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Evaluation of Char Characteristics and Combustibility of LowRank-Coal Blends with Different Reflectance Distributions Tae-Yong Jeong, Yanuar Yudhi Isworo, and Chung-Hwan Jeon Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.9b01092 • Publication Date (Web): 18 Aug 2019 Downloaded from pubs.acs.org on August 23, 2019
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Energy & Fuels
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Evaluation of Char Characteristics and
2
Combustibility of Low-Rank-Coal Blends with
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Different Reflectance Distributions
4
Tae-Yong Jeong a,1, Yanuar Yudhi Isworo a,1, Chung-Hwan Jeon a,b,*
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a
6
of Korea
7
b
8
KEYWORDS. Coal blending; Mean random vitrinite reflectance (Rr%); Microlithotype;
9
Char classification; Char morphology; Unburnt combustibles
School of Mechanical Engineering, Pusan National University, Busan 46241, Republic
Pusan Clean Coal Center, Pusan National University, Busan 46241, Republic of Korea
10
ABSTRACT. Petrographic analysis can provide valuable information about pulverized
11
coal used in coal-fired power plants. In this study, petrographic analysis was used to
12
determine the effect of blending on the combustion of low-rank coal from Mongolia and
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two bituminous coals from Russia. After blending these coals based on their calorific
14
values and combusting them in a drop tube furnace, the unburnt combustibles in the char
15
were analyzed. The coal rank, determined from the mean random vitrinite reflectance,
16
was closely correlated with the proportion of each single coal in the blend. Char
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component analysis showed that the generated char particles were not affected by the
18
coal rank but had a strong relationship with the microlithotype of the raw coal. In contrast,
19
for single coals, the unburnt combustibles at equal temperatures were affected by the
20
coal rank. Morphological analysis of the char types revealed that the geometric tendency
21
of each coal was in agreement with the char formed at different temperatures. However,
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combustion results for the blended samples exhibited somewhat complicated tendencies.
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The unburnt combustibles showed interactions between coals relating to their
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petrographic properties, such as vitrinite reflectance and char components.
25
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1. Introduction
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Since the industrial revolution, coal has been used as a fuel source worldwide because
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of its abundance, low price, and efficient and abundant reserves. It became a major global
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energy source from the 1950s to the early 1970s, when oil and gas prices rose worldwide
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[1]. Currently, coal provides 30% of the global energy demand and contributes 40% and
31
70% of the energy utilized for electric power and steel production, respectively [2].
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However, because of the increasing demand and diminishing supplies of high-rank coal,
33
along with the rising oil prices since the 2000s, countries highly dependent on imported
34
resources, including the Republic of Korea, are implementing policies such as the flexible
35
securement of coal resources and diversification of coal suppliers. The Republic of Korea
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is entirely dependent on imported coal for power generation, as the fourth-largest coal-
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importing country following China, India, and Japan [3]. Since these countries are all
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located in Asia, the Korean national policy requires the utilization of low-rank coal that
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can be more easily secured from various production sites [4]. Low-rank coal such as
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brown coal (or lignite) and sub-bituminous coal comprises more than half of the coal
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reserves worldwide [5]. However, it has lower thermal efficiency than high-rank coal
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because of its higher moisture content and lower calorific value. It also poses potential
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safety risks during transportation and storage, has high operational costs, and leads to
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many problems in the combustion process in coal-fired power plants [6].
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With these considerations, various properties and combustion characteristics of low-rank
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coal, especially brown coal (or lignite) for coal-fired power generation, have been
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examined [7, 8]. The studies on brown coal mostly focused on improving the physical
48
properties of raw materials using blended coal combustion or biomass addition [2, 9, 10].
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However, the combustion of coal blends may exhibit different combustion characteristics
50
from those of the raw coal. It has been recognized that the conventional predictable
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properties associated with fuel composition such as proximate, ultimate analysis and
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heating value remain additive, while many characteristics associated with combustion are
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reported to be non-additive [11, 12]. So, it may be challenging to determine the interaction
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between the blended coal components that yield acceptable combustion results. One
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method that may address such problems and provide useful information on the use of
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pulverized coal in coal-fired power plants is petrographic analysis [13]. By analyzing the
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optical and morphological properties of coal, petrographic analysis correlates the organic
58
and inorganic matter in coal to its combustion parameters such as temperature, reacting
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gas environment, and coal rank. Many researchers have used petrographic analysis to
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investigate the correlations among maceral compositions, ranks, and burnout behaviors
61
of coals, leading to the establishment of a correlation with reflectance, the reactivity
62
relationship between vitrinite and inertinite among maceral substances, and the
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connection between the microlithotype and maceral components of coal. The influence
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of coal particles on the morphology and type of char during pyrolysis and combustion has
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been examined closely [14–19]. Although many studies have used petrography,
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continuous petrographic research should be conducted with the expanding development
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and application of various coal types. In addition, further research is needed in coal-
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importing countries, including the Republic of Korea. Therefore, in this study, three types
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of coal were selected for blending and combustion. One is a low-rank coal from Mongolia,
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a potential major coal supplier to the Republic of Korea for future energy security. The
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other two are bituminous coals from Russia, which has been increasing its coal exports
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to the Republic of Korea. The combustion characteristics of these coals were examined
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in single and blended conditions based on various calorific values. After being combusted
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in a drop tube furnace (DTF), the unburnt combustibles in the collected char were
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analyzed using a petrographic analyzer. Possible correlations between the char
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characteristics (including microlithotype, components, and morphology) and combustion
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behavior were experimentally investigated.
78 79
2. Experimental section
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2.1 Petrographic analysis
81
2.1.1 Sample preparation
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Three unblended coal samples given by one of Korean power plant from its coal
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stockyard facility were studied: two bituminous coals from Russia (KRSNY (KSN) and
84
Glencore (GLC)) used as the main coal in domestic coal-fired power plants, and a lignite
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coal (Baganuur (BGN)) from Mongolia, which has become a potential coal supplier owing
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to the Korean policy to secure stable supply. The raw samples were in form of general
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coal feed stockyard 2 mm size, then pulverized into typical 75-90µm power plant boiler
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coal feed size using blade-rotating pulverizer. The pulverized sample, then air-dried using
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room-temperature oven (34-35°C) to maintain moisture excess for about 5 hours. Then
90
samples are ready to be used as coal petrographic sample. About 1 gr of coal sample
91
was put into standard cylindrical mold (diameter ±32mm, height ±31mm), and mixed with
92
epoxy resin and 1-2 drops of liquid catalytic chemical hardener to accelerate the
93
compaction process [20].
94
After completely stirred and mixing, the sample mold then safely keeps in open air
95
temperature to get self-dried for about 3-4 hours. Then after 3-4 hours dried, to have
96
perfectly dried sample, and to maintain the moisture access, the sample mold then moves
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into air-dried temperature oven, with room temperature (around 35ºC). The dried samples
98
then underwent two preparation steps: grinding and polishing using automatic grinding-
99
polishing machines (Model: BESTPOL P262, Korea) equipped with automated and
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motorized sample place-holders [20]. The grinding process used grinding paper with the
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sequential grit sizes of 180, 400, 800, and 1200 µm for 1 min of rotation per each size.
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To eliminate the grinding scratches, the samples were then polished using two special
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fabric pads (1 and 6 µm). The result was a smooth sample surface for examination under
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the petrographic microscope.
105
106
2.1.2 Petrographic analysis procedure
107
An optical reflection-type microscope was used to measure the intensity of light
108
reflected by the prepared samples. Standard setups were used to measure the vitrinite
109
reflectance for ranking the coal or other types of carbon-derived/organic materials [21].
110
This work used an Axioscope-A0 microscope (Carl-Zeiss) equipped with white and UV
111
light sources, a spectro-photometer, and a software program to measure the coal-vitrinite
112
reflectance. Total magnification used in this research were 200x and 500x. The 200x was
113
used to analyze the char morphology since it could cover many char particles, which was
114
helpful in later image processing. The 500x magnification was used for the vitrinite
115
reflectance, maceral and microlithotype analysis, using white light source. Because
116
maceral distinctively auto fluoresces when irradiate with UV light, a UV light source was
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used to classify some macerals based on its fluorescence color light. The white light
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source was also used for char morphology scanning and recording. After examining the
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entire sample surface to ensure a clear microscopic view, 500 representative points were
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recorded to determine the char wall thickness through image analysis. The images were
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processed using a semi-automatic stepping stage point counter (PetrogTM Digital
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Stepping Stage). An illustration of the petrographic microscope unit is displayed in Fig. 1.
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124 125
Fig. 1. Main petrography microscopy unit.
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2.1.3 Petrography of single and blended coals and their char
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Three types of petrographic analysis were performed for single and blended coals:
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vitrinite reflectance, maceral, and microlithotype composition determination. The analysis
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followed the ASTM standard D2799 and the International Committee of Coal and Organic
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Petrology (ICCP) system 1994 for maceral composition determination [22-24], while for
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microlithotype composition following ISO 7404-4 standard. The microlithotype
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classification previously proposed for pulverized fuel was used to relate the microlithotype
134
to specific char morphotypes [25].
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For binary blended coals, the volume percentage of each coal was measured based
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on the vitrinite reflectance and maceral composition (microlithotype) analysis, using the
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same procedure as that reported previously [26, 27] because of the complexity of
138
identifying blended coal components. In addition, because coal char is a key factor in the
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coal utilization process, petrographic analysis was applied to coal char classification [40,
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41]. Depending on the research goal, coal char can either refer to that originating from
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the pyrolysis, or unburnt char particles in the final combustion product of the parent coal
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under certain processing conditions. The char classifications were based on the works by
143
Bailey et al. and Valentim et al. [25, 28].
144
145
2.1.4 Image processing analysis
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Image processing analysis has been previously used to identify the morphology of coal
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char and correlate it with combustion characteristics [29, 30]. Using image analysis
148
system software which processed the captured image from the petrographic microscope,
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three methods were employed in the associated image analysis (char void percentage,
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semi-automated analysis, and distance transformation) to identify morphological
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characteristics such as the existence of voids, char wall thickness, and the development
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of whole char particles. The image analysis technique was based on the gray-scale image
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typed-file which was converted from the original image file taken from the petrography
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microscope. The gray scaled based image file then processed to create 2-dimensional
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contour lines image which extracted from the gray-scale pixel level from char particle body
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image, which possible then to measure char morphology geometrical aspects (surface
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area and char wall thickness) [18]. Such analysis using computer software is superior to
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manual char morphology identification. The combustion working group for the ICCP has
159
applied image analysis to combine all the char types identified by different operators into
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a single coal char atlas at Nottingham University [17].
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2.2 DTF study
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2.2.1 Sample preparation and specification of DTF
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Of the three coal samples, KSN and GLC exhibit similar calorific values, and these
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values are higher than that of BGN as can be seen in Table 1. However, these coal types
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differ by more than a factor of two in the mean random vitrinite reflectance (Rr%) value,
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which is an index for coal rank, as can be seen from the petrographic analysis results
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discussed later. BGN comes from the coal-bearing province (or basin) called Choir–
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Nyalga located in the eastern part of Mongolia, formed between the late Jurassic period
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and the early Cretaceous period of the Mesozoic era. This coal has the characteristics of
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fluvial/lacustrine deposits and low rank [31], as well as a low calorific value, high moisture
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content, and the lowest Rr% value. As it is expected to be imported into Korea in the
173
future, BGN was selected as the low-rank coal in this study.
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Prior to the experiment, the three coal types were pulverized using a ball mill and filtered
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through a sieve to collect particles of 75–90 μm in size. Proximate and ultimate analyses
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were conducted using a thermogravimetric analysis system (TGA-701; LECO Co.) and
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TruSpec elemental analyzer (LECO Co.) in accordance with ASTM D5142 and
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ASTM3176, respectively. The calorific values were measured by bomb calorimeter using
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AC600 (LECO Co.) referred to ASTM D5865 procedure. Table 1 shows the analysis
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results of the coal samples.
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Table 1. Properties of Studied Coals Proximate analysis
Ultimate analysis
GCV*
(wt.%, AR*)
(wt.%, DAF*)
(AR)
Moi.
V.M.
Ash
F.C.
C
H
N
O*
S
MJ/kg (kcal/kg)
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KSN
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27.1
18.9
45.3
78.9
3.9
2.7
13.6
0.7
28.28
(RUS)
4
9
2
0
3
4
7
6
(6,758)
GLC
33.2
47.6
76.7
5.4
1.4
15.7
0.6
26.88
1
2
4
2
4
3
7
(6,424)
25.4
34.1
65.8
4.9
0.7
27.8
0.5
17.84
1
6
9
9
4
2
(4,264)
8.55
9.42 (RUS) BGN
37.4
9.75
2.99 (MGL) 183 184
4
6
*AR: As-received basis; DAF: Dry ash-free basis; GCV: Gross calorific value; Oxygen determined by difference.
185 186
A drop tube furnace (DTF) was used in the combustion experiments. The equipment
187
could generate a uniform temperature field in the reaction zone and provide temperatures
188
up to 1,500 ℃, enabling the maintenance of constant particle temperatures as
189
combustion progressed and the observation of the combustion characteristics of the fuel
190
under relatively stable conditions. The experimental setup was composed of a reactor for
191
high-temperature reactions, a feeding section for injecting coal particles, and a sample
192
collection section. A detailed description of the DTF is provided in a previous study [32].
193
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2.2.2 Collection of unburnt combustibles in DTF
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To simulate the unburnt combustibles generated from single or blended coals in actual
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pulverized coal-fired boilers, the temperature inside the DTF was maintained at 1,300 ℃.
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The coal particle size was 75-90 μm and the particle residence time was about 2.21 s,
198
assuming particle slip velocities based on Stoke’s Law [33]. A total of 3 g of coal was
199
supplied at the rate of 0.3 g/min for 10 minutes, and N2 was used as the carrier gas. The
200
atmospheric gas based on N2 was supplied at the stoichiometric ratio (SR, λ) of 1.16 for
201
reactions inside the furnace. In all experiments in this study, out-furnace or bunker
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blending was applied for blended coals, and blending was based on the gross calorific
203
values (GCV) of each coal samples for reaching specific calorific values. Table 2 shows
204
the experimental parameters of the DTF. In each experiment, residual solid particles after
205
combustion were collected by the cyclone, and the unburnt combustible fraction was
206
measured using the ash tracer method according to the following equation [34].
207
Unburnt combustible fractionchar (%) =
[(1 ― (
𝐴𝑠ℎ𝑟𝑐
)(
100 ― 𝐴𝑠ℎ𝑟𝑐
))] × 100,
100 ― 𝐴𝑠ℎ𝑢𝑐 𝐴𝑠ℎ𝑢𝑐
(1)
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where Ashrc and Ashuc denote the ash contents of the raw coal sample and the unburnt
209
char, respectively. The measurement was repeated three times, and the deviation of the
210
unburnt combustible fraction from the mean value was within ±1.0% for single coals and
211
within ±2.0% for blended coals.
212 213
Table 2. Experimental Conditions of the DTF Parameters
Setting condition
Bituminous coal
Glencore (RUS), KRSNY (RUS)
Lignite coal
Baganuur (MGL)
Blending condition (GCV, kcal/kg)
5,400
Coal particle size (μm)
75–90
Coal feeding rate (g/min)
0.3
Setting temperature (℃)
900
Total flow rate (L/min)
5
Carrier gas (N2, L/min)
1
5,600
5,800
6,000
1,300
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Energy & Fuels
Stoichiometric ratio (λ)
1.16
214 215 216
3. Results & Discussion
217
3.1 Petrographic analysis of single and blended coals
218
3.1.1 Single coals and their char
219
In this study, the vitrinite reflectance was used to indicate the coal rank, in addition to
220
the volatile matter (VM), fixed carbon (FC), and GCV used by the ASTM coal rank
221
classification [35]. KSN has the highest Rr% (1.28), followed by GLC (0.56) and BGN
222
(0.35). With its highest rank, KSN has the brightest dominant vitrinite maceral, while GLC
223
has both darker and brighter vitrinite macerals. BGN has the lowest Rr% and darker
224
dominant vitrinite maceral than the other two coals.
225
From the petrographic analysis, the three coals have significantly different
226
compositions in the macerals (Table 3). KSN has the highest rank (Rr%) but the lowest
227
vitrinite content (59.2%), and mainly contains inertinite (40.8%). No liptinite is found in it
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during maceral examination, as the liptinite composition is absent in high-rank coal [27].
229
With its lowest rank, BGN has the highest vitrinite content (93.9%) and lowest inertinite
230
composition (2.0%), together with 4.1% liptinite. The maceral compositions of GLC and
231
BGN are similar except for the inertinite composition (GLC: 14. 9%, BGN: 2.0%).
232
233
Table 3. Results of Mean Random Vitrinite Reflectance (Rr%), Maceral, and
234
Microlithotype Analysis (vol.%, MMF*) in Single Coals KSN
GLC
BGN
MV-Bituminous
HV-Bituminous
Lignite
1.28
0.56
0.35
Vitrinite
59.2
83.0
93.9
Liptinite
-
2.1
4.1
Inertinite
40.8
14.9
2.0
Coal rank Mean random vitrinite reflectance (Rr%)
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Vitrite
30.2
45.7
60.5
Inertite
45.7
15.5
1.3
Clarite-V
-
2.0
7.5
Vitrinertite-V
9.4
15.0
23.7
Vitrinertite-I
7.5
5.7
3.4
Durite-I
-
3.4
-
Trimacerite-V
-
5.8
1.2
Trimacerite-I
-
3.5
-
Carbominerites
7.2
3.4
2.4
MPG1**
39.6
68.5
92.9
MPG2**
53.2
28.1
4.7
235
* MMF: Mineral matter free basis.
236
** Microlithotype precursor of Group 1 (MPG1, Vitrite + Liptite + Clarite-V + Clarite-L +
237
Vitrinertite-V + Trimacerite-V + Trimacerite-L); Microlithotype precursor of Group 2
238
(MPG2, Inertite + Vitrinertite-I + Durite-L + Durite-I + Trimacerite-I).
239
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Microlithotype analysis was performed to obtain the relationship between the formed
242
char and the parent coal’s macerals and microlithotype, as well as to analyze the maceral
243
composition for each coal sample. It is possible to correlate the parent coal’s petrographic
244
properties to the char formed in laboratory-scale experiments [18, 36]. Table 3 shows the
245
macerals and microlithotype of single coals, together with the microlithotype composition
246
of MPG 1 and MPG 2 for each microlithotype in the parent coal’s maceral, which
247
determine the morphology of the char. Some parts of microlithotype particle classification
248
in Table 3 are intentionally omitted because the result is equal to 0 (liptite, clarite-L,
249
trimacerite-L, and durite-L). The results show that the microlithotype of each coal follows
250
the main maceral group trends.
251
KSN has the largest inertite content because it has a dominant inertinite maceral
252
content (40%), which supports the influence of the microlithotype of each coal on the
253
existence of group 2 char (MPG 2) after combustion. GLC has 14. 9% inertinite (smaller
254
than KSN) but a high vitrinite content (83.0%); this condition allows GLC to be classified
255
as MPG 1 dominant (68.5%) with 28.1% MPG 2. BGN with its lowest rank has the highest
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256
vitrinite composition and the lowest inertinite maceral content. Therefore, it is classified
257
as MPG 1 dominant with only 4.7% MPG 2 in the composition. All the microlithotype
258
compositions are summarized in terms of MPG 1 and MPG 2. KSN with its high rank has
259
the lowest content in the microlithotype group with a highly porous char morphology (MPG
260
1), whereas it has the highest volume percentage in MPG 2. In contrast, BGN has the
261
highest MPG 1 volume content and the lowest MPG 2 content. The result for GLC is
262
between those of KSN and BGN coals. While the microlithotype of the parent coal is the
263
main factor determining the char formed during combustion, the conditions during char
264
production also influence char characteristics. Therefore, experiments were performed at
265
two different temperatures for single and blended coals to correlate the maceral of the
266
parent coal with the produced char.
267
The char classifications for individual coals are shown in Table 4. From low to higher
268
temperature, as we can see in Table 4, the group 1 type of char is increasing. The
269
researchers who proposed the char classification system based it on the physical and
270
optical characteristics of char, or char morphology [22]. At a higher temperature, the
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Page 22 of 62
271
combustion process may be more intense, with the surface of the char particles shrinking
272
because of the changes in the carbon structure owing to the reactions between char wall
273
surfaces and oxygen, as well as thermal effects. Correspondingly, the formation of group
274
2 char containing thick-walled particles decreased with increasing temperature, especially
275
for inertinite-derived mixed-solid and solid particles. Such effects of reaction temperature
276
on formed char components have been previously reported [19, 37]. KSN, which is
277
associated with MPG 2 coal, produced predominantly mixed-solid and solid char particles
278
at 900 °C with dominant group 2 (90.01%) char and minimal group 1 char (9.99%) (Table
279
4). At a higher temperature (1,300 °C), the content of group 1 char (tenui-crassi spheres
280
and tenuinetwork, including crassinetwork) increased for KSN owing to the enrichment of
281
altered mixed-solid char under heating and oxygen diffusion. Meanwhile, the content of
282
group 2 char (mixed-solid and solid) decreased at higher temperatures. GLC has the
283
same tendency as KSN with group 1 char increasing and group 2 char decreasing with
284
temperature. GLC has 74.18% group 2 char and 25.82% group 1 char. Being an MPG 1
285
dominant coal, BGN shows the same tendency as the other two coal types with respect
286
to temperature. The char produced from BGN is also in accordance with its microlithotype,
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being dominated by group 1 at both temperatures. These results are supported by a
288
previous observation [28] that the chars produced are mainly influenced by the maceral
289
make-up (petrographic composition) and coal rank; in this study, the chars produced are
290
also correlated with temperature differences.
291
292
Table 4. Classification of Single-coal Char (vol.%) Generated during Combustion at
293
Different Temperatures KSN
GLC
BGN
900
1,300
900
1,300
900
1,300
℃
℃
℃
℃
℃
℃
Tenuisphere
0.35
0.67
-
20.27
44.41
45.48
Crassisphere
6.21
9.33
0.67
2.67
9.67
11.64
Tenuinetwork
3.43
6.00
25.15
28.67
28.67
32.35
Crassinetwork 16.10
22.00
27.33
33.37
15.37
10.28
Mixed solid
36.67
35.87
10.33
1.33
-
38.54
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Page 24 of 62
Solid
35.37
25.33
10.98
4.69
0.55
0.25
Group 1*
9.99
16.00
25.82
51.61
82.75
89.47
Group 2*
90.01
84.00
74.18
48.39
17.25
10.53
294
* Group 1: total volume fraction of (Tenuisphere + Crassisphere + Tenuinetwork); Group
295
2: total volume fraction of (Crassinetwork + Mixed solid + Solid).
296
297
298
The petrographic microscope images of char from single coals produced in the DTF at
299
900°C and 1,300°C are displayed in Fig. 2. The classification results demonstrate that at
300
equal combustion temperatures, char components are not correlated with the calorific
301
values and rank of the parent coals, but are affected by the composition of the parent
302
coals’ microlithotypes. As the temperature increases, each single coal generates a higher
303
percentage of thin-walled char particles (tenuisphere, crassisphere, and tenuinetwork),
304
and some of the thick-walled char particles are also transformed into thin-walled ones.
305
Thus, temperature significantly influences the morphology of the char, as confirmed by
306
the previous DTF studies [18, 19, 37].
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307
308 309
Fig. 2. Representative images of single-coal char samples.
310
311
Using the geometry of the char wall measured with the image analysis (as described in
312
Section 2.1.4), the surface areas and densities of char particles were analyzed. The
313
surface areas of char particles were measured from the entire surface, bounded by the
314
wall line that defines the particle body configuring one char particle. The algorithm used
315
in the image analysis system software were based on the gray-scale of the pixels which
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Page 26 of 62
316
form the char particle morphology. The wall thicknesses were related to the density using
317
the gray pixels forming the body of the char particle inside the wall line. Each sample was
318
mapped for 500 char particles. The final results based on the average size of the char
319
morphological content are shown in Table 5. The KSN char has 22% crassinetwork; thus,
320
the geometric measurements of the crassinetwork (surface area and wall thickness) are
321
averaged over the 22% crassinetwork content. The measured char particle geometry
322
supports the findings in char morphology classification where increasing the combustion
323
temperature (from 900 °C to 1,300 °C) causes the wall of the particles and the surface
324
area to shrink under increasing thermal effect and oxygen diffusion reaction [16, 37, 38].
325
Under higher temperatures, the surface area for group 1 char decreased (Table 5). The
326
walls of group 2 char became thicker, possibly from the swelling of the carbon chains
327
during their interactions. The images in Fig. 2 also confirm this observation. The char wall
328
surface area decreased with increasing temperature for group 1 char, and the mixed-solid
329
and solid char particles became denser. The results imply that a higher-rank parent coal
330
produces char particles with thicker walls, and during the pyrolysis and combustion of
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331
pulverized coal, the higher-rank coal tends to be less reactive than the lower-rank one.
332
This finding is also supported by Alonso et al. [38].
333 334
Table 5. Geometrical Morphology of Single-coal Char Generated during Combustion at
335
Different Temperatures KSN
GLC
BGN
900 ℃
1,300 ℃
900 ℃
1,300 ℃
900 ℃
1,300 ℃
Tenuisphere
765.26
341.29
543.37
423.45
345.57
300.27
Crassisphere
747.85
987.45
742.51
697.25
987.45
229.73
Tenuinetwork
1,058.34
437.45
1,084.53
987.65
354.87
325.59
Crassinetwork
1,235.78
1,123.25
1,207.94
1,145.67
458.97
415.69
Mixed solid
1,116.54
1,134.67
1,108.45
1,087.15
578.23
515.47
Solid
1,058.34
957.45
1,043.29
994.25
252.78
213.21
Surface area [µm2]
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Page 28 of 62
Wall thickness [µm3] Tenuisphere
1,234.23
1,007.51
928.74
805.32
553.25
421.35
Crassisphere
1,114.56
945.23
1,087.62
945.24
467.28
225.32
Tenuinetwork
1,343.23
1,145.67
1,365.43
1,112.32
743.54
387.35
Crassinetwork
1,655.34
1,275.64
1,495.17
1,259.34
889.29
621.35
Mixed solid
2,856.34
3,838.45
2.761.33
3,274.21
759.25
845.57
Solid
1,985.44
2,262.67
2,965.28
3,154.35
429.34
542.90
336 337 338
3.1.2 Blended coals and their char
339
The mass/weight ratio used for blending the coals in this study was based on the coal
340
calorific values. Petrographic analysis was also applied to investigate the characteristics
341
of each blend and correlate them with the combustion properties. In this study, two main
342
coals (KSN, Rr = 1.28 followed by GLC, Rr = 0.56) were blended with a lower-rank coal
343
(BGN, Rr = 0.35). Based on the previous research21,22, the maceral composition for
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Energy & Fuels
344
each component of the coals in each maceral group was based on their original vitrinite
345
reflectance and also the associated macerals (liptinite and inertinite). Fig. 3 (a) represents
346
the random vitrinite reflectance of each single coal, which is the main parameter for
347
predicting the distribution of the vitrinite reflectance of the blended coals. For blending
348
cases, the notation of the blending samples to be used later is defined as in consecutive
349
order the first letter of the high rank coal, the first letter of the low rank coal, and the firstly
350
two numerals of the calorific value by the blending condition. An interesting issue arises
351
when identifying macerals for each component in the binary GB case of Fig. 3 (b): the
352
vitrinite reflectance values of the blended coals are not significantly different and thus the
353
vitrinite reflectance ranges overlap. Meanwhile, for the KSN/BGN case, the random
354
vitrinite reflectance differs significantly between the lower-rank coal (BGN) and the higher-
355
rank one (KSN). These observations are expected to affect the combustibility.
356
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Page 30 of 62
357
(a)
358
359 360
(b)
(c)
361
Fig. 3. Distribution of random vitrinite reflectance for (a) single coals and (b, c) blended
362
coals with different calorific values.
363
364
The petrographic method used for the component analysis of coal blends can identify
365
the blending ratio for each coal with a certain deviation. This deviation is primarily
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Energy & Fuels
366
influenced by the identification of the random vitrinite reflectance values and the
367
associated maceral (liptinite and inertinite) reflectance and morphology, which are well-
368
known characteristics for coal maceral identification. The results for the blended cases
369
are presented in Table 6.
370
371
Table 6. Component Identification in Coal Blends Based on Random Vitrinite Reflectance
372
Value (vol.%) GLC–BGN blends GB54
GB56
GB58
KSN–BGN blends GB60
KB54
KB56
KB58
KB60
Blend 29–71 42–58 56–44 70–30
23–77 34–66 46–54 57–43
28.11
40.94
54.92
69.07
20.84
31.23
42.89
53.89
–
–
–
–
–
–
–
–
71.89
59.06
45.08
30.93
79.16
68.77
57.11
46.11
52.65
55.07
40.26
25.29
80.01
65.86
55.85
43.00
(wt.%) Blend
LRV
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Page 32 of 62
LRL
2.60
1.85
-
1.00
-
2.80
2.07
1.00
LRI
0.20
-
0.32
-
0.19
0.10
0.50
0.10
TLR_Coal
55.45
56.92
40.58
26.29
80.20
68.76
58.42
44.10
HRV
18.75
22.58
40.05
45.52
6.53
17.07
23.27
32.10
HRL
0.59
1.54
3.02
1.74
3.22
-
-
0.87
HRI
3.40
6.80
8.75
8.89
10.05
14.17
18.31
22.93
THR_Coal
22.74
30.92
51.82
56.15
19.80
31.24
41.58
55.90
NAV
19.44
11.68
7.60
15.56
-
-
-
-
NAL
0.40
-
-
-
-
-
-
-
NAI
1.97
0.48
-
2.00
-
-
-
-
TNA_Comp
21.81
12.16
7.60
17.56
-
-
-
-
LRC_Corr
70.92
64.80
43.92
31.89
80.20
68.76
58.42
44.10
HRC_Corr
29.08
35.20
56.08
68.11
19.80
31.24
41.58
55.90
Deviation**
0.97
5.74
1.16
0.96
1.04
0.01
1.31
2.01
373
* LRV, low-reflectance vitrinite; LRL, low-reflectance liptinite; LRI, low-reflectance
374
inertinite; TLR_Coal, total low-rank coal; HRV, high-reflectance vitrinite; HRL, high-
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375
reflectance liptinite; HRI, high-reflectance inertinite; THR_Coal, total high-rank coal; NAV,
376
non-assignable vitrinite; NAL, non-assignable liptinite; NAI, non-assignable inertinite;
377
TNA_Comp,
378
TNA_Comp); HRC_Corr, (THR_Coal)100/(100 − TNA_Comp).
379
total
non-assignable
components;
LRC_Corr,
(TLR_Coal)100/(100-
** Difference from actual value in coal blends (in volume percent).
380
381
382
The microlithotype analysis results for the blended coals are presented in Table 7. The
383
tendency for microlithotype in the blended samples follows the actual composition of each
384
coal sample because the blending compositions are based on the weight ratio to fulfill the
385
targeted calorific value. A larger proportion of high-rank coal in the blend means a higher
386
obtainable calorific value, and vice versa. For the GB blends, because both parent coals
387
are vitrinite-rich, the main difference in their maceral contents is in the inertinite; GLC as
388
a highly volatile coal contains more inertinite than BGN. For this reason, for all GB cases,
389
the inertinite content is mainly originated from GLC and increases with the calorific value
390
of the coal. Thus, the microlithotype analysis indicates that all GB blends are dominated
391
by the MPG 1 microlithotype, and all the microlithotypes comprise vitrinite-dominant
392
macerals because both parent coals are also vitrinite-rich. From GB54 to GB60, the MPG
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Page 34 of 62
393
1 type results are slightly different because both parent coals are vitrinite-rich, while the
394
MPG 2 type increases with the proportion of the higher-rank coal (GLC). For the KB
395
blends, the microlithotype results from Table 7 also show the same general trend as that
396
for GB. From the lowest calorific value (KB54) to the highest one (KB60), the inertite
397
content increases, in agreement with the composition ratio of KSN in the blend. All the
398
KB blends are dominated by the MPG 1 type and also with significant MPG 2 composition
399
unlike the GB cases.
400
401
Table 7. Mean Random Vitrinite Reflectance, Maceral, and Microlithotype Analysis
402
(vol.%, MMF) in Coal Blends GLC–BGN blends
KSN–BGN blends
GB54 GB56 GB58 GB60
KB54
KB56
KB58
KB60
Rr%
0.35
0.52
0.60
0.61
0.53
0.75
0.87
0.91
Vitrinite
88.2
90.2
88.4
87.1
86.6
83.4
80.3
79.6
Liptinite
4.8
2.2
2.2
2.9
3.0
2.1
1.9
0.9
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Energy & Fuels
Inertinite
7.0
7.6
9.4
10.0
10.4
14.5
17.8
19.5
Vitrite
52.6
50.5
49.9
48.9
52.2
50.2
47.8
43.3
Inertite
3.2
4.4
10.7
13.6
11.5
16.0
21.7
25.1
Clarite-V
5.9
5.1
2.2
1.1
5.4
3.6
4.0
2.0
Vitrinertite-V
27.1
26.4
17.1
14.2
19.9
21.1
17.1
15.5
Vitrinertite-I
4.0
6.7
9.7
12.0
4.4
4.8
5.3
7.8
Durite-I
1.0
1.5
1.9
2.4
-
-
-
-
Trimacerite-V
2.5
2.1
5.0
6.4
2.9
0.8
0.7
2.5
Trimacerite-I
1.0
1.5
1.8
-
-
-
-
-
Carbominerites
2.7
1.8
1.7
1.4
3.7
3.5
3.4
3.8
MPG-1
88.1
84.1
74.2
70.6
80.4
75.7
69.6
63.3
MPG-2
9.2
14.1
24.1
28.0
15.9
20.8
27.0
32.9
403
404
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Page 36 of 62
405
Char production from single coal combustion was discussed in the previous section.
406
Table 8 presents a similar analysis conducted for the blended coals. The trend for the
407
coal char produced at different combustion temperatures is in agreement with the
408
microlithotype distribution in Table 7.
409
When blending the medium-volatile bituminous GLC with BGN, the content of group 1
410
char, which is the representative group with thin-walled char, decreases with the
411
increasing coal rank under the same temperature, while the opposite is observed for
412
group 2 char. In Table 8, for GB blends from the lowest calorific value to the highest,
413
group 2 char decreases at the higher temperature. Under the higher temperature, group
414
1 char tends to increase, while the thick-walled group 2 char tends to decrease. This
415
finding agrees with the previously discussed single-coal char results and may originate
416
from the more intense thermal effect, which affects the thin-walled particles more than it
417
does the thick-walled ones. This is also supported by the morphology of the char from
418
blended coals, as observed under the petrographic microscope in Fig. 4.
419
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Table 8. Classification of Chars (vol.%) Generated during Blending Combustion at
421
Different Temperatures GLC–BGN blends
KSN–BGN blends
GB54
GB56
GB58
GB60
KB54
KB56
KB58
KB60
Tenuisphere
29.03
15.94
15.23
5.67
1.06
0.29
-
0.25
Crassisphere
7.06
36.32
26.87
35.40
17.39
9.87
9.65
1.93
Tenuinetwork
30.15
6.97
4.85
5.80
0.84
5.15
1.00
5.13
Crassinetwork
18.84
28.08
22.73
31.45
21.12
11.18
21.27
18.35
Mixed solid
11.35
11.60
14.58
10.80
28.19
40.23
36.45
31.94
Solid
3.57
1.09
15.74
10.88
31.40
33.28
31.63
42.40
Group 1
66.24
59.23
46.95
46.87
19.29
15.31
10.65
7.31
Group 2
33.76
40.77
53.05
53.13
80.71
84.69
89.35
92.69
Classification at 900 °C
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Classification at 1,300 °C Tenuisphere
32.93
14.30
8.74
2.38
6.06
0.22
0.17
2.24
Crassisphere
4.63
28.46
37.03
39.28
17.39
15.37
16.33
10.72
Tenuinetwork
34.48
23.82
8.37
9.32
0.84
7.10
1.98
3.87
Crassinetwork
15.81
24.02
29.92
35.62
21.12
14.95
24.15
10.46
Mixed solid
9.88
8.90
10.08
8.00
23.19
38.20
32.42
39.02
Solid
2.27
0.50
5.86
5.40
31.40
24.16
24.95
33.69
Group 1
72.04
66.58
54.14
50.98
24.29
22.69
18.48
16.83
Group 2
27.96
33.42
45.86
49.02
75.71
77.31
81.52
83.17
422
423
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424 425
Fig. 4. Representative char samples produced from blended coals at 900 °C and
426
1,300 °C.
427
428
For all KB blends, because KSN is the carrier of an inertinite-rich microlithotype, the
429
associated char is dominated by group 2 char (thick-walled particles). From 900 °C to
430
1,300 °C, the char morphology changes similar to that observed for the GB blends: at the
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Page 40 of 62
431
higher temperature, the thin-walled char increases and the thick-walled char decreases.
432
However, a significant difference between the KB and GB blends is observed in Fig. 4,
433
which displays the char morphology under the petrographic microscope. A higher-rank
434
coal tends to produce thick-walled char particles, possibly because of the high aromaticity
435
of carbon chains therein, which yields stronger carbon chains [25]. This is also confirmed
436
by the image analysis: both the surface area and wall thickness of char particles increased
437
for higher-rank coals (see Table 9).
438
Considering the morphology of char in blended coals derived from the microlithotype
439
of the parent coals, the effect of the combustion temperature could be expected for each
440
blending case. Both the thermal effect and the reaction with oxygen during combustion
441
facilitate the transformation of microlithotypes into char particles, with stronger effects on
442
the thin-walled microlithotype so that it burns more intensely. Table 9 shows an increasing
443
volume percentage of thin-walled char particles, attributed to the thinning of the particle
444
walls (i.e., thick-walled particles are converted into thin-walled ones). Hence, while the
445
surface area of the thick-wall chars decreases, the thickness of the char body increases
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446
owing to the swelling of the carbon particles because the inertinite-rich microlithotype
447
reacts more slowly during heating and remains during swelling. The mixed-solid char
448
particles may be affected by the thermal effect and oxygen diffusion to the outer surface
449
of the particle wall because of the existing pores/voids and are then transformed into solid
450
particles. The trend of the GB char with regard to temperature is as expected: a higher
451
temperature yields fewer thick-walled particles, as observed experimentally by
452
Rosenberg et al. [19].
453
Fig. 4 displays the representative char morphology from each coal blend combusted at
454
900 °C and 1,300 °C. For both the GB and KB blends, the char morphology components
455
under the same temperature are not directly correlated with the calorific value and the
456
coal rank, unlike the case for single coals. For each blended coal under different
457
combustion temperatures, the trends are similar to those of the single coals (as the
458
temperature increases, the content of group 1 char increases while that of group 2 char
459
decreases) for the same reasons. As discussed previously for the single-coal char, image
460
analysis for the blended coals can identify the changes in the char under different
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Page 42 of 62
461
experimental conditions. In general, as the temperature increases, all char particles
462
change in size, and their surface areas decrease because of the interaction of the outer
463
wall surfaces with thermal and oxygen diffusion (Table 9).
464 465
Table 9. Geometrical Morphology of Chars Generated during Blending Combustion at
466
Different Temperatures. GLC–BGN blends GB54
GB56
KSN–BGN blends
GB58
GB60
KB54
KB56
KB58
KB60
Surface area [µm2] at 900°C Tenuisphere
387.45
521.57
515.67
546.76
350.13
410.15
387.32
435.55
Crassisphere
385.43
556.87
689.47
832.21
240.34
310.17
324.55
458.90
Tenuinetwork
425.57
745.67
987.34
1,132.4
368.45
456.23
425.90
576.35
497.56
836.39
1,015.9 1,250.4
425.12
460.25
467.76
689.56
653.27
867.34
987.10
587.34
550.33
588.78
887.60
Crassinetwor k Mixed solid
1,250.7
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Energy & Fuels
Solid
335.87
821.28
988.90
1,065.3
235.67
320.17
342.31
765.23
Surface area [µm2] at 1,300°C Tenuisphere
325.56
335.67
500.37
387.32
265.43
211.43
112.35
258.90
Crassisphere
235.67
503.25
625.77
750.13
157.45
167.54
121.57
234.21
Tenuinetwork
417.89
725.45
890.45
945.27
287.23
285.56
280.23
354.32
387.46
797.21
995.86
1,147.6
284.23
275.88
256.78 445.12
Mixed solid
489.27
657.32
1,143.7 1,157.8
320.12
368.35
355.10
624.43
Solid
285.65
789.45
1,034.6 1,143.3
121.24
157.45
250.45
550.33
Crassinetwor k
Wall thickness [µm3] at 900°C Tenuisphere
527.45
587.33
886.64
950.12
565.23
568.34
500.43 525.76
Crassisphere
565.76
643.87
987.65
1,154.4
487.45
453.78
447.76 1,025.6
Tenuinetwork
687.54
786.48
1,020.6 1,224.3
734.87
621.43
576.8
895.84
832.21
1,067.9 1,600.1
825.10
587.12
578.24 1,237.2
1,115.4
Crassinetwor k
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Page 44 of 62
Mixed solid
756.90
1,054.7 1,125.4 2,243.3
845.30
585.76
610.92 1,016.2
Solid
578.57
857.35
1,245.3 1,657.3
450.55
389.43
397.55 987.12
324.34
621.34
780.56
400.33
321.56 256.67 345.23
515.25
797.21
1,054.2
212.34
280.88 254.35 815.89
527.30
957.58
1,175.4
415.65 375.32
287.45 835.64
710.27
921.63
1,522.2
615.21 225.90
270.75 921.14
1,157.2 1,201.5 2,265.4
924.12 600.13
625.90 1,187.2
942.65
525.67 415.67
420.14 1,005.3
Wall thickness [µm3] at 1,300°C 287.3 Tenuisphere 9 335.3 Crassisphere 8 421.3 Tenuinetwork 5 Crassinetwor k
557.2 4 812.1
Mixed solid 7 734.2 Solid
1,355.8 2,367.4
7 467 468
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469
3.2 Petrographic analysis and DTF combustion experiment
470
3.2.1 Single coal combustion
471
The unburnt combustible fraction in the residual char collected after single-coal
472
combustion at different temperatures was measured, and the ratios of group 1 and group
473
2 according to the morphology classification are expressed as the composition of the
474
unburnt combustibles, as shown in Fig. 5. The unburnt combustible contents are higher
475
at the lower temperature than at the higher temperature, which is caused by the slower
476
reaction of the char wall at lower temperatures [16]. Referring to Fig. 5, BGN as the lowest
477
rank coal has the least amount of unburnt combustible because it has a higher content of
478
group 1 char than group 2 char. Group 1 char consists of thin-walled char particles with
479
weak carbon structures that react easily with thermal effects and oxygen diffusion. Under
480
both temperature conditions, the trend of unburnt combustibles among three coals follows
481
the coal rank. This is because, from the lowest to the highest coal rank, the composition
482
of group 2 chars (mainly composed of thick-walled particles) increases, and the low
483
combustibility of the thick-walled particles yields a high level of unburnt combustibles.
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Page 46 of 62
484
485 486
Fig. 5. Char type distribution in terms of the unburnt combustibles for single coals at
487
different temperatures.
488
489
As the reaction temperature increases, KSN exhibits a lower reduction rate in the
490
unburnt combustibles compared to BGN. As also proposed by Bailey et al. [25] and
491
Shibaoka [39], coal particles dominated by vitrinite generally undergo sudden combustion
492
and tend to form porous or vesicular char. Such char particles have thin walls, and thus
493
the intermolecular crosslinking is easily destroyed as the temperature rises.
494
As mentioned in Section 3.1.1, the composition of char particles (group 1 and group 2)
495
depends on the parent coal’s microlithotype. Furthermore, during combustion, thin and
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Energy & Fuels
496
porous char particles gradually become thinner and disappear, while dense and thick char
497
particles dominated by inertinite gradually become thicker with decreasing surface areas
498
under thermal effects. The particles generated from inertinite remain solid because they
499
are less affected by the increased temperature, and tend to form dense particles, thereby
500
exhibiting lower reactivity than lower-rank coal. These results are supported by the
501
tendencies of group 1 and group 2 chars with regard to temperature in the char
502
classification as well as the char particle morphology analysis results in Tables 4 and 5.
503
504
505
3.2.2 Blended coal combustion
506
Fig. 6 shows the unburnt combustibles for each blending combustion condition at
507
different temperatures on the calorific value basis, and the ratios of the char groups. Fig.
508
7 implies a correlation between the unburnt combustibles from the blends and the Rr%
509
under the same combustion conditions for both temperatures (900 °C and 1,300 °C). In
510
Fig. 6 (a), the results of GB blends can be largely divided into two regimes, two with lower
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Page 48 of 62
511
calorific values (GB54 and GB56) and the other two with higher calorific values (GB58
512
and GB60). In GB54 and GB56, the unburnt combustibles of the blends are reduced quite
513
significantly compared to that of the single GLC coal regardless of the temperature. This
514
is similar to the trend of the distribution curve in Fig. 3 (b), which indicates that BGN coal,
515
supplied in a relatively larger proportion, controls the overall reaction.
516
517 518
(a)
(b)
519
Fig. 6. Char group composition ratio in terms of the unburnt combustibles from blended
520
coals at different temperatures: (a) GLC+BGN (GB), (b) KSN+BGN (KB).
521
522
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Energy & Fuels
523 524
(a)
(b)
525
Fig. 7. Correlation between mean random vitrinite reflectance and unburnt combustibles
526
at different temperatures for single and blended coals with different calorific value bases:
527
(a) GLC+BGN (GB), (b) KSN+BGN (KB).
528
529
Factors affecting the unburnt combustibles can be clearly identified in Fig. 7 (a) for
530
GB54, whose Rr% value is identical to that of BGN coal. These phenomena indicate that
531
the combustibility is significantly influenced by the BGN content. The correlation
532
coefficient (R2) between GB blending coal’s mean random vitrinite reflectance with
533
unburnt combustible was 0.7569 and 0.8952 for 900 °C and 1,300 °C, respectively. As
534
for GB56, however, the overlapping random vitrinite reflectance region impedes the clear
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Page 50 of 62
535
identification of the coal type with a stronger influence on combustibility. In other words,
536
the amount of unburnt combustibles of GB56 is slightly higher than that of GB54 because
537
of the increase in Rr%, calorific value, fuel ratio, and ash content, but the difference is not
538
significant. At relatively low temperatures, the effect of BGN with a thin-wall char structure
539
is greater, and at higher temperatures, the effect of GLC, which exhibits a thicker-walled
540
char structure than BGN, is greater. This is similar to the char group and morphology
541
classifications based on the composition and the geometry of char particles under the
542
given temperature conditions, as shown in Table 8 and 9.
543
In contrast, the blended combustion results of GB58 and GB60 are dominated by GLC,
544
like in Fig. 6 (a) and 7 (a). The Rr% values are located in a similar range to that of single
545
GLC. At the lower temperature, the unburnt combustibles of GB58 and GB60 are nearly
546
equal. As their Rr% values are identical, in this case, we can conclude that their unburnt
547
combustibles are dominantly influenced by the Rr% value. This is also strongly influenced
548
by the char group proportion of each blending case, which has identical proportions of
549
group 1 and group 2 chars (Table 8). However, at the higher temperature, the unburnt
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Energy & Fuels
550
combustibles consistently increased as the calorific value increased. Although the amount
551
of unburnt combustibles is lower than that at the lower temperature, the blending fraction
552
of the low-rank coal decreased with the increasing blending ratio; therefore, the unburnt
553
combustible content was affected by the high-rank coal. In addition, the char wall structure
554
of low-rank coal with good reactivity became thinner or disappeared under high-
555
temperature conditions, resulting in more combustion residues of the high-rank coal,
556
which has relatively poor reactivity.
557
Meanwhile, in the KB blends, the coal rank increased as the calorific value increased
558
as shown in Fig. 3 (c), and the peak of the Rr% curve was clearly divided into two regimes.
559
As the calorific value increased, the influence of KSN coal became stronger as confirmed
560
in Fig. 6 (b) and 7 (b). In other words, the unburnt combustibles of Fig. 6 (b) and 7 (b)
561
according to the increase in the calorific value were affected by the ratio or the Rr% of
562
blending. Herein, in the lower calorific value regime (54 and 56), the KB blends, which
563
should have higher unburnt combustibles, showed lower unburnt combustibles than those
564
of the GB blends owing to the competition of the oxidation reaction between the coals in
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Page 52 of 62
565
the blended sample. When two coals have a large difference or gap in their ranks (as
566
represented by the random vitrinite reflectance in blended cases), the lower-rank coal
567
with the lower vitrinite reflectance value ignites rapidly during combustion, which helps to
568
ignite the higher-rank coal to improve combustion. As a result, the unburnt combustibles
569
are lower.
570
571
4. Conclusion
572
In this study, the char morphological characteristics of single and blended coals used
573
in Korean power plants were investigated using petrographic analysis to examine the
574
correlations between the char and the combustibility of different coals. The results can be
575
summarized as follows:
576
(1)
577
correlated with the microlithotype/macerals compositions from the parent coals. The char
578
from single or blended coals follows the microlithotype of the parent coals, and is not
579
correlated with the mean random vitrinite reflectance, rank, or the calorific value.
For both single and blended coals, the char produced during combustion is
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Energy & Fuels
580
(2)
Through image analysis by petrographic microscopy, the geometry (surface area
581
and the char wall thickness) of char and the unburnt combustibles of the char produced
582
during the combustion of single and blended coals was measured. Group 1 chars showed
583
an increase in volume in the high-temperature environment, while group 2 chars showed
584
a decrease, owing to the different char wall structures (thin vs. thick walls) interacting with
585
the thermal effect.
586
(3)
587
random vitrinite reflectance and coal rank at both low and high temperatures, and are
588
correlated with the group classification of the produced chars.
589
(4)
590
relatively low unburnt combustible levels are obtained from low-rank coal compared to
591
single-coal combustion. For the distribution with the overlapping reflectance, the
592
properties of each coal and the characteristics of each char in the blend should be
593
considered, rather than the influence of a specific coal.
The unburnt combustibles generated from single coals are influenced by the mean
For blended coals with different distributions of mean random vitrinite reflectance,
594
595
AUTHOR INFORMATION
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596
Corresponding Author
597
*C.H. Jeon,
[email protected]; Tel.: +82-51-510-3051; fax: +82-51-510-5236.
598
Author Contributions
599
1
Page 54 of 62
The authors contributed equally.
600
601
ACKNOWLEDGMENT
602
This research was supported by Science and Technology Support Program through the
603
National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT
604
(MSIT) (2017K1A3A9A01013746).
605 606
ABBREVIATIONS
607
ICPP, International Committee of Coal and Organic Petrology; DTF, drop tube furnace;
608
GCV, gross calorific values; AR, as-received basis; DAF, dry ash-free basis; GCV, gross
609
calorific value; MMF, mineral matter free basis; LRV, low-reflectance vitrinite; LRL, low-
610
reflectance liptinite; LRI, low-reflectance inertinite; TLR_Coal, total low-rank coal; HRV,
611
high-reflectance vitrinite; HRL, high-reflectance liptinite; HRI, high-reflectance inertinite;
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Energy & Fuels
612
THR_Coal, total high-rank coal; NAV, non-assignable vitrinite; NAL, non-assignable
613
liptinit; NAI, non-assignable inertinite; TNA_Comp, total non-assignable components;.
614
615
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