Turning sewage sludge and medical waste into energy: sustainable process synthesis via surrogate-based superstructure optimization

Abstract

Waste-to-energy (WtE) conversion offers a promising solution for sustainable waste management, but identifying economically viable and environmentally sustainable pathways remains a significant challenge. To address this issue, this study presents an optimal process design for simultaneously converting medical waste and sewage sludge into energy based on a novel superstructure optimization framework. The superstructure integrates waste plasma gasification, CO₂ capture, and fuel production, with economic profit and carbon emissions of each unit quantified through high-fidelity process simulations. To reduce the computational complexity, high dimensional model representation (HDMR)-based surrogate models are developed utilizing simulation data. With a compact surrogate model, efficient mixed-integer nonlinear programming is employed to identify the optimal pathway toward maximizing profit. The results reveal that producing hydrogen is the most economically favorable option, yielding a profit of 228.68 $ per h and carbon emissions of 3.82 t CO₂ equivalent (CO₂-eq) per h in the case study. Sensitivity analysis shows that increasing the ratio of medical waste enhances economic benefits but also raises carbon emissions. Additionally, the critical role of carbon tax in selecting low-carbon pathways while balancing economic viability is demonstrated. Compared to traditional waste treatment and energy production methods, the identified optimal processes demonstrate superior performance in carbon reduction, with emissions of 1.35 kg CO₂-eq per kg mixed waste under carbon tax conditions. This research highlights the effectiveness of HDMR surrogating in superstructure optimization and offers valuable insights for sustainable WtE conversion.