Photo catalytic Degradation of Monocrotophos in an Immobilized
Bead Photo catalyst Using Factorial Design of Experiments
K.SIVAGAMI
Research Scholar
DEPARTMENT OF CHEMICAL ENGINEERING
INDIAN INSTITUTE OF TECHNOLOGY MADRAS
OUTLINE

Introduction

Scope and Objectives

Materials and methods

Results and Discussion


Statistical design of experiment

Batch recirculation studies in IBPR

MCP degradation kinetics

Evaluation of properties of immobilized beads
Summary
INTRODUCTION
Pesticides
Major sources of
pesticide pollution industries,
agriculture,
domestic activities
contaminated water
bodies, sediments
and soil through
rain water
Pesticides are very
harmful because of
their toxicity and
carcinogenic nature.
They are
bioaccumulative and
relatively stable in
environment.
EPA Classification of Chemical Pesticides

Organophosphate Pesticides
(e.g. Monocrotophos)

Organochlorine Pesticides
(e.g. Endosulfan, DDT and chlordane).

Pyrethroid Pesticides
(e.g. Bifenthrin and Cypermethrin)

Carbamate Pesticides
(e.g. Alcamate and Aldicarb)
Endosulfan
C9H6Cl6O3S
Structural features of organo phosphates
A terminal oxygen connected to phosphorus by a
double bond, i.e. a phosphoryl group
Two lipophilic groups bonded to the phosphorus
A leaving group bonded to the phosphorus, often a
halide
monocrotophos
Various methods available
Treatment Methods
Physical
Separation
Advanced Oxidation
Processes
Biodegradation
Phase Transfer from
one phase to another
e.g. adsorption by
activated carbon
Needs secondary
treatments
Some persistent
organic chemical to be
lethal for microbes
Limited by Toxicity
Complete
mineralization of
pollutants in to
CO2, H2O and
mineral acid
TiO2 Photocatalysis Mechanism
Image source ref - ( Suri et al, 1993)
Objectives of the work

The main objective of this study is to evaluate the
effectiveness of heterogeneous photocatalytic oxidation
using slurry and immobilized TiO2 photoreactor system
for removal of organo phosphorous pesticides.

Design and fabrication of immobilized bead photo reactor
(IBPR)

Evaluation of physical and chemical characteristics of
immobilized beads

Modelling of experimental data with rate kinetic model

To identify the intermediates form during treatment
Materials and Methods
The technical grade pesticides
Monocrotophos (78% purity) Sriram Pesticides.
 TiO2 with surface area 15 m2/g ( CDH, India).
Analysis of pesticides

HPLC(JASCO Pu-2089 plus) with PDA detector

Phenomenex C18 Column ( 450 x 2.5 mm)

Mobile phase : Acetonitrile/Water ratio - 70:30
Side view of Immobilized Bead Photo Reactor
Immobilized Bead Photo Reactor (IBPR)
Experimental Set up
Schematic representation
of floating photo catalyst
TiO2 coated polymeric beads
15W UV lamp housing
TiO2 beads circulation inside the reactor
Immobilized Bead Photo Reactor- Full view
STATISTICAL DESIGN OF EXPERIMENT

In traditional single-factor optimization approach, each quantity is considered to be
independent on other process variables

In the statistical optimization process all the variables are considered simultaneously
where different degree of interaction of the same variable and interaction among all
different variables are also considered.

This approach also decreases the number of experiments required and there by
reduces the cost and labor.

Photocatalytic degradation is a complex process where there are possible interactions
between the process variables.

“A full factorial design which includes all combination for each factor is a powerful tool
for analysing complex processes. (Ghosh and Swaminathan, 2004).
CENTRAL COMPOSITE DESIGN (CCD)

CCD contains an imbedded factorial or fractional factorial design.It consists of 2 k
experiments where k (K=3) is the number of variables in which each variable is
placed either high (+) or low (-) level,

fixed no. of center point (four) experiments in place of replicates and

Two axial points on the axis of each design variables at a distance of (α) for
rotatability in the design ( Khuri et al, 1987).

Thus a total of 18(23+2*3+6=20) experiments including six at center point were
used as given in Table 2.

The range of experimental variables are shown in Table 1 .
Table1. Experimental range and levels of independent variables
for MCP degradation
-α
-1
0
+1
α
Initial pesticide conc (mgL1)
0.95
3
6
9
11.05
Catalyst conc (gL-1)
0.64
2
4
6
7.36
pH
3.63
5
7
9
10.36
Parameter
Table 2 - EXPERIMENTAL DESIGN FOR MONOCROTOPHOS DEGRADATION IN IBPR REACTOR
Factor 1
Factor 2
Factor 3
pH
Initial conc of pesticide(mg/L)
Catalyst (g/ 200g beads)
1
6
7
7.36
53
2
6
7
4
50
3
9
9
2
35
4
9
5
2
40
5
3
9
6
59
6
6
7
4
51
7
3
5
6
71
8
11.05
7
4
38
9
0.95
7
4
75
10
9
5
6
46
11
6
7
4
53
12
6
10.36
4
40
13
6
7
0.64
43
14
3
9
2
55
15
9
9
6
38
16
6
7
4
51
17
3
5
2
65
18
6
3.64
4
57
19
6
7
4
53
20
6
7
4
50
S.No.
Removal
Efficiency (%)
Photo catalytic degradation of Monocrotophos
1.20
1.20
1.00
1.00
0.80
C/C0
C/C0
0.80
0.60
0.40
0.60
Run 1
0.40
0.20
Run1
Run 2
Run 3
0.20
Run 2
0.00
0.00
0
2
4
6
8
10
12
14
Time (hr)
6 mg/l MCP, 5 pH, 4 g TiO2/ 200g beads
0
1
2
3
4
5
6
7
Time (hr)
6 mg/l MCP, 5 pH, 4 g TiO2/ 200g beads
Effect of initial concentration in MCP degradation
Batch recirculation studies
•Four liters of pesticide solution
6 mg/l
0.90
12 mg/l
1 mg/l
0.80
0.70
C/C0
•Different concentration of
Monocrotophos and TiO2 are
equilibrated for 5 min and batch
recirculated through immobilized bead
photo reactor
1.00
0.60
0.50
The effect of following parameters are
studied in degradation
0.40
•Initial concentration of pesticide
0.20
0.30
0
2
4
6
8
Inital concentration (mg/l)
•Catalyst load
•pH
Different initial conc. Of MCP,
5 pH, 4 g TiO2/ 200g beads
Effect of Initial concentration in pesticide degradation

The equilibrium adsorption of reactants on the catalyst
surface and the reaction rate of OH radicals with other
chemicals are significant in the rate of degradation.

At higher pesticide concentrations, there would be more
adsorption of pesticide on TiO2 resulting in a lesser
availability of catalyst surface for hydroxyl radical
generations.

It also adsorb more photons from the UV light thus
reducing the photonic energy available for hydroxyl
radical generation.

Similar result was observed by (Kormann et al, 1991)
Effect of pH in MCP degradation

The surface charge of photocatalyst is
highly dependent on the solution pH
because of its amphoteric nature;
1.00

The zero point charge, pHzpc for
Titania is around 6.9
pH 3
pH 7
0.90
pH 10.3
0.80


The pKa value of monocrotophos is
around 4.5
C/C0

At acidic pH the protanated form
predominates while at higher pH it
exists in the anion form.
0.70
0.60
0.50
The electrostatic interaction between
the (+)ve charged surface and
protonated pesticide favors adsorption
and increases its removal
0.40
0.30
0
2
4
6
8
Time (hrs)
6 mg/l MCP conc., 4 g TiO2/ 200g beads
At different pH
Effect of catalyst load in MCP degradation
1.00
0.90
0.80
2 g
4 g
6 g
1.00
0.80
0.70
C/C0
C/C0
1.20
2g
4g
6g
0.60
0.60
0.50
0.40
0.40
0.20
0.30
0.00
0
0
2
4
6
8
2
4
6
Time (hr)
Time (hr)
Effect of increase in surface area2g TiO2/
200g of beads at conc of 6 mg/l, 5 pH
Effect of catalyst load in 200 g of
beads at conc. of 6 mg/l, 5 pH
Effect of catalyst load in MCP degradation
•
The catalyst concentration plays an important role in the chemical reactions
and has a significant effect on the process efficiency.
•
Active sites are proportional to the catalyst concentration, it will affect the
degradation significantly.
•
This behavior may be attributed to the shadowing effect at increase in
surface are of catalyst where the suspended TiO2 beads reduces the
penetration of light to the solution.
•
For a constant amount of beads, increasing the catalyst load above 4 g/
200g beads shows decrease in removal efficiency due to unavailability of
catalyst sites for reaction.
Statistical design of experiment

The data obtained through the statistically designed experiment
was fitted to a second order polynomial equation.
Y= βo +Σ βiXi+ Σ βiiXi2 + Σ βiXiXj
where Y is the response variable.

The coefficients of the equation were estimated using a statistical
program MINITAB 14 (Minitab Inc, USA)

The regression analysis of the data was also done using the same
program. The multiple correlation coefficient R and determination
coefficient R2 were used to test the validity of the model.

Analysis of Variance (ANOVA) was used to test the significance
and adequacy of the model.
Table 3 – Estimated Regression coefficients for MCP degradation
Term
Coefficients
St. Dev
T - Value
P- Value
Constant
51.33
0.4597
111.655
0.000
pH
-4.66
0.3050
-15.266
0.000
inital conc of pollutant
-11.22
0.3050
-36.785
0.000
catalyst
2.62
0.3050
8.599
0.000
Initial*Initial
1.86
0.2969
6.255
0.000
pH*pH
-0.97
0.2969
-3.271
0.008
Catalyst *Catalyst
-1.15
0.2969
-3.866
0.003
pH* inital conc
of pollutant
1.13
0.3985
2.823
0.018
pH* catalyst
-0.62
0.3985
- 1.568
0.148
inital conc*catalyst
-0.12
0.3985
- 0.314
0.760
Polynomial regression equation

The results of the experiments were fitted into a second order
polynomial regression model as shown in the following equation

Y = 51.33 – 4.66 x^1 – 11.22 x^2 + 2.62 x^3 +1.86 x1^2 -0.97x2^21.15 x3^2 +1.13 x^1x^2 -0.62 x^1 x^3-0.12 x^2 x^3

Where Y is the response variable, percentage removal of MCP

X1, X2 and X3 are the coded form of the parameters like pH, initial
pollutant concentration and catalyst concentration
Statistical analysis of regression coefficients

The significance of the coefficients were tested using the students ‘t’
test and the probability ‘p’ value which are also given in Table 3.

A p value below 0.05 indicates that test parameter is significant at
5% level of significance.

In general, the larger the magnitude of t and smaller the value of p,
more significant is the corresponding coefficient term (Montgomery,
1991).

It was observed that the coefficients of the main effects of pH and
catalyst concentrations were more significant than those of others.
Table 4 - ANOVA for IBPR degradation of MCP
Source
DF
Seq SS
Adj SS
Adj MS
F
P
Regression
9
2213.85
2213.85
245.983
193.62
0.000
Linear
3
2109.20
2109.20
703.065
553.39
0.000
Square
3
91.27
91.27
30.425
23.95
0.000
Interaction
3
13.38
13.38
4.458
3.51
0.057
Residual Error
10
12.70
12.70
1.270
Lack-of-Fit
5
3.37
3.37
0.674
0.36
0.856
Pure Error
5
9.33
9.33
1.867
Total
19 2226.55
S = 1.127
R-Sq = 99.4%
R-Sq(adj) = 98.9%
Analysis of ANOVA

The F values for the model and for each of the response
variables were calculated by dividing the mean sum of
square due to model variance by that due to error
variance.

As seen from table 4 the F value for the model is highly
significant this is reflected in the relatively high
correlation coefficient R2 = 0.98.

This is due to the fact that the range of variables are in
the optimal region.
2 Dimensional Contour plots for MCP Batch Degradation
Contour Plot of removal
Contour Plot of removal
45
55
65
75
7
6
42
52
62
72
82
10
9
5
8
pH
4
7
3
6
2
5
1
4
1
2
3
4
5
6
7
8
9
10
11
1
initial conc of mcp
2
3
4
6
7
8
initial conc of mcp
Hold values: pH: 7.0
Hold values: catalyst: 4.0
Contour Plot of removal
40
45
50
55
7
6
catalyst conc
5
5
4
3
2
1
4
5
6
7
pH
Hold values: initial: 6.0
8
9
10
9
10
11
3 Dimensional Response Surface Plots for MCP Batch Degradation
Optimized conditions are
pH = 7
 Pollutant concentration = 1 mg /L
 Catalyst load = 4 g/L
 Monocorotophos removal efficiency in
optimized conditions is about 80%

Effect of aeration and MCP degradation in sunlight
1.20
1.2
1.00
1
0.80
0.8
C/C0
C/C0
Withour air
0.60
With air
0.6
0.4
0.40
sunlight
0.20
0.2
UV C light
0
0.00
0
2
4
Time (hr)
6
0
2
4
Time (hr)
6
Effect of light wavelength
C-C-C
1.20
1.5
1.4
-ln (C/C0)
1.00
0.80
1.3
C/C0
UV-C light intensity (mW/m^2)
1.40
1.6
1.2
0.60
0.40
1.1
1
Along the width of inlet
0.20
0.9
Along the width of centre
Along the width of oulet
0.00
C-C-C
A-C-A
C-A-C
A-A-A
0
1
2
Length
3
4
A-C-A
1.00
C-A-C
A-A-A
0.80
y = 0.0013x
0.60
R2 = 0.9439
y = 0.0035x
2
R = 0.9817
0.40
y = 0.001x
2
R = 0.9607
0.20
y = 0.0008x
R2 = 0.9409
0.00
0
0.8
1.20
100
200
Time (min)
300
400
0
100
200
Time (min)
300
400
pH and conductivity changes in
MCP degradation
TOC degradation
250
1.2
8.3
1.0
200
0.8
0.6
0.4
TOC degaradation (UV+TiO2)
TOC degradation (UV)
0.2
8.2
150
8.1
pH
Conductivity (micro S/cm)
TOC/TOC initial
8.4
8
100
Change in conductivity (UV)
change in conductivity (UV+TiO2)
50
0.0
0
50
100
150
200
250
change in pH (UV+TiO2)
300
Time(min)
7.8
change in pH (UV)
0
0
5 ppm MCP degradation, UV-C lamp, 4 g TiO2
7.9
50
100
150
Time (min)
200
250
7.7
300
Batch Kinetic studies

The rate expression is given in Equation 1 for semibatch system
V  dC pest 
rate  T  
  kobs C pest
Vi 
dt 
 C pesticide
ln 

 Co pesticide

 t
   kobs


V 

kobs   T  kobs
 Vi 
VT and Vi  the total volume of liquid treated and volume of the reactor (irradiated volume) (l)
dCpest/dt  the observed rate (mgL-1.min -1),
Cpest  MCP concentration (mgL-1) at time t
C0 pest the initial pesticide concentration, (mgL-1)
t  reaction time (min),
Kobs  the pseudo-first-order rate constant. (min-1 )
Langmuir-Hinshelwood (L-H) kinetics

The rate of Moncrotophos degradation over illuminated TiO2 fitted the
Langmuir-Hinshelwood (L-H) kinetics model
r 






dC
KC


dt
 (1  kKC ) 
( 1)
r= the oxidation rate (mg/L min),
C= Reactant concentration (mg/L),
t= the illumination time, k= the reaction rate constant (mg/L min),
K= the adsorption coefficient (L/mg).
When Co is small, eq (1) can be simplified to a apparent first-order equation
C 
ln  0   kKt  K app t
 C 
If the adsorption coefficients for all organic molecules present in the reacting mixture are effectively
equal. Then rate of reaction
Rrxn 
kL  H K pesticideC pesticide
1  K
pesticide
Co pesticide 
 kobs C pesticide
The relationship between k obs and Co can be expressed as a linear equation
 C0 pesticide  
1
1



kobs
 kL  H
  k L  H K pesticide




12
y = 1.1368x + 0.7811
R2 = 0.9773
1.60
y = 0.1318x
y = 0.2412x 2
R = 0.9693
R2 = 0.9734
y = 0.0861x
y = 0.195x R2 = 0.9719
R2 = 0.977
y = 0.0933x
y = 0.163x R2 = 0.9925
R2 = 0.9751
1.40
-ln(C/C0)
1.20
1.00
0.80
0.60
1/Kobs
10
1ppm MCP 4 g/l 7 pH
6 ppm 0.64 g/l 7 pH
8
6
4
6 ppm 4 g/l tio2 10.3 pH
2
6 ppm MCP 4 g/l TiO2 3 pH
0
0
3 ppm MCP 6 g/l tio2 5 pH
5
10
initial conc (ppm)
9 ppm MCP 6 g TiO2 9 pH
0.40
pseudo-first-order kinetic rate constant,
kobs for different initial conc. of pesticide
0.20
0.00
0
1
2
3
4
5
Time (hr)
K = 0. 885 Lmg-1
kL-H = 1.31 mg L-1 min-1
6
7
Co (mg/L)
1/kobs
R2
3 at 5 pH
1.03
0.977
6 at 3 pH
4.50
0.98
6 at 10.3 pH
7.58
0.97
9 at 9 pH
11.63
0.97
Characterization of Catalyst film
Properties
SEM AND EDAX ANALYSIS OF TiO2 COATED POLYMERIC BEADS
Element
•
•
•

SEM image of TiO2 coated bead
(50, 100 micro meter)
EDAX analysis of TiO2 coated bead
Table shows elemental Analysis in the
coated bead
Though the coating was spread over the
entire surface uniformly few spots of
agglomerates (by circle) as
shown in Figure
Wt%
At%
OK
45.81
70.80
NaK
00.67
00.72
MgK
00.35
00.36
AlK
00.67
00.61
SiK
00.74
00.65
CaK
01.40
00.86
TiK
50.36
26.00
Matrix
Correction
ZAF
SEM image of catalyst thickness on bead
2 g TiO2 on 200g of beads
4 g TiO2 on 200g of beads
UV-Visible spectroscopic analysis of TiO2 film
3.9
Absorbance
3.7
CDH
CDH+BINDER
Optical characteristics of
catalyst
3.5
Wavelength range of 300–1300
nm.
3.3
3.1
2.9
2.7
2.5
300 500 700 900 1100 1300
w avelength (nm)
Absorbance spectra of pure
TiO2 -CDH catalyst and TiO2 binder catalyst coating .
Binder did not affect the
absorbance of catalyst much.
Intensity (a.u)
XRD analysis of catalyst film
4500
Pure CDH
4000
3500
PURE CDH
3000
2500
0
20
40
60
80
2θ
3900
intensity (a.u)
3700
Catalyst film
3500
3300
3100
2900
2700
2500
0
10
20
30
40
50
60
70
80
2θ
The peaks corresponding to 25.7, 38.1, 48.7, 54.5 and 63.30 indicate that
the anatase phase was predominant .
It indicates high photocatalytic activity of the immobilized TiO2 surface
GC-MS intermediates identification
DMMP Di methyl sulfone Methyl Phosphate
GC-MS intermediates identification
Tri methyl Phosphite
DMMP
Mass spectrum of Monocrotophos
%
127
100
0
30
58
43
30
40
50
60
67
97
79 82
70
80
90
109
100
110
119
120
164
130
140
150
160
170
180
180
192
190
223
200
210
220
GC-MS intermediates profile
8000000
160000
7000000
140000
6000000
MCP
5000000
Methyl Phosphate
Area under the curve
Area under the curve
DMMP
4000000
3000000
2000000
Di methyl sulfone
Trimethl Phosphite
120000
100000
80000
60000
40000
1000000
20000
0
0
2
4
Time (hr)
6
0
0
1
2
3
Time (hr)
4
5
6
Summary

The performance of the immobilized bead photo reactor, with
floating beads developed in this study was evaluated for MCP
removal.

The pesticide (MCP) degradation was higher at low pesticide
concentration and in acidic pH.

Increasing the catalyst concentration up to 4 g/L increased the
pesticide removal and higher catalyst dose decreased the removal
due to shielding effect.

The data obtained for IBPR using statistically designed experiment
were fitted to a quadratic polynomial model to predict the degradation efficiency in terms of the parameters.

Statistical analysis of the data in terms of ANOVA showed very good
correlation between the model and the experimental results. It was
also observed that the linear effects of the parameters were more
significant than the interaction effects.
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
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
Shankar, M. V., S. Anandan, N. Venkatachalam, B. Arabindoo and V. Murugesan
(2004) Novel thin-film reactor for photocatalytic degradation of pesticides in
aqueous Solutions. J. Chem. Technol. Biotechnol., 79, 1279–1285.

S.Chen and Cao Gengyu (2005), Photocatalytic degradation of organophosphorus
pesticides using floating photocatalyst TiO2 · SiO2/beads by sunlight, Solar
energy, 79(1), pp. 1-9 .

Balaram Kiran Avasarala, Siva Rao Tirukkovalluri, Sreedhar Bojja (2011),
Photocatalytic degradation of monocrotophos pesticide—An endocrine disruptor
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1240

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