J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

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Kinetic and morphology study of alginate-vineyard pruningwaste biocomposite vs. non modified vineyard pruning wastefor dye removal

Xanel Vecino1, Rosa Devesa-Rey1,2, Salvador Villagrasa3, Jose M. Cruz1, Ana B. Moldes1,⁎

1. Chemical Engineering Department, School of Industrial Engineering (EEI), University of Vigo, Campus As Lagoas-Marcosende,36310 Vigo-Pontevedra, Spain2. Defense University Center, Naval Academy, University of Vigo, Plaza de España 2, 36920 Marín-Pontevedra, Spain3. Materials Engineering Department, School of Industrial Engineering (EEI), University of Vigo, Campus As Lagoas-Marcosende, 36310 Vigo,Pontevedra, Spain

A R T I C L E I N F O

⁎ Corresponding author. E-mail: amoldes@uv

http://dx.doi.org/10.1016/j.jes.2015.05.0321001-0742 © 2015 The Research Center for Ec

A B S T R A C T

Article history:Received 31 January 2015Revised 27 May 2015Accepted 28 May 2015Available online 28 September 2015

In this work a comparative bioadsorption study between a biocomposite consisting ofhydrolysed vineyard pruningwaste entrapped in calcium alginate spheres and non entrappedvineyard residue was carried out. Results have demonstrated that the biocomposite basedon lignocellulose-calcium alginate spheres removed 77.3% of dyes, while non entrappedlignocellulose eliminated only removed 27.8% of colour compounds. The experimental datawere fitted to several kinetic models (pseudo-first order, pseudo-second order, Chien–Claytonmodel, intraparticle diffusion model and Bangham model); being pseudo-second order thekineticmodel that better described theadsorptionof dyes onto bothbioadsorbents. In addition, amorphological study (roughness and shape) of alginate-vineyard biocomposite was establishedunder extreme conditions, observing significant differences between hydrated and dehydratedalginate-vineyard biocomposite. The techniques used to carry out this morphological studyconsisted of scanning electron microscopy (SEM), perfilometry and 3D surface analysis.© 2015 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences.

Published by Elsevier B.V.

Keywords:Immobilized alginate-vineyardDyesKinetic studiesRoughnessSpherical shape

Introduction

Nowadays environmental requirements are becoming of greatimportance, since there is an increased interest in the industrialuse of renewable resources such as lignocellulosic residues forthe formulation of eco-friendly adsorbents (Kim et al., 2014;Alves et al., 2013; Deng et al., 2011; Perez-Ameneiro et al., 2014a).Thus, significant efforts are now beingmade in the research anddevelopment of polysaccharide derivatives as the basic mate-rials for new applications. In particular, the increasing costs ofconventional adsorbents certainly make lignocellulosic-basedmaterials, composed by natural polymers, one of the most

igo.es (Ana B. Moldes).

o-Environmental Science

attractive bioadsorbents for wastewater treatment (Sharma andRajesh, 2014; Kumar et al., 2014). Different studies havedemonstrated that lignocellulosic-based polymers have excep-tional removal capabilities for certain pollutants such as dyesand metal ions as compared to other low-cost adsorbents andcommercial activated carbons (Batzias et al., 2009; Rosas-Castoret al., 2014; Sidiras et al., 2013; Velazquez-Jimenez et al., 2013).Thus, cellulose-based biocomposites, has been widely used inwastewater purification due to its good biocompatibility, andexcellent handling, which can be easily formulated into spheres,membranes and hollow fibres. Cellulose is composed of β-1,4linked glucopyranose units, with polymer chains associated by

s, Chinese Academy of Sciences. Published by Elsevier B.V.

159J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

hydrogen bonds forming bundles of fibrils, also called microfi-brillar aggregates, where highly ordered crystalline regionsalternate with disordered amorphous domains. Therefore, peatand grape marc compost, entrapped in calcium alginatehydrogels, have been proposed for their dye-binding capabilityfrom wastewater (Vecino et al., 2013; Perez-Ameneiro et al.,2014b). Nevertheless, peat and composted grape marc haveother uses like soil amendments that can prevent their use asbioadsorbents in comparison with the lignocellulosic fraction ofvineyard pruning waste. Moreover it was observed that thelignocellulosic fraction of vineyard pruning waste, encapsulatedin calcium alginate beads, has excellent properties for theremoval of micronutrients from wastewater (Vecino et al.,2014); although it would be important to evaluate the capacityof this lignocellulosic residue to remove other contaminants likedyes and study the adsorption mechanism under differentkinetic models. In addition it would be interesting to know ifthe immobilization of this lignocellulosic residue in calciumalginate spheres increases the bioadsorption capacity of vine-yard pruning waste in comparison with the raw hydrolysedvineyard pruning waste.

This work deals with a comparative study between thedirectly utilization of the lignocellulosic fraction of vineyardpruning waste against the utilization of an alginate-vineyardbiocomposite spheres, for the removal of dye compoundsfrom an agro-industrial effluent. Different kinetic models(pseudo-first order, pseudo-second order, Chien–Claytonmodel, intraparticle diffusion model and Bangham model)were used to explain the adsorption of dyes onto the twobioadsorbents. Moreover, 3D surface visualizations andperfilometry analysis of hydrated and dehydrated calciumalginate spheres, containing vineyard pruning waste, wereincluded in this study.

1. Materials and methods

1.1. Preparation of the lignocellulosic fraction of vineyardpruning waste

Lignocellulosic residue was collected from a local wine-producer (Galicia, North-West Spain). Vineyard pruning wastewas dried and milled (<1 mm), homogenized in a single batchandhydrolysedwithH2SO4 following themethodologyproposedby Bustos et al. (2004). After hydrolysis a solid fraction composedby cellulose and lignin was dried and sieved up to a particlesize of 0.5 mm and submitted to a quantitative hydrolysis inorder to determine the cellulose and lignin concentration in thebioadsorbent (Vecino et al., 2014). Thus the percentage ofcellulose in the adsorbent was calculated on the basis of glucosein the liquid phase, which was analysed by high performanceliquid chromatography (HPLC) equipped with diode array detec-tion (DAD) and refractive index detection (RID) (Agilent Technol-ogies 1200 Series, Germany). Separation was performed using aRezexRHM-MonosaccharideH+ (8%) column (Phenomenex,USA)with thecolumnovenkept at 65°C. Themobile phase consisted inMilli-Q water plus 0.005 N of H2SO4, the injection volume was20 μL and the flow rate was 0.4 mL/min.

Otherwise, the solid residue that remains after quantitativehydrolysis, was considered as the Klason lignin.

1.2. Development of the alginate-vineyard biocomposite spheres

Alginate-vineyard biocomposite spheres were prepared bymixing 1.25% of cellulosic residuewith 2.2% of sodium alginate,in order to formanemulsion thatwas introduceddrop-wise in acrosslinking solution of calcium chloride 0.475 mol/L (Vecinoet al., 2014).

For comparative purposes, during the kinetic adsorptionstudy, hydrolysed vineyard pruningwastewas alsousedwithoutencapsulation.

1.3. Morphology characterization of lignocellulosic powder andalginate-vineyard biocomposite

1.3.1. Scanning electron microscope (SEM) imagesPreviously to obtain SEM images, the alginate-vineyardbiocomposite was washed with sodium cacodylate 0.1 mol/Lbuffer and fixed with 2.5% of glutaraldehyde in cacodylate0.1 mol/L buffer during 2–4 hr at 4°C. Following, the alginate-vineyard biocomposite was introduced in 1% OsO4 incacodylate 0.1 mol/L buffer during 1 hr at 4°C. Dehydrationwas carried out with 30% of ethanol during 15 min and thenethanol using a different graded series (50%–2× 15 min; 70%–2× 15 min; 80%–2× 15 min; 90%–2× 15 min and 100%–3×15 min) and amylacetate:ethanol in an ordered series (1:3–2×15 min; 2:2–2× 15 min; 3:1–2× 15 min and amylacetate 100%–3× 15 min) in order to replace the ethanol for a liquid misciblewith liquid CO2. The biocomposite was dried at the chambercritical point, cut in liquid N2, covered with gold and observedusing SEM (Jeol JSM-6700F FEG) operating at an accelerationvoltage of 5.0 kV for secondary-electron imaging (SEI/LEI).

The lignocellulosic powder undergoes non dehydrationprocess. Thepowderwas coveredwithgold andobservedby SEM.

1.3.2. 3D surface roughness analysis3D images of alginate-vineyard biocomposite were obtainedwith an Infinite Focus-SL Alicona GmbH (Graz, Austria) usingan objective lense 10×, lateral resolution of 2 μm and verticalresolution of 500 nm. This system allows intuitive and quickmeasurement of micro structured surfaces, due to the highresolution and high density of number of points measured(4 millions of points); it is possible to calculate the diameterand the surface roughnesswithin the same 3Dmeasurement ofthe alginate-vineyard biocomposites. Post-processing MeasureSuite software provides the tools to filter out the 3D measure-ment into waviness and roughness components by using acut-off frequency filter of 80 μm.

In addition, an optical profilometer Zeta-20™ (Zeta Instru-ments, CA) was used in order to obtain a 3D surface visualizationand roughness parameters (Ra, Rq, Rz, Rp, Rv) using Z scan rangeof μm and controlled by Zeta 3D software.

The roughness and radius of calcium alginate spherescontaining the lignocellulosic adsorbent were studied during22 min of hydration followed by a period of 75 min of dehydra-tion at 19.5°C and 73 min of rehydration.

1.4. Commercial dye

Amaranth is a commercial dye (85%, Acros organics, USA) thatwas used as standard to obtain the amount of dye compounds

160 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

contained in the winery effluent. Eq. (1) shows the linearrelationship between the colour index (CI) of dye compoundscontained in the winery effluent and the concentration ofamaranth dye. CI of winery effluents was quantified bymeasuring the absorbance at 620, 520 and 420 nm (Eq. (2)).Therefore, the amount of colour compounds in wastewaterwas measured as equivalents of amaranth dye.

Ci ¼ 19:4663� CI−0:2238 ð1Þ

CI ¼ A620 þ A520 þ A420 ð2Þ

1.5. Dye compounds from winery industry

Agro-industrial effluent with the presence of dyes compoundswas obtained from a local winery industry in Galicia, North-West of Spain, and kept at 4°C before use.

1.6. Bioadsorption of dyes: kinetic experiments

In order to establish the bioadsorption kinetics, batch adsorptionexperiments were carried out in 250 mL Erlenmeyer flasksplaced in an orbital shaker at 150 rpm and 25°C. The solid/liquidratio usedwas 1:1 (V/V). Sampleswere obtainedat 5, 10, 20, 30, 40,50, 60, 90 and 120 min for analysis of dye compounds and filteredthrough a 0.45 μm pore size membrane (PTFE Hydrophilic,Advantec, Japan) before analysing them by a double-beamspectrophotometer (Jasco V-650, Spain).

The adsorption capacity for the alginate-vineyardbiocomposite and lignocellulosic powder was calculated ateach time, qt (mg/g), following the Eq. (3):

qt ¼C0−Ctð ÞV

Wð3Þ

where,C0 andCt (mg/L) are the concentrations of dye compoundsin thewinerywastewater before andafter treatment respectively,V is the volume of the winery wastewater used during batchexperiments (L) andW (g) is the mass of lignocellulosic residue.

The percentage of dye removed (R) from wastewater wascalculated following Eq. (4).

R% ¼ CI−C F

CI

� �� 100 ð4Þ

where, CI and CF are initial and final dye contents.The kinetic bioadsorption of dyes onto the bioadsorbents

was studied using different kinetic models: pseudo-first order(Lagergren, 1898), pseudo-second order (Ho and McKay, 1999),Chien–Clayton model (Chien and Clayton, 1980), intraparticlediffusion (Weber and Morris, 1963) and Bangham model(Aharoni and Ungarish, 1977).

2. Results and discussion

2.1. Chemical characterization of lignocellulosic powder andalginate-vineyard biocomposite

The bioadsorbent obtained after quantitative hydrolysis withsulphuric acid of vineyard pruning waste, was composed by

39.0% cellulose and 40.1% lignin, being these percentagessimilar to those reported by Moldes et al. (2007).

2.1.1. Scanning electron microscopy (SEM) studyFig. 1 shows high-resolution imagines of non-encapsulatedhydrolysed vineyard pruning waste (Fig. 1a, b, c), the externalsurface of the biocomposite, consisting of calcium alginatehydrogel (Fig. 1d, e, f) and internal surface of vineyard pruningwaste contained in the calcium alginate spheres (Fig. 1g, h, i)at different magnifications, respectively. Images revealed highamount of irregular and interconnected pores in the surface ofvineyard pruning waste. These pores may be the areas whereinteraction sites are available to dye adsorption.

2.1.2. 3D surface roughness analysisSurface roughness, often shortened to roughness, is a measureof the texture of a surface. Roughness values can either becalculated on a profile (line) or on a surface (area). The mostcommon profile roughness parameters consist of Ra, Rq, Rz, Rpand Rv (UNE ISO 4287:1999/A1:2010; UNE ISO 4288:1998; UNEISO, 11562:1998) whereas area roughness parameters compriseSa, Sq, Sz, Sp and Sv (UNE ISO, 25178-2:2013).

Sa and Sq parameters represent a general measure ofthe texture comprising the surface of the alginate-vineyardbiocomposite, which may be used to indicate significant devia-tions in the biocomposite characteristics.Moreover, Sp, Sv, and Szare parameters evaluated from the absolute highest and lowestpoints found on the surface. Sp, the maximum peak height, isthe height of the highest point, Sv, themaximum valley depth, isthe depth of the lowest point (expressed as a negative number)and Sz the maximum height of the surface, is calculated fromSz = Sp − Sv. Table 1 shows the Sa, Sq, Sz, Sp and Sv values ofcalcium alginate biocomposite spheres, based on vineyardpruning waste, before and after dehydration process. Moreover,radiusandsurface roughnessparametersweremeasured to trackthe hydration and dehydration process. These parameters arevery robust and representative of the hydration and dehydrationprocess, as they are measured over a significant area of thealginate-vineyard biocomposites. Fig. 2a and b shows thevariation in the radius and Sa respectively of alginate-vineyardbiocomposite spheres after a cycle of hydration and dehydrationprocess. As it can be observed in Fig. 2a and b calcium alginatespheres containing vineyard pruningwaste recovered its originalshape and size. It was observed that the manipulation duringthe rehydration process did not have a strong influence on theradius and surface roughness parameters. On the other hand,Fig. 3 shows 3D images of the alginate-vineyard biocompositeevaluated in this work, before (Fig. 3a) and after (Fig. 3b)dehydration processes based on a profile roughness. In thiscase it was observed that the profile roughness of dehydratedalginate-vineyard biocomposite was five times higher than notdehydrated biocomposite.

In addition, 3D roughness parameters based on the valuesof Ra, Rq, Rz, Rp and Rv values were obtained in this work;where Ra is defined as the roughness average, Rq as theroot-mean-square roughness, Rz as the average maximumprofile height, Rp as the maximum profile peak height and Rvis the maximum profile valley depth (Mummery, 1993; Korkutet al., 2008). Table 1 includes the differences found in theseparameters before and after dehydration of the lignocellulosic

Fig. 1 – High-resolution images of surfaces obtained by SEM at different magnifications. (a, b, c) non encapsulated vineyardpruning waste at magnification of ×200, ×1500, ×3300, respectively; (b, c, d) external surface of calcium alginate-vineyardbiocomposite at magnification of ×33, ×5000, ×25,000, respectively; (e, f, g) internal surface of calcium alginate-vineyardbiocomposite at magnification of ×33, ×5000, ×25,000, respectively. SEM: scanning electron microscopy.

161J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

biocomposite and Fig. 4a and b shows 3D surface imagesemployed to obtain these parameters. The strong increase inroughness after dehydrating the biocomposite is obvious. In

Table 1 – Different roughness parameters based on ISO standar

Parameters

Radius (mm)Area (mm2)

Roughness parameters based on ISO 4287/4288/11562 Pa (μm)Pq (μm)Pz (μm)

Roughness parameters based on ISO 25178 Sa (μm)Sq (μm)Sz (μm)Sp (μm)Sv (μm)

Roughness parameters based on ISO 4287/4288 Ra (μm)Rq (μm)Rz (μm)Rp (μm)Rv (μm)

addition, Fig. 4c shows the surface texture of the alginate-vineyard biocomposite spheres before and after dehydrationprocess.

ds.

Alginate-vineyardbiocomposite

Dehydrated alginate-vineyardbiocomposite

2.06 1.6812.94 7.104.05 10.535.64 14.84

23.41 63.495.60 11.468.31 16.26

166.15 302.92102.13 125.1064.02 177.810.13 0.790.17 1.090.67 4.530.65 1.990.33 6.67

bDehydration in process Dehydration in processa2.52.42.32.22.12.01.91.81.71.6

Rad

ius

(mm

)

0 20 40 60 80 100 120 140 160 180 0 20 40 60 80 100 120 140 160 180

16

14

12

10

8

6

4

Sa (

µm)

Time (min) Time (min)

Hydration Dehydration Rehydration

Fig. 2 – Variation of the radius (a) and area roughness (Sa) (b) of alginate-vineyard biocomposite after a cycle of hydration-dehydration.

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Furthermore, based on the normative of the SpanishAssociation for Standardisation and Certification (UNE ISO,1101:2013), Fig. 5 shows the spherical shape in 3D images ofalginate-vineyard biocomposite, at initial state (Fig. 5a) andafter dehydration (Fig. 5b) used to calculate the radius by fittingthe alginate-vineyard biocomposites surface to a sphere.

Important differences were observed between hydratedand dehydrated biocomposite. Table 1 includes the radius andarea of alginate-vineyard biocomposite spheres, correspondingwith these images.

In addition, some researchers (Mattsson et al., 2008)have reported that the roughness parameters preferred inmicrometrology are the P-parameters (Pa, Pq and Pz) based onprimary profile data introduced in ISO standards 4287 (UNEISO 4287:1999/A1:2010) and 4288 (UNE ISO 4288:1998); wherePa is defined as the arithmetic mean deviation of the assessedprofile, Pq is the root mean square deviation of the assessedprofile (equivalent to the standard deviation of the surfacestructure) and Pz is the maximum height of profile. Table 1shows the difference between Pa, Pq and Pz values before andafter dehydrationprocess of the alginate-vineyard biocomposite.It can be observed that after dehydration the roughness of thelignocellulosic biocomposite was highly increased.

a

-10

0

10

20

0 0.2 0.4 0.6 0.8 1.0 1.2 1.61.4 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4

Path legth

Dep

th (

µm)

Fig. 3 – Waviness and roughness images used to calculate surfacvineyard biocomposite (a) before and (b) after dehydration proce

2.2. Adsorption of dye compounds on vineyard pruning wastebioadsorbents: a kinetic study

It has been demonstrated that hydrolysed vineyard pruningwaste, entrapped in calcium alginate beads, has exceptionalcapabilities for the removal of anionic and cationicmicronutrients, as well carbon and nitrogen in an industrialwastewater (Vecino et al., 2014), however there are notcomparative studies about this entrapped and non entrappedvineyard pruning waste adsorbent for the removal of dyecompounds. Furthermore, kinetic studies were carried out toknow the dye adsorption mechanism onto both adsorbents,entrapped and non entrapped hydrolysed vineyard pruningwaste.

Fig. 6 shows the kinetic profile of dye removal obtainedduring the adsorption of dye compounds onto the bioadsorbentsbased invineyard pruningwaste. The dye compounds in the rawwastewater gave a CI of 1.81, which corresponds, with 35.6 mg/Lof dye compounds measured as equivalents of amaranth dye.

When vineyard pruning waste was encapsulated in calciumalginate spheres, the lignocellulosic adsorbent increased itsadsorption capacity in comparison with the utilization of nonimmobilized vineyard pruningwaste for the same concentration

b

0 0.2 0.4 0.6 0.8 1.0 1.2 1.61.4 1.8 2.0 2.2 2.4 2.6 2.8

Path legth

-50

0

50

100

Dep

th (

µm)

e roughness (Pa, Pq, Pz; Sa, Sq, Sz, Sp, Sv) of the alginate-ss.

Fig. 4 – Surface roughness images of (a) alginate-vineyard biocomposite, (b) dehydrated alginate-vineyard biocomposite, and(c) 3D surface images hydrated and dehydrated biocomposites.

163J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

of lignocellulosic residue (1.25 g). Non encapsulated vineyardpruning waste only eliminated 27.8% of dye compounds,whereas alginate-vineyard biocomposite removed 77.3%; thesedata correspond with a reduction of CI of 1.31 and 0.41respectively. Only when the amount of vineyard pruning wasteincreased up to 7.56 g, which is the dry weight of thealginate-vineyard biocomposite spheres, the same percentageof dyes removal was obtained (77.7%).

The bioadsorption of dye compounds onto alginate-vineyardbiocomposite were conveniently represented by kinetic models,whicharehelpful topredict thebehaviour of thesebioadsorbents.

Eq. (5) represents the linear form of the pseudo-first ordermodel (Lagergren, 1898):

log qe−qtð Þ ¼ logqe−k1

2:303t ð5Þ

where, qe (mg/g) and qt (mg/g) are the concentration of adsorbeddyes at equilibrium and at a defined time t, respectively, and k1(1/min) is the rate constant of pseudo-first order adsorption.

The kinetic coefficients obtained in this case showed thatthere is a clear difference betweennon-encapsulated hydrolysedvineyard pruningwaste and the alginate-vineyard biocomposite

formulated (Table 2). Thus, non encapsulated vineyard pruningwaste gave a theoretical capacity of 0.48 mg/g, whereasentrapped vineyard pruning waste in calcium alginate spheresincreases the capacity until 1.23 mg/g. Fig. 7a shows thecorrelation between the experimental data and the theoreticaldata when these were described by using pseudo-first orderkinetic model. Non-encapsulated vineyard pruning waste wasused at two different concentrations (1.25 g and 7.65 g), observ-ing that only when the concentration of vineyard pruning wasteincreased up to 7.65 g similar capacity with encapsulatevineyard pruning waste can be obtained.

Moreover, sorption kinetics were also described using apseudo-second order model following Eq. (6) (Ho and McKay,1999):

tqt

¼ 1k2q2e

þ 1qe

t ð6Þ

where, k2 (g/mg min) is the equilibrium rate constant of pseudo-second order adsorption. In this case, Eq. (6) does not have theproblem of assigning an effective qe. If the pseudo-second orderkinetic equation is applicable, theplot of t/qt against t should give

a b

1000

-1000

0(µm

)

-2 0 2 4(mm)

Fig. 5 – 3D simulation to a sphere of alginate-vineyard biocomposite (a) at an initial state and (b) after dehydration process.

164 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

a linear relationship, from which qe and k2 can be determinedfrom the slope and intercept of the plot, and there is not need toknow any parameter beforehand.

Table 2 includes the kinetic parameters obtained aftermodelling the experimental data following pseudo-second orderkineticmodel and Fig. 7b shows the variation of the experimentaldata when they were adjusted to this pseudo-second orderkinetic model, observing that there are a close agreementbetween the experimental and theoretical capacities predictedby the model. The best capacities predicted by the model(2.07 mg/g) were achieved using alginate-vineyard biocomposite.Furthermore, adsorption kinetics can also be adjusted to theElovich equation (Elovich and Larionov, 1962a, 1962b), which,although firstly was used to explain the adsorption kinetics ofgases on solids, it has been successfully applied for theadsorption of solutes from a liquid solution (Eq. (7)).

dqtdt

¼ α exp −βqtð Þ ð7Þ

0 10

20

30

40

50

60

70

80

20 40 60 80 100 120

Dye

rem

oval

(%

)

Time (min)

Cellulosic-based biocompositeCellulosic residue (1.25 g)

Cellulosic residue (7.65 g)

0

Fig. 6 – Percentages of dye removal obtained during thetreatment of wastewater from winery industry usingvineyard pruning waste as bioadsorbent.

Chien and Clayton (1980) proposed the simplification ofEq. (7) by assuming αβt ≫ 1, and considering the boundaryconditions qt = 0 for t = 0 and qt = qt at t = t. In the Chien–Clayton expression (Eq. (8)), α (min mg/g) is the initial sorptionrate, and β (g/mg) is related to the extent of surface coverageand activation energy for chemisorption.

qt ¼1β

ln αβð Þ þ lntð Þ ð8Þ

Regarding the kinetic parameters obtained after applyingthe Chien–Clayton kinetic model (Table 2), it was observed thatα value predicted by this model to the encapsulated vineyardpruning waste was higher (1.74) than that obtained using 1.25 gof vineyard pruning waste without entrapping; howeverwhen the concentration of non-encapsulated vineyard pruningwaste was increased to 7.65 g higher initial sorption rateswere obtained deduced by the higher α values achieved (3.01);although the adsorption capacity was lower than usingvineyard pruning waste encapsulated in calcium alginatespheres (Fig. 7c).

Moreover, in order to determine whether the adsorptionprocess is governed only by intraparticle diffusion or if itis more complex and involves more than only one diffusiveresistance such as surface adsorption, ion exchange, complexa-tion, complexation–chelation or microprecipitation; experimen-tal data have been fitted to the intraparticle diffusion model(Weber and Morris, 1963) following Eq. (9).

qt ¼ kPt0:5 þ C ð9Þ

where kP is the intraparticle diffusion rate constant (mg/(g·min))and C is the intercept (mg/g), and it is related to the thickness ofthe boundary layer. The slope of the linear part of the curve of qtvs. t0.5 – kP – indicates the rate of adsorption controlled byintraparticle diffusion (see Fig. 7d). When the intercept – C –

Table 2 – Comparison of kinetic parameters for pseudo-first order, pseudo-second order, Chien–Clayton, intraparticlediffusion and Bangham kinetic models.

Kinetic model Kineticparameters

Values

Alginate-vineyardbiocomposite

Lignocellulosic residue(1.25 g)

Lignocellulosic residue(7.65 g)

Pseudo-first order qe exp (mg/g) 1.965 0.786 0.359qe calc (mg/g) 1.229 0.483 0.167k1 (1/min) 0.033 0.040 0.033r2 0.960 0.955 0.899

Pseudo-second order qe exp (mg/g) 1.965 0.786 0.359qe calc (mg/g) 2.070 0.828 0.368k2 (1/min) 0.058 0.178 0.555r2 0.998 0.999 0.999

Chien–Clayton model α 1.737 0.631 3.015β 3.291 7.733 25.167r2 0.997 0.959 0.994

Intraparticle diffusion model kp 0.107 0.043 0.014C 0.912 0.380 0.223r2 0.938 0.826 0.911

Bangham model α 0.335 0.254 0.237k0 0.006 0.005 0.002r2 0.998 0.916 0.994

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equals zero, then the intraparticle diffusion is the only controllingstep. However, if C does not pass through the origin, it indicatesthat there are other processes involved in the rate of adsorption.In this case, the intraparticle diffusionmodel gaveCvalueshigherthan 0,which indicates that there are other processes, apart fromthe intraparticle diffusion, involved in the rate of adsorption.These results are similar to thoseachievedby someauthorsusingothers lignocellulosic residues. Thus, Perez-Ameneiro et al.(2014b) found that, the intercept was between 0.325 and 0.172using a lignocellulosic biocomposite based on composted grapemarc.

Finally, following Eq. (10) experimental data were fitted toBangham model (Aharoni and Ungarish, 1977):

log logc0

c0−qtm

� �� �¼ log

k0m2:303 V

� �þα logt ð10Þ

a

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5

0 10 20 30 40 50 60 70 80 90 100

log

(qe-

q t)

Time (min)

t0.5 (min0.5)

Tim

b

0 50

100 150 200 250 300 350 400

0 20 40

t/qt (

min

g/m

g)

d

0.0

0.5

1.0

1.5

2.0

2.5

0 1 2 3 4 5 6 7 8 9 10

q t (m

g/g)

e

-1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0

0.0 0.5 1.0

log

(log

(C

0/C

0-q tm

))

Fig. 7 – Kinetic plots for the adsorption of dye compounds onto t(a) Pseudo-first order; (b) pseudo-second order; (c) Chien–Clayton

where, C0 (mg/L) is initial concentration of adsorbent insolution, V (L) is the volume of solution, m (g/L) is the weightof adsorbent used per litre of solution, qt (mg/g) the amount ofadsorbent retained at time t, and α (<1) and k0 are constants. Assuch, log (log (C0 / (C0 − qtm))) valueswere plotted against logt inFig. 7e. The linearity of these plots confirms the applicability ofthe Bangham equation and indicates that diffusion of dyes intopores of the adsorbent controls the adsorption process (Aharoniet al., 1979) although according to the intraparticle diffusionmodel other processes are involved in the elimination of dyesfrom wastewater.

For all the kinetic studies, good correlation coefficients (r2)were obtainedwith values between 0.899 and 0.999 (see Table 2),although the best r2 were obtained using the pseudo-secondorder kinetic model. Thus, pseudo-second order was the modelthat better explained the behaviour of the bioadsorption process

e (min)60 80 100 120

c

0.0

0.5

1.0

1.5

2.0

2.5

0 1 2 3 4 5 6

q t (m

g/g)

lnt

1.5 2.0 2.5 logt

Cellulosic-based biocomposite

Cellulosic residue (1.25 g)

Cellulosic residue (7.65 g)

he studied biocomposites applying different kinetic models.model; (d) intraparticle diffusion model; (e) Bangham model.

166 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S 3 8 ( 2 0 1 5 ) 1 5 8 – 1 6 7

and that the intraparticle diffusion is not the only controllingstep. Several authors like Huayue et al. (2014) prepared a novelmagnetic calcium alginate/maghemite hydrogel beads or Genlinet al. (2014) fabricated an adsorbent consisting of carboxymethylcellulose-acrylic acid observing that the adsorption of copper (II)and dyes respectively, also follows a pseudo-second order kineticadsorption mechanism.

3. Conclusions

In comparison with classical adsorbents such as activatedcarbons, alumina or silica gels, vineyard pruning wasteentrapped in calcium alginate spheres appear as an eco-friendly, biodegradable and manageable alternative for theefficient removal of dye compounds from industrial wastewater.Among all kinetic models evaluated pseudo-second is themodel providing the best fit. Evaluation of alginate-vineyardbiocomposite roughness, by different methods, revealed thatbiocomposite was very sensitive to dehydration providing anincrease in roughness, although once rehydrated; thebiocomposite recovered its shape and original roughness whatsuggests that this biocomposite is verymalleable and it can serveas a potential adsorbent for the effective treatment of industrialeffluents in treatment plants.

Acknowledgments

Authors wish to thank to the Spanish Ministry of Economyand Competitiveness (this work was funded by FEDER fundsunder the project CTM2012-31873). Xanel Vecino gratefullyacknowledges the University of Vigo for her predoctoralcontract andwe are also grateful to P. Martinez for his technicalassistance (ScienTec Iberica).

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