Archives of

Pollution of water in the environment by toxic organic pollutants such as pesticides has become a global distress for water quality and as a basis of serious hazards for humans and animals. The Cresols denote groups of chemical phenolic compounds used widely in resin industrialized, herbicide such as dinitro-o-cresol, pharmaceuticals and surfactants. Wastewater from these industries along with petrochemicals hold a high concentration of Cresol derivatives. These pollutants retain an important hazard to the environment, as they are poisonous and recalcitrant in nature (1).
p-Nitro Cresol is a phenolic compound, wildly employed in the petrochemical, chemical and pharmaceutical businesses. It has been also listed as one of the important pollutants by the US-EPA (2).
There are three classical methods for the treatment of wastewater such as physical, chemical and biological methods. The classical systems have great operational costs, secondary pollution and a longer reaction time, so, using new methods without these problems are desirable. Advanced oxidation processes (AOPs) have been explored as successful approaches to treat environmental pollutants in water (3–4). Among these processes, Fenton treatment has been broadly used to degrade environmental pollutants (5), particularly in wastewater.
Different AOPs have been applied for the degradation of aromatic pollutants in aqueous phase. For instance, heterogeneous photo catalysis, Sonocatalysis, Ozonation (6–9), UV/H₂O₂ (10), Fenton and photo-Fenton processes (11–12) have been employed. The Fenton method is a good choice because it needs slight energy and low cost of chemicals (13). The Fenton technique generates hydroxyl radicals (OH•) proficiently based on the reaction between Fe (II) and H₂O₂ (Eqs.1, 2).
 
→  +  + (1)
→  +  +         (2)
 
Also, Fe (III) can interrelate with the unused hydrogen peroxide, giving back Fe (II) (Eq. 2) (14).
Aims of the study:
The main purpose of this project is to use a Box-Behnken design of experiment for the optimization of operational factors such as pH, initial concentration of hydrogen peroxide and Ferrous ions on degradation of p-Nitro Cresol in Fenton process.
 

Materials & Methods

Materials
p-Nitro Cresol was acquired from the Merck Company of Germany and used without further purification. Distilled water was used in all of the experiments. Ferrous Sulfate hepta hydrate (FeSO₄.7H₂O) as the source of Fe (II), hydrogen peroxide solution (30% w/w), H₂SO₄ and NaOH are all supplied from Merck.
Photo reactor
The experiments were made in a glass cylindrical batch photo reactor with 1 liter of capacity. The light source was a mercury lamp, Philips 15 W (UV-C), which was immersed perpendicularly in the center of the reactor. The system was prepared with a sampling system. The reactor was equipped with a jacket of water and external circulating flow through a thermostat for regulating temperature fixed at 25 °C. The solution in the reactor was mixed well by stirrer. A pH meter, PT-10P Sartorius Instrument from Germany Company was employed to regulate the initial pH of the solution. Water bath, BW 20G model from Korean company was used for fixing temperature at 25 °C in all tests. The degradation of p-Nitro Cresol was calculated with high performance liquid chromatography (HPLC) from Knauer, Germany. A reverse phase column with 150 mm in length and 4.6 mm in diameter was filled with 3 μm Separon C₁₈. The Isocratic method was used with a solvent mixture of 30% deionized water and 70% of methanol with a flow rate of 1 ml. min–1.
General procedure
In each test, about 1000 ml of synthesized wastewater holding p-Nitro Cresol was used. Altered concentrations of Fe²⁺, H₂O₂ and pH were used for optimization in Fenton process. An aqueous solution containing 10% of sodium sulphite was used to quench the reactions. The samples were taken and calculated by UV/Vis spectrophotometer and confirmed by high performance liquid chromatography (HPLC). The COD was measured based on standard methods (15). The removal percent for the p-Nitro Cresol and COD were achieved as in Eqs. (3) and (4):
p−Nitro Cresol   (3)

(4)

Where (C)₀ and (COD)₀ are the concentration of p-Nitro Cresol and amount of COD at the start of the treatment and (C) and (COD) are the concentration of p-Nitro Cresol and amount of COD at time t, in that order.
 

Results

The experimental design method was used and the percentage of the degradation of the p-Nitro Cresol was selected as responses to consider the optimum conditions. The BBD was employed with three independent variables involving the concentration of Ferrous ion (CF), hydrogen peroxide (CHP) and pH. The input variables and their levels in the experiment were presented in Table 1. In all runs, the time of reaction was 45 min.
Table1)The range and levels of the variables.

Factors	Symbol	Range and levels
		-1	0	+1
Ferrous, mM		0.3	0.6	0.90
Hydrogen peroxide, mM		8	16	24
pH	pH	2	3	4

 
Data analysis
The Box-Behnken experimental designs requests less runs rather than all other RSM designs (16). The following model was fitted to the response variable (Y) in the form of a polynomial equation (Eq. 5):
 

(5)

Where b₀ is a constant, ε is the residual term, b_ij is the linear interaction effect between the input variables, x_i and x_j (i=1,2 and 3; j=1,2 and 3), b_iis the slope of the variable, b_ii is the second order of input variable (x_i). The ANOVA was employed to explore the significance of each term in the polynomial equation (17). The MINITAB 17 was used to determine the coefficients of Eq. (5) with RSM. The experimental design involved 15 tests and the natural values of these factors for the removal of p-Nitro Cresol are presented in Table 2.

Table 2) Experimental design for three independent variables and the response.

Run No.		Manipulated variables					Removal of p-Nitro Cresol, %
						Exp.		Pred.
1		0.3	8	3		36.7		34.0000
2		0.9	8	3		50.0		51.0000
3		0.3	24	3		71.0		70.0000
4		0.9	24	3		92.0		94.7000
5		0.3	16	2		69.1		68.7250
6		0.9	16	2		87.3		83.2250
7		0.3	16	4		54.4		58.4750
8		0.9	16	4		85.3		85.6750
9		0.6	8	2		39.5		42.5750
10		0.6	24	2		84.5		85.8750
11		0.6	8	4		43.5		42.1250
12		0.6	24	4		81.6		78.5250
13		0.6	16	3		94.6		94.4667
14		0.6	16	3		94.1		94.4667
15		0.6	16	3		94.7		94.4667

 

 

Discussion

Central composite design model
The objective of this section was to determine the optimum condition for maximum removal of p-Nitro cresol in Fenton process. The stages of CCD were studied by many investigators (18–19). The 3-factors CCD matrix and experimental results achieved by the removal of the p-Nitro Cresol is presented in Table 2.
The correctness of the model are illustrated in Fig. 1, which compares the experimental values against the predicted responses of the model for the degradation of p-Nitro Cresol.
These results were exposed a good agreement between predicted and experimental values. It was observed that the predicted response from the model is in agreement with the experimental values.
 

Figure 1) Comparing the experimental and predicted value for the removal of p-Nitro Cresol in Fenton process.
ANOVA tests for the removal of p-Nitro Cresol by Fenton process
In this study, by BBD and RSM, the effects of three independent variables on the response function were studied to obtain the optimal conditions. The mathematical relation between the response and three important variables can be appraised by a quadratic polynomial equation (20). The equation for the removal of the p-Nitro Cresol is presented in the following equation (Eqs. 6):
Removal of p−NitroCresol(%) 164.8 125.4  13.60  56.9                  (6)
 
All of the obtained results from BBD, the observed values and predicted response values with residuals for all runs are presented in Table 3.

Table 3) ANOVA tests for quadratic models for the removal of p-Nitro Cresol by Fenton process.

Sources		DF	SS	MS	F-value	P-value
Fenton
Model		9	6418.45	713.16	48.87	0.000
	Linear	3	4075.91	1358.64	93.09	0.000
		1	869.45	869.45	59.57	0.001
		1	3176.05	3176.05	217.62	0.000
		1	30.42	30.42	2.08	0.208
	Square	3	2275.49	758.50	51.97	0.000
		1	380.08	380.08	26.04	0.004
		1	1770.19	1770.19	121.29	0.000
		1	391.40	391.40	26.82	0.004
	2-Way Interaction	3	67.05	22.35	1.53	0.315
		1	14.82	14.82	1.02	0.360
		1	40.32	40.32	2.76	0.157
		1	11.90	11.90	0.82	0.408
	Error	5	72.97	14.59
	Lack – of – fit	3	72.76	24.25	234.73	0.004
	Pure error	2	0.21	0.10
Total		14	6491.42
	Model Summary	S	R2
		3.82025	98.88%	96.85%	82.06%