Publications by authors named "Ana M S Paulo"

Quantitative image analysis (QIA) is a simple and automated method for process monitoring, complementary to chemical analysis, that when coupled to mathematical modelling allows associating changes in the biomass to several operational parameters. The majority of the research regarding the use of QIA has been carried out using synthetic wastewater and applied to activated sludge systems, while there is still a lack of knowledge regarding the application of QIA in the monitoring of aerobic granular sludge (AGS) systems. In this work, chemical oxygen demand (COD), ammonium (N-NH), nitrite (N-NO), nitrate (N-NO), salinity (Cl), and total suspended solids (TSS) levels present in the effluent of an AGS system treating fish canning wastewater were successfully associated to QIA data, from both suspended and granular biomass fractions by partial least squares models.

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The tolerance of aerobic granular sludge (AGS) to variable wastewater composition is perceived as one of its greatest advantages compared to other aerobic processes. However, research studies select optimal operational conditions for evaluating AGS performance, such as the use of pre-adapted biomass and the control of wastewater composition. In this study, non-adapted granular sludge was used to treat fish canning wastewater presenting highly variable organic, nutrient and salt levels over a period of ca.

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The surfactant sodium lauryl ether sulfate (SLES) is widely used in the composition of detergents and frequently ends up in wastewater treatment plants (WWTPs). While aerobic SLES degradation is well studied, little is known about the fate of this compound in anoxic environments, such as denitrification tanks of WWTPs, nor about the bacteria involved in the anoxic biodegradation. Here, we used SLES as sole carbon and energy source, at concentrations ranging from 50 to 1000 mg L, to enrich and isolate nitrate-reducing bacteria from activated sludge of a WWTP with the anaerobic-anoxic-oxic (A/O) concept.

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