Electro-coagulation coupled electro-flotation process: Feasible choice in doxycycline removal from pharmaceutical effluents

3.1 Effect of current density and time of electrolysis

In all electrochemical reactions, the reaction rate is controlled by current density and time of electrolysis which determine the coagulant production rate and the total production of coagulant respectively. The percentage removal of DCH as a function of time at different current densities (3.59 mA cm⁻²–14.39 mA cm⁻²) is shown in Fig. 3A. It can be illustrated that the current density of 5.39 mA cm⁻² was the optimum current density based on the maximum DCH removal and consumed time for electrolysis. The removal of DCH was almost 90% after 80 min. The residual DCH concentration was in the range 1.60–5.18 mg L⁻¹. Although the DCH removal was remarkable with the residual DCH concentration of 0.53 mg L⁻¹ at 14.39 mA cm⁻², the consumption of current was 2.7 times higher with respect to the optimized current (current density = 5.39 mA cm⁻²) which leaves the residual DCH concentration of 0.76 mg L⁻¹.

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Figure 3 Removal of DCH as a function of current density (A) and pH of the solution (B). Conditions: (A) pH = 7, [DCH] = 100 mg L⁻¹, Q = 52 L min⁻¹, d = 1 cm, conductivity = 1.78 mS cm⁻¹; (B) [DCH] = 100 mg L⁻¹, CD = 5.39 mA cm⁻², Q = 52 mL min⁻¹, d = 1 cm, conductivity = 1.78 mS cm⁻¹.

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The rate of DCH removal was directly proportional to current density because of the increased production of the coagulant (Al³⁺ ions) on the anode. As a result of increased flocs generation rate, the DCH removal efficiency was enhanced. In other words, the higher the current density, the greater will be the generated flocs to trap the DCH molecules from the aqueous solution. After the time of electrolysis in the range of 50–60 min, the residual DCH concentration was very low. The rate of its sorption onto the generated flocs at constant rate tends to decrease for a particular current density.

3.2 Effect of pH

The pH of any electrolyte drives the fate of electro-coagulation process (Yavuz et al., 2011). The pH of the electrolytic medium increases during the flocculation–sorption phase and gets stabilized in the pH range 7.52–7.91 for various initial DCH concentrations at an initial pH of 7.0 as reported by Yavuz et al. (2011). The associated increase in pH may be corroborated due to the electrolysis of water leading to hydrogen evolution and OH⁻ production (Malakootian et al., 2010). The relative stability of pH after the process could be ascertained due to the formation of Al(OH)₃ flocs with less solubility between the pH values of 6 and 8 (Emamjomeh and Sivakumar, 2009). The effect of pH on DCH removal is shown in Fig. 3B. The removal of DCH at different pH values of 6.03, 7.04, 7.52 and 8.02 was conducted with the initial DCH concentration of 100 mg L⁻¹. The increased precipitation at higher pH leading to the generation of greater flocs enhances the DCH removal efficiency. The removal of DCH was achievable between 98.5% and 99.4% in the pH range 6.03–8.02. Similar observation was experienced in the study of boron removal by Ezechi et al. (2014).

The main reactions that take place during electro-coagulation at the two electrodes are as follows:

Under acidic condition (pH < 3.3) due to protonation, the cationic form of DCH (+00) develops the electrostatic repulsion with predominant cationic monomers of Al³⁺ and Al(OH)²⁺ and lessens the removal efficiency of DCH (Ouaissa et al., 2014). The possibility of DCH speciation at various pH values (Zhang et al., 2011) as zwitterion (±0) was due to the loss of proton from the phenolic diketone moiety. On the other hand, the pH between 6.03 and 8.02 generates Al³⁺ and OH⁻ ions to form various monomers such as Al(OH)₂⁺, Al(OH)₂²⁺ and other polymeric species such as Al₆(OH)₁₅³⁺, Al₇(OH)₇⁴⁺, Al₁₃(OH)₃₄⁵⁺ which were finally converted into the insoluble amorphous Al(OH)_3(s) through complex polymerization/precipitation kinetics (Merzouk et al., 2009). The formation of Al(OH)_3(s) is therefore optimal in the 4–9 pH range. In addition, the cathode (Al) may be chemically attacked by OH⁻ ions generated together with H₂ at high pH values as

However, the pH affects also the bubble size (Glembotskii et al., 1975). Typical bubble sizes in electro-coagulation always fall in the range of 20–70 μm (Adhoum et al., 2004). They are far smaller than those observed in conventional air-assisted floatation, which provides both sufficient surface area for gas–liquid–solid interfaces and mixing efficiency to favor the aggregation of tiny destabilized particles. Hydrogen bubbles, which usually obey to a lognormal size distribution, are also known to be the smallest at about neutral pH (Fukui and Yuu, 1985). The best removal of DCH could be accomplished by charge neutralization and sorption in the presence of the constituent monomers and polymers. The acquired surface positive sites with large surface area on the amorphous structure of hydrolyzed Al(OH)₃ make the viability of sorption with the macromolecular organic DCH anions rather existing as a free hydrated metal ion (Zhou et al., 2008). It is also envisaged that the DCH at basic conditions prevails as either a monovalent or a divalent anion due to deprotonation of tricarbonyl system and phenolic diketone moiety. As a consequence, high removal of DCH may be associated, due to the attractive force between the positive aluminum and negative DCH ions, and hence the sorption of the latter onto Al(OH)₃. These active flocs facilitate the rapid sorption of soluble DCH compound being entrapped by the colloidal particles and ultimately get separated from the aqueous medium by sedimentation or hydrogen floatation (Ghernaout et al., 2009). The surface complexes of zwitterionic species were previously suggested by Figueroa et al. (2004).

3.3 Effect of spacing between electrodes (SBE)

The spacing between electrodes and effective surface area depends on the construction of the electrode assembly. The variation in voltage drop (η_IR) is governed by the following equation (Ghosh et al., 2008a):

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Figure 4 Removal of DCH as a function of initial DCH concentration (A) and spacing between electrodes (B). Conditions: (A) pH = 7, CD = 5.39 mA cm⁻², Q = 52 mL min⁻¹, d = 1 cm, conductivity = 1.78 mS cm⁻¹; (B) pH = 7, [DCH] = 100 mg L⁻¹, CD = 5.39 mA cm⁻², Q = 52 mL min⁻¹, conductivity = 1.78 mS cm⁻¹.

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3.4 Effect of initial DCH concentration

The initial concentration provides an important driving force to overcome all mass transfer resistance of solutes between the aqueous and the solid phase (Ji et al., 2009). The removal efficiency of DCH as a function of initial DCH concentration at 5.39 mA cm⁻² is shown in Fig. 4A. The percentage of DCH removal was decreased with respect to the increase in the initial concentration and could easily be distinguishable up to 50 min. But after 50 min, the residual DCH concentration falls between 2.3 mg L⁻¹ and 2.6 mg L⁻¹. As per Faraday’s law, at a constant current density, the generated aluminum flocs for a particular time remain constant for various DCH concentrations (60–180 mg L⁻¹). But the requirement of aluminum flocs will be greater for the higher DCH concentration and hence becomes insufficient to capture the extra organic DCH species. Evidently single, smooth and continuous graphical curves leading to saturation which suggests the monolayer coverage of DCH on the surface of Al(OH)₃ were reported (Lakshmi et al., 2013).

3.5 Effect of supporting electrolytes

In order to increase the conductivity of wastewater due to resistance between the electrodes, the addition of sodium chloride is suggested during electro-coagulation process.

Researchers used sodium chloride to increase the conductivity of the solution; nevertheless, sodium nitrate and sodium sulfate were also used as electrolytes (Aber et al., 2009). On increasing the salt concentration, the power consumption of electrolytic cells is reduced due to the reduction in cell voltage at constant current density (Kashefialas et al., 2006). Although the type of electrolyte has no effect in favor of the removal efficiency, it provides the pronounced effect on cell voltage and current consumption during the EC process. It is also reported that at high anode potential, direct oxidation of organic compounds or H₂O may also take place (Ge et al., 2004). The influence of sodium chloride was remarkable in facilitating the removal of DCH, whereas the influence of sodium nitrate and potassium chlorides was alike and their effect on the removal of DCH was almost closer to each other. The inter-wined curves shown in Fig. 5B illustrate that no appreciable influence was observed due to the addition of sodium nitrate and potassium chlorides. The conductivity of the solution remains practically constant during the treatment as shown in Fig. 5C. The average electrical conductivity of DCH electrolyte in the presence of sodium chloride was recorded to be 1.78 mS cm⁻¹. The electrical conductivity of the DCH electrolyte in the presence of KCl and NaNO₃ was recorded as 1.45 mS cm⁻¹ and 1.22 mS cm⁻¹ respectively. Hence it is apparent that high conductivity of the EC system due to NaCl enables the DCH removal of about 90% at the end of 30 min but for the other salts (KCl and NaNO₃) the same percentage of removal could be achieved after 60 min. From the above observations, it is quite understood that half of the power is expendable to achieve 90% removal of DCH in the presence of sodium chloride as compared to the other potassium chloride and sodium nitrate as supporting electrolytes.

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Figure 5 Removal of DCH as a function of circulating flow rate (A), electrolyte interference (B) and evolution of conductivity as a function of time for each electrolyte (C). Conditions: (A) pH = 7, CD = 5.39 mA cm⁻², [DCH] = 100 mg L⁻¹, d = 1 cm, conductivity = 1.78 mS cm⁻¹; (B) pH = 7, [DCH] = 100 mg L⁻¹, CD = 5.39 mA cm⁻², Q = 52 mL min⁻¹, d = 1 cm; (C) pH = 7, [DCH] = 100 mg L⁻¹, CD = 5.39 mA cm⁻², d = 1 cm, Q = 52 mL min⁻¹.

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3.6 Effect of circulation flow rate

The effect of the circulating flow rate of 52 mL min⁻¹, 82 mL min⁻¹ and 100 mL min⁻¹ on the removal of DCH at a concentration of 100 mg L⁻¹ is shown in Fig. 5A. In general, the performance of the EC column toward removal of desired solute is inversely proportional to the flow rate.

The percentage of DCH removal increased with respect to the decrease in the flow rate. High removal of DCH can be attributed to the increased residence time of DCH molecules inside the EC column due to the restricted flow rate and hence long reaction time between DCH species and the aluminum flocs (Lin and Peng, 1996). Contrarily, low residence time due to the short stay of DCH species inside the EC column facilitates insufficient interaction between DCH species and the aluminum flocs (Bratby, 2006). It is reported that (Al-Shannag et al., 2012) the increasing circulating flow rate will generate high mixing levels within the EC unit that could facilitate the transport process of colloidal pollutants to be adsorbed onto the active sites of coagulants. Conversely, at very high circulating flow rate, the coagulants would dissociate and lead to the hindrance of the sorption process with decreased removal efficiency. From the observed results, an increased difference of 12.75% was observed from the flow rate of 52–100 mL min⁻¹ after the time of 30 min. But the margin of increased difference was halved (6.82%) after 60 min. On proceeding to 90 min and 120 min, the differential margin was about 2.21% and 1.82% respectively. A longer electrolysis time of about 120 min was needed to achieve the maximum DCH removal for the high flow rate of 100 mL min⁻¹.

3.7 Kinetic models

The study on adsorption kinetics is significant because it provides valuable insight into the reaction pathway and the corresponding sorption mechanism. The sorption mechanism depends on the physical and chemical characteristics of the adsorbent and also on the mass-transfer process. The dynamics of DCH sorption onto Al(OH)₃ at an optimized pH (7.02) with respect to different spacing between electrodes, initial DCH concentrations, supporting electrolytes and circulating flow rate was validated using kinetic models such as pseudo-first-order, pseudo-second-order, intra-particle diffusion and Elovich models. The figured parameters of the kinetic models are represented in Table 2.

Based on pseudo-first-order and pseudo-second-order models, it is possible to elucidate the mechanism of adsorption and potential rate controlling steps (Chutia et al., 2009) of DCH sorption onto Al(OH)₃ flocs.

Pseudo-first-order model is a simple adsorption kinetic model (Eq. (8)), suggested by Lagergren (1898) and further referred by Ho et al. (1996), which is unable to apply throughout the range of tested contact time. The kinetic parameters q_e and k₁ were calculated from the intercept and slope respectively using Eq. (8) and are shown in Table 2. The regression values (R²) inferred that the DCH sorption complies fairly well with the pseudo-first-order model.

According to pseudo-second-order kinetics (Eqs. (9) and (10)), the rate of adsorption is directly proportional to the number of active sites on the adsorbent surface. The kinetic parameters calculated from the pseudo-second-order equation (Eq. (10)) were q_e, k₂ and h from the slope and intercept values (q_e = 1/slope; k₂ = slope²/intercept; h = 1/intercept). The increase in the q_e value from 52.63 mg g⁻¹ to 200.04 mg g⁻¹ was recorded with respect to the DCH concentration. The R² values for all the variables (Table 2) were quite plausible and corroborate that the pseudo-second-order seems appreciable with the DCH sorption kinetics. Based on the regression values, it may be ascertained that the pseudo-second-order was more validated than the pseudo-first-order model (Isa et al., 2014; Kamaraj and Vasudevan, 2015).

It is inferred from the Weber–Morris intra-particle diffusion plot (Eq. (11)) that the initial curved portion reflects the film or boundary layer diffusion effect and the subsequent linear portion (plateau) depicts the intra-particle diffusion effect. The graphical plots deviate from passing through the origin and this deviation may be caused due to the difference between the rate of mass transfer in the initial and final stages of DCH sorption and the complex mechanism. The mechanism of sorption thus involves the contribution of both the surface adsorption and intra-particle diffusion to the rate determining step. The thickness of boundary layer, determined from the intercept value C is inversely proportional to the external mass transfer. The value of C seems to be very sensitive with respect to the change in initial DCH concentration, SBE, supporting electrolyte and circulating flow rate. The regression values indicate the intra-particle diffusion model did not fit satisfactorily with the DCH sorption dynamics (Kamaraj et al., 2013).

Elovich model (Eq. (12)) is one among the useful kinetic models (Aharoni and Tompkins, 1970) and predicts the behavior of sorption over the whole range of variable studied. This fact strongly supports its validity and suggests that the adsorption is rate-determined by a chemisorptions step (Juang and Chen, 1997).

The value of 1/B gives about the number of available sites for sorption in the adsorbent. The magnitude of 1/B increased with respect to the increase in the initial concentration of DCH in several folds was established. On the contrary, the decrease in the available sites (1/B) was observed from 13.89 to 7.81 when the circulating flow rate was increased from 52 mL min⁻¹ to 100 mL min⁻¹ and becomes evident for the descending DCH removal efficiency. The calculated values of initial adsorption rate (A) and constant of desorption (B) with corresponding regression coefficients indicated that the Elovich model fits fairly well with the present system on DCH sorption onto Al(OH)₃ flocs (Kamaraj et al., 2013).

3.8 Isotherm model: Dubinin–Kaganer–Radushkevich (DKR) model

Dubinin–Kaganer–Radushkevich (DKR) isotherm is more general than Langmuir isotherm owing to its disagreement for a homogenous surface or a constant adsorption potential. Using DKR equation with reference to the present system, the constant β gives the free energy, E (kJ mol⁻¹) for the transfer of 1 mol of DCH ion from infinity to the surface of Al(OH)₃ flocs and can be computed using the relationship (Onyango et al., 2004) as shown in Eqs. (13)–(15). The magnitude of E is helpful in understanding the nature of DCH ion sorption. The recorded values of E with respect to the variation of DCH concentration and spacing between electrodes are 7.905 kJ mol⁻¹ and 15.813 kJ mol⁻¹ respectively. As the values are in the range of 8–16 kJ mol⁻¹, it may be suggested that the nature of bonding is governed by chemical forces (Swain et al., 2009). The present sorption system fits well with the DKR model and was supported by the R² values (Fig. 6) as reported by Kamaraj et al. (2013).

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Figure 6 DKR model for DCH and SBE variations.

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3.9 Characterization studies

The material after the EC/EF process was characterized by FTIR, SEM and XRD studies. The assignments of Fourier Transform IR study which occur at different frequencies are shown in Table 3 (Fig. 7B). The broadband appears between 3500 cm⁻¹ and 3000 cm⁻¹ with an assignment of 3307.56 cm⁻¹. This displacement was due to the displacement of OH band by overlapping of hydrogen bonds and the superimposition of NH band. The absence of >C⚌O stretching frequency (>C⚌O at 1715 cm⁻¹, —COOH between 1700 and 1730 cm⁻¹) may be associated due to the newly formed bond between carbonyl oxygen and aluminum ions (as >C—O—Al).

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Figure 7 X-ray diffraction pattern (A) and FTIR of electro-generated coagulant with DCH (B).

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The X-ray diffraction patterns (Fig. 7A) for DCH and DCH adsorbed Al(OH)₃ illustrate the amorphous and crystalline merged amorphous patterns respectively. The narrow diffraction peaks at 18.8°, 20.3°, 27.9°, 40.3° and 53.2° are assigned to bayerite (PDF No. 20-11). The retained amorphous pattern of DCH is perturbed with the overlapping crystalline pattern due to the DCH adsorbed polymorph, Al(OH)₃. In support of the present study, it was reported that the formation of bayerite was predominant at near neutral pH (pH ⩾ 7) and higher pH values (Carrier et al., 2007). The amorphous or slightly crystalline nature of electro-generated aluminum hydroxides and oxo-hydroxides was remarkable because of the very slow crystallization process. Hence the reflections of Bragg showing very broad bumps with low intensity for the phases were analyzed at short distances (Drouiche et al., 2009).

The scanning electron micrograph (Fig. 8) shows that the aluminum floc-bound DCH material was at greater heterogeneity with irregular, sharp edged particles and exposing a rough surface. The precipitated grains constitute the distinguished geometries and make the formed aggregates with no well defined structural pattern.

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Figure 8 Scanning electron micrographs of electro-generated aluminum coagulant.

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3.10 Energy, electrodes and chemicals consumptions

Energy consumption and sacrificial electrodes are very important economical parameters. In this study, we used an average potential for EC and EF with a current density of 5.39 mA cm⁻². The electrical energy consumption of the process (EEC) was calculated using the following equation (Isa et al., 2014):

Current efficiency (φ) which depends on the anodic dissolution is calculated as follows (Ghosh et al., 2008b):

Specific Electrical Energy Consumption (SEEC) is calculated as a function of aluminum electrodes weight consumption during EC in kW h per kg of Al (Nandi and Patel, 2014).

Table 5 represents the details of the current efficiency, amount of generated sludge and the consumption of specific electrical energy, electrode and electrolyte during the EC–EF process.

In supporting the obtained results, the consumption of electrical energy (C_energy) for NaNO₃ is 2.53 times higher than for NaCl. The amount of electrode consumed was intermediate for NaCl (61.8 g) when compared with KCl (60.1 g) and NaNO₃ (63.7 g). The sludge generation after the electrolysis process was two times higher for NaCl as compared to that of KCl. Hence it may be accounted that the influence of electric charge to generate more sludge was higher for NaCl than the other two supporting electrolytes. The specific electrical energy consumption (SEEC) for the supporting electrolytes is in the following order: NaNO₃ > KCl > NaCl. SEEC was observed about 3 times higher for NaNO₃ than NaCl and KCl during the process of EC. The difference in SEEC among the electrolytes may be attributed by the developed resistance between the electrodes with a particular electrolytic solution. In this case, the resistance developed was higher for NaNO₃ then KCl and NaCl electrolytic solutions. As a consequence of increased resistance, the voltage across the electrodes was increased. This behavior ultimately leads to increased total power consumption and SEEC for achieving the necessary current density to facilitate the EC process. The current efficiency (φ) of 119.4%, 122.8% and 126.5% was evaluated for the supporting electrolytes of NaCl, KCl and NaNO₃ respectively.