Alpha Factors in Full Scale Wastewater Aeration System-1

ALPHA FACTORS IN FULL-SCALE WASTEWATER AERATION

SYSTEMS

Diego Rosso and Michael K. Stenstrom

Civil and Environmental Engineering Department, University of California, Los Angeles. 5714 Boelter Hall, Los Angeles, CA, 90095-1593

ABSTRACT

Surface active agents depress gas transfer at gas-liquid interfaces. They are present as measurable trace contaminants at all environmental and at most industrial gas-liquid interfaces. This paper presents the results of several studies, including lab and full scale studies that show the depression of gas transfer, usually quantified by the alpha factor, can be related to the Reynolds number and the level of wastewater treatment. Our results offer a tool for mass transfer prediction from flow regime and dynamic surface tension properties.

KEYWORDS

Aeration, alpha factor, oxygen transfer, activated sludge

INTRODUCTION

Aeration is an essential process in the majority of wastewater treatment processes and accounts for the largest fraction of plant energy costs (Reardon, 1995). The impact of contamination on aeration performance is usually quantified by the α factor (ratio of process water to clean water mass transfer coefficients, or KLapw/KLacw). Differences in α amongst aeration systems were noted in the 1930's (Kessener and Ribbius, 1935), but were generally forgotten until the energy crisis of the 1970’s increased the awareness for energy efficient technologies. Prior to the 1980s, many plants were designed with α of 0.8, which was considered as a “universal” α for all types of aeration systems. Lower flow regime gas-liquid interfaces (such as the ones produced by fine-pore diffusers) generally have lower α factors than higher flow regime interfaces (produced by coarse bubble diffusers or surface aerators) for similar conditions (Stenstrom and Gilbert, 1981). It has been shown that different aeration methods have different α, and for fine-pore diffusers the initial α decreases over time in operation due to fouling or scaling (Rosso

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Copyright 2006 Water Environment Foundation. All Rights Reserved©

and Stenstrom, 2005). Furthermore, for fine-bubble systems α is a function of process conditions such as the mean cell retention time (MCRT) or the airflow rate (Rosso et al., 2005).

There exists a debate over the reasons for different α factors for different aeration methods. Part of the difficulty is the reliance on different experimental methods to measure α factors, and the variations in the range of interfacial flow regimes. This research work summarizes previously observed phenomena, and explains the microscopic phenomena that cause different contamination effects at different flow regimes. The effects of contamination on gas-liquid interfaces due to surfactants were analyzed, compared, and explained for the cases of high and low interfacial velocities. These regimes correspond respectively to: 1. coarse-bubble and surface aerators: 2. fine-pore diffusers. The results of two laboratory studies using dynamic surface tension measurements and several other laboratory- and full-scale studies verify the conclusions. These results, along with our previously published work on the impact of MCRT and ageing or fouling on aeration efficiency, will be useful for aeration system design.

MATERIALS AND METHODS

Aeration tests were performed in a well-mixed vessel, according to the standard procedure by the American Society of Civil Engineers (ASCE, 1984, 1991). Volumetric mass transfer coefficients (kLa, time-1), oxygen transfer rates in standard conditions (SOTR, massO2⋅time-1), oxygen transfer efficiency in standard conditions for clean water (SOTE, %), and oxygen transfer efficiency for surfactant solutions (αSOTE, %) were calculated. The α factor was calculated as the ratio αSOTE/SOTE. The surfactants utilized in this study were sodium dodecyl sulfate, Tergitol (sodium tetradecyl sulfate), iso-amyl alcohol, and polyacrylic acid. Additional, previous investigations from our laboratory were also included (Rosso et al., 2006).

RESULTS AND DISCUSSION

Figure 1 shows the evolution of mass transfer coefficients with increasing time. As time elapses, surfactant molecules migrate towards the surface, and hinder the interfacial renewal process, resulting in a rapid decrease in the volumetric mass transfer coefficient kLa, which is the product of liquid film coefficient, kL and interfacial area (a). Since bubbles are stable at smaller diameters in contaminated waters, the interfacial specific area is higher. Since kLa decreases, kL must decrease more rapidly than the interfacial area (a) increases. Eckenfelder and Barnhart (1961) observed that kL decreases with increasing surfactant concentrations, but kLa is minimum at low surfactant

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concentrations, and partially recovers at higher concentrations. This is the effect of a larger interfacial area (a), but reduced liquid film coefficient kL. In the case of moving interfaces, as for diffused and surface aerators, turbulence exists behind the interfacial laminar films. The Reynolds number is defined as:

(Re)d u

ν⋅

= (1)

where d = characteristic length u = velocity ν = kinematic viscosity. At a given interfacial flow regime, hence at a given interfacial (Re), the film renewal rate is decreased with increasing contamination, and lower internal gas circulation rates in bubbles (Garner and Hammerton, 1954). The intuitive concept of “molecular obstruction” is usually considered the cause of mass transfer depression. This phenomenon is dominant for stagnant gas-liquid interfaces, with zero interfacial fluid velocity, when molecular diffusion through the stagnant film is the only transport mechanism. For moving interfaces, turbulent transport towards the interface is the driving force for mass transfer, for two reasons: interfacial renewal rates and actual area covered by the surfactant molecules. Higher contaminations with lower surface tensions cause higher boundary layer thickness, creating lower probability for turbulent eddies to reach the interface and carry “fresh” bulk fluid gas packets, causing lower renewal rates. Fig.1 shows different mass transfer coefficients at same contaminations (50mgSDS/l). The higher mass transfer coefficients from higher interfacial velocities (characterized by higher interfacial Péclet numbers) are shown in Fig.1. The same contaminations yield different mass transfer coefficients in different flow regimes; furthermore, higher interfacial velocity results in mass transfer coefficients in the same range, higher in average value than the range of mass transfer coefficients at low interfacial velocity. If the molecular obstruction phenomena were dominant, reduced transfer should also occur for certain aliphatic alcohols, which show mass transfer enhancement (α>1), instead of depression (Zlokarnik, 1980). If molecular obstruction is assumed dominant, it should be the same for both high and low interfacial velocities. Nevertheless, mass transfer depression has a higher magnitude at lower interfacial velocities, confirming that molecular obstruction is negligible for flowing systems. Figure 2 shows the decline in α factors with increasing time for selected measurements. The horizontal axis on this graph shows the mean bubble age (tB), which is the average hydraulic retention time of bubbles in the vessel. The measurement of kLa is performed according to the ASCE method with a series of bubbles re-aerating over a time-scale of minutes. At a given interfacial velocity, the rate of decline in α factor is greater for surfactants with greater molecular diffusivity. Conversely, higher molecular weight

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surfactants require generally greater time to migrate to the bubble interface, resulting in reduced depression of α factors for the same mean bubble age. Also, higher interfacial flow velocities resist the decline in α caused by surfactant accumulation, due to the higher interfacial renewal rates. Later in this paper this figure will be readdressed with regard to wastewater process conditions.

Figure 3 shows the evolution of α with increasing (Re) and compares them to other types of aeration. For fine-pore diffusers, (Re) was calculated using the equivalent wet diameter of the bubble column over the diffusers deq, scaled for the volume fraction φ of liquid in the column. Coarse-bubble experiments were performed with a single nozzle, and (Re) was calculated for a single coarse-bubble using the bubble diameter dB as characteristic length. Data from Eckenfelder and Ford (1968) were included in Fig.3 and show α for turbines at different rotation regimes. For these data, (Re) was calculated for a droplet with diameter dD of 5mm travelling in the air at 5 metres from the turbine shaft. Equation 2 summarizes the definition of characteristic lengths for the three cases above:

for fine-bubbles

for coarse-bubbles

for surface aerators

eqcolumn

bubble

droplet

dd

dd

d

φ⎧

= →⎪⎪⎪ →= ⎨⎪⎪

→⎪⎩

(2)

The trendline in Fig. 3 confirms the behaviour of α versus turbulence predicted by Eckenfelder and Ford (1968). The dashed portion of the trendline shows an interfacial flow regime that is usually not encountered in aeration systems. Viscous-flow domains [with (Re) < 10] are usually not encountered in wastewater practice, with the possible exception of membrane bioreactors (Wagner et al., 2002). In this region, there is practically no effect of flow on α, as the gas-transfer resistance is due primarily to the transport within the bulk liquid. In the transitional-flow domain, where fine-bubble aerators operate, an increase in (Re) results in a decline in α. Within this region [50 < (Re) < 5000] gas-transfer is controlled by the surfactant interfacial migration, higher at higher (Re). In the laminar regime, i.e. the domain of fine-bubble diffusers, an increase of (Re) results in an increase of surfactant transport to the interface, hence a decrease in alpha. As (Re) increases into the turbulent regime, the surface renewal rate becomes high enough to shear surfactants off the surface, which increases the alpha factor. Coarse-bubble diffusers, jets, and surface aerators have a regime in the inertial-flow domain. For these gas-liquid interfaces, the higher range of (Re) results in higher interfacial renewal rates, and lower interfacial surfactant accumulation. The trendline shows that at very high (Re), α can be restored, and if the energy density is sufficient,

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values of α larger than 1.0 are possible. The reasons for the higher α include ionic interfacial effects due to the presence of inorganic salts, such as in seawater, or of some concentrated aliphatic alcohols (Zlokarnik, 1980). Another reason is the entrainment of foam created by surfactants. Such foams are either ephemeral or do not exist without surfactants. These foams can be stable and composed of fine bubble aggregates with high interfacial areas. Operations at these conditions have low aeration efficiency, since values of α approaching or higher than 1.0 may be reached only at the expense of additional energy. At extremely high energy densities, corresponding to (Re) > 105, the higher interfacial shear rate reduces the thickness of the laminar film. At the upper limit, the interfacial resistant film will reduce its thickness to a few layers of water molecules, and the phenomenon of liquid vaporisation will be dominant, as when turbines or pumps cavitate. The cross-hatched area in Figure 3 corresponds to a region where mass transfer is affected by local energy density. In this region, (Re) and the energy density may be independent and produce different mass transfer rates. For example, the results from Hwang and Stenstrom (1979) were collected in a small vessel with higher energy density while the results from Eckenfelder and Ford (1968) were collected in a large vessel. This phenomenon creates a range of α using experimental setups where (Re) and energy density are not controlled (Bass and Shell, 1977).

RECOMMENDATIONS FOR FULL-SCALE OPERATIONS

The choice of alpha factors for biological process design is crucial for overall efficiency and economic viability of the aeration process (Rosso and Stenstrom, 2005). Aeration systems for biological environmental processes are traditionally designed relying upon data collected from re-aeration tests in pure water. The scale-up factors are commonly left to the designer’s experience. However, this has resulted in frequent overestimation of performance. Pure water re-aeration tests are characterized by bubbles belonging to the fluid-sphere regime, while process water tests can be characterized by both the fluid- and solid-sphere regimes. Bubble diameter, air flowrate, and contaminant quantitative and qualitative characteristics determine the transition between the two regimes. In our experimental setup full scale conditions were produced for a single bubble. The bubble characteristics (diameter, velocity, time scale) and surfactant concentrations are in the same range as in full scale. The difference between laboratory and full scale is only the number of bubbles. Our aeration experiment was performed using a full-scale diffuser and confirms that the similitude between the laboratory- and full-scale system is maintained. Fig. 2 shows the celerity of gas transfer depression operated by surfactants: the departure between the two solutions begins at bubble formation and reaches a steady value before bubble detachment. In aerated biological processes such as sequencing batch reactors,

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PFR, or CSTR reactors, the average hydraulic retention time for a fine-bubble is in the order of 20-80 s. This reduces the time of bubble formation to a negligible fraction of the total bubble residence time. Therefore, the gas transferred in the bubble formation process is a negligible fraction of the total gas transferred. When sizing aeration systems for contaminated liquids it is necessary to take the corrected kLa value that can be estimated from Fig.3, and not the 0.8 value traditionally used for design. Our results showed that for fine-pore aerators, alpha factors typically reach a value in the range from 0.2 to 0.8 before bubble detachment, depending on the contaminant characteristics. This implies a design over sizing of 1.25 to 5 times the aeration capacity in pure water. Figure 4 shows α or αF factors for conventional, nitrification-only, and nitrification/denitrification activated sludge processes. The dataset used to plot this graph is based on 100 off-gas testing experiences throughout the US. Higher MCRT operations have in general higher alpha factors, due to the higher uptake of dissolved substrate (which is a surfactant) by the more numerous bacterial population. The increase in alpha between N-ONLY and NDN is due to the prompt uptake of low molecular weight surfactant by the selectors in the denitrification zone. These low molecular weight surfactants are the molecules with the most deleterious and rapid effects on gas transfer (Rosso et al, 2006).

SUMMARY AND CONCLUSIONS

Commercially available surfactants were used to concurrently measure dynamic surface tension and mass transfer coefficients. Measurements were performed from bubble formation to bubble detachment, showing that for fine-bubbles in aqueous surfactant solutions, surface contamination equilibrates before detachment. Therefore, after bubble detachment and during the transit of bubbles through the liquid, the liquid-side gas transfer coefficient is reduced to a steady-state process value, always lower than the gas transfer coefficient in pure water. Our experimental evidence shows a reduction of 20-80% of pure water values in surfactant solutions, which confirms full-scale field measurements of α in the range of 0.2 to 0.8. By accumulating at the interface, surfactants lower the surface tension, reduce interfacial renewal, and reduce the diffusion of gas into the liquid. For a given contamination, interfaces with higher renewal rates have higher mass transfer. For a given flow regime, hence a given renewal rate, higher contamination results in lower mass transfer. At higher renewal rates, the variation due to different contamination is smaller than the variation at lower renewal rates. We conclude that higher flow regimes can offset contamination. Results explain why fine-bubble diffusers have greater mass transfer depression than coarse-bubble or surface aerators. The high turbulence associated with coarse-bubble aerators makes them behave more like surface aerators than fine-bubble aerators. High turbulence aerators may achieve better transfer rates, but at the expense of greater energy

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density, and lower aeration efficiency (kgO2⋅kWh-1). Results also describe the variability of α measured at small scale, due to uncontrolled energy density.

REFERENCES:

American Society of Civil Engineers - ASCE (1984, 1991). Measurement of Oxygen Transfer in Clean Water. ASCE 2-91, American Society of Civil Engineers, New York.

Bass, S.J., and Shell, G.L. (1977) Evaluation of oxygen transfer coefficients of complex wastewaters, Proc. 32nd Industrial Waste Conf., Purdue University, Lafayette, IN.

Eckenfelder, W.W., and Barnhart, E. L. (1961) The Effect of Organic Substances on the Transfer of Oxygen from Air Bubbles in Water, AIChE J., 7(4), 631-634.

Eckenfelder, W. W., and Ford, D. L. (1968) New concepts in oxygen transfer and aeration, in Advances in water quality improvement, E. F. Gloyna, and W. W. Eckenfelder Jr. (eds.), University of Texas Press, Austin, TX, 215-236.

Garner, F.H., and Hammerton, D. (1954) Circulation inside gas bubbles, Chem. Eng. Sci., 8(1), 1-11.

Hwang, H.J., and M.K. Stenstrom (1979) The Effect of Surface Active Agents on Oxygen Transfer, UCLA-ENG-79-30, University of California, Los Angeles.

Mancy, K.H., and Okun, D.A. (1960) Effects of Surface Active Agents on Bubble Aeration, J. Water Poll. Cont. Fed., 32(4), 351-364.

Masutani, G., and Stenstrom, M.K. (1991) Dynamic Surface Tension Effects on Oxygen Transfer, J. Environ. Eng., 117(1), 126-142.

McKeown, J.J., and Okun, D.A. (1961) Effects of surface-active agents on oxygen bubble characteristics, Int. J. Air. Wat. Poll. 5(2-4), 113-122.

Reardon, D.J. (1995) Turning down the power, Civ. Eng. 65(8) 54-56. Rosso, D., Iranpour, R. and Stenstrom, M.K. (2005). Fifteen Years of Off-gas Transfer

Efficiency Measurements on Fine-Pore Aerators: Key Role of Sludge Age and Normalized Air Flux. Wat. Environ. Res. 77(3), 266-273.

Rosso, D., Stenstrom, M.K. (2005) Comparative economic analysis of the impacts of mean cell retention time and denitrification on aeration systems, Wat. Res. 39, 3773-3780.

Rosso, D., Huo, D.L., and Stenstrom, M.K. (2006) Effects of interfacial surfactant contamination on bubble gas transfer, Chem. Eng. Sci, in press.

Stenstrom, M.K., and Gilbert. R.G. (1981) Effects of Alpha, Beta and Theta Factors in Design, Specification and Operations of Aeration Systems. Wat. Res., 15, 643–654.

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Wagner, M., Cornel, P, and Krause, S. (2002) Efficiency of different aeration systems in full scale membrane bioreactors, Proc. 75th WEFTEC conference, Chicago, IL.

Zlokarnik, M. (1980) Koaleszenzphänomene im System gasförmig/flüssig und deren Einfluß auf den O2-Eintragbei der biologischen Abwasserreinigung, Korresp. Abw., 27(11), 728-734.

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2.0

4.0

6.0

8.0

10.010

4 kLa

(t B) [

s-1 ]

0.1 2.0 3.0 4.0 5.0tB [s]

4.8

4.84.9

4.9

7.27.3

7.6

6.9

7.1

6.1

6.1

6.1

6.8

Labels are log(Pe) for selected points.Bars represent one standard deviation.

0.05

0.025%IAAv/v (H)

50 mgSDS/l (H)

50 mgSDS/l (M)

100 mgSDS/l (M)

Figure 1. Evolution of mass transfer coefficients over increasing bubble surface age tB.

(H: data from Rosso et al., 2005; M: data from Masutani and Stenstrom, 1991).

0.20

0.40

0.60

0.80

1.00

α

0.04 0.08 0.12 0.16 0.20 0.24

tB [s]

Data from Rosso et al. (2006)

50 mgSDS/l0.025%IAAv/v

Figure 2. Evolution of α factors with increasing bubble surface age tB.

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1x102 1x103 1x104 1x105

(Re)

0.2

0.4

0.6

0.8

1

1.2

α

Fine-bubble (Rosso et al., 2005a)Coarse-bubble (this study)Surface aerator (Hwang and Stenstrom, 1979)Turbine (Hwang and Stenstrom, 1979)Turbine (Eckenfelder and Ford, 1968)

diffusional transport advectional transport

Figure 3. α factors at different interfacial flow regimes. The low (Re) zone is the

domain of fine-bubble aerators, while higher (Re) correspond to coarse-bubble, jets, surface mixers, and turbines. The shaded area represents a family of trendlines parametric in the energy density.

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0.0

0.2

0.4

0.6

0.8

1.0α

or α

F

CONVCONVCONVCONVCONVCONVCONVCONV N- ONLYN- ONLYN- ONLYN- ONLYN- ONLYN- ONLYN- ONLYN- ONLY NDNNDNNDNNDNNDNNDNNDNNDNNDNNDNNDNNDN

Process type Figure 4. Alpha and AlphaF factors for each process type. Key: CONV = conventional

activated sludge process; N-ONLY = nitrification only; NDN = Nitrification / denitrification. The dataset used to plot this graph is based on 100 off-gas testing experiences throughout the US. Higher MCRT operations have in general higher alpha factors, due to the higher uptake of dissolved substrate (which is a surfactant) by the more numerous bacterial population. The increase in alpha between N-ONLY and NDN is due to the prompt uptake of low molecular weight surfactant by the selectors in the denitrification zone.

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Alpha Factors in Full Scale Wastewater Aeration System-1