Kinetic Models in Anaerobic Digestion Process: Solving Methods, Applications, and Potential Integration with Machine Learning

Anaerobic digestion is a crucial biological process in waste management and the generation of valuable bioproducts (e.g., biohydrogen, biomethane, and volatile fatty acids). Understanding the kinetics is fundamental for optimizing the system. This paper comprehensively analyzed and summarized the kinetic models commonly applied in anaerobic digestion processes. The mathematical formulations, advantages and disadvantages, and applications of these models in microbial growth, substrate utilization, and product formation were discussed in detail. Microbial growth kinetics can be described using the Logistic and Gompertz models. Substrate consumption can be represented by the Monod, Andrews, and Aiba models, and bioproduct formation can be characterized by the Gompertz, Logistic, first-order, and Cone models. Additionally, the potential integration of Machine Learning (ML) techniques with traditional kinetic modeling is explored as a promising approach to improve model accuracy and process control. Solving methods for the kinetic models were developed using EXCEL and MATLAB, and are provided in the Supporting Information. Overall, this paper will contribute to the knowledge and application of kinetic models in optimizing anaerobic digestion processes.