above, this PhD research project was focused on developing a decision support system for a biomass company in the energy sector based on CE and sustainability models with a life cycle thinking approach. With the CE and sustainability model, a set of circularity and sustainability indicators is developed, and it is considered a criteria set to assess the circularity and sustainability of biomass companies and BSC. The life cycle thinking approach is employed to provide a comprehensive assessment for BSC. It is also basic to collect data from BSC and give value to indicators for assessing and ranking alternatives. The trade-off existing in alternatives is solved by using Multiple-criteria decision-making methods. That is integrated into the methodology framework of the decision support system.The PhD research project is structured around two main objectives. First, from CE and sustainability models, a set of circularity and sustainability is development. Secondly, a DSS tool is created. The set of developed indicators considers various stages during the BSC, such as feedstock plantation, processing, transportation, energy conversion, and end-of-life management, being aligned with the United Nations Sustainable Development Goals (SDGs) and the EC’s guidelines on the transition to CE. Meanwhile, the creation of a DSS includes proposing a methodology framework for DSS, creating software in MATLAB GUI and Script as a new tool for DSS, and applying this tool to the rice straw supply chain as testing for the case study.Regarding the case study, a rice straw supply chain for energy production in the Pavia region of Italy is selected. The data for the case study was collected during the internship period at the ENI company, such as parameters of the plant and process. The current of the rice straw supply chain is assessed by the DSS tool, and a re-edited version of this tool was taken. The alternatives of CE applications in the case study were performed through an external internship at the IMDEA Energy Institute (Spain). The data on alternatives is gathered based on the results of the simulation of the chemical process by Aspen plus@ at the IMDEA Energy Institute for suitable parameters of the current supply chain. The sustainability and circularity indicators methodology framework and case study developed during this PhD research project have been published in international journals and conference proceedings. The results of the application and details of the decision support system are present in this thesis. The results of calculating indicators for all indicators show that global warming potential (GWP) is 1.21E+03 ton CO2eq/yr to 55.7E+03 ton CO2eq/yr. Meanwhile, rice straw's acidification potential (AP) in this study ranges from 9.66 tonnes of SO2 eq/yr to 563 tonnes of SO2 eq/yr. The internal rate of return (IRR) of the rice straw supply chain is from 5.92% to 11.3%. In addition, the net present value (NPV) of the case study ranges from 0.72 to 5.79 million euros. Furthermore, the rate of informal labour is from 71.9% to 82.10%, while the percentage of recycling rate out of all waste is from 96.61% to 99.2%, the circular material use is from 54.8% to 88.2%, and the proportion of material losses in primary material is from 14.61% to 15.5%. The ranking results indicate that the digestate pyrolysis option has the best sustainability and circularity points among the other options.This PhD project research shows that the application of a comprehensive approach encompassing Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (SLCA) to identify sustainability indicators brings about significant advantages to the biomass supply chain. Existing research seldom integrates all three methodologies simultaneously. This integrated approach enhances the understanding of sustainability implications across the biomass supply chain, paving the way for a more holistic assessment.Moreover, the utilization of the Life Cycle Thinking (LCT) tool and Material Flow Analysis (MFA) for circularity indicators introduces a novel dimension to the existing literature. The incorporation of these tools instills confidence in simulating both circularity and sustainability, a consideration often overlooked in previous studies. The resulting circularity and sustainability indicators offer a standardised set that serves as a step-by-step guide for achieving Sustainable Development Goals (SDGs) and transitioning to a circular economy, aligning with the European Commission's roadmap.The development of a Decision Support System (DSS) methodology framework marks another crucial contribution, particularly by integrating circularity and sustainability within a unified framework for biomass companies in the supply chain. Unlike existing frameworks, this approach employs the PROMETHEE II and Entropy methods, leveraging life cycle results to enhance reliability and streamline calculations. Overcoming the limitations of PROMETHEE, this framework incorporates a multiple-criteria decision-making approach to address trade-offs in sustainability and circularity alternatives. This not only improves the robustness of the framework but also extends its applicability to general companies beyond the biomass sector.Furthermore, the accompanying software in this study presents a more practical and potent DSS tool for ranking alternatives. Its flexibility, allowing the use of the DSS tool for calculating sustainability and circularity indicators for individual alternatives, provides users with a versatile platform. The ability to choose indicator groups and methods for weighting indicators enhances the adaptability of the framework, making it applicable in various scenarios for policymakers and researchers committed to advancing circular economy and sustainability initiatives. In summary, based on methods for application, methodology framework and useful software, the DSS tool developed in this thesis can be used to support companies in the biomass supply chain, managers, practitioners, policy-makers, and researchers in assessing and selecting alternatives for application of CBMs to transfer into CE.