A comparative study of adsorption and regeneration with different agricultural wastes as adsorbents for the removal of methylene blue from aqueous solution

Sana Dardouri*,Jalila Sghaier

Unité de Thermique et Thermodynamique des Procédés Industriels,Ecole Nationale d’Ingénieurs de Monastir,Avenue Ibn Jazzar,5019 Monastir,Tunisia

1.Introduction

Today,water pollution became a real threatening to mankind due to the rapid industrial development.The discharged wastewater of textile industry,which contains persistent organic dyes,is one of the most causes of water contamination.During dying and printing in textile industry,a major fraction of dye is disappearing in the water which makes discharge colored.The main environmental problem in the textile industry is the treatment of liquid waste and their chemical loads.These dyes rejected by the industry represent a threat to the environment because of its low biodegradation and its high resistivity to classic purification treatment[1].The presence of dyes in water is harmful for human health and the environment due to their toxic and mutagenic in fluence on human being[2].Several research studies have been devoted to the study of toxicity and mutagenic and carcinogenic effects of different types of dye on aquatic organisms(poison,algae,etc....).Among various commercial dyes,only basic dyes are toxic for algae[3].These textile ef fluents are dramatic sources of pollution of ecosystems and aquatic life.They present a danger of bioaccumulation which can affect humans by transport through the food chain.

The methylene blue(MB)is one of the most popular dyes used in textile industries and in color of paper,wools,cotton,silk,etc.[4].The MB has also found use in medicalapplications.Itowns an antiseptic propriety againstbacterialinfection and itis used as an antidote for cyanide poisoning[5].Beyond its medical applications,the presence of MB in water threat human health in various manners.Because of its high water solubility dyes can move through rivers and affect the quality of water.MB as a cationic dye can readily interact with negatively charged surface cells and penetrate into the cells[6].

In order to reduce the negative effect of dyes,many proper treatments of wastewaters have recently attracted growing scientific attention.Various techniques have been applied for dye removal from wastewaters such as adsorption[7–10],coagulation– flocculation,membrane filtration,chemical precipitation,and ion exchange.Many techniques fordye removalare proposed incorporating physical,biological and chemical treatments.The non-biodegradable nature of many dyes makes the adsorption technique as the most suitable process and a more popular method for dye removal from aqueous solutions because adsorption has the advantages of high efficiency, flexibility,design simplicity,easy handling and economic feasibility[11].Many adsorbents are used for MB removal from aqueous solutions such as activated carbon[12],clay[13],zeolite[14],sludge[15],almond gum[16],cashew nutshell[17],olive pomace[18],almond peel[19],sawdust[20],sonochemically synthesized MnWO4and MnMoO4nanomaterials[21],BaWO4[22],BaMoO4[23],CuWO4and Cu3Mo2O9[24].

The sawdust is lignocellulosic waste materials which are available in large quantities in industry and is an abundant forestry residue and a renewable low cost adsorbent which can be used for removing pollutants from wastewater[25].The sawdust can be used as adsorbent for the removal of MB dye from aqueous solutions.The adsorption amount of dye was found to be increased with increase in initial dye concentration and in contact time.Based on the experimental results of MB adsorption into sawdust and adsorption models applied,it can be concluded that equilibrium data fitted well in the Langmuir isotherm equation[20].

Many studies have revealed that almond shells could be effectively used to remove dye from an aqueous solution[26,19].Based on the analysis of process mechanism involved in the sorption behavior of MB in almonds shell con firms that the sorption is contolled by the particle-diffusion process[19].It was found by using batch studies that the adsorption capacity of MB with an initial concentration of 100 mg·L?1is equal experimentally and numerically to 52.35 mg·g?1and 54 mg·g?1respectively.

Several low-cost adsorbents are reported for the removal of heavy metals,agricultural waste such as olive stones,peach stones,almond shell[27]and sheep manure waste[28].In this work,sheep manure waste(SMW)which is available in abundance are chosen as adsorbent for the removal of methylene blue.

In this research study,adsorption/desorption of MB on almond shell,manure sheep and sawdustin a fixed bed column was investigated with the objective to(i)evaluate the adsorption capacity of adsorbents,(ii)predicts a breakthrough curve modeland(iii)evaluates the removal efficiency and the regenerability of three adsorbents.

2.Materials and Methods

2.1.Materials

As low adsorbents,three materials have been used in the removal of MB from aqueous solutions:internal almond shell(IAS),sheep manure waste(SMW)and sawdust.These wastes were collected from the region of Sousse,in Tunisia.They were used directly for adsorption experiments without any treatment.The other adsorbents were dried in the air and crushed to a fine powder.

The methylene blue used as adsorbent(basic blue 9,CI 52015)is a cationic dye with a molecular formula C16H18CIN3S·3H2O and a molar mass of 373.9 g·mol?1.The wavelength of maximum absorbance for MB is 663 nm.

2.2.Fixed bed column sorption experiments

The adsorption experiments were conducted using a glass column with an internal diameter of 3.25 cm and a heightof 25 cm.The column was packed with the materials—bed length of 5 cm.The MB solution with inlet concentration of 100 mg·L?1was pumped at the top of the column using a peristaltic pump(ROTHCYCLOI)ata constantvolumetric flow rate of 4 ml·min?1.Samples were collected and were analyzed by spectrophotometer UV–visible(HACH LANGE DR3900).

2.3.Column desorption and recycling

To evaluate the feasibility ofadsorbents forpracticaluse and its reusability,the regeneration of these adsorbents was carried out through adsorption–desorption cycle.After adsorption had taken place,the adsorbed dye was eluted using water at a flow rate of 4 ml min?1.The samples of the ef fluent were analyzed and all experiments were carried out in duplicate.After the elution time,the adsorbent was reused in a second cycle for adsorption at the same conditions than the first cycle to study the reuse of the adsorbent.

3.Results and Discussion

3.1.Breakthrough curves and analysis of mass transfer zone

As shown in the obtained breakthrough curves(Fig.1),the breakthrough time increases in order sawdust＜IAS＜SMW(Table 1).It was observed that the breakthrough time of MB in sheep manure and almond shell was 904 min and 764 min respectively.However,compared with that in sawdust,the breakthrough time was 128 min.The breakthrough curve of sheep manure is very steep.This result convinces that the adsorption capacity of MB in manure was significantly important and indicates that the mass transfer coefficient decreased from sawdust to SMW.

Besides the concentration,gradients in batch systems are dissimilar than that of continuous flow system[29],the experimental results obtained using the batch systems appear difficult to apply to the processing of large volumes of water[30].Continuous adsorption experiments are mostly used in several applications in chemical engineering mainly in the adsorption of the components of a fluid flowing through a bed of a porous adsorbentmaterial.This adsorption process on porous solids can be divided into four stages.(a)Transport of the adsorbate from the bulk of the solution to the exterior film encircling the adsorbentmaterial(outer diffusion),(b)movementof the adsorbate through the external liquid film boundary layer to external surface sites of adsorbents,(c)migration of the adsorbate particles within the pores of the porous adsorbent by intraparticle diffusion(inter diffusion),(d)sorption ofadsorbate atinnerand outersurfaces ofthe adsorbent[31].

To provide more information about the adsorption process,the quantities of MB retained in the bed until the exhaustion time(qex),the height of the mass transfer zone(HMTZ),the fractional capacity(FC)and the percentage of saturation of the column(S)are determined.

Fig.1.Breakthrough curves representing MB adsorption onto IAS(circles),SMW(squares)and sawdust(triangles).

Table 1Adsorption capacity(q ex),fraction capacity(FC)and Height of mass transfer zone(H MTZ)for different adsorbents

The adsorption capacity at an exhaustion time(qex)is calculated according the Geankoplis model[32]:whereCtandC0are the MB ef fluent and inlet concentration(mg·L?1);Uis the flow rate(ml·min?1),mis the mass of adsorbent(g)andtexis the exhaustion time(min).The fractional capacity represents the quantity ofMB eliminated compared to the elimination capacity ofadsorbent in the mass transfer zone:

Eq.(3)represents the mass transferzone,which is the totalheightofthe adsorbent progressively being saturated.It can be expressed as:

whereHMTZis the heightof the mass transfer zone(cm);His the height of the fixed bed(cm),texis the exhaustion time(min);tbis the breakthrough time(min)and FC is the fractional capacity.

The percentage of saturation of bed column is calculated according to:

The adsorption capacities at exhaustion time(qex)follow the order sawdust＜IAS＜MSW and proves the results concluded from the breakthrough curves in Fig.1.The difference in the shapes of the breakthrough curves for three adsorbents can be explained by the internal diffusion of MB from the bulk liquid to the mesopores and than the micro pores which causes slower adsorption kinetics[31]However,the more particle size decreases,the more in fluence of the external film external mass transfer on the sorption becomes much more significant.The SMWhas a low in filtration rate compared to the IAS and sawdust(Fig.2).This means that the SMW has the lower permeability coefficient,which decreases with the particle sizes.In general,the particles with small sizes have small spaces between them and it is inversely proportional to the surface area.This can explain the tailing in the breakthrough curve(Fig.1).The particle size of materials and its in filtration kinetics are related and have the same effect on the adsorption capacity ofthe material.Indeed,large pores make more contribution to transfer water in porous media than small pores which are filled.This small pore entrapped water flow as a liquid transport through weakly conductive pore medium and it accedes in the form of films to solid particle.As the in filtration kinetic increases,the ability of a material to transfer water and solutes increases.The SMW has the lower in filtration rate(Fig.2)and inhibits the water to in filtrate in its porous space which makes more contact time between adsorbate and the solid surface of SMW.This high residence time can explain the length of breakthrough time(tbk=904 min).

During the dynamic contact of solid and liquid in bed column,the length and shape of the mass transfer zone(MTZ)provide insight about the performance of fixed bed columns.The area where the relative adsorbate concentration changes from 0.05 to 0.95 represents the region of MTZ where sorption practically takes place in fixed beds[33].The shape of the curve is used to determine the height of the mass transfer zone.If this height is small,this is indicated by the existence of faster kinetics and lower diffusion resistance in the sorption process.The height of MTZ value increases as MSW＜IAS＜sawdust(Table 1),thereby,the mass transfer efficiency has the opposite order,where SMW has the highest value.The same notes for fractional capacity.

Fig.2.Cumulative in filtration versus square root of time for IAS,SMW and sawdust.

3.2.The breakthrough curves modeling

To betterdescribe the fixed bed column and to predictthe MB breakthrough many models are used to fitthe experimentaldata.The analysis of breakthrough curves is done using four of these modes,viz.,Thomas model,Yoon Nelson model,Wolborska model and modified-dose–response model.

3.2.1.Thomas model

The Thomas model assumes that a Langmuir isotherm and second order kinetic fitted well the experimental data.It was also assumed that adsorption is limited by mass transfer with no axial dispersion derived with adsorption.It allows the calculation of the adsorption rate constant.The equation of the Thomas model can be described as:

wherekthis the Thomas rate constant(ml·min?1·mg?1),q0is the equilibrium adsorption capacity(mg·g?1),mis the mass of the adsorbent,C0andCtare the MB concentrations in the ef fluent and at timet(mg·L?1)and υ is the flow rate(ml·min?1).

The values ofkthandq0are determined using non-linear fitting and shown in Table 2.The correlation coefficient(R2)values ranging from0.89 to 0.95 and being higher for IAS.The adsorption capacity values obtained from this modelare compared with the experimentalcapacity,noting an error of 16%,37%and 11.8%for AS,SMW and sawdust,respectively.

Table 2Predicted parameters for,Thomas,Yoon Nelson,and Wolborska and Modified-dose response models for MB adsorption on IAS,SMW and sawdust materials

3.2.2.Yoon Nelson model

The Yoon Nelson model assumes that the rate of decrease in the probability of adsorption for each adsorbate molecule depends on the probability of adsorbate adsorption and the probability of an adsorbate breakthrough on the adsorbent[34].The model can be expressed by Eq.(6):

wherekYNis the Yoon Nelson rate constant(min?1)and τ is the time required for reach 50%adsorbate breakthrough(min).

The Yoon Nelson model is mathematically similar to the Thomas model as noted above.Therefore,the fitting results as shown in Table 2 were also good enough.For sawdust,the theoretical and experimental time required for 50%of adsorbate breakthrough corresponds accurately(average percentage errors＜2%).

3.2.3.Wolborska model

The model developed by Wolborska[35]is based on the application of equations of mass transfer for diffusion mechanisms used for the low concentration breakthrough curve.A simplified version is given by:

where β is the kinetic coefficientof the external mass transfer(h?1),N0is the exchange capacity(mg·L?1),B= βC0/N0;A= βZ/U.

This modelis applied in the description of the breakthrough curve in the range of low concentration.The values of the Wolborska model parameters for three adsorbents are presented in Table 2.For sawdust,compared to Thomas model and Yoon Nelson model,the Wolborska model is the worst and does not fit the breakthrough curve acceptably especially in the first region of BTC.The Wolborska model is valid only for the concentration region up to 30 mg·L?1.

3.2.4.Modified-dose–response model

The modified-dose–response model is also used to predict the breakthrough behavior in column adsorption.Mainly atloweror higher time periods of the breakthrough curve,the use of this model reduces the error resulting from the use of the Thomas model.The model equation is expressed as:

whereaandbare both the constant of the modified-dose–response model.

Modified dose–response modelwas also used to fitthe experimental data and the parameters of this model are also shown in Table 3.The values ofR2from modified dose–response(0.93–0.97)were larger than those from other models.Compared with the fitted curves(Fig.3)from the used models at same condition, fitted curve from modified dose–response model is closer to experimental curves.

For the models used to describe the experimental data,Modified dose–response model fitted the data from column experiments significantly better than other model for the first cycle,while in the second cycle this model cannot be applied in the fitting of SMW and it is the weakest model in the fitting of experimental data of sawdust.Thus,the modified dose–response is applied specially in the first part of breakthrough curve.

Fig.3.Experimental and predicted breakthrough curves for MB removal based on Thomas model(a),Yoon Nelson model(b),Wolborska model(c)and modified-dose response model(d)for adsorption of MB onto IAS(circles),SMW(squares)and sawdust(triangles).

3.3.Column regeneration

A potential and an effective adsorbent for dye removal must have a good adsorption capacity and have also a good desorption of dye.That is why,it is necessary to investigate the desorption of MB from IAS,SMW and sawdust.

The elution curve showed an asymmetric shape forthree adsorbents(Fig.4)which has a strong decrease at first tracking by a light decrease.The wide decrease is marked for sawdustwith an ef fluentconcentration of 1.2C/C0at the initial time,therefore in the first part of adsorption curve represent the majority of MB amount desorbed from bed.Unlike,IAS and SMWhas the maximumequalto 0.48C0and 0.12C0respectively and only SMW reached a negligible ef fluent concentration.As shown in Fig.4,the elution curve demonstrates the faster elution kinetic of sawdust compared to IAS and SMW,which need longer desorption time to reach low concentration and achieve null values.The desorption efficiency of three materials follows the order SMW＜IAS＜sawdust.

Fig.4.Elution curve for MB desorption from the three adsorbents fixed-beds:Experimental data,pseudo- first and pseudo second order modeling.

Lagergren's pseudo- first order[36]and pseudo-second order models[37]are represented by Eqs.(9)and(10),respectively,and were used in the present work to model the experimental data by nonlinear regression.

In these expressions,qandqesymbolize the dye adsorbed amount per mass unit of adsorbent,at timet,and at equilibrium,respectively,andk1andk2are the kinetic constants.The calculated correlation coefficient values for first order and second-order kinetics were found to be greater than 0.9,which shows the applicability of both these kinetic models(Fig.4).Thus both the present pseudo- first-order and pseudosecond order kinetic expressions were tested for its consistency in predicting the amount of dye desorbed for the entire time.

After desorption studies two cycles of adsorption are carried out and the breakthrough curves obtained for the adsorption desorption cycles are shown in Fig.5.The breakthrough curves for the first and second cycle have practically the same shape.A significant decrease of the breakthrough time(tbk)is observed from the first to the second cycle with reduction of the amount of MB sorbed per unit mass of adsorbent in the column.The decrease of breakthrough time can be caused by the losses ofdye particles during the elution step.The reduction ofsaturation of bed column from the first of the second cycle(Table 1)and the decrease of residence time caused by the increase of the external film massresistance atthe surface ofthe adsorbentsresultin a lowerremoval efficiency(Fig.6a)[38].

Contrary to desorption efficiency,the regeneration efficiency increases as SMW＜sawdust＜IAS(Fig.6b).The worst regeneration efficiency is obtained with SMW despite its high adsorption capacity compared to other adsorbent,due to the difficulty of desorbing from the micropores.

Fig.5.Breakthrough curves for MB column adsorption before and after regeneration on(a)IAS,(b)sawdust and(c)SMW.First adsorption cycle(empty symbol),second cycle after regeneration(full symbol).

4.Conclusions

Adsorption of MB in three different adsorbents,IAS,SMW and sawdust is studied in this work in a continuous fixed bed column,and the breakthrough curves and the adsorption parameters were determined.The adsorption capacity follows the order sawdust＜IAS＜MSW.Also,the sawdust has the largest mass transfer efficiency due to its high permeability and faster in filtration kinetic.Modified dose–response,Wolborska,Thomas and Yoon Nelson models were used to predict the breakthrough curves obtained from the experimental data.The four used models can be applied in the first part of the breakthrough curves,but modified dose–response is the best model in the first cycle and also the fit is the best for sawdust and IAS caused by the fast adsorption kinetics.Successive adsorption desorption cycle was carried out to evaluate the regenerability of three adsorbents.Adsorption capacity decreases after regeneration of all the adsorbents.IAS and sawdust represent the higher regenerability of 92%and 84%respectively.

Fig.6.Comparison column capacity before and after regeneration process and regeneration efficiency for IAS,SMW and sawdust.

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