Removal of organic micropollutants in the biological units of a Swedish wastewater treatment plant

The present study investigates the presence and removal of target organic micropollutants in a large Swedish wastewater treatment plant designed for nutrient removal including activated sludge, trickling filters, nitrifying moving bed biofilm reactors (MBBRs) and post-denitrifying MBBRs. A total of 28 organic micropollutants were analysed, at concentrations ranging from few ng/L to µg/L, in the influent and effluent of the different biological reactors in two sampling campaigns. The observed micropollutant removal efficiencies of the wastewater treatment plant varied from insignificant (< 20%) to high (> 90%) between compounds. The activated sludge reactor, being the first in line, contributed to most of the removal from the water phase. Additional removal of a few compounds was observed in the biofilm units, but most of the persistent compounds remained stable through all biological treatments.

Artificial Neural Network as a Virtual Sensor of Nitrate Nitrogen (V) Concentration in an Activated Sludge Reactor

The paper discusses the use of an artificial neural network to control the operation of wastewater treatment plants with activated sludge. The task of the neural network in this case is to calculate (predict) the readings of the probe measuring the concentration of nitrate nitrogen (V) in one of the biological reactor tanks. Neural networks are known for their ability to universal approximation of virtually any relationship, including the function of many variables, but the process of “training” the network requires the presentation of many sets of input data and corresponding expected results. This is a difficulty in the case of wastewater treatment plants, because some key process parameters are usually not measured online (samples are taken and measurements are taken in the laboratory), and even if they are, the time intervals are large. Bearing in mind the aforementioned difficulty, this work uses a set of input data consisting only of information that can be measured with measuring probes. As a result of the conducted experiments a high compliance of the probe’s prediction with the expected values was obtained. The paper also presents data preparation and the network “training” process.

Usage of textile dyes BB41 and BR46 for microscopic examination of filamentous bacteria in activated sludge reactor: a new staining method

The existence of certain filamentous organisms may indicate one or more operation and control problems in activated sludge reactors. Microscopic evaluation of these filamentous organisms needs staining methods that can be achieved after some steps. This study is the first to show that textile dyes such as Astrazon Blue FGGL (BB41) and Astrazon Red FBL (BR46) can be used to identify filamentous organisms. Both dyes were used as a new, effective, and easy method for detecting the presence of filamentous bacteria. When contacted with BB41 and BR46, the filamentous bacteria and their characteristics were easily observed under the microscope. According to sources, textile dyes used in this study have not been used to diagnose filamentous bacteria before. According to the findings of this study, important morphological properties of filamentous bacteria were easily observed using BB41 and BR46. “Attached growth, branching, septa, and granules of various nutrients” were clearly seen by the stains (BB41 and BR46) with the help of this method. This method may allow the examiners to examine the specimens of filamentous bacteria in the activated sludge reactors. Detailed information has been presented in this paper.

A comparative study of an anaerobic-oxic (AO) system and a sequencing batch biofilm reactor (SBBR) in coating wastewater treatment and their microbial communities

Coating wastewater from paper mills has been characterized by a high chemical oxygen demand (COD), high total suspended solids (TSS) and a high degree of color. In this paper, a sequencing batch biofilm reactor (SBBR) and an anaerobic-oxic (AO) system that consisted of a hydrolytic acidification reactor and an activated sludge reactor (HAASR) were implemented to treat coagulated coating wastewater from a paper mill. The COD, color and TSS removal efficiencies of the SBBR were 87.7 %, 33.5 %, and 41.4 %, and those of the HAASR were 85.3 %, 22.5 % and 19.4 %, respectively. It is proposed that more recalcitrant compounds were removed by the SBBR than by the HAASR. The microbial communities of the SBBR sludge and the HAASR sludge were evaluated and indicated that the SBBR sludge had lower microbial richness and diversity than the HAASR sludge. Moreover, Proteobacteria and Bacteroidetes were the dominant bacteria in both the HAASR and SBBR sludges.