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Surface water quality is declining due to climate change, leading to increased concentrations of soluble metals, natural organic matter (NOM), turbidity, and algal blooms. These changes pose challenges to traditional water treatment plants, needing innovative approaches. Ferrate(VI) was explored as a potential solution to address climate change-related water emergencies, either alone or in combination with conventional reagents to producing potable water.

The paper reports the main results of an experimental campaign carried out on two bench scale pilot plants for the treatment of synthetic shipboard slops. In particular, two membrane bioreactors (MBRs) with submerged configuration were analyzed. One MBR pilot plant (namely, Line A) was fed with synthetic shipboard slop and was subjected to a gradual increase of salinity. Conversely, the second MBR pilot plant (namely, Line B) was fed with the same synthetic shipboard slop but without salt addition, therefore operating as a “control” unit. Organic carbon, hydrocarbons and ammonium removal, kinetic constants, extracellular polymeric substances (EPSs) production and membranes fouling rates have been assessed. The observed results highlighted a stress effect exerted by salinity on the biological performances, with lower removal efficiencies in the Line A compared to Line B. Significant releases of soluble EPS in Line A promoted an increase of the resistance related to particle deposition into membrane pores (pore fouling tendency), likely due to a worsening of the mixed liquor features. Such a condition enhanced the reduction of the “pre-filter” effect of the cake layer.

The paper focused on the evolution and the comparison of the extracellular polymeric substances (EPSs) content during the granulation process in two Granular Sequencing Batch Airlift Reactors (GSBAR) (3,5 L) fed with synthetic (R1) and industrial wastewater (R2). The results showed that in both the reactors the EPSs, in particular proteins (PN), were mainly produced during the feast phase because of the high substrate availability, especially under conditions of metabolic stress. Then, the EPSs content reduced during the famine period, because of biodegradation by bacteria. More in detail, during the granulation process, a greater polysaccharides (PS) consumption occurred in both reactors, whereas the PN content reduced significantly only in R2. As a result, the PN/PS ratio increased significantly during the granules formation, confirming the key role of proteins on the granulation process. In R2, the granules produced a greater amount of PN on average, and this resulted in a more rapid granulation. Nevertheless, due to the several consumption of PN during the famine period, the granules in R2 resulted weaker and less dense compared with the granules in R1. For this reason, the granules in R2 were more susceptible to breakage. Overall, although the industrial wastewater favored a more rapid granulation, the excessive consumption of the EPSs, led to the structural weakening of the granules.

AbstractSensitivity and uncertainty analysis, although can be of primarily importance in mathematical modelling approaches, are scarcely applied in the field of membrane bioreactor (MBR). An integrated mathematical model for MBR is applied with the final aim to pin down sources of uncertainty in MBR modelling. The uncertainty analysis has been performed combining global sensitivity analysis (GSA) with the generalized likelihood uncertainty estimation (GLUE). The model and methodology were applied to a University Cape Town pilot plant. Results show that the complexity of the modelled processes and the propagation effect from the influent to the effluent increase the uncertainty of the model prediction. It was found that the uncertainty of nitrogen and phosphorus model outputs increases from the first reactor-section plant to the last. Results show also that the GSA-GLUE methodology is a valid tool for uncertainty assessment for MBR modelling. Furthermore, the GSA-GLUE allows to identify the most critical processes/plant sections and the key sources of uncertainty where attention should be paid in view of model predictions improvement.

Sensitivity and uncertainty analysis, although can be of primarily importance in mathematical modelling approaches, are scarcely applied in the field of membrane bioreactor (MBR). An integrated mathematical model for MBR is applied with the final aim to pin down sources of uncertainty in MBR modelling. The uncertainty analysis has been performed combining global sensitivity analysis (GSA) with the generalized likelihood uncertainty estimation (GLUE). The model and methodology were applied to a University Cape Town pilot plant. Results show that the complexity of the modelled processes and the propagation effect from the influent to the effluent increase the uncertainty of the model prediction. It was found that the uncertainty of nitrogen and phosphorus model outputs increases from the first reactor-section plant to the last. Results show also that the GSA-GLUE methodology is a valid tool for uncertainty assessment for MBR modelling. Furthermore, the GSA-GLUE allows to identify the most critical processes/plant sections and the key sources of uncertainty where attention should be paid in view of model predictions improvement.