S

B

SD

a

ARRAA

KNSIBRR

1

laet2dtaatttatwti

bvnd

0d

Ecological Engineering 37 (2011) 1589– 1594

Contents lists available at ScienceDirect

Ecological Engineering

j ourna l ho me page: www.elsev ier .com/ locate /eco leng

hort communication

iosorption of reactive dye by waste biomass of Nostoc linckia

harma Mona, Anubha Kaushik ∗, C.P. Kaushikepartment of Environmental Sci. and Engineering, Guru Jambheshwar University of Science & Technology, Hisar-125001, Haryana, India

r t i c l e i n f o

rticle history:eceived 1 February 2011eceived in revised form 28 March 2011ccepted 10 April 2011vailable online 12 May 2011

a b s t r a c t

Potential of spent biomass of a cyanobacterium, Nostoc linckia HA 46, from a hydrogen bioreactor wasstudied for biosorption of a textile dye, reactive red 198. The waste biomass was immobilized in calciumalginate and used for biosorption of the dye from aqueous solution using response surface methodology(RSM). Kinetics of the dye in aqueous solution was studied in batch mode. Interactive effects of initialdye concentration (100–500 mg/L), pH (2–6) and temperature (25–45 ◦C) on dye removal were examinedusing Box-Behnken design. Maximum adsorption capacity of the immobilized biomass was 93.5 mg/g

eywords:ostoc linckiapent biomassmmobilizationiosorptioneactive dye

at pH 2.0, initial concentration of 100 mg/L and 35 ◦C temperature, when 94% of the dye was removed.Fourier transform infrared (FT-IR) studies revealed that biosorption was mainly mediated by functionalgroups like hydroxyl, amide, carboxylate, methyl and methylene groups present on the cell surface.

© 2011 Elsevier B.V. All rights reserved.

od2afbelaiea

carbtaosp

SM

. Introduction

Dyes are used extensively in several industries, including textile,eather tanning, plastic, cosmetics, food processing, carpet, papernd pharmaceutical industries. Wastewaters containing dyes arextremely difficult to treat due to complex aromatic structure, syn-hetic origin and fade-resistant designing of the dyes (Celekli et al.,009). Reactive dyes with azo-based chromophores combined withifferent reactive groups are much in use in the textile industry, ashey can bind to textile fibers like cotton through covalent bondsnd are popular because of their bright color, simple applicationnd water-fast characteristics (Aksu and Tezer, 2005). About halfhe reactive dyes are reported to get lost in the effluent after dyeinghe fibers, which are highly resistant to removal by conventionalreatment methods, and about 90% remain unaffected even afterctivated sludge treatment (Pierce, 1994). The colored wastewa-ers not only influence the aesthetic acceptability of the receivingaters, but also influence aquatic life by hindering light penetra-

ion and disturbing the food chain organisms leading to ecologicalmbalance (Pearce et al., 2003).

In recent years, many microbial systems have been tried asiosorbents for removal of different types of dyes. Unlike con-

entional biosorbents, microbial biomass used as biosorbent doesot generate huge quantities of sludge (Robinson et al., 2001) andue to their genetic diversity, metabolic versatility and widespread

∗ Corresponding author. Tel.: +91 1662 263164; fax: +91 1662 277942.E-mail address: anubhakaushikes@gmail.com (A. Kaushik).

2

2

u

925-8574/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.ecoleng.2011.04.005

ccurrence, they are emerging as a viable alternative to reme-iate pollution problems caused by dyes (Ambrosio and Takaki,004). Several bacteria (Chen et al., 2003), fungi (Khalaf, 2008)nd algae (Celekli et al., 2009) have been used as biosorbentsor removal of reactive dyes from wastewaters, but reports oniosorption of reactive dyes by cyanobacteria are very few (Ertugrult al., 2008). Recently researchers have used various wastes, likeow-cost agro-wastes (Akar et al., 2009), Citrus sinensis (Asghernd Bhatti, 2010), fermentation waste of Corynebacterium glutam-cum (Vijayaraghavan and Yun, 2007) and Mentha arvensis (Hanift al., 2009), for biosorption of reactive dyes and heavy met-ls.

In the present study, we have utilized the waste biomass of ayanobacterium Nostoc linckia from a lab-scale hydrogen biore-ctor after its immobilization as a biosorbent for removal of theeactive dye RR 198. Kinetic behavior of the dye was studied inatch mode and response surface methodology (RSM) was usedo optimize the interacting process parameters (pH, temperaturend initial dye concentration) to achieve maximum biosorptionf the dye. FT-IR studies were carried out to understand theurface properties of the biosorbent involved in the biosorptionrocess.

. Materials and methods

.1. The organism

N. linckia HA-46, a hydrogen producing cyanobacterium, wassed in the present study. The source, identification and culturing

1 nginee

dp

2

lhoopddcbibt

2

owRd1(

2

rtpt(t(asud

R

A

wut

2m

rdtt

t

Y

wXe

oaIhm

Y

wfix

lppf(arfaetstc

2

aft4s

3

3

teo(3r

loca(Mu

590 S. Mona et al. / Ecological E

etails of the organism have been already described in our earlieraper (Mona et al., 2011).

.2. Preparation of biosorbent

Spent biomass of the cyanobacterium was collected from aab-scale hydrogen bioreactor, after 7 days, when the rates ofydrogen production declined substantially indicating exhaustionf cyanobacterial carbohydrates. The waste biomass was washed,ven-dried at 80 ◦C for 24 h, powdered and immobilized by sus-ending 0.1 g dry weight of the N. linckia biomass in 5 mL of doubleistilled water, mixed with 4% sodium alginate solution (w/v) andropped into 0.5 M calcium chloride solution using a syringe whenyanobacterial beads (3.0 ± 0.1 mm diameter) were formed. Theeads entrapping the cyanobacterium were kept overnight at 4 ◦C

n CaCl2 solution (0.5 M) followed by repeated washing with dou-le distilled water and were stored at 4 ◦C in distilled water prioro their use as the biosorbent.

.3. The dye (reactive red 198)

Commercially available reactive red 198 dye (RR 198) wasbtained from a local textile mill in India and was used as suchithout any purification (dye purity was approximately 80%).R 198 is one of the most representative and commonly usedyes for dyeing textile goods. A stock solution of reactive red-98 dye (1000 mg L−1) was prepared and desired concentrations100–500 mg/L) of the dye were obtained by further dilution.

.4. Batch studies

Kinetic studies for determining the optimum contact timeequired for maximum dye removal at different initial dye concen-rations (100, 300 and 500 mg/L) were conducted in batch mode atH 2.0. Prior to this, the optimum pH (2.0) for maximum adsorp-ion of the dye had been determined by shaking the dye solution100 mg/L) over a pH range (1.0–7.0) with immobilized cyanobac-erium in Erlenmeyer flasks on orbital shaker at 120 rpm for 2 hdata not shown). For kinetic studies samples were withdrawnt fixed time intervals from the flasks in triplicates and analyzedpectro-photometrically at 523 nm, the �max for RR 198, for resid-al dye concentration in the aqueous solution. Percent removal andye adsorption by the biosorbent were calculated as follows:

emoval of dye (%) = C0 − Ce

C0× 100 (1)

dsorption capacity (mg/g) = (C0 − Ce)VM

(2)

here C0 is the initial dye concentration (mg/L) and Ce is the resid-al concentration of the dye (mg/L) at different time intervals, V ishe volume (mL) and M is the mass of the biomass (g).

.5. Optimization of process parameters using response surfaceethodology (RSM) approach

The RSM approach was adopted in order to achieve best dyeemoval response from our biosorption system by experimenting atifferent combinations of the operating variables viz. pH, tempera-ure and initial dye concentration at the already optimized contactime.

RSM represents the independent process variables in this quan-itative form:

= f (X1, X2, X3, . . . , Xn) ± ε (3)

sgpo

ring 37 (2011) 1589– 1594

here Y is the amount of dye removed (%); f is response function, X1,2, X3,. . ., Xn are independent variables and ε is the experimentalrror.

Response surface was plotted from the expected responsebtained from the model, but since the value of f was unknown,

suitable lower order polynomial was used (Sharma et al., 2009).nstead of linear there was a curvature in the response, hence aigher-order polynomial, i.e. quadratic model, was used, whichay be stated in the form of the following equation:

= ˇo +∑

ˇixi +∑

ˇiixii2 +

∑ˇijxixj + ε (4)

here ˇo is the constant, ˇi the slope or linear effect of the inputactor xi, and ˇij the linear by linear interaction effect between thenput factor xi and xj and ˇij is the quadratic effect of input factori (Benyounis et al., 2005).

Box-Behnken model of RSM was used in the study with twoevels (the minimum and the maximum) for each of the threearameters. For calculation of 10 coefficients of second-orderolynomial equation 17 experiments are required to be per-ormed. In the experimental design model, initial dye concentration100–500 mg/L), pH (2–6) and temperature (25–45 ◦C), were takens input variables and percent dye removal was taken as theesponse of the system. The experimental design matrix derivedrom the Box-Behnken model is shown in Table 1. Both estimatednd actual adsorption of the RR 198 dye by the biosorbent in differ-nt experimental conditions of the model has also been shown inhe same table. Each run was performed in triplicate and the tablehows the mean values for % biosorption. The data were subjectedo analysis of variance and the coefficient of regression (R2) wasalculated to find out the goodness of fit of the model.

.6. Fourier transform infrared (FT-IR) study

The FT-IR spectra of the cyanobacterium before and afterdsorption of RR 198 were obtained using the KBr disk techniqueollowing the procedure outlined by Aravindhan et al. (2007). Theransmission FT-IR spectra were then recorded between 400 and000 cm−1 using Perkin-Elmer, Model Spectrum BX Series FT-IRystem.

. Results and discussion

.1. Biosorption kinetics

Kinetics of biosorption of the dye at different initial concentra-ions (100, 300 and 500 mg/L) showed that the at all concentrationsquilibrium was obtained at 120 min showing 74–78% removalf the reactive dye (data not shown). The adsorption capacitymg/g) of the cyanobacterial beads was found to be 74.2, 259.1 and44.4 mg/g at initial dye concentrations of 100, 300 and 500 mg/L,espectively as shown in Table 2.

In the present study, the adsorption of RR 198 on immobilized N.inckia was analyzed using two simple kinetic models, pseudo first-rder and pseudo second-order models. Assuming the biosorptionapacity for reactive red 198 to be proportional to the number ofctive sites on the cyanobacterial beads, Lagergren rate equationLagergren, 1898) and pseudo second order rate equation (Ho and

cKay, 1999) were applied as described by Celekli et al. (2009) tonderstand the adsorption of the dye as a function of time.

Though a linear relationship of log(qe − qt) versus t was obtained

uggesting the applicability of this model, but the first order Lager-ren equation is generally applicable only during the initial rapidhase of adsorption (Aravindhan et al., 2007). The pseudo secondrder model, on the other hand, better described the kinetics of RR

S. Mona et al. / Ecological Engineering 37 (2011) 1589– 1594 1591

Table 1Box-Behnken design matrix for three variables showing observed and predicted response for dye removal along with adsorption capacity of cyanobacterial beads.

Experimental run pH Temperature (◦C) Initial dyeconcentration(mg L−1)

Response %removal of dye(observed)

Response %removal of dye(predicted)

Adsorptioncapacity (mg/g)

1 2 25 300 91.30 91.6 273.82 6 25 300 39.65 39.4 118.83 2 45 300 57.86 58.14 173.64 6 45 300 41.80 41.42 125.55 2 35 100 93.90 93.2 93.56 6 35 100 66.89 66.9 66.67 2 35 500 84.32 84.4 422.58 6 35 500 40.98 41.68 204.99 4 25 100 61.20 61.52 61.3

10 4 45 100 48.60 49.0 48.611 4 25 500 48.20 47.8 242.112 4 45 500 29.10 28.8 145.313 4 35 300 58.0 58.06 174.114 4 35 300 58.60 58.06 175.515 4 35 300 58.0 58.06 174.216 4 35 300 57.60 58.06 172.917 4 35 300 58.10 58.06 174.2

ANOVA for the RSM model: Fmodel = 1567.55 (P < 0.0001, df = 9); Flack of fit = 5.23 (P > 0.05, df = 3) R2 = 0.9995 (P < 0.001, df = 16).

Table 2Kinetic model parameters for dye adsorption on algal beads at different initial RR 198 dye concentrations (at temperature 25 ◦C, pH 2.0 and 120 rpm).

Initial dyeconcentration (mg/L)

Experimetal qe (mg/g) First-order model Second-order model

Theoretical qe (mg/g) k1 (min−1) R2 Theoretical qe (mg/g) k2 (g mg−1 min−1) R2

100 74.2 59.9.7 0.027 0.817 75.3 0.0128 0.9970.040.03

1vcsiomwigtobs

3

ic

Y

wvcmFi

efi

ciiv

smmT2atactcapoamlvifotCl

300 259.1 238.7

500 344.4 319.9

98 adsorption on immobilized N. linckia as the linear plot of t/qersus t showed better fitness of data at different initial dye con-entrations as compared to the pseudo first order plot (Figs. nothown). The values of k1, k2 and qe calculated from the slope andntercept of the plots are given in Table 2 and the theoretical valuesf qe obtained from the graph have been compared with experi-ental values of qe. The values of qe for the first order kinetic modelere not equal or approaching the experimental value, thus dimin-

shing the validity of this model for the present system. However,ood agreement was observed between calculated and experimen-al values of qe, from second order kinetic model with high valuesf R2 (Table 2). The behavior of the dye biosorption by the spentiomass was comparable to that reported with fresh biomass ofome algae for removal of dyes (Mohan et al., 2003).

.2. Response surface quadratic model

The quadratic model consisting of 12 trials plus 5-centre pointsnvolving three parameters viz, temperature, pH and initial dyeoncentration gives the predicted response, Y as follows:

= +58.06 − 17.26A − 7.8B − 8.50C + 12.17A2 − 12.58B2

+ 1.29C2 + 8.90AB − 4.08AC − 1.63BC (5)

here Y is the predicted response and A, B and C are the codedalues of the test variables, pH, temperature (◦C) and initial dyeoncentration (mg/L), respectively. Statistical significance of theodel was checked by Analysis of Variance (ANOVA) and the

-values along with determination coefficient (R2) have been

ncluded as a foot note of Table 1.

The model was found to be highly significant (P < 0.0001), asvident from the value of FModel. Goodness of the biosorption datatted to the model was verified by computing the determination

dat3

1 0.827 261.3 0.0136 0.9972 0.857 349.5 0.0159 0.998

oefficient R2 (0.9995), which indicated that 99% of total variationsn dye degradation could be explained by the model. A non signif-cant F value for the Lack-of-fit test further verified the statisticalalidity of the quadratic model.

The regression equations of the model are graphically repre-ented as three-dimensional response surface plots (Fig. 1a–c). Theain goal of response surface is to track efficiently for the opti-um values of the variables such that the response is maximized.

here was a sharp decline in biosorption rate as pH increased from.0 to 6.0 (Fig. 1a), showing that removal of the dye is favored incidic environment. Reactive dyes have negative electrical struc-ure of the chromophore group (Ozer et al., 2005), and therefore,t low pH there is greater electrostatic attraction to the positivelyharged surface, leading to more biosorption of the dye. Further,he sulphonic groups present in the RR 198 dye possess negativeharge at higher acidity of the solution, because their pka valuesre lower than zero (Lima et al., 2008). With increasing pH, theositively charged sites decline leading to a drop off in bindingf dyes to the cell surface (O’Mohany et al., 2002). Hydrogen ionlso acts as a bridging ligand between the cell wall and the dyeolecule (Aksu and Tezer, 2005), thus favoring dye biosorption at

ower pH. Biosorption rate increased as the temperature was ele-ated from 25 to 32.5 ◦C followed by a decline thereafter (Fig. 1a)ndicating increased affinity of the binding sites on the biomassor the dye with rise in temperature up to 32.5 ◦C. A similar trendf initial increase followed by decline in biosorption with risingemperatures was observed for biosorption of reactive dyes byhlorella vulgaris (Aksu and Tezer, 2005), where decline in equi-

ibrium uptake of the dye at high temperatures was interpreted as

ue to exothermic nature of the process. Interactive effects of pHnd temperature may be seen in the 3-D plot Fig. 1(a). Removal ofhe dye between pH 2 and 4 increases with rise in temperature up to2.5 ◦C followed by a decline thereafter. But, at higher pH (5–6), dye

1592 S. Mona et al. / Ecological Engineering 37 (2011) 1589– 1594

36.250.464.678.893.1

2.00

3.00

4.00

5.00

6.00

100.00

200.00

300.00

400.00

500.00

pHIni �al dye Con c.

(mg/L)

36.250.464.678.893.1

2.00

3.00

4.00

5.00

6.00

25.00

30.00

35.00

40.00

45.00

pHTemperature (˚C)

a b

cTemperature (˚C)

36.250.464.678.893.1

25.00

30.00

35.00

40.00

45.00

100.00

200.00

300.00

400.00

500.00

Ini�al dye Conc.

(mg/L)

% Removal of dye

Removal of dye

Removal of dye

F d pH (d

rtt(arir(prlCmdctFawfoopit

pnwtwwttttoaStbb

3

b

ig. 1. Three-dimensional response surface plot for (a) the effect of temperature anye concentration on decolorization of reactive red 198 dye.

emoval is favored at high temperature of 45 ◦C. Initial dye concen-rations provide an important driving force to overcome all massransfer resistance of dye between the aqueous and solid phasesAravindhan et al., 2007; Marungrueng and Pavasant, 2006). Thedsorption of RR 198 at different initial dye concentrations withespect to varying pH is shown in Fig. 1(b). It was observed thatncreasing initial dye concentration significantly decreased dyeemoval and the decline was more prominent at higher pH range5–6), which could be due to greater toxicity of the dye at higherH. Reduced dye removal at higher concentration has also beeneported for other microbial biosorbents such as Caulerpa scalpel-iformis for basic yellow dye (Marungrueng and Pavasant, 2006),. vulgaris for reactive dyes (Aksu and Tezer, 2005) and Spirogyraajuscule for reactive red 120 (Celekli et al., 2009), which might be

ue to some inhibitory effects caused due to toxicity of dye at higheroncentrations (Korbahti and Rauf, 2008). The interactive effects ofemperature and initial dye concentration are shown in Fig. 1(c).or all initial concentrations, maximum dye removal took placet 32.5 ◦C. At higher temperature of 45 ◦C, however, dye removalas more adversely affected as initial dye concentration increased

rom 100 to 500 mg/L. Since various functional groups are presentn the cell surface and they are influenced by temperature, pH and

ther factors, it becomes difficult to explain clearly the adsorptionrocess with respect to a single factor (Tien, 2002). Hence, overall

nteractive effects of various factors were considered to determinehe dye removal response.

lwiv

b) effect of initial dye concentration and pH (c) the effect of temperature and initial

The optimum values of the variables can be analyzed by saddleoint or by checking the maxima formed by the X and Y coordi-ates. The conditions obtained at the saddle point for best responseere temperature range of 25–35 ◦C, pH 2 and initial dye concen-

ration 100–300 mg L−1, when 91–94% color removal was achieved,hile 85% removal was observed when initial dye concentrationas 500 mg/L. Under respective optimal combinations of pH and

emperature, adsorption capacities of the biosorbent were foundo be 93.5, 273.8 and 442.5 mg/g at 100, 300 and 500 mg/L ini-ial dye concentrations, respectively (Table 1), which are higherhan the adsorption capacities of the biosorbent achieved basedn kinetic studies (Table 2). Thus, optimization of multiple inter-cting factors seems useful in improving the biosorption process.ince the dye concentration reported in the wastewaters of tex-ile mills is up to 100 mg/L, pH 2.0 and 35 ◦C temperature woulde suitable for the removal of the dye using N. linckia wasteiomass.

.3. Surface characterization of the biosorbent by FT-IR

Vibrational spectra of N. linckia biomass before and after dyeiosorption are illustrated in Fig. 2, both of which show a simi-

ar pattern. However, shifting and intensification in some peaksere observed after dye loading. The broad peak at 3318.19 shift-

ng to 3407.7 cm−1, suggests overlap of O–H and N–H stretchingibrations, indicating the presence of both surface free hydroxyl

S. Mona et al. / Ecological Enginee

FR

g22gTvobv(biirogtmtrs

4

udiaTacaBfbf

ce

A

Rs

R

A

A

A

A

A

B

B

C

C

C

D

E

H

H

K

K

L

L

M

M

M

O

O

P

ig. 2. The FT-IR spectra of N. linckia biomass (A) before and (B) after adsorption ofR 198.

roups and chemisorbed water on the biosorbent (Sari and Tuzen,008). The shifting and intensification of peaks from 2925.49 to927.03 cm−1 indicates C–H symmetric stretch of the methyleneroups (–CH2) and deformation vibration of methyl groups (–CH3).he peak at 1654.86 cm−1 may be attributed to C O stretchingibration of carboxylate (–COO–) or N–H deformation vibrationf amide I groups. The peaks at 1250.34 and 1155.24 cm−1, visi-le mainly on dye loaded biomass are due to the C–O stretchingibration of ketones, aldehydes and lactones or carboxyl groupsChandrasekhar and Pramada, 2006). Thus, amide, hydroxy, car-oxylate, C–O, methyl and methylene groups seem to participate

n RR 198 biosorption on the surface of Nostoc, causing shiftsn wave numbers, due to change in bonding energy in the cor-esponding functional groups (Balaria and Schiewer, 2008). Lackf any distinct new peaks or major shift after dye loading sug-ested little likelihood of any biodegradation of the dye duringhe biosorption process (Daneshvar et al., 2007). Since degradation

etabolites of reactive dyes have usually been reported to be toxic,he present system that does not seem to involve degradation of theeactive dye would be safe for removal of the dye from aqueousystem.

. Conclusions

Spent biomass of N. linckia from hydrogen bioreactor provedseful for biosorption of the toxic RR 198 dye. The Box-Behnkenesign of RSM allowed optimization of three important interact-

ng parameters and 94% of the dye could be removed at pH 2.0nd 35 ◦C temperature when initial concentration was 100 mg/L.he response surface quadratic model involving multiple inter-cting parameters made it possible to improve the adsorptionapacity (qe) of the biosorbent as compared to the maximumdsorption capacity obtained by using simple kinetic models.

iosorption capacity of waste biomass of the cyanobacterium was

ound comparable to that of fresh biomass of some other micro-ial systems indicating that the biomass waste of cyanobacteriumrom hydrogen bioreactors instead of being dumped could be effi-

P

R

ring 37 (2011) 1589– 1594 1593

iently utilized for removal of toxic reactive dyes from textileffluents.

cknowledgement

Financial support by the Council of Scientific and Industrialesearch (CSIR), New Delhi, to Ms. Mona Sharma in the form ofenior research fellowship (SRF) is gratefully acknowledged.

eferences

kar, S.T., Ozcan, A.S., Akar, T., Ozcan, A., Kaynak, Z., 2009. Biosorption of a reactivetextile dye from aqueous solutions utilizing an agro-waste. Desalination 249,757–761.

ksu, Z., Tezer, S., 2005. Biosorption of reactive dyes on the green alga Chlorellavulgaris. Process Biochem. 40, 1347–1361.

mbrosio, S.T., Takaki, G.M.C., 2004. Decolorization of reactive azo dyes by Cunning-hamella elegans UCP 542 under co-metabolic conditions. Bioresour. Technol. 91,69–75.

ravindhan, R., Rao, J.R., Nair, B.U., 2007. Removal of basic yellow dye from aqueoussolution by sorption on green alga Caulerpa scalpelliformis. J. Hazard. Mater. 142,68–76.

sgher, M., Bhatti, H.N., 2010. Mechanistic and kinetic evaluation immobilized andchemically treated. Ecol. Eng. 36, 1660–1665.

alaria, A., Schiewer, S., 2008. Assessment of biosorption mechanism for Pb bindingby citrus pectin. Sep. Purif. Technol. 63, 577–581.

enyounis, K.Y., Olabi, A.G., Hashmi, M.S.J., 2005. Effect of laser welding parame-ters on the heat input and weld-bead profile. J. Mater. Proc. Technol. 164/165,978–985.

elekli, A., Yavuzatmaca, M., Bozkurt, H., 2009. Kinetics and equilibrium studies onthe adsorption of reactive red 120 from aqueous solution on Spirogyra majuscule.Chem. Eng. J. 152, 139–145.

handrasekhar, S., Pramada, P.N., 2006. Rice husk ash as an adsorbent for methyleneblue-effect of ashing temperature. Adsorption 12, 27–43.

hen, K.C., Wu, J.Y., Huang, C.C., Liang, Y.M., Hwang, S.C.J., 2003. Decoloriza-tion of azo dye using PVA-immobilized microorganisms. J. Biotechnol. 101,241–252.

aneshvar, N., Ayazloo, M., Khataee, A.R., Pourhassan, M., 2007. Biological decol-orization of dye solution containing malachite green by microalgae cosmariumsp. Bioresour. Technol. 98, 1176–1182.

rtugrul, S., Bakır, M., Dönmez, G., 2008. Treatment of dye-rich wastewater by animmobilized thermophilic cyanobacterial strain: Phormidium sp. Ecol. Eng. 32(3), 244–248.

anif, A., Bhatti, H.N., Hanif, M.A., 2009. Removal and recovery of Cu(II) and Zn(II)using immobilized Mentha arvensis distillation waste biomass. Ecol. Eng. 35,1427–1434.

o, Y.S., McKay, G., 1999. Pseudo second-order model for sorption processes. ProcessBiochem. 34, 451–465.

halaf, M.A., 2008. Biosorption of reactive dye from textile wastewater by non-viable biomass of Aspergillus niger and Spirogyra sp. Bioresour. Technol. 99,6631–6634.

orbahti, B.K., Rauf, M.A., 2008. Application of response surface analysisto the photolytic degradation of basic red 2 dye. Chem. Eng. J. 138,166–171.

agergren, S., 1898. Zur theorie der sogenannten adsorption geloster stoffe. KungligaSvenska Vetenskapsakademiens, Handlingar 24, 1–39.

ima, E.C., Royer, B., Vaghetti, C.P., Simon, S.N., Cunha, B.M., Pavan, F.A., Ben-venutti, E.V., Cataluna-Veses, R., Airoldi, C., 2008. Application of Brazilianpine-fruit shell as a biosorbent to removal of reactive red 194 textile dyefrom aqueous solution kinetics and equilibrium study. J. Hazard. Mater. 155,536–550.

arungrueng, K., Pavasant, P., 2006. Removal of basic dye (Astrazon Blue FGRL)using macroalga Caulerpa lentillifera. J. Environ. Manag. 78, 268–274.

ohan, S.V., Bhaskar, Y.V., Karthikeyan, J., 2003. Biological decolorization of simu-lated azo dye in aqueous phase by algae Spirogyra species. Int. J. Environ. Pollut.21, 211–222.

ona, S., Kaushik, A., Kaushik, C.P., 2011. Hydrogen production and metal–dyebioremoval by a Nostoc linckia strain isolated from textile mill oxidation pond.Bioresour. Technol. 102, 3200–3205.

’Mohany, T., Guibal, E., Tobin, J.M., 2002. Reactive dye biosorption by Rhizopusarrhizus biomass. Enz. Microb. Technol. 31, 456–463.

zer, A., Akkaya, G., Turabik, M., 2005. Biosorption of acid red 274 on Enteromorphaprolifera in a batch system. J. Hazard. Mater. 126, 119–127.

earce, C.I., Lloyd, J.R., Guthric, J.T., 2003. The removal of colour from textile wastew-ater using whole bacterial cell: a review. Dyes Pigments 58, 179–196.

ierce, J., 1994. Colour in textile effluents-the origins of the problem. J. Soc. DyersColour 110, 131–134.

obinson, T., Mcmullan, Marchant, R., Nigam, P., 2001. Remediation of dyes in textileeffluent: a critical review on current treatment technologies with a proposedalternative. Bioresour. Technol. 77, 247–255.

1 nginee

S

S

Tien, C.-J., 2002. Biosorption of metal ions by freshwater algae with different surface

594 S. Mona et al. / Ecological E

ari, A., Tuzen, M., 2008. Biosorption of cadmium(II) from aqueous solution by red

algae (Ceramium virgatum): equilibrium, kinetic and thermodynamic studies. J.Hazard. Mater. 157, 448–454.

harma, P., Singh, L., Dilbaghi, N., 2009. Optimization of process variables for decol-orization of Disperse Yellow 211 by Bacillus subtilis using Box-Behnken design.J. Hazard. Mater. 164, 1024–1029.

V

ring 37 (2011) 1589– 1594

characteristics. Process Biochem. 38, 605–613.ijayaraghavan, K., Yun, Y.S., 2007. Utilization of fermentation waste (Corynebac-

terium glutamicum) for biosorption of reactive black 5 from aqueous solution. J.Hazard. Mater. 141, 45–52.