investigating the reaction kinetics of tropical...
TRANSCRIPT
Thesis for the Degree of Doctor of Philosophy
Investigating the Reaction Kinetics of Tropical Wood
Biomass - A Prospect for Energy Recovery
Kehinde Olubukola Oluoti
1
1. Introduction
1.1 Aim of the study
The aim of this study was to extensively examine the availability and the candidacy of
tropical wood biomass towards energy recovery purposes. The set of kinetic
parameters necessary as a prelude towards a viable deployment of the fuel material
were evaluated. This was with a view to verifying the thermal properties of the
materials under varied pyrolysis and gasification reaction conditions, employing
several kinetic methods and models. The materials were subjected to pretreatment
reactions (such as energy densification and torrefaction) in order to determine
properties such as energy yield, hydrophobicity, etc. as compared to the non-tropical
samples which are already being deployed for energy recovery purposes in the
developed countries.
1.2 Justification
Biomass wood waste is regarded as a viable option for the development of clean and
renewable energy. Going by the status quo, energy conversion from fossil fuels
releases a lot of greenhouse gases (GHG) into the atmosphere at the detriment of the
humankind. Compared to fossil fuels, wood fuel conversion is “carbon neutral” and
would reduce the net CO2 atmospheric emission levels. Moreover, The Inter-
governmental Panel on Climate Change’s (IPCC) last assessment report, for example,
outlined the emissions reductions needed from countries the world over to stabilize
concentrations of (GHG) consistent with limiting warming to 2°C. Further research has
continued to examine the global GHG emissions reductions necessary to avert
2
dangerous climate change, with the general decision to go renewable as regards
energy production. In essence, wood waste utilization for energy production is an
acceptable option and a research into thermal properties of the tropical wood waste is
highly important so as to enhance its use for energy conversion purposes in the
tropical countries.
1.3 Biomass
Biomass as a renewable source is made of organic materials readily available to
generate a number of energy resources such as electricity, gaseous or liquid fuels, and
heat. Biomass resources for fuel purposes include fuelwood, agricultural waste and
crop residue, sawdust and wood shavings. Over the years in Nigeria, fuelwood and
charcoal have constituted between 32 % and 40 % of total primary energy
consumption largely dominated by households (Oyedepo, 2012). In 2008, about 80 %
of Nigerian households were dependent on firewood as cooking fuel. In the developed
world however, bioenergy has not only been well established but extensively
researched. With the development of state-of-the-art products and services, modern
bioenergy has indeed been a tremendous success in satisfying humanity needs in
terms of provision of essential energy services (Silveira, 2005).
1.4 Wood waste and national need
In developing countries such as Nigeria, wood-processing companies and industries
generate a huge amount of waste in form of wood shavings, sawdust, etc. and are,
often openly burnt without control, thereby emitting particles and gases into the
atmosphere (Oguntoke et al., 2013). Pollutants from wood burning include
particulates, sulphur oxides, nitrous oxides, formaldehyde, carbon monoxide and
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organic matter. In addition, burning about I kg of wood releases close to 129 μg/m3 of
carbon monoxide, 700 μg/m3 of formaldehyde, 3300 μg/m3 of particulates, and 800
μg/m3 of benzene into the environment (Mohagheghzadeh et al., 2006). Dioxins and
plicatic acids are other constituents present in the wood smoke.
The world’s population has increased sharply from 1.65 billion to well over 6 billion
people in the 20th century (Akinola & Fapetu, 2015) . One of the direct consequences
of this is the overall increase in the world’s energy demand. Emodi and Boo (2015)
suggested strategies in sustainable energy development. These strategies, among
others, include the replacement of fossil fuels by various forms of renewable energy
(RE). Wood, being the most common form of biomass is considered relevant in this
direction. In essence, with the Government’s political will coupled with effective
application of public-private partnership (PPP), factors such as:
proper management; finance and adequate studies of the electricity
need/requirement of the host areas;
feasibility study of the proposed installation sites; and
the technical know-how concerning the deployment of mini-grid systems for
localities not connected to the national grid
Power provision as the national need could be effectively addressed and so made
available to the teeming populace not yet connected to the national grid.
1.5 Energy from biomass – alternative technologies
In poor countries of the world, biomass fuels (predominantly wood fuels) are common
source of bioenergy. With their technologies being majorly traditional, efforts are
being made to improve on the technologies by integrating biomass harvesting for
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energy purposes. According to Silveira (2005), about 1 percent of the world’s
electricity production comes from biomass. When used to generate energy, wood
waste is considered carbon-neutral because it releases no more carbon into the
atmosphere than it absorbs during its lifetime.
Table 1.1: Inter-relation and overview assessment of primary and integrated
conversion technologies
Primary conversion Form of
energy
recoverable
Integrated
conversion
technology
connection
Remarks
Heat Gas-fired boiler Commercial
(steam for
steam turbine)
Fixed and fluidized bed
gasification of wood
waste and other
forestry products
Power
Gas turbine Commercial
Micro turbine Commercial
Fuel cell Emerging
Stirling engine Emerging
Internal combustion
engine
Commercial and
highly deployed
Indirect fired gas
turbine
Commercial
Biomass pyrolysis Heat Oil-fired boiler Commercial
Power Indirect fired gas
turbine
Commercial
5
Stirling engine Emerging
Direct conversion of
biomass in gasifiers
(fixed and fluidized
bed)
Heat Heat exchanger Commercial
Power Steam turbine Commercial
As a result, bioenergy can reduce the amount of carbon dioxide released into the
atmosphere if it replaces non-renewable sources of energy. However, with direct and
integrated conversion technologies, energy trapped within biomass structure can be
transformed into power/or heat. The transformation options include pyrolysis,
gasification, and anaerobic digestion. Examples of integrated technologies (Paper II)
include steam turbine, indirect fired gas turbine, gas-fired boiler, internal-combustion
engine (IC), micro turbine, oil-fired boiler, gas turbine, fuel cell, heat exchanger and
Stirling engine. Most prominently, integrated conversion technologies further
transform the combusted gas into heat and power. A description of the different
options is found in Table 1.1.
1.6 Gasification
Currently, combustion is a mature technology which is suitable for biomass conversion.
The combustion process converts chemical energy stored in biomass into heat,
mechanical power and electricity using equipment such as furnaces, boilers, steam
turbines and generators. However, the gasification process has synthetic gas (syngas)
as the key product which mostly consists of carbon monoxide (CO) and hydrogen (H2),
which can be converted into energy (steam and/or electricity), other gases, fuels,
and/or chemicals. According to Young (2010), converting syngas to different products
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can be categorized under different options. These are power option, Biochemistry
option, and chemistry option and each option has its special output (Chen et al., 2011).
These options are illustrated below:
1. Power option: Generates heat and/electricity.
2. Chemistry option: Converts syngas into fuels and chemicals by catalytic
chemistry.
3. BioChemistry option: Converts syngas into products such as methanol, ethanol,
Converts syngas into products such as methanol, ethanol,
etc. using biotechnology processes
The use of bioenergy not only could replace the use of fossil fuels but also keep
atmospheric concentrations of greenhouse gases at acceptable levels. It also helps to
achieve the objectives of the framework convention on climate change (FCCC). Studies
about bioenergy potential estimation give a thorough understanding of the sources,
types, amount and distribution of bioenergy potentials. All these aspects can help
assess how much bioenergy can substitute and supplement energy shortage, the
possible degree to which bioenergy could contribute to decrease greenhouse gas, and
how to arrange rational development and utilization of bioenergy.
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2. Background
2.1 Resource recovery in the developing world
Resource recovery is a well-researched phenomenon in the developed world, with
countries tending towards zero waste societies (Taherzadeh & Richards, 2016). In
Africa, its implementation is far from encouraging going by the site of heaps of wastes
around towns and cities in most countries in the continent. However, governments of
these countries are making frantic efforts to change the situation. For low income
countries, the average solid waste generated in markets, households, and from
horticultural and agricultural practices is about 0.4 - 0.6 kg/person/day (Cofie et al.,
2009). The organic waste fraction in the form of wood waste remains the largest
population which can be recovered for energy purposes (Demirbas, 2009). Figure 2.1
shows the organic matter in municipal solid waste for some African cities.
Figure 2.1: The percentages of organic matter in the municipal solid waste of some
major African cities (modified from Cofie et al. (2009))
0
20
40
60
80
100
Ibadan Kampala Accra Kigali Nairobi
Org
anic
mat
ter,
%
Some African cities
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2.2 Forests and sawmills in Nigeria
2.2.1 Forest resources
Across Local Government Areas (LGAs) in Nigeria, forest income plays an important
role in poverty alleviation (Fonta & Ayuk, 2013). The forest is not only important for
material goods but also a valuable ecological and cultural resource. The forestry
subsector has over the years contributed immensely to the socio-economic
development in the country. It ranks among one of the highest revenue and
employment generating sectors. It also serves as resource base for many forest
industries.
The major wood processing industries in Nigeria are typically large capacity facilities
industry such as large sawmills, plywood mills, pulp and paper plants and a large
numbers of small scale wood products manufacturing companies such as furniture
industries, cabinet makers and carpentry. Round-wood in Nigeria comes mostly from
natural high forest zone of the country, in particular from the Southern State of Cross
River, Edo, Delta, Ogun, Ondo, Ekiti, Osun and Oyo States of Nigeria (Bello and
Mijinyawa, 2010).
Forests are seen by most people, particularly planners and decision makers, as a
source of one product: wood. Yet they are the source of a host of non-wood products
of immense value to the communities within and around them. These products include
foods, fibres, wildlife, water, building and handicraft materials, gums, spices, dyes,
animal fodder and medicines.
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Figure 2.2: A map showing the forest region in eastern Nigeria (Culled from Okoji
(2001))
With reference to the latter, FAO (1994) estimates that the active ingredients in 25
percent of all prescription drugs come directly from medicinal plants, although not all
of the these grow in forest habitat, and that the global value of plant based drugs is
about US $43 billion a year. The implication is, therefore, that non-timber forest
resources multiply opportunities for entrepreneurship. In addition, forests constitute a
vital part of the environment. They conserve watersheds, soil and water. They protect
land from wind and water erosion, modulate climate and sequester carbon thereby
buffering the global warming attributed to increasing levels of CO2. Although forests
provide these resources, deforestation is taking place at an accelerating rate in south
eastern Nigeria. About 350,000 ha of forest and natural vegetation are lost annually
due to various factors. In the Cross River State, for example, Atte (1997) estimates that
as much as 14000 ha of the moist lowland tropical forest is lost each year as a result of
deforestation.
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2.2.2 Sawmills
A sawmill is an installation or facility in which cut logs are sawed into standard-sized
boards and timbers (Figure 2.3). The saws used in such an installation are generally
three types: the circular saw, which consists of a disk with teeth around its edge; the
band saw, which consists of a hoop of flexible metal that runs over pulleys and has
teeth along one edge; and the log gang saw, which consists of saw blades separated by
desired distances in a frame that oscillates as a log is fed into it. Logs are fed to gang
saws through pressure rollers that ensure straight cutting.
Figure 2.3: Lumbering activities in a Nigerian sawmill
With other saws the log rides on a conveyor or carriage. Provision is made for
placement of the log in a new position for each cut, by the worker who rides the
carriage or by one who operates the saw. Sawmills account for about 93% of the total
number of wood-based industries in Nigeria.
These mills are concentrated in the southwestern part of the country, with Ondo,
Ogun and Lagos States having the largest numbers. The main type of log conversion
machine used in these mills is the CD horizontal band saw. The Lumber recovery factor
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in most sawmills varies between 45 and 50%. This implies that about 50-55 % of log
input into sawmills are left as wood residues or wastes.
2.3 Wood waste management
With the generation of a lot of wastes- sawdust, wood off-cuts, wood backs, plain
shavings, wood rejects, etc. coupled with an absence of proper disposal methods,
these wastes are burnt in the open air along the bank of streams and rivers (Figure
2.4). As the demand for woods and its products increases, the volume of wastes being
generated cannot but increase. Hence, one of the greatest environmental problems
facing our cities and towns today is how to properly dispose of the waste being
generated daily by the ever-increasing activities of the sawmill industries. Odewunmi
(2001) observed that waste generation is a concomitant aspect of living; it cannot be
banished but can only be managed. The problems posed by these wastes are many:
they degrade the urban environment, reduce its aesthetic value, produce offensive
odors during the rains and pollute the air with smoke when burnt uncontrollably.
Figure 2.4: Poor wood waste management in Nigeria
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They also constitute health hazards in themselves if they are not timely disposed and
thus become breeding places for worms and insects. The sawdust is often spilled into
the lagoons, waterways, etc. and sometimes blocking the drainages and canals into the
lagoon.
The blockages of canals and drainages also cause flooding in the hinterland during
raining season. They also constitute bad working environment for those working in the
area, due to accumulation of wastes over a period of time, most especially during
raining season. Personal information from respondents on the waste disposal system
in the mills (Bello and Mijinyawa, 2010) is as obtained below:
Table 2.1: Mill waste disposal methods in the mill site
Waste Disposal Method Frequency
Response
Percentage
Response
Dump sites for wood waste to be disposed via burning
10 15.56
Heap wastes within the open spaces and burn on daily basis
31 48.45
Local food vendors and villagers pack for domestic use
12 18.77
Disposal for Agricultural uses and animal bedding
6 9.38
Other means of disposal apart from above
5 7.82
Total 64 100
Source: Bello and Mijinyawa (2010)
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2.4 Potentials for improving energy access through renewable energy
While at the same time combating the challenges of global warming, achieving
sustainable development through energy security is crucial. In this regard, the
utilisation of renewable energy resources, such as solar, wind, hydro, biomass and
geothermal energy, appears to be one of the most efficient and sustainable ways of
achieving this target. Globally, there has been upward trend in the utilisation of
renewable energy in the generation of modern energy (electricity). Table 2.2 presents
the developments and share of renewable energy in electricity generation in some
countries. Renewable, except hydro, have zero shares in power generation in Nigeria
despite its abundant existence in the country. Meanwhile, economically-feasible
renewable energy potential in Nigeria is projected to contribute with 2,036 MW, 6,905
MW and 68,345 MW to the electricity production in the country in the short, medium
and long-term respectively. This would then provide more than 37% of Nigeria’s total
energy consumption in the long-run. The national wood timber demand is projected to
increase to 91 million tonnes by 2030. This has great implications on sustainable
environment, food security and health of the low income households who depend
largely on wood fuels.
The strategic ways of controlling this problem is a dual approach of reducing
consumption rate through promotion of more efficient wood stoves and deployment
of alternatives to fuelwood through policy instrument and development of renewable
energy technology. Specifically, the government needs to address the problems posed
by deforestation by making use of these resources efficiently through improved
renewable energy technologies, thereby reducing the direct use of traditional biomass
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(fuelwood, crop residue, municipal wastes, sawdust, etc.) and improves modern
energy access.
Table 2.2: Share of electricity generation from renewable sources for selected
countries, 2000 –2006 (modified from Oseni (2012))
Year 2000 Year 2006
Country Including hydro Excluding
hydro
Including hydro Excluding
hydro
Austria 72.3 2.8 67.6 8.4
Germany 6.3 2.5 12.0 8.7
Italy 18.9 2.5 18.0 5.4
Portugal 30.3 4.2 34.0 10.4
Spain 16.3 3.0 18.7 9.6
UK 2.6 1.3 5.0 4.1
Turkey 24.9 0.2 26.3 0.2
Nigeria 40.3 0.0 34.7 0.0
With the envisaged deployment of wood waste for power production (Paper II), the
conversion technologies (pyrolysis and gasification) are extensively examined. It is
however worthy of note that there are similarities in the conversions of coal and
biomass. This informs the possibility of employing the services of the existing coal-
conversion facilities for the conversion of wood waste biomass (Oluoti et al., 2014).
While biomass can be described as a young coal with a known minimum gasification
temperature at 800 °C, coal has 900 °C as its minimum gasification temperature
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(Higman C., 2008). However, biomass (especially wood) in the lower gasification
temperature range produces a lot of tars (Devi et al., 2003; Swierczynski et al., 2008).
Preceding the gasification process is the devolatilization process, equally known as
pyrolysis. The raw wood waste is processed as fuel and fed into a gasifier. With the
help of an oxidant mostly (O2 or steam), the fuel in the gasifier is converted first into
char, tars, and gases during pyrolysis and then turned into ash, giving out the synthetic
gas (syngas). The syngas can be cleaned and sent into a gas engine or turbine to
produce electricity (Paper II). The schematic diagram of the process is seen in figure
2.5.
Figure 2.5: Flow diagram for power production from wood waste using gasification
(Paper II)
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2.4.1 Pyrolysis – overview, products and applications
During thermal conversion of biomass, the first step after drying is devolatilization,
which starts the release of the volatile matter from the solid fuels. This step is also
known as pyrolysis and it occurs in an inert atmosphere (Bulushev & Ross, 2011). In
general, thermochemical conversion of biomass falls into two main approaches which
are pyrolysis and gasification (Canabarro et al., 2013; Sharma et al., 2015). Biomass
conversion via pyrolysis and gasification is represented in figure 2.6.
Figure 2.6: Energy conversion of biomass (pyrolysis and gasification) to chemical fuels
and additives
For non-catalytic pyrolysis of biomass (as the case of wood), the mode of pyrolysis
employed determines the relative amount in which the biomass itself, char, liquid and
gas are formed as well as, the type of the pyrolysis system employed (Bulushev & Ross,
17
2011). According to Bridgwater (2006), the different models employable for pyrolysis
reaction are fast, slow, and intermediate. The complete description is as shown in
Table 2.3. During pyrolysis, hemicellulose decomposes between 250–400 °C and about
20 wt. % of char is produced as the reaction temperature goes up to around 720 °C.
Compared with hemicellulose, cellulose decomposes at a temperature in the range of
310 –430 °C, leaving behind about 8 wt. % char. Lignin has a decomposition
temperature in the range of 300 – 530 °C.
Table 2.3: Modes of pyrolysis, reaction circumstances and product distribution
Reaction circumstances Products (100%)
Model Working
temp. (°C)
Exposure time Gas Liquid Char
Fast 500 Short (1s) 13 75 12
Slow 400 Very long 35 30 35
Intermediate 500 Moderate (about 10-20 s)
30 50 20
The char yield from lignin breakdown is about 55 wt.% (Williams & Besler, 1996). For
the carbohydrate content of the biomass, they depolymerise even at low temperature
to give smaller units. As dehydration takes place at about 300 °C, unsaturated
polymers and chars are produced. At temperatures higher than 300 °C, there is
massive rupture of C-C and C-H bonds and thus giving the products of pyrolysis in the
process (Brezinsky et al., 1988). The products include CO, CO2 and CH4. From pyrolysed
wood wastes, both the gases and the solid residues are useful in heat recovery
applications. The latter can further be used for agricultural purposes, especially in the
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production of fertilizer. Bio-oil as the liquid product has wider applications (Czernik &
Bridgwater, 2004), and can be upgraded to high-quality hydrocarbon fuels for further
use in boilers, engines and turbines. Applications of pyrolysis oil (bio-oil) include: heat
and power, transport fuel and biorefinery to other products.
Heat and power
Bio-oils are already being used in place of fossil fuels for medium or large-scale (co-)
combustion of natural gas, coal or heating oil-fired boilers, furnaces and turbines
(Czernik & Bridgwater, 2004). Aside its GHG savings of about 90 % compared to the
fossil fuel (FAO, 2008), it ensures some sustainability as the source (wood biomass) is
renewable.
Transport fuels
Second generation (advanced) biofuels can be obtained from bio-oils via direct
upgrading or through co-refining in existing refineries. It is also obtainable from
synthetic gas being processed and upgraded catalytically to produce fuels such as
DME, methanol and Fischer-Tropsch diesel. The two identified routes being envisaged
(Graça et al., 2013) for the production of biofuels from bio-oil include:
(1) Hydrodeoxygenation (HDO) of bio-oil to produce fuel or a feedstock
capable of being used in oil refinery.
(2) Processing of bio-oil to produce synthetic gas and then further processed to
transport fuel.
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2.4.2 Gasification – overview, products and applications
Gasification is a thermo-chemical process in which combustible gases are obtained
from the transformation of biomass undergoing thermal treatment (Zheng, 2013).
During the process, fuel biomass is exposed to a temperature range of about 850 -
1100 °C under an atmosphere of controlled oxygen (no combustion) or steam. The
product gases (syngas) from the process can be used to produce varieties of chemicals
and transport liquid fuels (Swanson et al., 2010). The type of gasifier employed for the
conversion and the way the fuel is fed in into the unit determine the name of the
gasification technology employed. The three generic fixed-bed gasification
technologies are updraft, downdraft and cross-draft. Other technologies are bubbling
bed, circulating fluidized, entrained bed, spouted bed and cyclone. The gasification
technology employed is usually optimized based on the feedstock as regards the
residence time and the operating temperature employed. According to Mullen et al.
(2010), about 35-45 % of energy contained in biomass feedstock is consumed during
the gasification process. For the purpose of power generation, integration of biomass
gasification with a gas engine is effective in small-scale (less than 10 MW power
output). For higher power output, steam turbines are employed. Syngas conversion to
transportation liquid fuels and other chemicals (bio-refinery) is made possible via for
example the Fischer-Tropsch process.
2.5 National need - wood waste to the rescue
For Nigeria as a country, the use of renewable materials such as wood waste to
address some national need is a possibility. The dwindling oil prices, the increasing
population and the pressing need to improve on the social amenities have made it
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necessary to go the way of renewable option for solutions. Inadequate power
provision is a national issue that could be addressed with the use of the abundant
renewable wood wastes. Nigeria could harness this huge dump of wood wastes to
augment the existing power supply and also provide electricity for those not
connected to the national grid (Paper II). Such conversion however, would require the
application of energy recovery processes such as pyrolysis and gasification (Paper I).
This also would involve the study of the reaction conditions and product analysis
(Paper III, IV, and V). The kinetic parameter results from these studies would assist in
the design of suitable reactor for the optimum conversion of these resources for
energy use. Considering the totality of biomass waste produced in Nigeria, it is
estimated that about 41 TWh of electricity may come from biomass waste resources
(Figure 2.8)
Figure 2.8: Biomass resources in Nigeria and their power generating potentials (Paper
II).
0
5
10
15
20
25
30
Fuel wood Agrowaste Sawdust Municipal solidwaste
TWh
Biomass resources in Nigeria
Electricity generationpotential
21
3. Experimental and Methodologies
3.1 Biomass fuel samples
A total of six tropical biomass species were employed during the research. They were
obtained as sawmill wastes from Nigeria. Their local (Nigerian) and the botanical
names are as indicated in the Table 3.1. Also listed are their numerical values for
density (Air-dry).
Table 3.1: List of wood waste samples employed in this study
S/no Local name Botanical name
1 Teak Tectona grandis (Paper I)
2 Obobo Guarea thompsonii (Paper I)
3 Ayinre Albizia gummifera (Paper III)
4 Ahun Alstonia congensis (Paper IV)
5 Araba Ceiba pentandra (Paper IV)
6 Arere Triplochiton scleroxylon (Paper V)
All samples were collected as wood logs and further sun-dried (supervised) for an
average of about three weeks. This is done to ensure low moisture content. Prior to
being used for experimental runs, the sun-dried samples were size-reduced using
RETSCH SM 100 cutting mill to an average final size in the range of 0.20 to 2.00 (Paper
I, III, IV, and V).
22
Tabl
e 3.
2: C
ombi
ned
com
posit
ion
in m
ass-
% o
f dry
fuel
s and
hig
her h
eatin
g va
lues
(HHV
) in
kJ/g
dry
fuel
for a
ll th
e w
ood
sam
ples
Loca
l
nam
e
Bota
nica
l nam
e M
oist
ure
%
(105
°C)
Ash
%ts
(550
°C)
C %
ts
(dry
)
H %
ts
(dry
)
N %
ts
(dry
)
S %
ts
(dry
)
HHV
kJ/g
Tea
k Te
cton
a gr
andi
s 7.
7 1.
0 51
.2
6.2
0.19
0.
012
19.0
3 ±
0.02
Obo
bo
Guar
ea th
omso
nii
6.6
5.3
48.3
5.
7 0.
34
0.03
5 18
.78
± 0.
16
Ayi
nre
Albi
zia g
umm
ifera
5.
3 1.
5 49
.4
6.1
0.36
0.
027
19.2
9 ±
0.08
Ahu
n Al
ston
ia c
onge
nsis
7.0
1.1
51.4
6.
0 0.
49
0.03
3 18
.08
± 0.
21
Ara
ba
Ceib
a pe
ntan
dra
6.6
1.5
49.7
6.
0 0.
45
0.02
9 18
.43
± 0.
11
Are
re
Trip
loch
iton
scle
roxy
lon
7.5
1.9
50.1
6.
0 0.
53
0.04
6 18
.44
± 0.
09
ts=t
otal
solid
, C=c
arbo
n, H
=hyd
roge
n, N
=nitr
ogen
, S=s
ulph
ur
23
3.1.1 Proximate and ultimate analyses for all the wood samples
The respective energy content of the above-listed samples is a function of their
chemical compositions (Chen et al., 2014). It is important to note that the presence of
inorganics and moisture reduces the energy content of the samples (Wilson et al.,
2011). The proximate and ultimate analyses of the samples were made at BELAB AB
and the results as shown in Table 3.2. Except for Obobo with higher ash content
compared to others, all other results are similar for the samples considered in this
study.
Figure 3.1: Bomb calorimeter
3.1.2 Heating values
The calorific values (HHV) of the materials were evaluated using ASTM D240 and ASTM
D5865 standards. A bomb calorimeter (Fig. 3.1) manufactured by IKA was used (model
C 200). The analysis was initialized by weighing about 0.5 g of the materials in a
24
crucible and placed inside the calorimeter. The runs were duplicated and the results as
shown in Table 3.2.
3.2 Thermogravimetric analysis
In solid-phase thermal degradation studies, thermogravimetric analysis is widely used.
It has widespread applications in biomass pyrolysis and gasification studies as
employed in Branca et al. (2007); Momoh et al. (1996); Stenseng et al. (2001); Teng
and Wei (1998). The thermogravimetric analyser (TGA) brand employed throughout
this research is a DynTherm HP by Rubotherm GmbH and shown in Fig. 3.2.
Figure 3.2: Thermogravimetric analyser (TGA)
It measures the loss in mass during thermal decomposition as a result of release of
volatiles as the reaction proceeds under preferred range of operating conditions such
as temperature, pressure, heating rates and gas flow rates. The main components are
the automated gas-dosing system and the suspension magnetic balance. It is an
25
electromagnetic balance, which makes it specifically suitable for high pressure as there
is no physical connection between the test area and the balance. The complete unit is
controlled by a software called MessPro.
3.2.1 Mass loss
The property being investigated employing thermogravimetric analysis is mass (White
et al., 2011), and it is measured as the changes in sample mass as the reaction
proceeds. The data generated can be graphically represented in several ways. An
example of such is the mass loss curve in paper IV (Figure 3.3a). For the Teak sample
employed at different heating rates, the differences in pyrolysis zones are evident.
(a)
20
40
60
80
100
0 20 40 60 80 100
Wei
ght (
% w
t)
Time (min)
26
(b)
Figure 3.3: (a) Weight loss for Teak at different heating rates (Paper I) (b) Derivative
plots for Araba at different heating rates (Paper IV).
3.2.2 Derivative thermogravimetry (DTG)
Taking the first derivative of the mass loss gives DTG curves (i.e., -dm/dt ) (Figure 3.3b)
provides the instantaneous reaction rate (Mészáros et al., 2004). It is also possible
from the DTG curves to obtain the peak temperature (where the maximum conversion
rate occurs) for the decomposition process (Vamvuka et al., 2003). Figure 3.3b
represents the DTG curves for Araba at different heating rates.
3.3 Torrefaction experiment and property change measurements
Alongside the TGA, torrefaction experiments were conducted (Paper IV) with the aid
of Nabertherm oven (model p330) under a controlled nitrogen atmosphere with a flow
rate of 0.833 Lmin-1 and a heating rate of 20 °C/min, the fuel samples were exposed to
different temperatures of either 150, 200, 250 or 300 °C. The samples were held in the
torrefaction reactor (the oven) for varied number of minutes (holding times). The
0
5
10
15
20
25
30
0 20 40 60 80 100
Deriv
. wei
ght (
% w
t/m
in)
Time (min)
27
resulting masses (chars at high temperatures) obtained were subsequently used for
mass and energy yield estimations. Moisture uptake measurement (hydrophobicity)
was also carried out using a constant climate chamber HPP108 (manufactured by
Memmert) set at a relative humidity of 85 % and a temperature of 45 °C (typical
conditions in the tropics) for a total time of 24 hours.
3.4 Analysis of char morphology
Biomass gasification is preceded by devolatilization (pyrolysis) reaction. During the
process, the reaction temperature is maintained at a high temperature of 800 °C
leading to the release of steam and other volatiles. The remaining solid is referred to
as chars. Aside other factors, the pyrolysis conditions such as temperature, pressure,
heating rates, etc. employed during the reaction determines the microstructure of the
produced chars (Altun et al., 2003; Aouad et al., 2002; Demirbas, 2004; Mani et al.,
2010). The varied char morphology as regards pore and fibre orientations and
alignments are investigated using a Quanta FEG 200/400/600 scanning electron
microscope (SEM) with an operating voltage of 10 kV (Figure 3.4a). For further spot
analysis of SEM micrographs, an Astec SEM-EDX spot analyser (Figure 3.4b) was used.
The elemental percentage compositions of the selected areas are characterized by the
spot analyser, specifying the average, minimum, maximum and the sum.
28
(a) (b) Figure 3.4: (a) Quanta FEG 200/400/600 scanning electron microscope (SEM), (b) Aztec SEM-EDX spot analyser.
3.5 Thermochemical processes and parameter determination
The thermogravimetric analyser (TGA) was employed to determine the kinetic
parameters during thermal conversion. In literature, several thermochemical processes
are available and these include combustion, pyrolysis, gasification and liquefaction.
The TGA offers the opportunity to either only pyrolyse the samples to form chars
(Paper I, II, and V) or continue through to gasification (Paper I, II, and V).
For the pyrolysis process, the pre-treated sample is first dried to a constant mass at a
temperature of 105 °C in the TGA. The pyrolysis is made by heating the sample in inert
atmosphere of nitrogen gas to the required pyrolysis temperature with a pre-
determined heating rate (Paper I, III, IV, and V). For the gasification process, the char
obtained from the pyrolysis process is isothermally gasified using a gasifying agent (Air,
O2, CO2, or steam). Meanwhile, kinetic parameters derived experimentally are affected
by reaction conditions such as temperature (Demirbas, 2004; Grønli et al., 2002),
heating rate (Cetin et al., 2004; Mermoud et al., 2006), residence time (Scott & Piskorz,
29
1982), particle size (Demirbas, 2004), and pressure (Cetin et al., 2005). In terms of char
formation, the quantity of the char produced in cellulose pyrolysis varies with the
reaction pressure and the sample size (Yan et al., 2010). Yuan et al. (2011) discovered
that the residence time of the volatiles in the biomass matrix during the
devolatilization process determines the extent of the char produced. Mermoud et al.
(2006) also studied the influence of heating rate on the steam gasification of wood
char particles.
3.5.1 Pyrolysis kinetics
Generally, the kinetic expressions for biomass thermal decomposition can be
expressed under isothermal or non-isothermal conditions and formulated with respect
to a combination of solid-state reaction kinetic and Arrhenius equations. For
isothermal conditions, the form is
= exp . ( ) (1)
And for non-isothermal form with accompanying heating rate = written as
= . exp . ( ) (2)
The combination of , , and ( ) are designated as the kinetic triplet and often
employed to investigate biomass pyrolysis reactions. The models and methods used
throughout this study together with their governing equation are displayed in Table
3.3.
30
Table 3.3: List of methods employed for kinetic parameter determination
Category Method Governing Equation
Flynn-Wall-Osawa
(FWO)(Paper I) log = log ( ) 2.315 0.4567
Kissinger-Akahira-
Sunose (KAS) (Paper
I)
ln = 1 ln ( )
Model-free
Methods
Friedman (Paper I,
V) ln = ln + ln(1 )
Li-Tang (Paper I) ln = + ( )
Kissinger (Paper I) ln = ln + ln (1 )
Model-
fitting
Method
Coats & Redfern
(Paper I and IV) ln ( ) = ln 1 2 –
Kennedy and Clark
(Paper I)
ln ( )( ) =
The term ( ) in Equation 1 denotes the changes in physical or chemical properties of
the samples as the gasification proceeds and it has different expressions when
considering each of the above-listed models (Zhang et al., 2014). For the model-fitting
methods, the recurrent term represents the integral function of the various
mechanisms (Khawam & Flanagan, 2006a; Maitra et al., 2007; White et al., 2011). The
31
various solid-state reaction models employed throughout this research study included:
Reaction order (Paper I and IV); Avrami-Erofeev (Paper I); Diffusional 1D (Paper I); and
Contracting geometry (Paper I).
The full list of the used models (mechanisms) and that of others together with their
various expressions for and are well represented in the works of White et al.
(2011), Khawam and Flanagan (2006a) and Maitra et al. (2007). Cadenato et al. (2007)
and Budrugeac et al. (2007) established that a reaction mechanism can be declared
suitable based on the correlation coefficient (R2) and that the closer the R2 to unity,
the better the assumed mechanism represents the reaction. In the event of similar R2
values between different assumed mechanisms, Cadenato et al. (2007) and Budrugeac
et al. (2007) suggested comparing the calculated activation energies at different
models with the average activation energy from iso-conversional methods (Paper I).
3.5.2 Gasification kinetics
Biomass gasification follows a trend whereby the fuel is pyrolysed or devolatilized to
produce char. The solid carbonaceous fuel is being converted into combustible gas by
partial combustion (Sheth & Babu, 2010), and subsequently gasified using gasifying
agents such as air, CO2 or steam. However, the quality and nature of the chars
produced during pyrolysis depend on different factors such as biomass characteristics
and process conditions (Guizani et al., 2015). Compared with the initial process of char
formation (pyrolysis), the char conversion (gasification) process that follows is rate-
limiting meaning that this step is often slower than the initial pyrolysis. The kinetic
study of gasification is important to understand its reactivity in the process gasifier
(Ollero et al., 2003; Ollero et al., 2002). According to Zhang et al. (2014), different
32
kinetic models are employed for the conversion analysis of chars formed under
different reaction conditions. For this reason, the interpretation of the conversion data
from the biomass gasification reaction throughout this study was made using four
selected gas-solid gasification models: Shrinking-core model (SCM) (Paper I and III);
volumetric reaction model (VRM)(Paper I and III); modified volume reaction model
(mVRM)(Paper III); and Random pore model (RPM)(Paper V). Table 3.4 gives a brief
description of the four kinetic models listed above.
The apparent kinetic reaction constant for each model is determined from the plot of
their respective linearized rate equations (Paper III). For a group of models employed
as above, the widely applied statistical methods to determine the relative ability of
each models to describe the experimental data include correlation coefficients (R2)
values and average error test (Paper V). The process starts with the pyrolysis of the
raw fuel samples into char and the gasification of the char follows producing ash as the
left-over in the presence of a single (or mixed) gasifying agent.
33
Ta
ble
3.4:
Em
ploy
ed g
as-s
olid
reac
tion
mod
els a
nd th
eir a
ssum
ptio
ns
Mod
els
Assu
mpt
ions
Li
near
form
of r
ate
Equa
tion
Conv
ersio
n Eq
uatio
n SC
M
Reac
tion
star
ts a
t the
ext
erna
l sur
face
(Now
icki
et a
l., 2
011;
Zo
u et
al.,
200
7) a
nd m
oves
tow
ards
the
cent
re p
rodu
cing
an
unr
eact
ed in
ner m
ater
ial w
ith c
ontin
uous
ly sh
rinki
ng
core
(Bel
l et a
l., 2
010;
Kum
ar e
t al.,
200
8).
Part
icle
dia
met
er d
ecre
ases
whi
le th
e po
rosit
y is
cons
tant
(S
eo e
t al.,
201
0).
Grai
ns (w
ith a
ssum
ed sp
heric
al sh
ape)
und
ergo
es re
duce
d co
re d
iam
eter
as t
he re
actio
n pr
ocee
ds (F
erm
oso
et a
l.,
2008
).
3[1(1)
]=
=1(1
t/3)
VRM
The
char
par
ticle
s un
derg
o a
hom
ogen
ous
reac
tion
(Seo
et
al.,
2010
) with
a d
ecre
asin
g su
rfac
e ar
ea a
s th
e co
nver
sion
proc
eeds
(Kar
mak
ar &
Dat
ta, 2
011)
.
-ln( 1) =
=1(
) m
VRM
Th
e ap
pare
nt r
ate
cons
tant
cha
nges
with
the
sol
id r
eact
ion
(Yi,
1984
).
-ln( 1) =(
)
=1exp (
() ) RP
M
Pore
su
rfac
es
over
lap,
re
duci
ng
the
area
av
aila
ble
for
reac
tion
(Fer
mos
o et
al.,
200
9).
Char
s ar
e po
rous
mat
eria
ls fil
led
with
cyl
indr
ical
por
es
havi
ng u
nequ
al d
iam
eter
s (Irf
an e
t al.,
201
1).
Pore
size
s in
crea
se a
s ga
sific
atio
n re
actio
n pr
ocee
ds,
with
po
re w
alls
bein
g m
erge
d le
adin
g to
a r
educ
ed n
umbe
r of
po
res (
Bell
et a
l., 2
010)
.
( 2 )[(1
ln( 1) )
1]=
=1exp [(1
1+2
)/]
34
35
4. Results and Discussions from the Appended Papers
4.1 National need- electricity
Nigeria’s electricity consumption per capita is one of the lowest in the world and it is
standing at 115 kWh per person. This is about 3 % of what is obtainable in South Africa
(Paper II). The effect of non-availability of stable and adequate supply of electricity has
made the Federal Government of Nigeria, companies and individuals to explore the
possibility of generating power from renewable sources. With the decreasing power
production level coupled with ever-increasing population in Nigeria, the problem of
power supply could get worse. At the moment, only about 50 % of the total population
has access to electricity (Ohiare, 2015). To improve on the power supply, the use of
wood waste for power production cannot be over-emphasized. Sambo (2009)
estimated that the total amount of wood waste produced by the lumber industry in
Nigeria is about 1.8 million tonne/yr and this could generate about 1.3 TWh of
electricity (Paper II). For Paper II, the emphasis was on the biomass and the
technicalities of the energy conversion/recovery towards the purpose of electricity
production. The technicalities of conversion include: Pyrolysis and its kinetics (Papers I
and V); Gasification and its kinetics (Papers I, III, and V); Torrefaction (a pretreatment
method) and its kinetics (Paper IV); and Reaction parameter variations (Papers I, III, IV,
and V) were all studied. As a representation of tropical wood samples, the species
employed were: Tectona grandis (Paper I); Albizia gummifera (Paper III); Alstonia
congensis (Paper III); Ceiba pentandra (Paper IV); and Triplochiton scleroxylon (Paper
V). Apart from taking care of waste wood material to prevent health and
36
environmental hazards, its envisaged conversion to electricity addresses the power
shortage in the country.
4.1.1. Biomass power technologies
To address the national need (power problem), gasification of the abundant wood
waste could be of great importance as it involves the conversion of the fuel into
electrical power. Other products as highlighted earlier are heat and other biofuels for
other applications other than power. Studies in Paper II have shown that the
integration of biomass gasification technology for the production of fuel gas for use in
the different biomass power technologies employed (i.e. gas turbine, micro gas
turbine, steam turbine, internal combustion engine and Stirling engine) enhanced the
overall electrical performance (which exceeded 30 %).
4.1.2 Evaluation of biomass power technologies
For the purpose of mini-grid deployment towards the production of power (small-
scale) using biomass and waste as fuel, the power technologies listed above are
evaluated for electrical efficiency and economic feasibility. It is however good to note
that most of these technologies are yet to be commercially deployed. Therefore, the
proposed evaluations were made based on the parameters obtained from
demonstration plants and other information gathered from the operating conditions
(Reference conditions). Meanwhile, using an example of Ile-Ife city in the southwest of
Nigeria, the wood residue generated per day was estimated at 20 tonne/day. The
biomass power technologies evaluations were based on this figure. For economic
evaluation, the indicators considered include the fixed capital cost (or total capital
cost) (CFCC) and total capital investment cost (CTCI). The electrical efficiency of each
37
power technology was evaluated from the reference plants based on the energy value
of the biomass fuel and process modifications in some of the technologies. The cost
and efficiencies for the processes are shown in Table 4.1.
It is estimated that the steam the turbine and gas turbine technologies require more
capital compared to others. The working capital cost (CWCC) (or running capital cost) is
assumed to be 20 % of the CFCC (Syed et al., 2012). It is also clear from the result array
(Table 4.1) that the costs for the Stirling engine and the internal combustion engine are
the lowest of all and therefore considered as good candidates for small-scale power
production. However, issues relating to the use of referenced pilot-scale conditions
could be observed here regarding the electrical efficiency results for the Biomass
Power Technologies. Although a better electrical efficiency for internal combustion
engine compared to micro gas turbine was displayed, literature review indicates the
opposite. Gimelli et al. (2012) indicated that a micro gas turbine operating at 6 bar
pressure could increase its electrical performance to 31 % below an electric output
range of 500 KW. The direct implication of this is that micro gas turbine compared to
internal combustion engine gives a better electric performance when used for mini-
grid micro power application is desired.
Table 4.1: Economic and electrical performance evaluation results for biomass power
technologies
Biomass power
technologies
Economic evaluation
Electrical performance
CFCC ($/kWel) CTCI ($/kWel) Electric efficiency (%)
Micro Gas Turbine 6100 7300 30
Gas Turbine 6200 7400 29
38
Internal Combustion Engine 2800 2800 33
Stirling Engine 3300 3900 20
Steam Turbine 6200 7500 23
4.2 Biomass pyrolysis – the kinetics and reaction model mechanism
A fundamental and typical graphical representation of generated data from the
devolatilization runs of any of the samples listed in Table 3.1 is shown in Fig. 3.3 (a) &
(b). Employing different heating rates (°C/min) and temperatures as variables for the
devolatilization reaction, a compilation of the main pyrolysis temperature range (i.e.
temperature interval for the maximum material loss (Kumar et al., 2008)) and the peak
temperature for Ahun and Araba (Paper IV) is shown in Table 4.2. Kissinger (1956)
defined peak temperature as the temperature at which the maximum reaction rate
occurs. Peak temperatures increase with heating rate (Pantoleontos et al., 2009;
Vamvuka et al., 2003; Várhegyi, 2007) Várhegyi (2007) and Vamvuka et al. (2003).
Araba and Ahun (Paper IV) followed the trend as shown in Table 4.2.
Table 4.2: Active pyrolysis temperature range and peak for the devolatilization process
for Ahun and Araba (Paper IV)
Ahun Araba
Heating rate (°C/min)
Active pyrolysis range (°C)
Peak temperature (°C)
Active pyrolysis range
(°C)
Peak temperature
(°C) 5 202 - 277 253.76 165 - 273 257
10 213 - 280 252.46 184 - 275 259
15 222 - 287 260.94 195 - 286 272
20 238 - 283 272.56 205 - 288 276
39
4.2.1 Iso-conversional (model-free) approach
From the model-free method mentioned earlier, and using Teak as an example,
evaluated results for Ea
clear from the figure that the activation energy changes with conversion, . A slight
jump is observed between conversions 0.1 to 0.3 and according to Yao et al. (2008),
the jump is attributed to the material experiencing accelerated decomposition. Also
from the figure, observations show that at conversions beyond 0.6, a distorted trend is
observed which indicates decomposition with multi-step reaction mechanism.
However, comparison of the Ea results from the model-free methods with those from
Tsamba et al. (2006), Slopiecka et al. (2012) and Yao et al. (2008) shows a good
agreement.
Conversion ( )
Figure 4.1: Profile plot of activation energy (Ea ) against conversion ( ) values from Iso-
conversional methods (Paper I)
E a (k
J/m
ol)
40
4.2.2 Model-fitting approach
Khawam and Flanagan (2006a) listed the basis for the classification of models used in
the study of solid-state kinetics. These include geometrical contraction, reaction
order, diffusion and nucleation. The four mechanisms employed in this model-fitting
approach include Avrami-Erofeev, Reaction order, Diffusional and Contracting
geometry (Paper I). In the work of Khawam and Flanagan (2006b), it was claimed that
a suitable reaction mechanism can however be identified and also characterized based
on the values of correlation coefficient (R2), i.e. the closer the value to unity the better
the chance of being selected.
According to , the calculated activation energies from different
models could be compared with the average activation energy from model-free
methods. In evaluating the Ea results involving the sample conversion (Obobo), four
mechanisms were considered with third order as the average Ea values obtained at n=3
for all the mechanisms were in agreement with those from model-free methods.
Meanwhile, It is clear from the displayed results (Table 4.3) that only the Reaction
order and Diffusional models gave results in agreement with what was obtained from
the iso-conversional methods.
Table 4.3: Obobo and its reaction model mechanism results (Modified from Paper I)
Model Average activation
energy, Ea (KJ/mol)
Average pre-exponential
factor, A (min-1) R2
Reaction order 149.48 6.37E+16 0.9762 Avrami-Erofeev
22.69
12.00E+00
0.9579
Diffusional (1D)
149.99
7.82E+13
0.9682
Contracting geometry
79.77
1.60E+08
0.9779
41
Considering the results for Obobo from the two methods (model-free and model-
fitting), the Ea values obtained are similar to those reported in the literature for non-
tropical species (Slopiecka et al., 2012; Tsamba et al., 2006; Yao et al., 2008). Since
these non-tropical samples are already deployed for energy recovery purposes, the
tropical counterparts are equally looking good as promising fuel stock for energy
recovery.
4.3 Gasification of wood biomass – kinetic model approach
Some of the gasifying agents commonly used include CO2 (Paper I and IV), steam
(Paper III), air (Cao et al., 2006; Gil et al., 1999), hydrogen (Cheng et al., 2012), air-
steam (Lv et al., 2004; Meng et al., 2011), and O2-enriched air (Mastellone et al., 2012).
According to Zhang et al. (2006), gasification reactivity of the product char from the
pyrolysis reaction are influenced by several factors. These factors may include the type
of gasifying agent, reaction conditions and the char properties (e.g. morphology). In
this work however, CO2 and steam are the two gasifying agents employed, while the
reaction conditions include the partial pressures of CO2 (Paper I), partial pressures of
steam (Paper III), gasification temperatures (Paper III). As listed in Table 3.4, the
models were employed due to the reason of their assumptions being in tune with the
nature of the tropical biomass employed in this study as requisites for their optimum
conversion.
With the biomass fuel particle in form of sawdust and turning to char after being
pyrolysed, the assumptions above are adaptable to the char properties. Therefore, the
model could be used to interpret the gasification reaction of the chars. In Paper I,
Tectona grandis was pyrolysed and the chars subsequently gasified. The char
42
conversion was evaluated with gas-solid reaction models such as VRM and SCM and
the gasification rate estimated. Table 4.4 gives the char formation and conversion
history together with the evaluated gasification rate constants.
It is clear from the results that VRM gave a better description of the conversion
reaction and Obobo looks more reactive compared to Teak considering their
respective K for the two different models (VRM and SCM) considered.
Table 4.4: Pyrolysis-gasification conversion and model determination of apparent
gasification rate constant, K (min-1) of Teak and Obobo
Fuel
Pyrolysis conditions
Gasification conditions
Employed models
Apparent
gasification rate constant
(min-1)
Botanical name
Local name
Heating rate (°C min-1)
Temp. (°C)
Gasifying agent
Temp. (°C)
Tectona
grandis
Teak 2 - 20 900 CO2 1000 VRM
SCM
0.1784 ± 0.01
0.1333 ± 0.02
Guarea
thomsonii
Obobo 2 - 20 900 CO2 1000 VRM
SCM
0.2285 ± 0.02
0.1652 ± 0.03
Apart from the apparent gasification kinetic rate constant, K from the plots of different
models, other kinetic parameters are also evaluated. These parameters included the
activation energy, Ea and the Frequency factor, A evaluated via the Arrhenius plot
using concentrations, flow rates or partial pressures during gasification reaction at
different reaction temperatures. For example, a combined Arrhenius plot for both
linear (model-free) and calculated (model-fitting) data for Ayinre sample undergoing
steam gasification at a partial pressure of 3.0 bar (Paper III) is shown in Figure 4.2. The
kinetic constants (Ea & A) are shown in Table 4.6.
43
Figure 4.2: Combined Arrhenius plot for linear and calculated (model-fitting) data for Ayinre at a partial pressure of 3.0 bar (Paper III)
Table 4.5: The evaluated kinetic parameters (Ea (kJ/mol) and A (h-1)) for steam gasification of wood char using experimental and calculated (model-fitting) data from different models (Paper III)
Data Type Ea (kJ/mol) A (h-1)
Experimental 48.13 5.09E + 02
SCM 49.29 3.45E + 02
VRM 49.89 1.55E + 03
mVRM 32.54 1.79E + 04
From the result array in Table 4.5 above, mVRM with the lowest activation energy
value at 32.54 kJ/mol and the corresponding Frequency factor 1.79E + 04 is best suited
to describe the experimental reaction having, when compared to other models, the
highest R2 value at 0.9959 (Paper III).
-1.0
1.0
3.0
5.0
7.0
0.75 0.80 0.85 0.90 0.95 1.00 1.05
lnK
(h-1
)
1000 K/T
Linear model
SCM
VRM
mVRM
44
4.4 Reaction parameter variation and the effects
Variations in process variables affect the nature and the rates of lignocellulosic
decomposition reactions (Pinto et al., 2003). In this thesis, an example of the effects of
reaction variables on the reaction kinetics of the wood fuel under investigation was
demonstrated by the reaction behaviour Ayinre under steam gasification with varied
partial pressures and gasification (Paper III). Table 4.6 below represents the evaluated
char gasification rate constants as estimated with paired reaction variables of
gasification temperatures and steam partial pressures. The general trend indicates an
increase in gasification rate constant with increase in steam partial pressure and the
reaction temperature. Another means of showing the impact of operating condition is
demonstrated by Figure 4.3, indicating a typical trend involving the effect of varying
the temperatures of reaction on the char conversion reaction considering a particular
steam partial pressure (in this case 4.0 bar). The higher the reaction temperature, the
faster the reaction time.
Table 4.6: Char gasification rate constant results KVRM (min-1) from steam partial pressure and gasification temperature as paired reaction variables
2.0 bar 3.0 bar 4.0 bar 5.0 bar
700 °C 0.05 0.06 0.07 0.08
800 °C 0.11 0.09 0.20 0.19
900 °C 0.17 0.14 0.31 0.24
1000 °C 0.24 0.25 0.29 0.33
45
Figure 4.3: Effect of varying reaction temperature on char conversion reaction (Paper III).
At chosen conditions of elevated temperatures and absence of oxygen, wood samples
are pyrolysed to produce chars (Park & Jang, 2012; Tripathi et al., 2016). The different
chars produced often have varied reaction rates during gasification. In other words,
the reactivity of chars is strongly dependent on its formation history (Chen et al., 1997;
Okumura et al., 2009). In the work of Chen et al. (1997), birch wood was pyrolysed
under varied reaction conditions. A rapid heating rate for the birch sample gives a char
with higher reactivity compared with those produced with a slow heating rate. From
paper V, the effect of varied pyrolysis conditions on the morphology and gasification
reactivity of Arere was studied.
Similar to the earlier results (Cetin et al., 2005; Okumura et al., 2009), It was found that
the reactivity of chars formed decreased with increasing pyrolysis pressure. With
increased pressure, the pores become larger with thinner walls and less surface area is
available for the reaction. The char conversion during gasification is faster with
increased pyrolysis heating rate. This is due to the fact that the pores collapse and then
0.1
0.3
0.5
0.7
0.9
0 20 40 60 80 100
Conv
ersio
n
Reaction time, min
700°C800°C900°C1000°C
46
fragmentize, leading to an increased surface area available for reaction. An overall
representation of the phenomenon is as represented in Figure 4.4 indicating the effect
of pyrolysis conditions (heating rate and pressure) on the reactivity of the reacting
char.
A detailed representation of the effects of variations in the pyrolysis conditions relative
to the gasification reaction constant K is represented in Figure 4.4. An example of a
trend from the figure shows that at a pyrolysis pressure of 1.0 bar, increasing the
heating rate of the raw fuel conversion during pyrolysis from 5 to 20 °C/min gave
gasification reactivity increasing from 0.0369 to 0.0398 min-1. However, increasing the
pyrolysis pressure to 6.0 bar (for example) produces a decreasing range of K values for
the respective heating rate considered as compared to those from 1.0 bar.
Figure 4.4: The effect of pyrolysis conditions (pressure and heating rate) on the reactivity of Arere char undergoing gasification reaction (modified from Paper V).
0.034
0.035
0.036
0.037
0.038
0.039
0.040
0.041
0.0 2.0 4.0 6.0 8.0
Reac
tivity
, min
-1
Pyrolysis pressure, bar
5 °C/min
10 °C/min
20 °C/min
47
4.4.1 Analysis of fuel char microstructures – SEM approach
Changes in pyrolysis conditions (heating rate and pressure) and their effects on the
morphology and gasification reactivities of Arere chars were investigated (Paper V).
The scanning electron microscope (SEM) probe was deployed to expose the
micrographic changes in orientations and populations of the pores as the gasification
reaction proceeds using the Back-scattered electron (BSE) imaging method. This leads
to different reactivities for different chars. Cetin et al. (2005) claimed that the
diameters of the pores increase with pyrolysis pressure, leading to a reduction in the
number of pores. With this, the available surface for reaction is reduced resulting in
the eventual reduction in gasification reactivities for the chars.
Considering heating rate during pyrolysis, it can be summed up that at high heating
rates; the pores are highly ruptured leading to an increase in total area available for
reaction with the gasifying agent. The varied reactivity was as a result of different
orientations and microstructures of the chars. An example of this is shown in Figure
4.5 representing the morphology of chars formed at a constant heating rate of 5
°C/min (noted as H5) and at increasing pressure (i.e., P1H5, P4H5, P6H5. Where P1, P4,
and P6 represent 1, 4, and 6 bar, respectively). From the micrograph denoted P1H5, the
near-natural microstructural orientation of micro fibres and mini pores. Micrograph
P4H5 shows a considerable growth in the number of visible pores with distinct
measurable diameters with the pyrolysis pressure being increased to 4.0 bar. From
micrograph P6H5, the pyrolysis pressure was increased to 6.0 bar and the pores are
now bigger with larger measurable diameters compared to those of lower pyrolysis
pressures.
48
Figure 4.5: Pore structure and distribution of chars showing the effect of increased
pyrolysis pressure (paper V).
However, a different trend is observed with an increasing heating rate. The pores
rupture with increasing heating rate leading to increased surface area available for
reaction by the gasifying agent. The resultant effect is the increased gasification
reactivities obtained.
4.5 Metal crystals in biomass chars
Biomass components play an important role in the pyrolysis characteristics and
product distribution of biomass (Raveendran et al., 1996) with emphasis on distributed
Alkali and Alkaline Earth Metal (AAEM) species in biomass.
In the work of Lv et al. (2010), AAEM species present in the ash were investigated and
it was found out that the alkaline and the alkaline earth metals have strong influence
on the reactivity of biomass. Fahmi et al. (2007), found that during conversion,
biomass experiences strong catalytic effect from the AAEM species within the body of
the converting mass. However, the interaction between the AAEM species and the
converting char provides a platform for analysing the catalytic activity of the AAEM
species (Lv et al., 2010). Other authors such as Asadullah et al. (2010) and Gil et al.
P1H5 P4H5 P6H5
49
(2015) also corroborated both the existence and the catalytic influence of AAEM. They
worked with chars from olive and coffee wastes and suspected high reactivity
responses most probably as a result of the catalytic effect of the AAEM species. In
paper V, chars produced under different pyrolysis conditions were examined with
respect to its microstructure. The micrographs obtained were further spot-analysed
with SEM-EDX. The results indicated presence of metal crystals predominantly
consisting of calcium. An example of such analysis is as shown in Figure 4.6a & b and
the percentage compositions of the crystals analysed are displayed in Tables 4.8 and
4.9, respectively.
Figure 4.6: BSE images of analysed regions for Arere chars produced at 10 °C/min
heating rate and 1.0 bar (a), and 20 °C/min and 6.0 bar (b)-modified from paper V.
Table 4.8: Results of the spot analyses of the BSE images of an Arere char produced at 10 °C/min at 1.0 bar. The regions analysed are 1, 2, 3 and 4, according to Fig. 4.6(a). All results are given in weight % (modified from Paper V). Spectrum C O Na Mg P S K Ca Total
1 46.1 32.9 0.2 - - 0.4 0.7 19.7 100.0
2 41.3 40.2 - - - 0.4 0.3 17.9 100.0
3 85.3 12.7 0.4 0.1 - - 1.0 0.5 100.0
a b
50
4 86.2 12.1 0.2 - 0.2 - 0.7 0.6 100.0
Table 4.9: Results of the spot analyses of the BSE images of an Arere char produced at 20 °C/min at 6.0 bar. The regions analysed are 1, 2, 3, 4 and 5, according to Fig. 4.6(b). All results are given in weight % (modified from Paper V).
Spectrum C O Na Mg Al S K Ca Total 1 41.9 38.7 - - 0.1 - 0.3 19.0 100.0
2 89.9 7.6 0.1 0.1 0.1 0.2 0.9 1.2 100.0
3 90.0 8.0 0.1 - 0.2 - 0.8 0.8 100.0
4 89.7 6.6 0.1 0.2 0.2 0.2 1.3 1.8 100.0
5 45.7 35.3 - - - - 0.4 18.7 100.0
It can be concluded from the work of Di Blasi et al. (1999) and Gil et al. (2015) that the
predominant calcium present within the biomass body as shown above could be
responsible for the high reactivity of wood biomass chars as already reported in the
literatures.
4.6 Mechanisms and rate laws of CO2 and steam gasified chars.
According to Karlström et al. (2015), the reactivity towards CO2 of a biomass is similar
to that towards steam. It is observed that the latter has a slightly higher reactivity
compared to the former (most times by a factor of 2-5). During CO2 gasification of
biomass chars, the oxygen exchange mechanism (Di Blasi, 2009) is represented as
follows:
K1 Cf + CO2 C(O) + CO (1)
51
K2 C(O)+ CO Cf + CO2 (2)
K3 C(O) CO (3)
Where Cf, C(O) represent an active sight and a carbon-oxygen complex, respectively.
K1, K2, and K3 are rate constants.
The steady state concentration of C(O) is lowered by the presence of CO as an inhibitor
(eqn. 2). Applying the steady state assumption for the C(O) complex, the CO2
gasification rate, r (which accounts for temperature and reactant partial pressure
effects) with respect to eqns. (1) – (3) is given as (Di Blasi, 2009):
= (4)
Where , are the partial pressures of CO and CO , respectively. However, in the
event of the inhibiting effect exerted by CO being negligible together with the fact that
the concentration of CO is small, a simple global model can be applied (Di Blasi, 2009)
as thus:
C + CO 2 CO, = ( / ) (5) Where A, E, and R are the frequency factor, the activation energy and the universal gas
constant, respectively. The symbol n is an empirical parameter that represents the
reaction order. Similar to CO2 gasification is the steam type. However, gasification with
steam is more complex due to the action of H2, CO2 and CO following the equilibrium
of the water gas shift reaction.
CO + H2O = CO2 + H2 (6)
52
The reaction is often slow especially in the absence of catalysts or inorganic matter in
biomass. Two basic mechanisms are involved in the steam gasification of biomass and
they are the oxygen exchange mechanism and the hydrogen inhibition (Barrio et al.,
2008; Hüttinger & Merdes, 1992). Laurendeau (1978) established that oxygen
exchange mechanism (eqns. 7 – 9) is preferred due to its ability to be supported by
pieces of confirmatory evidence.
K1 Cf + H2O C(O) + H2 (7)
K2 C(O) + H2 Cf+ H2O (8)
K1 C(O) CO (9)
An elementary mechanism for the carbon-steam reaction is represented as
2Cf + H2O C(H) + C(OH) (10)
C(OH) + Cf C(O)+ C(H) (11)
2C(H) Cf + H2 (12)
C(O) CO (13)
C(H) and C(OH) are intermediates which are short-lived, leaving the steps in eqns. (10)
- (13) reduced to the oxygen exchange mechanism as represented by the eqns. (1) –
(3). Similar to CO2 gasification, most kinetic analysis of char gasification with steam
consider a global model:
53
C + H2O 2 CO + H2, = ( / ) (14)
In paper III, Ayinre chars were steam gasified and the rate parameters for the char
activation reaction rate (similar to that of eqn. 14) was obtained. This result, together
with others from wood biomass materials from the literature are summarised in Table
4.10.
The kinetic result in Table 4.10 indicates that the exponent of the steam partial
pressure is in the range 0.4 – 1.0 for wood biomass (except for the Japanese Ceder
which gave 0.22). Ayinre gave the lowest apparent activation energy and one of the
highest exponential values (0.58). These two phenomena point to the fact that tropical
wood biomass samples are highly reactive during thermal treatment for energy
recovery. The presence of calcium (as part of AAEM) in Arere, as shown in the char
spot analysis, is an added factor supporting the enhanced reactivity.
54
Tabl
e 4.
10:
Stea
m g
asifi
catio
n ra
te e
xpre
ssio
ns fo
r cha
rs w
ith th
e ac
com
pany
ing
pyro
lysis
and
gas
ifica
tion
cond
ition
s.
Fuel
Re
fere
nce
Pyro
lysis
Con
ditio
n T g
(K)
P H2O
(kPa
) St
eam
gas
ifica
tion
reac
tion
rate
,
Popl
ar
woo
d
Haw
ley
et
al. (
1983
)
Part
icle
size
rang
e 1
– 2
mm
at
973
K
1073
– 1
273
0.88
- 23
=6.57
×10exp (156 )
Birc
h Ba
rrio
et a
l.
(200
8)
Slow
pyr
olys
is at
873
; (0
.045
–
0.06
3) m
m c
har
1023
– 1
123
10 –
30
=2.62×10e
xp237. (() )
Ayin
re
Pape
r III
Sl
ow p
yrol
ysis
at 1
0 K/
min
, 117
3
K
973
– 12
73
20 –
50
=179×10e
xp (32.54 ). ( 1)
Saw
dust
part
icle
Kojim
a et
al. (
1993
)
In a
flui
dise
d be
d at
112
3 –
1123
K
1123
– 1
123
0 - 5
8 =1173
exp (179 ).
Woo
d
chip
Sun
et a
l.
(200
7)
Char
form
atio
n no
t spe
cifie
d 97
3 –
1123
30
- 91
=15.9
3×10exp (
171.4 ). ( 1)
Japa
nese
Cede
r
Mat
sum
oto
et a
l. (2
009)
Char
form
atio
n no
t spe
cifie
d 11
73 –
147
3 25
- 30
0 =9.99
×10exp136
. (() )
55
5. Conclusions and Future Studies
5.1 Conclusions
Wood waste could be deployed to tackle part of the power production problem if
effectively put into use. With abundant wood waste, a country such as Nigeria could
benefit from proper management and eventual deployment for power-generating
purposes. Due to perceived differences in weather, soil properties, local temperature,
etc. the kinetic properties of these tropical samples are a key to achieving an optimum
energy recovery when deployed for energy use.
The kinetic results (most especially the parameters) are highly useful in the design, re-
design, configuration or reconfiguration of the existing or new gasifiers (or reactors)
for fuel conversion purposes.
Energy densification via torrefaction of the tropical biomass wood samples can
enhance the deployment of torrefied samples for mini-grid applications. Ahun and
Araba (tropical samples) behave in a similar manner as compared with Olive mill waste
and Willow biomass samples during torrefaction which indicates a possibility of using
these tropical wood biomasses for power-production via mini-grid system. In essence,
for places far away from production source, the raw wood materials can be energy-
densified and made transportable to be used for power need and conversions far from
the production source. Also, the kinetic results of torrefaction process (as a
pretreatment) can be optimised to get the optimum treatment mechanism for the raw
fuel materials for future energy recovery purposes.
56
5.2 Future studies
Further studies are suggested be directed towards converting the tropical wood
samples using a pilot-scale fixed-bed reactor. This is important for determining the
behaviour of the samples close to what is obtainable on an industrial scale.
Furthermore, since only the stem parts were used in the present study, a focus on the
use of a mixture of several parts of the samples would be of great importance as wood
samples from the sawmills are not just stem parts but a mixture of several parts and
different shapes of the wood, such as bark, sawdust, coarse residues (off-cuts, edgings,
and stumps), planer shavings, etc. Finally, single gasifying agents were used in the
present study. Attempt should be made to make use of a mixture of different gasifying
agents and also at varied partial pressures and then compare the results in terms of
the energy and other product yields. This would expand the database as regards the
conversion of tropical biomass with a view to obtaining an optimum yield under
optimum conversion conditions.
57
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