1
2
3
ADSORPTIVE REMOVAL OF METHYLENE BLUE DYE BY
MELON HUSK: KINETIC AND ISOTHERMAL STUDIES
4
Olajire, A. A1*; Giwa, A. A1 and Bello, I.A2
5
6
7
8
9
10
11
12
13
14
15
16
1
Industrial and Environmental Chemistry Unit,
Department of Pure and Applied Chemistry,
Ladoke Akintola University of Technology,
Ogbomoso – Nigeria
2
Physical Chemistry Unit
Department of Pure and Applied Chemistry,
Ladoke Akintola University of Technology,
Ogbomoso – Nigeria
17
ABSTRACT
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
The adsorption capacity of Methylene blue (MB) dye from aqueous solution onto raw
melon husk (RMH) was investigated under various experimental conditions. Batch
studies were performed to evaluate the effect of various experimental parameters such as
contact time, initial concentration of MB dye and dosage of RMH on the efficiency of the
sorption process. Optimum conditions for MB dye removal were found to be at an
adsorbent dosage of 8.0 g/L of solution for an equilibrium time of 120 min. Equilibrium
isotherms for the adsorption of MB dye on RMH were analyzed by Freundlich, Langmuir
and Temkin isotherm models and the goodness of fittings were inspected using linear
regression analysis (R2) and sum-of- square-error (SSE). The equilibrium data were well
described by Langmuir and Temkin equation at all range of operating parameters.
Lagergren, Elovich and Morris – Weber equations were employed to study kinetics of
sorption process. The sorption process was very rapid at the initial stage as 80% of the
dye was removed within the first 5 mins. The kinetics of the adsorption followed pseudo
– second order model with R2 values ranging from 0.999 to 1 for all initial dye
concentrations studied.
Keywords : Melon husk, isotherm, kinetics, methylene blue dye, adsorption.
35
36
37
38
*Author for all Correspondences, E-mail<olajireaa@yahoo.com>
39
Tel: +2348033824264
40
41
42
1. INTRODUCTION
43
There are several methods which can be used to treat dye wastewater. These include
44
biological, chemical and physical1. All these methods were found inefficient and
45
incompetent because of the stability of the dye towards light, oxidizing agents and
46
aerobic degradation. Among these methods, adsorption is widely used for its maturity and
47
simplicity. Of different adsorbent materials, activated carbon is the most popular for the
48
removal of pollutants from wastewater. However, its widespread use is restricted due to
49
high cost2. As such, numerous alternative materials have been investigated to adsorb dyes
50
from aqueous solution, using Methylene Blue as the model basic dye, such as guava leaf
51
powder3, dehydrated wheat bran carbon4, diatomaceous silica5, wheat shell6, NaOH-
52
treated pure kaolin7, bamboo charcoal8, silver fir (Abies amabilis) sawdust9 and activated
53
carbon from sugar beet molasses10.
54
Basic dyes are the brightest class of water soluble dyes used by the textile
55
industries, and Methylene blue is one of the most frequently used dyes in all industries11.
56
It dissociates into cation and chloride ion in aqueous solution12. Presence of this dye in
57
water leads to various health effects like eye burns, and irritation to the gastrointestinal
58
tract
59
methamoglobinemia, cyanosis and dyspnea, if inhaled directly. It may also cause
60
irritations to the skin7,13.
with
symptoms
of
nausea,
vomiting
and
diarrhea.
It
may lead
to
61
Two important physicochemical aspects for the evaluation of adsorption processes
62
as a unit operation are the adsorption equilibria and the adsorption kinetics. Equilibrium
63
relationships between adsorbent and adsorbate are described by adsorption isotherms,
64
usually the ratio between the quantity adsorbed and that remaining in the solution at a
2
65
fixed temperature at equilibrium. In the study of adsorption isotherm, linear regression is
66
frequently used to determine the best-fitting isotherm. The linear least-squares method
67
with linearly transformed isotherms has also been widely applied to confirm experimental
68
data, and isotherms using coefficients of determination. However, such transformations
69
of non-linear isotherms to linear forms implicitly alter their error structure, and may also
70
violate the error variance and normality assumptions of standard least squares14,15. It has
71
been reported that bias results from deriving isotherm parameters from linear forms of
72
isotherms, for example, Freundlich parameters producing isotherms which tend to fit
73
experimental data better at low concentrations and Langmuir isotherms tending to fit the
74
data better at higher concentrations16. Moreover, it has been also presented that using the
75
linear regression method for comparing the best-fitting isotherms is not appropriate17.
76
The advantage of using the non-linear method is that there is no problem with
77
transformations of non-linear isotherms to linear forms, and also they had the same error
78
structures when the best-fitting isotherms are compared18.
79
In this study, melon husk, an agricultural waste material, was used as the adsorbent
80
for its zero-cost and convenient acquisition in local markets. A non-linear method of
81
three widely used isotherms, the Langmuir, Freundlich and Temkin, were compared in an
82
experiment examining Methylene Blue adsorption onto melon husk. The data have also
83
been explained on the basis of kinetic models.
84
85
86
87
88
89
3
90
91
2. MATERIALS AND METHODS
92
93
2.1 Preparation of adsorbent
94
95
The melon husk used in this work was obtained from Aaradaa Market, a popular
96
farm produce market in Ogbomoso, Southwestern Nigeria. Debris and other relatively big
97
foreign materials were hand-picked from the husk, after which it was thoroughly washed
98
with distilled water, to remove soil and dust, drained and sun-dried. The dried material
99
was then ground, sieved into different particle sizes, and stored in air-tight containers as
100
raw melon husk (RMH) adsorbent.
101
102
103
2.2 Adsorbate
104
Methylene blue (Color index (C.I), 52015; λmax., 664 nm; molecular weight,
105
355.90), a cationic dye, used in this study was obtained in commercial purity (M & B
106
Laboratory Chemicals), and was used without any further purification.
107
108
109
N
H3C
N
CH3
N
S
+
CH3
Methylene blue; C.I, 52015
110
111
CH3 Cl
Mol. weight, 355.90
4
.3 H O
2
112
A stock solution of the dye was prepared by dissolving an accurately weighed
113
quantity of the dye (1.000 g) in deionized distilled water (ddH2O) to make a 1000 mg/L
114
solution. The experimental solutions of desired concentrations were prepared by
115
accurately diluting the stock solution with ddH2O.
116
117
2.3 Batch studies
118
For each study, a 25 mL of MB dye solution (of varying concentrations, ranging
119
from 5 to 500 mg/L) was prepared in a 250 mL leak-proof reaction bottles and a varying
120
amount of adsorbent, ranging from 0.025 to 0.75 g, was added to each bottle. The bottles
121
were tightly fixed in a horizontal shaker (SM 101 by Surgafriend Medicals) and the
122
shaking proceeded for 2 hrs to establish equilibrium, after which the mixture was left to
123
settle for ten minutes, and then filtered.
124
The absorbance of the filtrate was determined with UV–Visible Spectrophotometer
125
(Genesys 10 UV-VIS Scanning Spectrophotometer) adjusted at λmax (664 nm) of MB dye.
126
By referring to the calibration curve of the dye, the corresponding concentration of the
127
dye in the equilibrium solution was obtained. The percentage removal of MB dye and
128
equilibrium adsorption uptake, qe (mg/g) was calculated using the following
129
relationships:
130
131
132
133
% Sorption 
qe 
100 (Co  Ct )
Co
(Co  Ce )V
m
(1)
(2)
where q e is the amount of MB dye adsorbed (mg/g) at equilibrium; Co and Ct are the
initial concentration (at t = 0) and its concentration at time t = t (mg/L); m is the mass of
5
134
135
RMH (g); V is the volume of MB dye (L).
2.4 Error functions
136
The most common way to validate the isotherms is by inspecting the goodness of
137
fit using linear regression coefficients, R2. The R2 in the range of 0.9 to 1 indicates that
138
the isotherms have a satisfying agreement to the particular adsorption system in which the
139
value close to 1 is highly desirable. However, an occurrence of the inherent bias resulting
140
from the linearization might affect the final judgment. Therefore, an additional non-linear
141
regression error function has been considered to further validate the applicability of the
142
tested isotherms.
143
The sum-of-square-error (SSE) provides a better fit at the higher concentration
144
data as the magnitude of errors and the square of the errors increase with an increment in
145
concentration19. The mathematical formula of SSE used in this study is given by the
146
following equation20, 21.
SSE 
147
 (qe, exp .  qe, cal. ) 2 / N
148
where
149
qe cal is the amount of sorbate adsorbed at equilibrium calculated from the model (mg g-1),
150
qe,exp is the equilibrium value obtained from experiment (mg g-1) and N is the number of
151
data points.
152
153
3. RESULTS AND DISCUSSION
154
The adsorbent prepared from raw melon husk (RMH) was studied for dye
155
adsorption and the results, thus obtained, were analyzed for the sorption efficiency of dye
156
from aqueous solution, under different experimental conditions. The results of the studies
157
are explained in the following sections.
6
158
159
3.1 Effect of sorbent dosage
160
161
The effect of sorbent dosage on MB dye-sorption by RMH was studied (Fig.1) by
162
varying adsorbent dosage from 0.025 g to 0.750 g in 25 mL of 50 mg/L solution of the
163
MB dye while keeping other parameters (contact time, agitation speed, particle size,
164
temperature) constant.
165
As evident from Figure1, the adsorption capacity (qe) decreases with increasing
166
adsorbent dosage. However, percent sorption increases very rapidly from 90.19 to
167
99.66% as the dosage of RMH was increased from 0.025 g to 0.200 g and stays almost
168
constant up to 0.750 g of sorbent dosage. An increase in the sorption with the sorbent
169
dosage can be attributed to greater surface area and the availability of more adsorption
170
sites22, 23. At higher dosage, however, the incremental dye sorption becomes low, as the
171
surface dye concentration and MB dye solution come to equilibrium with each other.
172
173
174
175
3.2 Effect of the initial concentration of MB dye
176
shown in Figure 2. Adsorption capacity (qe) increases with increasing initial
177
concentration of MB dye. The increase in the initial concentration of the dye enhances the
178
interaction between the MB dye molecules and the surface of the adsorbent24. For
179
instance, an increase in the initial concentration of the MB dye from 5 mg/L to 500 mg/L
180
led to an increase in adsorption capacity (qe) from 1.249 to 47.38 mg/g. There was,
181
however, a corresponding decrease in percent sorption from 99.89 % to 37.91 %. Similar
The effect of the initial concentration of MB dye on the adsorption by RMH is
7
182
observation had also been reported by others22, 25, where decrease in percent sorption with
183
increasing initial concentration of sorbate resulted in increased adsorption capacity.
184
The relatively higher percentage sorption observed at low initial concentrations of
185
dye may be due to the high ratio of sorptive surface to the dye concentration, which
186
implied that a fewer number of dye molecules were competing for the available binding
187
sites on the adsorbent26. With increasing MB dye initial concentration however, the
188
sorptive surface to dye concentration decreases leading to reduced percent sorption27.
189
190
3.3 Effect of contact time
191
Our adsorption results reveal fast uptake of adsorbate species at the initial stages
192
of contact period. In fact, in all the initial concentrations of MB dye used, over 80%
193
sorption was achieved within the first 5 min. As contact time increases, the adsorption of
194
MB dye in the solution increases rapidly at the beginning with a gradual slow down until
195
it remained at about 120 minutes, which was then taken as the equilibrium time. A plot of
196
percent sorption against time (t) depicts a typical contact time for the sorption of MB dye
197
by RMH (Fig. 3). The initial rapid phase, which indicates a very spontaneous sorption
198
process, may be due to the large number of vacant sites available at the initial period of
199
the sorption28. The increase in quantity adsorbed continued slowly until a quasi-static
200
point is reached at about 120 min.
201
202
203
204
3.4 Adsorption isotherm models
205
and the adsorbate adsorbed on the surface of the adsorbent at equilibrium at constant
206
temperature. The equilibrium adsorption isotherm is very important to design the
An adsorption isotherm is the relationship between the adsorbate in the liquid phase
8
207
adsorption systems. For solid-liquid systems, several isotherms are available. The
208
Langmuir isotherm takes an assumption that the adsorption occurs at specific
209
homogeneous sites within the adsorbent and the equation takes the form29, 30:
qe 
210
q m k a Ce
1  k a Ce
(3)
211
where qe is the amount of dye adsorbed per unit mass at equilibrium (mg/g); qm is the
212
maximum possible amount of dye that can be adsorbed per unit mass of adsorbent
213
(mg/g); Ce is concentration of sorbate in the solution at equilibrium (mg/L); ka is the
214
sorption equilibrium constant. The linearised form of equation (3) is
Ce
C
1

 e
qe k a q m q m
215
216
A plot of
(4)
Ce
1
versus Ce gives a straight line (Fig. 4), with a slope of
and
qm
qe
1
. The effect of isotherm shape can also be used to predict whether an
k a qm
217
intercept
218
adsorption system is “favorable” or “unfavorable.” According to Hall et al.31, the
219
essential features of the Langmuir isotherm can be expressed in terms of a dimensionless
220
constant separation factor or equilibrium parameter KR, which is defined by the following
221
relationship:
222
KR 
1
1  K a Co
(5)
223
where KR is dimensionless separation factor; Ka is Langmuir constant ( L/mg); Co is the
224
initial concentration of sorbate (mg/L). The separation factor, KR, indicates the nature of
225
the adsorption process as given in Table 1. The Langmuir isotherm model was chosen for
226
the estimation of maximum adsorption capacity corresponding to complete monolayer
9
227
coverage on the RMH. The Langmuir data are given in Table 2. The sorption capacity,
228
qm, which is a measure of the maximum sorption capacity corresponding to complete
229
monolayer coverage showed that RMH adsorbent seemed to have a high monolayer
230
adsorption capacity. The adsorption coefficient, Ka, related to the apparent energy
231
(surface energy) of sorption was found to be 0.991 L/mg. The high magnitude of qm
232
(47.39 mg/g) indicates that the amount of MB dye per unit weight of sorbent (to form a
233
complete monolayer on the surface) seems to be high. A moderate Ka-value implies
234
moderate surface energy in MB dye-RMH system, thus indicating a probable moderate
235
binding between MB dye and sorbent32. The values of KR for initial dye concentrations
236
from 5 to 500 mg/dm3 were found to range from 0.00209 to 0.01680. The KR values
237
indicate that adsorption is more favourable for the Methylene blue/RMH system as they
238
fall between 0 and 1 (Table 1). The Langmuir model shows a strong conformation to
239
experimental data based on satisfactorily values of the obtained linear regression
240
coefficient, R2 and non-linear error analysis (Table 2).
241
242
243
244
245
The Freundlich isotherm is an empirical equation employed to describe the
heterogeneous system33. The equation is given below:
qe  K f Ce
1/ n
(6)
The linear form of the equation is:
log q e  log K f 
1
log C e
n
(7 )
246
where qe is the amount of MB dye adsorbed per unit mass of adsorbent (mg/g); Kf (L/g)
247
and n are Freundlich constants which are measures of adsorption capacity and intensity
248
of adsorption respectively34, Ce is the equilibrium concentration in mg/L.
10
249
From the straight line, obtained by plotting log qe against log Ce (Fig. 5), the
250
corresponding slope and intercept can be determined from 1/n and log Kf values. The
251
Freundlich data are given in Table 2, with regression factor, R2, of 0.8732 and sum of
252
error square (SSE) of 11.28. The values of Freundlich parameters n and Kf are 3.211 (i.e.
253
1/n = 0.311) and 12.578 respectively. From the Freundlich equation, the high value of Kf
254
of RMH (12.578) indicates high uptake of MB dye from aqueous solution32. Furthermore,
255
it was observed that the n-value satisfy the condition(s) of heterogeneity35, i.e 1 < n < 10
256
as well as 0 < 1/n < 1. The value of 1/n less than 1 describes a favorable nature of
257
methylene blue adsorption onto RMH, however, the model is not able to describe the
258
experimental data properly because of the poor linear correlation and high SSE values
259
(Table 2).
260
261
262
The Temkin isotherm was studied to explore the energy distribution pattern of the
RMH adsorbent. The linear form of the Temkin isotherm model can be expressed as;
q  a  b In Ce
(8)
263
where “q” is the amount of adsorbate adsorbed per unit weight of adsorbent, “a” is a
264
constant related to adsorption potential of the adsorbent and “b” is a constant related to
265
adsorption intensity. Temkin isotherm contains factors that explicitly take into account
266
the interactions between adsorbing species and the adsorbate.
267
The Temkin isotherm parameters generated from the Temkin isotherm plot (Fig. 6)
268
are given Table 2. Its correlation coefficient, R2 of 0.983 is also high, which is an
269
indication that the more energetic adsorption sites are occupied first by molecules of MB
270
dye, and that the adsorption process is likely to be chemisorption [36]. The Temkin
11
271
model shows a strong conformation to experimental data based on satisfactorily values of
272
the obtained linear regression coefficient, R2 and non-linear error analysis (Table 2).
273
274
3.5 Kinetic study
275
The modeling of the kinetics of adsorption of MB dye by RMH was investigated
276
by four common models, namely the Largergren pseudo-first order37, Ho’s pseudo-
277
second order17, 38, 39, Elovich model40 and Morris – Weber41 equations.
278
The pseudo-first order model was described by Largergren as;
log (qe  qt )  log qe 
279
k1t
2.303
(9)
280
The qe (mg g–1) is the amount of dye adsorbed at equilibrium, qt (mg g–1) is the amount
281
of dye adsorbed at time t and k1 is the pseudo first-order rate constant. A plot of log (qe
282
– qt) versus agitation time gives a straight line (Fig. 7), with coefficient of correlation, R2,
283
for the five different initial concentrations of MB dye investigated ranging from 0.8 –
284
0.9816. The values of pseudo-first order rate constant, k1, computed from the slope of the
285
linear plot, ranged from 1.41 x 10–2 – 4.08 x 10–2 min-1 (Table 3). The experimental qe
286
values did not agree with the calculated values based on the high values of its SSE. This
287
therefore shows that the adsorption of MB dye onto RMH does not follow a pseudo- first
288
order kinetics.
289
The pseudo-second order model42 is expressed as
290
t
1 t
 
qt h q e
(10)
291
h  k 2 qe
(11)
2
12
292
where qe is the amount of the solute adsorbed at equilibrium per unit mass of adsorbent
293
(mg g–1) , qt is the amount of solute adsorbed (mg g–1) at any given time t (min) and k2 is
294
the rate constant for pseudo-second-order adsorption (g mg–1 mm–1) and h, known as the
295
initial sorption rate.
296
If the sorption follows pseudo-second order, h, is described as the initial rate
297
constant as t approaches zero. From the plot (Fig. 8), values of k2, R2 and qe were
298
calculated (Table 3). The correlation coefficients obtained for the pseudo-second-order
299
kinetic model are very high; and are close or equal to unity (0.999 – 1) for the initial MB
300
dye concentrations studied. There is also a very good agreement between the
301
experimentally obtained and calculated values of qe based on the low values of its SSE
302
(Table 3). This shows that the mechanism of the adsorption of MB dye by RMH can best
303
be described by the pseudo-second-order kinetic model, based on the assumption that the
304
rate limiting step may be chemisorption involving valence forces through sharing or
305
exchange of electrons between the hydrophilic edge sites of the RMH and MB dye ions
306
38, 43
307
increase in sorption capacity from 1.23 to 24.51 mg/g; which is also in agreement with
308
observations of others44, 45.
309
. Increasing the initial concentration of MB dye from 5 to 100 mg/L causes an
The Elovich model is expressed as46, 47;
qt 
1

In ( ) 
1

In t
(12)
310
where  is the initial adsorption rate (mg g 1 min 1 ),  is the desorption cons tan t
( g mg 1 ) and qt is the amount of solute adsorbed (mg g 1 ) at any given time, t (min .)
13
311
A plot of qt versus In t gives a straight line with intercept
312
(Fig. 9).
1
In ( ) and slope,  

 
1
313
Table 3 shows the kinetic data of Elovich model for the adsorption of MB dye on
314
RMH. The initial adsorption rate, α; desorption constant, β; and the correlation
315
coefficients, calculated from the plot for the different initial concentrations of MB dye are
316
given in Table 3. The correlation coefficients obtained from the Elovich kinetic model are
317
also high; ranging from 0.8714 to 0.9591. Thus, Elovich equation could also be a good
318
model for the adsorption process48.
319
The relationship between the initial concentrations of MB dye, Co, and the Elovich
320
initial adsorption rate, α, was also investigated. As shown in the table (Table 3), the
321
values of α increase with increasing Co, until a maximum is reached, after which a further
322
increase in Co resulted in a decrease in α. For instance, α rose from 4.5 x 1066 to 3.6 x
323
10111 mg g– 1 min– 1 with an increase in Co from 5 mg/L to 25 mg/L (Table 3). Further
324
increase in Co from 25 mg/L through 50 mg/L to 100 mg/L recorded a drastic fall in α
325
from 3.6 x 10111 to 1.6 x 109 mg g–
326
observed between Co and the Elovich model desorption constant, β. For instance, an
327
increase in Co from 5 mg/L to 25 mg/L led to a decrease in β from 133.333 to 42.918 g
328
mg–1 (Table 3).
329
330
331
1
min–1. However, an inverse relationship was
The kinetics of sorption of MB dye was also investigated using Morris-Weber
equation41 in the following form:
qt  K id t
(13)
14
332
where qt is the sorbed concentration at time “t”, and “Kid” is the rate constant of
333
intraparticle transport. According to Morris and Weber41, a plot of sorption capacity at a
334
given time, qt, versus √t should be a straight line if intraparticle diffusion is involved; and
335
if it is the only rate-determining factor, the line passes through the origin. However, if the
336
plot has an intercept (i.e. does not pass through the origin), it shows that intra-particle
337
diffusion may not be the only factor limiting the rate of the sorption process49. A
338
modified form of Morris-Weber equation that takes care of boundary layer resistance was
339
therefore proposed as48, 50, 51:
340
341
342
qt  K id t  X i
(14)
where Xi depicts the boundary layer thickness [51].
1
343
The qt was plotted against, t 2 for the sorption of MB on RMH for different initial
344
dye concentrations (Fig. 10). The correlation coefficients obtained from the plots were
345
not high (0.6612 – 0.9689) and the straight lines do not pass through the origin (the
346
intercepts > 0). The deviation of these lines from the origin indicates that intra-particle
347
diffusion may be a factor in the sorption process, but not the only controlling step52. The
348
values of Kid computed from the slopes of the plot ranged from 0.003 – 0.3398 mg g-1
349
min-1/2. The larger the intercept, the greater is the contribution of the surface sorption
350
(boundary layer resistance) in the rate–limiting step53. Both Kid and Xi have direct
351
relationship with the initial concentration of MB dye (Table 3). Evidently from our
352
results, the higher the initial concentration, the greater is the effect of boundary layer and
353
its contribution on the rate determining step.
354
15
355
3.6 Error Analysis
356
Ho15 reported that it is better to use the non-linear analysis method for analyzing
357
the experimental data instead of linear regression analysis alone to compare the best-
358
fitting isotherms. When using the non-linear method, there was no problem with
359
transformations of non-linear isotherms to linear forms. In this study, a non-linear
360
analysis was used to compare the best-fitting isotherms using sum-of-error square.
361
Analysis of nonlinear error function (SSE test), revealed that both Langmuir and
362
Temkin models are applicable since the resulting errors were very small (Table 2). These
363
findings are very important to indicate that RMH might have homogenous and
364
heterogeneous surface energy distributions. However, the Freundlich model is not able to
365
describe the experimental data properly because of the poor linear correlation and high
366
SSE values (Table 2). The SSE value more than 5% is not recommended due to
367
intolerant margin of deviation between the experimental data and the model calculated
368
data.
369
Further verification of the applicability of the kinetic models was also tested with
370
the sum of error squares (SSE) and linear regression. The higher the value of R2 and the
371
lower the value of SSE, the better is the goodness of fit and therefore the applicability of
372
the kinetic model. Values of SSE calculated from pseudo-second order equation were
373
very low at all the concentration range considered, when compared with those of others
374
(Table 3), which further confirms the validity of the applicability of the pseudo-second
375
order kinetic model to the present sorption process over the other kinetic models
376
investigated in this study.
377
378
16
379
CONCLUSION
380
Raw melon husk (RMH) is able to adsorb Methylene Blue dye from aqueous solutions.
381
Optimum sorption of MB dye by RMH is achieved at an adsorbent dosage of 0.200 g/L
382
of solution for an equilibrium time of 120 minutes. It is successful to use the coefficient
383
of determination of the non-linear method for comparing the best fit of the Langmuir,
384
Freundlich, and Temkin isotherms. The Temkin and the Langmuir isotherms had higher
385
coefficients of determination than that of Freundlich isotherm but Langmuir might be the
386
best-fitting isotherm. The kinetic data can best be described by the pseudo second order
387
kinetic model. Apparently, it can be concluded that the most applicable isotherm to
388
describe methylene blue dye–RMH adsorption system are Langmuir and Temkin
389
isotherms. Their values of regression coefficients, R2 and the non-linear error function
390
(SSE) are satisfactory. The Freundlih isotherm is the least applicable isotherm as the
391
linear regression coefficients, R2 were less than 0.9 and the sum of error square (SSE) is
392
more than 5%.
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
REFERENCES
[1] Robinson, T., Mc Mullan, G., Marchant, R., Nigam, P. (2001). Remediation of dyes
in textile effluent, a critical review on current treatment technologies with a
proposed alternative. Bioresour. Technol., 77, 247 – 255.
[2] Babel, S. and Kurniawan, T.A. (2003). Low-cost adsorbents for heavy metals uptake
from contaminated water: A review. J. Hazard. Mater. 97, 219-243.
[3] Ponnusami, V., Vikram, S. and Srivastava, S.N. (2008). Guava (Psidium guaiava) leaf
powder: Novel adsorbent for removal of Methylene blue from aqueous
solutions. J. Hazard. Mater. 152, 276-286.
[4] Özer, A. and Dursun, G. (2007). Removal of Methylene blue from aqueous solution
by dehydrated wheat bran carbon. J. Hazard. Mater. 146, 262-269.
[5] Al-Qodah, Z., Lafi, W.K., Al-Anber, Z., Al-Shannag, M. and Harahsheh, A. (2007).
Adsorption of Methylene blue by acid and heat treated diatomaceous silica.
Desalination. 217, 212- 224.
[6] Bulut, Y. and Aydin, H. (2006). A kinetics and thermodynamics study of Methylene
blue adsorption on wheat shells. Desalination. 194, 259-267.
17
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
[7] Ghosh, D. and Bhattacharyya, K.G. (2002) Adsorption of Methylene blue on
kaolinite. Appl. Clay. Sci. 20, 295-300.
[8] Zhu, Y.N., Wang, D.Q., Zhang, X.H. and Qin, H.D. (2009). Adsorption removal of
Methylene blue from aqueous solution by using bamboo charcoal. Fresen.
Environ. Bull. 18, 369-376.
[9] Zafar, S.I., Bisma, M., Saeed, A. and Iqbal, M. (2008). FTIR spectrophotometry,
kinetics and adsorption isotherms modelling, and SEM-EDX analysis for
describing mechanism of biosorption of the cationic basic dye Methylene blue
by a new biosorbent (Sawdust of Silver Fir; Abies Pindrow). Fresen. Environ.
Bull. 17, 2109-2121.
[10] Aci, F., Nebioglu, M., Arslan, M., Imamoglu, M., Zengin, M. and Kucukislamoglu,
M. (2008). Preparation of activated carbon from sugar beet molasses and
adsorption of Methylene blue. Fresen. Environ. Bull. 17, 997-1001.
[11] Reid R. (1996). Go green - A sound business decision. 1, Journal of the Society of
Dyers and Colourists; 112:103-105.
[12] Tor, A. and Cengeloglu, Y. (2006) Removal of Congo red from aqueous solution by
adsorption onto acid activated red mud, J. Hazard. Mater.;138:409-415.
[13] Senthilkumaar, S., Varadarajan, PR., Porkodi, K., Subbhuraam, C.V. (2005).
Adsorption of Methylene blue onto jute fiber carbon: Kinetics and equilibrium
studies, J. Colloid Interface Sci.;284:78-82.
[14] Ratkowsky, D.A. (1990). Handbook of Nonlinear Regression Models. New York:
Marcel Dekker.
[15] Ho, Y.S. (2004). Selection of optimum sorption isotherm. Carbon. 42, 2115-2116.
[16] Richter, E., Schutz, W. and Myers, A.L. (1989). Effect of adsorption equation on
prediction of multicomponent adsorption equilibria by the ideal adsorbed
solution theorys. Chem. Eng. Sci. 44, 1609-1616.
[17] Ho, Y.S. (2004). Citation review of Lagergren kinetic rate equation on adsorption
reactions. Scientometrics, 59 (1), 171-177.
[18] Ho, Y.S. (2006). Isotherms for the sorption of lead onto peat: Comparison of linear
and non-linear methods. Pol. J. Environ. Stud. 15, 81-86.
[19] Gunay, A. (2007). Application of nonlinear regression analysis for ammonium
exchange by natural (Bigadic) clinoptilolite. J. Hazard. Mater. 148(3): 708-713.
[20] Arslanoglu, F. N., Kar, F. and Arslan, N. (2005). Adsorption of dark coloured
compounds from peach pulp by using granular activated carbon. Journal of Food
Engineering, 68(4): 409-417.
[21] Tseng, R.-L., F.-C. Wu and R.S. Juang, (2003). Liquid-phase adsorption of dyes and
phenols using pinewood-based activated carbons. Carbon, 41(3): 487-495.
[22] Azhar, S.S; Liew, G.A; Suhardy, D; Hafiz, F.K; Irfan H.M.D (2005). Dye removal
from aqueous solution by using adsorption on treated sugarcane bagasse. Am. J.
Appl. Sci. 2(11), 1499-1503.
[23] Esmaili, A; Ghasemi, S; Rustaiyan, A (2008): Evaluation of the activated carbon
prepared of algae gracilaria for the biosorption of Cu(II) from aqueous solution.
American-Eurasian J. Agric. & Env. Sci. 3(6), 810-813
[24] Haris, M.R.H., Sathasvam, K. (2009). The removal of methyl red from aqueous
solution using banana pseudostem fibers. Am. J. Appl. Sci., 6(9), 1690–1700.
[25] Daniela, S. and Doina, B. (2005). Equilibrium and kinetic study of reactive dye
18
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
brilliant red He-3b adsorption by activated charcoal Acta. Chim. Stov. 52, 73-79.
[26] Gupta, R. and Mohapatra, H. (2003). Microial biomass: An economical alternative
for removal of heavy metals from waste water. Indian J. Expt. Biol., 41, 945 –
966.
[27] Bansat, M., Singh, D., Garg, V.K and Rose, P. (2009). Use of agricultural waste for
the removal of nickel ions from aqueous solution: equilibrium and kinetic
studies. Int. J. Environ. Sci. and Engr., 1(2), 108 – 114.
[28] Wong, S.Y., Tan, Y.P., Abdullah, A.H., Ong, S.T. (2009). The removal of basic and
reactive dyes using quartenised sugar cane bagasse. J. Phy. Sci., 20 (1), 59– 74.
[29] Langmuir, I. (1918). The adsorption of gases on plane surfaces of glass, mica and
platinum, Journal of American Chemical Society; 40:1361-1403.
[30] Ho, Y.S., Huang, C.T. and Huang, H.W. (2002). Equilibrium sorption isotherm for
metal ions on tree fern, Process Biochem., 37:1421-1430.
[31] Hall, K.R., Eagleton, L.C., Acrivos, A., Vermeulen, T. (1966). Pore- and soliddiffuion kinetics in fixed-bed adsorption under constant-pattern conditions. Ind.
Eng. Chem. Fund.; 5:212-223.
[32] Aksu, Z and Yener, J. (2001). A comparative adsorption/biosorption study of monochlorinated phenols onto various sorbents. Waste Manage., 21, 695 – 702.
[33] Freundlich, H.M.F. (1906). Über die adsorption in lösungen, Z. Phys. Chem. 57A,
385–470.
[34] Malik, P.K (2004): Dye removal from wastewater using activated carbon developed
from sawdust: Adsorption equilibrium and kinetics. J. Hazard. Mater. 113, 81–88.
[35] Khalid, N., Ahmad, S., Toheed, A. (2000). Potential of rice husk for antimony
removal., Appl. Radiat. Isot., 52, 30 – 38.
[36] Lain-Chuen, J., Cheng-Cai, W., Chung-Kung, L., Ting-Chu, H. (2007). Dyes
Adsorption onto organoclay and MCM-41. J. Env. Eng. Manage. 17(1), 29-38
[37] Lagergren, S. (1898). Zur theorie der sogenannten adsorption gelöster stoffe.
Kungliga Svenska Vetenskapsakademiens. Handlingar, Band 24(4), 1-39.
[38] Ho, Y.S. (2006). Review of second-order models for adsorption systems. Journal of
Hazardous Materials, 136 (3), 681-689.
[39] Ho, Y.S. and McKay, G. (1998). Sorption of dye from aqueous solution by peat.
Chemical Engineering Journal, 70 (2), 115-124.
[40] Zeldowitsch, J. (1934). Über den mechanismus der katalytischen oxydation von CO
an MnO2. Acta Physicochimica URSS, 1 (3-4), 449-464.
[41] Weber, Jr., W.J. and Morris, J.C. (1963). Kinetics of adsorption on carbon from
solution. Journal of the Sanitary Engineering Division-ASCE, 89, 31-59.
[42] Ho, Y.S (1995): Adsorption of heavy metals from waste streams by peat. Ph.D
thesis, The University of Birmingham, Birmingham, UK.
[43] Gucek, A., Sener, S., Bilgen, S., Mazmanci, A. (2005). Adsorption and kinetic
studies of cationic and anionic dyes on pyrophyllite from aqueous solutions. J.
Colloid Interf. Sci., 286, 53-60.
[44] Oladoja, N.A., Asia, I.O., Aboluwoye, C.O., Oladimeji, B., Ashogbon, A.O. (2008).
Studies on the sorption of basic dye by rubber (herea brasiliensis) seed
shell. Turkish J. Eng. Env. Sci. 32, 143-152.
[45] Malarvizhi, R., Sulochana, N. (2008). Sorption isotherm and prepared from wood
apple shell. J. Env. Prot. Sci. 2, 40-46
19
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
[46] Sparks, D.L. (1986). Kinetics of reactions in pure and mixed systems in soil physical
chemistry. CRC Press, Florida, 21 – 25.
[47] Okiemen, F.E. and Onyega, V.U. (1989). Binding of cadmium, copper, lead and
nickel ions with melon (Citrullus vulgaris) seed husk. Biological waste, 29,
11 –16.
[48] Igwe, J.C. and Abia, A.A. (2007). Adsorption kinetics and intraparticulate
diffusivities for bioremediation of Co(II), Fe(II) and Cu(II) ions from wastewater
using modified and unmodified maize cob. Int. J. Phy. Sci., 2(5), 119 – 127.
[49] Ho, Y.S., Mckay, G. (2003). Sorption of dyes and copper ions onto biosorbents.
Proc. Biochem., 38, 1047 – 1061
[50] Mckay, G., Poots, J.P. (1980). Kinetics and diffusion processes in colour removal
from effluent using wood as adsorbent. J. Chem. Technol. Biotechnol., 30,
279 – 292.
[51] Abia, A.A; Didi, O.B; Asuquo, E.D. (2006). Modeling of Cd2+ sorption kinetics
from aqueous solutions onto some thiolated Agricultural waste adsorbents. J.
Appl. Sci. 6(12), 2549-2556.
[52] Onge, S.A., Seng, C.E., Lom, V.(2007). Kinetic of adsorption of Cu(II) and Cd(II)
from aqueous solution on rice husk and modified rice husk, Elect. J. Env. Agric.
and Food Chem., 6(2), 1764 – 1774.
[53] Arvoli, S. and Thenkuzhali, M. (2008). Kinetics, mechanistics, thermodynamics and
equilibrium studies on the adsorption of rhodamine B by acid activated low
cost carbon. E- Journal of Chemistry, 5(2), 187 – 200.
20
549
550
551
Table 1: The process nature of separation factor
KR
KR > 1
KR = 1
0<K<1
KR = 0
552
553
554
555
556
557
558
Type of process
Unfavorable
Linear
Favorable
Irreversible
Table 2: Isotherm model parameters for adsorption of MB dye onto RMH
Freundlich
R2
0.873
SSE(%)
kf
11.28
12.578
Langmuir
1/n
0.3114
R2,
0.999
SSE(%)
3.71
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
21
qmax
47.39
Temkin
ka
0.991
R2
0.983
SSE(%) a
2.46
23.17
b
4.72
585
586
587
588
589
590
Table 3: Comparison of rate constants and other parameters for various kinetic
models at different initial concentrations
Parameters
qe (expt.)
Pseudo-first order
R2
k1
qe (cal.)
SSE(%)
Pseudo –second order
R2
k2
qe (cal.)
h
SSE(%)
Elovich model
R2
α
β
SSE(%)
Morris-Weber
R2
Kid
Xi
SSE(%)
C0 (mg/L)
5
1.232
10
2.468
25
6.192
50
12.426
100
24.347
0.864
0.016
0.037
103.2
0.910
0.024
0.031
129.7
0.800
0.014
0.070
125.5
0.741
0.017
0.632
508.9
0.982
0.041
3.725
427.3
1.000
2.106
1.231
3.19
0.1
1.000
3.358
2.468
20.4
0.1
1.000
1.306
6.188
50.0
0.4
1.000
0.165
12.407
25.3
1.6
0.999
0.037
24.509
22.4
1.2
0.861
4.5x1066
133.33
0.68
0.817
3.2x10107
104.17
0.15
0.893
3.6x10111
42.92
0.22
0.923
1.4x1019
4.05
4.69
0.959
1.6x109
1.07
27.66
0.9689
0.003
1.193
0.23
0.6612
0.0033
2.432
0.45
0.7394
0.0081
6.078
1.47
0.7363
0.0844
11.515
12.32
0.8619
0.3398
20.867
68.15
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
22
50
102
45
100
40
qe (mg/g)
30
96
25
94
20
qe
% MB Sorption
15
% MB Sorption
98
35
92
10
90
5
0
88
0
606
607
608
609
0.2
0.4
RMH dosage (g)
0.6
0.8
Fig. 1: Effect of adsorbent dosage on MB dye removal
50
120
45
qe (mg/g)
35
80
30
qe
% MB sorption
25
60
20
40
15
10
% MB sorption
100
40
20
5
0
0
610
611
612
613
100
200
300
400
500
Initial concentration of MB (mg/L)
0
600
Fig. 2: Effect of MB dye concentration on sorption by RMH
14
120
12
100
qt (mg/g)
80
8
60
6
qt
%MB Sorption
4
20
2
0
0
614
615
616
617
40
% Mb Sorption
10
50
100
150
0
200
t (min)
Fig. 3: Effect of contact time on sorption of MB onto RMH
23
7
6
5
Ce/qe
4
3
2
1
0
0
618
619
620
621
50
100
150
200
250
300
350
Ce (mg/L)
Fig. 4:
Langmuir sorption isotherm of MB onto RMH
2
1.8
1.6
1.4
log qe
1.2
1
0.8
0.6
0.4
0.2
0
-3
622
623
624
625
-2
-1
0
1
2
3
log Ce
Fig. 5: Freundlich sorption isotherm of MB dye onto RMH
24
60
50
40
qe
30
20
10
0
-6
-4
-2
0
2
4
6
8
-10
ln Ce
626
627
628
629
Fig. 6: Temkin sorption isotherm of MB dye onto RMH
1
0.5
0
log (qe-qt)
0
20
40
60
80
100
120
140
-0.5
5mg/l
10mg/l
25mg/l
50mg/l
100mg/l
-1
-1.5
-2
-2.5
-3
630
631
632
633
t (min)
Fig. 7: Pseudo first-order kinetic plot for the sorption of MB onto RMH
25
140
120
100
5mg/l
10mg/l
t/qt
80
25mg/l
50mg/l
100mg/l
60
40
20
0
0
50
100
150
200
t (min)
634
635
636
Fig. 8: Pseudo -second order kinetic plot for the sorption of MB onto RMH
30
25
5mg/l
qt (mg/g)
20
10mg/l
25mg/l
50mg/l
15
100mg/l
10
5
0
0
637
638
639
640
1
2
3
4
5
6
ln t
Fig. 9: Elovich plot for the sorption of MB onto RMH
26
30
25
qt
20
5mg/l
10mg/l
25mg/l
50mg/l
100mg/l
15
10
5
0
0
641
642
643
644
645
2
4
6
8
t
10
12
14
1/2
Fig. 10: Morris-Weber equation for the sorption of MB onto RMH
27