Evaluation of Char Characteristics and Combustibility of Low-Rank

37 importing country following China, India, and Japan [3]. Since these countries are all. 38 located in Asia, the Korean national policy requires the...
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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

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Combustibility of Low-Rank-Coal Blends with

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Different Reflectance Distributions

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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;

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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

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ABSTRACT. Petrographic analysis can provide valuable information about pulverized

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coal used in coal-fired power plants. In this study, petrographic analysis was used to

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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

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values and combusting them in a drop tube furnace, the unburnt combustibles in the char

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were analyzed. The coal rank, determined from the mean random vitrinite reflectance,

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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

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coal rank but had a strong relationship with the microlithotype of the raw coal. In contrast,

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for single coals, the unburnt combustibles at equal temperatures were affected by the

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coal rank. Morphological analysis of the char types revealed that the geometric tendency

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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.

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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

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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,

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along with the rising oil prices since the 2000s, countries highly dependent on imported

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resources, including the Republic of Korea, are implementing policies such as the flexible

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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

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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

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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

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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

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of coals, leading to the establishment of a correlation with reflectance, the reactivity

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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.

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2. Experimental section

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2.1 Petrographic analysis

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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

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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

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samples are ready to be used as coal petrographic sample. About 1 gr of coal sample

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was put into standard cylindrical mold (diameter ±32mm, height ±31mm), and mixed with

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epoxy resin and 1-2 drops of liquid catalytic chemical hardener to accelerate the

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compaction process [20].

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After completely stirred and mixing, the sample mold then safely keeps in open air

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temperature to get self-dried for about 3-4 hours. Then after 3-4 hours dried, to have

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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

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then underwent two preparation steps: grinding and polishing using automatic grinding-

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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.

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2.1.2 Petrographic analysis procedure

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An optical reflection-type microscope was used to measure the intensity of light

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reflected by the prepared samples. Standard setups were used to measure the vitrinite

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reflectance for ranking the coal or other types of carbon-derived/organic materials [21].

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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

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reflectance. Total magnification used in this research were 200x and 500x. The 200x was

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used to analyze the char morphology since it could cover many char particles, which was

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helpful in later image processing. The 500x magnification was used for the vitrinite

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reflectance, maceral and microlithotype analysis, using white light source. Because

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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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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

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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

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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

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Bailey et al. and Valentim et al. [25, 28].

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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

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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

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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

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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

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could generate a uniform temperature field in the reaction zone and provide temperatures

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up to 1,500 ℃, enabling the maintenance of constant particle temperatures as

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combustion progressed and the observation of the combustion characteristics of the fuel

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under relatively stable conditions. The experimental setup was composed of a reactor for

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high-temperature reactions, a feeding section for injecting coal particles, and a sample

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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,

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assuming particle slip velocities based on Stoke’s Law [33]. A total of 3 g of coal was

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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

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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

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values (GCV) of each coal samples for reaching specific calorific values. Table 2 shows

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the experimental parameters of the DTF. In each experiment, residual solid particles after

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combustion were collected by the cyclone, and the unburnt combustible fraction was

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measured using the ash tracer method according to the following equation [34].

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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

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char, respectively. The measurement was repeated three times, and the deviation of the

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unburnt combustible fraction from the mean value was within ±1.0% for single coals and

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within ±2.0% for blended coals.

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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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Stoichiometric ratio (λ)

1.16

214 215 216

3. Results & Discussion

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3.1 Petrographic analysis of single and blended coals

218

3.1.1 Single coals and their char

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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

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(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.

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From the petrographic analysis, the three coals have significantly different

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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].

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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

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(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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Energy & Fuels

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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Energy & Fuels

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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Energy & Fuels

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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Energy & Fuels

420

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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Page 38 of 62

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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Energy & Fuels

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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Energy & Fuels

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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