Bioresource Technology Reports 13 (2021) 100615
Contents lists available at ScienceDirect
Bioresource Technology Reports
journal homepage: www.sciencedirect.com/journal/bioresource-technology-reports
A comparative study for biomass gasification in bubbling bed gasifier using
Aspen HYSYS
Furkan Kartal, Uğur Özveren *
Department of Chemical Engineering, Marmara University, Goztepe Campus, 34722 Kadikoy, Istanbul, Turkey
A R T I C L E I N F O
A B S T R A C T
Keywords:
Biomass
Gasification
Aspen HYSYS
Bubbling bed gasifier
Thermodynamic analysis
This study presents bubbling bed gasification characteristics of the agricultural and livestock wastes performing
sensitivity analysis in the Aspen HYSYS process simulator. Effects of operating conditions on syngas composition,
syngas exergy, and syngas lower heating value were examined. Sensitivity analysis results indicated the optimum
steam/biomass ratio (0.2–0.3) and gasifier temperature (700 ◦ C–800 ◦ C) to produce syngas with the highest
quality. The novelty of the work can be divided into two parts: initially, it is a comparative study for gasification
of agricultural and livestock wastes in bubbling bed gasifier and secondly, although fluidized gasifiers have been
modeled and comparative studies have been conducted with Aspen Plus® before, there are no similar analyses
for bubbling bed gasifiers for agricultural and livestock wastes in Aspen HYSYS, according to our best knowledge.
The deductions of this study are significant in terms of development of bubbling bed gasifiers for biomass.
1. Introduction
The demand for energy is rising in our modern world day by day due
to industrial development and population growth. A massive proportion
(about 80%) of our energy requirement is met by fossil fuels such as coal,
natural gas, and oil (Asif and Muneer, 2007). However, the utilization of
fossil fuels causes many health and environmental problems, further,
limited resources of fossil fuels pose concerns for future energy use.
Therefore, attention to clean and renewable energy technology has
increased in recent years, and studies are carried out on sustainable
solutions. Among these renewable energy sources, biomass is a unique
resource that can be found in many forms, abundantly, and widely
available all over the world (Perea-Moreno et al., 2019).
Biomass energy has attracted more interest over recent decades and
it is considered as an energy source that can be used instead of fossil
fuels in the near future (Lan et al., 2018). Since biomass is carbonneutral, it does not increase the greenhouse gas concentration in the
atmosphere as a result of the oxidation. Contrary to fossil fuels, biomass
can be converted into valuable chemicals through various thermo­
chemical and biochemical cycles, rather than being used as a primary
energy source. Considering all these properties, biomass is viewed as a
more eco-friendly, renewable, and sustainable alternative energy source
that can be used instead of fossil fuels. The utilization of waste biomass
as solid fuels is one of the ways to achieve cleaner energy generation.
Turkey compensates for the majority of its energy requirements by
coal and natural gas (Melikoglu, 2017). However, Turkey has insuffi­
cient natural-gas reserves to supply for its increasing energy demand
(Melikoglu, 2013), and taking necessary precautions is a key to avoid
foreign dependence. Compared to various renewable energy sources,
biomass is seen as having a significant stake for Turkey.
Turkey has significant biomass and bioenergy potential (Melikoglu
and Albostan, 2011). Its biomass energy potential is 32.0 Mtoe per
annum including annual crops, forest residues, perennial crops, residues
from the wood industry, leftovers from agro-industry, animal wastes,
and other biomass sources, according to Demirbas (2008). The total
recoverable bioenergy potential is predicted to be of about 16.92 Mtoe
according to Kaygusuz (Kaygusuz and Türker, 2002), including livestock
farming wastes, forestry and wood processing residues, municipal
wastes, and primary agricultural residues. Considering all these reports,
increasing the share of biomass energy utilization possesses strategic
importance for Turkey to reduce foreign energy dependence.
Many thermochemical techniques are employed to convert biomass
into favorable gaseous products, however the gasification is a promising
method with its high efficiency, the availability of diverse solid fuels, the
ability to produce at various capacities, and the low concentrations of
hazardous emissions (Pauls et al., 2016). Furthermore, gasification is a
less complex and more inexpensive method than biochemical routes
(Sikarwar et al., 2017). Gasification is a thermochemical conversion
* Corresponding author.
E-mail address: ugur.ozveren@marmara.edu.tr (U. Özveren).
https://doi.org/10.1016/j.biteb.2020.100615
Received 9 October 2020; Received in revised form 2 December 2020; Accepted 3 December 2020
Available online 8 December 2020
2589-014X/© 2020 Elsevier Ltd. All rights reserved.
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
process of carbonaceous materials into product gas which primarily
includes CO, CO2, H2, and CH4 with some unconverted char, tar, and
ash, additionally trace amount of nitrogen, oxygen, and sulfide
including chemical structures (Özveren, 2013). Due to their low energy
density, biomass cannot produce high heat in the combustion processes,
but they can be converted into a product gas with high efficiency by the
gasification technique (Hosseini et al., 2015). Therefore, the develop­
ment of biomass gasification techniques is of interest to many re­
searchers and engineers.
The quality of the syngas can be affected by feedstock, operating
conditions of the gasifier, design parameters, and the gasifier agent. The
gasification agent to be used in the process may differ depending on the
desired syngas composition, quality, and operation cost. For example,
the air is one of the widely preferred gasification agents because of its
cheapness, but syngas possesses a low calorific value. High-quality
syngas is produced with oxy-gasification processes whereas opera­
tional costs are also increasing (Puig-Gamero et al., 2018). Among many
gasifying agents, steam is preferred for producing H2-rich and highquality syngas (Nipattummakul et al., 2010). Hydrogen is used in
various industrial-scale processes such as fuel-cells, saturating com­
pounds, cracking of hydrocarbons, hydrogenation process, and pro­
duction of diverse chemicals like methanol, ammonia, etc.
Recently, many researchers and engineers are developing models for
physical, chemical, and biological systems using process simulators to
minimize experimental procedures. Process models are critical in
analyzing system behavior, measuring performance, and examining the
impact of various operating parameters. Although Aspen Plus® is
practiced many times by researchers in the modeling of the numerous
biomass and coal gasification processes (Fernandez-Lopez et al., 2017;
Im-orb and Arpornwichanop, 2016; Lan et al., 2018; Niu et al., 2013;
Zhai et al., 2016), fluidized bed gasifier models developed using Aspen
HYSYS are only a few. Aspen HYSYS is an equation-oriented software
that operates on the basis of mass-energy balance and phase equilibrium
database to analyze the effects of diverse process parameters. It is an
important software for chemical process design and can be used to
simulate the gasification systems of solid fuels. If a well-designed
simulation model can be developed, the determination of system pa­
rameters can be evaluated with less time and cost to optimize running
conditions for a bubbling bed gasifier.
Bassyouni et al. (2014) developed a downdraft gasifier model
simulation using Aspen HYSYS simulator for date palm waste gasifica­
tion. The authors defined the biomass as an unconventional hypothetical
solid component in HYSYS and developed a set of six reactor models
simulated various reaction zones of the downdraft gasifier. After vali­
dating the downdraft gasifier model with a laboratory-scale gasifier,
researchers examined the effect of gasifier temperature and steam/
biomass ratio on syngas composition. However, the downdraft gasifier
model developed by the researchers is specific to date palm and their
lab-scale reactor. González et al. (2018) were studied the gasification
process in Aspen HYSYS to evaluate hydrogen production for oil sludge
from crude oil refinery. The authors aimed to produce hydrogen by
blending petroleum waste with biomass. The researchers used air and
superheated steam mixtures as gasifying agents and evaluated gasifi­
cation parameters like temperature, syngas chemical composition, and
gas yield. Milani et al. (2017) aimed to propose and analyze alternative
options for hybridizing Concentrated Solar Power (CSP) with biomass,
through gasification for power generation. The authors mentioned the
hybrid CSP-biomass power plant through gasification is an innovative
concept that allows the integration of a combined cycle for power
generation, sun-biomass hybridization, and syngas storage. In addition,
the technical and economic performance that belongs to the hybrid
system was reported by the authors. However, the bubbling bed gasifi­
cation characteristics of different biomass wastes have not been reported
using Aspen HYSYS in a comparative study until now.
The objective of this study is to investigate the gasification charac­
teristics of different biomass using the Aspen HYSYS process simulator.
The bubbling bed gasifier model was developed based on a minimization
of the Gibbs free energy at equilibrium that means the residence time is
long enough to allow the chemical reactions to reach an equilibrium
state. The modeling work focuses on examining the effect of temperature
and steam to biomass ratio on the syngas composition, exergy, and lower
heating value. The novelty of the work can be divided into two folds:
initially, it is a comparative study for various biomass and secondly,
although fluidized gasifiers have been modeled and comparative studies
have been conducted with Aspen Plus® before, there are no similar
analyses for bubbling bed gasifiers in Aspen HYSYS, according to our
best knowledge.
2. Methodology
2.1. Feedstock characteristics
In the current paper, ten different biomass were selected as a solid
fuel for the modeling of the gasification process. All of the biomass are
waste of agricultural and livestock production in Turkey and pose po­
tential for biomass-based energy plants. The proximate analysis and
ultimate analysis results of the samples were taken from the ECN (En­
ergy Research Center of The Netherlands Organization for Applied Sci­
entific Research) laboratories biomass classifications (Phyllis, 2013).
Proximate analysis and ultimate analysis results of biomass are given in
Table 1.
2.2. Model description
The steady-state equilibrium model of bubbling fluidized bed gasifier
for the biomass gasification process was developed in Aspen HYSYS V11.
If a convenient bubbling bed gasifier model can be created; chemical
composition, exergy, and lower heating value of syngas can be examined
by performing a case study on the developed model. Soave-RedlichKwong (SRK) equation of state (EOS) was selected as a fluid package
for calculation of the physical properties of components according to the
suggestions of the AspenTech user manual (Aspen Technology, 2013).
The simulation was developed under the following assumptions:
Table 1
Proximate analysis and ultimate analysis results of solid fuels (Phyllis, 2013).
Component
Almond
shell
Cotton
stalk
Hazelnut
shell
Horse
manure
7.85
16.80
12.80
11.09
5.30
19.22
22.10
22.86
20.64
80.02
70.13
57.30
63.74
59.55
14.38
2.80
51.71
6.13
41.35
0.76
0.03
3.80
53.60
5.20
38.90
1.30
1.00
0.59
47.42
5.58
46.03
0.10
0.87
8.71
54.33
6.81
37.15
1.54
0.16
0.30
49.58
5.56
43.97
0.82
0.08
Component
Olive
pits
Peanut
shell
Rice
husk
Sunflower
shell
Wheat
straw
Moisture (a.r. %)
Fixed carbon (a.
r. %)
Volatile matter
(a.r. %)
Ash (a.r. %)
C (d.a.f. %)
H (d.a.f. %)
O (d.a.f. %)
N (d.a.f. %)
S (d.a.f. %)
6.08
15.29
7.99
18.66
10.00
–
9.84
–
15.10
14.98
77.01
65.85
–
–
62.32
1.62
49.59
6.28
35.92
0.42
0.05
7.50
51.83
5.82
40.35
1.80
0.20
15.42
46.97
6.70
45.78
0.42
0.02
2.52
52.95
6.68
39.17
1.00
0.21
7.60
48.24
6.07
44.36
0.80
0.25
Moisture (a.r.
%)
Fixed carbon (a.
r. %)
Volatile matter
(a.r. %)
Ash (a.r. %)
C (d.a.f. %)
H (d.a.f. %)
O (d.a.f. %)
N (d.a.f. %)
S (d.a.f. %)
2
Oak
wood
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
• The entire gasification system was operated in steady-state and
isothermally.
• Tar and other heavy hydrocarbons were neglected in the syngas
composition.
• All reactions occur fast and reach the chemical equilibrium.
• Char only contains carbon.
• Since ash is an inert component and does not react, biomass was
defined on an ash-free basis.
• All sulphur and chlorine compounds were formed into H2S and HCl.
• Reactors were operated at atmospheric pressure, and pressure drops
were neglected.
(1)
where “aij” expresses the number of atoms of the “j”th element in a mole
of “i”th species, “λi” stands for the Lagrange multiplier, “αi” is the
respective activity term, “ni” is the number of moles of “i”th species, and
the “L” implies the Lagrange function. The process flowsheet diagram of
the bubbling fluidized bed gasifier model is shown in Fig. 1.
Gasification agent (“Steam”) and fuel (“Biomass”) represent the
input material streams. The “Steam” stream contains pure water at
200 ◦ C, and the “Biomass” stream includes the moisture content along
with the elemental composition (carbon, hydrogen, oxygen, nitrogen,
sulphur, chloride) of the solid fuel. “X-103” component splitter block
separates the solid carbon and other fluids into the “GBR-103” reactor.
The “GBR-103” Gibbs reactor was constantly operated at 400 ◦ C and
simulated low-temperature thermochemical processes compared to the
gasification process. The most important reason for including a lowtemperature Gibbs reactor in the bubbling fluidized bed gasifier model
is to obtain similarity with the experimental syngas compositions in the
Model validation section. Moreover, at high temperatures especially
800 ◦ C and beyond, methane is consumed and cannot be observed in
syngas whereas methane gas in syngas has been reported in experi­
mental studies. Briefly, “GBR-103” reactor simulates gas-phase reactions
together with the following solid-gas phase reactions:
Char partial combustion : C + 0.5 O2 →CO ( − 111 MJ/kmol)
(3)
Water − gas reaction : C + H2 O ↔ CO + H2 ( + 131 MJ/kmol)
(4)
Hydrogenation : C + 2 H2 ↔ CH4 ( − 75 MJ/kmol)
(5)
The “TEE-100” block splits the gaseous components produced in the
“GBR-103” reactor (Gas-1) into “Gas-11” and “Gas-12” streams. The
“Gas-12” stream does not flow into the “GBR-100” reactor, flows directly
to the “MIX-101” block, and contributes to the product gas “ProdGas”.
Thus, methane gas can be observed in syngas, otherwise methane will
reach chemical equilibrium and be depleted in the “GBR-100” reactor
which was operated at high temperatures. Table 2 briefly explains the
descriptions of the blocks in the bubbling bed gasifier model.
The “Gas-11” stream flows into the “GBR-100” reactor, where the
Gibbs free energy is minimized at 800 ◦ C, and possible chemical com­
ponents are produced. In addition to steam-methane reforming and
oxidation reactions, the Boudouard reaction and water-gas shift reaction
also takes place in the Gibbs reactor:
The gasification process was simulated with two Gibbs reactors. This
modeling method, called non-stoichiometric because of the information
on any reaction in the process is not fully known, seems an appropriate
approach to be used for a complex phenomenon such as gasification
(Ramos et al., 2019). Gasification reactions occur based on a chemical
method called Gibbs free energy minimization. Gibbs free energy of a
system is minimized by performing the Lagrange multiplier method in
Aspen HYSYS process simulator as follows:
∑k
∂L
= ∆G0f ,i + RTlnαi +
λi aij = 0
j=1
∂ni
Char complete combustion : C + O2 →CO2 ( − 393 MJ/kmol)
Boudouard reaction : C + CO2 ↔ 2CO ( + 172 MJ/kmol)
(6)
Water − gas shift reaction : CO + H2 O ↔ CO2 + H2 ( − 41 MJ/kmol)
(7)
Steam− methane reforming reaction : CH4 +H2 O↔CO+3H2 (+206 MJ/kmol)
(8)
The gaseous compounds (Gas-2) produced in the “GBR-100” reactor
Table 2
Descriptions of the ASPEN HYSYS unit blocks.
Block ID
Aspen HYSYS
UnitOPS
Description
GBR-103
(400 ◦ C)
Gibbs reactor
GBR-100
(800 ◦ C)
Gibbs reactor
X-103
TEE-100
Component
splitter
Component
splitter
Tee
MIX-101
Mixer
Simulates the reactions between reactants to
calculate possible products using Gibbs free
energy minimization method.
Simulates the reactions between reactants to
calculate possible products using Gibbs free
energy minimization method.
Separates the char (carbon) and volatiles in
biomass.
Separates the undesired components (water,
nitrogen, etc.) in the product gas.
Splits the gas product (Gas-1) that produced in
the “GBR-103” reactor as 92% into Gas-11 and
8% into Gas-12.
Creates product gas by combining Gas-12 and
Gas-2.
X-100
(2)
Fig. 1. Aspen HYSYS flowsheet diagram of the gasification process.
3
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
were combined with the “Gas-12” stream to create the product gas
(ProdGas). The “X-100” component splitter, which is the last unit block
in the bubbling bed gasifier model, was used to separate the components
(water, nitrogen, etc.) in the product gas but not desired in the syngas.
The streams at the bottom of the reactors (L1 and L2) contain possible
liquid products, however, there are no components in these streams for
high-temperature processes such as the gasification process. Finally, the
Q1 and Q2 streams indicate the energies flowing into the reactors or
receiving from the reactors, so that all reactors were operated
isothermally.
Table 4
Relative error between bubbling bed gasifier model and experimental studies.
To measure the accuracy of the newly developed bubbling bed
gasifier model, syngas compositions were compared with the results of
experimental studies in the literature. The gasification process was
simulated under the identical conditions in experimental studies by
using input variables such as gasifier temperature, characteristics of
biomass, the flow rate of solid fuel and gasification agent, etc. A com­
parison of syngas compositions in experimental studies and newly
developed bubbling bed gasifier model results is given in Table 3.
As demonstrated in Table 3, the results of the bubbling bed gasifier
model successfully show similarity with experimental studies when they
were executed under the same operating conditions and with the same
input variables. Although poultry litter and pine wood have unique
physicochemical properties and experiments were conducted under
different operating conditions, the bubbling bed gasifier model was able
to simulate the gasification process. However, the fact that the model is
independent of the design parameters, neglecting reaction kinetics and
fluid mechanics, and the no residence time in the reactor (rapid reaction
occurrence and reaching chemical equilibrium) cause syngas composi­
tions to differ from experimental results. The deviation of the simulation
outcomes from literature results is calculated by implementing the
relative error. The relative error can be described as:
Relative errors are summarized in Table 4.
In particular, the conversion of hydrocarbons into hydrogen, carbon
monoxide, and carbon dioxide gases in chemical equilibrium makes the
prediction of methane gas difficult. In addition, the presence of methane
in the syngas with small concentrations resulted in a large relative error
(%). This challenge was observed in other equilibrium models and re­
ported by other researchers (Han et al., 2017; Tavares et al., 2020).
Table 3
Comparison of syngas composition between literature and model.
Poultry litter (Pandey et al.,
2016)
Pine wood (Song et al.,
2012)
Gasifying agent
Fuel feed rate (kg/h)
Steam/biomass ratio
(kg/kg)
Equivalence ratio
Gasifier temperature
(◦ C)
Steam/air
0.66
0.24
Steam
0.1378
1.2
0.3
700
–
820
Syngas composition (%v/v.
dry)
Experimental
Model
Experimental
Model
H2
CO
CO2
CH4
17.58
9.35
17.74
2.59
17.83
9.02
16.86
2.41
60.0
17.5
18.0
6.0
60.27
15.32
22.44
1.59
H2
CO
CO2
CH4
1.42%
− 3.52%
− 4.96%
− 6.94%
0.45%
− 12.45%
24.66%
− 73.50%
3.2.1. Effect of temperature on syngas composition
The temperature of a gasifier is one of the most influential factors
that affect the syngas composition crucially. In this study, the impact of
temperature on syngas composition is investigated by varying temper­
atures from 600 ◦ C to 1000 ◦ C. The effect of gasifier temperature on
syngas composition is presented in Fig. 2.
Many complex endothermic and exothermic reactions occur during
the gasification process, and the temperature significantly affects the
equilibrium state of the chemical reactions. Higher temperatures shift
the chemical equilibrium to the side of reactants in the case of
exothermic reactions, and to the side of products in the case of endo­
thermic reactions, according to the Le Chatelier’s principle (Motta et al.,
2018). As seen in Fig. 2, while the temperature increases from 600 ◦ C to
1000 ◦ C, the molar concentration of H2 initially rises and then it starts to
decrease. This increasing and decreasing behavior is observed in all
types of biomass and the hydrogen fraction is roughly between 51% and
59%. The increase in hydrogen concentration at high temperatures can
be explained by a lower rate of hydrogen combustion due to lack of
oxygen in the reactor (Singh et al., 2016), higher rate of water gas shift,
and the forward reaction of the water-gas, which is an endothermic
reaction in the solid-gas phase. Moreover, the hydrogen achieved its
highest concentration between 700 ◦ C and 760 ◦ C. Rice husk produced
hydrogen at the highest fraction in syngas with 0.5938 at 710 ◦ C, and
oak wood produced the lowest hydrogen fraction with 0.5659 at 720 ◦ C.
Methane concentration decreases rapidly as the temperature increases,
further, there is no methane in syngas composition especially after
800 ◦ C. The forward reaction of steam-methane reforming at high
temperatures reaches chemical equilibrium and leads to the decompo­
sition of methane gas. The biomass with the highest fraction of methane
in the syngas composition at temperatures below 800 ◦ C was olive pits
(from 10% to zero) whereas the fuel containing the least methane in
syngas was observed as the hazelnut shell (from 5.7% to zero). Further, a
negative correlation was noted between carbon monoxide and carbon
dioxide concentrations as the gasifier temperature increased. The carbon
monoxide fraction increased from 11 to 14% to 26–30% whereas the
carbon dioxide fraction decreased from 23 to 28% to 10–16%. The
variation of concentrations of chemical compounds in the syngas can be
explained by the equilibrium states of Boudouard, water-gas, water-gas
shift, and steam-methane reforming reactions. Similar observations
have been published in the literature by other researchers (Ismail et al.,
2020; Ku et al., 2015; Monteiro et al., 2017).
(9)
Sample
Literature (Song et al.,
2012)
In this section, the impact of gasifier temperature and steam to
biomass ratio on syngas composition, exergy, and lower heating value
during the gasification process of biomass was discussed using the newly
developed Aspen HYSYS model. During these parametric studies, the
rest of the parameters were kept constant while one of them was varied.
In this context, the gasifier temperature was varied between 600 ◦ C and
1000 ◦ C and the steam to biomass mass ratio between 0 and 1.5.
3.1. Model validation
Simulation output − Experimental output
× 100
Experimental output
Literature (Pandey et al.,
2016)
3.2. Parametric study
3. Results
Relative Error (%) :
Syngas
component
3.2.2. Effect of temperature on syngas exergy and syngas lower heating
value
Exergy is defined as the amount of work a system can do when
brought into thermodynamic equilibrium with its environment. Exergy
4
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 2. Effect of gasifier temperature on syngas composition (steam/biomass:1.0).
is one of the key parameters to analyze and define system performance.
Usually, lower heating value (LHV) is used to measure the practical
amount of fuel energy available. Thus, the determination of the syngas
LHV and exergy obtained at the end of the gasification process is
significantly important. In the Aspen HYSYS simulator, LHV and phys­
ical exergy values of syngas can be obtained from the stream properties
section, however, an external calculation is required for the chemical
exergy value. The chemical exergy of a gas mixture is expressed as fol­
lows (Dincer and Rosen, 2012):
∑
∑
EX ch =
xi ln(xi )
xi EX 0ch + RT0
(10)
value.
Exergy can be grouped as physical exergy and chemical exergy
(excluding potential, kinetic, nuclear effects, etc.) (Marmolejo-Correa
and Gundersen, 2015). Syngas mass exergy also refers to the sum of
physical and chemical exergy. The gasifier, operated at high tempera­
tures, produces hot gas products with significant capacity to work, so
resulted in an increment in physical exergy. However, with rising tem­
perature, the composition of the syngas changes and affects the chemical
exergy critically.
When the behavior between 600 ◦ C and 1000 ◦ C was examined, it
was observed that there was a constant increase in mass exergy and mass
lower heating value. The hydrogen concentration which was increased
until 750 ◦ C and the carbon monoxide concentration, which was
continuously increased with the temperature, raised the mass exergy. A
slight change can also be observed in the slope of the exergy curve after
750 ◦ C due to the hydrogen reduction. It can be noted that methane also
contributed to this behavior because it has the highest chemical exergy
where “R” is the universal gas constant (8.314 kJ/kmol.K), “T0” is the
environmental (reference) temperature (298.15 K), “xi” is the molar
fraction of a component, and “EX0ch” is the standard chemical exergy
(Kotas, 2013) of a gaseous component. Fig. 3 depicts the effect of gasifier
temperature on syngas mass exergy and syngas mass lower heating
5
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 2. (continued).
among the gaseous components in syngas. Even though hydrogen (after
750 ◦ C) and methane demonstrate a decreasing behavior, the increment
of carbon monoxide and syngas temperature prevents the mass exergy
from declining (Zhang et al., 2015). When the reactor temperature was
increased from 600 ◦ C to 1000 ◦ C (66%), the total exergy of syngas
increased by approximately 10% for all biomass.
Biomass with the highest mass exergy is olive pits with 3748 kcal/kg
(800 ◦ C) whereas the biomass with the lowest mass exergy is hazelnut
shell with 3152 kcal/kg (800 ◦ C). Horse manure, which provides the
highest hydrogen fractions at high temperatures produced syngas with
the second highest mass exergy value. Zhang et al. (2011) reported that
total exergy value of syngas was calculated between 5000 and 10,000
kJ/kg during the air gasification process of wood chips, pine sawdust,
and rice husk. These values are lower than our parametric results
(12,000–16,000 kJ/kg), however considering that the steam gasification
process produces higher-quality syngas, the results are quite reasonable.
In particular, the LHV of the syngas is undoubtedly influenced by fuel
characteristics, gasifying agent, and operating temperature. For
instance, the high moisture content in solid fuel decreases the LHV.
Further, LHV of syngas is low because of the nitrogen gas in the air
gasification process, however since hydrogen-rich syngas is produced in
steam gasification processes, LHV is quite high compared to other at­
mospheres (Gagliano et al., 2018). Increment of gasifier temperature
increases not only the syngas production but also its LHV. As can be seen
from Fig. 3, the increase in operating temperature enhanced syngas LHV
for all biomass. The biomass with the highest syngas lower heating value
was olive pits with 3708 kcal/kg (at 800 ◦ C) whereas the biomass with
the lowest syngas lower heating value was hazelnut shell with 3110
kcal/kg (at 800 ◦ C). The syngas LHVs of all biomass demonstrated
growth of about 14% when the gasifier temperature was increased from
600 ◦ C to 1000 ◦ C (66%). Consequently, high gasifier temperature raises
syngas energy as other authors have reported (Zhang et al., 2015).
The syngas LHV increases in parallel with the gasifier temperature
even though the H2 concentration decreases at high temperatures. CO,
6
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 3. Effect of gasifier temperature on syngas exergy and lower heating value (steam/biomass:1.0).
whose concentration is constantly increasing with temperature, appears
to be more effective on syngas LHV. Although CH4 is three times more
influential on syngas LHV than H2 and CO, was present in low concen­
trations. Similar observations were reported in the literature by other
researchers (Tavares et al., 2020; Zhang et al., 2015).
various types of biomass (Dou and Song, 2010; Ku et al., 2014). Addi­
tionally, the increment of H2O drives the forward reaction of the watergas shift which provides a higher fraction of H2 and CO2 (Hussain et al.,
2016). Moreover, continuous H2O supply increases CH4 decomposition
by the forward reaction of steam-methane reforming (Nikoo and
Mahinpey, 2008). The higher amount of H2O provides greater partial
pressure in the gasifier, which favors the forward reactions of water-gas,
water-gas shift, and steam reforming (Monteiro et al., 2017) however,
the temperature of the gasifier diminishes, and water vapor generation
costs are not negligible. As the SBR increased, the H2 fraction in the
syngas composition raised constantly, for all biomass. The increment of
H2 fraction was from 40 to 43% to 60% for the rice husk, wheat straw,
and hazelnut shell whereas the increase for other biomass was much
more severe. For example, the H2 fraction increased from 0.087 to 0.599
for olive pits, the biomass with the greatest change observed. However,
the growth in hydrogen production does not enhance in parallel with the
increase in the SBR. The optimum SBR for all biomass seems to be
3.2.3. Effect of steam to biomass ratio on syngas composition
The steam to biomass ratio (SBR) is identified as the proportion of the
steam entering the gasifier to the biomass provided to the gasifier
(Ramos et al., 2018). In addition to deciding the suitable gasifying
environment, determining the ratio of atmosphere/solid fuel is one of
the key parameters. In this study, the effect of steam to biomass ratio on
syngas composition, mass exergy and mass LHV was investigated. The
gasifier temperature was kept constant at 800 ◦ C in each case study. The
effect of SBR on syngas composition is given in Fig. 4.
As the SBR increases, the H2 fraction in the syngas enhances due to
heterogeneous char-steam reactions and this has been observed for
7
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 4. Effect of SBR on syngas composition (gasifier temperature:800 ◦ C).
between 0.2 and 0.3. Beyond this point, the hydrogen production rate
decreases, and system efficiency diminishes. Further, there is an incre­
ment in CO2 with a drastic decrease in CO as the SBR increases. Beyond
the optimum SBR point (0.2–0.3), the increment of CO2 production was
escalated more. Thus, the optimum SBR point is related not primarily to
the hydrogen concentration but also to the carbon dioxide concentra­
tion, which reduces the syngas quality. The behavior of the SBR on
syngas composition is in agreement with available literature (Monteiro
et al., 2017).
As seen in Fig. 5, the increase of SBR reduced the syngas mass exergy
and lower heating value. Enrichment of syngas with carbon dioxide and
decrement of carbon monoxide in syngas constantly decreased the mass
exergy, despite the continuous increase in hydrogen fraction. In addi­
tion, the carbon dioxide fraction demonstrated a massive increase as
SBR increased, which was effective in the continuous reduction of syn­
gas mass exergy. Horse manure and olive pits distinguished as the
biomass with the highest mass exergy values in syngas. As SBR ranged
from 0.1 to 1.5, mass exergy decreased from 4715 kcal/kg to 3508 kcal/
kg for horse manure and from 4818 kcal/kg to 3531 kcal/kg for olive
pits. When the SBR was increased between 0.1 and 1.5, the total exergy
of syngas decreased by 30%–35% depending on the fuel type. A similar
observation is reported by Rupesh et al. (2016) for the air/steam gasi­
fication procedure of biomass.
Similar to exergy, lower heating value followed a decreasing trend as
a result of an increase in SBR, as illustrated in Fig. 5. This can be
explained by the concentration of carbon monoxide in the syngas
3.2.4. Effect of steam to biomass ratio on syngas exergy and syngas lower
heating value
The significant effect of SBR on syngas chemical composition also
affects the mass exergy and mass LHV characteristics of syngas. Fig. 5
illustrates the effect of SBR on syngas mass exergy and the mass LHV for
the selected biomass. The SBR was ranged between 0.1 and 1.5 and the
gasifier temperature was kept constant at 800 ◦ C.
8
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 4. (continued).
continuously decreased as SBR enhanced. Moreover, an increase in the
CO2 fraction which causes a diminishing effect on syngas mass LHV was
also observed due to the water-gas shift reaction. The biomass with the
highest syngas mass LHV was olive pits with 4473 kcal/kg (at SBR:
0.25), while the biomass with the lowest syngas mass LHV was hazelnut
shell with 3674 kcal/kg (at SBR: 0.25). As a result, the syngas LHVs of all
biomass depicted a decrease of about 26%, when the SBR was increased
from 0.1 to 1.5.
Exbiomass = ß*LHV biomass
(11)
where “ß” is a coefficient that given the ratio of the chemical exergy to
the LHV. ß is developed by Szargut and Styrylska (1964) using statistical
correlations for solid biofuels:
〈
〉
1.0414 + 0.0177 HC − 0.3328 OC 1 + 0.0537 HC
ß=
(12)
1 − 0.4021 OC
3.2.5. Influence of temperature and SBR on exergy efficiency
Exergy analysis method is conveniently used to indicate the energy
quality, operational efficiency, and practical usefulness of a system. In
this method, executed based on mass and energy balance, the exergy
values of all streams entering and leaving the BFB gasifier model are
calculated. In most cases, the physical exergy of biomass is considered
zero whereas the chemical exergy highly depends on the chemical
composition of the fuel (Saidur et al., 2012).
(
)
[O]
LHV biomass = 0.0041868(1 + 0.15[O] ) 7837.667[C] + 33888.889[H] −
8
(13)
where “[C]”, “[H]”, and “[O]” weight percentages (% daf.) (Section 2.1)
of carbon, hydrogen, and oxygen, respectively. Ultimately, the exergetic
efficiency of a gasifier model can be written as follows (Echegaray et al.,
2016):
9
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 5. Effect of SBR on syngas exergy and lower heating value (gasifier temperature:800 ◦ C).
ηexergy =
εche,syngas + εphy,syngas
εche,biomass + εphy,steam
increment was approximately 7% for all biomass samples. Identically,
Rupesh et al. (2016) stated that the exergy efficiency increased at high
temperatures for product gas and increment was between 5% - 15%
depending on the biomass properties. Similar observations were re­
ported by other researchers (Couto et al., 2017; Zhang et al., 2012).
On the other hand, the high amount of steam in the reactor decreases
CO and increases CO2 due to the water-gas shift reaction, further, di­
minishes the energy and exergy value of syngas, as discussed in Sections
3.2.3 and 3.2.4. The growth in SBR was observed as a 15% - 24%
decrease in exergetic efficiency depending on the characteristics of the
fuel. According to Rupesh et al. (2016), an increase in SBR from 0.0 to
3.5 resulted in a decrease in the exergetic efficiency of product gas by
approximately 10%. Similar results were reported by other authors
(Echegaray et al., 2016).
(14)
where “εche,syngas” and “εphy,syngas” are the chemical exergy and the
physical exergy of syngas respectively, “εche,biomass” represents the
chemical exergy of biomass, and “εphy,steam” is the physical exergy of
steam. Fig. 6 depicts the variation of exergetic efficiency with the tem­
perature and SBR for the all biomass samples.
The exergetic efficiency increases with the rise of the gasifier tem­
perature whereas exergetic efficiency decreases with the addition of
steam. As discussed in Sections 3.2.1 and 3.2.2, CO2 decreases while CO
increases due to the Boudouard reaction, energy and exergy of syngas
increase at high temperatures, in other words, high-quality syngas is
produced. When the exergetic efficiency was examined, it was observed
that the efficiency increased at high gasification temperatures and
10
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
Fig. 6. Effect of temperature and SBR on the exergetic efficiency of gasification process.
4. Conclusions
editing. Uğur Özveren: Conceptualization, Data curation, Formal
analysis, Funding acquisition, Investigation, Methodology, Project
administration, Resources, Software, Supervision, Validation, Visuali­
zation, Writing – original draft, Writing – review & editing.
In this paper, a steady-state equilibrium bubbling bed gasifier model
was developed using Aspen HYSYS software for different biomass that
are being generated and abundantly existing in Turkey. To measure the
accuracy of the model before proceeding parametric study, syngas
compositions were compared with experimental results and the esti­
mated gas concentrations were found to be in good agreement. Results
show that the optimum gasifier temperature was between
700 ◦ C–800 ◦ C and the optimum SBR was among the 0.2–0.3. Further­
more, horse manure is the waste that produces one of the highest-quality
syngases in the bubbling bed gasifier.
Declaration of competing interest
The authors whose names are listed immediately below certify that
they have no affiliations with or involvement in any organization or
entity with any financial interest (such as honoraria; educational grants;
participation in speakers’ bureaus; membership, employment, consul­
tancies, stock ownership, or other equity interest; and expert testimony
or patent-licensing arrangements), or non-financial interest (such as
personal or professional relationships, affiliations, knowledge or beliefs)
in the subject matter or materials discussed in this manuscript.
Author names: Furkan Kartal and Ugur Özveren.
CRediT authorship contribution statement
Furkan Kartal: Data curation, Investigation, Software, Supervision,
Validation, Visualization, Writing – original draft, Writing – review &
11
F. Kartal and U. Özveren
Bioresource Technology Reports 13 (2021) 100615
References
Milani, R., Szklo, A., Hoffmann, B.S., 2017. Hybridization of concentrated solar power
with biomass gasification in Brazil’s semiarid region. Energ. Conv. Manag. 143,
522–537.
Monteiro, E., Ismail, T.M., Ramos, A., Abd El-Salam, M., Brito, P., Rouboa, A., 2017.
Assessment of the miscanthus gasification in a semi-industrial gasifier using a CFD
model. Appl. Therm. Eng. 123, 448–457.
Motta, I.L., Miranda, N.T., Maciel Filho, R., Maciel, M.R.W., 2018. Biomass gasification
in fluidized beds: a review of biomass moisture content and operating pressure
effects. Renew. Sust. Energ. Rev. 94, 998–1023.
Nikoo, M.B., Mahinpey, N., 2008. Simulation of biomass gasification in fluidized bed
reactor using ASPEN PLUS. Bio. and Bioenerg. 32 (12), 1245–1254.
Nipattummakul, N., Ahmed, I., Kerdsuwan, S., Gupta, A.K., 2010. High temperature
steam gasification of wastewater sludge. Appl. Energ. 87 (12), 3729–3734.
Niu, M., Huang, Y., Jin, B., Wang, X., 2013. Simulation of syngas production from
municipal solid waste gasification in a bubbling fluidized bed using Aspen Plus. Ind.
Eng. Chem. Res. 52 (42), 14768–14775.
Özveren, U., 2013. Theoretical and Experimental Investigation of Biomass and Coal
Gasification.
Pandey, D.S., Kwapinska, M., Gómez-Barea, A., Horvat, A., Fryda, L.E., Rabou, L.P.,
Leahy, J.J., Kwapinski, W., 2016. Poultry litter gasification in a fluidized bed
reactor: effects of gasifying agent and limestone addition. Energ. Fuel. 30 (4),
3085–3096.
Pauls, J.H., Mahinpey, N., Mostafavi, E., 2016. Simulation of air-steam gasification of
woody biomass in a bubbling fluidized bed using Aspen Plus: a comprehensive
model including pyrolysis, hydrodynamics and tar production. Bio. and Bioenerg.
95, 157–166.
Perea-Moreno, M.-A., Samerón-Manzano, E., Perea-Moreno, A.-J., 2019. Biomass as
renewable energy: worldwide research trends. Sustainability 11 (3), 863.
Phyllis, E., 2013. ECN Phyllis classification. Forest Residue Chips, Pine Spruce 3156.
Puig-Gamero, M., Argudo-Santamaria, J., Valverde, J., Sánchez, P., Sanchez-Silva, L.,
2018. Three integrated process simulation using aspen plus®: pine gasification,
syngas cleaning and methanol synthesis. Energ. Conv. Manag. 177, 416–427.
Ramos, A., Monteiro, E., Silva, V., Rouboa, A., 2018. Co-gasification and recent
developments on waste-to-energy conversion: a review. Renew. Sust. Energ. Rev. 81,
380–398.
Ramos, A., Monteiro, E., Rouboa, A., 2019. Numerical approaches and comprehensive
models for gasification process: a review. Renew. Sust. Energ. Rev. 110, 188–206.
Rupesh, S., Muraleedharan, C., Arun, P., 2016. Energy and exergy analysis of syngas
production from different biomasses through air-steam gasification. Front. Energ. 1-13.
Saidur, R., BoroumandJazi, G., Mekhilef, S., Mohammed, H., 2012. A review on exergy
analysis of biomass based fuels. Renew. Sust. Energ. Rev. 16 (2), 1217–1222.
Sikarwar, V.S., Zhao, M., Fennell, P.S., Shah, N., Anthony, E.J., 2017. Progress in biofuel
production from gasification. Prog. Energ. Combust. Sci. 61, 189–248.
Singh, G., Mohanty, B., Mondal, P., Chavan, P., Datta, S., 2016. Modeling and simulation
of a pilot-scale bubbling fluidized bed gasifier for the gasification of high ash Indian
coal using Eulerian granular approach. Int. J. Chem. React. Eng. 14 (1), 417–431.
Song, T., Wu, J., Shen, L., Xiao, J., 2012. Experimental investigation on hydrogen
production from biomass gasification in interconnected fluidized beds. Bio. and
Bioenerg. 36, 258–267.
Szargut, J., Styrylska, T., 1964. Approximate evaluation of the exergy of fuels. Brennst.
Wärme Kraft 16 (12), 589–596.
Tavares, R., Monteiro, E., Tabet, F., Rouboa, A., 2020. Numerical investigation of
optimum operating conditions for syngas and hydrogen production from biomass
gasification using Aspen Plus. Renew. Energ. 146, 1309–1314.
Zhai, M., Guo, L., Wang, Y., Zhang, Y., Dong, P., Jin, H., 2016. Process simulation of
staging pyrolysis and steam gasification for pine sawdust. Int. J. Hydro. Energ. 41
(47), 21926–21935.
Zhang, Y., Li, B., Li, H., Liu, H., 2011. Thermodynamic evaluation of biomass gasification
with air in autothermal gasifiers. Thermochim. Acta 519 (1–2), 65–71.
Zhang, Y., Li, B., Li, H., Zhang, B., 2012. Exergy analysis of biomass utilization via steam
gasification and partial oxidation. Thermochim. Acta 538, 21–28.
Zhang, Y., Zhao, Y., Gao, X., Li, B., Huang, J., 2015. Energy and exergy analyses of syngas
produced from rice husk gasification in an entrained flow reactor. J. Clean. Prod. 95,
273–280.
Asif, M., Muneer, T., 2007. Energy supply, its demand and security issues for developed
and emerging economies. Renew. Sust. Energ. Rev. 11 (7), 1388–1413.
Aspen Technology, I., 2013. Getting Started Modeling Processes With Solids (USA).
Bassyouni, M., ul Hasan, S.W., Abdel-Aziz, M., Abdel-hamid, S.-S., Naveed, S.,
Hussain, A., Ani, F.N., 2014. Date palm waste gasification in downdraft gasifier and
simulation using ASPEN HYSYS. Energ. Conv. Manag. 88, 693–699.
Couto, N., Silva, V., Monteiro, E., Rouboa, A., 2017. Exergy analysis of Portuguese
municipal solid waste treatment via steam gasification. Energ. Convers. Manage.
134, 235–246.
Demirbas, A., 2008. Importance of biomass energy sources for Turkey. Energy Policy 36
(2), 834–842.
Dincer, I., Rosen, M.A., 2012. Exergy: Energy, Environment and Sustainable
Development. Newnes.
Dou, B., Song, Y., 2010. A CFD approach on simulation of hydrogen production from
steam reforming of glycerol in a fluidized bed reactor. Int. J. Hydro. Energ. 35 (19),
10271–10284.
Echegaray, M.E., Castro, M., Mazza, G.D., Rodriguez, R., 2016. Exergy Analysis of Syngas
Production Via Biomass Thermal Gasification.
Fernandez-Lopez, M., Pedroche, J., Valverde, J., Sanchez-Silva, L., 2017. Simulation of
the gasification of animal wastes in a dual gasifier using Aspen Plus®. Energ. Conv.
Manag. 140, 211–217.
Gagliano, A., Nocera, F., Bruno, M., 2018. Simulation models of biomass thermochemical
conversion processes, gasification and pyrolysis, for the prediction of the energetic
potential. In: Advances in Renewable Energies and Power Technologies. Elsevier,
pp. 39–85.
González, A.M., Lora, E.E.S., Palacio, J.C.E., del Olmo, O.A.A., 2018. Hydrogen
production from oil sludge gasification/biomass mixtures and potential use in
hydrotreatment processes. Int. J. Hydro. Energ. 43 (16), 7808–7822.
Han, J., Liang, Y., Hu, J., Qin, L., Street, J., Lu, Y., Yu, F., 2017. Modeling downdraft
biomass gasification process by restricting chemical reaction equilibrium with Aspen
Plus. Energ. Conv. Manag. 153, 641–648.
Hosseini, S.E., Wahid, M.A., Ganjehkaviri, A., 2015. An overview of renewable hydrogen
production from thermochemical process of oil palm solid waste in Malaysia. Energ.
Conv. Manag. 94, 415–429.
Hussain, M., Tufa, L.D., Azlan, R., Yusup, S., Zabiri, H., 2016. Steady state simulation
studies of gasification system using palm kernel shell. Process. Eng. 148, 1015–1021.
Im-orb, K., Arpornwichanop, A., 2016. Techno-environmental analysis of the biomass
gasification and Fischer-Tropsch integrated process for the co-production of bio-fuel
and power. Energy 112, 121–132.
Ismail, T.M., Ramos, A., Monteiro, E., Abd El-Salam, M., Rouboa, A., 2020. Parametric
studies in the gasification agent and fluidization velocity during oxygen-enriched
gasification of biomass in a pilot-scale fluidized bed: experimental and numerical
assessment. Renew. Energ. 147, 2429–2439.
Kaygusuz, K., Türker, M., 2002. Biomass energy potential in Turkey. Renew. Energ. 26
(4), 661–678.
Kotas, T.J., 2013. The Exergy Method of Thermal Plant Analysis. Elsevier.
Ku, X., Li, T., Løvås, T., 2014. Eulerian–Lagrangian simulation of biomass gasification
behavior in a high-temperature entrained-flow reactor. Energ. Fuel. 28 (8),
5184–5196.
Ku, X., Li, T., Løvås, T., 2015. CFD–DEM simulation of biomass gasification with steam in
a fluidized bed reactor. Chem. Eng. Sci. 122, 270–283.
Lan, W., Chen, G., Zhu, X., Wang, X., Liu, C., Xu, B., 2018. Biomass gasification-gas
turbine combustion for power generation system model based on ASPEN PLUS. Sci.
Tot. Environ. 628, 1278–1286.
Marmolejo-Correa, D., Gundersen, T., 2015. A new efficiency parameter for exergy
analysis in low temperature processes. Int. J. Exergy. 17 (2), 135–170.
Melikoglu, M., 2013. Vision 2023: forecasting Turkey’s natural gas demand between
2013 and 2030. Renew. Sust. Energ. Rev. 22, 393–400.
Melikoglu, M., 2017. Vision 2023: status quo and future of biomass and coal for
sustainable energy generation in Turkey. Renew. Sust. Energ. Rev. 74, 800–808.
Melikoglu, M., Albostan, A., 2011. Bioethanol production and potential of Turkey.
J. Eng. Arch. Gazi Unv. 26 (1), 151–160.
12