The increased generation of food waste is a global and national problem. The purpose of the study is to investigate the factors that influence food waste and the role of technology in tackling food waste in the Netherlands. One of the main findings of the research is food waste is that consumer food waste is mainly influenced by food passing expiry date, food that is left too long in the fridge and consumers buying too much food. In final household consumption, digital platforms and applications enable individuals to share and donate their food, thereby creating awareness on food waste prevention and the environmental benefits.
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In this masterclass, Toine Timmermans, director Stichting Samen tegen Voedselverspilling (Foundation Together against Food Waste), explains what is food waste , what the effects of food waste are on our environment, how much we waste and what we can do about it. He also gives many examples how we can reduce food waste.
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In this masterclass, HAS lector Rob Bakker and teacher-researcher Annelies Verspeek-van der Stelt explain wat is the definition of food waste, what is a food waste hotspot, en what entals food waste measurement en monitoring. Examples are given of food waste measurement at HAS green academy.
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In this proposal, a consortium of knowledge institutes (wo, hbo) and industry aims to carry out the chemical re/upcycling of polyamides and polyurethanes by means of an ammonolysis, a depolymerisation reaction using ammonia (NH3). The products obtained are then purified from impurities and by-products, and in the case of polyurethanes, the amines obtained are reused for resynthesis of the polymer. In the depolymerisation of polyamides, the purified amides are converted to the corresponding amines by (in situ) hydrogenation or a Hofmann rearrangement, thereby forming new sources of amine. Alternatively, the amides are hydrolysed toward the corresponding carboxylic acids and reused in the repolymerisation towards polyamides. The above cycles are particularly suitable for end-of-life plastic streams from sorting installations that are not suitable for mechanical/chemical recycling. Any loss of material is compensated for by synthesis of amines from (mixtures of) end-of-life plastics and biomass (organic waste streams) and from end-of-life polyesters (ammonolysis). The ammonia required for depolymerisation can be synthesised from green hydrogen (Haber-Bosch process).By closing carbon cycles (high carbon efficiency) and supplementing the amines needed for the chain from biomass and end-of-life plastics, a significant CO2 saving is achieved as well as reduction in material input and waste. The research will focus on a number of specific industrially relevant cases/chains and will result in economically, ecologically (including safety) and socially acceptable routes for recycling polyamides and polyurethanes. Commercialisation of the results obtained are foreseen by the companies involved (a.o. Teijin and Covestro). Furthermore, as our project will result in a wide variety of new and drop-in (di)amines from sustainable sources, it will increase the attractiveness to use these sustainable monomers for currently prepared and new polyamides and polyurethanes. Also other market applications (pharma, fine chemicals, coatings, electronics, etc.) are foreseen for the sustainable amines synthesized within our proposition.
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
Micro and macro algae are a rich source of lipids, proteins and carbohydrates, but also of secondary metabolites like phytosterols. Phytosterols have important health effects such as prevention of cardiovascular diseases. Global phytosterol market size was estimated at USD 709.7 million in 2019 and is expected to grow with a CAGR of 8.7% until 2027. Growing adoption of healthy lifestyle has bolstered demand for nutraceutical products. This is expected to be a major factor driving demand for phytosterols. Residues from algae are found in algae farming and processing, are found as beachings and are pruning residues from underwater Giant Kelp forests. Large amounts of brown seaweed beaches in the province of Zeeland and are discarded as waste. Pruning residues from Giant Kelp Forests harvests for the Namibian coast provide large amounts of biomass. ALGOL project considers all these biomass residues as raw material for added value creation. The ALGOL feasibility project will develop and evaluate green technologies for phytosterol extraction from algae biomass in a biocascading approach. Fucosterol is chosen because of its high added value, whereas lipids, protein and carbohydrates are lower in value and will hence be evaluated in follow-up projects. ALGOL will develop subcritical water, supercritical CO2 with modifiers and ethanol extraction technologies and compare these with conventional petroleum-based extractions and asses its technical, economic and environmental feasibility. Prototype nutraceutical/cosmeceutical products will be developed to demonstrate possible applications with fucosterol. A network of Dutch and African partners will supply micro and macro algae biomass, evaluate developed technologies and will prototype products with it, which are relevant to their own business interests. ALGOL project will create added value by taking a biocascading approach where first high-interest components are processed into high added value products as nutraceutical or cosmeceutical.
