1
The Marine Macroalga Cystoseira baccata as Biosorbent for Cadmium(II)
2
and Lead(II) Removal: Kinetic and Equilibrium Studies.
3
P. Lodeiro, J.L. Barriada, R. Herrero* and M. E. Sastre de Vicente
4
Departamento de Química Física e Enxeñería Química I, Universidade da Coruña,
5
Alejandro de la Sota 1, 15071 A Coruña, Spain.
6
*Corresponding author e-mail: erob@udc.es; Phone: (34) 981 167000 (ext. 2126);
7
Fax: (34) 981 167065
8
1
9
Capsule: Marine macroalgae constitutes a promising material for the development of a
10
low cost biosorption technology for the removal of lead(II) and cadmium(II) from
11
wastewaters.
12
13
ABSTRACT
14
This work reports kinetic and equilibrium studies of cadmium(II) and lead(II)
15
adsorption by the brown seaweed Cystoseira baccata. Kinetic experiments
16
demonstrated rapid metal uptake. Kinetic data were satisfactorily described by a
17
pseudo-second order chemical sorption process. Temperature change from 15 to 45 ºC
18
showed small variation on kinetic parameters. Langmuir-Freundlich equation was
19
selected to describe the metal isotherms and the proton binding in acid-base titrations.
20
The maximum metal uptake values were around 0.9 mmol·g-1 (101 and 186 mg·g-1 for
21
cadmium(II) and lead(II), respectively) at pH 4.5 (raw biomass), while the number of
22
weak acid groups were 2.2 mmol·g-1 and their proton binding constant, KH, 103.67
23
(protonated biomass). FTIR analysis confirmed the participation of carboxyl groups in
24
metal uptake. The metal sorption was found to increase with the solution pH reaching a
25
plateau above pH 4. Calcium and sodium nitrate salts in solution were found to affect
26
considerably the metal biosorption.
27
28
Keywords: biosorption; marine macroalgae; cadmium(II); lead(II); potentiometric
29
titration
30
2
31
INTRODUCTION
32
Pollution by metal ions has become a major issue throughout many countries
33
because the contents of metal ions in potable waters and wastewaters often exceed the
34
admissible sanitary standards.
35
The effluents from industrial processes represent one of the most important
36
sources of heavy metal pollution. If these discharges are emitted without treatment, they
37
may have an adverse impact on the environment and consequently on human health.
38
Cadmium, lead and mercury are the heavy metals with the greatest potential hazard due
39
to their high toxicity, so they deserve special consideration.
40
In recent years, one of the main goals regarding heavy metal removal from
41
wastewater consists in the reduction of these pollutants at very low levels. Conventional
42
techniques such as precipitation or ion exchange are not useful in this case or when the
43
metals are present at concentrations between 1 to 100 mg·L-1. Therefore, the
44
development of an alternative technology must be considered.
45
Biosorption as a wastewater treatment process has been found to be an
46
economically feasible alternative for metal removal. Basically, it can be based on the
47
following mechanisms: physical adsorption, ion exchange, complexation and
48
precipitation. Biosorption may not necessarily consist of a single mechanism. In many
49
sorption processes several mechanisms often act in combination and it is difficult to
50
distinguish between the single steps (Lacher and Smith, 2002).
51
Among the different biological substrates studied, algal biomass has received
52
much attention due to the cost saving, low sensitivity to environmental and impurity
53
factors, the possible contaminant recovery from the biomaterial and its elevated
54
adsorption capacity, higher than activated carbon and comparable to those of synthetic
55
ion exchange resins. This is the case of C. baccata, which constitute a renewable,
3
56
ubiquitous natural marine resource, available in large quantities in littoral zones and
57
therefore, an inexpensive sorbent material.
58
The algal cell wall plays an important role in proton and metal binding due to its
59
high content in polysaccharides with acid functional groups (Crist et al., 1988; Schiewer
60
and Volesky, 1997). The main substances of this type in brown algae are alginates,
61
which usually constitute around 20-40 % of the total dry weight (Percival and
62
McDowell, 1967), and fucoidans. Moreover, the carboxyl groups of alginates are likely
63
to be the main functionalities involved in metal binding reactions (Schiewer and Wong,
64
2000) because of their higher abundance with regard to both carboxyl and amine groups
65
of the proteins.
66
The present work reports the study of the lead(II) and cadmium(II) binding to
67
raw biomass of C. baccata. The biosorption process has been analysed through batch
68
experiments with regard to the influence of the initial metal concentration, pH, salinity
69
of the solution and temperature. In order to investigate the sorption behaviour both,
70
kinetic and equilibrium models were tested.
71
72
MATERIALS AND METHODS
73
Biomass
74
Samples of the brown marine alga Cystoseira baccata were collected from the
75
coast of A Coruña (Galicia, NW Spain) in July 2002. The alga was washed with tap and
76
deionised water to eliminate impurities, oven dried at 60 ºC overnight, crushed with an
77
analytical mill, sieved (size fraction of 0.5-1 mm) and stored in polyethylene bottles
78
until use. The samples for the potentiometric titrations were acid-treated, in order to
79
transform the biomass into its fully protonated form, by soaking and shaking it in a 0.2
80
mol·L-1 HNO3 solution in a rotary shaker (175 rpm) for 4 h, at a biomass concentration
4
81
of 10 g·L-1. Afterwards, the material was rinsed thoroughly with deionised water until
82
pH 4.5 was attained. Following filtration, treated biomass was dried in an oven at 60ºC
83
overnight.
84
Kinetic studies
85
The experiments were carried out at natural pH (between 4-4.3 for lead and 4.6-
86
5.3 for cadmium), adding 0.25g of the biomass to 100 ml of a 2 mmol·L-1 solution of
87
lead(II) (from Pb(NO3)2) or cadmium(II) (from Cd(NO3)2·4H2O) and sufficient NaNO3
88
salt to keep the ionic strength at 0.05 mol·L-1 in a glass cell furnished with a
89
thermostated jacket (the experiments were carried out at 15, 25, 35 and 45.0  0.1 ºC).
90
A nitrogen stream was used to remove dissolved O2 and CO2.
91
A lead(II) or cadmium(II) ion selective electrode (PbISE from Radiometer and
92
CdISE from Orion) with a Ag/AgCl reference electrode (Orion), previously calibrated
93
in the corresponding metal concentration at the same ionic strength was employed to
94
follow the reaction kinetics.
95
The metal uptake at each moment was calculated from the equation:
q M ,t 
V  (C M ,i  C M ,t )
ms
(1)
96
where V is the volume of metal solution, CM,i is the initial metal concentration, CM,t is
97
the concentration of metal in solution at a given time, and ms is the mass of sorbent (dry
98
weight).
99
100
Adsorption isotherms
101
Samples (40 mL) of twelve lead(II) solutions of several concentrations, from
102
0.048 to 9.65 mmol·L-1 (10 to 2000 mg·L-1) and eight cadmium(II) solutions, from
103
0.089 to 3.11 mmol·L-1 (10 to 350 mg·L-1), prepared by dissolving Pb(NO3)2 and
104
Cd(NO3)2·4H2O respectively, in deionised water, were placed in a 100 mL Erlenmeyer
5
105
flask containing 0.1 g of alga. The mixtures were stirred in a rotary shaker at 175 rpm
106
for 4 hours until equilibrium was reached. Solutions of NaOH and HNO3 were used for
107
pH adjustment to a value of 4.5  0.1. After that, the algal biomass was filtered through
108
a 0.45 m pore size cellulose nitrate membrane filter and the filtrate was analysed for
109
the remaining metal ion concentration by differential pulse anodic stripping
110
voltammetry (DPASV) using a 757 VA Computrace (Metrohm) with a conventional
111
system of three electrodes: hanging mercury drop electrode as working electrode, Pt
112
auxiliary electrode and 3 mol·L-1 Ag/AgCl as reference electrode.
113
The amount of metal sorbed at equilibrium, QM, which represents the metal
114
uptake, was calculated from the difference in metal concentration in the aqueous phase
115
before and after adsorption, according to an equation formally identical to Eq. 1, but
116
referred to the equilibrium concentration; where now CM, the equilibrium concentration
117
of metal in solution, substitutes CM,t.
118
119
Potentiometric titrations
120
For each titration, ca. 0.5 g of protonated algal biomass were placed in a
121
thermostated titration cell at 25.0  0.1 ºC, with 100 mL of 0.05 mol·L-1 NaNO3
122
solution. Inert gas (nitrogen 99.9995%) was bubbled into the solution. A certain amount
123
of HNO3 was also added to yield an initial pH value ca. 2. The titrating solution (0.05
124
mol·L-1 NaOH, prepared with boiled deionised water and standardised with potassium
125
hydrogen phthalate, Carlo Erba PRE) was added from a Crison microBu 2031 automatic
126
burette. Emf measurements were done by a Crison micropH 2000 meter equipped with
127
a GK2401C Radiometer combination glass electrode (saturated Ag/AgCl as reference).
128
The procedure followed for the titrations and glass electrode calibrations is described in
129
greater detail elsewhere (Rey-Castro et al., 2003).
6
130
131
The amount of proton bound (mmol·g-1) is calculated from the acid and base
additions by means of charge balance considerations:
Q H  Q max, H 
V C V a C a K w
VT 
 C H  b b

ms 
VT
CH



(2)
132
where Vi, Ci are the volume and concentration of the acid and base added (subscripts a
133
and b refer to acid and base, respectively), VT is the total volume in the titration vessel,
134
KW is the ionic product of water, CH is the concentration of protons that remains in
135
solution and Qmax,H is the total amount of titratable groups, calculated from the
136
equivalence point of the titrations.
137
138
Fourier Transform Infrared analysis
139
FTIR spectroscopy was used to identify the chemical groups present in the alga.
140
The samples were examined using a Bruker spectrophotometer (model Vector 22)
141
within the range 400-4000 cm-1. The relation alga/KBr employed was approximately
142
1% in weight. The background obtained from the scan of the air (without sample in the
143
spectrophotometer window) was automatically subtracted from the sample spectra.
144
145
Influence of pH on metal biosorption
146
The dependence of Cystoseira baccata metal uptake on pH was studied through
147
batch sorption experiments in the pH range from 1 to 5.5, with an initial lead(II) or
148
cadmium(II) concentration of 2.41 mmol·L-1 and 2.5 g·L-1 algal doses. The pH was
149
adjusted by addition of NaOH and HNO3 solutions.
150
151
RESULTS AND DISCUSSION
152
1. Kinetics of adsorption
7
153
Kinetic studies of cadmium(II) and lead(II) adsorption by the algae Cystoseira
154
baccata were developed in order to determine the minimum necessary time to achieve
155
the sorption equilibrium. Moreover, the temperature dependence of metal biosorption
156
was also studied.
157
Among several studies on biosorption kinetics of metals by seaweed biomass it
158
was found that the sorption rate increases sharply at the beginning of the process,
159
followed by a slower uptake rate as equilibrium is approached. The batch experiments
160
carried out for an initial metal concentration of 2 mmol·L-1(Figure 1) showed that over
161
90% of total adsorption is reached in around 17 minutes for the cadmium(II) adsorption
162
(50% in 1 minute) and in around 47 minutes for lead(II) (50% in 5 minutes).
163
Equilibrium sorption experiments were conducted during approximately 4 hours, hence
164
we ensured that equilibrium conditions were attained.
165
This fast metal uptake observed for Cystoseira baccata is of particular
166
importance to process design and operation in practical uses. The mechanism of
167
biosorption and potential rate controlling steps, such as mass transport and chemical
168
reaction procedures, must be investigated to properly understand adsorption kinetics.
169
When the biomass is employed as a free suspension in a well-agitated batch system, the
170
effect of external film diffusion on biosorption rate can be assumed not significant and
171
ignored in any kinetic analysis.
172
Various models have been tested to analyse the kinetics of sorption process (e.g.
173
Elovich, diffusion, pseudo-first and pseudo-second order equations). Only the pseudo-
174
second order equation proposed by Ho (Ho, 2003; Ho et al., 1996) was able to fit the
175
kinetic data in the whole data range. In this model, the rate-limiting step is a biosorption
176
mechanism involving chemisorption, where metal removal from solution is due to
177
purely physicochemical interactions between biomass and metal solution (Aksu, 2001).
8
178
Nevertheless, the fact that experimental data may be fitted by a rate equation is not
179
sufficient evidence to consign the corresponding mechanism.
180
181
The rate law equation, Eq. 3, can be considered a pseudo-second order chemical
biosorption process with respect to the algal sites, and is expressed as:
dq M ,t
dt
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183
184
 k  (QM  q M ,t ) 2
where k is the pseudo-second order constant of sorption.
Separating variables in Eq. 3 and integrating for the boundary conditions
qM,t = 0 at t = 0 and qM,t at time t, the following equation is obtained:
q M ,t 
185
(3)
QM2 k  t
1  QM k  t
(4)
which can be linearised to the following equation:
t
q M ,t

1
1

·t
2
k ·QM QM
(5)
186
The equilibrium sorption capacity, QM, and the pseudo-second order rate
187
constant, k, were experimentally determined from slope and intercept of straight-line
188
plots of t/qM,t against t. The values obtained are illustrated in Table 1 where the good
189
regression coefficients attained are shown. These parameters can change depending on
190
experimental conditions as it was found by Lodeiro et al. (Lodeiro et al., 2004), who
191
obtained simple empirical equations to derive the dependence of k and QM on ionic
192
strength, algal mass and initial metal concentration.
193
The kinetic model described above was recently derived in a general way by
194
Azizian (Azizian, 2004), who determined the conditions for its application and also
195
identified the real meaning of the observed rate coefficients as a complex function of
196
initial concentration of solute.
9
197
In order to obtain the temperature dependence of cadmium(II) and lead(II)
198
biosorption, a temperature range between 15-45 ºC was tested in the kinetic
199
experiments. The data obtained obey the pseudo-second order model with great
200
accuracy, which is reflected by the high regression coefficients. Fitting parameters
201
according to Eq. 5 are shown in Table 1, with the experimentally obtained QM values.
202
The effect of temperature on metal biosorption by the alga C. baccata is
203
practically negligible in the range studied. The changes in temperature did not produce
204
any significant differences in cadmium(II) and lead(II) uptake or in its corresponding
205
pseudo-second order rate constants. This fact is clearly illustrated in the Arrhenius plot
206
showed in Figure 2. Only a small increase in k for the cadmium(II) biosorption at 45ºC
207
was obtained, probably due to a slight deterioration of the matrix structure of the
208
biomass that may take place at this high temperature, and could facilitate the metal
209
uptake. This effect is not observed with the lead ion. An explanation could be found
210
taking into account that under these conditions, lead(II) uptake almost duplicates
211
cadmium ones. Therefore, the higher presence of this divalent metal could favour the
212
interchain cross-linking of the alginate present in brown algae. In this way, the alginate
213
chains yield an array of cavities known as the egg-box structure (Davis et al., 2003;
214
Percival and McDowell, 1967; Sobeck and Higgins, 2002) which stabilise the algae
215
matrix.
216
The effect of temperature on the biosorption process found in the literature
217
presents different and opposite behaviours. Martins et al. (Martins et al., 2004), Aksu
218
and Kutsal (Aksu and Kutsal, 1991), Ajmal et al. (Ajmal et al., 2003), and Kobya
219
(Kobya, 2004), reported higher uptake capacities in different organism as temperature
220
increases. On the other hand, Ahuja et al. (Ahuja et al., 1999), de Rome and Gadd (de
221
Rome and Gadd, 1987), Aksu and Kutsal (Aksu and Kutsal, 1990), Ho et al. (Ho et al.,
10
222
2004) and Dal Bosco et al. (Dal Bosco et al., 2005) reported practically temperature-
223
independent effect on biosorption capacity. In contrast, Cruz et al.(Cruz et al., 2004) and
224
Aksu (Aksu, 2001), obtained a decrease in the uptake capacity with temperature
225
increase. Even a more complex situation was described by Benguella and Benaissa
226
(Benguella and Benaissa, 2002), for the adsorption of cadmium by chitin where an
227
initial increase in the capacity of sorption was followed by a subsequent reduction.
228
229
2. Adsorption equilibrium
230
Sorption equilibrium is established when the concentration of a sorbate in a bulk
231
solution is in dynamic balance with that of the sorbent interface. The degree of the
232
sorbent (alga) affinity for the sorbate (metal) determines its distribution between the
233
solid and liquid phases. The analysis of equilibrium data is important to develop
234
mathematical models, which could be used for the quantitative description of the
235
results. The equation parameters and the underlying thermodynamic assumptions of
236
these equilibrium models should be capable of predicting metal biosorption, reflecting
237
the mechanism of the sorbate uptake and the influence of variables such as pH, ionic
238
strength, presence of competing cations, etc. However, in most cases equilibrium
239
models are used empirically as functional expressions capable of simulating favourable
240
equilibrium uptake curves if environmental parameters, such as pH, are controlled
241
carefully during experiments.
242
Several models are often used to interpret equilibrium data. We selected the
243
simple Langmuir, Freundlich and Langmuir-Freundlich (LF) equations (Table 2) to fit
244
the experimental data. Although these models shed out no light on the mechanistic
245
aspect of biosorption, they remain a useful and convenient tool for comparing results
246
from different sources on a quantitative basis, providing information on sorption
11
247
potential and reproducing the usual equilibrium uptake process behaviour with easily
248
interpretable constants; i.e. Qmax represents the maximum biosorption capacity and b is
249
an affinity parameter. A high value of parameter b indicates a high affinity of the
250
biosorbent for the sorbate; n is an empirical parameter, which varies with the degree of
251
heterogeneity and Kf is related to biosorption capacity.
252
Figure 3 shows fitted data corresponding to the cadmium(II) and lead(II)
253
biosorption by raw Cystoseira baccata biomass at pH 4.5. The conversion of these
254
isotherm equations to linear forms can alter their error structure and may also violate the
255
error variance and normality assumptions of standards least squares (Ho et al., 2005).
256
Therefore, the non-linear analysis might be a method to prevent such imprecision. The
257
adjustable parameters obtained from non-linear regression analysis (Qmax, b, n and Kf)
258
and the regression coefficients are listed in Table 2.
259
The LF isotherm exhibited lower errors and better fits than the other models
260
used for both metals. The use of three adjustable parameters produces a better fit of the
261
data compared to a two-parameter isotherm. One must be aware that does not prove the
262
validity of the model or its underlying assumptions.
263
The maximum uptake values obtained with the LF isotherm are around 0.9
264
mmol·g-1, which correspond to 186 mg·g-1 in the case of lead and to 101 mg·g-1 for
265
cadmium, equivalent to 19% and 10% of the total dry weight of the alga, respectively.
266
The fact that the maximum biosorption capacities are very similar for both metals could
267
be attributed to the limited availability of adsorption sites or to model fitting artifacts as
268
well.
269
These uptake values are comparable with maximum capacities obtained by using
270
other marine algae (Cruz et al., 2004; Holan and Volesky, 1994; Lodeiro et al., 2005;
271
Matheickal and Yu, 1996).
12
272
It must be pointed out that, compared to a large number of adsorbent materials
273
proposed in literature for metal recovery applications, the seaweed used in the present
274
study shows remarkably higher cadmium and lead biosorption ability. For instance,
275
values of 0.07, 0.12 and 0.18 mmol·g-1 for cadmium uptake have been reported for
276
activated carbon (Leyva-Ramos et al., 1997), chitin (Benguella and Benaissa, 2002) and
277
fungus (Yan and Viraraghavan, 2003), respectively. In the case of lead uptake, the
278
values found were 0.35 mmol·g-1 using hardwood bark (Jang et al., 2005), 0.138
279
mmol·g-1 with phosphate rock (Cao et al., 2004) or 0.26 mmol·g-1 employing fungus
280
(Yan and Viraraghavan, 2003). On the other hand, a few natural or synthetic materials,
281
which have been proposed for metal uptake, have comparable or even higher uptake
282
capacities (Chamarthy et al., 2001; Dal Bosco et al., 2005). More extensive
283
compilations of the adsorption of metals by different biosorbent materials can be found
284
in the literature (Bailey et al., 1999; Vegliò and Beolchini, 1997; Volesky, 2003; Wase
285
and Forster, 1997).
286
It should be noted that the maximum adsorption capacity is not the only
287
parameter that must be taken into account in the screening of different biomass species.
288
Biosorption processes are strongly dependent on initial conditions in terms of initial
289
metal and initial biomass concentration, essential for designing proposes. Moreover, it
290
is important to consider the affinity of the sorbent for the sorbate, which is reflected in
291
parameter b. Table 2 shows a great difference in this parameter involving cadmium and
292
lead (4 and 70 L·mmol-1, respectively), which clearly indicates a greater affinity of the
293
alga by lead ions at low concentrations. Moreover, as it is showed in Figure 3, the
294
higher b value makes lead isotherm to have a greater initial slope.
13
295
In order to denote the importance of initial conditions in sorption processes we
296
obtained Eq. 6 by combination of the mass balance equation for equilibrium (Eq.1
297
referred to equilibrium conditions) with the LF isotherm.

m s C M ,i  C M   1  b  C M 

1
V
Qmax  b  C M  n
1
n

(6)
298
Since Qmax, b and n can be determined from experimental data, Eq. 6 may be
299
used to estimate the biosorbent dosage, ms/V, required to achieve a specific level of
300
purification in a batch system; the differences found in the theoretical values with
301
respect to experimental one (2.5 g·L-1, mass of algae per volume of solution) ranged
302
between 4 to 9 % (except for the lowest initial concentration). Furthermore, the above
303
equation can be reordered with the aim of getting a theoretical CM value as a function of
304
initial metal concentration and algae dosage. These equilibrium metal concentrations
305
obtained for lead(II) and cadmium(II) are in good agreement with experimental values
306
(data not shown). Therefore, the equation validity is demonstrated.
307
If Eq. 6 is rearranged, we obtained the following expression, that can be used to
308
determine the dosage required to remove a specific percentage of metal from solution
309
(%E) as a function of CM,i :
% E  C M ,i
m s % E  C M ,i


V
100  Qmax 100  b 1n  Q  1  0.01  % E   C  1n
max
M ,i
310
(7)
where %E = (CM,i-CM)·100/CM,i.
311
As an example, Figure 4 shows the alga dosage required to remove 90% of
312
cadmium and lead ions from solution as a function of initial metal concentration.
313
Obviously, the increase in metal concentrations implies an augment in biosorbent
314
dosage to attain the same solution purification grade. This plot and Eq. 6 constitute
14
315
useful information to decide the proper biomass dosage in order to reduce the metal
316
pollution of an effluent to the desired value.
317
318
3. Acid-base properties
319
The acid-base titrations of protonated biomass samples allow the estimation of
320
the maximum amount of acid functional groups, Qmax,H (Table 3), from the maximum of
321
the first derivative of the titration curves (Herrero et al., 2005), using the following
322
equation:
Q max, H 
V eq  C a
(8)
ms
323
where Veq is the volume of tritant (NaOH) at the equivalence point and Ca is the NaOH
324
concentration.
325
The total number of weak acid groups determined in 0.05 mmol·L-1 NaNO3 was
326
2.2 ± 0.1 mmol·g-1. This amount is around 2.5 times greater than the maximum metal
327
uptake capacities obtained with the raw biomass (0.9 mmol·g-1). This fact can be
328
explained as a combination of two factors. First, since the raw biomass is stabilised with
329
Na, K, Ca and Mg ions present in seawater, metal ions must compete with these major
330
ions for the active binding sites, and therefore not all the binding sites are occupied by
331
the heavy metal. Second, it can be expected a certain degree of multidentism in the
332
binding mechanism, i.e., more than one acid group can be involved in the binding to a
333
single metal ion.
334
The second most abundant acidic functional group in brown algae is the sulfonic
335
acid of fucoidan; however, no evidence of its presence was found in the titration curves.
336
Langmuir-Freundlich (Eq. 9) and Langmuir models (Eq. 9 with n=1) were used
337
for the description of proton ion binding to seaweed biomass (Figure 5).
15
QH 
Q max, H  10  log K H  pH 
1  10  log K H  pH 
1 n
1 n
(9)
338
This equation is formally identical to the employed in equilibrium studies section (see
339
Table 2) but referred to proton uptake, where now the parameter b is expressed as KH,
340
the proton binding constant and CH, the concentration of protons that remains in
341
solution, is expressed as pH (-Log CH). The term log KH corresponds to the mean value
342
of the affinity distribution function.
343
While Langmuir isotherm represents a single discrete site model, LF model
344
consists in a continuous distribution of affinities. The advantage in the use of this
345
isotherm is demonstrated by the accurate simulation of experimental data; this is a
346
consequence of considering the width of the distribution (chemical heterogeneity) in
347
only one additional parameter (1/n) compared with a homogeneous model (Langmuir
348
isotherm). Figure 5 showed that the unimodal LF isotherm was able to describe
349
successfully the experimental data in the range 2 < pH < 6.
350
Table 3 shows the values determined from the fit of experimental data points to
351
Eq. 9 with its regression coefficients. The log KH value obtained with LF model, 3.67, is
352
in good agreement with the values corresponding to carboxyl groups from mannuronic
353
and guluronic acids (3.38 and 3.65) of alginate (Haug, 1961), or the value for alginic
354
acid (Rey-Castro et al., 2004). Therefore, these groups are likely to be responsible for
355
lead(II) and cadmium(II) sorption. As expected, ionic strength does not influence in the
356
number of acidic groups titrated, but strongly affects their apparent log KH values. A
357
physicochemical model that accounts for the effects of pH and ionic strength on the
358
proton binding equilibria of algae was recently proposed by Rey-Castro et al. (Rey-
359
Castro et al., 2003).
360
16
361
4. Fourier Transform Infrared analysis
362
Numerous chemical groups have been proposed to be responsible of biosorption
363
metal binding by algae (hydroxyl, carboxyl, sulfhydryl, sulfonate, etc.); their
364
importance for metal uptake depends on factors such as the quantity of sites, its
365
accessibility, chemical state or affinity between site and metal (Wase and Forster,
366
1997).
367
The confirmation of the presence of these groups has been achieved by Fourier
368
Transform Infrared analysis. The FTIR spectra of the raw C. baccata biomass with and
369
without metal-loaded are shown in Figure 6. The carboxyl ions gives rise to two bands:
370
a strong asymmetrical stretching band at 1635 cm-1 and a weaker symmetrical band at
371
1420 cm-1 for the raw alga (Sheng et al., 2004). When the biomass was loaded with the
372
lead ion some differences in the distance between these two peaks appeared, so it led to
373
the conclusion on the participation of carboxyl groups in the metal uptake. However, in
374
the case of cadmium loaded no shifts were found with respect to the raw alga; this fact
375
could be explained if we take into account that lead ion binding is greater and stronger
376
than cadmium ones. Moreover, the alga was not pretreated, so the presence of cations
377
from seawater could interfere in the IR peak analysis.
378
The FTIR analysis shows broad bands at 3420 cm-1 that represent bounded –OH
379
and –NH groups. The bands at 1161 cm-1 were due to the –C–O stretching of ether
380
groups, while the –C–O stretching of alcoholic groups was assigned at 1057 cm-1. –CH
381
stretch could be ascribed to the band that appeared at 2925 cm-1. The bands at 1234 cm-1
382
that represent –SO3 stretching appear in the spectrum at the same wavenumber before
383
and after metal binding. This could implicate that these groups, mainly present in
384
sulfonic acids of polysaccharides, such as fucoidan, were not involved in metal
17
385
complexation by raw C. baccata; however, a decrease in the intensity of the peak can be
386
observed after metal uptake, so its role in this case is not clear.
387
388
5. Effect of pH on metal uptake
389
The biosorption capacity of the alga strongly depends on equilibrium solution
390
pH, so characterisation of its effect on adsorption studies is necessary for an accurate
391
evaluation of equilibrium parameters. Therefore, if the metal binding groups are weakly
392
acidic or basic, the availability of free sites is dependent on the pH.
393
This behaviour is also observed in the results of the present study. A
394
representative example, corresponding to C. baccata binding to lead(II) and
395
cadmium(II), is shown in Figure 7. It is seen that the plot of metal bound vs. pH
396
displays an S shape. This curve is characteristic of other seaweeds (Cordero et al., 2004;
397
Lodeiro et al., 2005; Lodeiro et al., 2004) and it has been interpreted as a result of the
398
change in the ionic state of the acid functional groups involved in the metal binding, as
399
it was mentioned above.
400
At pH values below 2 the metal uptake is small, especially for cadmium, but not
401
negligible, which can be a consequence of the presence of a relatively low amount of
402
very strong acid groups like sulfonic groups from fucoidans (Fourest and Volesky,
403
1996). This would confirm the hypothesis of the participation of these groups in metal
404
uptake mentioned in the FTIR analysis. Above pH 4 the increase in the metal sorption is
405
almost insignificant, and the uptake reaches a plateau.
406
Another aspect that must be taken into account is the speciation of metals in
407
solution that is also pH dependent. The speciation of lead and cadmium ions were
408
obtained by means of MINEQL+ program (Schecher and McAvoy, 1992), which shows
409
that free cadmium(II) and lead(II) ions are the predominant species formed in the pH
18
410
interval studied (Lodeiro et al., 2004) (between 3.5 and 5). At pH values higher than 8
411
for cadmium, or higher than 5 for lead, several hydroxyl low-soluble species can be
412
formed, i.e. Cd(OH)2, Cd(OH)3- or Pb(OH)2. Equilibrium experiments were carried out
413
at pH 4.5, where the maximum uptake capacity was achieved and metal precipitation
414
was avoided.
415
The application of biosorption as a viable commercial technique implies the
416
recovery of bound metals and the subsequent recycling of the biosorbent. The fact that
417
at low pH the metal adsorption is greatly reduced can be applied for its recuperation
418
from the alga. Percentages of metal recuperation greater than 90% were achieved in
419
different algae-metal desorption studies (Aldor et al., 1995; Holan et al., 1993; Kuyucak
420
and Volesky, 1989), reinforcing the environmental character of algal biosorbents for
421
metal recovery process (Schiewer and Volesky, 2000). Therefore, the possibility of
422
using the algae in sorption-desorption cycles is a great advantage for its possible
423
practical uses. In our group, further work has been developed on this topic by batch and
424
dynamic column studies with a pretreated alga, obtaining promising results (Lodeiro,P.,
425
Herrero, R. and M.E. Sastre de Vicente, in preparation).
426
427
6. Effect of salinity on metal uptake
428
Industrial effluents may contain a mixture of cations. Light metals like sodium
429
and calcium are usually present, especially after pretreatment by precipitation. Although
430
the elimination of these cations is not the purpose of biosorption studies, they can
431
compete and interfere for binding sites with the metal ion to be eliminated.
432
Despite the pH value, another important parameter in biosorption is the ionic
433
strength. It is often stated in literature that an increase in ionic strength suppresses metal
434
uptake as a result of the screening of electrostatic charge (Schiewer and Volesky, 1997).
19
435
This fact is relevant to the way that the metal is electrostatically or covalently bound.
436
Alternatively, other sorbable ions can compete with the divalent cations of interest for
437
binding to the biomass, affecting biosorption (Schiewer and Wong, 2000).
438
Moreover, the anions of the metal salts that balance the positive charge of the
439
metal ion are necessarily present in solution. These anions may also affect the metal
440
uptake forming complexes in solution.
441
Figure 8 shows the cadmium(II) and lead(II) uptakes by C. baccata in the
442
presence of calcium and sodium nitrate salt at several concentrations. The bars represent
443
metal removal from solution as the percentage of the original uptake, when no
444
background electrolyte was present in solution. Within the concentration range
445
examined, it is evident that metal uptake is affected by the presence of the salts. The
446
level of competition mainly depends on two ways: the competition of cations for the
447
same binding sites and the strength of binding to these sites.
448
The importance of sodium for metal binding is increased at the same time as this
449
light metal augmented its concentration in solution. In a general way, ions like sodium,
450
which are bound weakly through mostly electrostatic attraction, are effective in
451
competing only with other weakly bound ions. However, even heavy metals that tend to
452
form complexes, are partially bound through electrostatic attraction as a consequence of
453
the higher concentrations of all metals near binding sites, than in the bulk solution
454
(Schiewer and Volesky, 2000). Therefore, their covalent binding is consequently also
455
reduced when background salts are added to solution.
456
This is clearly reflected in Figure 8, where it is showed that lead(II) adsorption is
457
much less affected than cadmium(II) by the presence and increase of sodium ions in
458
solution, particularly at concentrations above 0.01 mol·L-1. This fact denotes the more
459
covalent character of lead (electrostatic factors do play a secondary role in this case)
20
460
and, as a consequence, its stronger binding capacity makes that the influence of this
461
background ion was less significant.
462
On the other hand, it is also showed in Figure 8 that the presence of divalent
463
calcium ions exerts a stronger influence on metal uptake than in the case of sodium,
464
which is reflected even at lower salt concentrations. This could be consequence of its
465
higher electrostatic accumulation and its greater affinity for the binding sites (Volesky,
466
2003). As it was expected, the influence of calcium ions on lead adsorption is less
467
important than in the case of cadmium uptake, due to the reasons explained above.
468
In order to determine the possible influence of nitrate salt on metal uptake,
469
speciation calculations with the MINEQL+ program were completed for lead and
470
cadmium in presence of different salt concentrations at pH value of 4.5. For both metals
471
only two species were predicted to exist in solution: M+2 and MNO3+.
472
Even without a deliberate salt addition NO3- ions are present in solution due to
473
the salts of metals employed; in this situation, the complex MNO3+only represents less
474
than 1 % of the total species concentration in the case of cadmium or 5 % if M is the
475
lead ion.
476
The MNO3+ complex formation is favored by the increase in nitrate
477
concentration and it is also more favorable for lead(II) ions. However, there is no clear
478
relation between the decrease in metal uptake and the reduce of M+2 species in solution;
479
this implies that the nitrate ions do not contribute in excess to reduce metal binding due
480
to the complex formation, and only the blockade of sites in the biosorbent could weakly
481
influence the metal uptake as a result of electrostatic attraction.
482
483
7. Conclusions
21
484
The results of this work indicate that the brown marine macroalgae Cystoseira
485
baccata constitute a promising material for the development of a low cost biosorption
486
technology for the removal of lead(II) and cadmium(II) from water effluents. The fast
487
kinetics of the adsorption process together with the high sorption capacities of this
488
seaweed towards lead(II) and cadmium(II) can be compared favorably with other
489
sorbents.
490
Kinetic data was described by a pseudo-second order model obtaining the kinetic
491
rate constant and the equilibrium sorption capacity of the alga. These parameters were
492
found to not change with the variation in temperature.
493
494
LF equation was able to describe the metal isotherms and the proton binding in
acid-base titrations of protonated alga.
495
The presence and participation of carboxylic groups in metal uptake was
496
confirmed by FTIR analysis. Moreover, some other groups were also identified as
497
components of algae structure.
498
Solution pH was found to be an important parameter affecting biosorption. The
499
characteristic sigmoidal shape of the adsorption-pH curves, where the uptake capacity is
500
almost negligible at pH≤ 2, is very useful to perform adsorption-desorption cycles.
501
Further experimental work regarding metal desorption studies or the use of chemical
502
pretreatments would be required in the future.
503
The presence of calcium and sodium nitrate salts in solution was found to affect
504
considerably the metal biosorption from 0.01 mol·L-1 salt concentration. The decrease
505
in metal adsorption was higher when calcium, instead of sodium nitrate, was used.
506
Furthermore, the metal uptake reduction was always more pronounced in the case of
507
cadmium uptake, which reveals its weaker binding to biomass sites.
508
22
509
510
ACKNOWLEDGEMENTS
The
authors
wish
to
thank
Xunta
de
Galicia
through
project
511
PGIDT02TAM10302PR and Ministerio de Ciencia y Tecnología through project BQU
512
2002-02133 for financial support. The authors would like to thank Dr. I. Bárbara and
513
Dr. J. Cremades (U. of A Coruña) for the collection and classification of the alga.
514
23
515
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516
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606
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610
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629
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630
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631
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632
633
28
634
FIGURE CAPTIONS
635
Figure 1
636
Sorption of lead(II) (squares) and cadmium(II) (triangles) as a function of
637
contact time, for aqueous suspensions of raw C. baccata (2.5 g·L-1) in 0.05 mol·L-1
638
NaNO3. The symbols correspond to the experimental points and the solid lines represent
639
the best fits to Eq. 3. Initial metal concentration: 2 mmol·L-1, T = 25 ºC, natural pH
640
(around 4 for lead and 5 for cadmium).
641
Figure 2
642
Effect of temperature on the pseudo-second order rate kinetic constant for
643
cadmium(II) (triangles) and lead(II) (squares) biosorption. Initial metal concentration: 2
644
mmol·L-1, I= 0.05 mol·L-1 NaNO3.
645
Figure 3
646
Metal biosorption isotherms for suspensions of raw C. baccata (2.5 g·L-1) in
647
deionised water at pH= 4.5 ± 0.1 and 25 ºC. The symbols correspond to the
648
experimental points and the lines represent the fits to Langmuir (dashed lines),
649
Freundlich (dotted lines) and Langmuir-Freundlich (solid lines) isotherms.
650
Figure 4
651
Algae dosage required to remove 90% of available lead(II) (solid line) and
652
cadmium(II) (dashed line) as a function of initial metal concentration (Eq. 7 with the
653
parameters obtained from LF isotherm fit listed in Table 2).
654
Figure 5
655
Proton binding by acid-treated C. baccata (in absence of metal) in 0.05 mol·L-1
656
NaNO3. Symbols represent experimental points, solid line corresponds to the best fit of
657
a Langmuir-Freundlich isotherm, Eq. 9, and dashed line to a simple Langmuir isotherm,
29
658
equivalent to Eq. 9 with n=1. In both cases, the value of Qmax,H was set equal to the total
659
amount of titratable groups, determined from the equivalence point of the titrations.
660
Figure 6
661
FTIR spectra for raw C. baccata in absence of metal, raw C. baccata Pb-loaded
662
and raw C. baccata Cd-loaded.
663
Figure 7
664
Effect of pH on cadmium(II) (triangles) and lead(II) (squares) biosorption by C.
665
baccata (2.5 g·L-1) in deionised water at pH= 4.5 ± 0.1 and 25 ºC, with initial metal
666
concentration of 2.41 mmol·L-1. The lines guide the eye.
667
Figure 8
668
Sorption of (a) cadmium(II) and (b) lead(II) as a function of the concentration of
669
added NaNO3 (white bars) and Ca(NO3)2 (grey bars) at pH= 4.5 ± 0.1 and 25 ºC by C.
670
baccata (2.5 g·L-1). Initial metal concentration: 2.41 mmol·L-1. The reference value
671
100% indicates the metal sorption in absence of added salt.
672
673
674
675
676
677
678
679
680
681
682
30
683
TABLES
684
685
Table 1
686
Experimental QM,exp values and kinetic parameters for metal uptake obtained
687
from pseudo-second order rate model. 2.5 g·L-1 of algal dose (raw C. baccata) with
688
ionic strength adjusted to 0.05 mol·L-1 with NaNO3 at 2 mmol·L-1 initial metal
689
concentration and natural pH (around 4 for lead and 5 for cadmium). The errors
690
represent the differences in medium values obtained from two experiences.
Cadmium(II)
T
QM,exp
QM
k
(ºC)
(mmolg-1)
(mmolg-1)
(gmmol-1min-1)
15
0.45 ± 0.03
0.46 ± 0.05
1.1 ± 0.3
0.9995
25
0.49 ± 0.02
0.50 ± 0.01
0.87 ± 0.01
0.9991
35
0.50 ± 0.03
0.51 ± 0.02
1.07 ± 0.01
0.9996
45
0.41 ± 0.02
0.42 ± 0.03
1.48 ± 0.06
0.9998
r2
Lead(II)
QM,exp
QM
k
r2
(mmolg-1)
(mmolg-1)
(gmmol-1min-1)
15
0.71 ± 0.03
0.73 ± 0.02
0.25 ± 0.01
0.9997
25
0.66 ± 0.02
0.69 ± 0.01
0.21 ± 0.01
0.9998
35
0.65 ± 0.03
0.68 ± 0.01
0.21 ± 0.01
0.9998
45
0.69 ± 0.01
0.72 ± 0.02
0.20 ± 0.02
0.9999
691
692
693
31
694
Table 2
695
Adsorption isotherms and the corresponding parameters estimated for metal
696
binding by the raw C. baccata (2.5 g·L-1) in deionised water at pH= 4.5 ± 0.1 and 25 ºC.
697
Fitting errors are also shown.
Qmax
Model
Equation
QM 
Lang.
Qmax  b  C M
1  b  CM
Qmax  (b  C M )1 n
QM 
1  (b  C M )1 n
LF
b
Metal
n
r2
(mmol·g-1)
(L·mmol-1)
Cd
0.69 ± 0.04
11 ± 3
0.98
Pb
0.88 ± 0.02
77 ± 10
0.98
Cd
0.9 ± 0.1
4±2
1.6 ± 0.2
0.995
Pb
0.91 ± 0.02
70 ± 8
1.4 ± 0.1
0.994
kf
(n-1)/n
(mmol
L1/ng-1)
Freund.
QM  k F ·C M
1n
Cd
0.67 ± 0.02
3.1 ± 0.3
0.97
Pb
0.74 ± 0.06
6±1
0.84
698
699
700
Table 3
701
702
Optimal parameters estimates for proton binding by the acid-treated C. baccata
in 0.05 mol·L-1 NaNO3.
Model
Qmax,H (mmol·g-1) a
log KH b
nb
r2
2.2 ± 0.1
3.67 ± 0.01
1.88 ± 0.01
0.997
2.2 ± 0.1
3.61 ± 0.05
1
0.80
LF
Langmuir
703
a
704
of heavy metal.
705
Langmuir isotherm, Eq. 9 with n=1, to the proton binding data.
Estimated from the equivalence point of the acid-base titrations performed in absence
b
Calculated from least-squares fit of the LF isotherm, Eq. 9, or
32
706
FIGURES
707
708
709
Figure 1
710
711
712
713
714
715
716
717
718
719
720
33
721
722
723
Figure 2
724
725
726
727
728
729
730
731
732
733
734
735
34
736
737
738
Figure 3
739
740
741
742
743
744
745
746
747
748
749
750
35
751
752
753
Figure 4
754
755
756
757
758
759
760
761
762
763
764
765
36
766
767
768
Figure 5
769
770
771
772
773
774
775
776
777
778
779
780
37
781
782
783
Figure 6
784
785
786
787
788
789
790
791
792
793
794
795
38
796
797
798
Figure 7
799
800
801
802
803
804
805
806
807
808
809
810
39
811
(a)
812
813
(b)
814
815
Figure 8
40