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To find a possible trade-off between effluent quality, sludge production, energy consumption and GHG emissions, this study monitored the carbon and nutrient removal and greenhouse gas (GHG) emissions in a membrane bioreactor (MBR) pilot plant with intermittent aeration (IA). The pilot plant was operated by alternating aerobic and anoxic conditions inside the biological reactor. Up to 98.2 % of carbon and 76.4 % of nitrogen were respectively remove through this MBR pilot plant with IA. The carbon footprint was equal to 2.4 kgCO2eqm−3. Indirect emissions contributed the most to the carbon footprint (55.3 %), mainly due to energy consumption, despite the alterations in aeration during the pilot plant operation. The result of this study provides theoretical guidance for building the wastewater treatment plant in a sustainable way.

Chemical absorption–biological reduction based on Fe(II)EDTA is a promising technology to remove nitric oxide (NO) from flue gases. However, limited effort has been made to enable direct energy recovery from NO through production of nitrous oxide (N2O) as a potential renewable energy rather than greenhouse gas. In this work, the enhanced energy recovery in the form of N2O via biological NO reduction was investigated by conducting short-term and long-term experiments at different Fe(II)EDTA–NO and organic carbon levels. The results showed both NO reductase and N2O reductase were inhibited at Fe(II)EDTA–NO concentration up to 20 mM, with the latter being inhibited more significantly, thus facilitating N2O accumulation. Furthermore, N2O accumulation was enhanced under carbon-limiting conditions because of electron competition during short-term experiments. Up to 47.5% of NO–N could be converted to gaseous N2O–N, representing efficient N2O recovery. Fe(II)EDTA–NO reduced microbial diversity and altered the community structure toward Fe(II)EDTA–NO-reducing bacteria-dominated culture during long-term experiments. The most abundant bacterial genus Pseudomonas, which was able to resist the toxicity of Fe(II)EDTA–NO, was significantly enriched, with its relative abundance increased from 1.0 to 70.3%, suggesting Pseudomonascould be the typical microbe for the energy recovery technology in NO-based denitrification.

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.

AbstractSludge dewatering represents, nowadays, one of the greatest operational cost to wastewater treatment cycle. Physical–chemical and biological parameters are recognized to influence the sludge dewaterability. However, many authors agree in identifying the sludge origin as one of the main aspect involved in sludge dewaterability. Indeed, the sludge origin such as the processes involved in liquid–solid separation, seriously affect the sludge features. In order to elucidate the key factors influencing the dewaterability process, the present work is aimed to investigate the influence of the treatment plant lay-out on sludge dewaterability. The analyzed sludge samples were derived from four conventional activated sludge and two membrane bioreactor wastewater treatment plants. Experimental investigation was focused to highlight difference in sludge dewaterability derived from the application of European Standards adopted for sludge characterization. The achieved results confirmed the complexity of the inter-relationships between many factors affecting the sludge dewaterability.

Sludge dewatering represents, nowadays, one of the greatest operational cost to wastewater treatment cycle. Physical–chemical and biological parameters are recognized to influence the sludge dewaterability. However, many authors agree in identifying the sludge origin as one of the main aspect involved in sludge dewaterability. Indeed, the sludge origin such as the processes involved in liquid–solid separation, seriously affect the sludge features. In order to elucidate the key factors influencing the dewaterability process, the present work is aimed to investigate the influence of the treatment plant lay-out on sludge dewaterability. The analyzed sludge samples were derived from four conventional activated sludge and two membrane bioreactor wastewater treatment plants. Experimental investigation was focused to highlight difference in sludge dewaterability derived from the application of European Standards adopted for sludge characterization. The achieved results confirmed the complexity of the inter-relationships between many factors affecting the sludge dewaterability.

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.