Introduction

Optimization of oxygen supply in wastewater
treatment processes is needed in order to limit the energy expenditure of
wastewater treatment plants (WWTP) and to guarantee the treatment efficiency. To
this aim, models based on dimensional analysis [1,5]
or computational fluid dynamics (CFD) [2] were developed to predict oxygen
transfer efficiencies of classical fine bubble aeration systems. New treatment
processes based on coarse bubble aeration system coupled with fluidized biofilm
carriers (biomedia), which provide a large internal
area for bacterial growth (Moving Bed Biofilm Reactors - MBBR and Integrated
Fixed-Film Activated Sludge - IFAS), are now competitive and are often proposed
for WWTP upgrading and new building. In these new systems, the oxygen transfer
performance in the presence of biomedia is not well
established [3] and model adjustments are required for process optimization.
The aim of this study is to provide models issued from dimensional analysis
linking oxygenation performances in clean water to design and operating
parameters for inverse fluidized bed reactors.

Material and methods

Models are developed using a database of 77 oxygen
transfer performances measured on two rectangular semi-industrial scale pilots (the
characteristics of the pilots are described in Table 1).

Table 1.
Characteristics of the two semi-industrial scale pilots and operating
conditions

With: H_max = maximum liquid height / V_max = maximum volume of liquid / U_G
= superficial air velocity / FB = fine bubble aeration / CD = coarse bubble
aeration

The flexibility of these
experimental devices enables to study the impact of most design and operating
parameters such as reactor dimensions (surface, liquid height), characteristics
of the aeration system (fine / coarse bubble diffusion, number and location of aerators),
air flow rate and biomedia filling ratio (from 0 to 60%
in volume). For each configuration, the oxygen transfer performances were
determined in clean water according to the normalized non-steady state method
[4].

Results

In this abstract, results are presented only for
reactor 1. Results obtained on reactor 2 will be developed in the full version
of the manuscript.

Exploiting the database allows to highlight the impact of major parameters on the oxygen
transfer performances:

·       
Without
biomedia, the oxygen transfer coefficient (k_La₂₀)
was mainly controlled by the superficial gas velocity and the installed aeration
system (Figure 1), due to the bubble size and the resulting liquid flows. A
linear correlation between k_La₂₀ and U_G is
obtained, such as observed on full-scale plants [5].

Figure 1.
Oxygen transfer coefficient as a function of the superficial gas velocity for
fine bubble (FB) and coarse bubble (GB) aeration for different configurations
of reactor 1

·       
An
increase in the biomedia filling ratio led to an
increase in k_La₂₀ for coarse bubble aeration (Figure 2).
This increase could be related to a decrease in the mean bubble diameter and an
increase in the gas/liquid contact time due to biomedia
volume occupation. Preliminary results on reactor 2 showed that the oxygen
transfer performance of fine bubble aeration systems were less impacted by the biomedia filling ratio in comparison to than in coarse
bubble aeration.

Figure 2.
Oxygen transfer coefficient as a function of the superficial gas velocity and
the biomedia fill ratio (Reactor 1 ? Configuration 7
? V = 0.93 m³)

A model was developed on the basis of a dimensional
analysis. The transfer number (N_T) is related to the Reynolds number
(

), the ratio between the total
perforated area of the diffusers (S_p) and the total area of the
reactor (S) and the biomedia fill ratio (T_RB).

     (Eq.
1)

Where: k_La
is the oxygen transfer coefficient (s^-1), U_G the superficial
gas velocity (m.s^-1), n the liquid cinematic viscosity (m².s^-1),
h the diffuser submergence (m) and g the standard gravity (m.s^-2)

This model is made independent of the aeration
system characteristics (fine/coarse bubble) and enables to predict the transfer
number with an average accuracy of 6%.

Figure 3. Modeled versus experimental transfer numbers for fine
/ coarse bubble aeration without/with biomedia

Conclusions

The development of models in order to optimize
the oxygen transfer performances in inverse fluidized bed reactors commonly
used in wastewater treatment is needed. To this aim, a database of 77 oxygen
transfer measurements was built on two semi-industrial scale reactors. Exploiting
this database for reactor 1 points out the impact of design and operating parameters
on oxygen transfer performances. A model, based on dimensional analysis, is
also build, allowing to predict the transfer number
with an accuracy of 6%. Additional results on reactor 2 will be included in the
full version of the manuscript.

References

[1] Capela, S., M. Roustan et A. Héduit, 2001,
Transfer number in fine bubble diffused aeration systems, Water Science and
Technology, 43(11), 145-152

[2] Fayolle, Y., A. Cockx, S. Gillot, M. Roustan and A. Héduit, 2007, Oxygen transfer prediction in
aeration tanks using CFD, Chemical Engineering Science 62(24), 7163-7171

[3] Rosso, D., S.E. Lothman, M.K. Jeung, P.
Pitt, W.J. Gellner, A.L. Stone et D. Howard, 2011, Oxygen transfer and uptake,
nutrient removal, and energy footprint of parallel full-scale IFAS and
activated sludge processes, Water Research 45(18), 5987-5996

[4] NF-EN-12255-15, 2004, Wastewater treatment
plants - Part 15: Measurements of the oxygen transfer in clean water in
aeration tanks of activated sludge plants

[5] Gillot, S., S. Capela-Marsal,
M. Roustan, A. Héduit (2005) Predicting oxygen
transfer of fine bubble aeration systems ? Model issued from dimensional
analysis, Water Research, 39(7), 1279-1387.