The application of membrane bioreactors (MBR) for wastewater treatment is growing worldwide due to their compactness and high effluent quality. However, membrane fouling, mostly associated to biological products, can reduce MBR performance. Therefore, it is important to monitor MBRs as close to real-time as possible to accelerate control actions for maximal biological and membrane performance. 2D-fluorescence spectroscopy is a promising on-line tool to simultaneously monitor wastewater treatment efficiency and the formation of potential biological fouling agents. In this study, 2D-fluorescence data obtained from the wastewater and the permeate of a MBR was successfully modelled using projection to latent structures (PLS) to monitor variations in the influent and effluent total chemical oxygen demand (COD). Analysis of the results also indicated that humic acids and proteins highly contributed to the measured COD in both streams. Nevertheless, this approach was not valid for other performance parameters of the MBR system (such as influent and effluent ammonia and phosphorus), which is usually characterised through a high number of analytical and operating parameters. Principal component analysis (PCA) was thus used to find possible correlations between these parameters, in an attempt to reduce the analytical effort required for full MBR characterisation and to reduce the time frame necessary to obtain monitoring results. The 3 first principal components, capturing 57% of the variance, indicated and confirmed expected relationships between the assessed parameters. However, this approach alone could not provide robust enough correlations to enable the elimination of parameters for process description (PCA loadings ≤ 0.5). Nevertheless, it is possible that the information captured by 2D-fluorescence spectroscopy could replace some of the analytical and operating parameters, since this technique was able to successfully describe influent and effluent total COD. It is thus proposed that combined modelling of 2D-fluorescence data and selected performance/operating parameters should be further explored for efficient MBR monitoring aiming at rapid process control.

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