Modelling gas–liquid mass transfer in wastewater treatment: when current knowledge needs to encounter engineering practice and vice versa

Abstract

Gas–liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas–liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid–base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas–liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas–liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas–liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas–liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

Oxygen transfer and plant‐wide energy assessment of primary screening in WRRFs

“…The results from off‐gas testing consistently showed an increase in oxygen transfer efficiency for screened lines (both pilot and full scale) due to the lower loading conditions achieved after primary screening (Figure 8). The results are in agreement with previous studies (Amaral, 2019; Leary et al, 1968). The screened line at the pilot reactor resulted on average in an oxygen transfer 40 ± 3% higher (3.18 ± 0.63%/m) in relative comparison to the nonscreened (2.27 ± 0.58%/m) over the period of operations.…”

Modelling of the treatment of wastewater by photovoltaic solar electrochemical oxidation (PSEO) assisted by redox-flow batteries

“…In light of the previous studies the modeling and prediction of those treatments are key to understand in detail the behavior of these technologies working under non-constant operational conditions and to assess the level of removal under different weather conditions and consequently a fluctuating powering. Despite the research community has developed mathematical correlations capable of predicting the performance of those remediation technologies under different soft and constant operational conditions and a wide range of pollutants [19][20][21][22][23][24][25][26][27][28][29], there are not literature evidence of studies under realistic conditions (direct coupling with renewable energies). Regarding the green energy storage, a wide range of chemical, mechanical, electromagnetic, thermal or electrochemical systems have been studied in the last centuries [30].…”

Commercial Integrated Permeate Channel Ultrafiltration Membranes: Design, Modeling and Performance

“…Advanced CFD is characterized by the integration of process phenomena in CFD as described by Nopens et al [5,6]. In this case, process phenomena to include were the 2-phase interactions of bubbles and water, and the elevated liquid density due to the high mixed liquor suspended solids (MLSS) concentration typically present in MBRs, which is described elsewhere by Neves do Amaral et al [7]. Rehman-Nopens curves were used to transform the large amount of local shear values into clear graphs.…”