A proposed maceral index to predict combustion behavior of coal

S. Sua,*, J.H. Pohla, D. Holcombeb, J.A. Hartc

aDepartment of Chemical Engineering, The University of Queensland, Brisbane, Qld 4072, AustraliabACIRL Limited, 1 ACIRL St., Riverview, Qld 4303, Australia

cCRC for Black Coal Utilization, The University of Newcastle, University Drive, Callaghan, NSW 2308, Australia

Received 20 December 1999; accepted 25 July 2000

Abstract

To predict the combustion performance in pulverized coal-®red boilers, this paper examines existing indices and develops a maceral index

(MI). These indices were compared with the data of 68 coals and blends in a range of the mean vitrinite re¯ectance from 0.25 to 1.63. The

results showed that the fuel ratio and the mean vitrinite re¯ectance could qualitatively indicate the burnout of the coals and blends. The new

MI,

MI � L 1 V=R2

I1:25

HV

30

� �2:5

;

provides a useful correlation for the burnout of the coals and blends. The correlation coef®cient (r2) is 0.982 for the EER data, and 0.808 for

the ACIRL data. The MI also has potential to correlate ignition and ¯ame stability of the coals and blends. The MI predicts the burnout better

than the other indices. q 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Burnout; Flame stability; Maceral index; Prediction

1. Introduction

At present, there are two methods of predicting the

combustion behavior of coals and blends: experiment and

indices [1]. The ®rst one is a direct approach, i.e. to conduct

combustion experiments in test furnaces or operating plants.

This approach is expensive and requires a large quantity of

coal. The latter is predicting the combustion behavior by

using indices associated with the nature of coals.

Simple predictive indices of burnout and ¯ame stability

have been developed based on standard analyses of coal/

blends. Published simple indices for burnout prediction

include fuel ratio (FC/VM) [2], mean vitrinite re¯ectance

[3], percent of vitrinite with .0.96 random re¯ectance or

percent of vitrinite and inertinite with .0.96 random re¯ec-

tance [4]; and those for ignition and ¯ame stability are heat-

ing value, volatile matter and heating value of volatile

matter [5]. All of these existing indices for predicting the

burnout have large uncertainties. Consequently, this paper

developed a new index, the maceral index (MI), based on

maceral compositions, mean vitrinite re¯ectance and heat-

ing value. Examination of the existing indices and the new

MI was conducted based on the performance data of 68

coals and blends.

2. Experimental data

Table 1 summarizes the analysis of the burnout parameters

for the 68 coals and blends. The maceral volume percentage

was determined at Pennsylvania State University for the EER

data, and at the ACIRL for the ACIRL data. A sample of coal is

prepared as either a polished particulate block or a polished

block [6]. The block is examined using a re¯ected light micro-

scope and the macerals are identi®ed under an immersion

medium by their relative re¯ectance, color, morphology, and

¯uorescence characteristics. The proportion (volume percen-

tage) of each maceral is determined by a point-count proce-

dure [7]. In addition, the mean maximum re¯ectance of

vitrinite was determined in accordance with the standard [8].

The performance parameters of the coals and blends in

Table 1, including burnout, ignition and ¯ame stability,

Fuel 80 (2001) 699±706

0016-2361/01/$ - see front matter q 2001 Elsevier Science Ltd. All rights reserved.

PII: S0016-2361(00)00137-X

www.elsevier.com/locate/fuel

* Corresponding author. Present address: CSIRO Division of Exploration

and Mining, P.O. Box 883, Kenmore, Qld 4069, Australia. Tel.: 161-7-

3327-4679; fax: 161-7-3327-4455.

E-mail address: shi.su@dem.csiro.au (S. Su).

S. Su et al. / Fuel 80 (2001) 699±706700

Table 1

Burnout parameters of coals and blends (K, W stands for component coals; O, X stands for blends; L stands for unknown coals and blends)

Coal or blenda FC/VM R Liptinite

(% mmf)

Vitrinite

(% mmf)

Inertinite

(% mmf)

MI

Tests in the ACIRL furnace [1]

100A K 0.94 0.44 24.91 59.5 11.7 10.50

67A/33B O 1.31 0.63 17.1 54.9 26.1 2.02

67B/33A O 1.66 0.77 9.99 52.6 36.0 0.99

100B K 2.47 1.01 3.18 48.3 47.0 0.40

100C K 1.52 0.61 3.66 73.3 22.7 4.05

75C/25D O 1.57 0.63 3.72 64.0 31.4 2.08

50D/50C O 1.67 0.62 5.17 61.3 32.7 1.95

100D K 1.81 0.64 8.44 30.0 59.6 0.45

67A/33E O 1.14 0.61 4.74 78.2 15.8 4.91

33E/67A O 1.44 0.63 4.08 70.4 24.1 2.81

100E K 1.77 0.8 1.20 66.5 30.4 1.45

Tests in the EER furnace [4,15±17]

100FL W 1.14 0.476 9.3 69 21.7 3.54

100LR W 1.23 0.45 5.3 76.3 18.4 7.45

100PM W 1.13 0.427 7.8 78 14.2 12.27

70PM/30K X 1.19 0.536 4.9 80.7 14.4 8.78

50FL/50PM X 1.21 0.456 11.9 69.4 18.7 5.94

40LR/40PM/20K X 1.27 0.599 8.8 78.6 12.6 8.24

75FL/25K X 1.35 0.542 9.5 67.9 22.6 3.80

75LR/25K X 1.23 0.531 8.2 78.3 13.5 9.46

50LR/50PM X 1.16 0.426 12.9 68.6 18.5 8.09

50BC/50OM X 1.80 1.2 1.7 57.8 40.5 0.32

100BC W 2.28 1.243 0.8 46.6 52.6 0.20

100OM W 1.19 0.523 9.5 80.5 10 11.98

80OM/20SR X 1.30 0.588 9.4 65.2 25.4 2.47

70OM/30SR X 1.39 0.697 6.5 67.5 26 1.72

60OM/40SR X 1.59 0.743 11.8 69.4 18.8 2.60

70OM/30SC X 1.85 0.859 6.75 81.3 12.1 4.42

Tests in the ACIRL furnace [1]

ACIRL1 L 2.17 0.65 3.0 33.8 63.3 0.41

ACIRL2 L 2.02 0.45 8.3 17.8 73.8 0.22

ACIRL3 L 1.41 0.4 2.5 59.5 37.3 1.74

ACIRL4 L 1.50 0.43 5.8 59.2 35.0 1.62

ACIRL5 L 1.29 0.41 7.1 63.8 29.1 2.64

ACIRL6 L 2.59 1.05 5.1 33.6 61.3 0.21

ACIRL7 L 1.91 0.7 2.1 59.4 38.5 1.16

ACIRL8 L 1.48 0.76 2.9 72.7 24.4 1.42

ACIRL9 L 1.23 0.67 13.0 68.9 18.0 4.99

ACIRL10 L 1.62 0.82 3.2 70.0 26.8 1.44

ACIRL11 L 1.63 0.7 4.5 62.2 33.4 1.53

ACIRL12 L 0.96 0.4 11.6 86.3 2.1 156.7

ACIRL13 L 0.92 0.35 22.4 54.6 23.0 6.76

ACIRL14 L 1.57 0.67 9.0 53.2 37.9 1.36

ACIRL15 L 1.80 0.93 3.8 72.1 24.2 1.63

ACIRL16 L 1.99 0.71 3.5 45.3 51.2 0.64

ACIRL17 L 3.42 1.2 1.4 26.4 72.2 0.09

ACIRL18 L 2.64 1.2 0 80.4 19.6 0.98

ACIRL19 L 1.73 0.7 3.9 59 37.2 1.12

ACIRL20 L 1.78 0.61 5.3 30.1 60.7 0.49

ACIRL21 L 3.57 1.27 0.6 24.2 67.9 0.08

ACIRL22 L 1.14 0.34 8.6 89.3 1.7 237.4

ACIRL23 L 4.14 1.63 0 71.8 23.2 0.62

ACIRL24 L 1.45 0.62 9.2 46.6 34.7 1.38

ACIRL25 L 1.43 0.57 3.7 45.6 26.7 1.02

ACIRL26 L 3.31 1.14 0.6 30.4 61.9 0.12

ACIRL27 L 1.57 0.38 3.5 50.6 42.8 3.25

ACIRL28 L 1.59 0.7 4 33.9 39.8 0.31

ACIRL29 L 0.98 0.34 5.6 86 7.3 38.13

ACIRL30 L 1.00 0.5 10.2 82.7 7.1 23.33

were determined in the Australian Coal Industry

Research Laboratory (ACIRL) furnace [1,9] and Energy and

Environmental Research Corporation (EER) furnace [4]. Both

of the ACIRL and EER furnaces were built with the same

structure and schematic diagram. However, the ACIRL

furnace has a resident time of 3.2 s, and the EER furnace

2.4 s. The nominal ®ring rates are 150 and 176 kW for the

ACIRL and EER furnaces, respectively. Their schematic

diagram is shown in Fig. 1. The burnout was determined by

using the ash tracer technique [10,11]. The ash samples were

taken at residence times of 3.2 and 2.4 s for the ACIRL and

EER furnaces, respectively. Ignition and ¯ame stability were

assessed by using stand-off distance at zero swirl [1].

3. De®nition of the MI

The burnout of coal/blends depends on the amount of

volatile matter, which is quickly released from the coal,

the resultant physical structure of the char, and the chemical

and/or diffusion rate of char burning. This relation funda-

mentally depends on maceral compositions of the coal/

blend. Macerals are divided into three main groups of lipti-

nite, vitrinite and inertinite. Liptinite has the highest hydro-

gen content and volatile matter. Its volatile matter is roughly

twice that of the associated vitrinite, and as a result, liptinite

has been linked with ignitability and ¯ame stability [12].

The liptinite is signi®cant only in the pyrolysis stage of

combustion, and affects the igniting process. General in¯u-

ence of macerals on combustion behavior can be schemati-

cally described as follows [12,13]:

In addition, the effect of vitrinite and inertinite on char

burnout can be complicated and depends on how their

concentrations effect the physical structure of the char

according to the test results on a limited number of coals

obtained by Thomas et al. [14]. Thomas et al. [14] found

that vitrinite in the re¯ectance range approaching 1.5 forms

fused particles with largely inaccessible surface areas.

These particles have decreasing rates of burning. However,

they found that inertinite above a re¯ectance of 1.5 does not

form fused particles but retains and increases pore structure

during burning, and has an increased rate of burning with

higher re¯ectance. Therefore, we have analyzed a number of

semi-empirical relations to relate properties of coal/blends

to burnout. These expressions are based on four observed

trends in the burnout as follows:

1. The high volatile liptinite burns out rapidly.

2. Vitrinite burns out at a rate that depends on its re¯ec-

tance.

3. Inertinite is generally, but not always, dif®cult to burn.

4. Other factors being equal, the burnout depends on the

heat release of the coal/blends.

Finally, we arrived at a semi-empirical expression to

predict that the burnout results of experiments in two similar

pilot-scale furnaces. This expressed predicted burnout

increased with liptinite content and vitrinite content, but

decreased with vitrinite re¯ectance, and decreased with

inertinite content. These factors were combined into the MI.

MI � �HVF�2:5�RF� �1�

HVF � HV=30 �2�

RF � L 1 V =R2

I1:25�3�

where L is the percent by volume liptinite, mineral matter

free, normalized to 100%; V the percent by volume vitrinite,

mineral matter free, normalized to 100%; I the percent by

volume inertinite, mineral matter free, normalized to 100%;

S. Su et al. / Fuel 80 (2001) 699±706 701

Table 1 (continued)

Coal or blenda FC/VM R Liptinite

(% mmf)

Vitrinite

(% mmf)

Inertinite

(% mmf)

MI

ACIRL31 L 1.49 0.72 3.6 76.3 19.5 4.27

ACIRL32 L 0.99 0.4 15.8 76.9 7.3 34.79

ACIRL33 L 0.84 0.25 16.5 79.9 3.6 146.8

ACIRL34 L 1.69 0.74 7.9 55 37.1 1.06

ACIRL35 L 1.58 0.8 4.6 70.9 24.5 2.11

ACIRL36 L 3.70 1.29 0 31.5 68.5 0.10

ACIRL37 L 1.00 0.54 6 90 4 46.14

ACIRL38 L 1.11 0.45 8.7 83 8.3 20.84

ACIRL39 L 1.21 0.55 6.3 86.1 4.7 40.30

ACIRL40 L 1.08 0.58 4.7 82.3 1.1 218.9

ACIRL41 L 1.21 0.57 4.1 84.1 7.8 20.08

a A, B C D, E, FL, LR, PM, K, BC, OM, SR, and SC stand for the component coals. The numbers before the component coals are their weight percentages in blends.

S. Su et al. / Fuel 80 (2001) 699±706702

Fig. 1. A schematic diagram of the ACIRL and EER test furnaces.

Fig. 2. Correlation between the burnout and the MI.

R the mean maximum vitrinite re¯ectance; and HV is the

heating value of the coal/blend, air dried, MJ/kg.

HVF is called a heating value factor, and 30 MJ/kg (air

dried) is a typical heating value of coal. HVF indicates the

in¯uence of moisture and ash on the ignition, ¯ame stability

and combustion density. RF indicates the reactivity of the

coal/blend.

4. Prediction and discussion

4.1. Prediction of the burnout by the MI

Fig. 2 shows that, taking into account the slightly differ-

ent conditions between the ACIRL and EER furnaces, the

MI correlates most of the data. The correlation coef®cient

(r2) is 0.982 for the EER data and 0.808 for the ACIRL data

for pure and blended coals. There is one EER point that

appears to have a lower burnout than predicted. As shown

in Fig. 2, there are 68 coals and blends from the USA,

Australia, Canada, and Indonesia, which cover the mean

vitrinite re¯ectance from 0.25 to 1.63. The EER data is

within 0.2% absolute burnout. We could not assess the accu-

racy of the ACIRL data, but ACIRL claims the data is

within 0.2% absolute burnout. However, eight points

marked with 1 were omitted from the correlation of the

ACIRL data. Two of these points are concerned with the

burnout of a pair of blends containing coal C and coal D.

The reason for this discrepancy is being investigated.

We attempted to improve the data ®t by taking into

account the effect of better burnout of inertinite with

increasing re¯ectance [14] by adding a term in the numera-

tor of Eq. (3) containing inertinite and vitrinite re¯ectance.

The inertinite re¯ectance was only available for some coals

and blends in Table 1. These attempts only marginally

improved the ®t and resulted in more complicated expres-

sions for the burnout and are not presented.

In addition, we looked at using assumed rates of indivi-

dual maceral particle burnout to improve the correlation

coef®cient of the expression (1). In general, this approach

will result in improved ®ts, but requires reaction rates

measured on individual vitrinite and inertinite particles.

We decided not to use the measured rates, as these values

are not generally available and are hard to obtain on coals.

4.2. Better prediction of burnout by the MI than the fuel

ratio and the mean vitrinite re¯ectance

We tried ®tting a general relationship between the burn-

out and the fuel ratio for 68 coals and blends in Table 1.

Fig. 3 shows the fuel ratio qualitatively indicates the burnout

of coals and blends even though the correlation coef®cient is

somewhat low, 0.2 and 0.47 for EER and ACIRL data,

respectively.

S. Su et al. / Fuel 80 (2001) 699±706 703

Fig. 3. A general correlation between the burnout and the fuel ratio.

As shown in Fig. 4, we also tried to ®nd a general rela-

tionship between the burnout and mean vitrinite re¯ectance

for all the coals and blends. The mean vitrinite re¯ectance

also qualitatively indicates the burnout of coals and blends.

Comparing Figs. 3 and 4, we found that the correlation

coef®cient of linear regression of the burnout to the mean

vitrinite re¯ectance is similar to the fuel ratio, even though

the mean vitrinite re¯ectance seems to correlate with the

burnout better than the fuel ratio. In fact, the mean vitrinite

re¯ectance linearly correlates the fuel ratio with the correla-

tion coef®cient of 0.77 [1]. Thus, either the mean vitrinite

re¯ectance or the fuel ratio can qualitatively predict the

burnout of coals and blends.

Comparing Fig. 2 with Figs. 3 and 4, we can say that the

MI provides a better correlation than the fuel ratio and the

mean vitrinite re¯ectance as an index to predict the burnout

of the coals and blends. In addition, the MI is more sensitive

in assessing the burnout than the fuel ratio. For example, the

difference of fuel ratio between coal A and coal E is 0.83 in

Table 1, but for the MI, 9.05. Therefore, the MI appears to

be a good index to predict the burnout of coals and blends.

There should be no burnout problem for the coal/blends

with the MI . 3, however, burnout problems are expected

for the coal/blends with the MI , 1. It should be pointed out

that an error of ,1.0% in burnout could occur for some

coals and blends with the MI , 1.0. However, all these

coal/blends have low burnout in any case.

In addition, Pohl [4,15,17] developed an index, percent of

vitrinite with .0.96 random re¯ectance, to assess the burn-

out. It has been successful in assessing coals and blends with

intermediate vitrinite re¯ectance. However, it is not useful

for those with low or high re¯ectance. For example, the

percent of vitrinite with .0.96 random re¯ectance is zero

for the blends and component coals from 100FL to 50LR/

50PM in Table 1, except it is 0.25 for 75FL/25K. Then, the

index was modi®ed to use the percent of all maceral compo-

nents with .0.96 random re¯ectance. While this index

works reasonably, it has never been proved and is limited

in the same way as the percent of vitrinite with .0.96

random re¯ectance. Finally, limited data indicates the initial

temperature, determined in Thermogravimetric Analysis

(TGA) burning pro®le, might correlate burnout [1]. The

reason for this seems to be that the initial temperature corre-

lates in general with coal properties.

4.3. Potential for correlating ignitability and ¯ame stability

We found the MI also has potential to correlate the ignit-

ability and ¯ame stability. Fig. 5 shows the correlation

between the stand-off distance and the MI for 11 coals

S. Su et al. / Fuel 80 (2001) 699±706704

Fig. 4. A general correlation between the burnout and the mean vitrinite re¯ectance.

and blends from A to E (Table 1) tested in the ACIRL

furnace, and 16 coals and blends from 100FL to 70OM/

30SC (Table 1) tested in the EER furnace. It is obvious

that there is a relationship between the ignitability or

¯ame stability and the MI, particularly for the data of the

ACIRL furnace. The higher the MI, the better the ignitabil-

ity or ¯ame stability. The correlation coef®cient is 0.77 for

the ACIRL data, excluding one point marked with 1.

However, the correlation coef®cient is only 0.34 for the

EER data. A possible reason is that the tests in the EER

furnace were carried out at a higher ®ring rate and a lower

primary air ratio, compared with those for the ACIRL data.

These conditions reduced the effect of fuel properties on

the ignitability and ¯ame stability. The stand-off distance

was measured by eye and may contain signi®cant errors.

A relationship between ignitibility/¯ame stability and the

MI is tentative depending on more accurate experimental

data.

5. Conclusions

Based on the performance data of 68 coals and blends,

tested in the ACIRL and EER furnaces, this paper examined

the existing indices, including the fuel ratio and the mean

vitrinite re¯ectance, and developed the new MI to predict

the burnout. The important conclusions are:

1. The mean vitrinite re¯ectance and the fuel ratio can

qualitatively predict the burnout of coals and blends.

2. The maceral index, MI, correlates the burnout, and has

potential for correlating the ignitability and the ¯ame

stability.

3. There should be no burnout problems for the coals and

blends with the MI . 3, however, burnout problems are

expected for the coals and blends with the MI , 1.

Acknowledgements

The authors wish to acknowledge the Commonwealth

Government funding under its CRC for Black Coal Utiliza-

tion research program, and the Queensland Department of

Mines and Energy Q-Therm Program for its speci®c funding

for the blending project.

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