Removal of Lead from Aqueous Solutions Using Fagus Orientalis Lipsky: Box-Behnken Experimental Design

Introduction
Advances in water and wastewater treatment technology need spur for the development of technologies that may be more effective and less costly. Nowadays, the contamination of water by toxic heavy metals through the discharge of industrial wastewater is a world wide environmental problem. The term heavy metal refers to the metallic elements having density greater than or equal to 6.0 g cm^-3.^1-3 The contamination of wastewaters and surface waters by toxic heavy metals is a worldwide environmental problem. These toxic metal ions commonly exist in process waste streams from mining operations, metal plating facilities, power generation facilities, electronic device manufacturing units, and tanneries. Because of economic and environmental factors, the removal and recovery of heavy-metal ions from industrial wastewater have been a significant concern in most industrial branches.^4,5 Lead has been recognized one of the most hazardous heavy metals since mining, acid battery manufacturing, metal plating, printing, textile, photographic materials, ceramic and glass industries, explosive manufacturing and also lead-containing piping materials are the main source of lead contamination.

The most commonly applied physicochemical treatment methods are: (a) precipitation as hydroxides, carbonates or sulfides and subsequent liquid-solids separation by gravity settling, and flotation or filtration, (b) sorption (adsorption, ion exchange), (c) membrane processes, (d) electrolytic recovery and (e) liquid-liquid extraction.^6-9 However, each method has its merits and limitations in application and they are often limited by technical and economical issues.¹⁰ Lead has

The use of multivariate experimental design techniques is becoming increasingly widespread in chemistry. Multivariate experimental design techniques, which permit the simultaneous optimization of several control variables, are faster to implement and more cost-effective than traditional univariate (one at a time) approaches.¹¹ One of the most popular multivariate design techniques is two level full/fractional factorial, in which every factor is experimentally studied at only two levels. Due to their simplicity and relatively low cost, full factorial design techniques are very useful for preliminary studies or in the initial steps of an optimization, while fractional factorial designs are almost mandatory when the problem involves a large number of factors. On the other hand, since only two levels are used, the models that may be fit to these designs are somewhat restricted. If a more sophisticated model is needed, as for the location of an optimum set of experimental conditions, then one must resort to augment response surface designs, which employ more than two factor levels. Among these, Box–Behnken is a second-order multivariate design technique based on three-level incomplete factorial designs that received widespread application for evaluation of critical experimental conditions, that is, maximum or minimum of response functions. The number of experiments (N) required for the development of this design is defined as N = 2k(k−1) + C₀, where k is the factor number and C₀ is the replicate number of the central point. ^12-14

The target of this study was to investigate the biosorption potential of Fagus Orientalis Lipsky tree leaves to treat wastewaters contaminated with lead. The metal loading capacity of yeast biomass was determined as a function of the initial metal ion concentration, contact time, biomass amount and pH using Box-Behnken design. The biosorption data were analyzed by Freundlich and Langmuir isotherm models. The effect of temperature and thermodynamic parameters was studied as well.

Experimental

Apparatus and Materials

The experiments were performed using a Shimadzu atomic absorption spectrometer (AA-680) equipped with deuterium background correction. An Pb hollow cathode lamps (Hamamatsu, Photonic Co. Ltd, L233-series) was used as the radiation source. The pH was determined with a model 780 Metrohm pH-meter with combined glass-calomel electrode. Box-Behnken design was accomplished with Minitab Version 16. All reagents used were of the highest available purity and at least analytical reagent grade. The water utilized in all studies was double-distilled and deionized. Metal ion solution used in this study was prepared by dilution of 1000 mg L^-1 stock solution of lead obtained by dissolving nitrate salt of lead in distilled and deionized water. Universal buffer solutions were prepared from boric acid, citric acid and phosphoric acid. The final pH was adjusted by the addition of 0.2 mol L^-1 sodium hydroxide.

Biosorbent Material

The Fagus Orientalis Lipsky tree leaves were gathered from twigs by clean plastic bags, washed with ion-free distilled water and then dried at 80° C for 24 h. The dried biomass was powdered by using mortar and pastel. The powdered biomass was sieved to the mesh of 40–50 and then stored in plastic bags to get ready for being used as a biosorbent in batch studies. 

Biosorption Studies

The biosorption of lead ion on the dried yeast biomass was investigated in batch biosorption equilibrium experiments. The effect of the initial metal ion concentration, contact time, biomass amount and pH using Box-Behnken design were studied. For this adsorption experiments, 10 ml of metal solution of known initial concentration was shaken with sorbent at 150 rpm, at the desired temperature (10, 20, 30, 40, and 50 °C), for 60 min, at the end of the period, after centrifugation, it was analyzed by using Atomic Absorption Spectrometer (Shimadzu AA-680). The concentrations of heavy metal ions were determined using an atomic absorption spectrophotometer before and after biosorption. Biosorption efficiency was expressed as:

Formula1

where C_i and C_e are the initial and residual concentrations of metal ion, respectively. The amount of adsorbed heavy metal ions per unit of biosorbent (mg g^-1) was obtained by using the following expression:

Formula2

where q is the amount of heavy metal adsorbed onto the unit amount of the biomass (mg g^-1), C₀ and C_e are the concentrations of the heavy metal in the initial and equilibrium solution (mg L^-1) and after  biosorption, respectively and V is the volume of the aqueous phase (L) and finally m is the amount of the biomass (g).

Results and Discussion

There are different factors that affect the adsorption of lead by biomass used in this process. Some of them are selected as suitable initial pH, concentration of lead, contact time and concentration of biomass. It is very important to optimize them in order to obtain good removal and strategy forms.

Factorial Design

A two level factorial 2⁴ design with two replicates of center point is performed in order to determine the influence of these factors on their interactions. The factorial design is evaluated using analytical response (removal of lead from aqueous solution). The experimental matrix and the removal for each trial are shown in Table 1. An analysis of the variance (ANOVA) demonstrated that, within the experimental range, pH, contact time and concentration of biomass were statistically significant and Pareto chart (see Fig. 1) interpretation it.

Figure 1: Pareto chart of main effects obtained from 24 full factorial designs. The vertical line defines the 95% confidence interval.   Click here to View figure

Table 1: Experimental design and the results obtained in removal.

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