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Mathematical modeling of municipal
solid waste plasma gasification in a
fixed-bed melting reactor
Qinglin Zhang
Doctoral Dissertation
Stockholm 2011
Royal Institute of Technology
School of Industrial Engineering and Management
Department of Material Science and Engineering
Division of Energy and Furnace Technology
SE-100 44 Stockholm, Sweden
_______________________________________________________________________
Akademisk avhandling som med tillstånd av Kungliga Tekniska Högskolan I Stockholm
framlägges för offentlig granskning för avläggande av teknologie doktorsexamen,fredagen
den 25 November 2011, kl. 10.00 i Lindstedtsvägen 5 Entreplan (D2), Kungliga Tekniska
Högskolan, Stockholm.
ISRN KTH/MSE--11/37--SE+ENERGY/AVH
ISBN 978-91-7501-141-7
Qinglin Zhang. Mathematical modeling of municipal solid waste plasma gasification in a
fixed-bed melting reactor
Royal Institute of Technology
School of Industrial Engineering and Management
Department of Material Science and Engineering
Division of Energy and Furnace Technology
SE-100 44 Stockholm
Sweden
ISRN KTH/MSE--11/37--SE+ENERGY/AVH
ISBN 978-91-7501-141-7
© the author
Dedicated to my beloved parents
谨以此文献给我挚爱的父母
Abstract
The increasing yield of municipal solid waste (MSW) is one of the main by-products of
modern society. Among various MSW treatment methods, plasma gasification in a fixed-bed
melting reactor (PGM) is a new technology, which may provide an efficient and
environmental friendly solution for problems related to MSW disposals. General objectives of
this work are to develop mathematical models for the PGM process, and using these models
to analyze the characteristics of this new technology.
In this thesis, both experimental measurement and numerical analysis are carried out to
evaluate the performance of both air gasification and air&steam gasification in a PGM reactor.
Furthermore, parameter studies were launched to investigate the effect of three main operation
parameters: equivalence ratio (ER), steam feedstock mass ratio(S/F) and plasma energy ratio
(PER). Based on the above analysis, the optimal suggestions aiming at providing highest
syngas calorific value, as well as system energy efficiency, are given.
Six experimental tests were conducted in a demonstration reactor. These tests are classified
into two groups: air gasification (case 1 and 2) and air&steam gasification (case 3 to 6). In all
these cases, the plasma gasification and melting of MSW produced a syngas with a lower
heating value of 6.0-7.0 MJ/Nm3. By comparing the syngas yield and calorific value, the
study found out that the steam and air mixture is a better gasification agent than pure air. It is
also discovered that the operation parameters seriously influence the operation of the PGM
process.
A zero-dimensional kinetic free model was built up to investigate the influence of operation
parameters. The model was developed using the popular process simulation software Aspen
Plus. In this model, the whole plasma gasification and melting process was divided into four
layers: drying, pyrolysis, char combustion&gasificaiton, and plasma melting. Mass and
energy balances were considered in all layers. It was proved that the model is able to give
good agreement of the syngas yield and composition. This model was used to study the
influence of ER, S/F and PER on average gasification temperature, syngas composition and
syngas yield. It is pointed out that a common problem for the PGM air gasification is the
incomplete char conversion due to low ER value. Both increasing plasma power and feeding
steam is helpful for solving this problem. The syngas quality can also be improved by
reasonably feeding high temperature steam into the reactor.
In order to provide detailed information inside the reactor, a two-dimensional steady model
was developed for the PGM process. The model used the Euler-Euler multiphase approach.
The mass, momentum and energy balances of both gas and solid phases are considered in this
model. The model described the complex chemical and physical processes such as drying,
pyrolysis, homogeneous reactions, heterogeneous char reactions and melting of the inorganic
components of MSW. The rates of chemical reactions are controlled by kinetic rates and
physical transport theories. The model is capable of simulating the pressure fields,
temperature fields, and velocity fields of both phase, as well as variations of gas and solid
composition insider the reactor. This model was used to simulate both air gasification and
air&steam gasification of MSW in the PGM reactor.
I
For PGM air gasification, simulated results showed that when ER varies from 0.043 to 0.077,
both the syngas yield and cold gas efficiency demonstrated a trend of increasing. This is
explained mainly by the increase of char conversion rate with ER. However, the increase of
ER was restricted by peak temperature inside the fixed-bed reactor. Therefore, it is not
suggested to use only air as gasification in the PGM process. The influence of plasma power
is not obvious when PER varies from 0.098 to 0.138.
The positive influences of steam addition on cold gas efficiency and syngas lower-heatingvalue are confirmed by the simulation results of PGM air&steam gasification. The main effect
of steam addition is the rouse of water shift reaction, which largely accelerates the char
conversion and final yields of hydrogen and carbon dioxide. The effect of steam injection is
affected by steam feeding rate, air feeding rate and plasma power.
Based on the above modeling work, Interactions between operation parameters were
discussed. Possible operation extents of operation parameters are delimitated. The optimal
points aiming at obtaining maximum syngas LHV and system CGE are suggested.
Key words: Mathematical modeling, plasma gasification, municipal solid waste, fixed-bed
II
Acknowledgment
First and foremost, I would like to express my sincere gratitude to my supervisors, Professor
Wlodzimierz Blasiak and Docent Weihong Yang for their excellent guidance, continuous help,
encouragement and support during my study in KTH.
I am very thankful to Mr. Liran Dor at Environmental Energy Resources Ltd. He has been a
great support to me and a link to the real industrial scale PGM reactor. Liran is a very nice
guy who always pleased to answer my questions. Many thanks for all the helps during the
development of the numerical models.
I would like to thank Amit, Efthymios, Kentaro, Pawel, Lan and all other colleagues and
friends in the Division of Energy and Furnace Technology. They are very helpful for my
study at KTH. I have learned a lot from discussions with them.
This work is supported by the Environmental Energy Resources (Israel) Ltd., the inventor and
owner of the PGM technology and the demonstration plant. The support from EER is very
important for my work, and is grateful acknowledged.
I am grateful to China Scholarship Council for offering partial scholarship for my PhD study.
Last but not least, I would like to express my deepest thank to my girlfriend Wen for her
support and love.
III
List of paper included in the thesis
Supplement I
Q. Zhang, L. Dor, D. Fenigshtein, W. Yang, W. Blasiak. Gasification of
municipal solid waste in the Plasma Gasification Melting process.
Applied Energy (2011), DOI:10.1016/j.apenergy.2011.01.041
Supplement II
Q. Zhang, L. Dor, W. Yang, W. Blasiak. Properties and optimizing of a
plasma gasification & melting process of municipal solid waste.
Paper #58 in the proceedings of International Conference of Thermal
Treatment Technology & Hazardous Waste Combustors (IT3/HWC).
May 17-20, 2010, San Francisco, California, USA.
Supplement III
Q. Zhang, L. Dor, W. Yang, W. Blasiak. An eulerian model for
municipal solid waste gasification in a fixed-bed plasma gasification
melting reactor.
Energy Fuels, 2011, 25 (9), pp 4129–4137.
Supplement IV
Q. Zhang, L. Dor, W. Yang, W. Blasiak. Modeling of steam plasma
gasification for municipal solid waste.
Submitted to Fuel Processing Technology, in June 2011.
Supplement V
Q. Zhang, L. Dor, L. Zhang, W. Yang, W. Blasiak. Performance analysis
of municipal solid waste gasification with steam in a Plasma Gasification
Melting reactor.
Submitted to Applied Energy, in July 2011.
IV
List of papers not included in the thesis
1.
Q. Zhang, A. Swiderski, W. Yang, W. Blasiak. Experimental and numerical studies of
pulverized coal combustion with high-temperature air. 8th European Conference on
Industrial Furnaces and Boilers, Vilamoura, Portugal, Match, 2008.
2.
Q. Zhang, A. Swiderski, W. Yang, W. Blasiak. Properties of pulverized coal combustion
in high temperature air/steam mixture. Finish-Swedish Flame Days. Naantali, Finland,
January, 2009.
3.
Q. Zhang, L. Dor, K. Umeki, W. Yang, W. Blasiak. Process modeling and performance
analysis of a PGM gasifier. 10th Conference on Energy for a Clean Environment. Lisbon,
Portugal, July, 2009.
4.
Q. Zhang, L. Dor, W. Yang, W. Blasiak. CFD modeling of municipal solid waste
gasification in a fixed-bed plasma gasification melting reactor. International Conference
of Thermal Treatment Technology & Hazardous Waste Combustors. Jacksonville,
Florida, USA, May, 2011.
5.
L. Dor, Q. Zhang, W. Yang, W. Blasiak. Development of a new waste-to-energy system
using plasma gasification & melting technology. International Conference of Thermal
Treatment Technology & Hazardous Waste Combustors. Jacksonville, Florida, USA,
May, 2011.
V
List of figures
FIGURE 1. RELATIONSHIP BETWEEN COMBUSTION HEAT AND EXTERNAL ENERGY ............................................ 3
FIGURE 2. CONFIGURATIONS OF THREE DIFFERENT GASIFICATION PROCESSES. A) CONVENTIONAL
GASIFICATION B) NORMAL PLASMA GASIFICATION C) PLASMA GASIFICATION MELTING ...................... 4
FIGURE 3. THE DEMONSTRATION OF THE AREA OF STUDY IN THIS WORK ........................................................... 6
FIGURE 4. ILLUSTRATION OF THE FLOW SHEET OF THE DEMONSTRATION PLANT [68]..................................... 17
FIGURE 5. THE SCHEME OF THE PGM REACTOR IN THE DEMONSTRATION PLANT ........................................... 18
FIGURE 6. SCHEME OF PGM GASIFICATION PROCESS........................................................................................ 22
FIGURE 7. SCHEME OF THE CFD MODEL ............................................................................................................ 26
FIGURE 8. GEOMETRY AND MESH OF THE 2D MODEL......................................................................................... 33
FIGURE 9. SYNGAS COMPOSITION OF CASES 1 AND 2.......................................................................................... 37
FIGURE 10. SYNGAS CHARACTERISTICS OF CASES 1 AND 2 ................................................................................ 38
FIGURE 11. MEASURED TEMPERATURE DISTRIBUTIONS OF CASES 1 AND 2....................................................... 39
FIGURE 12. SYNGAS COMPOSITIONS OF CASES 2, 3 AND 4 .................................................................................. 40
FIGURE 13. SYNGAS CHARACTERISTICS OF CASES 2, 3 AND 4 ............................................................................ 40
FIGURE 14. SYNGAS COMPOSITIONS OF CASES 3, 5 AND 6 .................................................................................. 43
FIGURE 15. SYNGAS CHARACTERISTICS OF CASES 3, 5 AND 6 ............................................................................ 43
FIGURE 16. COLD-GAS EFFICIENCY ..................................................................................................................... 44
FIGURE 17. APPEARANCE OF SLAG AFTER COOLING .......................................................................................... 45
FIGURE 18. EFFECT OF PER ON GASIFICATION AND PYROLYSIS TEMPERATURE .............................................. 47
FIGURE 19. EFFECT OF PER ON SYNGAS COMPOSITION AND TAR YIELD ........................................................... 48
FIGURE 20. EFFECT OF PER ON TOTAL SYNGAS YIELD AND SYNGAS LHV ....................................................... 49
FIGURE 21. EFFECT OF ER ON SYNGAS COMPOSITION AND TAR YIELD ............................................................. 50
FIGURE 22. EFFECT OF ER ON SYNGAS LHV AND SYSTEM CGE ....................................................................... 51
FIGURE 23. EFFECT OF SAMR ON SYNGAS COMPOSITION AND TAR YIELD ....................................................... 52
FIGURE 24. TEMPERATURE DISTRIBUTION ALONG THE SHAFT HEIGHT OF THE BASE CASE 1........................... 53
FIGURE 25. GAS TEMPERATURE DISTRIBUTION (K) IN THE BASE CASE 1........................................................... 55
FIGURE 26 GAS TEMPERATURE DISTRIBUTIONS IN DIFFERENT HORIZONTAL SECTIONS IN THE BASE CASE 1 . 56
VI
FIGURE 27 SYNGAS COMPOSITIONS OF THE BASE CASE 1, (A) MOLAR FRACTION OF CO, (B) MOLAR FRACTION
OF H2, (C) MOLAR FRACTION OF LHCS, (D) MOLAR FRACTION OF CO2, (E) MOLAR FRACTION OF H2O,
(F) MASS FRACTION OF TAR ........................................................................................................................ 57
FIGURE 28. TEMPERATURE DISTRIBUTION ALONG THE SHAFT HEIGHT FOR DIFFERENT ER VALUES .............. 59
FIGURE 29. PREDICTED TEMPERATURE DISTRIBUTIONS FOR DIFFERENT ER ................................................... 60
FIGURE 30. ECR VALUES ALONG THE SHAFT HEIGHT FOR DIFFERENT ER VALUES ......................................... 61
FIGURE 31. TEMPERATURE DISTRIBUTIONS ALONG THE SHAFT HEIGHT FOR DIFFERENT PER ....................... 62
FIGURE 32. PREDICTED GAS TEMPERATURE (K) DISTRIBUTIONS FOR DIFFERENT S/F VALUES........................ 64
FIGURE 33. EFFECT OF S/F ON η C AND η AT ER= 0.06 AND PER= 0.118 ......................................................... 65
FIGURE 34. PREDICTED CONTENTS OF MAIN SPECIES IN GAS PHASE FOR DIFFERENT S/F VALUES. (A) H2
VOLUME FRACTIONS, (B) CO VOLUME FRACTIONS, (C)LHCS VOLUME FRACTIONS, (D) TAR MASS
FRACTIONS ..................................................................................................................................................
66
FIGURE 35. PREDICTED GAS TEMPERATURE (K) DISTRIBUTIONS FOR DIFFERENT ER VALUES ........................ 67
FIGURE 36 EFFECT OF ER ON η C AT S/F= 0.167 AND PER= 0.118.................................................................... 68
FIGURE 37. PREDICTED CONTENTS OF MAIN SPECIES IN GAS PHASE FOR DIFFERENT ER VALUES. (A) H2
VOLUME FRACTIONS, (B) CO VOLUME FRACTIONS, (C)LHCS VOLUME FRACTIONS, (D) TAR MASS
FRACTIONS ..................................................................................................................................................
69
FIGURE 38. PREDICTED GAS TEMPERATURE (K) DISTRIBUTIONS FOR DIFFERENT PER VALUES ..................... 70
FIGURE 39. PREDICTED CONTENTS OF MAIN SPECIES IN GAS PHASE FOR DIFFERENT PER VALUES. (A) H2
VOLUME FRACTIONS, (B) CO VOLUME FRACTIONS, (C) LHCS VOLUME FRACTIONS, (D) TAR MASS
FRACTIONS ..................................................................................................................................................
71
FIGURE 40. DEFINITION OF POSSIBLE OPERATION EXTENT OF PER AND ER IN THE PGM PROCESS............... 72
FIGURE 41. DISTRIBUTIONS OF SYNGAS LHV IN REGION 1................................................................................ 74
FIGURE 42. DISTRIBUTIONS OF SYSTEM CGE IN REGION 1. .............................................................................. 74
FIGURE 43. DELIMITATION OF POSSIBLE OPERATION EXTENT OF SAMR AND ER IN THE PGM PROCESS...... 76
FIGURE 44. DISTRIBUTIONS OF SYNGAS LHV IN REGION 1’ .............................................................................. 77
VII
List of tables
TABLE 1. OVERVIEW OF SUPPLEMENTS AND THEIR OBJECTIVES ......................................................................... 7
TABLE 2. MSW PROXIMATE AND ULTIMATE ANALYSES..................................................................................... 20
TABLE 3. OPERATION PARAMETERS FOR TRIAL CASES. ..................................................................................... 21
TABLE 4. KINETICS DATA FOR PRIMARY AND SECONDARY PYROLYSIS ............................................................. 30
TABLE 5. KINETIC RATES OF HOMOGENEOUS REACTIONS ................................................................................. 31
TABLE 6. EXPRESSION OF
kk
FOR HETEROGENEOUS REACTIONS ......................................................................
32
TABLE 7. OPERATION CONDITIONS IN SERIES 1 .................................................................................................. 35
TABLE 8. OPERATION CONDITIONS IN SERIES 2 .................................................................................................. 36
TABLE 9. COMPARISON BETWEEN MEASURED AND PREDICTED RESULTS OF AIR AND STEAM GASIFICATION IN
THE PGM REACTOR (DRY BASIS) ...............................................................................................................
46
TABLE 10. SYNGAS YIELD AND COMPOSITIONS FOR THE BASE CASE 1 ............................................................... 53
TABLE 11. MEASURED AND PREDICTED SYNGAS YIELD AND MAIN COMPOSITIONS OF THE BASE CASE 2 ......... 63
VIII
Content
1. INTRODUCTION ............................................................................................................................................. 1
1.1 BACKGROUND ............................................................................................................................................... 1
1.2 HEAT OF GASIFICATION ................................................................................................................................. 2
1.3 PLASMA GASIFICATION MELTING – AN INNOVATION TECHNOLOGY FOR MSW DISPOSAL ............................ 3
1.4 OUTLINE OF THIS WORK ................................................................................................................................ 5
1.5 SUPPLEMENTS ............................................................................................................................................... 6
2. LITERATURE REVIEW ................................................................................................................................. 9
2.1 EXPERIMENTAL STUDIES RELATED TO PLASMA GASIFICATION AND MELTING OF MSW ................................ 9
2.1.1 MSW gasification.................................................................................................................................. 9
2.1.2 Gasification and melting .................................................................................................................... 10
2.1.3 Application of Plasma in gasification................................................................................................. 11
2.2 DEVELOPMENT OF GASIFICATION MODELS .................................................................................................. 13
2.3 REACTION RATES ........................................................................................................................................ 14
2.3.1 Drying................................................................................................................................................. 14
2.3.2 Pyrolysis ............................................................................................................................................. 14
2.3.3 Heterogeneous char reactions ............................................................................................................ 15
2.3.4 Homogeneous reactions ..................................................................................................................... 16
3. METHODOLOGY......................................................................................................................................... 17
3.1 TEST FACILITY............................................................................................................................................. 17
3.1.1 The demonstration plant ..................................................................................................................... 17
3.1.2 The PGM reactor ................................................................................................................................ 18
3.1.3 Measurement methods ........................................................................................................................ 19
3.1.4 Feedstock ............................................................................................................................................ 20
3.1.5 Test procedure .................................................................................................................................... 20
3.2 ZERO-DIMENSIONAL KINETICS-FREE MODEL ............................................................................................... 21
3.2.1 Drying................................................................................................................................................. 23
3.2.2 Pyrolysis ............................................................................................................................................. 23
IX
3.2.3 Char combustion&gasification........................................................................................................... 24
3.2.4 Melting................................................................................................................................................ 25
3.3 TWO-DIMENSIONAL CFD MODEL ................................................................................................................ 26
3.3.1 Conservation equations ...................................................................................................................... 26
3.3.2 Reaction model ................................................................................................................................... 29
3.3.2.1 Drying........................................................................................................................................................... 29
3.3.2.2 Pyrolysis ....................................................................................................................................................... 29
3.3.2.3Homogeneous reactions ................................................................................................................................. 30
3.3.2.4 Heterogeneous char reactions ....................................................................................................................... 32
3.3.3 Geometry and boundary conditions.................................................................................................... 33
3.3.4 Simulated cases .................................................................................................................................. 34
4. RESULTS AND DISCUSSION ..................................................................................................................... 37
4.1 MEASURED RESULTS ................................................................................................................................... 37
4.1.1 Syngas quality in air gasification ....................................................................................................... 37
4.1.2 Syngas quality in air and steam gasification ...................................................................................... 40
4.1.2.1 Influence of steam feed rate .......................................................................................................................... 40
4.1.2.2 Influence of plasma power and ER ............................................................................................................... 42
4.1.3 Energy efficiency ................................................................................................................................ 44
4.1.4 Slag properties.................................................................................................................................... 45
4.2 RESULTS FROM ZERO-DIMENSIONAL KINETICS-FREE SIMULATION .............................................................. 46
4.2.1 Model validation ................................................................................................................................. 46
4.2.2 Effect of Plasma Power ...................................................................................................................... 46
4.2.3 Effect of ER ......................................................................................................................................... 49
4.2.4 Effect of SAMR ................................................................................................................................... 51
4.3 CFD RESULTS OF AIR GASIFICATION ........................................................................................................... 52
4.3.1 Analysis of the base case 1 ................................................................................................................. 52
4.3.1.1 Model validation ........................................................................................................................................... 52
4.3.1.2 Temperature profiles..................................................................................................................................... 54
4.3.1.3 Nonuniformity of temperature distributions in horizontal sections .............................................................. 55
4.3.1.4 Composition profiles .................................................................................................................................... 57
X
4.3.2 Influence of ER ................................................................................................................................... 58
4.3.2.1 Gas temperature distribution......................................................................................................................... 58
4.3.2.2 Syngas composition ...................................................................................................................................... 59
4.3.2.3 Energy conversion ratio ................................................................................................................................ 60
4.3.3 Influence of PER ................................................................................................................................. 62
4.4 CFD RESULTS OF AIR AND STEAM GASIFICATION ........................................................................................ 63
4.4.1 Model validation ................................................................................................................................. 63
4.4.2 Effect of S/F ........................................................................................................................................ 64
4.4.3 Effect of ER ......................................................................................................................................... 67
4.4.4 Effect of PER ...................................................................................................................................... 70
4.5 OPTIMIZING OF THE PGM PROCESS ............................................................................................................. 72
4.5.1 Interactions between ER and PER ...................................................................................................... 72
4.5.2 Considering the oxygen equilibrium ................................................................................................... 75
5. CONCLUSIONS AND RECOMMENDATIONS ........................................................................................ 78
6. REFERENCE .................................................................................................................................................. 81
XI
Nomenclature
A
Pre-exponential factor
Av
Specific surface area (m-1)
C
Molar concentration (kmol m-3)
Cp
Heat capacity (J kg-1 K)
D
Diffusion coefficient of vapor in the bulk (m2 s-1)
ds
Particle diameter (m)
E

g
Activation energy (J kmol-1)
G
Gibbs energy (J)
H
Height (m)
H eva
Evaporation heat of moisture (J kmol-1)
H gasi
Heat of gasification (J kg-1)
h
Specific enthalpy (J kg-1)
K
Interphase momentum exchange coefficient (kg m-3 s-1)
k
Heat transfer coefficient (W m-2 K-1)
km
Mass transfer coefficient (m s-1)
kr
Kinetic coefficient (m s-1)
M
Molar weight (kg kmol-1)
M
Mass flow rate (kg s-1)
m
Mass transfer rate (kg m-3 s-1)
Nu
Nusselt number
P
Power (W)
Pr
Prandtl number
p
Pressure (Pa)
Q
Intensity of heat exchange (W m-3)
q
Heat flux (W m-2)
Re
Reynolds number
r
Reaction rate (kmol m-3 s-1)
rk
Turbulent mixing rate (kmol m-3 s-1)
r
Kinetic rate (kmol m-3 s-1)
Gravitational acceleration (m s-2)
XII
S
Source term
Sh
Sherwood number
T
Temperature (K)
t
Time (s)
v
Velocity (m s-1)
v
Stoichiometric coefficient
x
Thickness of reactor wall (m)
Y
Mass fraction
Greek symbols
α
Volume fraction
λ
Thermal conductivity (W m-1 K-1)
ρ
Density (kg m-3)
φ
Angle of internal friction
τ
Stress tensor (Pa)
µ
Dynamic viscosity (Pa s)
Subscripts
agent
Gasification agents
air
Air
char− gasi
Char gasification reactions
cel
Cellulosic species
Cx H y
Light Hydrocarbons
CO
Carbon monoxide
CO 2
Carbon dioxide
drying
Drying
feedstock
Feedstock
g
Gas phase
gasi
Gasification
XIII
H2
Hydrogen
H 2O
Steam
i
ith species
MSW
MSW
moi
Moisture
O2
Oxygen
p
Phase p
pla
Plasma
pri
Primary pyrolysis
pyro
Pyrolysis
q
Phase q
s
Solid phase
sec
Secondary pyrolysis
stoic
Stoichiometric condition
tar1
Primary tar
tar 2
Secondary tar
vol
Volatiles
XIV
1. Introduction
1.1 Background
Municipal solid waste (MSW) is one of the main by-products of human society. In recent
decades, the development of economy in concurrence with changing lifestyle leads to a rapid
increase of MSW yield. According to a recent report by United Nations Environment
Programme (UNEP), the total amount of MSW generation globally in 2007 is about 2.12
billion tones. This number is still increasing at a rate of 7% annually [1].
The conventional MSW disposal method is landfill. Large amount of land is occupied by
landfill every year. Moreover, if landfill is carried out in an improper way, serious
environment problems related to air, water and soil can be aroused [2]. From this point of
view, landfill is not an environmental friendly waste disposal method.
The main components of MSW are food waste, wood, paper, cardboard, plastics, rubbers,
fabrics, metals and stones, and more than half of the MSW compositions are organic species,
which can be used as energy sources. Recently, the conception of energy recovery from MSW
has been a very hot topic, thus leading to a comprehensive study on waste-to-energy
technologies. Besides energy recovery, another advantage of waste-to-energy conception is
that it can sharply reduce the mass and volume of the original waste by 80-95% depending on
the composition of the MSW, since the organic components are consumed during waste-toenergy processes.
Gasification is a thermal conversion process which converts solid fuels to a combustible gas
by partial combustion. In a sense, gasification is an ‘old’ technology since its first appearance
is about 100 years ago [3]. In recent decades, due to rapid increasing of energy usage, as well
as perceived potential shortages of oil and nature gas, it starts to revive the interest in solid
fuel gasification as an important process to produce gaseous fuels. The application of
gasification in waste-to-energy process is recognized as a promising method to provide a
successful solution for MSW energy usage [4-6].
1
1.2 Heat of gasification
Gasification is generally an endothermic process. The heat of gasification is defined as the
amount of heat required to gasify unit mass of a solid fuel into gaseous products, initially at
standard temperature and pressure. For an ideal gasification process, the heat of gasification
can be divided into three parts: heat required for releasing of moisture, heat required for
devolatilization of volatile species and heat required for char gasification:
H gasi = H drying + H pyro + H char − gasi
Generally, the heat of gasification can come from different sources:
•
Reaction heat from partial combustion of feedstock;
•
Sensible heat from external sources such as preheated gasification agents, hot sand,
heat pipe and heat radiant tubes;
•
Other energy sources such as plasma and microwave;
For conventional gasification, the heat of gasification is mainly from partial combustion of
feedstock. When external energy sources (either sensible heat or other forms of energy) are
used, the heat of gasification can be provided mainly by external energy. In that case,
combustion of feedstock can be prevented.
Figure 1 shows schematically the relationship between combustion heat and external energy
in a gasification process. When no external energy is used, which represents the conventional
gasification, all the heat needed for gasification is provided by combustion of feedstock.
When external energy sources are introduced, the heat from external energy shows a linear
increase with the power of external energy. There exists a critical value of external energy,
where the external energy source supplies the energy needed for preheating, drying and
pyrolysis. If no heat is provided from combustion, the case is a standard pyrolysis. If the
energy required for char gasification can be provided by combustion, then the case turns to
gasification. The value of external energy can keep on increasing, and when value of external
energy reaches the heat of gasification, combustion of feedstock can be completely prevented.
In that case, pure steam gasification is available.
2
char-gasi
H drying+H pyro H
0
Hcri
External energy
Hear from combustion
Hear from external sources
Figure 1. Relationship between combustion heat and external energy
The prevention of combustion can leads to two main benefits: Firstly, the total calorific value
of syngas increases. This syngas can be very good gaseous fuel and chemical engineering
feedstock. Secondly, the concentrations of combustible gases are enhanced since the dilution
by N2 in air can be prevented. As a result, the syngas lower-heating-value (LHV), as well as
total energy efficiency of gasification with external energy sources is higher than
conventional gasification.
1.3 Plasma Gasification Melting – an innovation technology for
MSW disposal
The study on plasma gasification has been very popular recently. [7-9]. There are two main
advantages of using thermal plasma in the gasification process. Firstly, thermal plasma
provides extra energy to the gasification system, thus receiving all benefits of preventing
combustion. Secondly, the high temperature plasma flow can melt the inorganic components
from MSW. As a result, problems caused by fly and bottom ash can be prevented. After
cooling down, the slag will turn to a vitrified solid, in which heavy metals are locked. This
vitrified solid can be used as good construction material.
3
a) Conventional
gasification
b) Normal plasma
gasification
c) PGM
Figure 2. Configurations of three different gasification processes. a) Conventional gasification
b) Normal plasma gasification c) Plasma Gasification Melting
Figure 2a shows the general configuration of conventional gasification. Since the heat of
gasification is provided by feedstock combustion, a large volume of air is needed. The
produced syngas has a large volume, but a low LHV due to dilution by a large fraction of N2.
The configuration of normal plasma gasification is shown in Figure 2b. In normal plasma
gasification processes, high temperature plasma flows are injected onto the solid fuel surface
from the top [10-12]. Since sensible heat is supplied by plasma generators, the request of
chemical heat from partial combustion decreases. The reduced combustion can be directly
reflected by decreasing equivalence ratio. As a result, the syngas LHV value and gasification
efficiency increase. However, it has to be point out that the syngas outlet temperature in this
configuration is very high. A relatively large plasma power is needed for normal plasma
gasification.
In order to further increase the energy efficiency, the plasma gasification melting (PGM)
process is developed. The configuration of normal plasma gasification is shown in Figure 2c.
The PGM reactor can be divided into two parts: the gasification shaft and the melting
chamber. In the melting chamber, several plasma Torches are settled. These plasma torches
4
ionizes the air (or any other gas) flowing through the torches, thus forming plasma jets which
extends beyond the tip of the torch. The plasma jets melt the inorganics of the MSW (also
known as ash), which enters the melting chamber. The actual melting/vitrifying of the
inorganics occurs at 1300 to about 2000°C. The hot gases with residual heat then flow into the
gasification shaft. The gasification shaft is a typical updraft fixed-bed gasifier. In this stage,
gasification of organic species in MSW happens, so a combustible gas mixture known as
syngas is produced. During the gasification process, the gases are further cooled by the MSW.
The temperature at the syngas outlet is about 200-400 °C.
By using the PGM technology, the following benefits can be achieved:
1. The required plasma power of PGM is lower than normal plasma gasification since the
flow rat e of ash in the melting chamber is much less than that of the raw MSW;
2. The syngas temperature at the outlet is much lower than normal plasma gasification,
thus leading to higher energy efficiency;
3. Syngas LHV can be enhanced due to less combustion;
4. Lower pollutant emission due to low reaction temperature.
1.4 Outline of this work
Since the PGM is an entirely new conception, the knowledge about this technology is still
poor. No relevant study is found in literatures. Before real industrial application of the PGM
technology, both experimental validation and numerical analysis of the PGM process are
needed.
This work provides comprehensive information of the characters of the PGM process, both
experimentally and numerically. Firstly, the results of a serious of experimental tests in an
industrial scale PGM reactor are analyzed. The results are used as fundamental of the
subsequent study. Then, a 0-dimentional model is used to simulate the PGM process, so as to
study the influences of different operation parameters. For further understanding of the
information inside the reactor, a computational fluid dynamic (CFD) model is then used to
5
simulate the exact behavior of the PEM reactor at different operation conditions. Both pure air
and air&steam mixture are used in above work, so as to find out the best gasification agent for
PGM. Based on the analysis, optimizing suggestions for PGM reactor designing are given.
Generally, the content of this thesis can be divided into four parts, which are listed below:
•
Experimental study of a demonstration PGM reactor
•
Process simulation of the PGM reactor (0-dimentional simulation)
•
CFD simulation of the PGM reactor
•
Optimizing of the operation parameters of PGM process
Figure 3. The demonstration of the area of study in this work
1.5 Supplements
The supplements in this thesis are illustrated in Table 1.
6
Table 1. Overview of supplements and their objectives
Supplements
Event:
Objective:
• Temperature distribution
Experimental test of a demonstration
PGM reactor
• Syngas composition of PGM without steam
• Syngas composition of PGM with steam
• Developing a 0-dimentional model for PGM
0-dimentional simulation of the PGM
process
• Influence of sensible heat from plasma
• Influence of steam feeding rates
• Validation of the CFD model
CFD simulation of PGM air
gasification
• Temperature distributions and gas compositions in
the reactor;
• Influence of plasma power
• Influence of ER
• Influence of ER in with steam addition
CFD study of PGM with steam
addition
• Influence of steam feeding rates
• Influence of plasma power
Performance analysis and optimizing
of the PGM reactor
• Effect of single operation parameters
• Interaction between operation parameters
• Delimitation of possible operation condition
• Optimal operation conditions
In Supplement I, results from test runs of a demonstration industrial scale PGM reactor are
shown and analyzed. The temperature distributions and syngas compositions are demonstrated in
PGM both without and with steam injection. The energy efficiency of the PGM reactor is then
analyzed.
In Supplement II, a 0-dimentional model for PGM process is introduced. Cases for air PGM and
air&steam PGM are simulated. Attentions are paid to the syngas composition and energy
efficiency of PGM process. For air PGM, there exists a lower limit of air/MSW mass ratio for
100% conversion of MSW. When the air/MSW mass ratio exceeds the limitation, the syngas
LHV will descend by dilution of CO2 and N2. For air&steam PGM, high temperature steam as
gasification agent can reduce the limitation of air/MSW mass ratio, so further enhance the
syngas quality.
7
In Supplement III, a 2-dimentional CFD model is developed to simulate the PGM process using
Eulerian-Eulerian multiphase approach. The model considers the main chemical and physical
processes, such as drying, pyrolysis, homogeneous reactions, heterogeneous char reactions, and
melting of the inorganic components of MSW. The accuracy of this model is validated by the
experimental data demonstrated in Supplement I. Then, the characteristics of air PGM, such as
temperature distribution, syngas composition, tar yield, and energy conversion ratio at the
proposed condition are discussed.
In Supplement IV, the CFD model is further improved with more complex steam reaction
mechanisms. It is used to study the effects of steam addition in the PGM process. . It is found
that injection of high temperature steam is important for increasing the cold gas efficiency and
syngas lower-heating-value. The effect of steam injection is affected by steam feeding rate, air
feeding rate and plasma power. Based on the simulated results, an optimal condition is
suggested for air and steam gasification in the PGM reactor is given.
In Supplement V, optimizing of the operating conditions of PGM process is performed. Effects
of single operation parameters are analyzed. Then, the interactions between operation
parameters are discussed. Based on the above discussions, the possible operation condition of
PGM is delimitated. The optimal points aiming at obtaining maximum syngas LHV and
system CGE are given.
8
2. Literature review
As one of the promising MSW disposal methods, gasification has attracted more and more
attentions. MSW gasification has been frequently studied both experimental and numerical. The
main objective of this thesis is to develop mathematical models for fixed-bed plasma gasification
and melting of MSW. Therefore, at the first part of this literature review, the previous progresses
related to MSW gasification, especially plasma gasification and melting are introduced. Then,
attentions are paid to relevant literatures on mathematical modeling of gasification, as well as
relevant chemical and physical processes such as drying, pyrolysis, homogeneous reactions,
heterogeneous char reactions and melting of the inorganic components of MSW.
2.1 Experimental studies related to plasma gasification and melting
of MSW
2.1.1 MSW gasification
Experimental studies on gasification of both individual MSW components (such as food
waste [13-15], paper [16-17], cardboard [17-18], wood [19-21], and plastics [22-25]) and real
MSW samples [26-30] have been carried out by different researchers.
Ahmed and Gupta [13, 16-18] studied the gasification characteristics of various organic
components of MSW. Compared to pyrolysis, gasification was found to give better results in
terms of increased material destruction, and increased yields of combustible gases due to char
gasification. However, the time required for gasification was more as compared to pyrolysis.
Steam gasification provided higher energy efficiency and syngas LHV than air gasification.
The gasification temperature had a positive effect on both gasification speed and syngas yield.
It was also found that the inorganic constituents in food waste had a catalytic effect for
gasification.
Maitri et al. [27] performed MSW air gasification in a spout-fluid bed reactor. The result
showed decreasing trends of syngas higher-heating-value (HHV) and tar yield with increasing
primary air equivalence ratio (ER). The tar content in syngas was further reduced when
secondary air was supplied in the freeboard due to an increase in temperature. It was also
9
found that recirculation of carryover had a positive effect on both syngas HHV and
gasification efficiency.
Pinto et al. [28] studied gasification of mixtures of biomass and plastic wastes. They showed
that addition of plastics, especially the polyethylene (PE), clearly favored the release of
hydrogen and the decrease in CO content. The productions of light hydrocarbons were also
favored by plastics addition. The authors suggested that the steam/waste mass ratio should be
higher than 0.6 to ensure complete gasification. It was also suggested that gasification process
was strongly dependent on run temperature. A gasification temperature up to 900°C helped
the increase of hydrogen formation and reduced tars and hydrocarbons through thermal
cracking.
Dalai et al. [29] reported their experiment results on steam gasification of refuse derived fuels
(RDF) in a fixed-bed gasifier. In their paper, they confirmed the positive effects of
temperature on gasification speed. However, the gasification temperature was found to have a
negative effect on syngas LHV. The optimum gasification temperature for CO and H2
production was found to be 725 °C. The steam/waste mass ratio also showed a notable effect
on syngas LHV, and a ratio of 2 was suggested to be optimum in terms of syngas yield at 725
°C. The flow rate of carrier gas did not show any significant effect on products yield or their
distributions.
Anna et al. [30] studied the effect of feeding steam on the characters of waste gasification
with preheated gasification agent. The results confirmed that injection of steam has positive
effect on syngas calorific value. Meanwhile, a decrease of the total amount of detected tar in
response to steam addition is found. It was believed that the decrease in tar content was
attributed to steam reforming.
2.1.2 Gasification and melting
During the thermal treatment processes of MSW, the inorganic components may turn to fly
and bottom ash. The ash contains significant concentrations of heavy metals such as lead,
chromium, copper, zinc [31-32], as well as organic pollutants such as dioxins. High
temperature melting, which is also known as vitrification, is one of the most promising
solutions of ash problems.
10
Park et al. [33] reported the vitrification of fly ash along with the properties of the glasses and
leaching characteristics of heavy metal ions. It was pointed out that the produced glasses
showed Vickers hardness of 4000–5000MPa, bending strength of 60–90MPa and indentation
fracture toughness of about 0.9MPam1/2. Meanwhile, the glasses showed the excellent
resistance against leaching of heavy metal ions with Cd2+< 0.04 ppm, Cr3+< 0.02 ppm, Cu2+<
0.04 ppm and Pb2+< 0.2 ppm.
Jung et al. [34] investigated the behavior of metals in ash melting and gasification-melting of
municipal solid waste. Eight ash-melting and three MSW gasification-melting facilities with a
variety of melting processes and feedstock were selected in their study. The results showed
that the distribution ratio of metals could be predicted by the boiling point of each metal.
Metals with high boiling temperature were deposited to slag, while metals with low boiling
temperature might evaporate and exist in fly ash. The chlorine content in feedstock affected
the volatility of Cu and Pb by the formation of highly volatile chlorides. The volatility of Zn
was decreased in an oxidizing atmosphere by forming a non-volatile oxide compound.
Xiao et al. [35] studied the gasification and melting behavior of MSW. They found that the
combination of fluidized –bed gasification and swirl-melting produced a syngas with high
LHV value. Meanwhile, almost all the dioxins were decomposed, and most of the heavy
metals could be solidified. The solidification ratios of Ni, Cd, Cr, Cu, Pb and Zn were
respectively 95%, 48%, 75%, 54%, 43% and 83% approximately.
Calaminus et al. [36] developed a fixed-bed gasification and melting process called the
Thermoselect High Temperature Recycling process. This process combined slow degassing
with fixed-bed oxygen blown gasification and melting in a closed loop system. An industrial
scale demonstration plant of this process was been set up in northern Italy, and long term
operation of the plant had been performed.
The state-of-the-art of the MSW thermal treatment residue melting was summarized by Sakai
[37].
2.1.3 Application of Plasma in gasification
The application of thermal plasma in gasification has been an interesting topic since the end
of the 20th century.
11
Ivan et al. [38] studied the influence of different operation factors on solid fuel steam plasma
gasification. It was suggested that the ash content in feedstock, as well as the ER, strongly
influence the performance of the plasma gasification. There exists a temperature limit over
which the process does not proceed. They also suggested that the plasma gasification is also
affected by other factors.
Galvita et al. [39] reported their results on coal gasification in steam and air atmosphere under
arc plasma conditions. It was found that for Podmoskovnyi brown coal, Kuuchekinski
bituminous coal and Canadian petro coke, the gasification degree to synthesis gas were
92.3%, 95.8 and 78.6% correspondingly in the plasma gasification process. The amount of
produced syngas was 30–40% higher in steam than in air gasification.
Kalinenko et al. [40] studied plasma-steam gasification of brown coals in an entrained-flow
reactor. The results showed that the degree of carbon gasification was 90.5-95%. Meanwhile,
the level of sulfur conversion into the gas phase was 94.3-96. 7%. They also found that
plasma steam gasification produced a high quality syngas, in which the concentration of CO
and H2 amounted to 84.7-85.7%.
Moustakas et al. [41-42] carried out a series of experiments in a demonstration plasma
gasification/vitrification reactor. Their aim was to examine the efficiency of plasma
gasification/ vitrification in dealing with hazardous waste. It was found that the plasma
gasification/vitrification had advantages in treatment of various waste, especially waste
having major organic part. Plasma gasification/vitrification resulted in significant volume
waste reduction, ranging from about 5:1 for ash input to maximum 50:1 for solid waste. They
also pointed out that the cost of the plasma system was high, so more work should be done on
the design of the plasma gasification/ vitrification system.
Despite the fact that these works are good references for the study on plasma gasification and
melting, rare work has been found on detailed performance study, or the process optimization
of a plasma gasification and melting process. The available experimental data on plasma
gasification melting, especially industrial-scale operational data, is very limited. This situation
serious has hindered the understanding and application of plasma gasification melting
technology.
12
2.2 Development of gasification models
Gasification model can be divided into different categories. Considering the time dependence,
gasification models can be divided into kinetic models and kinetic free models. Considering
the geometry dependent, gasification can be divided into zero-dimensional models, onedimensional models, two-dimensional model and three dimensional models.
The earliest and simplest gasification models are equilibrium models. The equilibrium models
are zero-dimensional kinetic free models, in which the gasification products are calculated by
equilibrium assumption. The equilibrium model was used by Manfrida et al. [43] for coal
gasification simulation and by Ruggiero et al. [44] and Zainal et al. [45] for biomass
gasification simulation. The drawback of the equilibrium models is that the accuracies of
these models are often inadequate since reality usually deviates from equilibrium predictions.
In order to overcome the drawbacks of equilibrium models, the stratified models are
developed. In stratified models, the gasification process is divided into several zones such as
drying, pyrolysis, char gasification and combustion. In each zone, different chemical reactions
are considered. Heat and mass balances are also simulated in every individual zone. The
stratified model was used by Vittorio et al. [46] to simulate updraft coal gasification. The
results showed that the accuracy of the stratified model was in the satisfactory level for
analyzing the gasification performance at different operation conditions.
Neither of above models considers reaction kinetics and transport phenomena during
gasification process, so they are kinetic free models. If reaction kinetics is considered in
gasification model, the variation of syngas composition and detail physical properties with
time can be simulated. Zero-dimensional kinetic models are used by Manurung et al. [47] and
Blasi et al. [48] to simulate downdraft gasifiers. At KTH, a zero-dimensional kinetic model
was used by Yang et al. [49] to simulate fixed-bed gasification with high preheated air.
In zero dimensional gasification models, the influence of reactor geometry cannot be
reflected. From 1990s, studies on one-dimensional gasification became popular [50-51]. In
these models, the vertical movements of both feedstock and gas are considered. The variation
of physical and chemical properties of both feedstock and gases along the reactor height can
be simulated with these models.
13
In recent years, CFD technology has been used as a powerful tool for the simulation of
gasification processes. The Euler-Lagrange discrete phase approach and Euler-Euler
multiphase approach were successfully used for entrained-flow gasification [52-54] and
fluidized-bed gasification [55-57].
For fixed-bed gasification, Rogel and Aguillon [58] developed a 1-D + 2-D method to
simulate the performance of a biomass stratified downdraft gasifier. In their model, the mass
and energy balances within particles were written for a one dimensional system, and the mass,
momentum and energy balances of gas phase was written for a two-dimensional system.
2.3 Reaction rates
Generally, the reactions in MSW gasification can be classified into four groups: drying,
pyrolysis, heterogeneous char reactions and homogeneous reactions.
2.3.1 Drying
Drying is the first process to take place during the gasification of feedstock. Despite its
seemly simplicity, drying of feedstock is a complex combination of three steps: evaporation
of free water, desorption and evaporation of absorbed water, and separation of chemically
bound water [59].
The global reaction rate of drying has been assumed to be diffusion limited [48, 60] or
kinetically controlled [61-63]. For fixed-bed gasification, most of the researchers adopted the
diffusion limited assumption.
2.3.2 Pyrolysis
Pyrolysis is the thermal decomposition of solid fuels in the absence of oxidizers. Due to the
complexity in both reaction paths and products generated, the detail kinetics of pyrolysis is
still unclear. Various empirical global models have been developed to describe the pyrolysis.
Generally, these models can be classified into three categories: one step pyrolysis models,
competing parallel pyrolysis models and pyrolysis models with secondary tar reactions.
14
The one step pyrolysis models are simplest pyrolysis model in which the pyrolysis reaction is
expressed by a single global reaction:
r
Feedstock 
→
αGas + βTar + γChar
(2-1)
The kinetic rate r is expressed using an Arrhenius expression. The one step pyrolysis models
are common used by researchers due to its simplification [49, 64].
The competing parallel pyrolysis models assumed that feedstock decomposes directly into
each product i by a series of independent reactions:
ri
Feedstock 
→
Pr oductsi
(2-2)
where ri is the kinetic rate of the reaction i . The competing parallel pyrolysis models are
available for gasification of fine particles where the secondary tar cracking is not significant
due to very limited residence time in high temperature area. For fixed-bed gasification of
MSW, it is not a good choice.
In the pyrolysis models with secondary tar reactions, the whole pyrolysis is divided into two
steps: At first, feedstock decomposes into primary tar, char and gases, and then the primary
tar decomposes into secondary tar and secondary gases by thermal cracking [65]. The
decomposition of feedstock can use either one step models or competing parallel models.
2.3.3 Heterogeneous char reactions
The word “char” indicates to the solid residual from pyrolysis, which is mainly a mixture of
carbon and ash.
The heterogeneous reactions involve two distinct phases. Thus, the mass transfer around the
feedstock particle has to be considered. Two different models are usually used to describe the
mass diffusion at the particle surface: the shrinking-core model and the ash-segregated model.
In the shrinking-core model, the reaction core is assumed to be surrounded by a shell of inert
material (the remaining ash in the reacted area). Therefore, the gaseous reactants have to
diffuse through the ash layer before reaching the reaction core. In the ash-segregated model,
15
as soon as the residual ash forms at the particle surface, it detaches and disintegrates into
small particles. As a result, the reaction core is always exposed to the gas environment [66].
The ash-segregated model is only suitable for feedstock with low ash content. For MSW
gasification, since the ash content is 10-20wt%, depending on the MSW source, the shrinkingcore model is more appropriate.
2.3.4 Homogeneous reactions
During the gasification process, reactive gas species are produced. Gas phase reactions occur
among these species (such as water-gas shift reaction, steam reforming of light hydrocarbons
and combustion of combustible species). The rates of these reactions should be calculated by
considering both the kinetic and turbulent mixing rates.
16
3. Methodology
3.1 Test facility
3.1.1 The demonstration plant
An industrial-scale PGM demonstration plant is located in Yblin Israel. A series of trial runs
were performed in this plant to investigate the characteristics of the PGM process.
The demonstration plant was constructed in 2007. The designed capacity of the plant is 20
tons of MSW per day. The process flow sheet is shown in Figure 4. MSW is fed into the
reactor through airtight feeding chambers placed at the upper part of the plasma chemical
reactor, where gasification reactions occur. Syngas produced from gasification flows into the
afterburner and is combusted there. The hot flue gas from combustion is sent to the boiler to
produce steam, which drives a steam turbine connected to an electrical generator. The
generated electricity, besides providing power for the plasma torches and the rest of the
system, can be sold to outside users. The fly ash is removed from the flue gas in the scrubberevaporator. SOx is absorbed in the reactor absorber and removed using a bag filter. The solid
residue from gasification is melted by the plasma jet and collected by the slag collectors.
Figure 4. Illustration of the flow sheet of the demonstration plant [68]
17
3.1.2 The PGM reactor
Figure 5. The scheme of the PGM reactor in the demonstration plant
The core of the PGM plant is the plasma chemical reactor, which is a typical fixed-bed
updraft gasification reactor. The scheme of the reactor is shown in Figure 5. Generally, the
reactor is a fixed-bed counter current gasification shaft, with a plasma melting chamber
located at the bottom of the shaft. Plasma torches are placed at the ceiling of the melting
chamber. Primary air flows into the melting chamber through the torches, where it is ionized
so forming plasma jets which extend beyond the tip of the torches. The temperature of the
plasma jets may reach up to 6000 K. The plasma jets supply the necessary heat to melt the
inorganic components of the feedstock, which reached the bottom of the reactor. Secondary
air nozzles are placed around plasma nozzles. Secondary air at room temperature is injected
through secondary air nozzles. The flow rate of secondary air is adjustable thus the feeding
rate of total air can be controlled. High temperature steam at 1000°C is fed into the reactor
from steam nozzles placed at the side wall of the melting chamber. An airtight feeding pipe is
18
placed at the top of the reaction shaft. MSW is fed into the reactor intermittently from the
shaft top every half an hour. The total height of the reaction shaft is 7.02m, and the height of
the fixed-bed is 6.11 m.
3.1.3 Measurement methods
To measure the temperature distributions inside the plasma chemical reactor, thermocouples
are placed both along the gasifier shaft and in the syngas conduit. The thermocouple positions
depend on their height above the reactor bottom, H. If H < 1.0 the thermocouples are placed
in the reactor wall, behind the refractory layer, to prevent damage to the thermocouples at
high temperature. If 1.0 ≤ H ≤ 2.0, the thermocouples are placed both behind the refractory
layer and inside the reactor. For H ≤ 2.0, thermocouples are placed inside the reactor. To
obtain the actual temperature inside the reactor, temperature compensation must be made for
the thermocouples placed behind the refractory layer. According to the heat conducting law,
the heat flux through the reactor wall can be written as:
q = λ1
(T1 − T0 )
(T − T )
= λ2 2 1
∆x1
∆x2
(3-1)
where λ1 is the average thermo conductivity of the reactor wall outside the refractory layer, λ2
is the thermo conductivity of the refractory layer, T0, T1, and T2 are temperatures at the outer
wall surface, behind the refractory layer and inside the reactor, respectively, Δx1 is the
thickness of reactor wall outside the refractory layer, and Δx2 is the thickness of the refractory
layer. We assume that the wall material of both the refractory layer and the reactor wall
outside the refractory layer are uniform. The ratio of λ1 and λ2 can be calculated from the
measured temperature at 1.0 ≤ H ≤ 2.0. The temperature inside the reactor at H < 1.0 range
can then be calculated as:
′
T2 =
λ1 ∆x 2 ′ (T1′ − T0 ′ )
λ 2 ∆x1′
′
+ T1
(3-2)
19
3.1.4 Feedstock
The feedstock used by the PGM gasifier is MSW collected in Israel. The proximate and
ultimate analyses of the MSW are given in Table 2. In the reality, the size of MSW particles
varies from 1-100 mm.
Table 2. MSW proximate and ultimate analyses
Proximate analysis (in dry basis except moisture)
Moisture
20.0 %
Fixed carbon
10.7 %
Volatile
77.6 %
Ash
11.7 %
Ultimate analysis (in dry basis)
Carbon
50.5%
Hydrogen
5.6%
Oxygen
30.7%
Nitrogen
1.1%
Chlorine
<0.1%
Sulphur
0.3%
LHV of raw MSW (MJ/kg)
12.89
3.1.5 Test procedure
In the trial runs, two groups of tests were carried out. The first were with air gasification of
MSW (Cases 1 and 2), and the second were with air and steam gasification (Cases 3–6). The
feed rate of MSW was set at 600 kg/h during all runs. Trial runs were conducted with
different operating parameters, such as plasma power, secondary air feed rate and steam feed
rate, as shown in Table 3. Before each run, the reactor was preheated for 12 hours with plasma
air.
20
Table 3. Operation parameters for trial cases.
MSW
Plasma
Plasma
Air
Steam
Steam
Flow Rate
Power
Air
Injection
Injection
Temperature
(kg/h)
(KW)
(kg/h)
(kg/h)
(kg/h)
(℃)
1
600
240
120
0
0
1000
2
600
240
120
60
0
1000
3
600
240
120
60
70
1000
4
600
240
120
60
100
1000
5
600
240
120
35
70
1000
6
600
260
130
13
70
1000
Case
Number
3.2 Zero-dimensional kinetics-free model
In this work, a zero-dimensional kinetics-free model for fixed-bed plasma gasification and
melting process was developed using Aspen Plus. The model schematized the PGM process
into four different sections: drying, pyrolysis, char gasification and combustion, and plasma
melting. Moisture, volatiles, fixed-carbon and ash were removed from feedstock in these
sections, respectively. The simplified scheme of the PGM gasifier model is shown in Figure
6.
21
Syngas
and tar
MSW
Drying
Pyrolysis
Steam
Char Gasification
and Combustion
Plasma Melting
Slag
Plasma air
Figure 6. Scheme of PGM gasification process
The following model assumptions are used in this work:
•
The system is zero dimensional. Material properties like temperature (of gas phase and
solid phase), gas composition and solid composition in each zone is expressed by
“mean” values, which are calculated from the mass and energy balance.
•
The flow of solid is from top to the end, while the gas flow is from the bottom to the
top. No reflux for each phase is allowed.
•
The ash-free fuel is composed of C, H and O. The gas-phase species included in this
model are CO, H2, CO2, H2O, CH4, C2H4, O2, N2 and tars (including primary tar from
cellulosic group, primary tar from plastic group and secondary tar).
•
The heat loss of each section is calculated from the measured temperature layout of
gasifier wall surface and the gasifier structure.
22
3.2.1 Drying
In the drying section, raw MSW is heating up by hot syngas and decomposed into dry MSW
and steam. The energy balance of heat exchanger is described as:
∑ M i
i
Tsyngas − in
∫ C p,i dT = M MSW −dry
Tsyngas − out
 Tsyngas − out



+
C
dT
M
C p , H 2O dT + H eva / M H 2O 
p , MSW − dry
H 2O
∫
∫
T

TMSW − in
 MSW −in

TMSW − out
(3-3)
Considering the impact of heat gradient inside MSW particles, the outlet temperature of
drying process is set to 120 ºC. The heat capacity of MSW is calculated using the correlation
given by IGT [69].
3.2.2 Pyrolysis
Compared with coal, MSW have higher content of volatiles. For an updraft gasifier model, the
pyrolysis process is especially important because most of the gas and tar yield in this section
will join the gas produced in the char gasification section and be released from the outlet of
the gasifier without further reactions.
The heterogeneous MSW composition determines the complication of pyrolysis. According to
the pyrolysis characteristics, the composition of MSW can be divided into two main groups:
cellulosic fractions (Wood, paper, vegetation and cardboard) and plastics (PE, PP, PVC and
rubber). In this model, the pyrolysis of each group was simulated separately. A two-step
pyrolysis model [65] was applied to both groups: feedstock decomposes into primary tar, char
and primary gases in the primary pyrolysis. Then, primary tar decomposes into secondary tar
and secondary gases by thermal cracking.
The primary pyrolysis reactions of both groups are written as:
→ αGascel , pri + βTarcel , pri + γAsh + δC
Cellulosic species 
(3-4)
→ α ′Gas pla , pri + β ′Tarpla , pri + γ ′Ash + δC
Plastic species 
(3-5)
23
The yields of the primary pyrolysis products, including the composition of produced gases
and tars are taken from literatures [70-71]. To simplify the model, all light hydrocarbons
except CH4 are considered as C2H4.
The cracking reactions of primary tars are written as:
Tarcel , pri 
→ εTarsec + ζGascel ,sec
(3-6)
→ ε ′Tarsec + ζ ′Gas pla ,sec
Tarpla , pri 
(3-7)
The yield of primary tar cracking of the cellulosic group is taken from Hla [70]. No literature
data is found for the secondary pyrolysis of plastic mixture, so the yield of primary tar
cracking of the plastic group is calculated from elementary balance. The composition of
secondary tar is assumed to be benzene.
It has been proved that for a fixed-bed gasifier, the tar production is sensitive to the pyrolysis
temperature. In this model, the extent of primary tar cracking is controlled by pyrolysis
temperature [72]:
Y = exp(− A(T pyr − T0 ))
(3-8)
where T0=500°C. The constant A varies for different feedstock, and can be calculated from
test results. The Combustion values of MSW and tars are calculated based on their elementary
compositions, using the empirical correlation given by Boie [73].
3.2.3 Char combustion&gasification
Char coming from the pyrolysis zone will meet and react with gasification agents (H2O and
O2) in the gasification and combustion section. Lots of homogeneous and heterogeneous
reactions are involved in this process. Due to the high temperature in the char gasification and
combustion section, chemical equilibrium is assumed in this section, and the Gibbs free
energy theory is applied in this section.
In the Gibbs theory, the second law of thermodynamics can be expressed as:
(dG )T , P ,m
≤0
(3-9)
24
It states that the Gibbs function always decreases for a spontaneous, isothermal, isobaric
change of a fixed-mass system in the absence of all work effects except boundary work. This
principle allows us to calculate the equilibrium composition of a mixture at a given
temperature and pressure.
It can be expressed as:
[
(
Gmix = ∑ N i g i ,T = ∑ g i0,T + RT ln pi / p 0
)]
(3-10)
where: N i is the number of moles of the ith species, g i ,T is the Gibbs function of the pure
species. The superscript
0
means properties at standard pressure.
For fixed temperature and pressure, the equilibrium condition becomes
dG mix = 0
(3-11)
3.2.4 Melting
The inorganic components (ash) of the MSW coming from the gasification and combustion
zone were melted by high temperature plasma air in the plasma melting section.
The composition of the inorganic components is assumed according to the original
composition of the MSW. Based on the assumed composition, the heat capacity of the
inorganics is calculated as following:
n
C p ,ash = ∑ ω i C p ,i
i =1
(3-12)
The melting latent heat of the inorganics is calculated similarly to that of the heat capacity.
The heat loss of the plasma melting process is set to 30% of the total plasma energy, which is
summarized from the tested temperature distribution inside the melting chamber.
25
3.3 Two-dimensional CFD model
In this model the Eulerian multiphase approach was applied. The conservation equations of
mass, momentum and energy are solved for both gas and solid phases. Mass, momentum and
energy exchange is allowed between phases. The scheme of the model was shown in Figure 7.
Figure 7. Scheme of the CFD model
3.3.1 Conservation equations
Gas Phase
The Eulerian conservation equations for species mass, momentum and energy are solved for
the gas phase. The equations are written as follow [74]:
∂
(α g ρ g Yi ) + ∇ ⋅ (α g ρ g Yi vg ) = m i + S i
∂t
(3-13)
26
∂
(α g ρ g vg ) + ∇ ⋅ (α g ρ g vg vg ) = −α g ∇p + ∇ ⋅ τ g + α g ρ g g + K sg (vs − vg ) + m sg vsg
∂t
(3-14)
∂
(α g ρ g hg ) + ∇ ⋅ (α g ρ g vg hg ) = −α g ∂p + τ g : ∇vg − ∇ ⋅ qg + S g + Qsg + m sg hsg
∂t
∂t
(3-15)
Solid Phase
∂
(α s ρ sY j ) + ∇ ⋅ (α s ρ sY j vs ) = m j + S j
∂t
(3-16)
The momentum equation of solid phase is written as:
∂
(α s ρ s vs ) + ∇ ⋅ (α s ρ s vs vs ) = −∇p s + ∇ ⋅ τ s + α s ρ s g − m sg vsg
∂t
(3-17)
The energy equation of the solid phase is written as:
∂
(α s ρ s hs ) + ∇ ⋅ (α s ρ s vs hs ) = −α s ∂p + τ s : ∇vs − ∇ ⋅ qs + S s + Qgs − m sg hsg
∂t
∂t
(3-18)
where p s and τ s denote the solid pressure and shear stress, which are defined to express the
normal and the shear stress parts of solid-phase stress. The solid-phase stress is a function of
solid volume fraction. At fixed-bed condition, the value of ∇p s , which is several orders of
magnitude larger than the fluid-solid stress, becomes the main driving force of granular flow
[75-76]. In other words, the influence of the fluid-solid stress on solid motion can be ignored
(the detailed numerical expressions of the solid-phase stress and fluid-solid stress are
introduced in the next section). This idea was used by Johnson and Jackson [77] to describe
non-reaction shearing granular flow. In the present work, the idea is also adopted so that the
fluid-solid stress term is disregarded in the solid phase momentum equations. This
simplification is very helpful for the convergence of the solid momentum equation since it
largely prevents the solution of interphase non-linear terms, which is the main cause of nonconvergence for Euler-Euler approach.
The energy equation of the solid phase is written as:
∂
(α s ρ s hs ) + ∇ ⋅ (α s ρ s vs hs ) = −α s ∂p + τ s : ∇vs − ∇ ⋅ qs + S s + Qgs − m sg hsg
∂t
∂t
(3-19)
27
Gas-solid stress
The gas-solid stress is ignored for the solid phase. However, it is considered in the momentum
equation of the gas phase. The gas-solid stress is simulated using the Ergun equation [78].
The interphase momentum exchange coefficient K sg is written as:
ρ g α s vs − v g
α (1 − α g )µ g
K sg = 150 s
+ 1.756
2
ds
α g ds


(3-20)
Solid phase stress
The solid phase stress is composed of two parts: the normal stress part and the shear stress
part. For fixed-bed gasification, the flow of solid phase should be treated as a plastic flow
[79]. The normal stress part is expressed by solid pressure p s [80]:
ps = α s p ∗
(3-21)
p ∗ is expressed by an empirical power law:
(
p∗ = A α g − α g∗
)
n
(3-22)
where α g∗ is the gas volume fraction at minimum fluidization. Empirical values of A = 10 25
(Pa) and n = 10 are used.
For the shear stress part, only the frictional viscosity is considered. Since the flow of solid
phase is dense flow, where the solid volume fraction for the solid phase is near the packing
limit, the Schaeffer’s formulation [81] of frictional viscosity is applied:
µs =
ps sin φ
2 I2D
(3-23)
Interphase heat transfer
The intensity of heat exchange between the solid and gas phases is assumed to be a function
of the temperature difference between solid and gas phase:
28
Qsg = −Qgs = k sg (T s−Tg )
(3-24)
The heat transfer coefficient is written as:
k sg =
6κ gα sα g Nu s
ds
(3-25)
2
Here Nu s is the Nusselt number correlated by Gunn [82]:
(
)(
Nu s = 7 − 10α g + 5α g 1 + 0.7 Re 0s .2 Prg
2
0.33
) + (1.33 − 2.4α
)
+ 1.2α g Re 0s .7 Prg
2
g
0.33
(3-26)
3.3.2 Reaction model
3.3.2.1 Drying
In this model, a drying model which is popular used in fixed-bed combustion or gasification
of MSW and biomass [83-87] is applied:
(
r1 = Av k m C moi − C H 2O
)
when Ts < 100  C
(3-27)
or
r1 = Qsg / H evp when Ts ≥ 100  C
(3-28)
The Mass transfer coefficient k m is calculated according to the Sherwood number [88-89]:
km =
ShD
d
(3-29)
3.3.2.2 Pyrolysis
In this work, a two-step pyrolysis model is applied. The pyrolysis of MSW is divided into two
steps: at first, MSW decomposes into char, gas and primary tar. Then the primary tar
decomposes into gas and secondary tar by thermal cracking [65].
→ αGas + β Pr imary tar + γChar
MSW 
(3-30)
29
Pr imary tar 
→ Gas + Secondary tar
(3-31)
It has been confirmed by experiments that the two-step pyrolysis model can correctly predict
the pyrolysis yields, especially tar yields at various conditions [90-91]. It is very appropriate
for modeling pyrolysis in the updraft fixed-bed gasification since the tar problem is the most
significant in this constitution.
Table 4. Kinetics data for primary and secondary pyrolysis
Reaction
Reaction rate (kmol m-3 s-1)
Source
Primary pyrolysis of
cellulosic group
 − 1.60 × 10 4 
 ρ v1
r = 3.20 × 105 (1 − α g )exp
Ts


Chan et
al. [93]
A3,1 = 9.3 ×1013 , E3,1 = 2.34 ×105
A3, 2 = 1.2 × 1012 , E3, 2 = 2.07 × 105
Primary pyrolysis of
plastic group

 − E3,i  
 ρ v 2
r = (1 − α g )∑  Yi A3,i exp

i =1 
 RTs   ,
6
A3,3 = 6.3 × 1010 , E3,3 = 1.84 × 105
A3, 4 = 5.0 × 10 , E3, 4 = 1.73 × 10
10
5
Wu et al.
[94]
A3,5 = 9.5 × 1010 , E3,5 = 1.80 × 105
A3, 6 = 1.5 × 1012 , E3, 6 = 1.64 × 105
Secondary pyrolysis
 − 1.12 × 10 4 
 ρ tar1
r = 9.55 × 10 4 α g exp


Tg


Boroson
et al. [90]
MSW is the mixture of different species. Generally, most of the organic components of MSW
can be divided into two groups: the cellulosic group (wood, paper, cardboard and textile et al.)
and plastics group (polystyrene, polypropylene, polyethylene, and polyvinyl chloride et al.
[92]). The pyrolysis characters of these two groups are different. In this work, the differences
are considered by using individually pyrolysis kinetics for each group (shown in Table 4).
The interactions between species are not considered in this model.
3.3.2.3Homogeneous reactions
The following homogeneous reactions are considered in this model:
r1
H 2 + 1 / 2O2 →
H 2O
(3-32)
30
r2
C x H y + (2 x + y ) / 4O2 →
xCO + y / 2 H 2O
(3-33)
r3
CO + 1 / 2O2 →
CO2
(3-34)
r4
( x + y / 2) H 2 + xCO
C x H y + xH 2O →
(3-35)
r5
CO + H 2O ←→
H 2 + CO2
(3-36)
Chemical reaction rates of (3-32)-(3-36) are considered by choosing the minimum of the
kinetic rates and turbulent mixing rates:
rk = min (rrk , rtk ) , k = 1 − 5
(3-37)
Turbulent mixing rates are calculated using the eddy dissipation model:
 Y
Y 
ε
rtk = 4.0 ρ min i , j 
vM v M 
k
 i i j j
(3-38)
where i and j denote reactants of reaction k .
Kinetic rates of homogeneous reactions are shown in Table 5.
Table 5. Kinetic rates of homogeneous reactions
Kinetic rate (kmol m-3 s-1)
Source
rr1 = 3.56 × 108.4 α g exp(− 3670 / Tg )CH 2 CO2
1.1
rr 2 = 1.0 × 1011.7 α g exp(− 24369 / Tg )CC x H y CO2
0.7
Varma et al. [95]
1.1
Dryer et al. [96]
0.8
rr 3 = 1.3 × 1011α g exp(− 62700 / Tg )CCOCH 2 O CO2
0.5
Howard et al. [97]
0.5
rr 4 = 3.0 × 108 α gTg exp(− 15083 / Tg )CC x H y CH 2 O
exp(− 7914 / Tg )CCO2 CH 2

rr 5 = 0.03α g exp(− 7250 / Tg ) CCOCH 2 O −
0.0265

Jones et al. [98]



Grebenshchikova [99], Yoon et al.
[100]
31
3.3.2.4 Heterogeneous char reactions
Heterogeneous char reactions involved in this model include the following overall reactions:
C+
γ +1
2
γ
r
O2 →
CO +
CO
γ +2
γ +2
γ +2 2
6
(3-39)
r7
C + H 2O →
CO + H 2
(3-40)
r8
C + CO2 →
2CO
(3-41)
r9
C + 2 H 2 →
CH 4
(3-42)
In reaction (3-39) the ratio of produced CO and CO2 is calculated as [67]:
CO / CO2 = 2500 exp(− 6420 / Tg )
(3-43)
The heterogeneous reaction rates are estimated using the unreacted shrinking core model, in
which the real reaction rate depends on surface film diffusion and reaction kinetics [101]. For
all heterogeneous char reactions, first order of reaction is assumed with respect to gaseous
reactants.
 1  Av ρi

rk = 
 vi M i  1 + 1
km kk
k = 6−9
(3-44)
where i is the gaseous reactants of reaction k .The expressions of k k are shown in Table 6.
Table 6. expression of k k for heterogeneous reactions
k k (m s-1)
Source
k6 = 0.685Ts exp(− 9000 / Ts )
Evans et al. [102]
k7 = 5.714Ts exp(− 15600 / Ts )
Yoon et al. [100]
k8 = 5.89 × 10 2 Ts exp(− 26801 / Ts )
Hobbs et al. [60]
k9 = 3.42 × 10−3 Ts exp(− 26801 / Ts )
Hobbs et al. [60]
32
3.3.3 Geometry and boundary conditions
Geometry used in this work should be a reflection of the real 3D geometry so that it can
capture most flow characteristics of a real PGM process. The geometry of the trial gasifier is
approximately symmetrical in the width direction, so the longitudinal section of the gasifier
can be used as the 2D geometry. Since the void fraction of the hillock of concretionary slag is
very small, the hillock was excluded from the flow field. The total number of mesh cells is
10107. In the areas associated with plasma injections and secondary air injections, the mesh
was refined.
Figure 8. Geometry and mesh of the 2D model
In order to express the feeding of MSW, a mass source of solid phase was defined as at the
top of the fixed-bed. Since this is a steady model, the feeding of MSW is assumed to be
continuous. For all cases, the feeding rate is 600kg/h. Mass flow inlet conditions are defined
at the corresponding positions of plasma air and secondary air inlets. The outlet of syngas is
defined as a pressure outlet. The relative pressure at the outlet is set to -700 Pa, which is the
measured result for the pilot reactor. The melting of unreacted solid residual is represented by
33
a mass and energy sink of solid phase. Another energy sink is defined in the melting
chambers to express the heat transfer from gas phase to slag. The motion of slag after melting
is ignored in this model. The reactor walls are defined as no slip walls. An empirical
temperature distribution is defined at the reactor wall to calculate the heat loss from the wall.
3.3.4 Simulated cases
Two series of CFD simulations were carried out in this work:
•
Series 1: air gasification of the fixed-bed plasma gasification;
•
Series 2: air and steam gasification of the fixed-bed plasma gasification.
In order to increase the versatility of the results, dimensionless numbers are used to
characterize and classify the operation parameters of PGM process.
The amount of available air per kilogram of MSW is represented by the equivalence ratio
(ER), defined as:
ER =
(M
/ M MSW )
(M air / M MSW )stoic
air
(3-45)
where M air / M MSW is the air/MSW mass flow ratio in the real cases and (M air / M MSW )stoic is
the air/MSW mass flow ratio for a stoichiometric combustion where the fuel is fully
combusted.
The amount of plasma energy per kilogram of MSW is expressed by dimensionless plasma
energy ratio (PER), which is defined as:
PER =
Ppla
LHVMSW ⋅ M MSW
(3-46)
where Ppla is the heat power of plasma generators, LHVMSW is the low heating value of raw
MSW, and M MSW is the mass flow rate of raw MSW.
34
The amount of steam feeding rate is expressed by steam air mass ratio (SAMR, in0
dimensional simulations) and steam feedstock mass ratio (S/F, in 2-dimensional simulations):
SAMR =
M H 2O
M
(3-47)
air
S/F =
M H 2O
M
(3-48)
MSW
In each series, a simulation of a typical case named the base case was performed. The results
of the base case were compared with the measured results from the demonstration reactor to
evaluate the availability of the model. Then, groups of simulations were performed to study
the influence of operation parameters. The detailed operating conditions of each series are
shown in Table 7 and Table 8.
Table 7. Operation conditions in series 1
Base case 1
(Case 2 in measurement)
Group 1
Group 2
Operation parameters
Plasma power (kw)
240
240
200 - 280
Air feeding rate (kg/h)
180
130 - 230
180
Steam feeding rate (kg/h)
0
0
0
ER
0.06
0.043 – 0.077
0.06
S/F
0
0
0
PER
0.118
0.118
0.98 - 0.138
After dimensionless treatments
35
Table 8. Operation conditions in series 2
Base case 2
(Case 3 in measurement)
Group 3
Group 4
Group 5
Operation parameters
Plasma power (kw)
240
240
240
220 - 260
Air feeding rate (kg/h)
180
180
130 - 230
180
Steam feeding rate (kg/h)
70
0 - 150
100
100
ER
0.06
0.06
0.043 – 0.077
0.06
S/F
0.117
0 - 0.250
0.167
0.167
PER
0.118
0.118
0.118
0.108 - 0.128
After dimensionless
treatments
36
4. Results and discussion
4.1 Measured results
4.1.1 Syngas quality in air gasification
Two tests were performed without steam feeds (Cases 1 and 2). In both cases, the plasma
power is 240kw. In Case 1, the secondary air flow rate was set to zero. In Case 2, the feed rate
of secondary air was calculated by assuming that the total air feed rate equals the
stoichiometric demand for converting all fixed carbon in the feedstock into CO. The results
from both cases are presented in Figure 9 and Figure 10.
Figure 9. Syngas composition of Cases 1 and 2
37
Figure 10. Syngas characteristics of Cases 1 and 2
Both cases showed good results in terms of the lower heating value (LHV) of the product
syngas, here 6–7 MJ/Nm3. This was mainly due to the low ER in the PGM process (0.04 in
Case 1 and 0.06 in Case 2). A low ER ratio prevents the dilution of syngas with nitrogen from
air; a substoichiometric oxygen level suppresses the formation of CO 2 , which is the other
main noncombustible gas in syngas. Due to the concentration of combustible gases in the
syngas, the total gas yields here (0.67 and 1.06 Nm3/kg MSW in Cases 1 and 2, respectively)
were lower than that of conventional gasification. In both cases, the H 2 /CO molar ratio was
approximately 1.5, which is somewhat higher than that of common gasification processes,
mainly due to the high contents of hydrogen and oxygen in the feedstock.
Despite the common features of the two cases, some important differences in syngas
composition and yield were found. Firstly, a significant increase of gas yield was observed
when a higher ER was used. This increase was partly due to the N 2 content of the secondary
air, which led to the decrease of LHV in Case 2, and partly due to the cracking of tar favored
by the higher temperature associated with increasing ER.
38
Figure 11. Measured temperature distributions of Cases 1 and 2
Figure 11 is the measured temperature distribution along the reactor chamber of Cases 1 and
2. It can be found that the temperature of Case 2 is 100-200 ºC higher than that of Case 1,
with an exception near the bottom. The bottom temperature of Case 2 is lower than that of
Case 1 due to the additional low temperature air injection. Another reason for the increase in
gas yield from Case 1 to Case 2 was likely the insufficient carbon conversion in Case 1, as
shown by chemical-equilibrium calculations. A low ER ratio in the PGM ensures high syngas
quality. However, when the ER is too low, as in Case 1, the gasification agent cannot supply
enough oxygen to convert char into CO or CO 2 . Insufficient carbon conversion is an adverse
condition for gasification as it reduces both the gas yield and energy efficiency. In Case 2, the
feeding of secondary air solved this problem. The increased O 2 enhanced the CO content in
syngas, as shown in Figure 9. An interesting result from the two cases is that although the
syngas yield changed significantly, the volume fraction of H 2 in the syngas was relatively
unchanged. This indicates an increase of H 2 production with increasing ER. The positive
effect on H 2 yield in response to increased ER is in accordance with the results by Pinto et al.
[103] and Anna et al. [30]. The increased H 2 production with increased ER was likely the
result of favorable conditions for the secondary pyrolysis of primary tar. According to the
Boroson’s theory [90], pyrolysis can be divided into two steps: primary pyrolysis and
secondary pyrolysis. H 2 is mainly produced from the secondary pyrolysis step, which is
sensitive to pyrolysis temperature. A higher temperature due to increasing ER thus favored
secondary pyrolysis, and more H 2 was produced. Another effect of increasing temperature
with ER was the decrease in total light hydrocarbon (THC) content. The relationship between
pyrolysis temperature and THC yield has been reported by Anh et al. [104] and Li et al. [105],
and the mechanism was explained by Anthony et al.[106].
39
4.1.2 Syngas quality in air and steam gasification
4.1.2.1 Influence of steam feed rate
Along with Case 2, experiments for Cases 3 and 4 were performed to investigate the influence
of the steam feed rate. The plasma and air settings of Cases 3 and 4 were the same as for Case
2 but with different steam feed rates (70 and 100 kg/h, respectively). The results from Cases 2,
3, and 4 are presented in Figure 12 and Figure 13.
Figure 12. Syngas compositions of Cases 2, 3 and 4
Figure 13. Syngas characteristics of Cases 2, 3 and 4
We found that adding high-temperature steam is favorable for the PGM process. The total gas
yield increased significantly, and the gas LHV also increased with steam feeding. Generally,
40
it is believed that the increase of gas yield with steam feeding is due to the water-gas shift
reaction:
CO + H 2O = CO2 + H 2 .
(4-1)
This reaction undoubtedly played some role in the yield increase, especially with excess
steam. However, the increase of LHV in our cases cannot be explained solely by this reaction.
Examining the composition of the syngas, we found that as the steam feed rate was increased
from Case 2 to 4, the THC content increased significantly. The CO content, in contrast,
increased from Case 2 to Case 3 but decreased from Case 3 to Case 4. In all three cases, the
fluctuation in H 2 content was very small. Similar results were reported by Blasiak et al. [107],
who studied the high-temperature air and steam gasification of biomass in an updraft fixedbed gasifier. A possible explanation for this phenomenon is the steam reforming of tar at high
temperature. The mechanism and kinetics of tar steam reforming have been reported by Li et
al. [108]. The global reaction can be written as follows:
Cm H n + aH 2O = bCO + cH 2 + dC x H y ,
(4-2)
where Cm H n represents tar and C x H y the light hydrocarbons.
A strict restriction of the steam-reforming reaction is that it can only occur at high
temperature. It was pointed out by Jess et al. [109] that at a temperature of approximately
1,200 ºC, the steam reforming of tar can go to completion in less than 10 s. As we measured
during the tests, the global gasification temperature was in the range of 1,000–1,200 ºC.
Considering the scale of the reactor, it is very likely that there was a strong steam-reforming
reaction during the air and steam gasification process. Therefore, the steam reforming of tar
and the water-gas shift reaction together resulted in the increased syngas yield.
Comparing the results of Cases 3 and 4, a notable difference is that the H 2 /CO molar ratio
increased greatly. This may be due to the promotion of the water-gas shift reaction by the
excess steam in Case 4. According to Li et al. [108], the priority of tar steam reforming is
higher than the water-gas shift reaction at high temperature due to the occurrence of the
following reaction:
41
C m H n + mCO2 = 2mCO + n H 2
2
(4-3)
When there is insufficient steam for reforming, as in Case 3, the water-gas shift reaction is, in
a sense, suppressed. When steam is supplied in excess, the water-gas shift reaction then
becomes much more intensive, resulting in a high H 2 /CO molar ratio.
4.1.2.2 Influence of plasma power and ER
The experiments in Cases 5 and 6 were conducted to investigate the influence of plasma
power and ER in air and steam gasification. In both cases, the steam feed rate was 70 kg/h, the
same as in Case 3; the plasma power and ER were then varied. The results from Cases 5 and 6
are presented in Figure 12 and Figure 13 with Case 3 for comparison.
42
Figure 14. Syngas compositions of Cases 3, 5 and 6
Figure 15. Syngas characteristics of Cases 3, 5 and 6
The results for Cases 3 and 5 were similar. The slight difference in gas yields can be
explained by the reduced air feed and lower tar cracking and reforming related to the reduced
combustion due to the lower ER. However, some significant differences in syngas
composition were found when comparing Case 6 with Cases 3 and 5 taken together. The
overall increase of combustible gases, especially of H 2 , may be mainly due to the sensitivity
of tar cracking and reforming to temperature. In the PGM process, more than half of the
energy need for gasification is from the plasma torches. The increased plasma power in Case
6 led to a significant increase of gasification temperature, which prompted the cracking and
reforming of tar. The reforming reaction of light hydrocarbons may have also taken place, as
in Eq. (4-3), enhancing the yield of H 2 .
C x H y + xH 2O = xCO + ( x + 2 / y ) H 2 .
(4-4)
43
4.1.3 Energy efficiency
The cold-gas efficiency (CGE) is a standard criterion frequently quoted to express the energy
efficiency of a gasification process. For a PGM process, the definition of CGE was modified
to
η=
m syngas ⋅ LHVsyngas
m feedstock ⋅ LHV feedstock + Psteam + Pplasma
× 100% ,
(4-5)
where m syngas and m feedstock denote the mass flow rates of the syngas and the feedstock,
respectively, while LHVsyngas and LHV feedstock are their lower heating values on a mass basis.
Psteam denotes the power used to heat the steam, and Pplasma is the plasma power.
The combustion value of the MSW was calculated from an empirical expression given by
Boie et al. [110]:
HHV = 83.22C + 274.3H − 25.8O + 15 N = 9.4Cl + 65 P .
(4-6)
Figure 16. Cold-gas efficiency
The CGE results of all six cases are shown in Figure 16. Here, the CGE varies from 30% to
60%. The energy efficiency of air gasification is lower than that of air and steam gasification.
The CGE was the lowest for Case 1; Case 6 had the highest. For air gasification, increasing
ER was beneficial for increasing energy efficiency, whereas the influence of ER was not
obvious for air and steam gasification.
44
There are three main sources of energy loss in gasification: the chemical energy in the tar, the
sensible heat of the syngas, and the heat loss of the system. Because a PGM reactor is an
updraft fixed-bed reactor, the sensible heat of the syngas cannot be the main energy loss. The
normal system heat loss is approximately 2–5% of the total energy, so the main energy loss
for PGM should be chemical energy in the tar.
4.1.4 Slag properties
The inorganic components of MSW were melted to form a slag. The discharging of slag was
not continuous in the trial reactor. Instead, it was controlled by a valve placed at the exit of
the melting chamber. At most times, the valve is closed, and the volume of slag inside the
combustion chamber increases continually. When it reaches a certain level, the valve is
opened. The melted slag flows out of the melting chamber and into the slag collector. When
the collector is full, the valve is closed again, and the collector is transmitted into the open air
for cooling. When it exits the melting chamber, the slag is a glowing liquid. After four hours
of cooling, it becomes a black, vitreous solid. The appearance of the slag after cooling is
shown in Figure 17.
Figure 17. Appearance of slag after cooling
During these tests, the output of slag was approximately 25 kg/h. Due to the high density of
this slag (2,300 kg/m3), the volume ratio of slag to raw MSW is approximately 1:50. The
45
composition can vary with the feedstock, but the main contents should be SiO 2 and CaO.
Undesirable materials such as heavy metals are locked in the slag, so that the slag is virtually
inert, meeting the most demanding TCLP Standards. This slag can be used as a good building
material.
4.2 Results from zero-dimensional kinetics-free simulation
4.2.1 Model validation
The comparison of measured results and predicted results of air and steam gasification in the
PGM demo-reactor are shown in Table 9. Results are shown in terms of syngas yield, syngas
LHV and the H 2 /CO molar ratio. By comparing the predicted results with the measured
results, it was found that the results from modeling are in the acceptable ranges for analyzing
the character of PGM process.
Table 9. Comparison between measured and predicted results of air and steam gasification in
the PGM reactor (dry basis)
Case number
3
4
5
6
ER
0.060
0.060
0.052
0.048
PER
0.118
0.118
0.118
0.128
SAMR
0.389
0.556
0.452
0.490
Steam temperature (ºC)
1000
1000
1000
1000
Syngas yield (Nm3/kg MSW)
1.36
1.38
1.26
1.29
Syngas LHV (MJ/Nm3)
8.23
8.43
8.24
8.70
H2/CO
1.24
1.53
1.45
1.70
1.27
1.32
1.16
1.14
Syngas LHV (MJ/Nm )
8.48
8.70
8.05
8.38
H2/CO
1.16
1.33
1.32
1.41
Operation parameters
Measured results
Predicted results
Syngas yield (Nm3/kg MSW)
3
4.2.2 Effect of Plasma Power
The high-temperature plasma air injection is the most important significance of the PGM
process. It supplies heat for the melting of the inorganic component of MSW. After that, the
46
residual heat provides sensible heat to gasification. In this way, the power of plasma affects
the energy equilibrium of the whole gasification process, and directly influences the
temperature profile, syngas composition, tar yield and stability of the gasification process. A
serious of cases are simulated to investigate the effect of PER on gasification characters in
PGM process. In these cases, the values of ER and SAMR are set to 0.06 and 0.389
respectively, which are testified as “reasonable” values for PGM air and steam gasification by
previous test runs. The value of PER varies from 0.098 to 0.137.
The effect of PER on the average temperature in the gasification and pyrolysis zone is
illustrated in Figure 18. It was found that both gasification temperature and pyrolysis
temperature increase linear with PER. This is easy to understand since increasing PER
enhance the average temperature of feeding air, and increases the heat supply for gasification
and pyrolysis.
Figure 18. Effect of PER on gasification and pyrolysis temperature
Figure 19 shows the syngas composition, as well as tar yield with different PER. All the
gaseous species are shown in volume fractions on dry basis, and tar is shown by tar-MSW
mass ratio on dry basis. It was found that the volume fractions of all combustible gaseous
increase with PER, while the trends of CO 2 and N 2 are opposite. The increment of
combustible gases is mainly due to promoted tar cracking by increasing pyrolysis temperature.
At the same time, the total yields of incombustible gases like CO 2 and N 2 do not vary much.
Considering the increasing of combustible gases with PER, the decreasing trends of CO 2 and
N 2 volume fractions are understandable.
47
Figure 19. Effect of PER on syngas composition and tar yield
Figure 20 shows the effects of PER on syngas yield and syngas LHV, where both results are
calculated on dry basis. It was found that both the syngas yield and syngas LHV increase with
PER. This is not hard to understand since the increase of combustible gas yields by tar
cracking is profitable for both quantity and quality of syngas. When PER increase from 0.098
to 0.137, the syngas yield increases from 0.96 to 1.08 Nm3/kg MSW. At the same time the
syngas LHV varies from 7.32 to 9.31 MJ/Nm3. It seems the positive effects of PER provides a
possible method for not only solving the tar problem, but also increase the syngas yield and
quality. However, it has to be noticed that beneficial effects of increasing PER is not
unlimited. As we can see in Figure 18, the temperature inside the reactor also increases with
PER. A high PER value may leads to the formation of a high temperature zone in the
combustion and gasification section. Too high temperature challenges the thermostability of
the reactor wall. Furthermore, the low-melting-point components in the solid residual like
SiO 2 may be melted in the gasification and combustion section if the temperature is too high.
The partial melting of solid residual will dramatically decrease the void fraction in the fixedbed, and leads to the occurrence of bridging. It can be found from Figure 18 that when PER=
0.26, the average temperature in the gasification section has reached 1330 ºC. This
temperature is already too high for an engineering application.
48
Figure 20. Effect of PER on total syngas yield and syngas LHV
4.2.3 Effect of ER
For a conventional gasifier, the energy needed for feedstock heating up, pyrolysis and char
gasification is mainly from the partial combustion of char. The equivalence ratio (ER) for
conventional gasifier should be around 0.3 to fulfill the need of energy. For PGM air and
steam gasification, heat can be supplied by plasma and high temperature steam, so the ER for
a PGM gasifier will be much lower (0.04-0.10). It is worthwhile to study the influence of ER
on the performance of a PGM gasifier.
Theoretically, the effects of ER on gasification process should be considered from two aspects.
On one side, higher ER provides more chemical heat by combustion. It is known that
increased heat supply is beneficial for both syngas yield and LHV value, so this effect of ER
is positive. On the other side, higher ER means more combustion in the reactor, which will
consume some combustible gases. Additionally, the increasing N 2 introduced into the reactor
dilutes the content of combustible gases. From this point of view, the ER also has negative
effects on syngas production. The final influence of ER on PGM process should be a
combination of these two aspects.
A group of simulations with different ER was carried out to study the exact influence of ER
on PGM process. The values of SAMR and PER are set to 0.389 and 0.118, respectively. The
value of ER varies from 0.04 to 0.08.
Figure 21 shows the syngas composition and tar yield with different ER value. It was found
that when ER increases, the volume fractions of CH 4 , C 2 H 4 and N 2 increase, and the volume
49
fraction of H 2 and tar yield decrease. The volume fraction of CO first increases and then
decreases. An opposite trend was found for CO 2 volume fraction. The increase of CH 4 and
C 2 H 4 volume fractions can be understand as the result of positive effect of ER on tar cracking,
while the increase of N 2 and decrease of H 2 volume fractions are the results of negative
effects of ER. The variations of CO and CO 2 volume fractions are affected by both aspects.
Figure 21. Effect of ER on syngas composition and tar yield
Figure 22 shows the variation of syngas LHV and system CGE with increasing ER. It was
found that the influence of ER on syngas LHV can be divided into two parts. When ER
increases from 0.04 to 0.07, the syngas LHV increases from 6.11 to 8.63MJ/Nm3. The
positive effect of ER is dominant. When ER increases from 0.07 to 0.08, the syngas LHV
keeps almost constant. It seems negative effect of ER starts to appear in this range, and
counterbalances the positive effect. For system CGE, however, the effect of increasing ER is
positive in all ER range.
50
Figure 22. Effect of ER on syngas LHV and system CGE
4.2.4 Effect of SAMR
The feeding of high temperature steam influences the PGM process from two aspects. Firstly,
steam is involved in chemical reactions such as water-gas reaction and water gas shift reaction.
In that case, it influences the chemical equilibrium of the PGM system. Secondly, the high
temperature steam changes the total mass and energy flow inside the reactor, and influence
the energy balance of the system.
As an example, the effect of different SAMR on syngas composition and tar yield for
ER=0.06 and PER=0.118 is shown in Figure 23. It was found that the most important effect of
increasing SAMR is the variation of H 2 , CO, and CO 2 volume fractions. When the SARM
increases from 0 to 0.67, the volume fraction of H 2 in syngas increases from 9.5% to 21.3%.
The volume fraction of CO 2 increases similarly from 12.4% to 20.2%, while the volume
fraction of CO decreases from 26.8% to 14.9%. The similar trends were also reported by other
researchers [111-117]. This phenomenon is the result of promoted water-gas shift reaction
( CO + H 2O ←
→ H 2 + CO2 ) by increasing steam feeding rate. It was also found that the yield
of tar shown a slight decreasing trend when the SAMR increases. At the same time, the CH 4
and C 2 H 4 volume fractions increase slightly. It is believe that this phenomenon is the result of
steam preheating, which introduces extra energy to the PGM system, and increases the global
temperature of pyrolysis. It was reported by Lewis et al. [118] that the critical steam
temperature for supporting energy supply in steam-only gasification process is above 1200 ºC.
In PGM process, due to the heat supply from plasma air and char combustion, the critical
steam temperature should be reduced. It was implied by the tar decreasing that the critical
51
steam temperature at the analyzed condition is lower than 1000 ºC. As a result of the extra
heat supply by high-temperature steam, the syngas yield and LHV increase slowly with
SAMR. It was also found that the effect of SAMR on syngas composition weakens with
increasing SAMR. The effect is most remarkable when SAMR varies from 0 to 0.1.
Figure 23. Effect of SAMR on syngas composition and tar yield
4.3 CFD results of air gasification
4.3.1 Analysis of the base case 1
4.3.1.1 Model validation
In order to evaluate the availability of the model, simulation data of temperature distribution
along the reaction shaft axis, as well as the syngas composition was compared with measure
data obtained from test runs of the base case 1. Results are shown in Figure 24 and Table 10.
The predicted and measured temperature profiles fit each other well. However, a slight
deviation was found at the reactor height 4.5 to 6.1 meter. Two reasons can explain this
deviation: firstly, the assumption of continuous feeding of MSW in the model leads to
imprecise temperature prediction near the fixed-bed top. Secondly, the uncertainty of
pyrolysis mechanisms also affects the accuracy of the temperature prediction in the pyrolysis
52
section. Considering the possible variation of MSW composition with time and area, the
disparities between predicted and measured results are acceptable.
8
Measured gas temperature
Reactor height y (m)
7
Predicted gas temperature
6
Predicted solid temperature
5
4
3
2
1
0
0
500
1000
1500
2000
2500
T (K)
Figure 24. Temperature distribution along the shaft height of the base case 1
Table 10. Syngas yield and compositions for the base case 1
Syngas
Predicted
Measured
Deviation
H2
Vol% (wet basis)
19.19
19.50
-0.016
CO
Vol% (wet basis)
17.21
15.20
0.132
LHCs
Vol% (wet basis)
7.22
6.90
0.046
Incombustible gases
Vol% (wet basis)
56.68
58.40
-0.029
1.062
1.063
-0.001
Nm3/kg MSW
Syngas yield
(wet basis)
53
Table 10 shows a comparison of predicted and measured syngas yields and composition for
the base case. It can be seen that the predicted yields and compositions of syngas are also in
good agreement with the measurements despite of an acceptable deviation related to CO. The
model slightly overestimates the CO volume fraction with the deviation equal to 0.132. It is
believed that this deviation is mainly caused by the overestimation of peak temperature due to
disregarding partial melting in the fixed-bed. Generally, the deviations of the predicted results
are in acceptable level for understanding the characteristics of PMG process.
4.3.1.2 Temperature profiles
The distribution of gas temperature in the base case is shown in Figure 25. It is found that
plasma air temperature reduces rapidly due to radiation and heat exchange with unmelted
inorganics. During this process, the plasma air also mixes with secondary air. The average gas
temperature at the gas-bed boundary is about 1800 K. When air flows into the fixed-bed, gas
temperature increases dramatically to around 2400 K due to char combustion. Then, gas
temperature rapidly decreases to around 1000K. This decrement can be explained by intense
heat exchange between phases and endothermic char gasification. Since the gasification agent
used in this case is air, the main char gasification here should be the boudouard reaction.
When gas temperature reaches 1000K, the temperature decreasing rate starts to slowdown
gradually. In this zone, the boudouard reaction generally stops. The heat transfer between gas
and solid phase also becomes slow due to the decrease of temperature differences (see Figure
24). At the reactor height 5.0-6.1 m, where pyrolysis and drying of MSW take place, gas
temperature starts to decrease visibly again from around 860K to 450K. After flowing out of
the fixed-bed area, no reaction or heat exchange happens for gases, so that the gas temperature
nearly keeps constant.
54
Figure 25. Gas temperature distribution (K) in the base case 1
4.3.1.3 Nonuniformity of temperature distributions in horizontal sections
In the PGM reactor, the temperature distribution in a horizontal section is not uniform. This
nonuniformity can be reflected from Figure 25.
Figure 26 shows detailed gas temperature distributions at different horizontal sections in the
base case. The nonuniformity of gas temperature is the most significant at the y=1.0 m section,
where the gas temperature varies from 1430 to 2080 K. The peak temperature in this section
appears at 0.40 < x < 0.55 m area, which is corresponding to the horizontal position of gasbed interface at the y=1.0 m section. The position of peak temperature denotes that char
combustion only occurs in a thin layer near the gas-bed interface. From engineering point of
view, high peak temperature should be prevented since it causes problems such as bridging
and damage of reactor wall. In order to prevent the problems caused by high peak temperature,
the intensity of char combustion have to be restrict the by controlling the ER value.
55
The temperature distribution in the y=2.0 m section shows a similar trend to the y=1.0 m
section. However, the difference between shaft axis temperature and peak temperature
dramatically decreases to about 150 K. It denotes that the nonuniformity of gas temperature
becomes weak with increasing height due to horizontal heat transfer. In the y=3.0 m and
y=4.0 m sections, the differences between axis temperature and peak temperature are not
visible. In all these four sections, the temperature decline near the reactor wall is caused by
heat loss from the reactor wall.
2200
y=1.0 (m)
y=1.5 (m)
y=2.0 (m)
y=4.0 (m)
2000
Tg (K)
1800
1600
1400
1200
1000
800
600
0
0.1
0.2
0.3
0.4
0.5
0.6
Horizontal distance from the shaft axis x (m)
Figure 26 Gas temperature distributions in different horizontal sections in the base case 1
56
4.3.1.4 Composition profiles
Figure 27 Syngas compositions of the base case 1, (a) molar fraction of CO, (b) molar fraction of
H2, (c) molar fraction of LHCs, (d) molar fraction of CO2, (e) molar fraction of H2O, (f) mass
fraction of tar
Figure 27 (a) – (e) shows the volume fractions of CO, H 2 , LHCs, CO 2 and H 2 O in the gas
phase. Since only air is used as gasification agent in this work, the water-gas reaction and
water-gas shift reaction are restrained. H 2 can only be produced from the pyrolysis step. This
phenomenon is well presented in Figure 27 (a). A similar trend is also found for LHCs. CO is
generated from both char combustion and pyrolysis. As we can see in Figure 27 (c), the
volume fraction of CO reaches about 18% after heterogeneous char reactions. The volume
fraction of CO does not change much during pyrolysis. However, the yield of CO from
pyrolysis is still remarkable since the gas volume increases significantly during pyrolysis.
A significant of the PGM technology is that it produces a high quality syngas. As we can see
in Figure 27, the volume fractions of CO and H 2 reaches around 20% at the syngas outlet, and
the volume fraction of LHCs is about 7%. The lower heating value (LHV) of the wet syngas
reaches about 6.79 MJ/Nm3 in the base case, which is a very high value for MSW gasification.
57
It is believed that the high LHV value is mainly due to low ER value in the PGM process,
which prevents the direct dilution of combustible gases from N 2 . Low ER also provides a
substoichiometric O 2 environment, which suppress the formation of CO 2 .
Tar yield is one of the main problems involved in the fixed-bed gasification, which reduces
the energy efficiency and causes blockage to the pipeline of syngas. The mass fraction of tar
in the gas phase is demonstrated in Figure 27 (f). The tar mass fraction at the syngas outlet is
about 16.8%, which reflects a tar yield ratio of 0.193 kg/kg MSW.
4.3.2 Influence of ER
The ER is one of the most important operation parameters of gasification. It determines the
level of MSW partial combustion, and directly influences the temperature profile, syngas
composition and stability of the gasification process. The ER required for a typical PGM air
gasification varies from 0.05 to 0.10, while the ER for conventional gasification is about 0.3.
Few scientific works has been found on the characteristics of gasification in low ER
conditions. Studying the influence of ER on the performance of a PGM gasifier is of both
scientific and engineering values.
In this study, a group of cases with different ER values are simulated. The ER value varies
from 0.043 to 0.077. The PER values for all cases are set as 0.118.
4.3.2.1 Gas temperature distribution
Figure 28 shows the predicted gas temperature distributions at the shaft axis with different ER
values. It can be found that the gas temperature shows an increasing trend with ER. This
phenomenon is more significant in the lower part of the reaction shaft, where the pear
temperature increases from 1250 K to 2750 K. The temperature increase with ER is explained
by prompted char combustion due to increases O 2 flow rate. According to chemical
equilibrium calculation, for 100% conversion of carbon in char, the ER value should be about
0.13, which is much higher than the ER values in the simulated cases. No doubt that the
increasing trend of gas temperature will continue if the ER keeps increasing. However, in
order to restrict the peak temperature under 2273 K, the ER value in PGM air gasification
58
should be controlled less than 0.067. This may results in insufficient combustion of char,
which leads to low energy efficiency.
Figure 28. Temperature distribution along the shaft height for different ER values
4.3.2.2 Syngas composition
Figure 29 shows the variation of syngas composition, as well as the tar-MSW mass ratio with
ER value. It is found that when ER increases, the volume fractions of H 2 , LHCs and CO 2
decrease, and the volume fraction of CO increases. The increasing of CO volume fraction can
be explained by prompted char combustion with increasing ER, while the decreasing of H 2
and LHCs volume fractions is explained by dilution of syngas by introduced N 2 . It is
interesting to find that the CO 2 volume fraction also decrease when ER increases. This
phenomenon may be caused by increasing combustion temperature with ER, which prevents
the formation of CO 2 during char combustion. Moreover, the tar-MSW mass ratio is also
increasing slightly with ER. This increasing is the result of increasing heating rate with ER in
the pyrolysis zone.
59
Syngas composition (vol. %,
wet basis)
20
0.19
15
0.18
10
0.17
5
0
Tar-MSW mass ratio
0.2
25
0.16
0.04
0.05
0.06
0.07
0.08
ER
CO
H2
LHCs
CO2
tar
Figure 29. Predicted Temperature distributions for different ER
4.3.2.3 Energy conversion ratio
In order to quantify the energy conversion from MSW to syngas, the energy conversion ratio
(ECR) was defined and used:
ECR =
M H 2 ⋅ LHVH 2 + M CO ⋅ LHVCO + M LHC ⋅ LHVLHC
× 100%
⋅ LHV
+P
M
MSW
MSW
(4-7)
pla
The ECR is a very important process parameter which characterizes the combustion value of
the gas phase. It illustrates the variation of syngas composition during the gasification process,
and can be used as an index for the gas quality. The ECR value at the syngas outlet is the cold
gas efficiency (CGE).
60
Figure 30. ECR values along the shaft height for different ER values
Figure 30 shows the ECR value in the horizontal sections along the shaft height. In all cases,
the energy conversions mainly happen in two sections: char combustion and pyrolysis. It is
found that the ER has a positive effect on energy conversion in the char combustion section.
When ER varies from 0.043 to 0.077, the ECR will increase from 0.02 to about 0.06. No
doubt that this increasing is caused by prompted char combustion due to increasing O 2 . The
increasing of gas temperature with ER also has a positive effect on energy conversion since it
pushes reaction (20) to produce more CO rather than CO 2 .
Volatiles take up to 77.6% of the total MSW mass. Most of the energy conversion happens in
the pyrolysis section, which is corresponding to the shaft height 4.5-5.5 m in the reactor. Only
a slight negative effect on energy conversion is found for ER. The proper reason is that the
enhanced heating rate caused by increasing ER, which results in an increasing tar yield. The
increasing of tar yield has been demonstrated in Figure 29.
Since the influence of ER on ECR is more significant in the char combustion section, it is
possible to increase the system CGE by increasing ER. However, as discussed previously, the
increasing of ER is restricted by peak temperature. The ER value in PGM air gasification
should be lower than 0.067. A practical solution to this problem is to inject additional steam
into the reactor. The numerical study on air&steam gasification in PGM reactor will be
presented in the future.
61
4.3.3 Influence of PER
The most important significance of the PGM process is the high-temperature plasma air
injected from the bottom of the reactor. The high-temperature plasma flow supplies heat for
both gasification residual melting and reactions related to gasification process. The value of
PER may directly influence the temperature profile, syngas composition, tar yield and
stability of the gasification process. In this work, the influence of PER is investigated. The
value of PER varies from 0.098 to 0.138. The ER value for all cases is set as 0.060.
Figure 31. Temperature distributions along the shaft height for different PER
Figure 31 shows the predicted gas temperature distributions at the shaft axis with different
PER values. It was very interesting to find that the temperature distributions for all these cases
are similar. When PER increases from 0.098 to 0.138, the increment of peak temperature
along the shaft axis is less than 200K. A possible explanation for this phenomenon is the heat
loss in the melting chambers. Firstly, intense heat transfer exists between plasma air and slag
since the high-temperature and high-velocity plasma flow was directly injected into the slag
pool which exists at the bottom of the melting chamber. Secondly, the strong heat radiation
leads to large heat loss from the chamber wall. During the running of the pilot reactor, it is
found that heat loss from the chamber wall reaches about 30% of the total plasma power. It is
also found that the heat loss increases with PER value.
62
A thermodynamic calculation is done by authors to estimate the lower limit of PER to satisfy
the heat request for melting the inorganic components. The result shows that when the PER
value is larger than 0.09, the plasma flow can supply enough heat for the melting process.
From the view point of energy efficiency, the optimal PER value for PGM air gasification
should be about 0.09.
4.4 CFD results of air and steam gasification
4.4.1 Model validation
The simulated results were evaluated by comparison with measured results from the base case
2. The results are shown in Table 11. Generally, the predicted yield and composition of
syngas are in agreement with the measurements. However, a non-ignorable deviation exists
between predicted and measured CO. Meanwhile, an underestimation is found for CO 2
content. It is believed by authors that the deviation is mainly caused by overestimation of
fixed-bed peak temperature due to disregarding the melting in the fixed-bed. According to
previous researchers, melting of inorganic components in MSW starts when the solid
temperature reaches around 1800 K. The melting process is a highly endothermic, so that
further increase of solid temperature can be restrained. However, the possible melting in the
fixed-bed is not considered in the model, so the peak temperature may be overestimated. The
overestimation of solid temperature therefore influences the yield of char combustion, thus
overestimating the CO content in syngas. Despite the deviation between simulated and
measured results, the accuracy of this model is acceptable for analyzing the characters of air
and steam gasification in the PGM reactor.
Table 11. Measured and predicted syngas yield and main compositions of the base case 2
Syngas
Unit
Predicted
Measured
Deviation
H2
Vol% (wet basis)
19.49
20.44
-0.046
CO
Vol% (wet basis)
19.21
16.10
-0.193
LHCs (light hydrocarbons)
Vol% (wet basis)
6.79
7.42
-0.085
Vol% (wet basis)
6.59
>10.0
-
1.368
1.359
-0.006
CO 2
Syngas yield
3
Nm /kg MSW (wet basis)
63
4.4.2 Effect of S/F
The gas temperature distribution at various S/F values when ER=0.06 and PER=0.118 is
shown in Figure 32. When S/F increases from 0 to 0.25, the temperature distribution along the
reaction shaft becomes more uniform. Meanwhile, the area of char reaction zone, where the
gas temperature is above 1000 K, is increasing. Significant advantages are obtained from
these variations: firstly, the uniformity of gas temperature prevents the formation of very high
temperature, which challenges the heat resistance of wall materials; secondly, the increase of
char reaction zone increases the reaction time of gasification agents with char. Another
advantage of increasing S/F is that increased steam feeding rate enhances the rate of watershift reaction, which is an important char gasification reaction.
Figure 32. Predicted gas temperature (K) distributions for different S/F values
In order to characterize the conversion of char, the char conversion efficiency η C is defined as
the percentage of carbon in the MSW converted into gas species. The energy efficiency of
PGM is represented by cold gas efficiencyη .
The effects of S/F on η C and η are indicated in Figure 33. It is found that steam injection has
a notable positive effect on both η C and η . When steam is not injected, the value of η C is only
about 23%, which is far from complete gasification of char. When S/F varies from 0 to 0.208,
the value of ηC increases dramatically from 22% to 96%. Further increase of S/F from 0.208
to 0.250, however has very limited effect on η C . It is known that the incomplete conversion of
char is disadvantageous for gasification since it reduces the cold gas efficiencyη . It is found
64
that the variation of η with S/F has similar trends to that of η C , which implies that the
enhance of ηC with S/F is the main cause for η variation. From this point of view, the point
S/F=0.208 is a critical point or optimizing of the air and steam gasification of a PGM reactor.
Figure 33. Effect of S/F on η C and η at ER= 0.06 and PER= 0.118
Figure 34 shows the contents of main gaseous species inside the reactor at different S/F
values. When S/F increases from 0 to 0.208, the volume fractions of H2 and CO generally
show an increasing trend, especially at the bottom half of the reaction shaft where char
gasification reactions take place. This is mainly caused by promoted water-shaft reaction and
other char reactions due to increasing steam injection. When S/F further increases from 0.208
to 0.25, the volume fractions of CO seems decreasing. This phenomenon corresponds to the
variation of ηC with S/F. Since char conversion almost completes at S/F=0.208, further
increasing of S/F mainly promoted the water-gas shift reaction so the total yield of CO is
reduced. It is also found that most of the Light hydrocarbons (LHCs) are produced in the
pyrolysis section, while the effect of methanation reaction is not visible. The explanation of
this phenomenon may be the relatively high temperature in the gasification section which
accurate the reforming of LHCs. Finally, it is found that the overall tar yield shows a
decreasing trend with increasing S/F. this is mainly due to favored tar cracking and reforming
due to higher gas temperature in the pyrolysis section.
65
Figure 34. Predicted contents of main species in gas phase for different S/F values. (a) H2 volume
fractions, (b) CO volume fractions, (c)LHCs volume fractions, (d) tar mass fractions
66
4.4.3 Effect of ER
In this work, the effect of ER on air and steam gasification in the PGM reactor is studied at
S/F= 0.167 and PER= 0.118 condition.
Figure 35 demonstrates the gas temperature
distributions at three typical ER values. It is found that increase of ER has a positive effect on
both overall temperature and peak temperature inside the reactor. The increasing of gas
temperature is the results of favored char combustion. It is known that increasing of
gasification temperature is favorable since it accelerates reaction rates, and influences the
energy equilibrium of endothermic gasification reactions. However, a high peak temperature
may challenge the hear resistance of wall materials. Moreover, the bridging problem may
happen at high temperature condition since part of the inorganic component of MSW may be
melted. When ER increases from 0.043 to 0.077, the value of peak gas temperature increases
from 2100 K to about 2500 K. Even after taking into account the overestimation of peak
temperature with the model, the peak temperature at ER=0.077 is still too high for practical
running of the PGM reactor.
Figure 35. Predicted gas temperature (K) distributions for different ER values
Figure 36 shows the variation of ηC with different ER values. The ηC increases all the way
with ER, and reaches about 100% at ER=0.08. This phenomenon can be explained by two
reasons. Firstly, the enhanced char combustion by increased ER directly favors char
conversion. Moreover, char combustion increases the global temperature inside the reactor,
thus accelerates the endothermic char gasification reactions such as water-shift reaction and
boudouard reaction. From this point of view, complete char conversion thus the highest cold
gas efficiency can be obtained at ER value of 0.077. However, considering the high peak
temperature at ER= 0.77, it is not suggested to use such high ER value. In real operation, it is
67
more applicable to use a relative low ER value like 0.06, while increase the S/F to increase the
ηC .
Figure 36 Effect of ER on η C at S/F= 0.167 and PER= 0.118
Figure 37 shows the contents of main gaseous species inside the reactor at different ER
values. It is shown that the CO volume fraction increases evidently with ER. The increase of
CO content is explained by enhanced char combustion due to increasing ER. The total yield
of H2 is also enhanced by favored water-shift reaction due to temperature increase. However,
this positive effect is counteracted by the dilution from N2 due to enhanced ER. As a result,
the final volume fraction of H2 does not change much with ER. The yield of tar is sensitive to
the temperature in the pyrolysis section. As we can see in Figure 37 (d), the mass fraction of
tar reduces visible when ER increases. Cracking and reforming of tar also produces
combustible gases, thus increasing the η value. This is another positive effect of increasing
ER.
68
Figure 37. Predicted contents of main species in gas phase for different ER values. (a) H2 volume
fractions, (b) CO volume fractions, (c)LHCs volume fractions, (d) tar mass fractions
69
4.4.4 Effect of PER
The high-temperature plasma air injection is the most important significance of the PGM
process. Other than supplying heat for the melting of the inorganic component of MSW, the
plasma injection also preheats gasification agent to around 1700 K, thus influence the energy
balance inside the PGM reactor. The effect of PER value on gas temperature at ER=0.06 and
S/F=0.167 is shown in Figure 38. When PER increases from 0.108 to 0.128, the gas
temperature only increases slightly. This phenomenon can be explained by two reasons.
Firstly, the plasma flow is injected directly into the slag pool at the bottom of the melting
chamber. The outward slag flow take away much of increased sensible heat from plasma.
Secondly, heat loss from strong radiation in the melting chamber also increase with PER
value. As a result, only a small part of the increased plasma energy is introduced to the fixedbed.
Figure 38. Predicted gas temperature (K) distributions for different PER values
Figure 39 is the contents of main gaseous species inside the reactor at different PER values.
With the increase of PER, both H2 and CO shows a slight increasing trend. As introduced
previously, the enhancement of gas temperature favors char gasification reactions and also
cracking and reforming of tar. However, this positive effect is also not significant.
70
Figure 39. Predicted contents of main species in gas phase for different PER values. (a) H2
volume fractions, (b) CO volume fractions, (c) LHCs volume fractions, (d) tar mass fractions
71
4.5 Optimizing of the PGM process
4.5.1 Interactions between ER and PER
In the PGM process, the required heat for MSW gasification comes from two sources: the
sensible heat of plasma air and chemical heat from char combustion. In other words, the
energy equilibrium of PGM gasification is controlled by both PER and ER. From this point of
view, the effects of PER and ER are connected to each other. When study the energy
equilibrium of the PGM process, the interaction between PER and ER should be considered.
The SAMR value was set to 0.389 in this study.
Figure 40. Definition of possible operation extent of PER and ER in the PGM process
Figure 40 shows the delimitation of possible operation extent of PER and ER in the PGM
process. Three curves are defined to restrict the logical area for PGM:
•
ERpla, min shows the minimum of ER requested for generating plasma flow. In PGM
process, air is used as the carrier of sensible heat from plasma generators. The
relationship between PER and ERpla, min is linear. The gradient of the ERpla, min
denotes the ratio between MSW LHV and the thermal enthalpy of plasma air:
k = (m air / m MSW )stoic
LHVMSW
h pla
(4-8)
72
ERgasif, min shows the ER needed for complete gasification (i.e. no solid carbon
residual and enough temperature for gasification and pyrolysis). In this work, the
request for complete gasification is satisfied when the syngas temperature at the outlet
is higher than 120 ºC.
•
ERtem, max shows the maximum of ER to prevent too high temperature in the char
combustion and gasification section. If this temperature is too high, the wall material
of the reactor might be damaged. In this study, the maximum of the temperature is set
to 1300 ºC.
•
PERmel, min shows the minimum of PER required for melting all the solid residual.
Four different regions are divided by these curves:
•
Region 1: In this region, the PGM process can operate normally. The energy supplied
by plasma and char combustion is enough for MSW gasification to take place. The
temperature in the gasification and combustion zone is not too high to damage the
reactor wall.
•
Region 2: In this region, the energy supplied by plasma, char combustion and High
temperature steam is not enough for supporting MSW gasification.
•
Region 3: In this region, the temperature of the char combustion and gasification
section is higher than 1300 ºC. In other words, the temperature in char combustion and
gasification section may damage the reactor wall.
•
Region 4: In this region, the energy supplied by plasma flow is not enough for melting
of solid residual from MSW gasification.
It can be found from Figure 40 that when PER is less than 0.045, the plasma energy is not
enough for entirely melting of inorganic components in MSW. When PER increases from
0.045 to 0.13, the energy require for inorganic components melting is satisfied. The extent of
available ER is limited by ERtem, max and ERgasif, min. In other words, the minimum of available
ER is restricted by entire energy supply, and the maximum of available ER is controlled by
gasification and combustion temperature. When PER further increases from 0.13 to 0.14, the
lower limit of ER does not exist anymore, which means the energy supply is enough for PGM
73
even the secondary air feeding is set to 0. If PER is higher than 0.14, the PGM is not available
because the temperature at the char gasification and combustion section is too high. Generally
speaking, the available PER extent is 0.045-0.14. Increase of PER narrows the variation range
of ER.
Figure 41. Distributions of syngas LHV in Region 1
Figure 42. Distributions of system CGE in Region 1.
74
The distribution of syngas LHV, as well as system CGE in region 1 is demonstrated in Figure
41 and Figure 42. It was found that the maximum syngas LHV in region 1 is about 9.5, while
the minimum is about 4.0. It has been discussed previously that the LHV variation is mainly
caused by thermal cracking of primary tar. The large difference between maximum and
minimum syngas LHV illustrates that the extent of tar cracking is a very important factor
which determines the quality of syngas in PGM process. Furthermore, it is obvious that the
effect of PER on syngas LHV is stronger than that of ER. The positive effect of ER on syngas
LHV is due to promoted primary tar cracking caused by chemical heat from combustion.
However, the ER still have some negative effects on syngas LHV. For example, increased
combustion by increasing ER consumes some combustible gases in syngas. Additionally, the
introduced N2 also dilutes the contents of combustible gases. These negative effects somehow
weaken the positive effect of ER. So the maximum LHV was found in the area with highest
PER value. The dependence of LHV on ER and PER has been confirmed by previous running
of the pilot PGM reactor.
From Figure 42 it was found that the maximum CGE in region 1 is about 0.62 and the
minimum is about 0.22. The maximum CGE appears when ER=0.08 and PER=0.10. The
large difference of CGE is also explained by the influence of the extent of tar cracking. The
influences of PER and ER on CGE have similar intensity. An interesting phenomenon found
in Figure 42 is that the effects of ER and PER on CGE shows a linear relation. It implies that
the influence of ER and PER can be further synthesized to a unified parameter. The further
correlation of ER and PER can be an interesting topic of our future work.
4.5.2 Considering the oxygen equilibrium
Steam and air are two popular gasification agents which supply oxygen for the gasification
process. As the material base of gasification, the oxygen supply directly influence the
conversion of C during gasification and combustion section. From this perspective, the ER
and SAMR may also have internal connecting with each other.
Figure 43 shows the delimitation of possible operation extent of SAMR and ER in the PGM
process at PER =0.118. Three curves are used to restrict the possible operation conditions for
SAMR and ER: ERpla, min, ERgasif, min, and ERtem, max.
75
Figure 43. Delimitation of possible operation extent of SAMR and ER in the PGM process
These curves defined 3 main regions with different operation conditions: In region 1’, the
PGM process can work continuously; in region 2’, the energy supplied by plasma and char
combustion is not enough for MSW gasification; in region 3’, the temperature of the char
combustion and gasification section is too high. It was found that when SAMR increases, the
maximum of possible ER increases and the minimum of possible ER in region 1’ decreases.
Increase of SAMR means enhanced oxygen supply from steam. In that case, the oxygen
equilibrium in the reactor is affected, and the requested air decreases. The increase of
maximum ER can be explained by the increases of total heat capacity with increasing SAMR,
which increases the uniformity of temperature distribution inside the reactor. This uniformity
is also beneficial to syngas LHV because the temperature difference between gasification and
pyrolysis will be reduced.
76
Figure 44. Distributions of syngas LHV in Region 1’
The distribution of syngas LHV in region 1’ is demonstrated in Figure 44. It was found that
the syngas LHV in region 1’ varies from 6.5 to 9.0 MJ/Nm3. The increase of SAMR has
positive effects on syngas LHV. This positive effect may be mainly due to the high
temperature of steam, which also introduce some heat into the PGM system. At the same
time, the decreased temperature difference between gasification and pyrolysis section by
increasing SAMR enhances the potential of LHV increase by larger energy supply. An
interesting phenomenon found in Figure 44 is that the effect of increasing ER on syngas LHV
changes when SAMR is larger than 0.55. In this area, the LHV first increase, and then start to
decrease when ER keep increasing. The maximum of LHV appears at about ER=0.055. This
result illustrate that the positive aspect of ER effect by increasing chemical heat is not always
dominant. The negative aspects such as consumption of combustible gas and dilution from N2
play important roles in high SAMR condition. The suggested ER in high SAMR condition is
0.055.
77
5. Conclusions and recommendations
Experimental tests have been performed to study the performance of air gasification
and air&steam gasification in the PGM reactor. The following are the main discoveries:
•
The syngas produced from the PGM has a high LHV (6–7 MJ/Nm3).
•
In air gasification, the syngas yield increased significantly with increasing ER,
whereas the LHV decreased slightly.
•
Feeding high-temperature steam into the PGM reactor greatly increased syngas yield,
with even higher gas LHV. The feeding of high-temperature steam can further reduce
the air demand for gasification.
•
The energy efficiency of air and steam gasification was much higher than that of air
gasification. The CGE of PGM air and steam gasification can reach approximately
60%. Tar formation represents the main energy loss for the PGM reactor.
A zero-dimensional kinetics-free gasification model was developed. The accuracy of this
model is confirmed by the measurements from the tests. The influence of operation
parameters are studied with this model:
•
The performance of PGM reactors with high-temperature steam feeding is analyzed by
both test measurement and model prediction. The effects of three dimensionless
operation parameters are discussed. PER has positive effect for both syngas yield and
syngas LHV. The main reason for this effect is the favored tar cracking by increasing
heat supply.
•
The ER has two contradictory effects on syngas LHV: the positive effect by increasing
chemical heat and the negative effect by syngas combustion and N2 dilution. When ER
is lower than 0.065, the positive effect is dominant; When ER is larger than 0.065, two
effects counterbalance each other. The effect of ER on CGE is positive in the studied
region.
78
•
The SAMR mainly influence the equilibrium of water-gas shift reaction in the PGM
process. Steam at 1000 ºC can supply some heat for pyrolysis, so the SAMR also have
slight positive effect on syngas yield and LHV.
A two-dimensional Eulerian-Eulerian multiphase model was also introduced in this work.
This model was proved to be good enough for prediction the performance of the PGM, when
air or air&steam mixtures are used as gasification agents.
For air gasification:
•
Analysis of the base case 1 by means of CFD revealed that the horizontal temperature
distribution inside the reactor was non-uniform. In addition, maximum peak
temperature of the reactor was observed at the gas-solid interface. PGM air
gasification produced a syngas with a LHV of 6.79MJ/Nm3. The tar yield is around
0.193 kg/kg MSW.
•
Further investigation of the PGM process by means of developed model revealed that
ER has positive influence on the calorific value of the syngas. Increase of ER from
0.043 to 0.077 showed around 5% increase in cold gas efficiency. However, the
maximum allowable ER for present gasification system was restricted to about 0.067
due to increase in peak temperature of the reactor.
•
The influence of PER on PGM air gasification is not obvious. The optimal PER value
was considered as about 0.09 considering energy efficiency.
•
Although PGM air gasification provided good calorific value of the syngas
(LHV=6.79MJ/Nm3) , detrimental effect on char conversion was observed.
Minimization of this problem will be addressed in our future research.
For air & steam gasification:
•
Injection of high temperature steam has a positive effect on both syngas LHV value
and reactor cold gas efficiency. The main reason is that high temperature steam
supplies both oxygen atoms and sensible heat for char gasification, so that the char
convention ratio is highly enhanced. At the studied condition, the positive effect of
79
increasing S/F value is significant when S / F ≤ 0.208 . When S / F ≥ 0.208 , the effect
becomes very limited.
•
The value of ER influences both chemical and energy balance inside the reactor.
Increasing ER promotes both the char combustion and water-gas reaction. Thus
increasing char conversion. At the studied condition, a theoretical maximum of cold
gas efficiency can be obtained at ER= 0.077, which corresponds to complete char
conversion ratio. However, this maximum value cannot be reached in reality since the
peak temperature at this condition is too high. An optimal ER value should be around
0.6 in reality.
•
Increasing the plasma power also has a slight positive effect on syngas yield and LHV
value. However, the influence of PER is weaker than that of ER and S/F. From
economic point of view, the PER should be chosen as the minimum value which
satisfies the energy request for melting the inorganics of MSW.
Some optimizing work was done based on the proposed models:
•
The available extent of PER and ER is defined at air/steam gasification conditions.
•
The possible range for PER at the studied condition is 0.045-0.14. Increase of PER
narrows the variation range of ER. The optimal syngas LHV can be obtained when the
PER reaches its maximum. The effect of ER and PER on syngas CGE seems can be
synthesized to a unified parameter.
•
The available extent of SAMR and ER is defined at PER=0.118. Increasing SAMR
broadens the available range of ER. When SAMR>0.6, the secondary air is not
necessary anymore. The optimal syngas LHV can be obtained at SAMR=0.8 and
ER=0.055.
80
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