Modelling an industrial anaerobic granular reactor using a multi-scale approach

Abstract

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (X) and methanogens (X) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (X,X, X) and acetogens (X,X). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed.

Model‐based analysis and optimization of a full‐scale industrial high‐rate anaerobic bioreactor

“…This can, however, be done using a model based on a biofilm structure (Batstone et al, ; Feldman et al, ; Wanner et al, ). A biofilm model for the same system has been developed and yields similar results for the data sets available (Feldman et al, ). To simulate the effect of precipitation in the granules, special attention should be placed on defining a precipitation framework (Kazadi Mbamba, Tait, Flores‐Alsina, & Batstone, ) to determine saturation conditions.…”

“…Furthermore, the focus should be placed on density variation (Winkler, Kleerebezem, Strous, Chandran, & van Loosdrecht, ), as well as the description of VSS and ISS concentrations in the granules (Ekama & Wentzel, ). The use of a biofilm model can indicate the long‐term effect of intra‐granular precipitation on CH 4 production (Feldman et al, , ).…”

“…These effects cannot be modeled with the current model, where an artificial loop is introduced to mimic the hydraulics of the reactor and the high biomass concentrations. This can, however, be done using a model based on a biofilm structure (Batstone et al, 2004;Feldman et al, 2017;Wanner et al, 2006). A biofilm model for the same system has been developed and yields similar results for the data sets available (Feldman et al, 2017 (Ekama & Wentzel, 2004).…”

“…In these situations, granular type models could be implemented since they account for mass transfer limitations and microbial competition/affinity within the biofilm (Wanner et al, ). The works of Batstone, Keller, and Blackall (), Odriozola, López, and Borzacconi (), and Feldman et al () show the benefits of using multi‐scale models (biofilm, granule, reactor) when predicting process performance, microbial community structure, and how these interact, and how they are affected by changing loading conditions.…”

“…In these situations, granular type models could be implemented since they account for mass transfer limitations and microbial competition/affinity within the biofilm (Wanner et al, 2006). The works of Batstone, Keller, and Blackall (2004), Odriozola, López, and Borzacconi (2016), and Feldman et al (2017) show the benefits of using multi-scale models (biofilm, granule, reactor) when predicting process performance, microbial community structure, and how these interact, and how they are affected by changing loading conditions. High-rate conditions can also be empirically represented by artificially separating the hydraulic and the sludge retention time (Batstone, Torrijos, Ruiz, & Schmidt, 2002;Vanhooren, Van Hulle, De Pauw, & Vanrolleghem, 2002), without the need of overcomplicated biofilm reactors.…”