Dynamically predicting nitrous oxide emissions in a full-scale industrial activated sludge reactor under multiple aeration patterns and COD/N ratios.

The use of digital tools has become essential for quantifying and predicting greenhouse gas (GHG) emissions in urban wastewater treatment plants (WWTPs), enabling the development of operational regimes with a high probability of achieving net-zero targets. However, comprehensive studies documenting validation of model predictions-such as effluent quality, process economics, and emission factors-remain scarce within full-scale industrial settings. This paper aims to develop a decision support tool (DST) for (dynamically) predicting nitrous oxide (NO) emissions in full-scale industrial activated sludge reactors (ASRs) and suggesting mitigation strategies.

Modelling and set-point definition for the development of a joint control system of two interconnected wastewater treatment plants and its application in practice.

The use of activated sludge models (ASMs) is a common way in the field of wastewater engineering in terms of plant design, development, optimization, and testing of stand-alone treatment plants. The focus of this study was the development of a joint control system (JCS) for a municipal wastewater treatment plant (mWWTP) and an upstream industrial wastewater treatment plant (iWWTP) to create synergies for saving aeration energy. Therefore, an ASM3 + BioP model of the mWWTP was developed to test different scenarios and to find the best set-points for the novel JCS.

Ex-situ bioremediation of polycyclic aromatic hydrocarbons in sewage sludge.

Polycyclic aromatic hydrocarbons (PAH) are regarded as environmental pollutants. A promising approach to reduce PAH pollution is based on the implementation of the natural potential of some microorganisms to utilize hydrocarbons. In this study Proteiniphilum acetatigenes was used for bioaugmentation of sewage sludge to improve the PAH removal.