Subscriber access provided by CORNELL UNIVERSITY LIBRARY
Article
Pyrolysis and combustion of typical wastes in a newly designed macro-TGA: characteristics and simulation by model components Yanqiu Long, Aihong Meng, Shen Chen, Hui Zhou, Yanguo Zhang, and Qinghai Li Energy Fuels, Just Accepted Manuscript • Publication Date (Web): 25 May 2017 Downloaded from http://pubs.acs.org on May 25, 2017
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Energy & Fuels is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
Page 1 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
1
Pyrolysis and combustion of typical wastes in a newly designed
2
macro-TGA: characteristics and simulation by model components
3
Yanqiu Longa, Aihong Menga, Shen Chena, Hui Zhoub, Yanguo Zhanga,1, Qinghai Lia
4
a
5
Department of Thermal Engineering, Tsinghua University, Beijing 100084, P.R. China b
6 7
Key Laboratory for Thermal Science and Power Engineering of Ministry of Education,
Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA
8
Abstract
9
The pyrolysis and combustion characteristics of three biomass and five model components in a newly
10
designed macro thermogravimetric analyzer (macro-TGA) were compared, respectively. The
11
comparison of model components combustion in TGA and macro-TGA was conducted, too. The
12
results showed that the behavior of model components combustion was significantly different between
13
TGA and macro-TGA. In macro-TGA, the maximum peak of DTG curves derived from model
14
components combustion occurred at similar temperature, compared to their pyrolysis; while for
15
biomass, the main peaks appeared earlier in combustion. The biomass could be simulated by main
16
components well both in pyrolysis and combustion in macro-TGA, while five model components
17
(hemicellulose, cellulose, lignin, starch and pectin) simulation fitted the experimental result better than
18
three ones (hemicellulose, cellulose and lignin). However, the fractions differed from each other
19
significantly in different atmosphere simulation.
20
Keywords: Pyrolysis; combustion; simulation; macro-TGA; model components.
1. Introduction
21 22
Solid waste, including biomass and municipal solid waste (MSW), has been used as renewable
23
fuels in power or heat generation. Combustion, pyrolysis and gasification were the main thermal
24
processes in utilities. Pyrolysis was thought of the fundamental process of thermochemical utilities. 1
Corresponding author: TEL:+86-10-62783373, FAX:+86-10-6279-8047, E-mail:
[email protected] 1
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
25
Char, tar and combustible gases are the main products of pyrolysis, which might lead to quick soiling
26
in industrial processes [1]. Oxidative pyrolysis especially combustion would reduce char and tar
27
leading to much more energy intensive products. Generally speaking, hemicellulose accounts for
28
16-23%, cellulose accounts for 42-49%, and lignin accounts for 21-39% of biomass [2]. The other
29
components, such as pectins, starches, nucleic acids and minerals [3] are normally omitted or
30
ignorable for less fraction or complication. Many researchers have studied biomass pyrolysis and
31
combustion based on the three main components of biomass [4-15], in which thermogravimetric
32
analysis (TGA) is the most commonly applied technique, and through it, the continuous mass loss
33
characteristics of samples could be obtained by TGA to understand their pyrolysis or combustion
34
mechanisms. However, the mass of each sample in TGA is normally less than 20 mg. While MSW is
35
normally very complicated and uneven distribution in their components and shapes [16, 17], it’s
36
difficult to keep consistent samples in different experiments in such a small quantity of samples. Due
37
to the limited sample mass, studies on pyrolysis and combustion behavior or their impact factors were
38
also conducted on fixed bed reactor with a greater mass of samples [6, 18-20].
39
As well known, municipal solid waste (MSW) is a complicated mixture of food residue, paper,
40
plastics and some other components. Even though there was much research about MSW and biomass
41
waste, it is difficult to get universal principles in waste utilities research and design. Due to the
42
complicated properties of waste, it is huge challenging to investigate all real waste, so we aimed to
43
establish a pseudo-components simulation system of MSW, in which the behavior of a single MSW
44
sample or MSW mixtures could be simulated by main components based on TG curves, because DTG
45
curves are much more sensitive than TG curves to amplify the changes in the TG curves to highlight
46
the differences between different experiments. Through the pseudo-components simulation system,
47
the thermal behavior of complicated MSW or mixtures could be predicted. To obtain well repeated
48
results for samples or their mixture, we developed a fixed-bed reactor system with real-time weight
49
function as macro-TGA [21, 22]. The mass of a sample in macro-TGA could be 0.5-4 g, which allows
50
us to investigate thermal degradation behavior of real MSW samples or its mixture by a similar way as
51
TGA. To get more fundamental data for the simulation system and further research in thermal
2
ACS Paragon Plus Environment
Page 2 of 18
Page 3 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
52
treatment of MSW, studies including pyrolysis, combustion and CO2 gasification of individual
53
components or compounds and their mixtures were conducted.
54
In our earlier studies, we had conducted some research on pyrolysis or gasification of typical
55
waste in TGA [21-24], in which the comparison of pyrolysis in TGA and macro-TGA was conducted,
56
as well as pyrolysis and CO2 gasification of components in macro-TGA [22, 23, 25]. The
57
pseudo-components simulation of three biomass samples had been investigated to check its feasibility
58
of the simulation system in different atmosphere, such as N2 and CO2. In this study, we focused on the
59
comparison of thermal degradation in inert gas and oxidative atmosphere in macro-TGA. Comparison
60
in biomass simulation by five model components (hemicellulose, cellulose, lignin, starch and pectin)
61
and three ones (hemicellulose, cellulose and lignin) was conducted. To deeply understand the
62
combustion behavior of components in macro-TGA, their combustion characteristics in TGA was
63
analyzed and compared.
64 65
2. Materials and methods 2.1 Materials and their characterization
66
Xylan, microcrystalline cellulose and dealkaline lignin were the representation of hemicellulose,
67
cellulose and lignin, respectively. Cellulose, hemicellulose, pectin and starch samples were purchased
68
from Sigma-Aldrich, and lignin samples from Tokyo Chemical Industry (TCI). The real biomass
69
including poplar stem, orange peel and Chinese cabbage were used as feedstock to investigate the
70
simulation of their pyrolysis or combustion by the main components. The samples were prepared in a
71
granular form with a size of less than 150 µm. Before the experiments, all the samples were dried at
72
105 °C for at least 2h. The proximate and ultimate analyses of the samples were shown in Table 1.
73
Table 1 Proximate and ultimate analyses of the samples. Proximate analyses, % Ad Vd FCd 2.11 78.56 19.33
Cellulose
0.00
95.21
Lignin
16.15
Starch
0.14
Samples Hemicellulose
St,daf 0.01
Ultimate analyses, % Cdaf Hdaf Ndaf 39.18 6.32 0.00
Odaf 54.49
4.79
0.01
44.51
6.25
1.29
47.94
54.60
29.25
5.67
63.86
4.45
0.18
25.84
95.20
4.66
0.19
43.83
5.21
0.20
50.57
3
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Pectin Orange peel Chinese cabbage 74
Page 4 of 18
3.38 2.91
74.53 76.49
22.09 20.6
0.16 0.19
44.25 48.73
4.97 5.92
0.48 1.43
50.14 43.73
9.91 7.54
67.60 73.85
22.49 18.61
0.61 0.22
47.48 51.36
5.88 5.89
4.11 1.53
41.92 41.00
Poplar stem d: dry basis; daf: dry and ash free basis; St,daf: total sulfide at dry and ash free basis.
75
As seen in Table 1, the volatile in cellulose and starch is the most and their proximate analyses
76
are similar. It is corresponding to that cellulose and starch has similar components, in which the
77
glucose molecules are linked via β-1-4 linkages and α-1-4 linkages, respectively. The ash and fixed
78
carbon of lignin are the most and the volatile is the least, while those of hemicellulose are between
79
those of cellulose and lignin. The proximate analysis of pectin is close to that of hemicellulose, while
80
its ultimate analysis looks much more like starch and cellulose. Because of deakaline process, the
81
sulfur in lignin is much higher than others. Chinese cabbage shows lowest volatile matter and highest
82
ash in the three real biomasses.
83
2.2 Apparatus of pyrolysis and combustion
84
As shown in Fig. 1 [22], the macro-TGA system includes carrier gas unit, reaction unit and
85
real-time weight unit. The carrier gas comes from high-pressure gas cylinder with two-stage
86
pressure-release valves. In the pyrolysis and combustion of samples, nitrogen and air, respectively, is
87
used as the carrier gas with the flow of 1 NL/min, which is fed from the bottom of the quartz tube to
88
bring out the gas products immediately. The carrier gas is fed to system to be preheated 1 h before the
89
samples feeding.
90
The quartz tube is 1500 mm height with i.d. 60 mm, whose outside is surrounded by the tube
91
heater with 5 kW. The maximum temperature is 1200 oC with the maximum heating rate of 40 °C/min.
92
There are extra zones with 250 mm height of the quartz tube in the top and the bottom out of the
93
heating zone, respectively. The tube heater is monitored by the temperature control & data acquisition
94
unit.
4
ACS Paragon Plus Environment
Page 5 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
95 96 97 98
Energy & Fuels
1–crucible; 2–quartz tube; 3–metal wire; 4–electronic balance; 5–heater; 6–rotameter; 7– high-pressure gas; 8–outlet. Fig. 1. The schematic system of macro-TGA.
99
During the experiments, each of the samples (approximate 1.5 g, except for starch approximate
100
0.5 g) was placed manually in the quartz crucible, which was put in the constant temperature zone of
101
the quartz tube. The quartz crucible is i.d. 30 mm with 30 mm height, and hanged by the metal wire of
102
0.2 mm diameter to the electronic balance. The electronic balance of Metter Toledo ME204E with the
103
maximum weight of 220 g and precision of 0.1 mg, is set on the platform top of the reaction unit and
104
the weight data is real-time acquireded by the data acquisition system.
105
The heating rate was 10 oC/min in all pyrolysis and combustion experiments. Before the
106
experiments, the signal background of empty crucible was carried out. The background signal was
107
subtracted in every experiment, and the real mass was calculated based on the relationship between
108
temperature and weight. The repeated experiments showed that the macro-TGA had good
109
reproducibility.
110
The TGA measurements were performed by a Netzsch STA409C in a gas flow of 100 ml/min of
111
air or N2 and the heating rate was 10 oC/min.
112
2.3 Biomass simulation
5
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 6 of 18
113
Biomass simulation based on the assumption that thermal degradation of a compound or mixture
114
could be simulated by superposition of TG curves of its components. The detailed method was
115
described in our previous studies [14, 22, 26]. Actually, different compounds are consist of different
116
components, not only the five ones, or not all the five ones. Here, the combustion of biomass was
117
simulated by five or three model components to verify this method, and simulation by five
118
components and three components was compared.
119
The weight loss of biomass could be denoted as m(t), representing that the relative mass m was a
120
function of temperature t. Eq. (1) could be derived according to mass conservation as follows:
121
m = ∑ m
i=1,2,…,n
(1)
122
Here, m1, m2, m3 m4 and m5 denoted the hemicellulose mass, cellulose mass, lignin mass, starch
123
mass and pectin mass, respectively. Supposing the interaction among m1, m2, m3 , m4 and m5 could be
124
neglected,the optimal xi was obtained by the least square method using MATLAB calculation based
125
on m and mi. The constraint condition was that the mass fraction sum was 1, i.e.∑ = 1. When
126
simulation by three components was conducted, n=3.
127
To evaluate the overlap ratio of two TG curves, N sets of data were exported from the curves and
128
the overlap ratio was determined as follows [14]:
129
∑N ∆m(t ) area sandwiched by two curves R = 1− = 1− total area N
130 131
132
133
Here,
∆m (t )
(2)
denoted the absolute value of difference of two curves corresponding
temperature.
3. Results and discussion 3.1 Comparison of pyrolysis and combustion characteristics
134
The pyrolysis and combustion characteristics, TG (in wt%) and DTG (in wt%/°C) curves of
135
the components in TGA and macro-TGA were compared in Fig. 2 and Fig. 3, respectively. Almost all
136
volatile matters were separated out and fixed carbons were burned in combustion, corresponding to
6
ACS Paragon Plus Environment
Page 7 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
137
Energy & Fuels
the proximate analyses shown in Table 1.
138
In TGA, compared to pyrolysis, combustion of cellulose, starch and pectin looked like
139
undergoing pyrolysis firstly, then char residue igniting [1, 15, 27], while it was more complicated for
140
hemicellulose and lignin. Combustion of pure cellulose showed that it lost most mass before 500 °C,
141
which was similar to the earlier studies [15, 27]. Pyrolysis and combustion of hemicellulose differed
142
from the prior data reported [15]. It suggested that the xylan samples were much more complicated
143
with random and amorphous structure. D. Shen et al.[15] reported that at higher temperature oxygen
144
enhanced the mass loss of xylan and increased oxygen shifted the DTG peak to lower temperature. It
145
differed from what we observed. The degradation behavior of lignin in the present study also differed
146
distinctly from that showed in [15], in which Organosolv lignin degraded within 600 °C. It was due to
147
different kinds of lignin exhibit different thermal behavior as shown in our earlier pyrolysis
148
investigation [14]. Even though in combustion there were two obvious DTG peaks for two kinds of
149
lignin, it looked like that two significant DTG peaks in lignin pyrolysis compressed at a much narrow
150
temperature zone but were both amplified in combustion in the present study, as Figure 2 showed.
151
Compared to their pyrolysis, there were an additional DTG peak in combustion of starch and pectin,
152
while that of pectin combustion occurred lately at 765 °C. It indicated that the char residue of pectin
153
was more difficult to degrade. Obviously, the presence of oxygen accelerated and enhanced the
154
decomposition of all component samples. However, behavior of samples differed from each other.
155
Except for lignin, the first DTG peak of biomass components combustion occurred earlier or close to
156
that of pyrolysis. All the maximum mass loss rate of combustion increased and the residue decreased
157
as shown in Fig. 2.
7
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
158 159
Fig. 2 The TG/DTG curves of pyrolysis and combustion of biomass components in TGA
160
In comparison of components pyrolysis and combustion in macro-TGA, their first stage of
161
degradation, normally within 400 °C (except of hemicellulose within 300 °C), matched each other
162
well. Two stages were identified in TG curves for all samples combustion in macro-TGA. The first
163
stage of combustion of each component underwent almost the same mass loss as their pyrolysis in TG
164
curves to exhibit similar peak in DTG curves, as shown in Fig. 3. The second stage of combustion
165
appeared to follow pyrolysis, which made the whole combustion process looked like ‘pyrolysis +
166
combustion of the residue formed’ [29]. However, differed from that in TGA, existence of oxygen
167
stimulated the decomposition slowly in macro-TGA so that there was no obvious DTG peak at higher
168
temperature except for starch as shown in Fig. 3. In macro-TGA, except for starch whose combustion
169
almost finished within 600 °C, combustion of all other samples lasted close to 1000 °C. It might be
170
due to less mass of starch and its drastic volumetric expansion during thermal process, which
171
accelerated its reaction to oxygen. An obvious peak exhibited at 485 °C with the mass loss rate of
172
0.35 %/°C when starch combusted in macro-TGA. For other samples, oxygen enhanced the
173
decomposition gradually. For lignin, the peak at around 810 °C was significantly enhanced by oxygen
8
ACS Paragon Plus Environment
Page 8 of 18
Page 9 of 18
174
and the mass loss rate was 0.28 %/°C, which was 0.13 %/°C in pyrolysis. As observed from Fig. 3,
175
decomposition behavior in macro-TGA of cellulose looked like that of starch, except of shorter
176
combustion time for the later, and the maximum DTG peak occurred 35 °C earlier for starch. Similar
177
to this, the exhibition of hemicellulose and pectin looked alike.
40 2 20
60
3
40
2
20
0 0
200
178
400 600 o Temperature ( C)
800
0 1000
1
0 0
200
400 600 o Temperature ( C)
0 1000
800
5
0.8 100
0.6
0.4
40 0.2 20 0 0
179 180
200
400 600 o Temperature ( C)
800
Mass (%)
60
4
3
o
Air
Air
80 Mass loss rate (%/ C)
N2
Starch N2
100
Lignin
80
o
4 Mass (%)
Mass (%)
4
60
Mass Loss Rate (%/ C)
5
Air
80
o
Pectin-air
Hemicellulose N2
60 2
40
1
20 0
0.0 1000
0
200
400 600 Temperature (°C)
800
Mass Loss Rate (%/oC)
Cellulose-air Pectin-N2
80
6 100
6
Mass Loss Rate (%/ C)
Cellulose-N2
100
Mass (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
0 1000
Fig. 3 The TG/DTG curves of pyrolysis and combustion of biomass components in macro-TGA.
181
Differed from what exhibited in TGA, the first DTG peak of all components in combustion
182
occurred at the same temperature or very close to that in pyrolysis in macro-TGA. The residue of all
183
samples was almost ash with the existence of oxygen, corresponding to Table 1.
184
As shown in Fig. 4, all biomass samples in macro-TGA volatilize in a wider temperature than
185
biomass pyrolysis and combustion in TGA [1, 20]. In comparison to their pyrolysis, the first peak of
186
DTG curves appeared 6-11 °C earlier in combustion, as well as the second peak (17-21 °C earlier),
187
and there was an additional significant peak around 800-1000 °C. Chinese cabbage volatilized in a
188
wider range of temperature than other two biomasses in pyrolysis. Differed from components
189
pyrolysis and combustion, real biomass pyrolysis and combustion was affected by its intrinsic
9
ACS Paragon Plus Environment
Energy & Fuels
190
structure, components (e.g. main components, minerals), interactions between components, and many
191
other factors. Chinese cabbage began to decompose at around 200 °C might due to inert moisture
192
evaporation. The first peak of pyrolysis and combustion of orange peel and Chinese cabbage at
193
296-303 °C might attribute to hemicellulose or pectin, while that of poplar stem occurred at
194
330-338 °C might relate to starch. The second peak of pyrolysis or combustion DTG curves of orange
195
peel and poplar stem might relate to cellulose or lignin, while that of Chinese cabbage looked like that
196
of starch. As mentioned above, oxygen shifted the DTG peaks of real biomass to lower temperature, as
197
what happened in TGA [28]. 1.4
Orange peel
Chinese cabbage
1.0
0.6 40 0.4 20
80 Mass (%)
60
Air N2
o
0.8
Mass Loss Rate (%/ C)
Air N2
80 Mass (%)
100
200
198
400 600 o Temperature ( C)
800
1.0 0.8
60
0.6 40
0.4
0.2
20
0.0 1000
0
0.2
0 0
1.2 Mass Loss Rate (%/oC)
1.2 100
0.0 0
200
400 600 Temperature (°C)
800
1000
1.4 Poplar stem Air N2
1.0
o
80
1.2 Mass Loss Rate (%/ C)
100
Mass (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 10 of 18
0.8
60
0.6 40 0.4 20
0.2
0 0
200
400 600 o Temperature ( C)
800
0.0 1000
199 200
Fig. 4 The TG/DTG curves of pyrolysis and combustion of real biomass in macro-TGA.
201
3.2 Comparison of model components combustion in TGA and macro-TGA
202
Pyrolysis of model components in TGA and macro-TGA has been compared and reported in early
203
study [22]. The comparison of components combustion in TGA and macro-TGA was performed, as
204
shown in Fig. 5. All samples began to degrade in TGA earlier than macro-TGA to indicate that there
10
ACS Paragon Plus Environment
Page 11 of 18
205
was heat transfer delay in macro-TGA with or without oxygen [22]. 6 6
Cellulose 5
3
40
Mass (%)
o
80 60
20
2
0
1
20
0 1000
0
-20 0
200
206
400 600 o Temperature ( C)
800
3
40
2 1
0
200
400 600 o Temperature ( C)
800
1.8
5
1.4
60
0.8 40
0.6 0.4
20
Mass (%)
Mass (%)
o
1.2 1.0
60
0
200
207
400 600 o Temperature ( C)
800
4
3
40 2 20 1
0
0.2 0
macro-TGA TGA
80
o
macro-TGA TGA
80
0 1000
Starch
100
1.6
Lignin
Mass loss rate (%/ C)
100
4
o
macro-TGA TGA
Mass Loss Rate (%/ C)
4
60 Mass (%)
Hemicellulose 5
Mass loss rate (%/ C)
macro-TGA TGA
80
100
Mass Loss Rate (%/ C)
100
0.0 1000
-20 0
200
400 600 Temperature (°C)
800
0 1000
7 Pectin
6
macro-TGA TGA
5
o
80
Mass Loss Rate (%/ C)
100
Mass (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
4
60
3 40 2 20
1
0 0
200
400 600 o Temperature ( C)
800
0 1000
208 209
Fig. 5 The TG/DTG curves of combustion of biomass components in TGA and macro-TGA.
210
The residue of combustion in macro-TGA was less than that in TGA to indicate their combustion
211
completed deeply, as Table 2 showed. As shown in Fig. 5, similar to their pyrolysis [22], with the
212
existence of oxygen, the DTG peaks in macro-TGA were also shifted to higher temperature in
213
comparison to those in TGA, while the shape of DTG curves of hemicellulose and lignin differed
214
significantly between macro-TGA and TGA. For cellulose, combustion in TGA finished within 600 °C
11
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 12 of 18
215
and the maximum mass loss rate of 3.791 %/°C appeared at 328 °C; while that in macro-TGA took
216
place at the whole experiment and the maximum delayed approximate 60 °C. The delay was due to
217
heat transfer, alike to pyrolysis. Even though there was thermal clustering to inhibit the degradation of
218
the first stage for cellulose, oxygen exhibited stronger promotion on its ignition and combustion. For
219
hemicellulose, it took similar time to burn out in TGA and macro-TGA, but TG curve from TGA could
220
be regarded as several segments according to its slope. Besides a shoulder peak around 250 °C, there
221
were both two obvious peaks for lignin combustion in TGA and macro-TGA. But it took short time to
222
burn out for lignin in TGA to indicate oxygen promoted lignin degradation dramatically. The starch
223
degradation was shifted to higher temperature from TGA to macro-TGA; however, the char
224
combustion stage was promoted and accelerated in macro-TGA. Oxygen also promoted the
225
degradation of pectin in macro-TGA, but it looked like that char was ignited and burnt suddenly at
226
720-780 °C in TGA.
227
Table 2 The DTG characteristics and residue of model components combustion. Sample
DTG1 o
(wt%/ C)
TGA macro-TGA TGA Hemicellulose macro-TGA TGA Lignin macro-TGA TGA Starch macro-TGA TGA Pectin macro-TGA As mentioned in early study Cellulose
228
App.
T1(oC)
DTG2 o
(wt%/ C)
T2(oC)
3.791 328 0.102 1.852 387 0.069 0.673 246 0.663 3.592 300 0.246 0.552 406 0.534 0.285 391 0.281 2.591 316 0.368 2.299 351 0.35 1.373 236 0.775 3.758 289 0.08 [22, 25], in macro-TGA heat
DTG3 (wt%/oC)
T3(oC)
495 609 282 0.281 321 0.085 459 816 481 485 765 382 0.105 transfer shifted the
475 937
937 DTG
Residue (wt%) 2.25 0.05 5.69 3.91 18.97 18.52 6.56 0 7.21 3.16 peaks to
229
higher temperature and main peak temperature of components between TGA and macro-TGA
230
exhibited linear relationship on pyrolysis and CO2 gasification. But as mentioned above, with the
231
existence of oxygen, the main peaks temperature of components combustion varied complicated
232
between TGA and macro-TGA. As Table 2 showed, except of lignin, the maximum DTG peak
233
temperature of other components combustion in macro-TGA delayed 35-59 °C, compared to those in
12
ACS Paragon Plus Environment
Page 13 of 18
234
TGA. For lignin, even though oxygen showed dramatic promotion in its whole decomposition, the
235
first DTG peak delayed more than 60 °C in combustion in TGA, as Fig. 2 showed. Furthermore, the
236
temperature delay for its pyrolysis in macro-TGA was 40 °C . While compared to its pyrolysis in
237
macro-TGA, the delay of lignin combustion in macro-TGA was about 10 °C. Thus, it looked
238
unusually that the first DTG peak occurred earlier for combustion in macro-TGA.
239
3.3 Biomass simulation and its comparison
240
Because the components combustion behavior, TG and DTG characteristics in TGA significantly
241
and irregularly differed from their pyrolysis, which made it difficult to simulate and compare, here we
242
focused on the simulation of reactions in macro-TGA. Biomass pyrolysis or combustion was regarded
243
to relate to their main components. Biomass simulation was based on linear combination of TG curves
244
of the five model components and three ones (cellulose, hemicellulose and lignin), respectively. The
245
comparison of simulated curves and experimental curves was shown in Fig. 6. The simulation results
246
were shown in Table 3. As shown in Table 3, the overlap ratios of all samples were higher than 0.98,
247
indicating that they could be expressed and simulated by main components well. 100
100
Orange peel, N2 80
Orange peel, Air
60
40
20
60 40 20
0 0
248 249
Exp. Cal.5 Cal.3
80
Exp. Cal.5 Cal.3
Mass (%)
Mass (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
200
400 600 o Temperature ( C)
800
1000
0 0
200
(a)
13
ACS Paragon Plus Environment
400 600 o Temperature ( C)
800
1000
Energy & Fuels
100 100
Chinese cabbage, N2 80
40 20
60
40
20
0
0 0
250 251
Exp. Cal.5 Cal.3
80
Mass (%)
Mass (%)
Chinese cabbage, Air
Exp. Cal.5 Cal.3
60
200
400 600 o Temperature ( C)
800
0
1000
200
400
600
800
1000
o
Temperature ( C)
(b) 100
100
Poplar stem, N2
Poplar stem, Air
Exp. Cal.5 Cal.3
80
Exp. Cal.5 Cal.3
80
60
Mass (%)
Mass (%)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 14 of 18
40
20
60
40
20
0 0
200
400 600 o Temperature ( C)
800
1000
0 0
200
400
600
800
1000
o
Temperature ( C)
252 253 254
(c) Fig. 6 The simulation of biomass combustion and pyrolysis by main components: (a) Orange peel; (b)
255
Chinese cabbage; (c) poplar stem.
256
Table 3 The simulation of biomass combustion and pyrolysis in macro-TGA by main components. Sample
Atm. N2
Orange peel Air
Chinese cabbage
N2 Air N2
Poplar stem Air 257
mi
Overlap ratio
Cellulose 0.0881
Hemicellulose 0.2151
Lignin 0.1554
Starch 0.2194
Pectin 0.3220
0.1894
0.6695
0.1411
/
/
0.9863
0.0000 0.1873 0.0000 0.0829 0.0000 0.0107 0.2565
0.2752 0.7026 0.1888 0.5596 0.3172 0.5659 0.1860
0.1888 0.1101 0.3694 0.3575 0.4376 0.4234 0.2994
0.2156 / 0.1974 / 0.0452 / 0.2581
0.3204 / 0.2444 / 0.2000 / 0.0000
0.9907 0.9871 0.9850 0.9810 0.9861 0.9844 0.9878
0.4311
0.2922
0.2767
/
/
0.9850
0.0504 0.3434
0.1614 0.2940
0.4721 0.3626
0.3160 /
0.0000 /
0.9904 0.9857
/: not include.
14
ACS Paragon Plus Environment
0.9904
Page 15 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
258
As observed from Fig.6, there were obvious differences between experimental TG curves and
259
fitted curves around 250-290 °C in orange peel simulation for both simulation methods, especially for
260
its pyrolysis. For Chinese cabbage, the mass difference around 170-220 °C was stable but it increased
261
sharply around 220-290 °C between experiment and simulation in its pyrolysis; there was similar
262
appearance around 230-290 °C in its combustion. In macro-TGA, moisture evaporated at around
263
200 °C because of heat transfer delay suggesting that there was inert water in Chinese cabbage more
264
or less. It suggested that there might be something decomposed earlier than hemicellulose and pectin
265
in fruit or vegetable waste like orange peel and Chinese cabbage. Furthermore, the mass loss of
266
Chinese cabbage above 800 °C in fitted curve was faster than that in TG curve might due to more
267
mass fraction of lignin in simulation. More cellulose in simulation resulted in faster mass loss around
268
390-500 °C, while less lignin made it slowly around 700-850 °C in poplar stem pyrolysis, compared to
269
experimental result. The obvious difference between two simulation methods appeared around
270
300-400 °C. In comparison of simulation results shown in Table 3, when the simulation was
271
conducted by three components, mass fractions of cellulose and hemicellulose increased significantly,
272
while lignin reduced. For orange peel, when simulation conducted by three components, mass lost
273
faster than experiment result and five components simulation around 300-350 °C, while it began
274
slowly around 350-400 °C. It might be due to much more hemicellulose fraction, which was more
275
than the sum of hemicellulose and pectin in five components simulation. Similar characteristics
276
exhibited on Chinese cabbage pyrolysis; while it was better for Chinese cabbage combustion
277
simulation. For poplar stem, mass loss of three components simulation deviated that of experiment
278
and five ones simulation around 300-390 °C due to more hemicellulose faction, too. Compared the
279
simulation results by five components and three ones, the difference between simulation and
280
experiment were less for five components than that of three ones, especially around 300-400 °C, as
281
shown in Fig. 6. It was supported by the overlap ratios. The overlap ratios from three components
282
simulation were less than those from five components simulation, as Table 3 showed. In much
283
pyrolysis or combustion, biomass decomposition mechanisms were analyzed based on cellulose,
284
hemicellulose and lignin [4, 5, 7, 30, 31]. As mentioned above, the decomposition behavior of
15
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
285
cellulose and starch looked alike, as well as hemicellulose and pectin. It indicated that three main
286
components (cellulose, hemicellulose and lignin) simulation could be applied to predict pyrolysis and
287
combustion behavior of biomass in macro-TGA. However, the various detailed characteristics brought
288
to more deviation. Undoubtedly, introduction of more main components, i.e. starch and pectin, could
289
help to refine the TG characteristics and increase simulation accuracy.
290
Actually, there were significant differences in mass fraction of main components between
291
pyrolysis and combustion of each sample. For different analysis or data basis, they also varied from
292
each other during decomposing in same atmosphere [22, 25], then the unified data were important. It
293
was because the simulation was only based on TG curves to seek the optimum overlap ratio. As
294
mentioned above, at N2 and air atmosphere, the behavior of different samples changed in various ways.
295
Because mass loss characteristics of different samples, especially component materials and real
296
biomass, varied differently in different atmosphere, TG or DTG characteristics of real biomass would
297
appear to match different components. For instance, the maximum DTG peak of orange peel pyrolysis
298
occurred at 296 °C, which was between that of hemicellulose (302 °C) and pectin (291 °C). While that
299
of its combustion appeared at 290 °C, which was much close to that of pectin (289 °C). The case of
300
Chinese cabbage pyrolysis and combustion was similar. The various mass loss changes between
301
pyrolysis and combustion of various samples would lead to difference in simulation results as Table 3
302
showed. Thus, the simulation results, mass fraction of pyrolysis and combustion was obvious different.
303
Furthermore, when the mass fraction of components derived from pyrolysis was applied to the
304
simulation of combustion of a biomass sample, the overlap ratio would decrease obviously. It was
305
because that the model components were not real ones. The detracted process of model components
306
would induce more or less deviation. Thus, the model components were also called
307
pseudo-components. However, in previous studies, even though the mass fraction of
308
pseudo-components varied more or less in different cases through optimum overlap ratio seeking, the
309
simulation results of biomass pyrolysis in TGA could be applied to macro-TGA based on the
310
pseudo-components model [22, 25], as well as pyrolysis and CO2 gasification in macro-TGA. It
311
indicated that the pseudo-components simulation results could be applied across in inert atmosphere
16
ACS Paragon Plus Environment
Page 16 of 18
Page 17 of 18
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
312
without bringing much more difference in simulating curves, while it was difficult to get coincident
313
results between inert and oxidative atmosphere. However, the simulation results could still help to
314
analyze and understand pyrolysis or combustion of a compound sample.
315
4. Conclusions
316
The behavior of mass loss of components and biomass combustion was significantly different
317
between TGA and macro-TGA. In TGA combustion, hemicellulose and lignin exhibited different
318
characteristics compared to pyrolysis. The maximum DTG peak from components combustion
319
occurred at similar temperature to their pyrolysis in macro-TGA. While for biomass, they appeared
320
6-21°C earlier. Biomass could be simulated by main components well, not matter pyrolysis or
321
combustion, and the simulation conducted by five model components (hemicellulose, cellulose, lignin,
322
starch and pectin) matched the experimental result better than by three ones (hemicellulose, cellulose
323
and lignin).
324 325
Acknowledgements The financial support from National Natural Science Foundation of China (No. 21376134) is
326
gratefully acknowledged.
327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347
References [1]. Amutio, M., et al., Kinetic study of lignocellulosic biomass oxidative pyrolysis. Fuel, 2012. 95: p. 305-311. [2]. Sannigrahi, P., A.J. Ragauskas and G.A. Tuskan, Poplar as a feedstock for biofuels: A review of compositional characteristics. Biofuels, Bioproducts and Biorefining, 2010. 4(2): p. 209-226. [3]. Sullivan, A.L. and R. Ball, Thermal decomposition and combustion chemistry of cellulosic biomass. 2012. p. 133-141. [4]. Qu, T., et al., Experimental study of biomass pyrolysis based on three major components: hemicellulose, cellulose, and lignin. Industrial & Engineering Chemistry Research, 2011. 50(18): p. 10424-10433. [5]. Pasangulapati, V., et al., Effects of cellulose, hemicellulose and lignin on thermochemical conversion characteristics of the selected biomass. Bioresource Technology, 2012. 114: p. 663-669. [6]. Burhenne, L., et al., The effect of the biomass components lignin, cellulose and hemicellulose on TGA and fixed bed pyrolysis. Journal of Analytical and Applied Pyrolysis, 2013. 101: p. 177-184. [7]. Stefanidis, S.D., et al., A study of lignocellulosic biomass pyrolysis via the pyrolysis of cellulose, hemicellulose and lignin. Journal of Analytical and Applied Pyrolysis, 2014. 105: p. 143-150. [8]. Peters, B., Prediction of pyrolysis of pistachio shells based on its components hemicellulose, cellulose and lignin. Fuel Processing Technology, 2011. 92(10): p. 1993-1998. [9]. Bahng, M., et al., Current technologies for analysis of biomass thermochemical processing: A review. Analytica Chimica Acta, 2009. 651(2): p. 117-138. [10]. DIBLASI, C., Modeling chemical and physical processes of wood and biomass pyrolysis. Progress in 17
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394
Energy and Combustion Science, 2008. 34(1): p. 47-90. [11]. Barneto, A.G., et al., Simulation of the thermogravimetry analysis of three non-wood pulps. Bioresource Technology, 2010. 101(9): p. 3220-3229. [12]. Yang, H., et al., Characteristics of hemicellulose, cellulose and lignin pyrolysis. Fuel, 2007. 86(12– 13): p. 1781-1788. [13]. Hosoya, T., H. Kawamoto and S. Saka, Cellulose–hemicellulose and cellulose–lignin interactions in wood pyrolysis at gasification temperature. Journal of Analytical and Applied Pyrolysis, 2007. 80(1): p. 118-125. [14]. Zhou, H., et al., The pyrolysis simulation of five biomass species by hemi-cellulose, cellulose and lignin based on thermogravimetric curves. Thermochimica Acta, 2013. 566: p. 36 - 43. [15]. Cheng, K., W.T. Winter and A.J. Stipanovic, A modulated-TGA approach to the kinetics of lignocellulosic biomass pyrolysis/combustion. Polymer Degradation and Stability, 2012. 97(9): p. 1606-1615. [16]. Zhou, H., et al., Classification and comparison of municipal solid waste based on thermochemical characteristics. Journal of the Air & Waste Management Association, 2014. 64(5): p. 597-616. [17]. Cheng, H.F., et al., Municipal solid waste fueled power generation in china: a case study of waste-to-energy in changchun city. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2007. 41(21): p. 7509-7515. [18]. Aguiar, L., et al., Influence of temperature and particle size on the fixed bed pyrolysis of orange peel residues. Journal of Analytical and Applied Pyrolysis, 2008. 83(1): p. 124-130. [19]. Schröder, E., Experiments on the pyrolysis of large beechwood particles in fixed beds. Journal of Analytical and Applied Pyrolysis, 2004. 71(2): p. 669-694. [20]. Skreiberg, A., et al., TGA and macro-TGA characterisation of biomass fuels and fuel mixtures. Fuel, 2011. 90(6): p. 2182-2197. [21]. Zhou, H., et al., A novel method for kinetics analysis of pyrolysis of hemicellulose, cellulose, and lignin in TGA and macro-TGA. RSC Advances, 2015. 5: p. 26509-26516. [22]. Meng, A., et al., Pyrolysis and simulation of typical components in wastes with macro-TGA. Fuel, 2015. 157: p. 1-8. [23]. Chen, S., et al., TGA pyrolysis and gasification of combustible municipal solid waste. Journal of the Energy Institute, 2015. 88(3): p. 332-343. [24]. Zhou, H., et al., The pyrolysis simulation of five biomass species by hemi-cellulose, cellulose and lignin based on thermogravimetric curves. Thermochimica Acta, 2013. 566: p. 36-43. [25]. Meng, A., et al., Pyrolysis and gasification of typical components in wastes with macro-TGA. Waste Management, 2015. [26]. Meng, A., et al., Pseudo-component model to predict the thermochemical behaviour of combustible solid waste. Journal of Tsinghua University (Science & Technology), 2014. 54(2): p. 235-239 (in Chinese). [27]. Shafizadeh, F. and A.G.W. Bradbury, Smoldering Combustion of Cellulosic Materials. Journal of Building Physics, 1979. 2(3): p. 141 -152. [28]. Shen, D., et al., Thermal degradation of xylan-based hemicellulose under oxidative atmosphere. Carbohydrate Polymers, 2015. 127: p. 363-371. [29]. Conesa, J.A. and A. Domene, Biomasses pyrolysis and combustion kinetics through n-th order parallel reactions. Thermochimica Acta, 2011. 523(1-2): p. 176-181. [30]. Chen, T., et al., Gasification kinetic analysis of the three pseudocomponents of biomass-cellulose, semicellulose and lignin. Bioresource Technology, 2014. 153: p. 223-229. [31]. Lv, G. and S. Wu, Analytical pyrolysis studies of corn stalk and its three main components by TG-MS and Py-GC/MS. Journal of Analytical and Applied Pyrolysis, 2012. 97: p. 11-18.
18
ACS Paragon Plus Environment
Page 18 of 18