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Applied Water Science

, Volume 7, Issue 8, pp 4743–4756 | Cite as

Photocatalytic degradation and photo-Fenton oxidation of Congo red dye pollutants in water using natural chromite—response surface optimization

  • Mohamed Shaban
  • Mostafa R. AbukhadraEmail author
  • Suzan S. Ibrahim
  • Mohamed .G. Shahien
Open Access
Original Article

Abstract

Refined natural Fe-chromite was characterized by XRD, FT-IR, reflected polarized microscope, XRF and UV spectrophotometer. Photocatalytic degradation and photo-Fenton oxidation of Congo red dye by Fe-chromite was investigated using 1 mL H2O2. The degradation of dye was studied as a function of illumination time, chromite mass, initial dye concentration, and pH. Fe-chromite acts as binary oxide system from chromium oxide and ferrous oxide. Thus, it exhibits photocatalytic properties under UV illumination and photo-Fenton oxidation after addition of H2O2. The degradation in the presence of H2O2 reached the equilibrium stage after 8 h (59.4%) but in the absence of H2O2 continued to 12 h (54.6%). Photocatalytic degradation results fitted well with zero, first order and second order kinetic model but it represented by second order rather than by the other models. While the photo-Fenton oxidation show medium fitting with the second order kinetic model only. The values of kinetic rate constants for the photo-Fenton oxidation were greater than those for the photocatalytic degradation. Thus, degradation of Congo red dye using chromite as catalyst is more efficient by photo-Fenton oxidation. Based on the response surface analysis, the predicted optimal conditions for maximum removal of Congo red dye by photocatalytic degradation (100%) were 12 mg/l, 0.14 g, 3, and 11 h for dye concentration, chromite mass, pH, and illumination time, respectively. Moreover, the optimum condition for photo-Fenton oxidation of dye (100%) is 13.5 mg/l, 0.10 g, 4, and 10 h, respectively.

Keywords

Chromite Binary oxide Congo red dye Photocatalysis Photo-Fenton oxidation 

Introduction

Rapid urbanization, industrialization and economic development in recent years lead to a continuous influx of toxic materials such as heavy metals, dyes, and pesticides into a water body which frequently causes water pollution (Shaban et al. 2017a). Water pollution became one of the biggest environmental problems all over the world. It is usually hazardous to human populations and the environment (Seliem et al. 2016). Therefore, the removal of water contaminants is critical demand in the contemporary world.

Dyes are aromatic compounds used for coloring applications (Ibrahim and Sani 2010). Dyes are widely used in several modern industries such as textile, leather, paper, printing, paint, pigments, rubber and plastic. More than 100,000 types of commercially synthetic dyes are known in the world. The annual production of dye is about 7 × 105–1 × 106 tons. From this amount, 10 to 15% discharged into the surrounding environment and water bodies as untreated effluents (Yusuf et al. 2015). Dyes are toxic and non-degradable pollutants and their presence in natural water impedes the light penetration which upset the photosynthesis of aquatic plants (Sun et al. 2013). Also, dyes can degrade the water quality and cause allergy, dermatitis, cancer, skin irritation, dysfunction of kidneys, liver and reproductive system in humans (Shaban et al. 2017b; Gupta et al. 2006).

Several techniques have been investigated for dye removal from water. These methods included physical, chemical and biological methods (Shaban et al. 2017c; Robinson et al. 2001). The physical methods represented by adsorption, coagulation, and filtration. Other methods also were used in the degradation of dyes such as ultrasonic power, hydrodynamic cavitational techniques, sonochemical reactors, and sonophotocatalytic degradation process (Sivakumar and Pandit 2001, 2002; Gogate et al. 2004; Panda and Sivakumar 2017). Adsorption by low-cost materials is efficient in dye removal, but such method produces a lot of solid waste (Sivakumar et al. 2013). The chemical methods involved oxidation of dye into CO2 and inorganic ions through the production of hydroxyl radical (Herrmann 1999). The hydroxyl radical can be generated by direct photolysis of oxidants as O3 and H2O2, with UV irradiation, Fenton, and photo-Fenton process or by photocatalytic process using semiconductors (Reza et al. 2015). The combination of the previous techniques can enhance the generation of the hydroxyl radical.

Low cost and environmental heterogeneous photocatalysts were preferred in the degradation of dyes and water remediation applications (Sivakumar et al. 2004). The main advantage of dye degradation using heterogeneous photocatalysts is the ability to profiteer the sunlight in the production of hydroxyl radicals (Shaban et al. 2017d; Sivakumar et al. 2010). In the recent period, several natural minerals such as anatase, rutile, magnetite and ilmenite possess band gap energies which qualify them for photochemical reactions (Bubacz et al. 2010). Such minerals are easily and widely available, cheap, efficient, and present in very high reserves around the world. Thus, they are future promising materials for photocatalytic degradation of organic pollutants. It has been reported that addition of H2O2 to dye solution in the presence of such catalysts can enhance the degradation capacity (Lucas et al. 2007). The mixture of H2O2 and ferrous sulfate produce hydroxyl radicals. Degradation of dyes through this process is known as Fenton’s oxidation (Bandala et al. 2006). Hydroxyl radicals can also be generated from H2O2 in the presence of iron oxides, Fe3+-immobilized silica and Fe-exchanged Y zeolite (Noorjahan et al. 2005).

To the best of our knowledge, the evaluation and application of natural chromite minerals as heterogeneous photocatalyst for degradation of organic pollutants are not investigated so far. Chromite is an oxide mineral—FeO.Cr2O3 (68% Cr2O3, 32% FeO) belonging to the spinel group and crystallizes in the isometric system. It is the main source of chromium in the world and used for various purposes in metallurgical, refractory and chemical industries (Abubakre et al. 2007). Here, we have studied the photocatalytic and photo-Fenton oxidation characterization of natural chromite for low-cost degradation of Congo red dye in water. Moreover, the effect of the operating parameters such as illumination time, initial concentration, catalyst mass and solution pH is addressed to investigate the degradation mechanisms of dye by fitting the resulted data to kinetic modeling. Also, we used response surface methodology (RSM) and statistical central composite rotatable design (CCRD) to evaluate the interactive effect of the selected parameters and the ideal optimum conditions for maximum removal of Congo red dye by chromite.

Materials and methods

Materials and characterization

Refined chromite sample was used as catalyst and delivered from central metallurgical research and development, represented to podiform chromite deposits, Marsa Alam, Egypt. The chemical composition of the raw chromite sample was obtained using X-ray fluorescence spectrometry (Panalytical Axios advanced XRF technique). The structure of the chromite sample was obtained by X-ray powder diffraction (XRD, Philips APD-3720) with Cu Kα radiation worked at 20 mA and 40 kV in the 2θ range of 5–70 at a scanning speed of 5°/min. Fourier transform infrared spectrum (FT-IR-8400 S Shimadzu) was used to determine the chemical structural groups of chromite. Petrography and optical properties of the sample under reflected light were done by Nikon reflected polarized microscope attached with a computer program. The UV–visible absorption spectra of the mineral sample were measured using Shimadzu UV spectrophotometer (M160 PC) at wavelength number range from 200 to 900 nm at room temperature using dimethylsulfoxide (DMSO) as a solvent and reference.

Photocatalytic and photo-Fenton oxidation studies

Degradation of Congo red dye was carried out to evaluate the photocatalytic and photo-Fenton oxidation characterization of natural chromite mineral. Congo red dye was purchased from Sigma-Aldrich Company, Egypt. Sodium hydroxide and hydrochloric acid were used for modifying the pH of the solutions. Hydrogen peroxide 30% w/v was used as an oxidant to enhance the degradation of Congo red dye. The degradation experiments were conducted under artificial visible light irradiations lamp (blended metal halide lamp 400 W). The experiments were performed as a function of illumination time, chromite dose, the initial concentration of dye and pH, either in the presence or absence of H2O2. All the photocatalytic degradation tests were performed after adsorption–desorption equilibrium of Congo red dye using chromite.

Effect of illumination time

The effect of illumination time on the degradation of Congo red dye was carried out by stirring 0.04 gm of chromite with 100 mL of the dye solutions (25 mg/L) for different time intervals (1, 2, 4, 6, 8, 10 and 12 h). The same tests were performed again after adding 1 mL of H2O2 to the solution. Then the dye solutions were separated by centrifuge to determine the dye concentration by UV–Vis spectrophotometer.

Effect of photocatalyst mass

Effect of chromite amount on the degradation of dye was tested by stirring different amounts of it (0.02, 0.04, 0.08, 0.1 and 0.12 g) with 100 mL of Congo red dye solution (25 mg/L) as separated tests for 2 h. The experiments were performed in the absence of H2O2 and after adding 1 mL of it to the solution. Then the dye solution was separated by centrifuge to determine the rest dye concentrations.

Effect of initial dye concentration

The effect of the initial concentration was tested by stirring 0.04 g of chromite with 100 mL of the dye solutions of different initial concentrations (10, 15, 20, 25, 30, 35 mg/L) for 2 h as separated experiments. This was done in the absence of H2O2 and with 1 mL H2O2. After equilibration, solids and solutions were separated; and the dye solution for analysis.

Effect of pH

To study the influence of pH on degradation process, 0.04 gm from chromite was stirred with 100 mL of Congo red dye solutions (25 mg/l) of different pH values (pH 2, pH 3, pH 4, pH 5, pH 6, pH 8, pH 9, and pH 10) for 2 h either in the absence of H2O2 or after adding 1 mL from it. The solids and solutions were separated and collected for analysis using UV–Vis spectrophotometer.

The degradation percentage of Congo red dye was calculated according to Eq. 1.
$${\text{Degradation (\% )}} { = }\frac{{ 1 0 0 (C_{0} {-} C_{\text{e}} )}}{{C_{0} }} ,$$
(1)
where C 0 and C e are the dye concentrations in the initial solution and the solution after treating with the photocatalyst.

Statistical optimization

Response surface methodology (RSM) associated with central composite rotatable statistical design (CCRD) of quadratic polynomial model was designed for the four selected parameters [illumination time (1 to 12 h), initial concentration (10 to 35 mgL), chromite mass (0.02 to 0.14 g) and pH(3 to 5)] to detect the interaction between such parameters and the predicted optimum conditions for the maximum degradation of Congo red dye. The experiments were performed based on the tests suggested by the statistical design and limited by best results obtained in the previous tests.

The data obtained were fitted to a second order polynomial equation (Eq. 2),
$$Y = \beta_{0} + \sum\nolimits_{i = 1}^{4} {\beta_{i} X_{i} + } \sum\nolimits_{i = 1}^{4} {\beta_{ii} X_{i} } + \sum\nolimits_{i = 1}^{3} {\sum\nolimits_{j = i + 1}^{4} {\beta_{ij} X_{i} X_{j} } } ,$$
(2)
where Y is the removal of dye (%); β 0, β i , β ii , ij are the constant coefficients X i are the uncoded independent variables. Subsequent regression analyses, analyses of variance (ANOVA) and response surfaces were performed using the Design Expert Software (version 6.0.5). Optimal reaction parameters for maximum removal were generated using the software’s numerical optimization function.

Results and discussion

Characterization

XRD pattern of the chromite concentrate was represented in Fig. 1a. The sample composed mainly of chromite as the dominant mineral phase. It was detected with their characteristic peaks at 2θ = 18.89o, 30.87o, 36o, 43.6o, and 63o. The main characteristic peak at 2θ 36o is corresponding to the crystal plane with Miller indices of 311, which is the characteristic peak of face-centered cubic spinel. The detected sharp peaks of chromite revealed its excellent crystallinity, which is promising for photocatalytic reaction.
Fig. 1

a XRD pattern of the chromite sample, b FT-IR spectrum of chromite, c morphological and optical properties of chromite under reflected light microscope (between crossed Nicole), and d UV–Vis absorbance spectrum of chromite

The average crystallite size (D) of chromite was calculated according to the Scherrer equation (D = (0.9λ)/W Cos (θ)). Where W is the full width at half maximum in radians, θ is the Bragg’s angle, and λ is the X-ray wavelength (CuKα = 0.15405 nm). The calculated D is about 22.7 nm. Also, the average microstrain is estimated to be 0.4611%. The positive sign of microstrain indicates that the stress in the natural chromite is tensile in nature. To gain more information on the number of defects in the natural chromite, the dislocation density (δ) is estimated using Williamson and Smallman’s relation, \(\delta = \frac{N}{{D^{2} }}\). Where N is a factor equals unity for the minimum dislocation density. The values of minimum δ are 1.94 × 10−3 dislocation/nm2, which imply a good lattice structure of the chromite sample.

Figure 1b illustrates the FT-IR spectrum of the natural chromite sample. The present absorption bands at wavenumber from 500 to 1000 cm−1 were attributed to the bond between groups II and III transition metal cations in spinel oxides and oxygen anion (Moroz et al. 2001). The FT-IR bands at (500–600 cm−1) were assigned for the stretching vibration of Cr–O for the chromite mineral (Durrani et al. 2012). The other detected bands were attributed to the present minerals contaminations, especially of serpentine or any other silicate minerals (Ucbas et al. 2014).

Under reflected light microscope, the chromite minerals appear as cataclastic grains of medium gray color (Fig. 1c). The chromite grains are of different shapes, sizes and occur as separated grains or in aggregated form. Light reflectivity from chromite surface was measured using reflected polarized light microscope (Fig. 1c). It commonly shows low reflection value that range from 11.5 to 13.3 at wavelength 546 nm and from 11.5 to 13 at wavelength 589 nm (Ineson 1989). The mean value of light reflection by the studied chromite sample was determined, and it is about 12.84; this value is close to the value obtained by Ineson (1989).

The optical properties of chromite are a critical parameter for the application of it in optoelectronic devices. The ultraviolet–visible absorbance spectrum of chromite is represented in Fig. 1d. The diagram shows two main absorption peaks, the first around 350 and 370 nm in the UV region and the second peak around 550 and 630 nm in the visible region. The detected spectral band in the UV region is characteristic to the optical absorption band of the chromite spinels (Durrani et al. 2012). This band is attributed to the assignments of Cr3+ ions in the octahedral sites. The other band in the visible region may be related to Fe ions in the spinel structure.

Major oxides of the refined chromite sample from XRF analysis listed in Table 1. Data from the table revealed that the sample is of the high-quality type with Cr2O3 content 56.7%. The present iron oxide is represented by 24.5% ferrous oxide and about 4% ferric iron oxide, which indicates that the chromite sample is Fe-chromite. The rest of oxides (CaO, MgO, Al2O3, and SiO2) are present in minor amounts and the total percentage of them is about 15%.
Table 1

The level and range of independent variables chosen for the removal of Congo red dye from aqueous solution

Factor

Name

Low actual

High actual

Low coded

High coded

A

Illumination time

1 h

12 h

− 1

1

B

Initial concentrations

10 mg/L

35 mg/L

− 1

1

C

Chromite mass

0.02 g

0.14 g

− 1

1

D

pH

3

5

− 1

1

Photocatalytic and photo-Fenton oxidation behavior of chromite

Fe-chromite is a molecular compound with chemical formula FeCr2O4 with spinel structure (Abubakre et al. 2007). In general, spinel minerals are binary oxide materials. In the case of Fe-chromite, it contains ferrous oxide (FeO) and chromium oxide (Cr2O3). Fe+2 ions occupy the tetrahedron sites, and Cr+3 ions occupy the octahedral sites in the spinel structure (Fig. 2). Therefore, chromite contains two functional groups of Cr2O3 and FeO. Such chemical functional groups give chromite mineral photocatalytic and photo-Fenton oxidation properties (Singh et al. 2015).
Fig. 2

a Crystal structure of Fe-chromite mineral, b mechanisms of photocatalytic degradation and photo-Fenton oxidation of dye by chromite

Chromium (III) oxide (Cr2O3) is a p-type semiconductor with wide band gap energy (Santulli et al. 2011). Under the irradiation of UV light, the outer surface electrons from chromium octahedral sites can be excited from the valence band to the conduction band. This will result in the formation of the electron–hole pair in the valence band (Reza et al. 2015). The holes can react with an electron donor (water molecules or hydroxide ions) and produce oxidizing free radical (hydroxyl radical), which will oxidize dyes on the surface (Ng et al. 2012; Akbal 2005). Also, the holes can oxidize the dye pollutants by direct electron transfer (Reza et al. 2015). Such mechanism can be summarized in Fig. 2 and in Eqs. 36 (Akbal 2005):
$${\text{Cr}}_{2} {\text{O}}_{3} + {\text{hv}} \to {\text{e}}_{\text{CB }}^{ - } + {\text{h}}_{\text{VB}}^{ + } ,$$
(3)
$${\text{h}}_{\text{VB}}^{ + } + {\text{H}}_{2} {\text{O }} \to {\text{H}}^{ + } + {\text{OH}}^{ \cdot } ,$$
(4)
$${\text{OH}}^{ \cdot } + {\text{Dyes}} \to {\text{Degredation,}}$$
(5)
$${\text{h}}_{\text{VB}}^{ + } + {\text{Dyes }} \to {\text{Oxidation of dyes}} .$$
(6)
Besides its role as photocatalytic oxide, FeO acts as the active radical for Fentons and photo-Fenton oxidation in the natural chromite. In the Fentons oxidation reactions, the ferrous ions react with hydrogen peroxide and from free hydroxyl radicals (Torrades et al. 2008). The presence of light enhances the oxidation of dyes as it accelerates the reduction of ferric ions into ferrous ions and promotes the direct formation of hydroxyl radicals (Feng et al. 2003). Fe+2 in this process is regenerated again through the so-called Fenton-like reaction between Fe+3 and H2O2. The Fenton oxidation reaction can be written as in Eqs. 711 (Abou-Gamra 2014):
$${\text{Fe}}^{2 + } + {\text{H}}_{2} {\text{O}}_{2} \to {\text{OH}}^{ \cdot } + {\text{Fe}}^{3 + } + {\text{OH}}^{ - } ,$$
(7)
$${\text{Fe}}^{{ 3 { + }}} + {\text{H}}_{ 2} {\text{O}}_{ 2 } \leftrightarrow {\text{Fe}} - {\text{OOH}}^{{ 2 { + }}} + {\text{H}}^{ + } ,$$
(8)
$${\text{Fe}} - {\text{OOH}}^{{ 2 { + }}} \to {\text{HO}}_{ 2}^{ \cdot } + {\text{Fe}}^{{ 2 { + }}} ,$$
(9)
$${\text{Fe}}^{{ 3 { + }}} + {\text{HO}}_{ 2}^{ \cdot } \leftrightarrow {\text{Fe}}^{{ 2 { + }}} + {\text{O}}_{ 2} + {\text{H}}^{ + } ,$$
(10)
$${\text{Fe}}^{3 + } + {\text{UV}} + {\text{H}}_{2} {\text{O}} \to {\text{OH}}^{ \cdot } + {\text{Fe}}^{2 + } + {\text{H}}^{ + } .$$
(11)
Figure 3 shows the removal of Congo red dye using UV only without chromite, using H2O2 only without UV and chromite, using H2O2 and UV without chromite, using chromite without light and H2O2, using chromite in the presence of light and using chromite in the presence of light and H2O2. At the upper limit of reaction time (12 h), the removal percentage of Congo red dye reaches 8.43% using the light source only, 17.3% using H2O2 only, 24.32% using the light source and H2O2 without the catalyst, 16.78% using chromite without light source and H2O2, 54.6% using chromite in the presence of light and 60% using chromite in the presence of light and 1 mL H2O2. The adsorption capacity of chromite and the photolysis effect of the light source reflect the photocatalytic and photo-Fenton oxidation properties of chromite.
Fig. 3

Effect of illumination time on the removal of Congo red dye using chromite + UV, chromite + UV + H2O2, chromite without UV or H2O2, UV only without chromite or H2O2, H2O2 only without chromite or UV and UV + H2O2 without chromite

Degradation of Congo red dye

Effect of illumination time

The relation between the illumination time and the degradation percentage of Congo red dye appears in Fig. 3. From the figure, the degradation of Congo red using chromite increased from 23.6 to 54.6% with increasing the illumination time from 1 h to 12 h. The addition of hydrogen peroxide caused rising in the degradation efficiency, where the degradation value increased from 24.17 to 60% in the same time range. The effect of hydrogen peroxide related to their reaction with ferrous oxide within chromite lattice. This response resulted in the formation of active hydroxyl radicals as in Eq. (7), as well as other hydroxyl radicals produced from the photolysis of hydrogen peroxide under the effect of light as in Eq. 12 (Muruganandham and Swaminathan 2004):
$${\text{H}}_{ 2} {\text{O}}_{ 2} + {\text{Uv}} \to {\text{OH}}^{ \cdot } + {\text{OH}}^{ \cdot } .$$
(12)

It is worth to be mentioned that while the degradation of Congo red dye by chromite increased gradually with contact time, there is a deviation from the behavior in the presence of hydrogen peroxide. The degradation curve with the contact time shows nearly constant values with increasing the illumination time from 8 to 12 h (59.4 to 60%). This can be attributed to the consumption of H2O2 and Fe+2, which reduce the rate of dye degradation (Alalm et al. 2015).

Kinetic studies

Three kinetic models were used (zero, first order, and second order kinetic models) to investigate the degradation of Congo red dye using chromite in the presence and absence of H2O2. The three kinetic models were expressed as in Eqs. 1315 for zero, first order, and second order kinetic models, respectively (Sun et al. 2009):
$$\frac{{{\text{d}}c}}{{{\text{d}}t}} = - k_{0} ,$$
(13)
$$\frac{{{\text{d}}c}}{{{\text{d}}t}} = - k_{1} \;c,$$
(14)
$$\frac{{{\text{d}}c}}{{{\text{d}}t}} = - k_{2} c^{2} ,$$
(15)
where C is the concentration of Congo red dye; k 0, k 1, and k 2 are the apparent kinetic rate constants of zero, first and second order reaction kinetics, respectively; t is the reaction time.
Equations 1618 resulted from the integrations of Eqs. 1315 (Sun et al. 2009):
$$C_{\text{t}} = C_{0} - k_{0} t,$$
(16)
$$C_{\text{t}} = C_{0} e^{{ - k_{1} t}} ,$$
(17)
$$\frac{1}{{C_{\text{t}} }} = \frac{1}{{C_{0} }} + k_{2} t ,$$
(18)
where Ct is the concentration of Congo red dye after illumination time (t).
The zero order kinetic model was represented by regression plotting of C t versus time (Fig. 4a) and the first order kinetic model was investigated from the linear relation between In (C0/C) and time (Fig. 4b). While the second order kinetic model was studied through the linear relation between 1/C t and time (Fig. 4c). The kinetic parameters for the selected models were listed in Table 2. By comparing the correlation coefficient (R 2) value from the three models, it can be seen that R 2 values based on the second order kinetic model were 0.96 and 0.82 for degradation by chromite only and after addition of H2O2, respectively. Therefore, second order kinetic model was much better than zero order and first order kinetic models to represent the photocatalytic degradation and photo-Fenton oxidation of Congo red dye in solution (Table 2).
Fig. 4

a Linear relation of zero order kinetic model, b linear relation of the first order kinetic model, c linear relationship of the second order kinetic model

Table 2

Major oxides of the refined chromite sample

Major oxides

Percentage (%)

Cr2O3

56.7

Fe2O3

4

FeO

24.5

CaO

2.3

MgO

6.3

Al2O3

3.5

SiO2

2.85

Loss on ignition

4

Also, the R 2 values indicated the better fit of the photocatalytic degradation process with the kinetic models as compared to photo-Fenton oxidation after the addition of H2O2. Photo-Fenton oxidation of Congo red dye using chromite show only medium fitting with the second order kinetic model (R 2 = 0.82). Well fitting of the photocatalytic degradation results with the three kinetic models revealed that there are parallel mechanisms operated during the degradation of Congo red dye (Wang et al. 2008).

The values of the kinetic rate constants for the photo-Fenton oxidation process were greater than the values for the photocatalytic degradation process. This confirmed that the degradation efficiency of Congo red dye by chromite is better after the addition of H2O2, i.e., by photo-Fenton oxidation process (Alalm et al. 2015).

Effect of chromite mass

The effect of chromite mass on the degradation process either based on the photocatalytic degradation or photo-Fenton oxidation after the addition of H2O2 was represented in Fig. 5a. From the figure, the removal efficiency of Congo red dye increased by 20, 27, 36.8, 41.2 and 44% with increasing the chromite mass by 0.02, 0.04, 0.08, 0.1 and 0.12 gm, respectively. With the addition of 1 mL H2O2 to the system, the removal efficiency increased by 27.6, 37.5, 46.4, 53.2 and 60.4% with the same applied chromite mass. This might be attributed to the increase in the produced hydroxyl radicals with increasing the chromium and ferrous oxide according to Eqs. 5 and 9 (Huang et al. 2008).
Fig. 5

a The effect of chromite mass on the degradation of Congo red dye, b the relation between ro and the chromite mass

Galindo et al. (2001) set an empirical relation between the degradation rate and the mass of the used catalyst (r o ∝ [MC] n [dye]), where r o is the reciprocal initial rate, MC is the mass of the used catalyst and n is an exponent less than 1 for the studied dye, in relation to low mass of the used catalyst. The relation was represented by linear regression plot of ln (chromite mass) versus Ln (lo) with high correlation coefficient (R 2 = 1) in Fig. 5b. The results revealed that the degradation rate depends on the chromite mass and follows a similar relationship (r o ∝ [TiO2]0.93) reported by Galindo et al. (2001).

Effect of initial concentration

The relationship between Cong red dye initial concentration and the degradation efficiency by chromite, either in the absence or presence of H2O2 is shown in Fig. 6. The degradation of Congo red dye was decreased by 62, 49.85, 35.2, 27.2, 26.7 and 25.5% with increasing the initial dye concentration by 10, 15, 20, 25, 30 and 35 mg/L using chromite without H2O2. Within the same initial dye concentrations, the degradation after adding of H2O2 was reduced by 74, 65, 48.9, 37.7, 30.5, and 27.3%. This behavior may be related to the fact that increasing the initial dye concentration causes increasing in the amount of adsorbed dye on the surface of chromite. Therefore, the production of hydroxyl radical will be decreased as there are only a fewer available active sites for adsorption of hydroxyl ions and the generation of hydroxyl radicals (Behnajady et al. 2006). Also increasing dye concentration will act as blocking surface between the photons and the catalyst surface. Hence, the absorption of a photon by chromite will decrease, and it turn the degradation efficiency will decrease.
Fig. 6

Effect of initial Congo red dye concentration on the degradation efficiency

Effect of pH

The effect of pH value on the degradation of Congo red dye by chromite before and after the addition of H2O2 in the system represented in Fig. 7. The degradation decreased gradually from 33% to 12.9% with increasing the pH value from 3 to 10 in the case of chromite without H2O2. Decreasing the removal efficiency with increasing the pH value might me related to the protonation of the chromite surface at acidic conditions (pH < 4). Thus, the active site became positively charged which enhances the adsorption of acidic dyes such as Congo red dye (Abudaia et al. 2013). This, in turn, supports the degradation and oxidation of dye anions. However, at higher pH values, the dye anions repel far from the negatively charged chromite surface, so degradation ratio decreases.
Fig. 7

Effect of the initial solution pH on the removal of dye

While in the presence of H2O2 the degradation efficiency increased from 35 to 37.6% with increasing the pH value from 3 to 4. Then the degradation decreases with increasing the pH from 4 to become 14.6% at pH 10, i.e., pH 4 is the optimum value. pH value of the solution plays a significant role in the Fenton oxidation process as it influences the generation of hydroxyl radicals and the concentration of ferrous ions (Ercan et al. 2015). Below pH 4, the reduction in the degradation rate was attributed to the scanning of the hydroxyl radicals with hydrogen ions (Bahmani et al. 2013). Also under such high acidic conditions, the present hydrogen peroxide can capture a proton and form H3O2 +. Therefore, the used hydrogen peroxide will become electrophilic causing reduction in the reactivity between hydrogen peroxide and ferrous ions (Herney-Ramirez et al. 2008).

At alkaline conditions (pH > 4), the degradation efficiency was decreased as a result of reducing the oxidation potential of hydroxyl radicals (Sun et al. 2007), precipitation of Fe(OH)3 which reduce the concentration of dissolved Fe3+, and finally the less stability of hydrogen peroxide at alkaline conditions (Rodrigues et al. 2009). All the previous conditions will result in decreasing the produced hydroxyl radicals, and hence the degradation efficiency of Congo red dyes by chromite through a photo-Fenton oxidation process.

Statistical analysis and optimization

Fitness of the model

The experimental runs which were designed by the central composite rotatable statistical design (CCRD) and the required responses (degradation of Congo red dye %) are shown in Table 3. The second order quadratic polynomial statistical model was selected to represent the relations between the operating parameters (illumination time, chromite mass, the initial concentration of Congo red dye, and pH) and the removal efficiency of dye. Model F-values for the removal of dyes by photocatalytic degradation and photo-Fenton oxidation were obtained from the analysis of variance (ANOVA). The model F-values are 55.5 and 62.6 for photocatalytic degradation and photo-Fenton oxidation, respectively. These values indicate the high significances of used models with only a 0.01% noise for the designs.
Table 3

Parameters of studied kinetic models

Kinetic model

Parameters

Chromite + UV

Chromite + H2O2 + UV

Zero order kinetic model

k (mg/min)

0.74

0.77

R2

0.92

0.72

First order kinetic model

K1 (min−1)

0.05

0.054

R2

0.94

0.77

Second order kinetic model

k2 (L/mol min)

0.0035

0.004

R2

0.96

0.82

The mathematical regression equations of the quadratic polynomial model, which represent the relations between the removal of Congo red dye (%) and the operating parameters, were obtained from Design Expert Software (Version 6.0.5) and expressed for coded units as follows:

Y1 = + 60.97 + 17.49 X A − 19.67 X B + 14.12 X C − 3.46 X D − 13.31X A2 + 7.95 X B2 − 7.73 X C2 − 0.23 X D2 + 1.38 X A X B + 1.18 X A X C + 0.75 X A X D − 2.62 X B X C − 0.15 X B X D − 0.96 X C X D

Y2 = + 73.49 + 17.78 X A − 18.44 X B + 12.72 X C − 2.84 X D − 14.61 X A2 + 6.53X B2 − 4.96 X C2 − 3.06 X D2 + 2.42 X A X B − 0.33 X A X C + 0.42 X A X D − 0.15 X B XC − 0.34 X B X D + 0.53X CX D.

Where Y1 and Y2 are the removal of Congo red dye by photocatalytic degradation and photo-Fenton, respectively, A is the illumination, B is the initial dye concentration, C is the chromite mass and D is the pH value.

The regression plot between the actual removal of dye from the experimental tests and the predicted results obtained using the model equations show good agreement with a high determination coefficient (R 2 > 0.9) (Fig. 8). This gave an indication of the significance of the quadratic polynomial model and its suitability to represent the actual relations between the removal efficiency and the selected variables.
Fig. 8

Correlation between predicted removal of dye and experimental values

Interaction effect and optimization

The interaction effect between the operating parameter was expressed in 3D response surface diagrams (Fig. 9). Response surface plots regarding two selected factors at any time maintaining all other factors at fixed levels are suitable in understanding the effect of the main parameters and the interaction between them and can be represented by 3D diagrams. The elliptical shape of the curve designates a good interaction of the two variables, and circular shape indicates no interaction between the variables (Abukhadra et al. 2015).
Fig. 9

3D response surface diagrams for the interaction between the operating parameters during photodegradation of Congo red dye by chromite (af), and Fenton’s oxidation of Congo red dye by chromite (gl)

The diagram revealed that the effect of each parameter on the degradation behavior is fixed at any given value for the other parameters. However, the degradation efficiency is controlled by the interaction effect of the other parameters.

The interaction effect of the operating parameters on the photocatalytic degradation of Congo red dye using chromite alone without H2O2 is shown in Fig. 9. The degradation of dye is increased with increasing the illumination time from 1 to 12 h at any given value for the other factors (Fig. 9a–c). However, the degradation capacity was controlled mainly by the interaction effect of the initial concentration. At fixed conditions of pH 4, 0.08 g chromite mass and 10 mg/L dye concentration, the removal efficiency increased from 59% to about 91.5% with increasing the time from 1 to 12 h. At the same operating conditions with raising the dye concentration to 35 mg/L, the removal efficiency increased from 17 to 54.85% in the same time range.

The interaction effect of chromite mass with the other operating parameters is shown in Fig. 9b, d and f. At fixed illumination time 6 h and fixed conditions of 20 mgL initial Congo red concentration and pH 4, the degradation efficiency increased from 35 to 75% by increasing the chromite mass from 0.02 to 0.14 g. Also using the optimum chromite mass (0.14 gm), the degradation efficiency increased from 75% after 6 h of illumination to about 80% after 12 h of illumination. This revealed that the optimum illumination time, initial Congo red concentration and chromite mass are 12 h, 10 mg/L and 0.14 g, respectively.

The interaction effect of pH with the other selected factors also controls the degradation efficiency of dye at any given value for the other parameters. The high acidic conditions are the optimum media for maximum degradation of dye at any given value of the other factors. At optimum conditions of time (12 h), chromite mass (0.14 g) and initial dye concentration (10 mg/L), the degradation capacity increased from 96.4 to 98.9% with decreasing the solution pH value from 5 to 3, respectively (Fig. 9c, e, and f).

For the degradation of Congo red dye by photo-Fenton oxidation using chromite with 1 mL H2O2, the removal efficiency shows noticeable increasing with the illumination time from 1 to 8 h. Then the degradation rate slightly increased from 8 to 12 h. However, the degradation capacity with the time was controlled by the interaction effect of the other factors (Fig. 9g, h, and i). The degradation efficiency was increased from 68.5 to 99.2% by increasing the contact time from 1 h to 12 h, respectively. This occurred at operating conditions of 10 mg/L initial dye concentration, pH 4 and 0.08 g chromite mass. With using the upper limit for the dye concentration (35 mg/L), the degradation efficacy increased from 26.7 to 67% for the same time range.

The interaction effect of chromite mass with the effect of the other parameters was represented in Fig. 9h, j and l. The interaction effect of it with the illumination time can be explained by fixed conditions of initial dye concentration (20 mg/L), illumination time (6 h) and pH (4). At these conditions, the degradation capacity increased from 53 to 87.2% with increasing the chromite mass from 0.02 to 0.14 g, respectively. By fixing the applied mass at 0.14 gm, the degradation increased from 87.2% after 6 h to about 94% after 12 h. At 10 mg/L as initial dye concentration (lower limit), 12 h as contact time and pH 4, the removal of dye increased from 81.7% to about 100% by increasing the chromite mass from 0.02 g to 0.14 g. This revealed that the optimum illumination time, initial Congo red concentration and chromite mass are 12 h, 10 mg/L and 0.14 g, respectively.

In the photo-Fenton oxidation, pH 4 is the optimum pH for the maximum degradation of Congo red dye. The interaction effect of the solution pH value with the other operating factors was represented in Fig. 9i, k and l. At fixed operating conditions of illumination time (6 h), chromite mass (0.08 g) and initial dye concentration (20 mg/L), the degradation capacity was investigated to be 75.3% at pH3, 77.2% and 69% at pH 5. While at the optimum conditions of 12 h, 0.14 g, 10 mg/L and pH 4, the removal efficiency increased to about 100%.

Taking advantage of the quadratic programming and the statistical analysis of the design, the suggested solutions for maximum degradation of Congo red dye were obtained directly from Design Expert’s optimization function. The predicted solutions for the optimum conditions with their predicted values were listed in Table 4. The statistical prediction for the suggested optimum solution revealed that 12 mg/L from Congo red dye can be completely removed (100%) using 0.14 g chromite as catalyst for 11 h at pH3. Also, 10 mg/L from the dye can be completely removed using 0.11 gm chromite as catalyst for 8 h at pH3. The predicted optimum conditions for the removal of Congo red dye using photo-Fenton oxidation appears in Table 5. The predicted conditions revealed that about 13.5 mg/l Congo red dye can be completely removed (100%) using 0.10 g chromite in the presence of 1 mL H2O2 for 10 h at pH3. Also, 10 mg/L from the dye can be completely removed using 0.08 gm chromite in the presence of H2O2 for 8 h at pH 4. This shows that the photo-Fenton oxidation of Congo red dye using chromite can achieve higher efficiency at lower illumination time and with smaller amounts from chromite than the photodegradation process using chromite as photocatalyst.
Table 4

Results of the experimental runs designed according to the CCRD

Run

Illumination time(A)

Initial concentration (mg/l) (B)

Chromite mass (C)

PH (D)

Chromite + UV

Chromite + UV + H2O2

1

12.00

35.00

0.02

5

32

42

2

6.00

20.00

0.08

4

64.8

77.2

3

12.00

35.00

0.14

5

55.9

70.8

4

1.00

20.00

0.08

4

34

44.7

5

6.00

20.00

0.08

5

57.5

69.1

6

6.00

20.00

0.08

4

64.8

77.2

7

12.00

10.00

0.14

5

96.4

100

8

12.00

20.00

0.08

4

69

80

9

1.00

10.00

0.14

5

64.3

73

10

6.00

20.00

0.02

4

35.6

53.4

11

1.00

35.00

0.02

3

4

12.6

12

12.00

10.00

0.02

5

66.3

78.4

13

12.00

10.00

0.14

3

98.9

100

14

12.00

35.00

0.14

3

68.2

77.6

15

6.00

10.00

0.08

4

90.2

100

16

1.00

10.00

0.14

3

71.9

77.8

17

1.00

10.00

0.02

3

38.5

49

18

1.00

10.00

0.02

5

28.6

40.6

19

12.00

35.00

0.02

3

33

47.9

20

1.00

35.00

0.14

3

22.4

32.3

21

6.00

20.00

0.08

3

68.3

75.3

22

6.00

20.00

0.14

4

75.2

87.2

23

12.00

10.00

0.02

3

70.5

84.8

24

6.00

35.00

0.08

4

43.4

55.6

25

1.00

35.00

0.02

5

1

6.7

26

1.00

35.00

0.14

5

11.3

25.7

Table 5

The suggested solutions for the maximum removal of Congo red dye using Chromite and Chromite + H2O2

Number

Contact time (min)

Initial concentration (mg/l)

Dose (g)

pH

Removal efficiency (%)

Desirability

Chromite + UV

1

10

10

0.13

5

99

1.000

2

8

10

0.11

3

100

1.000

3

10

10

0.12

4

99

1.000

4

11

12

0.14

3

100

1.000

5

8

10

0.12

4

99.6

1.000

Chromite + UV + H2O2

 

1

10

12.5

0.11

5

100

1.000

2

10

13.5

0.10

3

100

1.000

3

10

10

0.08

3

100

1.000

4

8

10

0.08

4

100

1.000

5

10.5

13

0.13

4

100

1.000

Conclusion

In this study, the removal of Congo red dyes from industrial water using Fe-chromite ore is investigated. The effect of the main working parameters that are influencing the dye removal such as contact time, ore mass, initial dye concentration, and medium pH are studied. The statistical central composite rotatable design (CCRD) and the response surface method (RSM) are used to evaluate the effect of parameters interaction and to deduce the optimum conditions for maximum dye color degradation.

Results showed that the color degradation via photocatalytic mechanism was fitting with the zero, first order and second order kinetic models. However, the photocatalytic mechanism was represented better with the second order. Meanwhile, the photo-Fenton oxidation showed moderate fitting with the second order kinetic model only. However, the values of kinetic rate constants for the photo-Fenton oxidation were greater than those for the photocatalytic degradation. Therefore, the degradation of Congo red dye using chromite ore is suggested to be conducted via the photo-Fenton oxidation mechanism. Based on the response surface analysis, the predicted conditions for maximum removal of Congo red dye using chromite ore were 10 h illumination contact time, 0.10 g ore mass, 13.5 mg/l initial dye concentration, and medium pH = 4. The statistical prediction for the suggested optimum solution revealed the complete reduction of Congo red dye at initial concentration of 12 mg/l using 0.14 g chromite as catalyst for 11 h at pH 3. On the other hands, 10 mg/l from the dye can be completely removed using 0.11 g chromite as catalyst after 8 h at pH 3.

Notes

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Copyright information

© The Author(s) 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Mohamed Shaban
    • 1
  • Mostafa R. Abukhadra
    • 1
    • 2
    Email author
  • Suzan S. Ibrahim
    • 3
  • Mohamed .G. Shahien
    • 2
  1. 1.Nanophotonics and Applications Lab, Physics Department, Faculty of ScienceBeni-Suef UniversityBeni SuefEgypt
  2. 2.Geology Department, Faculty of ScienceBeni-Suef UniversityBeni SuefEgypt
  3. 3.Central Metallurgical Research and Development Institute (CMRDI)CairoEgypt

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