Multi-criteria optimisation of subcritical wet oxidation for sludge treatment

Subcritical wet oxidation (SWO) is an environmentally-friendly solution for sewage sludge volume reduction. However, little study has comprehensively optimised SWO conditions across various aspects. This study developed a multi-objective model using genetic algorithms (GAs) to optimise SWO conditions, considering sludge deconstruction, emissions, energy balance, and resource recovery. The multi-criteria optimisation approach highlights the significant environmental benefits of SWO, including substantial sludge volume reduction and effective pollutant removal. An in-depth analysis of temperature, reaction time, and severity factor revealed their critical roles in enhancing sludge deconstruction and resource recovery efficiency. GAs predicted optimal conditions at 271 ± 2 °C and 51 ± 1 min, with confirmation experiments showing only 12% discrepancy between predicted and actual outcomes. This study provides practical insights for efficient sewage sludge treatment and sustainable wastewater management.