Chemical Engineering Journal 237 (2014) 430–442

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Chemical Engineering Journal

journal homepage: www.elsevier .com/locate /ce j

Arsenate adsorption on waste eggshell modified by goethite, a-MnO2

and goethite/a-MnO2

1385-8947/$ - see front matter � 2013 Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.cej.2013.10.031

⇑ Corresponding author. Tel.: +381 11 3303750.E-mail address: jasmina.markovski@tmf.bg.ac.rs (J.S. Markovski).

Jasmina S. Markovski a,⇑, Dana D. Markovic b, Veljko R. Ðokic b, Miodrag Mitric a, Mirjana Ð. Ristic b,Antonije E. Onjia a, Aleksandar D. Marinkovic b

a Vinca Institute of Nuclear Sciences, University of Belgrade, PO Box 522, 11001 Belgrade, Serbiab Faculty of Technology and Metallurgy, University of Belgrade, Karnegijeva 4, 11120 Belgrade, Serbia

h i g h l i g h t s

� Eggshell is used as a low-cost, abundant, porous material suitable for modification.� Pretreated eggshell is modified by goethite, a-MnO2 and goethite/a-MnO2.� High sorption ability is obtained with novel sorbent materials.� Visual MINTEQ software is used for equilibrium speciation modeling.

a r t i c l e i n f o

Article history:Received 20 August 2013Received in revised form 8 October 2013Accepted 10 October 2013Available online 23 October 2013

Keywords:ArsenateEggshellGoethitea-MnO2

AdsorptionMINTEQ

a b s t r a c t

An efficient adsorbents for arsenate removal was developed by modification of calcined eggshell withgoethite (calcined eggshell/goethite; sorbent 1), a-MnO2 (calcined eggshell/a-MnO2; sorbent 2) andhybride system goethite/a-MnO2 (calcined eggshell/goethite/a-MnO2; sorbent 3). Methods and processesfor preparation of novel adsorbents were defined and obtained materials were characterized by BET, XRD,SEM and FTIR analysis. The influence of functionalization methods, solution pH, contact time, tempera-ture, interfering ions and initial arsenate concentration on efficiencies of arsenate adsorption were stud-ied in a batch system. Based on the orthogonal distance regression (ODR) fitting, using R2, MARE andRMSRE statistical criteria, Langmuir and Sips equations were chosen for description of adsorption equilib-riums on sorbents 1 and 3, respectively. The maximum adsorption capacities of 33.38 mg g�1,13.54 mg g�1 and 47.04 mg g�1 for sorbents 1–3, respectively, were obtained. Time-dependent studyrevealed that pseudo-second-order equation fitted well the kinetic data, while the Weber Morison modelpredicted intra-particle diffusion as main adsorption rate controlling step. Thermodynamic parametersindicated exothermic, feasible and spontaneous nature of adsorption process on sorbents 1 and 3. Resultsof Visual MINTEQ equilibrium speciation modeling program was used for studying pH, ionic strength andinterfering ions influences on arsenate adsorption.

� 2013 Elsevier B.V. All rights reserved.

1. Introduction

The rapid development through urbanization, industrializationand intensified technology changing has resulted in a generationof large quantities of environment pollutants. Heavy metals are re-ported as priority pollutants considered to be one of the most haz-ardous, so widespread contamination of surface and groundwaterby arsenic as a toxic human metalloid present global public healthproblem of primary concern. Arsenic is 20th abundant element inearth’s crust and can be naturally found in water due to geologicprocesses, and, in spite of numerous prohibitions which restrictedarsenic production, as a result of pesticides, herbicides and fertiliz-

ers uses, smelting and mining operations, fossil-fuel combustion,waste disposal, etc. [1,2]. Arsenic occurs in natural waters in inor-ganic and organic forms. Inorganic species predominate anddepending on the oxidation–reduction condition and water pH,different form of arsenite, As(III), exists mainly in groundwaterand arsenate, As(V), in surface water [3]. On the basis of arsenictoxicity and cancer-related effect to human body, World HealthOrganization recommended the maximum concentration level(MCL) (maximum permitted concentration – MPC) for arsenic indrinking water should not exceed 10 lg dm�3 [4].

In order to accomplish arsenic below recommended MCL value,numerous technologies were developed for natural water treat-ment: oxidation/precipitation, coagulation/coprecipitation, nano-filtration, reverse osmosis, electrodialysis, adsorption, ionexchange, foam flotation, solvent extraction and bioremediation

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 431

[5]. However, the applications of these methods has been limiteddue to numerous disadvantages such as high operational and cap-ital cost, technically complex, problems of disposal, generation ofsludge and high energy consumption [6,7]. Therefore, scientificattention is focused on developing economic, biodegradable andnaturally occurring material which can be used for removal of pol-lutants applying economically favorable and efficient processes.Literature survey demonstrated a large number of investigationswhich reported heavy metal removal by using low-cost, naturallyabundant and easily available adsorbents: agricultural waste (nutshell, rice and almond husk, saw dust of various plants, bananaand orange peel, tea and coffee waste) [8–11], industrial by-prod-ucts: fly ash, green sand, red mud, blust-furnance slag, waste iron[10,11], and natural materials zeolite and clay [10,11].

Herein, we used eggshell, low-cost, abundant and porous mate-rial which is suitable for further modifications, and performingoptimization of adsorbent properties it was possible to improvephysical integrity and adsorption potential for arsenate removal.Negligible amount of eggshell waste is used as fertilizer and feedfor human and animal supplement, while huge quantity is dis-posed to landfills. It has been estimated that eggshell possess be-tween 7000 and 17000 pores [12], contains mainly of calciumcarbonate (calcite) (85–95%), magnesium carbonate (1.4%), phos-phate (0.76%), organic matter (4%) and sodium, potassium, zinc,manganese, iron and copper in trace [13]. Eggshell is consideredto be low-cost waste material of animal origin, previously usedas sorbent in the process of Cu(II), Pb (II), Cd(II), Cr(III), Cr(VI)[13–15], reactive red and malachite green dye [16,17], carbon(IV)oxide and phosphate removal [18,19]. Based on our knowledge, ar-senic removal has been studied by the use of low cost sorbent (cel-lulose, chitosan, coconut coir pith, human hair, orange waste, redmud, etc.) [20], while Zhang et al. [21] and Oke et al. [22] in theirworks applied eggshell membrane and dry eggshell in unmodifiedform for arsenate adsorption.

With the aim of achieving high adsorption capacity and goodphysical integrity of modified eggshells, a few steps, analogous torecommended by other authors, were applied in the optimizationprocess of the new adsorbents synthesis: (a) eggshell was calcined[18], (b) pretreated eggshells were modified by metal oxide nano-particles (iron oxyhydroxide and MnO2) [23], and (c) adsorptionexperiments were performed in a batch system assisted by ultra-sonic power [24]. Influences of pH, contact time, temperature andinitial arsenate concentration were studied in order to evaluateadsorption performance of modified eggshell for arsenate removal.Effect of pH and interfering ions are evaluated experimentally andby MINTEQ modeling [25]. Adsorption performances of modifiedeggshells were compared with those of other adsorbents.

2. Materials and methods

2.1. Chemicals and reagents

All chemicals and reagents used for eggshell modification,adsorption experiments and study of interfering ions influenceare listed in Supplementary material.

2.2. Adsorbents preparation

Overall process of adsorbents preparation was consisted fromthree steps:

� Raw waste poultry eggshells were collected from a fast food res-taurant in Belgrade, Serbia. Eggshells were washed severaltimes in tap water, boiled in deionized water for one hour andfinally dried in oven at 100 �C for 3 h. The membranes were

separated from dried eggshells by hand. The powdered materialwas obtained by grinding in ball mill and was screened througha set of sieves to obtain particle size of roughly 200 lm.� According to paper of Witoon [18], washed and powdered egg-

shells was prepared for the third step by calcination at 900 �Cfor one hour under N2 atmosphere in order to obtain the highestporosity of the calcined eggshells.� Modifications of calcined eggshells by oxide metal particles

were achieved analogously to literature methods [26–28], anddetails of synthesis are given in Supplementary material.

Also, for comparative purpose, analogously to preparation ofsorbents 1–3, were obtained sorbents 10–30 based on dried eggshellas support.

2.3. Characterization methods

The information about characterization methods is provided inSupplementary material.

2.4. Adsorption study

Details on Adsorption experiments (Section 2.4.1); Influence ofpH on arsenate adsorption (Section 2.4.2); Equilibrium and ther-modynamic studies (Section 2.4.3); Kinetic studies (Section 2.4.4)and Desorption experiments (Section 2.4.5) are presented in Sup-plementary material.

2.4.6. Error functions and statistical analysisExperimental data was used for calculation of equilibrium, ki-

netic and thermodynamic parameters. The OriginPro 8.5� com-puter program was used for data analysis.

In order to evaluate adsorbent capabilities and compute variousadsorption parameters, the following isotherm models were com-pared: Langmuir, Freundlich, Redlich–Peterson, Sips and Jovanovic.Unknown parameters of the isotherm models were determinedusing the method of orthogonal distance regression (ODR) alsoknown as the errors in variables problem. The use of ODR modelingprocedure is statistically correct in the case when values of bothaxes are affected by measurement error, which is manifested whenfitting the experimental data by adsorption isotherm models [29].The value on the x axis is equilibrium concentration, Cf, which isdetermined by instrumental analysis and thus inevitably affectedby the measurement error. Equilibrium adsorbent loading, whichis on the y axis, is calculated from the adsorbate equilibrium con-centration, and as a result an error in this concentration appears inboth coordinates. Additionally, q is prone to sources of error in themeasurement of Cin, V and m.

Fitting by means of ODR procedure is actually minimization ofthe shortest distances between the curve and the experimentaldata points (in the classical method of nonlinear fitting the verticaldistances are minimized). ODR is the most accurate and precisemethod to determine the isotherm parameters, when tested on alarge number of generated data with assumptions of various noiseprecision models to describe the measurement error in solute con-centration determination. ODR as a procedure for realization of aminimization of the error function could be presented by followingequation:

ODR ¼Xn

i¼1

qi � qi

qi

� �2

þ Cfi � Cfi

Cfi

!224

35; ð1Þ

where n, qi, qi, Cfi and Cfi denote the number of data points, theexperimental and the estimated values of adsorption capacity andequilibrium adsorbate concentration, respectively, is suitable for

432 J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442

fitting adsorption isotherms when the measurements of initial andfinal adsorbate concentrations are affected by heteroscedastic errorand no replicates were done. In Eq. (1) weighting is performed by1/qi and 1/Cfi for the y and x axes, respectively, and thus at the sametime heteroscedasticity is taken into account and the scaling is per-formed so that dimensionless values, independent of units, can beadded together to form the sum of error function.

Necessary calculations were performed using Matlab R2007bsoftware. Build in Matlab function fminsearch, based on theNelder–Mead simplex direct search algorithm [30], was used.Another build in function, dsearchn, was incorporated in the scriptas tool to find the set of values ðCfi; qiÞ for each points of iteration inthe course of minimization procedure.

The Bartlett’s test [31] was performed on ICP–MS precisionstudy data, and it was shown that the variances are not equal atdifferent concentrations, so it was concluded that the mentioned,particular form of ODR, should be applied in the adsorption studypresented in the paper.

2.4.7. Modeling of adsorption processesSurface complexion models (SCMs), chemical models based on

mechanistic and atomic scale approach, are developed to predictthe adsorption of heavy metal ions by different form of oxideadsorbents [32]. MINTEQ is a SCMs computer program which is ap-plied for modeling of the adsorption processes in this work. MIN-TEQ includes two models: mathematical structure from MINEQL[33] and thermodynamic data base, temperature correction ofequilibrium constants using either the Van’t Hoff relationshipand ionic strength correction with the extended Debye–Hückelequation or the Davies equation from WATEQ3 [25]. Protonation/deprotonation constants (logK) and arsenate intrinsic surface com-plexation constants and model parameters are given in Table S1.

3. Results and discusion

3.1. Optimization of adsorbent preparation

In order to obtain adsorbents of optimal mechanical compact-ness (integrity/stability), and high efficiency for arsenate removalwith a uniform distribution and optimal quantity of nanosized de-posit: goethite, a-MnO2 and goethite/a-MnO2 coating on calcinedeggshell support, it was an unavoidable task to conduct optimiza-tion of synthesis procedure for all sorbents (details are given in thepart 2.2 Adsorbent preparation). Optimization goals, maxima ofadsorption capacities and minimum of loaded oxides, were ob-tained for sorbent 1 (1.0% of FeSO4⁄7H2O solution), sorbent 2(0.44 g of KMnO4) and for sorbent 3 (65 cm3 of 0.10 mol dm�3

FeSO4⁄7H2O solution and 1.0 g of KMnO4).

3.2. Adsorbents characterization

In the first instance, after synthesis, it was necessary to identifyelemental composition as well as textural parameters: specific

Table 1Elemental content of dry eggshell, calcined eggshell, and sorbents 1–3.

Material Elemental content (%)

Ca2+ Mg2+ Fe3+ Mn2+

Dry eggshell 32.2 1.31 1.53 0.537Calcined eggshell 31.7 1.22 1.35 0.314Sorbent 1 30.8 0.903 8.90 0.425Sorbent 2 20.4 1.11 1.48 14.4Sorbent 3 17.5 0.810 13.1 9.23

a Oxygen in metal oxide (mainly CaO, MgO, FexOy, etc.), phosphorus compounds etc.

surface area, pore volume and mean pore diameter of dry eggshell,calcined eggshell and sorbents 1–3. ICP–MS and BET analysis wereperformed and results are presented in Tables 1 and 2,respectively.

The parameters of adsorbents syntheses (given in part 3.1. Opti-mization of adsorbent preparation) were the factors which governadsorption performance and the morphological properties of ob-tained adsorbents. Significantly higher specific surface area andmesopore volume of calcined eggshell vs dried eggshell was resultof the thermal treatment. Witoon in his study [18] revealed thatthe liberation of CO2 during calcination creates small pores, dueto thermal decomposition of calcite, while formation of the largerpores was a result of aggregation, sintering or merging processesbetween nanoscale calcite grains [18]. In such a way obtained cal-cined eggshells was potentially better starting material of higherpurity and porosity for further modifications. The fact that texturalparameters of calcined eggshell was significantly lower than thoseof three synthesized sorbents is an evidence that precipitation ofgoethite, a-MnO2 and goethite/a-MnO2 create higly porous nano-scaled film which also cover surfaces of inner pores contributingto the increased values of textural parameters (Table 2). Similartrend, but of lower values of the textural parameters, were foundfor sorbents 10–30 (Table S2).

In many studies were shown relationship between texturalparameters and adsorption capacity [23]. Results of three differentmodifications of calcined eggshells, applied in this work, demon-strate that highest surface area (250 m2 g�1), mesopore volume(0.710 cm3 g�1) and mesopore diameter (10.2 nm) of sorbent 3and the highest adsorption capacity (Table 3). Such result and low-er values of isoelectric point, determined after vs before arsenateadsorption, were an indication that larger numbers of surface ac-tive sites is available for arsenate adsorption, and that specificadsorption, rather than a simple electrostatic interactions, is amechanism of main contribution to overall adsorption mechanism[34].

3.3. XRD analysis

Phases and structure characterization of dried eggshell, calcinedeggshell and sorbents 1–3 were carried out using the X-ray diffrac-tion (XRD) analysis, and obtained XRD patterns are shown in Fig. 1.

X-ray diffraction patterns of eggshell show the typical crystal-line phases of pure calcite (ICDD PDF2 No. 85-1108). When the egg-shell was calcined 1 h at 900 �C, peaks at 2h values of 32.3�, 37.4�,53.9�, 64.2� and 67.4� indicated CaO as pure phase (ICDD PDF2No. 86-0402). In a spectrum of calcined eggshell/goethite, hybridnature of sorbent 1 is presented by new peaks at the angle 2h of17.8�, 21.2�, 33.2�, 34.7� and 36.6� specific for goethite (ICDDPDF2 No. 81-0464), and also peaks which correspond to calcite, ob-tained by reaction of CaO with CO2 during precipitation of goethite.Diffraction patterns of sorbent 2 indicated mainly presence ofamorphous form of precipitated MnO2, but, despite on that, XRDconfirmed that deposit introduced on calcined eggshell is a-MnO2

K+CO2�

3 SO2�4

R Othera

0.0813 52.8 – 88.5 11.50.0635 – – 34.6 65.40.0964 45.5 – 86.6 13.42.98 – 57.3 97.7 2.303.99 – 47.8 92.4 7.60

Table 2Textural properties and pHPZC of dry eggshell, calcined eggshell, and sorbents 1–3.

Material Specificsurfacearea (m2 g�1)

Mesoporevolume(cm3 g�1)

Mesoporediameter(nm)

pHPZCa pHPZC

b

Dry eggshell 0.801c 0.00324c 0.826 4.8 3.7Calcined eggshell 10.5c 0.0135c 21.6 – –d

Sorbent 1 183 0.0933 16.3 9.5 7.1Sorbent 2 122 0.0621 8.09 5.3 4.2Sorbent 3 250 0.710 10.2 8.5 6.7

a Before adsorption.b After adsorption.c Similar results to textural properties obtained by Witoon [18].d Measurement was inaccurate due to significant material dissolution.

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 433

(ICDD PDF2 No. 44-0141). On the same diffraction pattern (d) canbe noticed peaks which confirm presence of CaSO4 (ICDD PDF2No. 89-1458), a phase probably obtained by chemical transforma-tion of CaCO3 in presence of MnSO4⁄H2O during modification. InXRD pattern of calcined eggshell/goethite/a-MnO2 (hybride sor-bent 3), presence of goethite (ICDD PDF2 No. 81-0464) and a-MnO2 (ICDD PDF2 No. 44-0141) are evident. Beside of these mainpeaks, there can be observed small peaks corresponding toCa(SO4)(H2O)0.5 (ICDD PDF2 No. 83-0439) and FeSO4(H2O)7 (ICDDPDF2 No. 76-0657) phases. Appearance of the peaks, which couldbe attributed to Ca(SO4)(H2O)0.5, is a result of analogous transfor-mation found for sorbent 2. Also, small amount of unreactedFeSO4(H2O)7, incorporated in the bulk of hybride material, was

Table 3Adsorption isotherm parameters for arsenate removal on sorbentsa 1 and 3.

Isotherm model Sorbent 1

25 �C 35 �C 45

Langmuir Equation S2Qo (mg g�1) 33.38 ± 2.81 29.49 ± 2.24 24b (L mg�1) 1.16 ± 0.342 1.32 ± 0.381 1.5b (L mol�1) 86907 98894 11R2 0.995 0.995 0.9MARE 0.0832 0.0681 0.0RMSRE 0.156 0.120 0.1

Freundlich Equation S3KF (mg g�1) (dm3 mg�1)1/n 14.98 ± 2.49 13.42 ± 2.51 11n 1.96 ± 0.812 1.93 ± 0.932 1.9R2 0.941 0.915 0.9MARE 0.0852 0.107 0.1RMSRE 0.103 0.127 0.1

Redlich–Peterson Equation S4aR (mg�1) 1.16 ± 0.341 1.32 ± 0.383 2.0g 1.0c 1.0c 0.9KR (dm3 g�1) 33.38 ± 2.81 29.49 ± 2.24 44R2 0.995 0.995 0.9MARE 0.174 0.150 0.1RMSRE 0.327 0.286 0.2

Sips Equation S5aS (dm3 mg�1) 0.265 ± 0.163 0.423 ± 0.285 0.6bS 0.581 ± 0.252 0.632 ± 0.541 0.6KS (dm3 g�1) 79.95 ± 18.6 51.07 ± 22.9 35R2 0.978 0.979 0.9MARE 0.0721 0.0711 0.0RMSRE 0.0790 0.0802 0.0

Jovanovic Equation S6qm (mg g-1) 23.78 ± 7.81 22.14 ± 7.75 19KJ (dm3 g�1) 2.59 ± 1.05 2.54 ± 1.02 2.9R2 0.884 0.888 0.8MARE 0.396 0.382 0.3RMSRE 0.577 0.570 0.5

a Analogously for sorbent 2 maximum capacity of 13.54 mg g�1 from Langmuir was ob Redlich–Peterson model does not converge for Sorbent 3 at 25 �C.c Fixed at bound (there is no confidence interval).

detected. Additionally, semi-quantitative XRD analysis showed8.1% of goethite content in sorbent 1. Due to predominant amor-phous form of goethite and a-MnO2, quantitative analysis wasnot possible to be applied for sorbents 2 and 3.

3.4. Morphological characterization

A highly porous calcined eggshell was used as a support formodification with goethite (calcined eggshells/goethite; sorbent1), a-MnO2 (calcined eggshells/a-MnO2; sorbent 2) and goethite/a-MnO2 (calcined eggshells/goethite/a-MnO2; sorbent 3). Themorphologies of milled calcined eggshell and sorbents obtainedby subsequent modifications were examined by FEG-SEM tech-nique, and representative images are shown in Fig. 2.

It can be observed (Fig. 2a and b) that the particles of milled(grinded) calcined eggshell consist of de-agglomerated and agglom-erated mostly spherical particles with diameter of 191.2 ± 49.71 nm(mean values of 100 determination). Their surface is generallysmooth and without sharp edges. Obtained results relating to struc-turing of calcite during thermal treatment indicate important differ-ences with respect to one obtained by Witoon [18]. According toWitoon, calcination led to transformation of the structure of driedeggshell from the irregular crystal structure to interconnected skel-eton structure, and the size of the obtained skeletons was found tobe approximately 1–3 lm with the voids between these skeletonsof 500 nm. The introduction of goethite (Fig. 2c and d) leads toagglomeration, i.e., incorporation of initial spherical particles of

Sorbent 3

�C 25 �C 35 �C 45 �C

.56 ± 1.04 47.04 ± 3.51 40.34 ± 7.54 33.68 ± 3.711 ± 0.303 1.58 ± 0.405 1.53 ± 1.06 1.46 ± 0.6213129 118374 114627 10938398 0.996 0.978 0.991554 0.134 0.171 0.13730 0.294 0.297 0.271

.51 ± 1.81 23.91 ± 0.67 19.81 ± 2.3 15.80 ± 2.439 ± 0.821 1.80 ± 0.465 1.81 ± 0.582 1.85 ± 0.75323 0.906 0.948 0.92807 0.160 0.138 0.13533 0.184 0.186 0.166

5 ± 2.03 –b 96.2 ± 56.3 73.0 ± 40.43 ± 0.10 – 0.46 ± 0.52 0.48 ± 0.66.65 ± 15.1 – 1938 ± 293 1181 ± 20898 – 0.954 0.93707 – 0.141 0.13835 – 0.187 0.167

11 ± 0.412 2.09 ± 0.515 0.381 ± 0.285 1.01 ± 0.70065 ± 0.0921 1.18 ± 0.180 0.642 ± 0.420 0.811 ± 0.343.72 ± 4.12 43.52 ± 3.62 78.44 ± 72.9 38.49 ± 13.894 0.998 0.985 0.993463 0.172 0.126 0.129580 0.350 0.185 0.198

.07 ± 7.75 35.93 ± 15.4 28.64 ± 12.4 25.20 ± 11.51 ± 0.961 2.11 ± 1.13 3.24 ± 1.23 2.52 ± 1.1424 0.831 0.780 0.84399 0.456 0.479 0.41885 0.611 0.629 0.599

btained.

Fig. 1. XRD patterns of dry eggshell (a), calcined eggshell (b), sorbent 1 (c), sorbent2 (d) and sorbent 3 (e).

434 J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442

calcite in goethite, leading to layered agglomerates with particlesize of 518.2 ± 319.4 nm (368.7 ± 225.6). a-MnO2 completely coversthe initial spherical particles of calcite with sharp, needle-like struc-tures of length 276.1 ± 19.92 nm and width of 40.41 ± 3.702 nm(Fig. 2e and f). Finally, modification of calcined calcite with hybridsystem goethite/a-MnO2 leads to the formation of highly porous,cauliflower-like particles (126.3 ± 68.10), which consist of verysmall needle-like nanosized crystallites (Fig. 2g and h). It could besupposed that not only precipitation of goethite/a-MnO2 but alsosome reaction of supporting material, calcined calcite and precipita-tion reagents, take place providing such material morphology.

3.5. FTIR analysis

FTIR spectra of the dried and calcined eggshell, and sorbents1–3 were recorded before and after arsenate adsorption in orderto obtain qualitative estimations of the differences in the corre-sponding spectra. Analysis of the FTIR spectra before arsenateadsorption provided information about the presence of functionalgroups at adsorbent surface. Evaluation of the differences in thepeak intensity, peak shifting and peak appearance/disappearance

Fig. 2. FEG-SEM images of calcined eggshell (a,b), sorben

was an indication of the types of interaction between surface func-tional groups and adsorbed arsenate species. Formation of surfacecomplexes or any kind of electrostatic interactions was reflected asbond strength changes, i.e. vibration frequencies, recorded aswavelength value changes. Band shifts to lower or higher frequen-cies indicates bond weakening or strengthening, respectively. FTIRspectra of dried (a) and calcined (b) eggshells and adsorbents 1–3,before (a–e) and after (f–h) reaction with arsenate solution(4.31 mg dm�3), are given in Fig. 3.

Spectra of non-treated eggshell (Fig. 3a) show three main FTIRpeaks at 712 cm�1 (m4 in plane band), 875 cm�1 (m2 out of planeband) and 1420 cm�1 (m3 anti-symmetric stretching) of calcite, inaccordance to literature data [35]. Band observed at 1449 cm�1

in spectrum (b), attributed to Ca–O stretching mode of calciumoxide. In spectrum (c) of sorbent 1 characteristic peaks are ob-served at 1127, 1023 and 978 cm�1 due to the different vibrationmodes of hydroxyl groups (Fe–OH) present at goethite surface[34,36]. For sorbent 2 the peak at 514 cm�1 is assigned to theMn–O and Mn–O–Mn broad band vibrations at the low-frequencyregion [37]. The spectrum of sorbent 3 shows complex band struc-ture of peaks as a result of the integrity of binary system goethite/a-MnO2 causes changes of vibration modes of the constituents.

Differences between bands structure in spectra of sorbents 1–3,before and after adsorption, could be noticed from Fig. 3. Broadband at �3400 cm�1, ascribed to OH stretching vibration, asym-metric and symmetric, is not affected by adsorbed arsenate oxya-nions. A gradual weakening of the Fe–OH bands (peaks at 1127,1023 and 978 cm�1) resulted in disappearance in spectrum of sor-bent 1 for Cin > 4.31 mg dm�3. New band, corresponding to As–Ostretching vibration of coordinated arsenic species, appeared at796 cm�1, corresponding to the frequency of the As–O–Fe bandof complexed arsenate [34,36]. FTIR spectra of sorbent 2, beforeand after adsorption, is not useful for explanation of bond forma-tion, but irrespectively to that disappearance of the most intensivebands at 514 cm�1 in calcite/a-MnO2 spectra, and its weakening isa indication that Mn–O bond contribute to arsenate complexation.Similar observation was found for sorbent 3, and together withappearance of the peak at 849 cm�1, spectrum (h), indicate thatadsorption of arsenate, except of formation of surface complexesas for sorbent 2, uncomplexed/unprotonated As–O–Fe surfacestructure indicate existence of physically precipitated solid phase[34,36].

t 1 (c and d), sorbent 2 (e and f) and sorbent 3 (g,h).

Fig. 3. FTIR spectra of dry eggshell (a), calcined eggshell (b), sorbent 1 (c and f), sorbent 2 (d and g), sorbent 3 (e and h) before and after arsenate adsorption, respectively.

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 435

3.6. Influence of pH on arsenate adsorption

In accordance with an important role of water acidity/basicityon speciation of arsenate and its removal efficiency, the experi-mental study and theoretical modeling calculations on arsenate re-moval in presence of sorbent 1, as a function of pH, wereperformed and presented in Fig. 4. Herein, modeling of pH influ-ence of arsenic adsorption on sorbents 2 and 3 were not performeddue to lack of input parameters from quantitative XRD data. Forcomparative purpose and evaluation of the most convenient tech-niques applicable for arsenate removal in the presence of sorbents1 and 3, two methods were applied: classical stirring and ultra-sound treatment, and both produced different results, i.e. adsorp-tion capacity is lower for 12% in the case of former. Ultrasoundtreatment (sonication) is a useful method very often used forintensification of different processes. Ultrasonic waves producemicroscopic bubbles in the liquid which collapse creating shockwaves, which are highly effective in increasing the material wet-ting and help in efficient conducting mass transfer controlled pro-cesses. Because of that next experiments were conducted underultrasound treatment.

It is obvious that arsenate adsorption on sorbent 1 shows amaximum of arsenate removal in a pH range 4–7, and after steeplydecreases reaching minimum adsorption capacity at pH > 12. Sim-ilar trend was found for sorbents 2 and 3 (Fig. S1). Accordingly, pH5 is chosen as optimal value to be used in following examinations.

Fig. 4. Effect of pH on As(V) adsorption on sorbent 1 obtained by the use of differentmodels (CAs(V) = 0.100 mg dm�3, m/V = 100 mg dm�3).

Triprotic arsenic acid (H3AsO4) is present in molecular form atpH < 2, and in a range of highest adsorption, As(V) species are in io-nic forms (H2AsO�4 or HAsO2�

4 ), and, as weak acid, shows usuallythe most effective adsorption at pH near pKa [28].

At a pH value lower than pHPZC (Table 2), the functional groupsat metal oxide surface are protonated and positively chargedadsorbent surface are more susceptible for arsenate ions attrac-tions. Ionization state of adsorbent surface contribute enhance-ment of the electrostatic attraction with negatively chargedarsenate ions (H2AsO�4 ;HAsO2�

4 ). At pHin < pHPZC high removalcapabilities of all sorbents is of electrostatic nature and ligand ex-change phenomena, i.e. formation of inner-sphere surface com-plexes [38]. When pHin > pHPZC, increases of both ionization ofthe adsorbent surface group and concentration of HAsO2�

4 , due topH-dependent arsenic speciation [28], cause repulsion of nega-tively charged adsorbate/adsorbent surface groups at boundarylayer of the solid interface.

Theoretical modeling of pH influence on arsenate removal wereperformed by using eight models incorporated in MINTEQ pro-gramme, with intention to select the best one which could be usedfor description of adsorption results. Results of modeling, using logK for surface complexation reactions and modeling parameters gi-ven in Table S1, indicated high level of accordance with experi-mental data. The best fitting of experimental results for sorbent 1was obtained using Dzombak & Morel HFO model (Fig. 4).

The effective operational application of adsorbent is stronglydependent on the water composition being treated. The influenceof co-existing ions naturally present in water, which could havedetrimental effect on exchange/sorption efficiency of arsenate re-moval [39], was also studied. Experiments were performed byusing model water spiked with different concentration of phos-phate (Fig. S2), sulphate (Fig. S3), silica (Fig. S4), salt (ionic strengthof solution) (Fig. S5), calcium (Fig. S6) and magnesium (Fig. S7).Theoretical and experimental results were in accordance for sor-bent 1, and only experimental data were presented for sorbent 3(Figs. S8–S11). Presence of phosphate and silica ions at concentra-tion higher than 10 mg dm�3, (Figs. S2, S4, S8 and S9, respectively),caused greatest adsorption decrease both in experimental studyand the theoretical modeling. No significant influences of phos-phate and silica in pH range 4–6 on adsorption efficiencies was no-ticed, on that way, according to this study, sorbents 1 and 3 aregood alternative for practical application of arsenate removal evenin presence of interfering ions normally found in natural waters.Due to similar chemical properties phosphate showed largest com-petitiveness for the same surface adsorptive sites, it could suppressthe adsorption of arsenate [40], or displace adsorbed arsenate fromsurface [41]. Presence of sulphate showed low detrimental effect

Table 4Kinetic parameters obtained by the use of pseudo-second-order equation for arsenateadsorption on sorbents 1–3.

Sorbent qe (mg g�1) K´ (g mg�1 min�1) R2

1 0.919 ± 0.0171 0.110 ± 0.00911 0.9912 0.865 ± 0.0353 0.0731 ± 0.0126 0.9743 0.938 ± 0.0125 0.256 ± 0.0194 0.987

436 J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442

on arsenate adsorption (Fig. S3). Improvement of adsorption per-formances of sorbents 1 and 3 was obtained at increased concen-tration of calcium and magnesium at pH higher than 10 (Figs. S6,S7, S10 and S11). Also, modeling and experimental results indicateslight increase of arsenate adsorption in case of increased ionicstrength (Fig. S5). In the work of Goldberg and Johnston [42] great-er arsenate adsorption with increasing ionic strength is explainedas higher activity of the counter ions in solution available to com-pensate the surface charge generated by specific ion adsorption,and also suggesting an inner-sphere adsorption mechanism. Pre-sented results are in accordance with literature ones, related toarsenate adsorption on goethite [28], and the used concentrationsof competing anions are higher than arsenic concentration, indicat-ing benefit of possible adsorbent application for arsenic removalfrom real water samples.

3.7. Adsorption isotherms and ODR analysis

State of interaction between solutes and adsorbent can be de-scribed by using equilibrium adsorption isotherms which directlyillustrate the conditions at which highest adsorption capacitieswas attained. Five commonly used isotherm models were appliedfor fitting of the experimental adsorption data:

� Langmuir model, which assumes monolayer adsorption withequal energy and enthalpy for all adsorption sites.� Freundlich model, which is based on the assumption of adsorp-

tion on heterogeneous surfaces and possibly in a multilayerform.� Redlich–Peterson, which approaches the Langmuir model at

low concentration values and the Freundlich model at highconcentrations.� Sips model, which is a derivative of Langmuir equation assum-

ing the case when the solute molecule occupies two sites on thesorbent surface, and� Jovanovic model, which assumes multilayer adsorption on

homogenous surface.

Herein, apart from the R2, the quality of fitting experimentaldata was evaluated by mean of absolute relative error (MARE)and root mean squared relative error (RMSRE), which are definedby the following equations:

MARE ¼ 1n

Xn

i¼ 1

qi � qi

qi

��������; and ð2Þ

RMSRE ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1n

Xn

i ¼1

qi � qi

qi

� �2s

ð3Þ

The use of these two statistical criteria is suggested since R2 it-self is not a good parameter to be solely used for comparison of thequality of experimental data fitting by using different isothermmodels [43]. According to definitions of MARE and RMSRE criteria,they give more reliability to observations at low equilibrium con-centration values. The values of adsorption isotherm parameterson three temperatures, obtained by ODR method, for both sorbents1 and 3, are presented in Table 3.

Except of these results, adsorption studies showed that driedeggshell showed low adsorption capacity of 2.861 mg g�1. There-fore dried eggshell are not included in following discussion. Mod-ifications of dried eggshells with goethite (sorbent 10), a-MnO2

(sorbent 20) and goethite/a-MnO2 (sorbent 30) provide sorbents oflower adsorption capacities (Table S2). From that point of view cal-cined eggshells was a material of choice for modification to obtainsorbents of preferable adsorption performance (Tables 3–5).

The graphical presentation of the fitting of experimental data,obtained by using Langmuir and Sips adsorption isotherms, andapplying ODR method are given in Figs. 5 and 6.

At first glance, the highest correlation coefficients were ob-tained by using Langmuir and the Sips equations for sorbents 1and 3. The Redlich–Peterson equation was fitted with the con-straint on the g: 0 6 g 6 1 and it converged to the Langmuir mod-el for sorbent 1, since the g parameter was determined to be 1 fortwo lower temperatures, and close to 1 for the highest of theexamined temperatures. Redlich–Peterson isotherm, for sorbent3, does not converge at 25 �C and reduces to the Freundlich mod-el at 35 and 45 �C. The Freundlich and Jovanovic isotherm hadmarkedly lower R2, and high MARE and RMSRE values. Thus itcan be concluded that multilayer adsorption is not likely to occur.Both the Langmuir and Sips isotherm suggest that the adsorptionreaches monolayer saturation. According to fitting curves onFigs. 5 and 6, it was difficult to confirm which equation providesbetter correlation of the experimental data by using theoreticalisotherm curves. Therefore, the R2, MARE and RMSRE coefficientswere used simultaneously as criteria for analysis of the goodnessof experimental data fitting. For sorbent 1, it was found thatLangmuir isotherm gives the higher values of R2 coefficient at25, 35 and 45 �C, while Sips isotherm gives somewhat lower val-ues of MARE and RMSRE at each temperature (Table 3). Consider-ing that R2 uniformly treat all points, whereas MARE and RMSREgive more importance to points at lower concentrations, Lang-muir equation was chosen to describe adsorption equilibriumfor sorbent 1. The statistical criteria, namely R2, MARE and RMSRE,for sorbent 3 indicates that the Sips model could be used for fit-ting of the adsorption data at 25, 35 and 45 �C. At 25 �C, the bestfitting was chosen based on the value of coefficient R2, while allof three coefficients were in favor of Sips model at higher temper-atures. Adsorption study shows that monolayer saturation of bothsorbents 1 and 3 surface prevails. However, the differences be-tween sorbents 1 and 3 are reflected by adsorbate enthalpiesand sorption activation energy. Therefore, arsenate adsorptionon sorbent 1 was described by the process where arsenate speciespossess equal affinity to equivalent localized sites at adsorbentsurface producing monolayer coverage. On the other hand, forsorbent 3, Sips model, combined Langmuir and Freundlich, pre-dicts heterogeneous adsorption where arsenate molecule pos-sesses different enthalpies and adsorption activation energies.Obtained results are in accordance with morphology and chemi-cal composition of the sorbent.

A dimensionless constant RL was also calculated, according toEquation S7, using Langmuir isotherm constants from Table 3and Cin of 0.36 mg dm�3. It was found that calculated RL constantsfor both sorbents were between 0 and 1 (0.70, 0.68, 0.71 for sor-bent 1; 0.64, 0.64, 0.65 for sorbent 3 at 25, 35 and 45 �C, respec-tively), indicating favorable adsorption process.

3.8. Adsorption kinetics

The adsorption isotherms, as empirical models, does not giveany information about underlying mechanisms and the time afterwhich system attain thermodynamic stability. In order to get

Table 5Kinetic parameters of the Weber–Morris (intra-particular) model for arsenate adsorption.

Sorbent kp1 (mg g�1 min�0.5) C (mg g�1) R2 kp2 (mg g�1 min�0.5) R2 kp3 (mg g�1 min�0.5) R2

1 0.135 ± 3.03 ⁄ 10�3 0.010 ± 3.17 ⁄ 10�3 0.998 0.0601 ± 9.61 ⁄ 10�3 0.916 0.0154 ± 4.35 ⁄ 10�3 0.8712 0.102 ± 5.21 ⁄ 10�3 0.0092 ± 10.2 ⁄ 10�3 0.992 0.0823 ± 8.35 ⁄ 10�3 0.957 0.0132 ± 3.78 ⁄ 10�3 0.8943 0.174 ± 10.2 ⁄ 10�3 0.097 ± 31.5 ⁄ 10�3 0.987 0.0970 ± 10.5 ⁄ 10�3 0.957 0.00910 ± 2.21 ⁄ 10�3 0.892

Fig. 5. Adsorption isotherms for sorbent 1 at 25 and 45 �C (m/V = 100 mg dm�3, Cin = 0.100, 0.360, 1.36, 3.02, 4.31, 5.08, 6.25 and 7.40 mg dm�3, pH = 5.0 ± 0.10).

Fig. 6. Adsorption isotherms for sorbent 3 at 25 and 45 �C (m/V = 100 mg dm�3, Cin = 0.100, 0.360, 1.36, 3.02, 4.31, 5.08, 6.25 and 7.40 mg dm�3, pH = 5.0 ± 0.10).

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 437

insight into the mechanism of arsenate adsorption, as well as po-tential rate controlling steps which could be either diffusionalmass transport or chemical reaction, different kinetic models wereused for fitting kinetic data: pseudo-first order or Lagergreen mod-el, pseudo-second order or Ho–McKay model, Roginsky–Zeldovich-Elovich equation and second-order rate equation, and adsorptiondiffusion models: liquid film linear driving force rate equation, li-quid film diffusion mass transfer rate equation, homogeneous soliddiffusion model, parabolic or Weber–Morris model, Dunwald–Wagner model and double exponential model. Based on the high-est values of correlation coefficient, R2, which is a measure of con-formity between experimental data and ones calculated by usingeither pseudo-second-order (Eq. S8) or intra-particle (Weber–Mor-ris) diffusion kinetic model (Eq. S9) [44], both of them showed themost appropriate description of kinetic processes for sorbents 1–3(Tables 4 and 5, Figs. 7 and 8). The kinetic parameters of arsenateadsorption, presented in Tables 4 and 5, showed that both sorbents

possess high affinity with respect to arsenate ion, and satisfactoryrate at which system attain equilibrium.

An literature overview of the kinetic of arsenate adsorption ondifferent materials, natural origin and modified with ferric oxyhy-droxide (Table S3), indicated large diversty of results. Mainly,materials modified with iron oxyhydroxide showed higher adsorp-tion rate, except sawdust, while kinetic processes in presence ofsorbents 1–3 are of intermediate value. Evaluation of the adsor-bents based on two criteria, sorption kinetic (Table S3) and maxi-mum adsorption capacity (Table S4), indicate that the optimaladsorbent performance of sorbent 3 are reflected by intermediaterate of equilibration attainment on that providing high extent ofarsenic removal.

The non-linear least-squares methods analysis of kinetic data,using pseudo-second-order kinetic rate equation, resulted insignificantly higher second-order rate constant for sorbent 3, andsomewhat lower values of adsorption capacity for sorbent 1.

Fig. 7. Plot of pseudo-second-order model for arsenate adsorption on sorbents 1and 3 at 25 �C (m/V = 100 mg dm�3, Cin = 0.100 mg dm�3, pH = 5.0 ± 0.10).

Fig. 8. Intra-particle diffusion plot for arsenate adsorption on sorbents 1 and 3 at25 �C (m/V = 100 mg dm�3, Cin = 0.100 mg dm�3, pH = 5.0 ± 0.10).

438 J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442

However, the pseudo-second-order equation describes kineticsdata through generalized approach, and observes process as onerate-controlling step which could not identify the contribution ofdiffusional processes. Thus, to predict the actual rate-controllingstep involved in the adsorption process of As(V), the intra-particleWeber–Morris diffusion model was applied (Table 5, Fig. 8). The in-tra-particle diffusion model provides a more comprehensive ap-proach for defining of adsorption mechanism, which is usuallyconsisted of a series of distinct consecutive steps [45]. Generallythe overall process, transport from the infinity of solution to theadsorbent surface, consists from four steps: transport in the bulk,diffusion through the liquid film surrounding the surface of theparticle (external mass transfer or film diffusion), diffusion throughthe pores inside of particles (intra-particle diffusion) and last stepis a chemical reaction (adsorption/desorption) of adsorbate withactive sites present at surface matrix, i.e. mass action [46].

Results of intra-particle Weber–Morris diffusion model showedmulti-linear plot (Fig. 8), i.e. three linear sections of the plot qt ver-sus t1/2, with fast kinetic in first step following by gradual attain-ment of equilibrium for both adsorbents. Multi-linear plot doesnot pass through the origin suggesting that intra-particle diffusionis not the sole rate-limiting step, but other step, e.g. film diffusion,could be process of highest resistance in definite period of time

(Table 5, Fig. 8). Therefore, first linear part demonstrates externalmass transfer from bulk solution, related not only to instantaneousadsorbate bonding at the most readily available adsorbing sites atouter surface, but also could be due to the contribution of adsorp-tion at surface of the pores with largest diameter close to the par-ticle surface. Lower rate constants for sorbent 1 are a consequenceof resistance of the thickness of the particle surface boundary layerand large differences in textural parameters (Table 2). This proper-ties contribute to significant differences of adsorption rates, i.e. kp1

and kp2 values, higher value for sorbent 3 due to developed specificsurface area (250 vs 183 m2 g�1), and mesopore volume (0.710 vs0.0933 cm3 g�1) (Table 2). Larger differences are even more pro-nounced in relation to sorbent 2. The second linear segment is re-lated to the process of gradual attainment of equilibrium whichincludes resistance due to intra-particle diffusion as an intermedi-ate mechanism, i.e. saturation of adsorptive sites at macro andmesopore surfaces. While in the course of final stage, i.e. third step,slow transport of arsenic species inside micro pores dominate andattainment of adsorption/desorption equilibrium denote overallsaturation of available adsorptive sites [47]. On the basis of rateconstant values (Table 5), i.e. lower kp1 and kp2 values for sorbent1, it suggest that intra-particle diffusion is a rate controlling step,and comparison with sorbent 3, it denote larger resistivity in pres-ence of sorbent 1 in tune with higher values of textural parametersof sorbent 3 (Table 2). Considering that chemical reaction of arse-nate with surface groups is fast process [38], and significant differ-ences of K´ values (Table 4) indicate that availability of thefunctional group is primary controlled by diffusional transportthrough pores system in second and third steps. Structure of theporous adsorbent, i.e. pores network, consists from macroporeswhich extends into particle interior and branched into tree likesystem of meso and micropores. The arsenate ions must diffusethrough whole pore systems to reach total surface area withinthe particles, where the intra-particle diffusion, resistance due todiffusional transport inside pores, slow down overall process con-tributing to formation of time-dependent concentration gradientdue to fast kinetic process at surface, until saturation of all avail-able surface sites was achieved.

3.9. Thermodynamic study

To determine the temperature effect of the arsenate adsorptionon sorbents 1 and 3, adsorption experiments were performed at 25,35 and 45 �C. The Gibbs free energy (DG�), enthalpy (DH�) and en-tropy (DS�) of adsorption were calculated using the Van’t HoffEquations S10 and S11. A sorption isotherms does not have any int-ristic thermodynamic definition, and its significance depends onconditions of the system under study. Anyway, empirical approach,applied for calculation of thermodynamic data, provides the datanecessary for understanding of sorption process. Calculated ther-modynamic parameters are presented in Table 6.

The negative values of Gibbs free energy and positive standardentropy changes indicate exothermic and spontaneous nature ofadsorption process on both sorbents, and spontaneity of adsorp-tion increases at higher temperature. Based on free energy change[48], the calculated DG� values suggest that interactions betweenAs(V) ions and sorbents 1 and 3, are the result of both physisorp-tion and chemisorption contribution.

The negative values of DH� show that arsenate adsorption onsorbents 1 and 3 are exothermic processes with more preferableadsorption at lower temperature. Adsorption increases with tem-perature decreasing could be attributed to physical forces weaken-ing, possible destabilization of adsorbent surface at highertemperature, i.e. reversible processes are more feasible, or destruc-tion of active sites [16]. The changes in entropy values were posi-tive, indicating an increase in randomness of the system due to

Table 6Calculated Gibbs free energy, enthalpy and entropy of arsenate adsorption.

Sorbent DGo (kJ mol�1) DHo (kJ mol�1) DSo (J mol�1 K�1)

298 K 308 K 318 K

1 �44.83 ± 0.881 �45.39 ± 0.940 �46.43 ± 0.911 �21.10 ± 0.375 79.36 ± 2.783 �46.21 ± 0.893 �46.52 ± 0.933 �47.48 ± 0.960 �27.45 ± 0.483 62.61 ± 2.03

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 439

arsenate adsorption, i.e. arsenate adsorptions are entropy-drivenprocess. Many contributing factors influence entropy increasesas: anion exchange contribute to increased number of mobile spe-cies released to the bulk of solution, processes of hydration/rehy-dration of the solvation shell of exchangeable ions, and thecondition at surface regarding short and long range interactions,i.e. any kind of attraction/repulsion between moieties present atadsorbent surface contribute to increased overall randomness ofthe system. All of these processes and ones discussed in Section 3.8Adsorption kinetics gave, from energetically point of view, contribu-tion to enthalpy change of the system.

3.10. Desorption and reusability study

Desorption experiments were performed using sorbents 1 and3. Sodium hydroxide and strong acids are most commonly usedto elute arsenate, and selection of eluent depends on the arsenicadsorption mechanism and nature of sorbent [5]. It was expectedthat increased concentration of OH- ions should compete withthe already present arsenate on sorbent surface, hence sodiumhydroxide solution has been used as desorbing agent. Ternary mix-ture NaOH/NaCl/–NaOCl was satisfactorily used to oxidize lowerstate to MnO2, due to presence of As(III), and regenerate magnetitenanoparticle modified with Fe–Mn binary oxide [49]. Result ofdesorption study are given in Table 7.

The most efficient desorption system was NaOH/NaCl (0.5/0.5)for both sorbents 1 and 3. Desorption was enhanced at high pH val-ues because arsenate ions were deprotonated and easily exchangedwith hydroxyl ions. Although a small quantity of arsenate was irre-versibly bonded on sorbents 1 and 3, but still of 94% and 97%,respectively, were desorbed in a regeneration process of first cycle(Table 7). A mixture sodium hydroxide and sodium chloride (0.5/0.5) solution was the most effective, for both sorbents 1 and 3, acondition which provide good regenerability without significantinfluence on adsorptive capacity in subsequent adsorption cycle.Addition either oxalate or hypochlorite in regenerate solutionhad small influences on regeneration efficiencies, but ternary sys-tem NaOH/NaCl/NaOCl will be used for regeneration of sorbent 3after As(III) removal in future study. Throughout five consecutivecycles, desorption efficiencies was decreased to 88% and 91% forsorbents 1 and 3, respectively. Except of this, no bleeding of iron

Table 7Results of arsenate desorption for sorbents 1 and 3.

Desorption agent Cdesorption agent (mol dm�3) Arsenate desorbed (%)

Sorbent 1 Sorbent 3

NaOH 0.2 65 680.5 84 87

NaOH/NaCl 0.2/0.2 75 780.5/0.2 89 930.5/0.5 94 97

NaOH/NaCl/oxalate 0.2/0.2/0.01 75 940.5/0.2/0.01 89 97

oxide as well as iron ions was observed if presented methodologywas applied.

3.11. A short comparative review of low-cost adsorbents and onesbased on HFO, and discussion of the adsorption mechanism

A large variety of technologies for arsenate removal was devel-oped [5–11], among them the greatest interest was dedicated toadsorption due to prominent advantages: simplicity, economic via-bility, technical feasibility and possibility for transfer at full scaleapplication. Sorption is a general term that includes processes atthe solid/solution interface of multi-component system in whicha solute (organic or inorganic pollutants) is attracted to the adsor-bent surface and forms attachment via either physical or chemicalbonds [50]. The overall adsorption mechanisms is generally com-plex processes which is consisted from a number of appropriatemechanisms: the co-existence of physisorption, i.e., ion exchange,surface interactions, electrostatic attraction and chemisorption,i.e., surface complexation [51,52], which participate at different ex-tent in overall process.

Although, a huge numbers of publications, dealing about arsenicspecies/compounds removal from water were developed at labora-tory level (Table S4), brought to the quality to satisfy demand ofthe market, i.e. commercial products [53,54], or transferred tothe level of applied technologies [5,53–55], there is still open taskfor development of new hybrid high performance adsorbents. Oneof commercial adsorbent, Lewatit FO36 [54], is weakly basic anionexchange resin doped with a nano-scaled film of iron oxide, hy-drated iron oxides (HFO), covering the inner surfaces of the poresof the polymer bead thus integrates the anion exchange functionwith sorption. It is intended for selective oxoanions removal withregeneration capability, and for efficient and low cost operationaltreatment for the removal of arsenic species from water. Insteadof cross-linked polystyrene matrix, used for deposition of HFO, inour work we tried to developed a novel sorbents materials basedon waste eggshells to attain or to overcome adsorptive propertiesof Lewatit FO36. Comparing with other HFO based adsorbents(Table S4) and from literature data for textural parameters andcapacities of synthetic and natural goethite [56], showed that sor-bent 3 possess higher adsorption capacity, except akaganeite(Table S4), and also in relation to binary hybrid system Fe–Mn.Therefore, in this work by synthesis of sorbents 1 and 3 couplepoints were achieved: efficient arsenate removal from water, highaffinity, acceptable kinetic and possibility for the use in the pro-cesses of ground water remediation even in presence high concen-tration of competing ions.

The overall adsorption mechanism, according to publishedworks related to study of similar systems [34,36,39,41–43,57] in-cludes pH-dependent protonation/deprotonation surface reactionsand generally presented surface complexation reactions whichcontributes to effective arsenate adsorption on sorbents 1 and 3,presented by set of equilibria, is given in Table 8. These assump-tions were based on similarity of the surface complexation, i.e. for-mation of inner sphere complexes, on goethite [38] and MnO2 [58].

From the mechanistic point of view determination of adsorp-tion rate (adsorption kinetic), i.e. rate limiting step, kinetic of thesurface reaction and characterization of surface complexes are

Table 8Ionization and complexation reactions at metal oxide surfacea governed by solutionpH and coverage degree.

Surface hydrolysis reactions@FeOHþ Hþ�XOHþ2@FeOH�XO� þ Hþ

Inner-sphere monodentate oxyanion/goethite surface complexes@FeOHþ H2AsO�4 �@FeHAsO�4 þ H2O

@FeOHþ HAsO2�4 �@FeHAsO�4 þ OH�

Inner-sphere bidentate oxyanion/goethite surface complexes@2FeOHþ H2AsO�4 �@Fe2HAsO�4 þ H2O

@2FeOHþ HAsO2�4 �@Fe2HAsO�4 þ 2OH�

a Analogous equilibria could be drawn for active sites existing at a-MnO2 surface.

440 J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442

necessary data to get deep insight into adsorption processes. Asmacroscopic parameter of the system, the pH change duringadsorption processes, i.e. release/consumption of hydrogen ionby surface functional groups and contribution of different mecha-nisms (Table 8) at operational pH, could contribute to overall pHchange and thus help to select reaction pathways/steps of higherprobability. The pHf/pHin relationship (Fig. S12) indicates complexadsorption mechanism with respect to both sorbents 1 and 3, withsimilar differences in whole pHin range what indicates that similaradsorption reactions take place at different extent. Slight increasespHf with increasing pHin, shows alteration of adsorption mecha-nism contribution with pHin changes. For both sorbents at lowerpH, up to pH 7 for sorbent 1 and pH 10 for sorbent 3 (pHf = pHin),hydrogen ion consumption, i.e. hydroxide release form surface[36], are the processes of the largest contribution, which is con-firmed by pHf/pHin relationship, and it is in accordance with pla-teau of highest arsenate removal (Fig. 4).

Similar conclusions were obtained from point of zero chargechange (Table 2) and solution ionic strength effect on arsenateadsorption. Increased arsenate uptake with increasing ionicstrength of solution, cause formation of an inner-sphere complexesand negative charge build up, i.e. increases the net negative chargeat adsorbent surface [38] and in electrical double layer extendingfrom the surface due to exclusion of hydroxide anion. At higher io-nic strength of solution, increased concentration of counter cationsare available to compensate the surface negative charges, gener-ated by specific adsorption of As(V) [42,59]. Such behavior, i.e. fa-voured As(V) adsorption in presence of cations or increased ionicstrength of solution, was obtained in presented study (Figs. S4and S5). Additionally, shift of isoelectric point of goethite with spe-cifically adsorbed ions to lower value (Table 2) and results of FTIRanalysis before and after adsorption (Fig. 3; c and f for sorbent 1; eand h for sorbent 3, respectively) were in accordance with forma-tion of inner-sphere surface complexes.

Large number of the work was devoted studying hydrous ferricoxide (HFO) based adsorbents, their properties, adsorption perfor-mances and mechanism, as well as adsorption rate. Interaction ofarsenic species with active groups at HFO surface were attributedto the presence of (FeO(OH)) groups, i.e. pH dependent surface ion-ization generate FeOHþ2 , FeOH, and FeO� functional groups, andthese results are mainly based on extended X-ray adsorption finestructure (EXAFS) [38] and FTIR spectroscopy [35,42,60]. At pH 5,OHþ2 and OH forms of goethite surface groups are dominant andresponsible for the selective binding of molecular and ionic formsof arsenic species [61]. Availability of surface active sites is closelyrelated to the magnitude of textural parameters of adsorbents, i.e.increased surface area and porosity (Table 2) inevitably lead to in-creased capacity (Table 3).

The final step in an overall process is adsorption/desorption ofadsorbate at surface active sites, and it is fast process dependenton concentration of adsorbate and active sites. Two-step arsenate

adsorption/desorption mechanism at goethite surface was pro-posed according to results of chemical relaxation via conductivityduring pressure-jump relaxation experiments [38]. The first faststep involved initial ligand exchange forming a monodentate com-plex, while the next slow step represents a second ligand exchangeresult in the formation of an inner-sphere bidentate binuclearcomplex [38,57]. Additionally, determination of spatial arrange-ment and geometrical parameters of arsenate surface complexeswas done by Fendorf et al. [57]. It was achieved by measurementof oxyanion–Fe distances, i.e. local coordination environment ofadsorbed arsenate, by using EXAFS method. Three different arse-nate surface complexes on goethite were defined: a monodentate,bidentate-mononuclear and bidentate–binuclear with parametersof appropriate surface structures [38,57]. At low surface coveragethe monodentate complex predominate, while at higher bidentatewas favored [38,57].

Very often FTIR techniques was used for analysis of adsorptionprocesses or bonding types of adsorbate/adsorbent [34,36,42,60].The force constant of the As–O–Fe bond increases with coordina-tion number increase and decreases compared to uncomplexedAs–O [60]. The shorter bond distance results in a stronger forceconstant, i.e. higher infrared frequency. Consequently, the stretch-ing vibration frequency of the uncomplexed/unprotonated As–O–Fe is located at higher position (866 cm�1), while the frequencyof the complexed As–O–Fe band is located at lower frequency(823 cm�1). At higher surface coverage bidentate binuclear com-plex is a preferential type of bonding [38], where two of four As–O bonds are bonded to iron atom, and the remaining two are pres-ent as unprotonated and/or protonated, depending on pH. Goodaccordance of present results (Section 3.5 FTIR analysis) with liter-ature data was found.

EXAFS analysis and molecular modeling was used for determi-nation of As(V)–Mn inter-atomic distance in formed surface com-plex. Results indicated that As-MnO2 complex is bidentatebinuclear corner sharing (bridged) complex occurring at MnO2

crystallite edges and interlayer domains [58]. In accordance withpresented literature data it was postulated possible arsenate com-plexation reaction, depending on solution pH and coverage degree,with functional groups at surface of sorbents 1–3 (Table 8).

The significance of this work is reflected trough development ofcomposite adsorbent materials based on waste eggshell, calcinedand modified in order to gain novel naturally based sorbents ofthe optimal morphological properties, enhanced affinity and reac-tivity with respect to arsenate, and expecting to be economicallyviable and reliable for water treatment. Most of researchers in aprevious decade were used eggshells of different origin aftermechanical treatment [13,14,17,22] as adsorptive material. Nowa-days, many techniques were developed, including surface modifi-cation [19] or eggshell powder was encapsulated throughimmobilization with porous polymer: agar, polyacrylamide, algi-nate, cellulose acetate and polyvinyl alcohol [62] giving new com-posite adsorptive materials. Obtained materials and processes oftheir production inevitably bear some drawback which limitedtheir application, and their effectiveness is confined at high levelof the contaminant of interest. Literature survey on arsenate re-moval by low-cost biological adsorbents showed evidently theirlow capacities (Table S4), except two: orange juice residue andchitosan. Results presented herein showed significant improve-ment of adsorbent properties of composite materials based on cal-cination of eggshell and subsequent goethite, a-MnO2 andgoethite/a-MnO2 precipitation.

In summary, the optimal methods for goethite, a-MnO2 andgoethite/a-MnO2 loading on calcined eggshell were developed,technically simple with possibility for implementation on large-scale production. The optimal methods of metal oxide precipitationare the main factors influencing adsorbent properties. Modeling of

J.S. Markovski et al. / Chemical Engineering Journal 237 (2014) 430–442 441

experimental adsorption data, using MINTEQ program, helps inunderstanding relation between different solution parametersand adsorption processes. Such methodology as an systematic ap-proach gave broad range of results useful for definition of furtherinvestigations related to syntheses of new adsorbents of hybridorigin, controlled and optimized porosity and based on low specificgravity of chemically or thermally processed base material.

4. Conclusion

Within presented research, results of the adsorption studies ofarsenate on goethite and goethite/a-MnO2 coated calcined egg-shell, named sorbents 1 and 3, showed good adsorption capabili-ties for arsenate removal. Adsorption capacities obtained fromLangmuir isotherms at 25 �C were 33.38 and 47.04 mg g�1 for sor-bents 1 and 3, respectively, while adsorption studies for sorbent 2showed low adsorption capacity of 13.54 mg g�1. Therefore, sor-bent 2 did not used for detailed sorption investigation. Mathemat-ical description of the adsorption equilibria was accomplished bythe use of Langmuir, sorbent 1, and Sips, sorbent 3, models selectedaccording to ODR fitting, using R2, MARE and RMSRE statistical cri-teria. The kinetic of arsenate adsorptions were fast process con-trolled by rate limiting intra-particle diffusional transport. Thebest adsorption performance of sorbent 3 was discussed to be con-sequence of adsorbent highest specific surface area, mesopore vol-ume and diameter, as well as contribution of hybride nature, i.e.synergetic effect of both phases goethite and a-MnO2. Results oftheoretical modeling, obtained by the use of HFO model, incorpo-rated in MINTEQ, were in a good agreement with experimentaldata, and illustrated negligible influence of coexisting ions pre-sented in natural water, except phosphate which caused certainarsenate percentage adsorption decrease. Negative values of Gibbsfree energy changes, positive standard entropy changes and nega-tive values of enthalpy, indicate exothermic and spontaneous pro-cesses of adsorption. The results obtained in this study providebetter understanding of the adsorption phenomena and indicatedthe potential usefulness of modified low cost sorbents for the arse-nate removal.

Acknowledgements

The authors acknowledge financial support from Ministry ofEducation, Science and Technological developments of the Repub-lic of Serbia, Projects Nos. III43009, 172013 and 172007.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.cej.2013.10.031.

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