Design and optimization of anaerobic digestion systems by advanced microbial community dynamics modelling

The rising global demand for alternative energy and the challenge of organic waste pollution have intensified interest in anaerobic digestion (AD) as a viable and effective waste-to-energy technology. The efficiency of AD depends largely on microbial community dynamics and operational optimization. This study was designed to assess, model, and optimize an AD system for co-digestion of chicken waste and food waste using Response Surface Methodology (RSM). Fifteen experimental runs were conducted in custom-fabricated digesters (height 46 cm, diameter 28 cm, 15 L capacity) under mesophilic conditions (35 ± 2 °C) to evaluate the effects of substrate concentration (8–12 kg), pH (5–9), and retention time (7–21 days) on biogas yield (BGY), chemical oxygen demand (COD), volatile fatty acids (VFA), and microbial community dynamics (MCD). Analysis of variance (ANOVA) showed significant model adequacy with P-values of 0.0003 for BGY and < 0.0001 for COD, VFA, and MCD, confirming excellent fit for the quadratic regression models of BGY, COD, and VFA, and a linear model for MCD. Coefficients of determination (R²) were 0.9876, 0.9943, 0.9969, and 0.9726 for BGY, COD, VFA, and MCD, respectively, indicating strong agreement between predicted and experimental values. Optimal conditions substrate concentration of 12 kg, pH 7.63, and retention time of 21 days, yielded maximum BGY (378.6 kPa), COD (14.009 g/L), VFA (39.435 g/L), and MCD (18,505.1 cells/mL). These results indicate that integrating microbial community modeling with RSM significantly enhances the predictive accuracy and operational efficiency of anaerobic digestion systems for renewable energy generation.