Journal of Materials Science and Chemical Engineering, 2013, 1, 33-38 Published Online October 2013 (
Copyright © 2013 SciRes. MSCE
Discoloration on Methylene Blue Solutions by Direct
and Catal ytic Ozon a t io n
Antonio D. Rodriguez-Lopez1*, Jose Garcia-Garr ido 1*, Cynthia Perez-Ramiro1,
Esperanza M. Garcia-Castello2
1Grupo de Tecnologías de Control de Aguas y Residuos (TECAR), Universitat Politècnica de València,
Camino de Vera, Valencia, Spain
2Institute of Food Engineering for Development, Universitat Politècnica de València,
Camino de Vera, Valencia, Spain
Email: *, *
Received August 2013
During textile manufacturing, huge amounts of wastewaters characterized by removed impurities and high concentra-
tions of dye are produced. These wastewaters cause several problems when they are discharged to the environment. The
use of ozone in wastewater treatment results of interest. In this work we propose to assess the discoloration rate of dif-
ferent synthetic wastewaters as a function of pH, dye concentration (methylene blue (MB)) and reaction time. A com-
parison of discoloration rate between conventional ozonation and catalytic ozonation salts of copper, zinc, silver and
nickel was also performed. For the optimization of the ozonation process of colored solutions, it was used a central
composite experimental design with five replicates of the center point resulting to evaluate the influence of the inde-
pendent variables at different ranges of pH, [MB] and time. In the catalyst-assisted ozonation, [MB], pH and the reac-
tion time were fixed to 100 mg/L, 5.5 and 15 min, respectively. The optimized experimental conditions to provide
maximum discoloration were pH = 3.3; [MB] = 8.6 mg/L and time = 74.3 min. Regarding the catalyst-assisted ozona-
tion, it was found that CuSO4 catalyst gave better color reduction if compared with other catalysts assayed.
Keywords: Textile Wastewater; Methylene Blue; Discoloration; Ozonation; Catalytic
1. Introduction
Textile industry is one of the most common and essential
sectors in the world [1]. It is considered one of the long-
est and most complex manufacturing industrial chains,
covering the entire production cycle from raw materials
to semi-processed products (yarns, woven and knitted
fabrics with their finishing process), and final products
(carpets, home textiles, clothing and industrial use tex-
tiles) [2,3]. At the EU, the over the 80% of the textile
production are headed by Italy, Germany, UK, France
and Spain [2].
During the textile manufacturing, huge amounts of
water as well as chemical products are consumed [4].
Hence, wastewaters are characterized by their high vo-
lume, removed impurities and high concentrations of dye.
In this sense, from 30% [5] to 50% [6] of the dye used in
the textile processing are present mainly as hydrolyzed in
Textile wastewaters cause several problems when they
are discharged to the environment due to color provided
by dyes. There are esthetic problems [2,3,5,6] as well as
toxic problems to aquatic life since colored wastewaters
avoid the light penetration and in addition, dyes or their
derivat ives present harmful properties [1,5,7].
Therefore, color removal must be one of the targets to
treat both textile dyeing and dye manufacture wastewa-
ters [8,9]. Physicochemical and biological treatments of
these wastewaters have been proposed. Conventional
physicochemical processes are effective to remove dyes
[10,11], but are expensive [3,12]. Another drawback is
that physicochemical treatments transf er the pollutants to
other phase but not eliminate the problem [13]. The ac-
cumulation of toxic compounds in the sludge can create
disposal problems that might also lead to a secondary
pollution [3,11 ,12].
Biological treatments are considered not to be com-
pletely adequate. In textile wastewater, there are resistant
pollutants to biological degradation, and so, color is re-
duced but not up to levels that allow direct discharge
Other alternatives for the textile wastewater color re-
moval are anaerobic treatments [5], activated carbon [11],
*Corresponding a uthors.
Copyright © 2013 SciRes. MSCE
combined processes as fluidized biofilm process-chemi-
cal coagulation-electrochemical oxidation [15] or acti-
vated carbon and sequencing batch reactor (SBR) [12].
However studies and investigations on other options of
wastewater treatments such as ozonation or advanced
oxidation processes (AOPs) are necessary to remove the
color completely [3].
The use of ozone in wastewater treatment results of
interest because there is no sludge production; the per-
formance is very easy; the required space is small and
residual ozone can be easily decomposed to oxygen and
water [13]. Regarding the AOPs, they are based on the
generation of hydroxyl radicals in water. These radicals
are highly reactive and nonselective oxidants that can
oxidize different organic compounds [13].
Most studies about AOPs are focalized in photocata-
lytic oxidation, Fenton (FO), photo-Fenton and ozone
oxidation have been attempted individually or combined
with UV, TiO2 or H2O2 oxidants to decolorize the textile
wastewater [1,13,16-19] but there are no many studies to
treat to decolorate with ozone and other catalyst as cop-
per, zinc , si l ver or nicke l [ 20].
In this work we propose to assess the discoloration rate
of different synthetic wastewaters as a function of pH,
dye concentration (methylene blue (MB) [9]) and reac-
tion time. A comparison of discoloration rate between
conventional ozonation and catalytic ozonation salts of
copper, zinc, silver and nickel was also performed.
2. Introduction
2.1. Chemicals
The substrate of the reaction, methylene blue
(C16H18ClN3S·(2-3)·H2O; MW 319.9 g/mol (d.b.)), was
purchased from Prolabo (VWR Prolabo, Fontenay-sous-
Bois, France), was employed without further purification.
Zinc oxide (ZnO), copper (II) sulfate pentahydrate (Cu-
SO4·5H2O), potassium iodide (KI), sodium hydroxide
(NaOH) and sulfuric acid (H2SO4) were obtained from
Prolabo too.
Other reagents, as Zinc sulfate heptahydrate
(ZnSO4·7H2O), titanium dioxide (TiO2), nickel (II) sul-
fate hexahydrate (NiSO4·6H2O), copper (II) sulfate an-
hydrous (CuSO4) and silver sulfate (AgSO4) were pur-
chased from Merck (Darm st adt , Ge rmany).
2.2. Ozonation System
The laboratory system used is depicted in Figure 1. It
consisted in two columns: the first column (ozonation
reactor) was a PVC pipe with a diameter of 3.5 cm and a
height of 1 m. The experimental volume was fixed at 500
mL and presented an outlet at the bottom for the sample
extraction, as well as an upper connection to the second
column for the outflow of ozone in excess.
Figure 1. Schematic diagram of reactor system.
This second reactor, with the same dimensions and
volume than the first one contained a solution of 2% IK.
Ozone was generated directly from oxygen in air by a
G300 Hidro device (ZonoSistem, Cádiz, Spain). The
average gas flow generated was 0.76 L/min, with an av-
erage generation rate of 0.86 mg O3/min, thus, the O3
concentration in the inlet of the first reactor inlet was
1.14 mg/L.
2.3. Experimental Design
2.3.1. Direct Ozonation Process
For the optimization of the ozonation process of colored
solutions, it was used a central composite (CCD) expe-
rimental design with five replicates of the center point
resulting in a 19 runs to evaluate the influence of the in-
dependent variables at different ranges: pH (3.3 - 11.7),
methylene blue concentration (7.9 - 92.0 mg/L) and reac-
tion time (9.5 - 110.4 min). Natural and coded variables
are shown in Table 1. The response considered was the
final absorbance in order to calculate the color reduction.
The effect of these three independent variables on col-
or reduction was studied trough a Response Surface Me-
thodology (RSM). The use of RSM is useful for model-
ing and analysing when a response is influenced by sev-
eral variables and the objective is to optimize this re-
sponse [21].
2.3.2. Catalyst-Assisted Oz o nation Process
In the catalyst-assisted ozonation, the laboratory system,
the MB solution volume and the ozone concentration
were the same than used in the direct ozonation. The MB
concentration, pH and the reaction time were fixed to
100 mg/L, 5.5 and 15 min, respectively.
Copyright © 2013 SciRes. MSCE
Table 1. Natural and coded (in brackets) variables for the
experimental factors pH, Methylene Blue concentration and
reaction time in the central composite design for the direct
ozonation of organic dye solutions.
Run pH (X1) [MB] (mg/L) (X2) t (min) (X3)
1 10 (+1) 25 ( 1) 90 (+1)
2 5 (1) 75 (+1) 90 (+1)
3 7.5 (0) 50 (0) 60 (0)
4 7.5 (0) 50 (0) 110.4 (+ 1 .68)
5 7.5 (0) 50 (0) 9.5 (1.68)
6 5 (1) 25 (1) 30 (1)
7 11.7 (+1.68) 50 (0) 60 (0)
8 7.5 (0) 92 (+1.68) 60 ( 0 )
9 7.5 (0) 50 (0) 60 (0)
10 5 (1) 75 (+1) 30 (1)
11 7.5 (0) 8 (1.68) 60 ( 0 )
12 3.3 (-1.68) 50 (0) 60 (0)
13 7.5 (0) 5 0 (0) 60 (0)
14 5 (1) 25 (1) 90 (+1)
15 10 (+1) 75 (+1) 30 (1)
16 7.5 (0) 5 0 (0) 60 (0)
17 10 (+1) 75 (+1) 90 (+ 1 )
18 10 (+1) 25 (1) 30 (1)
19 7.5 (0) 5 0 (0) 60 (0)
Several catalyst were assessed (ZnO, CuSO4·5H2O,
CuSO4, AgSO4, NiSO4·6H2O, TiO2 and ZnSO4·7H2O).
Different doses of catalyst were evaluated (0, 2, 20 and
200 mg/L). To study the evolution of the discoloration
rate with time, samples were taken each 5 min.
2.4. Analytical Determinations
2.4.1. Ozone Measurement
The ozone concentration was determined by bubbling the
gas generated in a solution of IK, Na2HPO4 and KH2PO4
to 2%, 0.73% and 0.35%, respectively, and subsequent
titration with sodium thiosulfate 0.002 M daily prepared
2.4.2. Discoloration Rate
The discoloration rate or color reduction was determined
as expressed in Equation (1). The absorbance was meas-
ured in a Genesys 5 spectrophotometer (Spectronic In-
struments, USA) at the maximum wavelength for the
Methylene Blue (665 nm) [6,7].
( )
% 100%
Abs Abs
Rcolor x
where Absf is the absorbance at requested time and Abs0
is the initial absorbance of each solution.
2.4.3. pH Measurement
The pH of the different solutions was measured by a
pH-meter (pH & ION meter GLP 22, Crison, Spain). The
pH of the feed solutions shown in Table 1, were adjusted
by using 0.1 M NaOH and 0.1 M H2SO4.
All the analyses were done in triplicate. Data used in
the statistical analysis were the average of these three
values. Results were analyzed using the software “Stat-
graphics” version Centurion XVI, from StatPoint Tech-
nologies, Inc, USA. Linear and quadratic effects of the
three variables considered, as well as their interactions on
the response variables studied were calculated. Their
significance was evaluated by analysis of variance
(ANOVA). The proposed model, to which the experi-
mental data were fitted, was a second-order polynomial
model (Equation (2)).
011 1
nn n
i iii iij ij
i iji
ββ ββ
=== +
=++ +
∑∑ ∑
where Y is the response var iable; β0, βi (i = 1, 2, 3), βij (I
= 1, 2, 3; j = 1, 2, 3) and βii(i = 1, 2, 3) are the coeffi-
cients for independent, linear, interaction and quadratic
terms, respectively.
3. Results and Discussion
3.1. Direct Ozonation Process
Experimental results shown that the color reduction pre-
sented values higher than 95% in all runs excepting for
the run 5 in which the reaction time was the lowest as-
sayed (9.5 min). Thus, it seems that at times considered
in the experimental design proposed, the color reduction
evolution has been missed. From reaction time higher
than 60 min, the reduction color presented an asymptotic
trend close to 100% ( Figure 2).
Results obtained in terms of color reduction by direct
ozonation were fitted to a second-order polynomial mod-
el (Table 2).
For a confidence level of 95%, the p-value of the sig-
nificant effects must be lower than 0.05. It was found
that the significant terms were linear and quadratic terms
corresponding to the time reaction (positive and negative
effect, respectively). The RSM plot for the color reduc-
tion is depicted in Figure 2. There is a reduction of the
color reduction as th e MB concentration increases.
Copyright © 2013 SciRes. MSCE
Figure 2. Response surfase plot for the color reduction as a
function of the Methylene blue concentration and time. The
pH was fixed at 7.5.
Table 2. Second-order model equation for the response
surface fitted to the experimental data points obtained in
the direct ozonation of organic dye solutions as a function of
pH (1), NaCl concentration (2) and time (3).
Coefficient Rcolor
β0 82.06410
β1 2.47667
β2 0.22735
β3 0.89928
β12 0.00102
β13 0.00405
β23 0.00078
β11 0.18457
β22 0.00177
β33 0.00604
R2 67.5
It was found that for experimental conditions of MB
concentration 50 mg/L and reaction time 60 min, the
color reduction reaches values close to 100%, regardless
the pH assayed. Thus, pH is the experimental variable
that presents less influence on the color reduction. Ac-
cording to the obtained model, it was possible to optim-
ize the experimental conditions that should provide
maximum values of color reduction. These experimental
conditions were: pH = 3.3, MB concentration = 8.6 mg/L
and reaction time = 74.3 min. The expected color reduc-
tion would be 107%. Under a physical point of view, this
mathematical value implies a total color reduction. In
order to validate the optimization proposed, an extra ex-
periment was done under the optimum conditions. The
color reduction obtained was 99.4%, what means a devi-
ation of the optimum expected value of 0.6%.
3.2. Catalyst-Assisted Ozonation Process
Figure 3 shows the absorbance evolution with the time
reaction course for all the catalysts assayed as well as for
an experiment without any catalyst to make the proper
comparison. Initial absorbances at 665 nm for all expe-
riments are in a range of (12.57 - 13.27), this small dis-
persion was expected since at t = 0, the absorbance
should be the absorbance that presents the MB feed solu-
tion of 100 mg/L. Evolution with all catalysts follows the
same decreasing trends but with different slopes.
The r eduction color of th e MB feed solution with time
is depicted in Figure 4. Catalyst that sh owed lowest col-
or reduction response after 15 min was CuSO4·5H2O,
whilst the best catalyst at the end of the treatment is by
far, the CuSO4.
When no catalyst was used, the color reduction is lo-
cated among values obtained by catalysts until a reaction
time of 10 min, afterwards, the color reduction shown is
clearly l ower exce pt by the experim e nt wit h CuSO4·5H2O.
Once the experiment was over, the highest color re-
duction was shown by the CuSO4 reaching values up to
68.5%. Regarding the color reduction shown by the ex-
periment without catalyst (only with ozone) the maxi-
mum values were 41.0%. Comparing both maximum
color reduction with CuSO4 catalyst and without catalyst,
it was found differences of color reduction of about 67.1%
for the CuSO4 catalyst. Catalyst doses assayed had a de-
terminant effect on the color reduction after 15 min of
reaction time (Figure 5).
Figure 3. Absorbance variation with the reaction time
course with differents catalysts and without catalyst. Cata-
lyst dose fixed at 200 mg/L.
[MB] (mg/L)
Color removal (%)
Time (min)
020406080100 020 40 60 80 100 120
Copyright © 2013 SciRes. MSCE
Figure 4. Color reduction variation with the reaction time
course with differents catalysts and without catalyst. Cata-
lyst dose fixed at 200 mg/L.
Figure 5. Effect of the CuSO4 catalyst dose on the color
4. Conclusions
For the direct ozonation treatment, variables studied (pH,
[MB], t) had different effects on discoloration rate. Time
was the most significant variable and pH presented low-
est influence on color reduction. The optimized experi-
mental conditions to provide maximum discoloration (pH
= 3.3; [MB] = 8.6 mg/L and time = 74.3 min) were suc-
cessfully validated with a deviation of 0.6%.
Regarding the catalyst-as siste d o zon ation , it wa s f ound
that CuSO4 catalyst gave better color reduction if com-
pared with other catalysts assayed (CuSO4 > TiO2 > Ni-
SO4·6H2O > ZnO > ZnSO4·7H2O > Ag2SO4 > Cu-
SO4·5H2O) and presented a 67.1% of color reduction vs.
the 41.0% reached with the experiment without catalyst
at the same experimental conditions (pH = 5.5; [MB] =
100 mg/L; t = 15 min). In addition, catalyst dose had a
determinant effect on color reduction at 15 min of reac-
tion time.
From these results, further and deep studies to optim-
ize color reduwction rates as a function on dose and prize
of catalyst are proposed as next research steps.
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