Fast ADM1 implementation for the optimization of feeding strategy using near infrared spectroscopy

Optimization of feeding strategy is an essential issue of anaerobic co-digestion that can be greatly assisted with simulation tools such as the Anaerobic Digestion Model 1. Using this model, a set of parameters, such as the biochemical composition of the waste to be digested, its methane production yield and kinetics, has to be defined for each new substrate. In the recent years, near infrared analyses have been reported as a fast and accurate solution for the estimation of methane production yield and biochemical composition. However, the estimation of methane production kinetics requires time-consuming analysis. Here, a partial least square regression model was developed for a fast and efficient estimation of methane production kinetics using near infrared spectroscopy on 275 bio-waste samples. The development of this characterization reduces the time of analysis from 30 days to a matter of minutes. Then, biochemical composition and methane production yield and kinetics predicted by near infrared spectroscopy were implemented in a modified Anaerobic Digestion Model n°1 in order to simulate the performance of anaerobic digestion processes. This approach was validated using different data sets and was demonstrated to provide a powerful predictive tool for advanced control of anaerobic digestion plants and feeding strategy optimization.