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Removal of ciprofloxacin from hospital wastewater using electrocoagulation technique by aluminum electrode: Optimization and modelling through response surface methodology
Accepted Manuscript Title: Removal of ciprofloxacin from hospital wastewater using electrocoagulation technique by aluminum electrode; optimization and modelling through response surface methodology Authors: Saeid Ahmadzadeh, Ali Asadipour, Mostafa Pournamdari, Behzad Behnam, Hamid Reza Rahimi, Maryam Dolatabadi PII: DOI: Reference:
S0957-5820(17)30143-X http://dx.doi.org/doi:10.1016/j.psep.2017.04.026 PSEP 1056
To appear in:
Process Safety and Environment Protection
Received date: Revised date: Accepted date:
18-1-2017 18-4-2017 24-4-2017
Please cite this article as: Ahmadzadeh, Saeid, Asadipour, Ali, Pournamdari, Mostafa, Behnam, Behzad, Rahimi, Hamid Reza, Dolatabadi, Maryam, Removal of ciprofloxacin from hospital wastewater using electrocoagulation technique by aluminum electrode; optimization and modelling through response surface methodology.Process Safety and Environment Protection http://dx.doi.org/10.1016/j.psep.2017.04.026 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Removal of ciprofloxacin from hospital wastewater using electrocoagulation
technique
by
optimization
modelling
through
and
aluminum response
electrode; surface
methodology
Saeid Ahmadzadeh *a,b, Ali Asadipour c, Mostafa Pournamdari c, Behzad Behnam b, Hamid Reza Rahimi d, Maryam Dolatabadi *e a
Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran. b
Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran. c
Department of Medicinal Chemistry, Faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran. d
Department of Toxicology and Pharmacology, faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran. e
Department of Environmental Health, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
*Corresponding authors E-mail: [email protected] (S. Ahmadzadeh) [email protected] (M. Dolatabadi) Tel.: +98 3431325241; Fax: +98 3431325215
1
Graphical abstract
Graphical Abstract Caption: Major pathways of antibiotics release into the environment which cause antibiotic resistance for human.
HIGHLIGHTS
Hospital wastewater were used for real sample analysis in the current work
Removal of CIP was successfully optimized using response surface methodology
Electrical energy consumption at optimum operating conditions was 0.613 kWh.m-3.
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Abstract Pharmaceuticals as severe contaminants of surface and ground water around the manufacturing communities and residential zones received growing attention recently. Since, there is no report on ciprofloxacin (CIP) removal using electrocoagulation (EC) process by aluminum electrodes, the present work deals with efficient removal of CIP from hospital wastewater using mentioned method. Response surface methodology (RSM) was used to evaluate the main effects of parameters, their simultaneous interactions and quadratic effect to achieve the optimum condition for EC process. According to the obtained results from regression analysis, it was found that the experimental data are best fitted to the second-order polynomial model with coefficient of determination (R2) value of 0.9086, adjust correlation coefficient (Adj.R2) value of 0.8796 and predicted correlation coefficient (pred. R2) value of 0.7834. EC process was applied successfully with removal efficiency of 88.57% under optimal operating condition of pH 7.78, inter-electrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07 M NaCl with the initial CIP concentration of 32.5 mg.L-1. The experimental efficiency was in satisfactory agreement with the predicted efficiency of 90.34%. The obtained results revealed that, sweep flocculation as a determinant mechanism controlled the adsorption of CIP molecules on aluminum hydroxide precipitates. Electrode consumption and electrical energy consumption were found to be
66.80 g.m-3 and 0.613 kWh.m-3, respectively. The obtained results from real sample analysis revealed that the initial CIP concentration of 154±6 µgL-1 of hospital wastewater were found to reached to zero after applying optimal condition of EC process.
Keywords: Hospital wastewater treatment; Electrocoagulation process; Al electrode; Ciprofloxacin; Response surface methodology; Electrical energy consumption
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1. Introduction The 1960s was a decade that for the first times the presence of pharmaceuticals and personal care products (PPCPs) were diagnosed in surface waters in United States and Europe. Antibiotics as one of the most widely used PPCPs are approximately 90% excreted in urine and up to 75% in animal excrement, entering to the wastewater system as their parent forms (El-Shafey et al., 2012). Ciprofloxacin (CIP) as a synthetic antibiotic has been widely used for treatment of bacterial infectious disease in humans and animals. It is noteworthy to mention that drug manufacturers and hospitals are the most important sources of contaminated wastewaters. Inappropriate disposal of unused or expired CIP and its incomplete metabolization severely results in its increasing contamination in surface water during the last decade (Dewitte et al., 2008; El-Shafey et al., 2012). According to the statistics presented by the health communities, the amount of CIP contamination discerned in surface water and underground water were within the concentration range of 1˂µg.L-1, respectively. However, the detected amount of CIP in the waste water of hospitals and drug manufacturers is much higher up to 150
µg.L-1 and 50 mg.L-1, respectively, which is
extremely harmful to the health of the human beings (El-Shafey et al., 2012). Most of the conventional treatments such as activated sludge and trickling filter applied in wastewater treatment plants were unsuccessful which results in releasing them in environment and consequently contamination of surface water, soil and ground water. It is reported that the presence of CIP in daily drinking water may cause nervousness, nausea, vomiting, headaches, diarrhea and tremors. Higher concentrations may cause serious adverse effects including thrombocytopenia, acute renal failure, and elevation of liver enzymes, eosinophilia and leucopenia. On the other hand, the presence of CIP in water sources results in development of bacteria resistant to antibiotics which seriously emerging threat to public health and requires action across all government sectors and societies (Bajpai et al., 2012; Wang et al., 2010; Wu 4
et al., 2010; Zaidi et al., 2016). The treatments of resistant bacteria are difficult, costly and toxic which require alternative medications or higher doses (Somayajula et al., 2012; Vasudevan, 2014; Vasudevan et al., 2011a, b).
"Here Fig. 1" Literature surveys revealed that developing an efficient and economical procedure for CIP contamination removal from drinking water supply and wastewaters before releasing them into the environment received a great attention, recently. Since CIP is resistant to microbial metabolism, it cannot be efficiently degraded by means of biological treatment processes (Palmisano et al., 2015). Several techniques such as Adsorption (Gandhi et al., 2016; Kamaraj et al., 2015; Kamaraj et al., 2014a, b; Kamaraj et al., 2017; Kamaraj and Vasudevan, 2016), advanced oxidation process (Dewitte et al., 2008) , have been studied for removal of CIP from the contaminated water. However, among all of them electrochemical techniques such as electrocoagulation (EC) as an advanced, efficient and economical technique received extensive practical applicability by providing satisfactory result for treating various wastewater contaminants such as heavy metals (Kamaraj and Vasudevan, 2015), fluoride (Emamjomeh and Sivakumar, 2009), dyes (Daneshvar et al., 2006), drug (Khandegar and Saroha, 2013a) , phenol (Vasudevan, 2014). EC technique included coagulation process in which coagulant agent gets produced in situ through electrochemical reactions of sacrificial anode dissolution. (Khandegar and Saroha, 2013b). Electro-synthesized of coagulant provide competitive advantages of producing less sludge thus lowering the sludge disposal cost, removing many species that chemical coagulation cannot remove and the produced sludge is more readily filterable and can be utilized as a soil additive. Other considerable advantages of EC technique including low cost process and maintenance, no harmful substances generation, producing low amount of TDS and secondary pollutants and removing the smallest size of
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colloidal particles caused its increasingly usage. However, it does not require any chemical storage like adsorption or biological processes. Besides the current studies using electrochemistry, on the other hand, using electrochemical sensors as a device which provides a certain type of response that is directly related to the quantity of a chemical species such as contaminants, showed a rapid growing scientific studies in environmental monitoring field and practiced by the current research group recently (Ahmadzadeh et al., 2015a; Ahmadzadeh et al., 2015c; Fouladgar and Ahmadzadeh, 2016; Kassim et al., 2011; Pardakhty et al., 2016; Rezayi et al., 2014; Soltani et al., 2016). To the best of our knowledge, there is not any report on CIP removal using EC process by aluminum electrodes. So far only one report based on EC process was found for CIP removal from aqueous solution using iron electrode (Barışçı and Turkay, 2016). However, the reported EC process suffered from low removal efficiency for CIP contaminants in its optimized concentration of 5 mg.L-1 in compare to the current work with optimized concentration of 32.5 mg.L-1 CIP contaminants. Hence developing of EC process using aluminum electrodes can be regarded as a new and potential research area for CIP contamination removal from hospital and industrial wastewater. Since, most of the reported studies are based on one factor at the time method, in the current study, RSM was used to evaluate the main effects of parameters, their simultaneous interactions and quadratic effect to achieve the optimum condition for EC process. The effects of various operating parameters such as electrolyte type and concentration, inter-electrode distance, initial CIP concentration, pH, current density and reaction time were investigated to achieve the best efficient and CIP contamination remove condition.
2. Materials and methods 2.1. Chemicals 6
CIP (C17H18FN3O3·HCl·H2O, 385.8mol.wt.) purchased from darou pakhsh pharmaceutical company, Mashhad, Iran. The mobile phase was prepared using HPLC grade acetonitrile and analytical grade Hydrochloric acid. Electrolytes including MgSO4, NaCl, KNO3, Na2SO4, and CaCl2 were purchased from Merck Company. Hydrochloric acid and sodium hydroxide from Sigma-Aldrich were used for pH adjustments. Acetic acid and ethanol were obtained from Merck Company. All reagents used are analytical reagent grade with the highest available purity which used without any further purification except for vacuum drying over P2O5. All the solutions were prepared using de-ionized water.
2.2. Experimental procedure All experiments were conducted in batch mode by plexiglas electrochemical cell with dimensions of 12×5×5 cm to hold a sample of 250 mL using two aluminum plate electrodes with immersed dimensions of 3×2×0.2 cm. The pH adjustment was carried out by adding small volumes of 0.01 N of HCl or NaOH to the solutions and measured using Metrohm 827 pH/mv meter. KNAUER Smartline HPLC (C8 column; 250×4.6×5 mm) with a UV detector at a wavelength of 272 nm was used for quantitative determination of residual CIP. A mixture of hydrochloric acid 10 mµ and acetonitrile with a ratio of 80/20 (vol.%) was applied as mobile phase with an injection flow rate of 1 mL/min. The solution for extracting the CIP contaminant from wastewater was prepared using absolute ethanol/H2O containing 1% HOAc, 99:1 v/v and 0.8 g Na2SO4.
2.3. Statistical design In order to improve the removal efficiency of CIP, central composite design (CCD) was applied to optimize the experimental conditions under response surface methodology (RSM) category of Design Expert 7 software. In the present work, the CCD consists of 2n factorial
7
points, 2n axial points and moreover a given number of center points, where n is equal to 4 which is the number of numeric factors including initial CIP concentration, solution pH, current density and reaction time. The investigated factors and levels of each factor are presented in Table 1. Experimental data from the CCD was analyzed and fitted to a secondorder polynomial model expressed as below: 𝑛 𝑌 = 𝛽0 + ∑𝑛𝑖=1 𝛽𝑖 𝑋𝑖 + ∑𝑛𝑖=1 𝛽𝑖𝑖 𝑋𝑖2 + ∑𝑛−1 𝑖=1 ∑𝑗=𝑖+1 𝛽𝑖𝑗 𝑋𝑖 𝑋𝑗
(1)
where Y, β0, βi, βii, βij, Xi and Xj denote the predicted response of CIP removal, the intercept parameter, the linear coefficients, the quadratic coefficients, the interaction coefficients and the coded values of independent factors, respectively (Asaithambi et al., 2016; Doltabadi et al., 2016; Mohan et al., 2015). "Here Table 1"
3. Results and discussion 3.1. Preliminary evaluation of electrocoagulation process The effect of electrolyte type and concentration on the removal efficiency of CIP were investigated. The maximum removal was obtained using NaCl as electrolyte at equilibrium time of 20 min (see Fig. 2). Literature surveys revealed that addition of appropriate electrolyte significantly improved the efficiency of EC process due to increasing the conductivity of the wastewater which affects the Faradic yield, cell voltage and consequently energy consumption of the process.
"Here Fig. 2" The presence of NaCl electrolyte plays an important role to overcome the adverse effects of other anions such as CO32-, HCO3− and SO42− which may result in precipitation of Ca2+ cations as insulating layer on the surface of the cathode and increasing the ohmic resistance
8
of the EC cell. However, the extra amount of NaCl caused irregular dissolution of Al electrode, therefore the electrolyte dose of the NaCl (0.01-0.1M) were optimized and presented in Fig.3 The obtained results revealed that the removal efficiency of CIP remained almost unchanged in the range of 0.07 to 0.1 M of electrolyte dose. Therefore, NaCl electrolyte with the optimized concentration of 0.07 M was used for further studies.
"Here Fig. 3" Furthermore, the effect of inter-electrode distance on the removal efficency of CIP was investigated. It is known that, the drop in ohmic potential of the EC cell is proportional to the inter-electrode spacing and on the other hand the distance between electrodes affects the electrolysis energy consumption especially when sample conductivity is low (Khandegar and Saroha, 2013a). The distance between electrodes was changed in the range of 1.0 to 3.0 cm where the current density loading of 15 mA.cm-2, initial CIP concentration of 50 mg.L-1 and pH 7.5 were kept constant. The obtained results revealed that the lowest residual CIP concentration was 4.0 mg.L-1 at inter electrode distance of 1 cm. At inter-electrode distance of 1.5, 2, 2.5 and 3 cm, residual CIP concentrations of 8.35, 16.14, 23.5 and 30.5 mg.L-1 were obtained, respectively. The obtained results were in accordance with other reported investigations that showed by reducing the inter-electrode distance, the resistance of motion was reduced due to shorter travel path and consequently the electrical energy consumption were decreased and efficiency of the process improved. The experimental conditions along with the obtained results of 30 experiments according to RSM design are summarized in Table 2, as it can be seen; the removal of CIP was changed from 41.42 % to 97.25 %.
"Here Table 2"
9
3.2. Fitting of the process model and statistical analysis To evaluate the effects of independent factors including initial CIP concentration, solution pH, current density and reaction time on removal efficiency of CIP, thirty runs were carried out designed by response surface methodology. To obtain the regression equation the experimental results were fitted to the quadratic model. The quadratic polynomial model in terms of coded factors only for significant terms (terms with P-value ≤ 0.05) is expressed as below: 𝑅𝑒𝑚𝑜𝑣𝑎𝑙 (%) = 75.41 − 8.11𝑋1 + 6.04𝑋2 + 7.97𝑋3 + 3.05𝑋4 + 3.96 𝑋1 𝑋3 − 4.48𝑋22 − 1.93𝑋42
(2)
where X1, X2, X3, and X4 denote the initial CIP concentration, solution pH, current density, and reaction time, respectively. The adequacy of model was checked and the obtained results are summarized in Table 3. "Here Table 3" As it can be seen from Table 3, the ANOVA test confirmed that the applied quadratic model was significant with 95% confidence level and F-value of 31.25. Since the amount of P-value probability was more than 0.05, no evidence of lack of fit for the model was observed. Furthermore, the values of the correlation coefficient (R2), adjusted correlation coefficient (Adj. R2) and predicted correlation coefficient (pred. R2) were found to be 0.9086, 0.8796 and 0.7834, respectively, which indicates the experimental and model predicted values are in good agreement. Furthermore, the obtained amount of 20.79 for adequate precision which is more than 4, indicates an adequate signal to noise ratio.
3.3. Pareto analysis Graphical Pareto analysis provides noteworthy information about the importance of the operational parameters to interpret the obtained results. Pareto analysis indicates the 10
percentage effect of each factor on the CIP removal efficiency as the response, according to the equation expressed as bellow: 𝑏2
𝑃𝑖 = ∑ 𝑖 2 × 100 (𝑖 ≠ 0) 𝑏𝑖
(3)
where bi represents the estimation of the significant effect of the operational parameters. As it can be seen from Fig. 4, the contributions of the operational parameters (X1, X2, X3 and X4) on the percentage of CIP removal efficiency are 30.65%, 17.00%, 29.60% and 4.33%, respectively. Moreover, the contribution of the interaction effect (X1X3) in the percentage of CIP removal was found to be 7.30%. The contributions of the quadratic effects of (X22 and X42) on the CIP removal efficiency were found to be 9.35% and 1.73%, respectively.
"Here Fig. 4" 3.4. Electrocoagulation experiments According to the Eq. (2) obtained for quadratic polynomial model it can be concluded that the average value of CIP removal efficiency is 75.41 % when all operational parameters are fixed at their center point values. Since the magnitude of coefficients in front of each term shows the importance degree of that term, it is noteworthy to mention that, the most influencing terms among the significant operational parameters were found to be initial CIP concentration, followed by current density, pH and reaction time, respectively. According to the Eq. 2, it can be concluded that the removal efficiency of CIP decreased 16.22% (2×8.11) by increasing its concentration from 32.5 (-1 level) to 77.50 mg.L-1 (+1 level). However, the removal efficiency increased 15.94% (2×7.97) when current density increased from 7.5 mA.cm-2 (-1 level) to 12.50 mA.cm-2 (+1 level). The obtained results revealed that increasing in the initial concentration of the CIP contaminant resulted in decreases of removal efficiency of CIP. As it can be seen from Fig. 5,
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at the center point of the mentioned significant operational parameters including 10 mA.cm-2 current density, 7.0 pH and 17.5 min reaction time, the removal efficiency of CIP decreases from 83.52% to 67.31% by increasing its concentration from 32.5 to 77.5 mg.L-1. This is probably due to the fact that the number of metal hydroxide flocs formed may be insufficient to sediment the greater number of CIP molecules at higher initial contaminant concentrations. It was found that, the removal efficiency was decreased with respect to the increase in the initial concentration of CIP. It is known that, at a constant current density, according to Faraday’s law, the generated aluminum flocs during a certain time remain constant for various CIP concentrations. However, in the higher CIP concentration, the requirement for aluminum flocs will be greater and therefore it becomes insufficient to remove the extra organic CIP.
"Here Fig. 5" To investigate the effect of pH on removal efficiency of CIP, the EC processes were carried out over wide pH range of 4.0 to 10.0. It is known that, due to the protonation of amine group of CIP in pH lower than 6.1; the mentioned molecules exist in a cationic form. However, owing to the loss of a proton from the carboxylic group, CIP exist in an anionic form in pH higher than 8.7. Furthermore, due to the charge balance between the two groups mentioned above in the pH range of 6.1-8.7, CIP molecules exist in zwitterion from. 3D surface plots of Fig.6 demonstrated the combined effects of solution pH and CIP concentration on removal efficiency.
"Here Fig. 6" The obtained results revealed that, increasing the solution pH resulted in improving the removal efficiency of CIP contaminant and the maximum removal efficiency observed at pH
12
value of 7.75. It can be seen that, the effect of pH on the removal efficiency in the range of 5.5-7 in more significant in compare to the range of 7-8.5. Moreover, it is noteworthy to mentioned that at low initial pH condition, aluminum hydroxides which are the hydrolysis products of Al3+ are soluble; therefore they are not capable to absorb the pollutants. Al(OH)2+ and Al(OH)2+ are the main cationic species of Al3+ hydrolysis reactions (Asaithambi et al., 2012). Al3+ ions which generated electrochemically from the sacrificial anode can go through hydrolysis process to produce a series of activated intermediates that are able to destabilize the CIP contaminant molecules present in the wastewater to be treated. As it can be seen from the reactions bellow, the destabilized particles then aggregate to form flocks: Cathode reaction: 2H2O + 2e-
H2(g) + 2OH-
(1)
Al3+ + 3e-
(2)
Al(OH)3 + 3H+(aq)
(3)
Aln(OH)3n
(4)
Anode reaction: Al In the solution: Al3+ (aq) + 3H2O nAl(OH)3
The generated cationic hydroxides complexes (Aln(OH)3n) as coagulants are able to remove CIP contaminant efficiently by adsorption and neutralizing its surface charge and consequently forming flocs. Adsorption of pollutant molecules on metal hydroxide precipitates, which is known as “sweep flocculation” mechanism controlled the efficient removal of CIP contaminant. The effect of current density on the removal efficiency of CIP contaminant was investigated and presented in Fig.7. As it can be seen, the removal efficiency of CIP increased from 67.45% to 83.38% by increasing the current density from 7.5 to 12.5 mA.cm-2 at the center
13
point of the significant operational parameters including 55 mg.L–1 CIP concentration, 7.0 pH and 17.5 min reaction time.
"Here Fig. 7" Current density as a significant operational parameter can affect the efficiency of EC process by controlling the concentration of generated Al3+ and OH- and production rate of metal hydroxides as coagulants, bubble production rate, size and growth of the flocs for sedimentation of the CIP contaminants through controlling the reaction rate of anode dissolution rate and cathode in EC process (Aziz et al., 2016; Daneshvar et al., 2006). According to the obtained results presented in Fig.8, it was found that the reaction time of EC process affected the removal efficiency of CIP contaminant. As it can be seen the removal efficiency of CIP increased from 70.84% to 76.54% by increasing the reaction time from 11.25 to 23.75 min in the constant value of 55 mg.L–1 CIP concentration, 7.0 pH and 10 mA.cm-2 current density as the center point of the mentioned significant operational parameters. The observed curvature in the plot indicates that there is an optimum range of 18–23 min for reaction time with maximum value of approximately 20 min, however, beyond the optimum electrolysis time the removal rate decreased as a result of the desorption phenomenon. The reaction time of 20 min which is required to reach the equilibrium remains unaltered at different CIP concentration from 10–100mg.L-1.
"Here Fig. 8" 3.5. EC process optimal condition The optimal operating condition of pH 7.78, inter-electrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07 M NaCl with the initial CIP concentration of 32.5 mg.L-1 was presented to the designed quadratic model to achieve the
14
superior removal performance. The obtained experimental value for CIP removal efficiency and predicted value by model were 88.57% and 90.34%, respectively (see Table 4). It can be concluded that, there is a satisfactory agreement between the obtained experimental CIP removal efficiency and as estimated by the quadratic model. Hence, it confirmed the accuracy and precision of the designed model in successful prediction of CIP removal efficiency.
"Here Table 4" 3.6. CIP contaminant removal from hospital wastewater The real samples of wastewater were prepared through mixing of 1 mL hospital wastewater with 5 mL of extracting solution and stirring for 15 seconds and immediately centrifuging at 3000 rpm for 5 min. Subsequently, the supernatant was collected and the remained sediment re-extracted using 5 mL of extracting solution once more. Afterwards, the obtained supernatants centrifuged at 3000 rpm for 5 min and filtered using 0.22 µm PTFE syringe filter and were injected into the HPLC system (Yoosefian et al., 2017). The obtained results revealed that, the initial CIP contaminant concentration of 154±6 µgL-1 reached to zero after applying EC process under optimal condition.
3.7. Evaluation of electrical energy and electrode consumption The amount of aluminum electrode consumption during EC process under optimal condition was found to be 0.0167 g during a single run using the Eq. 4, expressed as below. 𝐼𝑡𝑀 𝐸𝐿𝐶 = ( ) 𝑛𝐹
(4)
where I, t, M, n and F denote applied electrical current (A), reaction time (s), molecular mass (g.mol-1), the number of electrons and Faraday’s constant (96,485 C.mol-1), respectively. The obtained amount of aluminum electrode consumption during a single run revealed that
15
for treatment of 1 m3 of hospital wastewater under optimal condition of EC process, 66.80 g of the electrode was consumed. On the other hand, the amount of electrical energy consumption during EC process under optimal condition was found to be 0.327 kWh.m-3 using Eq.5 expressed as follow(Ezechi et al., 2014): 𝐸𝐸𝐶 = (
𝑈𝐼𝑡 ) 𝑉
( 5)
where U, I, t, and V denote applied voltage (V), applied electrical current (A), reaction time (h) and volume of sample (L), respectively. 3.8. Adsorption kinetics To investigate the CIP adsorption kinetics, the pseudo-first order kinetic model widely used. As it can be seen from Eq.6, the linear form of pseudo-first order model was presented, where qe and qt denote the adsorption capacities at equilibrium and at time t (mg.g-1), respectively. k1 is the rate constant of pseudo-first order adsorption (min-1) (Vasudevan and Lakshmi, 2011). log( 𝑞𝑒 − 𝑞𝑡 ) = log(𝑞𝑒 ) − 𝑘1 𝑡/2.303
(6)
As it can be seen from Table 5, the values of the parameters are presented. The pseudosecond order rate described as follow (Kamaraj et al., 2016): 𝑡 𝑞𝑡
=
1 𝑘2 𝑞𝑒2
+
𝑡 𝑞𝑒
(7)
where qe as the equilibrium adsorption capacity and k2 as the pseudo second- order constants (g.mg-1 min-1) can be obtained from the slope and intercept of plot t/qt versus t. The obtained results revealed that the adsorption of CIP on Al flocs best fitted to the pseudosecond-order kinetic model with R2 =0.9711. Some other thermodynamic investigations were conducted by the current research group where qualified our studies to a great extant and can 16
be extended in further investigation (Ahmadzadeh et al., 2011a; Ahmadzadeh et al., 2011b; Ahmadzadeh et al., 2015b; Rounaghi et al., 2009).
"Here Table 5" 3.9. Adsorption isotherms In the current work the isotherms CIP adsorption were investigated according to Freundlich and Langmuir models. The Freundlich isotherm as an experimental equation described as follow, where kf and n denote Freundlich constants of adsorption capacity and adsorption intensity, respectively. 1
𝑙𝑜𝑔𝑞𝑒 = 𝑙𝑜𝑔𝐾𝑓 + (𝑛) 𝑙𝑜𝑔𝐶𝑒
(8)
The Langmuir isotherm in its mathematical format presented as follow, where qm (mg.g-1) and b denote the maximum adsorption capacity and the energy constant respectively. 𝐶𝑒 𝑞𝑒
=
𝐶𝑒 𝑞𝑚
+
1 𝑏𝑞𝑚
(9)
As it can be seen from Table 6, the obtained results revealed that the isotherm model of the adsorption best fitted into the Langmuir isotherm with R2 coefficient of 0.9954. It can be concluded that the adsorption of CIP on flocs follow monolayer adsorption model.
"Here Table 6" 4. Conclusions The current work was aimed to investigate the effect of independent variables on the removal efficiency of CIP from hospital wastewater using response surface methodology. The experimental obtained results revealed that under optimal condition of pH 7.78, interelectrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07M NaCl with the initial CIP concentration of 32.5 mg.L-1, the CIP removal efficiency of 88.57% was achieved which is in satisfactory agreement with the predicted 17
removal efficiency of 90.34% by the designed quadratic model and it confirmed the accuracy and precision of the model in successful prediction of CIP removal efficiency. It can be concluded that the adsorption of CIP molecules on aluminum hydroxide precipitates, which is known as sweep flocculation mechanism controlled the efficient removal of CIP contaminant from hospital wastewater. The obtained results revealed reasonable operating cost of 66.8 g.m-3 electrode consumption and 0.613 kWh.m-3 energy consumption for CIP contaminant removal from hospital wastewater.
Acknowledgements The authors express their appreciation to Neuroscience Research Center and Pharmaceutics Research Center both affiliated to Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
18
References Ahmadzadeh, S., Kassim, A., Rezayi, M., Abdollahi, Y., Hossein, G., 2011a. A conductometric study of complexation reaction between meso-octamethylcalix [4] pyrrole with titanium cation in acetonitrile-ethanol binary mixtures. Int. J. Electrochem. Sci 6, 47494759. Ahmadzadeh, S., Kassim, A., Rezayi, M., Rounaghi, G.H., 2011b. Thermodynamic Study of the Complexation of p-Isopropylcalix [6] arene with Cs+ Cation in DimethylsulfoxideAcetonitrile Binary Media. Molecules 16, 8130-8142. Ahmadzadeh, S., Rezayi, M., Faghih-Mirzaei, E., Yoosefian, M., Kassim, A., 2015a. Highly Selective Detection of Titanium (III) in Industrial Waste Water Samples Using Mesooctamethylcalix [4] pyrrole-Doped PVC Membrane Ion-Selective Electrode. Electrochimica Acta 178, 580-589. Ahmadzadeh, S., Rezayi, M., Karimi-Maleh, H., Alias, Y., 2015b. Conductometric measurements of complexation study between 4-Isopropylcalix [4] arene and Cr 3+ cation in THF-DMSO binary solvents. Measurement 70, 214-224. Ahmadzadeh, S., Rezayi, M., Kassim, A., Aghasi, M., 2015c. Cesium selective polymeric membrane sensor based on p-isopropylcalix [6] arene and its application in environmental samples. RSC Advances 5, 39209-39217. Asaithambi, P., Aziz, A.R.A., Daud, W.M.A.B.W., 2016. Integrated ozone— electrocoagulation process for the removal of pollutant from industrial effluent: Optimization through response surface methodology. Chemical Engineering and Processing: Process Intensification 105, 92-102. Asaithambi, P., Susree, M., Saravanathamizhan, R., Matheswaran, M., 2012. Ozone assisted electrocoagulation for the treatment of distillery effluent. Desalination 297, 1-7. Aziz, A.R.A., Asaithambi, P., Daud, W.M.A.B.W., 2016. Combination of electrocoagulation with advanced oxidation processes for the treatment of distillery industrial effluent. Process Safety and Environmental Protection 99, 227-235. Bajpai, S.K., Bajpai, M., Rai, N., 2012. Sorptive removal of ciprofloxacin hydrochloride from simulated wastewater using sawdust: Kinetic study and effect of pH. Water SA 38, 673682. Barışçı, S., Turkay, O., 2016. Optimization and modelling using the response surface methodology (RSM) for ciprofloxacin removal by electrocoagulation. Water Science and Technology 73, 1673-1679. Daneshvar, N., Oladegaragoze, A., Djafarzadeh, N., 2006. Decolorization of basic dye solutions by electrocoagulation: an investigation of the effect of operational parameters. Journal of hazardous materials 129, 116-122.
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Dewitte, B., Dewulf, J., Demeestere, K., Van De Vyvere, V., De Wispelaere, P., Van Langenhove, H., 2008. Ozonation of ciprofloxacin in water: HRMS identification of reaction products and pathways. Environmental science & technology 42, 4889-4895. Doltabadi, M., Alidadi, H., Davoudi, M., 2016. Comparative study of cationic and anionic dye removal from aqueous solutions using sawdust‐based adsorbent. Environmental Progress & Sustainable Energy. El-Shafey, E.-S.I., Al-Lawati, H., Al-Sumri, A.S., 2012. Ciprofloxacin adsorption from aqueous solution onto chemically prepared carbon from date palm leaflets. Journal of Environmental Sciences 24, 1579-1586. Emamjomeh, M.M., Sivakumar, M., 2009. Fluoride removal by a continuous flow electrocoagulation reactor. Journal of Environmental Management 90, 1204-1212. Ezechi, E.H., Isa, M.H., Kutty, S.R.M., Yaqub, A., 2014. Boron removal from produced water using electrocoagulation. Process Safety and Environmental Protection 92, 509-514. Fouladgar, M., Ahmadzadeh, S., 2016. Application of a nanostructured sensor based on NiO nanoparticles modified carbon paste electrode for determination of methyldopa in the presence of folic acid. Applied Surface Science 379, 150-155. Gandhi, M.R., Vasudevan, S., Shibayama, A., Yamada, M., 2016. Graphene and Graphene‐ Based Composites: A Rising Star in Water Purification‐A Comprehensive Overview. ChemistrySelect 1, 4358-4385. Kamaraj, R., Davidson, D., Sozhan, G., Vasudevan, S., 2015. Adsorption of herbicide 2-(2, 4-dichlorophenoxy) propanoic acid by electrochemically generated aluminum hydroxides: an alternative to chemical dosing. RSC Advances 5, 39799-39809. Kamaraj, R., Davidson, D.J., Sozhan, G., Vasudevan, S., 2014a. Adsorption of 2, 4dichlorophenoxyacetic acid (2, 4-D) from water by in situ generated metal hydroxides using sacrificial anodes. Journal of the Taiwan Institute of Chemical Engineers 45, 2943-2949. Kamaraj, R., Davidson, D.J., Sozhan, G., Vasudevan, S., 2014b. An in situ electrosynthesis of metal hydroxides and their application for adsorption of 4-chloro-2-methylphenoxyacetic acid (MCPA) from aqueous solution. Journal of Environmental Chemical Engineering 2, 2068-2077. Kamaraj, R., Pandiarajan, A., Gandhi, M.R., Shibayama, A., Vasudevan, S., 2017. Eco– friendly and Easily Prepared GrapheneNanosheets for Safe Drinking Water: Removal of Chlorophenoxyacetic Acid Herbicides. ChemistrySelect 2, 342-355. Kamaraj, R., Pandiarajan, A., Jayakiruba, S., Naushad, M., Vasudevan, S., 2016. Kinetics, thermodynamics and isotherm modeling for removal of nitrate from liquids by facile one-pot electrosynthesized nano zinc hydroxide. Journal of Molecular Liquids 215, 204-211. Kamaraj, R., Vasudevan, S., 2015. Evaluation of electrocoagulation process for the removal of strontium and cesium from aqueous solution. Chemical Engineering Research and Design 93, 522-530.
20
Kamaraj, R., Vasudevan, S., 2016. Facile one-pot electrosynthesis of Al (OH) 3–kinetics and equilibrium modeling for adsorption of 2, 4, 5-trichlorophenoxyacetic acid from aqueous solution. New Journal of Chemistry 40, 2249-2258. Kassim, A., Rezayi, M., Ahmadzadeh, S., Rounaghi, G., Mohajeri, M., Yusof, N.A., Tee, T.W., Heng, L.Y., Abdullah, A.H., 2011. A Novel ion selective polymeric membrane sensor for determining thallium (I) with high selectivity, IOP Conference Series: Materials Science and Engineering. IOP Publishing, p. 012010. Khandegar, V., Saroha, A.K., 2013a. Electrocoagulation for the treatment of textile industry effluent–A review. Journal of environmental management 128, 949-963. Khandegar, V., Saroha, A.K., 2013b. Electrocoagulation for the treatment of textile industry effluent – A review. Journal of Environmental Management 128, 949-963. Mohan, S., Singh, Y., Verma, D.K., Hasan, S.H., 2015. Synthesis of CuO nanoparticles through green route using Citrus limon juice and its application as nanosorbent for Cr(VI) remediation: Process optimization with RSM and ANN-GA based model. Process Safety and Environmental Protection 96, 156-166. Palmisano, R., Campanella, L., Ambrosetti, B., 2015. Photo-Degradation of Amoxicillin, Streptomycin, Erythromycin and Ciprofloxacin by UV and UV/TiO2 Processes. Evaluation of Toxicity Changes Using a Respirometric Biosensor. Journal of Environmental Analytical Chemistry 2015. Pardakhty, A., Ahmadzadeh, S., Avazpour, S., Gupta, V.K., 2016. Highly sensitive and efficient voltammetric determination of ascorbic acid in food and pharmaceutical samples from aqueous solutions based on nanostructure carbon paste electrode as a sensor. Journal of Molecular Liquids 216, 387-391. Rezayi, M., Karazhian, R., Abdollahi, Y., Narimani, L., Sany, S.B.T., Ahmadzadeh, S., Alias, Y., 2014. Titanium (III) cation selective electrode based on synthesized tris (2pyridyl) methylamine ionophore and its application in water samples. Scientific reports 4, 0000-0025. Rounaghi, G., Mohajeri, M., Ahmadzadeh, S., Tarahomi, S., 2009. A thermodynamic study of interaction of Na+ cation with benzo-15-crown-5 in binary mixed non-aqueous solvents. Journal of Inclusion Phenomena and Macrocyclic Chemistry 63, 365-372. Soltani, H., Pardakhty, A., Ahmadzadeh, S., 2016. Determination of hydroquinone in food and pharmaceutical samples using a voltammetric based sensor employing NiO nanoparticle and ionic liquids. Journal of Molecular Liquids 219, 63-67. Somayajula, A., Asaithambi, P., Susree, M., Matheswaran, M., 2012. Sonoelectrochemical oxidation for decolorization of Reactive Red 195. Ultrasonics Sonochemistry 19, 803-811. Vasudevan, S., 2014. An efficient removal of phenol from water by peroxi-electrocoagulation processes. Journal of Water Process Engineering 2, 53-57. Vasudevan, S., Lakshmi, J., 2011. Studies relating to an electrochemically assisted coagulation for the removal of chromium from water using zinc anode. Water Science and Technology: Water supply 11, 142-150. 21
Vasudevan, S., Lakshmi, J., Sozhan, G., 2011a. Effects of alternating and direct current in electrocoagulation process on the removal of cadmium from water. Journal of Hazardous Materials 192, 26-34. Vasudevan, S., Lakshmi, J., Sozhan, G., 2011b. Studies on the Al–Zn–In-alloy as anode material for the removal of chromium from drinking water in electrocoagulation process. Desalination 275, 260-268. Wang, C.-J., Li, Z., Jiang, W.-T., Jean, J.-S., Liu, C.-C., 2010. Cation exchange interaction between antibiotic ciprofloxacin and montmorillonite. Journal of Hazardous Materials 183, 309-314. Wu, Q., Li, Z., Hong, H., Yin, K., Tie, L., 2010. Adsorption and intercalation of ciprofloxacin on montmorillonite. Applied Clay Science 50, 204-211. Yoosefian, M., Ahmadzadeh, S., Aghasi, M., Dolatabadi, M., 2017. Optimization of electrocoagulation process for efficient removal of ciprofloxacin antibiotic using iron electrode; kinetic and isotherm studies of adsorption. Journal of Molecular Liquids 225, 544553. Zaidi, S., Chaabane, T., Sivasankar, V., Darchen, A., Maachi, R., Msagati, T.A.M., Prabhakaran, M., 2016. Performance efficiency of electro-coagulation coupled electroflotation process (EC-EF) versus adsorption process in doxycycline removal from aqueous solutions. Process Safety and Environmental Protection 102, 450-461.
22
Figure caption Fig. 1 Major pathways of antibiotics release into the environment which cause antibiotic resistance for human. Fig.2 Effect of electrolyte type; CIP concentration 50 mg.L-1, current density 10 mA.cm2
,solution pH at 7, inter-electrode distance 1.0 cm and concentration of electrolyte 0.05 M.
Fig. 3 Effect of electrolyte dose; CIP concentration 50 mg.L-1, current density 10 mA.cm2
,solution pH at 7 and inter-electrode distance 1.0 cm.
Fig. 4 Graphical Pareto analysis of significant parameters effect on CIP removal. Fig. 5 Percentage of CIP removal as a function of initial CIP concentration; solution pH at 7, current density 10 mA.cm-2, reaction time 17.5 min. Fig. 6 Percentage of CIP removal as a function of initial CIP concentration and solution pH; current density 10 mA.cm-2, reaction time 17.5 min. Fig. 7 Percentage of CIP removal as a function of current density and initial CIP concentration; solution pH at 7, reaction time 17.5 min. Fig. 8 Percentage of CIP removal as a function of reaction time and initial CIP concentration; solution pH at 7, reaction time 17.5 min, current density 10 mA.cm-2.
23
Fig. 1
24
100
KNO3 KNO3
Removal CIP (%)
80
NaCl NaCl
60
NH4 Cl NH4Cl CaCl2 CaCl2
40
KCl KCl 20
Na2 SO4 Na2SO4
0
0
10
20
30
time(min) Fig. 2
25
40
50
100
0.1 M
Removal CIP(%)
80
0.07 M 60
0.05 M 40
0.03 M 20
0.01 M 0 0
5
10
15
20
time(min)
Fig. 3
26
25
30
35
35
Contributions (%)
30 25 20 15 10 5 0 X1 X1
X2 X2
X3 X3
X4 X4
X1X3 X1X3
Fig. 4
27
X22 X22
X42 X42
Fig. 5
28
86
CIP Removal (%)
78.5 71 63.5 56
8.50 7.75 B: Solution pH
7.00 6.25 5.50
32.50
43.75
55.00
66.25
77.50
A:Initial CIP Concentration (mg.L-1)
Fig. 6
29
CIP Removal (%)
A:Initial CIP Concentration (mg.L-1)
77.50
61
66.25
66 71
55.00
77 81
43.75
85
32.50 7.50
8.75
10.00
11.25
12.50
C: Current Density (mA.cm-2)
Fig. 7
30
Fig. 8
31
Table 1 Coded and actual values of numeric factors. Coded
Experimental Field
Variables Factors (Ui)
(Xi)
-α
-1 level
0
+1 level
+α
X1
A= Initial CIP Concentration (mg.L-1)
10
32.5
55
77.5
100
X2
B= Solution pH
4
5.5
7
8.5
10
X3
C= Current Density (mA.cm-2)
5
7.5
10
12.5
15
X4
D= Reaction Time (min)
5
11.25
17.5
23.75
30
32
Table 2 Experimental results of CIP removal as a function of coded and actual values of four factors in CCD matrix. Standard Actual values order A(mg.L-1) B
Coded values C(mA.cm-2)
D(min) X1 X2 X3 X4
1 2 3 4 5 6 7 8 9
32.5 77.5 32.5 77.5 32.5 77.5 32.5 77.5 32.5
5.5 5.5 8.5 8.5 5.5 5.5 8.5 8.5 5.5
7.5 7.5 7.5 7.5 12.5 12.5 12.5 12.5 7.5
11.25 11.25 11.25 11.25 11.25 11.25 11.25 11.25 23.75
-1 1 -1 1 -1 1 -1 1 -1
-1 -1 1 1 -1 -1 1 1 -1
-1 -1 -1 -1 1 1 1 1 -1
-1 -1 -1 -1 -1 -1 -1 -1 1
61.48 41.12 74.95 61.34 75.46 65.00 86.14 84.37 76.84
10
77.5
5.5
7.5
23.75
1
-1
-1
1
50.72
11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
32.5 77.5 32.5 77.5 32.5 77.5 10 100 55 55 55 55 55 55 55 55 55 55 55 55
8.5 8.5 5.5 5.5 8.5 8.5 7 7 4 10 7 7 7 7 7 7 7 7 7 7
7.5 7.5 12.5 12.5 12.5 12.5 10 10 10 10 5 15 10 10 10 10 10 10 10 10
23.75 23.75 23.75 23.75 23.75 23.75 17.5 17.5 17.5 17.5 17.5 17.5 5 30 17.5 17.5 17.5 17.5 17.5 17.5
-1 1 -1 1 -1 1 -2 2 0 0 0 0 0 0 0 0 0 0 0 0
1 1 -1 -1 1 1 0 0 -2 2 0 0 0 0 0 0 0 0 0 0
-1 -1 1 1 1 1 0 0 0 0 -2 2 0 0 0 0 0 0 0 0
1 1 1 1 1 1 0 0 0 0 0 0 -2 2 0 0 0 0 0 0
83.11 56.48 73.14 70.98 90.37 81.39 97.25 54.98 43.55 64.28 53.12 88.31 54.09 74.11 74.60 76.75 70.29 73.04 77.08 74.35
33
CIP removal (%)
Table 3 ANOVA results for response surface of quadratic model. Analysis of variance Response Source
degree Sum of square
P-value Mean square
F-value
freedom
CIP
Prob>F
Model
5079.127
7
725.5895
31.25373
< 0.0001
Residual
510.7541
22
23.21609
-
-
Lack of Fit
479.279
17
28.19288
4.478603
0.0526
Pure error
31.47508
5
6.295017
-
-
removal (%)
34
Table 4 Optimal condition and comparison between actual value and predicted value.
Parameters
Optimal value
Interelectrode distance (cm)
pH
(mg.L-1)
Electrolyte Type and dosage (M)
32.5
0.07 M NaCl
1
7.8
Initial concentration
35
Current density
Removal (%) (predict)
Removal
(mA.cm-2)
Reaction time (min)
12.5
20
90.34
88.57
(%) (experimental)
Table 5. Kinetic parameters for the adsorption of CIP on Al flocs.
First order kinetic
Second kinetic
R2
0.8349
K1(min-1)
157.14
2 order R
0.9711
K2 (g.min.mg-1)
1.02×10-5
qe (mg.g-1)
303.03
36
Table 6. Parameters obtained from Freundlich and Langmuir isotherms
Langmuir isotherm
Freundlich isotherm
qm (mg.g-1)
b (L.mg-1)
R2
Kf
n
R2
476.19
1.25
0.9954
309.88
2.45
0.9917
37
38
S0957-5820(17)30143-X http://dx.doi.org/doi:10.1016/j.psep.2017.04.026 PSEP 1056
To appear in:
Process Safety and Environment Protection
Received date: Revised date: Accepted date:
18-1-2017 18-4-2017 24-4-2017
Please cite this article as: Ahmadzadeh, Saeid, Asadipour, Ali, Pournamdari, Mostafa, Behnam, Behzad, Rahimi, Hamid Reza, Dolatabadi, Maryam, Removal of ciprofloxacin from hospital wastewater using electrocoagulation technique by aluminum electrode; optimization and modelling through response surface methodology.Process Safety and Environment Protection http://dx.doi.org/10.1016/j.psep.2017.04.026 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Removal of ciprofloxacin from hospital wastewater using electrocoagulation
technique
by
optimization
modelling
through
and
aluminum response
electrode; surface
methodology
Saeid Ahmadzadeh *a,b, Ali Asadipour c, Mostafa Pournamdari c, Behzad Behnam b, Hamid Reza Rahimi d, Maryam Dolatabadi *e a
Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran. b
Pharmaceutics Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran. c
Department of Medicinal Chemistry, Faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran. d
Department of Toxicology and Pharmacology, faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran. e
Department of Environmental Health, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
*Corresponding authors E-mail: [email protected] (S. Ahmadzadeh) [email protected] (M. Dolatabadi) Tel.: +98 3431325241; Fax: +98 3431325215
1
Graphical abstract
Graphical Abstract Caption: Major pathways of antibiotics release into the environment which cause antibiotic resistance for human.
HIGHLIGHTS
Hospital wastewater were used for real sample analysis in the current work
Removal of CIP was successfully optimized using response surface methodology
Electrical energy consumption at optimum operating conditions was 0.613 kWh.m-3.
2
Abstract Pharmaceuticals as severe contaminants of surface and ground water around the manufacturing communities and residential zones received growing attention recently. Since, there is no report on ciprofloxacin (CIP) removal using electrocoagulation (EC) process by aluminum electrodes, the present work deals with efficient removal of CIP from hospital wastewater using mentioned method. Response surface methodology (RSM) was used to evaluate the main effects of parameters, their simultaneous interactions and quadratic effect to achieve the optimum condition for EC process. According to the obtained results from regression analysis, it was found that the experimental data are best fitted to the second-order polynomial model with coefficient of determination (R2) value of 0.9086, adjust correlation coefficient (Adj.R2) value of 0.8796 and predicted correlation coefficient (pred. R2) value of 0.7834. EC process was applied successfully with removal efficiency of 88.57% under optimal operating condition of pH 7.78, inter-electrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07 M NaCl with the initial CIP concentration of 32.5 mg.L-1. The experimental efficiency was in satisfactory agreement with the predicted efficiency of 90.34%. The obtained results revealed that, sweep flocculation as a determinant mechanism controlled the adsorption of CIP molecules on aluminum hydroxide precipitates. Electrode consumption and electrical energy consumption were found to be
66.80 g.m-3 and 0.613 kWh.m-3, respectively. The obtained results from real sample analysis revealed that the initial CIP concentration of 154±6 µgL-1 of hospital wastewater were found to reached to zero after applying optimal condition of EC process.
Keywords: Hospital wastewater treatment; Electrocoagulation process; Al electrode; Ciprofloxacin; Response surface methodology; Electrical energy consumption
3
1. Introduction The 1960s was a decade that for the first times the presence of pharmaceuticals and personal care products (PPCPs) were diagnosed in surface waters in United States and Europe. Antibiotics as one of the most widely used PPCPs are approximately 90% excreted in urine and up to 75% in animal excrement, entering to the wastewater system as their parent forms (El-Shafey et al., 2012). Ciprofloxacin (CIP) as a synthetic antibiotic has been widely used for treatment of bacterial infectious disease in humans and animals. It is noteworthy to mention that drug manufacturers and hospitals are the most important sources of contaminated wastewaters. Inappropriate disposal of unused or expired CIP and its incomplete metabolization severely results in its increasing contamination in surface water during the last decade (Dewitte et al., 2008; El-Shafey et al., 2012). According to the statistics presented by the health communities, the amount of CIP contamination discerned in surface water and underground water were within the concentration range of 1˂µg.L-1, respectively. However, the detected amount of CIP in the waste water of hospitals and drug manufacturers is much higher up to 150
µg.L-1 and 50 mg.L-1, respectively, which is
extremely harmful to the health of the human beings (El-Shafey et al., 2012). Most of the conventional treatments such as activated sludge and trickling filter applied in wastewater treatment plants were unsuccessful which results in releasing them in environment and consequently contamination of surface water, soil and ground water. It is reported that the presence of CIP in daily drinking water may cause nervousness, nausea, vomiting, headaches, diarrhea and tremors. Higher concentrations may cause serious adverse effects including thrombocytopenia, acute renal failure, and elevation of liver enzymes, eosinophilia and leucopenia. On the other hand, the presence of CIP in water sources results in development of bacteria resistant to antibiotics which seriously emerging threat to public health and requires action across all government sectors and societies (Bajpai et al., 2012; Wang et al., 2010; Wu 4
et al., 2010; Zaidi et al., 2016). The treatments of resistant bacteria are difficult, costly and toxic which require alternative medications or higher doses (Somayajula et al., 2012; Vasudevan, 2014; Vasudevan et al., 2011a, b).
"Here Fig. 1" Literature surveys revealed that developing an efficient and economical procedure for CIP contamination removal from drinking water supply and wastewaters before releasing them into the environment received a great attention, recently. Since CIP is resistant to microbial metabolism, it cannot be efficiently degraded by means of biological treatment processes (Palmisano et al., 2015). Several techniques such as Adsorption (Gandhi et al., 2016; Kamaraj et al., 2015; Kamaraj et al., 2014a, b; Kamaraj et al., 2017; Kamaraj and Vasudevan, 2016), advanced oxidation process (Dewitte et al., 2008) , have been studied for removal of CIP from the contaminated water. However, among all of them electrochemical techniques such as electrocoagulation (EC) as an advanced, efficient and economical technique received extensive practical applicability by providing satisfactory result for treating various wastewater contaminants such as heavy metals (Kamaraj and Vasudevan, 2015), fluoride (Emamjomeh and Sivakumar, 2009), dyes (Daneshvar et al., 2006), drug (Khandegar and Saroha, 2013a) , phenol (Vasudevan, 2014). EC technique included coagulation process in which coagulant agent gets produced in situ through electrochemical reactions of sacrificial anode dissolution. (Khandegar and Saroha, 2013b). Electro-synthesized of coagulant provide competitive advantages of producing less sludge thus lowering the sludge disposal cost, removing many species that chemical coagulation cannot remove and the produced sludge is more readily filterable and can be utilized as a soil additive. Other considerable advantages of EC technique including low cost process and maintenance, no harmful substances generation, producing low amount of TDS and secondary pollutants and removing the smallest size of
5
colloidal particles caused its increasingly usage. However, it does not require any chemical storage like adsorption or biological processes. Besides the current studies using electrochemistry, on the other hand, using electrochemical sensors as a device which provides a certain type of response that is directly related to the quantity of a chemical species such as contaminants, showed a rapid growing scientific studies in environmental monitoring field and practiced by the current research group recently (Ahmadzadeh et al., 2015a; Ahmadzadeh et al., 2015c; Fouladgar and Ahmadzadeh, 2016; Kassim et al., 2011; Pardakhty et al., 2016; Rezayi et al., 2014; Soltani et al., 2016). To the best of our knowledge, there is not any report on CIP removal using EC process by aluminum electrodes. So far only one report based on EC process was found for CIP removal from aqueous solution using iron electrode (Barışçı and Turkay, 2016). However, the reported EC process suffered from low removal efficiency for CIP contaminants in its optimized concentration of 5 mg.L-1 in compare to the current work with optimized concentration of 32.5 mg.L-1 CIP contaminants. Hence developing of EC process using aluminum electrodes can be regarded as a new and potential research area for CIP contamination removal from hospital and industrial wastewater. Since, most of the reported studies are based on one factor at the time method, in the current study, RSM was used to evaluate the main effects of parameters, their simultaneous interactions and quadratic effect to achieve the optimum condition for EC process. The effects of various operating parameters such as electrolyte type and concentration, inter-electrode distance, initial CIP concentration, pH, current density and reaction time were investigated to achieve the best efficient and CIP contamination remove condition.
2. Materials and methods 2.1. Chemicals 6
CIP (C17H18FN3O3·HCl·H2O, 385.8mol.wt.) purchased from darou pakhsh pharmaceutical company, Mashhad, Iran. The mobile phase was prepared using HPLC grade acetonitrile and analytical grade Hydrochloric acid. Electrolytes including MgSO4, NaCl, KNO3, Na2SO4, and CaCl2 were purchased from Merck Company. Hydrochloric acid and sodium hydroxide from Sigma-Aldrich were used for pH adjustments. Acetic acid and ethanol were obtained from Merck Company. All reagents used are analytical reagent grade with the highest available purity which used without any further purification except for vacuum drying over P2O5. All the solutions were prepared using de-ionized water.
2.2. Experimental procedure All experiments were conducted in batch mode by plexiglas electrochemical cell with dimensions of 12×5×5 cm to hold a sample of 250 mL using two aluminum plate electrodes with immersed dimensions of 3×2×0.2 cm. The pH adjustment was carried out by adding small volumes of 0.01 N of HCl or NaOH to the solutions and measured using Metrohm 827 pH/mv meter. KNAUER Smartline HPLC (C8 column; 250×4.6×5 mm) with a UV detector at a wavelength of 272 nm was used for quantitative determination of residual CIP. A mixture of hydrochloric acid 10 mµ and acetonitrile with a ratio of 80/20 (vol.%) was applied as mobile phase with an injection flow rate of 1 mL/min. The solution for extracting the CIP contaminant from wastewater was prepared using absolute ethanol/H2O containing 1% HOAc, 99:1 v/v and 0.8 g Na2SO4.
2.3. Statistical design In order to improve the removal efficiency of CIP, central composite design (CCD) was applied to optimize the experimental conditions under response surface methodology (RSM) category of Design Expert 7 software. In the present work, the CCD consists of 2n factorial
7
points, 2n axial points and moreover a given number of center points, where n is equal to 4 which is the number of numeric factors including initial CIP concentration, solution pH, current density and reaction time. The investigated factors and levels of each factor are presented in Table 1. Experimental data from the CCD was analyzed and fitted to a secondorder polynomial model expressed as below: 𝑛 𝑌 = 𝛽0 + ∑𝑛𝑖=1 𝛽𝑖 𝑋𝑖 + ∑𝑛𝑖=1 𝛽𝑖𝑖 𝑋𝑖2 + ∑𝑛−1 𝑖=1 ∑𝑗=𝑖+1 𝛽𝑖𝑗 𝑋𝑖 𝑋𝑗
(1)
where Y, β0, βi, βii, βij, Xi and Xj denote the predicted response of CIP removal, the intercept parameter, the linear coefficients, the quadratic coefficients, the interaction coefficients and the coded values of independent factors, respectively (Asaithambi et al., 2016; Doltabadi et al., 2016; Mohan et al., 2015). "Here Table 1"
3. Results and discussion 3.1. Preliminary evaluation of electrocoagulation process The effect of electrolyte type and concentration on the removal efficiency of CIP were investigated. The maximum removal was obtained using NaCl as electrolyte at equilibrium time of 20 min (see Fig. 2). Literature surveys revealed that addition of appropriate electrolyte significantly improved the efficiency of EC process due to increasing the conductivity of the wastewater which affects the Faradic yield, cell voltage and consequently energy consumption of the process.
"Here Fig. 2" The presence of NaCl electrolyte plays an important role to overcome the adverse effects of other anions such as CO32-, HCO3− and SO42− which may result in precipitation of Ca2+ cations as insulating layer on the surface of the cathode and increasing the ohmic resistance
8
of the EC cell. However, the extra amount of NaCl caused irregular dissolution of Al electrode, therefore the electrolyte dose of the NaCl (0.01-0.1M) were optimized and presented in Fig.3 The obtained results revealed that the removal efficiency of CIP remained almost unchanged in the range of 0.07 to 0.1 M of electrolyte dose. Therefore, NaCl electrolyte with the optimized concentration of 0.07 M was used for further studies.
"Here Fig. 3" Furthermore, the effect of inter-electrode distance on the removal efficency of CIP was investigated. It is known that, the drop in ohmic potential of the EC cell is proportional to the inter-electrode spacing and on the other hand the distance between electrodes affects the electrolysis energy consumption especially when sample conductivity is low (Khandegar and Saroha, 2013a). The distance between electrodes was changed in the range of 1.0 to 3.0 cm where the current density loading of 15 mA.cm-2, initial CIP concentration of 50 mg.L-1 and pH 7.5 were kept constant. The obtained results revealed that the lowest residual CIP concentration was 4.0 mg.L-1 at inter electrode distance of 1 cm. At inter-electrode distance of 1.5, 2, 2.5 and 3 cm, residual CIP concentrations of 8.35, 16.14, 23.5 and 30.5 mg.L-1 were obtained, respectively. The obtained results were in accordance with other reported investigations that showed by reducing the inter-electrode distance, the resistance of motion was reduced due to shorter travel path and consequently the electrical energy consumption were decreased and efficiency of the process improved. The experimental conditions along with the obtained results of 30 experiments according to RSM design are summarized in Table 2, as it can be seen; the removal of CIP was changed from 41.42 % to 97.25 %.
"Here Table 2"
9
3.2. Fitting of the process model and statistical analysis To evaluate the effects of independent factors including initial CIP concentration, solution pH, current density and reaction time on removal efficiency of CIP, thirty runs were carried out designed by response surface methodology. To obtain the regression equation the experimental results were fitted to the quadratic model. The quadratic polynomial model in terms of coded factors only for significant terms (terms with P-value ≤ 0.05) is expressed as below: 𝑅𝑒𝑚𝑜𝑣𝑎𝑙 (%) = 75.41 − 8.11𝑋1 + 6.04𝑋2 + 7.97𝑋3 + 3.05𝑋4 + 3.96 𝑋1 𝑋3 − 4.48𝑋22 − 1.93𝑋42
(2)
where X1, X2, X3, and X4 denote the initial CIP concentration, solution pH, current density, and reaction time, respectively. The adequacy of model was checked and the obtained results are summarized in Table 3. "Here Table 3" As it can be seen from Table 3, the ANOVA test confirmed that the applied quadratic model was significant with 95% confidence level and F-value of 31.25. Since the amount of P-value probability was more than 0.05, no evidence of lack of fit for the model was observed. Furthermore, the values of the correlation coefficient (R2), adjusted correlation coefficient (Adj. R2) and predicted correlation coefficient (pred. R2) were found to be 0.9086, 0.8796 and 0.7834, respectively, which indicates the experimental and model predicted values are in good agreement. Furthermore, the obtained amount of 20.79 for adequate precision which is more than 4, indicates an adequate signal to noise ratio.
3.3. Pareto analysis Graphical Pareto analysis provides noteworthy information about the importance of the operational parameters to interpret the obtained results. Pareto analysis indicates the 10
percentage effect of each factor on the CIP removal efficiency as the response, according to the equation expressed as bellow: 𝑏2
𝑃𝑖 = ∑ 𝑖 2 × 100 (𝑖 ≠ 0) 𝑏𝑖
(3)
where bi represents the estimation of the significant effect of the operational parameters. As it can be seen from Fig. 4, the contributions of the operational parameters (X1, X2, X3 and X4) on the percentage of CIP removal efficiency are 30.65%, 17.00%, 29.60% and 4.33%, respectively. Moreover, the contribution of the interaction effect (X1X3) in the percentage of CIP removal was found to be 7.30%. The contributions of the quadratic effects of (X22 and X42) on the CIP removal efficiency were found to be 9.35% and 1.73%, respectively.
"Here Fig. 4" 3.4. Electrocoagulation experiments According to the Eq. (2) obtained for quadratic polynomial model it can be concluded that the average value of CIP removal efficiency is 75.41 % when all operational parameters are fixed at their center point values. Since the magnitude of coefficients in front of each term shows the importance degree of that term, it is noteworthy to mention that, the most influencing terms among the significant operational parameters were found to be initial CIP concentration, followed by current density, pH and reaction time, respectively. According to the Eq. 2, it can be concluded that the removal efficiency of CIP decreased 16.22% (2×8.11) by increasing its concentration from 32.5 (-1 level) to 77.50 mg.L-1 (+1 level). However, the removal efficiency increased 15.94% (2×7.97) when current density increased from 7.5 mA.cm-2 (-1 level) to 12.50 mA.cm-2 (+1 level). The obtained results revealed that increasing in the initial concentration of the CIP contaminant resulted in decreases of removal efficiency of CIP. As it can be seen from Fig. 5,
11
at the center point of the mentioned significant operational parameters including 10 mA.cm-2 current density, 7.0 pH and 17.5 min reaction time, the removal efficiency of CIP decreases from 83.52% to 67.31% by increasing its concentration from 32.5 to 77.5 mg.L-1. This is probably due to the fact that the number of metal hydroxide flocs formed may be insufficient to sediment the greater number of CIP molecules at higher initial contaminant concentrations. It was found that, the removal efficiency was decreased with respect to the increase in the initial concentration of CIP. It is known that, at a constant current density, according to Faraday’s law, the generated aluminum flocs during a certain time remain constant for various CIP concentrations. However, in the higher CIP concentration, the requirement for aluminum flocs will be greater and therefore it becomes insufficient to remove the extra organic CIP.
"Here Fig. 5" To investigate the effect of pH on removal efficiency of CIP, the EC processes were carried out over wide pH range of 4.0 to 10.0. It is known that, due to the protonation of amine group of CIP in pH lower than 6.1; the mentioned molecules exist in a cationic form. However, owing to the loss of a proton from the carboxylic group, CIP exist in an anionic form in pH higher than 8.7. Furthermore, due to the charge balance between the two groups mentioned above in the pH range of 6.1-8.7, CIP molecules exist in zwitterion from. 3D surface plots of Fig.6 demonstrated the combined effects of solution pH and CIP concentration on removal efficiency.
"Here Fig. 6" The obtained results revealed that, increasing the solution pH resulted in improving the removal efficiency of CIP contaminant and the maximum removal efficiency observed at pH
12
value of 7.75. It can be seen that, the effect of pH on the removal efficiency in the range of 5.5-7 in more significant in compare to the range of 7-8.5. Moreover, it is noteworthy to mentioned that at low initial pH condition, aluminum hydroxides which are the hydrolysis products of Al3+ are soluble; therefore they are not capable to absorb the pollutants. Al(OH)2+ and Al(OH)2+ are the main cationic species of Al3+ hydrolysis reactions (Asaithambi et al., 2012). Al3+ ions which generated electrochemically from the sacrificial anode can go through hydrolysis process to produce a series of activated intermediates that are able to destabilize the CIP contaminant molecules present in the wastewater to be treated. As it can be seen from the reactions bellow, the destabilized particles then aggregate to form flocks: Cathode reaction: 2H2O + 2e-
H2(g) + 2OH-
(1)
Al3+ + 3e-
(2)
Al(OH)3 + 3H+(aq)
(3)
Aln(OH)3n
(4)
Anode reaction: Al In the solution: Al3+ (aq) + 3H2O nAl(OH)3
The generated cationic hydroxides complexes (Aln(OH)3n) as coagulants are able to remove CIP contaminant efficiently by adsorption and neutralizing its surface charge and consequently forming flocs. Adsorption of pollutant molecules on metal hydroxide precipitates, which is known as “sweep flocculation” mechanism controlled the efficient removal of CIP contaminant. The effect of current density on the removal efficiency of CIP contaminant was investigated and presented in Fig.7. As it can be seen, the removal efficiency of CIP increased from 67.45% to 83.38% by increasing the current density from 7.5 to 12.5 mA.cm-2 at the center
13
point of the significant operational parameters including 55 mg.L–1 CIP concentration, 7.0 pH and 17.5 min reaction time.
"Here Fig. 7" Current density as a significant operational parameter can affect the efficiency of EC process by controlling the concentration of generated Al3+ and OH- and production rate of metal hydroxides as coagulants, bubble production rate, size and growth of the flocs for sedimentation of the CIP contaminants through controlling the reaction rate of anode dissolution rate and cathode in EC process (Aziz et al., 2016; Daneshvar et al., 2006). According to the obtained results presented in Fig.8, it was found that the reaction time of EC process affected the removal efficiency of CIP contaminant. As it can be seen the removal efficiency of CIP increased from 70.84% to 76.54% by increasing the reaction time from 11.25 to 23.75 min in the constant value of 55 mg.L–1 CIP concentration, 7.0 pH and 10 mA.cm-2 current density as the center point of the mentioned significant operational parameters. The observed curvature in the plot indicates that there is an optimum range of 18–23 min for reaction time with maximum value of approximately 20 min, however, beyond the optimum electrolysis time the removal rate decreased as a result of the desorption phenomenon. The reaction time of 20 min which is required to reach the equilibrium remains unaltered at different CIP concentration from 10–100mg.L-1.
"Here Fig. 8" 3.5. EC process optimal condition The optimal operating condition of pH 7.78, inter-electrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07 M NaCl with the initial CIP concentration of 32.5 mg.L-1 was presented to the designed quadratic model to achieve the
14
superior removal performance. The obtained experimental value for CIP removal efficiency and predicted value by model were 88.57% and 90.34%, respectively (see Table 4). It can be concluded that, there is a satisfactory agreement between the obtained experimental CIP removal efficiency and as estimated by the quadratic model. Hence, it confirmed the accuracy and precision of the designed model in successful prediction of CIP removal efficiency.
"Here Table 4" 3.6. CIP contaminant removal from hospital wastewater The real samples of wastewater were prepared through mixing of 1 mL hospital wastewater with 5 mL of extracting solution and stirring for 15 seconds and immediately centrifuging at 3000 rpm for 5 min. Subsequently, the supernatant was collected and the remained sediment re-extracted using 5 mL of extracting solution once more. Afterwards, the obtained supernatants centrifuged at 3000 rpm for 5 min and filtered using 0.22 µm PTFE syringe filter and were injected into the HPLC system (Yoosefian et al., 2017). The obtained results revealed that, the initial CIP contaminant concentration of 154±6 µgL-1 reached to zero after applying EC process under optimal condition.
3.7. Evaluation of electrical energy and electrode consumption The amount of aluminum electrode consumption during EC process under optimal condition was found to be 0.0167 g during a single run using the Eq. 4, expressed as below. 𝐼𝑡𝑀 𝐸𝐿𝐶 = ( ) 𝑛𝐹
(4)
where I, t, M, n and F denote applied electrical current (A), reaction time (s), molecular mass (g.mol-1), the number of electrons and Faraday’s constant (96,485 C.mol-1), respectively. The obtained amount of aluminum electrode consumption during a single run revealed that
15
for treatment of 1 m3 of hospital wastewater under optimal condition of EC process, 66.80 g of the electrode was consumed. On the other hand, the amount of electrical energy consumption during EC process under optimal condition was found to be 0.327 kWh.m-3 using Eq.5 expressed as follow(Ezechi et al., 2014): 𝐸𝐸𝐶 = (
𝑈𝐼𝑡 ) 𝑉
( 5)
where U, I, t, and V denote applied voltage (V), applied electrical current (A), reaction time (h) and volume of sample (L), respectively. 3.8. Adsorption kinetics To investigate the CIP adsorption kinetics, the pseudo-first order kinetic model widely used. As it can be seen from Eq.6, the linear form of pseudo-first order model was presented, where qe and qt denote the adsorption capacities at equilibrium and at time t (mg.g-1), respectively. k1 is the rate constant of pseudo-first order adsorption (min-1) (Vasudevan and Lakshmi, 2011). log( 𝑞𝑒 − 𝑞𝑡 ) = log(𝑞𝑒 ) − 𝑘1 𝑡/2.303
(6)
As it can be seen from Table 5, the values of the parameters are presented. The pseudosecond order rate described as follow (Kamaraj et al., 2016): 𝑡 𝑞𝑡
=
1 𝑘2 𝑞𝑒2
+
𝑡 𝑞𝑒
(7)
where qe as the equilibrium adsorption capacity and k2 as the pseudo second- order constants (g.mg-1 min-1) can be obtained from the slope and intercept of plot t/qt versus t. The obtained results revealed that the adsorption of CIP on Al flocs best fitted to the pseudosecond-order kinetic model with R2 =0.9711. Some other thermodynamic investigations were conducted by the current research group where qualified our studies to a great extant and can 16
be extended in further investigation (Ahmadzadeh et al., 2011a; Ahmadzadeh et al., 2011b; Ahmadzadeh et al., 2015b; Rounaghi et al., 2009).
"Here Table 5" 3.9. Adsorption isotherms In the current work the isotherms CIP adsorption were investigated according to Freundlich and Langmuir models. The Freundlich isotherm as an experimental equation described as follow, where kf and n denote Freundlich constants of adsorption capacity and adsorption intensity, respectively. 1
𝑙𝑜𝑔𝑞𝑒 = 𝑙𝑜𝑔𝐾𝑓 + (𝑛) 𝑙𝑜𝑔𝐶𝑒
(8)
The Langmuir isotherm in its mathematical format presented as follow, where qm (mg.g-1) and b denote the maximum adsorption capacity and the energy constant respectively. 𝐶𝑒 𝑞𝑒
=
𝐶𝑒 𝑞𝑚
+
1 𝑏𝑞𝑚
(9)
As it can be seen from Table 6, the obtained results revealed that the isotherm model of the adsorption best fitted into the Langmuir isotherm with R2 coefficient of 0.9954. It can be concluded that the adsorption of CIP on flocs follow monolayer adsorption model.
"Here Table 6" 4. Conclusions The current work was aimed to investigate the effect of independent variables on the removal efficiency of CIP from hospital wastewater using response surface methodology. The experimental obtained results revealed that under optimal condition of pH 7.78, interelectrode distance 1cm, reaction time 20 min, current density 12.5 mA.cm-2 and electrolyte dose of 0.07M NaCl with the initial CIP concentration of 32.5 mg.L-1, the CIP removal efficiency of 88.57% was achieved which is in satisfactory agreement with the predicted 17
removal efficiency of 90.34% by the designed quadratic model and it confirmed the accuracy and precision of the model in successful prediction of CIP removal efficiency. It can be concluded that the adsorption of CIP molecules on aluminum hydroxide precipitates, which is known as sweep flocculation mechanism controlled the efficient removal of CIP contaminant from hospital wastewater. The obtained results revealed reasonable operating cost of 66.8 g.m-3 electrode consumption and 0.613 kWh.m-3 energy consumption for CIP contaminant removal from hospital wastewater.
Acknowledgements The authors express their appreciation to Neuroscience Research Center and Pharmaceutics Research Center both affiliated to Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
18
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22
Figure caption Fig. 1 Major pathways of antibiotics release into the environment which cause antibiotic resistance for human. Fig.2 Effect of electrolyte type; CIP concentration 50 mg.L-1, current density 10 mA.cm2
,solution pH at 7, inter-electrode distance 1.0 cm and concentration of electrolyte 0.05 M.
Fig. 3 Effect of electrolyte dose; CIP concentration 50 mg.L-1, current density 10 mA.cm2
,solution pH at 7 and inter-electrode distance 1.0 cm.
Fig. 4 Graphical Pareto analysis of significant parameters effect on CIP removal. Fig. 5 Percentage of CIP removal as a function of initial CIP concentration; solution pH at 7, current density 10 mA.cm-2, reaction time 17.5 min. Fig. 6 Percentage of CIP removal as a function of initial CIP concentration and solution pH; current density 10 mA.cm-2, reaction time 17.5 min. Fig. 7 Percentage of CIP removal as a function of current density and initial CIP concentration; solution pH at 7, reaction time 17.5 min. Fig. 8 Percentage of CIP removal as a function of reaction time and initial CIP concentration; solution pH at 7, reaction time 17.5 min, current density 10 mA.cm-2.
23
Fig. 1
24
100
KNO3 KNO3
Removal CIP (%)
80
NaCl NaCl
60
NH4 Cl NH4Cl CaCl2 CaCl2
40
KCl KCl 20
Na2 SO4 Na2SO4
0
0
10
20
30
time(min) Fig. 2
25
40
50
100
0.1 M
Removal CIP(%)
80
0.07 M 60
0.05 M 40
0.03 M 20
0.01 M 0 0
5
10
15
20
time(min)
Fig. 3
26
25
30
35
35
Contributions (%)
30 25 20 15 10 5 0 X1 X1
X2 X2
X3 X3
X4 X4
X1X3 X1X3
Fig. 4
27
X22 X22
X42 X42
Fig. 5
28
86
CIP Removal (%)
78.5 71 63.5 56
8.50 7.75 B: Solution pH
7.00 6.25 5.50
32.50
43.75
55.00
66.25
77.50
A:Initial CIP Concentration (mg.L-1)
Fig. 6
29
CIP Removal (%)
A:Initial CIP Concentration (mg.L-1)
77.50
61
66.25
66 71
55.00
77 81
43.75
85
32.50 7.50
8.75
10.00
11.25
12.50
C: Current Density (mA.cm-2)
Fig. 7
30
Fig. 8
31
Table 1 Coded and actual values of numeric factors. Coded
Experimental Field
Variables Factors (Ui)
(Xi)
-α
-1 level
0
+1 level
+α
X1
A= Initial CIP Concentration (mg.L-1)
10
32.5
55
77.5
100
X2
B= Solution pH
4
5.5
7
8.5
10
X3
C= Current Density (mA.cm-2)
5
7.5
10
12.5
15
X4
D= Reaction Time (min)
5
11.25
17.5
23.75
30
32
Table 2 Experimental results of CIP removal as a function of coded and actual values of four factors in CCD matrix. Standard Actual values order A(mg.L-1) B
Coded values C(mA.cm-2)
D(min) X1 X2 X3 X4
1 2 3 4 5 6 7 8 9
32.5 77.5 32.5 77.5 32.5 77.5 32.5 77.5 32.5
5.5 5.5 8.5 8.5 5.5 5.5 8.5 8.5 5.5
7.5 7.5 7.5 7.5 12.5 12.5 12.5 12.5 7.5
11.25 11.25 11.25 11.25 11.25 11.25 11.25 11.25 23.75
-1 1 -1 1 -1 1 -1 1 -1
-1 -1 1 1 -1 -1 1 1 -1
-1 -1 -1 -1 1 1 1 1 -1
-1 -1 -1 -1 -1 -1 -1 -1 1
61.48 41.12 74.95 61.34 75.46 65.00 86.14 84.37 76.84
10
77.5
5.5
7.5
23.75
1
-1
-1
1
50.72
11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
32.5 77.5 32.5 77.5 32.5 77.5 10 100 55 55 55 55 55 55 55 55 55 55 55 55
8.5 8.5 5.5 5.5 8.5 8.5 7 7 4 10 7 7 7 7 7 7 7 7 7 7
7.5 7.5 12.5 12.5 12.5 12.5 10 10 10 10 5 15 10 10 10 10 10 10 10 10
23.75 23.75 23.75 23.75 23.75 23.75 17.5 17.5 17.5 17.5 17.5 17.5 5 30 17.5 17.5 17.5 17.5 17.5 17.5
-1 1 -1 1 -1 1 -2 2 0 0 0 0 0 0 0 0 0 0 0 0
1 1 -1 -1 1 1 0 0 -2 2 0 0 0 0 0 0 0 0 0 0
-1 -1 1 1 1 1 0 0 0 0 -2 2 0 0 0 0 0 0 0 0
1 1 1 1 1 1 0 0 0 0 0 0 -2 2 0 0 0 0 0 0
83.11 56.48 73.14 70.98 90.37 81.39 97.25 54.98 43.55 64.28 53.12 88.31 54.09 74.11 74.60 76.75 70.29 73.04 77.08 74.35
33
CIP removal (%)
Table 3 ANOVA results for response surface of quadratic model. Analysis of variance Response Source
degree Sum of square
P-value Mean square
F-value
freedom
CIP
Prob>F
Model
5079.127
7
725.5895
31.25373
< 0.0001
Residual
510.7541
22
23.21609
-
-
Lack of Fit
479.279
17
28.19288
4.478603
0.0526
Pure error
31.47508
5
6.295017
-
-
removal (%)
34
Table 4 Optimal condition and comparison between actual value and predicted value.
Parameters
Optimal value
Interelectrode distance (cm)
pH
(mg.L-1)
Electrolyte Type and dosage (M)
32.5
0.07 M NaCl
1
7.8
Initial concentration
35
Current density
Removal (%) (predict)
Removal
(mA.cm-2)
Reaction time (min)
12.5
20
90.34
88.57
(%) (experimental)
Table 5. Kinetic parameters for the adsorption of CIP on Al flocs.
First order kinetic
Second kinetic
R2
0.8349
K1(min-1)
157.14
2 order R
0.9711
K2 (g.min.mg-1)
1.02×10-5
qe (mg.g-1)
303.03
36
Table 6. Parameters obtained from Freundlich and Langmuir isotherms
Langmuir isotherm
Freundlich isotherm
qm (mg.g-1)
b (L.mg-1)
R2
Kf
n
R2
476.19
1.25
0.9954
309.88
2.45
0.9917
37
38