Lead biosorption by
Biotechnology has a great potential to remove heavy metals using the ability of different bacteria and other microorganisms to capture metal ions, mainly through biosorption. This ability has a high potential for the development of effective and economic processes for heavy metal bioremoval, especially for dilute solutions (<100 mg/L) [
Microorganisms and other biomass types have the advantage of having components as lipopolysaccharides, proteins, and phospholipids which have many functional groups. These groups confer a negative charge and thus offer the possibility of adding metal cations. This ability is present in all types of biomass, dead or alive. In the case of living microorganisms, other active cellular mechanisms are involved: synthesis of specific enzymes, action of cytoplasmic or membrane proteins, and so forth [
In order to improve biosorption effectiveness, the identification of additional microbial strains with high metal uptake capacity and specificity is a key aspect. In this way, the isolation of autochthonous microorganisms from contaminated sites is an interesting option to obtain metal-resistant strains [
Lead is known for its high environmental impact and toxicity [
In this work, the biosorption characteristics of
Ten strains were selected and identified by molecular techniques in a previous study from wastewater treatment plants [
For the biosorption experiments, the biomass was prepared by incubating the strain in tryptic soy broth (TSB, 30 g/L) medium at 30°C with stirring, after centrifugation at 6000 rpm and washing twice with electrolyte solution. The cells of
The infrared spectra of the biomass samples before and after metal uptake were recorded using a VERTEX 70 (Bruker Corporation) Fourier transform infrared spectrometer operating in the range of 4000–400 cm−1. Measurements were performed with lyophilised samples. The samples were measured using Attenuated Total Reflection (ATR). FTIR characterisation was performed to identify characteristic chemical functional groups of the bacterium
Field emission scanning electron microscopy (MERLIN of Carl Zeiss) coupled with energy dispersive X-ray spectroscopy was carried out to characterise the
High-resolution transmission electron microscopy and energy dispersive X-ray analysis (Philips CM-20) were used to determine the location of the metal within the cell. The samples were fixed, dehydrated, and dried as in the previous case; these were then treated with resin and were finally polymerised.
The test solutions of Pb(II) were prepared using Pb(NO3)2 and 0.1 M NaCl as an electrolyte. The initial pH was controlled with 0.1 M NaOH or 0.1 M HNO3.
The preliminary biosorption tests were performed in Erlenmeyer flasks with the ten strains (Section
Isothermal and kinetic studies were conducted as described above. Two kinetics experiments were performed, with two different concentrations of biomass and metal: Experiment number 1: 50 mg/L of Pb(II) and 0.11 g/L of dry biomass and Experiment number 2: 25 mg/L of Pb(II) and 0.28 g/L of dry biomass. The adsorbent was separated from the solution by centrifugation at predetermined time intervals (5–3600 min), with two flasks at each time point. Then, the residual lead concentration was analysed by AAS. The biosorption isotherm was obtained for a constant biomass concentration (0.52 g/L) and different concentrations of metal at 25°C.
In all cases, the amount of metal ions biosorbed per unit mass of dry biosorbent (lead biosorption capacity) was determined according to the following equation:
A Rotatable Central Composite Design (RCCD) with six central points was performed to evaluate the relationship between obtained results and experimental factors as well as optimise the working conditions. Biosorbent dosage (
According to the RCCD, the total number of experimental combinations is
Experimental design and response.
Run order | Factor | Response | ||
---|---|---|---|---|
|
pH |
|
|
|
12 | 0.55 | 5.50 | 25 | 104.02 |
6 | 0.80 | 4.30 | 34 | 118.51 |
13 | 0.55 | 4.75 | 10 | 80.97 |
11 | 0.55 | 4.00 | 25 | 87.42 |
1 | 0.30 | 4.30 | 16 | 67.27 |
15 | 0.55 | 4.75 | 25 | 105.02 |
18 | 0.55 | 4.75 | 25 | 105.75 |
4 | 0.80 | 5.20 | 16 | 86.16 |
10 | 1.00 | 4.75 | 25 | 94.99 |
19 | 0.55 | 4.75 | 25 | 108.65 |
5 | 0.30 | 4.30 | 34 | 127.21 |
9 | 0.10 | 4.75 | 25 | 122.13 |
3 | 0.30 | 5.20 | 16 | 76.36 |
7 | 0.30 | 5.20 | 34 | 138.52 |
16 | 0.55 | 4.75 | 25 | 105.31 |
2 | 0.80 | 4.30 | 16 | 79.17 |
20 | 0.55 | 4.75 | 25 | 106.18 |
8 | 0.80 | 5.20 | 34 | 119.79 |
14 | 0.55 | 4.75 | 40 | 163.53 |
17 | 0.55 | 4.75 | 25 | 106.18 |
The overall quadratic equation for biosorption capacity was
The response data were analysed by parameters obtained from the analysis of variance (ANOVA) using Design-Expert program, 8.0.7.1 version. The statistical significance was fixed at 5% probability level (
To know the biosorption mechanisms and speed of the process, it is important to study the mass transfer and chemical reactions. To do this, the experimental data have been adjusted to several kinetic models. In most cases, it is assumed that adsorption is controlled by chemical reaction and not by diffusion, which contributes to the mechanical agitation. However, we have tested three kinetic models of chemical reaction control and one of intraparticle diffusion. The kinetic models tested are shown in Table
Kinetic models tested.
Model | Equation |
|
|
Pseudo-first order or Lagergren [ |
|
Pseudo-second order [ |
|
Elovich [ |
|
Intraparticle diffusion or Weber and Morris [ |
|
Several adsorption isotherms have been tested to fit experimental data. The most widely used among them are the Langmuir and Freundlich models; other well-known models are the Sips and Redlich-Peterson equations (Table
Isotherm models used to represent the biosorption equilibrium.
Model | Equation |
---|---|
Langmuir [ |
|
Freundlich [ |
|
Sips [ |
|
Redlich-Peterson [ |
|
Ten strains isolated from wastewater treatment plants showed resistance to lead in our previous study [
Lead biosorption capacity from preliminary tests.
Isolates |
|
---|---|
Fungi | |
|
66.00 |
|
44.74 |
|
85.17 |
|
104.53 |
Yeasts | |
|
22.29 |
|
35.72 |
|
23.95 |
|
37.59 |
Bacteria | |
|
90.48 |
|
78.10 |
To choose the most suitable strain for heavy metals biosorption, other aspects of interest should be taken into account. It is very interesting to support microbial biomass in low cost inert solids. Therefore, microorganisms with greater ability to form biofilms are always the most appropriate [
FTIR analysis was performed to identify the main functional groups and to study their evolution during biosorption process. This technique has proved effective in obtaining structural information on metal-microbe bonds [
IR absorption bands: changes and possible assignment.
FTIR peak | Original biomass wavenumbers (cm−1) | Pb(II) loaded biomass wavenumbers (cm−1) | Displacement (cm−1) | Functional groups | Assignment |
---|---|---|---|---|---|
1 | 3282 | 3280 | 2 | –OH, –NH | Stretching vibrations of amino and hydroxyl groups |
2 | 2958 | 2957 | 1 | –CH3 | –CH3 asymmetric stretching |
3 |
2925 |
2924 |
1 |
–CH2 |
–CH2 asymmetric stretching vibrations |
5 | 2854 | 2853 | 1 | –CH2 | –CH3 asymmetric stretching vibrations |
6 | 1638 | 1639 | 1 | –CO, C–N | C=O and C–N stretching in amide I group |
7 | 1531 | 1534 | 3 | –CN, –NH | C–N stretching in amide II group and N–H bending |
8 | 1453 | 1453 | 0 | –CH2, –CO | –CH2 bending, symmetric C=O |
9 | 1396 | 1398 | 2 | –COO− | –COO− symmetric stretching of carboxyl groups |
10 | 1233 | 1236 | 3 |
|
P=O asymmetric stretching of phosphate groups, deformation vibration of C=O carboxylic acids |
11 |
1063 |
1058 |
5 |
|
P=O symmetric stretching of phosphate groups, –OH of polysaccharides |
13 | 993 | 993 | –C–O, –CH2 | C–O–C, C–O–P, and –CH2 stretching vibrations of polysaccharides | |
14 | 967 | 969 | 2 | N-containing bioligands | |
15 | 914 | 915 | 1 | N-containing bioligands | |
16 | 860 | 861 | 1 | S=O stretching | |
17 | 796 | 796 | 0 | N-containing bioligands | |
18 | 780 | 780 | 0 | N-containing bioligands | |
19 | 571 | 571 | N-containing bioligands | ||
20 | 515 | 539 | 24 | N-containing bioligands |
FTIR spectra of
Figure
SEM-EDX analysis of
The location of the metal within the cell was evaluated using HR-TEM-EDX technique. The micrographs obtained together with the corresponding EDX microanalysis (Figure
Transmission electron micrographs of a thin section of
Sorption kinetics is important because it describes the solute uptake, which also controls the residence time of the metal ions at the solid-solution interface. Figure
Experimental data and curves corresponding to the model that best fits the experimental results, pseudo-second order with boundary conditions:
Kinetic behavior during adsorption has been studied by numerous models [
Table
Integrated equations, boundary conditions, and kinetic parameters of the biosorption by
Exp. number 1 | Exp. number 2 | ||
---|---|---|---|
|
|||
|
|
103.2 | 78.15 |
|
0.00775 | 0.00607 | |
|
0.437 | 0.627 | |
|
5826 | 2781 | |
|
|
115.7 | 85.43 |
|
49.43 | 30.21 | |
|
0.0013 | 0.0018 | |
|
0.992 | 0.983 | |
|
81.65 | 124.5 | |
|
|||
|
|||
|
|
107.5 | 82.64 |
|
|
|
|
|
0.629 | 0.774 | |
|
3836 | 1686 | |
|
|
130.9 | 96.56 |
|
47.57 | 28.84 | |
|
|
|
|
|
0.996 | 0.974 | |
|
45.26 | 197.4 | |
|
|||
|
|||
|
|
26.55 | 7.176 |
|
0.07855 | 0.08845 | |
|
0.922 | 0.923 | |
|
811.1 | 570.1 | |
|
|
1.832 | 1.516 |
|
0.04807 | 0.06404 | |
|
45.76 | 26.39 | |
|
0.992 | 0.962 | |
|
78.03 | 286.7 | |
|
|||
|
|||
|
|
2.488 | 1.971 |
|
— | 0.241 | |
|
11718 | 5652 | |
|
|
1.305 | 1.146 |
|
48.84 | 31.50 | |
|
0.957 | 0.903 | |
|
439.8 | 719.0 |
Exp. number 1: 50 mg/L of Pb(II) and 0.11 g/L of dry biomass. Exp. number 2: 25 mg/L of Pb(II) and 0.28 g/L of dry biomass.
A Rotatable Central Composite Design was performed. Table
ANOVA for the response surface reduced quadratic model.
Source | Sum of squares | DF | Mean square |
|
|
---|---|---|---|---|---|
Model | 9588.53 | 8 | 1198.57 | 437.66 | <0.0001 |
|
4.10 | 1 | 4.10 | 1.50 | 0.2520 |
pH | 234.13 | 1 | 234.13 | 85.49 | <0.0001 |
|
8164.13 | 1 | 8164.13 | 2981.14 | <0.0001 |
|
18.39 | 1 | 18.39 | 6.72 | 0.0291 |
|
301.72 | 1 | 301.72 | 110.17 | <0.0001 |
|
161.57 | 1 | 161.57 | 59.00 | <0.0001 |
pH2 | 164.17 | 1 | 164.17 | 59.95 | <0.0001 |
|
387.29 | 1 | 387.29 | 141.42 | <0.0001 |
Residual | 24.65 | 9 | 2.74 | ||
Lack of fit | 16.26 | 4 | 4.06 | 2.42 | 0.1790 |
Pure error | 8.39 | 5 | 1.68 | ||
Cor total | 9613.18 | 17 | |||
|
|||||
CV % | 1.58 | ||||
|
0.9974 | ||||
Adj. |
0.9952 | ||||
Pred. |
0.9837 |
The model is significant (
The perturbation plots were obtained to study the effects of several factors. These plots showed that temperature has the greatest influence on Pb(II) removal efficiency, and the biosorbent dosage exerts less influence. This is shown in Figure
Response surface plot for biosorption of Pb(II) by
The empirical model given as (
Response surface plot for biosorption of Pb(II) by
Equilibrium data were obtained experimentally using different initial concentrations of Pb(II) between 50 and 320 mg/L and a constant biomass concentration (0.52 g/L), at 25°C and pH 5 (Figure
Biosorption equilibrium data and Freundlich isotherm for
Four isotherm equations have been examined in the present study. All parameters were adjusted by nonlinear regression. Table
Biosorption equilibrium parameters of the isotherm models by
Langmuir |
|
140.19 |
|
0.075353 | |
|
0.9395 | |
|
60.955 | |
|
||
Freundlich |
|
65.266 |
|
7.4312 | |
|
0.9901 | |
|
15.920 | |
|
||
Sips |
|
66.223 |
|
0.019748 | |
|
7.1713 | |
|
0.9901 | |
|
15.915 | |
|
||
Redlich-Peterson |
|
20850.6 |
|
319.3393 | |
|
0.86949 | |
|
0.9901 | |
|
15.923 |
The maximum biosorption capacity (
Maximum lead biosorption capacity of different microorganisms.
Biosorbent |
|
Reference |
---|---|---|
|
60.77 | [ |
|
48.79 | [ |
|
44.80 | [ |
|
70.42 | [ |
|
34.92 | [ |
Dried activated sludge | 131.60 | [ |
|
28.99 | [ |
|
227.70 | [ |
Immobilised |
30.04 | [ |
Recombinant |
108.99 | [ |
|
140.19 | In this study |
This work concluded that the isolate
Future research should be carried out to develop a robust immobilisation method for wastewater treatment, including continuous biosorption with reuse and recycling.
The authors declare that there is no conflict of interests regarding the publication of this paper.
The support of the Spanish Agency for International Development Cooperation (Project Reference A/018600/08) is greatly acknowledged.