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Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light
MOLLIQ-112118; No of Pages 9 Journal of Molecular Liquids xxx (xxxx) xxx
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Journal of Molecular Liquids journal homepage: www.elsevier.com/locate/molliq
Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light Z. Sheikholeslami a,b,⁎, D. Yousefi Kebria a, F. Qaderi a,⁎ a b
Department of Civil Engineering, Babol Noshirvani University of Technology, P.O. Box 484, Babol, Iran Department of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran
a r t i c l e
i n f o
Article history: Received 1 July 2019 Received in revised form 6 November 2019 Accepted 11 November 2019 Available online xxxx Keywords: Produced water Nanophotocatalyst Semiconductor Maghemite Aromatic hydrocarbon
a b s t r a c t Nanophotocatalytic process among various methods is used more for BTEX removal as an aromatic hydrocarbon in produced water. For this purpose, γ-Fe2O3 nanoparticle, which has significant efficiency to remove and degraded the contaminants. γ-Fe2O3 photocatalysis nanoparticle was synthesized by co-precipitation process, and the nanoparticle characteristics were determined by XRD, SEM and DRS. The main factors impact were studied including: pH (2–8), photocatalyst concentration (0–300 mg/l) and visible light irradiation intensity (0–270 W). The experiments were applied by a CCD and analyzed by using RSM. From the results analysis the polynomial formula has been derived for the model. For the first time, the effects of interactions of the main factors were investigated and the interactive diagrams were presented. The results show that the maximum BTEX removal efficiency (90.94%) was observed in 3.64 of pH, 167 mg/l of the nanoparticle concentration, and 180 W of the light intensity. © 2019 Published by Elsevier B.V.
1. Introduction Oil extraction process has many byproduct such as produced water (PW) [1], which the ratio of water to oil in PW is around 3:1 [2]. PW contains complex chemicals compositions such as dissolved and dispersed oils, metals, and hydrocarbons [3]. BTEX (benzene, toluene, ethylbenzene, xylene isomers) is an aromatic hydrocarbons, which is extremely harmful on both human health as well as ecosystem functions [4,5]. The BTEX concentration of PW is 0.068–578 mg/l in the all of the world [6] which is too excessive allowed to be discharged in to the environment [7]. In the world the industries of oil and gas has attended to use the technologies of PW treatment, due to the BTEX hazardous environmental impacts [8]. For PW treatment physical, chemical, and biological methods have been suggested [9]. One of the most efficient and appropriate for water treatment technologies is Advanced Oxidation Processes (AOPs) [10]. Among different methods of AOPs, the photocatalytic process, due to the performance of the process at temperature and ambient pressure, production of fewer intermediate products and lower costs, is one of the great promising technologies for water and wastewater treatment [11]. Recent years, the researchers were interested in semiconductor photocatalytic nanoparticles [12]. In photocatalytic semiconductors by receiving energy the electrons which exist in the valence bands (VB) can be transferred and excited to band of conduction. Consequently many ⁎ Corresponding authors at: Department of Civil Engineering, Babol Noshirvani University of Technology, P.O. Box 484, Babol, Iran. E-mail addresses: [email protected] (Z. Sheikholeslami), [email protected] (F. Qaderi).
electron-positive hole pairs (e− and h+) come into existence [13]. Subsequently, the reactance between h+ in CB and water are generated the hy droxyl radicals [OH] which are powerful oxidants and react with organic and toxic compounds. At the beginning of oxidation reactions, ½ OH radicals perform an important role [14]. Maghemite (γ-Fe2O3) nanoparticles are a kind of semiconductors [15]. Different methods have been utilized in the γ-Fe2O3 nanoparticles synthesis, such as sol-gel, co-precipitation, micro emulsion and hydrothermal synthesis [16]. One-step coprecipitation method is illustrated in this paper for the γ-Fe2O3 nanoparticles synthesis. In this way, pure γ-Fe2O3 with a mediocre particle size under 30 nm will be composed without any α-Fe2O3 and Fe3O4 [17]. Among the different parameters visible light irradiation intensity, pH, and photocatalyst concentration are the most considerable important factors in a photocatalytic process [18]. In last years, many researchers have considered the photocatalytic process of γ-Fe2O3 nanoparticles for degradation of various pollutant [19]. Ghavami et al. [20] investigated the degradation of toxic crystal violet (CV) in wastewater with synthesized magnetic nanocomposite, which containing reduced graphene oxide with γ-Fe2O3, silver and titanium dioxide. The results indicated the removal efficiency was obtained 97% with high recovery and stability of nanocomposite [20]. Fakhri et al. [21] evaluated the application of γ-Fe2O3/SiO2 nanocomposite for Erythromycin antibiotic removal by using RSM. Conforming to the results the highest degradation efficiency and the best correlation coefficient were respectively obtained 87.17% and 0.9354. The experimental conditions were included: pH = 7, 6 mg/l of Erythromycin concentration, 500 mg/l of γFe2O3/SiO2 concentration and the time of tests was 6 min [21]. Wang et al. [22] prepared the mesoporous magnetic Fe2O3 nanoparticles for
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Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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methyl orange (MO) degradation from aqueous solution. The experimental tests were applied in absence of photocatalyst, absence of H2O2 and absence of visible light irradiation. According to the results, in the first condition, which the tests applied without any photocatalyst, there was no significant change in MO degradation. Also, by adding the nanoparticles but without H2O2, and by adding nanoparticles and 30% H2O2 to MO solution in absence of visible light irradiation the maximum degradation were respectively obtained 6.12% and 6.62%; but, when the above solution subjected to the visible light the best degradation was achieved almost 100% [22]. Pouretedal [23] studied the photocatalytic application of TiO2/Zr and TiO2/N nanomaterial under visible light for degradation of trinitrotoluene (TNT) and 2,4-dinitrotoluene (2,4DNT), in polluted solution. The removal efficiency was determined after 12 h, which was obtained 35.9% for the presence of TiO2, 42.4% for the presence of TiO2/Zr and 61.5% for the presence of TiO2/N; finally, the best activity was attained 67.7% in 2.0 g/l of TiO2/Zr,N nanoparticles concentration [23]. Niu et al. [24] studied the photocatalytic performance of γ-Fe2O3/BiOI for sulfapyridine and methyl orange degradation in wastewater. γ-Fe2O3/BiOI was synthesized by microwave hydrothermal and sol-gel methods. According to the experiments the band gap of composite catalyst was 1.75 eV, and the medium pore size was 6.756 nm. After subjecting the wastewater for 120 min under the tungsten lamp the sulfapyridine and methyl orange removal efficiency was achieved 64.1% and 67.6% subsequently [24]. Sheikholeslami et al. [25] utilized synthetized γ-Fe2O3 nanoparticles for photocatalytic BTEX removal in produced water. The results demonstrated that the removal efficiency was attained 82%, when the photocatalysis nanoparticles concentration was 170 ppm, the pH was 3 and the wastewater for 90 min subjected under UV light with 100 W intensity [25]. According to the recent researches BTEX is considerably detrimental to the environment and humans' health. Thus degradation of BTEX from wastewater is really important. Considering that, in most studies, the γFe2O3 nanoparticle to degradate different contaminants was doped with other nanoparticles, although γ-Fe2O3 nanoparticle has high efficiency for pollutants degradation. Therefore in the present paper, BTEX was considered as an indicator of PW, and γ-Fe2O3 as photocatalyst were synthesized by co-precipitation process. Consequently, with change the effective factors including photocatalyst concentration, pH, and the visible light irradiation intensity, the removal performance of BTEX has been investigated by COD test. For the first time in this paper, maghemite nanoparticle have been applied to remove and degrade the BTEX as an indicator of produced water, and the experiment was designed by DESIGN EXPERT software, the achieved results and predictions are analyzed by using RSM, and the interactions of the main factors were investigated, and the interactive diagrams were presented. Based on the prior scientists, no article has been carried out about applying maghemite nanoparticle on the BTEX removal in produced water.
Table 1 Range of scrutinized parameters. Factor
Levels −α −1 0 (−1.5)
pH Photocatalyst (mg/l) Visible light irradiation intensity (nominal visible light lamp power)
2 0 0
3 50 45
+1
+α (+1.5)
5 7 8 150 250 300 135 225 270
2.2. γ-Fe2O3 nanoparticles synthesis Wet chemical method was used to synthesize maghemite nano particle. For this purpose FeCl3 and FeCl2·4H2O Dissolved in the HCl 2 M to make FeCl3 solution 1 M and FeCl2 tetrahydrate solution 2 M, then these solutions mixed by a mass ratio of 2:1 (Fe (II):Fe (III)), in next step NH4OH was added dropwise with stirring the solution for 2 h to produced γ-Fe2O3 nanoparticles. The pH value equals to 9.5. The dark brown sediments produced were washed 3 times with ethyl alcohol and water, and they were dried at 55–70 °C for 24 h [27]. 2.3. The photocatalyst characteristics XRD (X-ray powder diffraction) demonstrated the γ-Fe2O3 nanoparticles crystalline structure. SEM (Scanning electron microscope) has been applied to measure the nanoparticle size distribution and the structure virtues. Diffuse Reflectance Spectroscopy (DRS) are indicated the synthesized nanoparticles optical absorption characteristics. 2.4. Analytical methods Based on the standard method 5220 C the COD test (chemical oxygen demand) is utilized to evaluate γ-Fe2O3 nanoparticles removal efficiency [28]. 2.5. Design of experiments The Design Expert software discovers the optimum conditions for degradation, the experimental design, and analysis of the results as well [29] and demonstrating 3D graphs to analyze diverse processes [30]. In this work, CCD was employed to optimize photocatalyst concentration,
2. Experimental procedure For PW indicator, BTEX was utilized (Merck, purity: 99%). The chemicals to synthesize maghemite nanoparticles were FeCl3 (Merck, purity 99%), FeCl2·4H2O (Merck, purity 98%), hydrochloric acid (HCl 37% Merck), ammonium hydroxide (NH4OH, Merck, 25% of ammonia), distilled water and ethyl alcohol (Merck, purity 96%). To alter the pH of the solution sulfuric acid and sodium hydroxide were utilized. 2.1. Synthetic wastewater In this paper the concentration of BTEX was about 600 mg/l which is above the worldwide concentration. To make Synthetic wastewater, 600 mg of BTEX dissolved in 1 l of distilled water, after 60 min putted it in an ultrasonic bath, then for 24 h it was stirring on the magnetic stirrer, at last the solution was putted again in ultrasonic bath for 30 min [26].
Fig. 1. Laboratory pilot set-up: (1) Refrigerator, (2) fluorescent lamps, (3) balloon 50 cm3, (4) stirrer.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 2. XRD for γ-Fe2O3 nano-particles using Cu–Kα radiation.
pH, and visible light irradiation intensity as the three main independent factors. In this method, at five levels (−α, −1.5, 0, +1.5, +α) each independent variable is described and the number of experiments equal to 2k + 2k + 6 that k is the independent factors number [31]. The factors and their levels are displayed in Table 1.
2.6. Laboratory pilot set-up Fig. 1 is illustrated the laboratory pilot set-up for the photocatalytic process of PW which contains refrigerator to adjust the temperature (25 °C), fluorescent lamps (OL 40301 M, 45 W, 230 V, 50 Hz), balloon 50 cm3 with visible light transmittance glass to place samples under the visible light irradiation, and the magnetic stirrer to mix the wastewater and nanoparticles. Around each fluorescent lamp the light intensity was approximately 1500 lm. In this study, firstly, the effective range of pH, catalyst concentration, and light intensity was determined by performing the OFAT test design, then for optimizing the variables and applying the model, CCD and RSM were utilized. The effect of variables and the model significance were checked by applying the analysis of variance (ANOVA), P value and F value at 95% confidence level. 3. Experimental analysis 3.1. Photocatalyst nanoparticles analysis
Fig. 3. SEM for γ-Fe2O3.
XRD is a credible important technique to scrutinize crystalline material configuration, consist of atomic arrangement, crystallite size, and defections. According to the patterns of γ-Fe2O3 nanoparticles in Fig. 2 all of the peaks are in match with the standard structure and demonstrate well purity (based on JCBDS file, No. 04-0755). Confirming to the Scherrer equation, synthesized nanoparticles crystallite size was
Fig. 4. DRS pattern of γ-Fe2O3 nanoparticle.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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3.2. Experimental tests and results
Table 2 Various runs for utilized method. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Factor
Response
pH
Photocatalyst (mg/l)
Visible light intensity
Actual
Predicted
3 2 5 8 5 3 3 7 5 5 3 5 7 7 5 5 5 5 5 7
250 150 150 150 150 50 50 50 300 50 250 150 50 250 150 150 0 150 150 250
45 135 0 135 135 45 225 225 135 135 225 135 45 225 135 135 135 135 270 45
37.12 92.71 32.58 42.83 85.11 27.75 40.62 32.38 41.25 86.41 59.12 81.79 21.95 41.72 84.27 82.95 1 84.36 87.76 34.62
41.5 81.00 42.84 56.33 84.42 23.94 48.45 29.14 33.25 84.42 69.00 84.42 13.3 46.76 84.42 84.42 6.79 84.42 75.29 28.02
Confirming to the RSM by employing the experimental design, this study attempted to forecast the relevance between independent factors, and the responses. Based on Table 2, the experimental design involved 20 experiments. To discover the optimum conditions, the experimental design was specified as a function of the most significant independent factors including pH, photocatalyst concentration, and the visible light irradiation intensity that different combinations of the amount of factors were applied to admeasure COD removal. Some pretests was
about 11.5 nm (Eq. (1)). D ¼ λK=β cos θ
ð1Þ
D = middle size of the crystalline K = shape factor β = the line broadening of the XRD peak at half height λ = incident X-ray wavelength (1.54060 Å) θ = Bragg angle. By SEM, the morphology and particle size were indicated. Fig. 3 displays the SEM image of the nanoparticles which demonstrates the average diameter of synthesized γ-Fe2O3 nanoparticle about 22 nm. The nanoparticle morphology indicated an almost spherical shape. It is noteworthy that, due to the existence of nanoparticles agglomeration the particle size obtained by SEM was different from the crystallite size achieved by Scherrer equation. Fig. 4 depicts Diffuse Reflectance Spectrum (DRS) of nanoparticle, which specifies the optical absorption characteristics of γ-Fe2O3. According to Fig. 4 absorption bands can be distinguished between 250 and 600 nm that the visible wavelength range is about 40–50%. By drawing a tangent line to the fracture area, the wavelength of absorption was about 400 nm expresses that within the visible light range the γ-Fe2O3 nanoparticles have an appropriate photocatalytic performance.
Table 3 Analyzing RSM model. Source
Sum of squares
Mean of Degree of F-value P-value squares freedom
Model 13,814.48 1534.94 A-pH 844.77 844.77 972.49 972.49 B-γFe2O3 C-light intensity 1461.67 1461.67 AB 4.29 4.29 AC 37.58 37.58 BC 4.20 4.20 A2 505.34 505.34 2 B 8442.98 8442.98 C2 1308.77 1308.77
9 1 1 1 1 1 1 1 1 1
16.20 8.92 10.26 15.43 0.045 0.40 0.044 5.33 89.11 13.81
b0.0001 Significant 0.0137 0.0094 0.0028 0.8357 0.5429 0.8374 0.0436 b0.0001 0.004
Fig. 5. Analyze of accuracy of obtained formula.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 6. (a) COD removal diagram versus the pH (light intensity = 135 W, catalyst concentration = 150 mg/l); (b) COD removal diagram versus the catalyst concentration (light intensity = 135 W, pH = 3); (c) COD removal diagram versus the light intensity (catalyst concentration = 150 mg/l, pH = 3).
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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operated to determine the effective independent variables ranges which the pH ranges are 2–8, the photocatalyst concentration ranges are 0–300 mg/l, and the visible light intensity ranges are 0–270 W. 3.2.1. ANOVA and model fitting The ANOVA was used to access the interaction between the independent factors and the responses, which shows in Table 3. The null hypothesis for an ANOVA expresses there is no significant discrepancy among the variables. The substitute hypothesis presumes that there is
at least one significant discrepancy among the variables. In general, if the P-value b 0.05, the null hypothesis is rejected and the alternative hypothesis is verified. Also in this research, the model variables were evaluated by the P-value, and Fisher's F-test, which assessed statistical significance of the polynomial formula extracted as (Eq. (2)). CODR ¼ 67:24 þ 15:57A þ 0:95B þ 0:54C−3:66 10−3 AB−0:01 AC þ 8:055 10−5 BC−1:75 A2 −5:86 10−3 B2 −1:39 10−3 C 2 ð2Þ
Fig. 7. Effect of active parameters (a) light intensity = 135w, (b) catalyst concentration = 150 mg/l, (c) pH = 3.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 8. Response surface plot of two active parameter (light intensity = 185 W).
Based on ANOVA table, Eq. (2) and P-values show among the independent variables, A, B, C, A2, B2, C2 were notable in the model (Pvalue b 0.05). The predicted values and empirical data of COD removal performance are different with each other slightly, and respectively R2 was 0.93, which revealed nice agreement. “Adeq Precision” determines the signal to noise ratio, which larger than 4 is appropriate. In this model Adeq Precision is 11.28, which demonstrates an admissible signal. The coefficient of variation (CV) value is 17.66 that result a high accuracy and appropriate value in experimental validity. Fig. 5a represents the residuals plots to verify the appropriate standard deviation distribution between the predicted value and experimental data. The figure represents the common concept of the normal distribution of fundamental errors, due to the proximity of residuals to a straightforward line; there is no indication of uncommon empirical outputs. Residual value against predicted responses is illustrated in
Fig. 5b, which indicates due to casually scattering the experimental data between the range of ±3 the models are acceptable. Based on Fig. 5c the model has a considerable accuracy in forecasting amount, because almost all of the actual and predicted values stay around the correlation line.
3.2.2. 1D profiles In current section, response surface plot between each factors and the response is indicated distinctly. Fig. 6a shows COD removal versus the pH. The COD removal efficiency enhances, when the pH is in the acid range. Catalytic particles surface charge and agglomeration depend on pH, when pH b pHpzc (zero point charge of the γ-Fe2O3 is 5.5 [32]) the removal efficiency increases because the photocatalyst positive charge would appeal more anions [18]. Shahrezaei et al. achieved the same results [31].
Fig. 9. Response surface plot of two active parameter (catalyst concentration = 167 mg/l).
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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The influence of catalyst concentration on COD removal efficiency has been shown in diagram (b), which expressed the removal efficiency has improved by raising the photocatalyst concentration up to a particular amount (167 mg/l) and then decreased. Reaction speed is directly related to photocatalyst mass until specific amount, because certain area of nanoparticles could subjected to light, and in high concentration it reduced, thereupon the removal efficiency decreased [31]. The other researchers such as Dutta et al. [33], Salah et al. [34], Omar et al. [35], Shukla et al. [36] discovered the similar results. The removal efficiency depended on the light intensity (diagram c), because the rate of electron and hole production increased with increment of light intensity, hence the removal efficiency improved [37]. Ba-Abbad et al. obtained the same consequence [38]. 3.2.3. Interactive diagrams Interactive diagrams illustrate the synergistic or antagonistic impacts of the independent factors on response. Fig. 7a represents the interactive impact of the photocatalyst concentration and pH, which indicates by reducing the pH at the minimum (0 mg/l) and the maximum photocatalyst concentration (250 mg/l) the COD removal rate will increase. Base on Fig. 7b by reducing the pH at the least and the most visible light irradiation intensity the COD removal efficiency will improve. Based on Fig. 7c the COD removal rate increases up to the specific amount of photocatalyst concentration in the minimum and maximum light intensity. Eventually the diagrams display no interactions among the independent variables. 3.2.4. 3D diagrams The relevance among photocatalyst concentration, pH, and COD removal illustrates in Fig. 8. The optimum COD removal efficiency is achieved 90.95% when the photocatalyst concentration is 167 mg/l, and pH around 3.64. As displayed in Fig. 6, the COD removal rate improves, when the concentration of photocatalyst is increasing up to 167 ppm, and then reduces. Response surface plot between visible light irradiation intensity, pH and COD removal efficiency displays Fig. 9. Based on Fig. 9, the best COD removal rate is discovered 92% at 180 W of light intensity and pH about 3.64. Therefore, raising the visible light irradiation intensity, and reducing pH, has significant effect on COD removal. Response surface plot between light intensity, photocatalyst fraction, and COD removal shows Fig. 10. The optimum COD removal
efficiency is 92% that obtained at 180 W of visible light intensity, and 167 mg/l of photocatalyst concentration. Hence due to the one factor and 3D diagrams, independent variables are effective on removal performance. 4. Conclusion Owing to the favorable costs, applying the process at ambient temperature and lesser intermediate products, photocatalytic processes are more utilized in wastewater behavior. For the first time in this work the γ-Fe2O3 nanoparticles were utilized to eliminate BTEX under visible light. According to the results of the ANOVA the effective parameters were photocatalyst concentration, second-order effect of photocatalyst fraction, pH, second-order effect of pH, light Intensity, second-order effect of light Intensity. The predicted values and experimental data of COD removal efficiency are different slightly with each other, and respectively R2adj and R2 for the model were 0.87 and 0.93, which represent the model had great accordance to the experimental data. The catalyst concentration optimum values, pH and visible light irradiation intensity respectively were 167 ppm, 3.64, and 180 W. Declaration of competing interest This paper is original. References [1] S.E. Weschenfelder, A.C.C. Mello, C.P. Borges, J.C. Campos, Desalination 360 (2015) 81. [2] S. Jiménez, M.M. Micó, M. Arnaldos, E. Ferrero, J.J. Malfeito, F. Medina, S. Contreras, Chemosphere 168 (2017) 309. [3] J.M. Neff, Bioaccumulation in Marine Organisms: Effect of Contaminants From Oil Well Produced Water, Elsevier, 2002. [4] S. Picone, Transport and Biodegradation of Volatile Organic Compounds: Influence on Vapor Intrusion Into Buildings, 2012. [5] K. Khodaei, H.R. Nassery, M.M. Asadi, H. Mohammadzadeh, M.G. Mahmoodlu, Int. Biodeterior. Biodegradation 116 (2017) 234. [6] K. Lee, J. Neff, Produced Water: Environmental Risks and Advances in Mitigation Technologies, Springer, 2011. [7] E.T. Igunnu, G.Z. Chen, International Journal of Low-Carbon Technologies 9 (2012) 157. [8] J. Lu, X. Wang, B. Shan, X. Li, W. Wang, Chemosphere 62 (2006) 322. [9] J. Xu, N.M. Srivatsa Bettahalli, S. Chisca, M.K. Khalid, N. Ghaffour, R. Vilagines, S.P. Nunes, Desalination 432 (2018) 32. [10] C.F. Bustillo-Lecompte, D. Kakar, M. Mehrvar, J. Clean. Prod. 186 (2018) 609.
Fig. 10. Response surface plot of two active parameter (pH = 3).
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
Z. Sheikholeslami et al. / Journal of Molecular Liquids xxx (xxxx) xxx [11] M.N. Chong, B. Jin, C.W. Chow, C. Saint, Water Res. 44 (2010) 2997. [12] D.-R. Jung, J. Kim, C. Nahm, H. Choi, S. Nam, B. Park, Electron. Mater. Lett. 7 (2011) 185. [13] L. Zhang, M. Jaroniec, Appl. Surf. Sci. 430 (2018) 2. [14] A. Hernández-Ramírez, I. Medina-Ramírez, Photocatalytic Semiconductors, Springer, 2016. [15] P. Roushenas, Z. Yusop, Z. Majidnia, R. Nasrollahpour, Desalin. Water Treat. 57 (2016) 5837. [16] K. Ali, A.K. Sarfraz, I.M. Mirza, A. Bahadur, S. Iqbal, A. ul Haq, Curr. Appl. Phys. 15 (2015) 925. [17] E. Darezereshki, M. Ranjbar, F. Bakhtiari, J. Alloys Compd. 502 (2010) 257. [18] B. Liu, B. Chen, B. Zhang, IEEE Nanotechnol. Mag. 11 (2017) 4. [19] Z. Sheikholeslami, D.Y. Kebria, F. Qaderi, J. Therm. Anal. Calorim. 135 (2019) 1617. [20] M. Ghavami, R. Mohammadi, M. Koohi, M.Z. Kassaee, Mater. Sci. Semicond. Process. 26 (2014) 69. [21] A. Fakhri, S. Rashidi, I. Tyagi, S. Agarwal, V.K. Gupta, J. Mol. Liq. 214 (2016) 378. [22] J. Wang, X. Shao, Q. Zhang, G. Tian, X. Ji, W. Bao, J. Mol. Liq. 248 (2017) 13. [23] H.R. Pouretedal, J. Alloys Compd. 735 (2018) 2507. [24] J. Niu, Z. Zhang, P. Dai, B. Yao, X. Yu, Q. Zhang, R. Yang, Mater. Des. 150 (2018) 29.
[25] [26] [27] [28]
[29] [30] [31] [32] [33] [34] [35] [36] [37] [38]
9
Z. Sheikholeslami, D. Yousefi Kebria, F. Qaderi, J. Mol. Liq. 264 (2018) 476. B. Bina, M.M. Amin, A. Rashidi, H. Pourzamani, Water Resources 41 (2014) 719. E. Darezereshki, Mater. Lett. 64 (2010) 1471. A.P.H. Association, A.W.W. Association, W.P.C. Federation, W.E. Federation, Standard Methods for the Examination of Water and Wastewater, American Public Health Association, 1915. I.-H. Cho, K.-D. Zoh, Dyes Pigments 75 (2007) 533. A.R. Khataee, M. Fathinia, S. Aber, M. Zarei, J. Hazard. Mater. 181 (2010) 886. F. Shahrezaei, Y. Mansouri, A.A.L. Zinatizadeh, A. Akhbari, Powder Technol. 221 (2012) 203. H. Watanabe, J.e. Seto, Bull. Chem. Soc. Jpn. 59 (1986) 2683. A.K. Dutta, S.K. Maji, B. Adhikary, Mater. Res. Bull. 49 (2014) 28. N.H. Salah, M. Bouhelassaa, S. Bekkouche, A. Boultii, Desalination 166 (2004) 347. K. Omar, N. Aziz, S. Amr, P. Palaniandy, (2017). P.R. Shukla, S. Wang, H.M. Ang, M.O. Tadé, Sep. Purif. Technol. 70 (2010) 338. S. Ahmed, M. Rasul, W.N. Martens, R. Brown, M. Hashib, Desalination 261 (2010) 3. M.M. Ba-Abbad, M.S. Takriff, M. Said, A. Benamor, M.S. Nasser, A.W. Mohammad, International Journal of Environmental Research (2017) 1.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light Z. Sheikholeslami a,b,⁎, D. Yousefi Kebria a, F. Qaderi a,⁎ a b
Department of Civil Engineering, Babol Noshirvani University of Technology, P.O. Box 484, Babol, Iran Department of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran
a r t i c l e
i n f o
Article history: Received 1 July 2019 Received in revised form 6 November 2019 Accepted 11 November 2019 Available online xxxx Keywords: Produced water Nanophotocatalyst Semiconductor Maghemite Aromatic hydrocarbon
a b s t r a c t Nanophotocatalytic process among various methods is used more for BTEX removal as an aromatic hydrocarbon in produced water. For this purpose, γ-Fe2O3 nanoparticle, which has significant efficiency to remove and degraded the contaminants. γ-Fe2O3 photocatalysis nanoparticle was synthesized by co-precipitation process, and the nanoparticle characteristics were determined by XRD, SEM and DRS. The main factors impact were studied including: pH (2–8), photocatalyst concentration (0–300 mg/l) and visible light irradiation intensity (0–270 W). The experiments were applied by a CCD and analyzed by using RSM. From the results analysis the polynomial formula has been derived for the model. For the first time, the effects of interactions of the main factors were investigated and the interactive diagrams were presented. The results show that the maximum BTEX removal efficiency (90.94%) was observed in 3.64 of pH, 167 mg/l of the nanoparticle concentration, and 180 W of the light intensity. © 2019 Published by Elsevier B.V.
1. Introduction Oil extraction process has many byproduct such as produced water (PW) [1], which the ratio of water to oil in PW is around 3:1 [2]. PW contains complex chemicals compositions such as dissolved and dispersed oils, metals, and hydrocarbons [3]. BTEX (benzene, toluene, ethylbenzene, xylene isomers) is an aromatic hydrocarbons, which is extremely harmful on both human health as well as ecosystem functions [4,5]. The BTEX concentration of PW is 0.068–578 mg/l in the all of the world [6] which is too excessive allowed to be discharged in to the environment [7]. In the world the industries of oil and gas has attended to use the technologies of PW treatment, due to the BTEX hazardous environmental impacts [8]. For PW treatment physical, chemical, and biological methods have been suggested [9]. One of the most efficient and appropriate for water treatment technologies is Advanced Oxidation Processes (AOPs) [10]. Among different methods of AOPs, the photocatalytic process, due to the performance of the process at temperature and ambient pressure, production of fewer intermediate products and lower costs, is one of the great promising technologies for water and wastewater treatment [11]. Recent years, the researchers were interested in semiconductor photocatalytic nanoparticles [12]. In photocatalytic semiconductors by receiving energy the electrons which exist in the valence bands (VB) can be transferred and excited to band of conduction. Consequently many ⁎ Corresponding authors at: Department of Civil Engineering, Babol Noshirvani University of Technology, P.O. Box 484, Babol, Iran. E-mail addresses: [email protected] (Z. Sheikholeslami), [email protected] (F. Qaderi).
electron-positive hole pairs (e− and h+) come into existence [13]. Subsequently, the reactance between h+ in CB and water are generated the hy droxyl radicals [OH] which are powerful oxidants and react with organic and toxic compounds. At the beginning of oxidation reactions, ½ OH radicals perform an important role [14]. Maghemite (γ-Fe2O3) nanoparticles are a kind of semiconductors [15]. Different methods have been utilized in the γ-Fe2O3 nanoparticles synthesis, such as sol-gel, co-precipitation, micro emulsion and hydrothermal synthesis [16]. One-step coprecipitation method is illustrated in this paper for the γ-Fe2O3 nanoparticles synthesis. In this way, pure γ-Fe2O3 with a mediocre particle size under 30 nm will be composed without any α-Fe2O3 and Fe3O4 [17]. Among the different parameters visible light irradiation intensity, pH, and photocatalyst concentration are the most considerable important factors in a photocatalytic process [18]. In last years, many researchers have considered the photocatalytic process of γ-Fe2O3 nanoparticles for degradation of various pollutant [19]. Ghavami et al. [20] investigated the degradation of toxic crystal violet (CV) in wastewater with synthesized magnetic nanocomposite, which containing reduced graphene oxide with γ-Fe2O3, silver and titanium dioxide. The results indicated the removal efficiency was obtained 97% with high recovery and stability of nanocomposite [20]. Fakhri et al. [21] evaluated the application of γ-Fe2O3/SiO2 nanocomposite for Erythromycin antibiotic removal by using RSM. Conforming to the results the highest degradation efficiency and the best correlation coefficient were respectively obtained 87.17% and 0.9354. The experimental conditions were included: pH = 7, 6 mg/l of Erythromycin concentration, 500 mg/l of γFe2O3/SiO2 concentration and the time of tests was 6 min [21]. Wang et al. [22] prepared the mesoporous magnetic Fe2O3 nanoparticles for
https://doi.org/10.1016/j.molliq.2019.112118 0167-7322/© 2019 Published by Elsevier B.V.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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methyl orange (MO) degradation from aqueous solution. The experimental tests were applied in absence of photocatalyst, absence of H2O2 and absence of visible light irradiation. According to the results, in the first condition, which the tests applied without any photocatalyst, there was no significant change in MO degradation. Also, by adding the nanoparticles but without H2O2, and by adding nanoparticles and 30% H2O2 to MO solution in absence of visible light irradiation the maximum degradation were respectively obtained 6.12% and 6.62%; but, when the above solution subjected to the visible light the best degradation was achieved almost 100% [22]. Pouretedal [23] studied the photocatalytic application of TiO2/Zr and TiO2/N nanomaterial under visible light for degradation of trinitrotoluene (TNT) and 2,4-dinitrotoluene (2,4DNT), in polluted solution. The removal efficiency was determined after 12 h, which was obtained 35.9% for the presence of TiO2, 42.4% for the presence of TiO2/Zr and 61.5% for the presence of TiO2/N; finally, the best activity was attained 67.7% in 2.0 g/l of TiO2/Zr,N nanoparticles concentration [23]. Niu et al. [24] studied the photocatalytic performance of γ-Fe2O3/BiOI for sulfapyridine and methyl orange degradation in wastewater. γ-Fe2O3/BiOI was synthesized by microwave hydrothermal and sol-gel methods. According to the experiments the band gap of composite catalyst was 1.75 eV, and the medium pore size was 6.756 nm. After subjecting the wastewater for 120 min under the tungsten lamp the sulfapyridine and methyl orange removal efficiency was achieved 64.1% and 67.6% subsequently [24]. Sheikholeslami et al. [25] utilized synthetized γ-Fe2O3 nanoparticles for photocatalytic BTEX removal in produced water. The results demonstrated that the removal efficiency was attained 82%, when the photocatalysis nanoparticles concentration was 170 ppm, the pH was 3 and the wastewater for 90 min subjected under UV light with 100 W intensity [25]. According to the recent researches BTEX is considerably detrimental to the environment and humans' health. Thus degradation of BTEX from wastewater is really important. Considering that, in most studies, the γFe2O3 nanoparticle to degradate different contaminants was doped with other nanoparticles, although γ-Fe2O3 nanoparticle has high efficiency for pollutants degradation. Therefore in the present paper, BTEX was considered as an indicator of PW, and γ-Fe2O3 as photocatalyst were synthesized by co-precipitation process. Consequently, with change the effective factors including photocatalyst concentration, pH, and the visible light irradiation intensity, the removal performance of BTEX has been investigated by COD test. For the first time in this paper, maghemite nanoparticle have been applied to remove and degrade the BTEX as an indicator of produced water, and the experiment was designed by DESIGN EXPERT software, the achieved results and predictions are analyzed by using RSM, and the interactions of the main factors were investigated, and the interactive diagrams were presented. Based on the prior scientists, no article has been carried out about applying maghemite nanoparticle on the BTEX removal in produced water.
Table 1 Range of scrutinized parameters. Factor
Levels −α −1 0 (−1.5)
pH Photocatalyst (mg/l) Visible light irradiation intensity (nominal visible light lamp power)
2 0 0
3 50 45
+1
+α (+1.5)
5 7 8 150 250 300 135 225 270
2.2. γ-Fe2O3 nanoparticles synthesis Wet chemical method was used to synthesize maghemite nano particle. For this purpose FeCl3 and FeCl2·4H2O Dissolved in the HCl 2 M to make FeCl3 solution 1 M and FeCl2 tetrahydrate solution 2 M, then these solutions mixed by a mass ratio of 2:1 (Fe (II):Fe (III)), in next step NH4OH was added dropwise with stirring the solution for 2 h to produced γ-Fe2O3 nanoparticles. The pH value equals to 9.5. The dark brown sediments produced were washed 3 times with ethyl alcohol and water, and they were dried at 55–70 °C for 24 h [27]. 2.3. The photocatalyst characteristics XRD (X-ray powder diffraction) demonstrated the γ-Fe2O3 nanoparticles crystalline structure. SEM (Scanning electron microscope) has been applied to measure the nanoparticle size distribution and the structure virtues. Diffuse Reflectance Spectroscopy (DRS) are indicated the synthesized nanoparticles optical absorption characteristics. 2.4. Analytical methods Based on the standard method 5220 C the COD test (chemical oxygen demand) is utilized to evaluate γ-Fe2O3 nanoparticles removal efficiency [28]. 2.5. Design of experiments The Design Expert software discovers the optimum conditions for degradation, the experimental design, and analysis of the results as well [29] and demonstrating 3D graphs to analyze diverse processes [30]. In this work, CCD was employed to optimize photocatalyst concentration,
2. Experimental procedure For PW indicator, BTEX was utilized (Merck, purity: 99%). The chemicals to synthesize maghemite nanoparticles were FeCl3 (Merck, purity 99%), FeCl2·4H2O (Merck, purity 98%), hydrochloric acid (HCl 37% Merck), ammonium hydroxide (NH4OH, Merck, 25% of ammonia), distilled water and ethyl alcohol (Merck, purity 96%). To alter the pH of the solution sulfuric acid and sodium hydroxide were utilized. 2.1. Synthetic wastewater In this paper the concentration of BTEX was about 600 mg/l which is above the worldwide concentration. To make Synthetic wastewater, 600 mg of BTEX dissolved in 1 l of distilled water, after 60 min putted it in an ultrasonic bath, then for 24 h it was stirring on the magnetic stirrer, at last the solution was putted again in ultrasonic bath for 30 min [26].
Fig. 1. Laboratory pilot set-up: (1) Refrigerator, (2) fluorescent lamps, (3) balloon 50 cm3, (4) stirrer.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 2. XRD for γ-Fe2O3 nano-particles using Cu–Kα radiation.
pH, and visible light irradiation intensity as the three main independent factors. In this method, at five levels (−α, −1.5, 0, +1.5, +α) each independent variable is described and the number of experiments equal to 2k + 2k + 6 that k is the independent factors number [31]. The factors and their levels are displayed in Table 1.
2.6. Laboratory pilot set-up Fig. 1 is illustrated the laboratory pilot set-up for the photocatalytic process of PW which contains refrigerator to adjust the temperature (25 °C), fluorescent lamps (OL 40301 M, 45 W, 230 V, 50 Hz), balloon 50 cm3 with visible light transmittance glass to place samples under the visible light irradiation, and the magnetic stirrer to mix the wastewater and nanoparticles. Around each fluorescent lamp the light intensity was approximately 1500 lm. In this study, firstly, the effective range of pH, catalyst concentration, and light intensity was determined by performing the OFAT test design, then for optimizing the variables and applying the model, CCD and RSM were utilized. The effect of variables and the model significance were checked by applying the analysis of variance (ANOVA), P value and F value at 95% confidence level. 3. Experimental analysis 3.1. Photocatalyst nanoparticles analysis
Fig. 3. SEM for γ-Fe2O3.
XRD is a credible important technique to scrutinize crystalline material configuration, consist of atomic arrangement, crystallite size, and defections. According to the patterns of γ-Fe2O3 nanoparticles in Fig. 2 all of the peaks are in match with the standard structure and demonstrate well purity (based on JCBDS file, No. 04-0755). Confirming to the Scherrer equation, synthesized nanoparticles crystallite size was
Fig. 4. DRS pattern of γ-Fe2O3 nanoparticle.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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3.2. Experimental tests and results
Table 2 Various runs for utilized method. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Factor
Response
pH
Photocatalyst (mg/l)
Visible light intensity
Actual
Predicted
3 2 5 8 5 3 3 7 5 5 3 5 7 7 5 5 5 5 5 7
250 150 150 150 150 50 50 50 300 50 250 150 50 250 150 150 0 150 150 250
45 135 0 135 135 45 225 225 135 135 225 135 45 225 135 135 135 135 270 45
37.12 92.71 32.58 42.83 85.11 27.75 40.62 32.38 41.25 86.41 59.12 81.79 21.95 41.72 84.27 82.95 1 84.36 87.76 34.62
41.5 81.00 42.84 56.33 84.42 23.94 48.45 29.14 33.25 84.42 69.00 84.42 13.3 46.76 84.42 84.42 6.79 84.42 75.29 28.02
Confirming to the RSM by employing the experimental design, this study attempted to forecast the relevance between independent factors, and the responses. Based on Table 2, the experimental design involved 20 experiments. To discover the optimum conditions, the experimental design was specified as a function of the most significant independent factors including pH, photocatalyst concentration, and the visible light irradiation intensity that different combinations of the amount of factors were applied to admeasure COD removal. Some pretests was
about 11.5 nm (Eq. (1)). D ¼ λK=β cos θ
ð1Þ
D = middle size of the crystalline K = shape factor β = the line broadening of the XRD peak at half height λ = incident X-ray wavelength (1.54060 Å) θ = Bragg angle. By SEM, the morphology and particle size were indicated. Fig. 3 displays the SEM image of the nanoparticles which demonstrates the average diameter of synthesized γ-Fe2O3 nanoparticle about 22 nm. The nanoparticle morphology indicated an almost spherical shape. It is noteworthy that, due to the existence of nanoparticles agglomeration the particle size obtained by SEM was different from the crystallite size achieved by Scherrer equation. Fig. 4 depicts Diffuse Reflectance Spectrum (DRS) of nanoparticle, which specifies the optical absorption characteristics of γ-Fe2O3. According to Fig. 4 absorption bands can be distinguished between 250 and 600 nm that the visible wavelength range is about 40–50%. By drawing a tangent line to the fracture area, the wavelength of absorption was about 400 nm expresses that within the visible light range the γ-Fe2O3 nanoparticles have an appropriate photocatalytic performance.
Table 3 Analyzing RSM model. Source
Sum of squares
Mean of Degree of F-value P-value squares freedom
Model 13,814.48 1534.94 A-pH 844.77 844.77 972.49 972.49 B-γFe2O3 C-light intensity 1461.67 1461.67 AB 4.29 4.29 AC 37.58 37.58 BC 4.20 4.20 A2 505.34 505.34 2 B 8442.98 8442.98 C2 1308.77 1308.77
9 1 1 1 1 1 1 1 1 1
16.20 8.92 10.26 15.43 0.045 0.40 0.044 5.33 89.11 13.81
b0.0001 Significant 0.0137 0.0094 0.0028 0.8357 0.5429 0.8374 0.0436 b0.0001 0.004
Fig. 5. Analyze of accuracy of obtained formula.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 6. (a) COD removal diagram versus the pH (light intensity = 135 W, catalyst concentration = 150 mg/l); (b) COD removal diagram versus the catalyst concentration (light intensity = 135 W, pH = 3); (c) COD removal diagram versus the light intensity (catalyst concentration = 150 mg/l, pH = 3).
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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operated to determine the effective independent variables ranges which the pH ranges are 2–8, the photocatalyst concentration ranges are 0–300 mg/l, and the visible light intensity ranges are 0–270 W. 3.2.1. ANOVA and model fitting The ANOVA was used to access the interaction between the independent factors and the responses, which shows in Table 3. The null hypothesis for an ANOVA expresses there is no significant discrepancy among the variables. The substitute hypothesis presumes that there is
at least one significant discrepancy among the variables. In general, if the P-value b 0.05, the null hypothesis is rejected and the alternative hypothesis is verified. Also in this research, the model variables were evaluated by the P-value, and Fisher's F-test, which assessed statistical significance of the polynomial formula extracted as (Eq. (2)). CODR ¼ 67:24 þ 15:57A þ 0:95B þ 0:54C−3:66 10−3 AB−0:01 AC þ 8:055 10−5 BC−1:75 A2 −5:86 10−3 B2 −1:39 10−3 C 2 ð2Þ
Fig. 7. Effect of active parameters (a) light intensity = 135w, (b) catalyst concentration = 150 mg/l, (c) pH = 3.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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Fig. 8. Response surface plot of two active parameter (light intensity = 185 W).
Based on ANOVA table, Eq. (2) and P-values show among the independent variables, A, B, C, A2, B2, C2 were notable in the model (Pvalue b 0.05). The predicted values and empirical data of COD removal performance are different with each other slightly, and respectively R2 was 0.93, which revealed nice agreement. “Adeq Precision” determines the signal to noise ratio, which larger than 4 is appropriate. In this model Adeq Precision is 11.28, which demonstrates an admissible signal. The coefficient of variation (CV) value is 17.66 that result a high accuracy and appropriate value in experimental validity. Fig. 5a represents the residuals plots to verify the appropriate standard deviation distribution between the predicted value and experimental data. The figure represents the common concept of the normal distribution of fundamental errors, due to the proximity of residuals to a straightforward line; there is no indication of uncommon empirical outputs. Residual value against predicted responses is illustrated in
Fig. 5b, which indicates due to casually scattering the experimental data between the range of ±3 the models are acceptable. Based on Fig. 5c the model has a considerable accuracy in forecasting amount, because almost all of the actual and predicted values stay around the correlation line.
3.2.2. 1D profiles In current section, response surface plot between each factors and the response is indicated distinctly. Fig. 6a shows COD removal versus the pH. The COD removal efficiency enhances, when the pH is in the acid range. Catalytic particles surface charge and agglomeration depend on pH, when pH b pHpzc (zero point charge of the γ-Fe2O3 is 5.5 [32]) the removal efficiency increases because the photocatalyst positive charge would appeal more anions [18]. Shahrezaei et al. achieved the same results [31].
Fig. 9. Response surface plot of two active parameter (catalyst concentration = 167 mg/l).
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118
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The influence of catalyst concentration on COD removal efficiency has been shown in diagram (b), which expressed the removal efficiency has improved by raising the photocatalyst concentration up to a particular amount (167 mg/l) and then decreased. Reaction speed is directly related to photocatalyst mass until specific amount, because certain area of nanoparticles could subjected to light, and in high concentration it reduced, thereupon the removal efficiency decreased [31]. The other researchers such as Dutta et al. [33], Salah et al. [34], Omar et al. [35], Shukla et al. [36] discovered the similar results. The removal efficiency depended on the light intensity (diagram c), because the rate of electron and hole production increased with increment of light intensity, hence the removal efficiency improved [37]. Ba-Abbad et al. obtained the same consequence [38]. 3.2.3. Interactive diagrams Interactive diagrams illustrate the synergistic or antagonistic impacts of the independent factors on response. Fig. 7a represents the interactive impact of the photocatalyst concentration and pH, which indicates by reducing the pH at the minimum (0 mg/l) and the maximum photocatalyst concentration (250 mg/l) the COD removal rate will increase. Base on Fig. 7b by reducing the pH at the least and the most visible light irradiation intensity the COD removal efficiency will improve. Based on Fig. 7c the COD removal rate increases up to the specific amount of photocatalyst concentration in the minimum and maximum light intensity. Eventually the diagrams display no interactions among the independent variables. 3.2.4. 3D diagrams The relevance among photocatalyst concentration, pH, and COD removal illustrates in Fig. 8. The optimum COD removal efficiency is achieved 90.95% when the photocatalyst concentration is 167 mg/l, and pH around 3.64. As displayed in Fig. 6, the COD removal rate improves, when the concentration of photocatalyst is increasing up to 167 ppm, and then reduces. Response surface plot between visible light irradiation intensity, pH and COD removal efficiency displays Fig. 9. Based on Fig. 9, the best COD removal rate is discovered 92% at 180 W of light intensity and pH about 3.64. Therefore, raising the visible light irradiation intensity, and reducing pH, has significant effect on COD removal. Response surface plot between light intensity, photocatalyst fraction, and COD removal shows Fig. 10. The optimum COD removal
efficiency is 92% that obtained at 180 W of visible light intensity, and 167 mg/l of photocatalyst concentration. Hence due to the one factor and 3D diagrams, independent variables are effective on removal performance. 4. Conclusion Owing to the favorable costs, applying the process at ambient temperature and lesser intermediate products, photocatalytic processes are more utilized in wastewater behavior. For the first time in this work the γ-Fe2O3 nanoparticles were utilized to eliminate BTEX under visible light. According to the results of the ANOVA the effective parameters were photocatalyst concentration, second-order effect of photocatalyst fraction, pH, second-order effect of pH, light Intensity, second-order effect of light Intensity. The predicted values and experimental data of COD removal efficiency are different slightly with each other, and respectively R2adj and R2 for the model were 0.87 and 0.93, which represent the model had great accordance to the experimental data. The catalyst concentration optimum values, pH and visible light irradiation intensity respectively were 167 ppm, 3.64, and 180 W. Declaration of competing interest This paper is original. References [1] S.E. Weschenfelder, A.C.C. Mello, C.P. Borges, J.C. Campos, Desalination 360 (2015) 81. [2] S. Jiménez, M.M. Micó, M. Arnaldos, E. Ferrero, J.J. Malfeito, F. Medina, S. Contreras, Chemosphere 168 (2017) 309. [3] J.M. Neff, Bioaccumulation in Marine Organisms: Effect of Contaminants From Oil Well Produced Water, Elsevier, 2002. [4] S. Picone, Transport and Biodegradation of Volatile Organic Compounds: Influence on Vapor Intrusion Into Buildings, 2012. [5] K. Khodaei, H.R. Nassery, M.M. Asadi, H. Mohammadzadeh, M.G. Mahmoodlu, Int. Biodeterior. Biodegradation 116 (2017) 234. [6] K. Lee, J. Neff, Produced Water: Environmental Risks and Advances in Mitigation Technologies, Springer, 2011. [7] E.T. Igunnu, G.Z. Chen, International Journal of Low-Carbon Technologies 9 (2012) 157. [8] J. Lu, X. Wang, B. Shan, X. Li, W. Wang, Chemosphere 62 (2006) 322. [9] J. Xu, N.M. Srivatsa Bettahalli, S. Chisca, M.K. Khalid, N. Ghaffour, R. Vilagines, S.P. Nunes, Desalination 432 (2018) 32. [10] C.F. Bustillo-Lecompte, D. Kakar, M. Mehrvar, J. Clean. Prod. 186 (2018) 609.
Fig. 10. Response surface plot of two active parameter (pH = 3).
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Z. Sheikholeslami et al. / Journal of Molecular Liquids xxx (xxxx) xxx [11] M.N. Chong, B. Jin, C.W. Chow, C. Saint, Water Res. 44 (2010) 2997. [12] D.-R. Jung, J. Kim, C. Nahm, H. Choi, S. Nam, B. Park, Electron. Mater. Lett. 7 (2011) 185. [13] L. Zhang, M. Jaroniec, Appl. Surf. Sci. 430 (2018) 2. [14] A. Hernández-Ramírez, I. Medina-Ramírez, Photocatalytic Semiconductors, Springer, 2016. [15] P. Roushenas, Z. Yusop, Z. Majidnia, R. Nasrollahpour, Desalin. Water Treat. 57 (2016) 5837. [16] K. Ali, A.K. Sarfraz, I.M. Mirza, A. Bahadur, S. Iqbal, A. ul Haq, Curr. Appl. Phys. 15 (2015) 925. [17] E. Darezereshki, M. Ranjbar, F. Bakhtiari, J. Alloys Compd. 502 (2010) 257. [18] B. Liu, B. Chen, B. Zhang, IEEE Nanotechnol. Mag. 11 (2017) 4. [19] Z. Sheikholeslami, D.Y. Kebria, F. Qaderi, J. Therm. Anal. Calorim. 135 (2019) 1617. [20] M. Ghavami, R. Mohammadi, M. Koohi, M.Z. Kassaee, Mater. Sci. Semicond. Process. 26 (2014) 69. [21] A. Fakhri, S. Rashidi, I. Tyagi, S. Agarwal, V.K. Gupta, J. Mol. Liq. 214 (2016) 378. [22] J. Wang, X. Shao, Q. Zhang, G. Tian, X. Ji, W. Bao, J. Mol. Liq. 248 (2017) 13. [23] H.R. Pouretedal, J. Alloys Compd. 735 (2018) 2507. [24] J. Niu, Z. Zhang, P. Dai, B. Yao, X. Yu, Q. Zhang, R. Yang, Mater. Des. 150 (2018) 29.
[25] [26] [27] [28]
[29] [30] [31] [32] [33] [34] [35] [36] [37] [38]
9
Z. Sheikholeslami, D. Yousefi Kebria, F. Qaderi, J. Mol. Liq. 264 (2018) 476. B. Bina, M.M. Amin, A. Rashidi, H. Pourzamani, Water Resources 41 (2014) 719. E. Darezereshki, Mater. Lett. 64 (2010) 1471. A.P.H. Association, A.W.W. Association, W.P.C. Federation, W.E. Federation, Standard Methods for the Examination of Water and Wastewater, American Public Health Association, 1915. I.-H. Cho, K.-D. Zoh, Dyes Pigments 75 (2007) 533. A.R. Khataee, M. Fathinia, S. Aber, M. Zarei, J. Hazard. Mater. 181 (2010) 886. F. Shahrezaei, Y. Mansouri, A.A.L. Zinatizadeh, A. Akhbari, Powder Technol. 221 (2012) 203. H. Watanabe, J.e. Seto, Bull. Chem. Soc. Jpn. 59 (1986) 2683. A.K. Dutta, S.K. Maji, B. Adhikary, Mater. Res. Bull. 49 (2014) 28. N.H. Salah, M. Bouhelassaa, S. Bekkouche, A. Boultii, Desalination 166 (2004) 347. K. Omar, N. Aziz, S. Amr, P. Palaniandy, (2017). P.R. Shukla, S. Wang, H.M. Ang, M.O. Tadé, Sep. Purif. Technol. 70 (2010) 338. S. Ahmed, M. Rasul, W.N. Martens, R. Brown, M. Hashib, Desalination 261 (2010) 3. M.M. Ba-Abbad, M.S. Takriff, M. Said, A. Benamor, M.S. Nasser, A.W. Mohammad, International Journal of Environmental Research (2017) 1.
Please cite this article as: Z. Sheikholeslami, D.Y. Kebria and F. Qaderi, Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light, Journal of Molecular Liquids, https://doi.org/10.1016/j.molliq.2019.112118