Azo dye degradation from textile effluents has been the objective of research for several years due to the increasingly pollution problem that they generate. For the removal of these compounds, it has been applied different kind of process, since the physicochemical to biological, and has been degraded in diverse reactors. However, is a continuous search for an efficient, low cost and environmental impact to eliminate this problem. This presentation shows one part of the contribution to development a new process for treat waste water from textile industries that present an ecological problem.

1. 65 th CANADIAN CHEMICAL CONFERENCE
OCTOBER 4-7, 2015
CALGARY, ALBERTA, CANADA
Octavio OcampoThe man evolution
DEPARTAMENTO DE
INGENIERÍA QUÍMICA

2. Proposed Pathways for the Reduction of a
Reactive Azo Dye and kinetic reaction in an
Anaerobic Fixed Bed Reactor in an Up flow
Linda V. González-Gutiérrez , Eleazar M. Escamilla-Silva
65th Canadian Chemical Engineering Conference

3. Introduction
Azo dye degradation from textile effluents has been the objective of
research for several years due to the increasingly pollution problem that
they generate. For the removal of these compounds, it has been applied
different kind of process, since the physicochemical to biological, and has
been degraded in diverse reactors. However, there is a continuous search
for an efficient, low cost and low environmental impact process to
eliminate this problem.

4. Red reactive dye 272
MOLECULE TYPE USED
 Highly soluble colouring in water
 Slightly biodegradable
 Not chemically pure
 It has not been studied
S
O
O
O-S
O
O
-
O
OHNH
N
N
N
N
Cl
N
N
S
O
O
HO
N
H
Br
Br
O
Na Na

5. PROCESSES FOR AZO DIES REMOTION
PHYSICOCHEMICAL:
• MEMBRANE FILTRATION
• COAGULATION/FLOCULATION
• PRECIPITATION
• FLOTATION
• ADSORPTION
• ULTRASONIC MINERALIZATION
• PHOTOCATALYTIC DEGRADATION
• ELECTROLYSIS
• OXIDATION
• CHEMIAL REDUCTION

6. BIOLOGIC TREATMENT
• BIOSORTION WITH FUNGUS AND BACTERIAS
• ANAEROBIC DEGRADATION
• AEROBIC DEGRADATION
• COMBINED PROCESS ANAEROBIC/AEROBIC
ANAEROBIC REACTOR
•Co In  5.2 g/l 5200 ppm
•HRT  6-10 DAYS
•T  37°C
•SUPPORT R1 Y R2 GCA R3
ARENA
•DEGRADATION R1 75% R290%
R3100%
•OPERATION TIME
•INOCULUM  COW MANURE

7. Energy flow scheme of biological
processes
Anaerobic
Aerobic
100 %
(QOD)
Organic
Material
O2
H2O + CO2
Energy
Cells
CH4 + H2O
Cells
90 %
65 %
10 %
35 %

8. Objetive
 To study the degradation kinetics of reactive red
272 azo dye, in flask test and in an upflow
anaerobic fixed bed reactor.
 To obtain a representative kinetic model that can
be applied to high concentrations.
 To explain the reaction mechanism for the
degradation of the dye, identifying the products
in the reactor effluent.

9. Model Author Dye Process Co**
1st order Hu (1998) Reactive type batch, anaerobic 100 mg/L
pseudo 1st order Klančnik (2000) Cibacron Scarlet LS-
2G
batch 100 mg/L
1st order autocatalysis van der Zee et al
(2000)
Acid orange 7 batch, anaerobic with
antraquinone*
0.1-0.3 mM
1st order Willetts and Ashbolt
(2000)
Reactive red 235 UASB 50 mg/L
1st order Cruz and Buitrón
(2001)
Disperse blue 79 Biofilter anaerobic/aerobic 25-150 mg/L
1st order van der Zee et al
(2001)
Reactive red 2 UASB with antraquinone
AQDS*
200 mg/L
Cero order,
Michaelis-menten
Field and Brady (2003) Mordant yellow 10 Batch, anaerobic with
riboflavin*
200 mg/L
1st order autocatalysis Méndez-Paz et al
(2003)
Acid orange 7 batch and semi-continuous,
anaerobic
100-300 mg/L
1st order Yatmaz et al (2004) Remazol red RR photocatalysis 150 mg/L
Michaelis-menten Ramalho et al (2004) diverse batch with yeast 0.2 mmol/L
1st order Nikolova and Nenov
(2004)
Schwarz GRS Batch anoxic and anaerobic 10-100 mg/L
1st order dos Santos et al
(2005)
Reactive red 2 and
reactive orange 14
batch, anaerobic with
riboflavin*
0.3 mM
1st order Maas and Chaudhari
(2005)
Reactive red 2 Anaerobic
semi-continuous
100-200 mg/L
2nd and 1st order Sponza and Işik (2004) Direct black 38 batch
200-800
mg/L
Reduction Kinetics of azo dyes

10. Methodology

11.  Solids: gravimetric
 DQO: closed reflux
 Absorbance: 506 nm UV/Vis
 Other analytic techniques
 Identification of products:
 Extraction with Ethyl acetate
 Rotatory evaporator
 CG-MS
 Kinetic test in agitated flask (with activated carbon)
250 mL
1 g AC
w/wh 1 g/L Dextrose
5 mL sludge (6.6 g/L
TS)
0 to 96 h
Abs
DQO
Mechanical shaker
30oC
samples 3-96 h
Factors
Levels
-1 1
Q feeding flow (mL/min) 18 32
Ci red dye (mg/L) 250 500
Ci dextrose (mg/L) 500 1000
Ci yeast (mg/L) 500 1000

12. Effluent
tank
Feeding
tank Water Bath
Influent
30oC
Water Bath
effluent
Biogas
effluent
Effluent
tank
Feeding
tank Water Bath
Influent
30oC
Water Bath
effluent
Biogas
effluent
Anaerobic fixed bed reactor
Methodology
 Reactor in continuous operation test
Work volume, L 3
Inside diameter, cm 6
Inside diameter of the settle, cm 9.5
Total Longitude, cm 105.5
Initial porosity of the bed 0.53
Steady state porosity 0.19
Fixed bed volume, L 1.24
Superficial velocity (average), cm/min 0.52
Volumetric flow (average), mL/min 18
TRm (average), min 206.25

13. Results
0
1
2
3
4
5
6
200 300 400 500 600 700
Wavelength
Absorbance
0 h
48 h
72 h
0
1
2
3
4
5
6
200 250 300 350 400 450 500 550 600 650 700
Wavelength
Absorbance
influent
effluent
UV/Vis scan of the synthetic wastewater at the influent
And effluent of the reactor. Co = 250 mg/L
UV/Vis scan in batch analysis for an
initial dye concentration of 300 mg/L

14.  2 Mechanism: biosorption and biodegradation
 The reduction reaction rate depends on:
 Carbon source (primary substrate)
 Dye concentration
 Structure and fuctional groups
in the molecule
 Azo bond number
 Extracellular enzymes
 Is an extracellular process !!!

15. Granulation process

16. 01 2 ( )A
A A A A A
dC
r k C k C C C
dt
    
0 2
0
0 21
0 0
1 2
1 2
( )A k
A k
C t
AA
C tk t
A A
e k C kC
C k e C k e



 Change in reaction order
 Representative to high dye
concentration
 Kinetic model for the dye reduction (batch
analysis)
Experimental data and COK model fit for 250 and 500 mg/L test
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 20 40 60 80 100
C/Co
time, h
250 mg/L
COK 250
500 mg/L
COK 500

17. COK: Change in Order Kinetics
Ra2: multiple correlation coefficient
 Kinetic test results in batch analysis
Test
No.
CA0
mg/L
Dex
mg/L
k1
h-1
k210-3
L/mg h
% R
Color
% R
DQO
Ra2
COK
CM100
CM250
CM300
CM400
CM500
100
250
300
400
500
-
-
-
-
-
1.164
0.451
0.349
0.201
0.155
10.30
1.680
1.080
0.540
0.333
100.0
98.98
99.59
94.06
91.29
80.00
62.50
62.50
75.00
50.00
0.9948
0.9952
0.9899
0.9854
0.9753
CDx100
CDx250
CDx300
CDx400
CDx500
100
250
300
400
500
1000
1000
1000
1000
1000
1.551
0.403
0.356
0.228
0.252
13.63
1.490
1.090
0.589
0.564
100.0
99.16
99.74
95.96
94.40
15.63
75.00
42.50
53.13
66.25
0.9988
0.9972
0.9933
0.9891
0.9431

18. 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
100 200 300 400 500
CA0, mg/L
K1,h-1 with Dex
Without Dex
0
2
4
6
8
10
12
14
100 200 300 400 500
CA0, mg/LK2x10-3,L/mgh
with Dex
Without DexInitial dye concentration and dextrose (Dex) effect
in the first order kinetic constant k1 in COK
Initial dye concentration and dextrose (Dex) effect in the
second order kinetic constant k2 in COK

19.  0
a
A
AS
b e b aC
C
a

 

1 2 0
2
2 0
A
A
VTRm
Q
a k k C
b k C
  
 

Kinetic model parameters applied to the reactor
 Kinetic model to predict dye decoloration in the reactor
Co
dye
CAS
real
OL
Kg/m3d
TRm a b CAS
predicted
Error
abs
olut
e
250
300
300
350
350
400
400
500
500
6.122
5.095
10.57
6.343
8.217
8.053
10.29
14.33
11.73
8.546
12.71
11.80
12.57
7.680
9.076
7.859
10.47
8.378
4.044
4.231
4.231
4.583
5.500
5.500
5.864
5.500
5.500
1.139
1.142
1.142
1.145
1.145
1.148
1.148
1.154
1.154
3.848
5.541
5.541
7.543
7.543
9.852
9.852
15.39
15.39
5.849
7.212
7.212
8.398
7.223
9.293
9.051
14.19
14.19
0.045
0.415
0.318
0.324
0.121
0.154
0.120
0.010
0.210
OL: Organic Load

20. But after studying the kinetic part we asked the
question, as microorganisms act against these dyes?
But is a consortium of microorganism the the problem
is complex because there are thousands of enzymes
involved, but we can get the chemical process
something?

21.  Enzymes involved in the reaction:
 S-Adenosylmethionine
 Coenzyme A, Thymidine
 Acil-CoA dehydrogenase y 4-Hydroxybutyryl-CoA
dehydratase Azo bond number
deprotonation one-electron oxydation deprotonation
 Pyruvate:ferredoxin oxidoreductase y Methyl-CoM reductase
Coenzyme A, Thymidine
 Benzoyl-CoA reductase
 Bacteria that can reduce aromatics
 sulfate-reducing
 nitrate-reducing, denitryfying bacteria
 Fe(III)-reducing

22.  Degradation mechanism of reactive red 272
O
HO OH
HO OH
HO
dextrose
Substrate
Oxidated
substrate
NADH-NAD+
NADPH-NADP+
Activated carbon
surface groups
S
O
O
O-S
O
O
-
O
OHNH
N
N
N
N
Cl
NH3
+
Na Na
+
H3N
S
O
O
HO
N
H
Br
Br
O
+
4 e-
2 H+
4H+
S
O
O
O-S
O
O
-
O
OHNH
N
N
N
N
Cl
N
N
S
O
O
HO
N
H
Br
Br
O
Na Na
Ar-N=N-Ar’ + 4H+ + 2NAD(P)H Ar-NH3
+ + Ar’-NH3
+ + 2NAD(P)+
Ramalho and col. (2004)

23. Mass spectra of naphthalene
, 19-May-2006 + 23:48:06LV10 met B
10.00 20.00 30.00 40.00 50.00 60.00 70.00
Time0
100
%
27 Mar met B Scan EI+
TIC
1.27e10
2.27
18.97
3.61
11.443.73
9.41
Chromatogram of a sample of water in reactor effluent,
obtained at high dye concentration
, 19-May-2006 + 23:48:06LV10 met B
51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131
m/z0
100
%
27 Mar met B 4316 (21.698) Cm (4312:4322-4305:4330) Scan EI+
2.53e6128
127
51 6463
52 61
55
102747365 71
75 77 101
8786
83 9189 98
129
130

24. , 03-Sep-2005 + 19:42:15
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
m/z0
100
%
linda32 9132 (23.525) Cm (9124:9160-9116:9200) Scan EI+
1.09e843
421514
12
292816
18 26
2519 41
31
45
44
60
46
47
56 61
62
72 87
Pico a 23.53
10.15 20.15 30.15 40.15 50.15 60.15 70.15
Time0
100
%
0
linda32 Scan EI+
TIC
3.13e10
2.40
2.48
9.144.08 23.53
Chromatogram of a sample of water in reactor effluent,
obtained under best operation conditions in the reactor
Mass spectra of acetic acid

25.  In general the aromatic mineralization of substrates is given by the reaction
Organic matter CH4 + CO2 + H2 + NH3 + H2S
Anaerobic degradation mechanism of Naphthalene and
substituted naphthalene (Meckenstock et al, 2004)
 How the aromatic compounds are degraded in anaerobic environment?
COOH
O
O-
O
-
O
COOH
COOH
COOH
COOH
COOH
O
COOH
CO2

26.  Aromatic compounds found in the reactor effluent as the dye
concentration was increased in the influent
HO HO
OHO
O
OH
NHO
HO
O
O
O
OO
HO
Benzenepropanoic acid
2-phenylethanol p-cresol
2-benzylmalonic acid
(R)-2-acetamido-3-
phenylpropanoic acid
1,2,3,4-tetrahydro
naphthalene
naphthalene
1-isobutyl-4-
methylbenzene
1-ethylbenzene p-xylene m-xylene 1-ethyl-3-methyl
benzene
1-(4-ethylphenyl)
ethanone
ethyl 2-phenylacetate1-ethyl-2,4-dimethyl
benzene
1,2,3,4-tetramethyl
benzene

27. O
NH2
O
OO
OH
1,2-bencenedicarboxylic acid
mono(2-ethylhexil)ester
OH
O
HO
O
HO
O
OH
NH4
+
ammonium
O
OH
O
OH
O
OH
O
HO
Bezeneacetic acid
O
OH
hexanoic acid acetic acid 3-hydroxy-
butan-2-one
4-methyl-
pentan-2-ol
3-methylbutanamide
4-hydroxy-4-
methylpentan-2-one
butyric acid
pentanoic acid
4-methylpentanoic acid
O
OH
O
OH
propionic acid
isobutyric acid
C OO
Carbon dioxide
O
O
NH2
OH
HO
3,3-dimethylbutanamide 2-isopropoxypropane
pent-4-en-2-ol ethanol
 Identified compounds in the reactor effluent at good operation conditions

33. Conclusions
 The presented anaerobic process was effective to degrade reactive red
272.
 The proposed kinetic model fits very well the kinetics of dye reduction in
batch and continuous even in high concentration.
 k1 (h-1) and k2 (L / mg h) were increased with the use of dextrose as a
primary substrate and both are reduced when the dye concentration was
raised.
 Dye removal was improved with aided of dextrose.
 The main products identified in the reactor effluent, were: carboxylic acids,
amides, and alcohols; however, high dye concentrations and not enough
TRm take to a greater amount of aromatic compounds that can be toxic.
 The operation conditions should be ensured ~ 50% DQO removal.
The mechanism of partial mineralization involves specific enzymatic
reactions, probably by radicals, that involve the transfer of electrons and
hydroxyl and carboxyl groups.

34. ACKNOWLEDGEMENTS
SAGARPA-CONACYT GRANT : 2011-15-174560
ALL THE ORGANIZERS

35. THANKS FOR YOUR KIND ATTENTION

36. Up flow Anaerobic Fixed Bed Reactor
Wastewater flow feed
Treated waste water out Temperatura Checking
Biogas out
Water in for temperature control
Syntherized glass filter

37. S
zAC
z zAC 
convection dispersion
convection dispersion
z
AdC
dt
Bioparticle
RB
RC
r
=RB-RC
I
II
;Ap Ab
dC dC
dt dt
CAL CAb CAp
II I
Km

UAFB
Reactor
LC = 57.5 cm
Lf = 48 cm
CAS
CAi
CA0

38. I CAp core
II CAb biofilm
= 0
 = 1
 = r/RC
 = r/RC
C
B C
r R
R R





39. MATHEMATICAL SURVEY
• Residence time distribution
• To carry out the hydraulic characteristics of the reactor and to obtain the
residence time distribution, it was taken as a tracer a lithium chloride
solution.
2
2
1
2
C
Teórico
D
d
TR uL

  00
00
( )
( )







t C C dt
HRT
C C dt
00
00
( )
( )







t C C dt
HRT
C C dt
0
0
00
( )
( )







t C C dt
HRT
C C dt
2
2
1
2
C
Teórico
D
d
TR uL

 
dD
uL
NPe
1

dD
uL
NPe
1

0.875
Re1.01D d u L N  3
1
2
1
Re6.02 ScSh NNN 
P
Sheff
m
d
ND
k 

40. Effectiveness factor
1
1
eb
k
D
 
2 0
2
A
eb
k C
D
 
 
 
1 2
1 21 1
1 1 1
2 2 2 2 2
0 0 0
2 24
1 13
4 3 3
 
 
    
   
    
  A A b b b b L b A
A b b b b L bA A
R d R d Fo Fo d R
R Fo FoR R 
 
          

   

41. RESULTS AND DISCUSSIONS
Parameter HRT1 HRT2 HRT3 HRT4 HRT5 HRT6
RTm (min) 57.264 66.203 66.203 42.412 42.412 42.412
uL (cm/s) 0.0735 0.0631 0.0631 0.0985 0.0985 0.0985
NReL 54.962 47.468 47.468 74.096 74.096 74.096
BoL 11029.2 9461.54 9461.54 14769.2 14769.2 14769.2
dL 2.864 2.255 2.407 2.332 1.208 0.413
DL (cm2
/s) 10.026 6.828 7.287 11.022 5.709 1.953
PeL 0.349 0.443 0.415 0.429 0.828 2.420
ShL 45.403 42.246 42.246 52.283 52.283 52.283
kL (cm/s) 0.0176 0.0164 0.0164 0.0203 0.0203 0.0203

42. The hydraulic behavior of the reactor is
approximated to a plug flow reactor with axial
dispersion, and this effect is improved when the
volumetric flow (Q) is increased, therefore, when Q
is increased, the hydraulic of the reactor is closer to
a plug flow behavior.
The HRT was from 1.6 to 1.8 times the RTm at lowest
volumetric flow in the reactor, and from 1.1 to 1.3
times at highest volumetric flow.

43. 0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 400 600 800
P(t)
time, h
P(t)1 E1
P(t)2 E2
P(t)3 E3
P(t)4 E4
P(t)5 E5
P(t)6 E6
 
w
tt
f
sffExpExpaytP
C


1
110 )1()()(

44. 0.0
0.2
0.4
0.6
0.8
1.0
0 0.5 1
z
CA0 100 mg/L
CA0 250 mg/L
CA0 400 mg/L
CA0 500 mg/L
0.15
0.25
0.35
0.45
0.55
0.65
0.75
0.85
0.95
0 0.2 0.4 0.6 0.8 1

z
226.195 min
81.429 min
75.398 min
67.859 min
54.287 min

45. 0.0
0.2
0.4
0.6
0.8
1.0
0.00 0.05 0.10
Wa(Cadim)
Bioparticle radius
t  0.4
z
0.0
45
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.00 0.05 0.10
Wa(Cadim)
Bioparticle radius
t  1
z
0.04
5
0.0
0.2
0.4
0.6
0.8
1.0
0.00 0.05 0.10
Wa(Cadim)
Bioparticle radius
t  2
z
0.0
45
0.0
0.2
0.4
0.6
0.8
1.0
0.00 0.05 0.10
Wa(Cadim)
bioparticle radius
t  5
z
0.0
45

46. 0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0.00 0.02 0.04 0.06 0.08 0.10

bioparticle radius
226.195
min
81.429 min
75.398 min
0.0
0.2
0.4
0.6
0.8
1.0
0 0.2 0.4 0.6 0.8 1
L
z
Lf = 48
cm
Lf = 60
cm
Lf = 100
cm
Lf = 120
cm
Lf = 148
cm

47. DL (cm2
/min) 423.4 1
2 a
1.061
u (cm/min) 3.786 2
2 b
1.276
Km (cm/min) 0.984 1
c
1.030
Dep (cm2
/min) 2.5810-5
2
d
1.130
Deb (cm2
/min) 2.5810-3
 2
k1 (min-1
) 3.046  100
k2 (L/mgmin) 1.4710-2
Bi 34.27
asb (cm2
/cm3
) 36.81 Bm 459.22
Fop 0.091 dL 2.33
Fob 36.404

48. The proposed mathematical model for a fixed bed bioreactor was able
to predict the concentration profiles along the reactor and within the
bioparticle (carbon core and biofilm) for the degradation of a reactive
red azo dye using a kinetic model with a change in reaction order.
The profiles at different influent concentration showed an asymptotic curve
with a major activity of reaction in the lower zone of the reactor, and this
downward concentration is reduced as the influent dye concentration is
augmented. By the other hand, RTm does not have much influence in the
concentration profile along the reactor.
The profiles within the bioparticle illustrate the saturation of the particle and reflect the zone
of reaction in the biofilm; it can be seen the differences in the concentration values with
regard to the reaction zone along the reactor. The saturation rate of the bioparticles changes
with the RTm, at a larger time, the mass transfer is improved and the bioparticles are
saturated faster, without affecting the reaction.
CONCLUSSIONS

49. The calculation of the effectiveness factor showed that the rate
of reaction changes with regard to the position at the height of
the reactor, and depends of the dye diffusion when dye
concentration increases.
The proposed mathematical model will allow us to scale up the azo-dye
removal lab experiments to industrial bioreactors, and it can be
straightforward used for other reactions.