Improving Clarifier Models by Describing Extracellular Polymeric Substances

Improved settleability in activated sludge processes is an essential feature of new innovations. To accelerate the adoption of such technologies, the ability to link operational conditions with settling characteristics is needed to support process design and prediction of improvements in settleability. The previous works indicated that the threshold of flocculation (TOF) (Mancell-Egala et al., 2017a), which describes the collision efficiency of particles, was successfully introduced as a simple experimental method to calculate the flocculent settling coefficient (rp) in 1-D clarifier models and to enhance the ability to predict clarifier effluent solids. TOF also showed to have a clear relationship with effluent quality making it a useful operational parameter to detect flocculation limitations. In addition, extracellular polymeric substances (EPS) quality, most often expressed as a protein over polysaccharides ratio has been linked to flocculation behavior, densification and granulation (McSwain et al., 2005). This knowledge was used to develop an empirical function between the composition of (EPS) expressed as EPS-TKN/COD and TOF. This relationship between EPS composition and TOF was introduced as a means of linking biological process models (i.e. Sumo2C model) and 1-D clarifier models (Ngo et al., 2021b). Essential for this approach is the prediction of EPS amounts and quality from process models as a function of feast-famine, and other operational conditions as this defines settling behavior. This paper discusses three approaches for EPS prediction from process models and will provide insights on 2 which type of EPS modeling might be needed for different purposes. While this abstract describes different datasets tested for the different models, the full paper will provide a full comparison of the three models on the full-scale dataset collected at Blue Plains