Journal of Water Process Engineering Industrial

Journal of Water Process Engineering 23 (2018) 61–74

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Journal of Water Process Engineering journal homepage: www.elsevier.com/locate/jwpe

Industrial wastewater treatment by Aerobic Inverse Fluidized Bed Biofilm Reactors (AIFBBRs): A review

T

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Anup Kumar Swaina, , Abanti Sahooa, Hara Mohan Jenaa, Hemalata Patrab a b

Chemical Engineering Department, National Institute of Technology, Rourkela, Odisha, 769008, India Central Institute of Plastics Engineering & Technology, B - 25, CNI Complex, Patia, Bhubaneswar, Odisha, 751024, India

A R T I C LE I N FO

A B S T R A C T

Keywords: Industrial wastewater Inverse fluidization Aerobic treatment Biofilm reactor

Recent progress on Aerobic Inverse Fluidized Bed Biofilm Reactors (AIFBBRs) used for treatment of various industrial wastewaters is discussed in this article. For the effective operation of AIFBBRs, knowledge of phase holdup, pressure gradient, phase flow rates, minimum fluidization velocity, friction factor, bubble size and rise velocity; mass & heat transfer coefficients; residence time distribution; and settled bed to bioreactor volume ratio are essential. In this regard different aspects of AIFBBRs such as static bed height and shape, size, density, & type of carrier particles have been analyzed. Knowledge of the reaction conditions (time, temperature, and pH), type of microorganisms and nutrients, concentration of pollutants, and thickness of biomass growth on carrier particles are also essential. Various literatures reveal that AIFBBRs have better operational stability and have higher organic matter removal capacity. Future research aspects of AIFBBRs are also discussed in this article.

1. Introduction Although, 71% of the Earth's surface is covered with water [1], a mere 0.4% of all water on Earth is considered to be freshwater [2]. As the demand for the freshwater increases, its shortages also increase. The declining of freshwater is further aggravated due to the discharge of untreated and/or inadequately treated industrial wastewaters into waterbodies, which creates a risk of conflict, reduces food production, hinders industrial expansion, and increases environmental as well as human health hazards [2]. Due to these adverse effects, it is essential to treat industrial wastewaters with respect to different aspects such as oil and grease; organic content (biochemical oxygen demand – BOD, chemical oxygen demand – COD, or total organic carbon – TOC); pH; temperature; specific metals; suspended solids; nitrogen; phosphorus; or indicator microorganisms [2]. Methods adopted for treating industrial wastewaters are broadly classified into preliminary, primary, secondary, and tertiary categories [3], which comprise of various physical unit operations and chemical & biological unit processes [4]. Among these methods, the secondary treatment methods have drawn much attention primarily because of their potential to remove suspended solids, fine particulates, and soluble & colloidal organics by using bacteria and microorganisms. The secondary treatment systems include stabilization ponds, land disposal systems, anaerobic reactors, activated sludge systems, and aerobic biofilm reactors [4]. Amongst different types of secondary treatment systems, the aerobic

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biofilm reactor is the most recent system. Such reactors are compact [5], resistant to temperature changes & to toxicity loads [6], and can treat wastewaters with low concentration of organic pollutants. These reactors have higher degradation rates, higher (three times or more) organic load uptake capacity, less expensive to construct, and conceptually simpler than any other secondary treatment systems [7,8]. Based on the state of biomass fixation, the aerobic biofilm reactors are grouped into: reactors with suspended biomass, mixed reactors, and reactors with fixed/attached biomass [9]. Among the several types of aerobic biofilm reactors, the fixed/attached biomass reactors with moving beds, particularly the two- and three-phase aerobic inverse fluidized bed biofilm reactors (AIFBBRs) have gained much attention in recent years, in which the solid carrier particles are made to move continuously by hydraulic means [8]. In the three phase solid-liquid-gas conventional fluidization systems, when the density of the solid particles is less than the density of the continuous liquid phase, the fluidization of solid particles can be achieved either by the upward flow of both the gas and liquid or by a combination of the upward flow of the gas along with the downward flow of liquid [10]. In these two cases fluidization of solid particles occurs in the downward direction which is termed as inverse fluidization [11]. The main advantage of AIFBBRs over fixed bed reactors is that the filter medium is not getting clogged. These reactors offer high energy performance, low pressure drop, high gas holdup, and high heat & mass

Corresponding author. E-mail address: [email protected] (A.K. Swain).

https://doi.org/10.1016/j.jwpe.2018.02.017 Received 25 October 2017; Received in revised form 23 February 2018; Accepted 25 February 2018 2214-7144/ © 2018 Elsevier Ltd. All rights reserved.


A.K. Swain et al.

Table 1 General industrial wastewater characteristics [2]. Industry type

pH

T, 0C

BOD5, mg/l

COD, mg/l

TSS, mg/l

TKN, mg/l

O&G, mg/l

N, mg/l

Others, mg/l

Slaughterhouse Tobacco Starch Distillery (molasses as feed) Paper (recycled paper as product) Brewery Soft drinks Fastfood kitchen Noodles/Vermicelli Seafood (fish) Dairy (milk) Coffee (decafinated) Chili & sayo sauce Personal care (shampoo) Pharmaceutical (antibiotics & vitamins)

6–8.5 4–5.5 6–7 3.5–4 7–9 NA 5.5–10.5 6.2–8.9 4–10 ∼6 6–8 4–6.5 4.5 6–7.3 6–7

26–34 NA NA NA 40–60 18–40 35 NA 25–30 18–25 30–40 36–42 30–45 NA NA

500–750 760–4200 2700 59000 −120000 1550 800–1600 600 300–690 410–1050 750 480 2660 5000 500–800 100–1020

2000–2500 4500–11800 41000 100000–150000 2770 1250–2550 1440 770–1550 1000–2000 1440 920 4800 10000 2000–3400 150–1820

1000 140–600 23000 1000–2000 200 150–500 45 220–580 200 350 120 1000 800 30–40 300

15–300 NA NA NA NA 25–35 NA NA NA NA NA NA NA NA NA

150–250 10–40 15 NA 10 NA 80 50–190 20–800 NA 250 20–170 NA 400 NA

10–190 NA NA 1200 NA NA 3 NA NA NA NA NA NA NA NA

NA NA 2 (phenol) NA 800 (TDS) 20–30 (PO-P4) 35 (detergent) NA 1000 (TDS) 25 (TN) 85 (TN) NA 15 (TN) NA 15–30 (TN) 20 (sulphide)

NA

Not available,

O&G

Oil and grease,

TDS

Total dissolved solids,

TKN

Total Kjeldahl nitrogen,

TN

Total nitrogen.

[38]. BOD5, TSS, oil & grease, oil (animal, vegetable, & mineral), and pH belong to conventional pollutants’ category while the nonconventional pollutants include ammonia, hexavalent chromium, COD, fluoride, manganese, organic nitrogen, phenols, TOC, etc. [38]. As many as 129 number of priority pollutants are found in the literature reported by Keith and Telliard [39]. Further, the industrial wastewaters can be categorized into physical, chemical, biological, and radiological types [38,40]. The important physical characteristics are total solids content (floating, settleable, colloidal, and matter in solution), turbidity, odour, colour, and temperature [41]. The chemical characteristics are broadly classified as organic and inorganic types. Organic components include a combination of carbon, hydrogen, and oxygen along with nitrogen in some cases, for example, carbohydrates; fats, oil, & greases; phenols; and proteins. Small quantities of surfactants, organic priority pollutants, volatile organic compounds, agricultural pesticides, sulfur, phosphorus, and iron may also be present. The important inorganic components of industrial wastewaters are pH, alkalinity, chloride, nitrogen, sulphate, sulphides, H2S, and heavy metals. Biological characteristics include various microorganisms, some of which may be pathogenic in nature. All microorganisms are not harmful – some of these decompose the organic matter by aerobic or anaerobic means and reduce the cost of wastewater treatment [42]. Radiological characteristics include the radioactive materials generated from the nuclear power plant and from the mining of radioactive materials. Some of the reported characteristic values of industrial wastewaters are listed in Table 1.

transfer rates [11]. Higher oxygen concentration in the reacting liquid, effective control of the biofilm thickness, and higher mass transfer from liquid to biofilm are observed in these reactors [12]. Some more advantages of AIFBBRs are high volumetric efficiency, long term stability, and applicability to treat low concentration pollutants [13]. Due to vigorous motion of particles, clogging & channelling of the bed is not observed and a near constant biofilm thickness is maintained due to the particle-particle-wall collisions [10]. In such type of reactors, solids’ attrition is less as the movement of particles is facilitated in liquid medium. Carryover of coated microorganisms is also found to be minimum and refluidization in case of power failure is not a problem at all [14]. As low fluid velocities are required to fluidize the lighter solid particles, power consumption is low [15]. Simplicity in operation and handling, low processing cost, and low energy consumption [16] are some more attractive features of AIFBBRs. Also, these reactors offer low mass transfer resistance, better contact among phases, larger specific surface area of solid particles, faster biofilm formation, and greater biodegradation effect [17,18]. For these above mentioned features, AIFBBRs are now a days being used for the treatment of industrial wastewaters for the removal/control of pollutants like ferrous iron [12,19], aniline [20], phenol [17,18,21–29], and sulphate [30]. Treatment of wastewaters generated from industries like brewery [10], starch [15,31–34], textile [35], sugar [36], dairy [37], steel [16], etc. have already been carried out by different researchers using AIFBBRs. In the present work, literatures published on the use of AIFBBRs for industrial wastewater treatment are reviewed.

1.2. Transport mechanisms in aerobic biofilm systems 1.1. Industrial wastewater characteristics A biofilm, as per IUPAC (International Union of Pure and Applied Chemistry) definition, is the collection of microorganisms in which cells are attached to each other and to a solid surface by a matrix of extracellular polymeric substances secreted by microorganisms [43]. As the microorganisms are attached to a solid surface, these can be retained in the reactor for a longer duration which is an essential feature for wastewater treatment systems. The attachment of microorganisms depends on the factors like cell to cell interactions, presence of polymer molecules on the solid surface, composition of the medium [44], electrostatic charge on the surface of microorganisms, pH of the solution, degree of hydrophilicity of solid surfaces, surface roughness, and flow velocities past film surfaces [45]. In the aerobic biofilm reactors with fixed/attached biomass, the biological conversions occur at first within the biofilm with the oxygen, organic matter, and nutrients getting adsorbed on the solid surfaces. These are then diffused to the interior of the biofilm through the liquid film and then through the biofilm, where the metabolic reactions occur

Industrial wastewaters are the wastewaters generated from rawmaterial processing, manufacturing, and agro-industries, in which domestic wastewater may be present. Depending on the type of industries and its raw materials, the wastewaters have varied compositions. Some of these can be easily biodegradable, organically very strong, or largely inorganic which result in large values of BOD5 (5 day BOD), COD, and total suspended solids (TSS) [2]. For this reason, the industrial wastewaters are generally deficient in nutrients. The pH values are generally between 6 and 9. Dissolved metal salts may be present in higher concentrations. The discharge of industrial wastewaters may vary with the shift nature of the operations within a factory, number of working days per week, working hours per day, operating procedures followed, raw materials processed, type and size of the industry, level of recycling, etc. [2]. The majority of pollutants found in industrial wastewaters can be grouped into conventional, nonconventional, and priority pollutants 62


A.K. Swain et al.

Fig. 1. Transport mechanisms in biofilms [8,45,112].

Knowledge on the type of microorganisms, nutrients, and thickness of biomass growth on carrier particles along with the nature and concentration of pollutants are also necessary. Other than these, knowledge on the nature and type of impurities present in the system and the reaction conditions (time, temperature, and pH) are also required to be analyzed.

by the microorganisms. Organic matters present in the wastewater in the form of colloids or suspensions, do not diffuse into the biofilm directly until they are hydrolysed to low molecular weight organic matters. Oxygen, either present in the liquid or externally fed to the reactors in bubble forms, is consumed in the biofilm till the anaerobic conditions are attained. This implies that the biofilm consists of two regions: external aerobic region and internal anaerobic region. Reduction of nitrate & sulphate and formation of organic acids occur in the anaerobic region. The metabolic products thus formed are transported in the opposite direction back to the continuous liquid phase through the biofilm [45]. The substrate donor and electron acceptor are also required to be diffused to the biofilm for the progress of biochemical reactions [8]. The transportation steps are illustrated in Fig. 1. As oxygen is mainly required for the metabolic reactions in the aerobic region of the biofilm, its transfer from liquid phase or from the rising bubbles to the interior of the biofilms is important. But its transfer faces a series of mass transfer resistances from gas bubbles to the gas-liquid interface, through the gas-liquid interface, through the liquid film at the exterior of the gas-liquid interface, in the liquid medium, through the liquid film at the exterior of the liquid-cell interface, in the liquid-cell interface, and at the reaction sites. These are illustrated in Fig. 2. All these resistances depend on factors like hydrodynamics of air bubbles, system temperature, solubility of oxygen, cellular activity, solution composition, and interfacial phenomenon [46]. The growth of the biofilm on the solid surface consists of three stages. When the film is thin all the microorganisms grow under the same logarithmic rate while the growth rates are constant when the film thickness is intermediate. But if the organic matter supply rate falls below the minimum required rate for metabolic maintenance activity, then the biofilm thickness decreases. And when the film thickness is significant, parts of the biofilm are detached from the solid surfaces [45].

2.1. Hydrodynamic characteristics The hydrodynamic characteristics of two- and three-phase inverse fluidization systems were first reported by Fan et al. [11] using lighter density solid particles. Recent progresses in hydrodynamics and process aspects of AIFBBRs were well reviewed by Arun et al. [47] & Sur and Mukhopadhyay [48] respectively. Several research articles on hydrodynamics of AIFBBRs were published and some of these studies are briefed in Table 2. Renganathan and Krishnaiah [49] developed generalized equations for predicting minimum fluidization velocities in 2- and 3-phase inverse fluidized beds which covered a wide range of variables using lighter dense particles (250–917 kg/m3) in a size range of 0.08–12.9 mm and these equations satisfactorily reduced to limiting conditions of no gas and no liquid flow predicting the experimental data. Kim et al. [50] studied the axial dispersion in a 3-phase AIFBBR. The axial dispersion coefficient (Dz) was found to increase with the increase in the superficial gas or liquid velocities (Ug or Ul) but decrease with the increase in liquid viscosity (μl). The liquid phase contacting pattern (in terms of liquid mixing) is an important factor in design and operation of AIFBBRs which can be understood by RTD studies. The liquid phase RTD, residence time, Peclet number, and dispersion coefficient in a 2phase IFB were studied by Renganathan and Krishnaiah [14] using a pulse tracer technique and deconvolution method of analysis. It was found that the Dz increases as both Ul & Archimedes number (Ar) increases and is independent of static bed height (Hs). The stochastic method of Monte Carlo simulation was satisfactorily used by Renganathan and Krishnaiah [51] to study the hydrodynamic characteristics (pressure drop, bed voidage, and minimum fluidization velocity) of 2-phase IFB under steady- and unsteady-state conditions. Sivasubramanian and Velan [52] used dimensionless correlation and a modified gas perturbed liquid model (GPLM) to predict the experimental minimum liquid fluidization velocity (Ulmf) in a 3-phase AIFBBR. It was found that, both the models predicted the experimental Ulmf data well for both Newtonian and Non-Newtonian systems. While Sivasubramanian and Velan [53] used the modified GPLM to satisfactorily predict the Ulmf for 2-phase AIFBBR for both Newtonian and non-

2. Studies on AIFBBRs Knowledge on optimized operating conditions in terms of phase holdup, pressure gradient, phase flow rates, minimum fluidization velocity, friction factor, bubble size and rise velocity, settled bed to bioreactor volume ratio; mass & heat transfer coefficients; and residence time distribution (RTD) are essential for the effective operation of AIFBBRs for industrial wastewater treatment. It is also necessary to understand the bed dynamics at first with respect to the effects of static bed height and shape, size, density, & type of carrier particles. 63


A.K. Swain et al.

Fig. 2. Resistances in transport of oxygen [46].

et al. [63] designed an IFBBR which provided high fractional conversion at high substrate flow rates. The resistance to substrate transfer into the nano-support particles was found to be negligible. Das et al. [64] developed empirical correlations to determine the bed expansion characteristics of IFB using non-Newtonian liquids as a function of physical and dynamic variables of the system. An ANN model was also developed by them for the prediction of bed height.

Newtonian liquids. Renganathan and Krishnaiah [54] studied the quality of fluidization from the root mean square (RMS) voidage fluctuation. The RMS results showed a maximum value with respect to average bed void fraction, which is independent of Hs, and increased with increase in Ar number. Sánchez et al. [55] observed that the RTD were constant at different solid phase holdup (ϵs) in a 3-phase inverse turbulent bed (ITB) indicating that the liquid mixing in the reactor was not affected by the concentration of solids and the reactor behaved like a 2-phase reactor. Howley and Glasser [56] studied the stability of inverse fluidized bed (IFB) by the growth rate of one dimensional traveling waves (1D-TW), which was found to be in the direction of fluidization. Froude number (Fr) and fluid to solid density ratio were observed to affect the stability. Bruce et al. [57] have developed a model for the prediction of hydrodynamic variables such as phase holdups, bed expansion, and pressure drop. But the major drawback of this model is that it did not include the free open area of the supporting grid as a variable. Renganathan and Krishnaiah [58] studied the unsteady void fraction characteristics of AIFBBR using particle bed model and a good agreement was found between the experimental and model predicted results. Based on a Mellin transform, Montastruc et al. [59] modelled the gas and liquid RTD in an AIFBBR. It was observed that the increase in the gas flow rate leads to higher mixing intensity of the gas phase while for a decrease in the gas velocity, the IFB was observed to perform as a plug flow reactor (PFR). The liquid phase closely performed to disperse plug flow. Campos-Díaz et al. [60] developed a new mathematical model to estimate bed porosity (ϵ) as a function of Reynolds (Re) and Ar numbers in an AIFBBR by which a standard deviation of ≤1% between experimental and calculated ϵ values was obtained. Some other advantages of this developed model were negligible wall effects, better results for spherical particles with or without biofilm, and applicability to nonspherical particles. Das et al. [61] determined the minimum inverse elutriation velocity using single and binary systems of different polymeric materials and different non‐Newtonian fluids. The minimum elutriation velocity was found to be increasing with the increase in bed height but remained practically constant with varying liquid viscosity. Wang et al. [62] simulated the flow behavior of particles in an IFB by means of two-fluid model combined with kinetic theory of granular flow. Axial velocities of particles and the expanded bed height were found to be increased with an increase of liquid velocity. Temperature was observed to be independent of the flow of particles. Using immobilized enzyme nanosilica particles, Narayanan

2.2. Mass transfer characteristics The effective operation of AIFBBRs requires the knowledge of mass transfer characteristics (gas-liquid and liquid-solid) which can be evaluated in terms of mass transfer coefficients (k), oxygen transfer rate (OTR), and liquid-solid mass transfer resistance (Φ) [18]. The mass transfer coefficient, k, from the liquid to solid phase in an AIFBBR was first studied by Nikov and Karamanev [65] as a function of Ul for different types of liquid and solid phases. The effect of Ul on k was found to be negligible. But with the increase in μl and particle density (ρs), the k values were found to decrease. Nikolov et al. [66] observed that the Ul has a negligible effect on the volumetric oxygen mass transfer coefficient (kLa) but found the values of kLa to be increasing with the increase of Ug. Kim et al. [50] studied the gas-liquid (G-L) mass transfer in 3-phase IFB and it was observed that the values of kLa to be increasing with an increase in Ug but decreased with an increase in liquid viscosity. Dolas et al. [67] developed an ANN model to predict the k values of 3-phase AIFBBR using 10 mm polyethylene (PE) hollow spheres coated with benzoic acid (BA) and observed that the developed ANN model has an accuracy of more than 90%. In a 3-phase ITB, Sánchez et al. [55] observed that the kLa values to be independent of both solid holdup and superficial liquid velocity. Kim and Kang [68] studied the hydrodynamics and heat & mass transfer characteristics of the inverse and circulating 3-phase FBRs. In the IFBRs, it was found that the kLa values increased as Ug increased but with increasing Ul the kLa values increased initially but later approached an asymptotic value with a further increase in Ul. It was also observed that the kLa values for higher density particles were higher than lower density particles. Using aqueous ethanol solution and polypropylene (PP) particles in a 3-phase IFB, Hamdad et al. [69] observed the kLa values to be increasing with increasing Ug. The kLa values in aqueous ethanol solution were found to be greater than those in water when particles were present. Again the kLa values were found to be smaller for the case without particles. Liu 64


A.K. Swain et al.

Table 2 Existing information based on hydrodynamic studies of AIFBBRs. Reactor characteristics

Particle properties

Operational conditions

Parameters studied

Effects of variables

References

L-S & G-L-S systems, Plexiglas column, ID: 0.0762 m, Hc: 2.73 m.

PE & PP spheres, dp: 4.76–19.1 mm, ρs: 388–930 kg/m3.

Ul: 0.64–6.52 m/s, Ug: 0.14–30 m/s.

Bed expansion, flow regimes, gas holdups.

[11]

G-L-S system, Plexiglas column, ID: 0.0762 m, Hc : 2.73 m.

PE & PP spheres, dp: 6.35–9.53 mm, ρs : 822–930 kg/m3.

Ul: 0.0137–0.0428 m/s, Ug: 0.001–0.18 m/s, Hs/Hc: 0.15–0.33.

Bed expansion, flow regimes, gas holdup, bed porosity, pressure drop.

G-L-S system, Plexiglas column, ID: 0.0762 m, Hc: 2.73 m.

PE & PP spheres, dp: 4.76–19.05 mm, ρs : 822–930 kg/m3. Irregular shaped EPS beads, dp: 155–185 mm, ρs: 60–400 kg/m3.

Ul: 0.0136–0.0428 m/s, Ug: 0.0034–0.085 m/s. Ul: 0–0.95 m/s, Ug: 0–0.56 m/s.

Friction factor, pressure gradient, gas holdup.

G-L-S system, Perspex column, ID: 0.0753 m, Hc: 1.795 cm.

PP spheres, dp: 0.0125-0.0199 m, ρs : 135–947 kg/m3.

Ul: 0–0.0281 m/s, Ug: 0–0.12 m/s, Hs: 0.195–0.80 m.

Pressure gradient, minimum liquid fluidization velocity.

L-S system, Glass column, ID: 0.08 m, Hc : 1.34 m.

EPS & PE spheres, dp: 0.0023-0.0072 m, ρs: 96–930 kg/ m3.

Bed expansion, pressure drop.

G-L-S system, Altuglass column, ID: 0.17 m, Hc: 2.5 m (total height).

PP spheres, dp: 0.004–0.006 m, ρs : 862–877 kg/m3.

L-S system, Perspex column, ID: 0.0753 m, Hc : 1.795 m.

dp: 0.0125–0.02 m, ρs: 126–534 kg/m3.

Water & PEG solutions, μl: 0.001–0.003 kg/ m.s, ρl: 1000–1050 kg/m3, Hs/D: 1–5. 5% NaCl solution, Air: 1 atm & 200C, Liquid: 28 ± 0.20C. Ul: 0.02–0.15 m/s, Hs: 0.23–0.79 m.

Δpd ↑ with Ul till a break point then Δpd ↓ as Ul ↑ in liquid as continuous phase. In gas as continuous phase, ϵl ↑ as Ul or Ug ↑. ϵ ↑ as Ug ↑ till constrained fluidized condition then ϵ ↓ and then ↑. For a given Ug, ϵ ↑ with Ul in nonconstrained cond. ϵg ↑ with Ug. In bubbling fluidized regime: at constant Ul, ϵg ↑ & ϵl ↓ as Ug ↑ while at constant Ug, ϵ ↑ with Ul. At a certain Hs/Hc & Ul, ϵ ↑ with Ug, but as Ul ↑, Ug ↓ for same ϵ. In transition regime: ϵ ↓ as Ug ↑. In slugging regime: ϵ ↑ with Ug. In constrained regime: ϵg ↑ as Ul↓. ϵg ↓ as ϵs & Ul ↑ and as Ug ↑. Δpd ↓ as Ul ↑ prior to semi-fluidization. After this Δpd ↑ with Ul. ϵg ↑ with Ug. Fluidized bed condition, reduction in liquid circulation velocity, & increase in bubble residence time contributes to higher ϵg. ϵg ↓ as Ul ↑. Ul varies with Ug0.4. Δp per unit bed length ↑ with Ul, reached maximum at fluidization state, then decreased as bed expanded. Ulmf ↓ as Ug ↑. Ulmf was independent of Hs. As Hs/D increased, Δp increased with Ul till fluidization, then remained constant with Ul. ϵ ↑ with Ul for different μl.

G-L-S system, PVC column, ID: 0.08–0.38 m, Hc: 1.7–3.8 m

PE spheres & discs, dp: 0.0038-0.0045 m, ρs: 914–934 kg/ m3.

Ug: 0.0053-0.0242 m/s, Hs/Hc: 10–60%, ϵs: 0.05–0.34.

Bed expansion, pressure drop, Ug.

L-S system, Perspex column, ID: 0.1 m, Hc: 1.8 m.

LDPE & PP spheres, dp: 0.006 m, ρs: 830–940 kg/m3.

Bed expansion, pressure drop, Ulmf.

G-L-S system, PVC column, ID: 0.1–0.25 m, Hc: 1.5–5 m.

PP pellets & spheres, dp: 0.175–4 mm, ρs: 690–920 kg/m3. R1: LDPE oblate beads, dp: 0.00386 m, ρs: 930 kg/m3, R2: ρs :903–930 kg/ m3.

Hs: 0.06–0.27 m, Water & CMC solutions (0.1–0.4 wt.%), ρl : 1033–1048 kg/m3. Hs/Hc: 15–75%, T: 23 ± 10C, Ug: 0.001–0.015 m/s. R1: aeration, Hs/Hc: 10–40%, R2: centrifugal force.

G-L-S system, Acrylic tubes, ID: 0.15–0.22 m, Hc: 1.5 m, V: 24–56 l.

G-L-S system, R1: acrylic column, ID: 0.107 m, Hc: 0.5 m, R2: Pyrex column, ID: 0.16 m, Hc: 0.413 m.

G-L-S system, Plexiglass column, ID: 0.17 m.

PP hollow spheres, dp: 0.004–0.006 m, ρs: (862–877) ± 25 kg/m3.

G-L-S system, Duran glass, ID: 0.2 m, Hc : 6 m.

PP KMT® particles, ρs: 910 kg/m3, Specific surface area: 400 m2/m3.

Hs: 0.25–0.29 m, T: 28 ± 0.20C, NaCl, Na2HPO4, BA, IAA were used to have different μl. Vb/Vr: 0.3–0.7, Mbp: 0–29 mg/particle, T: 28–300C, pH: 6.5–7.0, Qg: (1–2) x10-2 m3/s, Ql: (2–40) x 10-5 m3/s.

Bed expansion, gas holdup, liquid circulation velocity.

[88]

[89]

[90]

[91]

[92]

Bed expansion, pressure drop, phase holdup.

Δpd ↓ as Ul ↑ till Ulmf, then increased with Ul. Ulmf ↓ as Ug or Ul. ∈ ↑ with Ul.

[93]

Bed expansion, pressure drop.

Δp ↑ with Ul till bed was fluidized and then remained constant. As ρs ↓, Δp ↑. Hb/Hs ↑ with Ul and was independent of Hs. Δp ↑ & ϵs ↓ as Ug ↑. Critical gas velocity was dependent on type of particles and independent of Hs/Hc, initial liquid height, & ID. Ug for total expansion of particles and homogeneous axial solids distribution ↓ with increase in ρs and Ws. Hb remained constant till Ulmf, then increased linearly for different Hs & ρs. As ρs ↓ Ulmf ↑. Δp ↑ with Hs & CMC conc. and ↑ as ρs decreased. Ulmf ↓ with increase in ρs and CMC conc. Δp & ϵg increased with Ug.

[94]

Flow regimes, bed expansion, pressure drop. Bed expansion, pressure drop, phase hold up.

Phase holdup, Ulmf.

Phase holdup, Ugmf.

[95]

[96]

[97]

Δp ↑ with Ug. ϵg in 2-phase region suddenly increased before fluidization, while ϵg in 3-phase region slightly decreased at critical fluidization point. Ugc decreased as particle loading increased. ϵs decreased as Ug increased. Addition of NaCl & BA increased ϵg. For larger bubble slip velocities, additives reduced ϵg. Ulmf decreased as Ug increased with addition of inhibitors.

[98]

For any Mbp, Ugmf ↑ with Vb/Vr. Ugmf decreased with an increase in Mbp. Vb/ Vr decreased as Mbp increased. For any Vb/Vr and Mbp, ϵg ↑ with Ug. After an optimal Vb/Vr, ϵg decreased as Ug increased.

[100]

[99]

[101] (continued on next page)

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Table 2 (continued) Reactor characteristics

Particle properties


Parameters studied


L-S system, Perspex column, ID: 0.094 m, Hc: 1.8 m.

PP & LDPE particles, dp: 0.004–0.008 m, ρs: 830–940 kg/m3.

Aq. CMC solutions: 0.1–0.3 (wt.%), ρl: 1033–1048 kg/m3.

Bed expansion, pressure drop, friction factor, Ulmf.

L-S & G-L-S system, Plexiglas column, ID: 0.127 m, Hc: 2.74 m.

PE spheres, dp: 0.0058 m, ρs: 910–946 kg/m3, Ws: 3.5 kg.

Water & water plus 50 ppm of a wetting agent, Hs: 0.5–0.54 m, Ul: 0–0.0264 m/s, Ug: 0–0.0165 m/s.

Pressure drop, gas holdup, ϵmf, Ulmf.

G-L-S system, IDR: 0.044–0.1 m, IDD: 0.064–0.1 m.

Ovipan spherical beads, dp: 0.002–0.0065 m, ρs: 72–815 kg/m3. PE spheres, dp: 0.0038 m, ρs : 910 kg/m3.

Hs: 0.15–0.8 m.

Liquid circulation velocity.

Ug: 0.004–0.015 m/ s, ϵs: 0.036–0.59.

Collision frequency, particle pressure.

Ul: 0–0.07 m/s, Ug : 0–0.008 m/s.

Phase holdup, pressure gradient, Ulmf.

Ug: 0.0075–0.04 m/ s.

Phase hold ups, Ugc.

Ulmf ↑ with dp. Ulmf increased as ρs and CMC conc. decreased. Ulmf was independent of Hs. f increased with Ws and μl. For 2-phase: ϵg ↑ with Ug. Dimensionless Δp ↓ initially as Ul ↑, then ↑ gradually beyond Ulmf. Δpf ↑ linearly with Ul and remained constant beyond Ulmf. For 3-phase: Ulmf ↓ as Ug ↑ . For any dp & ρs, Ulmf ↓ higher in absence of a wetting agent. ϵg ↑ & ϵl ↓ as Ug ↑. ϵmf ↓ steeply as Ug ↑ then ↑ gradually. For a given Ws, ϵg ↑ as ρs ↓. Liquid circulation velocity ↑ with Ug for various Hs, but as Hs ↑ liquid circulation velocity ↓. CF ↑ with ϵs/ϵs0 then leveled off then decreased at higher ϵs/ϵs0. CF ↑ with Ug & ϵs. Pp ↑ with ϵs/ϵs0 & Ug but decreases at higher ϵs/ϵs0. Δp ↓ as Ul ↑, minimum at Ulmf. Ulmf ↓ as Ug ↑. As Ug increases ϵg ↑, ϵl ↓, & liquid interstitial velocity ↑. As ρs ↓, Δp ↑ and Ulmf ↑ for increase in Ug. Both ϵg & ϵl ↑ with Ul or Ug. ϵs ↓ & ϵg ↑ as Ug increased both for hydrophobic & hydrophilic particles. As Hs/Hb & ρs ↑, Ugc ↓.

Water & aq. CMC solution (0.1-0.3 wt. %), μl: 0.000961–0.038 kg/m.s, ρl : 1000–1003 kg/m3. Glycerol: 30–50%, ρl: 1056–1107 kg/ m3, μl: (1.94-3.74) x10-3 kg/m.s, CMC: 0.1–0.3 wt.%, ρl : 1033–1046 kg/m3. Ul: 0–0.0357 m/s, Ug: 0–0.0157 m/s.

Axial dispersion coefficient

Dz ↑ with Ug or Ul, but decreased as μl increased.

[50]

Ulmf.

Ulmf ↑ as dp ↑ and ρp ↓. Δp per unit length ↑ with Ul till Ulmf then decreased. Ulmf ↓ as Ug ↑. As wt% of CMC ↑, Ulmf ↓ at a given Ug. Ulmf ↓ as Ul ↑ and with addition of viscous liquid and with increasing conc. Ulmf ↓ as Ug ↑. ϵl ↑ & ϵs ↓ along the length of the bed. ϵg is uniform throughout the bed. As Ug ↑, ϵs remained constant after full bed expansion, ϵl ↑ to a maximum & then ↓, and ϵg ↑ continuously. As Ws ↑, ϵg & ϵl ↓ and ϵs ↑. Surfactant reduced Ug to fluidize, surface mobility, & bubble rise velocity while ϵg ↑. db ↑ with Ug, Ul, & μl. Rising velocity ↑ with Ug & μl but ↓ as Ul increased. Frequency of bubbles ↑ with Ug & Ul but ↓ as μl increased.

[52]

G-L-S system, PVC column, ID: 0.1 m, Hc: 1.5 m.

L-S & G-L-S system, Acrylic column, ID: 0.152 m, Hc: 2.5 m.

G-L-S system, Acrylic column, ID: 0.115 m, Hc: 2 m.

G-L-S system, Acrylic column, ID: 0.152 m, Hc: 2.5 m.

PE & PP beads, dp: 0.004 m, ρs: 877.3–966.6 kg/m3, Contact angle: PP 840 & PE 850. LDPE & MDPE particles, dp: 0.0044 m, ρs: 926–940 kg/ m3. PE & PP beads, dp: 0.004 m, ρs: 877.3–966.6 kg/m3, Contact angle: PP 840 & PE 850.

G-L-S system, Perspex column, ID: 0.1 m, Hc: 1.8 m.

LDPE & PP particles, dp: 0.004–0.008 m, ρs: 830–940 kg/m3.


Spherical particles, dp: 0.0061 m, ρs : 917 kg/m3. PP particles, dp: 4 mm, ρs: 880 kg/ m3.



PE & PP beads, dp: 0.004 m, ρs: 877.3–966.6 kg/m3.

G-L-S system, Acrylic column, ID : 0.152 m, Hc: 2.5 m.

PE & PP beads, dp: 0.004nm, ρs: 877.3–966.6 kg/m3.

G-L-S system, Plexiglas column, ID : 0.284 m, Hc: 1.7 m.

HDPE particles, dp: 243 μm, ρs : 881.6 kg/m3. PE & PP beads, ρs: 877.3–966.6 kg/m3.


L-S system, Perspex column, ID: 0.047–0.072 m, Hc: 1.5–1.89 m.

LDPE, HDPE, & PP (spherical, cylindrical, disc) particles, dp:

Pressure drop, Ulmf, Ugmf, phase holdups.

Tap water & 0.5% wt aq. ethanol solution, Ul: 0–0.0278 m/s, Ug: 0–0.051 m/s, Ws: 0–7.9 kg. Aq. CMC solution, μl : 0.001–0.038 kg/ m.s, ρl : 1000–1003 kg/m3, Ul: (1–5)x10-2 m/s, Ug: (0.05-0.8)x10-2 m/s. Aq. CMC solution, μl: 0.001–0.038 kg/ m.s, ρl: 1000–1003 kg/m3. Ul: 0.03–0.05 m/s, Ug: 0.006–0.19 m/s, Ws: 5–15 vol%. Aq. CMC solution, μl: 0.001–0.038 kg/ m.s, T: 25 ± 0.50C.

Phase holdups.

Aq. CMC solution, Conc.: 0.2–0.8 kg/ m3, ρl:

Pressure drop, Ulmf.

66

Bubble size, rising velocity, frequency.

F, DP, exiting rate of media particles.

ϵg, bubble size, rise velocity. Phase holdups, bed porosity.

F & DP ↑ with Ug or Ul but ↓ as μl increased. F & DP for higher density particles exhibited higher values than that of lower ρs. ϵg ↑ with Ug, Ul, or Ws. db & Ub ↑ with Ug but decreased as Ul & Ws increased.

References

[102]

[103]

[104]

[74]

[105]

[106]

[69]

[107]

[108]

[70]

[109] ϵg ↑ with Ug, Ul, or ρs but ↓ as Ul increased. ϵl ↑ with μl. ϵs ↓ as Ug, Ul, or μl increased. ϵs for low density particles was higher than high density particles. ϵ ↑ with Ug, Ul, or μl. [110] Δp ↑ with Ws. Ulmf ↓ as CMC conc. increased and is independent of Ws. As column ID ↓, Ulmf remained almost constant but Δp increased. As % of (continued on next page)


A.K. Swain et al.

Table 2 (continued) Reactor characteristics

Particle properties


(3.13–5.64)x10-3 m, ρs: 900–944 kg/m3.

1001.69–1003.83 kg/m3, Ws: 0.2–1.0 kg for single sized particles & 0.5 kg for binary mixture of 20–80% ratio, T: 28 ± 20C. Glycerol conc.: 30–70%, ρl: 1056–1132 kg/m3, μl: (1.94–9.35) x 103 kg/m.s, Aq. CMC solution, Conc.: 0.1–0.3 wt%, ρl: 1033–1046 kg/m3. Hs: 0.2–1.0 m, HRT: 6–40 h, Ug: 0.00106–0.00318 m/s. Ug: 0.089–0.281 m/ s, Vb/Vr: 0.1–0.25, T: 280C, pH: 6.5, Phenol conc: 1200 mg/l.

G-L-S system, Perspex column, ID: 0.1 m, Hc: 1.8 m.

LDPE & PP particles, dp: 0.004–0.008 m, ρs : 830–940 kg/m3.

G-L-S system, Perspex column, ID: 0.1 m, Hc: 1.8 m, V: 0.0125 m3.

PP particles, ρs : 870 kg/m3, Surface area: 524 x 10-6 m2 per particle. PS beads, dp: 0.0035 m, ρs: 863 kg/m3, Surface area to volume ratio: 1.714 × 103 m2/m3.

G-L-S system, Aspect ratio: 10:1, ID: 0.01 m, Hc: 0.105 m, V: 0.0056 m3.

Parameters studied


References

lighter density particles ↑, Ulmf increased gradually but at higher %, Ulmf decreased.

Phase holdups, porosity.

ϵg & ϵ ↑ with Ug. ϵs & ϵl ↓ as Ug increased for a fixed Ul. ϵl ↑ with Ul. ϵg ↑ with increase in particle diameter. ϵg ↑ and ϵl ↓ with the variation in conc. of glycerol or CMC.

[111]

Umf, ϵg.

Ulmf was 0.000148 m/s. Ulmf was independent of Hs. Optimum ϵg was 0.4849 achieved at Hs = 0.8 m and Ug = 0.002548 m/s. Optimum Vb/Vr was 0.2. ϵg and db ↑ with Ug. Aspect ratio ↑ with Hs. Optimized Ug ↑ with aspect ratio. Δp ↑ with velocity and height of column until it reached Ugmf, after which Δp became constant. ϵg ↑ with Ug. At higher particle loading, ϵs increased.

[86,87]

Phase holdups, pressure drop, aspect ratio.

[17]

Collision frequency, DP Particle dispersion coefficient, f Friction factor, F Fluctuating frequency of fluidizing particles, Hb Total bed height (static and fluidized), IAA isoamyl alcohol, ID (= Internal column diameter, IDD and IDR Internal downcomer and riser diameters, LDPE Low density polyethylene, Mbp Biomass of cells per particle, PEG Polyethylene glycol, Pp Collision particle pressure, Qg Air/gas flow rate, Ql Liquid flow rate, R1 & R2 Reactors 1 & 2, S Solid phase, Ub Bubble rise velocity, Ugc Critical gas fluidization velocity, Ugmf Minimum gas fluidization velocity, Ws Weight of solids, Δp Pressure drop, Δpd Dynamic pressure gradient, Δpf Frictional pressure drop, ϵl Liquid phase holdup, ϵmf Voidage at minimum fluidization condition, ϵs0 Fixed bed solid phase holdup, ↑ Increasing, ↓ Decreasing, ρl Density of liquid. CF

D)

intraparticular diffusion due to low η values. While for larger particles, as η values were high the degradation was mainly controlled by chemical reactions. Also with the increase in biofilm thickness, the η values were found to increase. Further, η values were found to decrease with the increase in biofilm dry density. Higher biofilm dry density provided higher mass transfer resistance and hence low values of η [18]. Using nanosilica particles in an AIFBBR, Narayanan et al. [63] observed negligible resistance to substrate transfer into the nano-support particles. This was due to very large specific surface of nano-sized particles for which the η values for different kinetic equations and for wide range of substrate concentrations were unity.

et al. [70] used a modified internal airlift loop reactor and found the kLa values to be increasing with increasing Ug and Ul, while it decreased slightly with increasing solid loading. Using various Newtonian and non-Newtonian fluids, Sivasubramanian [71] observed the kLa values to be increasing with increase in particle diameter, decreasing with increase in solid loading, and decreasing with the addition of organic additives. Fahim et al. [72] used Bacillus subtilis to produce biosurfactant in a 3-phase AIFBBR which reduced the surface tension as a result the kLa values decreased. Oxygen transfer was found to increase upto 175% and upto 24% with the increase of Ug and Ul respectively. It was also observed that the oxygen transfer obtained (kLa upto 0.015/s) was higher than any other bioreactors used for biosurfactant production. A correlation was also developed based on dimensional analysis which could help in scale-up of biosurfactant production. Haribabu and Sivasubramanian [73] using a non-Newtonian (xanthan gum) fluid observed similar effect of Ul & Ug, solid loading, and concentration of xanthan gum on the kLa values as previously observed by Sivasubramanian [71] for aqueous carboxy methyl cellulose (CMC) solutions. Using polystyrene (PS) beads in an AIFBBR, Begum & Radha [18,28] observed the kLa values to be increasing with particle size (dp) and then decreasing. With the increase of Ug, both kLa and OTR were found to increase initially, then decrease for a short while, then again increase, and reached a constant value. Higher Ug produced bubbles of higher size (db) which dominated over the gas phase holdup (ϵg) values thereby decreasing the values of kLa and OTR. Mass transfer resistance is expressed in terms of effectiveness factor (η) and substrate diffusivity (De). Due to dense and stable biofilm on smaller sized particles, substrate diffusion into the biofilm was difficult. Thus De and η values were low and hence mass transfer resistance was high. While for larger particles with less dense and loosely packed biofilm, De and η values were high and hence mass transfer resistance was low. For smaller sized particles the degradation was mainly due to

2.3. Heat transfer characteristics Because the liquid viscosity is highly temperature dependent, the knowledge of heat transfer is a crucial factor for the industrial applications of AIFBBRs. The heat transfer characteristics of AIFBBRs were first studied by Cho et al. [74] in 2- and 3-phase fluidized beds using PE and PP beads. It was observed that the heat transfer coefficient (h) for higher density particles was higher than that of lower density particles. The h values were found to increase with Ug. It exhibited a maximum value with increasing Ul or ϵ. The Ul at which h was found to be maximum, decreased with increasing ρs or Ug. Kim and Kang [68] found the h values to be increasing with Ug in the AIFBBRs which is due to more vigorous bubbling caused by higher ϵg and turbulence and a similar phenomenon was also observed by Myre and Macchi [76]. The h values exhibited a maximum with increasing Ul which is due to decrease in ϵs at higher Ul. Heavier particles were found to be more effective for the heat transfer than the lower density particles which are due to their bubble breaking capability and frequent contacting with heater surfaces. Using PE and PP spheres and plates in pure water and aqueous solutions of CMC in 3-phase IFB, Son et al. [75] observed the h 67


A.K. Swain et al.

values to be increasing with increasing Ug or ρs but it decreased with increasing μl, whereas it was maximum with the variation of Ul or ϵ and the same had been observed by Cho et al. [74]. Further, Myre and Macchi [76] observed that the h values were reduced with the addition of surfactant which was due to the decrease of the amount and size of larger bubbles. At low ϵs the h values were found to be higher compared to h values at higher ϵs.

qs =

(2)

where, S is the residual substrate concentration of the solution. For some enzymatic reactions, the substrate may inhibit the cell growth and its own utilization under higher substrate concentrations. Various substrate inhibition kinetic models such as Haldane, Aiba, Teissier, Webb, and Yano and Koga are available to test with the experimental data [25]. For phenolic substrate, Begum & Radha [26,29] observed the Haldane equation to be fitted well both for μ and qs on the basis of highest correlation coefficient (R2) and the lowest root meansquare error (RMSE) values. The Haldane model equations are defined as

2.4. Biofilm and biomass characteristics The evaluation of biofilm and biomass characteristics are based on biofilm thickness and dry density, suspended and attached biomass concentration, COD, substrate removal efficiency, particle density [25–29], and superficial gas velocity [27,28]. Larger biofilm thicknesses on the particle surfaces do not enhance the degradation of wastewater rather limit the transfer of substrate and oxygen to the interior of the biofilm, which causes the detachment of the biofilm pieces leading to improper bioreactor performance. Therefore, the biofilm thickness should be maintained at such a value that the diffusional limitations are minimum. Karamanev and Nikolov [13] observed the optimal biofilm thickness to be 100 μm. The biofilm thickness and particle density were found to decrease while the biofilm dry density and suspended biomass concentration were found to increase with increasing Ug. All these are related to the COD removal efficiencies, which increased till a critical Ug is reached. However, above critical Ug the reverse happened [27,28]. Biofilm thickness gets affected by particle size which increased as particle size decreased. For smaller particle sizes, the thinner biofilms were advantageous in AIFBBRs contributing to higher COD removal efficiencies as they were more stable and dense [27]. Campos-Díaz et al. [60] observed that the attachment of biofilm on particle surface was due to clusters of microorganism agglomerates. Suspended biomass concentration in the bulk continuous liquid phase was found to be increasing during the initial period of degradation due to the attrition of biofilm and then it was decreasing steadily due to the reattachment of biomass on solid particles and substrate inhibition effect [26,29]. This concentration was found to decrease with the increase in solid particle sizes having thicker biofilms and vice-versa [27]. As the suspended biomass concentration decreased over the degradation period, the COD values were found to decrease proportionately with decreasing substrate concentration. This was due to the high tolerance of biofilms to higher substrate concentrations and constant biofilm thickness [26,27]. Due to the formation of less dense biofilm on the solid particles, the attached biomass concentration was found to decrease initially. As the degradation proceeds, the attached biomass concentration was found to increase due to stable and dense biofilm. For smaller sized solid particles, the attached biomass concentration was found to be higher due to thin, stable, and dense biofilm and vice-versa [27]. The COD removal efficiencies were found to be proportionately dependent on the attached biomass concentration [28].

μ = μmax

S Ks + S +

S2 Ki

(3)

and

qs = qsmax

S Ks + S +

S2 Ki

(4)

where, μmax is the maximum specific cell growth rate, qsmax is the maximum specific substrate degradation rate, Ks is the substrate affinity constant, and Ki is the substrate inhibition constant. When compared with other models, the Haldane model kinetic parameters such as Ki was found to be highest and Ks was found to be lowest for suspended biomass culture with respect to μ and qs [26,29]. For the attached biomass (biofilm) systems as the microorganisms were made to adapt well with higher substrate concentrations, both μ and qs were found to increase with initial substrate concentrations. Therefore, the non-inhibitory Monod model equations were used which are defined as

μ f = μ fmax

S Ks + S

(5)

and

qsf = qsfmax

S Ks + S

(6)

where, μfmax and qsfmax are the maximum specific cell growth rate and the maximum specific substrate degradation rate for the biofilm systems respectively. The R2 values with respect to μ and qs for Monod model were found to be higher than Haldane model indicating that the non-inhibitory Monod model fitted well with the experimental data. Also it was found that the Monod model kinetic parameter Ks was lower than that for Haldane model indicating that the microorganisms had a greater affinity towards phenolic substrate [26,29]. 3. Treatment of industrial/synthetic wastewater using AIFBBRs The application of AIFBBRs in treatment of industrial wastewaters by biological means over traditional methods has already gained much popularity in recent years, to treat a variety of toxic pollutants and industrial effluents which have been studied by many researchers. Reactors having varied geometry have been used under different operational conditions. Some of the reported operational conditions and performance of AIFBBRs for industrial wastewater treatment are briefed in Table 3 for future operational strategies and for a sustainable system.

2.5. Degradation kinetics The substrate degradation behavior can well be understood from (i) cell growth and substrate degradation kinetics, (ii) substrate inhibition kinetics for suspended biomass, and (iii) kinetic model for attached biomass (biofilm) systems [26,29]. The specific cell growth rate for batch systems (μ) is defined as

1 dX μ= X dt

1 dS X dt

3.1. Glucose solution Synthetic aqueous solutions of glucose (0.4–12 g glucose/l) were treated by Nikolov and Karamanev [12] in a draft tube type of AIFBBR by a mixed bacterial culture of aerobic heterophobic microorganisms using PE granules as biomass support particles. Under the experimental conditions of 60 l/h as gas flow rate, 3.2–18.2/h as dilution rates, and at 28–29 °C, the reaction rate at 90% conversion was found to be 80 mg

(1)

where, X is the cell concentration (dry). While the specific substrate degradation rate for batch systems (qs) is defined as 68


A.K. Swain et al.

Table 3 Operational conditions and performance of AIFBBRs for industrial wastewater treatment. Wastewater Sample

Microbes used

Glucose solution

Mixed bacterial culture of aerobic heterophobic microorganisms

Aqueous solution of FeSO4

Thiobacillus ferrooxidans

Reactor characteristics & particle properties V: 0.0017 m3, ID: 0.065 m, IDd: 0.03 m, PE granules: (Vp: 300 x 10-6 m3, dp: 0.002–0.003 m).

V : 0.0017 m3, ID: 0.065 m, IDd: 0.03 m, EPS spheres: (Vp: 400 x 10-6 m3, dp: 0.0008–0.001 m). V: 0.0017 m3, ID: 0.065 m, IDd: 0.03 m, EPS spheres: (Vp: 240 x 10-6 m3, dp: 0.0009 m, ρs : 330 kg/m3).


Effect of treatment/Performance

References

Glucose conc.: 0.4-12 g/l, Qg: 1.67 x 10-5 m3/s, Dilution rate: 3.2–18.2 /h, T: 28–29 0C.

Reaction rate at 90% conversion was 80 mg glucose consumed/l.h. Maximum rate was 1000 mg/l.h. AIFBBR was 3.6 times more effective at a glucose conversion of 90% compared to basic draft tube airlift reactor. At 70% conversion, AIFBBR was 4.4 times more effective and 10 times higher in maximal Fe2+ uptake compared to draft tube reactor (without EPS spheres). Substrate conversion decreased by 15% below 220C and decreased by 17% with complete range of outlet Fe3+ concentration. In pH range of 1.3–2.2, as fixed volume of support particles increased about 70%, conversion increased by 43%. Over a retention period of 10 h, BOD and COD conversions were 96 and 56% respectively. These AIFBBRs have nearly 17 times higher efficiency in comparison with mechanical surface aeration equipments. In batch cultivation of pseudomonas aeruginosa in aniline medium (2 g/l as initial conc.) rate of degradation was 1.8 times higher compared to reactors without carrier particles. In case of pseudomonas putida in continuous mode maximum degradation rate was 0.07 g/ l.h. Largest COD removal was obtained when the reactor was operated at Vb/ Vr = 0.5 and Ug = 0.018 m/s. 70% and 90% COD removal were achieved for raw wastewater and wastewater enriched with nutrients respectively. For inlet phenol concentrations of 59 and 80 mg/l, the maximum biological degradation were 180 and 170 mg/l.h at dilution rates of 3.6 and 2.4 /h respectively. For 1200 mg/l phenol, at Ul = 0.071 m/ s total degradation time was 70 h. For 2400 and 3000 mg/l, degradation started after 1 and 3 days respectively while for 3500 mg/l, degradation could not be started even after 10 days. Effluent pH reduced to 7.3 from 8.6. Largest COD removal (84%) occurred at Vb/Vr = 0.55, Qg = 1.11 x 10-5 m3/s, and 62 h of time. BOD and TSS removal at these conditions were 59 and 28% respectively. COD removal efficiency was 97.9% with complete degradation of phenol occurred at the end of 110 h.

[12]

Fe2+ conc.: 3–4 g /l, Qg: 1.67x10-5 m3/s, Dilution rate : 3.2–18.2 /h, T : 28–29 0C. Fe2+ conc.: 3.5–4 g /l, Qg: 5 x 10m3/s, Dilution rate: 1.08 /h, Inoculum: 10% of reactor volume, pH : 1.8–2.0, T: 27 0C.

6

V: 0.0017 m3, ID: 0.065 m, IDd: 0.03 m.

–

Aniline

Pseudomonas putida and Pseudomonas aeruginosa

ID : 0.1 m, Hc: 1.5 m, EPS beads: (dp: 0.0035 m, ρs: 650 kg/m3).

Ul: 0.0001–0.04 m/s, Ug : 0.01–0.1 m/s, T: 320C, Different amounts of solvent, glue, and adsorbent to improve the surface of EPS particles.

Brewery wastewater

Activated sludge from a biological treatment plant operated at the brewery

ID: 0.2 m, Hc: 6 m, KMT® PP particles: (ρs : 910 kg/m3, Specific surface: 400 m2/ m3).

Ug: 0.003–0.058 m/s, Vb/Vr: 0.45–0.60, pH: 6.5–7.0, T: 28–30 0C.

Phenol

Microbial consortium obtained from a contaminated site soil sample

V: 0.0009 m3, ID: 0.065 m, EPS spheres: (Vp: 0.0003 m3, ρs : 800 kg/m3, dp: 0.0008–0.0016 m).

Phenol conc.: 30–350 mg/l, Ql : (0.0138–1.8) x 10-6 m3/s, Qg : 7.22 x 10-5 m3/s.

Pseudomonas putida

V: 0.004 m3, ID: 0.3 m, Hc : 0.786 m, EPS beads: (dp: 0.001–0.00118 m, ρs: 713 kg/m3).

Phenol conc.: 500–3500 mg/l, Qg: 0.000017 m3/s, Solids loading: 11%.

Pseudomonas aeruginosa

ID : 0.1 m, Hc: 1.24 m, PP spheres: (dp: 0.008 m, ρs: 870 kg/m3).

T: 28–30 0C, Vb/Vr: 0.5–0.6, Hs: 0.45–0.6 m, Ql: (1.1–2.7) x 10-5 m3/s, Qg: (0.47–1.4) x 10-5 m3/s.

Pseudomonas fluorescence

Aspect ratio: 10:1, V: 0.0056 m3, ID: 0.1 m, Hc : 1 m, PS beads: (dp: 0.0035 m, ρs: 812 kg/m3). V: 0.0056 m3, ID: 0.1 m, Hc: 1 m, PS beads : (dp: 0.0035 m, ρs: 863 kg/m3, Surface to volume ratio: 1.714 × 103 m2/m3).

Phenol conc.: 600 mg/l, T: 300C, pH: 7.

Same as [26]

Phenol conc.: 400–1200 mg/l, T: 280C, pH: 6.5, Vb/Vr: 0.1, Ug: 0.095 m/s.

Phenol conc.: 1200 mg/l, T: 280C, pH: 6.5, Vb/Vr: 0.1–0.25, Ug: 0.089–0.281 m/s.

100% phenol degradation occurred for all initial concentrations of 400–1200 mg/l and final COD values were 19.87–121.69 mg/l respectively. Mean biofilm thickness, dry density, and average specific density obtained were varied between 137–141 mm, 82.9–83.8 to 120.3–130.4 kg/m3, 866–867 to 885–886 kg/m3 respectively. 100% phenol degradation and 98.5% COD removal occurred at Vb/Vr = 0.20, Ug = 0.220 m/s, ϵg = 0.0653, and 48 h of operation. COD removal efficiency increased till a particle aspect ratio of 1.787 then decreased.

[12]

[19]

[77]

[20]

[10]

[21]

[22]

[16]

[25]

[26,29]

[17]

[27,28] (continued on next page)

69


A.K. Swain et al.

Table 3 (continued) Wastewater Sample

Refinery wastewater

Microbes used

Activated sludge obtained from refinery operated biological treatment unit

Reactor characteristics & particle properties V: 0.0056 m3, ID: 0.1 m, Hc: 1.05 m, PS beads: (dp: 0.0029–0.0038 m, ρs : 619–926 kg/m3, Surface to volume ratio: 1660–2068 m2/m3). ID: 0.2 m, Hc: 6 m, PP particles: (ρs: 910 kg/m3, Specific surface: 400 m2/ m3).


Effect of treatment/Performance

Phenol conc.: 1200 mg/l, Vb/Vr: 0.2, Ug: 0.216–0.244 m/s, Hs: 0.1787 m.

Largest COD removal of 98.5% was observed for 3.5 mm particles at Ug = 0.220 m/s and 48 h of operation.

Vb/Vr: 0.45–0.60, pH: 6.5–7.0, T: 28–300C.

Largest COD removal (90%) was obtained at Vb/Vr = 0.55 and Ug = 0.029 m/s.

[80]

Vb/Vr: 0.50–0.60, pH: 6.5–7.0, T: 28–300C

Largest COD removal (98%) obtained at Vb/Vr = 0.55, Ug = 0.041 m/s, and t = 45 h. At Vb/Vr = 0.55, Ug = 0.036 m/s, and t = 50 h, conversions greater than 99% were achieved for all phenolic constituents of the wastewaters. Conversions of 90% were attained for other hydrocarbons. Largest COD removal (98%) was obtained at Vb/Vr = 0.55, Ug =0.021 m/s, and t = 25 h. Largest COD removal (95%) obtained at Vb/Vr = 0.55, Ug=0.024 m/s, and t = 30 h. Largest COD removal (96%) was obtained at Vb/Vr = 0.55, Ug = 0.046 m/s, and t = 65 h. Conversions greater than 95% was obtained for all phenolic constituents of the wastewaters and about 90% conversions were attained for all other hydrocarbons. Biotransformation rates were oxygen limited. For phenol to 4-cp ratio of 8:1 and Ug > 0.1 m/s, biodegradation was not oxygen limited. Maximum COD reduction occurred at Hs = 0.8 m. Optimum COD removal was 93.8% occurred at an initial substrate concentration of 2250 mg/l and for the HRT of 24 h.

[81]

4-chlorophenol

Pseudomonas putida

V: 0.004 m3, ID: 0.03 m, Hc: 0.786 m, EPS beads: (dp: 0.00118 m, ρs: 713 kg/m3).

Ug: 0.071 m/s, phenol:4-cp : 3:1 8:1, T: 250C, 9% EPS loading, 2.8% (10 g) GAC loading.

Starch wastewater

Mixed culture obtained from the sludge taken from the starch industry effluent treatment plant

ID: 0.092 m, Hc: 1.7 m.

Qg: 4.864x10-5 m3/s, pH: 5.9–6.1, Starch conc.: 2250–8910 mg/l, HRT: 8–40 h, BOD to COD ratio: 0.67.

PP particles: (dp: 0.01 m, ρs: 870 kg/m3, Specific surface: 390 m2/m3). V: 0.016 m3, ID: 0.096 m, Hc: 2.2 m, PP particles: (dp: 0.01 m, ρs: 870 kg/m3, Specific surface: 390 m2/ m3). ID: 0.092 m, Hc: 1.6 m, PP particles: (ρs: 870 kg/m3, Specific surface: 390 m2/ m3). V: 0.0125 m3, ID: 0.1 m, Hc: 1.8 m, PP particles: (ρs: 870 kg/m3, Surface area per particle: 0.000524 m2).

Qg: 6.25x10-5 m3/s, pH: 6.0.

Sludge taken from the starch industry effluent treatment plant

Domestic wastewater

Dairy

IDd

Domestic wastewater pit sludge

NA

Internal diameter of draft tube,

Pilot plant: 0.6 m length, 0.6 m width, 1.65 m water depth, & 0.53 m3 volume. Plastic hollow cylinders: ρs: 970 kg/m3, dp: (9.7 ± 0.3) x10-3 m, (8.1 ± 0.4)x10-3 m long, & surface area: 400 m2/m3. NA

Not available,

V

Column volume,

Vp

Hs: 0.8 m, Qg: 6.25x10-5 m3/s, pH: 6.0.

Hs: 0.4–1.0 m, Qg: (1.67-8.61)x10-5 m3/s.

Hs: 0.6–1.0 m, HRT: 6–40 h, Ug: 0.00106-0.00212 m/s, Conc.: 2–7.5 g/l. Hs: 0.6–1.0 m, HRT: 6.25–24 h, Ug: 0.00106-0.00318 m/s, Conc.: 910–3940 mg/l. Qg: (5–8.3) x 10-3 m3/s, T: 20–25 0C, HRT: 3.5–11.2 h.

Particle volume.

70

Reactor performance showed above 90% COD removal for lower organic loading rates. At low OLR of < 5 kg COD/m3.d and high OLR of > 20 kg COD/m3.d, the COD removal efficiency were > 90% and < 60% respectively. Maximum COD, BOD, and TSS removal were 94.3, 81, and 70% respectively observed at Hs = 0.8 m and Qg = 6.25 x 10-5 m3/s. 97.5% COD reduction was achieved at Hs = 0.8 m, Ug = 0.00212 m/s, and HRT = 40 h.

References

[82]

[83]

[84]

[85]

[24]

[31]

[32]

[15]

[34]

[86]

96.7% COD reduction was achieved at Hs = 0.8 m and Ug = 0.00318 m/s.

[87]

85% and 60% COD removal at volumetric organic loading rates of 500 and 900 g COD/m3.h respectively.

[37]


A.K. Swain et al.

activity of pseudomonas putida and pseudomonas aeruginosa in fixed condition in comparison with free suspended cells. Along with PAC, several other low cost adsorbents can be tried. Apart from using these two pseudomonas species, a mixed culture can also be tried.

glucose consumed per liter of reactor volume per hour. The maximum rate achieved was 1000 mg/l.h. When these results were compared with those obtained from basic draft tube airlift reactor (without PE granules) it was found that the AIFBBR was 3.6 times more effective at a glucose conversion of 90% and the ratio between the maximal glucose uptake was 14.8 times higher. As only a few hydrodynamic studies were reported prior to this work, the glucose uptake capacity could be higher if the optimized hydrodynamic conditions would be considered for the present AIFBBR. Karamanev and Nikolov [13] treated an aqueous solution of glucose and found that at over 80% substrate conversion, AIFBBR was 25 times more efficient than a chemostat and this increased to 100 as the substrate conversion decreased to 20%. This indicated that the AIFBBRs would be more efficient if operated in series.

3.5. Brewery wastewater Sokół [10] studied the treatment of local brewery industry wastewater using KMTR (Kaldnes Miljotechnologi AS) particles made of polypropylene. The wastewater was enriched in mineral salts as per the recommendations of Sokół [78] and Sokół and Migiro [79]. COD removal was found to be dependent on mean residence time (t), settled bed volume (Vb) to bioreactor volume (Vr) ratio, and Ug. For a set of t and Vb/Vr, initially the COD removal was found to increase monotonically but later found to decrease with an increase in Ug. This is due to the increase of the amount of oxygen transfer for the growth of microorganisms caused by the increase in Ug. While for a set of t and Ug, the COD removal was found to increase initially but later found to decrease with an increase of Vb/Vr ratio. An increase in COD removal was also observed upto an optimal Vb/Vr ratio mainly due to the increasing growth of microorganisms on the solid KMTR particles. Beyond the optimal Vb/Vr ratio, the COD removal was found to decrease as a large portion of the reactor volume was occupied with solid particles causing aeration to be difficult.

3.2. Ferrous iron solution The ferrous iron solution in wastewater is generally contributed by the wastewater generated during the leaching of metals in hydrometallurgy industries. Nikolov & Karamanev [12], Karamanev & Nikolov [19], and Nikolov & Karamanev [77] took Thiobacillus ferrooxidans to treat wastewaters containing ferrous iron using expanded polystyrene (EPS) spheres in a reactor having a volume of 1.7 l and diameter of 6.5 cm. With 3–4 g Fe2+/l, 60 l/h gas flow rate, and 3.2–18.2/h dilution rate Nikolov and Karamanev [12] observed the oxidation rate to be 0.7 g Fe2+/l.h with a maximum value of 2.1 g Fe2+/l.h at 70% conversion. Karamanev and Nikolov [19] carried out the degradation studies at a substrate dilution rate of 1.08/h for ferrous iron concentration of 3.5–4.0 g/l at 27 °C. The dissolved oxygen (DO) concentration was observed to decrease with an increase in reactor height for a fixed volume of support particles. But as the fixed volume of support particles increased, decrease in DO concentration was found to be higher with the same increase in reactor height. Outlet Fe3+ concentration was observed to inhibit the process at inlet Fe2+ concentration of above 6 g/l. The conversion of substrate was not affected much by temperature in the range of 13–38 °C, pH between 1.3–2.2, ferric iron concentration upto 14 g/l, or ferrous iron concentration from 4 to 13 g/l. It was also observed that in the low pH range, higher fixed volume of support particles favored higher conversion. Nikolov and Karamanev [77] observed the biofilm formation rate in AIFBBR to be 1.3–2 times faster than biodisk, fixed bed, and conventional 3-phase fluidized bed bioreactors. They also observed the temperature, pH, and the product and substrate concentrations in a wide range did not affect the process rate much.

3.6. Phenolic wastewater Using different bacterial species such as microbial consortium obtained from a contaminated site soil sample [21], pseudomonas putida [22–24], pseudomonas fluorescence [17,25–29], and pseudomonas aeruginosa [16] several researchers have used AIFBBRs to treat phenolic wastewaters discharged from a wide variety of industries. They have used either PS beads, EPS beads, or PP spherical balls as biomass support particles. The phenol degradation was dependent on initial phenol concentrations, liquid & air flow rates, dilution rates, solids’ loading, Vb/Vr ratio, temperature, and pH of the system. Loh and Liu [22] observed that for higher phenol concentrations the total degradation time decreased with the increase in gas velocity which indicated that degradation was oxygen limited. Aye and Loh [23] observed longer phase lag for higher recycle rates and the system was able to absorb the shock well upto 5000 mg/l. For synthetic phenolic effluents, Begum and Radha [25] found that the suspended biomass concentration increased gradually with increasing time while phenol was completely degraded at the end of nearly 5 days of treatment. The average specific density of bio-particles increased indicating the growth of biomass on solid particles [26]. Begum and Radha [17] observed an increasing trend of COD removal efficiency till a certain particle aspect ratio. Loh and Ranganath [24] integrated a fluidized bed of granular activated carbon (GAC) to the reactor already developed by Loh and Liu [22] for cometabolic biotransformation of 4-chlorophenol (4-cp) in the presence of phenol as a growth substrate. Pseudomonas putida was used for the degradation studies. A sharp drop in substrate concentration was observed at the beginning due to adsorption onto GAC. The co-metabolism was found to be oxygen limited at the higher phenol and 4-cp concentrations. For higher concentration ratios, the time for complete degradation was observed to be decreased with the increase in gas velocity. In treating refinery generated phenolic wastewaters using activated sludge obtained from refinery operated biological treatment unit, researchers such as Sokół [80], Sokół and Korpal [81], Sokół and Korpal [82], Sokół and Korpal [83], Sokół et al. [84], and Sokół and Woldeyes [85] have observed the dependency of the COD removal on t, Vb/Vr ratio, and Ug. They have also observed that the COD removal initially increased monotonically for a set of t and Vb/Vr ratio and then decreased with an increase in Ug. The COD removal was also observed to be initially increased for a set of t and Ug and then decreased with an

3.3. Dairy wastewater Rusten et al. [37] studied the degradation of dairy industry wastewater in an aerobic moving bed biofilm reactor using short plastic hollow cylinders (having a cross in the middle forming four channels). The pilot plant showed 85% and 60% COD removal at volumetric organic loading rates of 500 and 900 g COD/m3 h respectively. This type of reactor can suitably be used for treatment of effluents generated from food industries mainly due to the absence of clogging and channelling of the filter media and the ease of cleaning of biofilm media. 3.4. Aniline Aniline and many other aromatic amines are the pollutants generated from several industrial and agricultural activities. Nikov et al. [20] treated aniline in a turbulent AIFBBR using EPS beads. Pseudomonas putida and pseudomonas aeruginosa were used as bacterial species. Surface of EPS particles treated with powdered activated carbon (PAC) (15 wt%, mesh 160) as adsorbent, chloroform/alcohol (1/5) as solvent, and polymethylmethacrylate (PMMA) (2.5 wt%) as glue was found to have excellent environment for growth of pseudomonas putida. Aniline biodegradation studies showed an almost two times higher degradation 71


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velocities and decreases with liquid viscosity. It is observed that different microbes degrade different industrial wastewaters. Although some researchers have mentioned the specific microbial species for particular type of wastewater, these results are not full proof. Several possibilities are there for this. One of the many important reasons is that many polluting/harmful compounds remain in the industrial wastewaters along with the main pollutant, for example steel industry wastewater contains ammonia, cyanide, and many other compounds along with phenol. The presence of other compounds in the system may affect the treatment process in the AIFBBRs. Again many factors contribute to inhibit the treatment process being carried out by the useful microbes. Operating conditions such as temperature, pressure, pH, and impurities (other than the main component) present in the wastewater may inhibit the growth of microorganisms thereby affecting the treatment process. During the treatment process some of the side products are generated which may be harmful to the growth of microbes leading to the product inhibition. Further, if the system gets saturated with the product, the microbes do not get sufficient feed to grow as a result the process is affected. If more microbes are taken then they do not get sufficient feed to grow as a result they start dying because of reactant inhibition. Dilution rate, temperature, pH, and hydraulic retention time play major roles in the microbial degradation of wastewaters in AIFBBRs. Parameters like initial concentration, Vb/Vr ratio, liquid and gas flow rates, size and shape of carrier particles, and bed height determine the degree of treatment of the wastewater. Therefore, a thorough research work is essential on the operating condition, amount of microbes/polluted wastewater in addition to the identification of pollutants in wastewater. There is also a lot of scope for the kinetic study for continuous culture involving dilution rate in AIFBBRs.

increase in Vb/Vr ratio. Similar behavior was also observed by Sokół [10] while treating brewery industry wastewater. 3.7. Starch industry wastewater While treating starch industry wastewater in an AIFBBR, using a mixed culture obtained from the effluent treatment plant and irregular shaped PP particles, Rajasimman and Karthikeyan [31] observed the ratio of BOD to COD was 0.67, indicating that the starch industry wastewater was biologically degradable. The COD reduction was found to decrease as the initial substrate concentration increased and at low concentration the degradation occurred at a faster rate than at higher concentrations. It was also observed that as the flow rate increased, the COD reduction increased and then decreased after the flow rate reached a critical velocity. COD reduction was found to increase with increase in hydraulic retention time (HRT) for all initial substrate concentrations. Rajasimman and Karthikeyan [32] followed the same procedure as those of Rajasimman and Karthikeyan [31] and observed the data obtained to be best fitted to First order model with a R2 value of greater than 0.9. For the treatment of starch industry wastewater in an AIFBBR, Rajasimman et al. [33] used a Radial Basis Function neural network for modeling and found that neural network based model has very low root mean square error (RMSE) values, which implies that it is useful in predicting the system parameters with desired accuracy. Rajasimman and Karthikeyan [15] studied the performance of an AIFBBR at various organic loading rates (OLR) and observed the COD removal efficiency to be high at low OLR. It was also observed that the reactor has an ability to withstand sudden organic loading. While Rajasimman and Karthikeyan [34] observed the COD reduction to be dependent on the time, bed height, and air flow rates. It was also observed that for a given time and air flow rate, COD reduction increased initially and later found to decrease with an increase in bed height. Similarly, for a particular bed height, COD reduction was observed to be increased initially and then decreased with an increase in air flow rates.

5. Future perspectives Literatures reveal that wastewater of many more industries still need to be analyzed thoroughly by using inverse fluidization technology in AIFBBRs. There is a good scope for the use of irregular shaped polymeric particles as well as for naturally occurring substances which are lighter and hydrophobic in nature. Further, use of innovative accessories for AIFBBRs to speed up the treatment process is the topic of research which needs careful analysis for an economical and sustainable reason. Scope of using enriched microorganisms under optimum operating conditions for treatment of different industrial wastewaters can be studied to make the process further simpler.

3.8. Domestic wastewater Domestic wastewater might be present in industrial wastewater; hence its treatment is essential. Haribabu & Sivasubramanian [86] and Haribabu & Sivasubramanian [87] have treated domestic wastewater in an AIFBBR using PP particles as biocarriers and sludge taken from the domestic wastewater pit for inoculum preparation. The domestic wastewater was characterized by COD only having concentrations in the range of 910–7500 mg/l. It was observed that, % of COD reduction increased with the increase in superficial gas velocity and HRT while it was found to decrease with the initial concentration of wastewater.

Acknowledgements One of the authors, Anup Kumar Swain, is thankful to Indira Gandhi Institute of Technology (An Autonomous Institute of Govt. of Odisha), Sarang, Dhenkanal, Odisha, India for sponsoring his doctoral work at NIT, Rourkela, Odisha, India.

4. Critical analysis Through the literature review it is evident that the characteristics of AIFBBRs in terms of RTD, dispersion coefficient, voidage fluctuation, elutriation velocity, friction factor, collision frequency, liquid circulation velocity, fluctuating frequency, bubble rise velocity, and heat & mass transfer coefficients are dependent on the experimental conditions. Therefore it cannot be generalized. However, the parameters like bed porosity, phase holdups, pressure drop, superficial velocities, and minimum fluidization velocities can easily be correlated to have a preliminary idea on the performance of AIFBBRs. For three phase AIFBBRs, it can be concluded that as superficial gas velocity increases, the bed dynamics such as the pressure drop, bed porosity, and gas holdup increase while solid and liquid holdups decrease. Critical gas velocity is found to depend on the type of particles, initial liquid height, column ID, while it is independent of ratio of static bed height to column height (Hc). It is also seen that the pressure gradient increases with superficial liquid velocity till minimum fluidization velocity is reached and then decreases. Bubble size increases with superficial

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