In recent years industrialization has caused magnificent leaps in the high profitable growth of pharmaceutical industries, and simultaneously given rise to environmental pollution. Pharmaceutical processes like extraction, purification, formulation, etc., generate a large volume of wastewater that contains high chemical oxygen demand (COD), biological oxygen demand, auxiliary chemicals, and different pharmaceutical substances or their metabolites in their active or inactive form. Its metabolites impart non-biodegradable toxic pollutants as a byproduct and intense color, which increases ecotoxicity into the water, thus this requires proper treatment before being discharged. This study focuses on the feasibility analysis of the utilization of ultrasound cavitation (20 kHz frequency) together with a persulfate oxidation approach for the treatment of complex pharmaceutical effluent. Process parameters like pH, amplitude intensity, oxidant dosage were optimized for COD removal applying response surface methodology-based Box–Behnken design. The optimum value observed for pH, amplitude intensity and oxidant dosage are 5, 20% and 100 mg/L respectively with 39.5% removal of COD in 60 min of fixed processing time. This study confirms that a combination of ultrasound cavitation and persulfate is a viable option for the treatment of pharmaceutical wastewater and can be used as an intensification technology in existing effluent treatment plants to achieve the highest amount of COD removal.

  • Synergistic effect of ultrasonication and persulfate oxidation studied on pharma wastewater.

  • Box–Behnken method applied for process parameter optimization.

  • Significant reduction in the COD from the pharma wastewater within one hour of the reaction.

  • Potential choice for the implementation of the process as a pre-treatment option for wastewater treatment.

Environmental pollution is one of the global challenges of today's world (Spina et al. 2012; Singh & Prashant 2017). Industrial effluent and other hazardous discharges from industries are one of the prime concerns for developing countries like India. In India, one-third of water pollution in natural water bodies and marine pollution are induced by industrial wastewater (Kansal et al. 2013; Singh & Prashant 2017). At this time, high amounts of pharmaceutical substances are used for the protection and cure of diseases for humans and animals, which lead to the generation of huge quantities of wastewater from pharmaceutical industries (Mohapatra et al. 2014; Ghafoori et al. 2015). The USEPA reported the daily effluent produced from the pharmaceutical unit as 1.0068 × 109 L (Adishkumar et al. 2012). These effluents contain highly biologically active compounds which can cause damage to health in humans and animals, as well as promoting the development of antibiotic resistance genes, and interrupts the ecological balance of the aquatic environment by initiating irreversible transformation to aquatic fauna (Ng et al. 2014; Tiwari et al. 2020). Industrial wastewater quality is estimated, based on the amount of organic matter present, as COD, total carbon, BOD, and wastewater quality parameters. The wastewaters produced from pharmaceutical sectors are complex and hazardous with high COD, BOD, solids containing supplementary chemicals, and pharmaceutical secondary metabolites leading the wastewater to be classified under the ‘red category’ (Gadipelly et al. 2014; Changotra et al. 2017, 2019; Martínez et al. 2018).

Pharmaceutical wastewater contains a large amount of recalcitrant or bio-refractory molecules which are very difficult to degrade through conventional treatments. Hence, most is converted into other complex by-products as fluoxetine and endocrine disruptors, which has resulted in a multitude of undesirable problems like harm to reproduction and metabolism of aquatic organisms and feminization of fish populations (Ford & Fong 2016; Huang et al. 2016; Thanekar & Gogate 2019). Thus it is necessary to treat pharmaceutical wastewater efficiently before discharging it into any water bodies to avoid further damage to the environment and ecosystem, it also pollutes water bodies (Gadipelly et al. 2014; Changotra et al. 2017, 2019; Singh & Prashant 2017; Martínez et al. 2018).

Treatment processes like biological oxidation require longer time because they have a slower reaction rate (Crini & Lichtfouse 2019). Chemical coagulation is useful for removal of pollutant in the form of colloidal or suspended particles that do not settle rapidly, it requires a longer retention time and more sludge production (Verma et al. 2012). Adsorption reactors rapidly becomes less effective due to clogging and their regeneration are not cost-effective, hence, this decreases the acceptance of a certain type of metal molecule (Crini & Lichtfouse 2019). These demerits of treatment, make it not efficient to remove all hazardous compounds effectively from pharmaceutical wastewater (Jeworski & Heinzle 2000; Ayare & Gogate 2019). In recent times advanced oxidation processes (AOP) such as Fenton oxidation (Singh et al. 2013), ozonation (Cortez et al. 2010), ultraviolet/hydrogen peroxide (Hu et al. 2011), and ultrasound cavitation (Gągol et al. 2018) have been considered as a useful process for treatment of bio-refractory pollutants (Yang et al. 2015). Among the different AOP the ultrasound cavitation-based process has been seen as a promising process for the oxidation of various pollutants in industrial wastewater. The principle behind the ultrasonication process is the pressure variation in liquid caused by inducing ultrasound which produces cavitation for the treatment of wastewater (Thanekar & Gogate 2019). Cavitation occurs due to pressure difference in the outer flow and the pressure induced inside the system by sound waves as system pressure decreases or increases in flow velocity, which produces small cavities; with time these start to grow longer compared with higher system pressure (Dular et al. 2016). Furthermore, variation in pressure leads to cavity formation, growth, and collapse at the micro-scale duration. These three stages occur during the ultrasound cavitation process which leads to the generation of free radicals and releases a large amount of energy. This energy can be up to 5,000 K temperature and 1,000 Atm pressure in wastewater known as a ‘local hotspot’ which can be extremely suitable for the oxidation of pollutants (Leighton 1995; Thanekar & Gogate 2019). The main advantage behind this treatment is it does not require any chemicals to promote oxidation, no sludge formation, no visible light requirement (Vega & Peñuela 2018) and it breaks up the agglomerates (Jordens et al. 2016; Dong et al. 2020). In the same way, the presence of reactive nitrogen such as NO3, NO2, NO or degradation of other organic pollutants that contain nitrogen species forms nitrate radicals (), nitrite radicals (), and nitrogen oxide radicals (), etc. These reactive nitrogen radicals participate in redox reactions as well and help in the nitration reaction of the pollutants (Rayaroth et al. 2022). Ultrasound cavitation is useful for the treatment of active pharmaceutical compounds (Tran et al. 2015; Serna-Galvis et al. 2019; Estrada-Flórez et al. 2020), such as carbamazepine, diclofenac, ciprofloxacin (Beckett & Hua 2001; Rayaroth et al. 2016), and the tetracycline antibiotic (Soltani et al. 2019). Ultrasound cavitation accelerates the degradation of pollutants in combination with other oxidation processes like Fenton's reagent (Zhang et al. 2016), zinc oxide, the zinc oxide nanotube catalytic process (Soltani et al. 2019), hydrogen peroxide (Chandak et al. 2020), carbon tetrachloride, and persulfate ions (Anipsitakis & Dionysiou 2003) to generate radicals (Rayaroth et al. 2016). The persulfate dissociation can also occur due to high localized temperature developed by the ultrasound system (Wei et al. 2017). The combination of persulfate oxidation with the ultrasound cavitation system has been less studied by other research groups (Monteagudo et al. 2015, 2018; Wang & Zhou 2016). An alternative to hydrogen peroxide, persulfate ion has gained more attention due to the increased interest in the higher redox potential of sulfate radicals (2.5–3.1 V) compared with hydroxyl radicals. The hydroxyl radicals prefer to react by addition, hydrogen atom abstraction, as well as through electron transfer mechanisms, while prefer to react through electron transfer mechanisms, which makes them selective towards electron-donating groups such as amino (-NH2), hydroxyl (-OH), alkoxy (-OR), amino (-NH2), alkoxy (-OR), π electrons of aromatic compounds, and unsaturated bonds (Fedorov et al. 2020):
formula
(1)

The formation of sulfate radical occurs by breakage of the O-O bond of persulfate ions using different activation methods like heat (Tan et al. 2012), transitional metals (Liu et al. 2016), ultraviolet light (Xie et al. 2015; Arvaniti et al. 2020), ultrasound (Zou et al. 2014; Yang et al. 2019), and other means as shown in Equation (1) (Arvaniti et al. 2020). The homogeneous and heterogeneous catalytic activation of persulfate by using cobalt or manganese oxides, etc., has been studied by many researchers (Liang et al. 2012; Yuan et al. 2020). Among them, activation by ultrasound acts as an emerging method and is typically used for pharmaceutical wastewater treatment (Zou et al. 2014; Yang et al. 2019). The synergistic effect of combined cavitation and the persulfate process has been studied by Fedorov et al. (2022) and has computed the synergistic index for different combined process. The synergistic index of combined cavitation and persulfate varied from 1.52 to 4.43 for different pollutants (Fedorov et al. 2022). Therefore, it is significant to use a combined process for the treatment of pharmaceutical wastewater to achieve increased removal.

In the combined process multiple operating parameters influence or affect the removal efficiency. For complex systems governed by several parameters, generally, use of one parameter optimization at a time could provide misinterpretation due to lack of interaction effects, thus the Design of Experiment (DoE) is an effective tool for optimization. There are various DoEs available for optimization of parameters by reducing the number of experiments and cost (Dopar et al. 2011) like the Box–Behnken method for response surface methodology (RSM) which is a powerful design tool for modeling complex conditions (Tak et al. 2015). This tool estimates the relation between manageable input parameters and response variables (Khorram & Fallah 2018).

This study focuses on the combined effect of ultrasound cavitation and persulfate oxidation on the treatment of pharmaceutical wastewater. The synergistic effect of the combined process was investigated along with the effect of biodegradability of the combined process. The major process influencing factors of the combined ultrasound–persulfate process like pH, amplitude intensity, persulfate dosage, reaction time were investigated for their individual and the combined effects by using Box–Behnken design as an RSM for the treatment of pharmaceutical wastewater. The effect of reactive radicals on the removal of pollutants was investigated through scavenging tests.

Industrial wastewater

A wastewater sample of 40 L was collected from the pharmaceutical industry from Bharuch, Gujarat, India. Collected samples were stored in a refrigerator at 4 °C to avoid further biodegradation.

Chemicals

In this study, chemicals of analytical grade were used for the entire experimental process: potassium persulfate purity 98% purity, potassium dichromate 99% purity, mercury sulfate 98% purity, silver sulfate 98% purity, ammonium ferrous sulfate 99% purity, manganous sulfate 98% purity, ferric chloride 98% purity, di-potassium hydrogen phosphate 99% purity, potassium iodide 99% purity, potassium hydroxide 85% purity, sodium thiosulfate 98% purity were procured from M/s Merck India. Sulfuric acid of 98% purity, ferroin indicator, calcium chloride 96% purity, magnesium sulfate 99% purity, starch as an indicator were procured from M/s Finar India. All the required reagents were prepared using double-distilled water. For ultrasonic cavitation, a 20 kHz frequency probe-type sonicator made of Ti6Al4V titanium alloy with maximum power output of 750 W was used with a microprocessor-based programmable probe (Model No. VCX 500 with 17 mm solid probe diameter) and procured from Sonics Vibracell, USA.

Design of experiment (DoE)

Design-expert software was used to prepare DoE. The removal of organic matter from pharmaceutical wastewater was optimized using Box–Behnken design as RSM. Table 1 represents its coded and real value for lower level (−1), mid-level (0), high level (+1) for removal of organic matter as COD. Table 2 provides the details of a different combinations of experimental runs for the considered parameters pH (A), amplitude intensity% (B), persulfate dosage (C). The experimental range for the parameters was decided based on published literature.

Table 1

Coded and real values of the factors selected for Box–Behnken design

FactorsLow levelMid-levelHigh level
− 101
pH (A) 
Amplitude intensity % (B) 20 50 80 
Dosage (mg/L) (C) 100 250 400 
FactorsLow levelMid-levelHigh level
− 101
pH (A) 
Amplitude intensity % (B) 20 50 80 
Dosage (mg/L) (C) 100 250 400 
Table 2

Box–Behnken design

Experimental runspHAmplitude (%)Persulfate dosage (mg/L)COD remaining (mg/L)
50 100 11,200 
50 400 12,480 
80 100 10,944 
80 250 10,880 
50 250 9,440 
50 250 9,440 
20 100 8,320 
50 100 12,640 
80 250 12,640 
10 20 400 12,800 
11 20 250 12,800 
12 80 400 11,680 
13 50 400 12,960 
14 50 250 12,320 
15 20 250 11,200 
Experimental runspHAmplitude (%)Persulfate dosage (mg/L)COD remaining (mg/L)
50 100 11,200 
50 400 12,480 
80 100 10,944 
80 250 10,880 
50 250 9,440 
50 250 9,440 
20 100 8,320 
50 100 12,640 
80 250 12,640 
10 20 400 12,800 
11 20 250 12,800 
12 80 400 11,680 
13 50 400 12,960 
14 50 250 12,320 
15 20 250 11,200 

Mathematical representation of selected process parameters to the estimation of the dependent response y (COD removal) by coded terms is as mentioned below, by general model regression Equation (2):
formula
(2)
where, y is a response, β0 is the linear, quadratic and regression constant, βj, βjj and βij represent the coefficients for linear, quadratic, and second-order interaction effects, respectively. xj and xi represent the coded independent process variables.

Experimental procedure

All experiments were conducted in a cylindrical batch glass reactor with 250 mL of working volume (capacity of 500 mL). The schematic diagram of the experimental process reactor is shown in Figure 1. The temperature of the sample was maintained at 50 ± 10 °C for the heat-based activation of persulfate (Ahmadi et al. 2019), with ultrasound and the pH was adjusted using nitric acid (1 N) and sodium hydroxide (1 N). Ioannidi et al. (2022) reported an acceleration in degradation of pollutant when the temperature of the wastewater was increased from 40 °C to 60 °C, whereas in the current study the external heating of wastewater was not done, instead the temperature of the water was maintained within the 50 ± 10 °C range through a water circulation method. The addition of sulfate ions in the advanced oxidation process will convert the ion to sulfate radicals. The sulfate radicals generated through the addition of sulfate ion may oxidize the organic matter over the persulfate-generated sulfate radical. Thus, to study the efficiency of persulfate radicals on wastewater treatment, the addition of sulfate ions (sulfuric acid) was restricted and instead nitric acid was used. The persulfate dosage was added according to the real value of factors suggested by DoE. All 15 experimental runs were conducted according to values suggested by DoE. All the experiments were duplicated twice to check their reproducibility, a ±10% change in results was accepted and the experiments were repeated when the deviation in results was beyond ±10%. Treated samples were withdrawn during the experiment at a time interval of 15, 30, and 60 min and analyzed for COD. The COD of the sample was analyzed as per the standard method using the closed reflux method. The synergistic effect of the combined process (ultrasound cavitation and persulfate oxidation) was analyzed using Equation (3) (Rokhina et al. 2008; Li & Zhu 2016). The synergistic index of the combined process can be determined by comparing the removal efficiency of the stand-alone process (RRultrasoundcavitation, RRpersulfate oxidation) with that of the removal efficiency of the combined process (RR):
formula
(3)
where,
Figure 1

Schematic diagram of the experimental process.

Figure 1

Schematic diagram of the experimental process.

Close modal

RR – Removal rate of COD for the combined process

RRultrasound cavitation – Removal rate of COD for stand-alone ultrasound cavitation treatment

RRpersulfate oxidation – Removal rate of COD for stand-alone persulfate oxidation treatment.

If the synergistic index of the combined process is equal to one (SI = 1), the effect is called an additive effect. If SI > 1 the combined process effect is much greater than the sum of the sole process effect, this is called a synergistic effect and if SI < 1 the effect is termed as antagonism (Li & Zhu 2016).

Characteristics of pharmaceutical wastewater

Characterization of the pharmaceutical wastewater was done as per the APHA standard methods (Rice et al. 2012) and given in Table 3. The COD and BOD of the wastewater were 13,760 mg/L and 5,500 mg/L respectively with a BOD/COD ratio of 0.4.

Table 3

Characteristics of pharmaceutical wastewater

ParameterConcentration in mg/L (except pH)
pH 7.6–7.8 
Chloride 174.9 
Total solids 25,570 
Total organic carbon 2,815 
Biological oxygen demand 5,500 
Chemical oxygen demand 13,760 
BOD/COD 0.4 
ParameterConcentration in mg/L (except pH)
pH 7.6–7.8 
Chloride 174.9 
Total solids 25,570 
Total organic carbon 2,815 
Biological oxygen demand 5,500 
Chemical oxygen demand 13,760 
BOD/COD 0.4 

Analysis of variance (ANOVA)

The ANOVA in Table 4, provides the details of various coefficient values of process parameters and other details for COD removal from pharmaceutical wastewater with ultrasound cavitation treatment. The table shows that the model (Fischer test value) F-value is 9.42 and it shows the model value is significant as the P-value is less than 0.05, which implies that the model is significant. The significance of the P-value fixes the error probability of the regression co-efficient as significant. For optimized conditions of parameters quadratic and some of the interaction terms are significant, the parameter pH (A) is slightly significant, another parameter persulfate dosage (C) is significant, an interaction effect of amplitude intensity (B) and persulfate dosage (C), is also significant concerning model terms. According to the ANOVA, if the P-value of selected parameters is less than 0.05 (i.e. P < 0.05) then selected parameters are significant for the process efficiency, and when the P-value of parameters is greater than 0.05 (P > 0.05) then selected parameters are insignificant for the process efficiency. Table 5 gives the comparison of results between the predicted and experimental under different test conditions. The experimental results are comparable with the predicted with an error percentage variation of 0–30% under different parametrical conditions.

Table 4

ANOVA results for the obtained regression equations

SourceSum of squaresdfMean squareF-valueP-value
Model 3.115E + 07 3.461E + 06 9.42 <0.050 Significant 
A – pH 1.843E + 06 1.843E + 06 5.02 0.0652 Slightly significant 
B – Amp (%) 1.191E + 05 1.191E + 05 0.3241 0.5938  
C – Dosage 3.942E + 06 3.942E + 06 10.73 <0.050 Significant 
AB 4.096E + 05 4.096E + 05 1.11 0.3393  
AC 6.400E + 05 6.400E + 05 1.74 0.2441  
BC 5.345E + 06 5.345E + 06 14.55 <0.050 Significant 
A² 1.726E + 07 1.726E + 07 46.98 0.0010  
B² 1.150E + 06 1.150E + 06 3.13 0.1371  
C² 1.903E + 06 1.903E + 06 5.18 0.0719  
Residual 1.837E + 06 3.674E + 05    
Lack of fit 1.837E + 06 6.123E + 05    
Pure error 0.0000 0.0000    
Cor total 3.299E + 07 14 R2 = 94.43%    
SourceSum of squaresdfMean squareF-valueP-value
Model 3.115E + 07 3.461E + 06 9.42 <0.050 Significant 
A – pH 1.843E + 06 1.843E + 06 5.02 0.0652 Slightly significant 
B – Amp (%) 1.191E + 05 1.191E + 05 0.3241 0.5938  
C – Dosage 3.942E + 06 3.942E + 06 10.73 <0.050 Significant 
AB 4.096E + 05 4.096E + 05 1.11 0.3393  
AC 6.400E + 05 6.400E + 05 1.74 0.2441  
BC 5.345E + 06 5.345E + 06 14.55 <0.050 Significant 
A² 1.726E + 07 1.726E + 07 46.98 0.0010  
B² 1.150E + 06 1.150E + 06 3.13 0.1371  
C² 1.903E + 06 1.903E + 06 5.18 0.0719  
Residual 1.837E + 06 3.674E + 05    
Lack of fit 1.837E + 06 6.123E + 05    
Pure error 0.0000 0.0000    
Cor total 3.299E + 07 14 R2 = 94.43%    
Table 5

ANOVA analysis results

Coded factors
COD removal
Experimental runspHAmplitudePersulfate dosage (mg/L)Experimental (%) removalPredicted (%) removal
50 100 19% 22% 
50 400 8% 6% 
80 100 20% 20% 
80 250 21% 19% 
50 250 31% 32% 
50 250 31% 32% 
20 100 39% 36% 
50 100 7% 9% 
80 250 8% 7% 
10 20 400 7% 8% 
11 20 250 7% 10% 
12 80 400 21% 26% 
13 50 400 8% 5% 
14 50 250 31% 32% 
15 20 250 10% 12% 
Coded factors
COD removal
Experimental runspHAmplitudePersulfate dosage (mg/L)Experimental (%) removalPredicted (%) removal
50 100 19% 22% 
50 400 8% 6% 
80 100 20% 20% 
80 250 21% 19% 
50 250 31% 32% 
50 250 31% 32% 
20 100 39% 36% 
50 100 7% 9% 
80 250 8% 7% 
10 20 400 7% 8% 
11 20 250 7% 10% 
12 80 400 21% 26% 
13 50 400 8% 5% 
14 50 250 31% 32% 
15 20 250 10% 12% 

A mathematical representation of the independent variable to the dependent response by coded terms shown by this Equation (4):
formula
(4)

From the above equation, it is noticed that there is a positive effect of linear terms on COD removal except persulfate dosage (C). With the change in linear terms, the COD removal changes according to its coefficients. The quadratic terms with a negative sign show a negative impact on COD removal. This means that an increase in the values of the quadratic coefficient will decrease the removal of the COD removal. Other interaction terms (AB, AC, BC) have mixed responses on the COD. The term with interaction (BC and AC) with persulfate dosage (C) will increase COD removal. Negative quadratic terms in Equation (2) indicate that the reduction in COD removal has been quadratic.

For the identification order of each process parameter and its effect while keeping the other process parameters constant indicated in perturbation plots, Figure 2 then factors sensitivity on COD removal, which is indicated by the nature of the curve for each process parameter and the factor with more slope has more noticeable effects on COD removal (Muthukumaran et al. 2017; Milano et al. 2018). The plot shows that factor B has a prominent effect on COD removal followed by A and C, similar to that reflected in the table for ANOVA.
Figure 2

Profile of perturbation plot showing significant parameters affecting COD removal with factors pH (curve A) 2–8, amplitude (curve B) 20–80%, persulfate dosage 100–400 mg/L (curve C) with middle level values. Temperature 50 ± 10 °C.

Figure 2

Profile of perturbation plot showing significant parameters affecting COD removal with factors pH (curve A) 2–8, amplitude (curve B) 20–80%, persulfate dosage 100–400 mg/L (curve C) with middle level values. Temperature 50 ± 10 °C.

Close modal
The individual effect of each parameter plot is shown in Figure 3(a)–3(c), which indicates the effect of parameter pH, amplitude intensity, and persulfate dosage, respectively. These plots are made by taking one factor as a variable and the other two factors fixed at constant levels and the experimental results are shown at three different levels compared to predicated plots that are discussed in the following section.
Figure 3

Profile of an individual parameter plot with two reference curves based on ANOVA for process parameters. (a) pH from 2 to 8, with a fixed parameter amplitude of 50%, and persulfate dosage of 250 mg/L. (b) Amplitude from 20% (18 W) to 80% (78 W) with fixed parameter pH of 5, and persulfate dosage of 250 mg/L at mid-level. (c) Persulfate dosage 100–400 (mg/L) with fixed parameter of pH 5 and amplitude of 50%, on removal of COD with 95% of confidence interval band. Temperature 50 ± 10 °C.

Figure 3

Profile of an individual parameter plot with two reference curves based on ANOVA for process parameters. (a) pH from 2 to 8, with a fixed parameter amplitude of 50%, and persulfate dosage of 250 mg/L. (b) Amplitude from 20% (18 W) to 80% (78 W) with fixed parameter pH of 5, and persulfate dosage of 250 mg/L at mid-level. (c) Persulfate dosage 100–400 (mg/L) with fixed parameter of pH 5 and amplitude of 50%, on removal of COD with 95% of confidence interval band. Temperature 50 ± 10 °C.

Close modal

Effect of pH on COD removal

One of the important parameters that affects the process efficiency is pH. It plays a vital role in the generation of intermediate oxidants for the oxidation of various compounds it can also affect their condition during the cavitation process (Keenan & Sedlak 2008; Barik & Gogate 2017; Thanekar & Gogate 2019). Effects of pH on the degradation of organic pollutants were studied by varying pH from 2 to 8 with a fixed amplitude intensity of 50% and persulfate dosage of 250 mg/L and is shown in Figure 3(a). As shown in Figure 3(a), the maximum COD removal of 39% at pH 5 at a reaction time of 60 min was observed. Increasing pH from the lower level at pH 2 to mid-level pH 5, the removal efficiency also increased, further increasing the pH to 8 decreased the removal efficiency of COD. Maintaining the mid-level value of factors amplitude intensity of 50% and persulfate dosage of 250 mg/L at pH 2 and pH 8 corresponded to a predicated removal efficiency of 19 and 21% respectively.

The degradation of organic pollutants from the wastewater depends on the radicalization of the reactive compounds. The possible radicalization reactions of persulfate with respect to ultrasound as the activator are given below, in Equations (5)–(12). The significant radicals formed during the persulfate reaction are sulfate radicals and hydroxyl radicals. The radical compounds react with the organic compounds and are oxidized to by-products, carbon dioxide and water (see Li et al. 2013; Wang et al. 2015):
formula
(5)
formula
(6)
formula
(7)
formula
(8)
formula
(9)
formula
(10)
formula
(11)
formula
(12)
Excessive loading of persulfate dosage above 250 mg/L has proven a scavenger for the process under the acidic and non-acidic conditions as given in Equations (13)–(15) (Peyton 1993; Wei et al. 2018).
formula
(13)
formula
(14)
formula
(15)
The observed results show near acidic conditions as more effective compared to alkaline conditions for the degradation of pollutants under a similar kind of analysis as shown in the published literature (Thanekar & Gogate 2019). Due to this, removal was low at a higher levels of pH 8. Mid-level pH 5 showed maximum removal efficiency compared with the highly acidic pH 2, which was due to a higher amount of cavitation yield and effective generation of sulfate radicals by persulfate oxidant (Romero et al. 2010; Sarath et al. 2016). At pH 2 more numbers of protons are present in the form of which decreases effective decomposition of persulfate oxidant while increasing the pH, quantity of ions decreases in solution which leads to effective generation of sulfate radicals from persulfate as shown in given Equations (16)–(17) (Romero et al. 2010; Sarath et al. 2016):
formula
(16)
formula
(17)

Effect of amplitude on COD removal

Effect of power dissipation is one of the important influences in the ultrasound cavitation process, variation in amplitude generates more violent collapse of bubbles (Vega & Peñuela 2018). In this study, the effect of power dissipation on COD removal was studied by varying amplitude intensity from 20 to 80% (power dissipation 18–78 W) with fixed pH of 5 and persulfate dosage of 250 mg/L. The plot Figure 3(b) shows the variation in amplitude intensity at different levels and its effect on COD removal. The COD removal at 20, 50 and 80% of amplitude intensity is 27, 32 and 30% respectively. Maximum removal of 32% was observed at the mid-level of 50% (48 W), because Gaussian distribution probability of the cavitation bubble at the generation of cavitation is higher at lower amplitude (50%) and lower at higher amplitude (Feng et al. 2002). The amplitude intensity variation shows least significant by ANOVA as shown in Table 4. For higher power intensity at lower frequency, the decoupling effect occurs between sample solution and transducer. Thus bubble cloud formation occurs at the surface of the horn or transducer, resulting in a reduction in sound waves in the solution, hence at a lower frequency (20 kHz) the lower power cavitation becomes more effective (Sunartio et al. 2007).

Effect of persulfate oxidant on COD removal

Persulfate () is one of the strong oxidizing agents (Yang et al. 2019) for the degradation of organic matter. It becomes activated in the presence of ultrasound (Yang et al. 2019) as given in Equation (18) and produces sulfate radicals with an oxidation potential of 2.40 V. The persulfate radical is a more stable radical compared to hydroxyl radicals (Romero et al. 2010). Persulfate oxidation has strong oxidation ability and efficient performance in a wide range of pH (Amor et al. 2019):
formula
(18)
In this study, the effect of combined ultrasound activated persulfate oxidation on COD removal was studied by varying the persulfate dosage from 100 mg/L to 250 mg/L with fixed factors pH 5 and amplitude intensity of 50%, as shown in Figure 3(c). Maximum COD removal of 32% was observed at a lower level of persulfate dosage of 100 mg/L. Predicted removal at a mid-level of 250 mg/L dosages and a higher level of 400 mg/L dosages of persulfate was 31 and 21% respectively. The increase in persulfate dosage from 100 to 400 mg/L decreases the removal efficiency of COD. It shows that an increase in persulfate concentration leads to the existence of excess persulfate in the system with which sulfate radicals in the system react and produce sulfate ions, and also extra sulfate radicals react themselves, as given in Equations (19) and (20) (Vu et al. 2004; Wei et al. 2018) . The additional persulfate loading under particularly acidic solutions are reported as a scavenger, thus the rate of reaction slightly decreases with an increase in dosage (Peyton 1993; Wei et al. 2018):
formula
(19)
formula
(20)
Figure 4 shows the comparison of COD removal with stand-alone ultrasound, persulfate process compared with the combined ultrasound and persulfate process under optimum conditions. The combined process is more effective with a rate constant of 0.0094 min−1 and removal efficiency of 39.5% compared with the stand-alone ultrasound cavitation process with 8% COD removal under the optimum conditions of pH 5, amplitude 20% provide and persulfate oxidation process with 5% COD removal under 100 mg/L dosage. A similar effect was observed by Yang et al. (2019) for the removal of pollutant from the wastewater. The combined effect leads to a higher amount of cavitation yield production and effective generation of sulfate radicals by persulfate, it also improves the degradability through degradation of polysaccharides ions to monomer ions by a combined ultrasound–persulfate oxidation process (Zhou & Ma 2006; Chen et al. 2021).
Figure 4

Profile of percentage COD removal with individual treatment; ultrasound at pH 5, amplitude 20%; persulfate of 100 mg/L; temperature 50 ± 10 °C. Combined effect of ultrasound with persulfate at pH 5 and persulfate dosage of 100 mg/L, amplitude of 20%, temperature 50 ± 10 °C within 60 min reaction time.

Figure 4

Profile of percentage COD removal with individual treatment; ultrasound at pH 5, amplitude 20%; persulfate of 100 mg/L; temperature 50 ± 10 °C. Combined effect of ultrasound with persulfate at pH 5 and persulfate dosage of 100 mg/L, amplitude of 20%, temperature 50 ± 10 °C within 60 min reaction time.

Close modal

The synergistic index for the combined process has been computed based on the removal efficiency observed for the stand-alone process and for the combined process. When the wastewater was treated with ultrasound cavitation alone the maximum removal efficiency observed was 8% and that of persulfate oxidation was 5%. Whereas, when the persulfate process was activated with sonication the observed removal efficiency was almost 39.5%. Accordingly, the computed SI for the combined process was 3.038, which indicates there is a significant synergetic effect occurs when the ultrasound cavitation is combined with persulfate process as the reported synergetic index for the same process with different pollutants varies from 1.52 to 4.43 (Fedorov et al. 2022).

Effect of pH and amplitude on COD removal

The interaction effect of pH (A) and amplitude intensity (B) on COD removal is not significant based on ANOVA as shown in Table 4, its P-value is higher than 0.05 (P > 0.05). The combined effect of pH and amplitude on COD removal was studied by maintaining other parameters constant and the results are as shown in Figure 5(a). With the increasing amplitude at pH 2, removal of COD increased to 31% and, on the other hand, middle level pH 5 with amplitude up to 50% removal efficiency increased further as a result of the generation of effective cavitation and effective decomposition of persulfate (Sarath et al. 2016). By further increasing the amplitude to 80% at pH 5, this reduces removal due to reduction in the cavitation yield, thus increasing or decreasing amplitude beyond or below 50% under near acidic conditions has no significant impact on the removal efficiency (Thanekar & Gogate 2019).
Figure 5

Profile of the interaction effect plot for process parameters. (a) pH 2–8 to amplitude 20–80% (AB) maintaining persulfate dosage (mg/L) at middle level. (b) Amplitude 20–80% to persulfate dosage 100–400 (mg/L) (BC) maintaining pH at middle level. (c) pH 2–8 and persulfate dosage 100–400 (mg/L) (AC) maintaining amplitude % at middle level. Temperature 50 ± 10 °C.

Figure 5

Profile of the interaction effect plot for process parameters. (a) pH 2–8 to amplitude 20–80% (AB) maintaining persulfate dosage (mg/L) at middle level. (b) Amplitude 20–80% to persulfate dosage 100–400 (mg/L) (BC) maintaining pH at middle level. (c) pH 2–8 and persulfate dosage 100–400 (mg/L) (AC) maintaining amplitude % at middle level. Temperature 50 ± 10 °C.

Close modal

Effect of amplitude and persulfate dosage on removal

The interaction effect of amplitude intensity (B) and persulfate dosage (C) on COD removal is significant as indicated by ANOVA outputs shown in Table 4, its P-value is lower than 0.05 (P > 0.05). The interaction effect of amplitude intensity and dosage of persulfate on COD removal is shown in Figure 5(b). For an amplitude intensity of 20% and persulfate dosages of 100 mg/L, the COD removal is significant due to the high availability of activation energy at low amplitude which was required for breakage of O-O bond and generation of sulfate radicals (Wacławek et al. 2017). Under higher amplitudes of 50 and 80% the persulfate amount of 250 and 400 mg/L became excessive for the system, leading to scavenger reactions, which reduced the removal (Wei et al. 2018) compared to 20% amplitude and 100 mg/L of dosage.

Effect of pH and persulfate dosage on COD removal

The interaction effect of pH (A) and persulfate dosage (B) on COD removal was not significant as indicated by ANOVA (Table 4), its P-value is higher than 0.05 (P > 0.05). The interaction effect of pH and dosage of persulfate on COD removal at 50% amplitude intensity is shown in Figure 5(c). Under an acidic pH of 2 and 5 with 100 mg/L dosages, there is more significant COD removal efficiency when compared to the removal achieved at 250 mg/L and 400 mg/L dosages. Excessive loading of persulfate leads to less utilization of persulfate ions under acidic conditions (Wei et al. 2018), persulfate loading above some extent acted as a proven scavenger under acidic conditions (Peyton 1993; Wei et al. 2018). Increasing dosage under near neutral condition of pH 8 did not have a significant effect on COD removal.

The comparison of removal efficiency of combined persulfate process with sonication with other similar advanced oxidation processes is given in Table 6. It is apparent that the removal efficiency of the present combined process is comparable with that of other similar processes. The present work was done with real wastewater containing a very high COD of 13,760 mg/L and with a BOD/COD ratio less than 0.4. Also, it has been observed that the reaction time considered for the similar AOP process for the treatment pharmaceutical wastewater was very high compared to that of the present study.

Table 6

Comparison of combined persulfate and ultrasound processes with other similar processes for the treatment of pharmaceutical wastewater

Treatment technologyPollutantOperating conditionsEfficiencyReference
Photo Fenton COD pH – 3
COD – 8,370 ± 190
[Fe2+] = 0.05 mol/L
[H2O2] = 0.25 mol/L
Reaction time – 120 min 
58.4% Changotra et al. (2019
Electro-Fenton COD Batch experiment
Current density – 17 mA/cm2
Initial pH – 3
Fe2+/Fe3+/Co2+ – 1:1:2
Oxygen flow rate – 0.5 L/min
Reaction time – 2 h 
93% Quang et al. (2022
Electro-Fenton (EF) + photocatalytic oxidation (PcO) COD EF
Current density – 5 mA/cm2
Reaction time – 1 h
PcO
[TiO2] = 1.5 g/L
Reaction time – 4 h 
70.2% Başaran Dindaş et al. (2020
Aerobic biological treatment + Photo-Fenton COD pH –1 2.7 ± 0.25
COD – 8,370 ± 190 
62.2% Changotra et al. (2019
Aerobic biological treatment + electro-fenton COD pH – 12.7 ± 0.25
COD – 8,370 ± 190 
44.6% Changotra et al. (2019
Photocatalytic oxidation COD COD = 1,900 mg/L
pH = 4.5, catalyst dosage – 2 g/l
[H2O2] = 0.32 mM 
72.7% Berkün Olgun et al. (2021
Ultrasound + persulfate COD COD 13,760 mg/L, pH 5, amplitude 20%, persulfate dosage 100 mg/L and reaction time 60 min 39.5% Present study 
Treatment technologyPollutantOperating conditionsEfficiencyReference
Photo Fenton COD pH – 3
COD – 8,370 ± 190
[Fe2+] = 0.05 mol/L
[H2O2] = 0.25 mol/L
Reaction time – 120 min 
58.4% Changotra et al. (2019
Electro-Fenton COD Batch experiment
Current density – 17 mA/cm2
Initial pH – 3
Fe2+/Fe3+/Co2+ – 1:1:2
Oxygen flow rate – 0.5 L/min
Reaction time – 2 h 
93% Quang et al. (2022
Electro-Fenton (EF) + photocatalytic oxidation (PcO) COD EF
Current density – 5 mA/cm2
Reaction time – 1 h
PcO
[TiO2] = 1.5 g/L
Reaction time – 4 h 
70.2% Başaran Dindaş et al. (2020
Aerobic biological treatment + Photo-Fenton COD pH –1 2.7 ± 0.25
COD – 8,370 ± 190 
62.2% Changotra et al. (2019
Aerobic biological treatment + electro-fenton COD pH – 12.7 ± 0.25
COD – 8,370 ± 190 
44.6% Changotra et al. (2019
Photocatalytic oxidation COD COD = 1,900 mg/L
pH = 4.5, catalyst dosage – 2 g/l
[H2O2] = 0.32 mM 
72.7% Berkün Olgun et al. (2021
Ultrasound + persulfate COD COD 13,760 mg/L, pH 5, amplitude 20%, persulfate dosage 100 mg/L and reaction time 60 min 39.5% Present study 

In order to assess the effect of the oxidizing species in the present study, the radical scavenger tert-butyl alcohol was added. Tert-butyl is considered to be hydroxyl scavenger and has the effect of hydroxyl radicals in the electrolytic cell reaction (Li et al. 2017; Popat et al. 2019). At the optimum condition of pH 5, amplitude 20%, persulfate dosage of 100 mg/L, 1 mL of tert-butyl alcohol was added and the results are shown in Figure 6. From the figure it is very clear that the addition of tert-butyl alcohol did not cause any significant removal of COD, which shows that the hydroxyl and sulfate radicals have been scavenged. Whereas, without the addition of scavenger, significant removal of COD has been reported, which indicates the main oxidizing agents causing degradation of pharmaceutical waste water are hydroxyl radicals and persulfate radicals. A similar effect was observed by Popat et al. (2019) for the degradation of mixed industrial wastewater.
Figure 6

Effect of tert-butyl alcohol in the combined ultrasound and persulfate process (optimum condition: pH 5, amplitude 20%, persulfate dosage 100 mg/L, temperature 50 ± 10 °C and reaction time 60 min).

Figure 6

Effect of tert-butyl alcohol in the combined ultrasound and persulfate process (optimum condition: pH 5, amplitude 20%, persulfate dosage 100 mg/L, temperature 50 ± 10 °C and reaction time 60 min).

Close modal

The synergetic index of the combined persulfate sonication process was computed for the treatment of pharmaceutical wastewater. The synergetic index was found to be 3.038, which is higher than 1, indicating the high synergetic effect of the combined process. It can also be concluded that ultrasound can be a better activator for the persulfate process. At the optimum condition of parameters pH 5, amplitude intensity of 20%, and persulfate dosage of 100 mg/L, the maximum COD removal of 5,440 mg/L (39.5%) was observed at 60 minutes of reaction time. The observed results concluded that process parameters like pH and persulfate oxidant dosage are very significant parameters for COD removal from pharmaceutical wastewater. The removal efficiency of the persulfate process, sonication and the combined persulfate sonication is in the following order 5 < 8 < 39.5%, respectively. The BOD/COD ratio of the treated wastewater increased from 0.4 to 0.53, thus the biodegradability of the treated wastewater had increased. The synergistic effect of ultrasound cavitation and persulfate oxidation was more effective for the degradation of organic matter from pharmaceutical wastewater compared with the effects of the stand-alone processes under optimum conditions. The major parameters that affect economic feasibility are chemical cost and energy consumption for sonication, which comes under the operational cost, and the cost of the sonicator and the reactor are the initial investments.

The authors would like to thank the Centre for Biofuels and Bioenergy Studies (CBBS) in PDEU for providing laboratory facilities for performing characterization and property estimation. The authors are thankful to the Director, Pandit Deendayal Energy University, Gandhinagar, India and Director, National Institute of Technology, Calicut, India for providing encouragement and kind permission for publishing the article.

Karan Pandya: Methodology, Formal analysis, Writing – original draft, Writing – review and editing.

Thankappan Saraswathy Anantha Singh: Conceptualization, Methodology, Formal analysis, Supervision, Writing – original draft, Writing – review and editing.

Pravin Kodgire: Conceptualization, Methodology, Formal analysis, Supervision, Writing – original draft, Writing – review and editing.

Saji-Simon: Additional experimentation, Writing the revised article – review and editing.

Not applicable.

Not applicable.

Not applicable.

Not applicable.

Not applicable.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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