Optimization of Lead Adsorption Using Animal Bio Polymers by Factorial Design
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Transcript of Optimization of Lead Adsorption Using Animal Bio Polymers by Factorial Design
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
303
OPTIMIZATION OF LEAD ADSORPTION USING ANIMAL BIOPOLYMERS BY FACTORIAL DESIGN
A. Ratna Kumari1*, U.Kiran Babu2, K. Sobha3
1Department of Biotechnology, Bapatla Engineering College (autonomous), Bapatla-522 101, AP, India & Centre for
Biotechnology, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur-522 510, A.P., India, 2Department of
Biotechnology, Bapatla Engineering College, Bapatla-522 101, AP, India, 3Department of Biotechnology, RVR & JC
College of Engineering, Chowdavaram, Guntur – 522 019, AP, India.
INTRODUCTION
ISSN:2249-5347 IJSID
International Journal of Science Innovations and Discoveries An International peer
Review Journal for Science
Research Article Available online through www.ijsidonline.info
Received: 14.09.2011
Modified: 16.10.2011
Published: 29.12.2011
Key words: Adsorption,
Animal biopolymers,
Factorial design, lead.
*Corresponding Author
Address:
Name:
A. Ratna Kumari
Place:
Guntur, AP, India
E-mail:
ABSTRACT
Heavy metals present in the industrial effluents remain as alarming
pollutants due to their nondestructive nature, toxicity, bioaccumulation and
subsequent biomagnification. Animal biopolymers viz., chick and duck feathers’
fibers were treated with 5% tannic acid solution. From the preliminary studies it
was found that pH, contact time, and biosorbent dose are significant factors for
maximal biosorption of lead by both chick and duck feathers. To study the
interactive effects of these three independent parameters (Biosorbent dosage,
Contact time, pH) and their optimization for lead biosorption process by response
surface methodology (RSM), Box-Behnken design (BBD) was applied. The
regression equation coefficients (r2) are 0. 98098 & 0.91785 for chick and duck
feathers respectively and the data fitted to a second-order polynomial equation for
removal of lead (Pb). The critical values of the three parameters obtained for chick
feathers, with a maximum biosorption efficiency of 70.73%, are 1.9 g/L of
biosorbent, 24.56 hours of contact time, 6.94 pH. For duck feathers with a
maximum biosorption efficiency of 58.8%, the critical values obtained are 2.3 g/L
of biosorbent, 20.17 hours of contact time and 7.02 pH.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
304
INTRODUCTION
Water bodies are being overwhelmed with bacteria, waste matter and toxic substances (1). Among toxic
substances reaching hazardous levels are heavy metals (2). Contamination of water supplies with heavy metals is an
area of concern both nationally & internationally where the challenge to remediate hazardous metal containing
waste streams from present or past mining operations, industrial sites and ground waters is immense (3). Heavy
metals of concern include lead, chromium, mercury, uranium, selenium, zinc, arsenic, cadmium, silver, gold and
nickel (4). Heavy metal pollution in the aquatic system has become a serious threat today as they are non-
biodegradable and thus persistent (5). Metals are mobilized and carried into food web as a result of leaching from
waste dumps, polluted soils and water. The metals increase in concentration at every level of food chain and are
passed onto the next higher level–a phenomenon called bio-magnification (6) and cause several diseases and health
disorders in humans, and other living organisms (7). Thus, removal of heavy metals from industrial wastewater is of
prime importance (8).
Some of the conventional techniques for removal of metals from industrial wastewater include adsorption
(9), sedimentation (10), electrochemical processes (11), ion exchange (12), biological operations (13), cementation (14) ,
coagulation / flocculation (10) , filtration and membrane processes (14) , chemical precipitation and solvent
extraction (15- 16) . However, most available methods may show economical and technical disadvantages such as
high capital and operational costs, high sensitivity to operational conditions, significant energy consumption, or
sludge generation (17) & they also are ineffective when metals are present in high concentrations in aqueous
solution (18). With increasing environmental awareness and stringent government policies, it has become necessary
to develop new environmental friendly ways to clean up contaminants using low-cost methods and materials (19).
In this aspect, the relatively new technology termed biosorption has dominated. The major advantages of
biosorption over conventional treatment methods include low cost, the use of inexpensive and never exhausted
biosorbent materials, high efficiency of metal removal from dilute solutions, minimization of chemical and/or
biological sludge, no additional nutrient requirement, regeneration of biosorbent and the possibility of metal
recovery (20). The biosorption process involves a solid phase (sorbent or biosorbent; usually a biological material)
and a liquid phase (solvent, normally water) containing a dissolved species to be sorbed (sorbate, a metal ion) (1).
An adsorbent material (biosorbent), both living and nonliving, derived from suitable biomass can be used for the
effective removal and recovery of heavy metal ions from wastewater streams (21-22). Recently, the use of non-living
biomaterials as metal-binding compounds has been gaining advantage as these compounds require minimum care
and maintenance and can be obtained more cheaply (23) . Biomaterials of animal origin, generated as waste such as
animal bones (24-25), chick feathers (26) and duck feathers (27) have been used for removal of heavy metals.
In particular, lead has been classified as a serious hazardous heavy metal with high priority in the context
of environmental risk (17). This metal is extremely toxic and can damage kidney, liver, brain and reproductive
organs besides other adverse effects to humans (7) . At present, lead pollution is considered a worldwide problem
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
305
because this metal is commonly detected in several industrial wastewaters (28). Examples of these wastewaters are
those produced by processes such as mining, smelting, printing, metal plating, explosive manufacture, and dying.
Electroplating mainly discharges huge amounts of lead and its ingestion beyond the permissible level causes
various types of acute disorders in man such as anemia, alimentary symptoms, wrist and foot drop, renal damage,
embryo toxicity resulting in spontaneous abortions and sometimes encephalopathy. In children it causes
behavioral effects and intellectual impairment. In this context, local legislations have established rigorous
standards for lead concentrations in industrial effluents. Therefore, special attention has been given to develop
proper methods for lead removal from water (29).
During the last decade, several studies have shown that different synthetic and natural sorbents can be
used to remove lead ions from aqueous effluents (30-48). Many examples of natural sorbents are available in the
literature, and they include brewery biomass, cactus pulp, olive stone waste, chitosan, modified wool, cotton,
nutshells, rice hulls, pine bark, sawdust, sugar cane bagasse, fruit stones, and pyrolyzed coffee, among others (41-48).
In removal processes, most of these sorbents generally show Pb uptakes in the range of 1.0 - 100 mg/g. In
particular, chicken feathers and duck feathers are among the natural sorbents that can be used for water treatment
(27, 49-54). The feathers represent four to six percent of the total body weight and, as a consequence, are a waste
product generated in large quantities from commercial poultry industry. As a natural protein material, feather
fiber has polar and ionizable groups on the side chain of constant amino acid residues, which are able to bind
charged species. The adsorption of metal cations to feather fibers can be attributed to many characteristics such as
low solubility, complex physical form, relatively high content of reactive groups that can serve as binding sites or
that can be chemically modified, variety and juxtaposition of reactive sites that can allow cooperative reaction etc.
To date, the use of chicken feathers for sorption purposes has achieved satisfactory results for the removal of some
heavy metals, colorants, and organic toxic compounds (39, 49-54) & duck feathers are also used for the removal of
heavy metals (27).
Biosorption efficiency depends upon many factors, the critical ones being pH, contact time, and biosorbent
concentration. This work is, therefore, primarily aimed at evaluating the effects of pH, contact time, and biosorbent
dose on the percentage removal of lead by both Chick and Duck feathers. To study the cumulative/interactive effect
and optimization of lead biosorption process, a Factorial design was applied, varying the three independent
parameters (initial pH, Contact time, Biosorbent dosage). Response surface methodology was applied to the Box
and Behnken experimental design(55). To the best of our knowledge, there is no published report on optimization of
biosorption process for removal of lead with animal biopolymers (Chick and Duck feather) using response surface
methodology. As the Box–Behnken design minimizes the number of factor combinations and maintains good
precision of the predicted response (56-58), this matrix has been used for the optimization of biosorption process for
removal of lead using animal biopolymers (Chick and Duck feathers).
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
306
MATERIALS AND METHODS
Biosorbent preparation
Chick and Duck feathers were collected from poultry processing facilities. The feather fibers used were in
the form of barbs which were detached from the shaft of Chicken feathers and Duck feathers. These were washed
several times with deionised water. Feather fibers were immersed in 5% (w/v) aqueous solution of the Tannic acid
(material-to-liquor ratio 1:100) at 70°C for 1–13 hr. Tannic acid (TA) is a kind of plant polyphenol. It is reported
that TA can form insoluble products with keratin by tanning reaction, which can increase the chemical and physical
stability of protein. Moreover, TA can form chelates with many metal cations via the ortho dihydroxy (catehol) or
trihydroxy-benzene (galloyl) group (59). Feather fibers were removed after the incubation time, washed thoroughly
in a porcelain funnel with distilled water, and then dried at room temperature before metal adsorption
experiments.
Preparation of metal solution
All the reagents were Analytical Reagent Grade and were prepared in Double Distilled water. Dissolved
1.5980g of lead nitrate (Pb (NO3)2 ) in 100ml of Double Distilled water, diluted to 1 liter in a volumetric flask with
Double Distilled water. This was used as the source of Pb in the synthetic waste water. pH of the solution was
adjusted using 0.1N HCl or NaOH. Solutions of varying concentrations were prepared by diluting the stock solution
with Double Distilled water. Fresh dilutions were used for each adsorption study.
Lead (Pb) ion determination
The change in Pb concentration due to adsorption was determined using AAS (Atomic absorption
spectrophotometer) in flame at a wavelength of 283nm.
Effect of biosorbent concentration on Adsorption
The adsorption of lead by Chick and duck feather fibers was studied at increasing concentration of
biosorbent 0.05g, 0.10g, 0.15g, 0.20g, 0.25g, 0.30g respectively in 100ml of lead solution in 250 ml Erlenmeyer
flask at constant incubation time and pH 7. Final values were projected in g/L. The biosorbent was removed from
the solution by centrifugation and the supernatant was analyzed for the residual concentrations of lead ion using
Atomic Absorption Spectrophotometer. Each adsorption experiment was carried out twice, and the average was
used for adsorption study.
Effect of Contact Time on Adsorption
Optimum biosorbent concentration obtained for chick and duck feather were taken to monitor the effect of
time on adsorption. The adsorption experiments were carried out at different contact times viz., 5, 10, 15, 20, 25,
35, 45, 55, 65min with a fixed adsorbent dose at pH 7. The biosorbent was removed from the solution by
centrifugation and the supernatant was analyzed for the residual concentrations of lead ion using Atomic
Absorption Spectrophotometer.
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
307
Effect of pH on Adsorption
Optimum Biosorbent concentration and optimum contact time were used to monitor the pH effect on
adsorption. The adsorption experiments were carried out for different pH values 4-9 with a fixed adsorbent dose
concentration at optimum contact time. The biosorbent was removed from the solution by centrifugation and the
supernatant was analyzed for the residual concentrations of lead ion using Atomic Absorption Spectrophotometer.
Factorial Design
The Box–Behnken design (BBD) model, which is the standard RSM, was established using STATISTICA 6.0
for the optimization of biosorption process. The experimental design, three independent variables, i.e. pH (6.0-8.0),
time (15-35hrs) and biosorbent concentration (0.1-0.3g/100ml) were taken to effect biosorption of lead ions. The
experimental design was applied after selection range of each variable (maximum and minimum) as shown in
Table 1. The Box–Behnken design contained a total of 27 experiments. All the biosorption experiments were
conducted in 250mL Erlenmeyer flasks and then the filtrate was analyzed for residual lead concentration using
Atomic absorption spectrophotometer.
Statistical analysis
The quadratic equation model for predicting the optimal point was expressed according to the following
equation:
Y= β0 + Σ βi Xi + Σ βii Xi2 + Σ βij Xi Xj
where Y is the predicted response, β0 model constant; βi is linear coefficient, βii is the quadratic coefficient
and βij is the different interaction coefficients of the model;
In this study, the removal of lead was processed using the following equation
Y= β0 + Σ βi Xi + Σ βij Xi2 + Σ βij Xi Xj
= A0 + A1x1+ A2x2 + A3x3 + A4x1x2+ A5x1x3 + A6x2x3 + A7x1x1 + A8x2x2 + A9x3x3
in which Y is the response variable, percentage removal of lead and X1, X2 and X3 are the coded values of the
independent variables- biosorbent concentration, time, pH respectively.
STATISTICA 6.0, was used for regression analysis of the data obtained and to estimate the coefficient of the
regression equation. The quality-of-fit of polynomial model was expressed by the coefficient of determination r2
and statistical significance was checked. To visualize the relationship between responses and experimental levels
for each of the factors, the fitted polynomial equation was expressed as surface plots. Three dimensional plots
demonstrate relationships between the lead ion uptake with the paired factors (when other factor was kept at its
optimal level), describing the behavior of biosorption system in a batch process.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
308
Table 1: Box–Behnken design for the optimization of Biosorption of Lead (Pb) using Chick Feather
RESULTS & DISCUSSION
On treatment with tannic acid the chick & duck feather protein chemical and physical stability was
increased. 1ppm, 2ppm, 3ppm, 4ppm, and 5ppm lead solutions were prepared using stock solution. Absorbance
values were taken using atomic absorption spectrophotometer. Standard graph was plotted by taking known
concentration on X-axis and absorbance at 283 nm on Y-axis which is shown in Fig-1 and it obeyed Beer-lambert’s
law.
Effect of biosorbent concentration
Lead biosorption by chick & duck feathers were studied at various biosorbent concentrations ranging from
0.05g to 0.3 g in 100ml of 5ppm lead solution. The percent removal of lead increased with an increase in
biosorbent concentration because of an increasing adsorption surface area. The maximum biosorption efficiency
was obtained at 0.2 g of chick feather and 0.15g of duck feather, but further increase in biosorbent concentration
Box–Behnken design Chick feathers Duck feathers
Run
No
Biosorbent
Concentration
(g/100ml)
Time
(hrs)
pH % Removal
Efficiency
(Observed)
% Removal
Efficiency
(Predicted)
% Removal
Efficiency
(Observed)
% Removal
Efficiency
(Predicted)
1 0.1 15 6 41.46 39.2797 35.7 33.4519
2 0.1 15 7 43.90 43.3036 37.8 36.0796
3 0.1 15 8 46.34 45.7142 38.1 37.7963
4 0.1 25 6 48.78 50.6497 39.0 39.4657
5 0.1 25 7 53.65 53.6811 41.4 41.5852
6 0.1 25 8 53.69 55.0992 42.7 42.7935
7 0.1 35 6 56.09 55.7664 43.8 45.3685
8 0.1 35 7 57.33 57.8053 45.8 46.9796
9 0.1 35 8 58.29 58.2308 46.9 47.6796
10 0.2 15 6 60.48 64.4042 47.7 50.4657
11 0.2 15 7 63.41 65.8322 48.6 51.6519
12 0.2 15 8 65.85 65.6469 50.1 51.9269
13 0.2 25 6 68.29 67.4400 51.5 52.3296
14 0.2 25 7 70.73 67.8756 52.2 53.0074
15 0.2 25 8 68.29 66.6978 54.1 52.7741
16 0.2 35 6 65.85 64.2225 56.5 54.0824
17 0.2 35 7 63.41 63.6656 58.9 54.2519
18 0.2 35 8 60.97 61.4953 54.4 53.5102
19 0.3 15 6 56.09 53.6319 52.8 51.0352
20 0.3 15 7 53.65 52.4642 51.1 50.7796
21 0.3 15 8 48.78 49.6831 50.9 49.6130
22 0.3 25 6 47.07 48.3336 49.0 48.7491
23 0.3 25 7 46.34 46.1733 48.1 47.9852
24 0.3 25 8 41.51 42.3997 47.0 46.3102
25 0.3 35 6 36.40 36.7819 45.3 46.3519
26 0.3 35 7 32.01 33.6292 43.5 45.0796
27 0.3 35 8 30.11 28.8631 41.1 42.8963
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
309
decreased the maximum removal of metal ions because of saturation of biosorbent surfaces as shown in Fig- 2. The
percentages of removal of lead by chick and duck feathers were 41.6% and 37.5% respectively.
Fig- 1 Standard graph of lead
0
5
10
15
20
25
30
35
40
45
0.05 0.1 0.15 0.2 0.25 0.3
% r
em
ov
al
biosorbent concentration(g/100ml)
% removal by C.F.
% removal by D.F.
Fig - 2 Effect of biosorbent concentration (give units correctly) on biosorption using chick feather (C.F.) and duck
feather (D.F.)
Effect of contact time
The contact time was evaluated as one of the important parameters affecting the biosorption efficiency.
The adsorption experiments were carried out for different contact times with a fixed adsorbent dose concentration
at pH 7. Fig - 3 shows the biosorption efficiency of lead ions by chick and duck feathers as a function of contact
time. The lead uptake was found to increase with increase in contact time up to 25hrs for chick feathers & 35hrs
for duck feathers and after that, lead uptake slowly decreased. The fast initial metal biosorption rate was attributed
to the surface binding and the following slower sorption was attributed to the interior penetration (60). Different
kinds of functional groups, with different affinities to the metal ions, are usually present on the surface of feathers.
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
310
The active binding groups with higher affinities are firstly occupied (61). The percentages of removal of lead by
chick and duck feathers were 69.3% and 55.83% respectively.
Effect of pH
Biosorption of heavy metal ions is dependent on the pH of solution as it affects biosorbent surface charge,
degree of ionization etc. The pH of the solution influences both metal binding sites on the feather surface and the
chemistry of metal in solution. In order to demonstrate the effect of pH on biosorption capacity, uptake of lead ions
onto chick and duck feathers as a function of pH was studied in the pH ranges of 4 to 8 with a fixed adsorbent dose
concentration at optimum contact time. The percentages of removal of lead by chick and duck feathers
were76.66% and 58.95% respectively at pH7 as shown in Fig-4.
0
10
20
30
40
50
60
70
80
5 10 15 20 25 35 45 55 65
% r
em
ov
al
Time(hours)
% removal by C.F.
% removal by D.F.
Fig - 3 Effect of time on biosorption using chick feather (C.F.) and duck feather (D.F.)
0
10
20
30
40
50
60
70
80
90
4 5 6 7 8
% r
em
ov
al
pH
% removal by C.F
% removal by D.F
Fig-4 Effect of pH on biosorption using chick feather (C.F.) and duck feather (D.F.)
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
311
Factorial Design
The independent variables like biosorbent concentration, time, pH were used to optimize the adsorption by
chick and duck feathers and the results of percentage removal of lead in each case are presented in Table 1. The
percentage removal of lead depends on the individual effects of combinations of independent variables and the
results show a significant variation for each combination. Multiple regression analysis of the experimental data
was obtained from the following regression equation for the biosorption of lead
Equation-1
Y= β0 + Σ βi Xi + Σ βij Xi2 + Σ βij Xi Xj
= A0 + A1x1+ A2x2 + A3x3 + A4x1x2+ A5x1x3 + A6x2x3 + A7x1x1 + A8x2x2 + A9x3x3
The coefficients (p) were highly significant for both chick and duck feathers when compared with interactive
effects. Multiple regression coefficient (R) was estimated from the second-degree polynomial Eq. (1). The value of
r2 = 0. 98098 & 0.91785 for chick and duck feathers respectively which is closer to one indicates that the
correlation is best suited for predicting the performance of the biosorption system and the predicted values were
found to be very closer to the experimental results. The results obtained from the BBD, the student’s ‘T’
distribution, the p values and the parameter estimates for chick and duck feathers are given in Table 2& 3
respectively. The regression equation coefficients were calculated and the data fitted to a second-order polynomial
equation using MATLAB for removal of lead with chick & duck feathers. The optimum values of the test variables
and the corresponding maximum percentage removal of lead (70.73%) by chick feathers were obtained in coded
units as X1 =1.0705, X2 = 0.0038, X3 = 0.0186 & maximum percentage removal of lead (58.8%) by duck feathers
were obtained in coded units as X1 =565.5556, X2 = 1.3436, X3 = 10.7542 were shown in the following equations.
Final Polynomial Equation for chick feathers:
Y= -0.1456 + 1.0705x1 + 0.0038 x2+ 0.0186 x3 -0.0083x1x2-0.0260 x1x3 - 0.0001 x2x3- 1.7948 x1x1 -0.000
x2x3 - 0.0008 x3x3
Final Polynomial Equation for duck feathers:
Y= -63.5856+ 565.5556x1 + 1.3436 x2 + 10.7542 x3 -4.1500 x1 x2 -14.4167 x1 x3 -0.0508 x2x3 -822.2222
x1 x1 – 0.0006 x2 x3 - 0.4556 x3 x3
The maximum lead removal by chick and duck feathers was 70.73% and 58.8 respectively. This
experimental value closely agrees with the values obtained from the response surface methodology, confirming
that the RSM using the statistical design of experiments could be effectively used to optimize the process
parameters and to study the importance of individual, cumulative and interactive effects of the test variables in
biosorption.
Each contour plot represents a number of combinations of two test variables with the other variable kept
at its optimal level. The maximum percentage removal of lead is indicated by the surface confined in the smallest
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
312
curve of the contour plot. The studies of the contour plots also reveal the best optimal values of the process
conditions and are given below:
For chick feathers: biosorbent concentration 0.19g, time 25hrs, pH–7 and for duck feathers biosorbent
concentration 0.15g, time 35hrs, pH–7 which is shown in Fig - 5 to 8.
Fig - 5 Response surface contour plot showing interactive effect of biosorbent concentration
and time on the removal of lead by chick feathers.
Fig - 6 Response surface contour plot showing interactive effect of time and pH on the removal of lead by chick
feathers.
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
313
The graph was plotted by taking observed and predicted values which shows that both observed and
predicted values are adjacent to the line for both chick and duck feathers which are shown in graphs 1& 2.
Fig - 7 Response surface contour plot showing interactive effect of biosorbent concentration and time on the
removal of lead by duck feathers
Fig – 8 Response surface contour plot showing interactive effect of time and pH on the removal of lead by duck
feathers
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International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
314
Observed vs. Predicted Values3 3-level factors, 1 Blocks, 27 Runs; MS Residual=3.648408
DV: % Removal Efficiency
25 30 35 40 45 50 55 60 65 70 75
Observed Values
20
25
30
35
40
45
50
55
60
65
70
75
Pre
dict
ed V
alue
s
Graph - 1 Observed and predicted values for chick feathers
Observed vs. Predicted Values3 3-level factors, 1 Blocks, 27 Runs; MS Residual=4.512952
DV: % Removal Efficiency
30 35 40 45 50 55 60 65
Observed Values
30
35
40
45
50
55
60
Pre
dict
ed V
alue
s
Graph - 2 Observed and predicted values for duck feathers
The critical values obtained for chick feathers are 0.19 grams biosorbent, 24.56 hours, 6.94 pH and for
duck feathers are 0.23 grams biosorbent, 20.17hours, 7.02pH as shown in Table - 4. Therefore, it is apparent that
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315
the response surface methodology not only gives valuable information on interactions between the factors but also
leads to identification of feasible optimum values of the studied factors.
Table - 2: Effect Estimates ; Var.:% Removal Efficiency; R-sqr=.98098; Adj:.97091 3 3-level factors, 27 Runs;
Effect Std.Err. t(17) p -95.% +95.% Coeff.
Mean/Interc. 41.3222 0.636694 64.9013 0.000000 -230.44 -60.67 41.32222
(1)Biosorbant
concentration (gm)(L) 28.3889 1.800841 15.7642 0.000000 961.38 1179.54 14.19444
Biosorbant
concentration (gm)(Q) 35.8967 1.559574 23.0170 0.000000 -1959.35 -1630.31 17.94833
(2)Time(hrs)(L) -2.1667 0.900421 -2.4063 0.027771 2.63 5.00 -1.08333
Time(hrs)(Q) 3.1267 0.779787 4.0096 0.000908 -0.05 -0.01 1.56333
(3)pH(L) -0.7422 0.900421 -0.8243 0.421181 -4.76 41.95 -0.37111
pH(Q) 0.8067 0.779787 1.0345 0.315409 -2.45 0.84 0.40333
1L by 2L -16.6683 1.102786 -15.1148 0.000000 -9.50 -7.17 -8.33417
1L by 3L -5.1917 1.102786 -4.7078 0.000203 -37.59 -14.32 -2.59583
2L by 3L -1.9850 1.102786 -1.8000 0.089634 -0.22 0.02 -0.99250
Table - 3: Effect Estimates; Var.:% Removal Efficiency; R-sqr=.91785; Adj:.87437 3 3-level factors, 27 Runs;
Effect Std.Err. t(17) p -95.% +95.% Coeff.
Mean/Interc. 41.70370 0.708124 58.89325 0.000000 40.2097 43.19771 41.70370
(1)Biosorbant
concentration (gm)(L)
22.84444 2.002876 11.40582 0.000000 18.6187 27.07014 11.42222
Biosorbant
concentration (gm)(Q)
16.44444 1.734542 9.48057 0.000000 12.7849 20.10401 8.22222
(2)Time(hrs)(L) 2.60000 1.001438 2.59627 0.018825 0.4872 4.71285 1.30000
Time(hrs)(Q) 0.05556 0.867271 0.06406 0.949671 -1.7742 1.88534 0.02778
(3)pH(L) 0.44444 1.001438 0.44381 0.662780 -1.6684 2.55729 0.22222
pH(Q) 0.45556 0.867271 0.52527 0.606176 -1.3742 2.28534 0.22778
1L by 2L -8.30000 1.226506 -6.76719 0.000003 -10.8877 -5.71230 -4.15000
1L by 3L -2.88333 1.226506 -2.35085 0.031057 -5.4710 -0.29563 -1.44167
2L by 3L -1.01667 1.226506 -0.82891 0.418641 -3.6044 1.57104 -0.50833
Table - 4 Critical values; Variable: % Removal Efficiency Solution: maximum Predicted value at solution: 68.07936
(Chick feathers), 53.18945 (Duck feathers)
Chick feathers Duck feathers
Observed Critical Observed Observed Critical Observed
Biosorbant
concentration (g) 0.10000 0.19098 0.30000 0.10000 0.23246 0.30000
Time(hrs) 15.00000 24.56185 35.00000 15.00000 19.77395 35.00000
pH 6.00000 6.94208 8.00000 6.00000 7.02192 8.00000
CONCLUSION
This work has demonstrated the use of Box–Behnken design for determining the optimum process
conditions leading to the maximum percentage removal of lead from aqueous solutions. Using this experimental
design and multiple regression, the parameters namely, biosorbent concentration, pH and contact time were
studied effectively and optimized with a lesser number of experiments. This methodology could therefore be
successfully employed to study the importance of individual, cumulative and interactive effects of the test variables
in biosorption.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
316
ACKNOWLEDGEMENT
The authors express their thanks to the Department of Biotechnology, Bapatla Engineering College, Bapatla
for providing research facilities and valuable guidelines. The first author expresses her gratitude to Prof.
K.R.S.Sambasiva Rao, Director, Centre for Biotechnology, Acharya Nagarjuna University for his encouragement and
support during the period of study.
REFERENCES
1. Hima Karnika Alluri, Srinivasa Reddy Ronda, Vijaya Saradhi Settalluri, Jayakumar Singh. Bondili,
Suryanarayana. V and Venkateshwar. P. Biosorption: An eco-friendly alternative for heavy metal removal,
African Journal of Biotechnology, 2007, 6 (25), 2924-2931.
2. Regine HSF, Volesky B, Biosorption: a solution to pollution. Int. Microbiol, 2000, 3: 17-24.
3. Rajiv kumar & Dinesh Goyal, Comparative biosorption of Pb2+ by live algal consortium and immobilized dead
biomass from aqueous solution. Indian Journal of Experimental Biology, 2008, 46, 690-694.
4. Ahalya N, Ramachandra TV, Kanamadi RD, Biosorption of heavy metals. Res. J. Chem. Environ, 2003, 7: 71-78.
5. Baily SE, Olin TJ, Adrian DD, A review of potentially low-cost sorbents for heavy metals. Wat Res; 1999,
33:2469-79.
6. Paknikar KM, Pethkar AV, Puranik, Bioremediation of metalliferous Wastes and products using Inactivated
Microbial Biomass, Indian J. Biotechnol, 2003, 2: 426-443.
7. Godwin HA, The biological chemistry of lead, Current Opinion in Chemical Biology, 2001 5, 223-227.
8. Capponi F, Sartori M, Souza ML, Modified column flotation of adsorbing iron hydroxide colloidal precipitates,
Mineral Process, 2006, 79:167-73.
9. Sari A, Tuzen M, Soylak M, Adsorption of Pb(II) and Cr(III) from aqueous solution on Celtic clay, J Hazard
Mater, 2007, 144:41-6.
10. Song Z, Williams CJ, Edyvean RGJ, Sedimentation of tannery wastewater, Water Res, 2000, 34:2171-6.
11. Fahim NF, Barsoum BN, Eid AE, Removal of chromium(III) from tannery wastewater using activated carbon
from sugar industrial waste, J Haz Mat, 2006, 136:303-37.
12. Tiravanti G, Petruzzelli D, Passino R, Pretreatment of tannery wastewaters by an ion exchange process for
Cr(III) removal and recovery, Water Sci Tech, 1997, 36:197-207.
13. Kapoor A, Viraraghavana T, Biosorption of heavy metals on Aspergillus Niger. J Biores Tech, 1998, 63:109-13.
14. Fabianil C, Rusciol F, Spadonil M, et al., Chromium(III) salts recovery process from tannery wastewaters.
Desal, 1996, 108:183-91.
15. Brooks CS, Metal Recovery from Industrial Waste, Lewis Publishers, Inc., Michigan, USA, 1991.
16. Macchi G, Pagano M, Pettine M, et al., A bench study on chromium recovery from tannery sludge, Water Res,
1991, 25:1019-26.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
317
17. Volesky B, Detoxification of metal-bearing effluents: biosorption for the next century, Hydrometallurgy, 2001,
59, 203-216.
18. Taghi ganji M, Khosravi M, Rakhshaee R, International Journal of Environmental Science & Technology, 2005,
4, 265-271.
19. Chandra Sekhar K, Kamalaa CT, Chary NS, Sastry ARK, Nageswara Rao T, Vairamani M, Removal of lead from
aqueous solutions using an immobilized biomaterial derived from a plant biomass, Journal of Hazard Matter,
2004, 108, 111.
20. Veglio F, Beolchini F, Gasbarro A, 1997, Biosorption of toxic metals: an equilibrium study using free cells of
Arthrobacter sp, Process Biochemistry, 1997, 32: 99-105.
21. Niu, H, Xu XS, Wang JH, Removal of lead from aqueous solutions by Penicilium biomass, Biotechnol.Bioeng,
1993, 42: 785-787.
22. Muraleedharan TR, Iyengar L, Venkobachar L, Screening of tropical wood-rotting mushrooms for copper
Biosorption, Appl. Environ. Microbial, 1995, 61: 3507-3508.
23. Nabil ABDEL-JABBAR, Sameer AL-ASHEH, Factorial Design for the Analysis of Packed-bed Sorption of Copper
using Eggshell as a Biosorbent, Journal of environmental protection science, 2009, 3, 133 – 139.
24. Al-Asheh S, Abdel-Jabar N, Banat F, Packed-bed sorption of copper using spent animal bones: Factorial
experimental design, desorption and column regeneration. Adv Env Res, 2002, 6:221-7.
25. Banat F, Al-Asheh S, Mohai F, Multi-metal sorption by spent animal bones. Sep Sci Tech, 2002, 37:311-27.
26. Al-Asheh S, Banat B, Al-Rousan D, Beneficial reuse of chicken feathers in removal of heavy metals from
wastewater. J Cleaner Prod, 2002, 11:321-6.
27. Yang Chongling, Guan Litao, Zhao Yaoming, Yan Yurong, Sorption of Cu2+ and Zn2+ by Natural Biomaterial:
Duck Feather, Appl Biochem Biotechnol, 2007, 142, 168–178.
28. Davydova S, “Heavy metals as toxicants in big cities,” Microchemical Journal, 2005, 79, 133-136.
29. De la Rosa G, Reynel-Avila HE, Bonilla-Petriciolet A, Cano-Rodríguez I, Velasco-Santos C, Martinez-Hernandez
AL, Recycling Poultry Feathers for Pb Removal from Wastewater: Kinetic and Equilibrium Studies, World
Academy of Science, Engineering and Technology, 2008, 47.
30. Bailey S, Olin T, Bricka RR, Adrian D, A review of potentially low-cost sorbents for heavy metals, Water
Research, 1999, 33, 2469- 2479.
31. Machida M, Kikuchi Y, Aikawa M, Tatsumoto H, Kinetics of adsorption and desorption of Pb(II) in aqueous
solution on activated carbon by two-site adsorption model, Colloids and Surfaces A:Physicochemical and
Engineering Aspects, 2004, 240,179-186.
32. Goel J, Kadirvelu K, Rajagopal C, Garg VK, Removal of lead (II) from aqueous solution by adsorption on carbon
aerogel using a response surface methodological approach, Industrial Engineering Chemistry Research, 2005,
44, 1987-1994.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
318
33. Aljundi IH, Khleifat KM, Biosorption of lead by E. coli strains expressing Vitreoscilla hemoglobin: Isotherm
modeling with two-and three-parameter models. Engineering in Life Sciences, 2010, 10: 225–232.
34. Gercel O, Gercel H, Adsorption of lead (II) ions from aqueous solutions by activated carbon prepared from
biomass plant material of Euphorbia rigida, Chemical Engineering Journal, 2007, 132, 289- 297.
35. Gunay K, Arslankaya E, Tosun I, Lead removal from aqueous solution by natural and pretreated clinoptilolite:
Adsorption equilibrium and kinetics, Journal of Hazardous Materials, 2007, 146, 362-371.
36. Singh SP, Ma LQ, Hendry MJ, Characterization of aqueous lead removal by phosphatic clay: Equilibrium and
kinetic studies, Journal of Hazardous Materials, 2006, B136, 654-662.
37. Adela Kogej, Bla Likozar, Aleksander Pavk, Lead Biosorption by Self-Immobilized Rhizopus nigricans Pellets in
a laboratory Scale Packed Bed Column: Mathematical Model and Experiment, Food Technology and
Biotechnology, 2010, 48 (3), 344–351.
38. Bakircioglu Y, Bakircioglu D, Akman S, Biosorption of lead by filamentous fungal biomass-loaded tio2
nanoparticles, Journal of Hazard Mater, 2010, 178(1-3), 1015-20.
39. Al-Asheh S, Banat F, Al-Rousan D, Beneficial reuse of chicken feathers in removal of heavy metals from
wastewater, Journal of Cleaner Production, 2003, 11, 321-326.
40. Al-Ghouti M, Khraisheh M, Tutuji M, Flow injection potentiometric stripping analysis for study of adsorption of
heavy metal ions onto modified diatomite, Chemical Engineering Journal, 2004, 104, 83-91.
41. Babel S, Kurniawan T, Low-cost adsorbents for heavy metals uptake from contaminated water: a
review, Journal of Hazardous Materials, 2003, B97, 219-243.
42. De la Rosa G, Gardea Torresdey JL, Peralta-Videa JR, Herrera I, Use of silica-immobilized humin for heavy
metal removal from aqueous solution under flow conditions, Bioresource Technology, 2003, 90, 11-17.
43. Davila-Jimenez M, Elizalde-Gonzalez M, Geyer W, Mattusch J, Wennrich R, Adsorption of metal cations from
aqueous solution onto a natural and a model biocomposite, Colloids and Surfaces A:Physicochemical and
Engineering Aspects, 2003, 209, 243-252.
44. Fiol N , Villaescusa I, Martínez M, Miralles N, Poch J, Serarols J, Sorption of Pb(II), Ni(II), Cu(II) and Cd(II) from
aqueous solution by olive stone waste, Separation and Purification Technology, 2006, 50, 132-140.
45. Doyorum S, Celik A, Pb(II) and Cd(II) removal from aqueous solutions by olive cake, Journal of Hazardous
Materials, 2006, B138, 22-28.
46. Kapoor A, Viraraghavan T, Cullimore D, Removal of heavy metals using the fungus Aspergillus niger,
Bioresource Technology, 1999, 70, 95-104.
47. Sun QY, Lu P, Yang LZ, The adsorption of lead and copper from aqueous solution on modified peat-resin
particles, Environmental Geochemistry and Health, 2004, 26, 311-317.
48. Senthilkumar R, Vijayaraghavan K, Thilakavathi M, Iyer PVR, Velan M, Application of seaweeds for the removal
of lead from aqueous solution, Biochemical Engineering Journal, 2007, 33, 211-216.
A. Ratna Kumari et al., IJSID 2011, 1 (3), 303-319
International Journal of Science Innovations and Discoveries, Vol ume 1, Issue 3, November-December 2011
319
49. Kar P, Misra M, Use of keratin fiber for separation of heavy metals from water, Journal of Chemical Technology
and Biotechnology, 2004, 79, 1313-1319.
50. Sayed SA, Saleh SM, Hasan EE, Removal of some polluting metals from industrial water using chicken feathers,
Desalination, 2005, 181, 243-255.
51. Banat F, Al-Asheh S, Biosorption of phenol by chicken feathers, Environmental Engineering and Policy, 2000,
2, 85-90.
52. Gupta V, Mittal A, Kurup L, Mittal J, Adsorption of a hazardous dye, erythrosine, over hen feathers, Journal of
Colloid and Interface Science, 2006, 304, 52-57.
53. Mittal A, Adsorption kinetics of removal of a toxic dye, Malachite Green, from wastewater by using hen
feathers, Journal of Hazardous Materials, 2006a, B133, 196-202.
54. Mittal A, Use of hen feathers as potential adsorbent for the removal of a hazardous dye, Brilliant Blue FCF,
from wastewater, Journal of Hazardous Materials, 2006b, B128, 233-239.
55. Box G, Draper N, Empirical Model Building and Response Surfaces, John Wiley & Sons, New York, 1987.
56. 56. Ross T, Indices for performance evaluation of predictive models in food microbiology, J. Appl. Bacteriol,
1996, 81, 501–508.
57. Samapundo S, Devlieghere F, De Meulenar B, Geeraerd AH, Van Impe JF, Debevere JM, Predictive modelling of
the individual and combined effect of water activity and temperature on the radial growth of Fusarium
verticilloides and F.proliferatum on corn, Int. J. Food Microbiol, 2005, 105, 35–52.
58. Lahlali R, Serrhini MN, Friel D, Jijakli MH, Predictive modeling of temperature and water activity (solutes) on
the in vitro radial growth of Botrytis cinerea Pers, Int. J. Food Microbiol, 2007, 114, 1–9.
59. Khokhar S, Richard K, Apenten O, Food Chemistry, 2003, 81, 133–140.
60. Lodi A, Solisio C, Converti A, Del Borghi M, Cadmium, zinc, copper, silver and chromium(III) removal from
wastewaters by Sphaerotilusnatans, Bioproc. Eng, 1998, 19, 197–203.
61. Chojnacka K, Chojnacki A, Gorecka H, Biosorption of Cr3+, Cd2+ and Cu2+ions by blue-green algae
Spirulinasp.: kinetics, equilibrium and the mechanism of the process, Chemosphere, 2005, 59, 75–84.