A novel three-dimensional electro-Fenton system and its application for degradation of anti-inflammatory pharmaceuticals: Modeling and degradation pathways

Accepted Manuscript Title: A novel three-dimensional electro-Fenton system and its application for degradation of anti-inflammatory pharmaceuticals: Modeling and degradation pathways Authors: Hamed Mohammadi, Bijan Bina, Afshin Ebrahimi PII: DOI: Reference:

S0957-5820(18)30146-0 https://doi.org/10.1016/j.psep.2018.05.001 PSEP 1369

To appear in:

Process Safety and Environment Protection

Received date: Revised date: Accepted date:

21-1-2018 1-5-2018 3-5-2018

Please cite this article as: Mohammadi, Hamed, Bina, Bijan, Ebrahimi, Afshin, A novel three-dimensional electro-Fenton system and its application for degradation of antiinflammatory pharmaceuticals: Modeling and degradation pathways.Process Safety and Environment Protection https://doi.org/10.1016/j.psep.2018.05.001 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.

A novel three-dimensional electro-Fenton system and its application for degradation of anti-inflammatory pharmaceuticals: Modeling and degradation pathways Hamed Mohammadia, Bijan Binab, Afshin Ebrahimib,* a

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Student Research Committee, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran, Email: [email protected] b Environment Research Center, Research Institute for Primordial Prevention of Non-communicable disease, Isfahan University of Medical Sciences, Isfahan, Iran, and Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran, Email: [email protected]; [email protected].

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*Corresponding author: Afshin Ebrahimi

Environment Research Center, and Department of Environmental Health Engineering, Hezar Jerib Ave., Isfahan University of Medical Sciences, School of Heath, Isfahan 81676-36954, Iran. Tel.: +98 31 3792 3280; Fax: +98 31 3669 5849;

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E-mail address: [email protected]

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Graphical abstract

Highlights 

Removal of IBP and NPX by a novel 3D EF using iron-coated and bare nickel foam as

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CPEs.

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Operating parameters were optimized through response surface methodology (RSM).

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Optimum pH for IBP and NPX removal was found near the neutral.

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3D EF was more effective with excellent capacity in abating COD and reducing EC.

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Degradation pathway of IBP and NPX was proposed.

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Abstract A novel three-dimensional electro-Fenton (3D EF) system with iron- coated nickel foam particles (NFP-Fe) and bare nickel foam as catalytic particle electrodes (CPEs) was employed in this study. Its application in degrading ibuprofen (IBP) and naproxen (NPX), two widely-

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used nonsteroidal anti-inflammatory drugs (NSAIDs), exhibited high catalytic efficiency in a

near-neutral pH. Response surface methodology (RSM) was applied to assess the individual

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and interaction effects of several operating variables (pH, reaction time, concentrations of target compounds and current density) on the IBP and NPX removal efficiencies and energy consumption (EC). Based on the analysis of variance (ANOVA), the coefficient of

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determination (R2) was calculated and found to be above 99.4% for all the responses. The

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maximum IBP and NPX removal efficiencies were found to be 98.14% and 93.5% under the optimum conditions, respectively. After 60 min of treatment at a current density of 15

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mA/cm2 and pH 3-6, EC of 3D EF (168.6 and 112.19 kWh/kgCOD) was much lower than

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(two-dimensional) 2D EF (360.18 - 909.20 kWh/kgCOD). The kinetics analysis showed that the abatement of COD in both systems followed apparent pseudo first-order reaction.

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Furthermore, based on the major reaction intermediates were identified by a novel DLLME/GC/MS and the results of previous studies, the possible degradation pathway was

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proposed. The aforementioned results highlighted 3D EF as a promising alternative method

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for the remediation of aqueous solutions contaminated with NSAIDs.

Keywords: Three-dimensional electro-Fenton (3D EF), Iron- coated nickel foam (NFP-Fe), Ibuprofen, Naproxen, Degradation pathway

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1. Introduction

Sustainable development becomes a real challenge for the management and purification of specific effluents, such as liquid discharges from urban sewage and hospitals (Haidar et al., 2013). The global shortage of freshwater as well as increasing in global water consumption has been a source of concern, and the delay in scientific development of technology to control

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pollutants in the water streams has increased these concerns (Haidar et al., 2013; Heberer 2002). Among many chemicals that enter into the environment, non-steroidal anti-

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inflammatory drugs (NSAIDs) have been recently found in aquatic matrices (GonzálezAlonso et al., 2017; Lolić et al., 2015). The NSAIDs consist of a heterogeneous group of drugs having analgesic, antipyretic and anti-inflammatory features (Kaur et al., 2016).

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Among NSAIDs, ibuprofen (IBP) and naproxen (NPX) are the most commonly used drugs

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(Vulava et al., 2016). Many studies with respect to the ecotoxicities and the persistent

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properties of these substances have been reported (Cleuvers 2003; Heckmann et al., 2007; Im

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et al., 2014). IBP and NPX have been extensively detected in surface waters and even in tap

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water because of continuous input and incomplete removal of water and sewage treatment plants (Fernández et al., 2010; Kermia et al., 2016; Luo et al., 2014; Rao et al., 2016; Sun et

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al., 2015). Therefore, it is essential to develop an effective process for the removal of target compounds from water and wastewaters. Multifarious treatment technologies, such as

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adsorption (Al-Khateeb et al., 2017), membrane treatment (Qurie et al., 2015), and advanced oxidation processes (AOPs), have been widely applied for the treatment of NSAIDs

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wastewater (Rao et al., 2016; Feng et al., 2013; Loaiza-Ambuludi et al., 2014; MendezArriaga et al., 2010). AOPs are based on the in situ generation of hydroxyl radicals (OH°) and/or other strong oxidant species which are able to oxidize refractory organic compounds up to their ultimate oxidation degree, i.e. mineralization, yielding CO2, water, and inorganic ions as final products (Loaiza-Ambuludi et al., 2014; Eslami et al., 2016a). Among the AOPs,

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electrochemical advanced oxidation processes (EAOPs), especially electro-Fenton (EF) with attractive benefits, are being considered as the most perspective, economic and promising processes for the treatment of a wide variety of organic pollutants (Mousset et al., 2018; Oturan and Aaron, 2014). The EF is an environment-friendly method owing to its ability to produce in situ electro-generation of H2O2 from the continuous aeration on the cathode (Eq.

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(1)). Obviously, EF avoids acquisition and potential risks arisen from shipment, storage, and

handling of H2O2 (Mounia and Djilali., 2015). In EF process, Fe2+ is added to react with in

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situ electro-generated H2O2 for producing OH° (Eq. (2)) and continuously regenerated by a direct cathodic reaction (Eq. (3)). The OH° radicals produced are highly reactive and non-

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selective oxidant degrading the persistent organic pollutants (Gu et al., 2017, Wang et al., 2013).

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Fe3+ + e− → Fe2+

3+

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H2 O2 + Fe2+ → HO° + OH − + Fe

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O2 + 2H + + 2e− → H2 O2

(1) (2) (3)

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Unfortunately, it is well known that the electro-Fenton process has some drawbacks, such as working well only at low pH values (Zhou et al., 2007), releasing iron into the treated

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effluent (Bocos et al., 2014), and producing iron sludge after the neutralization step (Brillas et al., 2009; Garrido-Ramírez et al., 2013). In the past decades, many researchers have applied

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three-dimensional electrochemical (3D-E) process by packing some particles such as carbonaceous material, metal particles and clay between two-dimensional (2D) electrodes in

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the conventional electrochemical system to improve degradation efficiency (Sun et al., 2017; Zhang et al., 2013; Chu et al., 2016). Comparing with the conventional 2D electrochemical system, the addition of these particles can shorten the distance between the reactants and the electrodes and enhance the conductivity and mass transfer. Also, the large specific surface areas of these particles can increase reactive sites for catalytic reactions resulting in higher

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elimination efficiency (Shen et al., 2017; Can et al., 2014). Although these systems exhibited high pollutant removal efficiency, there are still some shortcomings limiting their practical application such as low current efficiency and operating at low pH (Qin et al., 2015). In literature, there are some reports on the combination of the EF and 3D-E systems with using carbonaceous material (Xu et al., 2008), metallic material (Liu et al., 2012) as the particle

the problem of iron sludge production is still present in these systems.

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electrodes. Despite the high efficiency of these systems in the decomposition of pollutants,

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Therefore, the main objective of this study was the synthesis of iron- coated nickel foam particles (NFP-Fe) electrodes as novel catalytic particle electrodes (CPEs) to apply the

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removal of NSAIDs as a model target pollutant in 3D EF reactor. Moreover, optimized values of important variables were obtained by means of response surface methodology (RSM)

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based on the central composite design (CCD), instead of the traditional “one-variable-at-a-

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time (OVAT)” approach, because the experimental design allows a depiction of the interactive influences among variables using fewer expenses, time and chemicals (Bezerra et

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al., 2008; Sakkas et al., 2010). Furthermore, the kinetics of degradation and the important operating parameters such as solution pH, reaction time, initial IBP and NPX concentrations,

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and current density (CD), were also investigated. In the meantime, the intermediates obtained from the IBP and NPX degradation were determined by a DLLME/GC/MS system to

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evaluate the possible reaction pathway of IBP and NPX. 2. Material and method

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2.1. Reagents and materials NPX (C14H14O3, 99% purity) and IBP (C13H18O2, 99%) were purchased from Sigma Aldrich Co., USA, and used as received without any further purification. Table 1 summarizes the main physicochemical characteristics of these drugs. Pb(NO3)2 (Sigma Aldrich), Triton X100 (Merck), and CuSO4・5H2O (Merck) were used for electrode preparation. Medium

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molecular weight chitosan (viscosity 200–800 cP), FeSO4·7H2O, Fe (NO3)3·9H2O, sulphuric acid and sodium hydroxide, acetic acid, sodium sulfate were all of the analytical grades and purchased from Sigma Aldrich Co. Glutaraldehyde 25% (Merck) was used as crosslinking agent. Titanium plate with 2 mm thickness (99.7%) was purchased from Sigma Aldrich Co. Nickel foam (Ni-foam) and graphite felt sheet were obtained from Nano bazar company.

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Acetone, chloroform, and methanol were of GC-grade and purchased from Sigma Aldrich

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Co.

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2.2. Preparation of Ti/PbO2 Electrode

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The Ti/PbO2 electrode was prepared in according to our previous study (Bonyadinejad et al., 2015). Briefly, the Ti substrate cut into a given strip. To eliminate the superficial layer of TiO2 and increase surface roughness, it was polished and degreased followed by etching. The

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cleaned Ti substrate was transferred to an electrochemical deposition cell, containing appropriate amounts of Pb(NO3)2, CuSO4.5H2O and Triton X-100 in solution. Finally, the electro-deposition of PbO2 was performed at a constant anodic current with continuous stirring. 2.3. Preparation of catalytic particle electrodes (CPEs)

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Chitosan solutions were prepared in 2% acetic acid under continuous stirring at room temperature for 1 h and then sonicated for 15 min on a Bandoelin DT 156. The iron-chitosan solutions were prepared by dissolving FeSO4·7H2O and Fe(NO3)3·9H2O in 1:2 iron molar ratio (Bocos et al., 2014), in chitosan solutions, and stirred at 60∘C for 4 h. Prior to the

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coating, nickel foam particles (4 mm×4 mm×2 mm) were washed with of H2SO4 (0.1 mol/L), and Milli-Q water in sequence to remove the oxidized surface layer. Then, Ni-foam

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particle was immersed for 24 h in iron solutions of chitosan as described above and 12 h in a

glutaraldehyde solution (1%), respectively. Glutaraldehyde was applied to improve iron fixation to the Ni-foam particles to increase crosslinking. Thereafter, the Ni-foam particles

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were cleaned with a known volume of Milli-Q water and vacuum-dried. This procedure was

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repeated five times from the beginning. However, the last vacuum-drying was continued for

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72 h.

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2.4. 3D EF reactor set up

Batch 3D and 2D EF experiments were performed in a plexiglas reactor with a working

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volume of 0.45 L (Fig. 1). In the system, graphite felt (5.5 cm×5 cm×3 mm) and Ti/PbO2

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(5.5 cm×4 cm×2 mm) electrodes were used as the cathode and the anode, respectively. NFP-Fe and bare nickel foam (4 mm×4 mm×2 mm) was used as CPEs. The electrodes

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were divided by perforated convection baffles (2 mm in diameter), to avoid short circuit. The removal process was started by applying the desired electrical current using adjustable DC

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power supply unit (HANI, Iran).

2.5. Analytical Procedure The X-ray diffraction (XRD) tests were performed using a Bruker, D8 Advance; Germany. The samples were scanned under Co Kα radiation (wavelength: 1.7890 °A) at 40 kV and 40

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mA. Scanning electron microscope (SEM; Philips XI30, Netherlands) was employed to observe the surface morphology of the Ti/PbO2 and CPEs. The concentrations of IBP, NPX and their intermediates were quantified by means of DLLME (dispersive liquid-liquid microextraction)/GC/MS. The pH of each sample was acidified to 1 with 1 mol L-1 HCl. A 10 mL conical centrifuge tube was used for 5 mL of the

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water sample. After that, 80 µL of chloroform as the extracting solvent (immiscible with water) in 1 mL of acetone as the dispersing solvent (miscible in water and extraction solvent)

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was injected rapidly into the sample solution using a 2 mL syringe. In this step, the cloudy solution was formed in the test tube. Then, the mixture was centrifuged for 5 min at 5,000

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rpm. The sedimented phase was taken with a 50 µL microsyringe and then was evaporated to dryness with a gentle stream of nitrogen at room temperature. The dried samples were derivatization

reaction

with

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μl

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to

N-Methyl-N-(trimethylsilyl)

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subjected

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trifluoroacetamide (MSTFA).

The derivatized target compounds were analyzed using an Agilent 7890A gas chromatograph

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(Agilent, USA) equipped with an Agilent 5975C MSD mass spectrometer using electron ionization (EI) mode. The GC analysis was performed on a fused silica capillary column (60

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m × 0.25 mm i.d., 0.25 μm film thickness). The helium carrier gas flow was constant and set at 2 ml/min. The selected ion monitoring (SIM) was used for selective quantification of IBF

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and NPX (m/z 160 and 278 for IBF and m/z 185 and 287 for NPX). Both the temperature of the vaporization injector and the transfer line were maintained at 300°C, and the ion source

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was set at 230°C. The injector was operated in split mode at the ratio of 5:1. The GC oven temperature program was as follow: initial temperature of 120 °C held for 4 min, then from 120 to 300 °C at 20 °C min-1, and finally, held for 6 min at 300 °C. Total run time was 26 min.

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COD concentration was measured colorimetrically using a DR5000 spectrophotometer (HACH Lange Company, USA). A Shimadzu TOC-VCSH analyzer (Japan) was used to measure the TOC of the samples. The specific surface area of bare nickel foam and NFP-Fe was determined by BET measurement (Quantachrome Instruments, NOVA 1000). The degradation efficiency of IBP, NPX, COD and TOC was calculated as follows (Eq. (4)): 𝐶0 −𝐶𝑒 𝐶0

× 100

(4)

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𝑅 (%) =

where C0 and Ce refer to the target compounds concentrations before and after the reaction,

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respectively. The EC per unit COD mass (kWh/kg COD) at time t was calculated as follows (Eq. (5)) (Liu et al., 2012): 𝐸

𝐸𝐶 = (𝐶𝑂𝐷 𝑐𝑒𝑙𝑙

. 𝐼. ∆𝑡

(5)

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𝑡 −𝐶𝑂𝐷𝑡+∆𝑡 ).𝑉𝑠

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where the ∆COD is the removal of COD values at ∆t (h) (in gO2 dm-3), Ecell is the average

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solution in batch mode (L).

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cell potential (v), I is the current intensity (A), and V is the total volume of the treated

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2.6. Experimental design and statistical analysis The response surface methodology (RSM) is a statistical method for empirical model

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building (Myers et al., 2016). Optimizing the process by investigating the effect of independent variables and their interactions on the response of the process, as well as

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reducing the runs of experiments and consequently less time or resources consumption are advantages of using the RSM design (Srivastava et al., 2015). The central composite design

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(CCD) coupled with RSM was applied to optimize and investigate the influence of independent variables on the measured response (Myers et al., 2016). Four experimental factors at five levels (-2, -1, 0, +1, +2) were taken into consideration as follows: pH (X1), time (min) (X2), concentration of IBU and NPX (mg/L) (X3), and CD (mA/cm2) (X4). Table 2 shows the operating ranges and levels of the independent variables.

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The design was performed with 30 experiments: 16 factorial points, 6 central points (in order to evaluate the pure error and consequently the lack of fit), and 8 axial points (Table 3). STATISTICA version 10 and Design Expert version 10.0.1 software were used for the experimental design, determination of the coefficients, the data analysis, and the graph plotting. The relationship between the response Y and the four independent variables were

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obtained by the following second-order regression model with the least-squares method (Eq. (6)) (Box and Draper., 1987; El-Ghenymy et al., 2012). k

Y = β0 + ∑ βi x i + i=1

k

∑ βii xi2 i=1

k

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k

+ ∑ ∑ βij xi xj + ε

(6)

i=1 i≠j=1

where Y is the predicted response by the model, β0 is a constant coefficient (intercept term),

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βi, βii, and βij are the coefficients for the linear, quadratic and interaction effects, respectively,

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xi and xj are the coded levels for the independent variables, k is the number of independent

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variables and ε is the experimental error. The dimensionless coded values of the process independent variable (𝑥𝑖 ) can be determined according to the Eq. (7). 𝑋𝑖 −𝑋0 ∆𝑋

× 100

(7)

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𝑥𝑖 =

where Xi is the real value of the independent variable, X0 is the real value of the independent

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variable at the center point, and ∆𝑋 refers to the value of step change.

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3. Results and discussion

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3.1. Characterization of the Ti/PbO2 Electrode and CPEs

Fig. 2a shows the SEM image of the surface microstructures of the Ti/PbO2 electrode. As it can be seen, the PbO2 layer is crack free and composed of packed faceted microcrystallites,

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similar to that reported in the literature (Bonyadinejad et al., 2016; Xu et al., 2013). Such

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morphology guarantees that only PbO2 is involved in the electrochemical degradation of the

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target compounds and protects the surface of the Ti substrate.

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Furthermore, Fig. 2b shows the XRD pattern of the Ti/PbO2 electrode. As it can be seen, PbO2 was deposited in the form of tetragonal β-PbO2, which occurs naturally as plattnerite. In

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addition, the presence of lead and oxygen atoms on the surface of the Ti/PbO2 electrode has been confirmed by energy-dispersive X-ray (EDX) spectrum (Fig. S1). In the case of CPEs,

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SEM observations (Fig. 2c) showed that Ni-foam was of network structure and the iron was covered in a Ni-foam network. Fig. 2d demonstrates the XRD patterns of NFP-Fe particles.

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The sharp peaks attributed to Ni and Fe elements were detected in the XRD patterns, suggesting Fe has been coated on Ni-foam. 3.2. Effect of CPEs and optimization The effects of the dosage of CPEs on COD removal efficiency are shown in Fig. 3a and b. According to Fig. 3a, the COD removal efficiency was increased significantly with the

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addition of NFP-Fe up to the dosage of 6 g/L. COD removal efficiencies at initial pH of 3 were 20.11%, 26.86% and 34.32% for 60 min electrolysis time when the amounts of NFP-Fe were 2, 4 and 6 g/L, respectively. By adding particle electrodes and applying the appropriate electric current, the NFP-Fe and bare Ni-foam particle electrodes formed micro-electrodes with different charges on both ends due to electrostatic induction (Zhu et al., 2011).

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Electrochemical reactions may take place on the surfaces of both the main and catalytic

particle electrodes, thereby expanding the reaction area and facilitating the mass transfer

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(Zhang et al., 2013). As shown in Fig. 3a, further increasing of the NFP-Fe dosage decrease

the 3D EF process efficiency, which may be related to the reaction between Fe2+ and OH° according to the following reaction (Eq. (8)) (Pajootan et al., 2014; Zhou et al., 2012):

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𝐹𝑒 2+ + 𝐻𝑂° → 𝐹𝑒 3+ + 𝐻𝑂−

(8)

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It is well known that presence of nickel produces superoxide radical (°O2-) by the reaction

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between the Ni-foam and the oxygen (Eq. (9)). The produced superoxide radical can then react with hydrogen ion to generate additional H2O2 according to Eq. (10) (Bounab et al.,

Ni + 2O2 → Ni2+ + 2° O− 2 + 2H + + e− → H2 O2

(9) (10)

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° − O2

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2015).

Therefore, in order to increase the production of H2O2 in the EF process, it was decided that a

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part of the CPEs would be bare Ni-foam particle electrodes. The dosage of bare Ni-foam particles in the range of 2-20 g/L was added to the solution containing 6 g/L of NFP-Fe at

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initial pH of 6 and CD = 15 mA/cm2 for 60 min (Fig. 3b). In the early stage of the reaction, the degradation of COD increased with the increase of bare Ni-foam and the effective electrode surface. COD removal efficiencies at pH 6 were 42.49%, 57.49% and 65.03% for 60 min electrolysis time when the amounts of bare Ni-foam were 8, 11 and 14 g/L, respectively. However, COD removal efficiency only increased 3.78% when bare Ni-foam

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dosage increased from 14.0 to 20 g/L, which was presumably due to the formation of shortcircuit current caused by excessive bare Ni-foam. Therefore, the amount of CPEs containing 6 g/L of NFP-Fe and 14 g/L of bare Ni-foam has been selected in the following experiments as the most suitable dosage. It should be noted that, no IBP and NPX adsorption occurred

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onto NFP-Fe and bare nickel foam (Fig. S2).

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3.3. Model Fitting

In this study, the combined effect of four independent variables (pH, reaction time, initial IBP and NPX concentration, and CD) was investigated on the three important process responses.

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NPX removal (Y1), IBP removal (Y2) and EC (Y3) were considered to be response variables.

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Experiments were performed with different combinations of the variables, which were

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designed using CCD. The CCD matrix and, the predicted and observed responses are shown

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in Table 3. A polynomial regression was performed to investigate the effect of coded

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independent variables on each response process. Best fitted models were then selected using backward variable selection method, which are indicated by semi-empirical expression Eqs.

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(11)-(13).

𝑌𝑁𝑃𝑋 (%) = 90.06 − 0.73𝑋1 + 7.15𝑋2 − 4.73𝑋3 + 7.61𝑋4 − 0.96𝑋1 𝑋3 − 2.11𝑋2 𝑋4 + 1.7𝑋3 𝑋4 − 2.8𝑋12 − 2.74𝑋22 − 1.34𝑋42

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𝑌𝐼𝐵𝑃 (%) = 83.4 − 0.86𝑋1 + 7.1𝑋2 − 4.94𝑋3 + 7.89𝑋4 − 0.55𝑋1 𝑋2 − 0.88𝑋1 𝑋3 − 2.38𝑋2 𝑋4 +

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1.6𝑋3 𝑋4 −2.92𝑋12 − 2.75𝑋22 − 1.07𝑋42

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𝑘𝑊ℎ

𝑌𝐸𝐶 (𝑘𝑔𝐶𝑂𝐷) = 124.04 + 2.77𝑋1 + 16.40𝑋2 − 25.57𝑋3 + 51.40𝑋4 − 3.15𝑋1 𝑋2 + 5.88𝑋1 𝑋3 − 11.81𝑋2 𝑋3 + 21.78𝑋2 𝑋4 − 22.90𝑋3 𝑋4 + 9.96𝑋12 + 6.78𝑋22 + 12.75𝑋32 + 5.08𝑋42

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(13)

Analysis of variance (ANOVA) was applied to check the significance and adequacy of the models. The degree of significance and accuracy of the final regression models were evaluated using P-value, F-value, R2 (determination coefficient) and adjusted R2 (Table 4). Moreover, validation of the final models was investigated using predicted R2, which confirms a good predictability of the models. Additional information of the ANOVA results for the

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final models including the sum of squares, mean squares, F-value and p-value for each

variable in the models are reported in Table S1. Also, lack of fitness tests for all of the

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models was insignificant, confirming a proper fit of these models. Finally, the assumptions of

the final regression models were confirmed using Anderson-Darling (Anderson and Darling.,

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1954), Breusch-Pagan (Breusch and Pagan., 1979), and Durbin-Watson (Durbin and Watson.,

3.4. Screening of main effects

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1951) tests.

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The effect of all single factors (Fig. 4) and interactions between them (Fig. 5) were considered in 3D EF process. The lines in these figures represent the estimated changes in

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responses (NPX, IBP, and EC) as each of the factors is moved from its low to high levels. 3.4.1. Single factors

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As shown in Figs. 4a, b, and c, three curves for each response are drawn that representing the effect of varying each variable while the other ones keep constant at midway value. The

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curve slope is proportional to the effect size whereas the line direction specifies a positive or negative influence of the effect. By considering at these curves, it can be found that: (i) applied CD (X4) is the most significant factor affecting NPX and IBP degradation; (ii) the EC of the process is mainly affected by the applied CD employed. 3.4.1.1. Effect of initial pH

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The electrochemical reactions occur in the aqueous solutions to degrade the organic contaminants which are highly dependent on the solution pH. It can be seen (Figs. 4a and b), the IBP and NPX removal efficiency were maximum at near- neutral pH and slightly acidic condition, and decreased when the pH was acidic or basic. This result suggests that in the presence of NFP-Fe, working in neutral conditions is suitable for the degradation of target

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compounds. This trend was related to the fact that the effect of acidic pH on Fenton and EF systems were reduced in 3D EF process. It is well known that the Fenton’s reaction occurs at

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acidic pH because Fe ions precipitate at pH higher than 4 and decrease decomposition efficiency (Rosales et al., 2012). The precipitation of iron never occurred in this

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heterogeneous system, because the chelating of chitosan with Fe ions avoid the formation of

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Fe (OH)3 and remove the negative effect of iron sludge generated in classical EF process at

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higher pH values. Furthermore, acidic media would cause the evolution of hydrogen on the

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surface of cathode according to Eq. (14), which is detrimental for the electro-generation of hydrogen peroxide.

(14)

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2𝐻 + + 2𝑒 − → 𝐻2

Moreover, very low working pH may result in the rapid corrosion and surface active sites

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reduction of Ni- foam particle electrodes as well as generate less •O2− via the activation of O2

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with nickel foam. While alkaline media decreases decomposition efficiency, because according to Eq. (10), the production of peroxide is reduced. These results demonstrated that the NFP-Fe played a great catalytic role in the removal of

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IBP and NPX at neutral pH. Fig. 4d shows the effect of pH on EC. As can be seen, EC was minimum at near- neutral pH and slightly acidic condition. 3.4.1.2. Effect of reaction time It was also investigated the influence of reaction time on the degradation of NPX and IBP as well as EC in 3D EF system. As it can be seen from Figs 4.a and b, it is found that the

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removal efficiencies of NPX and IBP were increased with increase in reaction time. These results indicate that the reaction time enhances the contact between the wastewater and the reactor system to remove the contaminant effectively from the wastewater (Pavithra et al., 2017). Moreover, the obtained results indicate clearly, as expected, consumption of energy increases with increasing the reaction time.

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3.4.1.3. Effect of initial concentrations of IBP and NPX

It is known that the initial concentration of the pollutant is always an important factor in any

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electrochemical process and thus, it is essential to examine the influence of the initial concentrations of target compounds. As shown in Fig. 4a and b, which is the output of the

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CCD, the IBP and NPX removal efficiencies significantly decreased with the increasing of

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initial concentrations of IBP and NPX. An explanation for this phenomenon is that the higher

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concentration of IBP and NPX causes the formation of recalcitrant intermediate by-products.

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These by-products reduce the IBP and NPX removal efficiencies through competition with the parent pollutants in reaction with radicals (Eslami et al., 2016b). Higher CD or a longer

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treatment time is required in high concentrations of IBP and NPX. This behavior also has been reported in other studies (Shen et al., 2017; Wu et al., 2008).

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The effect of the initial concentration on EC of 3D EF process is shown in Fig. 4c. The results demonstrated that increasing the initial concentrations of IBP and NPX decreased EC.

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This could explained with the fact that, high concentration of IBP and NPX pollutants directly increase the removed COD which subsequently in according to Eq.5, result in a

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decreased EC value.

3.4.1.4. Effect of CD The CD is one of the imperative factors in electrochemical processes, which influences the process efficiency and EC, significantly. The production rate of hydrogen peroxide (Eq. 1) and the OH° (Eq. 2) are mainly controlled by the applied CD during electrolysis. Figs. 4 (a, b

16

and c) show the effect of the CD on the IBP and NPX removal efficiencies as well as EC of process. As can be seen in Figs. 4 a, b, and c, the effect of CD had the greatest impact on the IBP and NPX removal efficiencies and the EC among the studied variables. It is found that removal efficiencies of IBP and NPX are increased with increasing CD in the range of 5- 25

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mA/cm2, due to the higher production of hydrogen peroxide and highly reactive OH° radicals.

3.4.2. Quadratic interactions

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The quadratic terms indicate which way the response surface is bending (the curvature of the

surface). The sign of the term is positive when the surface is convex and negative when the

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surface is concave. In our results, the most important negative quadratic interactions occur for

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two parameters (X2 and X4, Eq. (11) and Eq. (12)), corresponding to concave surfaces (Fig.

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4a and b) and showing lower removal efficiencies at the higher time and current density. In

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the other words, while an increase of reaction time causes an increase of the removal efficiencies, a too high reaction time causes a decrease in the removal efficiencies. This can

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explained the fact that, longer reaction time produces large amount of H2O2 which causes the autodecomposition of it to oxygen and water, and the recombination of OH° radicals, thereby

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decreasing the concentration of OH° radicals (Thirugnanasambandham and Sivakumar., 2015; Zhang et al., 2005), and reducing removal efficiencies of IBP and NPX (Eqs. (15) and

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(16)):

(15)

𝑂𝐻 ° + 𝑂𝐻 ° → 𝐻2 𝑂2

(16)

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2𝐻2 𝑂2 → 2𝐻2 𝑂 + 𝑂2

As mentioned earlier, an increase in CD led to an increase in OH° radical production, which in turn caused an increase in the removal efficiency, but further increase of CD would discharge of O2 at the anode via Eq. (17) and the evolution of hydrogen at the cathode via Eq.

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(14). These species inhibited the formation of OH° radical and decreased the removal efficiencies (Zhang et al., 2006). 2𝐻2 𝑂 → 4𝐻 + + 𝑂2

(17)

In the case of EC, positive quadratic interactions occurred for all variables corresponding to convex surfaces (Fig. 4c) and showing higher EC at higher values of all variables. For

consumption, too high concentrations induced an increase of EC.

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3.4.3. Interactions between the operating parameters

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example, while an increase of IBP and NPX concentrations caused a decrease of the energy

Fig. 5 should allow us to better understand the meaning of the interactions between the

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operating parameters. An interaction between variables happens when the change in response

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from the low level to the high level of one variable is not the same as the change in response

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at the same two levels of one another variable. That is, the influence of one variable is

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dependent upon a second variable. Two parallel lines (lines marked with + and −) mean there is no interaction between variables in question, crossing lines indicate the contrary. Since

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backward variable selection method is used for all models, it can be seen all significant interactions exist between variables from Eqs. (11)-(13), and Table S2. In the present

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experimental conditions, all these interactions, although statistically significant, did not

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exhibit an appreciable influence on the degradation and EC (see Table S2), except time/concentration (X2X3), time/CD (X2X4) and concentration/CD (X3X4) interactions on EC (Fig. 5c). Coming to the interaction between time and concentration (X2X3), we can see that

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whatever the IBP and NPX concentration, an increase in reaction time leads to an increase in EC as expected (Fig. 5c). Considering time/CD interaction (X2X4), Fig. 5d shows that significant interactions take place. As can be seen, for the highest CD, consumption of energy increased with the increasing reaction time; but at low level of CD, consumption of energy decreased with the

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increasing reaction time. This result is explained by the further removal of COD at a low level of CD with increasing time. For concentration/CD interaction (X3X4), plots indicate that whatever the CD, an increase in concentration leads to a decrease in the consumption of energy; but as shown in Fig. 5d, at a high level of CD, the effect size is greater. These results indicate that at high CD, the effect of concentration is much higher. Such information would

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not be obtained in a univariate study (one factor at a time) of the 3D EF process and

therefore, the use of experimental design of experiments over the conventional univariate

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optimization is essential.

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3.5. Models RSM plots and optimization conditions

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Three-dimensional response surface and contour plots provide a method to predict the NPX

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and IBP removal efficiencies and EC for different values of the test variables. Furthermore,

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these plots help in the identification of the type of interactions between variables and can be used to optimize the process efficiency (Anderson and Whitcomb., 2000; Lewis et al., 2001).

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3D response surface or contour plot gives us an infinite number of combinations of the two variables with the other maintained at their respective zero levels. In addition, use of the 3D

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response surfaces gives clearer insight into the interactions occurring. A circular contour of plots indicates that the interaction between the parameters is negligible. An elliptical or

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saddle nature contour of the response surfaces indicates that the interaction between the parameters is significant (Hazime et al., 2013). Fig. 6 shows the response surfaces plots of the

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NPX removal efficiency and EC for the most important pairs of affecting factors. The optimal conditions for increasing the NPX removal efficiency and reducing the EC were obtained from the Fig 6. For example, Fig. 6a exhibits the response surface plots for pH versus concentration of target compounds (CD = 15 mA/cm2 and time = 30 min). The most suitable conditions to have a NPX removal of about 95% are pH 6–6.5 and concentration of

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each drug comprised between 2 and 3 mg/L. This indicates that concentration of target compounds and pH critically affect the rate of the NPX removal but the interaction between them is not very remarkable because the contour plots are nearly circular. In addition, Fig. 6b represents the response surface plots for CD versus time (pH = 6 and concentration of each drug = 6 mg/L). To obtain NPX removal more than 90 %, 20 mA/cm2 < CD and time= 45-50

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min are required. Similar interpretations can also be implemented in other important interactions shown in Fig 6.

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3.6. Model validation and confirmation

To determine the optimum amount of factors which lead to the highest IBP and NPX removal

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efficiencies and lowest EC, optimization of influencing factors is necessary. The optimization

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was performed using Design Expert version 10.0.1 software. The desirable goal in

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degradation and EC was set on the maximum and minimum values, respectively. Optimum

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and EC were shown in Table 5.

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operating conditions obtained from the optimization of IBP and NPX removal efficiencies

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To validate that the models were satisfactory in predicting the maximum NPX and IBP degradation and minimum EC, additional experiments were carried out in optimized

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conditions. These results show that the experimental values are relatively close to the predicted values from semi-empirical Eqs. (11) - (13), which confirms the adequacy and

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validity of the models simulating the NPX and IBP removal efficiencies and EC.

3.7. COD and TOC removal under optimum conditions Under optimum conditions for the removal of IBP and NPX (Initial pH 6.3, reaction time= 38 min, CD= 17.5 mA/cm2) and initial concentrations of IBP and NPX = 10 mg/L, the obtained

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COD and TOC removal efficiencies were 49.42% and 29.11%, respectively. Moreover, the COD and TOC removal after 100 min of electrolysis were 83.2% and 60.09%, respectively. These results suggest that more COD and TOC removal could be achieved by increasing the

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electrolysis time.

3.8. Comparison of 2D and 3D EF systems

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A series of comparable experiments were conducted to remove COD in three different EF

systems at the same operational conditions: i) two-dimensional (2D) electro-Fenton, ii) 3D

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EF with NFP-Fe particle electrodes (denoted as 3D-M1) and iii) 3D EF with NFP-Fe and bare

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Ni-foam particle electrodes (denoted as 3D-M2). After 60 min electrolysis in optimal

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conditions for each process, the 3D-M2 system removed 66.03% of COD, while the 3D-M1

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and 2D systems removed only 33.99% and 34.28%, respectively. As can be seen from Fig. 7a, COD removal efficiency obtained by the 3D-M2 system was much higher than those of

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the 2D and 3D-M1 systems, which confirmed the key role of CPEs. Regression analysis was performed for all three 2D and 3D EF processes based on COD degradation. A linear

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relationship between ln (C0/C) and t (r2>0.95) confirms the COD degradation in all three processes followed a pseudo first- order reaction (Fig. 7b). The observed pseudo first-order

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reaction constant of 3D-M2 electrolysis (k3D-M2) were much higher than those of 2D and 3DM1 electrolysis (k2D and k3D-M1) at various pHs, especially pH = 6. In the case of 3D-M2

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systems, it is found that the ratio of k3D-M2 was increased by increasing the pH in the range of 3-7 (Table S2). In addition, one of the important differences between 2D and 3D EF is the effect of initial pH. As shown in Fig. 4c, the effects of acidic pH on Fenton and EF systems were reduced in the 3D EF process (see section 3.4.1.1). To evaluate the economic costs of EF processes, the EC of 3D-M1, 3D-M2 and 2D EF per unit COD mass (kWh/kg COD) were

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calculated at different pH (Fig. 7d). EC of 3D EF was much lower than 2D EF at all pHs (3DM2 < 3D-M1< 2D). When the pH increased, EC of 2D increased significantly, while 3D-M1 EF remained at a same order of magnitude and 3D-M2 EF showed a decreasing EC trend and an increasing difference from 2D EF. In sum, 3D EF was more cost-effective than 2D EF in degrading IBP and NPX. The detailed information of comparison of 2D and 3D EF systems

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was summarized in Table S2.

3.9. Stability of the electrodes and CPEs

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The stability of electrodes is a very important issue for their practical applications. Fig. 8

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shows the stability of electrodes for the degradation of IBP in optimal removal conditions.

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We cleaned the used Ti/PbO2, graphite felt and CPEs with deionized water and then reused

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without further treatment for 3D EF process under the same conditions. It was interesting to find that there was no significant loss in removal efficiency after 7 recycles, which could

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indicate the good physicochemical stability of the electrodes.

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However, when the degradation continued with further cycles, the removal efficiency decreased with decreasing graphite felt quality. After 9 cycles, the removal efficiency

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declined to 27%. This reduction in the removal efficiency could be stopped by cathode replacement. Moreover, the analysis showed that the specific surface area and estimated average pore size of NFP-Fe and bare nickel foam have not significantly changed before their

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application and after 7 recycles (Table S3). The physical characteristic of the PbO2 films was also analyzed using SEM image, after being used in the 3D EF process, for approximately 120 h (Fig. S3). The result obviously shows the same packed faceted microcrystallites after being used, with more cracks. The reusability of the Ti/PbO2 and NFP-Fe makes them promising for the practical wastewater treatment. 22

3.10. Intermediates and degradation pathways As we have already mentioned, IBP and NPX degradation intermediates by 3D EF process

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were identified by DLLME/GC/MS for the first time. Molecular structures were proposed for each intermediate on the basis of the molecular ion masses and MS fragmentation patterns

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(MS spectra for each intermediate provided in the supplementary materials). The detailed information of IBP and NPX intermediates was summarized in Table 6. All these intermediates were confirmed by the use of the GC/MS NIST library. The probability values

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of compounds 1, 3, 4, 5 and 6 are greater than 90%, indicating the match between these five

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intermediates and the reference compounds is very good. In the case of IBP intermediates,

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compound 1 (1-ethyl-4-(2-methylpropyl) –benzene) was discovered during the attack of OH°

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radical on IBP such as photochemical (Szabó ., 2010) and UV/Fe(III)/Oxone processes (Rao

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et al., 2016). Obviously, compound 2 (1-(1-hydroxyethyl)-4-isobutyl-benzene) is commonly detected during Fenton-related (Skoumal et al., 2009), electro-peroxone (Li et al., 2014),

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electrochemical (Chang et al., 2017) and combined advanced oxidation processes (Madhavan et al., 2010). Compound 3 (4’-(2-Methylpropyl) acetophenone) was also reported as a by-

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product of photochemical processes (Mendez-Arriaga et al., 2010; Ruggeri et al., 2013). Compound 4 (1-ethenyl-4-(2-methylpropyl)-benzene) was also identified during the

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UV/Fe(III)/Oxone process (Rao et al., 2016), oxidative treatment of IBP by KMnO4 (Caviglioli et al., 2002), photocatalytic process (Choina et al., 2013), and photochemical process with the presence of Rose Bengal (Vione et al., 2011). The possible reaction pathways for electrochemical degradation of IBP is proposed and shown in Fig. 9. Compound 1 was generated due to the attack of OH° radicals on the propanoic acid chain of IBP at the first stage. The attack on the propanoic acid and ethyl chains is more favorable 23

kinetically than benzene ring, which explains the lack of detection of ring-hydroxylated IBP intermediates (Ruggeri et al., 2013). The decarboxylation of the propanoic acid chain resulted in the production of compound 1. Compound 2 is believed to come from the hydroxylation of compound 1 due to the attack on the secondary carbon of the ethyl chain. The deprotonation of compound 2 led to the generation of compound 3 and dehydration of compound 2 gives

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compound 4.

In the case of NPX intermediates, all five aromatic by-products detected in this study were

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also identified during the Fenton-based electrochemical processes (Coria et al., 2016).

Compound 5 (2-Acetyl-6-methoxynaphthalene) is also reported during anodic oxidation

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process (Chin et al., 2014). Note that compound 6 (2-ethenyl-6-methoxynaphthalene) along

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with 1-(2-methoxy naphthalene-6-yl) ethane-1,2 diol is identified as major intermediates

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during photochemical processes (Szabó ., 2010). Fig. 9, describes the possible reaction

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pathways for NPX degradation by 3D EF process. Compounds 5 and 6 were generated by the hydroxylation of the methyl position of NPX, which are consecutively oxidized to compound

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7 (6-methoxy-2-naphthoic acid). Parallel hydroxylation and demethylation of compound 5 led to the generation of compound 8 (1-(6-h ydroxynaphthalen-2-yl)ethanone). Further

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degradation of the above naphthalene intermediates with the opening of one benzene ring

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generates compound 9 (phthalic acid) as a final aromatic by-product.

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4. Conclusions

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A novel 3D EF process with iron- coated Ni-foam (NFP-Fe) and bare Ni-foam as CPEs was

developed to decompose the IBP and NPX in aqueous solution. First, the single-factor

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experiment was used to optimize the CPEs dosage and the optimal dosage of 6 and 14 g/L were obtained for NFP-Fe and bare Ni-foam particles, respectively. The central composite

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design based on response surface methodology (RSM) was successfully used to optimize the

N

main experimental parameters (pH, time, the concentration of target compounds and current

A

density). The highest IBP and NPX removal efficiencies and lowest EC at optimum operating

M

conditions were found to be 93.51%, 98.14% and 77.93 kWh/kg COD, respectively. 3D EF showed a much better performance in a wide range of solution pH and was more cost-

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effective than conventional 2D EF. The kinetics analysis results confirmed that the degradation of COD in both 3D EF and conventional 2D EF processes followed pseudo first-

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order kinetics. Furthermore, the major reaction intermediates were identified by a novel DLLME/GC/MS technique, and the possible degradation pathway was proposed based on the

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intermediates and the results of previous studies. From the results, it is found that IBP and NPX were decomposed by the combined decarboxylation and hydroxylation reactions. The

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results indicated 3D EF process could serve as a promising alternative method for removing NSAIDs from aqueous solutions.

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Acknowledgements This study is a Ph.D. approved research project (No. 395130) performed at Isfahan University of Medical Sciences, Iran. The authors are thankful for the funding provided by the

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Department of Environmental Health Engineering and Environment Research Center.

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Pavithra, K.G., Kumar, P.S., Christopher, F.C. and Saravanan, A. 2017. Removal of toxic Cr (VI) ions from tannery industrial wastewater using a newly designed three-phase threedimensional electrode reactor. J. Phys. Chem. Solids. 110, 379-385.

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Qin, Y., Sun, M., Liu, H. and Qu, J. 2015. AuPd/Fe 3 O 4-based three-dimensional electrochemical system for efficiently catalytic degradation of 1-butyl-3-methylimidazolium hexafluorophosphate. Electrochim Acta. 186, 328-336.

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Mousset, E., Oturan, N., Oturan, M.A., 2018. An unprecedented route of OH radical reactivity evidenced by an electrocatalytical process: Ipso-substitution with perhalogenocarbon compounds. Appl. Catal. B Environ. 226, 135-146.

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Oturan, M.A., Aaron, J.J., 2014. Advanced oxidation processes in water/wastewater treatment: principles and applications. A review. Crit. Rev. Environ. Sci. Technol. 44, 25772641. Qurie, M., Khamis, M., Scrano, L., Bufo, S.A., Mecca, G. and Karaman, R. 2015. Removal of Two NSAIDs: Naproxen and Diclofenac and a Heavy Metal Cr (VI) by Advanced Membranes Technology. Case Stud. J. 4, 51-63. Ràfols, C., Rosés, M. and Bosch, E. 1997. Dissociation constants of several non-steroidal anti-inflammatory drugs in isopropyl alcohol/water mixtures. Anal. Chim. Acta. 350(1), 249255.

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Rao, Y., Xue, D., Pan, H., Feng, J. and Li, Y. 2016. Degradation of ibuprofen by a synergistic UV/Fe (III)/Oxone process. Chem. Eng. J. 283, 65-75. Rosales, E., Iglesias, O., Pazos, M. and Sanromán, M. 2012. Decolourisation of dyes under electro-Fenton process using Fe alginate gel beads. J. Hazard. Mater. 213, 369-377. Ruggeri, G., Ghigo, G., Maurino, V., Minero, C. and Vione, D. 2013. Photochemical transformation of ibuprofen into harmful 4-isobutylacetophenone: pathways, kinetics, and significance for surface waters. Water res. 47(16), 6109-6121.

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Sakkas, V.A., Islam, M.A., Stalikas, C. and Albanis, T.A. 2010. Photocatalytic degradation using design of experiments: a review and example of the Congo red degradation. J. Hazard. Mater. 175(1), 33-44.

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Shen, B., Wen, X.-h. and Huang, X. 2017. Enhanced removal performance of estriol by a three-dimensional electrode reactor. Chem. Eng. J. 327, 597-607.

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Skoumal, M., Rodríguez, R.M., Cabot, P.L., Centellas, F., Garrido, J.A., Arias, C. and Brillas, E. 2009. Electro-Fenton, UVA photoelectro-Fenton and solar photoelectro-Fenton degradation of the drug ibuprofen in acid aqueous medium using platinum and boron-doped diamond anodes. Electrochim Acta. 54(7), 2077-2085.

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Srivastava, V., Sharma, Y. and Sillanpää, M. 2015. Application of response surface methodology for optimization of Co (II) removal from synthetic wastewater by adsorption on NiO nanoparticles. J. Mol. Liq. 211, 613-620.

M

Sun, J., Luo, Q., Wang, D. and Wang, Z. 2015. Occurrences of pharmaceuticals in drinking water sources of major river watersheds, China. Ecotoxicol Environ Saf. 117, 132-140.

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Sun, Y., Li, P., Zheng, H., Zhao, C., Xiao, X., Xu, Y., Sun, W., Wu, H. and Ren, M. 2017. Electrochemical treatment of chloramphenicol using Ti-Sn/γ-Al 2 O 3 particle electrodes with a three-dimensional reactor. Chem. Eng. J. 308, 1233-1242.

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IP T SC R U

A

CC E

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M

A

N

Fig. 1. Schematic diagram of the 3D EF (a) and 2D EF (b) systems.

33

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Fig. 2. (a) SEM micrograph and (b) XRD pattern of Ti/PbO2 electrode, (c) SEM micrographs

A

N

U

of bare Ni-foam and NFP-Fe and (d) XRD pattern of iron- coated Ni-foam

M

30

ED

50 40 30 20 10

N F P -F e d o s a g e (g /L )

0 2

7 1

4 1

1 1

8

2

2 1

0

0 1

8

6

2

0

PT

10

(b )

60

5

20

C O D r e m o v a l e ffic ie n c y (% )

70

(a )

4

C O D r e m o v a l e ffic ie n c y (% )

40

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B a r e N i fo a m d o s a g e (g /L )

Fig. 3. Effect of the CPEs dosage on COD removal efficiency: (a) NFP-Fe dosage; (b) bare Ni-foam particles dosage, Operating conditions in (a): pH = 3, CD= 15 mA/cm2, time= 60

A

min; Operating conditions in (b): pH = 6, CD= 15 mA/cm2, time= 60 min and NFP-Fe dosage= 6 g/L.

34

IP T SC R U N A

M

Fig. 4. Graphical presentation of the statistical evaluation of the individual factors on the IBP

A

CC E

PT

ED

and NPX removal efficiencies (%) and EC (kWh/kg COD).

35

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Fig. 5. Graphical presentation of the statistical evaluation of the interactions of two factors on

ED

M

A

N

U

SC R

the IBP and NPX removal efficiencies (%) and EC (kWh/kg COD)

b

CC E

PT

a

d

A

c

36

e

f

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Fig. 6. Response surfaces generated from the CCD method using Eq. (12) for NPX removal

A

N

U

SC R

and Eq. (13) for EC per unit COD mass, for the most important pair of factors.

1 .5 0

M

(a )

50

ED

40 30 20

2 D a n d 3 D -M 1, p H = 3 3 D -M

1 .0 0

2

, pH = 6

y = 0 .0 1 6 4 x + 0 .1 3 3 2 R ² = 0 .9 9 1

0 .7 5

y = 0 .0 0 6 6 x + 0 .0 5 R ² = 0 .9 5 3

0 .5 0

3 D -M 2 , p H = 6

10

(b )

1 .2 5

L n (C 0 /C )

60

PT

C O D r e m o v a l e ffic ie n c y (% )

70

0 .2 5

2 D a n d 3 D -M 1, p H = 3

0 0

10

20

30

40

0 .0 0

50

60

0

70

10

20

30

40

50

60

70

R e a c tio n tim e (m in )

A

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R e a c tio n tim e (m in )

37

80

90

100

(C )

1000

3 D -M

2

3 D -M

1

(d )

2D

60

2D 3 D -M 1

E C ( k W h /k g C O D )

40

20

0

750

3 D -M 2

500

250

6

7

8

9

10

pH

pH

6

5

IP T

4

3

3

5

0 2

4

C O D r e m o v a l e f f ic ie n c y ( % )

80

SC R

Fig. 7. Comparison of performance in 2D and 3D EF systems in batch mode: (a) Comparison of COD removal efficiency at different reaction times; (b) Comparison of linear fitting of degradation curves; (c) Comparison of COD removal efficiency in different pH; (d)

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Comparison of EC in different pH. Operating conditions in (a) and (b): IBP0 = 10 mg/L,

N

NPX0= 10 mg/L, CD = 15 mA/cm2; Operating conditions in (c) and (d): IBP0 = 10 mg/L,

A

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M

A

NPX0= 10 mg/L, CD = 15 mA/cm2, reaction time= 60 min

Fig. 8. Stability of the electrodes and CPEs during 3D EF degradation of IBP. Operating conditions: pH= 6.3, IBP0 = 15 mg/L, CD= 15 mA/cm2

38

IP T SC R U N A M

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Fig. 9. Possible pathways for degradation of NPX and IBP judged by the intermediates determined in

A

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PT

this study.

39

CAS number Molecular formula Molecular weight (g/mol)

NPX 2-(6-Methoxy-2naphthyl) propionic acid 22204-53-1 C14H14O3 230.263

74-77

152-155

21

15.9

3.5

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IUPAC name

IBP 2-(4-Isobutylphenyl) propanoic acid 15687-27-1 C13H18O2 206.285

Chemical structure

N

3.3

4.57

M

1.5×10-7

A

4.52

3.39×10-10

ED

Melting point (°C) Solubility in water (mg/l at 25 °C) (Yalkowsky and Dannenfelser., 1992) Log Kow (Cleuvers 2004) pKa (water 20°C) (Ràfols et al., 1997) Constant of Henry's Law (atm/m3mol) (Tixier et al., 2003)

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properties

U

Table 1. Physicochemical properties of IBP and NPX

Variables

PT

Table 2. Independent variables (xi) and their coded levels used in the experimental design symbols

min mg/L mA/cm2

X1 X2 X3 X4

Actual values of the coded values -2 -1 0 +1 3 4.5 6 7.5 10 20 30 40 2 4 6 8 5 10 15 20

A

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pH Time C. of each drug Current density

Unit

40

+2 9 50 10 25

Table 3. Actual and model predicted values of NPX and IBP removal efficiencies and EC by 3D EF process based on CCD matrix

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

24 30 25 18 14 4 27 7 2 17 22 23 3 21 19 11 12 28 10 26 5 8 15 6 16 9 29 20 1 13

6 6 6 9 7.5 7.5 6 4.5 7.5 3 6 6 4.5 6 6 4.5 7.5 6 7.5 6 4.5 7.5 4.5 7.5 7.5 4.5 6 6 4.5 4.5

30 30 30 30 20 40 30 40 20 30 30 30 40 30 10 40 40 30 20 30 20 40 40 20 40 20 30 50 20 20

6 6 6 6 8 4 6 8 4 6 10 6 4 2 6 4 4 6 4 6 8 8 8 8 8 4 6 6 4 8

25 15 15 15 20 10 15 10 10 15 15 5 10 15 15 20 20 15 20 15 10 10 20 10 20 20 15 15 10 20

NPX removal (%); Y1

IBP removal (%); Y2

EC (kWh/kg COD); Y3

Actual

Predicted

Actual

Predicted

Actual

Predicted

99.27 91.23 89.73 77.53 80.69 91.01 91.21 80.12 73.43 80.03 79.73 69.99 90.92 99.25 64.07 98.25 97.86 89.72 89.93 89.35 61.54 76.21 95.49 58.58 91.85 89.72 90.12 93.93 71.91 84.05

100 90.23 90.23 77.49 80.72 91.00 90.23 80.49 73.61 80.40 80.19 69.57 90.71 99.12 64.87 98.56 98.37 90.23 89.42 90.23 60.84 76.95 95.12 58.12 91.11 88.79 90.23 93.46 72.50 83.92

94.36 84.55 83.5 70.02 74.18 84.5 84.9 72.84 66.92 73.52 73.22 63.98 85.01 92.74 57.26 92.74 90.35 83.01 84.78 82.53 54.23 69.00 88.98 52.07 84.5 84.31 82.81 87.63 64.3 77.54

94.98 83.55 83.55 70.08 74.58 84.28 83.55 73.90 67.05 73.52 73.13 63.43 84.61 92.90 58.28 93.16 91.36 83.55 83.65 83.55 53.23 70.07 88.85 51.58 83.55 83.25 83.55 86.67 65.18 77.69

243.60 119.68 127.27 171.17 138.85 115.09 121.17 78.11 97.478 156.42 118.85 44.902 114.06 231.08 124.79 313.38 308.72 125.08 196.33 126.42 112.00 103.28 179.33 126.51 201.45 214.15 124.57 177.37 104.61 135.14

247.15 124.04 124.04 169.43 138.79 118.23 124.04 73.67 99.07 158.36 123.92 41.54 114.38 226.19 118.38 310.33 306.63 124.04 200.34 124.04 114.36 101.04 178.00 129.14 197.82 216.65 124.04 183.97 107.82 131.57

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X4: (CD) (mA/cm2)

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X3: (C) (mg/L)

U

X2: (t) (Min.)

N

X1: (pH)

A

Standard Run

ED

M

Exp. No.

Model

Sum of squares 3696.45 3859.68 1.115E+005

df* 10 11 13

Mean square 369.64 350.88 8578.1

Fvalue 551.61 303.15 351.62

p-value Prob>F < 0.0001 < 0.0001 < 0.0001

A

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NPX IBP EC

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Table 4. ANOVA results of the selected quadratic mode

41

Adjusted Predicted R2 R2 0.996 0.994 0.991 0.994 0.991 0.983 0.996 0.993 0.983 *df: Degrees of freedom R2

Adequate precision 84.196 63.680 79.123

Table 5. Optimum operating conditions and confirmation experiments at optimum conditions EC (Y3) minimize 5.61 39.99 7.51 10 73.46* 77.93*

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NPX removal IBP removal )Y1) (Y2) Goal of model maximize maximize X1: Initial pH 6.3 6.24 X2: Reaction time (min) 37.92 37.79 X3: Initial C (mg/L) 4 4 X4: CD (mA/cm2) 15.77 18.91 Model prediction results (%) 99.28 94.86 Experimental results (%) 98.14 93.51 *The unit of EC for model prediction and laboratory result was kWh/kg COD Factor

Retention time (min)

Molecular structure

MW

Formula

Name

12.93

162

C12H18

2

16.01

178

C12H18O

3

16.33

4

1-ethyl-4-(2methylpropyl) -benzene

A

Prob. (%) in NIST library

93

1-(1-hydroxyethyl)-4isobutyl-benzene

57-91-117133-163-178

42

4’-(2-Methylpropyl) acetophenone

91-105-113134-161-176

96

1-ethenyl-4-(2methylpropyl)-benzene

65-91-104117-160

95

176

C12H16O

ED

M

m/z

77-91-105119-133-162

N

1

U

i) IBP intermediates

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Table 6. Intermediates detected by DLLME/GC/MS during IBP and NPX degradation by 3D EF process

13.59

160

C12H16

22.33

200

C13H12O2

2-acetyl-6 methoxynaphthalene

73-114-157185-200

98

19.88

184

C13H12O

2-ethenyl-6methoxynaphthalene

63-89-115141-163-184

93

7

19.43

186

C12H10O2

1-(6-hydroxy naphthalen-2yl) ethanone

57-71-93115-128153-171-186

62

8

21.67

202

C12H10O3

6-methoxy-2-naphthoic acid

115127144-187-202

70

6.58

166

C8H6O4

Phthalic acid

50- 75 -133149

22

5

A

CC E

6

PT

ii) NPX intermediates

9

42