RT Journal Article
T1 Uncovering optimal biorefinery designs for agricultural waste: Insights from superstructure optimization under uncertainty
A1 Hauwaert, Lucas van der
A1 Regueira López, Alberte
A1 Zondervan, Edwin
A1 Mauricio Iglesias, Miguel
K1 Superstructure optimization
K1 Stochastic optimization
K1 Early-stage biorefinery design
K1 OUTDOOR
K1 Agricultural waste management
AB This study explores the application of superstructure optimization to guide early-stage biorefinery design decisions under uncertainty. A case study on processing agricultural waste (potato peel waste) demonstrates the method's capacity to identify economically viable and robust pathways from two perspectives: waste owners and stakeholders invested in emerging technologies. For waste owners, stochastic optimization revealed that converting potato peel waste into animal feed is the most robust and economically attractive pathway, achieving an expected profit of 61.2 €/t of waste with minimal risk exposure. For technology developers, global sensitivity analysis of a polyhydroxyalkanoate (PHA) production route highlighted critical parameters for improvement, including PHA extraction yield and separation efficiency, to enhance economic performance and outcompete alternative production routes. The work includes enhancements to the OUTDOOR software, integrating uncertainty optimization and sensitivity analysis, to provide a comprehensive framework for evaluating design alternatives. This structured approach facilitates the identification of robust biorefinery configurations in the early design stage. It also allows stakeholders in emerging technologies to benchmark their processes against alternative designs, thereby identifying critical parameters for optimization
PB Elsevier
YR 2025
FD 2025
LK https://hdl.handle.net/10347/43784
UL https://hdl.handle.net/10347/43784
LA eng
NO Van der Hauwaert, L., Regueira, A., Zondervan, E., & Mauricio-Iglesias, M. (2025). Uncovering optimal biorefinery designs for agricultural waste: Insights from superstructure optimization under uncertainty. Journal of Environmental Management, 394, 127551. https://10.1016/j.jenvman.2025.127551
NO This project (AGRILOOP) has received funding from the European Union's Horizon Europe research and innovation programme and the UK Research and Innovation fund under the UK government's Horizon Europe funding guarantee, grant agreement No. 101081776. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. https://agriloop-project.eu/. Lucas Van der Hauwaert acknowledges CRETUS for supporting his research stay at the Institute Sustainable Process Technology (SPT) at the University of Twente. The Authors would also like to acknowledge the help of Benyamin Khoshnevisan and Mias Sommer Schjønberg from SDU+, Lionel Nguemna, Angela Marchetti and Mariana Villano from UNIROMA, Jan Broeze and Marta Rodrigues Illera from Wageningen Research, Angel Estevez Alonso from UGent, Annalisa Tassoni from UNIBO, Jan Linck from Ecozept, Alice Charpigny from DSS+, Diana Molina Delgado from FCAC, Aleksandra Zderic from Avebe and Michael Pil from AVECOM for their inputs and suggestions for the superstructure
DS Minerva
RD 4 may 2026