Process sustainability and feasibility optimization
Environmental issues are no longer an exclusive concern of NGOs, but citizens, governments and industries are showing interest in limiting the impact of the products that are massively consumed and willing to make efforts to achieve this. However, finding the best solutions is not always trivial. On the one hand, there is no clarity on which strategies are better and more desirable by society. On the other hand, it is also not evident which strategies would be feasible to implement in the current market conditions. In this context, it is necessary to have a methodology able to identify strategies that are feasible, implementable, and environmentally and economically optimal according to the preferences of the society towards a circular economy.
The iPRACS group develops a methodological framework to analyze the performance of the different strategies and to identify the optimal ones according to economic and environmental criteria. To this end, we use both Life Cycle Assessment (LCA) and Techno-Economic Assessment (TEA) in an integrated manner, and often collaborate with the Department of Engineering Management. Moreover, we extend the currently available methods by analyzing the interactions between horizontal and vertical competitors in order to propose contract agreements and policy instruments that would make these stakeholders choose the desirable options. We finally study the integration of sustainability assessment and optimization methods into early stage research, ideally allowing real-time decision making on desirable processing routes in ongoing projects.
Generic prediction and optimization of plastic recyclability using statistical entropy analysis
The complexity and diversity of plastics is at the heart of the plastic recycling challenge. And yet, all efforts to predict their recyclability thus far are based on material and energy balances of supposedly useful technologies within a certain waste management system. Hence, these methods are not very generic and the results mainly say something about the
system rather than about the innate characteristics of the materials. At iPRACS
we believe to have finally found a way to quantify the complexity and diversity
of plastics by using statistical entropy analysis. The method builds on the
(multi-level) statistical entropy analysis first used by Rechberger (TU Wien)
for waste management purposes. When coupled with more generic energy
indicators, this may yield a true, unbiased, universal recyclability predictor.
This predictor will be an innate material property rather than a characteristic
of a specific waste management system. With this method, we can now support in
a more quantitative way design-for-recycling, but also study optimal collection
schemes, and quantify the value of sorting/refining technologies in view of
their true purpose; reducing entropy. Future research at iPRACS consists of
further refinement of the method using realistic case studies as well as
complex processes such as reactive extrusion. Different relevant levels not
considered in the current framework, but necessary for addressing recyclability
as the geospatial and molecular level entropies will also be studied.