1. technology and computing

Mozambique Tilapia Fish Scales as Potential Biosorbent for Zn
and Pb Ions Removal: Kinetic and Isotherm Studies
N. Othman*, A. Abd-Kadir* and N. Zayadi*
'Mircopollutant Research Centre, Faculty of Civil and Environmental Engineering, University Tun Hussein Onn
Malaysia
(E-mail: nor:[email protected], aesiina@~ithm.edu.my,[email protected])
Abstract
The toxicity and presence of heavy metals in wastewater pose environmental-disposal problems because of
their non-biodegradability and persistence in the environment. Heavy metals in wastewater were removed by
using physical, chemical and biological treatment. Biosorption is one of the biological treatments emerging
as an alternative environmental friendly technology for the removal of metal ions from aqueous solutions.
The present study reports the use of Mozambique Tilapia (MTilapia) fish scales to remove zinc (Zn) and
plumhum (Pb) ions in wastewater. The characteristics of the fish scales were studied by X-ray fluorescence
(XW) spectroscopy, scanning electron microscopy (SEM), and Fourier-transform infrared (FTIR)
spectroscopy analyses before and after biosorption. XRF analysis before biosorption showed the presence of
calcium oxide, which confirmed the high-efficiency biosorption of Zn and Pb ions. SEM analysis revealed
bright bulky particles that indicated the presence of Zn and Pb ions. FTIR analysis verified that the carbonyl,
nitro, and amine groups in the absorbent played important roles in the reduction of Zn and Pb ions. The
results also show that optimum condition of Zn ion was best selected in domestic wastewater. Langmuir and
pseudo-second-order models exhibited the best fit data for isotherm and kinetic study. All these results
indicated that biosorption using M.Tiiapia fish scales is a promising method of removing Zn and Pb ions
from domestic wastewater.
Keywords
Biosorption, fish scale, Pb, M.Tilapia, Zn
1. INTRODUCTION
Zn and Pb ions are highly toxic and cumulative. Once in the environment, they are persistent and
can adversely affect human health. The presence of heavy metals in the environment especially in
water bodies is of extreme concern to the public, governments, and industries. Therefore, the
removal of heavy metals from wastewater has become one of the most concern environmental
issues (Nadeem et al., 2008a). Various methods are used to treat metal-containing wastewater, such
as ion exchange, electrodialysis, chemical precipitation, and reverse osmosis. The major
disadvantages of the employed methods namely, incomplete metal removal, high cost, and
production of toxic sludge that require safe disposal (Veglio and Beolchini, 1997).
In recent years, biosorption has emerged as an economic and eco-friendly option. Biosorption
involves the use of certain types of inactive or non-living microbial biomass that bind and
concentrate heavy metals from even low concentration of aqueous solutions (Volesky, 1990a). This
technique is a non-polluting process, easy to operate, and highly efficient in treating wastewater
containing low metal concentrations (Febrianto et al., 2009). Numbers of waste namely palm shell,
cork biomass, citrus peel were used in removing heavy metals (Chubar et al., 2004; Balaria and
Shiewer, 2008).
The scales of a number of fishes, namely, Labeo, Rohita, Catla catla, Atlantic cod, and Mtilapia
have been reported to give promising biosorption results worldwide (Zayadi and Othman, 2013a;
Zayadi and Othman ,2013b; Othman and Invan, 2011; Srividya and Mohanty, 2009; Nadeem et al.,
2008b; Rahaman et al, 2008). In the present work, A4 tilapia fish scales that are generally
considered as waste products were used as biosorbent for removing Zn and Pb ions from wastewater.
Focus was given on wastewater, adsorbent characterization and optimization, as well as kinetic and
sorption isothermal modeling.
2. MATERIALS AND METHODS
Preparation of biosorbent
Waste M .ilapia fish scales were obtained from the fish market at Parit Raja, Batu Pahat. The fish
scales were soaked in 15% nitric acid for 24 h to remove any adhering dust and soluble impurity.
The scales were further soaked and washed with distilled water until neutral pH and then dried in an
oven at 60 "C until constant weight. The dried scales were ground with a mortar grinder and the
pulverized scales were sieved to attain 150 pm particle size (Srividya et al., 2009; Sheikh and
Sweileh, 2008).
Preparation of stock solutions
Zn and Pb ion solutions were prepared by dissolving 0.440 g of zinc sulfate and 0.160 g of lead (11)
nitrate in 100 ml of ultrapure water to produce a 1000 mg/L solution each. The aqueous solutions
were then diluted from 1000 mg/L to desired concentration for kinetic and isotherm study. All
reagents used in this study were analytical grade.
Experimental design
Domestic wastewater samples were taken directly from the wastewater treatment plant located at
Tun Fatimah hostel in University Tun Hussein Onn, Batu Pahat. Sample of wastewater were
collected in the morning during peak flow, over dry season and active semester. The collected
samples were analyzed by Inductively Coupled Plasma-Mass Spectrometer (ICP-MS). Table 1
presents biosorbent dosage, contact time, and pH that were adopted from batch experiment in
previous study by Zayadi and Othman (2013b). The samples were shaken at 125 rpm and a constant
room temperature. Characterization of biosorbent was done using SEM, XRF, and FTIR analyses
Table 1. Working range of Zn and Pb ions in domestic wastewater.
Biosorbent dosage
Heavy metals
pH
(8)
'Ontact
time (hr)
Zn
6
0.02
3
Initial metal ion
concentration ( p g / ~ )
9.771 - 11.117
Tables 2 and 3 are working ranges of Zn and Pb ions for kinetic and isotherm studies respectively.
The correlation coefficient R' for both models was obtained using Microsoft Office Excel 2010
software.
Table 2. Kinetic Modeling.
Heavy metals
PH
Biosorbent dosage (g)
Concentration of heavy metal (pg/L)
Contact time- kinetic study (min)
Zn
Pb
6
0.02
10
5 to 300
5.5
0.001
0.3
5 to 300
Table 3. Isotherm Modeling.
Heavy metals
PH
Biosorbent dosage (g)
Contact time(hr)
Concentration of heavy metal isotherm study (pg/L)
Zn
Pb
6
0.02
3
5.5
0.001
2
10 to 17
0.3 to 1
Data analysis of biosorption efficiency
Zn and Pb ion uptake were calculated through the concentration difference method (Zayadi and
Othman, 2013b). The sorption percentage and uptake capacity of Zn and Pb ions were determined
using Eqs. (1) and (2):
Sorption (%) = [(Co - Cf) /Co] x 100
(1)
where Co is the initial metal concentration (pg1L) and Cf is the final metal concentration (pg1L).
q=(Co-Cf) (VIM)
(2)
where q is the metal uptake (pglg), Co is the initial metal concentrations in solution (pgll), Cf is the
final metal concentrations in solution (pgll), V is the volume of solution (I), and m is the mass of
biosorbent (g).
3. RESULTS AND DISCUSSION
Characteristic of fish scales
Previous studies reported that most part of fish has natural ability to concentrate metals or pollutants
in water. Fish is one of the most vulnerable to toxic substances present in water compare to other
water dwellers (Alibabic' et al., 2007).
Table 4 shows the presence of chemical compounds such as iron oxide (FeO) and Pb oxide (PbO)
of untreated fish scales through XRF analysis (Zayadi and Othman, 2013a; Zayadi and Othman,
2013b). The presence of FeO and PbO prove that fish scales has natural ability to concentrate
metals in water. The results of XRF analysis in Table 5 clearly shows the absence of FeO and PbO
after chemical pretreatment with nitric acid. A clean biosorbent is important to enhance the
efficiency of biosorption process. Among various chemical modification methods, chemical
pretreatment with diluted acid has been selected due to its simplicity and efficiency. Acid-washing
can removes the mineral elements and improves the hydrophilic nature of surface (Bhatnagar et al.,
2013). Tables 4 and 5 also demonstrate calcium oxide, (CaO) as the highest chemical compound in
biosorbent. The presence of CaO is important as it confirms the high potential and efficiency of
Mtilapia fish scales in adsorbing heavy metals (Qaiser et al., 2009).
Table 4. Chemical Composition and Concentration of Untreated Fish Scales
Formula
Concentration
Original (g)
7
Added (g)
c02
CaO
p205
so3
Table 5. Chemical Composition and Concentration of Treated Fish Scales.
Formula
Concentration
Original (g)
7
Added (g)
3
co2
0.10%
CaO
63.80%
p205
32.40%
so3
2.64Yo
MgO
0.24%
Si02
0.24%
Na2O
0.21%
SrO
0.17%
The FTIR Spectroscopy was used to identify the vibration characteristics of functional groups
present on biosorbent surfaces (Srividya & Mohanty, 2009). Figure 1 shows FTIR spectra of native
and metals loaded fish scale with the working range of 600-4000 cm-'. The biosorbent
characterization proved the involvement of carbonyl group (carboxylic acid, ketone, and aldehyde),
nitro compound, and amine group in the biosorption of Zn and Pb ions on Mtilapia fish scales. Ion
exchange might be responsible as mechanism of biosorption in this study (Pavia et al., 2009;
Nadeem et al., 2008).
Wave number (cm-1)
Figure 1. (a) FTIR spectra of native biosorbent, (b)FTIR spectra of Zn ion loaded biosorbent, (c)
FTIR spectra of Pb ion loaded biosorbent
SEM analysis of native biosorbent shows high contain of white region that indicates the present of
calcium and phosphorus (Figure 2). Figure 3 represents the micrograph of heavy metal ions loaded
with biosorbent that indicates SEM images contains shiny and bulky particles. This results agree
well with previous study by Srividya and Mohanty ( 2009) that revealed the shiny particle as heavy
metals loaded onto biosorbent surface..
Scale
~ebiosorbent)
Figure 3. SEM Micrograph of Mtilapia Scale (Heavy, metal loaded biosorbent).
Efficiency of fish scales in domestic wastewater
Domestic wastewater was used to determine the efficiency of fish scales in removing heavy metals.
Table 6 and 7 show removal and metal uptake of Pb and Zn ions under optimum condition of Pb
and Zn ions respectively. The highest removal of Zn and Pb ion were achieved at optimum
conditions of Zn ion with the removal 85.41 % and 78.29 %, respectively. Less adsorption occurred
in the actual wastewater sample compared to synthetic solutions due to the presence of other metals.
Other pollutants in wastewater such as organic micropollutants also impede the removal of
inorganic heavy metals (Barakat, 201 1).
Table 6. Removal and metal uptake of Pb and Zn ion under optimum condition of Pb ion.
Heavy
Removal (%)
Metal uptake (pg/g)
metal
Plumbum
77.30 - 82.21
23.100 - 26.900
Zinc
66.83 - 68.47
669.033 - 742.967
Table 7. Removal and metal uptake of Zn and Pb and ions under optimum condition of Zn ion.
Metal uptake (pglg)
Heavy metal Removal (%)
Zinc
82.01 - 85.41
41.358 -46.000
Plumbum
75.29 - 78.29
1.100- 1.310
Kinetic modeling
The experimental data were applied in kinetic models to ensure applicability of the treatment
method for application of adsorption and design of the batch reactor. The sorption kinetics is
significant to understand the control mechanism of Zn and Pb ion biosorption by Mtilapia fish
scales and the potential rate-limiting steps (e.g., mass transport and chemical reactions). This
models is important for scale-up optimization process in which it describe the behaviour of a batch
biosorption process operated under various experimental conditions (Gupta et al., 2001; Zafar et
al., 2007).
In this study, two kinetic models were used namely, pseudo-first-order Lagergren and pseudosecond-order models (Lagergern, 1898; Ho and Mckay, 2000; Mohd-Kamil, 2013). The former
assumes that metal sorption is first order in nature because it depends only on the number of metal
ions present at a specific time in solution. The latter model works well only in a region where
biosorption rapidly occurs (Lagergern, 1898).The pseudo-first-order Lagergren is presented as:
Log (qe - qr) = log q,
- (Ktt /
2.303)
(3)
where KI (mid1) is the rate constant of the pseudo-first-order adsorption model, and q, and q, (mg g') are the amounts of metal ions adsorbed onto biosorbent at equilibrium and at any time t (min),
respectively. q, and Kt can be calculated from the slope and intercept of the plot of log (qe - q,)
versus t.
In contrast to the pseudo-first-order kinetic model, the pseudo-second-order kinetic model assumes
that metal biosorption depends on the number of metal ions present in solution and the free
biosorption sites on the biosorbent surface (Ho and Mckay, 2000). The pseudo-second-order model
is expressed as:
where KZ is the rate constant of the pseudo-second-order biosorption model (g mg-' mid'). q, and
KZcan be calculated from the slope and intercept of the plot of tlq versus t.
To calculate these rate constants, the Lagergren and pseudo-first-order equations are plotted in
Figures 4 and 5 for Zn and Pb ions, respectively.
I
I
Figure 4. Linearized pseudo-first order kinetic model of Zn ion.
I
I
Figure 5. Linearized pseudo-first order kinetic model of Pb ion.
Meanwhile, Figures 6 and 7 show the plot of tlq, versus t of the pseudo-second-order kinetic model
for Zn and Pb ions, respectively. The reaction rate constants and correlation coefficients of pseudofirst-order are shown in Table 8, and the pseudo-second-order parameters are listed in Table 9.
I
I
Figure 6. Pseudo second-order kinetic model of Zn ion.
I
I
Figure 7. Pseudo second-order kinetic model of Pb ion.
Table 8. Pseudo-first order.
Pseudo-first order
Zn
Pb
Table 9. Pseudo-second order.
Pseudo-second order
Zn
Pb
A comparison between pseudo-first-order and pseudo-second-order kinetic parameters (Tables 6
and 7) suggested that the biosorption of Zn and Pb ions on fish scales followed pseudo-secondorder kinetics rather than pseudo-first-order kinetics because q, obtained from the pseudo-secondorder kinetic model closely agreed with the experimental value q,, whereas q computed from the
pseudo-first-order kinetic model did not agree with q,,. This finding indicated that pseudo-firstorder kinetics may be insuficient for interpreting the mechanism of Zn and Pb ion biosorption
(Deng et al., 2006). The correlation coefficient @ of the second-order kinetic model was closer to 1
than that of the first-order model. Both factors suggested that the sorption of Zn and Pb ions
followed the second-order kinetic model and rate-limiting step was chemical biosorption of Zn and
Pb ions onto Mtilapia fish scales.
Kinetic information has significant practical value in technological applications because kinetic
modeling effectively replaces time and material-consuming experiments, which is compulsoly for
process equipment design and can be used to determine the significant parameters in a bioreactor
design (Deng et al., 2006; Cruz et al., 2004). The final selected kinetic models should be those that
closely fit the data and represent a reasonable sorption mechanism. Thus, the best fit for the
experimental data of this study was achieved by applying the pseudo-second-order kinetic equation.
Sorption isothermal modeling
Sorption isothermal modeling is fundamental to the industrial application of biosorption because it
provides information for comparing different biosorbent under various operational conditions,
design, and optimization procedures (Benguella and Benaissa, 2002). In the present study, three
parameter models were examined, namely, the Langmuir, Freundlich, and Brunauer-Emmett-Teller
(BET) isotherms, to fit the data.
The Langmuir model is used to estimate the maximum metal uptake values where they cannot be
reached in the experiments and contains two important parameters of the sorption system, i.e., q,,
and b (Nelson et al., 2001; Tian et al., 2002).
The Langmuir monolayer sorption isotherm is based on three assumptions (Cruz et al., 2004). First,
the solid surface presents a finite number of energetically uniform identical sites. Second, no
interaction exists among adsorbed species, i.e., the amount adsorbed has no influence on the
adsorption rate. Third and last, a monolayer is formed when the solid surface reaches saturation.
Accordingly, the linearized Langmuir equation is given as:
where qe is the equilibrium sorption capacity (mg g-'), and C, is the equilibrium metal-ion
concentration (mg L-I). q,,, is the maximum amount of metal ion per unit weight of adsorbent to
form a complete monolayer on the surface (mg g-'), and b is a constant related to the affinity of
binding sites with the metal ions (L mg-l) (Langmuir, 1918).
The Freundlich isotherm model describes the sorption of solute from liquid to solid surfaces and
assumes that stronger binding sites are occupied first and that the binding strength decreases with
increased degree of site occupation (Khambhaty et al., 2009). The uptake of metal ions occurs on a
heterogeneous surface by multilayer adsorption, and the amount of adsorbate adsorbed infinitely
increases with increased concentration (Freundlich, 1906). The linearized Freundlich equation is
given as:
Log qe= log KF + [(l 1 n) log C,]
(6)
where KF is the Freundlich constant denoting adsorption capacity (mglg), and q, is the uptake of
metal per unit weight of biosorbent (mglg). C, is the equilibrium concentration of metal ions in
solution (mgll), and n is the emperical constant indicating adsorption intensity (Ilmg).
The BET isotherm is an equation for multimolecular adsorption on the biosorbent surface and
assumes that a Langmuir model applies to each other. Information regarding metal-uptake
capacities and differences in metal uptake between various species were provided in this model
(Pagnanelli et al., 2002). The linear form of the BET model is given as
where q is the amount of metal ions adsorbed per specific amount of adsorbent (mglg), C is the
equilibrium concentration (mgll), q, is the maximum amount of metal ions required to form a
monolayer (mglg), and Kg is the BET constant (Brunauer et al., 1938). The linearized form of
Langmuir adsorption isotherms for Zn and Pb ions obtained at different concentrations are given in
Figures 8 and 9, respectively. The corresponding constants and correlation coefficient (R')
associated with each linearized model are given in Table 10.
Ce
Figure 8. Langmuir isotherms of Zn ion by MTilapia fish scales
0.0111
0.000
0.001
0.100
0201
0.3w
oaw
orw
0.601
ce
Figure 9. Langmuir isotherms of Pb ion by MTilapia fish scales
Table 10. Langmuir isotherm.
Langmuir
R2
-
-
Zn
0.9968
Pb
0.9854
The plot of log Q, versus log C, (Freundlich model) for Zn and Pb ions are shown in Figures 10 and
11, and the constants KF and n can be evaluated from the slopes and intercepts, respectively. The
Freundlich constants are shown in Table 11.
2
0:.
0y4
i6
0:8]
Logce
Figure 10 Freundlich isotherms of Zn ion by MTilapia fish scales.
A
.
-1.5
-1
-0.5
0
Log Ce
Figure 11 Freundlich isotherms of Pb ion by MTilapia fish scales.
Table 11. Freundlich isotherm.
Freundlich
Zn
Pb
To calculate the rate constants Kg and q,, the BET equation is plotted for Zn and Pb ions, as shown
in Figures 12 and 13, respectively. The reaction rate constants and correlation coefficients of BET
are shown in Table 12.
amlo
:
am
am
~ ~ . ~ ~ ~
roxo oiox am om arm am
~
.
~
~
~
~
~
~
~
.
CdCi
Figure 12. Brunauer-Emmett-Teller (BET) isotherms of Zn ion by MTilapia fish scales.
I
I
Figure 13. Brunauer-Emmett-Teller (BET) isotherms of Pb ion by MTilapia fish scales.
Table 12. BET isotherm.
BET
Zn
Pb
Results of the Langmuir model better fitted the adsorption process of Zn and Pb ions by fish scales
than the Freundlich and BET models because of the high value of R'. Thus, the results of the
present study indicated that the removal of Zn and Pb ions occurred through monolayer adsorption
onto Mtilapia fish scales.
4. CONCLUSION
XRF analysis confirmed the presence of CaO in Mtilapia fish scales before biosorption. The
absence of Zn and Pb ions in native biosorbent enable good adsorption between fish scales and
wastewater containing heavy metals. SEM analysis before hiosorption further characterized native
fish scales as a rough surface dark and white regions. After biosorption in domestic wastewater,
SEM clearly showed the presence of biosorbent loaded with Zn and Pb ions in the form of bright
bulky particles. Carbonyl, nitro, and amine groups were confirmed in FTIR analysis of native
biosorbent and heavy metal ions loaded with biosorbent. In domestic wastewater, optimum
condition of Zn ion was best selected and more suitable to apply in wastewater.
To determine the mechanism of Zn and Pb ion removal, three parameter models were examined,
namely, the Freundlich, BET, and Langmuir isotherms. The correlation coefficient R' of the
Langmuir model for Zn and Pb ions was closer to 1 than those of the Freundlich and BET models.
Therefore, the removal of Zn and Pb ions occurred on a homogeneous surface by monolayer
adsorption. Moreover, kinetic models demonstrated that q, of the pseudo-second-order model was
closer to the experimental value q,, whereas the coefficient correlation R' was closer to 1 than the
pseudo-first-order model. Thus, pseudo-second-order kinetics best fitted the kinetic data, and the
rate-limiting step was a chemical biosorption process between Zn and Pb ions by MTilapia fish
scales. These results proved that these fish scales were highly efficient in removing Zn and Pb ions
from synthetic wastewater. Therefore, MTilapia fish scales have high potential as biosorbents
because they are low cost, locally available, abundant, and effective.
References
Akar, T. & Tunali, S. (2006). Biosorption characteristics of Aspergillus flavus biomass for removal
of Pb(I1) and Cu(I1) ions from an aqueous solution. Bioresource technology, 97(15), 17801787.
Brunauer, S., Emmett, P. H. & Teller, E. (1938). Adsorption of gases in multimolecular
layers. Journal of the American Chemical Society, 60,309-3 19.
Balaria, A. & Schiewer, S. (2008). Assessment of biosorption mechanism for Pb binding by citrus
pectin. Separation and Purzj?cation Technology, 63(3), 577-58 1.
Bayramoglu, G. & Ar~ca,M. Y. (2008). Removal of heavy mercury(II), cadmium(I1) and Zn(I1)
metal ions by live and heat inactivated Lentinus edodes pellets. Chemical Engineering
Journal, 143(1-3), 133-140.
Barakat, M. A. (201 1). New trends in removing heavy metals from industrial wastewater. Arabian
Journal of Chemistry, 4(4), 361-377.
Baral, S. S., Das, S. N. & Rath, P. (2006). Hexavalent chromium removal from aqueous solution by
adsorption on treated sawdust. Biochemical Engineering Journal, 3 1(3), 216-222.
Benguella, B. & Benaissa, H. (2002). Cadmium removal from aqueous solutions by chitin: kinetic
and equilibrium studies. Water research, 36(10), 2463-2474.
Chubar, N., Camalho, J. R. & Correia, M. J. N. (2004). Cork biomass as biosorbent for Cu(II),
Zn(I1) and Ni(1I). Colloids and Surfaces A: Physicochemical and Engineering Aspects,
230(1-3), 57-65.
Cruz, C. C. V., da Costa, A. C. a., Henriques, C. A. & Luna, A. S. (2004). Kinetic modeling and
equilibrium studies during cadmium biosorption by dead Sargassum sp. biomass.
Bioresource Technology,91(3), 249-257.
Deng, L., Su, Y., Su, H., Wang, X. & Zhu, X. (2006). Biosorption of copper (11) and lead (11) from
aqueous solutions by nonliving green algae Cladophora fascicularis: Equilibrium, kinetics
and environmental effects. Adsorption, 12(4), 267-277.
El-Sheikh, A. H. & Sweileh, J. A. (2008). Sorption of trace metals on fish scales and application for
lead and cadmium pre-concentration with flame atomic absorption determination. Jordan
journal of chemistry, 3(1), 87-97.
Ekmekyapar, F., Aslan, A,, Bayhan, Y. K. & Cakici, A. (2006). Biosorption of copper(I1) by
nonliving lichen biomass of Cladonia rangiformis hoffm. Journal of hazardous materials,
137(1), 293-298.
Febrianto, J., Kosasih, A.N., Sunarso, J., Ju, Y-S, Indraswati, N., Ismadji, S, (2009), Equilibrium
and kinetic studies in adsorption of heavy metals using biosorbent: A summary of recent
studies, Journal ofhazardous materials, 162,616445.
Freundlich, H. M. F. (1906). Uber die adsorption in losungen. ZeitschrifiJirrPhysikalische Chemie,
57(A), 385-470.
Gupta, V. K., Shrivastava, A. K. & Jain, N. (2001). Biosorption of chromium(V1) from aquoues
solutions by green algae spirogyra species. Water resources, 35(17), 4079-4085.
Ho, Y. S. & Mckay, G. (2000). The kinetics of sorption of divalent metal ions onto sphagnum moss
peat. Water resources, 34(3), 735-742.
Khambhaty, Y., Mody, K., Basha, S. & Jha, B. (2009). Kinetics, equilibrium and thermodynamic
studies on biosorption of hexavalent chromium by dead fungal biomass of marine
Aspergillus niger. Chemical Engineering Journal, 145(3), 489495.
Lagergren, S. K. (1898). About the theory of so-called adsorption of soluble substances. Kungliga
svenska vetenskapsakademiens handligar, 24(4), 1-39.
Langmuir, I., (1918). The adsorption of gases on plane surfaces of glass, mica and platinum.
Joztrnal of the American Chemical Society, 40, 1361-1403.
Mohd-Kamil, N. A. F., Alias, S., Othman, N. & Abdul-Talib, S. (2013). Degradation of
Phenanthrene by Coiynebacterium urealyticum in liquid culture and sand slurry. Malaysia
Joztrnal of Soil Science, 17(1), 111-126.
Nadeem, R., Hanif, M.A., Shaheen, F., Zafar, M.N., Iqbal, T. (2008a). Physical and chemical
modification of distillery sludge for Pb(1I) biosbrption. ~ournalof hazardous materials,
(150) 335-342.
~ a d e e m , R., Ansari, T.M., Khalid A.M. (2008b). Fourier transform infrared spectroscopic
characterization and optimum of Pb(I1) biosorption by fish (Labeo Rohita) scales. Journal of
hazardous materials, 156, 64-73.
Othman, N., Irwan, J.M. (201 1). Characterization and optimization of heavy metals biosorption by
fish scales, Regional Symposium on Engineering & Technology 2011. 21-23 November
201 1, ISBN 978-967-5995-06-4, 126-132.
Pavia, D. L., Lampman, G. M., Kriz, G. S. & Vyvyan, J. R. (2009). Introduction to Spectroscopy.
4'h ed. United States: Cengage Learning.
Pagnanelli F, Esposito A, Veglio F. (2002). Multi-metallic modeling for biosorption of binary
systems. Water Resouce, 36:4095-105
Qaiser, S., Saleemi, A. R., Umar, M. (2009). Biosorption of lead(I1) and chromium(V1) on
groundnut hull: Equilibrium, kinetics and thermodynamics study. Electronic Journal of
Biotechnology, 12(4).
Rahaman, M.S., Basu, A., Islam, M.R. (2008). The removal of As(II1) and As(V) from aqueous
solutions by waste materials. Bioresource Technology, 99,2815-2823.
Romera, E., Gonzilez, F., Ballester, A., Blkquez, M. L. & Mufioz, J. A. (2007). Comparative study
of biosorption of heavy metals using different types of algae. Bioresource technology,
98(17), 3344-3353.
Srividya, K., Mohanty, K., (2009), Biosorption of hexavalent chromium from aqueous solution by
catla catla scales: Equilibrium and kinetics studies. Chemical Engineering Journal, 155,
666-673.
Srivastava, V. C., Mall, I. D. & Mishra, I. M. (2006). Equilibrium modelling of single and binary
adsorption of cadmium and nickel onto bagasse fly ash. Chemical Engineering Journal,
117(1), 79-91.
Veglio, F., Beolchini, F. (1997). Removal of metals by biosorption: a review. Hydrometallurgy,
(44), 301-316.
Volesky, B. (1990a), Biosorption of heavy metals, CRC Press, Boca Raton, Florida, 3-5.
Yu, B., Zhang, Y., Shukla, A,, Shukla, S. S. & Dorris, K. L. (2000). The removal of heavy metal
from aqueous solutions by sawdust adsorption - removal of copper. Journal of hazardous
materials, 80(1-3), 3342.
Zafar, M. N., Nadeem, R. & Hanif, M. A. (2007). Biosorption of nickel from protonated rice bran.
Journal ofhazardous materials, 143(1-2), 478485.
Zayadi, N., Othman, N. (2013a). Biosorption of Zn and Pb ions by MTilapia fish scales,
International Conference on Environment 2012, 11- 13 Dec 20 12.
Zayadi, N., Othman. (2013b). Characterization and optimization of heavy metals biosorption by fish
scale. Advanced Materials Research, 795,260-265.
Zafar, M. N., Nadeem, R. & Hanif, M. A. (2007). Biosorption of nickel from protonated rice bran.
Journal of hazardous materials, 143(1-2), 478-485.