A Sequencing Batch Reactor (SBR) with activated sludge was operated with synthetic wastewater containing ibuprofen (IBU) to investigate the biomass stress-responses under long-term IBU exposure. There were 3 different phases: phase I as the control without IBU for 56 days, phase II (40 days), and phase III (60 days) containing IBU at 10 and 5 mg L − 1 each. The overall performance of the SBR as well as the extracellular polymeric substances (EPS) in terms of polysaccharides, proteins, and humic acid substances were estimated. Morphological parameters of microbial aggregates in the presence of IBU (phase II and phase III) were assessed by quantitative image analysis (QIA). Removal efficiencies of chemical oxygen demand (COD) and ammonium (NH 4 + ) were significantly reduced by IBU. Loosely bound EPS (LB-EPS) decreased during phase II and phase III, and tightly bound EPS (TB-EPS) was slightly higher in phase II than phase I. TB-EPS proteins were greater in phase II, perhaps to protect microbial cells from IBU exposure. These findings provided insight into both activated sludge stress-responses and EPS composition under long-term IBU exposure. Spearman correlation showed that EPS and morphological parameters significantly affected sludge settleability and flocculation. QIA also proved to be a powerful technique in investigating dysfunctions in activated sludge under IBU exposure.

No abstract

The monitoring of emerging pollutants in wastewaters is nowadays an issue of special concern, with the classical quantification methods being time and reagent consuming. In this sense, a FTIR transmission spectroscopy based chemometric methodology was developed for the determination of eight of these pollutants. A total of 456 samples were, therefore, obtained, from an activated sludge wastewater treatment process spiked with the studied pollutants, and analysed in the range of 200 cm −1 to 14,000 cm −1. Then, a k-nearest neighbour (kNN) analysis aiming at identifying each sample pollutant was employed. Next, partial least squares (PLS) and ordinary least squares (OLS) modelling approaches were employed in order to obtain suitable prediction models. This procedure resulted in good prediction abilities regarding the estimation of atrazine, desloratadine, paracetamol, β-estradiol, ibuprofen, carbamazepine, sulfamethoxazole and ethynylestradiol concentrations in wastewaters. These promising results suggest this technology as a fast, eco-friendly and reagent free alternative methodology for the quantification of emerging pollutants in wastewaters.

No abstract

In biological wastewater treatment (WWT), microorganisms live and grow held together by a slime matrix comprised of extracellular polymeric substances (EPS), forming a three-dimensional microbial structure of aggregates (flocs or granules) and by chemical binding forces. Furthermore, microscopic observations showed that microbial cells within the flocs were cross linked with EPS, forming a network of polymers with pores and channels. The EPS are typically composed of organic substances such as polysaccharides (PS), proteins (PNs), humic acid substances (HAS), nucleic acids, and lipids. It has been established that EPS play an essential role in aggregate flocculation, settling, and dewatering. Moreover, in the presence of toxic substances, such as pharmaceutical compounds and pesticides, EPS form a protective layer for the aggregated biomass against environmental disturbances that might play an important role in the transport and transformation of micropollutants. Some researchers indicated that there is an increase in EPS concentration under toxic conditions, which can induce an increase in the size of microbial aggregates. In this contribution, we critically review the available information on the impact of micropollutants on microbial EPS production and the relationship between EPS and microbial aggregate structure. Also, a general definition, composition, and factors that affect EPS production are presented.