Aeration is an energy-intensive process of aerobic biological wastewater treatment. An accurate model of oxygen transfer dynamics in activated sludge tanks would improve design and operation of aeration systems. Such a model should consider spatial and diurnal variation of α-factor as well as site-specific conditions that impact oxygen transfer. For this dynamic prediction a machine learning approach was used for the first time. The data-driven method was based on long-term ex-situ off-gas measurements with pilot-scale reactors (5.8 m height, 8.3 m³ vol) coupled to full-scale activated sludge tanks on the sites of two conventional and a two-stage activated sludge treatment plant. The ex-situ off-gas method allowed to quantify theoretical off-gas parameters in non-aerated zones and thus consider the whole activated sludge tank. We introduced the α₀-factor to compare aerated and non-aerated zones under nonsteady-state conditions. Like the established α-factor for steady-state conditions, the α₀-factor describes oxygen transfer inhibiting effects in activated sludge. α₀-factor was lowest in upstream denitrification zones. This indicates an anoxic elimination of oxygen transfer inhibiting wastewater contaminants which improved oxygen transfer in subsequent aerobic zones. Random Forest models predicted α₀-factor reliably in all examined activated sludge tanks even for stormwater events and seasonal variation. Model development only required online sensor data already available to operators. Our results suggest that machine learning models can dynamically predict α-factors in a variety of activated sludge processes, thus considering site-specific conditions in model training without manual calibration.

Aeration is an energy-intensive process of aerobic biological treatment in wastewater treatment plants (WWTP). Two-stage processes enable energy-efficient operation, but oxygen transfer has not been studied in depth before. In this study, α-factors were determined with long-term ex situ steady-state off-gas measurements in pilot-scale test reactors (5.8 m height, 8.3 m³) coupled to full-scale activated sludge basins. A two-stage WWTP with more than 1 Mio population equivalent was studied over 13 months including rain and dry weather conditions. Operating data, surfactant concentrations throughout the two-stage process, and the effect of reverse flexing on pressure loss of diffusers were examined. The values of α_mean, α_min, and α_max for design load cases of aeration systems were determined as 0.45, 0.33, and 0.54 in the first high-rate carbon removal stage and as 0.80, 0.69, and 0.91 in the second nitrification stage, respectively. The first stage is characterized by a distinct diurnal variation and decrease in α-factor during stormwater treatment. Surfactants and the majority of the total organic carbon (TOC) load are effectively removed in the first stage; hence, α-factors in the second stage are higher and have a more consistent diurnal pattern. Proposed α-factors enable more accurate aeration system design of two-stage WWTPs. Fouling-induced diffuser pressure loss can be restored effectively with reverse flexing in both treatment stages.

Performance of aeration systems in wastewater treatment plants (WWTP) under process conditions can be monitored with off-gas tests. The ex situ off-gas method transfers activated sludge from an adjacent aeration tank into aerated columns to determine oxygen transfer parameters (e.g., the α-factor). This method is an alternative to in situ off-gas testing with hoods at the tank surface; however, its application and measurement uncertainty have not been examined yet. We outline our experience from long-term off-gas testing with two pilot-scale test reactors (8.3 m³ volume). Global variance-based sensitivity analysis using Sobol’ indices revealed oxygen concentration in off-gas and dissolved oxygen as the most important input quantities to determine α-factors accurately. Measurement uncertainty of other instruments was negligible. These findings are transferable to in situ off-gas hoods because the methods are similar. Random measurement error of α-factors was estimated with uncertainty analysis and comparison measurements to a relative standard deviation of about ± 2.8% for our ex situ pilot setup. Diffuser fouling, biofilm growth, or sensor drift caused systematic errors avoidable by maintenance. Additional mixing of bubble column due to sludge inflow into ex situ tanks led to a systematic overestimation of α-factors at lower airflow rates. Hence, the ex situ off-gas method is not suitable to determine α-factors for the design of aeration systems but offers unique possibilities for research of oxygen transfer dynamics and development of aeration equipment because ex situ columns can be operated independently from a full-scale activated sludge tank.

Aeration is usually the most energy-intensive part of the activated sludge process, accounting for 50% to 80% of the total requirement. To achieve high efficiency, designers and operators of WWTPs must, therefore, consider all influencing factors, including salinity. With increasing salinity, oxygen transfer increases compared to tap water (TW), due to the inhibition of bubble coalescence. Previous saline water (SW) experiments showed that by using small slits in the diffuser membrane design, oxygen transfer and aeration efficiency increase further. In this study, we present a modified approach for considering the salt effect on oxygen transfer and assess the transferability of SW results to saline-activated sludge (sAS) conditions. Therefore, we operated a pilot-activated sludge plant over 269 days with a saline industrial wastewater influent. The oxygen transfer of disc-diffusers with two different membrane designs was measured continuously via the off-gas method. The salt concentration (c_Salt) measured via ion analysis ranged between 4.9 and 11 g/L. Despite a high c_Salt fluctuation, COD elimination was >90% all the time. Our results confirm previous SW results. Oxygen transfer in sAS is up to three times higher compared to non-saline conditions. Aeration efficiency shows that despite a higher pressure drop, diffusers with smaller slits are to be recommended in order to improve aeration in sAS.