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.