UNIVERSITY OF CALGARY Study of the Pyrolysis of Straw Biomass

Transcription

UNIVERSITY OF CALGARY
Study of the Pyrolysis of Straw Biomass for Bio-oil Production
and its Catalytic Upgrading
by
Aqsha Aqsha
A THESIS
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY IN CHEMICAL ENGINEERING
GRADUATE PROGRAM CHEMICAL AND PETROLEUM ENGINEERING
CALGARY, ALBERTA
APRIL 2016
© Aqsha Aqsha 2016
Abstract
This thesis presents a comprehensive study of the pyrolysis of lignocellulosic biomass (sawdust,
wheat, oat, flax and barley straws). In the first part of the study, the pyrolysis of sawdust was
observed using a thermogravimetric analyzer (TGA), in order to understand the devolatilization
process and to obtain its global kinetic parameters. The influences of particle size, initial weight
of the sample and heating rate on the devolatilization of sawdust particles were assessed. It was
observed that the pyrolysis of sawdust differed significantly with variations in heating rate. As
the heating rate increased, the char yield also increased. The kinetic parameters, including
activation energy (E), frequency factor (k0) and order of reaction (n), for the two stages
considered in the model were: E A2 = 79.53 (kJ/mol), EA3 = 60.71 (kJ/mol); k02 = 1.90 × 106
(1/min), k03 = 1.01 × 103 (1/min); n2 = 0.91, n3 = 1.78, respectively.
In the second part of the study, the pyrolysis of several Canadian straw biomasses was studied
using a TGA and a bench-scale horizontal fixed-bed reactor. The effects of various catalysts on
product yields are discussed. When using zeolite catalysts, the bio-oil and bio-char yields of the
straw pyrolysis increased to 46.44% and 38.77%, respectively, while the gas yield was decreased
to 13.65%. The use of the catalyst zeolite ZY-SS had the most significant effect on overall biooil and bio-char yields, increasing the bio-oil yield by about 2% and the bio-char yield by 8%.
A screening of different catalysts unveiled that Ni-Mo/TiO2 was the most active catalyst. The
structure was investigated using Brunauer-Emmett-Teller (BET) surface area showed that the NiMo/TiO2 catalyst presented a higher surface area and more optimal mesopores than Ni-V/TiO 2.
ii
Based on the results, it appears that the significant hydrodeoxygenation (HDO) activity for both
the catalysts attributed to a high dispersion of metals and acidic sites, which was affected by the
interaction between the nickel and the titania support. The activation energy (E) values for
guaiacol reactions over Ni-Mo/TiO2 and Ni-V/TiO2 were 93.6 and 98.4 kj/mol, respectively; and,
the E values for anisole reactions over Ni-Mo/TiO 2 and Ni-V/TiO2 were 80.9 and 53.9 kj/mol,
respectively.
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Acknowledgement
Alhamdulillah. First and foremost, I would like to express my highest gratitude to Allah The
Creator and Muhammad His Messenger, for providing me with the ability to think and to invent
as well as His guidance throughout my entire life.
I would also like to express my sincere gratitude to my supervisor, Dr. Nader Mahinpey, for his
continuous support of my PhD study and research, and for his patience, advice and immense
knowledge. His guidance has helped me throughout the research and writing of this thesis. I
cannot imagine having a better supervisor and mentor for my PhD study.
My sincere thanks also goes to Dr. Lakshmi Katta, Dr. Puli, Dr. Thila, Dr. Feridoun and Dr.
Karami who provided me with opportunities to gain knowledge, as well as training during my
early days in the laboratory. Without their valuable support, expertise and input, it would not
have been possible to conduct this research.
My sincere thanks goes to Mansour Tijani for his frequent help and discussions during the last
few months of my research. I also want to mention my sense of gratitude to Ludivine Grass,
Camilla Fernandes De Oliveira and Aurore Coussirat-Bourg for their contribution to the research
during their internships in the laboratory.
I thank my fellow lab mates (Ranjani, Hashem, Ehsan, Shuba, Alireza, Kavan, Bahareh, Arturo,
Mansour, Crystal and Marlon) for the stimulating discussions, the long hours of working
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together before deadlines, and all the fun we have had over the last six years. I also thank my
fellow internship students (Aruna, Rebecca, Andy, Ragav, Marco, Thais, Varada, Lucas, Felipe,
Diego, Maria, Samantha, Yifei, Qinran, Tommy and Bruce), who spent their time with me during
laboratory sessions. I also thank Spensix 3B, Badjitoe, Kakegawa, Soulmates, TK2000,
Himatekers, Bukaka Fellow (Tongkeng) and all my teachers for their moral support and their
interaction with me during my PhD study.
Last but not the least, I would like to thank my wife Belladonna Maulianda, my son Nafi
Rabbani and my family for supporting me spiritually throughout the writing of this thesis and my
life in general.
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Dedication
I dedicate this work to my beloved wife, son and family.
vi
Table of Contents
Abstract ........................................................................................................................... ii
Acknowledgement ......................................................................................................... iv
Dedication ...................................................................................................................... vi
Table of Contents .......................................................................................................... vii
List of Tables ...................................................................................................................x
List of Figures and Illustrations .................................................................................... xii
List of Symbols, Units, Chemical Formulas and Abbreviations ...................................xv
CHAPTER 1: INTRODUCTION .......................................................................................1
1.1 Overview ....................................................................................................................1
1.2 Literature Review ......................................................................................................4
1.2.1 Introduction to Biomass ....................................................................................4
1.2.2 Pyrolysis of Lignocellulosic Biomass ...............................................................7
1.2.2.1 Slow (Conventional) Pyrolysis ................................................................8
1.2.2.1 Fast Pyrolysis ...........................................................................................9
1.2.3 Kinetic Study of Pyrolysis of Biomass ............................................................10
1.2.4 Pyrolysis Behaviors of Lignocellulosic Biomass ............................................11
1.2.5 Bio-Oil Production from Lignocellulosic Biomass .........................................12
1.2.6 Bio-Oil Upgrading ...........................................................................................13
1.3 Objectives ................................................................................................................15
1.4 Organization of the Thesis .......................................................................................16
1.5 Outcome of the Thesis .............................................................................................18
1.5.1 Published peer-reviewed journal papers and contribution: .............................18
1.5.2 Submitted peer-reviewed journal papers and contribution:.............................21
1.5.3 Published peer-reviewed conference proceedings and contribution: ..............22
1.6 References ................................................................................................................25
CHAPTER 2: RESEARCH METHODOLOGY AND SETUP .......................................30
2.1 Study of Biomass Pyrolysis and its Devolatilization Kinetics Using TGA.............31
2.1.1 Ultimate (Elemental Analysis) using Elemental Analyzer ..............................32
2.1.2 Proximate Analysis using TGA .......................................................................33
2.1.3 Thermal Degradation (Devolatilization) using TGA ......................................34
2.2 Bio-oil Production from Biomass Using Bench-scale Pyrolysis Reactor................35
2.3 Bio-oil Upgrading Using Catalyst ...........................................................................38
2.4 References ................................................................................................................39
CHAPTER 3: STUDY OF SAWDUST PYROLYSIS AND ITS DEVOLATILIZATION
KINETICS ................................................................................................................40
3.1 Presentation of the Article .....................................................................................40
3.2 Abstract ..................................................................................................................41
3.3 Introduction ............................................................................................................42
3.4 Experimental Section .............................................................................................45
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3.4.1 Materials ..........................................................................................................45
3.4.2 Proximate Analysis ..........................................................................................45
3.4.3 Pyrolysis Experiment using TGA ....................................................................46
3.5 Results and Discussions .........................................................................................46
3.5.1 Ultimate and Proximate Analysis of Sawdust Sample ....................................46
3.5.2 Pyrolysis of Sawdust .......................................................................................49
3.5.2.1 Effect of Particle Size ............................................................................50
3.5.2.2 Effect of Initial Sample Weight .............................................................52
3.5.2.3 Effect of Heating Rate ...........................................................................54
3.5.2 Kinetics of Sawdust Pyrolysis .........................................................................56
3.6 Conclusions ............................................................................................................60
3.7 Acknowledgement .................................................................................................61
3.8 References ..............................................................................................................62
CHAPTER 4: CATALYTIC PYROLYSIS OF STRAW BIOMASSES (WHEAT, FLAX,
OAT AND BARLEY STRAW) AND THE COMPARISON OF THEIR PRODUCT
YIELDS ....................................................................................................................65
4.2 Abstract ..................................................................................................................67
4.3 Introduction ..............................................................................................................68
4.3 Experimental Section .............................................................................................70
4.4.1 Raw Biomass Sample and catalysts ................................................................70
4.4.2 Proximate and Elemental Analysis ..................................................................71
4.4.3 Pyrolysis Experiment.......................................................................................72
4.4.4 Product Analysis and Characterization ...........................................................74
4.4 Results and Discussions .........................................................................................74
4.5.1 Proximate and Elemental Analysis ..................................................................74
4.5.2 Pyrolysis of Raw Biomass ...............................................................................78
4.5.3 Catalytic Pyrolysis of Raw Biomasses ............................................................81
4.5.4 Analysis of Pyrolysis Products ........................................................................81
4.5 Conclusions ............................................................................................................87
4.6 Acknowledgement .................................................................................................88
4.7 References ..............................................................................................................89
CHAPTER 5: CATALYTIC HYDRODEOXYGENATION OF GUAIACOL AS LIGNIN
MODEL COMPONENT USING NI-MO/TIO2 AND NI-V/TIO2 CATALYSTS ...92
5.2 Abstract ..................................................................................................................93
5.3 Graphical Abstract .................................................................................................94
5.4 Introduction ............................................................................................................95
5.5 Experimental ..........................................................................................................97
5.5.1 Catalyst Preparation.........................................................................................97
5.4.2 Characterization Studies ..................................................................................98
5.4.3 Reaction Study: HDO of Guaiacol ..................................................................99
5.6 Results and Discussions .......................................................................................100
5.5.1 Catalyst Properties .........................................................................................100
5.5.2 Catalytic Activity...........................................................................................110
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5.7 Conclusions ..........................................................................................................126
5.8 Acknowledgement ...............................................................................................127
5.9 References ............................................................................................................128
CHAPTER 6: UPGRADING OF ANISOLE COMPONENT BY NI-MO/TIO2 AND NIV/TIO2 CATALYSTS: SYNTHESIS, CHARACTERIZATION AND KINETIC
MEASUREMENTS ................................................................................................131
6.1. Presentation of the Article ...................................................................................131
6.2. Abstract ................................................................................................................132
6.3 Introduction ............................................................................................................133
6.3. Experimental Section ...........................................................................................134
6.4.1 Catalysts Preparation .....................................................................................134
6.4.2 Characterization Studies ................................................................................135
6.4.3 Reaction Study: HDO of Anisole ..................................................................136
6.4. Results and Discussions .......................................................................................137
6.5.1 Structural Properties ......................................................................................137
6.5.2 Surface Analysis ............................................................................................140
6.5.3 Reaction and Kinetic Study of Anisole .........................................................145
6.5. Conclusions ..........................................................................................................154
6.6. Acknowledgement ...............................................................................................155
6.7. References ............................................................................................................157
CHAPTER 7: CONCLUSIONS AND SUGGESTIONS FOR FUTURE WORKS ......160
7.1. Relation between Chapters and Overall Achievement ........................................160
7.2. Conclusions ..........................................................................................................162
7.3. Suggestions for Future Work ...............................................................................165
APPENDIX A: LICENSE TO RE-PRINT ......................................................................166
A.1. License to re-print and re-use the content of WIT Publications (Chapter 3 & 4) 166
A.2. License to re-print of Chapter 3 – Study of Sawdust Pyrolysis and its Devolatilization
Kinetics ................................................................................................................168
A.3. License to re-print of Chapter 5 – Catalytic Hydrodeoxygenation of Guaiacol as
Lignin Model Component Using Ni-Mo/TiO2 and Ni-V/TiO2 Catalysts ............174
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List of Tables
Table 1.1 Typical elemental and water content of bio-oils from fast pyrolysis [4,5] ..................... 3
Table 1.2 Chemical composition of several types of biomass ........................................................ 6
Table 1.3 Typical properties of oils obtained through flash pyrolysis ......................................... 14
Table 3.1 Ultimate analysis of the sawdust in weight percentage ................................................ 46
Table 3.2 Proximate analysis of sawdust at different particle sizes ............................................. 48
Table 3.3 Char yield percentage for different values of particle size of the sample for sawdust
pyrolysis with initial weight of 10 mg and heating rate of 10 C/min. ................................. 52
Table 3.4 Char yield percentage for different values of initial weight of the sample for
sawdust pyrolysis with average particle size of 352 µm and heating rate of 10 C/min. ..... 52
Table 3.5 Char yield percentage for different values of heating rate of the sample for sawdust
pyrolysis with average particle size of 352 µm and initial weight of 10 mg. ....................... 54
Table 3.6 Weight loss and ultimate devolatilization yield of the devolatilization events with
average weight prior to devolatilization of 9.91 mg at different heating rates. .................... 58
Table 3.7 Kinetic parameters of the three events considered in the kinetic model. ..................... 59
Table 4.1 Chemical composition of wheat, oat, flax and barley straw samples ........................... 70
Table 4.2 Elemental composition and surface area data of the catalysts ...................................... 71
Table 4.3 Proximate and elemental analyses of biomasses .......................................................... 75
Table 4.4 Data comparison between raw biomass and its bio-char product ................................. 76
Table 4.5 Product yield comparison of the pyrolysis of wheat, oat, flax and barley straws
using a TGA .......................................................................................................................... 78
Table 4.7 Elemental analysis of bio-char produced from each biomass sample .......................... 79
Table 4.8 Proximate and CHNS analysis of bio-char products after pyrolysis ............................ 82
Table 4.9 Water content of bio-oil produced from pyrolysis ........................................................ 83
Table 4.10 Heating value (MJ/kg) of biomasses and its products ................................................ 83
Table 4.11 GC-MS analysis of bio-oil produced from straw biomass with and without
catalyst .................................................................................................................................. 85
x
Table 4.12 Micro-GC analysis of gas produced from wheat straw biomass with and without
catalyst .................................................................................................................................. 86
Table 5.1 Structural properties of metal–supported catalysts ..................................................... 104
Table 5.2 Structural properties of metal–supported catalysts ..................................................... 108
Table 6.1 Physico-chemical properties of Ni-Mo/TiO2 and Ni-Mo/TiO2 catalysts.................... 137
Table 6.2 Kinetic parameter of HDO reaction using Ni-Mo/TiO 2 and Ni-V/TiO2 .................... 154
xi
List of Figures and Illustrations
Fig. 1.1 Typical lignocellulosic biomass waste found in Canada (from left to right: wheat
straw, oat straw, flax straw and barley straw) ......................................................................... 2
Fig. 1.2 Devolatilization profile of biomass components [22] ....................................................... 8
Fig. 2.1 Diagram of the experimental setup .................................................................................. 30
Fig. 2.2 Schematic of pyrolysis experiment using TGA............................................................... 31
Fig. 2.3 Schematic of Perkin Elmer 2400 Elemental Analyzer [1] .............................................. 32
Fig. 2.4 TGA profile of calcium oxalate [2] ................................................................................. 34
Fig. 2.5 Experimental setup of bench-scale pyrolysis .................................................................. 35
Fig. 3.1 TG profile for proximate analysis of sawdust for the particle size of 250 µm. ............... 47
Fig. 3.2 Classification of devolatilization stages under nitrogen atmosphere. ............................. 49
Fig. 3.3 Pyrolysis curve of sawdust at different particle sizes of sample with heating rate of
10 °C/min and initial weight of 10 mg of sample. (a) TG profile and (b) DTG profile. ....... 51
Fig. 3.4 Pyrolysis curve of sawdust at different initial weights of sample with heating rate of
10 °C/min and particle size of 352 µm. (a) TG profile and (b) DTG profile. ....................... 53
Fig. 3.5 Pyrolysis curve of sawdust at different heating rates with particle size of 325 µm and
initial weight of 10 mg of sample. (a) TG profile and (b) DTG profile. ............................... 55
Fig. 3.6 Typical comparison of experimental data with predicted values at heating rate of 10
°C/min. .................................................................................................................................. 60
Fig. 4.1 Typical profile for proximate analysis using a TGA ....................................................... 72
Fig. 4.2 Thermogravimetric profiles of raw biomasses subject to pyrolysis. ............................... 73
Fig. 4.3 Location of straw biomasses and their biochar products on a Van Krevelen diagram. .. 77
Fig. 4.4 Product yields (wt%) from pyrolysis of straw biomass ................................................... 80
Fig. 4.5 Comparison of the product yields among the biomasses ................................................ 81
Fig. 5.1 X-ray diffraction patterns of anatase, Ni/TiO2, Ni-V/TiO2 and Ni-V/TiO2 before
reduction ............................................................................................................................. 102
Fig. 5.2 X-ray diffraction patterns of anatase, Ni/TiO2, Ni-V/TiO2 and Ni-V/TiO2 after the
reduction ............................................................................................................................. 103
xii
Fig. 5.3 TEM image of TiO2, Ni/TiO2, Ni-V/TiO2 and Ni-Mo/TiO2 catalysts ........................ 105
Fig. 5.4 Adsorption isotherms of fresh and reduced (a) TiO2 , (b) Ni-Mo/TiO2 and (c) NiV/TiO2 catalysts. Inset: Pore size distributions................................................................... 108
Fig. 5.5 TPD-NH3 profiles of TiO2, Ni/TiO2, Ni-V/TiO2 and Ni-Mo/TiO2 after the reduction
treatment ............................................................................................................................. 109
Fig. 5.6 Screening of catalysts. (a) Promoter effect: V, Mo, Cu, Fe. (b) Support effect: TiO 2,
Al2O3, ZrO2, Fe2O3, SiO2 for HDO of guaiacol. Reaction conditions: 300 °C, 1 mL of
guaiacol, H2 pressure of 100 psi, 5 h .................................................................................. 113
Fig. 5.7 Effect of catalyst on guaiacol conversion: Reaction conditions: 300 °C, 1 mL of
guaiacol, H2 pressure of 100 psi, 5 h. ................................................................................. 115
Fig. 5.8 Effect of Ni loading (0, 5, 10 and 20 wt%) on HDO of guaiacol. Reaction
conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi, 5 h..................................... 116
Fig. 5.9 Effect of temperature on HDO of guaiacol. Reaction conditions: 1 mL of guaiacol ,
H2 pressure of 100 psi, 5 h .................................................................................................. 117
Fig. 5.10 Pressure dependence on HDO of guaiacol (a) Ni-Mo/TiO2 and (b) Ni-V/TiO2.
Reaction conditions: 300 °C, 1 mL of guaiacol, 5 h ........................................................... 119
Fig. 5.11 Effect of reaction time on HDO of guaiacol (a) Ni-Mo/TiO 2 and (b) Ni-V/TiO2.
Reaction conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi ............................ 121
Fig. 5.12 Determination of order and rate constant by integral method: (a) Ni-Mo/TiO 2 and
(b) Ni-V/TiO2. Reaction conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi.... 123
Fig. 5.13 Effect of water on HDO of guaiacol: (a) Ni-Mo/TiO2 and (b) Ni-V/TiO2. Reaction
conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi, 5 h..................................... 126
Fig. 6.1 X-ray diffraction pattern of (a) TiO2, fresh Ni-Mo/TiO2 and Ni-Mo /TiO2 after the
reduction and (b) TiO2, fresh Ni-V/TiO2 and Ni-V/TiO2 after the reduction. .................... 138
Fig. 6.2 TEM images of Ni-V/TiO2 and Ni-Mo/TiO2 catalysts before (fresh, F) and after
reduction (R) ....................................................................................................................... 139
Fig. 6.3 Ni 2p spectra for Ni-Mo/TiO2 (fresh and reduced) and Ni-V/TiO2 (fresh and
reduced)............................................................................................................................... 141
Fig. 6.4 Ti 2p spectra for Ni-Mo/TiO2 (fresh and reduced) and Ni-V/TiO2 (fresh and reduced) 142
Fig. 6.5 Core level spectra of O 1s for Ni-Mo/TiO 2 (fresh and reduced) and Ni-V/TiO2 (fresh
and reduced) ........................................................................................................................ 143
Fig. 6.6 Mo 3d core level spectra for Ni-Mo/TiO2 (fresh and reduced) ..................................... 144
xiii
Fig. 6.7 V 2p core level spectra for Ni-V/TiO2 (fresh and reduced) .......................................... 144
Fig. 6.8 Effect of temperature on HDO of anisole. Reaction conditions: 1 mL of anisole, H 2
pressure of 100 psi, 6 h and using Ni-Mo/TiO 2. ................................................................. 146
pressure of 100 psi, 6 h and using Ni-V/TiO2. .................................................................... 146
Fig. 6.10 Effect of reaction time on HDO of anisole. Reaction conditions: 1 mL of anisole ,
H2 pressure of 100 psi, 300 °C and using Ni-Mo/TiO2....................................................... 147
Fig. 6.11 Effect of reaction time on HDO of anisole. Reaction conditions: 1 mL of anisole,
H2 pressure of 100 psi, 300 °C and using Ni-V/TiO2. ........................................................ 147
Fig. 6.12 Plots of the of anisole concentration versus reaction time of HDO of anisole using
Ni-Mo/TiO2 at (a) 250 °C, (b) 275 °C, (c) 300 °C and (d) 325 °C. .................................... 150
Fig. 6.13 Plot of the of logarithmic natural of rate constant versus 1/T of HDO of anisole
using Ni-Mo/TiO2 to determine the kinetic parameter ....................................................... 151
Fig. 6.14 Fig. 6.12 Plot of the of anisole concentration versus reaction time of HDO of
anisole using Ni-V/TiO2 (a) 250, (b) 275, (c) 300, (d) 325 °C temperatures ..................... 153
using Ni-V/TiO2 to determine the kinetic parameter .......................................................... 154
Fig. 7.1 Relation between chapters ............................................................................................. 161
xiv
List of Symbols, Units, Chemical Formulas and Abbreviations
Symbols
[C]
Weight percentage of carbon in biomass or compound
[O]
Weight percentage of oxygen in biomass or compound
[H]
[N]
A
C
d
dt
dT
E
Ei
H
HHV
k
ki
k0
k0i
n
ni
pH
Weight percentage of hydrogen in biomass or compound
Weight percentage of nitrogen in biomass or compound
Amount of ash from devolatilization process
Amount of carbon from devolatilization process
Diameter of particle (mm)
Derivative of time variable
Derivative of temperature variable
Activation energy (J/mol)
Activation energy of event i (J/mol)
Heating rate
High heating value
Rate constant (1/min)
Rate constant of event i
Pre-exponential factor (1/min)
Pre-exponential factor of event i
Order of the reaction
Order of the reaction from event i
Acidity
xv
R
Universal gas constant (J/Kmol)
T
Temperature (K)
t
V
V(t)
Vi(t)
Vi *
Time (min)
Amount of volatile material from devolatilization process
Mass fraction of volatile material yield up to time t
Accumulated amount of released volatile material from event i to
time t
Mass fraction of volatile material yield up to t = ∞
xvi
Greek Letters
Kα
X-ray spectral line
λ
Wavelength (nm)
θ
Angle of diffraction
xvii
Unit
1/min
Unit of rate constant: one over minute
°C
Temperature unit: degree in Celsius
°C/min
Degree of Celsius per minute
cm3
Unit of volume (space): cubic centimetre
cm3/g
Unit of pore volume: cubic centimetre per gram sample
cP
Unit of viscosity: centipoise
eV
Unit of energy: electron volt (1 eV = 1.602×10−19 joule)
g/cm
Unit of density: gram per unit volume of cubic centimetre
kJ/mol
Unit of activation energy: kilo Joule per mole
kV
Unit of electric potential: kilovolt
m
Unit of length: metre
m2/g
Unit of surface area: square metre per gram
mg
Unit of mass: milligram
µm
Unit of length: micrometre
min
Unit of time: minute
MJ/kg
Unit of energy density: mega Joule per kilogram weight
ml
Unit of liquid volume: millilitre
mL/min
Unit of gas flow rate: millilitre per minute
mm
Unit of length: millimetre
h
MP
Unit of time: hour
Mega Pascal
xviii
Mt
Unit of mass: megatons
nm
Unit of length: nanometre
PJ
Unit of energy: peta Joule
psi
Unit of pressure: pound per square inch
W
Unit of power: watt (1 W = 1 J.s)
Wt%
Percentage of weight
°
Unit of angle: degree
xix
Chemical Formulas
Al2O3
Aluminum oxide catalyst support
C=C
Chemical double bond between carbon atom
C1
Hydrocarbon with 1 atom carbon
C2
C2H4O2
Acetic Acid
C4H6O2
4-Hydroxybutyric acid lactone
C4H8O2
1-Hydroxy-2-butanone
C5H4O2
Furfural
C5H6O2
2-Furanmethanol
C5H8O3
Acetoxyacetone
C5H10O2
trans-1,3-Cyclopentanediol
C5H10O2
Tetrahydro-2-furanmethanol
C6H6O
Phenol
C6H8O
2-Methyl-2-cyclopenten-1-one
C6H8O
C6H8O2
2-Cyclopenten-1-one
(C6H10O5)n
Polysaccharide consisting of a linear chain of linked D-glucose
units
C6H12O2
4-Hydroxy-4-methyl-2-pentanone
C7H8O
o/m/p-Cresol
C7H8O2
Guaiacol
C8
xx
C8H10O2
4-Methylguaiacol (Creosol)
C8H10O3
2,6-Dimethoxyphenol
C9H12O2
4-Ethylguaiacol
C20
CH4
Methane gas
C-O
Chemical bond of carbon and oxygen atom
Co
Cobalt metal
Co–Mo
Cobalt and molybdenum active metal system
Co2P
Cobalt phosphide catalyst
CO
Carbon monoxide gas
CO2
Carbon dioxide gas
COS
Carbonyl sulphide
Cu
Copper
Cu(NO3)2·3H2O
Cupper nitrate trihydrate
Fe
Iron
Fe(NO3)3·9H2O
Iron nitrate nonahydrate
Fe2O3
Iron oxide catalyst support
Fe2P
Iron phosphide catalyst
H2
Hydrogen gas
H2O
Water
H2S
Hydrogen sulphide
La1−x.Ce.x NiO3
Perovskite system of lanthanum, cerium and nickel oxide
xxi
Mo
Molybdenum
MoP
Molybdenum phosphide catalyst
N2
Nitrogen gas
N2O
Nitrous oxide gas
NH3
Ammonia
(NH4)6Mo7O24
Ammonium heptamolybdate
NH4VO3
Ammonium metavanadat
Ni
Nickel
Ni-Mo
Nickel-molybdenum active metal
Ni-Mo/TiO2
Catalyst: nickel-molybdenum active metal on Titanium oxide
support
Ni-V
Nickel-vanadium active metal
Ni-V/TiO2
Catalyst: nickel-vanadium active metal on Titanium oxide
support
Ni2P
Nickel phosphide catalyst
NiMoO4
Nickel molybdate
Ni(NO3)2·6H2O
Nickel nitrate hexahydrate
NiO-CuO
Oxide form of nickel copper catalyst
NiO-Fe2O3
Oxide form of nickel iron catalyst
NiO-MoO3
Oxide form of nickel molybdenum catalyst
NiO-V2O5
Oxide form of nickel vanadium catalyst
NOX
Nitrogen oxides compound
O2
Oxygen gas
OH-
Hydroxide bond (group)
xxii
Pd
Nobel metal palladium
Pt
Nobel metal platinum
Rh
Nobel metal rhodium
SO2
Sulphur dioxide
SOX
Sulphur oxides compound
TiO2
Titanium oxide catalyst support
V
Vanadium
V2O5
Vanadium pentoxide
WP
Tungsten (wolfram) phosphide catalyst
ZrO2
Zirconium oxide catalyst support
xxiii
Abbreviations
BET
Brunauer-Emmett-Teller
C
Carbon element
C1
C8
C20
CCD
Charge-coupled device
CDME
Catechol dimethyl ether
CHNS
Carbon, hydrogen, nitrogen and sulphur
DTG
Derivative thermogravimetric
EDX
Energy-dispersive X-ray
ETR
Extended temperature range
FC
Fixed carbon
FID
Flame ionization detector
GC
Gas chromatography
GC-FID
Gas chromatography with a flame ionization detector
GC-MS
Gas chromatography / mass spectroscopy
GHG
Greenhouse gas
H
Hydrogen element
HDO
Hydrodeoxygenation reaction
HHV
Higher heating value
ICDD
The International Centre for Diffraction Data
xxiv
IUPAC
International Union of Pure and Applied Chemistry
KF
Karl-fischer
N
Nitrogen element
NOX
Nitrogen oxides compound
NSERC
Natural Science and Engineering Research Council of Canada
O
Oxygen element
PDF
Portable document format
pH
Acidity scale
PSD
Pore size distributions
Ref
Reference
S
Sulphur element
SOX
Sulphur oxides compound
TEM
Transmission electron microscopy
TG
Thermogravimetric
TGA
Thermogravimetric analysis or thermogravimetric analyzer
TPD
Thermo-programmed desorption
TPD-NH3
Thermo-programmed desorption of ammonia
XPS
X-ray photoelectron spectroscopy
XRD
X-ray Diffractometry or X-ray powder diffraction
UHV
Ultra-high vacuum
UHP
Ultra-high purity
FWHM
Full width at half maximum
xxv
CHAPTER 1: INTRODUCTION
1.1 Overview
Fossil fuels, which are categorized as a non-renewable energy, have been identified as a primary
source of greenhouse gas (GHG) emissions in our atmosphere. Based on a report from
Environment Canada in 2013, 79% of total Canada’s GHG emissions come from carbon dioxide
(CO2), 12% from methane (CH4) and about 7% from nitrous oxide (N2O) [1]. It is estimated that
total Canadian GHG emissions from fuel combustion reached 537 megatons (Mt) in 2010, or
roughly 1.8% of the world’s total GHG emissions [1]. Canada has been recognized as one of the
largest fossil fuels producer in the world and consumed high amount of electricity per capita.
Between 1990 and 2010, energy use in Canada increased by 22.3% or about 1.16% per year [1].
Based on data from Statistics Canada, fossil fuel consumption in Canada in 2010 represented
approximately 69% of its total energy consumption (8479.1 PJ), including hydro, nuclear, solar,
wind and biomass sources of energy, where the industrial sector accounted for the biggest share
of
energy
used
(38%),
followed
by
transportation
(31%),
residential
(16%),
commercial/institutional (12%), and agricultural (3%) sectors [1].
The production and use of fossil fuels have raised environmental concerns. As a result, the
production of renewable energy seems to be an interesting alternative to fulfill energy demand,
while lowering environmental impact.
1
Fig. 1.1 Typical lignocellulosic biomass waste found in Canada (from left to right: wheat
straw, oat straw, flax straw and barley straw)
Canada is a country endowed with abundant and varied natural resources, including massive
amounts of energy from sources such as petroleum, water, solar, wind and biomass. In 2015,
based on the data from Natural Resources of Canada, Canada produced about 25 million tonnes
wheat which also produced about the same amount of straw biomass. In addition, biomass
productivity from plantation vary between 10-15 oven dry tonnes per hectare per year. The use
of biomass or waste biomass, such as wheat straw, flax straw, barley straw or sawdust (Figure
1.1) in energy production provides several advantages from an environmental perspective. For
example, the plant growth to generate biomass consumes CO2 from the atmosphere, which
offsets the CO2 production created by the use of biomass as energy. The conversion of waste
biomass into energy and value-added chemicals will help meet the growing energy demand,
combat the increase in food crop prices, partially redirect biomass waste away from landfills and
simultaneously minimize environmental damage through reduced GHG emissions into the
atmosphere.
There are several methods known to convert biomass into energy. One such method is pyrolysis,
which is a thermal decomposition process with very limited amount of oxygen. The process is
typically carried out at a temperature range of 400 °C to 700 °C and at a near-ambient pressure
2
[2,3]. During pyrolysis, the large molecule structure of the biomass is broken down, producing
chemicals with smaller molecular structures. The process typically produces a hydrocarbon-rich
gas mixture, an oil-like liquid (bio-oil), and a carbon-rich solid residue (bio-char). The gas
product contains syngas (CO and H2) and CH4 and can be burned directly to produce heat or
electricity, while the bio-char can either be used as fertilizer or to produce activated carbon. The
bio-oil product, however, requires a further upgrading and/or separation processes, in order to be
used directly.
Although bio-oil is considered to be the most important pyrolysis product, due to its potential use
as a liquid fuel alternative, its properties have a downside. As shown in Table 1.1, bio-oil is
highly oxygenated [3,4], leading to a high viscosity, boiling point corrosiveness, as well as
relatively low chemical and thermal stability. Its composition is mainly determined by the type
of feedstock/biomass and the parameters of the pyrolysis process, such as temperature, heating
rate and residence time [5]. For example, pyrolysis using a slow heating rate tends to produce
more solid product than liquid product [6]. To overcome this problem, bio-oil can be upgraded
using several methods including catalytic cracking and steam reforming [7].
Table 1.1 Typical elemental and water content of bio-oils from fast pyrolysis [4,5]
Component
Wt%
Carbon
32-49
Oxygen
44-60
Water
15-30
Hydrogen
6-8.6
Nitrogen
0-0.2
3
In spite of the large amount of experimental data on the pyrolysis of various biomasses, there is
still considerable disagreement on the specific mechanisms of the pyrolysis process required for
the production of certain products, such as bio-oil and bio-char. For example, the detailed
mechanisms and reaction routes of slow pyrolysis and fast pyrolysis remain unclear. The best
methods to produce higher quality bio-oil and to upgrade bio-oil into a gasoline-like compound
are likewise undetermined. As a result, an investigation of the kinetics of pyrolysis, the effects of
several parameters on the pyrolysis product and its upgrading are needed, in order to answer
these questions.
1.2 Literature Review
1.2.1 Introduction to Biomass
When wood or lignocellulosic biomass is exposed to high temperatures, with or without the
presence of oxygen, changes occur in its chemical structure. Pyrolysis is a process involving high
temperatures that converts biomass into products, such as gaseous material, bio-oil and bio-char
in the absence of oxygen [7-10]. During pyrolysis, the biomass undergoes a very complex set of
reactions involving the formation of radicals in order to produce gaseous material, bio-oil and
bio-char [9,10]. The composition and quality of the pyrolysis products depend on certain
parameters, such as the reaction temperature, heating rate and residence time of the process [810]. It also depends on the type of biomass or, to be more specific, on the composition of the
biomass.
In Canada, biomass is widely available in the form of forestry and agricultural waste, including
wheat straw, flax straw, barley straw and wood/sawdust.They are categorized as lignocellulosic
4
biomasses. In general, lignocellulosic biomass is composed of extractive components (oil,
protein, sugar and others), ash and the three polymers that construct the cell walls: cellulose,
hemicelluloses and lignin linked together by ether and ester bonds [11,12].
Cellulose is a polysaccharide consisting of a linear chain of linked D-glucose units as represented
by the chemical formula (C6H10O5)n and is responsible for the production of flammable volatiles
during thermal degradation at a temperature range of 200 °C to 450 °C. Cellulose has a high
degree of polymerization (~10,000) and a large molecular weight (~500,000), which make it
highly insoluble. It is the main component of wood, representing up to about 40% of wood’s dry
weight [11-13].
Hemicellulose is also a polysaccharide, but with a branched and shorter chain of glucose units.
Unlike the cellulose crystalline structure, hemicellulose is amorphous, easier to hydrolyze, and
degrades within a smaller temperature range (200 °C to 260 °C). Lignin is randomly linked,
amorphous, and composed of many phenolic groups. The degradation of lignin usually occurs in
the temperature range of 225 °C to 450 °C, thereby producing a significant amount of phenolic
compounds, given its nature [12,13]. The amount of cellulose, hemicellulose and lignin of a
biomass can provide useful information to predict the product yield of a biomass.
Biomass can be categorized based on its polymer composition or its proximate and elemental
composition. In proximate analysis, the biomass is exposed to a drying temperature to determine
its moisture content. This temperature is gradually increased to 900 °C in a nitrogen (N 2)
atmosphere to obtain the volatile amount from its decomposition. The fixed carbon (FC) content
5
can also be determined through proximate analysis by replacing the N2 with oxygen (O2) to
allow combustion, which produces ash as the resulting material.
Elemental composition information, such as carbon, hydrogen, nitrogen, sulphur and oxygen (C,
H, N, S and O) can be used to estimate the heating value of the biomass and to predict the quality
of bio-oil that can be obtained through the pyrolysis process. In the elemental (i.e. ultimate)
analysis, the biomass sample undergoes a complete combustion around 1000 °C and is then
mixed, separated in the column and detected as an individual gas using a thermal conductivity
detector.
Table 1.2 shows the elemental composition of several types of biomass gathered from various
sources. As can be seen, the volatile content of a biomass ranges from 75% to 86% of its total
weight and contains as much as 47% oxygen.
Table 1.2 Chemical composition of several types of biomass
Species
Pine wood
Moisture
Fir wood
Beech wood
6.40
Oat straw
5.38
Flax straw
4.06
Rapeseed
Wheat straw
Rice straw
Coconut shell
Sugarcane
bagasse
Volatiles
16.81
80.49
19.42
74.80
18.30
74.48
77.57
75.84
4.00
86.04
5.58
79.82
13.61
11.26
16.07
FC
82.79
82.88
Spruce wood
Pine bark
Combustible
76.85
85.36
79.59
Ash
C
H
0.40
51.22
0.24
51.24
0.50
49.80
19.53
5.99
42.27
5.98
21.30
1.11
45.24
63.45
17.00
0.12
21.61
2.55
8.23
5.73
14.45
5.73
O
[14]
42.68
[14]
42.70
[15]
45.20
[17]
0.15
43.77
53.21
5.98
0.52
43.48
52.25
8.06
3.91
35.78
5.84
0.18
40.78
4.34
58.14
5.95
6.20
0.12
0.40
Ref
42.64
6.07
50.93
6
0.12
S
50.01
9.54
3.38
6.02
N
[14]
[14]
[16]
0.56
1.07
6.25
1.01
1.18
46.40
[17]
6.73
0.43
0.17
28.27
[18]
6.04
6.05
0.83
0.69
0.28
0.23
0.19
47.50
41.61
34.57
[17]
[18]
[18]
1.2.2 Pyrolysis of Lignocellulosic Biomass
Pyrolysis is used to convert biomass to gas, liquid and solid products by heating it in the absence
of oxygen. During pyrolysis, the biomass undergoes a very complex set of reactions involving
the formation of radicals in order to produce gaseous material, bio-oil and bio-char [9,19]. In
general, pyrolysis consists of two stages of devolatilization after the drying process. Primary
devolatilization (less than 400 C) mainly devolatilizes hemicelluloses and celluloses, whereas
secondary devolatilization (over 400 C) involves aromatization of components such as lignin
[20]. Although pyrolysis is an old technology, it has been improved in recent decades and is
becoming more attractive than many other thermochemical processes in order to produce liquid
fuel and chemicals [21].
Pyrolysis involves many chemical reactions (cracking, elimination, addition, substitution and
polymerization) and produces a large number of chemical components. Cracking will produce a
smaller chain of hydrocarbons (ranging from C1 to C8), while polymerization will produce a
longer chain of hydrocarbons (ranging up to C20). Since biomass contains around 45% oxygen,
most of the pyrolysis products are phenolic and poly-alcohol compounds.
7
Fig. 1.2 Devolatilization profile of biomass components [22]
Figure 1.2 shows the devolatilization profile of biomass components as the temperature
increases. As can be seen, xylan and cellulose are more likely to decompose at lower and smaller
ranges of temperature (200 °C to 400 °C) as compared to lignin (150 °C to 500 °C). Since most
biomass consists of about 10-40% lignin, performing pyrolysis at a temperature of around 500
°C is more favorable in terms of a high yield from the decomposition of cellulose, hemicellulose
and lignin.
1.2.2.1 Slow (Conventional) Pyrolysis
Based on its heating rate, pyrolysis can be divided into slow pyrolysis and fast pyrolysis.
Pyrolysis with a vapor residence time of 5-30 min is considered slow pyrolysis [3,13,23]. During
slow pyrolysis, the intermediate end product can undergo a secondary reaction, forming a longer
chain component that can lower the quality of bio-oil. Longer residence time also requires more
8
energy to process. Despite these disadvantages, slow pyrolysis may be easier to control and can
produce more bio-char product, which can be suitable for soil enrichment. Nonetheless, the oil
yield obtained from slow pyrolysis (25-50%) is lower than that from fast pyrolysis and may have
a different chemical composition [3,13].
1.2.2.1 Fast Pyrolysis
In the fast pyrolysis process, the heating rate can be as high as 1000 °C/min. The typical
residence time for fast pyrolysis is about 1-5 seconds with a reaction temperature range from 450
°C to 1000 °C [3,4]. The intent of fast pyrolysis is to limit the residence time of the liquid
product in order to prevent a secondary reaction that can lead to the formation of a longer chain
of hydrocarbon or a tar component. In addition to a fast heating rate and better control of reaction
temperature, another key to prevent a secondary reaction is the use of rapid cooling. Using fast
pyrolysis, a higher yield of liquid product can be obtained representing up to 75% of the weight
of the biomass [3,23].
The general changes that occur during pyrolysis are:
1. Heat transfer from a heat source to increase the temperature of the solid feedstock;
2. Initiation of primary pyrolysis reactions at this higher temperature releases volatiles and
forms char;
3. The flow of hot volatiles toward cooler solids results in heat transfer between hot
volatiles and cooler unpyrolyzed feedstock;
4. Condensation of some of the volatiles in the cooler parts of the fuel, followed by
secondary reactions, can produce tar;
9
5. Autocatalytic secondary pyrolysis reactions proceed, while primary pyrolytic reactions
(item 2, above) occur simultaneously in competition; and,
6. Further thermal decomposition, reforming, water gas shift reactions, radical
recombination and dehydrations can also occur, all of which are functions of the process
residence time.
1.2.3 Kinetic Study of Pyrolysis of Biomass
Many techniques can be used to study biomass pyrolysis to obtain kinetic parameters and to gain
insight into the devolatilization process of biomass pyrolysis. One technique that has been widely
used in the past is thermogravimetric analysis (TGA), which is a technique in which the mass of
the biomass is measured as a function of temperature or time while the sample is subjected to a
controlled atmosphere [24]. The mechanism of biomass thermal devolatilization, however, can
vary depending on the components and composition of the biomass.
TGA is a useful tool to study biomass devolatilization during pyrolysis. It provides data about
biomass conversion as the temperature changes. The measurement of mass loss using TGA can
yield information such as the thermal stability and kinetic parameters of the thermal events
during pyrolysis. This kinetic information is crucial for the design of pyrolysis reactors and
gasifiers [25,26]. Three stages can be distinguished during the heating process: drying, primary
devolatilization and secondary devolatilization [27]. The kinetics of these stages can be
determined by applying the Arrhenius equation to the separate slopes of constant mass
devolatilization [28]. In addition, a nonlinear approach can be used to optimize the parameters.
10
1.2.4 Pyrolysis Behaviors of Lignocellulosic Biomass
In the past few decades, many researchers have studied the pyrolysis behaviors of various
biomasses and their kinetics. Caballero et al. investigated the pyrolysis kinetics of almond shells
and olive pits and noted that the thermal devolatilization of lignocellulosic material can be
differentiated into two global processes: devolatilization of hemicelluloses together with lignin,
and cellulose devolatilization [29].
Researchers have also studied the influence of the heating rate on the pyrolysis of various
biomasses. Altun et al. investigated the effect of particle size and heating rate on the pyrolysis of
Silopi asphaltite [30]. They found that, by increasing the heating rate, the residue (bio-char and
ash) at the end of pyrolysis also increased. In another experiment, Lapuerta et al. performed a
non-isothermal pyrolysis of forestry waste using varying heating rates and showed that a curve
fitting method corresponded well with the experimental data to reflect the kinetic parameters
[31]. Kumar et al. studied the devolatilization of corn stover and concluded that the primary
devolatilization was followed the kinetics of first-order reaction rate [32].
Chouchene et al. observed the effect of particle size on the pyrolysis of olive solid waste under
nitrogen and oxidative atmospheres [33]. They found that samples smaller than 0.5 mm were the
most reactive. They also found that, during oxidative pyrolysis under 10% oxygen (O 2), olive
solid waste samples with diameters between 2 mm and 2.8 mm produced lower ash content and
higher char quantity.
11
In another study, Lester et al. examined the pyrolysis of olive solid waste using three different
particle sizes (53-75 mm, 106-150 m, and 150-212 mm) mixed with standard highly volatile coal
with particle sizes in the range of 106-150 mm under nitrogen conditions [34]. They found that
the particle size variations had a limited effect on the weight loss profile under the above
conditions.
Although many studies about biomass pyrolysis using thermogravimetric analysis have been
reported, the effects of important parameters, such as particle size, heating rate and initial sample
weight, have rarely been investigated for biomasses such as sawdust, oat straw or barley straw.
This information will be vital in the design of reactors for larger scale biomass pyrolysis and in
establishing global kinetic parameters for the devolatilization of lignocellulosic biomass.
1.2.5 Bio-Oil Production from Lignocellulosic Biomass
Lignocellulosic biomass can be converted to bio-oil through pyrolysis followed by catalytic
upgrading [3]. As previously mentioned, pyrolysis can be categorized as conventional pyrolysis
(slow pyrolysis) and fast pyrolysis, depending on the operating conditions. In slow pyrolysis,
biomass is heated up to 500 °C at a heating rate of less than 100 °C/min and a vapor residence
time of between 5 and 30 min, resulting mainly in char production [35]. In fast pyrolysis,
biomass is heated up to 500 °C, but at a faster heating rate (1000 °C/min and higher) and a vapor
residence time of less than 2 seconds. Fast pyrolysis naturally favors bio-oil as the main product
[36], unlike slow pyrolysis, which results in the production of bio-char.
12
Several chemical changes occur during pyrolysis. The primary pyrolysis reaction releases
volatiles and concurrently forms char. During the next step, condensation can occur in the cooler
parts of the system to form bio-oil. This process is naturally followed by secondary reactions that
produce tar. Reforming, dehydration and polymerization can also occur, depending on the
reaction time and the heating rate [3]. In the end, the volatile pyrolysis product can have more
than 120 components, ranging from unspecified low molecular products contain phenolic OHgroups to cyclic and bi-cyclic products [37].
Current and ongoing research in pyrolysis is aimed at increasing the yield of bio-oil while
increasing the quality of the oil through subsequent upgrading processes. This study researches
the impact of pre-treating the sample prior to the pyrolysis process in order to obtain a better
quantity and quality of bio-oil.
1.2.6 Bio-Oil Upgrading
As observed in Table 1.3, bio-oil has interesting properties. It consists mostly of carbon (44-55
wt%) and oxygen (40-50 wt%). One of the advantages of bio-oil is its high carbon content, since
this increases the high heating value of its combustion. Another advantage is its lower nitrogen
and sulphur content, resulting in a lower amount of sulphur oxides (SOx) and nitrogen oxides
(NOx) in the flue gas stream [29]. Bio-oil properties do, however, have some drawbacks: one of
the main disadvantages is the poor stability of the oil due to its high oxygen content.
Generally, the bio-oil from pyrolysis has a high oxygen (40-50 wt%) and water (20-50%) content
[29,30]. High oxygen content in the oil causes condensation, which leads to high viscosity (Table
13
1.3). Consequently, bio-oil possesses a lower heating value compared to petroleum fuels, such as
gasoline (45 MJ/kg), thereby demanding rigorous upgrading processes.
Table 1.3 Typical properties of oils obtained through flash pyrolysis
Parameter
Value
Yield (wt%)
50-75
Carbon (wt%)
44-55
Oxygen (wt%)
40-50
Hydrogen (wt%)
6-7
Nitrogen (wt%)
Water (wt%)
0.0-0.2
20-30
Density (g/cm )
1.2
3
Viscosity (cP. At 40 °C)
Higher Heating Value (HHV, MJ/kg)
40-200
20
Upgrading is frequently carried out using common hydrotreating and synthetic zeolite catalysts
[29,38,39]. The catalysts used in the upgrading process are selected based on their pore size,
acidity and molecular sieving properties, in order to obtain maximum hydrocarbon yields
[39,40]. Other than that hydrodeoxygenation (HDO) process can also be used in order to reduce
oxygen content to produce fine chemicals such as phenol [40-43]. When using zeolites, although
no hydrogen is required for the process, their capability for deoxygenation of lignocellulose
phenolic compounds is limited due to poor hydrocarbon yield and easy decomposition by
extensive coke deposits or dealumination by hydrolysis [44]. For better result, oxide metal
catalyst is mixed with bio-oil and H2 gas is used as reaction gas during HDO [41,42]. Zhang et
al. (2015) perform a fast pyrolysis using magnetic solid base catalyst K3PO4/Fe3O4 and
successfully increased the yield of phenolic component about 1.5 times compared to non14
catalytic pyrolysis. They conclude that the catalyst would promote the decomposition of lignin to
increase the phenolic yield [41].
1.3 Objectives
The scope of this research was to maximize the yield of bio-oil from the pyrolysis of various
straw biomasses and to synthesize and utilize a catalyst during the post-treatment phase to
increase the quality of the bio-oil. In particular, the study focused on the role of the catalyst in
the upgrading process to enhance bio-oil properties to produce gasoline-like biofuel or valueadded chemicals.
The hypothesis of this study was that the use of catalyst in the pyrolysis of the biomass would
increase the yield and enhance the quality of the bio-oil produced by the pyrolysis and, at later
stage, would also be effective for the upgrading of the bio-oil into value-added chemicals. This
study investigated the kinetics of the pyrolysis process, the synthesis of the metal catalyst and the
catalytic upgrading process of selected bio-oil components.
In order to test the hypothesis, the following specific objectives were set:
1. Determine the mechanism and global kinetics of pyrolysis of lignocellulosic biomass
under different parameters, such as heating rate, particle size and initial weight of the
sample (Chapter 3).
2. Investigate the use of heterogeneous conventional solid acid catalysts (e.g. zeolite based
catalysts) to enhance the yield and quality of bio-oil and to characterize the pyrolysis
products (Chapter 4).
15
3. Study the application of oil hydrogenation catalysts (nickel, Ni, nickel-molybdenum, NiMo, nickel-vanadium, Ni-V, supported over alumina) in the presence of hydrogen on the
guaiacol (bio-oil main component) upgrading process (Chapter 5).
4. Study the application and kinetics of oil hydrotreating and hydrogenation catalysts (Ni,
Ni-Mo, Ni-V supported over alumina) in the presence of hydrogen on the anisole (bio-oil
components) upgrading processes (Chapter 6).
1.4 Organization of the Thesis
This thesis consist of seven chapters, organized consecutively in a paper-based format. Chapters
3 to 6 was written in a paper-based format and 2 of them have been published and the other 2
have been submitted to peer-reviewed journal paper. Brief description of each chapter is
explained below.

In Chapter 1, the author provides the overall background of the research project. A
condensed literature review was written to describe few important definitions, finding and
progress in the area of pyrolysis of biomass. In addition, the author also wrote the objective
and the outcome of the research project in term of publications.

Chapter 2 explains the research methodology that has been used by the author including the
study of pyrolysis kinetics using TGA, the bench-scale reaction of pyrolysis and also the biooil upgrading process. In this chapter, the author present the experimental setups constructed
based on the information from literature review.

Chapter 3 presents the first published paper about the pyrolysis kinetics of pyrolysis of
sawdust. In this publication, the author showed the methodology to obtain the kinetic
parameters such as reaction order and the energy activation. The effect of several parameters
16
such heating rate, the initial weight and particle size was also discussed to gain the optimum
condition for bench-scale pyrolysis process.

In Chapter 4, the author wrote about the result from bench-scale pyrolysis of four different
straw biomass (wheat, oat, flax and barley straw) and analyze the yield of the products
including the bio-char, bio-oil and gaseous material. TGA instrument was also used to gather
important information such as proximate analysis that can be used as an early prediction of
the product yield that can be obtained during bench-scale process.

Chapter 5 explains the catalyst synthesis, characterization and upgrading process of one of
the main component of bio-oil, guaiacol. In this study, catalyst screening was performed
under hydrodeoxygenation reaction using temperature range between 200-350 °C. Among
various catalysts, Ni-Mo/TiO2 (prepared by impregnation technique) was chosen to
understand the influence of reaction parameters, such as temperature, reaction time, H 2
pressure, and quantity of the catalyst.

Chapter 6 discusses about upgrading process of other component of bio-oil, anisole. The
reaction study was done on hydrodeoxygenation reaction of anisole using the same catalyst
that previously used for guaiacol. The comparison between the upgrading of both component
was shown in order to see the consistency of the process in reducing the oxygen content of
bio-oil components. In addition, determination of kinetic parameter was also provided in this
chapter.

Chapter 7 provides the general conclusion that can be drawn from the result of each phase of
the study. The author also offers few suggestions and future that can should be done in order
to gather other important information that will be useful for the commercialization of the
research project.
17
1.5 Outcome of the Thesis
The author has published 2 peer-reviewed journal papers (chapter 1 and chapter 3), 3 peerreviewed international conference proceedings, and submitted a third (chapter 2) and fourth
manuscript (chapter 4) as the first author. In addition, the author has published 3 peer-reviewed
journal paper as co-author for
related
work in pyrolysis and torrefaction and currently submitted
one manuscript as co-author in a work related to pyrolysis of municipal solid waste. A list of
these publications follows:
1.5.1 Published peer-reviewed journal papers and contribution:
1. Aqsha, A., Mahinpey, N., Mani, T., Salak, F. & Murugan, P., Study of sawdust pyrolysis
and its devolatilisation kinetics, The Canadian Journal of Chemical Engineering, 89(6), pp.
1451-1457, 2011.
2. Vincent, S.S., Mahinpey, N. & Aqsha. A., Mass transfer studies during CO2 gasification of
torrefied and pyrolyzed chars, Energy, 67, pp. 319-327, 2014.
3. Aqsha, A., Katta, L. & Mahinpey, N., Catalytic Hydrodeoxygenation of Guaiacol as
Lignin Model Component Using Ni-Mo/TiO2 and Ni-V/TiO2 Catalysts, Catalysis Letters,
145 (6), pp. 1351-1363, 2015.
4. Shi, H., Mahinpey, N., Aqsha, A., Silbermann, R., Characterization, thermochemical
conversion studies, and heating value modeling of municipal solid waste, Waste
Management, 48, pp. 34-47, 2016.
18
5. Tijani, M.M., Aqsha, A. & Mahinpey, N., Development of Oil-Spill Sorbent from Straw
Biomass Waste: Experiments and Modeling Studies, Journal of Environmental
Management, in press, doi:10.1016/j.jenvman.2016. 02.010, 2016.
Candidate’s and other author’s contribution to Paper 1:
The candidate designed the study with help from Mani, Salak and Murugan. The candidate
searched the literature, selected the relevant articles, performing the experiment. The candidate
analyzed and interpreted the data and prepared the manuscript with help from Mani and Murugan
while Mahinpey review and critically revised the manuscript for important intellectual content.
This study was completed under the guidance of the postdocs and supervisors. All authors
critically revised the manuscripts and contributed intellectually to each work.
The candidate contribute in the design of the experiment and conducting the analysis of char
product. The candidate prepared experimental setup and helping in the purchasing process of
most of the apparatus. The candidate also involved in data analysis, derived the mass transfer
model, and the review of the manuscript. All authors critically revised the manuscripts and
contributed intellectually to each work.
The candidate designed the research and conducted the study with help from Katta and Tijani.
Katta has trained the candidate in the catalyst synthesis and preparation and provided her thought
on the type of analysis that were performed during the study. Tijani involved in helping the
19
candidate to setup the equipment and assist in the pyrolysis experiment. Candidate and Katta
worked together in writing the manuscript and discussing the result. Katta provided her expertise
in analyzing the result from charatcterization of the catalyst, while Tijani contributed in extracted
TGA data and CHNS data. This study was completed under the guidance of the postdoc (Katta)
and supervisors. All authors critically revised the manuscripts and contributed intellectually to
each work.
The candidate was involved in the proposal stage of the study that was submitted to Alberta
Innovates – Energy and Environment Solutions. The candidate contribute in the design of the
experiment and conducting the sampling from a waste management facility (landfill) in Red
Deer during summer 2013. The candidate also provide his help for data analysis and the review
of the manuscript. All authors critically revised the manuscripts and contributed intellectually to
each work.
The candidate was involve in the writing of NSERC-Engage proposal with ECCO Recycling Inc
as industry partner. The candidate contribute in the design of the experiment and prepare the
sample that was obtain from ECCO Recycling facility. The candidate provided the training of the
instruments (CHNS, TGA and BET) to Tijani and also involved in data analysis related to
absorbency value. All authors critically revised the manuscripts and contributed intellectually to
each work.
20
1.5.2 Submitted peer-reviewed journal papers and contribution:
1. Aqsha, A., Tijani, M.M. & Mahinpey, N., Catalytic Pyrolysis of Straw Biomasses (Wheat,
Flax, Oat and Barley Straw) and the Comparison of Their Product Yields, Energy
Conversion and Management, submitted, 2016.
2. Aqsha, A., Katta, L., Tijani, M.M. & Mahinpey, N., Upgrading of Anisole Components by
Ni-Mo/TiO2
and
Ni-V/TiO2
Catalysts:
Synthesis,
Characterization
and
Kinetic
Measurements, Energy & Fuel, submitted, 2016.
3. Shi, H., Mahinpey, N., Aqsha, A., Silbermann, R., Production of Value Added Chemicals
from Waste Coffee Cups via Catalytic Pyrolysis, Catalysis Communications, submitted.
The candidate designed the study and prepare the experimental setup. The candidate searched the
literature and performing the entire experiment with the help of Tijani. The candidate analyzed
and interpreted the data and prepared the manuscript. Tijani was involved in data extraction
related to bench-scale pyrolysis experiment and GC-MS analysis. This study was completed
under the guidance of the postdocs and supervisors. All authors critically revised the manuscripts
and contributed intellectually to each work.
The candidate designed the research and conducted the study with help from Katta and Tijani.
Katta was involved in the early stage of the study, preparing the catalyst and analysing the XPS
data obtained from Dr. Pereira Lab. Tijani was involved in data extraction from TEM instrument
21
that was located in foothills hospital. This study was completed under the guidance of the
postdoc (Katta) and supervisors. All authors critically revised the manuscripts and contributed
intellectually to each work.
The candidate was involved in the proposal stage of the study that was submitted to Alberta
Innovates – Energy and Environment Solutions. The candidate contribute in the design of the
experiment and conducting the sampling from a waste management facility (landfill) in Red
Deer during summer 2013. The candidate also provide his help for data analysis and the review
of the manuscript. All authors critically revised the manuscripts and contributed intellectually to
each work.
1.5.3 Published peer-reviewed conference proceedings and contribution:
1. Aqsha, A., Kannaiyan, R., Mahinpey, N. & Martinuzzi R., Application of Subcritical
Water on Bioenergy Conversion, 10th International Symposium on Supercritical Fluids
(ISSF), Proceeding, San Fransisco, 2012
2. Aqsha, A., Tijani, M.M. & Mahinpey, N., Catalytic Pyrolysis of Straw Biomasses (Wheat,
Flax, Oat And Barley Straw) And The Comparison Of Their Product Yields, Energy
Production and Management in the 21st Century, WIT Press, pp. 1007-1016, 2014.
3. Aqsha, A., Mahinpey, N., Katta, L., Gras, L. & Lim, C.J., Synthesis of Novel Catalysts For
Hydrodeoxygenation Of Bio-oil: Guaiacol As A Model Component, Energy &
Sustainability V, WIT Press, pp. 489-498, 2014.
22
The candidate designed the study and prepare the experimental setup of the glycerol
decomposition using subcritical water experiment. The candidate searched the literature and
performing the experiment related to glycerol decomposition. Kannaiyan was performing most
of the experiment related to lignin decomposition and fungal pretreatment. The candidate and
Kannaiyan analyzed and interpreted the data and prepared the manuscript. The candidate present
the manuscript in the ISSF conference and collecting the feedback from the audience. This study
was completed under the guidance of the both supervisors Dr. Mahinpey and Dr. Martinuzzi. All
authors critically revised the manuscripts and contributed intellectually to each work.
The candidate designed the study and prepare the experimental setup. The candidate searched the
literature and performing the entire experiment with the help of Tijani. The candidate analyzed
and interpreted the data and prepared the manuscript. Tijani was involved in data extraction
related to bench-scale pyrolysis experiment and GC-MS analysis. This study was completed
under the guidance of the postdocs and supervisors. All authors critically revised the manuscripts
and contributed intellectually to each work.
The candidate designed the research and conducted the experiment with help from Katta. Katta
has trained the candidate in the catalyst synthesis and preparation and provided her thought on
the type of analysis that were performed during the study. Candidate and Katta worked together
23
in writing the manuscript and discussing the result. Katta provided her expertise in analyzing the
result from characterization of the catalyst. Gras was an internship student who assist on samople
preparation during HDO reaction experiment. This study was completed under the guidance of
the postdoc (Katta) and supervisors. All authors critically revised the manuscripts and
contributed intellectually to each work.
24
1.6 References
[1]
Natural Resource of Canada, Energy Efficiency and Trends in Canada 1990 to 2010, pp. 142, 2011.
[2]
Demirbas, A., Ozturk, T. & Demirbas, M.F., Recovery of energy and chemicals from
carbonaceous materials, Energy Sources Part A, 28, pp. 1473-1482, 2006.
[3]
Mohan, D., Pittman C.U. & Steele, P.H., Pyrolysis of wood/biomass for bio-oil: a critical
review, Energy Fuels, 20, pp. 848-889, 2006.
[4]
Bridgwater, A.V., Meier, D. & Radlein, D., An overview of fast pyrolysis of biomass, Org.
Geochem., 30, pp. 1479-1493, 1999.
[5]
Oasmaa, A. & Czernik, S., Fuel oil quality of biomass pyrolysis oils - state of the art for the
end user, Energy Fuels, 13, pp. 914-921, 1999.
[6]
Garcia-Perez, M., Wang, X.S., Shen, J., Rhodes, M.J., Tian, F.J. & Lee, W.J., Fast
pyrolysis of oil mallee woody biomass: effect of temperature on the yield and quality of
pyrolysis products, Ind. Eng. Chem. Res., 47, pp. 1846-1854, 2008.
[7]
Zhang, Q., Chang, J., Wang, T. & Xu, Y., Upgrading Bio-oil over Different Solid
Catalysts, Energy Fuels, 20, pp. 2717-2720, 2006.
[8]
Gupta, R.B. & Demirbas, A., Gasoline, Diesel and Ethanol Biofuels from Grasses and
Plants, Cambridge University Press, pp. 140-157, 2010.
[9]
Yaman, S., Pyrolysis of biomass to produce fuels and chemical feedstocks. Energy
Convers. Manag., 45, pp. 651-671, 2004.
[10] Schniewind, A.P., Concise encyclopedia of wood and wood based materials. Pergamon
Press, pp. 271-273. 1989.
25
[11] Higuchi, T., Biochemistry and molecular biology of wood, Springer, Berlin Heidelberg,
New York, 1997.
[12] Shafizadeh, F., Introduction to pyrolysis of biomass, J. Anal. Appl. Pyrol., 3, pp. 283-305,
1982.
[13] Basu, P., Biomass Gasification and Pyrolysis Practical Design and Theory, Academic
Press, Elsevier, pp. 33-38, 2010.
[14] Peng, J.H., A Study of Softwood Torrefaction and Densification for Production of High
Quality Wood Pellets, PhD Thesis of University of British Columbia, 2012.
[15] Demirbas, A., Pyrolysis of ground beech wood in irregular heating rate conditions, J. of
Anal. and App. Pyrolysis, 73(1), pp. 39-43, 2005.
[16] Sensoz, S., Angin, D., Yorgun, S. and Kockar, O.M., Biooil Production from an Oilseed
Crop: Fixed-Bed Pyrolysis of Rapeseed (Brassica napus L.), Energy Sources, 22(10), pp.
891-899, 2000.
[17] Mani, T., Murugan, P. and Mahinpey, N., Pyrolysis of Oat Straw and the Comparison of
the Product, Energy & Fuels, 25, pp. 2803-2807, 2011.
[18] Tsai, W.T., Lee, M.K. and Chang, Y.M., Fast pyrolysis of rice straw, sugarcane bagasse
and coconut shell in an induction-heating reactor, J. of Anal. and App. Pyrolysis, 76(1-2),
pp. 230-237, 2006.
[19] Mahinpey, N., Murugan, P., Mani, T. & Raina, R., Analysis of bio-oil, bio-gas and bio-char
from pressurized pyrolysis of wheat straw using a tubular reactor. Energy Fuels, 23, pp.
2736-2742, 2009.
[20] Fisher, T., Hajaligol, M., Waymack, B. & Kellogg, D., Pyrolysis behaviour and kinetics of
biomass derived materials. J. Anal. Appl. Pyrolysis, 62, pp. 331-349, 2002.
26
[21] Scott, D.S. & Piskorz, J., The continuous flash pyrolysis of biomass, Can. J. Chem. Eng.,
62, pp. 404-412, 1984.
[22] Shafizadeh,
F.,
Chemical
Composition
and
Thermal
Analysis
of
Cottonwood, Carbohydrate Res., 16, pp. 273-277, 1971.
[23] Jahirul., M.I., Rasul, M.G., Chowdhury, A.A. & Ashwath, N., Biofuels Production through
Biomass Pyrolysis - a Technological Review, Energies, 5, pp. 4952-5001, 2012.
[24] Menczel, J.D. and Prime, R.B., Thermal analysis of polymers fundamental and
applications. John Wiley & Sons: New Jersey, 2009.
[25] Dirion, J.L., Reverte, C. and Cabassud, M., Kinetic parameter estimation from TGA:
optimal design of TGA experiments. Chem. Eng. Res. Des., 86, pp. 618-625, 2008
[26] Kojima, T. Assavadakorn, P. and Furusawa, T., Measurement and evaluation of
gasification kinetics of sawdust char with steam in an experimental fluidized bed. Fuel
Process. Technol., 36, pp. 201-207, 1993.
[27] Mani, T., Murugan, P., Abedi, J. and Mahinpey, N., Pyrolysis of wheat straw in a
thermogravimetric analyzer: Effect of particle size and heating rate on devolatilization and
estimation of global kinetics. Chem. Eng. Res., 478, pp. 1-7, 2010.
[28] Gang, W. and Aimin, L., Thermal devolatilization and kinetics of mixtures of polylactic
acid and Biomass during co-pyrolysis. Chin. J. Chem. Eng., 16(6), pp. 929-933, 2008.
[29] Caballero, J.A., Conesa, J.A., Font, R. and Marcilla, A., Pyrolysis Kinetics of Almond
Shells and Olive Stones Considering Their Organic Fractions, J. Anal. Appl. Pyrolysis, 42,
pp. 159-175, 1997.
[30] Altun, N.E., Hicyilmaz, C. and Kök, M.V., Effect of particle size and heating rate on the
pyrolysis of Silopi asphaltite. J. Anal. Appl. Pyrolysis, 67, pp. 369-379, 2003.
27
[31] Lapuerta, M., Hernandez, J.J. and Rodriguez, J., Kinetics of devolatilization of forestry
wastes from thermogravimetric analysis. Biomass Bioenergy, 27, pp. 385 - 391, 2004.
[32] Kumar, A., Wang, L., Dzenis, Y.A., Jones, D.D. and Hanna, M.A., Thermogravimetric
characterization of corn stover as gasification and pyrolysis feedstock. Biomass Bioenergy,
32, pp. 460-467, 2008.
[33] Chouchene, A., Jeguirim, M., Khiari, B., Zagrouba, F. and Trouvé, G., Thermal
devolatilization of olive solid waste: influence of particle size and oxygen concentration.
Resour. Conserv. Recy., 54, pp. 271-277, 2010.
[34] Lester, E., Gong, M. and Thompson, A., A method for apportionment in biomass/coal
using thermogravimetric analysis. J. Anal. Appl. Pyrolysis, 80, pp. 111-7, 2007.
[35] Bridgwater, A.V., Catalysis in thermal biomass conversion. Appl. Catal. A, 116, pp. 5-47,
1994.
[36] Bridgwater, A.V., Renewable fuels and chemicals by thermal processing of biomass.
Chem. Eng. J., 91, pp. 87-102, 2003.
[37] Meier, D. & Faix, O., State of the art of applied fast pyrolysis of lignocellulosic materials a review, Biores. Tech., 68, pp. 71-77, 1999.
[38] Adjaye, J.D. & Bakhshi, N.N., Production of hydrocarbons by catalytic upgrading of a fast
pyrolysis bio-oil. Part I: Conversion over various catalysts, Fuel Process. Technol., 45, pp.
161-183, 1995.
[39] Wang, H., Male, J. & Wang, Y., Recent Advances in Hydrotreating of Pyrolysis Bio-Oil
and Its Oxygen-Containing Model Compounds, ACS Catalysis, 3(5), pp. 1047-1070, 2013.
[40] Mu, W., Ben, H. X., Ragauskas, A. & Deng, Y. L., Lignin pyrolysis components and
upgrading – technology review, Bioenergy Res., 6, pp. 1183-1204, 2013.
28
[41] Zhang, Z., Lu, Q., Ye, X., Li, W., Hu, B. & Dong, C., Production of phenolic-rich bio-oil
from catalytic fast pyrolysis of biomass using magnetic solid based catalyst, Energy
Convers.. & Manage., 106, pp. 1309-1317, 2015.
[42] Kim, J. S., Production, separation and applications of phenolic-rich bio-oil – a review,
Bioresour. Technol., 178, pp. 90-98, 2015.
[43] Effendi, A., Gerhauser, H. & Bridgwater, A.V., Production of renewable phenolic resins by
thermochemical conversion of biomass: a review, Renew. Sust. Energy Rev., 12, pp. 20922116, 2008.
[44] Huber, G. W., Iborra, S. & Corma, A., Synthesis of transportation fuels from biomass:
chemistry, catalysts, and engineering, Chem. Rev., 106(9), pp. 4044-4098, 2006.
29
CHAPTER 2: RESEARCH METHODOLOGY AND SETUP
This research was divided into four different phases, as depicted in Figure 2.1. Phase 1 included
the kinetic study of biomass pyrolysis using thermogravimetric analysis (TGA), while phase 2
consisted of the study of bio-oil production using bench-scale pyrolysis. Phase 3 involved
catalyst synthesis and catalyst screening of the bio-oil component, and phase 4 encompassed
upgrading the main components of the bio-oil, guaiacol and anisole, in order to reduce their
oxygen content and transform the components into value-added chemicals. In this chapter, the
pre-treatment method, pyrolysis experimental setup and bio-oil upgrading experimental scheme
are explained in detail.
Chemicals
Fig. 2.1 Diagram of the experimental setup
30
2.1 Study of Biomass Pyrolysis and its Devolatilization Kinetics Using TGA
Sawdust pyrolysis experiments were performed in the first phase of this project, subject to
changes in various parameters including particle size, initial sample weight and heating rate. The
devolatilization kinetics of biomass was studied using nonlinear optimization. Reaction kinetic
parameters were obtained for the three different stages of pyrolysis.
Samples used in this study were typical Canadian biomasses, such as sawdust (mix of wood),
wheat straw, flax straw, barley straw and oat straw. For experimental purposes, the biomasses
were ground in the laboratory mill and then sieved into different average particle sizes, varying
from 75 to 1400 µm. In the first phase, the sawdust sample was analyzed using an elemental
analyzer and then subjected to proximate analysis and the pyrolysis process using TGA (Figure
2.2). The TGA instrument was also used in every phase of the study in order to perform
proximate analysis and pyrolysis to learn about the parameters affecting process product yields.
Fig. 2.2 Schematic of pyrolysis experiment using TGA
31
2.1.1 Ultimate (Elemental Analysis) using Elemental Analyzer
Ultimate analyses were performed using an elemental analyzer (2400 Elemental Analyzer,
Perkin Elmer) in order to determine the carbon, hydrogen, nitrogen and sulphur (C, H, N and S)
compositions of the biomass samples. The 2400 Elemental Analyzer consisted of four major
zones, including the combustion, gas control, separation and detection zones (Fig. 2.3). The
determination was based on the Pregl-Dhumas method, where samples were combusted (975 °C)
in a pure oxygen environment and later reduced (500 °C) for the analysis of carbon dioxide
(CO2), steam (H2O), nitrogen (N2) and sulphur dioxide (SO2) [1]. After combustion, the gases
were captured in the mixing chamber, separated using the chromatography technique and later
detected by a thermal conductivity detector. Prior to measurement, the instrument was prepared
(filling the combustion tube, start-up, leak test) and calibrated using standard chemical cystine
(29.99% C, 5.03% H, 11.66% N, 26.69% S).
Fig. 2.3 Schematic of Perkin Elmer 2400 Elemental Analyzer [1]
32
The measurements were done using small sample quantities (about 2 mg). The samples were
accurately weighed and then wrapped using small tin capsules purchased from the vendor. Prior
to biomass analysis, few blank capsules were analyze to determine the instrument factor (kfactor) needed for the final calculation. A standard sample Cystine (C 6H12N2O4S2) was also
measured and the result was compared to its theoretical C, H, N and S content. The
measurements were repeated two to three times to obtain the average accurate value of 2 decimal
points.
2.1.2 Proximate Analysis using TGA
A proximate analysis of the sample was carried out using a TGA (STA6000, Perkin Elmer).
Ceramic crucibles were used in order to minimize any thermal lag and to optimize heat transfer
between thermocouples and crucibles. The instrument was equipped with a built-in mass flow
controller in order to use certain flow rates of inert and reaction gas. In order to calibrate the
instrument, a run using calcium oxalate (Fig. 2.3) was performed and matched with theoretical
values provided by the vendor. The analysis of the biomass included the determination of its
moisture, volatile material, fixed carbon (FC) and ash contents.
33
Fig. 2.4 TGA profile of calcium oxalate [2]
About 10 mg of the sample were used for all the reactions. Initially, each sample was kept at 25
°C for 4 min in a N2 atmosphere and then heated to 110 °C with a N2 flow rate of 45 mL/min to
determine its moisture content. A temperature of 110 °C was maintained for 5 min to achieve a
constant weight before proceeding to the next step. The sample was heated to 900 °C at a heating
rate of 80 °C/min, and this temperature was held for 5 min. In order to determine the FC content
of the remaining solid (char), as well as its ash content, the carrier gas was switched from N 2 to
air atmosphere at 900 °C and was held at this temperature for 7 min. The entire process was
completed in about 32 min.
2.1.3 Thermal Degradation (Devolatilization) using TGA
The non-isothermal experiments were performed at atmospheric pressure under an N 2
environment with a flow rate of 20 mL/min, beginning at room temperature and increasing to
800 °C. Pyrolysis was carried out by varying the heating rates from 5 to 20 °C/min, the particle
size of the sample from 150 to 1400 µm and the initial weight of the sample from 5 to 20 mg.
34
Weight losses corresponding to increases in temperature were continuously recorded. In this
study, all the experiments were replicated twice and had variations of less than 1%.
2.2 Bio-oil Production from Biomass Using Bench-scale Pyrolysis Reactor
In order to obtain a significant yield of pyrolysis product, bench-scale pyrolysis was performed
and analyzed. In this study, biomass was pyrolized on a bigger scale (10,000 times) than with the
TGA. As can be seen in Figure 2.5, a stainless steel rod was used as a reactor to fit the available
horizontal furnace and connect with the condenser, liquid collector and micro gas
chromatography (micro-GC).
Catalyst Powder
Biomass Feedstock
Stainless Steel Rod
(Tubular Reactor)
Heat Trace
N2
Thermocouples
Furnace
Condenser
Gas Filter
Online
Micro GC
He
Ice Bath
Fig. 2.5 Experimental setup of bench-scale pyrolysis
The feedstock included several types of biomass (wheat straw, flax straw, oat straw and barley
straw) with particle sizes between 150 and 2000 m in the amount of 50-100 g for each
35
experiment. Before the experiments, the samples were ground in a laboratory mill and may have
undergone subcritical pre-treatment and analysis using an elemental analyzer (2400 Elemental
Analyzer, Perkin Elmer) to determine their composition.
The bio-oil production through pyrolysis was performed in a horizontal stainless steel fixed-bed
reactor (400 cm3 in volume) in an N2 atmosphere with ambient pressure. The reactor was
connected to the fluid gas separator in order to collect the bio-oil while the gas was analyzed by
micro-GC in real time to determine its composition. The reaction temperature varied between
300 and 500 C with reaction times of between 5 and 30 min.
Pyrolysis product yields were determined gravimetrically by measuring the weight of the
produced bio-oil and bio-char. The bio-oil was collected from the gas liquid separator, while the
bio-char was the residual solid inside the reactor after the reaction was finished. The gas yield
itself was determined by the difference between the total and combined weights of the produced
bio-oil and bio-char. The experiments were carried out in series of four to study the effect of
pyrolysis parameters (temperature, heating rate and reaction time) on the product yields and
quality, in order to determine the optimal operating conditions that would produce the maximum
yield and the best quality of bio-oil.
The first series of experiments was performed to study the effect of the heating rate on the
pyrolysis product yields and quality. These experiments were conducted using four different
heating rates: 20, 50, 100 and 200 C/min. The reaction times varied according to the heating
rates used in the experiments. The second series of experiments were performed to study the
36
effect of the particle size on the pyrolysis yields and quality. The particle sizes of the samples
were 100-150, 250-300, 600-1000 and 1500-2000 m. Different particle sizes can affect the heat
transfer rate during the reaction, which may impact the product yield and quality.
The characterization of the bio-oil was performed using several instruments. The elemental ratio
(C, H, N, S and oxygen, O) of the bio-oil was determined using an elemental analyzer (Perkin
Elmer 2400 CHNS analyzer). The density of bio-oil was measured by pycnometer. In order to
measure the viscosity of the bio-oil, a viscometer was used at room temperature (25 C). The pH
of the bio-oil was measured using a pH meter to evaluate the corrosiveness of the bio-oil.
The higher heating value (HHV) of the oil was either calculated based on the composition
obtained from the ultimate analysis or was measured using a bomb calorimeter. The water
content of the bio-oil was determined by applying the Karl-Fisher titration method. Since the
bio-oil was presumed to contain more than a hundred chemicals, the analysis of the compounds
was determined by gas chromatography / flame ionization detector (GC-FID) and gas
chromatography / mass spectroscopy (GC-MS).
The bio-char product produced from the pyrolysis was evaluated using an elemental analyzer in
order to determine its composition and with Brunauer-Emmett-Teller (BET) surface area
analysis to determine its porosity and surface area. The gaseous product was analyzed using a
micro-GC to determine its composition (CO2, carbon monoxide, CO, hydrogen gas, H2, methane,
CH4, N2).
37
2.3 Bio-oil Upgrading Using Catalyst
The upgrading of the bio-oil was performed using two different catalysts (nickel molybdenum,
Ni-Mo and nickel vanadium, Ni-V catalyst with titanium oxide base). The upgrading process
was conducted in a batch reactor of a 30 cm3 size. The catalyst in the form of particles (size <150
m) was mixed with the bio-oil inside the reactor at certain ratios (1, 5, 10%). The reaction
temperature varied between 250 C and 325 C.
At the end of the reaction, the catalyst was removed from the liquid product, washed with
hexane, dried at 100 C and was regenerated using hot air (over 500 C). The weight of the
residual oil from the washing process was measured and analyzed. The liquid product was
analyzed using GC-FID and GC-MS to detect the chemical compounds in the upgraded bio-oil.
Several analyses, such as elemental analysis and density, viscosity, pH, HHV and water content
measurements, were conducted with the same procedures as discussed previously. The gaseous
product was analyzed using a micro-GC.
38
2.4 References
[1] PerkinElmer, Organic Elemental Analysis, 2400 Series II CHNS/O Elemental Analysis
Guide, 2011.
[2] PerkinElmer, A beginner’s Guide, Thermogravimetric Analysis (TGA) STA 6000
Documentation, 2010.
39
CHAPTER 3: STUDY OF SAWDUST PYROLYSIS AND ITS DEVOLATILIZATION
KINETICS
3.1 Presentation of the Article
This paper provides guidelines to determine the global kinetics of the pyrolysis of biomass and to
understand the devolatilization process of biomass under pyrolysis temperatures. A
thermogravimetric analyzer was used to perform the devolatilization process by varying three
parameters: the particle size of the biomass (sawdust), the initial weight of the sample and the
heating rate over a wide range of temperature (25 to 900 °C) under a nitrogen atmosphere. This
was done to observe the different trends of devolatilization due to the composition of the
biomass.
Based on the results, the devolatilization process was modeled using a differential equation and
later solved using an integration and nonlinear optimization numerical approach. As a result, the
devolatilization process of the sawdust samples during pyrolysis was divided into three noninteracting stages. The first stage was identified as the moisture loss process, the second as the
cellulose and hemicelluloses devolatilization, and the third as being dominated by lignin
devolatilization. The reaction orders for stages 2 and 3 were 0.9 and 1.7, respectively. Based on
the activation energy and reaction order data obtained from the model, stage 2 represented the
cellulose and hemicellulose devolatilization, while the third stage represented a lignin
devolatilization.
In addition, ultimate and proximate analyses were performed in order to provide more
information about elemental composition of the sample.
40
Study of sawdust pyrolysis and its devolatilization kinetics
Aqsha Aqsha, Nader Mahinpey, Thilakavathi Mani, and Feridoun Salak
Department of Chemical and Petroleum Engineering, Schulich School of Engineering,
University of Calgary, Calgary, Canada, AB T2N 1N4.
This article was published in The Canadian Journal of Chemical Engineering, 89(6), pp. 1451-1457, 2011.
3.2 Abstract
Pyrolysis of sawdust was studied using a thermogravimetric analyzer (TGA) to understand the
devolatilization process and to obtain its global kinetic parameters. The influences of particle
size, initial weight of the sample and heating rate on the devolatilization of sawdust particles
have been studied. Results from proximate analysis show that smaller particle size has more ash
content compared to larger particle size. The TG and derivative TG curve for variation in particle
size and initial weight of the sample showed significant difference in the third stage of the
pyrolysis. In addition, the pyrolysis of sawdust differed significantly for variation in heating rate.
As the heating rates increased, the char yield also increased. The devolatilization kinetics was
studied considering different stages of pyrolysis. The kinetic parameters for thermal
devolatilization of the sawdust were determined through a nonlinear optimization method of two
independent parallel nth-order reaction models. The kinetic parameters such as activation energy,
frequency factor and order of the reaction for the two stages considered in the model were:
E2 = 79.53 (kJ/mol), E3 = 60.71 (kJ/mol); k02 = 1.90 × 106 (1/min), k03 = 1.01 × 103 (1/min);
n2 = 0.91, n3 = 1.78, respectively. The results show good agreement between the proposed model
and the experimental data of the sawdust pyrolysis.
41
3.3 Introduction
Traditionally, using biomass as fuel by direct combustion is not as efficient and comfortable
compared with the energy produced from crude oil or coke combustion due to the high amount
of smoke and ash produced. Nowadays, biomass can be converted to various forms of energy
through several different processes (chemical, biological and thermochemical) as an alternative
to coal and oil. Pyrolysis is one of the thermochemical conversion processes that have been
commonly used to convert biomass into bio-oil and bio-char [1]. Although pyrolysis is an old
technology, it has been improved in recent decade and is becoming more attractive than many
other thermochemical processes [2, 3].
Pyrolysis is used to convert biomass to solid, liquid and gas by heating it in the absence of
oxygen. During pyrolysis, the biomass undergoes a very complex set of reactions involving the
formation of radicals in order to produce bio-oil and bio-char [4]. In general, pyrolysis consists
of two stages of devolatilization. Primary devolatilization (less than 400 °C) consists of mainly
devolatilization of hemicelluloses, whereas secondary devolatilization (over 400 °C) involves an
aromatization process of components such as lignin [5].
Many techniques have been used to study the biomass pyrolysis to obtain the kinetic parameters
and to gain insight into the devolatilization process of biomass pyrolysis. However,
thermogravimetric analysis (TGA) is the most widely used technique for biomass pyrolysis.
TGA is a technique in which the mass of the biomass is measured as a function of temperature or
time while the sample is subjected to a controlled atmosphere [6]. However, the mechanism of
42
thermal devolatilization of biomass could vary depending on the components and composition of
the biomass.
TGA is a useful tool to study biomass devolatilization during pyrolysis, since it provides data
about biomass conversion as temperature changes. Measurement of mass loss from biomass
using TGA can yield information such as thermal stability and kinetic parameters of the thermal
events during pyrolysis. The kinetic information is crucial for the design of pyrolysis reactors
and gasifiers [7, 8].
Three stages can be distinguished during the pyrolysis process that correspond to drying, primary
devolatilization and secondary devolatilization [9]. The kinetics of these stages can be
determined by the application of the Arrhenius equation corresponding to the separate slopes of
constant mass devolatilization [10]. In addition, a nonlinear approach has been used to optimize
the parameters.
In the past few decades, pyrolysis behaviors of various biomasses and their kinetics have been
studied by many researchers. Caballero et al. (1997) investigated the pyrolysis kinetics of
almond shells and olive stones and noted that the thermal devolatilization of lignocellulosic
material can be differentiated into two global processes [11]. The first is devolatilization of
hemicelluloses together with lignin and the second is related to cellulose devolatilization.
Researchers have also studied the influence of heating rate on pyrolysis of various biomasses.
Lapuerta et al. (2004) performed non-isothermal pyrolysis of forestry wastes with varying
heating rates and showed that an optimization method has good agreement with the experimental
43
data to obtain the kinetic parameters [12]. The devolatilization of corn stover has been studied by
Kumar et al. (2008) and reported that the primary devolatilization follows the first-order reaction
[13]. Chouchene et al. (2010) observed the effect of particle size on pyrolysis of olive solid waste
under nitrogen and oxidative atmospheres [14]. The samples having a size lower than 0.5 mm
was found to be more reactive compared to larger size particles. Low ash content and higher char
quantity was produced from olive solid waste with diameters between 2 and 2.8 mm during
oxidative pyrolysis under 10% O2 content [14]. In another study, Lester et al. (2007) examined
olive solid waste pyrolysis of three different particle sizes (53 < d <75 mm, 106< d < 150 mm and
150 < d < 212 mm) mixed with a typical high volatile coal with a particle size of 106-150 mm
under nitrogen conditions [15]. It was found that the particle size variations have a limited effect
on the biomass weight loss under the conditions studied. Meanwhile, the study conducted by
Chen et al. (2010) found that the increase of particle size of Beech wood under the explored
range (350-800 µm) significantly decreases the apparent pyrolysis rate, and therefore increases
the required time for completing pyrolysis reaction [16].
Although many studies about biomass pyrolysis using TGA have been reported, the effects of
important parameters such as particle size, heating rate and initial sample weight have rarely
been investigated for sawdust. In the present study, sawdust pyrolysis has been performed
considering the effects of various parameters, such as particle size, sample initial weight and
heating rate. The devolatilization kinetics of sawdust has also been studied using nonlinear
optimization. Reaction kinetic parameters were obtained by considering the three different stages
that occurred during pyrolysis. This research aims in investigating the pyrolysis characteristics
44
and kinetics of sawdust and the effect of several parameters on sawdust pyrolysis that are
instrumental for scaling up the pyrolysis process.
3.4 Experimental Section
3.4.1 Materials
The sawdust samples used in this study were the mixture of sawdust obtained from a waste wood
recycling company. The sawdust was ground in the laboratory mill and then sieved into different
average particle sizes varying from 75 to 1400 µm.
3.4.2 Proximate Analysis
Proximate analysis of sawdust was carried out using a TGA (STA6000; Perkin Elmer). Ceramic
crucibles were used in order to minimize any thermal lag and to optimize heat transfer between
thermocouples and crucibles. The analysis of sawdust includes determination of its moisture,
volatile material, fixed carbon and ash contents. About 10 mg of the sample was used for all the
reactions. Initially, the sample was kept at 25 °C for 4 minutes in a nitrogen atmosphere and then
heated to 110 °C with a nitrogen flow rate of 45 mL/min to determine its moisture content. The
temperature of 110 °C was maintained for 5 minutes to achieve constant weight before
proceeding to the next step. The sample was heated to 900 °C at a heating rate of 80 °C/min, and
this temperature was held for 5 minutes. In order to find the fixed carbon content of the
remaining solid (char), as well as ash content, the carrier gas was switched from nitrogen to air
atmosphere at 900 °C and was held at this temperature for 7 minutes. The entire process was
completed in 32 minutes. Ultimate analysis has been done by using Elemental Analyzer (2400
Elemental Analyzer, Perkin Elmer).
45
3.4.3 Pyrolysis Experiment using TGA
The non-isothermal experiments were performed in atmospheric pressure under nitrogen
environment with a flow rate of 20 mL/min from room temperature to 800 °C. Pyrolysis was
carried out by varying the heating rates from 5 to 20 °C/min, the particle size of the sample from
150 to 1400 µm and the initial weight of the sample from 5 to 20 mg. Weight losses occurring in
correspondence to temperature rises were continuously recorded with a computer working in
coordination with the instrument. In this study, all the experiments were replicated twice with an
uncertainty of less than 1%.
3.5 Results and Discussions
3.5.1 Ultimate and Proximate Analysis of Sawdust Sample
Table 3.1 shows the ultimate analysis and the high heating value (HHV) of sawdust calculated
based on the equation proposed by Demirbas [17]:
HHV = {33.5[C] + 142.3[H]−15.4[O]−14.5[N]} × 10−2
(3.1)
HHV, [C], [H], [O] and [N] represent the HHV, carbon, hydrogen, oxygen and nitrogen contents
of material, respectively. The heating value reported in this work was within the range of the
value (15 000-20 500 kJ/kg) reported by Demirbas for 16 different kinds of biomass [17]. The
ultimate analysis corresponds to the average composition of CH 1.59N0.03S0.01.
Table 3.1 Ultimate analysis of the sawdust in weight percentage
Sawdust
a
C
49.28
H
6.59
N
1.70
Calculated from the composition of the sawdust
46
S
1.25
HHVa (kJ/kg)
19298
Figure 3.1 illustrates the TGA profile of the sawdust drying, devolatilization, consequent char
formation, and finally, char oxidation for the proximate analysis. The first weight loss, around
110 °C, corresponds to the moisture loss of the sample. At temperatures below 110 °C, moisture
content is reduced by up to 5% of the sample weight. The second weight reduction
corresponding to increasing the temperature to 900 °C is attributed to devolatilization and
pyrolysis of mainly organic materials. All the volatiles were evolved at 900 °C, and only the char
remained. In this step, the yield of the volatile material is up to 67% of the initial weight of
sawdust sample. The fixed carbon content can be found from the oxidation of the produced char
by switching the carrier gas from nitrogen to air at 900 °C. In this step, the char is oxidized into
carbon dioxide and carbon monoxide. The weight differences before and after switching the gas
were used to determine the fixed carbon content, which is up to 18% of the weight sample. The
remaining residue represents the ash content.
900 C
Ash
Fixed carbon
Volatiles
25 C
110 C
Moisture content
Fig. 3.1 TG profile for proximate analysis of sawdust for the particle size of 250 µm.
47
The TGA profile of proximate analysis differed with the particle size of the sample. The volatile
material increased as the particle size increased from 150 to 1400 µm as shown in Table 3.2. On
the other hand, as the particle size increased, the ash content decreased. This might be caused by
the distribution of biomass particle during grinding and sieving processes. When biomass was
grounded, there is possibility that part of the biomass that contain the inorganic components
(ash) was breakdown into smaller particle size. As a result, larger particles produced smaller
amounts of ash. Similar results were reported by Mani et al. (2010) with particle size between
325 and 1350 µm of a wheat straw sample and also by Zanzi et al. (2002) in pyrolysis of olive
waste and wood [9, 18]. In another study, Chouchene et al. (2010) observed comparable results
with particle size between 2 and 2.8 mm of olive waste during oxidative pyrolysis, except that
the volatile material decreased as particle size increased [14]. Chouchene et al. (2010) noted that
this behavior might be caused by the larger heat propagation rate associated with smaller particle
size, which could have, therefore, released a greater quantity of volatile material [14]. In
addition, this may be due to the inorganic components separated from the lignocellulosic
structure during size reduction of the sample and tend to accumulate in smaller size fractions
[19].
Table 3.2 Proximate analysis of sawdust at different particle sizes
Sieve size
(µm)
Average size
(µm)
212-300
256
106-150
420-600
600-850
850-1000
1000-1400
Volatiles (%)
Fixed carbon (%)
Ash (%)
<150
56.97 (±0.33)
17.65 (±0.23)
10.75 (±0.74)
505
70.13 (±0.02)
18.35 (±0.31)
4.01 (±0.06)
725
925
1200
60.01 (±0.05)
69.35 (±0.27)
69.18 (±0.03)
77.03 (±0.45)
Uncertainty values are given in parentheses.
48
18.03 (±0.04)
17.63 (±0.33)
17.51 (±0.42)
18.15 (±0.16)
9.02 (±0.12)
4.61 (±0.40)
5.01 (±0.02)
1.01 (±0.21)
3.5.2 Pyrolysis of Sawdust
As shown in Figure 3.2, several events can be distinguished during the thermal pyrolysis of the
sawdust sample. Pyrolysis of sawdust involving thermal devolatilization consisted of a very
complex set of reactions. The reactions can be represented as the sum of thermal devolatilization
reactions of the individual components of lignin, cellulose and hemicellulose. As the temperature
increased, the rate of the devolatilization process also increased. Generally, during pyrolysis, the
moisture is removed initially at a temperature below 110°C [20]. Above 110 °C, the chemical
bond breaks to release the volatile compounds. It has been reported that hemicelluloses degrades
fast when compared to cellulose and lignin [21]. Above 200 °C, the celluloses and lignin started
to break and released more volatiles upto 400 °C. Beyond 400 °C, the degradation rate is slow
corresponding to the degradation of lignin components.
Stage 2
Stage 1
Stage 3
Fig. 3.2 Classification of devolatilization stages under nitrogen atmosphere.
49
The derivative thermogravimetric (DTG) curve could assist in explaining the TG curve. In
Figure 3.2, the spread of the reaction over temperatures of 25-900 °C appears as a relatively
broad peak. The area under the peak represents the weight loss during the reaction. Thus, relative
mass losses may be compared. When initial slow reactions are followed by fast reactions above
200 °C and then a second slow reaction initiates at 380 °C, there is a gradient change in the DTG
curve. This information is used in this study to distinguish the different stages of each process
and their respective reaction kinetics.
3.5.2.1 Effect of Particle Size
The influence of the particle size was investigated for six different particle sizes of sawdust
ranging between <150 and 1400 µm. As shown in Figure 3.3, particle size does not have a
significant effect on the TG profile of the first and the second stages of sawdust pyrolysis. In
contrast, as the particle size increased from 150 to 1400 µm, the char yield decreased (Table 3.3).
This may be due to the amount of heat transferred to different sizes of particles. The samples
consisting of larger particle may have had higher rate of heat transfer. As a result, during the
second stage (primary devolatilization), larger amounts of sample were decomposed and less
amounts of char remained at the end. Haykiri-Acma (2006) also obtained similar results for nonisothermal pyrolysis of hazelnut shell to study the role of particle size in the range between 150
and 1400 µm [22]. It has been found that the char yield is less for smaller particle size. A
comparable result was also reported by Demirbas (2004) for the effect of temperature and
particle size of various biomasses on char yield and reactivity [23]. Figure 3.3b shows DTG
curves for different particle sizes in sawdust pyrolysis.
50
(a)
(b)
Fig. 3.3 Pyrolysis curve of sawdust at different particle sizes of sample with heating rate of
10 °C/min and initial weight of 10 mg of sample. (a) TG profile and (b) DTG profile.
51
Table 3.3 Char yield percentage for different values of particle size of the sample for
sawdust pyrolysis with initial weight of 10 mg and heating rate of 10 C/min.
Average particle size (µm)
<150
256
505
725
925
1200
Char yield (%)
17.26 (±0.01)
15.16 (±0.05)
15.38 (±0.61)
15.94 (±0.03)
13.73 (±0.02)
11.85 (±0.66)
3.5.2.2 Effect of Initial Sample Weight
Figure 3.4 shows the influence of initial weight of the sample for sawdust pyrolysis. It is shown
that the change in pyrolysis behavior was observed in the third stage due to the change of initial
amount. According to the TG/DTG curves, it was clear that the char yield increased as the initial
weight increased. However, initial weight did not have significant effect on the first and the
second stages of the pyrolysis of the sawdust (Figure 3.4). The effect of the initial weight of the
sample was mainly studied to understand the role of inert gas diffusion into the bed sample. By
increasing the initial weight, the inert gas will encounter a higher diffusion resistance inside the
bed. Since the bed sample was getting higher inside the crucible, the gas that act as the heating
medium had to travel longer into the bulk and the heat transfer also would be affected adversely
and thus more char is produced (Table 3.4).
Table 3.4 Char yield percentage for different values of initial weight of the sample for
sawdust pyrolysis with average particle size of 352 µm and heating rate of 10 C/min.
Initial weight (mg)
5
10
15
20
Char yield (%)
9.54 (±0.39)
16.23 (±0.11)
18.13 (±0.33)
19.99 (±0.18)
52
(a)
(b)
Fig. 3.4 Pyrolysis curve of sawdust at different initial weights of sample with heating rate
of 10 °C/min and particle size of 352 µm. (a) TG profile and (b) DTG profile.
53
3.5.2.3 Effect of Heating Rate
In this experiment, pyrolysis was carried out using four different heating rates. Figure 3.5a and b
shows the TG and DTG curves for different heating rates from 5 to 50 °C/min. It was clear that
heating rates have a significant effect on the TG/DTG profile of sawdust pyrolysis on all three
stages. It can be seen that the TG curve shifted as the heating rate increased. As the heating rate
increased the char yield also increased. At the lower heating rate, the heat transfer between the
crucible and the sample were more efficient. This resulted in a proper drying and devolatilization
during the second stage. As a result, fewer residues were produced at the slow heating rate. In
contrast, at higher heating rate, the devolatilization process occurred sooner due to the increased
rate of heat transfer between the crucible and the sample. Faster heating rates cause the primary
devolatilization to complete rapidly because the temperature for secondary devolatilization has
been reached rapidly. From the DTG curves for different heating rates (Figure 3.5b), it was
concluded that the peak of the rate of devolatilization shifted to the higher value as heating rate
increased. Since the faster heating rate led to less efficient heat transfer, the devolatilization rate
increase faster than at lower heating rates, thus shifting the peak of the devolatilization rate. As a
result, char yield percentage increased as the heating rates increased, as shown in Table 3.5.
Table 3.5 Char yield percentage for different values of heating rate of the sample for
sawdust pyrolysis with average particle size of 352 µm and initial weight of 10 mg.
Heating rate (C/min)
Char yield (%)
10
16.23 (±0.11)
50
20.30 (±0.13)
5
20
11.81 (±0.35)
22.17 (±1.55)
54
(a)
(b)
Fig. 3.5 Pyrolysis curve of sawdust at different heating rates with particle size of 325 µm
and initial weight of 10 mg of sample. (a) TG profile and (b) DTG profile.
55
3.5.2 Kinetics of Sawdust Pyrolysis
In order to scale up the pyrolysis process, kinetic information is needed. Furthermore, kinetic
information can provide a better understanding of the mechanisms of thermal processes of
sawdust. The objective of the kinetics is to provide mathematical relationships between
temperature and conversion.
According to Figure 3.2, three visible events can be distinguished during the heating process of
the sawdust sample. The first weight loss corresponds to the moisture release and the drying of
the sample (30-110 °C). In a second event, between 110 and 400 °C, the lightest volatile
compounds evolve and this event is usually called primary devolatilization. Finally, the last step
corresponds to the secondary devolatilization, which happens above 400 °C.
In this work, experimental results were correlated as a function of the yield of volatile material
using a nonlinear model. The total volatile material can be obtained using the relation:
V  1  (C  A)
(3.2)
where C and A are the mass of fixed carbon and ash content, respectively. The final accumulated
yield of each event is represented by V1*, V2* and V3*. In practice, once the fixed carbon and ash
content is known, the final volatile material yield can be obtained as the remaining fraction. The
sawdust pyrolysis was assumed as two independent parallel devolatilization reactions (mainly
primary and secondary devolatilization), which are described by nth-order reactions as follows:


ni
dVi t 

 k i Vi  Vi t 
dt
(3.3)
56
where Vi(t) is the accumulated mass of released volatile material from event i up to time t, Vi* is
the ultimate yield of volatile material from event i up to t = ∞, ni is the reaction order of event i
and ki is the rate constant of event i:
 E 
k i  k 0i exp  i 
 RT 
(3.4)
where k0i is the pre-exponential factor, Ei is the activation energy for event i, R is the gas
constant and T is the temperature of the system. The total volatile material yield is computed by
the addition of:
V t    Vi t 
(3.5)
V    Vi
(3.6)
3
i 1
3

i 1
Since the process was held at constant heating rate (H), Equation (3.3) can be expressed as:


dVi t 
V  Vi t 
 ki i
dT
H

ni
(3.7)
Integration of Equation (3.7) gives:
Vi  Vi t 

Vi

T

 k exp E i / RT   
 1  (1  ni )    0i
 dT 
H
 
0 

1 /(1 ni )
(3.8)
Equation (3.8) contains an integral that can be solved by analytical solution. However, the
analytical solution contain a special function, thus required complex mathematical solution to
solve the problem. Various simplifications have been tried, and previous studies have presented
57
several approximations with varying complexity and accuracy [24]. In this study, the modified
Donskoi approximation was used to replace the integral form in Equation (3.8) [25].
Vi  Vi t 

Vi


 k 0i RT 2 exp E i / RT  

 1  (1  ni )  

Ei H



1 /(1 ni )
(3.9)
The kinetic parameters such as pre-exponential factor, activation energy and reaction order for
each event can be obtained by a nonlinear regression method on the TG data of the sawdust
pyrolysis.
In this work, a nonlinear optimization method was used to obtain the kinetic parameters of
pyrolysis of sawdust under different heating rates (5, 20 and 50 °C/min), which minimized the
sum of square differences between experimental and predicted values of evolved volatile
material in each stage (Table 3.6). In this process, GraphPad Prism was used to optimize the
parameters. The code built in the GraphPad consisted of an optimization algorithm to minimize
the error between the data and the model proposed. The challenge in this process was to have a
good value for an initial estimate for the optimization.
Table 3.6 Weight loss and ultimate devolatilization yield of the devolatilization events with
average weight prior to devolatilization of 9.91 mg at different heating rates.
Ultimate devolatilization yield
Heating rates
Weight after
(C/min) devolatilization (mg)
5
(wt% of total mass loss)
V1*
1.13
9.65
V2*
73.03
V3*
17.31
10
1.59
7.97
77.10
14.93
50
2.08
5.58
80.00
14.41
20
2.04
6.53
58
80.79
12.68
The kinetic parameters k0, E and n are listed in Table 3.7. The pre-exponential factor decreased
from the order of 106 to 103, and the activation energy also decreased from 80 to 61 kJ/mol for
stages 2 and 3 of the sawdust pyrolysis, respectively. The decrease in the activation energy might
be caused by the reactions that happened in each stage. Lignin degradation may be dominant in
the third stage, leading to lower activation energy. The order of the reaction of primary
devolatilization is approaching 1 (n = 0.9) and for the secondary devolatilization it was 1.78.
Comparison of reaction orders obtained from present work with the literature revealed that
primary devolatilization (stage 2) represents the devolatilization of cellulose and hemicelluloses
and the secondary devolatilization represents the degradation of lignin [26].
Table 3.7 Kinetic parameters of the three events considered in the kinetic model.
Stage 1
Stage 2
Stage 3
k0 (min-1)
1.41
1.90  106
1.01  103
E (kJ/mol)
4.81
79.53
60.71
n
0.36
0.91
1.78
Figure 3.6 shows good agreement between the experimental and predicted value of accumulated
volatile material yield curves (with respect to total volatile loss) at a heating rate of 10 °C/min.
According to this result, it was clear that the devolatilization data predicted from this model was
very similar to the experimental data obtained from TGA. In general, this model might be used to
predict the TG curves for different heating rates.
59
Fig. 3.6 Typical comparison of experimental data with predicted values at heating rate of
10 °C/min.
3.6 Conclusions
Pyrolysis of sawdust has been analyzed using TGA to study the effect of particle sizes, initial
weights and heating rates. The results from the proximate analysis showed that the volatile
material evolution was higher with larger particle sizes. In the pyrolysis process, the char yield
decreased as the particle size of the sample became larger. On the other hand, reducing the
particle size of the sample or increasing the initial weight or increasing the heating rate of
pyrolysis process increased the char production.
The devolatilization process of the sawdust samples during pyrolysis was divided into three noninteracting stages. The first stage was identified as the moisture loss process, the second as the
cellulose and hemicelluloses devolatilization and the third as being dominated by lignin
devolatilization. A modified devolatilization kinetic model was used to obtain the kinetic
60
parameters of the reactions. The reaction orders for the stages 2 and 3 were 0.9 and 1.7
respectively. Based on the activation energy and reaction order data obtained from the model, the
stage 2 represented the cellulose and hemicellulose devolatilization while the third stage by
lignin devolatilization. The result shows good agreement between the proposed model and the
experimental data for different heating rates of the process.
3.7 Acknowledgement
The authors wish to acknowledge the financial support of the Natural Science and Engineering
Research Council of Canada (NSERC).
61
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[17] Demirbas, A., Calculation of higher heating values of biomass fuels. Fuel, 76(5), pp. 431434.
[18] Zanzi, R., Sjostrom, K. & Bjornbom, E., Rapid Pyrolysis of Agricultural Residues at High
Temperature, Biomass Bioenergy, 23, pp. 357-366, 2002.
63
[19] Bridgeman, T.G., Darvel, L.I., Jones, J.M., Williams, P.T., Fahmi, R., Bridgwater, A.V.,
Barraclough, T., Shield, I., Yates, N., Thain S.C. & Donnison, I.S., Influence of Particle
Size on the Analytical and Chemical Properties of Two Energy Crops, Fuel, 86, pp. 60-72,
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[20] Kim, S.S., Kim, J., Park, Y.H. and Park, Y.K., Pyrolysis Kinetics and Decomposition
Characteristics of Pine Trees, Bioresour. Technol., 101, pp. 9797-9802, 2010.
[21] Becidan, M., Skreiberg, Ø. & Hustad, J.E., Products Distribution and Gas Release in
Pyrolysis of Thermally Thick Biomass Residues Samples, J. Anal. Appl. Pyrolysis, 78, pp.
207-213, 2007.
[22] Haykiri-Acma, H., The role of particle size in the non-isothermal pyrolysis of hazelnut
shell. J. Anal. Appl. Pyrolysis, 75, pp. 211-216, 2006.
[23] Demirbas, A., Effects of temperature and particle size on bio-char yield from pyrolysis of
agricultural residues. J. Anal. Appl. Pyrolysis, 72, pp. 243-248, 2004.
[24] Cai, J., Yao, F., Yi, W. & He, F., New temperature integral approximation for nonisothermal kinetics. AIChE J., 52, pp. 1554-1557, 2006.
[25] Donskoi, E. & McElwain, D.L.S., Approximate modelling of coal pyrolysis. Fuel, 78, pp.
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64
CHAPTER 4: CATALYTIC PYROLYSIS OF STRAW BIOMASSES (WHEAT, FLAX,
OAT AND BARLEY STRAW) AND THE COMPARISON OF THEIR PRODUCT
YIELDS
In this work, the pyrolysis of four different straw biomasses (wheat, oat, flax and barley straws)
was studied using a bench-scale pyrolysis system that was built in the University of Calgary’s
engineering machine shop and laboratory. The reactor was a batch-type horizontal reactor
enclosed by a horizontal split tubular furnace and consisted of a stainless-steel tube with a length
of 535 mm and an inside diameter of 22.5 mm. Thermocouples were placed within the reactor
system to measure the furnace, sample, reactor and outlet temperatures.
Pyrolysis creates three end-products: bio-char in the form of solid powder, bio-oil in the form of
black liquid, and gaseous materials. In order to determine the yield of each product (solid, liquid
and gas products), the reactor was connected to a condenser and liquid trap to recover the bio-oil.
The bio-char remained in the reactor, and the gaseous product yield was calculated by
subtraction. In this series of experiments, a zeolite catalyst was used in order to observe the
effect of the catalyst during pyrolysis.
Bio-char was recovered from the reactor and later analyzed using a thermogravimetric analyzer
for proximate analysis, the CHNS/O (carbon, hydrogen, nitrogen, sulphur and oxygen) analyzer
for elemental analysis, a calorimeter for determination of the heating value and a BrunauerEmmett-Teller system (BET Micromeritics ASAP 2020) for surface area measurement.
65
Bio-oil was analyzed using gas chromatography-mass spectrometry (GC-MS HP 6890) to
determine its chemical composition and later underwent elemental analysis and heating value
measurements. In addition, a Karl-Fischer titrator (KF Methrohm 870 Titrino) was used to
determine the water content of the bio-oil.
66
Catalytic Pyrolysis of Straw Biomasses (Wheat, Flax, Oat and Barley Straw)
and the Comparison of their Product Yields
A. Aqsha, M.M. Tijani & N. Mahinpey
Department of Chemical and Petroleum Engineering, Schulich School of Engineering, The
University of Calgary, Calgary, Canada, AB T2N 1N4
This article has been submitted to Energy Conversion and Management peer-reviewed journal in February 2016.
4.2 Abstract
In this study, the pyrolysis of several Canadian straw biomasses was studied using a
thermogravimetric analyzer and a bench-scale horizontal fixed-bed reactor, in order to better
understand the devolatilization process and to obtain information about the product yields of
these biomasses. The straw biomasses were converted through pyrolysis performed in a fixedbed reactor at temperatures of 500 °C to study the influence of the feedstock on product yields.
The effects of various catalysts on product yields are also discussed. When using zeolite
catalysts, the bio-oil and bio-char yields of the straw pyrolysis were increased to 46.44% and
38.77%, respectively, while the gas yield was decreased to 13.65%. The use of catalyst zeolite
ZY-SS had the most significant effect on overall bio-oil and bio-char yields, increasing the biooil yield by about 2% and the bio-char yield by 8%. This catalyst had the most significant effect
on the pyrolysis of flax straw, where the bio-oil yield was increased to 46.44%. In the pyrolysis
of oat straw, the use of the catalyst consistently decreased the gas yield; however, the bio-oil
yield increased the most significantly (43.32%) with the use of catalyst zeolite ZY-NS. The use
of zeolite ZY-NS also increased the bio-oil yield during the pyrolysis of barley straw (43.03%).
67
Keywords: Biomass, Biofuels, devolatilization process, kinetic of pyrolysis, proximate analysis,
pyrolysis of biomass.
4.3 Introduction
Using several different processes (chemical, biological and thermochemical), biomass can be
converted into various types of chemicals that can be used either as alternatives to fossil fuel,
such as gasoline and petrodiesel, or as value-added chemicals. Lignocellulosic straw biomasses
(wheat, flax, oat and barley) are considered promising renewable feedstock sources for the
production of chemicals and biofuels, and they are widely available in the Canadian Prairies. The
use of biomass or waste biomass, such as wheat straw, flax straw, barley straw, or sawdust, for
energy production will provide several advantages from an environmental perspective.
Pyrolysis is a thermochemical process that can be used to break down certain materials into a
liquid product called bio-oil [1]. Although pyrolysis is an old technology, it is becoming more
attractive than other thermochemical processes, as a result of significant progress in the past
decade [2, 3]. During pyrolysis, the applied heat decomposes the materials into a volatile
compound (condensed and uncondensed material) that will later produce bio-char, bio-oil, and
gaseous material.
Similar to wood, straw biomass from wheat, flax, oat, and barley is primarily composed of
cellulose, lignin, and hemicellulose [4]. Each straw biomass has a different composition that is
suspected to have a significant effect on the product yield and composition [5]. The temperature
68
of the reaction, heating rate, particle size, and residence time also have considerable influence on
the properties of the product and its composition [6, 7]. For instance, Haykiri-Acma [8]
suggested that increasing the heating rate to 50 °C/min leads to higher conversion rates due to
the better mass and heat transfer inside the reactor [9]. In addition, a temperature of 500 °C
should be used to maximize the liquid oil yield [10]. If these parameters are not met, secondary
reactions may occur, thereby decreasing the oil yield and leading to a higher yield of gas and
char [11].
Recently, the use of pyrolysis to produce fine chemicals that have low oxygen content such as
phenol has gained some attention [12-14]. It was suspected that low lignin content in biomass
caused the low production of phenolic compound [12]. Zhang et al. (2015) perform a fast
pyrolysis using magnetic solid base catalyst K3PO4/Fe3O4 and successfully increased the yield of
phenolic component about 1.5 times compared to non-catalytic pyrolysis. They conclude that the
catalyst would promote the decomposition of lignin to increase the phenolic yield [15]. Other
researchers also proposed the high density polyethylene (HDPE) material to be used in copyrolysis of almond shell to produce bio-oil containing higher hydrogen to carbon and oxygen
ratio [16]. They successfully reduced oxygen content up to 86% and produced bio-oil with H/C
ratios close to transport fuel. However providing pure and dry HDPE for co-pyrolysis might be
difficult due to the waste management system that most of the time combined this waste type
with other municipal solid waste.
In this research, the results of experimental studies on the pyrolysis of several Canadian straw
biomasses (wheat, flax, oat, and barley) are described. The pyrolysis of the straw biomasses was
69
performed in a fixed-bed reactor at temperatures of 500 °C to study the influence of the
feedstock on product yields. The effects of various catalysts on the product yields were also
investigated. To evaluate the effects of the zeolite catalyst on the straws, three forms of zeolite
catalysts were used (silica-sodium-based solution, silica-based solution and H-form of the silicabased solution), which were named as ZY-NS, ZY-SS and HZY-SS, respectively. The results
from the comparison of biomasses provide useful information about the suitability of each
biomass for particular end products, such as bio-char, bio-oil, and gaseous material.
4.3 Experimental Section
4.4.1 Raw Biomass Sample and catalysts
The straw biomass samples (wheat, flax, oat, and barley) used in this study were obtained from a
farm in Saskatchewan, Canada. The straw biomasses were ground and sieved to obtain an
average particle size of less than 1 mm. The chemical composition of the samples according to
various documented sources is set out in Table 4.1 while the elemental composition of the
catalysts and their surface area are presented on Table 4.2
Table 4.1 Chemical composition of wheat, oat, flax and barley straw samples
Cellulose
Hemicellulose
Lignin
a
Wheat Straw Oat Straw Flax Straw Barley Straw
34.2a
37.6a
53.0b
33.8c
13.9a
12.9a
24.0b
13.8c
23.7a
23.3a
13.0b
21.9c
Adapa et al [17]; b Buranov and Mazza [18]; c Mussatto and Teixeira [19]
70
Table 4.2 Elemental composition and surface area data of the catalysts
Si/Al
Si (%wt)
Al (%wt)
Na (%wt)
BET (m2/g)
ZY-NS ZY-SS HZY-SS
1.67
2.26
19.1
15.7
31.9
13.1
645
2.26
35.5
41.29
12.0
10.8
656
18.2
437
4.4.2 Proximate and Elemental Analysis
Proximate analyses of the straw biomasses were performed using a thermogravimetric analyzer
(TGA, NETZSCH TG 209 F1 Libra). All experiments consisted of three steps: drying,
devolatilization in a nitrogen inert atmosphere, and combustion with air (Figure 4.1). About 10
mg of each sample with a particle size of 1 mm were used for this experiment. Initially, each
biomass sample was kept at 25 °C for 4 min in a nitrogen atmosphere. The moisture content was
determined from the weight loss when the sample was heated at a rate of 85 °C/min up to 110 °C
and held constant for 5 min.
Devolatilization began once the temperature reached 110 °C, and a heating rate of 80 °C/min
was maintained up to 900 °C. The final temperature was held constant for 7 min in an air
atmosphere to allow for complete combustion. The flow rate of the nitrogen and air was
maintained at 45 mL/min.
71
Fig. 4.1 Typical profile for proximate analysis using a TGA
Elemental analyses were performed using a 2400 carbon, hydrogen, nitrogen, sulphur, oxygen
(CHNS/O) analyzer (2400 elemental analyzer, Perkin-Elmer). The combustion time was about 5
minutes, and the packing of the combustion tube consisted of chromium oxidizer, silver tungstate
on magnesium oxide, and silver vanadate. The solid sample was placed in a tin capsule, while
the liquid was placed in a sealed aluminium capsule.
4.4.3 Pyrolysis Experiment
Pyrolysis experiments were carried out using the TGA and a batch-type horizontal reactor
enclosed within a horizontal split tubular furnace. The reactor consisted of a stainless-steel tube
with a length of 535 mm and an inside diameter of 22.5 mm. Thermocouples were placed within
the reactor system to measure the temperatures of the furnace, pyrolysis reactor, and outlet.
Nitrogen was used as the inert gas with a constant flow rate of 50 mL/min throughout the
process. During the experiments, each sample was heated at a rate of 100 °C/min to a final
temperature of 500 °C at atmospheric pressure.
72
At the end of the reactor, volatile products (gas and liquid) were isolated using a separator that
was submerged in a 0 °C liquid water-ice chamber. The liquid product (bio-oil) was collected at
the end of the reaction and measured using a laboratory scale.
Fig. 4.2 Thermogravimetric profiles of raw biomasses subject to pyrolysis.
For each experiment, 10 g of the straw biomass were loaded into the stainless steel reactor. Each
experiment was performed with the same weight at a temperature of 500 °C for about 1 hour.
The product yields were calculated using the weight data of the bio-char, bio-oil and gas
products, and the initial biomass sample. All experiments were performed at least twice, and the
uncertainty associated with the data was within 2%. Figure 4.2 provides the profiles of the raw
biomasses subject to pyrolysis using a TGA.
73
4.4.4 Product Analysis and Characterization
Pyrolysis creates three end products: bio-char in the form of solid powder, bio-oil in the form of
black liquid, and gaseous materials. Bio-char was recovered from the reactor and later analyzed
using the TGA for the proximate analyses, the CHNS/O analyzer for elemental analyses, a
calorimeter for determination of the heating values, and a Brunauer–Emmett–Teller system (BET
Micromeritics ASAP 2020) for surface area measurements.
Bio-oils were analyzed using gas chromatography / mass spectrometry (GC-MS HP 6890) to
determine its chemical composition and also underwent elemental analyses and heating value
measurements. In addition, a Karl-Fischer titrator (KF Methrohm 870 Titrino) was used to
determine the water contents of the bio-oils.
4.5.1 Proximate and Elemental Analysis
The results of the proximate and elemental analyses of all four biomass samples are presented in
Table 4.3. These results demonstrate that the moisture content of the biomasses was in the range
of 3-5%, the volatile content about 74-76%, the fixed carbon in the range of 14-19%, and the ash
content below 5%.
The data from these analyses of condensable (bio-oil) and non-condensable (gas) materials
produced during pyrolysis can be used to predict the composition of products derived from
pyrolysis. It was predicted that the combined amount of bio-oil and gaseous materials produced
through pyrolysis would be approximately 75%. Based on the elemental analysis data, the bio-oil
74
product would be expected to contain a high amount of oxygen. The elemental analyses also
proved that the sulfur contents of the biomasses were very small (~1%), while the oxygen
contents were about 45% (calculated by difference). Both values are common among straw and
wood biomasses.
Table 4.3 Proximate and elemental analyses of biomasses
Proximate Analysis (wt%)
Wheat Straw
Oat Straw
Flax Straw
Barley Straw
5.30
4.38
4.75
2.69
Moisture
Volatile
75.88
74.04
74.80
75.64
Ash
4.69
3.21
1.12
4.38
Fixed Carbon
Elemental Analysis (wt%)
14.12
18.37
19.32
17.28
C
43.64
43.26
46.76
44.83
N
0.68
0.88
1.11
0.93
H
S
O*
5.82
6.12
1.08
1.14
44.09
45.39
6.34
1.14
43.53
6.25
1.18
42.43
* Weight of O was obtained by subtracting the sum of the CHNS and ash contents from 100% (percentage).
Table 4.4 presents the data comparison of the various raw biomasses and their bio-char products
using proximate and elemental analyses. The volatile matter, as a percentage of biomass, was
reduced to as low as 18.23 % after pyrolysis (bio-char). The proximate analyses revealed that the
bio-chars were composed of about 66.03% fixed carbon and 22.2% volatile matter. The high
amount of carbon increased the energy density of the char, which is reflected in the heating value
data measured with the calorimeter.
75
The elemental analyses demonstrated that the bio-chars had carbon compositions in the range of
66.42% (oat straw) to 72.61% (barley straw), representing increases about 53.5% and 62% from
their original values, respectively. The oxygen content was greatly reduced from 44.09% to a
value as low as 13.46% (wheat straw). These results suggest that most of the oxygen transformed
into liquid and gaseous products, while most carbon remained as solid products.
Table 4.4 Data comparison between raw biomass and its bio-char product
Biomass Sample
Proximate Analysis (wt%)
Moisture
Raw
wheat
straw
5.30
Raw oat Raw flax
straw
straw
4.38
4.75
Raw
barley
straw
2.69
Wheat
Flax
Barley
Oat straw
straw biostraw biostraw biobio-char
char
char
char
3.67
4.93
2.83
2.26
Volatile Matter
75.88
74.04
74.80
75.64
26.65
20.78
18.23
23.14
Ash
4.69
3.21
1.12
4.38
12.13
11.22
4.55
5.52
Fixed Carbon
Elemental Analysis (wt%)
14.12
18.37
19.32
17.28
57.55
63.08
74.40
69.09
C
43.64
43.26
46.76
44.83
67.87
66.42
71.73
72.61
N
0.68
0.88
1.11
0.93
3.02
1.26
2.32
1.73
H
S
Oa
5.82
1.08
6.12
1.14
6.34
1.14
6.25
1.18
2.97
0.55
2.34
2.80
0.49
0.61
3.09
0.62
44.09
45.39
43.53
42.43
13.46
20.28
17.99
16.44
H/C Molar Ratio
1.59
1.69
1.62
1.66
0.52
0.42
0.47
0.51
O/C Molar Ratio
0.76
0.79
0.70
0.71
0.15
0.23
0.19
0.17
C3.6H5.8O2.8
C3.6H6.1O2.8
C3.9H6.3O2.7
C3.7H6.2O2.7
C5.7H2.9O0.8
C5.5H2.3O1.1
C6.0H2.8O1.1
C6.0H3.1O1.0
17.97
17.51
18.62
17.95
23.40
23.99
27.67
27.70
2.438
1.535
2.579
1.889
6.056
1.991
1.661
2.287
H/Ceff Molar Ratio =
(H-2×O)/C
Empirical Formula
Heating Value (MJ/kg, dry)
Surface Area (m2/g, dry
basis)
a
0.07
0.11
0.22
0.24
0.22
0.01
0.09
O was obtained by subtracting the sum of the CHNS and ash contents from 100% (percentage).
76
0.17
Fig. 4.3 Location of straw biomasses and their biochar products on a Van Krevelen
diagram.
The hydrogen/carbon (H/C) molar ratio, effective hydrogen/carbon (H/Ceff) molar ratio and
oxygen/carbon (O/C) molar ratio of each raw material and bio-char product were also calculated
to investigate whether the raw samples and bio-char products had any similarities. It was found
that the H/C ratios of the raw biomasses and bio-chars were around 1.6 and 0.5, respectively.
According to the Van Krevelen diagram (Figure 4.3), the straw biomass samples (wheat, oat,
flax, and barley) were located in the biomass zone, while bio-char products were located below
the coal zone. This suggests that the produced bio-char products had higher heating values than
those of the raw biomasses and had compositions that were closer to those of coal. In addition,
the empirical analysis showed a notable reduction in hydrogen, which suggests the formation of
methane (CH4), H2 and H2O during pyrolysis, which was confirmed by the gas analysis and the
Karl Fischer titration of bio-oil.
77
4.5.2 Pyrolysis of Raw Biomass
The three end products of the pyrolysis process were collected and measured to determine the
yield of each product. The bio-char product was gathered from the reactor in the form of black
solid powder, bio-oil was collected from the condenser unit connected to the reactor, and gaseous
product was determined by the difference.
A comparison can be made between the volatile content produced (Table 4.5) during pyrolysis
using a TGA and the combined yields of the bio-oil and gas from each sample (Table 4.6)
produced using a bench-scale reactor. It was shown that the yields of both products during
pyrolysis were close to the volatile content data of each sample with a discrepancy of about 79%. The total bio-oil and gas yields were always below the volatile content produced in
proximate analyses.
Table 4.5 Product yield comparison of the pyrolysis of wheat, oat, flax and barley straws
using a TGA
Yield
Moisture
Volatiles
Char + Ash
5.6
68.8
25.6
4.6
69.1
26.3
4.5
74.4
21.1
3.6
73.2
22.6
Table 4.6 Product yield comparison of the pyrolysis of wheat, flax, oat and barley
straws using bench scale reactor
Yield
Bio-char
Bio-oil
Gaseous product
36.2
40.5
23.3
32.7
40.0
27.3
78
32.1
33.5
27.7
30.7
40.2
35.8
The results suggest that the volatile products (liquid and gas) produced during pyrolysis
contained a higher oxygen percentage (less carbon in total) compared to the volatile materials
produced from the proximate analysis procedure. This discrepancy may have been a result of
differing temperature conditions of the processes and can also be explained by analyzing the biochar product resulting from pyrolysis as shown in Table 4.5. The elemental analyses of the biochar produced during pyrolysis still contained about 2-3% hydrogen and as high as 20% oxygen.
The hydrogen, oxygen, and carbon in the char can be used to produce more volatile materials
(bio-oil and gaseous product) with the use of a catalyst, a faster heating rate, or perhaps a
different pyrolysis temperature.
The lower sulfur content of the bio-chars (Table 4.7) compared to those of the raw biomass
samples (Table 4.3) and the GC-MS analysis results suggest that half of the sulfur may have
been converted to sulfur dioxide (SO2) by oxidation, hydrogen sulfide (H2S) by reduction, and
carbonyl sulfide (COS). In a previous study, Shao et al. [20] concluded that SO 2, H2S and CO
gases can be produced under pyrolysis in the temperature range of 200°C to 500°C).
Table 4.7 Elemental analysis of bio-char produced from each biomass sample
Composition
Char
Char
Char
Char
C
67.87
66.42
71.73
72.61
N
3.02
1.26
2.32
1.73
H
S
2.97
0.55
2.34
0.49
79
2.8
0.61
3.09
0.62
The various yields of the pyrolysis products, such as liquid, gas and char, from all biomasses are
presented in Figure 4.4. The wheat straw biomass produced the maximum bio-oil yield of 40.2%,
while the maximum gas yield of 30.9% was obtained from barley straw. The yields of the biochar products, were in the range of 32.1% to 36.2%. The difference between the product yields
of each biomass may have been influenced by the cellulose, hemicellulose and lignin
compositions of the raw biomasses (Table 4.1). However, there were no clear trends between the
structural compositions of the biomasses and the product yields.
Gas
Fig. 4.4 Product yields (wt%) from pyrolysis of straw biomass
The combined amount of bio-oil and gas products did not exceed the amount of volatile
compounds that were produced during proximate analysis (Table 4.3) and from TGA pyrolysis
(Table 4.5). Nonetheless, the ash composition data from the proximate analyses suggest that the
higher the ash content of the biomass resulted in less volatile produced during pyrolysis. This
may indicate that inorganic compound within biomass (ash) will not have a direct impact on the
cracking of biomass into volatiles.
80
4.5.3 Catalytic Pyrolysis of Raw Biomasses
Three different catalysts were used to examine their respective effects on product yields. As
shown in Figure 4.5, the use of catalyst ZY-SS (#2) had the most significant effect in increasing
the yields of bio-oil (by about 2%) and bio-char (by up to 8%). The use of catalyst #2 also had
the most significant effect on the pyrolysis of flax straw, increasing its bio-oil yield up to 46.4%.
In the pyrolysis of oat straw, the use of a catalyst decreased the gas yield; however, the yield of
bio-oil had the highest increase (43.3%) with the use of catalyst ZY-NS (#1). The use of catalyst
#1 also increased the bio-oil yield during the pyrolysis of barley straw (43.0%).
Gas
Fig. 4.5 Comparison of the product yields among the biomasses
4.5.4 Analysis of Pyrolysis Products
Proximate and CHNS analyses were performed of the bio-char products from pyrolysis. The
compositions of the proximate analyses and CHNS compositions between raw biomasses and
bio-chars from pyrolysis reactions using different feedstocks and catalysts were compared. As
can be seen in Table 4.8, bio-chars contained higher percentages of carbon. The pyrolysis broke
81
down the chemical bonding of biomasses and released more hydrogen and oxygen from their
chemical structure, forming volatile material that later condensed as bio-oil, with the remainder
as non-condensable gases. The carbon percentage increased from about 44% up to about 72%
(char from barley straw).
Table 4.8 Proximate and CHNS analysis of bio-char products after pyrolysis
Sample
Catalyst Moisture Volatile
Wheat straw
-
3.67
26.65
Flax straw
-
2.83
18.23
Oat straw
Barley straw
-
-
4.93
2.26
20.78
23.14
Fixed
Carbon
Ash
C
H
N
S
57.55
12.13 67.87 2.97 3.02 0.55
74.40
4.55
63.08
69.09
11.22 66.42 2.34 1.26 0.49
5.52
71.73 2.80 2.32 0.61
72.61 3.09 1.73 0.62
Wheat straw
#1
2.11
13.99
53.78
30.11 61.34 2.79 1.19 0.46
Flax straw
#1
1.83
7.50
75.41
15.25 62.89 2.77 2.03 0.57
Wheat straw
#2
1.79
13.18
54.49
30.55 59.82 2.87 1.29 0.61
Flax straw
#2
1.49
13.97
72.97
11.57 60.12 2.63 1.48 0.45
Wheat straw
#3
1.64
8.08
58.67
26.62 67.32 2.46 1.14 0.52
#3
0.84
14.18
68.40
Oat straw
Barley straw
Oat straw
Barley straw
Oat straw
Flax straw
Barley straw
#1
#1
#2
#2
#3
#3
3.44
2.02
2.82
2.35
8.70
20.87
14.10
20.97
2.60
13.32
2.29
24.90
68.77
62.61
64.70
61.78
52.44
59.23
19.09 64.11 2.29 1.06 0.56
14.51 65.38 3.12 2.02 0.63
18.38 64.36 2.37 1.15 0.54
14.90 64.93 3.33 1.40 0.70
31.64 62.44 2.55 1.00 0.59
16.58 58.67 2.23 1.66 0.42
13.58 69.27 2.97 1.28 0.62
Bio-oil produced from pyrolysis often contains water in the range of 15% to 30% [20, 21]. The
high amount of water is considered one drawback of pyrolytic oil. In our study, the water
contents of the bio-oils produced from pyrolysis were determined using a Karl-Fischer titration
system and are presented in Table 4.9. The water contents of the products of all reactions ranged
82
from 11.66% to 17.56%. When there was no additional catalyst present during the reaction,
water formed during the reaction and increased the initial value of water content of the biomass,
ranging from 2.75 to 5.3% to about 14.2% to 17.6%. The use of a catalyst, however, showed
very little influence on water formation and only reduced it by about 2%.
Table 4.9 Water content of bio-oil produced from pyrolysis
Sample
Wheat straw
No Catalyst
Oat straw
Flax straw
Barley straw
17.6
Water content of bio-oil (% weight)
KS23-ZY-NaSi
KS20-Sisol
HZY Sisol
15.5
15.4
15.5
17.1
16.4
14.2
16.5
13.1
11.7
15.7
12.1
12.5
16.0
14.6
12.3
Table 4.10 Heating value (MJ/kg) of biomasses and its products
Sample
Wheat straw
Oat straw
Flax straw
Barley straw
No catalyst
23.40
23.99
27.67
27.70
KS20-Sisol
21.48
22.97
25.27
24.64
Raw biomass
Bio-char product
KS23-ZY-NaSi
HZY Sisol
Bio-oil product
17.97
21.43
21.57
17.51
21.44
21.44
18.62
23.54
26.51
17.95
24.68
26.20
No catalyst
27.16
27.08
27.39
27.47
KS20-Sisol
27.26
27.66
27.42
27.93
KS23-ZY-NaSi
HZY Sisol
27.07
26.97
27.73
27.13
83
27.39
27.41
27.47
27.93
Table 4.10 presents a clear comparison of the heating values among the raw biomasses and their
pyrolysis products. As can be seen for all of the samples, the heating values of the bio-char and
bio-oil products were higher (up to a 55% increase) compared to their original heating values
(raw biomass). However, when the heating value of the product from the non-catalytic pyrolysis
was compared to the product from the catalytic pyrolysis, there was no significant increase or
reduction.
The GC-MS analyses showed that most of the chemicals produced from pyrolysis contained 1, 2
or 3 oxygen atoms. By performing a further upgrading reaction, such as hydrodeoxygenation, the
amount of oxygen can be reduced from these chemicals. It was also observed that most
components that were produced contained an aromatic ring (benzene, furan and cyclopentane)
and had carbon atoms ranging from C2 to C8. Table 4.11 shows 18 components that were
produced in all reactions, with or without catalyst; however, there was a variation in terms of
their concentrations (% area). For example, a few components, including 1-hydroxy-2-butanone,
furfural, acetoxyacetone, 2-cyclopenten-1-one, guaiacol and 2,6-dimethoxyphenol, had higher
concentrations, ranging from 4% to 19% while the rest of the components had concentrations of
mostly below 2%. Catalyst ZY-SS (#2) doubled and almost tripled the production of furfural in
the pyrolysis of wheat and flax straws, respectively.
84
Table 4.11 GC-MS analysis of bio-oil produced from straw biomass with and without catalyst
Sample & catalyst in the reaction
Sample and catalyst used in the pyrolysis
Wheat
Oat
Flax
Barley
Wheat
Oat
Flax
Barley
Wheat
Oat
Flax
Barley
Wheat
Oat
Flax
Barley
C2H4O2
1.28
2.89
1.06
1.74
1.58
1.95
0.86
1.45
-
-
-
-
1.10
1.89
0.94
1.03
trans-1,3-Cyclopentanediol
C5H10O2
0.43
2.59
1.47
1.93
1.70
1.81
0.80
1.00
2.57
1.85
0.71
0.70
0.85
4-Hydroxy-4-methyl-2pentanone
C6H12O2
0.94
3.68
2.65
1.93
1.61
Acetoxyacetone
C5H8O3
4.10
5.22
5.43
Chemical
Formula
1-Hydroxy-2-butanone
C4H8O2
Acetic Acid
-
-
5.52
11.07
9.13
10.64
2.74
5.44
C6H8O
1.81
C6H8O
Tetrahydro-2-furanmethanol
o/m/p-Cresol
Furfural
2-Furanmethanol
C5H4O2
4-Ethylguaiacol
2,6-Dimethoxyphenol
8.22
7.65
8.32
5.16
8.09
11.09
4.25
10.16
19.26
5.16
16.91
2.79
1.39
1.86
6.17
7.58
4.08
6.69
15.41
11.31
7.96
6.48
8.15
4.81
1.31
6.14
3.04
4.16
2.51
3.01
5.56
7.67
5.50
5.82
3.65
5.19
3.54
2.40
2.66
2.35
2.58
1.81
2.31
3.39
1.97
3.95
3.52
2.13
2.18
1.79
2.14
2.64
3.04
2.45
2.50
3.22
2.88
1.94
2.71
2.95
3.25
2.80
2.24
2.78
C5H10O2
1.58
3.83
3.11
2.07
1.96
2.72
2.44
4.00
3.21
2.42
3.63
2.16
2.47
C7H8O
5.14
1.76
3.54
C8H10O2
2.03
1.39
C8H10O3
6.85
C6H8O2
C7H8O2
C9H12O2
1.75
3.51
5.42
9.88
1.09
4.71
4.61
4.68
2.05
4.35
5.69
9.54
4.86
with catalyst #3 (HZY-SS)
3.26
C5H6O2
C6H6O
4-Methylguaiacol (Creosol)
7.55
with catalyst #2 (ZY-SS)
12.81
Phenol
Guaiacol
9.23
with catalyst #1 (ZY-NS)
11.81
C4H6O2
2-Cyclopenten-1-one
5.49
-
6.32
4-Hydroxybutyric acid lactone
-
4.29
0.98
3.90
2.56
3.28
2.24
3.97
0.54
3.62
3.21
3.67
2.63
2.23
3.63
1.88
3.37
1.57
3.02
3.39
5.51
7.22
5.66
4.49
5.32
9.13
15.59
7.75
10.89
6.76
11.24
2.55
2.23
1.52
1.55
1.96
2.10
10.06
3.96
1.97
2.77
1.38
8.39
3.33
4.40
1.52
0.39
6.58
7.49
85
1.22
3.85
2.44
3.11
6.62
7.72
1.19
2.75
1.29
2.76
5.28
2.26
5.60
6.94
1.78
2.63
4.26
3.93
6.92
11.14
5.40
16.23
1.84
3.21
1.65
3.95
3.09
4.12
3.30
1.32
4.01
4.08
5.48
2.84
3.55
1.48
1.20
9.62
4.19
5.01
3.69
6.60
4.09
3.96
5.54
1.96
6.36
2.84
4.13
5.60
1.36
4.16
4.14
3.88
4.97
2.45
3.16
3.93
4.32
5.49
0.96
1.60
0.90
5.13
6.89
3.31
9.94
8.80
2.16
6.40
0.92
3.44
2.37
1.88
4.97
4.07
3.88
2.30
6.27
3.66
2.42
2.87
1.25
7.51
10.08
1.95
1.31
6.79
0.94
2.96
6.26
2.05
6.55
Table 4.12 Micro-GC analysis of gas produced from wheat straw biomass with and without
catalyst
H2
CH4
CO
CO2
No catalyst
0.9%
1.2%
28.8%
68.1%
KS20-Sisol
1.8%
1.4%
34.7%
61.3%
KS23-ZY-NaSi
HZY Sisol
1.7%
1.3%
1.5%
1.5%
31.0%
30.6%
64.9%
65.5%
The comparison of hydrogen (H2), methane (CH4), carbon monoxide (CO) and carbon dioxide
(CO2) compositions of the pyrolysis reactions of wheat straw are shown in Table 4.12. While the
production of H2 and CH4 are only about 3% of the total amount, CO and CO2 accounted for
most of the produced gases (around 96%). The use of catalyst has changed the distribution of gas
compositions as can be seen in Table 4.12. The production of H 2 gas increases when catalyst was
used. The increase of CH4 gas about 11.5% to about 24.6% was also noticed for the catalytic
reaction. The increase of H2 and CH4 gases can be related to the composition of bio-oil and also
the yield of bio-char. It can be seen from Table 4.11, when the catalyst was used, there is an
increase in most oxygen rich compound. When rich oxygen compounds was formed, cracking of
cellulose or lignin molecule will release more H2 and CH4 in the gas phase. In addition, there is
also an increase of bio-char yield when catalyst was used (Fig. 4.5).
From the analysis of the products, we found that there are no significant change on C, H and O
composition of bio-char. However interesting result was found on bio-oil composition produced
from pyrolysis with and without catalyst. The use of zeolite based catalyst increased the
production of rich-oxygenated compound (with benzene and cyclopentane ring) that we were
86
trying to avoid despite the increase of the bio-oil yield. The use of a catalyst, however, showed
very little influence on water formation and only reduced it by about 2%. From calorimeter
measurement, the heating values of the bio-char and bio-oil products were higher (up to a 55%
increase) compared to their original heating values (raw biomass). From gas product analysis, we
found that there is an increase of H2 and CH4 gas when catalyst was used that can be related to
the composition of bio-oil and also the yield of bio-char.
4.5 Conclusions
The results of the proximate analyses of raw biomasses can be used to predict product yields
produced during pyrolysis, with the total yields of bio-oil and gaseous product consistently lower
than the volatile content. The ash composition values from the proximate analyses suggest that a
higher ash content suppressed the production of gaseous product. The pyrolysis of four different
biomasses was performed both with and without a catalyst. It was observed that the bio-oil yield
during the pyrolysis increased with the use of a zeolite-based catalyst. The use of a zeolite ZYSS catalyst showed the most significant effect in increasing the bio-oil yield during the pyrolysis
of wheat and flax straws, increasing its bio-oil yield up to 46.4%, whereas the use of zeolite ZYNS showed the most significant effect during the pyrolysis of oat and barley straws. From GCMS analysis of bio-oil, it was found that catalyst ZY-SS (#2) doubled and almost tripled the
production of furfural in the pyrolysis of wheat and flax straws.
87
4.6 Acknowledgement
The authors wish to acknowledge the financial support of the Natural Sciences and Engineering
Research Council of Canada (NSERC) and the Ministry of Higher Education of the Kingdom of
Saudi Arabia. We would like to thank Aurore Coussirat-Bourg for her contribution in the
experimental part of this study.
88
4.7 References
[1]
Mahinpey, N., Murugan, P., Mani, T. & Raina, R., Analysis of bio-oil, bio-gas and bio-char
from pressurized pyrolysis of wheat straw using a tubular reactor. Energy and Fuels, 23,
pp. 2736- 2742, 2009.
[2]
Scott, D.S. & Piskorz, J., The continuous flash pyrolysis of biomass. Canadian Journal of
Chemical Engineering, 62, pp. 404-412, 1984.
[3]
Mohan, D., Pittman, C.U. & Steele, P.H., Pyrolysis of Wood/Biomass for Bio-Oil: A
Critical Review. Energy Fuels, 20, pp. 848-889, 2006.
[4]
Bicho, P.A. & Stumborg, M.A., Wheat straw: a viable fibre source for Canada? Pulp &
Paper Canada, pp. 146-149, 1998.
[5]
Wang, S., Guo, X., Wang, K. & Luo, Z., Influence of the interaction of components on the
pyrolysis behavior of biomass. Journal of Analytical and Applied Pyrolysis, 91(1), pp. 183189, 2011.
[6]
Beis, S.H., Onay, Ö. & Koçkar, Ö.M., Fixed-bed pyrolysis of safflower seed: influence of
pyrolysis parameters on product yields and compositions. Renewable Energy, 26 (1), pp.
21-32, 2002.
[7]
Vamvuka, D., Bio-oil, solid and gaseous biofuels from biomass pyrolysis processes - an
overview. International Journal of Energy Research, 35(10), pp. 835-862, 2011.
[8]
Haykiri-Acma, H., Yaman, S. & Kucukbayrak, S., Effect of heating rate on the pyrolysis
yields of rapeseed. Renewable Energy, 31(6), pp. 803-810, 2006.
[9]
Biagini, E., Fantei, A. & Tognotti, L., Effect of the heating rate on the devolatilization of
biomass residues. Thermochimica Acta, 472(1-2), pp. 55-63, 2008.
89
[10] Mani, T., Murugan, P., Abedi, J. & Mahinpey, N., Pyrolysis of Wheat Straw in a
Thermogravimetric Analyzer: Effect of Particle Size and Heating Rate on Devolatilisation
and Estimation of Global Kinetics. Chemical Engineering Research and Design, 478, pp.
1-7, 2010.
[11] Hosoya, T., Kawamoto, H. & Saka, S. Pyrolysis behaviors of wood and its constituent
polymers at gasification temperature. Journal of Analytical and Applied Pyrolysis, 78 (2),
pp. 328-336, 2007.
[12] Mu, W., Ben, H. X., Ragauskas, A. & Deng, Y. L., Lignin pyrolysis components and
upgrading – technology review, Bioenergy Res., 6, pp. 1183-1204, 2013.
[13] Kim, J. S., Production, separation and applications of phenolic-rich bio-oil – a review,
Bioresour. Technol., 178, pp. 90-98, 2015.
[14] Effendi, A., Gerhauser, H. & Bridgwater, A.V., Production of renewable phenolic resins by
thermochemical conversion of biomass: a review, Renew. Sust. Energy Rev., 12, pp. 20922116, 2008.
[15] Zhang, Z., Lu, Q., Ye, X., Li, W., Hu, B. & Dong, C., Production of phenolic-rich bio-oil
from catalytic fast pyrolysis of biomass using magnetic solid based catalyst, Energy
Convers.. & Manage., 106, pp. 1309-1317, 2015.
[16] Önal, E., Uzun, B. B. & Pütün, A. E., Bio-oil production via co-pyrolysis of almond shell
as biomass and high density polyethylene, Energy Convers. Manage., 78, pp. 704–710,
2014.
[17] Adapa, P., Tabil, L. & Schoenau, G., Compaction characteristics of barley, canola, oat and
wheat straw. Biosystems Engineering, 104, pp. 335-344, 2009.
90
[18] Buranov, A. U. & Mazza, G., Lignin in straw of herbaceous crops. Industrial Crops and
Products, 28, pp. 237-259, 2008.
[19] Mussatto, S. I. & Teixeira, J.A., Lignocellulose as raw material in fermentation processes.
Current Research, Technology and Education Topics in Applied Microbiology and
Microbial Biotechnology, pp. 897-907, 2010.
[20] Oasmaa, A. & Czernik, S., Fuel Oil Quality of Biomass Pyrolysis Oils - State of the Art for
the End Users. Energy & Fuels, 13, pp. 914-921, 1999.
[21] Bridgewater, A. V., Review of fast pyrolysis of biomass and product upgrading. Biomass
and Bioenergy, 38, pp. 68-94, 2012.
91
CHAPTER 5: CATALYTIC HYDRODEOXYGENATION OF GUAIACOL AS LIGNIN
MODEL COMPONENT USING NI-MO/TIO2 AND NI-V/TIO2 CATALYSTS
In order to understand the behavior of the bio-oil component during the upgrading process, a
hydrodeoxygenation (HDO) reaction was performed for a main bio-oil component called
guaiacol. In this work, we focused on catalyst screening and the distribution of the product
formed by the reaction. The objective of the study was to find a suitable catalyst that could be
used to transform highly oxygenated components such as guaiacol into lesser oxygenated
compounds, such as benzene, cyclohexane and phenol.
The catalysts were prepared using an incipient wetness impregnation technique with an aqueous
solution of the respective metal precursors. The experiments were performed in a 30 mL batch
reactor made of stainless steel (Swagelok). Reaction parameters such as temperature, reaction
time and hydrogen gas to guaiacol ratio were varied using the optimized catalyst. Blank reactions
(without hydrogen, without catalyst, without hydrogen and catalyst, and bare support) were also
carried out under identical conditions.
92
Catalytic Hydrodeoxygenation of Guaiacol as Lignin Model Component Using
Ni-Mo/TiO2 and Ni-V/TiO2 Catalysts
Aqsha Aqsha , Lakshmi Katta , Nader Mahinpey
This article was published in Catalysis Letters, 145(6), pp. 1351-1363, 2015.
5.2 Abstract
Catalytic hydrodeoxygenation of guaiacol (2-methoxy phenol), an oxygen rich lignin model
compound, has been investigated aiming at the elucidation of active catalysts for production of
deoxygenated products. All catalysts were synthesized by impregnation technique. Screening of
different catalysts unveiled Ni-Mo/TiO2 as the most active catalyst. Ni-Mo/TiO2 was compared
with Ni-V/TiO2 to understand the influence of promoter (Mo and V); nevertheless, Ni-V/TiO 2
produced no positive effect compared to Ni-Mo/TiO2. Structural investigation was performed
using XRD, TEM, BET surface area and TPD measurements. As evidenced by XRD and TEM,
all catalysts composed of nano-sized particles. Ni-Mo/TiO 2 showed small sized finely dispersed
particles, on the other hand large particles and loss of dispersion noted for Ni-V/TiO 2 and
Ni/TiO2, respectively. BET surface area measurement depicted Ni-Mo/TiO2 catalyst presented
high surface area with optimal mesopores than Ni-V/TiO 2. The NH3-TPD data revealed that NiMo/TiO2 acidic strength is higher than the Ni-V/TiO2. Influence of catalysts and reaction
variables were investigated using both Ni-Mo/TiO2 and Ni-V/TiO2 to determine their potential
93
role on guaiacol conversion. High activity of Ni-Mo/TiO 2 during wide range of conditions could
be attributed to: (i) small sized and finely dispersed active metal particles, (ii) more mesopores,
and (iii) high acidic strength. Water as a solvent, showed no impact on Ni-V/TiO 2 performance,
while on Ni-Mo/TiO2, guaiacol conversion and phenol selectivity inclined to decrease.
5.3 Graphical Abstract
Keywords: Hydrodeoxygenation, Lignin, Ni-based catalyst, Impregnation, Guaiacol
94
5.4 Introduction
Due to depletion in petroleum resources combined with increasing energy demand and inevitable
environmental concerns from fossil fuels, it is vital to develop economical and energy-efficient
processes for the sustainable fuel production. To achieve this, several approaches have dragged
preponderance attention [1–6]. Utilization of biomass to produce bio-fuels is one of the simplest
and cheapest methodologies for the development of sustainable energy [7]. Nonetheless,
presence of excess oxygen in liquid products derived thermochemical processes of lignocellulose
biomass imparts poor stability and low heating values, which made these oils unsuitable to be
used as transportation fuel [8]. Bio-oils can be upgraded into liquid transportation fuel by
numerous processes: hydrotreating (hydrodeoxygenation), zeolite cracking, and emulsification
with diesel fuel [9]. Amongst, catalytic hydrodeoxygenation (HDO: hydrogenolysis of C-O
linkage in presence of hydrogen) of bio fuels became a convincing approach to mimic them as
crude oils [2, 10].
HDO pathway normally requires a bi-functional catalyst consisting of a reducible site (active
metals) and an acidic center (support or metal-support interface) together facilitate the
hydrogenation and a proper alignment for the hydrogenolysis processes (also catalyzes
dehydration, alkylation, isomerization and condensation reactions) [11]. Recently, there has been
much progress in HDO of pyrolysis bio oils employing different types of catalysts such as,
zeolites [12], sulfided metal systems (Co, Co–Mo, Ni–Mo, etc.) [13–16], noble metals (Pd, Rh,
Pt, etc.) [16–20] and metal phosphides [21] nevertheless, some of these systems exposed with
potential limitations. In case of zeolites, although no hydrogen is required for the process, their
95
capability for deoxygenation of lignocellulose phenolic compounds is limited due to poor
hydrocarbon yield and easy decomposition by extensive coke deposits or dealumination by
hydrolysis [2, 16]. Sulfide (Ni-Mo, Co-Mo) catalysts require H 2S to maintain HDO activity
which contaminates bio-oil components with sulphur and potentially problematic due to waterinduced catalyst deactivation and coke accumulation, while noble metals are expensive and nonabundant [22]. Exploring inexpensive metals combinations (at least one of the metals are active
for hydrogenation) together with acidic support could alleviate deoxygenation activity [11, 23–
25].
It is worth noting that HDO processes of both continuous and batch reactions are majorly carried
out under the conditions typical of crude oil hydrotreatment (50 bar pressure of pure H 2).
Bridgwater et al. estimated that 62 kg of H2 is required to deoxygenate per tonne of bio-oil [26].
Escalona et al. studied La1−x Ce x NiO3 perovskite reactivity using 5 MP H2 pressure that yields
cyclohexanol and methyl cyclohexanol as major products [27]. However, it is desirable to avoid
hydrogenation of aromatics in the bio-oils since the increase in H2 consumption would decrease
the octane number. Also, minimizing hydrogen demand is important for reducing the cost of
biomass derived liquids. Reports on production of aromatics utilizing the mild operational
conditions hitherto are scarce and to be reconciled. Olcese et al. [28] studied effect of pyrolysis
gas at atmospheric pressure using guaiacol, in which phenol and cresol were identified as major
products analogous to our observation. Wu et al. studied HDO of guaiacol at ambient conditions
deploying nickel phosphide catalysts [29]. Zhao et al. [25] illustrated HDO of guaiacol under
96
ambient pressure utilizing silica-supported transition metal phosphide catalysts (i.e., Ni 2P, Fe2P,
MoP, Co2P, and WP) led to phenol and benzene selectively.
The development of water tolerant catalysts is another critical challenge as water is a major
byproduct in the bio-oil production [30]. Therefore, studying the conversion of guaiacol in
presence of water is more practical than in organic solvents. Based on the aforementioned
background, current study is focused on HDO of guaiacol carried at moderated pressures and
temperatures (100 psi and 300 °C). Guaiacol is an important building block consensus preferred
choice as a prototype compound that represent lignin and many of its derivatives [31]. The
objectives of the current work are: (i) screening of several catalysts varying metals and support
to achieve prominent catalyst, (ii) relating the structural behavior of catalysts with catalytic
performance to understand structure–activity relationships, (iii) studying the effect of reaction
conditions, and (iv) understanding the effect of water presence on catalytic performance.
5.5 Experimental
5.5.1 Catalyst Preparation
All the chemicals were purchased from Sigma-Aldrich and Alfa-Aesar. The catalysts were
prepared by incipient wetness impregnation technique with an aqueous solution of the respective
metal precursor: adequate amounts of nickel nitrate hexahydrate (Ni(NO 3)2·6H2O), ammonium
heptamolybdate ((NH4)6Mo7O24), Ammonium metavanadate (NH4VO3), cupper nitrate trihydrate
(Cu(NO3)2·3H2O) and iron nitrate nonahydrate (Fe(NO3)3·9H2O) are used to obtain nickel (Ni,
10 wt%), molybdenum (Mo, 10 wt%), vanadium (V, 10 wt%), copper (Cu, 10 wt%) and iron
97
(Fe, 10 wt%) oxides, respectively. First, suspension of commercial support in the metal precursor
solution was stirred on a hot plate at 70 °C until complete evaporation attained. Impregnated
sample was oven dried at 110 °C for 12 h. The dried samples were subsequently calcined in air at
500 °C for 3 h to obtain final catalysts NiO-MoO3 (Ni-Mo), NiO-V2O5 (Ni-V), NiO-CuO (NiCu), NiO-Fe2O3 (Ni–Fe) deposited onto ZrO2, TiO2, Al2O3, Fe2O3 supports.
5.4.2 Characterization Studies
An energy-dispersive X-ray (EDX) analyzer was used for the elemental analysis of the samples.
The EDX analyzer attached to the scanning electron microscope allowed for the determination of
the elemental composition at any point of interest on the catalyst surface. Powder X-ray
diffraction data were acquired on a Rigaku Multiflex X-ray Diffractometer equipped with Cu Kα
radiation (λ = 0.1548 nm) to identify the phase constitutions in the samples. The step size and the
time per step were respectively, fixed at 0.02° and 1 s in the range 2θ of 20°–80°. Crystallite size
is measured using Scherrer’s equation with the help of highest intense peaks. Crystalline phases
were identified using reference data ICDD PDF files. The BET surface area, pore volume and
pore size distribution of the samples were determined using ASAP 2020 equipment. Prior to the
experiment, samples were degassed at 200 °C for 2 h to remove any surface adsorbed residual
moisture. The TEM studies were made on a Tecnai F20 instrument equipped with a slow-scan
CCD camera and at an accelerating voltage of 200 kV. Samples for TEM were prepared by
dispersing them ultrasonically in ethyl alcohol and after dispersion a droplet was deposited on a
copper grid supporting a perforated carbon film and allowed to dry. The dried specimen is used
for the examination under the microscope. NH3-TPD data was collected on a Micromeritics
98
Autochem 2910 Automated System. Prior to the analysis, the samples (approximately 50 mg)
were treated with pure Helium gas at 200 °C for 2 h. After treatment the temperature was
lowered to 100 °C and the sample was saturated with anhydrous NH3 (3.99 % in He) at a flow
rate of 30 mL min−1 for 1 h. Subsequently, the samples were purged again with 30 mL min −1 of
pure helium (UHP helium 99.999 %) for 2 h in order to remove any weakly bound (physisorbed)
NH3 and then sample temperature was reduced to 50 °C. Temperature was raised to 800 °C at 5
°C min−1 ramping rate and then desorbed gas was monitored after baseline established.
5.4.3 Reaction Study: HDO of Guaiacol
HDO of guaiacol is carried out in a batch reactor. All the samples are pre-activated at 350 °C for
2 h at 5 °C min−1 under one atmosphere H2 pressure. The experiments were performed in a 30
mL batch reactor of Swagelok made from stainless steel. 10 wt% catalyst to guaiacol were
loaded in the reactor. The mixture was then heated to desired temperature using subcritical bath
in the requisite hydrogen atmosphere. After completing the reaction, the reactor was placed in a
water bath to bring the reactor to room temperature (~25 °C). The reaction mixture was
subsequently analyzed by GC–MS (Agilent 7890) equipped with a flame ionization detector
(FID). HP-5MS capillary column (diameter 0.25 mm, thickness 25 µm, length 30 m) was used
for separation and the column temperature was 100 °C. The major products detected in GCMS
were: cyclohexanol, cyclohexanone, phenol, anisole, cresol, catechol dimethyl ether (CDME),
creosol and catechol. Reaction parameters such as, temperature, reaction time and H 2/guaiacol
ratio are varied using optimized catalyst. Blank reactions (without hydrogen, without catalyst,
without hydrogen and catalyst, and bare support) are also carried under identical conditions.
99
Conversion was checked to be negligible with sole guaiacol (3.8 %) disclosing the important role
of catalyst and hydrogen. We also tested non reduced sample to check the effect of reduction on
catalytic performance which is found to be lower than the reduced samples. All the experiments
were at least performed in duplicate and the results were well reproducible within ±3 % range of
conversion. Conversion, selectivity and yield were calculated on the basis of the following Eqs.
(1–3) [32]:
Conversion (%) = [(guaiacolin − guaiacolout) / guaiacolin] × 100
(5.1)
Selectivity (%) = (the mass of specific products/the mass of all products) × 100
(5.2)
Yield (%) = Conversion (%) × Selectivity (%) / 100
(5.3)
5.5.1 Catalyst Properties
Wide-angle XRD results of both fresh and reduced Ni-Mo/TiO 2, Ni-V/TiO2 and Ni/TiO2 samples
were compiled in Figs. 5.1 and 5.2, respectively. For comparison, spectrum of titania support
was also incorporated in the X-ray diffraction patterns of metal catalyst. The XRD patterns of all
the samples along with pristine titania exhibited intense peaks at 2θ of 25.2°, 36.9°, 37.8°, 38.5°,
48.1°, 53.8°, 55.1°, 62.6°, 68.7°, 70.3°, 75.0° indexed as (101), (103), (004), (112), (200), (105),
(211), (204), (116), (200), (215) reflections of TiO2 anatase (ICDD 75-1537) [33] and weak
peaks centered at 2θ of 27.4°, 36.1°, 39.1°, 41.2°, 56.6° indexed as (110), (101), (200), (111),
(220) corresponding to rutile phase of TiO2 (ICDD 82-0514) [34]. Compared to pure titania,
metal deposited titania peaks slightly shifted towards left side indicating that high ionic radius Ni
100
metal could slightly incorporated into the support oxide. Deposited titania peaks are much
sharper and intensified than the pure titania implying sintering of the particle during the
deposition/calcination treatment. Crystallite size for bare titania is 17.4 nm (Table 5.1), after the
deposition crystallite size of titania for Ni/TiO 2, Ni-Mo/TiO2, and Ni-V/TiO2 found to be slightly
increased except for Ni-Mo/TiO2 and maintained same with reduction treatment. Fresh samples
X-ray reflections at 2θ of 37.2°, 43.3°, and 62.9° corresponding d spacing 2.412, 2.088, 1.477 Å
are characteristic of cubic NiO phase (ICDD 78-0423) [35]. MoO3 diffraction patterns
corresponding to the orthorhombic phase were observed at 2θ of 23.6°, 26.8°, 52.3° and NiMoO 4
phase formation was identified at 2θ of 28.8°, 32.5°, and 43.9° [36, 37]. Peaks at 2θ of 20.7°,
22.1°, 26.6°, 31.5°, 34.8° are characteristic of V2O5 (ICDD 72-0598). Peaks displayed at 2θ of
44.2°, 51.8°, 76.3° for reduced catalysts (Fig. 5.2) corresponding d spacing 2.034, 1.762, 1.246 Å
are typical of Ni metal (ICDD 04-0850) [38].
101
* VNiOO ;
30
Ni/TiO 2
*
#
TiO 2
40
50
2Theta ( )
0
60
)A
(2
15
16
)A
00
)A
(1
(2
)A
X
(2
04
10
01
)
(1
(1
20
^*
Ni-V/TiO 2
4
(1
05
)
(2 A
11
)
A
(2
20
)R
)R
X
*
)A
X
XX
^#
00
^
5
^ NiMoO
(2
#
2
(101) R
(103) A
(004) A
A
((112)
20
( 1 0) R
11
)R
#
A
Intensity (a.u.)
X
# MoO 3 ;
Ni-Mo/TiO 2
70
Fig. 5.1 X-ray diffraction patterns of anatase, Ni/TiO2, Ni-V/TiO2 and Ni-V/TiO2 before
reduction
The crystallite size data of the Ni metal calculated using the diffraction line at 2θ of 44.2° is
presented in Table 5.1. As given in the table, the crystallite size of Ni metal found to be much
smaller for Ni-Mo/TiO2 (8.2 nm) followed by Ni-V/TiO2 (10.3 nm) and Ni/TiO2 (16.3 nm).
Based on crystallite size data it is clear that addition of promoter (Mo and V) prevents the
agglomeration of Ni metal and promotes the dispersion, this observation is also supported by
TEM and BET discussed in subsequent section. No peaks due to Mo and V (metal form) for the
102
reduced samples (Fig. 5.2) in the investigated region indicate either they are in the amorphous
state or present as highly dispersed small crystallites beyond the XRD detection.
Ni-Mo/TiO 2
Ni-V/TiO 2
$ Ni
40
50
2Theta ( )
0
60
)A
(2
15
16
(2 ) A
00
)A
(1
)A
04
(2
5)
A
11
(2 ) A
20
)R
(2
(1
0
)A
00
(2
(101) R
(103) A
(004) A
(112) A
(2
00
(1 ) R
11
)R
)R
10
)A
01
(1
(1
30
TiO 2
$
$
Intensity (a.u.)
20
Ni/TiO 2
70
Fig. 5.2 X-ray diffraction patterns of anatase, Ni/TiO2, Ni-V/TiO2 and Ni-V/TiO2 after the
reduction
TEM study was conducted to see the distribution of the metal particles over the support oxide
(Fig. 5.3). For comparison, TEM of bare titania is also presented. All the TEM images show the
catalyst material composed of highly crystalline nanosized particles of homogenous distribution.
Pure TiO2 image shows the particles ranging between 20 and 30 nm with cubic and hexagonal
103
shapes. After metals (Ni, Mo, V) deposition, enlarged support particles formed without any clear
shape. Ni-Mo/TiO2 and Ni-V/TiO2 images showed at least more than one different sized particles
other than titania deduced two kinds of metals presence. All the metals particles are spherical in
shape and homogenously distributed around the titania particle. It is clear from TEM of Ni/TiO 2
sample that metals strongly attached to titania support and formed agglomerated clusters, when
V and Mo added to the Ni/TiO2, uniformly distributed particles around titania support are
noticed. Particles of Ni-Mo/TiO2 are markedly smaller and smooth, while Ni-V/TiO2 showed
bigger particles and composed of coarse boundaries. Few moiré patterns (indicated with arrows)
appeared due to lattice mismatches between the layers.
Table 5.1 Structural properties of metal–supported catalysts
Elemental
crystallite size (nm)a
Sample
TiO2
Ni-V/TiO2
Ni-Mo/TiO2
a
Ni metal
Anatase
10.3
18.9
-
8.2
17.4
16.8
Composition (wt %)b
Ni
Mo/V
12.4
9.1
-
11.4
-
11.6
Total acidity
(peak area)c
0.41
1.10
1.13
XRD Sherrer’s equation; bEDX analysis; cTPD-NH3 desorption
104
20 nm
Ni/TiO2
TiO2
Ni-Mo/TiO2
Ni-V/TiO2
Fig. 5.3 TEM image of TiO2, Ni/TiO2, Ni-V/TiO2 and Ni-Mo/TiO2 catalysts
The elemental compositions of Ni-Mo/TiO 2 and Ni-V/TiO2 catalysts are presented in Table 5.1.
As shown in the table, the actual metal loading is close to the theoretical value of 10 %. Nitrogen
adsorption–desorption isotherms of Ni-Mo/TiO2 and Ni-V/TiO2 catalysts along with bare support
under fresh and reduced conditions are shown in Fig. 5.4. Pore size distributions (PSD) are
presented as inset in the Fig. 5.4. All samples exhibited type IV isotherm (IUPAC classification)
105
with a plateau at high relative pressure indicating the mesoporous nature of the materials with
limited microporosity, which is also supported by PSD. The changes in specific surface area,
pore volume and average pore diameter before and after the reduction treatment are presented in
Table 5.2. The reduction treatment of TiO2 support has no influence on surface area, nevertheless
an increment was noted for Ni-Mo/TiO2 and Ni-V/TiO2. Compared to bare support, pore volume
and pore diameter are higher for metal deposited support similar to the observation noted by
Yang et al. [39]. Increased amount of micro (13 m2/g) and macropores (0.18 cm3/g), respectively
manifested on Ni-Mo/TiO2 and Ni-V/TiO2 after reduction treatment. It has been reported that
mesopores of the catalysts would improve mass and heat transfer in reactions, and, therefore,
micro and macropores are of less significance in the conversion of guaiacol [40]. An increase in
mesopore volume is observed for both Ni-V/TiO2 and Ni-Mo/TiO2, although average pore
volume (exception for Ni-V/TiO2) and pore diameter decreased after the reduction. Increase in
surface area of Ni-V/TiO2 and Ni-Mo/TiO2 under reduced conditions could be ascribed to an
increase in the mesopore volume. Though Ni-Mo/TiO 2 (0.28 cm3/g) has same pore volume
(meso + macro) to that of Ni-V/TiO2 under reduced conditions, Ni-Mo/TiO2 attained large
amount of mesopores (0.14 cm3/g) as confirmed from the Fig. 5.4b, c, and Table 5.2.
Pretreatment on Ni-Mo/TiO2 lead to an increase in micro and mesopores at the cost of
macropores indicate shrinking of the pores and thus making easy metal accessibility. The
decrease in the average pore volume comprehends the close proximity between the guaiacol,
metal sites and acidic sites for effective guaiacol hydrodeoxygenation [30].
106
200
1.4x10
-3
-3
TiO2 reduced
1.0x10
3
Pore Volume (cm /g)
3
Quantity Absorbed (cm /g)
-3
150
100
8.0x10
-4
6.0x10
-4
4.0x10
-4
2.0x10
-4
0.0
0
40
80
0.0
6.0x10
-4
5.0x10
-4
3
150
4.0x10
-4
3.0x10
-4
2.0x10
-4
100
1.0x10
-4
0.0
160
0.4
0.6
200
Relative Pressure (p/p )
0
0.8
Ni-Mo/TiO2 fresh
0
40
80
Pore diameter (nm)
120
1.0
(b)
Ni-Mo/TiO2 reduced
3
Pore volume (cm /g)
200
0.2
120
Pore diameter (nm)
50
0
(a)
TiO2 fresh
1.2x10
160
50
0
0.0
0.2
0.4
0.6
107
0
0.8
1.0
6.0x10
-4
5.0x10
-4
4.0x10
-4
3.0x10
-4
2.0x10
-4
1.0x10
-4
Ni-V/TiO2 fresh
3
150
100
(C)
Ni-V/TiO2 reduced
3
Pore volume (cm /g)
200
0
40
80
120
Pore diameter (nm)
50
0
0.0
0.2
0.4
0.6
0
0.8
1.0
Fig. 5.4 Adsorption isotherms of fresh and reduced (a) TiO 2 , (b) Ni-Mo/TiO2 and (c) NiV/TiO2 catalysts. Inset: Pore size distributions
Table 5.2 Structural properties of metal–supported catalysts
Sample
Surface area
(m2/g)d
TiO2
51
Ni-Mo/TiO2
43
Ni-V/TiO2
42
TiO2
49
Ni-Mo/TiO2
58
Ni-V/TiO2
51
Total pore
volume
(cm3/g)d
Mesopore
volume (cm3/g)d
Fresh catalysts
Average pore
diameter
(nm)d
0.16
0.08
12.5
0.30
0.12
28.1
0.27
0.09
Reduced catalysts
25.6
0.13
0.08
11.2
0.28
0.14
19.5
0.28
0.10
108
22.2
d
BET analysis
Ni-Mo/TiO2
Ni-V/TiO2
Ni/TiO2
TCD Signal (a.u.)
TiO2
100
200
300
400
500
Temperature ( C)
0
600
700
Fig. 5.5 TPD-NH3 profiles of TiO2, Ni/TiO2, Ni-V/TiO2 and Ni-Mo/TiO2 after the reduction
treatment
In order to compare the acidity of samples, thermo-programmed desorption of ammonia (TPDNH3) profiles of all the samples after reduction are presented in Fig. 5.5, while the relative peak
areas are tabulated in Table 5.1. The low (T < 200 °C) and high temperature (250–450 and 600
°C) desorbed peaks designated as weak, medium, and strong acid sites. The desorption profiles
of both TiO2 and Ni/TiO2 reveal that a moderate amount of weak acid sites, as evidenced by the
small desorption peaks centered at around 200 and 300 °C. For Ni-V/TiO 2 and Ni-Mo/TiO2, the
desorption peaks at 200 °C amplified, and additionally two new peaks at 400 and 600 °C
developed with similar desorption pattern. The desorption peaks of Ni-V/TiO 2 and Ni-Mo/TiO2
109
apparently demonstrates Ni, Mo and V incorporation together increases the overall strength of
acidic sites [41]. From the table it could be realized that the order of acidic strength follows the
trend: TiO2 < Ni/TiO2 < Ni-V/TiO2 < Ni-Mo/TiO2. It has been reported that the strong acidic
sites are pivotal for the reaction wherein, guaiacol molecule could first adsorb on acidic sites
through C-O bond and then strong acidic sites favors hydrogenolysis and dehydration reactions
[42]. Based on acidic strength, it is probable that Ni-Mo/TiO2 could be an efficient HDO
catalyst.
5.5.2 Catalytic Activity
Under present reaction conditions, all the catalysts lead more than ten products. We only
presented the species accounting for more than 1 % of the total products. Guaiacol conversion
products are mainly determined by methoxy, hydroxyl and benzene ring. Based on literature and
product distribution a reaction network is proposed in Scheme 1 [15]. As shown in the scheme,
there are four major reactions pathways realized in the HDO of guaiacol: (1) direct
hydrogenation of aromatic ring, (2) demethoxylation, (3) demethylation, and (4) transalkylation
directing to a variety of products such as cyclohexanone, cyclohexanol, anisole, phenol, cresol,
catechol, CDME and creosol. Trace amounts of benzene, cyclohexane, 1,2-cyclohexane diol,
methyl cyclohexanone, methoxy cyclohexanone and cyclohexene are also noted. Demethylation
of guaiacol furnishes catechol (Eq. 1(a) in Scheme 1) [43]. Guaiacol can transform to phenol in
two routes: demethylation of guaiacol to catechol and then deoxygenation to phenol or direct
demethoxylation of guaiacol to phenol (Eq. 1(b) and (c) in Scheme 1) [44].
110
OCH3
OH
OH
(a)
+H2
-CH4
OH
(b)
OH
+H2
-H2O
(1)
(c) +H2
OCH3
OH
OCH3
OH
-CH3OH
+H2
OCH3
(2)
-H2O
OH
Inter CH3 transfer
CH3
+
-H2O
OCH3
HO
OH
H3CO
OCH3
OH
OCH3
OH
OH
+3H2
O
+2H2
+2H2
+H2
+H2
+H2
OH
(4)
(5)
O
-CH3OH
O
OH
OH
-CH3OH
OCH3
(3)
CH3
OCH3
+
OCH3
Intra CH3 transfer
OCH3
OH
OH
(6)
OH
(7)
Scheme 1. Schematic representation of possible reaction pathways of HDO of guaiacol
111
The methoxy group that removed during the formation of phenol was identified in GCMS as
methanol. Anisole is formed by the deoxygenation to remove OH group of guaiacol (Eq. 2 in
Scheme 1) [45]. Intermolecular methyl transfer followed by deoxygenation results in o- and mcresol (Eq. 3 in Scheme 1). Intramolecular methyl transfer leads to catechol, CDME and creosol
(methyl transfer to oxygen to form CDME and methyl transfer to carbon to form o-, m-, pcreosol) (Eq. 4 in Scheme 1). The transalkylated products are obtained by the acidic sites [46].
Hydrogenation of guaiacol/phenol leads to cyclohexanol and cyclohexanone (Eqs. 5, 6, 7 in
Scheme 1). No observation of aromatic ring condensed products such as bicycles under present
conditions confirming catalysts are mute to polymerization of guaiacol.
Screening of catalysts varying promoter (V, Mo, Cu, Fe) and support (TiO 2, Al2O3, ZrO2, Fe2O3,
SiO2) under nominal conditions (300 °C, 5 h and 100 psi hydrogen) towards HDO of guaiacol
are presented in Fig. 5.6a, b. Promoter effect on Ni supported ZrO2 is presented in Fig. 6a.
Among various bimetallic combinations Ni-Mo and Ni-V are prominent and showed guaiacol
conversion ~42 and 23 %, respectively with major deoxygenated products. Effect of support is
evaluated utilizing Ni-Mo deposited TiO2, Al2O3, ZrO2, Fe2O3, and SiO2 supports, presented in
Fig. 5.6b. Irrespective of the type of the support, conversion found to be similar and ranged
between 43 and 47 % except for Ni-Mo/Fe2O3. The activity data disclosed that Ni-Mo and Ni-V
bimetalic clusters and TiO2 support combination presented high conversion with prominent low
oxygenated products, whilst rest of the catalysts showed major amount of undesirable products.
112
Guaiacol conversion
Product selectivity with one oxygen
Product selectivity with two oxygens
Conversion / Selectivity (%)
80
60
40
20
0
80
Conversion / Selectivity (%)
(a)
Ni-V/ZrO 2
(b)
Ni-Mo/ZrO 2
Ni-Cu/ZrO 2
Ni-Fe/ZrO 2
Guaiacol conversion
Product selectivity with one oxygen
Product selectivity with two oxygens
60
40
20
0
Ni-Mo/TiO 2 Ni-Mo/ZrO 2 Ni-Mo/Al2O 3 Ni-Mo/Fe2O 3 Ni-Mo/SiO 2
Fig. 5.6 Screening of catalysts. (a) Promoter effect: V, Mo, Cu, Fe. (b) Support effect: TiO 2,
Al2O3, ZrO2, Fe2O3, SiO2 for HDO of guaiacol. Reaction conditions: 300 °C, 1 mL of
guaiacol, H2 pressure of 100 psi, 5 h
113
Reaction data prompted us to consider Ni-Mo/TiO 2 and Ni-V/TiO2 catalysts for further
investigation in order to study the guaiacol reactivity under variable conditions to optimize the
catalytic performance. Products distribution is greatly affected by the choice of catalyst: phenol
and creosol are the main products while cyclohexanone, anisole, catechol and CDME are the
minor products over Ni-Mo/TiO2. Cyclohexanol is additionally noticed on Ni-V/TiO2 catalyst.
Formation of cyclohexanol, cyclohexanone, phenol and anisole indicates a competition between
hydrogenation of C=C aromatic system and hydrogenolysis of C-O, which is controlled by the
mode of adsorption of guaiacol on the catalyst. Phenol is viewed as major product under our
reaction conditions on all the catalysts [47]. Removal of oxygen from phenol is
thermodynamically more difficult than the other oxygenates [48]. Similar observation was noted
by Bui et al. [13] while studying catalytic conversion of guaiacol using Al 2O3, TiO2 and ZrO2
oxides, wherein TiO2 support formed phenol as major product.
The influence of catalyst and metal on guaiacol conversion is presented for Ni-Mo/TiO 2 in Fig.
5.7. The guaiacol conversion in the absence of catalyst and on the support is fairly low (10 and
15 %, respectively). Since the support is barely active, the conversion is ascribable to the metal
phase. In order to understand metallic effect we have compared guaiacol conversion of NiMo/TiO2 with Ni/TiO2 and Mo/TiO2. As seen from the figure, bimetallic Ni-Mo catalyst gave
noticeably better results than mono metallic Ni and Mo catalysts and the result was not just an
average of mono metallic catalysts. Ni/TiO2, Mo/TiO2 and Ni-Mo/TiO2 systems yield phenol of
5.2, 5.8 and 13.6 %, respectively. Additionally, Ni-Mo/TiO 2 showed meager portions of catechol
and CDME compared to the respective mono metallic catalysts. Enhanced performance of Ni114
Mo/TiO2 with reference to Ni/TiO2 and Mo/TiO2 signify the feasible bimetallic interaction.
Effect of Ni metal loading (0, 5, 10 and 20 %) was provided in Fig. 5.8. Catalytic activity with
absence or low Ni metal loadings is sluggish due to inadequate active sites, the performance
raised with Ni loading suggesting the homogeneous distribution of metals with corresponding
increase in the active sites. Subsequently, activity dropped down at higher Ni loadings (20 wt%).
Similar observation was noted by Sepúlveda et al. [47] wherein, guaiacol activity decreased with
increased Re loading (>0.6 atoms per nm2). The poor performance at high metal loadings could
be accounted for loss of active sites due to Ni metal aggregates.
50
Conversion (%)
40
30
20
10
0
Blank
TiO 2
Ni/TiO 2
Catalyst(s)
Mo/TiO 2 Ni-Mo/TiO 2
Fig. 5.7 Effect of catalyst on guaiacol conversion: Reaction conditions: 300 °C, 1 mL of
guaiacol, H2 pressure of 100 psi, 5 h.
115
Conversion (%)
50
40
15
Conversion
Cycloehexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
12
9
Yeild (%)
60
30
6
20
3
10
0
10Mo/TiO 2
5Ni-10Mo/TiO 2
10Ni-10Mo/TiO 2
Ni metal loading (wt%)
20Ni-10Mo/TiO 2
0
Fig. 5.8 Effect of Ni loading (0, 5, 10 and 20 wt%) on HDO of guaiacol. Reaction
conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi, 5 h
The dependence of the guaiacol conversion on Ni-Mo/TiO 2 and Ni-V/TiO2 at different
temperatures was displayed in Fig. 5.9. From the figure it is very clear that the deoxygenation
strongly depends on the reaction temperature. As expected the conversion is very low at 200 °C
and increased in slant with temperature up to 300 °C for both the catalysts. A dramatic increase
is noticed for Ni-Mo/TiO2 from 300 °C and reached about 96.5 % at 350 °C. Ni-V/TiO 2 showed
negligible conversion until 300 °C and then a sudden rise is noticed at 350 °C with about 85.9 %
conversion.
116
(a)
Conversion (%)
80
60
Conversion
Cyclohexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
Xylenol
40
Ni-Mo/TiO 2
30
Selectivity (%)
100
20
40
10
20
100
200
(b)
Conversion (%)
80
60
250
300
350
Tem perature ( C)
0
40
Ni-V/TiO2
Conversion
Cycloehexanol
Cycloehexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
Xylenol
30
20
40
10
20
0
0
Selectivity (%)
0
200
250
300
Temperature ( C)
0
350
0
Fig. 5.9 Effect of temperature on HDO of guaiacol. Reaction conditions: 1 mL of guaiacol ,
H2 pressure of 100 psi, 5 h
117
The product distribution also exhibited noticeable temperature dependence, the selectivity of
deoxygenated products at 200 °C quite low and then increased accordingly with temperature.
The selectivity of catechol and CDME decreased with temperature for Ni-Mo/TiO 2 while those
are slightly elevated for Ni-V/TiO2. At 350 °C dimethyl phenol appeared for both the catalysts. It
is clear from the figure that between the two catalysts Ni-Mo/TiO 2 showed promising selectivity
towards phenol and cresol.
A crucial role is demonstrated by H2 as a co-reactant for the removal of oxygen from the
guaiacol. To illustrate the importance of H2, guaiacol conversion and product selectivity at
different mole ratios of H2/guaiacol on Ni-Mo/TiO2 and Ni-V/TiO2 catalysts are presented in Fig.
5.10. Initially, the guaiacol conversion was 19.1 and 34.6 % for Ni-Mo/TiO 2 and Ni-V/TiO2,
respectively. Under low hydrogen pressures, the high oxygenated transalkylated products
catechol, CDME and creosol yields predominated specifically on Ni-V/TiO 2, and phenol and
other low oxygenated products are low. This could be due to in the absence of hydrogen, methyl
transfer and/demethylation prevails. With an increase in H2 pressure deoxygenated products
intensified at the expense of catechol and CDME due to high H2 coverage. The products data
underline the importance of H2 and points out the advantage of high pressure operation to obtain
complete deoxygenated products.
118
(a)
60
Conversion (%)
50
40
60
Ni-Mo/TiO 2
Conversion
Cyclohexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
50
40
Selectivity (%)
70
30
30
20
20
10
10
70
Conversion (%)
60
0
(b)
50
40
1.0
0.5
Hydrogen/Guaiacol mole ratio
Conversion
Cyclohexanol
Cyclohexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
2.0
Ni-V/TiO 2
60
50
40
30
30
20
20
10
10
0
0
Selectivity (%)
0
0
1.0
0.5
Hydrogen/Guaiacol mole ratio
2.0
0
Fig. 5.10 Pressure dependence on HDO of guaiacol (a) Ni-Mo/TiO 2 and (b) Ni-V/TiO2.
Reaction conditions: 300 °C, 1 mL of guaiacol, 5 h
119
Consistent with previous reports, with increase in the H 2 pressure the selectivity for the
formation of deoxygenated products raised conversely, the major oxygenated products are prone
to decrease [46, 49]. With raise in H2 pressure the guaiacol conversion (34.0–40.9 for Ni-V/TiO2
and 22 to 67.2 % for Ni-Mo/TiO2) and phenol selectivity (10–25 % for Ni-V/TiO2 and 9.3–38 %
for Ni-Mo/TiO2) slowly raised. Catechol (21.4–1.9 % for Ni-V/TiO2; 32.1–0 % for Ni-Mo/TiO2)
and CDME (39.3–6.8 for Ni-V/TiO2; 32–13.9 % for Ni-Mo/TiO2) selectivities abruptly
decreased. At 2.0 molar ratio of H2/guaiacol, cyclohexanol and cyclohexanone increased to 16
and 10 %, respectively, with a meager decrease in phenol for Ni-V/TiO 2. This means
cyclohexanol and cyclohexanone formation initiated by both phenol and ring saturation of
guaiacol (Reaction 5, 6, 7 in Scheme 5.1). A stable propensity is observed for creosol selectivity
for both the catalysts. Anisole and cresol are quite stable for Ni-V/TiO 2 and a meager increase is
noted for the Ni-Mo/TiO2. The result of desired products with a raise in hydrogen pressure could
be due to the involvement of H2 in the equilibrium between the phenol, catechol and CDME.
High hydrogen pressure leads to a shift of catechol and CDME to phenol (and to subsequent
cyclohexanol and cyclohexanone) and low H2 pressure results the opposite effect.
Figure 5.11 shows guaiacol conversion and evolution of products with time over Ni-Mo/TiO 2
and Ni-V/TiO2. Conversion increased for both the catalysts with increase in the reaction time
without much change in the products selectivity. As increase in the reaction time the conversion
continued to be increased and reached a stable point within 8 h. About 42 % guaiacol conversion
was noticed on Ni-V/TiO2 and a remarkable increase in conversion of ~66 % was obtained on
Ni-Mo/TiO2. All the products have shown a stable behavior on both the catalysts.
120
100
Ni-Mo/TiO 2
Conversion
Cycloehexanone
Anisole
Phenol
Cresol
CDME
Catechol
Creosol
Conversion/ Selectivity (%)
80
60
40
20
0
100
2
4
6
8
Reaction time (h)
10
Ni-V/TiO 2
60
40
12
(b)
Conversion
Cycloehexanone
Anisole
Phenol
Cresol
CDME
Creosol
Catechol
80
Conversion/ Selectivity (%)
(a)
20
0
2
4
6
8
Reaction time (h)
10
12
Fig. 5.11 Effect of reaction time on HDO of guaiacol (a) Ni-Mo/TiO 2 and (b) Ni-V/TiO2.
Reaction conditions: 300 °C, 1 mL of guaiacol, H 2 pressure of 100 psi
121
In order to determine the reaction order and rate constant of the reaction, the activity data
(concentration and time) fitted to power-law equation. As can be seen in Fig. 5.12, the slope of a
plot of 1/CA as a function of time is linear with slope of k, thus HDO of guaiacol global kinetics
followed the second order mechanism. The rate constant of Ni-Mo/TiO 2 is three times higher
than the Ni-V/TiO2 and the high rate constant for Ni-Mo/TiO2 explains its high reactivity over
Ni-V/TiO2.
Ni-Mo/TiO2 has shown better performance over Ni-V/TiO2 at variable conditions, although the
latter has favored cyclohexanol formation. The support phase is same for both the catalysts,
therefore the activity difference could be originated from the metal phase and its prominent
interaction with support. The facile guaiacol conversion on Ni-Mo/TiO 2 compared to Ni-V/TiO2
appears to be due to the synergetic effect between acid sites and structural properties. As
indicated by XRD, BET and TPD the high activity of Ni-Mo/TiO 2 catalyst could be correlated
with the strength of acidic sites, greater mesopore volume and presence of highly dispersed small
sized metal active sites.
122
400
Ni-Mo/TiO2
(a)
1/Cguaiacol
300
200
y = 18.883x + 112.86
R² = 0.9897
100
0
0
250
4
6
8
Reaction Time (h)
10
12
(b)
Ni-V/TiO2
200
1/Cguaiacol
2
150
100
y = 5.9974x + 121.66
R² = 0.9308
50
0
0
2
4
6
8
Reaction Time (h)
10
12
Fig. 5.12 Determination of order and rate constant by integral method: (a) Ni-Mo/TiO 2 and
(b) Ni-V/TiO2. Reaction conditions: 300 °C, 1 mL of guaiacol, H 2 pressure of 100 psi.
123
Effect of water on guaiacol conversion is used to simulate the water content effect on the
catalytic performance in bio-oil. These experiments were carried out under the same conditions
as those performed without the water. Effect of water on guaiacol conversion and
phenol/catechol ratio at 0, 0.5, 1.0, and 1.5 mL for Ni-Mo/TiO 2 and Ni-V/TiO2 is presented in
Fig. 5.13. Remarkably, water has great impact on the overall conversion and product distribution
on Ni-Mo/TiO2. Guaiacol conversion and products such as, phenol, cresol, anisole decreased and
catechol increased for Ni-Mo/TiO2 with the addition of water indicating minimization of
deoxygenation, demethoxylation and transalkylation pathways. Conversion and phenol/catechol
ratio for Ni-Mo/TiO2 decreased from 43 to 20 and 1.26 to 0.45 %, respectively. Olcese et al. and
Leiva et al. also noticed similar observation [28, 50]. However, water presence has shown no
significant influence on guaiacol conversion or phenol/catechol ratio for Ni-V/TiO 2.
To understand the water intolerance of Ni-Mo/TiO2, we performed identical reactions using
Mo/TiO2 catalyst and the results are presented in Fig. 5.13c. Apparently, as water addition
increases, a decrease in the guaiacol conversion (20 to 14 %) and phenol selectivity, and an
increase in the catechol selectivity (phenol/catechol ratio 1.11 to 0.12) are noticed similar to that
of Ni-Mo/TiO2 catalyst. Halász et al. stated that at 300 °C water molecules dissociatively adsorbs
onto MoO3 and thus diminishes the number of Lewis acidic sites [51, 52]. Based on this
observation and our experimental evidence, it is confirmed that in presence of water, MoO 3
phase is the reason for the deactivation of Ni-Mo/TiO2 catalyst.
124
125
Fig. 5.13 Effect of water on HDO of guaiacol: (a) Ni-Mo/TiO 2 and (b) Ni-V/TiO2. Reaction
conditions: 300 °C, 1 mL of guaiacol, H2 pressure of 100 psi, 5 h
5.7 Conclusions
HDO of guaiacol was successfully studied using Ni-Mo/TiO 2 and Ni-V/TiO2 catalysts under
relatively low pressure (100 psi) and moderate temperatures (200–350 °C). Ni (10 wt%) − Mo
(10 wt%)/TiO2 showed prominent results with reference to un-promoted Ni/TiO2, Mo/TiO2 and
variable Ni metal loadings. Incorporation of Mo and V to Ni/TiO 2 not only enhanced dispersion
of metal species, but also improved the catalytic performance. Variations in the product
distribution and conversions were noted for both Ni-Mo/TiO 2 and Ni-V/TiO2 catalysts under
different reaction conditions, which could be attributed to differences in the dissemination of
active sites: metallic and acidic sites with the interference of promoter Mo and V, and particle
126
size distribution. With increase in temperature and H2/guaiacol mole ratio, both catalysts showed
improved conversion and selectivity. In particular, Ni-Mo/TiO 2 showed better selectivity for
phenol and cresol, while Ni-V/TiO2 showed prominent cyclohexanol along with phenol. Well
dispersed small sized metal particles, high surface area, mesopore structure and more acidic sites
could be the reason for the high activity of Ni-Mo/TiO2. A steady behavior is observed for timeon-stream study during 12 h for both catalysts confirm their stability. In aqueous medium, NiV/TiO2 maintained the guaiacol conversion and phenol/catechol ratio than Ni-Mo/TiO 2 proved
its tolerance to water presence.
5.8 Acknowledgement
Authors are grateful to the financial support of the Natural Science and Engineering Research
Council of Canada (NSERC). Lakshmi Katta thank university's Eyes High Program for the
Postdoctoral Fellowship. The authors also thank Ludivine Gras for her contribution in the
reaction part.
127
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130
CHAPTER 6: UPGRADING OF ANISOLE COMPONENT BY NI-MO/TIO 2 AND NIV/TIO2 CATALYSTS: SYNTHESIS, CHARACTERIZATION AND KINETIC
MEASUREMENTS
6.1. Presentation of the Article
In this chapter, the results from the reaction and kinetic studies of the hydrodeoxygenation of
guaiacol and anisole are presented. The hydrodeoxygenation of anisole was performed using two
different catalysts previously tested in the hydrodeoxygenation of guaiacol. Various reaction
temperatures (250, 275, 300 and 325 °C) and reaction times (2, 4, 6, 8 hours) were used in order
to determine the selectivity of the reaction. All of the samples were pre-activated at 350 °C for
two hours at 5 °C min–1 under atmospheric H2 pressure. The experiments were performed in a
30 mL batch reactor made of stainless steel (Swagelok). Additional analysis of the catalyst using
an X-ray photoelectron spectroscopy instrument was performed to provide a better understanding
of the catalyst surface.
Finally, a kinetic study of both the hydrodeoxygenation of guaiacol and anisole were performed
using the integral method. As a result, the reaction order, rate constant and energy activation of
the reactions were obtained.
131
Upgrading of Anisole Components by Ni-Mo/TiO2 and Ni-V/TiO2 Catalysts:
Synthesis, Characterization and Kinetic Measurements
Aqsha, A., Katta, L., Tijani, M.M. & Mahinpey, N.
This article has been submitted to Energy & Fuels in January 2016.
6.2. Abstract
This work reports the catalytic hydrodeoxygenation (HDO) of model components (anisole) of
lignocellulose biomass over Mo and V promoted Ni deposited titania support. The physicochemical properties of each material were elucidated, and reactions were studied over a wide
range of temperatures to enable examination of kinetic parameters. Crystallite sizes measured
using X-ray powder diffraction were corroborated well with the transmission electron
microscopy results. The presence of Ni, Ti, Mo and V species was confirmed through X-ray
photoelectron spectroscopy (XPS). Significant HDO activity for both the catalysts could be
attributed to high dispersions of metals and acidic sites, which were affected by interaction
between the Ni metal and the titania support. The higher activity of Ni-Mo/TiO 2 may have
resulted from the high Ni/Ti surface atomic ratio, which was confirmed by XPS. The major
product of the anisole HDO reactions was phenol. Interestingly, a considerable amount of
benzene and cyclohexane were also noticed in the anisole HDO reaction. The activation energy
132
values for anisole reactions over Ni-Mo/TiO2 and Ni-V/TiO2 were 80.9 and 53.9 kj/mol,
respectively.
Keywords: Anisole, bio-oil, catalyst, hydrodeoxygenation, model components.
6.3 Introduction
Sustainable alternative energies are viable solutions for the replacement of fossil fuels and can
greatly reduce the CO2 emissions associated with the transportation sector. Biomass, as an
energy alternative, can be effectively converted into bio-oil via several physical, thermal and
biological processes. Bio-oil has high potential as liquid fuel, as it contains less nitrogen and
sulphur than fossil fuel. However, the produced bio-oil possesses chemical and thermal
instability, due to the presence of a significant amount of oxygen [1-3].
Catalytic hydrodeoxygenation (HDO), a chemical method, is a feasible approach for the
upgrading of lignin derived bio-oils [4-7]. Lignin, consisting largely of aromatic linkages in
polymeric units, occupies a major part of the lignocellulose biomass; however, lignin-derived
bio-oils have received less research attention than cellulosic feedstock [8,9]. In the current
investigation, anisole have been chosen as representatives of compounds containing hydroxyl
and methoxy groups, both of which are abundant in lignocellulose. Although there have been
many reports presented on the HDO of lignin model components, studies on the use of anisole as
probes under a single roof have been limited.
133
Precious metal based catalysts and zeolites have been used for a wide variety of applications,
including the hydrogenolysis of oxygenated compounds [10-18]. However, a number of studies
have disclosed that cheaper ions, such as transition metal combinations, can be effective as
precious metal catalysts [19-21. Details about the reactivity over different bimetal catalysts and
operating conditions using guaiacol have been presented in our previous work [22].
It is also vital to determine kinetic parameters, such as the rate constant and activation energy, in
order to understand the complete reaction network. A pseudo first-order kinetic model has been
used by several researchers to devise the kinetic parameters for bio-oil. The objectives of this
study were the upgrading of anisole using nickel and molybdenum (Ni-Mo) and nickel and
vanadium (Ni-V) supported on titania as catalysts, which are quite active in the removal of
oxygen based on previous observations, and the provision of a quantitative foundation by
determining the kinetics of those reactions.
6.3. Experimental Section
6.4.1 Catalysts Preparation
The catalysts used in this work were prepared by incipient wetness impregnation. Requisite
amounts of nickel nitrate hexahydrate (Ni(NO3)2·6H2O), ammonium heptamolybdate
((NH4)6Mo7O24), and ammonium metavanadate (NH4VO3) were used to obtain nickel (Ni, 10
wt%), molybdenum (Mo, 10 wt%), and vanadium (V, 10 wt%) oxides, respectively. All the
chemicals were purchased from Sigma-Aldrich or Alfa Aesar.
134
The catalysts were prepared by first stirring a suspension of the commercial support into the
metal precursor solution on a hot plate at 70°C until complete evaporation was attained. The
impregnated sample was then oven dried at 110°C for 12 h. The dried samples were
subsequently calcined in air at 500°C for 3 h to obtain the final catalysts – NiO-MoO 3 (Ni-Mo)
and NiO-V2O5 (Ni-V) – deposited onto titanium dioxide (TiO 2) support
6.4.2 Characterization Studies
Powder X-ray diffraction (XRD) data were acquired using a Rigaku Multiflex X-ray
Diffractometer equipped with Cu−Kα radiation (λ = 0.1548 nm) to identify the phase
constitutions in the samples. The step size and time per step were fixed at 0.02° and 1 s,
respectively, in the range of 2θ from 20° to 80°. The crystallite size was measured using the
Scherrer equation, with aid of the highest intense peaks. Crystalline phases were identified using
reference data files (PDF) from the International Centre for Diffraction Data (ICDD).
The transmission electron microscopy (TEM) studies were made on a Tecnai F20 instrument
equipped with a slow-scan CCD (charge-coupled device) camera and at an accelerating voltage
of 200 kV. Samples for TEM were prepared by dispersing them ultrasonically in ethyl alcohol.
After dispersion, a droplet was deposited on a copper grid supporting a perforated carbon film
and allowed to dry. The dried specimen was used for examination under the microscope.
For the X-ray photoelectron spectroscopy (XPS) measurements, each sample was mounted and
pumped down from atmospheric pressure to ultra-high vacuum (UHV) pressure of 10 -7-10-8 Pa.
135
A monochromatic aluminium X-ray source was used. Wide energy surveys were carried out (0 –
1,200 eV) with pass energy of 187.85 eV to identify the elements in the sample using an X-ray
setting of 200 µm 50W/15KV. After identifying the elements present in the sample, an
acquisition with a smaller energy window (10 – 30 eV with pass energy of 23.5 eV) was
performed to obtain high-energy resolution spectra of each element requested, in order to
determine the chemical environment and oxidation states. The reference binding energy was
chosen as the C1s level of the adventitious carbon present at 284.6 eV.
6.4.3 Reaction Study: HDO of Anisole
The HDO experiments of anisole were carried out in a 30 mL batch reactor from stainless steel
(from Swagelok). All the samples were pre-activated at 350°C for 2 h at 5°C min–1 under one
atmosphere of hydrogen (H2) pressure. Ten wt% of the catalyst to the reactant (anisole) was
loaded in the reactor. The mixture was then heated to the desired temperature using a subcritical
bath in the requisite H2 atmosphere.
After completing the reaction, the reactor was placed in a water bath to bring it to room
temperature (~25 °C). The reaction mixture was subsequently analyzed with a gas
chromatography / mass spectrometry system (GC-MS, Agilent 7890) equipped with a flame
ionization detector (FID). An HP-5MS capillary column (diameter of 0.25 mm, thickness of 25
µm, and length of 30 m) was used for separation at a column temperature of 100°C. The major
products detected with GC-MS for the HDO of anisole were phenol, benzene, cyclohexane,
136
methoxycyclohexane, cyclohexanol, cyclohexanone and methylanisole. All the experiments were
performed at least twice, and the results were reproducible within a range of conversion of ± 3%.
6.4. Results and Discussions
6.5.1 Structural Properties
To determine the crystal phase and size, XRD measurements were carried out. The XRD results
of Ni-Mo/TiO2 and Ni-V/TiO2 under fresh and reduced conditions are presented in Figure 6.1.
For comparison, TiO2 anatase as purchased is also presented. The sharp well-defined peaks in the
diffraction patterns correspond to crystalline anatase and rutile phases. The diameters of the Ni
particles estimated from the full width at half maximum (FWHM) of the most intense reflections
using the Scherrer equation are displayed in Table 6.1 for all the catalysts. These data reveal that
the average sizes of the Ni metal active phase for the Ni-Mo/TiO 2 and Ni-V/TiO2 catalysts were
8.3 and 10.2 nm, respectively. No indications of Ni2O2 and Ni2O3 were found within the
investigated range.
Table 6.1 Physico-chemical properties of Ni-Mo/TiO 2 and Ni-Mo/TiO2 catalysts
Catalyst
Crystallite sizea (nm)
S.A.b (m2/g)
-
42
Ni-V/TiO2-F
Ni-V/TiO2-R
10.9
Ni-Mo/TiO2-F
Ni-Mo/TiO2-R
51
-
a
43
8.2
58
b
c
XRD: BET SA: XPS analysis
137
Ni/Tic
atomic ratio
0.107
0.093
0.123
0.131
(a)
Intensity (a.u.)
NiMo/TiO2-R
NiMo/TiO2-F
TiO2
20
30
40
50
2Theta ( )
0
60
70
80
Intensity (a.u.)
(b)
NiV/TiO2-R
NiV/TiO2-F
TiO2
20
30
40
50
2Theta ( )
0
60
70
80
90
Fig. 6.1 X-ray diffraction pattern of (a) TiO 2, fresh Ni-Mo/TiO2 and Ni-Mo /TiO2 after the
reduction and (b) TiO2, fresh Ni-V/TiO2 and Ni-V/TiO2 after the reduction.
138
Representative TEM images for both Ni-Mo/TiO2 and Ni-V/TiO2 under both fresh and reduced
conditions are presented in Figure 6.2. The size distributions were obtained by counting particles.
In all cases, the size of the metal was similar to that of the anatase phase, as confirmed by TEM.
Both metallic and oxidic phases were in close proximity, facilitating the metal-support
interactions and thus HDO reactivity.
Ni-Mo/TiO2-R
Ni-Mo/TiO2 -F
Ni-V/TiO2-F
Ni-V/TiO2-R
Fig. 6.2 TEM images of Ni-V/TiO2 and Ni-Mo/TiO2 catalysts before (fresh, F) and after
reduction (R)
139
6.5.2 Surface Analysis
XPS was used to elucidate the chemical composition and valence state of the metal components
at the surface. Elements identified in the given spectra were Ni, Ti, oxygen (O), V, Mo, and
carbon (C), which was due to adventitious carbons. Peaks in all the spectra were attenuated for
the reduced samples. Interestingly, in all the spectra (Ni 2p, Ti 2p, Mo 3d and V 2p), the high
binding energy peaks FWHM were much broader and thus shorter than the low binding energy
peaks.
Ni 2p is a complex spectrum with a mixture of core level and satellite peaks. Ni 2p spectra for
Ni-Mo/TiO2 (fresh and reduced) and Ni-V/TiO2 (fresh and reduced) were deconvoluted by
Gaussian curves representing Ni 2p3/2 and Ni 2p1/2 spin orbit levels, as presented in Figure 6.3.
All the samples showed major component peaks at 873.2 and 855.8 eV (BE = 17.4 eV)
corresponding to Ni 2p1/2 and Ni 2p3/2, respectively, due to Ni2+. Moreover, related satellite peaks
(shake-up features) were observed at ~6 eV (two broad peaks at 880.01 and 861.9 eV) higher in
the binding energy region.
Figure 6.4 shows core level spectra of Ti 2p of all the four samples. The two component peaks
were observed at binding energy values approximately 5.7 eV apart at 458.79 and 464.48 eV.
These two peaks were assigned to Ti 2p3/2 and Ti 2p1/2. The energy separation was due to the
expected oxidation state of Ti4+, which is consistent with the literature reports. No indications of
peaks due to reduce Ti (Ti3+) were noted for the reduced samples spectra [23].
140
Ni/Ti surface atomic ratios are presented in Table 6.1. It is obvious that the Ni/Ti was greatly
influenced by the promoter and treatment conditions. The Mo promoter enriched the Ni amount
over the surface compared to the V promoter. The reduction treatment of Ni-Mo/TiO 2 further
enhanced the surface Ni; however, the Ni amount decreased over Ni-V/TiO 2 with reduction
treatment.
Ni 2p 3/2
Ni-Mo/TiO 2-R
Ni-Mo/TiO 2-F
Ni-V/TiO 2-R
Ni-V/TiO 2-F
Ni 2p 1/2
Ni 2p 3/2
satellite
C/S
satellite
Ni 2p 1/2
Ni 2p
900
890
880
870
860
Binding energy (eV)
850
840
Fig. 6.3 Ni 2p spectra for Ni-Mo/TiO 2 (fresh and reduced) and Ni-V/TiO 2 (fresh and
reduced)
141
Ti 2p
Ni-Mo/TiO2-R
Ni-Mo/TiO2-F
Ni-V/TiO2-R
C/S
Ni-V/TiO2-F
Ti 2p1/2
470
465
Ti 2p3/2
460
Binding energy (eV)
455
450
Fig. 6.4 Ti 2p spectra for Ni-Mo/TiO2 (fresh and reduced) and Ni-V/TiO 2 (fresh and
reduced)
The core level spectra of O 1s are presented in Figure 6.5. The asymmetric O 1s spectra were
combinations of two component peaks (530.04 and 531.2 eV). The low binding energy peak
appeared due to Ti-O, and the high energy peak can be attributed to M-O. The Mo 3d core level
spectra for Ni-Mo/TiO2 (fresh and reduced) are presented in Figure 6.6, which indicates that
there were two different Mo species present on the surface. Both fresh and reduced samples
showed major 3d orbital doublets at 232.5 and 235.7 eV (BE = 3.2 eV), due to the inert Mo6+
state in MoO3 or NiMoO4.
142
C/S
Ni-Mo/TiO2-F
522
528
Ni-Mo/TiO2-R
534
540 522
Ni-V/TiO2-F
522
528
528
534
540
534
540
Ni-V/TiO2-R
534
540
522
Binding energy (eV)
528
Fig. 6.5 Core level spectra of O 1s for Ni-Mo/TiO 2 (fresh and reduced) and Ni-V/TiO2
(fresh and reduced)
Reduced Ni-Mo/TiO2 showed two shoulder peaks at 231.2 and 233.8 eV, which can be attributed
to Mo5+. V 2p core level spectra for Ni-V/TiO2 (fresh and reduced) sample are presented in
Figure 6.7. V 2p exhibited two symmetric peaks with a splitting of ~7.5 eV. The binding
energies of V 2p3/2 and V 2p1/2 peaks were observed at 516.9 and 524.4 eV, respectively, which
are characteristic of stoichiometric V2O5 and agreed well with values in the literature [24].
143
Mo
Mo
6+
3d 3/2
Mo
N i-M o/T iO 2 -R
3d 5/2
Mo
5+
C/S
Mo
Mo
3d 3/2
24 5
6+
240
6+
2 35
5+
6+
3d 5/2
2 30
N i-M o /T iO 2 -F
B inding energy (eV )
22 5
22 0
Fig. 6.6 Mo 3d core level spectra for Ni-Mo/TiO2 (fresh and reduced)
Ni-V/TiO 2-R
V 2p
C/S
Ni-V/TiO 2-F
V 2p 1/2
525
V 2p 3/2
520
515
Binding energy (eV)
510
Fig. 6.7 V 2p core level spectra for Ni-V/TiO 2 (fresh and reduced)
144
6.5.3 Reaction and Kinetic Study of Anisole
HDO reactions of anisole were carried out in a batch reactor, and their global kinetic analysis
using the integral method was used to calculate kinetic parameters, such as the reaction order,
rate constant, and energy activation.
Results from the HDO of anisole can be seen in Figures 6.8 to 6.10. Under the reaction
conditions, it was found that the reaction produced more than 10 different products; of these
products, we present the species that accounted for more than 1% of the total products. As shown
in Figures 6.8 and 6.9, nine major products were detected by GC-MS, including benzene,
cyclohexane, toluene, methoxycyclohexane, cyclohexanol, phenol, o,m,p-methylanisole, oisoprophylanisole, and p-isoprophylanisole. The anisole transformation can be achieved by
various reaction pathways, such as dealkylation, demethylation, deoxygenation, hydrogenation,
isomerization, and even ring opening reaction.
The effects of reaction temperature under the controlled conditions using Ni-Mo/TiO 2 and NiV/TiO2 were clearly seen for benzene, cyclohexane, phenol, and isoprophylanisole. As the
temperature increased, the production of benzene and phenol also increased; however, benzene
started to decrease beyond 275°C, perhaps due to competition from the reaction to produce more
phenol.
145
pressure of 100 psi, 6 h and using Ni-Mo/TiO2.
pressure of 100 psi, 6 h and using Ni-V/TiO2.
146
Fig. 6.10 Effect of reaction time on HDO of anisole. Reaction conditions: 1 mL of anisole ,
H2 pressure of 100 psi, 300 °C and using Ni-Mo/TiO2.
Fig. 6.11 Effect of reaction time on HDO of anisole. Reaction conditions: 1 mL of anisole,
H2 pressure of 100 psi, 300 °C and using Ni-V/TiO 2.
147
Based on the possible reaction pathways, anisole could have been transformed into benzene via
direct deoxygenation. Subsequently, benzene may have undergone hydrogenation and converted
to cyclohexane. The presence of H2 gas is vital to provide sufficient hydrogen bonding needed
for anisole transformation. The removal of methyl from anisole leads to phenol and further
produces toluene by hydrogenation.
Conversion pathways of anisole most likely began with hydrogenation of the benzene ring of
anisole, forming methoxycyclohexane, followed by the removal of methyl group to form
cyclohexanol. If the reaction continued to undergo the deoxygenation, cyclohexane would have
been produced. Similar observations were also mentioned by Jin et al. when performing HDO of
anisole using a Ni-based catalyst [25]. From the graph in Figure 6.9, we observed that the
formation of benzene was higher at lower temperatures (250 and 275 C) and started to decrease
at higher temperatures (300 and 325 C), which may have been caused by the hydrogenation and
methylation step.
Aside from varying the temperature of the reaction, effects of reaction time over HDO of anisole
were also studied. With both Ni-Mo/TiO2 and Ni-V/TiO2, the conversion increased from 18.7%
(2 hours) up to 59.9% (8 hours) and from 14.8% (2 hours) up to 46.1% (8 hours), respectively
(Figures 6.10 and 6.11). It was noticed that the use of Ni-Mo/TiO 2 favored the formation of
phenol. A similar observation was noted by Bui et al. when studying the catalytic conversion of
guaiacol using aluminum oxide (Al2O3), TiO2 and zirconium dioxide (ZrO2), where the TiO2
support formed phenol as the major product. It was also found that using a longer reaction time
148
favored benzene and cyclohexane-type molecules without any alkyl or alcohol branches. It is
clear that the product distributions were greatly affected by the use of catalyst.
(a)
(b)
149
(c)
(d)
Fig. 6.12 Plots of the of anisole concentration versus reaction time of HDO of anisole using
Ni-Mo/TiO2 at (a) 250 °C, (b) 275 °C, (c) 300 °C and (d) 325 °C.
150
In order to obtain kinetic parameters, HDO of anisole was performed under four different
temperature conditions and reaction times. For every reaction temperature, three different graphs
were plotted, in order to determine the reaction order of the reaction using the integral method.
Second-order reaction trends were found to match the data obtained, as shown in Figures 6.12
and 6.14 for Ni-Mo/TiO2 and Ni-V/TiO2, respectively. Since the reaction order had been
determined, the rate laws of the HDO of anisole could be written and rearranged as equations of
line. The plot of the logarithmic natural of the rate constant (ln k) and 1 over temperature (1/T) is
shown in Figures 6.13 and 6.15 for Ni-Mo/TiO 2 and Ni-V/TiO2, respectively. Using a linear
regression method, k and the energy activation (EA) can be determined. The values of the kinetic
parameters for HDO reactions using both catalysts is presented in Table 6.2.
using Ni-Mo/TiO2 to determine the kinetic parameter
151
(a)
(b)
152
(c)
(d)
Fig. 6.14 Fig. 6.12 Plot of the of anisole concentration versus reaction time of HDO of
anisole using Ni-V/TiO2 (a) 250, (b) 275, (c) 300, (d) 325 °C temperatures
153
using Ni-V/TiO2 to determine the kinetic parameter
Table 6.2 Kinetic parameter of HDO reaction using Ni-Mo/TiO 2 and Ni-V/TiO2
Catalyst
k (L/mol hr)
EA (kJ/mol)
Ni-V/TiO2
6481.6
53.89
Ni-Mo/TiO2
9735.2
80.93
6.5.Conclusions
The HDO of anisole was carried out in a batch reactor using Ni-Mo/TiO2 and Ni-V/TiO2
catalysts under relatively low pressure (100 psi) and moderate temperatures (250 to 325 °C).
Using XPS analysis, we found that the peaks in all the spectra were attenuated for the reduced
154
samples. Interestingly, the high binding energy peaks FWHM in all spectra (Ni 2p, Ti 2p, Mo 3d
and V 2p) were much broader and thus shorter than the low binding energy peaks. We suggest
that differences in the dissemination of active sites (metallic and acidic sites) with the
interference of promoters Mo and V and that particle size distribution in both Ni-Mo/TiO 2 and
Ni-V/TiO2 catalysts contributed to product distribution and conversions during the HDO
reaction.
Nine major products were detected by GC-MS including benzene, cyclohexane, toluene,
methoxycyclohexane, cyclohexanol, phenol, o,m,p-methylanisole, o-isoprophylanisole and pisoprophylanisole. With longer reaction times for Ni-Mo/TiO 2 and Ni-V/TiO2, the conversion
increased from 18.7% (2 h) up to 59.9% (8 h) and from 14.8% (2 h) up to 46.1% (8 h),
respectively.
The high activity of Ni- Mo/TiO2 can be explained by the well-dispersed small sized metal
particles, high surface area, mesopore structure and more acidic sites of the catalyst. A kinetic
analysis revealed that the reaction order was 2nd order in both reactions (using Ni-Mo/TiO2 and
Ni-V/TiO2); and, the activation energy values for anisole reactions over Ni-Mo/TiO 2 and NiV/TiO2 were 80.9 and 53.9 kj/mol, respectively.
6.6. Acknowledgement
The authors wish to acknowledge the financial support of the Natural Sciences and Engineering
Research Council of Canada (NSERC) and Ministry of Higher Education in Kingdom of Saudi
155
Arabia, and would like to thank Diego Costa and Camilla Fernandes de Oleivera for their
contribution in the experimental part of this study.
156
6.7. References
[1]
Yaman, S. Pyrolysis of biomass to produce fuels and chemical feedstocks, Energy Convers.
Manag., 45, pp. 651-671, 2004.
[2]
Fisher, T., Hajaligol, M., Waymack, B. & Kellogg, D. Pyrolysis behaviour and kinetics of
biomass derived materials, J. Anal. Appl. Pyrolysis, 62, pp. 331-349, 2002.
[3]
Ruddy, D. A., Schaidle, J. A., Ferrell III, J.R., Wang, J., Moens, L. & Hensley, J. E., Recent
advances in heterogeneous catalysts for bio-oil upgrading via ex situ catalytic fast
pyrolysis: catalyst development through the study of model components, Green Chem, 16,
pp. 454-490, 2014.
[4]
Bridgwater, A. V. & Peacocke, G. V. C., Fast pyrolysis processes for biomass, Renew.
Sustain. Energy, 4(1), pp. 1-73, 2000.
[5]
Huber, G. W., Iborra, S. & Corma, A., Synthesis of transportation fuels from biomass:
chemistry, catalysts, and engineering, Chem. Rev., 106, pp. 4044-4098, 2006.
[6]
Serrano-Ruiz, J. C. & Dumesic, J. A., Catalytic routes for the conversion of biomass into
liquid hydrocarbon transportation fuels, Energy Environ. Sci., 4(83), pp. 83-99, 2011.
[7]
Elliott, D. C., Historical Developments in Hydroprocessing Bio-oils, Energy & Fuels, 21,
pp. 1792 – 1815, 2007.
[8]
Bridgewater, A. V., Review of fast pyrolysis of biomass and product upgrading. Biomass
and Bioenergy, 38, pp. 68-94, 2012.
[9]
Mohan, D., Pittman, C. U. & Steele, P. H. Pyrolysis of wood/biomass for bio-oil: a critical
review. Energy & Fuels, 20, pp. 848-889, 2006.
157
[10] Zhao, C. & Lercher, J. A., Upgrading Pyrolysis Oil over Ni/HZSM-5 by Cascade
Reactions, Angewante Chemie, 51(24), pp. 5935-5940, 2012.
[11] Bui, V.N., Laurenti, D., Afanasiev, P. & Geantet, C., Hydrodeoxygenation of guaiacol with
CoMo catalysts. Part I: Promoting effectof cobalt on HDO selectivity and activity, Appl.
Catal. B: Environ., 101, pp 239-245, 2011.
[12] Bui, V.N., Laurenti, D., Afanasiev, P. & Geantet, C., Hydrodeoxygenation of guaiacol Part
II: Support effect for CoMoS catalysts on HDO activity and selectivity, Appl. Catal. B:
Environ., 101, pp 246-255, 2011.
[13] Lin, Y. C., Li, C. L., Wan, H. P., Lee, H. T. & Liu, C. F., Catalytic Hydrodeoxygenation of
Guaiacol on Rh-Based and Sulfided CoMo and NiMo Catalysts, Energy & Fuels, 25, pp.
890-896, 2011.
[14] Zhu, X., Lobban, L. L., Mallinson, R. G. & Resasco, D. E., Bifunctional transalkylation and
hydrodeoxygenation of anisole over a Pt/HBeta catalyst, J Catal., 281, pp. 21-29, 2011.
[15] Gutierrez, A., Kaila, R. K., Honkela, M. L., Slioor, R. & Krause, A. O. I.,
Hydrodeoxygenation of guaiacol on noble metal catalysts, Catal. Today, 147, pp. 239-246,
2009.
[16] Nimmanwudipong, T., Runnebaum, R., Block, D. & Gates, B., Catalytic Reactions of
Guaiacol: Reaction Network and Evidence of Oxygen Removal in Reactions with
Hydrogen, Catal. Lett., 141, pp. 779-783, 2011.
[17] Elliott, D. C. & Hart, T. R., Catalytic Hydroprocessing of Chemical Models for Bio-oil,
Energy & Fuels, 23, pp. 631-637, 2009.
158
[18] Ohta, H., Kobayashi, H., Hara, K. & Fukuoka, A., Hydrodeoxygenation of phenols as
lignin models under acid-free conditions with carbon-supported platinum catalysts, Chem.
Comm., 47, pp. 12209-12211, 2011.
[19] Olcese, R. N., Bettahar, M., Petitjean, D., Malaman, B., Giovanella, F. & Dufour, A., Gasphase hydrodeoxygenation of guaiacol over Fe/SiO2 catalyst, Appl. Catal. B: Env.,63, pp.
63-73, 2012.
[20] Wang, X., Rinaldi, R., Solvent effects on the hydrogenolysis of diphenyl ether with Raney
nickel and their implications for the conversion of lignin, ChemSusChem, 5, pp. 1455-1456,
2012.
[21] He, Z., Wang, X., Hydrodeoxygenation of model compounds and catalytic systems for
pyrolysis bio-oils upgrading, Catal. Sustain. Energy, 1, pp. 28–52, 2012.
[22] Aqsha, A., Katta, L., & Mahinpey, N., Catalytic Hydrodeoxygenation of Guaiacol as Lignin
Model Component Using Ni-Mo/TiO2 and Ni-V/TiO2 Catalysts, Catal. Lett., 145(6), pp.
1351-1363, 2015.
[23] Kruse, N. & Chenakin, S., XPS characterization of Au/TiO 2 catalysts: Binding energy
assessment and irradiation effects, App. Catal. A: General, 391, pp. 367-376, 2011.
[24] Valenzuela, R. X., Fierro, J. L. G., Corberan, V. C. & Mamedov, E. A., Ethane
oxidehydrogenation selectivity and reducibility of mixed NiVSb oxides, Catal. Lett., 40,
pp. 223-228 – 1996.
[25] Jin, S., Xiao, Z., Li, C., Chen, X., Wang, L., Xing, J., Li, W. & Liang, C., Catalytic
hydrodeoxygenation of anisole as lignin model compound over supported nickel catalyst,
Catal. Today, 234, pp. 125-132, 2014.
159
CHAPTER 7: CONCLUSIONS AND SUGGESTIONS FOR FUTURE WORKS
7.1. Relation between Chapters and Overall Achievement
In this research, three topics related to pyrolysis have been studied. The first topic is the kinetic
study of pyrolysis using thermogravimetric analysis (TGA) and the effect of several parameters
(particle size, heating rate, and initial weight). We performed the pyrolysis of sawdust biomass at
the beginning of the study and from the result we found that the reaction order of the pyrolysis is
around 1 (Chapter 3). We also be able to predict the yield of bio-oil, biogas and biochar through
the experiment that will be useful for the next stage of the research. Using the same technique,
we also pyrolysed the other type of straw biomasses (wheat, oat, flax and barley).
In Chapter 4, pyrolysis of straw biomasses has been scale-up to bench scale size experiment
(approximately 200 times of TGA scale ) in order to be able to collect certain amount of the
products that can be analysed and characterized. The setup was designed using stainless steel
horizontal rod surrounded by heating element of a furnace. From the experiment, the yield data
of pyrolysis product (biochar, bio-oil and gaseous product) were obtained and follow the
prediction data that were obtained using the method that was discussed in Chapter 3.
Bio-oil analysis that were obtained in the previous show the oxygen content were high and
therefore need un upgrading process to reduce the oxygen content. In the last two chapters
(chapter 5 and 6), bio-oil
upgrading component were performed using catalytic
hydrdeoxygenation (HDO) process. Two of common bio-oil components (guaiacol and anisole)
160
were chosen to represent the majority of phenol type component in the bio-oil and few catalysts
were synthesized and screened to achieve high conversion rate and yield. Screening of different
catalysts unveiled Ni-Mo/TiO2 as the most active catalyst for the HDO of guaiacol and anisole.
The relation between chapters can be seen in the diagram below.
Pyrolysis Research Study
Pyrolysis using TGA
(Chapter 3)
Biomass
analysis
Kinetic
analysis
Pyrolysis in bench-scale
reactor size (Chapter 4)
Bio-oil upgrading
(Chapter 5 and 6)
Reactor design and setup
Catalyst
synthesis
Pyrolysis of straw biomass
HDO of Guaiacol
& Anisole
Kinetic study of
HDO reaction
Fig. 7.1 Relation between chapters
161
7.2. Conclusions
The main objective of this study was to maximize the yield of bio-oil from the pyrolysis of
various straw biomasses and to synthesize a catalyst for utilization during the post-treatment
phase to increase the quality of the bio-oil. In order to meet this objective, the study was divided
into three different parts. In the first part of the study, pyrolysis of sawdust biomass was
performed using a thermogravimetric analyzer in order to understand the degradation process of
biomass and its kinetics. Several parameters were varied during the experiment to understand
their effect.
In the second part of the research, pyrolysis of several straw biomasses were conducted in a
bench-scale reactor based on the kinetics data obtained previously using a TGA. Three different
products (bio-char, bio-oil and gaseous material) were obtained from the process and analyzed
using several instruments to measure their heating value and composition. Catalysts were also
used in this stage to enhance the yield and quality of the bio-oil based on their respective
composition.
In the last stage, an upgrading process was conducted on the main components of the bio-oil, i.e.
guaiacol and anisole. A hydrodeoxygenation (HDO) reaction was selected with the aim of
reducing the oxygen content of bio-oil components to produce lesser oxygenated components
such as benzene and cyclohexane. Prior to the reaction, several different metal active catalysts
were synthesized using a wet impregnation method and further screened to determine the most
efficient catalyst for the HDO reaction.
162
Two catalysts, Ni-Mo/TiO2 and Ni-V/TiO2, were used for both the HDO of guaiacol and anisole
to study their activity. Temperature, reaction time and H2/guaiacol molar ratio were varied to
study their respective effect on the conversion and selectivity of the HDO reaction.
From these studies, we have made several conclusions:
 The results from the proximate analysis showed that the volatile material evolution was
higher with larger particle sizes. In the pyrolysis process, the char yield decreased as the
particle size of the sample increased.
 Reducing the particle size of the sample or increasing the initial weight or heating rate of
the pyrolysis process increased char production.
 The devolatilization process of the sawdust samples during pyrolysis was divided into
three non-interacting stages. The first stage was identified as the moisture loss process,
the second as cellulose and hemicelluloses devolatilization and the third as being
dominated by lignin devolatilization.
 A modified devolatilization kinetic model was used to obtain the kinetic parameters of
the reactions. The reaction orders for the stages 2 and 3 were 0.9 and 1.7, respectively.
 The results of proximate analyses on raw biomasses can be used to predict the product
yield produced during pyrolysis. The total yields of bio-oil and gas were consistently
lower than the volatile content produced in the proximate analysis.
 It was observed that the bio-oil yield during the pyrolysis increased with the use of a
zeolite-based catalyst.
163
 The HDO of guaiacol was successfully studied using Ni-Mo/TiO 2 and Ni-V/TiO2
catalysts under relatively low pressure (100 psi) and moderate temperatures (200 to 350
°C).
 Ni (10 wt%)/TiO2 and Mo (10 wt%)/TiO2 showed promising results with reference to unpromoted Ni/TiO2, Mo/TiO2 and variable Ni metal loadings. Incorporation of Mo and V
to Ni/TiO2 not only enhanced dispersion of metal species, but also improved the catalytic
performance.
 Variations in the product distribution and conversions were noted for both Ni-Mo/TiO 2
and Ni-V/TiO2 catalysts under different reaction conditions, which may have been
attributed to differences in the dissemination of active sites (metallic and acidic sites)
with the interference of promoters Mo and V and particle size distribution.
 With increases in temperature and H2/guaiacol mole ratio, both catalysts showed
improved conversion and selectivity.
 In particular, Ni-Mo/TiO2 showed better selectivity for phenol and cresol, while NiV/TiO2 exhibited more cyclohexanol along with phenol. Well-dispersed, small-sized
metal particles, high surface area, mesopore structure and more acidic sites may have
been the reasons for the high activity of Ni-Mo/TiO2.
 In an aqueous medium, Ni-V/TiO2 maintained a better guaiacol conversion and
phenol/catechol ratio than Ni-Mo/TiO2 and proved its tolerance to the presence of water.
164
7.3. Suggestions for Future Work
Suggestions for future work include:
1) Pressure is another important parameter for pyrolysis. Pyrolysis in higher pressure
conditions may have a positive effect on bio-oil production. In order to study this effect, a
high-pressure reactor is needed.
2) Nitrogen gas is used in most pyrolysis. Pyrolysis using hydrogen gas (H2) or methane
(CH4) should be performed to investigate whether the use of these gases can provide
hydrogen and methyl group sources that can alter the product composition of the
pyrolysis. There is a possibility that the use of H 2 or CH4 may significantly reduce the
oxygen content of bio-oil, hence increasing the quality of the bio-oil.
3) An HDO reaction on two or more bio-oil components (simultaneously) should be studied
to learn their interaction and to mimic the real composition of bio-oil.
4) It would also be interesting to find out what impact mixed gases (H 2 and CH4) may have
during an HDO reaction of the bio-oil component.
5) Use of combination of feedstock can be done between biomass and rich hydrocarbon
waste material such as plastic in order to increase the carbon and hydrogen ratio over
oxygen in bio-oil product.
165
APPENDIX A: LICENSE TO RE-PRINT
A.1.
License to re-print and re-use the content of WIT Publications (Chapter 3 & 4)
166
167
A.2. License to re-print of Chapter 3 – Study of Sawdust Pyrolysis and its Devolatilization
Kinetics
168
169
170
171
172
173
A.3. License to re-print of Chapter 5 – Catalytic Hydrodeoxygenation of Guaiacol as
Lignin Model Component Using Ni-Mo/TiO 2 and Ni-V/TiO2 Catalysts
174
175
176
177
178

UNIVERSITY OF CALGARY Study of the Pyrolysis of Straw Biomass

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