Predictive modeling and optimizing lactic acid recovery from co-fermentation of food waste and waste activated sludge...

The recovery of lactic acid (LA) from the co-fermentation of food waste and waste activated sludge is shifting from feasibility studies to process optimization and predictive modeling. This study extends the widely used International Water Association Anaerobic Digestion Model No.1 (ADM1) by incorporating lactic acid bacteria-mediated pathways and adjusted stoichiometry to simulate LA generation from sugars, implemented in the GPS-X simulation platform. The LA-modified ADM1 was calibrated under various temperatures (20, 35, and 50 ℃) and pH levels (7, 8, 9, 10, and 11), demonstrating a strong fit with experimental data (R² = 0.80-0.94). Key kinetic parameters, including the hydrolysis rate of carbohydrates (k_hyd,ch), the uptake rate of sugars to lactate (k_m,su,la), and the uptake rate of lactate (k_mla), were identified. Response surface analysis revealed significant parameter interactions, while global sensitivity analysis highlighted time-dependent variations in sugar, lactate, and acetate dynamics. The model was validated through long-term fermentation experiments under the optimal batch conditions (35 ℃ and pH 9) and successfully applied to predict LA production under various pH and temperature conditions. This study provides valuable insights for optimizing LA recovery from organic waste, advancing sustainable waste management, resource recovery, and the circular economy. Future extensions include incorporating LA isomers, chain elongation pathways, and nitrogen-related interactions to enhance predictive accuracy and practical applicability.