Plastics-based materials have a high carbon footprint, and their disposal is a considerable problem for the environment. Biodegradable bioplastics represent an alternative on which most countries have focused their attention to replace of conventional plastics in various sectors, among which food packaging is the most significant one. The evaluation of the optimal end-of-life process for bioplastic waste is of great importance for their sustainable use. In this review, the advantages and limits of different waste management routes—biodegradation, mechanical recycling and thermal degradation processes—are presented for the most common categories of biopolymers on the market, including starch-based bioplastics, PLA and PBAT. The analysis outlines that starch-based bioplastics, unless blended with other biopolymers, exhibit good biodegradation rates and are suitable for disposal by composting, while PLA and PBAT are incompatible with this process and require alternative strategies. The thermal degradation process is very promising for chemical recycling, enabling building blocks and the recovery of valuable chemicals from bioplastic waste, according to the principles of a sustainable and circular economy. Nevertheless, only a few articles have focused on this recycling process, highlighting the need for research to fully exploit the potentiality of this waste management route.

Combined heat and power (CHP) generation plants are an assessed valuable solution to significantly reduce primary energy consumption and carbon dioxide emissions. Nevertheless, the primary energy saving (PES) and CO2 reduction potentials of this solution are strictly related to the accurate definition and management of thermal and electric loads. Data-driven analysis could represent a significant contribution for optimizing the CHP plant design and operation and then to fully deploy this potential. In this paper, the use of a bi-level optimization approach for the design of a CHP is applied to a real application (a large Italian hospital in Rome). Based on historical data of the hospital thermal and electric demand, clustering analysis is applied to identify a limited number of load patterns representative of the annual load. These selected patterns are then used as input data in the design procedure. A Mixed Integer Linear Programming coupled with a Genetic Algorithm is implemented to optimize the energy dispatch and size of the CHP plant, respectively, with the aim of maximizing the PES while minimizing total costs and carbon emissions. Finally, the effects of integrating biogas from the Anaerobic Digestion (AD) of the Spent Coffee Ground (SCG) and Energy Storage (ES) technologies are investigated. The results achieved provide a benchmark for the application of these technologies in this specific field, highlighting performances and benefits with respect to traditional approaches. The effective design of the CHP unit allows for achieving CO2 reduction in the order of 10%, ensuring economic savings (up to 40%), when compared with a baseline configuration where no CHP is installed. Further environmental benefits can be achieved by means of the integration of AD and ES pushing the CO2 savings up to 20%, still keeping the economical convenience of the capital investment.

The last Intergovernmental Panel on Climate Change (IPPC) assessment report highlighted how actions to reduce CO2 emissions have not been effective so far to achieve the 1.5 C limit and that radical measures are required. Solutions such as the upgrading of waste biomass, the power-to-X paradigm, and an innovative energy carrier such as hydrogen can make an effective contribution to the transition toward a low-carbon energy system. In this context, the aim of this study is to improve the hydrogen production process from wet residual biomass by examining the advantages of an innovative integration of anaerobic digestion with thermochemical transformation processes. Furthermore, this solution is integrated into a hybrid power supply composed of an electric grid and a photovoltaic plant (PV), supported by a thermal energy storage (TES) system. Both the performance of the plant and its input energy demand—splitting the power request between the photovoltaic system and the national grid—are carefully assessed by a Simulink/Simscape model. The preliminary evaluation shows that the plant has good performance in terms of hydrogen yields, reaching 5.37% kgH2/kgbiomass, which is significantly higher than the typical value of a single process (approximately 3%). This finding demonstrates a good synergy between the biological and thermochemical biomass valorization routes. Moreover, thermal energy storage significantly improves the conversion plant’s independence, almost halving the energy demand from the grid.