Introduction

Colors are considered to be important pollutants in sewage because they create undesirable effects, may interfere with antibacterial growth and prevent the photosynthesis of aquatic plants and also increase the chemical oxygen demand (COD) of the water (Solache-Ríos et al. 2010). The inherent toxicity of some colors has deleterious effects on fishes and microorganisms and may even cause their death, while other colors may lead to eczema and cancer in humans (Mahanta et al. 2008; Verma and Banik 2013). Various industries are important sources of environmental pollution, and the effluents of these industries are, in most countries, emptied into the natural water system without any refinement or modification. Dyeing/textile industries produce vast amounts of effluents of which the main component is colors (Prado et al. 2008). Due to various combinations, Processing of the sewage from such factories and production centers is complicated due to the various combinations of components in the sewage. The textile industry is an economically important industry, and polluted water resources and colors used in these industries find their way through the sewers into the environment (Lewis 2014; Akcil et al. 2015). For this reason, the reduction and elimination of all types of dyes from industrial effluents are of considerable importance, and the dumping of color effluents into water resources is prohibited. There are various methods to remove dyes from sewage, such as adsorption, biodegradation, coagulation, filtration and reverse osmosis (Han et al. 2010; Yu et al. 2010). Surface adsorption is considered to be an efficient process among color removal methods due to its low cost, ease of operation and high efficiency (Alpat et al. 2008; Gök et al. 2010).

In past studies, researchers mostly studied one factor at any one time, which was a tedious and time-consuming approach. The design of any experiment can be considered to be an instrument of analysis for modeling and analyzing the effects of control agents as response variables. The traditional design of experiments on colors was problematic, particularly when the number of agents and the number of experiments were too large. The Taguchi design is a method used as an experimental technique to reduce the number of experiments using orthogonal arrays (Nalbant et al. 2007). In recent years, the use of nanoscale zero-valent iron (NZVI) particles has received broad scientific acceptance due to its high decolorization power and toxicity reduction capacity (Bigg and Judd 2000; Shojaei et al. 2017). In the study reported here, Acid Green 25 (AG-25) dye removal by NZVI particles was studied. The effect of time, pH, dye concentration and the catalyst amount were examined. The Taguchi method was used to optimize the process of AG-25 dye removal.

Experimental

Material and instrumentation

The materials used in this study include ferric chloride (FeCl3·6H2O), sodium borohydride (NaBH4), acetone ©3H6O), hydrochloric acid (HCl) and sodium hydroxide (NaOH) (all obtained from Merck KGaA, Darmstadt, Germany). AG-25 dye with laboratory purity level was prepared for use as the chromogenic material. The general specifications of the AG-25 dye are presented in Table 1. The stock solution (1000 mg L−1) was made from AG-25 dye, and double distilled water was used to dilute the dye solution to the desired volume. The solutions of HCl (0.1 M) and NaOH (0.1 M) were used to adjust the pH, and a pH meter was used to measure the pH. Qualitek-4 software was used to analyze the data. The morphology and size of the particles were observed by scanning electron microscopy (SEM). The crystal structure of the product was examined by X-ray diffraction (XRD) with Cu Kα radiation.

Table 1 General characteristics of Acid Green 25 dye

Preparation of NZVI particles

Nanoscale zero-valent iron particles were prepared by the liquid phase reduction method (Glavee et al. 1995). Sodium borohydride solution (0.3 M) was added dropwise into an equal volume of ferric chloride solution (0.1 M) during vigorously stirring under a N2 atmosphere. The reaction can be described by the following equation (Sun et al. 2006):

$$ 4 {\text{Fe}}^{ 3+ } + {\text{ 3BH}}^{ - }_{ 4} + {\text{ 9H}}_{ 2} {\text{O }} \to {\text{ 4Fe}}^{0} + {\text{ 3H}}_{ 2} {\text{BO}}^{ - }_{ 3} + {\text{ 12H}}^{ + } + {\text{ 6H}}_{ 2} . $$
(1)

Following the reaction, the solid was vacuum-filtered and washed with double-distilled water and acetone. The resulting black solid was allowed to stand for 30 min in a N2 atmosphere before use.

Taguchi design

In this study, the L16 model of the Taguchi method of experimental design was used to determine the optimal conditions for dye removal. The L16 model has four columns and 16 rows, with each column belonging to an agent and each row belonging to an experiment. For example, the first column shows the catalyst amount at the first level for the first four experiments and at the second level for the second four experiments. In the L16 model, each variable is examined at four levels. In other words, it is recommended that 16 experiments be used to investigate four variables at four levels. Given all of the possible combinations among the four factors, 44 = 256 experiments are necessary to cover all possible states; of these 256 experiments, the 16 experiments which have the greatest influence on four relevant variables are recognized and recommended in the Taguchi method using statistical methods (Taguchi et al. 2000; Roy 2001). These factors are pH, catalyst amount, dye concentration and time, whose values are given in Table 2.

Table 2 Levels and variables used for removal of the Acid Green 25 dye

The Taguchi method uses the signal/noise (S/N) ratio of the deviation of characteristic with the desired value. S/N ratios are different for each type of characteristic, and the larger the amount of characteristics, the better. The unit of the S/N ratio is the decibel (dB). The S/N ratio is defined as:

$$ \frac{S}{N} = \frac{{ - 10\;\log \left( {1/y_{1}^{2} + 1/y_{2}^{2} + 1/y_{3}^{2} + \cdots + 1/y_{n}^{2} } \right)}}{n} $$
(2)

where y i is the characteristic property, and n is the replication number of the experiment (Kim et al. 2004).

Batch decolorization process

We analyzed the efficacy of NZVI particles on AG-25 dye removal. For this purpose, 0.2–0.8 g of catalyst was added to 25 mL of the dye solution in 100-mL beakers. The pH of the sample solution was adjusted in the range of 4–8 using HCl and NaOH solution. The solution was stirred in the beakers using a magnetic stirrer at 200 rpm. To determine the remaining concentration and to calculate the percentage of AG-25 dye removal, the absorbance of solution was read at the wavelength of maximum dye using a UV–Vis spectrophotometer. All experiments were performed at ambient temperature. Each experiment was repeated three times, the mean values of each experiment were used as the final results in the calculations. In these experiments, Eq. (3) was used to determine the percentage of dye removal:

$$ {\text{Dye removal }}\left( \% \right) \, = \frac{{c_{\text{o}} - c_{\text{e}} }}{{c_{\text{o}} }} \times 100 $$
(3)

where C o (mg L−1) is the initial concentration and C e (mg L−1) is the equilibrium concentration of the dye.

Results and discussion

Characterization of the NZVI particles

Scanning electron microscopy images will contribute to surface examination of the materials. To this end, SEM images were taken of the sample (Fig. 1). According to Fig. 1, the synthesized iron nanoparticles have almost identical morphology, being spherical and superficially porous. The XRD patterns are shown in Fig. 2. The XRD analysis revealed the presence of NZVI as the main phase of the samples (2θ = 44.8°).

Fig. 1
figure 1

Scanning electron microscopy image of nanoscale zero-valent iron (NZVI) particles

Fig. 2
figure 2

X-ray diffraction pattern of NZVI particles

Determination of optimal conditions using the Taguchi method

The experimental results and the S/N ratio for dye removal calculated using Eq. (2) are shown in Table 3, and the mean S/N ratio for each level of the variables is shown in Table 4. In Table 4, the importance of each of the variables is specified for AG-25 dye removal. Dye concentration has the first and largest effect on the process of dye removal, followed by pH, catalyst amount and finally by time as the fourth independent variable affecting for the percentage of dye removal.

Table 3 Experimental results for percentage of Acid Green 25 dye removal
Table 4 Response for the Taguchi analysis of Acid Green 25 dye removal data

The S/N response graph for removal of AG-25 solution is shown in Fig. 3. The variance analysis was conducted to show the effect of each variable on the final result (Taguchi 1987). The results of the analysis of variance are shown in Table 5. Based on the results of variance analysis, initial dye concentration and pH are the most important variables in eliminating AG-25 dye, respectively. The degree of freedom for each factor is 3 and the total degree of freedom is 15.

Fig. 3
figure 3

Effect of catalyst amount (a), dye concentration (b), pH (c) and time (d) on dye removal

Table 5 Analysis of variance

Effect of catalyst amount

The amount of catalyst is an important parameter affecting the process of dye removal. As shown in Fig. 3a, the percentage of AG-25 dye removal was dependent on catalyst amount and sharply increased with increasing catalyst amount from 0.2 to 0.6 g. However, there is no significant increase in the efficiency of dye removal when the amount of catalyst surpassed 0.6–0.8 g. The most likely explanation for this result is that the sites of adsorption remained unsaturated during the process of adsorption, with the number of sites available for the site of adsorption increasing with increasing the catalyst amount. The percentage of dye removal is increased by increasing the amount of NZVI particles. The increase in efficiency could be obtained due to increasing the active surface available for chromogenic material (Dutta et al. 2016; Shojaei et al. 2017).

Effect of dye concentration

Dye concentration also provides a significant driving force to overcome the total resistance of transferring color mass between liquid and solid phases. We tested the effect of different amounts of dye (10–40 mg L−1). The results show that there was a decrease in the process efficiency with increasing concentration of the dye from 10 to 40 mg L (Fig. 3b), with the maximum amount of discoloration obtained at a dye concentration of 10 mg L−1. Adsorption was considerably decreased with increasing dye concentration due to saturation of the active sites of the catalyst and a parallel reduction in the adsorption surface available, resulting from the consistency of catalyst amount against an increasing amount of chromogenic material (Chompuchan et al. 2010; Li et al. 2006). Reductions in the concentration of pollutants in the environment provide molecules of absorbed material with a greater opportunity to react with adsorption sites; thus, the adsorption rate is increased in these conditions. Based on these results, we suggest that dilution is one method to increase the percentage of dye removal in polluted sewage (Vadivelan and Kumar 2005; Bulut and Aydın 2006).

Effect of pH

pH is a factor which impacts the process of adsorption by affecting the structure of the pollutants/color and catalyst (Shu et al. 2009; Almeelbi and Bezbaruah 2012). As shown in Fig. 3c) when the pH of a solution is acidic (pH 4), dye removal is very high but the discoloration is reduced by increasing the pH up to 8.5. Thus, an acidic pH is effective in achieving maximum dye removal. At an acidic pH, the surface of metallic iron is constantly kept clean so that the iron is constantly revived (Chamarro et al. 2001). Deposits of Fe(OH)3 cannot be formed at acidic pH, which in turn will increase the production of free electrons and prevent the creation of iron powder deposits. At an alkaline pH, Fe2+ is also converted into Fe3+ and removed from the catalytic cycle in the form of Fe(OH)3 (Önal et al. 2006; Ravikumar et al. 2006; Sun et al. 2006).

Effect of contact time

The results of the effect of contact time (40–160 s) are shown in Fig. 3d. According to these results, dye removal efficiency is significantly increased with increasing contact time. Both superficial adsorption capacity and dye removal percentage by the catalyst increased rapidly during the initial stages, followed by a slower pace, and in accordance with the time, the upward trend was paced to achieve equilibrium over a period of about 120 s. On the other hand, some degree of the saturated adsorption and penetration of pollutants into the pores of the catalyst will require more time due to the increase in contact time (Cao et al. 1999; Fan et al. 2009; Saha 2010; Satapanajaru et al. 2011).

Optimization

Any of these variables tested can be chosen to increase dye removal efficiency, as they have a large effect on the output response. Optimum conditions of the removal of AG-25 dye using NZVI particles are shown in Table 6. Optimization of the method resulted in dye removal values of >93%, which indicates the correct application of the Taguchi method and L16 model in designing the removal process of AG-25 dye by using NZVI particles.

Table 6 Optimum conditions derived by Taguchi method for removal of Acid Green 25 dye

The optimal parameters are a catalyst amount at level 3 (0.6 g), dye concentration at level 2 (20 mg L−1), pH at level 1 (4) and time at level 3 (120 s).

Conclusion

The results of these studies show that NZVI particles prepared by the synthesis method were an efficient catalyst the removal of AG-25 dye from solution. The use of the Taguchi method involving the L16 model for optimization of process variables was studied. The removal of AG-25 dye was dependent on the catalyst amount, dye concentration, pH and time. Each variable was analyzed at four levels, with the results showing that removal percentage increased with increasing catalyst amount and time and that there was an opposite effect with increasing dye concentration and pH. The results of the Taguchi method showed that dye concentration had the most important impact on the process of dye removal, followed by pH, catalyst amount, and time in decreasing order of impact. In total, 96.82% of the AG-25 dye was removed under the optimized optimal conditions (catalyst amount 0.6 g, dye concentration 20 mg L−1, pH 4, time 120 s), which shows that the process has the high capacity to remove AG-25 dye from the aquatic environment. Thus we consider this process to be a suitable option to remove AG-25 dye from solution.