Introducing new monitoring indices from the headspace of biogas digester via e-nose: A case study

This study focused on the monitoring of a biogas digester (BD) for treatment of food waste using an e-nose system. The e-nose system along with Principal Component Analysis (PCA) were applied to monitor the gaseous headspace of a mesophilic BD. In this method the digester was allowed to feed based on monitoring indices, i.e. “recovery time” and “position of sensors”, using e-nose data analysis. The results showed that the digester can be kept under the steady-state condition and good performance during evaluation phase, as organic acids to total alkalinity (FOS/TAC) was 0.2–0.3, pH was stabilized near to 8, the mean of volatile solids reduction and the daily methane production rate were 82% and 1.24 Nm³/m³ d, respectively. This study presents a robust monitoring of BD based on an adaptable reference point and graphical monitoring on plots of PCA that make it more flexible than the classical parameter monitoring with determined threshold.