Technical matchmaking and performance prediction

Matching Plant-based Food Waste (PBFW) and valorization technologies is currently aided through Waste Hierarchies; hierarchies containing different tiers of valorization technologies ranking favorable options. Literature shows matches made through Waste Hierarchies do not always lead to the most favorable matches in terms of Global Warming Potential. Besides that, Waste Hierarchies do not accommodate for technical aspects of matchmaking and thus suggest matches between PBFW and valorization technologies that are not feasible. In this thesis manuscript a model is presented capable of both technical matchmaking between PBFW and a selection of valorization technologies and predicting their valorization performance. The model uses the nutritional composition of PBFW streams as input values, calculates input:output ratios of feedstock and valorization products and expresses the valorization performance through potential GWP reduction. The offset rate is calculated based on the shared commodity between the valorization product and the offset product. The model is tested through case studies showing its possibilities and limitations. Further value to the model can be added by including the possibility to virtually mix different PBFW streams and use the final composition as input for the model. To accommodate for higher tier valorization technologies (e.g. the production of bio-based platform chemicals) more input variables, like cellulose, hemicellulose and lignin, are needed. The model could be combined with a database containing both the quantity and composition of PBFW streams and resource demands within a geographical area to develop both supply and demand included PBFW valorization strategies.

Yannick Schrik, MADE Student, AMS Institute

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