Appl Biochem Biotechnol DOI 10.1007/s12010-014-1076-y

Manganese Biosorption from Aqueous Solution by Penicillium camemberti Biomass in the Batch and Fix Bed Reactors: A Kinetic Study Rana Khalilnezhad & Mohammad Ebrahim Olya & Morteza Khosravi & Reza Marandi

Received: 31 January 2014 / Accepted: 21 July 2014 # Springer Science+Business Media New York 2014

Abstract Biosorption of manganese(II) using suspended and immobilized cells of fungal Penicillium camemberti (biomass) and nano-P. camemberti (nano-biomass) was studied by evaluating the physicochemical parameters of the solution such as initial manganese ion concentration, pH, temperature, dosage, and contact time in both batch system and fixed bed column. The maximum biosorption obtained from the batch process was 91.54 and 71.08 % for nano-biomass and biomass in initial concentration of 5 ppm, respectively. The Langmuir, Freundlich, Temkin, and BET isotherms isotherm models were used in the equilibrium modeling. The correlation coefficient of more than 0.90 turned out that the adsorption process of Mn(II) on biomass and nano-biomass were in accordance with both Langmuir and Freundlich isotherms. The sorption process followed a second-order rate kinetics indicating the process to be diffusion controlled. The results also demonstrate that an intra-particle diffusion mechanism plays a significant role in the sorption process. The structure of P. camemberti was characterized by FT-IR spectrums. Keywords Sodium alginate . Biosorption . Isotherm . Biomass . Fixed bed reactor . Batch

R. Khalilnezhad (*) : M. Khosravi Department of Applied Chemistry, Faculty of Chemistry North Tehran Branch, Islamic Azad University, Tehran, Iran e-mail: [email protected] M. Khosravi e-mail: [email protected] M. E. Olya Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran e-mail: [email protected] R. Marandi Department of Environmental Engineering, Faculty of Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran e-mail: [email protected]

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Introduction Heavy metals by industrial activities and further technological development of then natural environment have been published. The presence of heavy metals in aqueous sources is one of the most important problems that effects on health and environment. Thus the development of methods in order to eliminate heavy metals from the environment is very important [1]. These metals may enter the environment through industrial activities such as electroplating, metal smelting and refining, mining, power plants, textile industries, battery, ceramic, and glass. Therefore, it is important to develop methods that are able to remove heavy metals from the environment [2]. Chemical methods for the removal of these metals are ion exchange, chemical precipitation, reverse osmosis, etc. These methods are very expensive [2]. Today, biological separation processes have attracted much attention because the highperformance methods are considered to be economically viable [3]. Biological removal of metals has advantages such as low operating costs, high efficiency, high capacity to accept metals, chemical selectivity, and low sludge production [4]. Adsorption by microorganisms using methods has many advantages. For this purpose, used microorganisms such as fungi, bacteria, and algae for removing heavy metals [5]. In most cases, a non-living biomass of living biomass gives better separation of heavy metals. In living systems, biological and chemical oxygen demand and food is high. Furthermore, metal toxicity and other adverse factors make it difficult to keep them alive [4]. Penicillium is one of the most extensive fungi in the earthly environment. Penicillium has been widely used for dye and metal removal via biodegradation or biosorption. Dried Penicillium restrictum had been recently used for biosorption of Reactive Black 5 and Penicillium YW 01 for biosorption capacities of AB (C.I. Acid Black 172) [6]. Biomass cell walls, which mainly consist of polysaccharides, proteins, and lipids, offer many functional groups that can bind metal ions, and these include carboxylate, hydroxyl, phosphate, and amino groups. In some cases, adsorption on the external cell surface is a biomass defense system against toxic heavy metals, with the microorganisms producing an external polymeric layer to avoid metal penetration through the cell wall [7]. Many researchers reported on a batch system, but batch operations are not available in practice and the data of fixed bed column operations should be used to design an industrial process [8]. However, the data obtained under batch conditions are generally not applicable to most treatment system (such as column operations) where contact time is not sufficiently long for the attainment of equilibrium. Hence, there is a need to perform equilibrium studies using columns [9]. In this study, removal of manganese by pretreated Penicillium camemberti (biomass) and nano-P. camemberti (nano-biomass) has been studied in batch and packed bed column system. Important design parameters such as column bed height and flow rate of metal solution into the column have been identified. Metal sorption performance depends on some external factors such as pH, the presence of other ions in solution (which may be in competition), organic material in solution (such as complexing agents), cell metabolic products in solution (which may cause metal precipitation), and temperature [7].

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Materials and Methods Preparation of Biosorbent The non-living biomass of P. camemberti was used as a biosorbent for the sorption of metal ions from an aqueous solution. The fungus was cultivated in a liquid medium using the shakeflask method. The growth medium consisted of (g/l of distilled water) SABOURAUD-2 % Glucose Bouillon. Once inoculated, flasks were incubated on an orbital shaker at 150 rpm for 2 days at 47 °C. After incubation, the biomass was collected from the medium and washed with distilled water. Then it was boiled for 15 min in 500 ml of 0.3 N NaOH solutions and sieved through filtration using glass fiber filter papers (Whatman GF-C), and it was washed with deionized water until the pH of the wash solution was in near neutral range (pH 7.0±7.2). It was then dried at 60 °C in an oven for 2 days and powdered in a mixer [1, 8]. Preparation of Nano-biosorbent In this study, in order to make nano-biomass, the method of ball milling has been employed. This method is known as mechanical attrition or mechanical alloying. The reasons for employing this method are as follows: the production of separate nano-particles without aggregation, the simplicity of the process, method’s being economical, the lowness of the temperature of the process, the simplicity of the controlling of the process, and the characteristics of the powders produced. In this stage, the effects of different methods like ball mill, ultrasonic, the type of solvent, homogenizer, and liquid nitrogen on the size of the particles were experimented. We grind some dead and dry fungus by ball mill under the fixed time period of 60 min and fixed speed of 600 rpm and add the obtained granules to 20 ml of liquid nitrogen slowly and homogenize it. After 10 min, all of the nitrogen is vaporized from the beaker containing fungus due to the great volatility of liquid nitrogen. Because of the crystallization of the fungus particles, we grind them immediately for 60 min and then we add the obtained particles to 40 ml of distilled water slowly and homogenize the product for 5 min by the homogenizer machine. In the next step, the suspension particles obtained ultrason by ultrasonic machine for 60 minutes and immediately homogenize it for 30 minutes and then dry it in the temperature of 70–80 °C. After the fungus dries, we ball mill it in the mortar and grind it for 60 min under the speed of 600 rpm and prepare the obtained particles for photography by electronic microscope. In this method of nanoing, the size of the produced particles usually decreases by the increase in the time of grinding because more energy is transmitted to substance; therefore, more particles are ground and homogenizing results in the evenness of the size of the particles and decrease in the space among the size of the particles. The particles are crystallized due to the low temperature of liquid nitrogen and steady grinding results in the steady crushing of the particles [10, 11]. Figure 1 shows the SEM of the particles. Comparing the SEM pictures related to nano-biomass and biomass states shows the particles getting homogeneous and fine. Immobilization of Penicillium into Aliginate Beads P. camemberti was immobilized in sodium alginate polymer beads. Immobilization of fungal biomass was carried out by the entrapment method. Based on the technique of dropwise

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Fig. 1 SEM of a nano-biomass, b biomass

addition of cells suspended in sodium alginate solution into calcium chloride solution that the cells are immobilized in calcium alginate gel. Alginate solution of 2.1 % (w/ v) was prepared by dissolving 8 g of sodium alginate in 420 ml of hot deionized water into the stirred tank. The mixed powdered biomass by different percentage proportions with 100 ml alginate (sodium) 2.1 % (w/v) was shaken in a shaker to have a uniform mixture. The mixture was extruded by a syringe into 0.2 M calcium chloride solution under shaking by using a peristaltic pump. After 35 min, the beads were amassed from solution and washed with deionized water. Then beads were placed into a solution of calcium chloride (0.2 M) for 10 min, through Ca2+ diffused into the beads and produced the gelification on the bead surface. After that, the beads were washed with deionized water and kept in a solution of calcium chloride (0.2 M) for 60 min at 4 °C and finally washed with NaCl 0.7 % [8, 12]. Preparation of Manganese Solution The test solutions were prepared by diluting 1,000 mg/l of Mn (NO3)2⋅4H2O standard solution with deionized water to the desired concentrations (5, 10, 20, 40, and 60 mg/ l Mn). The pH of the working solution was maintained by adding 0.1 M HNO3 or 0.1 M NaOH [13, 14]. Batch Biosorption Experiments In the present study, the effects of the pH variations, concentration metal, biomass amount, contact time, and temperature of solution were under investigation. The biomass and nano-biomass capacity of Penicillium was determined by shaking 100 ml of Mn(II) solutions of various concentrations (5, 10, 20, 40, and 60 mg/L Mn) in a 250-ml flask, with homogeneously dry nano-biomass of weight 0.1 g. For the determination of metal biosorption rate, the filtrate was analyzed for residual Mn after contact periods of 5, 10, 20, 30, 40, 50, and 60 min. The effect of pH on Mn sorption by Penicillium was determined by adjusting the metal solution at different pHs 3, 4, 6, 7, and 8. The mixture was shaken on a rotary shaker at 150 rpm for 1 h at 25± 2 °C. Nano-biomass was separated from the metal solution by using filter paper for removing the suspended biomass and analyzed for residual metal concentration. The metal concentration in the supernatant solution was determined at 403.2 nm in a spectrophotometer [13].

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The amount of metal biosorbed by P. camemberti was calculated as follows (Eq. (1)): q¼

ðC o −C e ÞV W

ð1Þ

where V is the volume of Mn (II) solution (L), Co and Ce are the initial and equilibrium concentration of Mn (II) in solution (mg l−1), respectively, and W (g) is the amount of the added biosorbent on the dry forms [15]. The percent biosorption of Mn(II) was calculated as follows:
C i −C f 100 ð2Þ Biosorption ð%Þ ¼ Ci Where Ci and Cf are the initial and final Mn(II) concentration, respectively [8]. Modeling the biosorption-binding equilibrium is a prerequisite for work involving batch studies that represent the most effective configuration of the sorption-based process. The Langmuir and Freundlich isotherm equations are used to predict the sorption of manganese from aqueous solutions onto the P. camemberti biomass [8]. Column Fixed Bed Absorption Studies The applied column in the fixed bed continuous system is a glass column which is 1.5 cm in internal diameter and 50 cm in height. About 20 cm of its height has been packed with immobilized P. camemberti, and a valve has been fitted at the bottom of the column. The volume of the column is 28 ml, and the amount of biomass is 6 g [8]. The solution contains 5 ppm Mn(II) ion. The input flow rates of the column are 2, 4, and 6 (ml/min) that are set by a pump. The desired pH for each metal is the optimized pH that has been evaluated in the batch process. The metal samples are collected every 15 min and are prepared for concentration determination analyses by spectrophotometer [13].

Results and Discussion Effect of Initial Concentration on Mn(II) Biosorption The effect of initial manganese ion concentration on the biosorption of Mn(II) by the nanobiomass and biomass (0.1 g) was investigated when Mn(II) ion concentration ranged 5, 10, 20, 40, and 60 mg/L under a condition of pH=6, t=30 min, and temperature 25 °C (Fig. 2). The

Fig. 2 Effect of initial concentration of solution Mn(II) by nano-biomass and biomass

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experimental results showed that the percent biosorption of Mn(II) decreased with an increase in initial manganese ion concentration, and percent removal in nano-biomass is more than biomass. The biosorption of Mn(II) ion (5 mg/L) by nano-biomass and biomass is 91.54 and 71.08 %, respectively. The increase in Mn(II) uptake resulted from the increase in the driving force, i.e., concentration gradient of adsorption. The decrease in the removal efficiency of manganese ions might be owned to insufficient binding sites for adsorption. Also thought that a lower removal efficiency at higher concentrations was due to the saturation of binding sites [16]. Effect of pH Variations It is well known that the pH of the aqueous solution is an important controlling parameter in the adsorption process [17]. The effect of pH on biosorption of Mn(II) was studied at room temperature about 25 °C by 1 g adsorbent (nano-biomass, biomass) varying the pH of metal solution from 1.0 to 9.0 [8]. The plot of biosorption efficiency (%) versus pH is shown in Fig. 3. Little or no biosorption of Mn was observed for pH less than 3.0. The highest biosorption efficiency was obtained to be 98 and 58.41 % at pH 6–6.5 for nano-biosorbent and biosorbent, respectively [1]. The increase of pH increases the negative sorption sites and decreases H+ ion competition with the metal ions for sorption sites, while at higher pHs, the formation of negatively charged hydrolyzed ions decreases again the sorption of metal ions. At pH values higher than 6.0, Mn (II) ions precipitated out because of the high concentrations of OH− ions in the biosorption medium [4, 18, 19]. Effect of Temperature Temperature may play an important role in the biosorption of Mn(II). Therefore, batch experiments were performed at pH 6.0 and 0.1 g of nano-biomass and biomass to examine the temperature dependency of Mn(II) biosorption by dead fungal biomass [20]. The percent biosorption of Mn(II) on nano-biomass and biomass increased from 84.16 to 97.545 and 79.375 to 86.95 %, respectively, when temperature was increased from 30 to 50 °C at an initial concentration of 5 mg/L. The increase in biosorption capacity of biomass with temperature indicates an endothermic process. The increase in biosorption with temperature may be attributed to either the increase in the number of active surface sites available for biosorption on the adsorbent of the adsorbing species or the decrease in the thickness of the boundary layer surrounding the adsorbent with temperature so that the mass transfer resistance of adsorbate in the boundary layer decreases. Since diffusion is an endothermic process, greater biosorption

Fig. 3 Effect of pH on Mn(II) biosorption by nano-biomass and biomass

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will be observed at higher temperature. Thus, the diffusion rate of ions in the external mass transport process increases with temperatures [17]. Effect of Adsorbent Dosage on Mn(II) Biosorption The effect of biomass dosage on the biosorption of Mn(II) was studied using different P. camemberti biomass dosages ranging from 0.1 to 2 g/L in 100 ml Mn(II) solution (5 ppm ppm) under optimized condition of pH [6], contact time (10 min), and temperature 25 °C [8]. The result showed that an increase in adsorbent dosage resulted in an increase in Mn(II) biosorption efficiency. This is owing to the increase of adsorbent mass (more surface area available for adsorption) that would result in a greater availability of reactive groups (increase in the number of binding sites). It was clear that maximum biosorption capacities were observed at dosages below 1.5 g/L [16]. When the nano-biomass and biomass dosage were increased from 1 to 1.5 g/L, the removal increased from 98.4 to 99.88 % and 39.53 to 97.85 %, respectively. Research suggests that increasing the amount of dry biomass and nano-biomass particles in a solution made to stick together and be prevented from accessing metal to the active biomass surface. Thus, increasing the amount of biomass or nano-biomass will not have much impact on the uptake [21]. Effect of Contact Time on Manganese (II) Biosorption The biosorption efficiency of metal ions was evaluated as a function of contact time. The function of contact time on the biosorption of Mn(II) by biomass of P. camemberti was studied under shake-flask conditions at pH 6, at 150 rpm, using 100 ppm Mn(II) ion, and at room temperature of 25 °C. The relationship between manganese adsorption capacity and adsorption time indicates that manganese biosorption capacity increased obviously during the first 30 min of the metal-biosorbent contact. This phenomenon could be attributed to the availability of the large number of vacant sites on the adsorbent surface. The equilibrium was reached within 60 min. Therefore, the manganese (II) adsorption capacity and the concentration of the unadsorbed manganese (II) at the end of 60 min were given as the equilibrium values of qe (mg/g) and Ce (mg/L), respectively [8, 16]. Kinetic Modeling Lagergren pseudo-first-order and second-order kinetic models were used to evaluate the kinetics of the Mn(II) biosorption on the nano-biomass and biomass. The pseudo-first-order model is expressed as Eq. (3) logðqe −qt Þ ¼ logqe −

k1t 2:303

ð3Þ

Where qe and qt (mg/g) are the amount of the metal ions biosorbed at equilibrium mg/g and t (minutes), respectively, and k1 (min−1) is the rate constant of first-order adsorption [14, 22]. The intercept of the plot should be equal to log qeq. However, if the calculated qeq does not equal the equilibrium metal uptake, then the reaction is not likely to be first order even if this equation has a high correlation with the experimental data. The linear plots of log (qe −qt) versus t for the pseudo-first-order model for Mn (II) by biomass and nano-biomass are shown in Fig. 4. The correlation coefficients calculated for the pseudo-first-order equations for both

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Fig. 4 Pseudo-second-order kinetics of Mn(II) ion sorption by nano-biomass for different concentration (pH=6, dose=0.1 g/l, 150 rpm)

biomass and nano-biomass were found to be 0.944 and 0.988, respectively, and the calculated qe is not equal to experimental qeq as indicated in Table 1, suggesting the insufficiency of the pseudofirst-order model to fit the kinetic data for the initial manganese concentration examined [23]. The kinetic data were further analyzed through the pseudo-second-order relation. The pseudo-second-order kinetic model is expressed as follows: t 1 1 ¼ þ t qt k 2 q2e qe

ð4Þ

Where t is the contact time (minutes), k2 (g mg−1 min−1) is the rate constant, qe (mg/g) and qt(mg/g) are the amount of metal adsorbed at equilibrium and at any time, t (Fig. 4). qe and k2 can be determined from the slope and intercept of the plot, respectively [14, 24]. The rate constants and the correlation coefficients for both models are summarized in Table 1. The correlation coefficient for the pseudo-second-order adsorption was found to be 0.99 at an initial concentration of 5 mg/L for biomass and nano-biomass. The adsorption capacities calculated by the pseudo-second-order model are also close to those determined by experiments. Table 1 Kinetic parameters obtained from pseudo-first-order and pseudo-second-order for Mn(II) bisorption by P. camemberti (biomass) and nano-P. camemberti (nano-biomass)

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Therefore, it has been concluded that the pseudo-second-order adsorption model is more suitable to describe the adsorption kinetics of Mn(II) by biomass and nano-biomass [23, 25]. The most important mass transfer resistance for sorption from aqueous solutions has been established to be the internal (intra-particle) diffusion. The effect of external film diffusion on biosorption rate can be assumed to be insignificant and ignored in any engineering analysis because when the biomass is employed as a suspension of fine particles in a perfectly mixed batch or continuous systems, all the surface binding sites are available for metal uptake [26]. The intra-particle diffusion model can be defined as follows: qt ¼ K p t1=2 þ C

ð5Þ

where Kp is the intra-particle diffusion rate constant, and C of adsorption constant is the intercept [28]. The values of qt correlated linearly with values of t1/2, and the rate constant Kp directly evaluated from the slope of the regression line [27]. Table 2 shows that the C values or the boundary layer decreased with the increased initial Mn(II) concentration and adsorbent concentrations. Intra-particle diffusion model equation was applied to the experimental data for different initial Mn(II) concentrations. The rate constant values for intra-particle diffusion were obtained from the slopes of the linear portions of the plots of qt versus t1/2 for different initial Mn(II) and cone biomass concentrations, and results were presented in Table 2. Kp values decreased with increased adsorbent concentrations and increased with increased initial Mn(II) concentrations [26, 28]. Biosorption Isotherms Two different biosorption isotherms, the Langmuir and the Freundlich isotherm, were used to correlate the equilibrium data. The correlation with the amount of adsorption and the liquid-phase concentration was tested with the Langmuir, Freundlich, BET, and Temkin isotherm equation. Langmuir and Freundlich Isotherm The experimental data are applied to the Langmuir and Freundlich isotherm models as they incorporate constants that estimate the quantity of the biosorption capacity of a biosorbent. Traditionally, the Langmuir model is represented as q¼

bqmax C e ð1 þ bC e Þ

ð6Þ

Table 2 Comparison between adsorption parameters of inter-particle kinetic model Parameter

Nano-biomass

Biomass

Intra-particle diffusion

Intra-particle diffusion

C

R2

Kp

C

R2

Initial Mn(II) concentration (mg L−1)

Kp

5

0.173

3.476

0.831

0.121

3.277

0.921

10 20

0.251 0.574

6.593 9.881

0.978 0.934

0.169 0.162

5.344 8.876

0.937 0.897

40

0.747

0.889

0.763

9.444

0.889

18.05

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where, qe (mg/g) is the amount of metal adsorbed per mass of adsorbent biomass. qmax (mg/ g) is the adsorption capacity, defined as the maximum amount of metal ion forming a complete monolayer on the biomass surface, b (L/mg) is a constant related to the energy of adsorption, and Ce (mg/L) is the equilibrium concentration of the metal in the solution. After 30 min of adsorption reaction, the residual metal concentration that was considered as Ce was measured.    1 1 1 1 ð7Þ ¼ þ q bqmax Ce qmax The constants max q and b are the characteristics of the Langmuir isotherm and can be determined from Eq. 7 [8]. A plot of 1/q versus 1/Ce gives a straight line with a slope of (1/bqmax) and an intercept of(1/qmax). The Mn(II) biosorption performance by biomass and nano-biomass was achieved by measurements at initial concentrations of 5, 10, 20, and 40 mg/L; 120-min contact time, and pH 6.0. Linear transformation of the data using the Langmuir model allowed the computation of maximum metal removal capacities, qmax, and values of constant b. Values of Langmuir parameters are summarized in Table 3. The maximum biosorption capacity (qmax) of biomass and nano-biomass are 12.19 and 16.95 mg/g, respectively. The results indicated that the biosorption of Mn(II) by nano-biomass was higher than by biomass. The Freundlich isotherm is a nonlinear sorption model. This isotherm model intends a monolayer sorption on a heterogeneous surface suggesting the interactions between adsorbed molecules. The general Freundlich equation is given as follows: qe ¼ K F C 1=n e

ð8Þ

lnqe ¼ lnK F þ 1=nlnC e

ð9Þ

where, KF and n are Freundlich biosorption isotherm constants, being indicative of the extent of the biosorption and the degree of nonlinearity between solution concentration and biosorption, respectively. KF and 1/n are determined from the linear plot of lnqe versus lnCe [8, 23]. The values of Freundlich parameters are summarized in Table 3. From Table 3, the magnitude of Kf and n shows a higher uptake of Mn(II) using nano-biomass compared to biomass. The highest Kf and n values were 8.54 and 2.74 for nano-biomass and 5.30 and 2.97 for biomass, respectively. Table 4 also indicates that n is greater than unity, indicating that Mn(II) ions are favorably adsorbed by nano-biomass and biomass. Values of n>1 indicate the positive co-operativity in binding and heterogeneous nature of adsorption [22]. As shown in Table 3, the correlation coefficient of the Langmuir isotherms was more than 0.91. With regard to Freundlich, it was also over 0.90. This indicated that the data fits both Langmuir and Freundlich model well, although the former is better in the examined pH range

Table 3 The Langmuir, Freundlich, and Temkin adsorption isotherm constants for Mn(II) biosorption by biomass and nano-biomass Biosorbent

Langmuir qmax (mg/g)

Freundlich b (L/mg)

R2

Kf

n

Temkin R2

A (L/g)

B

R2

Biomass

12.19

1.025

0.910

5.296

2.976

0.995

6.05

2.957

0.941

Nano-biomass

16.95

1.78

0.946

8.542

2.747

0.994

11.08

4.095

0.893

Appl Biochem Biotechnol Table 4 Surface area of the resulting nano-biomass and biomass Sample

C Sample Vm weight (g) (cm3 g−1)

SBET Total pore volume Mean pore Saturated vapor (m2/g) (cm3/g) (p/p0 =0.99) diameter (nm) pressure (kPa)

Nano-biomass 0.1222

1.0013

5.655

Biomass

0.4059

3.6337 1.7668 0.0046208

0.2111

4.3583 0.022709

20.842

84.108

10.461

84.149

SBET surface area calculated using the BET equation, Vm volume required to cover the adsorbent surface with monomolecular layer (cm3 g−1 ), C adsorption coefficient expressive of energy of interaction with the surface

This biosorption characteristic indicates that the surface saturation is dependent on the initial metal ion concentrations. At low concentrations, adsorption sites took up the available metal more quickly. However, at higher concentrations, metals need to diffuse into the biomass surface by intra-particular diffusion and greatly hydrolyzed ions will diffuse at a slower rate [23]. Temkin Isotherm The derivation of the Temkin isotherm assumes that the fall in the heat of sorption is linear rather than logarithmic, as implied in the Freundlich equation. The Temkin isotherm has generally been applied in the following form. Temkin isotherm model is shown in Eq. (10): [17] qe ¼ RT=b lnðA C e Þ

ð10Þ

qe ¼ BlnA þ BlnC e

ð11Þ

where B=(RT)/b, qe (mg g−1), and Ce (mg L−1) are the amounts of adsorbed Mn (II) per unit weight of biosorbent and Mn(II) concentration in solution at equilibrium, respectively. Also, A is the equilibrium-binding constant corresponding to the maximum binding energy, b is the Temkin isotherm constant, T is the temperature (K), and R is the ideal gas constant (8.314 J mol−1 K−1) [17]. The values of A and B constants for the Temkin isotherm are presented in Table 3. BET Isotherm Brunauer-Emmett-Teller (BET) theory used to measure the surface area of microporous materials. Determining the surface area and pore volume is typically done using N2 gas adsorption. According to this method, the cumulative pore volume distribution was first calculated using points from the isotherm at relative pressures corresponding to previously calculated pore sizes [29]. The linearized BET isotherm is shown in Eq. (12): P 1 ¼ þ ðC−1ÞP=ðV m CP0 Þ V ðPo −PÞ V m C

ð12Þ

Where P is the pressure of adsorbate at equilibrium, P0 the saturated pressure of adsorptive, V volume of gas adsorbed at pressure P (cm3 g−1), Vm the volume required to cover the adsorbent surface with monomolecular layer (cm3 g−1), and C is the adsorption coefficient expressive of energy of interaction with the surface. The C and Vm value and the correlation coefficient for the BET isotherm are presented in Table 4.

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Comparing the SBET of biomass and nano-biomass shows that the nano-biomass increased the surface area. FT-IR Analysis In order to find out which functional groups play major roles in the adsorption of manganese ions, FT-IR spectral analysis of biosorbents were carried out. Figure 5 shows that the FT-IR spectra of nano-biomass before and after Mn(II) biosorption in the range of 500–4,000 cm−1 were taken and compared with each other to find out which functional groups are responsible for the Mn(II) biosorption. The broad absorption peak around 3,430–3,400 cm−1 is indicative of the existence of the –OH groups and the –NH groups. The O–H group stretch can also occur from carboxylic acids (COOH) and is extremely broad, ranging from 3,400 to 2,400 cm−1 which often interferes with C–H absorptions [16, 17, 30, 31]. The adsorption band at 1,637 cm−1 could be attributed to C=O stretching conjugated to a –NH deformation of –CN (amide I) group of protein peptide bond and chitosan. The 1,543 cm−1 band is caused from the stretching vibration of –CN and the deformation vibration of –NH (amide II) of peptide bond of proteins. P=O, (PO4−3) and P–OH groups are observed at the wavelengths of 1,160, 1,030–1,100, and 910–1,040 cm−1, respectively. CN groups appear at the wavelength of 1,000–1,350 cm−1. The results show that the peak intensities have decreased after performing the reaction, which is due to the reaction between the metal ions. It was proposed that the metal-binding process happened on the surface of dead fungal biomass. At the wavelength of about 1,230–1,280 cm−1, it is observed that some peaks have been disappeared, which belongs to C–O groups [8]. Fixed Bed Study Batch biosorption process analyzes to provide operational data related with the Mn(II) adsorption performance of a given biosorbent. On the other hand, continuous system is desired in most wastewater treatment plant in industries. The characteristic parameters of the fixed bed biosorption were examined to get data to optimize the processes in fixed bed column for the biosorption of Mn(II). In the studies of continuous system, the column has been filled with immobilized P. camemberti. After having filled the column with immobilized biomass, the effect of flow rate and bed height has been studied. All the effects on the process of biosorption of Mn(II) from the solution were depicted by breakthrough curves, which were plotted with Ce/Co ratio versus time.

Fig 5 The FTIR spectra of nano-biomass: (a) before Mn(II) adsorption. (b) after Mn(II) adsorption

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Fig. 6 The effect of flow rate of Mn(II) on biosorption by nano-biomass

Effect of Volumetric Flow Rate In the batch system, the efficiency of nano-state was higher, and that is why only the nano-biomass has been taken into account in the study of the flow rate effect in column. The investigation on the effect of flow rate on the single-component biosorption of manganese (II) on immobilized biomass and nano-biomass, the influent metal concentration was held constant at 5 ppm for Mn(II), bed height (20 cm) constant, and varying flow rate from 2, 4, and 6 ml/min. The breakthrough curve shown in Fig. 6 was a plot of dimensionless concentration (Ct/C0) versus time (t). It was shown that breakthrough generally occurred faster with faster flow rate. Breakthrough time reaching saturation was increased significantly with a decrease in the flow rate. In the foremost interval, the value of Ct/C0 increased quickly since it has reached 0.62, the change then became slowly. When at a low rate of influent, metal ions had more time to contact with microorganism that resulted in higher removal of metal ions in column. While increasing the flow rate, the results indicated that the adsorption capacity would reach the equilibrium value faster, which may cause a negative effect on the mass transferring efficiency of the metal ions [8, 30, 32]. The maximum Mn(II) biosorption was 98.97 % at a flow rate of 2 (ml/min). Results as in Fig. 6 show that the uptake of Mn(II) ion onto the nano-biomass Table 5 Effect of bed heights on the removal of manganese (%) Residence time (min)

Biomas

Nano-biomass

Column height (cm) 10 cm Total percentage removal of manganese (%)

30 cm Total percentage removal of manganese (%)

10 cm Total percentage removal of manganese (%)

30 cm Total percentage removal of manganese (%)

10 20

40.2 45.26

65.75 68.02

68.3 79.56

89.62 93.62

30

59.94

72.92

84.46

97.54

Appl Biochem Biotechnol

Fig. 7 Breakthrough curve of the effect of different bed heights a biomass b nano-biomass

decreases when the flow rate through the bed increases. The volume treated resourcefully until the breakthrough point declined by an augmentation in flow rate. Decreasing the contact time between the Mn(II) ion and the biomass at higher linear flow rates is a result of the process. Intra-particulate diffusion seems when the flow rate drops off the contact time in the column. At a higher flow rate, the biosorbent biomass acquires saturated in the early hours [8, 9]. Effect of Bed Height on the Biosorption of Manganese The effect of bed height on the biosorption of Mn(II) was investigated using various bed heights of 10 and 30 cm, as shown in Table 5. Accumulation of Mn(II) ion (5 mg/L) in the fixed bed column is fundamentally dependent on the number of immobilized biosorbents (biomass alginate) inside the column [8, 9]. As bed height increases, the breakthrough point time increases and the amount of manganese ions adsorbed on biosorbent surface also increases (Fig. 7). This is mainly due to the higher contact time between metal ion solution and P. camemberti surface and also due to more number of active sites and ionic groups of biomass and nanobiomass available for the sorption of manganese [12]. The column performance is improved to achieve higher yields of metal removal by keeping optimum operating conditions of biomass loading, residence time, temperature, pH, and initial metal ion concentration [12].

Conclusions Biosorption of Mn(II) by biomass and nano-biomass was studied, using a batch system and a continuous fixed bed. The results showed that this fungous species functions with a very low cost compared to the physical-chemical methods and more effectiveness than other methods for Mn(II) biosorption. This study showed that biomass and nano-biomasses are effective and inexpensive biosorbents for Mn(II) removal from aqueous solution as compared with other fungi species. The biosorption capacity of Mn(II) was influenced by pH, ion concentration, contact time, temperature, and biosorbent dose. The present study illustrated that the biomass and nano-biomass have a high adsorption capacity, and due to its surface adsorption mechanism, it is appropriate in order to eliminate. manganese ion. The nano-biomass shows a higher adsorption capacity compared to the biomass, and this may be due to the different structures of the cell wall.

Appl Biochem Biotechnol

The results explained that fungal biomass can be immobilized in alginate in the form of spherical beads with a porous structure. These spherical beads could remove the Mn(II) ions from aqueous solutions. The biomass-alginate beads exhibited excellent handling characteristics. The alginate seems to be a good choice as an immobilizing agent because it is an amorphous, heat resistant, and chemically fairly stable. The procedure described in this paper for producing beads can be scaled up for use by an industrial plant to manufacture large quantities of beads on a continuous or semi-continuous basis. The commercial development of immobilized biomass beads can only be considered after conducting a comparison of its cost and efficiency with other biomasses. Fixed bed column was used in the continuous system, since it is the most appropriate reactor for laboratory scale analyses. The biosorption capacity is strongly dependent on the inlet Mn(II) ion concentration, flow rate, and bed height. As the flow rate increased, the breakthrough curve becomes sharper, the break point time and adsorbed Mn(II) ion concentration dropped off.

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