Real-time monitoring of membrane bioreactors with 2D-fluorescence data and statistically based models.

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.

The link between nitrous oxide emissions, microbial community profile and function from three full-scale WWTPs.

Few attempts have been made in previous studies to link the microbial community structure and function with nitrous oxide (N2O) emissions at full-scale wastewater treatment plants (WWTPs). In this work, high-throughput sequencing and reverse transcriptase-qPCR (RT-qPCR) was applied to activated sludge samples from three WWTPs for two seasonal periods (winter and summer) and linked with the N2O emissions and wastewater characteristics. The total N2O emissions ranged from 7.2 to 937.0 g N-N2O/day, which corresponds to an emission factor of 0.001 to 0.280% of the influent NH4-N being emitted as N2O. Those emissions were related to the abundance of Nitrotoga, Candidatus Microthrix and Rhodobacter genera, which were favored by higher dissolved oxygen (DO) and nitrate (NO3-) concentrations in the activated sludge tanks. Furthermore, a relationship between the nirK gene expression and N2O emissions was verified. Detected N2O emission peaks were associated with different process events, related to aeration transition periods, that occurred during the regular operation of the plants, which could be potentially associated to increased emissions of the WWTP. The design of mitigation strategies, such as optimizing the aeration regime, is therefore important to avoid process events that lead to those N2O emissions peaks. Furthermore, this study also demonstrates the importance of assessing the gene expression of nosZ clade II, since its high abundance in WWTPs could be an important key to reduce the N2O emissions.