Benzene removal by nano magnetic particles under continuous condition from aqueous solutions

RESEARCH ARTICLE

Benzene removal by nano magnetic particles undercontinuous condition from aqueous solutions

Mohammad Mehdi Amin1, Bijan Bina1, Amir Masoud Samani Majd2, Hamidreza Pourzamani (✉)1

1 Environment Research Center, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran2 BAEN Department, Texas A&M University, TX 77843, USA

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2013

Abstract Benzene removal from aqueous solutions wasevaluated using Fe3O4 nano magnetic particles (NM) incontinuous condition. A 44 factorial design includinginitial benzene concentration, NM dose, contact time andpH was investigated in 16 experiments (Taguchi OAdesign). The results indicated that all factors weresignificant and the optimum condition was: pH 8,NM dose of 2000 mg$L–1, benzene concentrations of100 mg$L–1 and contact time of 14 min. The maximumbenzene uptake and distribution ratio in the optimumsituation were 49.4 mg$g–1 and 38.4 L$g–1, respectively.The nano particles were shown to capture 98.7% of thebenzene in optimum batch condition and 94.5% incontinuous condition. The isotherm data proved that theBrunauer-Emmett-Teller model fit more closely andproduced an isotherm constant (b) less than one, indicatingfavorable adsorption. Regeneration studies verified that thebenzene adsorbed by the NM could be easily desorbed bytemperature, and thereby, NM can be employed repeatedlyin water and wastewater management.

Keywords benzene, experimental design, Fe3O4, con-tinues condition, thermal recycling

1 Introduction

Benzene is one of the contaminators of air, surface waterand groundwater. It is volatile monoaromatic compoundoriginated from petroleum products [1,2]. Benzenepollutes groundwater through the leakage from under-ground storage, pipelines, improper waste disposal,inadvertent spills and landfills [3,4]. Epidemiologicalstudies show its serious adverse effects to human health

such as skin disease, sensory irritation, central nervoussystem depression, respiratory problems, leukemia, cancer,kidney disturbance and liver and blood systems disorders[5–7]. Benzene is classified as primary pollutants,regulated by the US Environmental Protection Agency(EPA), and was among the target compounds in EPA’s 33–50 program. It occupies sixth position in the priority list ofhazardous substances Comprehensive EnvironmentalResponse, Compensation and Liability Act (CERCLA)[6]. Maximum contaminant level of 5 μg$L–1 benzene hasbeen set as the standard for drinking water by the EPA[6,8].Benzene removal from aqueous solutions has been

studied in order to investigate a suitable method indifferent condition including bioremediation, volatiliza-tion, oxidation and adsorption [6–13]. The application ofadsorption methods by using resins [14], raw and modifieddiatomite [7], organo-clays [15] and carbon nano tubes[16,17] have been approved for benzene mitigation. Wanget al. [18] used magnetite (Fe3O4) to remove heavy metalfrom an aqueous solution at different pH values and metalconcentrations. Daifullah and Girgis [19] showed that howlow amounts of benzene can be absorbed by activatedcarbon. Organo-minerals that used as sorbents for benzeneby Koh and Dixon [20] was able to remove benzene in therate of 28 g$kg–1.Several studies used magnetic nano particles for

environmental pollutants removal without considering itseffect on the environment. Specifically, applying nanoparticles in water and wastewater treatment and releasingthem into the sinks. The idea of benzene removal usingmagnetic column might be a unique solution forcontaminated water and wastewater treatment withoutadding new pollutants to the environment. However, themajor challenge is selecting experimental conditions. Theeffective parameters are pH, nano materials dose, initialbenzene concentrations and contact time. The significantfactors affecting the removal of benzene by nano magnetic

Received September 17, 2012; accepted August 19, 2013

E-mail: [email protected]

Front. Environ. Sci. Eng.DOI 10.1007/s11783-013-0574-4

particle can be deduced, in a screening study, by applying afractional factorial design, a powerful tool, characterizedby a large number of potentially influential factors.The present study aimed to determine the removal

efficiency of benzene using nano magnetic particles; toestimate the influence of different variables and to evaluatethe simultaneous effect of the more significant variables.The originality of this paper is implementing continuouscondition in a magnetic column for preventing nanoparticle release in effluent. Also, this approach can reducethe space for water and wastewater treatment.

2 Materials and methods

2.1 Materials

A solution of 100 mg$L–1 of benzene was prepared bydissolving appropriate amounts of benzene (Merck, purity:99.7%) in deionized H2O. The mixture was solvedthoroughly by using an ultrasonic bath (Bandline SonorexDigitex DT156, Sonorex Digitec company, Germany) for60 min, and then, stirred continuously for 24 h at 25°C.After shaking, the solution was put in the ultrasonic bathagain for 30 min [21] and was used to prepare the initialsolution of benzene with 10–100 mg$L–1 concentrations.Standard series and samples were prepared using deionizedH2O as the desired concentrations.

2.2 Experimental conditions

Several experiments were conducted to evaluate theeffective parameters by changing one variable while theother parameters were held constant. All of the experi-ments were conducted in 110 mL glass flask. In eachexperiment, a varied amount of the adsorbents, 50–200mg, was added to 100 mL of benzene solution, by theinitial concentration (C0) of 10–100 mg$L–1. Also, pH waschanged from 2 to 11. These bathes were representatives ofthe low benzene level in polluted water by gasoline. Theglass flasks were sealed with 20 mm stopper. Theheadspace of each flask was minimized to exclude anycontaminant volatilization phenomena. After preparingeach batch, the flasks were placed on a shaker (OrbitalShaker Model KS260B, IKA company, Germany) andstirred at 240 r$min–1 in the room temperature for 2–20min. The solution samples were then settled for 2 min. Amagnetic field was used to separate the suspendedmagnetic NM. Continuous experiments were performedusing an up flow magnetic column with 5 cm diameter and20 cm length. The column was filled with a stainless steelwool and surrounded by two magnets with 0.15 Tesla fromits outside (Fig. 1). The column was operated at optimumcondition that earn in batch experiments with retentiontimes of 2, 8, 14, and 20 min.Before and after each experiment, the benzene concen-

tration was determined by using the gas chromatograph-flame ionization detection (GC-FID) and the gaschromatography–mass spectrometry (GC-MS) (model7890A, Agilent Company, United Stat). All of theexperiments were repeated three times and only the meanvalues were reported. Blank experiments, without theaddition of adsorbents, were also conducted to ensure thedecrease in the benzene concentration that actually hasbeen adsorbed on glass bottle wall or via volatilization.The pH of solution was measured at the beginning

(pHin) and at the end (pHfin) of each experiment. ThepHin was adjusted using 0.05 mol$L–1 HCl and0.05 mol$L–1 NaOH and determined by a pH meter(CyberscanpH1500, Thermo Fisher Scientific Inc, Nether-land). The amount of adsorbed benzene on adsorbent (qe,mg$g–1), distribution ratio (KD, L$g–1), and percentremovals (%R) were calculated as follows:

qe ¼ ðC0 –CtÞ �V

m, (1)

%R ¼ C0 –Ct

C0� 100, (2)

KD ¼ C0 –Ct

C0� V

m, (3)

where C0 and Ct (mg$L–1) are the benzene concentrationsat the start and end of each run, V (L) is the initial solutionvolume, and m (g) is the adsorbent weight.

2.3 Chemical analysis

Initial samples were quantified via GC-FID at injectiontemperature of 210°C, mode splitless 80 mL$min–1 at2 min, detector temperature of 250°C. The followingtemperature program was used: 36°C for 1 min and10°C$min–1 to 90°C, direct to 150°C with 25°C$min–1 rateand hold in 150°C for 6 min. The hydrogen gas was used asthe fuel (flow 30mL$min–1), air flow was 300 mL$min–1

Fig. 1 Up flow magnetic column used for continues experiments

2 Front. Environ. Sci. Eng.

and nitrogen was used as the makeup gas at a flow rate of30 mL$min–1. The column used was a CP-sil 5 Cb 25 m �320 μm � 1.2 μm with helium (purity 99.995%) as carriergas at flow rate of 1.11 mL$min–1.The GC-MS was used for determining of the benzene in

low concentrations and its results were lower than the GC-FID detection limit. The Agilent technologies systemconsists of 5975C Inert MSD with Triple Axis Detectorthat is equipped with a 7890A GC with a split/splitlessinjector. This system was used for the benzene determina-tion after treatment by Fe3O4. A fused silica column, HP-5ms (5% phenyl-95% dimethylpolysiloxane; 30 m �0.25 mm I.D, 0.25 μm), was employed with helium (purity99.995%) as carrier gas at a flow rate of 1 mL$min–1. Thecolumn temperature was programmed as follows: 40°C for10 min, increasing to 150°C at 10°C$min–1 and holding for2 min. The injector port was maintained at 250°C and 1 mLvolume of headspace was injected in splitless mode (2min). The effluent from the column was transferred via atransfer line held at 280°C and fed into a 70 eV electronimpact ionization source held at 280°C. The analysis wasperformed in the scan mode. The data were acquired andprocessed by the data analysis software.Static headspace analysis was performed using a CTC

PAL-Combi PAL headspace sampler. Experimental opti-mum parameters of the headspace sampler were based onwhat was reported in Table 1. The headspace gas wasinjected to the GC-MS injector from the automaticheadspace sampler after 25 min shaking at 70°C. Thevalue of headspace parameters that used in this study wereobtained by trial and error before using the GC-MS forbenzene determination. Also, standard series were appliedto calibrate the system. So, the benzene germ transmissionfrom water to headspace was based on standard curveobtained by standard series. Accordingly, the benzenetransmission steps from water to headspace were as sameas the standards, and therefore, the results of determinationwere reliable.

2.4 Adsorbents

During the experimental procedure, the nano magnetic

particles (NM) used as the adsorbent. The NM (Nanos-tructured & Amorphous Materials Inc., Untied State wascharacterized with the following specifications: Fe3O4, 20–30 nm, average particle size, 98+ % purity,≥40 m2$g–1

specific surface area, Stock #2650TR, CAS # 1317-61-9,Lot # 2650-031010.The X-Ray Diffraction (XRD) pattern was obtained for

the iron oxide particles to determine its crystalline phase(X-Ray Diffractometer, Bruker, D8ADVANCE, Germany(X-Ray Tube Anode: Cu, Wavelength: 1.5406 Å (Cu Kα),Filter: Ni)). Figure 2 shows XRD pattern for the magneticiron oxide (Fe3O4) particles. The particles are Fe3O4 andcrystalline in nature. The particle size and shape of ironoxide was determined by transmission electron micro-scopy (TEM Philips CM10) at 100 kV (Fig. 3). Theparticles had narrow distribution with diameter of 20–30 nm.

2.5 Recycling method

The reversibility of sorbents that used for benzene removalfrom aqueous solutions was evaluated via 2 successiveadsorption followed by 2 successive desorption processes.Recycling was also conducted at 105°C�2°C in an electricoven (Memmert D-91126, Schwabach FRG Company,Germany) for 24 h. Then, it was placed in a desiccator forcooling. All samples were performed at least in triplicate.

2.6 Analysis of data

To ascertain the individual effects of pH, NM doses, initialconcentrations of benzene, and contact time on removal ofbenzene, data analysis and also experiments numberreduction, design of experiments (DOE) software (DesignExpert 6 Stat-Ease, Inc., USA was used. The Taguchiorthogonal plan was applied by four factors at four levels(Table 2). The matrix involved 16 runs and each run wastriplicated. The corresponding factor values, in Table 2,were in compliance with the literature [11,18,20].An isotherm study was evaluated for the benzene

adsorption by the NM in the optimum conditionwith initial concentration of 0–100 mg$L–1 (interval10 mg$L–1), NM dose 2 g$L–1, contact time 14 min, and pH8. The water solubility (Sw) of benzene was estimated1790 mg$L–1 at pH 7 and an Isotherm Fitting Tool(ISOFIT) software was used to fit isotherm parameters toexperimental data. The ISOFIT is a software program thatfits isotherm parameters to experimental data via theminimization of a weighted sum of squared error (WSSE)objective function [22].The ISOFIT supports the number of isotherms, including

1) Brunauer-Emmett-Teller (BET), 2) Freundlich,3) Freundlich with Linear Partitioning (F-P), 4) General-ized Langmuir-Freundlich (GLF), 5) Langmuir, 6) Lang-muir with Linear Partitioning (L-P), 7) Linear, 8) Polanyi,9) Polanyi with Linear Partitioning (P-P), and 10) Toth.

Table 1 Experimental optimum parameters

parameter value

incubation time 25 min

incubation temperature 70°C

sample loop volume 250 μL

syringe/transfer line temperature 110°C

flash time 2 min with N2

loop fill time 0.03 min

injection time 1 min

sample volume 2mL in 10 mL vials

Mohammad Mehdi Amin et al. Benzene removal by nano magnetic particles 3

3 Results

3.1 Batch experiments performance

Table 3 shows the benzene removal percentage by the NM,

equilibrium amounts of the absorbed benzene on the NM(qe), and the distribution ratio (KD) under different initialbenzene concentrations, the adsorbent NM doses, contacttime and pH.Figure 4 shows the plots of effective factors on the

benzene removal process by the NM for determining theoptimum condition. The estimated effects of the factorsand their interactions can be seen in Table 4.

3.2 Continues experiments performance

The up-flow nano magnetic column was evaluated byusing the optimum condition obtained in batch experimentwith different contact time. Table 5 and Fig. 5 show thebenzene removal in the nano magnetic column. Thebenzene removal efficiency in batch and continuousexperiments were compared in Fig. 6.

3.3 Isotherm study

The ISOFIT evaluated the benzene adsorption by Fe3O4 inthe batch condition. Table 6 shows the qe for the optimumcondition of benzene removal by the NM in different initialbenzene concentrations. Table 7 summarizes some of thediagnostic statistics computed by ISOFIT and reported inthe output file. In Table 8, the Linssen measurement

Fig. 2 XRD pattern of Fe3O4

Fig. 3 TEM monograph of Fe3O4

Table 2 Controlling factors and their levels

factors level 1 level 2 level 3 level 4

benzene concentration/(mg$L–1) 10 30 70 100

NM dose/(mg$L–1) 500 1000 1500 2000

contact time/min 2 8 14 20

pH 2 5 8 14


indicated significant WSSE nonlinearity near the optimalparameter values. The statistical measures such as R2

N andDurbine Watson test (D) imply normally distributedweighted residuals with no serial autocorrelation. Figure7 contains plots of the fitted isotherms, organized intovisually indistinguishable groups, along with the observeddata points.

3.4 Nano magnetic particle recycling

Table 9 shows that the benzene removal percent by NM,was recycled in the first cycle (NMrec1) and was recycledin the second cycle (NMrec2) in optimum condition.Figure 8 compares raw NM with their recycling in cyclesof 1 and 2.

4 Discussion

Table 3 shows that more than 98% of benzene wasadsorbed by using Fe3O4 in run 10 and was agreed withother research [23]. Figure 4(a) indicates that the benzeneadsorption increased from 60.5% to 98.6% with rising theinitial benzene concentration from 10 to 100 mg$L–1. Qadriet al. obtained same results and showed the amount of dyeadsorbed increased from 3.6 mg$g–1 to 35 mg$g–1 as thedye concentration increased from 3.69 to 184 mg$L–1 [23].However, Wang et al. [18] showed that the adsorption ofmetals on Fe3O4 decreased sharply when the initial metalconcentration was higher than 35 mg$L–1. It was due to thedecrease in fraction of free ions in aqueous solution. Figure4(b) shows the most benzene removal happened in 2 g$L–1

Table 3 Design matrix and results of benzene removal by NM at different condition

runfactors response1: benzene

benzene concentration/(mgs$L–1) NM dose/(mg$L–1) time/min pH Ct/(mg$L–1) R/% qe/(mg$g–1) KD/(L$g–1)

1 30 500 8 8 4.4�0.1 85.3 51.2 11.6

2 30 2000 14 8 1.6�0.1 94.7 14.2 8.9

3 10 1500 14 8 0.6�0.1 94.3 6.3 10.9

4 70 500 14 11 4.1�0.3 94.1 131.8 32.1

5 10 1000 8 5 2.3�0.1 77.3 7.7 3.4

6 30 1000 2 11 8.2�0.3 72.8 21.8 2.7

7 100 1000 14 2 13.8�0.3 86.2 86.2 6.2

8 10 2000 20 11 0.4�0.1 95.7 4.8 11.1

9 30 1500 2 2 10.4�0.1 65.4 13.1 1.3

10 100 2000 20 8 1.4�0.3 98.6 49.3 35.4

11 100 500 20 5 8.3�0.1 91.7 183.4 22

12 100 1500 8 11 11.1�0.1 88.9 59.3 5.3

13 70 2000 8 2 9.8�0.2 86 30.1 3.1

14 70 1500 2 5 10.7�0.2 84.7 39.5 3.7

15 10 500 2 2 3.9�0.1 60.5 12.1 3.1

16 70 1000 20 8 3.2�0.3 95.4 66.8 21

Table 4 Effects of the factors and interactions obtained by fractional factorial design

factor/interaction degree of freedom sum of squares mean squares F value prob>F % contribution

A: benzene conc. /(mg$L–1) 3 1235 412 594 < 0.0001 21.4

B: NM dose /(mg$L–1) 3 1030 344 495 < 0.0001 17.9

C: contact time /min 3 2858 953 1374 < 0.0001 49.5

D: pH 3 498 166 239 < 0.0001 8.6

AB interaction 3 128 43 62 < 0.0001 2.2

lack of fit 30 21 0.7 – – 0.4

pure error 0 0.000 – – – 0.000

residuals 30 21 0.7 – – –


of NM dose and it was selected as the optimum conditionof NM dose. It shows that the higher initial concentrationof adsorbent enhances the sorption process. Figure 4(c)shows the highest rate of benzene was adsorbed to achievethe equilibrium in about 14 min. In benzene removal byNM, adsorbed benzene increased from 2 to 14 min andthen established. Also based on statistical analysis, therewere no significant difference between 14 and 20 mincontact time in benzene removal percent (values of“prob> |t|” greater than 0.1).The rapid adsorption of benzene by the NMwas because

of the external surface adsorption of magnetic nanoparti-cles in addition to the microporous adsorption process.Almost, all the adsorption sites of magnetic nanoparticlesexist in the exterior of the adsorbent, in comparison to theporous adsorbent; therefore, it is easy for the adsorbate toaccess these active sites and approach to equilibrium. Incontrary, the equilibrium time for the adsorption ofbenzene by some other adsorbents is much longer. Forinstance, adsorption of benzene onto granular activatedcarbon can reach equilibrium in more than 72 h [19], whilefor the benzene uptake onto organominerals is around 18 h

Fig. 4 Design expert plot of factors effect on benzene removal by NM in: (a) benzene concentration, (b) NM dose, (c) contact time,(d) pH

Table 5 Benzene removal by nano magnetic column

runfactors response1: benzene

benzene concentration/(mg$L–1) NM dose/(mg$L–1) time/min pH Ct/(mg$L–1) R/% qe/(mg$g–1) KD/(L$g–1)

1 100.3�1.9 2000 2 8 13.8�0.3 86.2 43.1 3.1

2 100�2.1 2000 8 8 9.2�1.6 90.8 45.4 4.9

3 100�2.4 2000 14 8 5.6�0.1 94.4 47.2 8.4

4 100�2 2000 20 8 5.5�0.3 94.5 47.2 8.5


[20] and for Fe3O4 used in this study was 14 min. Thebenzene removal by Fe3O4 was affected slightly by the pHof solutions. Figure 4(d) shows that the removal efficiencywas in minimum level, at pH = 2, and increased byincreasing the pH up to 8 and then reached plateau at pH =8 and higher. Again, there were no any significantdifferences between pH = 8 and 11 in benzene removalpercent (values of “prob> |t|” greater than 0.1). But whenFe3O4 was used for heavy metal removal, the amounts ofabsorbed metal increased sharply by increasing the pH inthe solutions to the threshold value (about 6.2) [18].It is likely that the adsorption of benzene on NM sorbent

was because of opposite charges between the sorbent andthe benzene. However, these results cannot be satisfacto-rily explained by the nature of the electrical charges onadsorbent surfaces since the zero points of charge for ironoxides are generally between 7 and 8. When pH is greaterthan 6, some iron oxides may precipitate and produce Fe

(OH)2 as colloidal suspensions with high specific surfacearea.The solution pH would affect both aqueous chemistry

and surface binding sites of the adsorbent. At low pH, theH ions would compete with benzene while the magneticnanoparticles had higher negative charge at higher pH.That enhanced the positively charged benzene capturingthrough electrostatic force of attraction.Thus, the optimum condition for benzene removal by

nano magnetic particle was at benzene concentration of100 mg$L–1, NM dose of 2000 mg$L–1, contact time of14 min, and pH of 8. The benzene removal by NM in theoptimum condition was 98.7%. Similar results wasreported for the best conditions of Cr(VI) biosorption onthe pinhao wastes where: pH = 2.0, C0 = 1200 mg$L–1,adsorbent dose = 1.5 g$L–1, contact time = 8 h. Themaximum Cr(VI) uptake in these conditions was125 mg$g–1 [24].In addition, there were significant interactions between

the initial benzene concentrations and NM dose factors. Asshown in Table 4, the statistical significance betweenparameters was tested by comparing the mean squareagainst the experimental error. In this case, five effectshave prob>F less than 0.05 and indicated that they aresignificantly different from zero at the 95% confidencelevel. The F value test showed that the contact time actedsignificantly in affecting the adsorption performance.Besides, the pH influences and the interaction betweenbenzene concentrations and NM doses seemed lesssignificant because of the F values of 239.3 and 61.6, forpH and interaction, respectively. As expected, the contacttime contributed to the major part in affecting theadsorption capability, i.e., 49.5%. It is one of the mostimportant parameters for determining adsorption capacityin liquid phase.Effective factors on the benzene removal followed this

order: contact time> benzene concentration>NM dose>pH> benzene concentration and NM dose interaction.So, the benzene removal by the NM could be expressed

Fig. 5 Benzene removal efficiency by nano magnetic column indifferent retention time

Fig. 6 Comparison of benzene removal efficiency by NM inbatch and continues experiments

Table 6 Adsorption capacity of benzene removal by NM in different

initial benzene concentration

initial benzene concentration/(mg$L–1)

adsorption capacity (qe)/(mg$g–1)

0 0.0

10 4.8

20 9.2

30 13.1

40 16.5

50 22.2

60 27.6

70 30.1

80 35.4

90 41.5

100 49.4


as the following equation:

Benzene removalð%Þ¼ 85:02 – ð6:36� benzene concentrationÞ

– ð5:94� NM doseÞ

þ ð1:98� contact timeÞ – ð0:04� pHÞ: (4)

Chen et al. [25] used the center composite design in

response surface methodology (RSM) to optimize thesynthesis of multi-wall carbon nanotubes (MWCNTs)–TiO2 composite for photocatalytic degradation of gaseousstyrene. The results showed that the photocatalyticdegradation efficiency of gaseous styrene reached 74.4%using the MWCNTs–TiO2 composite photocatalystsynthesized under the optimum parameters.Also, Sun et al. [26] applied the DOE to find an optimal

condition for the factors affecting on preparation, mor-phology and catalytic activity of nano-crystalline TiO2 thinfilms. The thin film prepared under the optimal condition

Table 7 Summary of selected diagnostics for benzene adsorbed by NM

isotherms AICc R2y R2

N M2 linearity assessment

BET 8.1 0.993 0.943 6.7�101 non-linear

Linear 10.7 0.990 0.828 4.6�10–9 linear

Langmuir 10.7 0.990 0.828 3�10–9 linear

F-P 10.7 0.990 0.828 7.6�10–9 linear

L-P 13.9 0.990 0.828 4�102 non-linear

Freundlich 13.9 0.990 0.834 2�101 non-linear

P-P 16.7 0.990 0.789 4.7�10–1 non-linear

GLF 17 0.990 0.986 4.9�101 non-linear

Toth 47.9 0.942 0872 2.4 non-linear

Polanyi 58.1 0.000 0.983 – uncertain

Notes: AICc, multi model ranking; R2y , correlation between measured and simulated observation; R2

N , correlation between residual and normality; M2, Linssen measure ofnon-linearity

Table 8 Selected ISOFIT post regression output (BET isotherm)

parameter or statistic ISOFIT result

overall quality of fit weighted sum of squared error 1.3�101

root of mean square error 1.2

Ry 0.997

parameter statistics bQ0 7.5�102

b 1.7�10–3

parameter std. error bQ0 1.8�101

b 1.7�10–1

test of assumptions Linssen (M2) M2 6.7�101

threshold 0.2

assessment non-linear

normality (R2N ) R2

N 0.943

critical value 0.861

assessment normal residuals

runs test number of runs 5

p-value 0.89

assessment no correlation

Durbine Watson test (D) D 1.3

p-value 0.699

assessment no correlation

Note: a) (CIlow, CIhigh), lower and upper 95% confidence bounds


had an average grain size of approximately 17.2 nm and anaverage roughness of 3.653 nm. The 1h photodegradationefficiency of methyl orange in an aqueous solution andtoluene in gaseous phase was obtained 98.9% and 100%,respectively.The DOE results of current research first analyzed by

using the direct observation analysis because the responsesversus the levels of different factors can be observeddirectly from a broken line plot. The mean value of thedegradation efficiencies for the corresponding factors ateach level was calculated according to the assignment ofthe experiment. Same as the Chen study, the results of thisstudy demonstrates that the experimental design methodsused in this work would have great significance indesigning and developing high performance efficiencyfor environmental protection and cost saving.The comparisons in qe and KD of this study with various

adsorbents such as carbon nano tubes (CNT), powderedactivated carbon (PAC) and granular activated carbon(GAC) reported in the literature are given in Table 10 andTable 11. Under analogous conditions, the present studyshowed better performance of benzene adsorption thanother adsorbents. This suggested that the NM is an efficientbenzene adsorbents. Moreover by decreasing the NMpreparation cost, the possibility of utilizing these noveltechniques may increase for the benzene removal inwater and wastewater treatment in the near future mayincrease.The benzene removal efficiency increased with increas-

ing retention time from 2 to 14 min and stopped increasingbetween 14 to 20 min. There was no significant differencebetween retention time 14 and 20 min in benzene removalefficiency (values of “Prob> |t|” greater than 0.1). Also,the results show that benzene removal efficiency in batchcondition was higher than the benzene removal incontinuous experiments because nano magnetic particlesstabilized on stainless steel wool by the magnetic field inthe column. That was mostly due to decreased levelabsorption area.Bystrzejewski et al. [28] used carbon-encapsulated

magnetic nanoparticles as mobile sorbents for removal ofheavy metal ions from aqueous solutions. The ion uptakesachieved 95% for cadmium and copper. The sorbents alsohave adsorption capacities between 1.23 mg$g–1 and 3.21mg$g–1.Table 7 shows that the corrected akaike information

criterion (AICc) values indicate that the linear isothermexpression provides the best fit of the sorption data.The BET model best fitted the experimental data, based

on its relatively lowest value of multi model ranking(AICc). The BET constant (b) was calculated to be lessthan unity for the majority of the adsorbate and adsorbentcombinations, indicating that the adsorption of the selectedcontaminants onto the NM samples was favorable. Non-linear regression techniques overcome many of thedeficiencies associated with trial-and-error and lineariza-tion approaches to isotherm fitting. However, the perfor-mance of nonlinear regression techniques can be impededby the presence of local minima or excessive parametercorrelation. In addition, the ISOFIT provided superior fitsfor the GLF and Polanyi isotherms based on theircorrelation coefficient R2

N that equal to 0.986 and 0.983,respectively. When fitting is more complicated and

Fig. 7 Plots of fitted isotherms and observed data: (a) Toth, P-P,GLF, Polanyi; (b) linear, Freundlich, Langmuir, F-P, L-P, BET

Table 9 Benzene removal by raw and recycled NM at optimum condition

adsorbentbenzene

C0 /(mg$L–1) Ct /(mg$L–1) removal percent /%

raw NM 100 1.4 98.7

NMrec1 100 2.2 97.8

NMrec2 100 2.6 97.4


depends on three and four parameter expressions, hybridmethod played an important role. The parameter statisticsshow relatively narrow confidence intervals and highcorrelation among two parameters for the BET exponentparameter.Table 8 contains the selected ISOFIT output for the BET

isotherm. The ISOFIT provided two “standard measures”for evaluating isotherm goodness of fit, namely the rootmean squared error (RMSE, Eq. (5)) and the correlationbetween measured and fitted observations (Ry, Eq. (6)).

RMSE ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

WSSE

ðm – pÞ

s

, (5)

Ry ¼Xm

i¼1ðwisi,obs – s

avgobsÞðwisi – s

avgÞXm


avgobsÞ2

Xm


avgÞ2 , (6)

where WSSE is weighted sum of squared error, m is thetotal number of experimental observations, p is the numberof isotherm parameters, wi is the weight given toobservation i, Si,obs is the i-th experimentally measuredsorbed concentration, Si is the i-th simulated sorbedconcentration computed via an isotherm expression, savgobs,and savg are the averages of the weighted measured andweighted isotherm simulated adsorbed concentrations,respectively.Repeated availability is an important factor for an

advanced adsorbent. Such adsorbent not only possesseshigher adsorption capability, but also should shows betterdesorption property, which will significantly reduce theoverall cost for the adsorbent.Although nano magnetic particles showed high benzene

sorption capacities form aqueous solution, their potentialuse was restricted in water treatment because of its cost.Thus, testing the reversibility of sorbents that used forbenzene removal would help to reduce their cost. For thispurpose as a part of the study, probability for used NMrecycling was investigated. It should be highlighted thatthe major advantage that the magnetic separation offeredwas the ability to recover the nanoparticles and reused theparticles for further benzene removal.Based on Fig. 8, the NM was reused for the benzene

removal through a large number of water and wastewatertreatment and regeneration cycles. But with increasing NMregeneration cycles, the benzene removal efficiency wasdecreased. There were statistics differences between rawNM, NMrec1, and NM rec2 in benzene removal percent(prob> t less than 0.05).The results could hint that no strong bonds were created

between the surface of NM and the benzene. The adsorbedbenzene by the NM could be easily desorbed bytemperature, and thereby NM can be employed repeatedlyin water and wastewater treatment.

Fig. 8 Design expert plot for raw and recycled NM in benzeneremoval at optimum condition

Table 10 Comparisons of qe for benzene adsorption via various adsorbents

adsorbents qe/(mg$g–1) condition reference

NM 183.4 pH: 5, T: 25, S/L: 0.5/1000, C0 = 100, Ct= 0.3 present study

CNT 18.1 pH: 7, T: 25, S/L: 0.06/100, C0 = 200 [11]

diatomite 0.2 pH: 8.54, T: 20, S/L: 33/100–5/100, C0 = 50, Ct= 240 [7]

GAC 183.3 pH: 7, T: 30, S/L: 0.15/100, C0 = 35–442 [27]

organominerals 28.8 S/L: 0.1/25, C0= 100, Ct= 18 [20]

PAC 4.76 pH: 6.5, T: 25, S/L: 0.5/100, C0 = 10, Ct= 72 [19]

Note: T = temperature /°C; S/L = solid/liquid /(g$mL–1); C0 = initial benzene concentration /(mg$L–1); Ct= contact time /h

Table 11 Comparisons of KD via various adsorbents

adsorbents KD /(L$g–1) condition reference

NM 38.4 pH: 8, T: 25, S/L: 0.2/100, C0 = 100, Ct= 14 present study

peach stones (PS) 0.428 T: 25, S/L: 0.1/100, C0 = 10 [19]

Note: T = temperature/°C; S/L = solid/liquid /(g$mL–1); C0 = initial benzene concentration /(mg$L–1); Ct= contact time /min


Shen et al. [29] applied 0.1 mol$L–1 NaOH to regenerateFe3O4 that was used for metal removal. They find that mostof the adsorbed ions were desorbed in first cycle.This is the key factor for whether a novel but expensive

sorbent can be accepted by the field or not. It is expectedthat the unit cost of NM can be further reduced in the futureby recycling heat processes. So, magnetic nanoparticlescan be attractive as a cost-effective sorbent in removingbenzene from the water and wastewater. The sorbentweight loss was neglected in the recycling processes.

5 Conclusions

The optimum condition was investigated to identify thehighest capability of magnetic nano particles for benzeneadsorption. Four control factors including benzene con-centration, nano particle dose, contact time and pH, at fourdifferent levels, were applied. It was concluded that theNM had a high capacity for the benzene adsorption fromthe aqueous solution in batch and continuous condition.The BET isotherm described the equilibrium adsorptiondata better than other isotherms alternative. After therecycling of nanomaterials, the NM was regenerated andreused. However, heating reduced adsorption capacity ofrecycled NM than raw NM. The application of magneticnanoparticles for benzene removal and recovery of themprovided a simple, but unique solution for benzeneremoval from water and wastewater. Benzene adsorptionby new types of commercially available nano magneticparticle (Fe3O4) showed that the adsorbents were reusable,cost-effective, and simple to use. It is expected that theFe3O4 nanoparticles with fine grain size (20–30 nm) willbe used as one of effective, convenient and low-costingmethods for removal and recovery of benzene from waterand wastewater.

Acknowledgements This article was the result of PhD dissertationapproved by the Isfahan University of Medical Sciences (IUMS). Theauthors wish to acknowledge to Vice Chancellor of Research at IUMS for thefinancial support Research Project # 389065.

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Benzene removal by nano magnetic particles under continuous condition from aqueous solutions