Influence of substrates concentrations on the dynamics of oxygen demand and aeration performance in ideal bioreactors

The effect of bioreactor configurations on the dynamics of aeration modelling was investigated by incorporating three different correlations from the literature to estimate alpha-factors into the aeration model. Estimated air flow rates using the three correlations were then validated against experimental data obtained from pilot sequencing batch reactors (SBRs). Two identical SBRs were operated in parallel; one received raw wastewater and the other received primary treated wastewater. The validated aeration model was then used to evaluate aeration dynamics in different bioreactor configurations, both for nitrification only and nitrification/denitrification, with the three different correlations. The current study is the first to investigate the validity of the aforementioned correlations using various bioreactor configurations and to establish that the bioreactor configuration not only impacts spatial and temporal biological oxygen demands as currently understood but also oxygen transfer efficiency. The first correlation based on the real-time bioreactor soluble chemical oxygen demand (sCOD) was able to predict the temporal measured air flow rate in the pilot SBRs. The second correlation based on the influent COD overestimated the air flow rates as it considered the impact of the influent loading rates on the alpha-factor and overlooked the improvement in alpha-factor due to biodegradation. The third correlation based on MLSS concentrations underestimated the air flow rates at the beginning of the aeration cycle as it ignored the impact of influent loading rates on the alpha-factor and considered only the insignificant change in MLSS during the aeration cycle. In terms of bioreactor configuration, the model-based analysis showed that the first correlation is suitable for designing SBR, plug flow reactor (PFR), step-feed PFR, and completely mixed stirred reactor (CSTR) systems, and the third correlation is suitable for designing CSTRs and membrane bioreactors (MBRs), while the second correlation was not accurate in any of the reactors modelled. When nitrification was targeted, the CSTR reduced aeration energy by 44 %-49 % compared to the PFR, and 41 %-43 % when both nitrification and denitrification were targeted. Compared to the plug-flow reactor, the step-feed PFR reduced aeration energy by 9% when nitrification only was targeted. However, when pre-denitrification was added, both systems showed the same aeration energy consumption. Pre-denitrification reduced organic loadings to aeration tanks and decreased aeration energy by 22 %, 11 %, 15 %, and 14 % in PFR, CSTR, PFR step feed and MBR systems, respectively. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

This study investigated the impact of bioreactor configurations on aeration modeling dynamics by incorporating different correlations. It was found that different correlations had varying effects on predicting air flow rates and that bioreactor structure not only affected spatial and temporal biological oxygen demands, but also oxygen transfer efficiency. The study established the suitability of different correlations for designing specific bioreactor systems, highlighting the need for considering the impact of influent loading rates on the alpha-factor.