Open Journal of Applied Sciences, 2012, 2, 216-223
doi:10.4236/ojapps.2012.24032 Published Online December 2012 (http://www.SciRP.org/journal/ojapps)
Modeling Experimental Design for Photo-Fenton
Degradation of Methomyl
Abdelhadi Abaamrane1,2*, Samir Qourzal2, Saïd Mançour Billah1, Ali Assabbane2, Yhya Ait-Ichou2
1Laboratoire de Génie des Procédés, Département de Chimie, Faculté des Sciences,
Université Ibn Zohr, Agadir, Morocco
2Equipe de Matériaux, Photocatalyse et Environnement, Département de Chimie, Faculté des Sciences,
Université Ibn Zohr, Agadir, Morocco
Received August 27, 2012; revised September 30, 2012; accepted October 10, 2012
ABSTRACT
Modeling experimental design was used to study the main effects and the interaction effects between operational pa-
rameters in the photocatalytic degradation of pesticide methomyl. The important parameters which affect the removal
efficiency of methomyl such as concentration of Fe(NO3)3, concentration of H2O2, initial concentration of the pesticide
and pH. The parameters were coded as x1, x2, x3 and x4, consecutively, and were investigated at two levels (–1 and +1).
The effects of individual variables and their interaction effects for dependent variables, namely, photocatalytic degrada-
tion efficiency (%) were determined. From the statistical analysis, the most effective parameters in the photocatalytic
degradation efficiency were initial concentrations of the methomyl and Fe(NO3)3. The interaction between initial con-
centration of the pesticide and Fe(NO3)3 was the most influencing interaction. The optimum conditions that were ob-
tained for the photocatalytic degradation of methomyl were: minimum quantity of contaminant: 6 × 10–5 mol·L–1,
maximum quantity of Fe(NO3)3: 5 × 10–4 mol·L–1, initial pH of the solution: 3 and maximum quantity H2O2: 10–2
mol· L –1.
Keywords: Methomyl; Photocatalytic Degradation; Response Surface Methodology (RSM); Full Factorial Design
1. Introduction
Pesticides are commonly used worldwide to face the
need for increasing and improving agricultural produc-
tion [1,2]. The detection of pesticides in storm and waste-
water effluent is reported to be a major obstacle as re-
gards wide ranging acceptance of water recycling. Fur-
thermore, their variety, toxicity and persistence can di-
rectly impact the ecosystem and threaten humans through
contamination of drinking water supplies (surface and
ground water).
Methomyl is an oxime carbamate insecticide (Figure
1). It is produced by reacting S-methyl-N-hydroxylthio
acetamidate (MHTA) in methylene chloride with gaseous
methyl isocyanate at 30˚C - 35˚C. Methomyl is highly
soluble in water (57.9 g·L−1) [3]. It has a low sorption
affinity to soil and can therefore easily cause groundwa-
ter contamination in agricultural areas.
Methomyl is effective in two ways: 1) as a “contact
insecticide” because it kills target insects upon direct
contact; and 2) as a “systemic insecticide” because of its
capability to cause overall “systemic” poisoning in target
insects, after it is absorbed and transported throughout
the pests that feed on treated plants. This insecticide is
mainly used in Morocco on a wide range of tomato crops.
However, it has been classified as a very toxic and ha-
zardous pesticide [4].
Recently, chemical treatment methods, based on the
generation of hydroxyl radicals (OH•), known as Ad-
vanced Oxidation Processes (AOPs), due to their effi-
ciency in oxidizing a great variety of organic contami-
nants [5-9].
The Fenton treatments are the requirement of H2O2,
Fe2+ salts and pH adjustment (mostly acidic). With the
additions of H2O2 and Fe2+ salts, highly reactive and un-
selective oxidants are produced as shown in Equation (1)
that leads to the formation of less powerful hydroperoxyl
Figure 1. Chemical structure of methomyl.
*Corresponding author.

A. ABAAMRANE ET AL. 217
radical as per Equation (2) [10,11].

•
2
HO

•
Fe2+ + H2O2 → Fe3+ + OH• + OH– (1)
Fe3+ + H2O2 → Fe2+ + + H+ (2)
2
HO
In order to overcome the sludge problem and enhance
the Fenton treatment, the photo-Fenton process was de-
veloped by introducing a UV light to the Fenton process.
In the presence of UV-irradiation, the Fe3+ complex
formed in Equation (1) can be photo reduced to Fe2+.
This could facilitate the reaction of photo reduced Fe2+
with more H2O2 molecules, which produce new OH•
(Equation (3)) and form a Fenton reaction cycle [12].
This cycle is useful for the progress of the Fenton treat-
ment with no continuous addition of Fe2+ and devoid of
ferric hydroxide sludge. Moreover, two OH• can be pro-
duced from hydrogen peroxide under the UV-irradiation
as shown in Equation (4) [13,14].
FeOH2+ + hν → Fe2+ + OH• (3)
H2O2 + hν → 2OH• (4)
In conventional AOPs methods, the experiments are
usually conducted by varying some studied parameters
while keeping others constant. To avoid repeating this pro-
cess for all influential parameters, factorial design [15,16]
is an experimental strategy that allows the simultaneous
manipulation of many factors and possible synergistic
and antagonistic interactions between them that are de-
termined. In addition, system optimization can be attained
performing a smaller number of experiments than that
needed for univariate techniques resulting in lower reagent
consumption and considerably less laboratory work.
The Response Surface Methodology (RSM) also is an
efficient experimental strategy for determining the opti-
mal conditions. This method is a collection of statistical
and mathematical techniques used for development, im-
provement, and optimization of certain processes in
which a response of interest is affected by several pro-
cess variables and the objective is to optimize this re-
sponse. RSM was applied to AOPs to design and formu-
late new processes and products. The results have been
satisfactory in studies that involve the application of fac-
torial design in the photocatalytic degradation of organic
compounds [17-20].
The objective of this study is to determine the optimal
experimental conditions for methomyl degradation in
photo-Fenton treatment combining H2O2/Fe2+/UV using
RSM, and to examine both single and combined effects
among independent variables of Fe(NO3)3, H2O2, metho-
myl concentration and pH.
2. Experimental
2.1. Reagents
De-ionized water is used throughout this study. Metho-
myl (C5H10N2O2S) is purchased from Merck Chemical
Company at highest purity (99.9%). Ferric nitrate nona-
hydrate (Fe(NO3)3‧9H2O) is provided by Prolabo. Hy-
drogen peroxide solution (35%, v/v) in stable form is
provided by Panreac. The pH of the pesticide solution is
adjusted by using H2SO4 or NaOH (Merck).
2.2. Experimental Apparatus
All photo-Fenton experiments were performed in a well
stirred, batch, cylindrical photoreactor with a total vo-
lume of 500 mL (Figure 2). The reactor is made of glass
and does not contain any metal parts. At the top, the re-
actor has inlets for feeding reactants, and ports for meas-
uring temperature and withdrawing samples. The reactor
was exposed to a luminous source composed of a me-
dium pressure mercury-lamp (Philips HPK, 125 W)
which emitted a maximum radiation at 365 nm, placed in
axial position inside a quartz sleeve. The agitation was
assured by means of a magnetic stirrer placed at the re-
actor base.
2.3. Procedures and Analysis
Preliminary experiments were carried out to screen the
appropriate parameters and to determine the experimen-
tal domain. From these experiments, concentration of
Fe(NO3)3, concentration of H2O2, initial concentration of
the pesticide and pH were the factors involved in this
study. Levels of the factors studied are shown in Table 1.
A two-level-four-factor (24) full factorial experiment
was designed to observe the effect of the parameters in-
fluencing photocatalytic degradation of pesticide me-
thomyl.
Figure 2. Schematic diagram of the photocatalytic reactor.

A. ABAAMRANE ET AL. 218
Table 1. Factors and levels used in the 24 factorial design
study.
Parameter name Code Low (–1) High (+1)
Fe(NO3)3 concentration
(mol·L–1) x1 10–4 5 × 10–4
H2O2 concentration
(mol·L–1) x2 10–3 10–2
Methomyl concentration
(mol·L–1) x3 6 × 10–5 1.23 × 10–4
Initial pH value x4 3 5.4
The photocatalytic efficiency was determined by using
the following equation:

0
0
AA
%
A
r
Y 1 00 (5)
where Y is the photocatalytic efficiency (%), A0 and Ar
both in (mol·L–1) are, respectively, the initial and residual
concentrations of methomyl in solution.
In this research, a 24 full factorial design was em-
ployed to fit a second-order polynomial model. The ge-
neral equation of the second degree polynomial is stated
as follows:
0iiiji j
xxxYa aaε 
 (6)
where Y is the dependent variable (response variable) to
be modelled, xi and xj are the independent variables (fac-
tors), a0, ai, aij are regression coefficients and is the
error.
ε
The analysis of results was performed with statistical
and graphical analysis software (Design-Expert 8.0.1, by
Stat-Ease Inc., USA). This software was used for regres-
sion analysis of the data obtained and to estimate the
coefficient of regression equation. ANOVA (analysis of
variance) which is statistical testing of the model in the
form of linear term, squared term and interaction term
was also utilized to test the significance of each term in
the equation and goodness of fit of the regression model
obtained [21]. This response surface model was also used
to predict the result by isoresponse contour plots and
three dimensional surface plots. Contour plot is the pro-
jection of the response surface as a two dimensional
plane where as 3D surface plots is the projection of the
response surface in a three dimensional plane [22].
3. Results and Discussions
3.1. Experimental Results and Its Evaluation
In the development of a degradation process, the number
of the necessary empirical experiments to determine the
process conditions can be reduced by using a practical
approach that exploits the known effects of system pa-
rameters on the degradation behaviour of methomyl. To
analyze the effect of changes in parameters involved and
to model the dimensional accuracy for various degrada-
tion conditions and to better evaluate the interaction be-
tween the parameters, the full factorial experimental de-
sign and response surface methodology was implemented.
The adequacy of the model is also tested by the method of
analysis of variance (ANOVA) and additional degradation
experiments [23]. This factorial design results in sixteen
tests with all possible combinations of x1, x2, x3 and x4. The
methomyl removal efficiency (Y) after 15 min light irra-
diation as shown in Table 2.
A first-order model with all possible interactions was
chosen to fit the experimental:
0112233 44
12 121313232314 14
24243434123 123124124
134 1342342341234 1234
Y aaxaxaxax
ax ax axax
axaxa xa x
axaxa x

 
 
 

(7)
The coefficients of the first-order polynomial equation
corresponding to each dependent variable were deve-
loped by multiple regression analysis using the Design-
Expert 8.0.1 statistical software.
Data analysis using the Design-Expert 8.0.1 statistical
software at 95% of confidence level permitted to obtain a
semi-empirical expression which consists of 12 statisti-
cally significant coefficients having absolute value greater
than zero, with a probability of 95% (p < 0.05):
Table 2. Experimental results of 24 factorial design for the
photo-Fenton degradation of methomyl.
Experiment x1x2x3x4 Y
(Experimental)
Y
(Predicted)
1 –1–1–1–1 98.94 98.99
2 +1–1–1–1 100 99.95
3 –1+1–1–1 99.37 99.32
4 +1+1–1–1 100 100.05
5 –1–1+1–1 66.62 66.67
6 +1–1+1–1 96.96 96.91
7 –1+1+1–1 73.68 73.63
8 +1+1+1–1 97.99 98.04
9 –1–1–1+1 96.68 96.63
10 +1–1–1+1 100 100.05
11 –1+1–1+1 98.27 98.32
12 +1+1–1+1 100 99.95
13 –1–1+1+1 58.33 58.28
14 +1–1+1+1 94.94 94.99
15 –1+1+1+1 63.10 63.15
16 +1+1+1+1 95.60 95.55

A. ABAAMRANE ET AL. 219
1234
1213231434
123 134
90.03 8.16 0.97 9.131.66
0.76 7.31 0.72 1.111.24
0.51 0.69
Yxxxx
x
xxx
xx
  
 

x (8)
The fit of the model was further checked by the coef-
ficient of determination R2. The R2 value is always be-
tween 0 and 1. The closer the R2 value is to 1, the better the
model predicts the response [24]. The statistically sig-
nificant variables at 95% level of confidence were tested
using analysis of variance (ANOVA) and were: R2 =
0.9995, x2 = 183.07 and F = 11.103 × 10–6; where R2 is the
correlation coefficient, x 2 the sum of quadratic residuals
and F is the F-value. The coefficients of multiple deter-
minations, R2, representing the fit of the models to the
experimental data was 0.9995 indicating that 99.95% of
the variability in the response could be explained by the
model.
Figure 4. The residual value plot of photo-Fenton degrada-
tion of methomyl.
A graph of the actual response values versus the pre-
dicted response values are shown in Figure 3. Actual
values are the experimental response data for a particular
run, and the predicted values were evaluated from the
model and generated by using the approximating function.
As can be seen in the Figure 3, the experimental results
are in good agreement with the values calculated by the
first-order polynomial equation.
Figure 4 shows the residual value and the order of the
corresponding observations. This plot can be helpful to a
designed experiment in which the runs are not randomized.
For residual activity data, the residuals appear to be ran-
domly scattered about zero. No evidence exists that the
regression terms are correlated with one another.
3.2. Analysis of RSM
variable. The response surface analyzes the geometric
nature of the surface, the maxima and minima of the re-
sponse and the significance of the coefficients of the ca-
nonical equation. The polynomial response surface model
obtained may be maximized or minimized to obtain the
optimum points. Whereas a contour plot is a graphical
technique for representing a three dimensional surface by
plotting constant z-slices called contours, on a two di-
mensional format. That is, given a value for z, lines are
drawn for connecting the (x,y) coordinates where that z
value occurs [25].
To investigate the individual and interactive effect of
these four factors on the methomyl removal efficiency,
three dimensional and contour plots were drawn with the
help of Design-Expert 8.0.1 statistical software and the
inferences thus obtained are discussed below.
The response surface graphs of methomyl removal are
shown in Figures 5-8. It can be shown from Figures 5-8
that a strong interaction exists among Fe(NO3)3 concen-
tration, initial methomyl concentration, H2O2 concentra-
tion and pH.
The 3D response surface, which is a three dimensional
graphic representation was used to determine the indi-
vidual and cumulative effect of the variable and the mu-
tual interaction between the variable and the dependent
Figure 5 shows the effect of Fe(NO3)3 concentration
and H2O2 concentration on methomyl removal efficiency.
The response surface of methomyl removal efficiency
gradually increased with increasing H2O2 concentration
from 10–3 mol·L–1 to 10–2 mol·L–1. The maximum value
of photo-Fenton degradation determined was 98% at
Fe(NO3)3 5 × 10–4 mol·L–1 and 10–2 mol·L–1 H2O2.
This can be explained by the effect of the additionally
produced hydroxyl radicals. This may be due to recom-
bination of hydroxyl radicals and also hydroxyl radicals
reaction with H2O2, contributing to the OH• scavenging
capacity (Equations (9)-(11)) [4].
H2O2 + OH• → H2O + (9)
2
HO 
2
HO

+ OH• → H2O+ O2 (10)
OH• + OH• → H2O2 (11)
Figure 6 shows the effect of Fe(NO3)3 concentration
and initial methomyl concentration on methomyl removal
Figure 3. Experimental and calculated values for methomyl
removal.

A. ABAAMRANE ET AL. 220
Figure 5. The response surface and contour plot as a function of Fe(NO3)3 dosage rate and H2O2 dosage of methomyl removal
at 15 min.
Figure 6. The response surface and contour plot as a function of Fe(NO3)3 dosage rate and initial methomyl concentration of
methomyl removal at 15 min.
Figure 7. The response surface and contour plot as a function of Fe(NO3)3 dosage rate and pH of methomyl removal at 15
min.

A. ABAAMRANE ET AL. 221
Figure 8. The response surface and contour plot as a function of initial methomyl concentration and pH of methomyl rem oval
at 15 min.
efficiency. The response surface of methomyl removal
efficiency gradually increased with increasing Fe(NO3)3
concentration from 10–4 mol·L–1 to 5 × 10–4 mol·L–1. The
maximum value of photo-Fenton degradation determined
was 100% at Fe(NO3)3 5 × 10–4 mol·L–1 and 6 × 10–5
mol· L –1 methomyl concentration.
The reason is when Fe2+ concentration increased, the
catalytic effect also accordingly increased. When the
concentration of Fe2+ was higher, a great amount of Fe3+
from the process of H2O2 decomposition by Fe2+ was
easy to exit in the form of Fe(OH)2+ in acidic environ-
ment.
Figure 7 shows the effect of Fe(NO3)3 concentration
and pH on methomyl removal efficiency. The response
surface of methomyl removal efficiency gradually in-
creased with decreasing initial pH value from 5.4 to 3.
The maximum value of photo-Fenton degradation deter-
mined was 98% at Fe(NO3)3 5 × 10–4 mol·L–1 and 3 initial
pH value.
The degradation decreased at pH values higher than
5.4, because iron precipitated as hydroxide, which re-
sulted in a reduction in the transmission of the radiation
[26]. Additionally, the oxidation potential of hydroxyl
radical was known to decrease with increasing pH [2-7].
Another reason for the inefficient degradation at pH > 3
is due to the dissociation and auto-decomposition of
H2O2 [1]. For pH values below 3, there action of hydro-
gen peroxide with Fe2+ is seriously affected causing the
reduction in hydroxyl radical production [27].
In Figure 8 the effect of initial methomyl concentra-
tion and pH on methomyl removal efficiency. The re-
sponse surface of methomyl removal efficiency gradually
decreased with increasing initial methomyl concentration
from 6 × 10–5 mol·L–1 to 1.23 × 10–4 mol·L–1. The
maximum value of photo-Fenton degradation determined
was 99% at 6 × 10–5 mol·L–1 methomyl concentration and
3 initial pH value.
The maximum photo-Fenton degradation efficiency of
methomyl obtained in this study was found to be 100%,
corresponding to the operating conditions of 5 × 10–4
mol· L –1, 10–2 mol·L–1, 6 × 10–5 mol·L–1 and 3, respec-
tively, for the Fe(NO3)3 concentration, H2O2 dosage, ini-
tial methomyl concentration and pH.
The interaction between Fe(NO3)3 concentration and
initial methomyl concentration was the most important
interaction. However, the interaction between Fe(NO3)3
concentration, H2O2 concentration and pH was least in-
fluencing because photo-Fenton degradation efficiency
does not change significantly.
4. Conclusion
The work presented here provides support for the degra-
dation of methomyl as a model for environmental con-
taminant. The experimental design used allows rigorous
analysis of the factors influencing methomyl degradation
in a photo-Fenton process. The optimum process condi-
tions obtained through a statistical method full factorial
experimental design was successfully determined to
maximize the methomyl degradation. The model pre-
dicted that initial methomyl concentration and Fe(NO3)3
has significant effects on photocatalytic methomyl deg-
radation. Maximal methomyl removal efficiency of
100% was obtained at the optimum conditions as follows:
Fe(NO3)3 concentration (5 × 10–4 mol·L–1), H2O2 con-
centration (10–2 mol·L–1), methomyl concentration (6 ×
10–5 mol·L–1) and initial pH value (3). The high correla-
tion of the model with the experimental results indicates
that RSM analytical procedure could be a general method
to describe the similar photo-Fenton system and to pre-
dict its behavior. Good agreement between predicted and

A. ABAAMRANE ET AL. 222
experimental data at the optimum conditions confirms
the usefulness of the model.
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