Practical applications of wastewater treatment plant modelling studies

Abstract: Practical applications of wastewater treatment plant modelling studies, particularly industrial cases, have been relatively limited. A potential reason for this is that commercial software applications (e.g. GPS-X, WEST-DHI, SUMO, BIOWIN, EFOR, SIMBA) including state-of-the-art implementations (ASM1, ADM1) were originally developed to predict the performance of urban wastewater systems treating domestic wastewater, and therefore fail to properly represent specific industrial processes. Industrial wastewaters have very diverse dynamics (compared to urban wastewater), which is a result of different production schemes/schedules within the factory. Variable pH, influent biodegradability, non-standard N:COD and P:COD ratios might challenge traditional biological processes. In some cases, high S loads decrease methane/biogas production (and potential energy recovery). Metals and some inorganic/organic compounds can inhibit microorganism growth and/or have severe toxicity effects. The high content of cations and anions promotes the formation of precipitates at different locations in the reactor (granules, pipes), which can have detrimental (decrease of methanogenic activity) or catastrophic (cementation) effects on reactor performance. The seminar will show how some of these  (hostile) phenomena may be included within mathematical models describing industrial wastewater as well as several case studies result of the collaboration between DTU Chemical Engineering and the Biotech industry, Water Utilities, Biogas companies within the Scandinavian region.

Bio: Xavier Flores-Alsina holds a Senior Researcher position at the PROcess SYStems engineering (PROSYS) of the Technical University of Denmark. He did his PhD between the University of Girona (Spain) and the University of Oxford (UK). He also gained post-doctoral experience in Canada (Laval U), Sweden (Lund U), Australia (U of Queensland) and South Africa (U of Cape Town). His main field of experience of mathematical modelling, data science, process control and artificial intelligence applied to water systems.