a review of the state-of-the-art in coal blending for power ... - CCSD

COOPERATIVE RESEARCH CENTRE FOR BLACK COAL UTILISATION 

Established and supported under the Australian Government’s Cooperative Research Centres Program 

A REVIEW OF THE STATE-OF-THE-ART IN 

COAL BLENDING FOR POWER GENERATION 

FINAL REPORT - PROJECT 3.16 

TECHNOLOGY ASSESSMENT REPORT 14 

by 

Prof Terry Wall*, Liza Elliott*, 

Dick Sanders**, and Ashley Conroy*** 

* CRC for Black Coal Utilisation 

** Quality Coal Consulting Pty Ltd 

*** Rio Tinto Technical Services 

May 2001 

Advanced Technology Centre, The University of Newcastle 

University Drive Callaghan NSW 2308 AUSTRALIA 

Telephone (02) 4921 7314 Facsimile (02) 4921 7168 

Email: black-coal@newcastle.edu.au

Black Coal CRC 

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Industry Participants 

ACARP Ltd Mr Ross McKinnon 

.......................................................................................................................... Mr Jim Craigen 

ARCO Resources Ltd........................................................................................ Mr William Ash 

BHP Innovation Pty Ltd ..................................................................................... Dr Michael Eamon 

.......................................................................................................................... Dr Louis Wibberley 

CS Energy ........................................................................................................ Dr Chris Spero 

.......................................................................................................................... Mr Peter Costelloe 

.......................................................................................................................... Mr Ivan Mapp 

.......................................................................................................................... Mr Adrian Hughes 

The Griffin Coal Mining Co Pty Ltd .................................................................... Mr Barry Eldridge 

Tarong Energy .................................................................................................. Mr Burt Beasley 

.......................................................................................................................... Mr Leigh Miller 

.......................................................................................................................... Mr Dave Gunn 

Stanwell Power ................................................................................................. Mr Des Covey 

BHP Coal Pty Ltd .............................................................................................. Mr Alan Davies 

.......................................................................................................................... Mr Sid McGuire 

Delta Electricity ................................................................................................. Mr Mal Park 

.......................................................................................................................... Mr Peter Coombes 

Oakbridge Pty Ltd ............................................................................................. Mr Barry Isherwood 

Pacific Power .................................................................................................... Mr Tom Bryant 

.......................................................................................................................... Mr George Wells 

.......................................................................................................................... Dr Allen Lowe 

CNA Resources ................................................................................................ Mr Rod Hall 

Peabody Resources.......................................................................................... Mr David West 

Queensland Dept of Mines and Energy............................................................. Dr Geoff Dickie 

.......................................................................................................................... Dr Rod Gould 

Rio Tinto (Pacific Coal) ..................................................................................... Mr Brian Horwood 

.......................................................................................................................... Mr Duncan Waters 

Rio Tinto (TRPL) ............................................................................................... Mr David Cain 

.......................................................................................................................... Dr Jon Davis 

Wesfarmers Coal Ltd ........................................................................................ Mr Peter Ashton 

Western Power ................................................................................................. Mr Keith Kirby 

.......................................................................................................................... Mr Jim Andrusiak 

Research Participants 

CSIRO .............................................................................................................. Dr John Wright 

.......................................................................................................................... Dr Jim Smitham 

.......................................................................................................................... Dr David Harris 

.......................................................................................................................... Dr Peter Nelson 

.......................................................................................................................... Dr John Carras 

.......................................................................................................................... Dr David French 

.......................................................................................................................... Dr Richard Sakurovs

Research Participants (cont) 

Curtin University of Technology......................................................................... Dr Barney Glover 

.......................................................................................................................... Prof R Van Berkel 

.......................................................................................................................... Prof Dong-ke Zhang 

.......................................................................................................................... Dr H B Vuthaluru 

.......................................................................................................................... Dr H M Yan 

The University of Newcastle.............................................................................. Prof Ron MacDonald 

.......................................................................................................................... Dr John Lucas 

.......................................................................................................................... Prof Terry Wall 

.......................................................................................................................... Prof Chris Hooker 

The University of New South Wales .................................................................. Prof David Young 

A.Prof R Harding 

The University of Queensland ........................................................................... Prof Don McKee 

.......................................................................................................................... Prof John Pohl 

.......................................................................................................................... Dr R Pagen 

.......................................................................................................................... A/Prof Victor Rudolph 

Dr J Joy 

Associated Parties 

ACIRL Ltd ......................................................................................................... Mr Greg Smith 

CRC for Clean Power from Lignite .................................................................... Mr Malcolm McIntosh 

Electricity Supply Association of Australia Ltd ................................................... Dr Harry Schaap 

J Happ Consulting............................................................................................. Mr Jim Happ 

Ultra-Systems Technology Pty Ltd .................................................................... Mr Lindsay Juniper

Cooperative Research Centre for 

Black Coal Utilisation 

Advanced Technology Centre 

The University of Newcastle 

Callaghan NSW 2308 

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Report Title: A REVIEW OF THE STATE-OF-THE-ART IN COAL BLENDING FOR POWER 

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Preface 

In 1999 ACARP identified the use of coal blends in power generation as a high 

priority area for research, and commissioned the Centre to provide a state of the art 

review. 

The review considered the available information on coal blends from two points of 

view – firstly, coal properties and their additivity and secondly, the performance of 

blends in pulverised fuel (pf) firing. The review has concluded that the level of 

understanding on properties is incomplete, and knowledge of performance is very 

poor for a number of plant performance issues. 

The report highlights areas for further research. Some tests were found to provide 

properties that were non-additive for blends, and/or provided a poor basis for 

predicting blend performance in a power station. These were: Hardgrove grindability 

index, crucible swelling number, ash fusibility temperatures, coal flow properties, 

volatile matter and crossing point temperature (for indicating spontaneous heating 

propensity). In addition, the following areas were indicated, for blends, as 

‘appropriate for future research effort, as properties are not readily related to plant 

performance and they also have a major impact on plant operations’: moisture, 

particle size and mineral composition (flow properties); nitrogen and ash fusibility 

(increased carbon in ash and ash deposition caused by NOx control); trace elements 

(changes in deportment); ash fusibility (deposition and ash character); sulphur (ash 

precipitation); nitrogen (NOx prediction). It is recommended that a model be created 

to use all properties to predict boiler performance changes when using blends. 

This project adds value to the existing body of knowledge on the characterization of 

coal blends previously reported by IEA Coal Research reports and established by 

Centre research by bringing it all together with a specific focus on its effects on coal 

combustion. The results of this work will assist export thermal coal suppliers in 

matching product to market needs. It also provides the current understanding of the 

effects of moving away from traditional feed stocks by blending the greater diversity 

of coals now available to generating authorities. 

Prof. Terry Wall 

Program Manager – Mineral Matter Reactions 

Black Coal CRC

ACKNOWLEDGEMENTS 

The authors wish to acknowledge the contribution of Ms Kathy Benfell, from the Department 

of Geology, The University of Newcastle, who assisted in providing a discussion on coal 

petrography, and Professor A Roberts, the Department of Mechanical Engineering, The 

University of Newcastle, who provided information on coal handling. The financial support of 

ACARP, and in-kind support from The Cooperative Research Centre for Black Coal Utilisation 

is also gratefully acknowledged. 

The permission of the International Energy Agency to reproduce significant sections from the 

IEA reports of A Carpenter and N Skorupska is also gratefully acknowledged. 

Project 3.16 State of The Art Review of Coal Blending for Power Generation Page 2

TABLE OF CONTENTS 

Acknowledgements ....................................................................................................................2 

Table of Contents .......................................................................................................................3 

Summary ....................................................................................................................................7 

Recommendations .....................................................................................................................8 

Coal properties ...................................................................................................................8 

Plant performance prediction............................................................................................10 

Further consolidation of knowledge and its useability......................................................12 

1 Introduction .......................................................................................................................13 

2 Blending: a summary review ............................................................................................14 

2.1 Why blend?.............................................................................................................14 

2.2 Definitions...............................................................................................................14 

2.3 Methodology...........................................................................................................14 

3 Important Coal Properties in blending: their testing, additivity and effects on power 

stations .............................................................................................................................19 

3.1 Proximate analysis .................................................................................................19 

3.2 Specific energy (calorific value, heating value) ......................................................32 

3.3 Total sulphur...........................................................................................................33 

3.4 Pyritic sulphur.........................................................................................................36 

3.5 Chlorine ..................................................................................................................38 

3.6 Ultimate analysis ....................................................................................................40 

3.7 Hardgrove grindability index (HGI).........................................................................43 

3.8 Abrasion index........................................................................................................47 

3.9 Crucible swelling number (CSN) ............................................................................49 

3.10 Ash fusibility (AFT) .................................................................................................50 

3.11 Ash analysis ...........................................................................................................53 

3.12 Trace elements.......................................................................................................56 

3.13 Coal flow properties................................................................................................58 

3.14 Size distribution ......................................................................................................59 

3.15 Petrographic analysis .............................................................................................60 

4 Other coal properties ........................................................................................................63 

4.1 Ash behaviour by advanced techniques ................................................................63 

4.2 Arsenic....................................................................................................................68 

4.3 Char reactivity.........................................................................................................68 

4.4 CO2 or Cm ..............................................................................................................69 

4.5 Crossing point temperatures ..................................................................................69 

4.6 Fixed carbon (FC) ..................................................................................................70 

4.7 Fly ash resistivity ....................................................................................................70 

4.8 Fuel ratio.................................................................................................................71 

4.9 Inherent moisture ...................................................................................................71 

4.10 Moisture holding capacity (MHC) ...........................................................................72 

4.11 Sulphate sulphur ....................................................................................................72 

4.12 Organic sulphur ......................................................................................................72 

4.13 Phosphorus ............................................................................................................72 

4.14 Relative density (RD) .............................................................................................72 

5 Specific Response to ACARP Research Priorities...........................................................73 


5.1 Blending Australian high rank coals with low rank coals........................................73 

5.2 Blending Australian high rank coals with high sulphur coals .................................74 

5.3 Blending Australian high rank coals with coals of different mineral matter 

composition ............................................................................................................74 

6 Technology transfer activities ...........................................................................................77 

7 Bibliography......................................................................................................................78 

Appendix 1 Supplementary reference tables .....................................................................84 

Appendix 2 Power station performance prediction indices ................................................88 

A2.1 Fuel ratio as a predictor of burnout efficiency ........................................................88 

A2.2 Sintering temperature for predicting fouling behaviour of coal ash........................89 

A2.3 Sodium in ash to predict fouling behaviour ............................................................89 

A2.4 Alkali metal content for prediction of fouling...........................................................89 

A2.5 Viscosity of laboratory ash for predicting slagging behaviour ................................90 

A2.6 The iron/calcium ratio to predict coal ash slagging propensity ..............................91 

A2.7 Base to acid ratio for predicting slagging behaviour: .............................................91 

A2.8 B/A x %S(db) to predict slagging propensity ............................................................92 

A2.9 Emission index: ......................................................................................................92 

A2.10 Erosion indices .......................................................................................................92 


TABLES 

Table 1: Summary of the plant performance issues recommended for further research...........7 

Table 2: Blending efficiencies of different stacking and reclaiming methods (after Zador, Fig. 

18, 1991) ...................................................................................................................16 

Table 3: Comparison of blending efficiencies for ash and sulphur (after Zador, 1991) ...........16 

Table 4: Blend additivity of main properties of power station feedstock ..................................20 

Table 5: Impact of key coal properties on power station plant performance ...........................21 

Table 6: The maximum operating flue gas temperature to avoid corrosion (Raask, 1985).....26 

Table 7: Manufacturers’ allowable mill outlet temperatures.....................................................29 

Table 8: The amount of liquid present in an ash sample at selected temperatures compared to 

the sample's deformation temperature (DT) (Gupta, 1998)......................................52 

Table 9: Table of key trace elements .......................................................................................56 

Table 10: The mode of occurrence of trace elements in coal described by Swaine and 

Goodarzi (1995). .......................................................................................................57 

Table 11: Classification of particle compositions into mineral groups......................................66 

Table 12: Summary of the issues associated with blending Australian coals with indigenous 

coals..........................................................................................................................76 

Table 13: Wall's table of the impact of coal properties on plant performance (Wall, 1988).....84 

Table 14: Su’s table of additivity of properties for coal blends (Su, 1999)...............................85 

Table 15: Skorupska’s table for the impact of coal quality on power station performance 

(Skorupska, 1993).....................................................................................................86 

Table 16: The boiler fouling predicted by ash sodium content (Raask, 1985).........................89 

Table 17: The value of the alkali metal content of coal with corresponding boiler fouling 

(Raask, 1985). ..........................................................................................................90 


FIGURES 

Figure 1: Types of stacking for blending (after Carpenter, 1995) ............................................15 

Figure 2: Methods of reclaiming (after Carpenter, 1995) .........................................................15 

Figure 3: Coal moisture content versus critical opening dimension (Roberts, 1988)...............24 

Figure 4: The interaction of NOx formation and carbon in ash when combustion utilises a low 

NOx burner. ...............................................................................................................32 

Figure 5: Sulphur Dioxide emissions as a function of coal sulphur content.............................34 

Figure 6: The relationship between deposit chlorine and fuel sulphur.....................................39 

Figure 7: Dependence of furnace wall tube corrosion (A, A’) and sulphate deposition (B) on 

chlorine content of coal .............................................................................................39 

Figure 8: NOX emissions as function of coal nitrogen content .................................................42 

Figure 9: The relationship between NOx formation and carbon in fly ash (Carpenter, 1995) ..42 

Figure 10: Mill power requirement as a function of HGI for blended and unblended coals .....45 

Figure 11: Mill Product Fineness as a function of HGI for Blended and Unblended Coals .....46 

Figure 12: 60% Coal ‘A’ + 40% Coal ‘B’ – Distribution of blend components in size fractions 46 

Figure 13: 40% Coal ‘A’ + 60% Coal ‘B’ – Distribution of blend components in size fractions 47 

Figure 14: Relationship between optimum grinding pressure in spindle mills and HGI...........47 

Figure 15: Electrical resistivity of coal ashes: A, low-sodium, low-sulphur coal; B, low-sodium, 

high-sulphur coal; D, high-sodium, high-sulphur coal. (Raask, 1985)......................55 

Figure 16: The effect of ash composition on the collection area of an electrostatic precipitator. 

(Paulson)...................................................................................................................55 

Figure 17: The partitioning of trace elements. Group 1 elements are found predominantly in 

the ash, group 3 elements are predominantly in the gas phase, and group 2 are 

mixed between the two states. (Clarke & Sloss, 1992) ............................................58 

Figure 18: The calculated grade efficiency of a selected electrostatic precipitator (Benitez, 

1993). ........................................................................................................................60 

Figure 19: Schematic illustration of Pearson’s (1991) plots of the vitrinite reflectance 

distribution of a single high-volatile bituminous coal (A), a blend of three bituminous 

coals (B), and reflectance of all the maceral components of a low volatile bituminous 

coal (C). From Taylor et al. (1998)............................................................................62 

Figure 20: Schematic diagram of TMA apparatus, and ash sample assembly prior to heating. 

..................................................................................................................................64 

Figure 21: CCSEM mineral detection process.........................................................................65 

Figure 22: Experimental output from an XRD analysis of coal ash..........................................67 

Figure 23: Typical fly ash resistivity profile as a function of temperature ................................71 

Figure 24: Unburnt Combustibles as a function of Fuel Ratio for Unblended and Blended 

Coals .........................................................................................................................88 

Figure 25: The capture efficiency, or formation of deposit of soda-lime glass and the 

corresponding particle viscosity................................................................................90 

Figure 26: The FeO-CaO-MgO equilibrium phase diagram showing the eutectic at 1160°C..91 


SUMMARY 

The review has considered the available information on coal blends from two points of view – 

firstly, coal properties and their additivity and secondly, the performance of blends in 

pulverised fuel (pf) firing. The review has concluded that the level of understanding on 

properties is incomplete, and knowledge of performance is very poor for a number of plant 

performance issues. 

The review has highlighted several research topics for which research is needed. 

Tests on the following coal properties require further research. These properties are not 

additive, in that the blend property is not the weighted average of the properties of the 

individual coals, and they also provide a poor basis for predicting blend performance: 

Hardgrove grindability index 

Crucible swelling number 

Ash fusibility temperatures 

Coal flow properties 

Volatile matter 

Crossing point temperature 

The following areas are appropriate for future research effort, as properties are not readily 

related to plant performance and they also have a major impact on plant operations: 

Coal property Plant aspect Plant performance issues 

moisture, 

particle size, 

mineral 

composition 

Coal handling Flow properties of blends 

nitrogen, 

Boiler NOx control causing increased carbon in ash and 

ash fusibility 

ash deposition 

trace elements Boiler Trace elements: changes in deportment with 

blends 

ash fusibility Boiler Deposition and ash character in blends 

sulphur Particulate 

removal 

Precipitation of ash from blends 

nitrogen NOx control Prediction of NOx from blends 

all Entire plant Model for the changing performance of a boiler 

with blended coals 

Table 1: Summary of the plant performance issues recommended for further research. 

This report summarises the understanding of blends and their impact on pf plants identified to 

date and elaborates on the key areas recommended above for future research on blends. 


Coal properties 

RECOMMENDATIONS 

Most of the commonly measured coal properties are additive for blends. However, some 

analytical tests for coal properties require consideration and the authors recommend more 

appropriate techniques be developed to provide the valuable information the industry looks for 

in these tests, as noted below. 

Hardgrove grindability index 

The Hardgrove grindability index has limitations in its use for explaining the behaviour of coals 

in crushing and grinding mills. The coal is crushed to less than 1.18 mm and any portion of 

the coal less than 0.6 mm is rejected. As this size fraction represents the more friable 

material, the test provides results on the least friable materials in the coal. When weathered, 

the coal will lose strength and an increased proportion of the sample will be removed, thereby 

producing an erroneous result. Because a different fraction of the coal can be removed at 

each test, depending on the sample and the grinding method, a coal with a high proportion of 

friable material (up to 50%) could possibly be considered equivalent to a coal with only a 

small proportion. This test is unsuitable for the comparison of individual coals, let alone coal 

blends. The authors suggest a revised test is required to be designed before any 

experimentation on the grindability of blends is attempted. 


Crucible swelling number is not routinely used as a test on thermal coals and has found 

relevance in coke making arenas, where the swelling behaviour of the coal effects the size 

and strength of the resulting coke. However, it is used as an indicator of char blockage on 

burner mouths in the power station arena. The test is completed by placing 1 gram of finely 

ground coal in a sealed crucible and heating over a burner. The sample is removed from the 

crucible and cooled and the size of the resulting button measured against standard profiles. 

Unfortunately, the test gives no indication of the size the coal has swollen to before any 

collapse, due to limited strength or effects of handling. Under pf conditions, the collapse 

experienced due to limited strength will most probably differ from that in the test, making the 

results of the test unsuitable for predictions based on swelling. The swelling character of the 

coal as measured by this test appears to have no relevance to the adherence of char to 

burners, even though it is used for this purpose. Prediction of coal burnout, and the resulting 

ash particle size of the coal, may be possible based on knowledge of the swelling behaviour 

of coal, but this may be more reliably obtained from total reflectograms. The char shape and 

size may be predictable (through correlations being developed) from reflectograms, which 

also allows calculation of char combustion rates and prediction of ash coalescence and 

fragmentation. 

Ash fusion temperatures (AFT) 

The ash fusion (or ash fusibility) temperature test is highly relied upon by the thermal coal 

industry to provide an indication of the likelihood of deposition within a pf boiler. The test aims 

to provide the temperatures at which the coal ash first deforms or becomes sticky 

(deformation temperature), when it is likely to form dense deposits because it has a tendency 

to agglomerate (sphere and hemisphere temperatures) and when the ash will form a slag 


which will flow down a boiler wall (flow temperature) (Raask, 1985). However, Gupta (1998) 

has shown that, at the deformation temperature, a significant amount of liquid is present in 

some samples, significantly overestimating the temperature at which ash becomes sticky. The 

significant variation in the amount of liquid present in ash samples suggests that this test 

cannot reliably predict difficult fouling and slagging problems, even if the test overestimates 

the temperature at which deposition will occur. Some difficulty has also been observed in 

obtaining similar AFT results from different laboratories, particularly for certain Australian 

coals where unreacted illite is responsible for liquid formation, which also casts doubt on the 

value of this test. 

Ash fusion temperatures do not provide any information on the sintering behaviour of the ash. 

Typical sintering temperatures for coal ash lie between 600°C and 1000°C, well below typical 

ash fusion temperatures for coal ash. More accurate techniques than ash fusion temperatures 

for measuring the fusibility behaviour of coal ash are now becoming available. One such 

technique is the thermomechanical analysis (TMA) of ash, which can be repeated in different 

laboratories without significant deviation in results. Thermomechanical analysis is completed 

by measuring the change in dimension of an ash sample while it is continuously heated. The 

main variable in this test is the heating rate applied to the sample. Various components of the 

ash effect the fusibility of the ash and these may be reflected in the change in dimension of 

the ash with temperature. However, more work is required to ensure the adequate utilisation 

of information in TMA results for coals and coal blends before its inclusion routinely in 

specifications for testing or marketing. 


The crossing point temperature, or relative ignition temperature (RIT), test is designed to 

indicate the comparative propensity of a coal to spontaneously heat. As the ignition 

temperature of a coal is dependant on many variables (test furnace conditions, including 

heating rate, sample mass and particle size and the availability of oxygen for combustion) the 

test is relative to other coals and does not provide a set value. 

When this test is conducted, the temperature of the sample coal and a furnace is measured 

while the furnace is heated. Once spontaneous heating starts, the temperature of the coal 

rises dramatically and heats to a temperature above the furnace temperature. The 

temperature at which the temperatures of the furnace and the coal are equivalent is the 

crossing point temperature. Work is required to evaluate its value to plant operations involving 

blends. 

Volatile matter 

In a pf furnace, coal experiences high heating rates (up to 10 6 °C/s, (Carpenter, 1995), which 

produce very fast devolatilisation. When volatile matter is determined in a laboratory, coal is 

heated from room temperature to 900°C for 7 minutes. The heating rate is 2°C/s. Elliott (1981) 

notes that the volatile matter produced from a coal is a strong function of heating rate. 

Therefore, the amount of volatile matter produced in laboratory conditions has no relevance to 

the amount of volatile matter produced in a boiler. If volatile matter is to be adequately used to 

predict behaviour – either flame ignition or coal burnout - within a boiler, a more appropriate 

test is required. 


Plant performance prediction 

Many of the effects on a pf plant of blending coal are not predictable based on the measured 

property of the blend. This indicates the wide variety of areas in which research can be 

completed, but as yet the understanding of the complex processes involved has still made 

prediction of coal performance in various aspects of the plant very difficult. In many cases, 

prediction of the behaviour of a single coal requires significant knowledge of the plant in which 

the coal is being fired. Many mechanisms can control the behaviour of the coal or ash in each 

aspect of the plant, depending on the coal composition, particle size and plant operation, 

making prediction of any kind difficult. Therefore prediction of blend behaviour is problematic 

unless there is a direct relationship between the coal property and the plant performance, 

such as the amount of ash in the blend as measured by the proximate analysis and the 

quantity of ash to be handled in a plant. 

Several areas have been highlighted below as needing further research. These represent the 

areas that the authors believe will have the largest impact on the lack of current knowledge, 

and represent the greatest benefit to the Australian coal industry. 

Flow properties of blends 

A significant understanding of the various properties of the coal, such as the effect of 

moisture, fines and mineral components that effect flow properties, has been presented in the 

literature. However, when blends are utilised, the impacts of these properties are somewhat 

unknown, for the blend tends to adopt much of the behaviour of the coal that is most difficult 

to handle. The ability to predict the behaviour of blends would enable the impact of the blend 

on coal handling to be determined without significant testing. Such correlations are as yet 

undetermined, and work to progress their development is recommended. 

The impact of NOx reduction on coal burnout and deposition 

NOx emissions from power stations utilising low NOx burners are usually controlled by altering 

the operating conditions of the burner. Unfortunately, this also results in an increase in carbon 

in ash and often increases the amount of ash deposition associated with iron compounds in 

the coal’s mineral matter. When a single coal is used, the decreased burnout of a given coal 

can be predicted based on operational experience. Generally the change in NOx and burnout 

follows a predictable trend, with the absolute value of the trend line dependant on the volatile 

matter of the coal. However, no knowledge of the behaviour of blends in this manner has 

been reported. It is unknown if the blend falls between the trends produced by the individual 

coals in that blend or if it occurs at another position on the figure. Pilot scale or full scale tests 

are necessary in order to establish such relationships for blends. 

Trace elements and changes in deportment with blends 

Due to increasing government regulations, the release of trace elements from coal into the 

environment is fast becoming a serious issue for the Australian coal industry. Work currently 

being undertaken is considering the deportment of these trace elements into the gas phase 

and collection of these elements by the ash. In these studies, the results have generally been 

published as a split between the gas phase and the ash, that is they show what proportion of 

the element, as a percentage, resides in the gas phase. However, just as sulphur can be 

captured by calcium based species and other basic ash components, sorbents for trace 


elements are expected to exist. Senior (2000) found that As and Se were collected from the 

gas stream by components of the ash. Arsenic appeared to react with calcium to form calcium 

arsenate but the reactant that appeared to be capturing selenium could not be determined. 

The addition of a coal to a blend may improve the performance of a plant, in regards to its 

trace element emissions, due to the presence of particular species in the ash of that coal. 

Scavenging by fly ash will also depend on the ash surface area, and hence its fineness. 

Research projects on trace element deportment should therefore also consider blends. 

Deposition and ash character in blends 

At present, deposition in a boiler is one of the most difficult aspects of plant operation to 

predict. This is mainly due to the non-linear relationship between the composition of the ash 

and its fusibility and melting behaviour, and the inadequacy of existing analytical techniques. 

New techniques which provide a more accurate picture of the ash behaviour have been 

developed in the past few years, but more research is required to ensure that the information 

provided by these techniques is interpreted correctly by applying them to real deposition 

situations. For example, the data provided by thermomechanical analysis has been used to 

explain fouling and slagging within furnaces, but has not been proved to provide adequate 

information that will allow prediction of deposition. As the ashes of the coals in blends interact, 

the relevance of such techniques to combustion utilising coal blends also needs to be 

considered. Work on deposition, that enables prediction of problems within boilers from 

individual coals and blends, should be supported. 

Precipitation of ash from blends 

One of the greatest advantages Australian coals hold is their low sulphur content. The 

industry is encouraging operators in other countries to consider blending Australian coals with 

their feed stock to reduce SOx emissions. However, reduced sulphur contents of the ash are 

thought to decrease the operating performance of electrostatic precipitators, and a strong 

impact on particulate removal performance may cast doubt on the value of lower sulphur 

Australian coals. Some rules of thumb exist, based on sulphur content, to guide operators in 

electrostatic precipitator performance, but these were produced on British coals, and must be 

validated for blends of Australian coals with overseas coals. 

Resistivity of ashes is measured on ash generated from full-scale boilers, from pilot scale 

combustors, or from drop tube combustion experiments. The surface layers responsible for 

the conductive path, necessary for required resistivity levels, are formed during the 

combustion process and the cooling of ash. Resistivity is not additive, and prediction of 

performance will be improved by research into the reasons for this, particularly for coals of 

differing sulphur levels. 

Prediction of NOx for blends (or single coals) 

As NOx forms from the nitrogen associated with the carbon in the coal, the volatiles of the 

coal and air nitrogen, and as NOx formation is dependant on operating conditions, it is 

generally difficult to predict NOx emissions for operating plants. Generally, if the nitrogen 

associated with a coal increases, operators will expect to observe an increase in NOx, and will 

alter operating conditions on this basis. Decreasing the oxygen concentration at the burner, to 

limit NOx formation, can result in significant slagging, and may be unnecessary as the form of 


the nitrogen associated with the coal is important. Knowledge of the reaction rate of each 

form of nitrogen can allow the final NOx concentration to be calculated from the operational 

parameters (i.e. oxygen concentration around burner, and gas temperature). Estimation of the 

NOx produced from coal nitrogen and operating conditions is possible with limited accuracy, 

and with less accuracy for blends. 

Model for the changing performance of plant with blended coals 

It is clear that the many facets of the pf plant interact: changing an operating condition of the 

plant to account for one aspect of the coals' character may significantly impact on areas of the 

plant not considered. As a simple example, changing a coal in a blend to reduce costs may 

increase the total moisture, resulting in a decrease in flame temperature, which will effect the 

heat transfer in the furnace and may alter the deposition of ash. The increased gas volume 

associated with increasing moisture will decrease the operating efficiency of particulate 

removal systems and any de-SOx plant. As the interactions within the plant are so complex, it 

would be unreasonable to expect an operator to ensure that changing one simple operating 

parameter does not have a negative impact on other areas. To assist operators with such 

decisions a model of the plant, including these interactions, should be developed. Even a 

listing of effects would be useful. This is a significant task. 

Further consolidation of knowledge and its useability 

The report presents a summary of current knowledge provided in the literature, with 

interpretations by the group commissioned by ACARP for the project. The outcomes given 

are not quantitative, and an extension of this effort would be to develop software incorporating 

a coal blending adviser, with calculated properties and indications of performance based on 

the average as well as individual coals. 

To ensure the value of the report and the future directions of research are optimised, the 

group suggests a survey of industry personnel who receive a copy of the report be completed. 

The survey would ask the participant to identify issues, both covered and not covered in this 

report, which they have experienced when coals are blended. This would confirm the findings 

of the report and ensure actions based on the report and any further work in this area would 

be well grounded. 

The value of reports from IEA Coal Research has been highlighted by the study. One such 

report – A Carpenter, Coal blending in power stations, IEACR/81, IEA Coal Research, July 

1995 – has been an excellent source summarising knowledge that prevailed prior to its 

release. We have interpreted some of the work reported somewhat differently, but the quality 

and comprehensive nature of the report has been evident. We recommend that Australia reestablishes 

its membership of IEA Coal research. 


1 INTRODUCTION 

Most coal properties are additive when applied to coal blends. That is, the value of the 

property for the blend can be determined from the property of the individual coals involved. 

Some tests used to determine particular coal properties do not use a representative sample of 

the whole coal (Hardgrove grindability index) or, because of the empirical test conditions, do 

not provide appropriate information for its use in the required application (crucible swelling 

number and volatile matter). Other tests do not provide a linear result for the blend when 

compared to the test result for the individual coals (ash fusion temperatures), ensuring that a 

test result for the blend itself must be obtained. Due to imperfect blending practices, these 

test results often do not provide an indication of the blend behaviour in a pf furnace. 

Current knowledge of plant behaviour for combustion of individual coals in some areas is 

adequate for predicting the behaviour of a blend. However, in many areas of a pf plant, 

prediction of performance of a blend is difficult and requires further research to provide 

acceptable accuracy in the prediction. In several cases, the behaviour of individual coals, in 

terms of their handling, combustion and waste stream characteristics, cannot be explained 

adequately nor related to coal properties, and further research is required to predict coal 

performance. 

The following discussion highlights the analytical techniques used to determine coal 

properties, and indicates their additivity for blends. The usefulness of these properties in 

terms of predicting power plant performance is discussed, and limitations in utilising coal 

property data are highlighted. As blending practise strongly impacts on the homogeneity of 

the blend, and therefore its behaviour in a pf plant, the discussion starts with an overview of 

blending methodology. 


2 BLENDING: A SUMMARY REVIEW 

The following is a summary of the relevant aspects on coal blending methodology, from 

Section 3 of Coal Blending For Power Stations, Anne M Carpenter, IEACR/81, July 1995. 

2.1 Why blend? 

Blending is necessary for many reasons. These include: indigenous coals may be too low in 

rank and/or high in ash; traditional feed coals have some quality deficiencies, which need 

compensating for; power stations have design limitations. 

2.2 Definitions 

Homogenisation is the processing of one type of material so that the inherent fluctuations in 

respect of quality and/or size distribution are evened out. 

In blending the aim is to achieve a final product with a well defined composition, from two or 

more coal types, so that the elements are very well distributed and no large pockets of one 

type can be identified. 

In mixing, traces of the individual components can still be identified. 

2.3 Methodology 

Blending is either by (i) placing the coals in layers, in their correct proportions, in the same 

stockpile, then reclaiming across the full face or (ii) placing the coals in different stockpiles 

and blending as they are reclaimed onto belts, another stockpile, or into bins, silos or 

bunkers. Some coals need to be homogenised before they are put into blends. 

Common methods of stockpile blending are shown in Figure 1. 

Most effective blending methods are chevron and windrow. The latter requires a slewing 

boom. It provides the minimum size segregation and the greatest blending efficiency. The 

ends of blend stockpiles are not representative and should be recycled to another pile (note 

that if the ends are not representative, then neither is the middle). 

For smaller operations, blending is often by reclaiming from different stockpiles with front-end 

loaders, and layering onto the blend stockpile with a bulldozer. This minimises spontaneous 

combustion risk, but is more mixing than blending, with higher standard deviation in the end 

product. 

Some common methods of reclaiming from blended stockpiles are given in Figure 2. 

Blending efficiency is the ratio of the variation of the individual components before stacking to 

the variation after reclaiming. This is improved if there is a bin between the blend and its end 

use. 

The highest blending efficiency at a conventional plant was found (Zardor, 1991) to result 

from a combination of windrow blending and pilgrim step reclaiming with a slewing bucket 

wheel reclaimer. For bridge style reclaimers, those with a drum gave better efficiencies than 

those with a single wheel. 


Strata 

Chevron 

Chevron-windrow 

Figure 1: Types of stacking for blending (after Carpenter, 1995) 

Figure 2: Methods of reclaiming (after Carpenter, 1995) 

Strata or skewed chevron 

Windrow 

Chevcon 

Portal 

scraper 

side 

Surprisingly, at a special blending plant, the relative efficiencies of windrow and chevron 

blending depended on whether ash or sulphur was the critical factor in the resultant blend. 

This outcome seems inexplicable. Zador gives efficiencies for windrow blending of five coal 

types, based on V and S. He defines blending efficiency as: 

Blending efficiency = Variations before stacking (@95% probability) 

Variations after reclaiming (@95% probability) 


Zador's Figure 18 gave blending efficiencies for different stacking rates, blending methods 

and reclaim methods. Reclaim rates were taken to be constant, at 2000 to 4000 t/h. Table 2 is 

a summary, and is for stacking rates of 1000, 2000 and 6000 t/h only. Obviously the number 

of windrows or chevrons, and hence the degree of blending, is inversely proportional to the 

stacking rate (assuming constant stacker travel rate). Efficiencies for rates between 2000 and 

6000 t/h can be reasonably estimated pro rata. 

Reclaim Stacking Chevron/Windrow 

Blending Efficiencies 

Chevron Windrow 

Method Rate t/h Ash Sulphur Ash Sulphur Ash Sulphur 

Bench 1000 1.42 1.11 1.72 1.26 2.25 1.40 

2000 1.34 1.09 1.58 1.21 2.01 1.32 

6000 1.28 1.06 1.51 1.17 1.86 1.26 

Block 1000 1.50 1.13 1.87 1.31 2.58 1.48 

2000 1.41 1.11 1.71 1.25 2.26 1.39 

6000 1.35 1.08 1.61 1.21 2.07 1.33 

Pilgrim Step 1000 1.59 1.16 2.02 1.37 2.87 1.57 

2000 1.48 1.14 1.83 1.30 2.48 1.46 

6000 1.41 1.10 1.71 1.23 2.24 1.39 

Table 2: Blending efficiencies of different stacking and reclaiming methods (after Zador, Fig. 18, 

1991) 

The ratio of the blending efficiencies for S to those for ash, for the same situation, are further 

perplexing, as shown in Table 3. 

B. E. Ash / B. E. Sulphur 

Reclaim Stacking Chevron/ Chevron 

Method Rate (t/h) Windrow Chevron Windrow 

Bench 1000 0.78 0.73 0.62 

2000 0.81 0.77 0.66 

6000 0.83 0.77 0.68 

Block 1000 0.75 0.70 0.57 

2000 0.79 0.73 0.62 

6000 0.80 0.75 0.64 

Pilgrim Step 1000 0.73 0.67 0.55 

2000 0.77 0.71 0.59 

6000 0.78 0.72 0.62 

Table 3: Comparison of blending efficiencies for ash and sulphur (after Zador, 1991) 

This suggests that the disparity between the blending efficiency for sulphur and that for ash is 

less at faster stacking rates i.e. when there are less cross sections of each blend component. 

It also suggests that the disparity is greatest for windrow blends. Neither of these outcomes 

seems logical. On the other hand it suggests that slower stacking rates (more component 

cross sections) and windrow blending improves the blending efficiency for ash at a greater 

rate than it does for sulphur. Again, this is inexplicable. 

Bins (including silos and bunkers) may be used to blend different coals, or to homogenise 

coals reclaimed from blended stockpiles. Because of their relative capacities, bins are often 

used for the "live" blending of coals reclaimed from different stockpiles. See also belt 

blending. 


Bin geometry usually precludes FIFO (first-in, first-out), the deviation ranging from minimal to 

extreme, depending on the segregation caused by hang-up. So bin blending efficiency is a 

function of the individual coal flow properties and bin geometry. 

In belt blending, different coals are loaded into separate bins, and blended by discharging 

them directly onto a common belt at controlled rates. McGlinchey, Jones and Marjanovic 

(1999) discuss the variances obtained within conical piles, from compartmented hoppers, and 

from belt blending. They conclude that "feeder belts discharging onto a central conveyor belt" 

and "compartment hoppers discharging onto a common belt … were shown to give very 

similar levels of variance in the proportioning of component coals, over a wide range of 

discharge conditions". 

Nine of eleven power stations surveyed by Gunderson and others (1994) blended the coals 

on belt conveyors. Evans and others (1991) stated that, at one USA power station, blends of 

subbituminous and bituminous coals could be controlled to within an accuracy of 1% using 

belt scales and variable speed feeders. At another site a 1% accuracy was achieved for three 

coals blended on a belt conveyor, which ran below each stockpile, using rotary plough 

feeders. 

Meiners (1990) describes a sophisticated system at an American power station for blending 

high and low sulphur coals, with the ratio decided by monitoring stack SO2 emissions. Details 

of the system are in Carpenter, 1995, page 22. 

During a visit to the USA in 1991, one of the authors of this report visited a high sulphur mine 

in Ohio, where their washed product was blended about 4:1 with low sulphur coal that had 

been barged up-river from mines in the south. The blend produced SO2 emissions from the 

adjacent power plant, conforming to the licence specification. The system involved a real-time 

analyser, coupled with a sophisticated logic system, to feed the low sulphur coal onto the belt 

carrying the high sulphur coal. Maximum precision was essential, to (i) ensure power station 

compliance on SO2 emissions and (ii) minimise the use of the expensive, imported blending 

coal. Note that the mine has since been forced to close, as a result of the more stringent 

emission requirements introduced in 1995. 

Blending control may be done by either the feedforward or feedback methods. For 

feedforward control an analyser on each of the individual coal streams feeds their quality 

(say, ash) value forward to a controller, which adjusts the rate at which it is fed into the blend. 

One major advantage of this method is that it takes account of changes in the properties of an 

individual coal, which may have occurred with time e.g. by oxidation. In a (cheaper) feedback 

control system the composition of the blend is continually analysed and, based on the result, 

the amounts of the components are adjusted to achieve the required blend composition. A 

disadvantage of this method is that there will always be a delay between the analysis point 

and the blend point. It is best suited to coals, which are not too dissimilar in quality, and where 

the time delays are small. 

The EMO terminal at Rotterdam uses feedforward control, based on a real-time elemental 

analyser and five bins containing imported coals, to supply blends to Dutch power stations. 


Computer modelling for blend control can be achieved by the simple use of spreadsheets, or 

by linear programming. These all depend on blend additivity. Models can also determine if the 

blending should be carried out at the supplier end, or the user end, of the chain. 


3 IMPORTANT COAL PROPERTIES IN BLENDING: THEIR TESTING, ADDITIVITY 

AND EFFECTS ON POWER STATIONS 

Many coal properties for blends can be predicted from the coal properties of the individual 

coals, simply by summing the proportion of each property based on the proportion of each 

coal in the blend. However, not all properties are additive, as set out in Table 4. 

The operator's ability to alter plant performance by blending coals depends on the coal 

properties selected, the impact of the property on the plant, and the efficiency of blending. 

The ability to predict the impact of a blend on plant performance depends strongly on the type 

of coals blended. When two coals of similar rank are blended, the impact on the plant is more 

predictable than when two coals of vastly different rank are blended. The discussion below 

can be taken to cover blending of two vastly different coals, but in general refers to blending 

coals of similar rank. 

As shown in Table 5, the impact of a blend property on the plant performance is considered to 

be predictable if the average value measured by an analytical test on the blend, not the blend 

constituents, can be used to indicate the expected change in performance. 

This section gives notes to accompany Table 4 and Table 5, which is a concise listing of the 

key properties for consideration when predicting power station performance from coal 

properties of blends. Other lists have been published in the past, which covered many of the 

properties discussed here. The tables of Wall (1988), Skorupska (1993) and Su (1999) are 

included in the appendices to this document. 

Note that references given to Standards, which define test procedures for each property, are 

for higher rank coals only. In most cases, separate methods are prescribed for lower rank 

coals. 

3.1 Proximate analysis 

The proximate analysis of coal comprises the moisture, ash, volatile matter and fixed carbon, 

the latter being by difference. These are normally reported on the as-analysed or air-dry 

basis. For the purpose of Table 4, the proximate analysis has been expressed on the as-fired 

or as-received basis, as this best refers to the condition of the coal received by the power 

station. 

Note the great differences in residence time, heating rate and final temperature, for these 

tests, between the empirical test furnace and a power station boiler. 

"Moisture" can contain light hydrocarbons, especially in lower rank coals, and so the moisture 

value may be too high and the volatile matter value too low. It is important to remember that 

laboratory volatile matter values include the mineral matter volatiles (predominantly water 

vapour and carbon dioxide), which are usually about 10% of the ash value. In an anthracite or 

semi-anthracite, for instance, the pure mineral matter may contain as much "volatile matter" 

as the pure coal component. 

Conversion from the air-dry to as-fired (as-received) basis is as follows, for example for ash: 

Aaf,% = Aad% x (100 - Maf%) / (100 - Mad%) 


where Maf = moisture as-fired (total moisture) 

Mad = air-dry moisture 

Calculation of analyses to different bases is described in the following Standards: Australian 

Standard AS1038.16; British Standard BS1016-100; ISO1170; American Standard D3180; 

Japanese Standard JIS M8812. 

PROPERTY Derived 

(empirical) 

Property? 

Function of 

Coal Rank, 

Coal Type, 

or Mineral 

Matter? 

Additive, 

Nonadditive 

Proximate analysis (as-fired) *1 

Moisture R, T, (M) A *7 

Ash D M A *8 

Volatile matter D R, T, (M) A *9 

Specific Energy *2 R, T, (M) A 

Sulphur - Total (M) A 

Pyritic M A 

Chlorine M (A) 

Ultimate Analysis (d.a.f.) 

Carbon R, (T) A 

Hydrogen R, T A 

Nitrogen A 

Hardgrove grindability index *3 D R, T, (M) N 

Abrasion Index D M (A) 

Crucible swelling number *4 D R, T N 

Ash fusibility temperatures D M N 

Ash analysis *5 M A *10 

Trace elements *6 M (A) 

Coal flow properties D R, T, M (N) 

Size distribution - coal R, T, (M) A 

Petrographic Analysis (v/v) 

Maceral analysis T A 

Maceral reflectogram R, T (A) 

Table 4: Blend additivity of main properties of power station feedstock 

Comments 

*1 Taken to be analagous to "as received". 

*2 Also described as Heating Value, Calorific Value. 

*3 Result refers to a specially prepared, sized and dedusted fraction of the sample. 

*4 Described as Free Swelling Index (ASTM). 

*5 AS1038 reporting order: SiO2, Al2O3, Fe2O3, CaO, MgO, Na2O, K2O, TiO2, Mn3O4, SO3, P2O5. 

*6 Concern: major As, B, Cd, Pb, Hg, Mo, Se; moderate Cr, Cu, F, Ni, V, Zn; minor Sb. 

*7 Moisture integrity may be lost on sampling; fines content differences may reduce voidage 

and cause some free moisture to drain from the blend. 

*8 Generally additive, except when high S, low Ca coal mixed with a low S, higher ash Ca coal. 

*9 May be higher than predicted, especially for blends of higher and lower rank coals. 

*10 With the exception of SO3. 


The table assumes perfect blending of coal. No consideration is given to the impact of blend properties due to imperfect blending. 

PROPERTY 

Proximate analysis (as fired) 

Coal handling Milling and firing Boiler Ash management Particulate removal SOx Control NOx control 

Moisture Not-Predictable Predictable Predictable 

Ash Predictable Predictable Predictable Predictable 

Volatile matter Not-Predictable Not-Predictable Not-Predictable 

Specific Energy Predictable Predictable Predictable 

Sulphur – Total Not-Predictable Not-Predictable Not-Predictable Not-Predictable Predictable 

Pyritic Not-Predictable Not-Predictable Not-Predictable Not-Predictable Not-Predictable 

Chlorine 


Carbon 

Hydrogen 

Predictable 

Nitrogen Not-Predictable 

Hardgrove grindability index Not-Predictable 

Abrasion index 


Ash fusibility temperatures Not-Predictable 

Ash analysis Not-Predictable Not-Predictable Not-Predictable 

Trace elements Not-Predictable Not-Predictable Not-Predictable 

Coal flow properties 

Size distribution - coal Not-Predictable 


(Spontaneous heating) 

Petrographic Analysis 

Not-Predictable 

Maceral reflectogram Not-Predictable Not-Predictable 

Predictable: The impact of the blend property on the boiler is predictable from the measured property. Not-Predictable: The impact of the property on the boiler is not 

predictable from the measured value, and knowledge of the properties of the individual coals is required to explain the coal behaviour. 

Table 5: Impact of key coal properties on power station plant performance 


3.1.1 Moisture (air-dry) 

The air-dry moisture, or moisture in the analysis sample, is that moisture which is lost by the analysis 

sample (minus 212 μm for AS, BS and ISO; minus 250 μm for ASTM), when it is heated in nitrogen 

(ASTM: in air) at 105°C to 110°C, to constant mass, after it has first been allowed to come to 

equilibrium with the laboratory atmosphere. Miyazu (1969) states that the ASTM method gives lower 

moisture values due to the use of air rather than nitrogen atmosphere, causing sample oxidation. 

Air-dry moisture is determined according to the following Standards: 

Australian Standard AS1038.3; American Standards D3172, D3173, D5142; British Standard 

BS1016-104.1; International Standard ISO331, ISO687, ISO11722; Japanese Standard JIS M8812. 

This moisture is not included in Table 4 or Table 5, as coal is never in this condition when used at a 

power station. It is needed, however, to recalculate analyses (carried out on air-dry coal) to other 

moisture bases, such as dry basis, or as-received basis. 

3.1.2 Moisture (as-fired) 

On the as-fired (as-received, as sampled, as-despatched) basis, the moisture is referred to as total 

moisture, a term used to describe coal in its "wet" condition. 

Analysis 

Australian Standard AS1038.1; American Standards D3302, D2961; British Standard BS1016.1; 

International Standard ISO589; Japanese Standard JIS M8811. 

The total moisture of coal comprises two components: 

Free moisture, Mf: that moisture which is lost by the coal sample in attaining equilibrium with 

the air to which it is exposed. 

Air-dry moisture, Mad: that moisture in the coal sample, after it has attained equilibrium with 

the surrounding atmosphere, which can only be removed by heating at 105°C to 110°C (in 

nitrogen for all methods except ASTM, which specifies air). 

Total moisture = Mf + Mad x (1 - Mf/100) 

The determination may be carried out in two stages, as above, or in a single stage in an oven (direct 

gravimetric) or, less commonly, in a single stage by distillation and collection of the moisture (direct 

volumetric). 

Blend additivity 

Additivity should apply to any form of moisture comprising internal (pore) and surface moisture 

components only. Where coals contain void moisture as well, however, i.e. moisture held between 

coal particles rather than on the particle surface, additivity may not precisely apply. It is possible that 

differences in size distribution of the blend components may mean that voids filled by moisture in one 

of the component coals may, when blended, become occupied by coal particles from another 

component, displacing the void moisture as stockpile drainage, and giving a lower than predicted 

result. 

As implied by Carpenter, differences between calculated and actual blend moisture values may reflect 

failure to retain the moisture integrity during and after sampling, rather than non-additivity of the 

property. 


This property will influence handling and storage performance, but becomes irrelevant from the milling 

stage onwards, when the as-fired moisture becomes the important property. 

Power station performance 

Total moisture increases transportation costs (is "ballast"), can cause handling and storage problems, 

and increases the requirement of air for drying in the pulveriser. It retards ignition and decreases 

flame stability, and affects volume and dew point of flue gases. 

Coal handling 

There is no simple relationship between coal handling behaviour and total moisture content. Handling 

behaviour relates to the ease with which a coal can be conveyed, discharged or reclaimed from a 

stockpile, storage bin or the hold of a ship. When coal does not flow freely, it can be described as 

having poor handling properties. 

The handling properties displayed by a coal result from a complex interaction of chemical and 

mechanical properties of the coal, equipment design features and environmental factors. The coal 

properties which impact on handling behaviour, many of which are interdependent, include ash value; 

moisture content, including surface and inherent moisture level; mineralogy, particularly the presence 

of swelling clays such as montmorillonite and/or bentonite; maceral composition; particle size 

distribution; extent of weathering; bulk density, both compacted and uncompacted; inter-particle 

cohesiveness; bulk strength; friability. 

For a given coal in a specific coal handling plant, changes in moisture content can significantly 

influence bulk strength and, as a consequence, the handling characteristics. While poor handling 

properties are generally associated with high coal moisture levels, flow properties do not in fact 

continue to deteriorate as moisture level is increased. Experience in flow property testing has shown 

that, for most coals, the most unfavourable flow properties occur at a moisture level between 70% and 

90% of the saturation moisture content (Roberts, 1998). Figure 3 shows a typical relationship between 

flow properties (as indicated by critical hopper opening 1 ) and coal moisture content. As shown, flow 

properties are most unfavourable at an intermediate moisture level 2 . 

The moisture level at which the least favourable handling properties occur, and the severity of those 

handling problems, differ from coal to coal depending on the influence of the other properties listed 

above. Similarly coals which are washed usually have a higher moisture content but can be easier to 

handle since many of the more troublesome components (especially degradable clays) are removed 

during the washing process. As a consequence, the flow properties of a blend are not predictable 

from knowledge of the blend moisture level alone. 

As was the case for coal handling behaviour, the influence of coal moisture level on dust generation 

will be different for different coals. For all coals, increasing the surface moisture level from a low value 

will reduce dust generation. However, the dust extinction moisture (DEM) level will differ from coal to 

1 

The determination of critical hopper opening is a common design requirement for materials handling systems. 

Larger the critical hopper openings are indicative of more inferior flow properties. 

2 

While the characteristic plot shows that flow properties improve at moisture levels in excess of the critical 

moisture level, this is not a desirable operating range, as the consistency of the coal approaches that of slurry as 

the moisture is increased. 


coal due to the influence of many factors on dust generation 3 . As such the dust generation behaviour 

of a blend is not predictable from knowledge of the blend moisture alone. 

Critical Opening Dimension B cr (m) 

1.2 

1.1 

1 

0.9 

0.8 

0.7 

0.6 

0.5 

6 8 10 12 14 16 18 20 22 

Moisture Content % (W.B.) 

Figure 3: Coal moisture content versus critical opening dimension (Roberts, 1998) 

Milling 

Increases in coal moisture adversely affect milling performance in a number of ways. Firstly, the 

reduction in the as-received calorific value associated with the increased moisture requires the 

processing of additional coal for the same boiler output, thereby putting additional demands on the 

milling systems. 

Increased surface moisture levels also impose additional demands on the drying capacity of the mill. 

In the typical coal milling arrangement, hot primary air enters the mill, entrains the pulverised coal and 

conveys it to the burners. The plant operator sets the temperature of the air at the mill outlet (i.e. 

when it is combined with the pulverised coal) in accordance with manufacturer’s recommendations. 

The temperature of the air at the mill inlet is changed in response to the mill outlet temperature setpoint 

and variations in the coal moisture content, by varying the proportions of hot air (directly from 

the air heater) and ambient (or tempering) air, which combine to make up the inlet air stream. 

Increases in coal moisture level result in an increase in the mill inlet air temperature required to 

maintain the desired mill outlet temperature. As the moisture level increases, a point is reached at 

which the mill inlet air stream consists entirely of hot air with no tempering air. Further increases in 

moisture will result in a decrease in mill outlet temperature, below the set point. Under these 

conditions, the risk of saturation conditions occurring and moisture precipitating at the mill outlet 

increases. This is an extremely dangerous situation as it may lead to agglomerating of pulverised 

coal, and subsequent blockage of, and fire in, the pulverised fuel pipe between the mill and the 

3 Many of the same factors, which influence coal flowability, also influence dust generation. 


urners. To avoid this situation when milling high moisture coals, the plant operator has little choice 

other than to reduce the demands on the drying capacity of the mill by reducing its throughput. This 

will require either additional milling plant to be brought into service to maintain boiler output, with the 

associated increase in auxiliary power consumption, or a reduction in unit output if no additional mill 

capacity is available. 

The response of milling systems to moisture increases, resulting from the introduction of a blend, is 

not entirely predictable from the moisture level alone. Other factors, including the resulting calorific 

value and the manner in which the moisture is distributed in the coal (i.e. inherent and surface) also 

need to be considered to more accurately predict the likely impact. 

Boiler 

Increasing the moisture content of the blend, whether within one coal or all the coals associated with 

the blend, will increase the energy required to evaporate water within the boiler. For example, a 

change in moisture content from 12% to 24% will decrease the boiler efficiency by approximately 

1.5%. Increasing the moisture content in a blend increases the volume of flue gas, and more energy 

is carried out of the furnace into the convective pass, increasing the quantities of superheat and 

reheat, making it difficult to maintain the design steam temperatures. If the furnace exit gas 

temperature increases, the efficiency of the boiler decreases. An increase of 20 o C represents a 

decrease of 1% in boiler efficiency. The increased gas velocities may result in increased draft losses, 

greater fan capacity requirements and increased tube erosion. The change in energy associated with 

the evaporation of water, and therefore the impact on the heat transfer within the boiler, is predictable 

(Carpenter, 1998). 

If the flue gas temperature increases, due to increased moisture in the gas stream, or more commonly 

due to high rates of deposition on the furnace walls, the design temperature for corrosion may be 

exceeded. Increased rates of corrosion in the superheater and other cooler parts of the boiler results 

(Raask, 1985). Table 6 shows the maximum operating temperatures for particular materials to avoid 

excessive corrosion. 

Particulate removal 

The increased gas volumes and velocities associated with increased coal moisture will decrease the 

efficiency of electrostatic precipitators (Carpenter, 1998). 

SOx control 

Increasing moisture increases the flue gas volume and affects the dew point of sulphate species in 

the gas, affecting the efficiency of any sulphur recovery equipment (Carpenter 1998). 

NOx control 

Moisture reduces the flame temperature and, as the rate of NOx formation from air nitrogen is 

temperature dependent, NOx emissions will decrease (Carpenter, 1998). 


Maximum Operating 

Temperature (K) 

Material ASTM Oxidation Corrosion 

Carbon Steel A178C, A210 840 780 

1 

Carbon - Mo 

2 

A209 T1a 840 795 

1 1 

Cr − Mo 

2 2 

A213 T2 850 795 

1 1 

1 Cr − Mo 

4 2 

A213 T11 865 840 

1 

2Cr − Mo 

2 

A213 T3b 895 840 

1 

2 Cr − Mo 

4 

A213 T22 910 855 

1 

5Cr − Mo 

2 

A213 T5 920 880 

9Cr − 1Mo 

A213 T9 980 920 

18Cr-8Ni A213 TP304 1145 1035 

16Cr-13Ni-3Mo A213 TP316 1145 1035 

Table 6: The maximum operating flue gas temperature to avoid corrosion (Raask, 1985). 

3.1.3 Ash 

Analysis 


BS1016-104.4; International Standard ISO1171; Japanese Standard JIS M8812. 

Ash is the incombustible residue remaining after the incineration of the analysis sample (minus 212 

μm for AS, BS and ISO; minus 250 μm for ASTM) to a constant mass under standard conditions of 

airflow and temperature (815°C for AS, BS, ISO and JIS; 750°C for ASTM). Note that the test 

temperatures in both cases are less than the decomposition temperature for CaCO3, but are greater 

than the dehydration temperature of kaolinite, montmorillonite and illite (Raask). Miyazu (1969) states 

that the ASTM method gives higher ash values because of its lower temperature. 


Although Su (1999) gives this as an additive property, there are well defined situations where nonadditivity 

applies. There seem to be no logical reasons why an actual blend ash value would ever be 

lower than that predicted from the weighted average value. However, as noted by Carpenter, the ash 

value of a blend is often higher than that calculated from the weighted average of the individual 

components, especially when lower rank coals are blended with higher rank coals. Carpenter explains 

this well, as resulting from the fixation of the sulphur from the higher rank coals, as sulphate, by the 

increased ash alkalis content of the lower rank blend components. Irrespective of rank however, if 

coal A, containing significant amounts of sulphur but little calcium, is mixed with coal B, containing 


significant amounts of calcium but little S, the ash of the blend will be greater than the weighted 

average of A and B. This is because the gases formed by the high sulphur, which escaped without 

fixation during ashing of A, are now fixed by the calcium in B. 



If the ash value of a coal or a blend is increased, the specific energy of the coal will decrease, 

ensuring that the amount of coal that must be handled to produce the equivalent amount of energy 

will increase. The impact of ash on coal handling is thus predictable. 

Boiler 

Ash provides a thermal load to the boiler. That is, increasing the amount of ash introduced into a 

boiler increases the energy required to heat that ash. This energy is lost to the steam raising system 

and more coal is required to maintain the steam temperature. The increased thermal load around the 

flame, caused by the increase in ash, causes a decrease in the peak flame temperature and reduces 

the heat transfer in the radiant section. This leaves a higher heat transfer in the convective section 

and, usually, a higher gas exit temperature. Changes in heat transfer within the boiler can result in 

increases in fouling, especially at the boiler exit (Lowe). The impact on the boiler of the quantity of ash 

in the coal is thus predictable. 

Ash management 

Obviously, increasing the amount of ash in a blend will increase the amount of ash that must be 

handled and disposed. 

The impact of low ash on the plant is generally predictable. However, some low ash coals can 

unpredictably produce ash with a high carbon content, which can have a high impact on ash disposal 

and the performance of electrostatic precipitators. This results from a low ash burden in the radiant 

zone of the furnace, causing a high heat flux within this area. The convective zone then cools and 

cannot generate enough steam, lowering the rate of combustion (Lowe, 1987). 


An increased quantity of fly ash will also produce a decrease in electrostatic precipitator (EP) 

performance, if the operating conditions of the EPs are not adjusted. An increase in the frequency of 

rapping of EPs may be required to ensure the layer of ash on the EP plates does not become too 

large for adequate operations (Carpenter, 1995). When the ash layer becomes too thick, the electric 

field observed by an approaching charged particle is relatively low, making attraction of the particle to 

the collection plate more difficult. Re-entrainment of ash particles from the collection plate may also 

occur. 

Similarly, an increase in the amount of ash will require shorter intervals between cleaning of fabric 

filters. 


3.1.4 Volatile matter 

Analysis 



This describes the loss in mass, corrected for moisture, when the analysis sample is heated out of 

contact with the air under standard conditions. (950°C ASTM; 900°C AS, BS, ISO and JIS). Miyazu 

(1969) states that the ASTM method gives higher volatile matter values of 0.5% to 1% due to the 

higher temperature. 


"Generally considered to be additive" but "some care in the application of the additivity rule … 

required" as Riley et al (1989) found actual blend values (ASTM method) were higher than calculated, 

especially for 50:50 blends and blends of extreme ranks. Carpenter gives examples where results 

were higher than predicted, especially for mixes of higher and lower rank coals. The mechanism for 

this is not apparent and is not explained. Results were worse for the 50:50 blends (as for ash). There 

seems to be no reason why results might ever be lower than predicted. 

Choudhury and Ganguly (1978) have shown that coals with high siderite content give falsely high 

volatile matter values, as during the test the carbon residue in the volatile matter crucible reduces the 

FeO (from decomposition of the FeCO3) to elemental iron. Also, the CO2 from the carbonates is 

thought to react with the coal carbon to form CO, again giving a high result. They give an equation to 

correct Vdmmf. Perhaps this might account for some instances of non-additivity, although how this 

mechanism would apply to blends is not clear. 



Increasing the volatile matter value of a coal is said to increase the potential for premature 

combustion of the coal in the milling system. 

Based on relative levels of coal reactivity, and the fact that coal pulverising mills are swept with hot 

air, there is an intuitive influence of coal volatile matter value (as a first order indicator of reactivity) on 

the risk of mill fires and explosions. Mill manufacturers typically specify allowable mill outlet 

temperatures on the basis of coal volatile matter value as for example in Table 7, which shows 

allowable mill outlet temperature limits for both Babcock and Wilcox (Stulz) and ABB-CE (Singer, 

1991). Pohl (1992) reported on the results of studies of a number of coals, covering a range of volatile 

contents, and focusing on the ignition of coal dust clouds, and observed that lower volatile coals were 

generally more difficult to ignite than higher volatile coals. 

A 1987 EPRI study (Carini and Hules) of mill fires and explosions, based largely on a survey of the 

US utility industry, and conducted primarily by Riley Stoker Corporation, examined the quality of 

correlations between a wide variety of plant (mill and unit), coal and operational (pertaining to both 

mill and unit) parameters, and the incidence of mill fires and explosions. The potential causative 

factors included: 


1 Plant 2 Coal 3 Operational 

Mill type Ash value Unit operation (base load, 

Mill capacity Type (bituminous, cycling, peaking) 

Number of mills per unit sub-bituminous, lignite, blend) Mill system operation 

Mill start up year Volatile matter value 

Moisture content 

Mill operation 

ABB-CE 

1.1.1.1.1.1 Coal Allowable Mill Outlet 

Temperature (°C) 

High rank, high volatile bituminous 

Low-rank, high volatile bituminous 

High-rank, low-volatile bituminous 

Lignite 

Babcock and Wilcox 

Coal type Volatile Content 

(% dmmf 4 ) 

Lignite and sub-bituminous 

High volatile bituminous 

Low volatile bituminous 

Anthracite 

30 

14 to 22 

14 

Table 7: Manufacturers’ allowable mill outlet temperatures 

Project 3.16 State of The Art Review of Coal Blending for Power Generation Page 29 

77 

66 

82 

66 

Allowable Mill Outlet 

Temperature (°C) 

52 to 60 

66 

66 to 82 

93 to 99 

Account was also taken of fire detection hardware, and mill inertising and extinguishing systems and 

media. The study found the factors, which appeared to be related to increasing frequency of mill fires, 

included: 

• Increasing mill capacity 

• More mills per unit 

• Use of vertical spindle mills ahead of ball mills ahead of high speed attrition mills 

• Increasing volatile content 

• Increasing coal moisture 

• Decreasing rank 

• Change from cycling to base load operation 

• Newer plant 

However: 

• No single parameter was identified as being critical in relation to the occurrence of mill fires and 

explosions. 

• Statistical relationships between the parameters listed above and the incidence of mill fires and 

explosions were found to be very weak and, for all parameters, the standard deviations were 

larger than the average values. 

4 dmmf – dry, mineral matter free basis

• No one parameter was identified as being a key discriminator, and a simplistic interpretation of 

the data suggests that the coal volatile matter value is actually the worst discriminator for both 

fires and explosions. 

The report pays considerable attention to the statistical relationships between volatile matter value 

and the incidence of mill fires and explosions, given the reliance of mill manufacturers on volatile 

matter value as a means of determining operating temperatures for the mills. In this context the report 

states: 

“….coal type and coal moisture content consistently appear in good discriminating 

groups while coal volatility content consistently shows up in the poorest 

discriminating groups. This observation about the surprising showing of coal 

volatility content remains unchanged whether the volatile content is based on an as 

received, dry, or dry, ash-free basis. It is probable that the combination of coal type 

and moisture content interact with operating conditions such as drying 

temperatures to influence fire and explosion hazard levels more significantly than 

coal volatility content by itself. Equipment and plant design factors such as mill type 

or mill capacity can appear either as good or bad elements for discrimination 

purposes depending on other factors in the group. The fact that coal volatility 

content or other factors do not appear among the groups providing the best 

discriminating (sic) does not mean that these factors are worthless in assessing 

hazard levels.” 

To add an additional level of complexity, Scott (1995) cites Zalosh (1987), who ascribed most mill 

fires to the effects of spontaneous combustion of static deposits of coal. This is supported by 

anecdotal experience which indicates that the state of repair and quality of maintenance for a given 

milling installation have a profound effect on the risk of mill fires, particularly for vertical spindle mills. 

As vertical spindle mills wear, the quantity of combustible material falling from the grinding bowl 

through the air gap and into the under-bowl region increases dramatically. The under-bowl region is 

the point of entry of the hot primary air (up to about 300°C) to the mill. If the combustible material is 

not removed promptly from the under-bowl region by the action of the shaft-mounted scrapers 5 , fires 

will inevitably result, irrespective of the specific properties of the coal. 

In summary, it appears that there are many factors, which influence the likelihood of mill fires and/or 

explosions occurring. The fact that mill manufacturers use coal volatile matter values to set mill 

temperature limits should not be interpreted as an indication that this is the most important contributor 

to the incidence of mill fires and explosions. Depending on the relative influence of all of the factors at 

a particular site, the influence of those parameters, which may intuitively appear to be more important, 

may be considerably diminished. 

Firing 

The volatile matter value, as measured by the proximate analysis, is significantly lower than the 

volatile matter value produced by a coal in a PF boiler. This is because the measured volatile matter 

value is dependant on the temperature and the heating rate. The temperature and the heating rate 

5 

The scrapers also wear and sometimes break away from their mounting to the mill shaft. Under these 

circumstances, the combustible material can build up in the under-bowl region. 


experienced in a PF boiler are significantly different to anything experienced under laboratory 

conditions. 

There is no one ideal volatile matter value, the desired value depending on the design of the burner in 

operation. The design of the burner, along with volatile yield, composition and heating value, 

determine the flame temperature and the flame stability. Therefore efficient operation of the burner 

requires the use of a suitable coal for a given burner. Lower rank coals have lower flame 

temperatures, as some components of the volatiles present in low rank coals ignite at lower 

temperatures. The flame temperature of low rank coals is also lower because the high moisture 

content of the coal “cools” the flame. However, the stability of the flame is usually increased with the 

amount of volatile matter present, which increases with decreasing rank of the coal. As the volatile 

matter is dependant on the volatile matter of each coal particle, if the blend contains two coals with 

significantly different volatile contents, two flames can develop, based on the devolatilisation of each 

of the blended coals. Evidence suggests that blending a low volatile coal with a small proportion of 

high volatile coal assists in flame stability and produces an even distribution of heat transfer 

throughout the boiler (Carpenter, 1995). 

Boiler 

The flame temperature and geometry strongly influence the chemistry of some ash components and 

gas pollutants. For example, increasing the flame temperature will increase NOx formation (see NOx 

control below). Increasing the temperature to which ash particles are exposed will also effect the 

stickiness of particles and may result in deposition. It is extremely difficult to predict the deposition of 

ash in boilers, due to the multitude of deposition mechanisms and the number of ash components that 

can initiate deposition. However, if the temperature that an ash particle experiences is above the 

melting temperature of that species, the possibility of deposit formation is increased. If the flame 

temperature is known, the susceptibility of deposit formation could be predicted from the melting and 

sintering temperatures of the ash components, though this is a complex task. However, as the volatile 

matter value of the blend measured by analytical methods does not provide an adequate indication of 

the amount of volatile matter released by the coal in the burner, the impact on the temperatures within 

the furnace cannot be predicted. 

A significant change in volatile matter value or flame temperature will also affect the heat transfer 

throughout the boiler, and char burnout. A sudden decrease in volatile matter value of the fuel, as 

experienced from inhomogeneous mixing of blended coals, will lower the flame temperature, 

decreasing the amount of heat transferred in the radiant section of the boiler and increasing the 

proportion captured by the convective section. If the carbon is relatively unreactive, such a change in 

volatile components in the fuel may also increase the amount of unburnt carbon in ash, requiring 

increased grinding of the coal (Carpenter, 1998). 

NOx control 

The nitrogen in NOx emitted from power stations comes from three sources: nitrogen from the 

atmosphere, nitrogen from the volatile component of the coal and nitrogen associated with the 

carbonaceous matter of the coal. Changing a blend volatile matter value may significantly impact on 

the NOx formed, because the amount of nitrogen available for reaction in the hottest part of the 

furnace is altered and the flame temperature is likely to change when the volatile content of the blend 

changes. However, as NOx formation is also dependent on burner design, operating conditions of the 


furnace and other formation mechanisms, predicting the change in NOx formation from volatile 

nitrogen is not always successful. 

Low NOx burners seek to impede the production of NOx by restricting the accessibility of the zone of 

initial combustion to oxygen. It is generally accepted that the majority of NOx resulting from the 

combustion of coal is produced during this volatile combustion phase. While this methodology is 

highly effective and can reduce NOx emissions to as little as 30% of the uncontrolled levels for some 

coals, it is best suited to higher volatile coals. Higher volatile coals will generally have proportionally 

more nitrogen associated with the volatile phase and less with the char and, as such, a technique, 

which targets the generation of NOx in the volatile combustion phase will obviously be more effective 

for these coals. The burnout efficiency of lower volatile coals also tends to be much more sensitive to 

burner stoichiometry than is the case for higher volatile coals, and as such NO x control strategies 

employed in the combustion process require a careful optimisation of NOx reduction burnout 

efficiency. For lower volatile coals, it is generally very difficult to achieve both high levels of NOx 

reduction and satisfactory burnout efficiency levels concurrently. The trend between NOx reduction 

and increased carbon in ash values is shown by the schematic in Figure 4. The trend shown in the 

figure has been observed during combustion of single coal feeds. Unfortunately, the behaviour of 

blends in this regard is unknown. High volatile coals are generally considered to provide greater 

flexibility in burner operation. 

NOx 

Volatile Matter 

Carbon in Ash 

Figure 4: The interaction of NOx formation and carbon in ash when combustion utilises a low NOx 

burner. 

3.2 Specific energy (calorific value, heating value) 

Analysis 

Australian Standard AS1038.5.1; American Standards D2015, D5865; British Standard BS1016-105; 


This is the quantity of heat released by the combustion of a known amount of the analysis sample in 

oxygen in a calorimeter bomb. The gross value determined in the laboratory includes the heat of 

formation of acids (HNO3 and H2SO4), which are corrected for in the published result. It also includes 

the heat gained when the water vapour condenses, in the bomb under pressure, to water. In a boiler 

this condensation does not occur and the (lower) net specific energy value is one where correction 

has been made for this. Purchase specifications for coal are increasingly giving the calorific value on 

a net, as-received basis, as this defines the actual heating value of the coal. 



The specific energy is the most important property of a power station feed coal. This property is 

diluted by moisture and mineral matter, so there is a strong correlation between dry specific energy 

and dry ash. Riley (1989) showed the heating value to be additive, as expected. Note, however, that 

specific energy is often calculated from a relationship with ash, with usually a very high correlation 

coefficient for a dry basis regression. Because ash may not be additive for certain combinations of 

coals, however (see section 3.1.3), specific energy may not be able to be precisely predicted from a 

weighted average set of their relationships with ash. 


On the as-fired basis, specific energy (calorific value, heating value) indicates the feed rate of coal 

required to achieve a given thermal output, and therefore the coal's value. However, specific energy 

indicates neither rank nor type, and therefore neither combustibility nor reactivity, especially on the 

as-fired basis. For example a coal having a specific energy of 22 MJ/kg as-fired might be either a low 

ash, high volatile matter, high total moisture lignite, or a very high ash, low volatile matter, low total 

moisture anthracite. On the other hand two coals of the same rank and specific energy might be either 

dull (with compensatingly lower ash or moisture values) or bright. 


As the specific energy of a coal decreases, the amount of coal to be handled to produce a given 

amount of energy increases. 

Boiler 

If the specific energy of a blend increases, the total amount of heat that is recovered in the boiler per 

kilogram of coal fired will increase, which will increase the steam pressure. To account for this, the 

processing rate of the mills will decrease until the steam pressure returns to a pre-set value. The size 

of the combustion zone will also change with a change in specific energy. A decrease in specific 

energy will increase the flow requirements of the primary air, forced draft and induced draft fans 

(Carpenter 1998). The impact of a change in the specific energy value of a blend is predictable. 

3.3 Total sulphur 

Analysis 

Australian Standards AS1038.6.3.1, AS1038.6.3.2, AS1038.6.3.3; American Standards D3177, 

D4239; British Standards BS1016-106.4.1, BS1016-106.4.2; International Standards ISO334, 

ISO351; Japanese Standard JIS M8813. 

Total sulphur is the sum of pyritic, sulphate and organic sulphur, and may be determined by one of 

the following three methods: 

Eschka Method: the analysis sample is heated with Eschka mixture (2MgO+CaCO3) in an 

oxidising atmosphere at 800°C and then leached with hydrochloric acid. After reacting the 

solution with barium chloride, the sulphate produced is precipitated as barium sulphate and 

weighed. 



High Temperature Method: the analysis sample is burnt in oxygen at 1350°C, the sulphur 

being converted to the gaseous oxides. These are converted to sulphuric acid and titrated 

against sodium borate. 

Infrared Analyser (instrumental): similar to the high temperature method, except that the 

gaseous oxides produced are evaluated by an infrared analyser. 

Sampling imprecision, increased by the high relative density of pyrite compared to coal, and the 

tendency of pyrite to be non-uniformly distributed through the size fractions, may mean that the blend 

total sulphur (where pyrite forms a significant fraction) may have high variance compared to the 

weighted average value calculated from the individual components. Otherwise, sulphur "appears to be 

additive" (Carpenter,1995). 


Figure 5 shows emission levels of sulphur dioxide as a function of coal sulphur levels determined in 

pilot scale coal combustion equipment (ACIRL) and shows why sulphur in coal is generally regarded 

as a reliable predictor of expected SO2 emission levels. 

Sulphur Dioxide, SO 2 (ppm, dry, 0% O 2 ) 

2000 

1500 

1000 

500 

0 

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 

Sulphur in Coal (% daf) 

Figure 5: Sulphur Dioxide emissions as a function of coal sulphur content 

Single Coals 

Blended Coals 

For these data, the regression coefficients (R 2 ) for the unblended and blended coals were determined 

to be 0.91 and 0.95, confirming that a strong correlation exists between coal sulphur content and 

sulphur dioxide emission levels for both blended and single coals alike. However, calculating the 

expected amount of SO2 emitted based on coal sulphur contents can in some cases lead to an 

overestimation, as sulphur will also form SO3 (usually only in small proportions) and species within the 

ash may absorb sulphur to form sulphates. 

Boiler (deposition) 

Sulphur which forms SO3 can re-adsorb on alkalis and alkali earth metals to form sulphates, which 

can condense on “cool” surfaces within the boiler, initiating deposit formation. The dewpoint 


temperature for both Na2SO4 and K2SO4 is approximately 1160K (Raask, 1985). When blending with 

a low rank coal with high Ca contents, the resulting CaSO4 can increase fouling and slagging 

observed within the boiler, and a significant increase in coal quantity may be required to meet the 

design boiler rating (Carpenter, 1998). 

Boiler (corrosion) 

SO3 has also been shown to initiate corrosion of boiler tubes, by reacting with the iron in the tube to 

form FeS or FeSO4 (Raask, 1985). When molten, the ash acts as a fluxing agent for the iron in the 

tube, and acts as transfer media for the flow of SO3 and corrosion products. Corrosion at the cool end 

of the boiler can occur when SO3 condenses. It is therefore important to maintain a temperature in 

excess of the dewpoint of SO3. However, the amount of SO3 produced and retained in the flue gas 

determines the dew point of SO3 for that gas. Therefore a high sulphur coal will require a higher 

temperature than a low sulphur coal, to avoid the SO3 dew point and subsequent corrosion 

(Carpenter, 1998). However, most Australian coals do not produce severe corrosion problems from 

sulphur attack, due to their low sulphur contents. Approximately 1-2% of sulphur in coal is converted 

to SO3 (Carpenter, 1998). 

Ash management 

Sulphates can report to the fly and bottom ash, and the sulphur content of the ash will affect the ability 

to sell ash to the construction industry. International standards generally specify the maximum 

allowable level of sulphur (present as SO3) in fly ash to be used as an admixture in concrete. For 

example, the ASTM standard C618 specifies that, for Class ‘F’ fly ash, the SO3 level shall not exceed 

5%. 


Sulphur in coal is generally regarded as having a beneficial effect on electrostatic precipitator (ESP) 

performance. Similarly, improvements in ESP performance have been found to result from the 

addition of sulphur trioxide (SO3) or sulphuric acid (H2SO4) to the gas stream. In both cases, these 

conditioning agents react with alkaline sites on the surface of fly ash particles to reduce the surface 

resistivity of the particles. While resistivity is a composite of surface and bulk resistivity, within the 

temperature range of interest (up to about 140°C for typical pulverised coal fired installations), surface 

resistivity is the dominant component. 

However, improvements in ESP collection efficiency, which occur as a result of sulphur in coal or the 

addition of sulphur-based flue gas conditioning agents, are not universal, and the collection efficiency 

of highly acidic ashes has been found to be largely unresponsive to these agents. There is no simple 

correlation between ash chemistry and the occurrence of acidic ashes. However, these ashes are 

generally observed to have low levels of alkaline components such as CaO. 

Sulphur from a coal blend will oxidise during combustion and, if it is able to form SO3, it will react with 

water vapour to form sulphuric acid. Sulphuric acid can react with fly ash particles, depending on their 

ash composition. Alkalies absorb the sulphur in sulphuric acid and the resulting sulphate phase has a 

decreased resistivity, resulting in improved ESP performance. Therefore, if the sulphur content of the 

ash in the gas stream increases, the performance of the electrostatic precipitators is expected to 

improve. However, the proportion of sulphur from the blend, associated with the fly ash, cannot be 

predicted. 


If the sulphur content of the fly ash decreases below 1wt%, not enough SO3 forms, changing the 

resistivity of the ash seen by the ESPs. When the sulphur content of the blend decreases, the 

moisture content usually increases, which increases the gas flow rate and/or temperature, causing the 

treatment time of the ESPs to decrease, lowering the efficiency (Raask). 

SOx emissions 

SOx is the generic term for the gaseous oxides of sulphur, SO2 (mainly) and SO3. Blending is often 

carried out to limit SOx emissions and avoid expensive desulphurisation plants. Replacing a high 

sulphur coal with a blend of a high sulphur coal and a low sulphur coal immediately decreases the 

total amount of sulphur entering the furnace and must decrease the amount of SOx produced. 

Similarly, adding a high sulphur coal to a low sulphur feed coal to decrease coal costs will be 

expected to increase SOx emissions as the total amount of sulphur fed to the furnace has increased. 

US coal fired power stations have been able to reduce SOx emissions, to meet emission standards, 

based on lowering the sulphur content of the feed coal by blending coals. When the sulphur content of 

the blend was reduced (Carpenter, 1998), a corresponding decrease in SO2 formation was observed. 

Reductions of up to 20% were achieved. However, blending can also limit the effectiveness of existing 

equipment, as noted above. The sulphur content of the coal is only a qualitative measure of the 

amount of SO2 that will be released. Other factors, such as the form of the sulphur in the coal, the 

volatile matter value, pyrolysis temperature, particle size and sulphate retention in the ash (which is a 

function of ash composition), all effect the amount of sulphur released into the atmosphere, making 

blending of coal to limit SOx emissions an imprecise practise. However, for typical calcium levels in 

bituminous coals, the amount of sulphur absorbed on ash is low and engineering correlations can be 

used to provide a general prediction of SOx emissions. Therefore, for most low alkali containing 

bituminous coals, the impact of sulphur when blending coals is predictable. 

When a high sulphur coal is blended with a coal with a low heating value, the resulting temperature 

and increased quantity of flue gas will decrease the efficiency of any desulphurisation equipment 

available. The cost of extra sorbent required by such equipment may greatly reduce the cost benefit 

associated with blending such coals (Carpenter, 1998). 

Emission limits within New South Wales are: 0.1g of SO3 or equivalent per cubic metre of gas 

(Australian Legal Information Institute, 2000). Many countries have emission limits based on the mass 

of emissions per MJ of coal energy, which requires comparison of coals for blending to consider the 

sulphur in terms of the specific energy of the fuel. (Carpenter, 1995). 

3.4 Pyritic sulphur 

Analysis 

Australian Standard AS1038.11; American Standard D2492; British Standard BS1016-106.5; 


The pyritic sulphur component of total sulphur is calculated from the determination of iron, soluble in 

nitric acid, following the removal of non-pyritic iron by hydrochloric acid. 



There is no apparent reason why the pyritic sulphur value should be biased high or low i.e. pyritic 

sulphur should be additive. Note, however, the comments on possible sampling imprecision, given in 

section 3.3. 



High pyritic sulphur coals are prone to spontaneous heating. As the pyrite is oxidised, heat is 

generated which may enhance coal oxidation rates. The form and distribution of pyrite in the coal 

strongly influence the threat of spontaneous heating, or even spontaneous combustion. Pyrite can 

occur as framboidal aggregates, radiating clusters, stalactite formations and in crystalline form (Deer 

et al, 1978). Therefore, predicting the tendency of a coal or blend to spontaneously heat, from the 

pyritic sulphur content, can be deceptive depending on the pyritic form. However, the majority of pyrite 

present in Australian coals is framboidal in nature (Corcoran, 1979). The risk of spontaneous heating 

can be diminished by washing the coal to remove pyrite. Due to its high relative density, pyrite 

separates readily in gravity based processes, providing that the pyrite has been first liberated from the 

coal by crushing. Pyrite is, however, a difficult mineral to remove from coal by surface type processes 

such as froth flotation, as its wetting properties are similar to those of coal. Some success has been 

achieved in a reverse flotation process (Osborne, 1988). 

Milling and firing 

Pyrite is a mineral which is both hard (hardness between 6 and 6.5), and dense (relative density of 5). 

Large particles of pyrite will impact strongly on any milling equipment, causing increased wear. Again, 

the impact of a pyritic coal on the milling equipment depends on the form and distribution of the pyrite 

in the coal. Blending coals with lower pyrite contents before milling will reduce this wear, compared to 

the high pyrite coal, as the milling equipment will be exposed to less pyrite. However, the reduction in 

wear behaviour is not linear with the proportion of hard minerals. Hard minerals are often retained in 

the grinding zone of a mill, resulting in increased wear, as discussed in section 3.11. Other difficulties 

arise when milling blends, as the coals' grindability will generally differ causing a large particle 

distribution or a bimodal distribution, as discussed in section 3.7. 

Boiler 

Pyrite causes slagging. Large, excluded pyrite particles, which are not fully converted to the oxide in 

the reducing atmosphere of low NOx burners, cause slagging because they become liquid and sticky. 

One form of pyrite in coal is “framboidal” (from the French, frambois - raspberry), which comprises 

aggregates of small particles, 1 μm to 10 μm in size. These particles will experience high 

temperatures, and often reducing conditions, promoting vaporisation and partial oxidation of the 

pyrite. This vaporised pyrite will condense on “cool” surfaces or react to form a sulphate, which may 

also condense, leading to deposit formations. The sulphur associated with pyrite will impact on the 

boiler performance as discussed in section 3.3. For this reason pyrite is associated with slagging, and 

the slagging indices for bituminous coal include Fe and/or S based on this understanding. Recent 

research by the CRC For Black Coal Utilisation, Newcastle, Australia has formulated slagging indices 

for coals containing Fe in the form of siderite (iron carbonate, FeCO3), and compared the indices of 

siderite-containing coals with those of pyrite-containing coals (Bailey, 1999 and McLennan, 1998). For 


oth pyrite and siderite, slagging depends on the mode of distribution of the minerals in the coal, and 

effects are not additive for blends. 

3.5 Chlorine 

Analysis 

Australian Standards AS1038.8.1, AS1038.8.2; American Standards D2361, D4208; British Standard 

BS1016-106.6.1; International Standards ISO352, ISO587; Japanese Standard JIS M8813. 

Analysis methods are similar to those used for sulphur. Chlorine may be determined by the Eschka 

method, where chlorine in the analysis sample is converted to chloride, extracted in nitric acid, and 

determined titrimetrically, or by high temperature techniques where the chlorine in coal is converted to 

hydrochloric acid and titrated. 


Although an almost insignificant component in Australian coals, chlorine may be more significant in 

sub-bituminous coals with which the Australian coals might be blended. Carpenter (1995) says that it 

is "probably additive". 


It is practically impossible to remove chlorine from coal by washing (Osborne, 1988). Chlorine is 

usually associated with the carbon matrix of the coal and removal of any significant fraction of 

chlorides in the coal requires long washing times. Blending therefore is generally the only technique 

available to reduce chlorine associated with a coal feed. 

Boiler 

For many years it was believed that corrosion associated with the presence of chlorine could be 

avoided by ensuring the chlorine content in fuel is maintained below 0.3 and above 0.25 (Raask, 

1985). However, recently Bryers (1992) has noted that reducing conditions may be required for 

corrosion to occur. Under oxidising conditions, chlorine forms HCl and will only be corrosive when the 

temperature is below the dew point of HCl. Under reducing conditions, HCl decomposes to Cl2, which 

directly attacks iron tubes to form FeCl2. FeCl2 has a low melting temperature and is highly volatile, 

reacting with oxygen to form iron oxide and fresh Cl2. FeCl2 also forms a porous scale on the tube 

surface, allowing CO attack to occur. Note that most Australian coals have Cl levels well below the 

0.3 level noted by Raask. 

Alkali-metal chlorides are also postulated to condense on heat transfer surfaces where they react to 

form sulphates. If insufficient sulphur is available, the chloride remains on the surface leading to 

corrosion. Figure 6 shows the relationship between deposit chlorine and fuel sulphur (Robinson et al, 

1997). 

Some researchers have found that the rate of deposition associated with sodium is directly 

proportional to the amount of NaCl in the coal. However, below a chlorine content of 0.4, the sodium 

is collected by silicates. When the available surface area of the silicates has been utilised, the excess 

sodium converts to sulphates, which result in deposition. The proportion of available sodium and 

equivalent metals which exhibit this behaviour is judged by the amount of chlorine in the coal, as the 

chlorine represents the delivery system of the metal ions to the boiler. The deposition and corrosion 


due to chlorine is described in Figure 7. Though the chlorine values noted above represent the total 

chlorine available in the coal, effectively only a proportion of chlorine is available for corrosion and 

deposition. This chlorine may be referred to as “Free Chlorine”, which cannot be determined from the 

normal analysis techniques. 

Deposit Chlorine (% dry mass) 

Fuel sulfur/(2xMax Fuel Alkali Chloride) 

Figure 6: The relationship between deposit chlorine and fuel sulphur. 

Maximum corrosion rate, nmh -1 

500 

250 

A A’ B 

0.4 0.8 

Chlorine in coal, % 

Figure 7: Dependence of furnace wall tube corrosion (A, A’) and sulphate deposition (B) on chlorine 

content of coal 


The presence of chlorine compounds in flue gases (usually present as HCl) is known to adversely 

affect the operation of both selective catalytic reduction (SCR) de-NO X plants and flue gas 

desulphurisation (FGD) plants. In SCR plants, the catalysts can be poisoned by chlorine compounds, 

thereby reducing their efficiency, reducing their effective life and increasing the required level of 

ammonia. 


2 

1 

Na2SO4 + K2SO4 Deposition, mg m-2s-1

In wet FGD plants, the HCl reacts with the calcium carbonate, thereby increasing the limestone 

consumption beyond that for the removal of SO2 only. High chloride concentrations may also 

adversely affect the by-product (gypsum) quality, the quality of the waste water, and necessitate 

additional use of corrosion-resistant materials in construction to ensure satisfactory service life. 

3.6 Ultimate analysis 

This consists of carbon, hydrogen, nitrogen, sulphur and oxygen (each expressed on a dry, ash-free 

basis). Although there are methods for the direct determination of oxygen, it is generally determined 

by difference. 

For sulphur see section 3.3. 

3.6.1 Carbon & hydrogen 

Analysis 

Australian Standard AS1038.6.1; American Standards D3176, D3178, D5373; British Standards 

BS1016-106.1.1, BS1016-106.1.2; International Standards ISO609, ISO625; Japanese Standards JIS 

M8813. 

Carbon and hydrogen may be determined by heating the analysis sample in oxygen in a high 

temperature furnace. Hydrogen is converted to water and carbon is converted to carbon dioxide, and 

these two gases are absorbed onto magnesium perchlorate and soda-asbestos respectively. The 

percentages of each are calculated by the increase in mass. Carbon and hydrogen may also be 

determined by the use of a high temperature infrared analyser. 

3.6.2 Nitrogen 

Analysis 

Australian Standard AS1038.6.2; American Standards D3176, D3179, D5373; British Standard 


Nitrogen is determined by decomposing the analytical sample catalytically with sulphuric acid to form 

ammonium sulphate. The ammonia, which is liberated by the addition of sodium hydroxide, is distilled 

and titrated against sulphuric acid. Nitrogen may also be determined by the use of a high temperature 

infrared analyser. 


Su (1999) concludes that C, H and N are additive. Carpenter (1995) says that C, H, N and S values 

"appear to be additive", while "oxygen content is probably additive as well." 

Oxygen is a direct indicator of coal rank (for unoxidised coal). It is determined by difference, however, 

and includes all of the errors in the C, H, N and S analyses. So the carbon value is a more precise 

measure of rank. 



NOx control 

NOx is the generic term used to describe the two oxides of nitrogen emitted by power stations: nitric 

oxide (NO) and nitrogen dioxide (NO2). The nitrogen that forms NOx comes from three sources: 

nitrogen in the coal volatiles, nitrogen in the carbonaceous matter of the coal, and atmospheric 

nitrogen. Nitrogen associated with air combusts at elevated temperatures, forming approximately 20% 

of the NOx produced in conventional pf combustors (Carpenter, 1995). Operational optimisation (low 

excess air), air staging/two-stage combustion (overfire air), low NOx burners, fuel staging (reburning 

with natural gas) and flue gas recirculation have all been utilised to lower NOx formation (IEA Coal 

Research: Hjalmarsson, 1990, Hjalmarsson and Soud, 1990). 

NOx formed from atmospheric nitrogen is termed “thermal NOx” and it can be controlled, though not 

eliminated, by air staging, which limits the reaction temperature and the oxygen available for 

combustion around the flame. NOx formation from nitrogen in the coal “fuel NOx”, can be limited by 

reducing the amount of air available for combustion during devolatilisation, by burner design (low NOx 

burners) and to some extent by air staging. Volatile nitrogen can form 60% to 80 % of the fuel NOx. 

Therefore the proportion of nitrogen associated with volatile components of the coal is important when 

blending coals to reduce NOx formation. Particle size can also effect NOx formation. Therefore 

grindability of a coal in a blend can also effect the NOx formed (Carpenter, 1995). 

Coal nitrogen cannot be used alone to predict NOx formation. For “unstaged combustion”, NOx 

formation can be predicted from the volatile nitrogen in the blend, based on the NOx emissions of the 

parent coals. Under staged combustion conditions, NOx decreases linearly as the proportion of the 

higher volatile coal increases. This occurs because most of the volatile nitrogen is reduced to 

molecular nitrogen and the majority of the NOx forms from char nitrogen. NOx from char is extremely 

difficult to control. The staging efficiency or percent reduction in NOx, compared to unstaged 

combustion, reaches a maximum with a high proportion of the high volatile coal. However, the staging 

efficiency does not follow a linear trend with changes in coal blend proportions. When the residence 

time of particles within the primary zone is long, the behaviour of the blend is linear. If the residence 

time is short, the blend behaviour is not predictable, suggesting NOx formation is dependant on the 

surrounding gas atmosphere and temperature, such that different rates of fuel nitrogen release from 

the coals in the blend ensure that the char experiences different conditions, thus effecting the NOx 

formation. 

Figure 8 shows NOX emission levels as a function of coal nitrogen determined in pilot scale coal 

combustion equipment (ACIRL Ltd). As shown, for both unblended and blended coals, there is no 

simple relationship between coal nitrogen content and NOX emission levels. 

Some thermal coal specifications set a nitrogen limit of 1.8% or 2.0%, dry and ash-free, for Australian 

export coals. These limits seem to have little technical relevance, for control of NOX emissions, in the 

light of Figure 8, and may be seen to have possible relevance in terms of marketing strategies only. 

Furthermore, test work reported by Conroy and Bennett (1997), in which a small number of Australian 

export coals were blended with overseas coals, found that the NOX emission levels resulting from the 

combustion of blends did not necessarily fall between that measured for the respective component 


coals when tested as single coals. In some cases, the NOX emission level measured for the blend 

was significantly higher than that determined for either of the component coals when tested alone. 

New South Wales regulations limit NOx emissions to 0.8 grams per cubic metre of gas (Australian 

Legal Information Institute, 2000). 

NOX (ppm, dry, 0%, O2) 

1400 

1200 

1000 

800 

600 

400 

200 

Unblended Coals 

Blended Coals 

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 

Nitrogen in Coal (%daf) 

Figure 8: NOX emissions as function of coal nitrogen content 

Boiler 

Use of NOx abatement technology has been shown to increase the propensity for slagging, and to 

increase the proportion of unburnt carbon in fly ash, as shown in Figure 9 (Carpenter, 1995). Slagging 

associated with NOx abatement technology occurs due to the formation of a reducing atmosphere in 

small regions within the furnace, resulting in reduction of iron bearing species. Slagging due to other 

species in the ash, such as calcium, is not effected by NOx abatement technologies. Increases in 

unburnt carbon in fly ash can usually be overcome by reducing the particle size of the coal, which will 

increase power costs and the wear of pulverising equipment. 

NO x 

slagging 

percent of over fire air 

Carbon in fly ash 

Figure 9: The relationship between NOx formation and carbon in fly ash (Carpenter, 1995) 


3.7 Hardgrove grindability index (HGI) 

Analysis 

Australian Standard AS1038.20; American Standard D409; British Standard BS1016-112; 

International Standard ISO5074; Japanese Standard not known. 

HGI is a measure of the ease with which coal may be ground. It uses a special ring and ball mill, 

under load, to grind a specially prepared -1180+600 µm portion of the test sample for a specified time. 

The amount of –75 μm material generated is compared to a calibration chart, based on a standard 

series of coals, and an index assigned. The higher the index the softer the coal. 


HGI is one of the key parameters for this study. It is used to predict the power station milling rate in 

particular. However, coals having the same HGI may vary significantly in their milling rates. 

To some extent there is conflicting evidence in regard to HGI additivity. HGI has been reported by 

some workers to be additive, when the blend coals have similar ranks, and/or have a narrow range of 

values. Others have found it to be non-additive. Because of the uncertainty, the restrictions, and the 

nature of the test itself, Table 4 shows it as non-additive. 

In a case study conducted on eastern US coals, Hower (1988) found that the weighted average HGI 

value for samples of single lithotypes agreed closely with the HGI value determined for a coal 

comprised of those lithotypes. He cautioned, however, against the use of his results to infer the 

additivity of blends of a variety of coals, and stated: 

“Each of the coals comprising a power plant feedstock is in turn a blend of a variety 

of lithotypes. A blend of a variety of coals is therefore likely to be a more complex 

mixture of lithotypes than any of the single coals in this study. This is particularly 

true when coals of varied rank are included in a blend in contrast to the isorank 

lithotypes in each of the individual seams in our sample population. Grindability 

would probably appear to be less additive in a complex blend than it is with the 

relatively simple channel and component lithotype sets discussed here.” 

In the conduct of the HGI test, a sample of the coal to be analysed is stage-crushed to a top size of 

1.18 mm. The fraction of coal finer than 0.60 mm is removed from the sample and discarded, leaving 

only the –1.18+0.60 mm fraction as the sample which is actually placed in the HGI test apparatus. 

The –1.18+0.60 mm fraction may represent as little as 50% of the initial sample mass. The Standard 

stipulates that the entire sample is to be discarded, and the sample preparation recommenced on a 

fresh sample, in the event that the percentage of the initial sample represented by this fraction falls 

below 50%. It is significant that HGI is the only test, being considered in this study, where the sample 

portion tested is not representative of the entire sample taken. This leads to outcomes which 

sometimes appear paradoxical, and is the main reason for the non-additivity conclusion. Waters 

(1986) found this feature of the HGI test, whereby a large proportion of the coal was removed prior to 

the conduct of the test, resulted in a HGI value for a binary mixture significantly lower than the value 

calculated on the basis of the HGI values and the proportions of each component in the mixture. In 

this case, the mass of each component coal in the test sample would not be represented in the same 

proportions as they would have been in the initial mixture, with the more friable (higher HGI) coal 

having been preferentially discarded in the sample preparation process. Waters found that only by 


formulating the HGI test sample after each component had been individually prepared to –1.18+0.60 

mm in the correct proportions of each component, was the resultant HGI closely approximated by the 

calculated value. As this is not in accordance with the standard method of sample preparation 

employed in the HGI test, under most circumstances it would have to be assumed that HGI is not 

additive. 

Effect of oxidation on HGI results 

In any discussion regarding the effects of oxidation on HGI, it is very important that the nature of the 

oxidation process is properly specified. There have been very few studies conducted on the effects of 

oxidation on HGI. For example Waters (1986) reported that oxidised coal has a lower HGI value i.e. is 

harder. Work published by Kona et al (1968), on the effects of oxidation on the properties of three US 

coals, found that oxidation substantially lowered HGI values. It should be noted however that, in this 

study, the coal samples were oxidised in an oven at temperatures of between 200°C and 300°C for 

periods ranging from 12 to 48 hours. These conditions bear no resemblance to those that prevail for 

natural low temperature oxidation or weathering. Outcrop coal oxidises at a much slower rate than 

that described by Kona et al (1968). As reported by Gray et al (1976), and consistent with common 

field experience, outcrop coal becomes “mechanically weak, fissured and easily degradable” and 

smut (the end result of oxidation) is powdery. Notwithstanding the inadequacies of the HGI test, 

weathered coal invariably reports a higher HGI value than its unweathered parent. The reason for the 

paradox is apparently that, during the preparation of the carefully crushed and sized -1180+600 µm 

test portion, oxidised particles report to the fines, which are screened out of the test portion, leaving it 

(relatively) harder. 



Hardgrove grindabilty index (HGI) provides an empirical measure of the relative ease of grinding a 

given coal. In practical terms, HGI is used to provide an indication of the power required to pulverise a 

given coal and, as such, is one of the factors used by power plant designers to determine capacity 

requirements for pulverising plant. In general, lower HGI coals have higher power and mill capacity 

requirements than higher HGI coals for the same tonnage of coal processed. HGI also provides a 

relative indication of the particle size distribution of the pulverised coal product, with higher HGI coals 

generally producing finer product than lower HGI coals. 

For the same rank, HGI can vary greatly with petrography. For example the Walloon coals of southwestern 

Queensland, with their high liptinite contents, have very low HGI values. Liptinite macerals 

are "tough" rather than brittle. Even though low HGI values may indicate relatively high mill power 

consumption for a highly liptinitic coal, that coal may burn exceptionally well due to its high volatile 

matter value. It may, therefore, be a highly desirable blend component to compensate for the poorer 

burnout characteristics of a very dull coal. Spero (1998) reported that the low HGI of Walloon coals 

led to, for the same mill power consumption as other feed coals, less of the pulverised fuel passing 75 

µm. Because of its higher reactivity, however, the carbon in ash values were lower than for the other 

feed coals. 

To assess the extent to which blended coals exhibit the same performance characteristics as 

unblended coals of the same HGI value, the results of numerous tests conducted in ACIRL’s pilot 

scale milling facilities have been examined. These results provide an excellent means of comparing 


the performance attributes of different coals, as all of the coals for which results have been presented 

have been tested under identical conditions in the same test equipment. Figure 10 shows mill power 

requirement as a function of HGI for a number of unblended and blended coals. 

Mill Power Requirement (kWh/t) 

16 

14 

12 

10 

8 

6 

4 


Blended Coals 

20 30 40 50 60 70 80 90 100 110 

Hardgrove Grindability Index 

Figure 10: Mill power requirement as a function of HGI for blended and unblended coals 

Figure 10 shows the expected overall trend of decreasing mill power requirement with increasing HGI. 

A cursory examination of the figure shows that, as a population, the blended coals do not exhibit 

behaviour largely different to that of the unblended coals. Regression analysis of the data populations 

confirms that there is no significant difference between the behaviour of unblended and blended coals 

in terms of the relationship between mill power and HGI and shows that: 

a) The relationship between mill power and HGI for unblended coals can be described by the 

equation: 

Power = 95 (HGI) -0.58 (R 2 = 0.63) 

b) The relationship between mill power and HGI for blended coals can be described by the equation: 

Power = 89 (HGI) -0.57 (R 2 = 0.65) 

Figure 11 shows mill product fineness as a function of HGI for a number of unblended and blended 

coals. While the expected general trend of increasing mill product fineness with increasing HGI can 

be observed for the overall data set, there is no compelling evidence to indicate that blended coals 

report behaviour that is substantially different to unblended coals of the same HGI value. 

More detailed studies of individual blends have, however, revealed differences between the milling 

behaviour of these coals and that of unblended coals. Conroy et al (1989) reported on the results of 

test work conducted on blends made up of varying proportions of two coals, with HGI values of 41 

(Coal ‘A’) and 79 (Coal ‘B’) respectively. In this test work, blends made up of 60% Coal ‘A’ with 40% 

Coal ‘B’, and 40% Coal ‘A’ with 60% Coal ‘B’ were subjected to pilot scale milling tests, along with the 

unblended Coal ‘A’ and Coal ‘B’. As shown in Figure 12 and Figure 13, analysis of the mill products 

showed substantial over representation of the higher HGI component (Coal ‘B’) in the finer size 

fractions indicating preferential grinding of this coal. 


Fineness (% passing 75um) 

80 

70 

60 

50 

40 


Blended Coals 

20 30 40 50 60 70 80 90 100 

Hardgrove Grindability Index 

Figure 11: Mill product fineness as a function of HGI for blended and unblended coals 

Mass Percentage (%) 

100% 

80% 

60% 

40% 

20% 

0% 

Coal 'B' 

Coal 'A' 

Passing 45 micron Between 45 and 75 

micron 

Size Fraction 

Retained on 75 micron 

Figure 12: 60% Coal ‘A’ + 40% Coal ‘B’ – Distribution of blend components in size fractions 

Earlier milling studies (Conroy and Trenaman, 1990a) on unblended coals revealed a relationship 

between the optimum level of applied grinding pressure in vertical spindle pulverisers and HGI. This 

relationship, shown in Figure 14 gives the value at which optimum mill performance is achieved 

across the range of HGI values. Operation at grinding pressures significantly in excess of these 

values has been found to result in excessive mill power consumption, sub-optimal mill product 

fineness and increasing levels of mill vibration. 


Mass Percentage (%) 

100% 

80% 

60% 

40% 

20% 

0% 

Coal 'B' 

Coal 'A' 

Passing 45 micron Between 45 and 75 

micron 

Size Fraction 

Retained on 75 micron 

Figure 13: 40% Coal ‘A’ + 60% Coal ‘B’ – Distribution of blend components in size fractions 

The blending study, described in part by Figure 12 and Figure 13, also assessed the optimum 

grinding pressure for the two blends constituted from Coal ‘A’ and Coal ‘B’, and found that an 

approximate hyperbolic relationship existed between optimum grinding pressure and HGI, with lower 

optimum grinding pressures associated with higher HGI coals. For the two blends tested, this study 

found that the optimum grinding pressure was significantly higher than that for unblended coals of 

similar HGI values, and almost equal to that required for the lower HGI component coal unblended. 

Figure 14: Relationship between optimum grinding pressure in spindle mills and HGI 

3.8 Abrasion index 

Analysis 

Australian Standard AS1038.19; American Standard nil; British Standard BS1016-111; International 

Standard ISO12900; Japanese Standard not known. 


Several abrasiveness tests are available. However, the results of each test do not rank a set of coals 

in the same order for abrasiveness, and the results of different tests cannot be compared (Sligar 

1986). Indices such as free silica and Hardgrove grindability have been shown by Sligar (1986) to be 

poor predictors of abrasiveness. The abrasion index of a coal as outlined in the Australian Standard is 

a measure of the wear caused by the coal and its contained mineral matter. It is calculated by 

measuring the loss in mass of the four blades used in milling a coal sample under standard 

conditions. 


This property was only listed in the Wall table (Table 13). Because it is a direct indicator of mill wear, it 

has been included in this report's Table 4. Free silica content, which may be estimated from ash 

analysis, is an indirect indicator of mill wear. Given that the abrasion index of a coal is directly 

determined as the amount of metal lost from steel blades when a standard mass of coal is subjected 

to a standard number of rotations of those blades in a mill, the values are probably additive, although 

no published reference could be found to substantiate this. An original reference to the test, by 

Yancey, Geer and Price (1951) makes no reference to blends. Sligar (1986) notes that this test 

assumes the results are additive for coal components. Therefore the results should be additive for 

coal blends. 



Sligar notes that the Abrasion Index is dependent on the amount of hard minerals present in the coal, 

such as quartz, pyrite and siderite. It is also dependent on the size of these particles, by the equation: 

( ) 2 

AI = a + b. 

dp. 

q + c dp. 

q , 

where AI is the abrasion index, a, b and c are constants, dp is the particle diameter (in micrometres) 

and q is the percentage of abrasive material. The constants are dependent on the mill in use, as mill 

wear is a function of the coal grindability and the type of mill used. 

Ball and tube mills have a significant proportion of metal to metal impact, which effects the rate of 

wear, but generally only operate at low speeds (10 to 20 rev/min). A hammer mill, on the other hand, 

will only have coal to metal contact (i.e. no metal to metal contact), and operates at high speeds (500 

to 1500 rev/min). The Australian standard test is believed to provide a strong indication of the rate of 

hammer wear in high speed mills. Roll wear in medium speed mills is believed to be predicted well by 

the standard test, but the overall wear is not predicted as well. Ball wear on a product coal basis is 

predictable for low speed mills. 

For roll mills, coal abrasiveness and roll grinding pressure are the major factors, which contribute to 

mill wear. Pacific Power (1993) produced correlations to predict mill wear rate (W) as: 

( AI × ) 1. 

8 

W = 0 . 017 GP + , 

where AI is the abrasion index as measured by the standard test, and GP is the roll grinding pressure. 

He also produced the following correlations, which link the mill wear with Hardgrove grindability, 

moisture and SiO2 in the sample and the mean hardness of the roll material (Brinell Hardness Number 

or BHN): 

⎡ 0. 017AI 

⎤⎡ 

− 0. 

000049BHN 

+ 0. 

57⎤ 

Or W = ⎢ 

+ 1. 

8⎥⎢ 

⎥ , 

⎣0. 

0091HGI 

− 0. 

265 ⎦⎣ 

0. 

55 ⎦ 


Or 

( Mar × SiO ) 

⎡ 0. 012 

2 ⎤⎡ 

− 0. 

000049BHN 

+ 0. 

57⎤ 

W = ⎢ 

+ 2. 

15⎥⎢ 

⎣ 

⎥ . 

⎣0. 

0091HGI 

− 0. 

265 ⎦ 0. 

55 ⎦ 

3.9 Crucible swelling number (CSN) 

CSN is a function of two discrete parameters, namely coal type (bright or dull) and rank. The higher 

the rank, the higher the carbon content and the lower the oxygen and hydrogen contents, and the 

lower the volatile matter value. The higher the "brights" or "reactive" maceral content (vitrinite plus 

liptinite), for a given rank, the higher the hydrogen content and volatile matter value. To achieve a 

high CSN value the coal must have sufficient volatile matter to create a frothy mass when the coal is 

rapidly heated in the absence of air through its fluid range. At the same time it must also have enough 

carbon to form walls around the bubbles, of sufficient thickness to support the mass as it sets. So it is 

a delicate balance. The higher volatile matter, bright coals of the Hunter Valley in New South Wales 

rarely reach a CSN value of 7, as the rank is not high enough to give strong walls around the gas 

bubbles. The lower volatile matter, higher rank, bright coals of the Bowen Basin in Queensland, 

however, may have CSN values of 9. Recent unpublished studies looked at the CSN values in a high 

rank coal deposit, where they varied from 0 to 9, depending on rank. At a reflectance of 1.70, the coal 

had a CSN of 9. Above this reflectance the CSN value reduced until, at a reflectance of 1.88, the CSN 

was zero. 

The effect of ash is interesting. Generally, mineral matter acts as a diluent i.e. CSN reduces with 

increasing ash value. However, in the case of a high volatile bituminous coal, where the CSN value is 

lower than it is capable of being, due to the collapse of the button during the test, increased mineral 

matter may provide a "stiffener" to the cell walls of the semi-coke produced, so that the button does 

not collapse, giving a higher value. 

Analysis 

Australian Standard AS1038.12.1; American Standard D720; British Standard BS1016-107.1; 

International Standard ISO501; Japanese Standard not known. 

A coke button is produced by allowing 1g of the analysis sample to swell in a covered crucible while 

being heated rapidly to 800°C in one and a half minutes and to 820°C in a further minute. The button 

is assigned a value by comparison of its swollen profile with a set of standard profiles. 


This property is referred to in Table 13 as B.S. Index, and by Su (Table 14) and Carpenter (1995) as 

Free Swelling Index (the ASTM terminology). Carpenter (1995) says that the FSI "is generally not 

additive for blends", also that the actual value for the blends studied was less than calculated, 

"especially in blends involving low rank coals". 

The non-additivity especially applies where there are large rank and type differences between the 

blend components. Other caking parameters such as dilatometer and Gray-King coke type are 

similarly non-additive. Coals of different ranks have different plastic ranges, meaning that they give off 

their volatile matter at different times, providing a further complication. 



Carpenter (1995) says that FSI (CSN) "provides an indication of the amount a coal charge will swell 

within a boiler and of char behaviour" and that "a high swelling number suggests that the coal particle 

may expand to form lightweight porous particles that could contribute to a high carbon content in the 

fly ash." Further, she says that "generally, the higher the FSI, the lower the combustion efficiency". 

Again, given the difference in heating rates in the test and in a boiler, she says that "the FSI may not 

provide a good indication of the swelling behaviour of coal under pf conditions". 

Statements like Carpenter's, inferring char morphology and unburned carbon in ash from CSN, 

needed to be read with caution. The ash values also need to be taken into account. For example, a 

higher rank coal and a lower rank coal may each have a CSN value of 5. The lower rank coal may 

have a low ash value, and produce a collapsed button because of its high volatile matter and 

relatively low carbon content. The higher rank coal may be a "natural 9" at low ash values, but may 

have this value reduced to 5 by its high ash value. Even though the CSN values are the same, the 

char and flyash would be significantly different for each. 

CSN is also used by some utilities to indicate the propensity of pulverised coal particles to build-up in 

coal burners. While it is theoretically conceivable that coals which have become plastic may adhere to 

the interior of coal burners under some circumstances, practical experience indicates that the risk of 

burner build-ups is no greater with higher CSN thermal coals than it is with lower CSN coals. Major 

US utility equipment manufacturers do not include CSN data as part of the suite of coal properties 

requested from a client for burner and boiler design purposes, and do not consider CSN to have any 

importance in the context of burner and boiler design. Furthermore, in the series describing evaluation 

criteria commonly used by the Japanese utility power industry, Okamoto (1997) indicates that the 

demise of stoker fired combustors saw the demise of CSN as a parameter of any relevance to 

combustion applications 6 , and that pulverised coal-fired installations utilise caking coals with few 

problems. 

3.10 Ash fusibility (AFT) 

This property is also referred to as ash fusion. Comments applicable to "reducing" test atmospheres 

are equally applicable to "oxidising", so these are not separately itemised in Table 4. 

The ash fusibility test was originally designed, in the 1920s, to indicate the likely clinker forming 

characteristics of ash from lump coal in stoker fired furnaces. In more recent times its results have 

been used to give an indication to the designers and operators of pulverised coal fired boilers of the 

likely ash deposition characteristics (slagging and fouling) of the coal to be fired. Except where the 

furnaces are specifically designed to handle fluid ash, combustion furnaces are designed on the 

premise that the ash will remain solid during its residence time. 

The ash fusibility temperatures are an indication of the fusibility behaviour of an ash between its 

solidus and liquidus temperatures, which are a function of the ash composition. Low deformation 

temperatures, in conjunction with high hemisphere temperatures, are misleading, due to the influence 

of unreacted illite in the laboratory ash, as shown by Wall et al, (1998). 

6 With caking coals, there was an associated risk of coal agglomerating on the grate and impeding the passage 

of air through the grate. 


Analysis 

Australian Standard AS1038.15; American Standard D1857; British Standard BS1016-113; 

International Standard ISO540; Japanese Standard JISM8801. 

This test is carried out by making a pyramid from moistened coal ash, then heating it through the 

range 900°C to 1600°C under a controlled atmosphere, either oxidising or reducing. Four standard 

temperatures are recorded, namely deformation, sphere, hemisphere and flow (Australian Standards) 

and initial deformation, softening, hemispherical and flow (American standards). In all standards the 

temperatures indicate (in order) the first rounding of the tip, a spherical shape (height equals width), a 

hemispherical shape (height equals half the width) and flow (nearly flat layer). The coal ash is 

prepared in a laboratory ash muffle, at temperatures between 800°C and 900°C. 


The non-additivity of ash fusibility temperatures is well known. The values can be predicted with some 

certainty, however, for a given coal, using relationships with ash composition e.g. the Schaefer Index 

or SI (Schaefer, 1933). Problems exist with the SI, however, as with other factors, when there is a 

significant number of ">" temperatures. Since the different blend components may have different SI 

relationships, the value of SI for predicting the ash fusibility of blends, from the values of the individual 

components, is uncertain. Carpenter (1995) however, referring to the work of Askew and Lief (1992), 

states that "the application of the regression equation for predicting AFT can be expected to be valid 

only for those coals and blends on which they were derived". This infers that the ash fusibility of 

blends can be predicted from the ash analysis of the blends, using the equations. The prediction of 

the ash fusibility of blends, from either the ash fusibility or ash analysis values of the individual blend 

components, is not confirmed. 

Carpenter (1995) also reports that, according to Lloyd et al (1993), the AFT of blends of North 

American coals increased with increasing amounts of Al2O3, CaO, K2O, Na2O and TiO2. The AFT 

consistently decreased with increasing amounts of MgO, SO3 and SiO2. Usually, but not always, 

increases in Fe2O3 content tended to lower the AFT. 


Boiler 

The build up of ash deposits on heat transfer surfaces reduces heat transfer from the combustion gas 

to the water-steam system and can cause blockage of gas flow, corrosion and erosion. Each 

decreases the efficiency of the plant. The deposits can be difficult to remove and can damage 

equipment when large deposits of fused material fall from walls. Ash deposition can occur by particle 

impaction, thermophoresis, vapour condensation or chemical reaction. Slagging and fouling is 

strongly influenced by equipment design, plant operating conditions, fuel reactivity and ash 

composition. Basic components of the coal ash, often referred to as fluxing components, lower the 

melting temperature of the ash and cause the formation of sticky particles that can initiate deposits. 

These basic components consist of Fe, Ca, Mg, Na, and K. Increasing the proportion of any of these 

constituents can result in increased deposition. 

Associations of these elements in the coal also have a high impact on the formation of low melting 

temperature particles. For example, iron associated with sulphur as pyrite will oxidise in the flame, 

producing a Fe-O-S melt, with a melting temperature of approximately 1080 o C. This melt phase is 


often associated with slagging propensity. If the pyrite is associated with the coal matrix, the heat from 

the burning particle will vaporise the pyrite, which can condense as a sticky layer and initiate deposit 

formation, or can produce H2S, which can be corrosive. Iron present as siderite (FeCO3), will 

decompose to FeO, which has a melting temperature of approximately 1380 o C. Pure siderites, and 

siderites with high calcium contents, are more likely to form molten particles that lead to deposition 

than are siderites containing magnesium, as these species are more likely to decompose (Bailey, 

1999). Again, included particles can vaporise resulting in condensation. Siderite particles, however, 

are less likely to vaporise than pyrite particles. Iron associated with clay particles (aluminosilicates, for 

example chlorite) is less likely to oxidise and form low melting temperature particles that can lead to 

deposition. 

Na, Ca and Mg can often become sulphated by capturing SO3 from the gas stream. These species 

have a low sintering temperature and are often associated with deposits within the convective pass. 

Na and K associated with organic species in the coal and are very volatile, and are often found to 

condense on the tubes within a boiler, which can initiate deposit formation. 

As most elements in the ash can occur as many different mineral species, it is impossible to predict 

the slagging and fouling propensity of an ash based on its oxide analysis. Ash fusibility temperatures 

are one method of considering the behaviour of an ash in a boiler, as they give an indication of the 

temperature at which highly sticky phases may form. Unfortunately, some ashes produce deformation 

temperatures that have significant amounts of liquid present (as high as 90% as shown in Table 8). 

High proportions of liquid phase at the deformation temperature provide an indication of the presence 

of molten phases in the boiler but do not give an indication of the temperature at which these phases 

became sticky (Gupta, 1998). Variability in the liquid content of the ash, at the deformation 

temperature, makes comparison of coals and prediction of the fouling and slagging behaviour 

extremely hazardous. The ash fusibility temperatures also provide little information about the change 

in sticky behaviour of an ash during its fusibility range, as some ashes have significantly high 

proportions of liquid at the deformation temperature. 

Ash 1 Ash 2 Ash 3 Ash 4 Ash 5 Ash 6 Ash 7 Ash 8 Ash 9 

DT 1240 o C 1050 o C 1230 o C 1320 o C 1090 o C 1390 o C 1110 o C 1210 o C 1320 o C 

Melt at 1100 o C >90% >75% >60% >15% 

Melt at 1200 o C >60% >40% >60% >90% >90% 

Melt at 1300 o C >80% >60% >75% >75% 

Melt at 1400 o C >90% >50% >80% >80% 

Table 8: The amount of liquid present in an ash sample at selected temperatures compared to the 

sample's deformation temperature (DT) (Gupta, 1998). 

There are so many different processes involved in deposition within boilers that it is impossible to 

accurately predict deposition behaviour of blends. In general, the deposition behaviour of the blend is 

worse than the behaviour of the parent coals. However, predicting the proportion of the blend which 

provides the worst deposition requires understanding of the impact of composition on the sintering 

and melting temperatures of the ash and an understanding of the mode of deposition for those 

particular coals. 


3.11 Ash analysis 

Analysis 

Australian Standard AS1038.14.1-3; American Standards D1757, D2795, D3682, D4326, D5016, 

D6349; British Standard BS1016-14; International Standard in draft; Japanese Standard JIS M8815. 

The composition of the coal ash, expressed in terms of the simple oxide forms, is determined by 

either one or more of the following techniques: 

• Wet chemical or gravimetric analysis 

• Atomic absorption spectrometry 

• X-ray fluorescence spectrometry 

• Optical emission spectrometry 

Results are expressed as "mass % of ash". 


Ash analysis oxides should be additive, with the exception of SO3, as discussed in section 3.1.3. Of 

greater importance than ash analysis is mineral matter analysis. Because of the paucity of references 

to this in routine testing results, however, it has not been included in Table 4. Mineral matter 

compositions should be additive, but interaction between mineral matter in the blend coals may result 

in different products in the ash. 



In industrial coal pulverisers, the products of the grinding process are conveyed from the grinding 

zone by the primary air. The various components of coal cover a wide range of particle sizes and 

specific gravities, and as such the extent to which the particles are entrained in the primary air stream 

can differ substantially, from one component to another. The hard minerals associated with coal, such 

as pyrite and quartz, which are the primary contributors to abrasive wear in coal pulverising and 

transport equipment, are less likely to be entrained in the primary air stream than the carbonaceous 

components of the coal due to two principal factors: 

(a) These components do not reduce in size as readily as the carbonaceous components of coal 

(b) These components have higher relative densities than the carbonaceous components of coal. 

(Relative densities of pyrite and quartz are approximately 5.0 and 2.6 respectively.) 

As such, these components tend to accumulate preferentially in the grinding zone. The results of pilot 

scale test work reported by Conroy and Trenaman (1990b) on an Australian domestic coal found that 

the quartz concentration in the grinding zone of the pulveriser was, under certain circumstances, more 

than twice the level found in the feed coal. This work also found that the extent to which the quartz 

concentrated in the grinding zone was influenced by the process conditions, including primary air flow 

rate and degree of internal classification. 

Boiler 

Some coals with fine silica minerals produce deposits on walls of pf furnaces, which result in poor 

heat transfer due to their reflective character. This character is due to dusty deposits, comprising fine 


ash particles (Wall, 1994). The problem can be overcome by blending, to create deposits with coarser 

ash particles or which form sintered deposits. 

Ash handling 

If the proportion of CaO, SiO2 or Al2O3 change, the handling behaviour of the ash can alter, making 

handling in wet sluiceways difficult due to plugging of the system and erosion problems. 


It is a fundamental requirement of the electrostatic precipitation process that the fly ash particles 

acquire an electrical charge. A higher charge on the particle results in more efficient operation of the 

electrostatic precipitator (ESP). Ash composition effects the resistivity of an ash, and therefore the 

efficiency of collection. Particle collection on the collector plate of an ESP is essentially a process of 

charged particle transfer, through a moving gas by an applied electric field. The collection of particles 

relies on movement of particles towards the collection plate, and the adhesion of particles on contact 

with the collecting surface. One of the major factors which influences the efficiency with which the fly 

ash particles are attracted to the collector plates is the strength of the electric field between the 

collector plates and the emitter wires. The electric field and the particle collection efficiency are 

dependent on the applied voltage. 

The automatic controls attempt to maintain maximum voltage to the ESP. The introduction of high 

resistivity fly ash will cause a reduction in the maximum applied voltage and the strength of the 

electric field. It may also lead to the onset of “back-corona”. Back corona occurs when a particle 

migrates to the collecting surface but fails to dissipate its charge, causing a high potential gradient in 

the dust layer on the surface of the plate. This layer disrupts the electrical field that induces particle 

migration, and repels the particles of like charge that are attempting to migrate to the collector plate, 

thus adversely impacting on collection efficiency. 

Blending of coals can change the resistivity of the ash, which is critical for electrostatic precipitator 

performance. High resistivity fly ash (above 10 11 ohm.cm) lowers the ESP performance by limiting the 

current that can pass through the ash layer residing on collection plates. Low resistivity fly ash (below 

10 8 ohm/cm) may also be a problem, as the ash easily loses its charge after contact with the collector 

plates. The uncharged particles may then be easily re-entrained in the flue gas. Resistivity can be 

reduced to unfavourable levels by the presence of high levels of unburnt carbon in the fly ash. This 

may occur as a consequence of poor combustion efficiency, or may simply be the result of firing a 

coal with a very low ash value. 

Sodium and sulphur are known to have a strong effect on the conductivity of fly ash, as shown in 

Figure 15. Decreasing the proportion of Fe2O3, K2O and Na2O, or increasing MgO, CaO and SiO2 in 

the fly ash, will increase the fly ash resistivity. The form of these elements is also important: the 

resistivity of muscovite, albite, quartz and kyanite are two to three orders of magnitude larger than 

those for kaolinite, illite and chlorite (Raask, 1985). Potter (1987) presented a correlation, which 

predicted the collection area required to attain 0.1g/Nm 3 for a 15% ash, based on ash composition, as 

shown in Figure 16. A correction factor f, to convert the collection area to the precipitator size for an 

ash percentage, A, was also presented: 

f = 1.364-0.488 log10 [(100/A)-1] 


RESISTIVITY, Ωm 

10 

8 

6 

400 

A 

B 

C 

D 


500 

TEMPERATURE, K 

Figure 15: Electrical resistivity of coal ashes: A, low-sodium, low-sulphur coal; B, low-sodium, highsulphur 

coal; D, high-sodium, high-sulphur coal. (Raask, 1985) 

PRECIPITATOR SIZE (m2/kg/s) 

130 

120 

110 

100 

90 

80 

70 

60 

50 

40 

30 

15% Ash 0.1g/m3 Outlet 

(Si + Al + Fe) IN ASH (%) 

600 

30 50 70 90 

Figure 16: The effect of ash composition on the collection area of an electrostatic precipitator. (Paulson)

If the temperature and particulate characteristics of fly ash change with a blend, then the performance 

of a fabric filter will change. An increased proportion of fines in the ash may cause clogging of the 

filter and possible agglomeration of the cake, causing difficulties in its removal. Condensation of 

vapours on the fabrics and disintegration due to acid attack may require a change in cloth material to 

avoid significant increases in emissions (Carpenter, 1995). 

3.12 Trace elements 

Analysis 

Australian Standard AS1038.10.1-5; American Standards D3683, D3684, D3761, D4606, D5987, 

D6357, D6414; British Standard BS1016-10; International Standard ISO601; Japanese Standard not 

known. 

Trace element analysis is performed on coal and ash samples, using similar techniques to those for 

ash analysis. Results are reported in mg/kg (Australian Standard), or parts per million, "ppm" (ASTM). 


Carpenter (1995) does not cover the subject of trace elements in blends. However, other IEA 

reporters do (Clarke and Sloss, 1992; Couch, 1995; Davidson and Clarke, 1996). Are trace elements 

additive, especially in coals of widely differing ranks? At present there seems to be no evidence to the 

contrary. See also Section 3.4 on the likely variance introduced by sampling. Add to this the possible 

variance that may come from sample preparation i.e. trace element pickup from the laboratory mills. 

See also the Clarke and Sloss report on the partitioning of trace elements into the power station 

waste streams. 

Table 9 shows the relative importance levels, and usual concentrations, of most trace elements. 

Component Level of Most Aust. Coals (ppm) Most Coals (ppm) Class Typ. NSW Flyash (ppm) 

Concern Mean Range Mean Range *1 Mean Range 

Antimony Sb Minor 0.5


The mechanisms for deportment of each trace element are not well understood. To date experiments 

considering the partitioning of trace elements between ash and gas phases have had difficulty closing 

mass balances. Work by the Black Coal CRC is currently aimed at improving the closure of these 

mass balances. The associations of the trace elements in the coal are believed to be very important, 

and will impact strongly on the resulting deportment. Table 10 shows the likely mode of occurrence of 

some trace elements as described by Swaine and Goodarzi (1995). 

Element Mode of Occurrence Level of 

confidence (2) 

Antimony In pyrite and accessory sulphides 4 

Arsenic In pyrite 8 

Barium Barite and other Ba-bearing minerals 6 

Beryllium Organic association 4 

Boron Organic association 6 

Cadmium In sphalerite 8 

Chlorine Chloride ions in pore water or adsorbed onto 

macerals 

Chromium Organic or clay association 2 

Cobalt In pyrite, some in accessory sulphides 4 

Copper Chalcopyrite 8 

Fluorine Various minerals 5 

Lead In galena 8 

Mercury In pyrite 6 

Manganese In carbonates, siderite and ankerite 8 

Molybdenum Probably sulphides 2 

Nickel Unclear 2 

Phosphorus Phosphates 6 

Selenium Organic association, in pyrite and accessory 

sulphides and selenides 

Silver Various sulphides 4 

Thallium Associated with pyrite 4 

Thorium Monazite with lower concentrations in xenotime 

and zircon 

Tin Sn oxides and Sn sulphides 6 

Vanadium In clays and organic association 3 

Uranium Organically associated, some in zircon 7 

Zinc Sphalerite 8 

(1) Elements in bold type are included in the EPA’s list of hazardous air pollutants. 

(2) A value of 10 indicates the highest level of confidence; a value of 1 indicates no confidence. 

Table 10: The mode of occurrence of trace elements in coal described by Swaine and Goodarzi (1995). 


6 

8 

8

Some trace elements are expected to report solely to the gas stream and others solely to the ash 

stream, while some trace elements partition to more than one stream, as shown in Figure 17. 

Increasing Volatility 

Hg 

Rn 

Br Cl F 

B Se I 

As Cd Ga Ge Pb 

Sb Sn Te Tl Zn 

Ba Be Bi Co 

Cr Cs Cu Mo Ni Sr 

Ta U V W 

Eu Hf La Mn Rb 

Sc Sm Th Zr 

Group 3 

highly 

volatile 

Group 2 

Mixed 

behaviour 

Group 1 

Low 

volatile 

Figure 17: The partitioning of trace elements. Group 1 elements are found predominantly in the ash, 

group 3 elements are predominantly in the gas phase, and group 2 are mixed between the two states. 

(Clarke & Sloss, 1992) 

Though some trace elements will be predictable in behaviour, such as mercury which appears to 

occur in the gas stream in most occasions, other elements which can occur in more than one phase 

cannot be considered predictable. Associations of the elements within the coal, and the availability of 

other species, which may act as a sorbent for the element, will change with blending and will effect 

deportment. 

3.13 Coal flow properties 

Analysis 

Australian Standard AS3880; American Standard not known; British Standard not known; 

International Standard ISO15117-1 draft; Japanese Standard not known. 

This group of properties is only given in the Wall table (Table 13), but is of great importance. Coal 

which will not flow cannot be fired. 

There are two major test methods employed, each of which is conducted over a range of total 

moisture values. The Durham Cone test, which is conducted on a 20 to 30 mm top size sample, 

involves the timed discharge of a test portion of standard mass and top-size from a vibrating mildsteel, 

conical hopper. In the Jenike Shear Cell test the pre-consolidated, 4 mm top size, sample is 


contained within a shear ring, cover and base. The force required to move the shear ring over the 

base, under load, is recorded. 


Roberts (2000) states that flow properties of blends are influenced when the minor component 

exceeds 20%. Properties are not additive, with blends tending to the character of the worst coal. The 

interactions are not understood or reported in detail. The known effects of moisture, fines and 

inorganic components on flow characteristics of single coals offer the possibility of establishing 

relationships, and predictions, through research. The testing of blends is the only option at present. 



The most obvious consequence of using a coal with difficult flow properties is that the coal flow to the 

power station will be reduced or interrupted. This is most likely to occur as a result of blockages in 

transfer chutes or coal bunkers feeding the pulverising mills. 

The design features of power stations will also impact on coal flow properties. For this reason, the 

coal handling plants at many power stations include such features as: 

• Dry storage or “slot” bunkers, to ensure that there is an adequate supply of dry coal available at 

all times. 

• Selection of chute lining materials to minimise wall friction. 

• Transfer chutes designed to eliminate protuberances and other features, which might encourage 

coal blockages. 

• Conical coal bunkers, designed in accordance with mass flow principles, so as to reduce the risk 

of coal flow to the mills being disrupted by “rat holing”, bridging or blockage, in the event that wet 

coal or coal with difficult flow properties is introduced. 

• Air cannons or similar types of devices, which are fitted to bunkers and used to re-establish coal 

flow when a disruption occurs. These are normally retro-fitted to coal storage bunkers in cases 

where the design features have been inadequate to ensure satisfactory material flow. 

3.14 Size distribution 

Analysis 

Australian Standard AS3881; American Standard D4749; British Standard BS1016-109; International 

Standard ISO1953; Japanese Standard not known. 

The size distribution of coal is obtained by passing a known amount of coal over a series of screens 

or sieves of different apertures. The mass percent retained and passing, for each size fraction, can 

then be calculated. Results are often graphed using a Rosin-Rammler scale, which has a log-log 

scale on the x-axis and a probability scale on the y-axis. 



While not in Su's (Table 14) or Carpenter's (1995) lists, size distribution is given in the Wall table 

(Table 13) and given significance in most of the stages in Skorupska's table (Table 15). It should 

logically be an additive property, and should not be different for blends of different ranks. 


Milling and firing 

As the top size of a mill feed increases, the capacity of the mill decreases. The effect on a mill’s 

capacity of changing the top size of a coal or blend is predictable, and is usually supplied by the mill’s 

manufacturer. The fines content, on the other hand, can have a strong impact on the mill’s 

performance. In roll mills, excessive fines can cause the rolls in the mill to skid across the charge 

rather than crush the sample. 


The size distribution of the coal impacts on the size distribution of the ash, which effects the 

performance of electrostatic precipitators. Ignoring any electrical conductance associated with 

variations in particle composition, larger particles are collected more efficiently. Therefore, increasing 

the particle size of a coal or blend should improve the collection efficiency of the precipitators 

(Paulson). However, an ESP can have poor efficiency at a given particle size, as shown in Figure 18, 

and altering the particle size of fly ash may result in poorer efficiency if the ESP's performance at that 

particular particle size is poor (Benitez, 1993). 

Grade efficiency 

1 

0.95 

0.9 

0.85 

0.8 

0.75 

0.01 0.1 1 10 

Particle diameter (μm) 

Figure 18: The calculated grade efficiency of a selected electrostatic precipitator (Benitez, 1993). 

3.15 Petrographic analysis 

Analysis 

Australian Standard AS2486, AS2856.2; American Standard D2798, D2799; British Standard 

BS6127; International Standard ISO7404; Japanese Standard not known. 

These tests provide information on the rank, the maceral composition, and the distribution of minerals 

in the coal sample. A maceral analysis is the maceral composition of coal expressed as a percentage, 

and is determined by point counting a polished grain mount of the coal viewed in reflected light. 


Macerals are the smallest microscopically recognisable organic constituents of coal. They derive from 

the original plant material and are identified by their morphology and relief. 

The standard analytical technique used to distinguish each maceral group, primarily by botanical 

form, (AS 2856.2, 1998) relies on the subjective identification of botanical components by a trained 

operator. An alternative approach is the maceral reflectogram, which is a graphical representation of 

the range of maximum and random reflectance values, in oil, of incident light from polished surfaces 

of coal macerals. This is an objective measurement directly related to the carbon content of the 

components. Standard procedures exist for the manual measurement of vitrinite reflectance, which 

may be applied to other coal macerals (AS 2486, 1989). There are no relevant standards for 

measurement of the reflectance of all of a coal’s components. The data are usually presented as a 

frequency distribution or histogram. Automation of reflectance measurement permits collection of 

millions of readings from a single sample, greatly improving the statistical soundness of the results. 

O’Brien et al. (1998) recently automated the collection of full maceral reflectograms (FMR) of single 

coals. Their technique permits identification of both maceral group proportions and the range of 

reflectance of all the coal components in a single measurement. Further development of the O’Brien 

et al. (1998) FMR technique is required before it can be used for blend identification. 

A microlithotype analysis gives the composition of maceral assemblages, called microlithotypes. It is 

rarely used in Australia. 


Petrographic analyses are not given in the Wall or Su tables (Table 13 and Table 14 respectively), but 

are included in Carpenter's (1995) table. Reflectance has long been used as a tool for distinguishing 

between blend components in coking (Stach et al., 1982). Pearson (1991) applied probability analysis 

to the distribution of vitrinite and whole coal reflectance for evaluating blend consistency. Vitrinite 

reflectance data from a single coal seam plot as a straight line on reflectance versus cumulative 

probability charts, using a non-linear probability scale (Taylor et al., 1998) - see Figure 19a. Plots of 

the vitrinite reflectance of blended coals show steps, which offset the linear vitrinite segments of each 

of the coals in the blends by their relative rank intervals, as shown in Figure 19b. Plots of the 

reflectance data from all of a coal’s components do not form straight lines because liptinite and 

inertinite reflectances do not have normal distributions. The distribution of inertinite reflectance is 

always skewed, which results in a flattening of the trace at high reflectance values, above the straight 

portion associated with vitrinite (Figure 19c). Thus, whole coal reflectance probability distributions 

show varying patterns depending on the rank, petrographic composition and number of coals in the 

blend (ibid). Computer modelling developed by Pearson (1991) can identify the proportions of 

component coals in blends of two or three coals from the whole coal reflectance data. 

These properties are obviously very important now as a predictive tool for coal combustion 

characteristics, especially for predicting char morphology. Although the maceral and microlithotype 

analyses are determined as a percentage by volume, and additivity is on a relative mass basis, there 

is no reason to suspect that these properties are non-additive. Carpenter (1995) states "Provided the 

macerals can be correctly identified, maceral composition is probably additive for blending coals", her 

qualification reflecting the subjectivity of the test. The additivity of reflectance values is unknown. They 

are probably additive. Carpenter (1995) is more circumspect, stating "The reflectogram of single coals 


is possibly not additive, but there appears to be little experimental evidence to support this 

conclusion." 

Figure 19: Schematic illustration of Pearson’s (1991) plots of the vitrinite reflectance distribution of a 

single high-volatile bituminous coal (A), a blend of three bituminous coals (B), and reflectance of all the 

maceral components of a low volatile bituminous coal (C). From Taylor et al. (1998). 


Boiler 

The proportions of the microscopically recognisable constituents of coal, or macerals, present in the 

coal, affect the type and size of char formed during combustion (Bailey et al, 1990; Rosenberg et al., 

1996; Benfell and Bailey, 1998). Maceral content also effects the char reactivity, resulting in variations 

in burnout. Historically, in bituminous coals, the maceral group vitrinite has been assumed to be more 

chemically reactive and fusible than the maceral group inertinite and, in particular, the maceral 

fusinite. However, for Permian coals such as those in Australia, the inertinite group macerals show a 

wide range of physical and chemical properties. In these coals, the major inertinite group maceral, 

semifusinite, can have reflectance values close to that of the accompanying vitrinite. The reflectance 

of the individual macerals is related to their fusibility such that low-reflecting semifusinite displays 

fusible behaviour in coking (Pearson and Price, 1985; Diessel and Wolff-Fischer, 1987; and 

Kruszewska, K., 1989). 

The extent of fusibility of the inertinite in a coal is one of the factors influencing the morphology of the 

daughter chars produced during pulverised fuel applications. The observed variations in char 

structure in turn influence the overall burning rate (Benfell et al, 2000). It is therefore important to 

determine both the amount of each maceral present, and their reflectance ranges, when assessing a 

coal for combustion purposes. 


4 OTHER COAL PROPERTIES 

Section 3 listed all of the essential coal properties from which power station performance may be 

attempted to be predicted for blends or single coals. Many experimental techniques exist to determine 

other, less fundamental, coal properties. These are often only used in research applications but, when 

applied to a problem at an operating plant, can often provide a valuable understanding of the 

mechanisms involved, and assist in obtaining the optimum solution. The following discussion aims at 

providing information on coal properties which are not essential, but which are often encountered. 

Advanced techniques discussed in this section have been limited to those techniques available at 

multiple sites within Australia, or freely available through selected laboratories. 

Several sources have been used to draw together the information presented below. Many of the 

techniques described have been utilised by groups within the Cooperative Research Centre for Black 

Coal Utilisation and ACIRL Ltd. A report by A. Carpenter (1995) has also been very useful. 

4.1 Ash behaviour by advanced techniques 

As noted in Section 3, the fusibility character of coal ash strongly affects, and is affected by, the 

operation of the boiler. Increased deposition reduces the heat transfer from the combustion of the coal 

to the steam cycle, while changes in the amount of heat generated in the radiant section of the 

furnace can induce deposit formation. 

As the ash fusion temperatures often do not provide enough information to explain slagging and 

fouling within the boiler, advanced analysis techniques have been developed which can assist in the 

explanation of ash behaviour. These techniques include thermomechanical analysis (TMA), computer 

controlled scanning electron microscopy (CCSEM), scanning electron microscopy (SEM), x-ray 

diffraction analysis (XRD), and drop tube furnace studies. The results of thermomechanical analysis 

and drop tube furnace studies for ash deposition are not additive because these tests describe the 

melting behaviour of the ash, and this is dependant on the ash composition. CCSEM and XRD results 

on the other hand, which describe the composition of mineral matter in the coal, are additive. 

Thermomechanical analysis 

Thermomechanical analysis measures the change in size of an ash sample as it sinters and melts, 

while the temperature is continuously increased. The melting behaviour can be used to predict the 

temperatures at which deposit formation may inhibit the heat transfer within a pf furnace. As this 

technique provides more information than ash fusibility temperatures, it is often used to provide a 

stronger guide to deposit formation, or to explain the observed fusibility behaviour of a coal ash. Due 

to the variability of ash behaviour, the behaviour of ash from a blend cannot be predicted from the 

TMA analysis of the individual coal ashes. 

Methodology 

A schematic diagram of a Setram TMA92 Thermomechanical Analyser is shown in Figure 20. 

Approximately 50 mg of sample is crushed to less than 106 μm, before being placed into a crucible. 

The sample is compacted with 260 kPa pressure and then a penetrating ram is inserted into the 

crucible. The entire sample assembly is placed into the TMA instrument and purged with high purity 

argon for ten minutes. When considering the melting behaviour of the ash alone, the sample 

assembly is heated from ambient conditions at a rate of 50°C per minute to 700°C, and then at 5°C 

per minute to 1600°C according to a standard procedure (Saxby, 1996). When the sintering behaviour 


of the ash is also being considered, the assembly must be heated at 5°C per minute from ambient (or 

a temperature well below the sintering temperature) to 1600°C. A load of 100 g is applied to the 

penetrating ram, resulting in a pressure of 140 kPa at the interface between the penetrating ram and 

the sample surface. As the sample is heated, the penetrating ram is forced into the ash, and may 

eventually contact the base of the crucible, if the slag completely flows into the annulus between the 

crucible and penetrating ram. Output from the TMA comprises the degree of ram penetration into the 

sample, expressed as a percentage of the original height of the sample, at a specific temperature. 

TMA measurements are usually conducted in sample assemblies constructed from molybdenum 

(Mo). 

Figure 20: Schematic diagram of TMA apparatus, and ash sample assembly prior to heating. 

Computer controlled scanning electron microscopy 

This technique determines the size, shape, quantity and composition of mineral grains in coal or ash. 

The chemical compositions obtained are classified into mineral types or categories. CCSEM based 

slagging indices proposed by Gibb (1996) use the concentration and distribution of slagging 

components to predict the slagging behaviour. The index is additive, as fly ash generally consists of 

alumino-silicate glasses. 


Methodology 

CCSEM samples are generated by mixing pulverised coal samples with finely ground carnuba wax, 

which are then pressed, cross sectioned, polished and carbon coated. The wax is chosen to produce 

a SEM contrast intermediate to that of the coal and minerals, as indicated in Figure 21. An electron 

beam scans across the sample, and minerals are detected by an increase in contrast above the 

mineral threshold. Mineral associations are determined as included or excluded by the contrast of the 

surrounding material, coal for included minerals and wax for excluded minerals. The beam then scans 

across the particle on a number of chords to determine the particle size. 

Figure 21: CCSEM mineral detection process. 

An energy dispersive x-ray detector measures x-ray counts as a function of x-ray energy to produce a 

spectrum for an individual mineral particle. Specialised software then determines the elemental 

concentrations from the x-ray counts of known characteristic peaks. Based on these element 

concentrations, particles are then classified into mineral groups according to specific criteria 

(Folkedahl et al. 1993), which are presented in Table 11. 

X-ray diffraction (XRD) analysis 

XRD analysis is completed on the ash of the coal produced by low temperature ashing, to determine 

the mineral species present in the coal. Used alone, the results are qualitative, providing information 

on the species present but not on the amount of each species. Siroquant analysis determines the 

amount of each species present from the XRD results. XRD analysis can also be used to determine if 

crystalline species are present in a deposit. 

Methodology 

The ash sample is ground to a fine homogeneous powder and placed between thin-walled glass 

slides, in cellophane capillary tubes or moulded into an appropriate shape before being positioned for 

analysis. The sample is hit by an x-ray beam, and the resulting diffraction pattern of the beam is 

recorded. The diffraction observed differs for the various crystals present in the ash, allowing 

identification of each crystalline material. 


Classification 

No. 

Mineral/chemical 

categories 

Compositional criteria (relative EDX* intensity) 

1 Quartz Al≤5, Si≥80 

2 Iron oxide/siderite Mg≤5, Al≤5, Si10, Ca+Mg≥80 

8 Ankerite Mg20, Ca+Mg+Fe≥80 

9 Kaolinite Na≤5, Al+Si≥80, K≤5, Ca≤5, 0.85, 

13 Ca-Al Silicate Na≤5, Al≥15, Si>20, 

Ca+Al+Si≥80 

S≤5, K≤5, Ca≥5, Fe≤5, 

14 Na-Al Silicate Na≥5, Al≥15, Si>20, 

Na+Al+Si≥80 

S≤5, K≤5, Ca≤5, Fe≤5, 

15 Aluminosilicate Na≤5, Al>15, Si>20, K≤5, Ca≤5, Fe≤5, Al+Si≥80 

16 Mixed Silicate Na20, Si>20, S≤5, K20, S≤5, K≤5, Ca>10, 

Ca+Si≥80 

Fe≤5, 

19 Ca Aluminate Al>15, Si≤5, P≤5, S≤5, Ca>20, Ca+Al≥80 

20 Pyrite S>40, Ca20, Ca>5, Ti>5, Fe≤5, Ba>5, S+Ca+Ti+Ba≥80 

29 Gypsum/Al 

Silicate 

Al>5, Si>5, S>5, Ca>5, Al+Si+S+Ca≥80 

30 Si Rich 65≤Si

Figure 22 shows the output from x-ray diffraction analysis. The size of the peaks is a function of the 

amount of each crystal present in the ash. Siroquant analysis models the peaks of the XRD analysis, 

generating a curve which matches the XRD results, allowing the quantity of each crystal present to be 

determined. 

Figure 22: Experimental output from an XRD analysis of coal ash. 

Drop tube furnace studies 

A drop tube furnace is basically a vertical tube furnace, which can provide high heating rates (10 4 to 

10 5 K/s), high temperatures (to 1800 o C), a dynamic dilute particle phase and an atmosphere 

simulating combustion. This ensures that the apparatus provides results appropriate for pf combustion 

in the following areas (Carpenter and Skorupska, 1993): 

• pyrolysis/devolatilisation mechanism: the effect of operating conditions and coal 

properties on pyrolysis products, 

• coal ignition, burnout and char combustion mechanisms, 

• nitrogen oxide production and 

• ash deposition mechanisms 

Drop tube furnaces are generally considered to be a research tool, and only to be used for 

fundamental studies. However, the results from these analyses are most appropriate for pf 

combustion and provide a high confidence without completing pilot scale or large scale tests. Results 

from drop tube studies on ash deposition are not additive, as the behaviour of the ash is dependant 

on its melting behaviour, which in turn depends on its composition. 

Methodology 

Coal is fed as dilute particles in a gas stream into the hot zone of the furnace, via a cooled probe. This 

ensures a fast heating rate. Depending on the area of consideration, the coal or ash is collected by a 


second probe at the base of the furnace and analysed for composition or carbon content. Since a 

mass balance is difficult to obtain across the furnace, the ash in the coal is used as a tracer when a 

drop tube is used to measure the char reactivity. That is, the amount of carbon left in the coal is 

determined based on the original proportion of ash in the coal. 

Entrained flow reactors 

An entrained flow reactor is effectively a drop tube furnace in which the coal particles are flowing in 

the gas stream at a velocity greater than their terminal velocity. These reactors are designed to 

ensure the gas flow is laminar, and that minimal mixing of the gas stream occurs. This is achieved by 

the addition of a “flow creator” at the coal feeder. 

Scanning electron microscopy (SEM) 

A scanning electron microscope can be used to study the composition of deposits, with special 

attention given to the layer attached to the metal surface, or to the composition of the bridging 

material within agglomerates. Knowledge of the composition and grain size of particles in these areas 

of deposits can be used to identify the elements associated with deposit formation, or to identify the 

mechanism for deposit formation. Once the mechanism of deposition is found, corrective action can 

be taken to stop deposit formation or to limit its impact on the boiler. 

Samples for SEM work are mounted in an epoxy block, and the surface of the block is then ground 

and polished, and coated with carbon prior to analysis. The SEM, operated in the secondary electron 

imaging mode, allows analysis of the sectioned surface of the deposits. 

4.2 Arsenic 

Arsenic is often associated with pyrite, and is therefore probably additive. It is one of a number of 

trace elements which need to be considered, in blend coals or singly, on environmental grounds. It is 

included in Table 4, under Trace Elements. Clarke and Sloss (1992) and Davidson & Clarke (1996) 

produced two good IEA reports on trace elements, one of which describes the partitioning of each 

trace element into the various waste streams in a power station. See also the IEA report by Couch, 

1995. 

4.3 Char reactivity 

Char reactivity refers to the rate of combustion of a coal. Unburnt carbon in fly ash results from the 

incomplete combustion of coal due to boiler operation, design and coal rank (increased rank 

decreases coal reactivity). Addition of a more reactive coal in a blend may starve the unreactive char 

of oxygen and increase the carbon in ash, although it may also increase the flame temperature, which 

may result in more burnout. Altering the proportion of excess air or the size of the coal will be more 

likely to impact on the carbon in ash values produced by a boiler. 

Fly ash with high carbon content is usually unsaleable, effecting an important by-product of the plant, 

and increasing difficulties in disposal. Increasing the carbon content in the fly ash will also lower the 

ash resistivity, but carbon also has a high affinity for SO3, and is highly prone to re-entrainment, 

decreasing the efficiency of the electrostatic precipitators (Carpenter, 1995). 

Char reactivity, as a value, is not additive. Char reactivity can be measured by themogravimetric 

analysis or by drop tube furnace experiments. See Section 4.1 for a discussion of drop tube furnace 


studies. Studies of coal pyrolysis, reactivity and NOx formation in drop tube furnaces have shown 

them to be generally additive, as the particle cloud in a drop tube is dilute and very little interaction 

occurs. The behaviour of the blends in these studies is strongly influenced by the gas conditions set 

by the operator. 

Thermogravimetric analysis 

Thermogravimetry is a technique in which the mass of a sample is monitored over time or 

temperature. A coal sample’s changing mass can be measured during combustion or pyrolysis at a 

set temperature, under specific atmospheres. This information allows the reactivity of the coal to be 

determined. Unfortunately, the heating rates of the sample achievable in this equipment are not as 

high as those experienced in pf boilers, and Elliott (1981) notes that the rate of heating effects the 

reactivity of a coal because carbon deposition can occur during volatile release, thus reducing char 

reactivity. The carbon structure of the coal can also alter slightly during heating, which also effects the 

char reactivity. 

When a blend is studied by TGA, the coals appear to interact, producing a different result than when 

each coal in the blend is studied individually and the results combined. In boilers this reaction will not 

occur as particles are separated in the gas stream during combustion. 

Methodology 

A coal sample is placed within a thermogravimetric analyser and the controlled atmosphere allowed to 

equilibrate. The mass of the sample is recorded continuously, while the temperature of the sample is 

increased at a set rate until pyrolysis or combustion occurs. The change in mass, indicating the 

amount of coal remaining, is often matched with analysis of the off-gas. 

4.4 CO2 or Cm 

Originally reported as CO2, this property is now reported as Cm or mineral carbon. 

Cm = CO2 x 0.273. 

It is only included in Wall's table (Table 13), as affecting the boiler, because it indicates the presence 

of the carbonate minerals, especially those of calcium and iron. Thus it is an indirect rather than direct 

property. It is probably additive. 

4.5 Crossing point temperatures 

Of the many tests available for indicating the propensity of a coal to heat spontaneously, the simple 

Crossing Point Temperature test or Relative Ignition Test (RIT) is the most common. In this test a 

granular sample of coal, of fine particle size, is heated at a fixed rate (2°C/min.) while oxygen is 

passed through it. At some point the temperature of the coal begins to increase at a greater rate than 

the controlled heating rate of the containing vessel, due to the onset of spontaneous heating. The 

point where the temperature of the sample crosses the temperature of the sample container is 

identified as the Crossing Point or Relative Ignition temperature. 

The ignition temperature is not a physical constant for a given coal, but rather is dependent on the 

prevailing conditions under which the test is conducted. This includes furnace design, method and 

rate of heating, coal particle size, mass of sample, oxidant type (i.e. air or oxygen) and flow rate. 


Results are evaluated by comparison with the results of reference coals of known self-heating 

propensity, hence the term Relative Ignition Temperature (RIT). Experience at the Australian Coal 

Industry Research Laboratories (ACIRL) has shown that RIT values in excess of 200°C are indicative 

of a low self-heating propensity, whereas RIT values less than 130°C are indicative of a high selfheating 

propensity. 

The original work at Australia's CSIRO by Kirov (1954) showed that there was a general increase in 

this temperature with rank, from about 120°C for brown coals and lignites to about 210°C for 

anthracites. Most coals fell within the range 140°C to 177°C. For example coals in the Hunter Valley 

of NSW, being of high volatile bituminous rank, generally have Crossing Point or Relative Ignition 

temperatures in the range 140°C to 150°C, while the higher rank South Coast coals have 

temperatures in the general range 160°C to 180°C. 

It is not known if this property is additive. It is suspected that it is not. Depending on the blending 

efficiency, pockets of lower rank coal might cause a spontaneous heating, even in a mixture with a 

higher rank coal. 

4.6 Fixed carbon (FC) 

This is not an analysed property. Rather, it is determined by difference i.e. 100 - moisture - ash - 

volatile matter (all on the same basis). Thus its additivity will depend on the additivity of the other 

three properties, and carries any errors in their determination. Although its name suggests that it 

comprises purely carbon, it also significantly includes nitrogen, sulphur and oxygen. So its use in 

predicting power station performance, alone or as a component of the "fuel ratio", seems of dubious 

value. Carpenter (1995) says that FC "can provide an estimate of the quantity of char that will be 

produced and indicate the amount of unburnt carbon that might be found in the fly ash". The ultimate 

analysis carbon would surely be more precise. 

4.7 Fly ash resistivity 

This property is only given in the Wall (Table 13) and Skorupska (Table 15) tables. References to fly 

ash resistivity have been made in sections 3.3 (total sulphur) and 3.11 (ash analysis). 

The electrical resistivity of fly ash is dependent on physical and chemical characteristics of the ash 

and the environment in which it is tested. Resistivity can be measured using both laboratory and insitu 

apparatus. The standard technique for laboratory measurements of resistivity is described in the 

American Society of Mechanical Engineers Performance Test Code 28, and the Institute of Electrical 

and Electronics (IEEE) Standard P-548-82. There is some considerable variation in the types of 

apparatus and techniques used for in-situ measurements of resistivity. 

Laboratory measurements of resistivity typically generate a profile of resistivity as a function of 

temperature as shown in Figure 23. 


Figure 23: Typical fly ash resistivity profile as a function of temperature 

Limited information pertaining to coal blends 7 suggests that the resistivity values for a blend made up 

of coals having vastly different resistivity values will be intermediate between those resistivity values. 

For blends made up of coals with reasonably similar resistivity values (i.e. differing by no more than 

one or two orders of magnitude), there is no indication of the additivity of resistivity values. 

4.8 Fuel ratio 

This is not in the Wall (Table 13), Su (Table 14) or Carpenter (1995) tables, but is given in 

Skorupska's table (Table 15). See also section 3.1.4 (volatile matter) and notes on fixed carbon in 

section 4.6 and Appendix A2.1. It is a coarse factor, useful for broad predictions only. The numerator 

and denominator both include properties which are not relevant to those power station performance 

characteristics that the fuel ratio is meant to predict For example FC includes N and O, and V includes 

mineral volatiles such as CO2 and H2O. The fuel ratio was used in 1877 by Fraser to design a coal 

classification system, which is expressed in integer values only, and is well suited to this type of 

application (van Krevelen 1993). 

4.9 Inherent moisture 

In its true context, this is an intrinsic property of the in situ coal, governed by the coal rank and type. It 

is often used, incorrectly, when the term air-dried moisture is intended. Comments are similar to those 

for MHC in section 4.10. 

7 

Conroy, A and Bennett, P “The Combustion Behaviour of Australian Export and Overseas Low Rank Coal 

Blends”, ACARP Project C3097 End-of-Grant Report, 1997 


4.10 Moisture holding capacity (MHC) 

For coals of bituminous rank and higher, and some sub-bituminous coals, with bed moisture values of 

30% and less, moisture holding capacity (MHC) is considered to be a useful estimate of bed moisture 

(Selvig & Ode, 1953). Solid coal, in situ, comprises internal (pore) moisture only, and this is what is 

determined by the moisture holding capacity test. The moisture holding capacity test, such as 

specified in Australian Standard AS1038 Part 17 (1989), is carried out on coal with a top particle size 

of 0.212 mm, whereas the equilibrium moisture test described in ASTM D1412 (1993) is carried out at 

the coarser top size of 1.18 mm. 

There is no reason why MHC should not be additive. 

MHC would not be used to directly predict coal performance at/in a power station. Rather it tends to 

indicate the rank (and type) of the coal, and to determine many of those parameters which are directly 

used to predict performance (moisture, volatile matter etc). 

There is little doubt that dust may be a significant problem when total moisture values are less than 

the moisture holding capacity of the coal i.e. when the surface moisture is nil. 

4.11 Sulphate sulphur 

This is usually only a minor component of fresh bituminous coals, but it may be in significant 

proportions in weathered lignites. There is no apparent reason why it should not be additive. 

4.12 Organic sulphur 

This is the major sulphur form in most coals. It is generally fairly constant (dry, mineral matter free) for 

a given coal, with the variation in total sulphur mainly coming from fluctuations in the pyritic sulphur. 

There is no apparent reason why it should not be additive. 

4.13 Phosphorus 

This is generally present as the mineral apatite, a calcium phosphate, either as finely disseminated 

"inherent mineral matter", or in thickened aggregations or bands. Forms of apatite include fluorapatite 

and chlorapatite. It should be additive. The phosphorous in coal may be calculated from the P2O5 in 

ash as follows: 

P in coal% = P2O5 in ash x 0.4366 x ash in coal%/100 

4.14 Relative density (RD) 

Since relative density varies with coal rank, coal type, and mineral type (especially iron bearing 

minerals), it is difficult to predict much from a single RD value. It is hard to imagine that anything 

useful could be predicted from RD, which could not be better predicted from other parameters. 

Relative density is non-additive on a mass weighted basis (it is a mass/volume, not mass/mass, 

function). 


5 SPECIFIC RESPONSE TO ACARP RESEARCH PRIORITIES 

Three areas where highlighted by ACARP as being extremely important to the Australian coal 

industry: 

• Blending Australian high rank coals with low rank coals, 

• Blending Australian high rank coals with high sulphur coals and 

• Blending Australian high rank coals with coals of differing mineral matter content. 

Though not discussed under these headings, each of these items has been discussed in detail in 

Section 3. Therefore, the following is a summary of the discussion, highlighting the important issues 

for each. Table 12 also lists each aspect, and the impact on plant performance. 

5.1 Blending Australian high rank coals with low rank coals 

Australian coals are frequently bought by overseas power facilities to blend with low rank or lignitic 

coals, producing an efficiency improvement for the facility. When Australian higher rank coals are 

blended with low rank or lignitic coals, several performance issues are expected. Coals with 

significantly different ranks will generally have different handling behaviour. Therefore, plants 

designed to handle lower rank coals should experience improved handling performance through the 

addition of lower moisture, higher rank coals. 

The high moisture levels associated with lignitic and sub-bituminous coals impact on handling, milling 

and firing. They also effect particulate removal and de-NOx and de-SOx equipment. Mills that are 

designed to crush lower rank coals will have increased capacities when used to crush higher rank 

coal. Generally, lower rank coals are more friable, resulting in a higher throughput for the mills. 

However, lower rank coals also have a very high moisture content, resulting in a higher air 

requirement for the mills. If the mills cannot efficiently remove this moisture to a sufficient level, 

agglomeration of the coal may occur, leading to plugging of the pulverised fuel pipe between the mill 

and the burners. The addition of higher rank coals (such as Australian export thermal coals) to the 

indigenous feed coal will reduce this possibility. Moreover, since Australian higher rank coals have 

higher thermal values, lower mill throughputs will be required. 

Lower rank (higher volatile matter content) coals are generally said to have a higher potential for 

premature (spontaneous) combustion during milling, compared to higher rank (lower volatile matter 

content) coals, which may be due to the relative ease of ignition of the lower rank coals, as discussed 

in section 4.5, and noted by Pohl (1992). However, other studies have not been able to show any 

correlation between the coal volatile matter and documented cases of fires and explosions. It is 

probable that coal type and moisture content, along with mill operating variables, influence the risk of 

fires in mills more than coal volatile matter content. Anecdotal evidence suggests maintenance of 

mills, especially spindle mills, is a more important variable. Therefore the addition of Australian higher 

rank coals to lower rank indigenous coals will tend to raise the relative ignition temperature and may 

reduce the risk of fires and explosions. 

The lower moisture content associated with a blend of bituminous coal and a lignitic coal (compared 

with the lignite alone) will require less energy to evaporate the water, resulting in lower flue gas 

volumes. The total amount of energy associated with the flue gas, and lost from the boiler, will 

decrease. Lower fan capacities may be required, and the incidence of erosion within the boiler would 


e expected to reduce. Due to this decrease in gas volume, the efficiency of the electrostatic 

precipitators, de-SOx and de-NOx plants would be expected to improve. 

Reducing the volatile matter value in a coal blend is also expected to reduce the stability of a flame, 

although the flame shape and size can be altered. A sudden decrease in the volatile matter value in 

the coal blend would be expected to lower the flame temperature, reducing the energy absorbed in 

the radiant section and increasing the proportion captured in the convective section. The carbon 

burnout of the ash may fall due to this rearrangement of heat throughout the furnace. 

In low rank coals, a higher proportion of coal nitrogen is associated with the volatile component of the 

coal. Utilisation of low NOx burners would therefore be expected to have a greater impact on NOx 

formation for low rank coal blends than for a blend with a higher rank coal. However, it is common for 

a reduction of NOX to be accompanied by an increase in carbon in ash. 

Low rank coals also have significantly different ash properties that can lead to deposition. As these 

issues are related to mineral matter they are discussed in 5.3 “Blending Australian coals with coals of 

different mineral matter composition” below. 

5.2 Blending Australian high rank coals with high sulphur coals 

The blending of coals can be utilised to reduce SOx emissions, as a strong correlation exists between 

coal sulphur content and the SO2 emitted, except when large proportions of species able to absorb 

sulphur are present, such as calcium and magnesium. In these cases, sulphate species are formed 

which decreases emissions. US power stations have experienced reduction in SOx emissions, by up 

to 20%, by blending coal feeds. 

Tube corrosion can also be associated with sulphur. FeS or FeSO4 can form from a reaction of 

sulphur with iron in the tubes of the furnace. These species act as a flux, and a transfer medium for 

SO3 to travel to the tube surface, enhancing further corrosion. The formation of FeS and FeSO3 

depends on the condensation of SO3, which is a function of the dew point of SO3 in the gas. High 

sulphur coals have higher dew points that low sulphur coals, indicating that high sulphur coals will 

produce higher amounts of corrosion by this mechanism. As Australian coals have a low proportion of 

sulphur, addition of a higher rank Australian coal will decrease corrosion. 

However, sulphur is known to improve the performance of electrostatic precipitators. In fact, SO3 and 

H2SO4 have been added to the gas stream prior to ESPs to improve their performance. Therefore 

blending coals to improve SOx emissions may adversely impact on the performance of electrostatic 

precipitators. 

Pyrite is a strong source of sulphur, but particular issues associated with pyrite in coal have been 

discussed in 5.3 “Blending Australian coals with coals of different mineral matter composition” below. 

5.3 Blending Australian high rank coals with coals of different mineral matter 

composition 

Many problems throughout a pf plant are associated with coal minerals, including abrasion in the mills 

and deposition in the boiler. Some problems are straight forward, while others are extremely complex, 

such as deposition. Many mechanisms exist for deposition in boilers. Each mechanism depends on 

the type of minerals present in the coal. Some of the major difficulties associated with coal mineral 


matter are given in Table 12. All of the problems associated with mineral matter in coal can be 

reduced or overcome by blending with coals which reduce the concentration of the offending mineral. 

Low rank coals usually contain higher proportions of the alkali earth metals than high rank coals, and 

are therefore prone to deposition due to sulphate formation. The sulphates condense on cool surfaces 

when the temperature drops below the dewpoint of the sulphate, leaving a “sticky” surface to collect 

particulates. 

Pyrite can also cause slagging. In the flame, pyrite forms an Fe-O-S melt, with a melting temperature 

of approximately 1080°C. Pyrite can also vaporise and then condense on cool tubes. The result of 

both mechanisms is a sticky phase that will trap other particles in the radiant zone, resulting in 

slagging. Iron species in general can also form slagging when used in boilers which have regions with 

a reducing atmosphere, as is often found with low NOx burners. The reduction of the iron bearing 

species results in a low melting temperature phase that will capture other particles. Australian export 

thermal coals are relatively low in pyritic sulphur, so that their blending with higher pyritic sulphur 

indigenous coals will mitigate these problems. 

Chlorine has been associated with corrosion in boilers, though this has been linked to reducing 

conditions in the boiler. Chlorine species in the flue gas are also known to adversely affect selective 

catalytic reduction de-NOx plants and desulphurisation plants. Blending is the only technique available 

for reduction of chlorine, because washing is unlikely to remove chlorine as it is usually bound to the 

organic matrix of the coal. Australian coals are generally low in chlorine. 

Fine silica can form highly reflective deposits on furnace walls, resulting in poor heat transfer. 

Generally this problem is overcome by blending coals to produce larger particle sized ash which is not 

as reflective, or ash that forms sintered deposits. 

If the concentrations of CaO, SiO2 or Al2O3 change, the handling behaviour of the ash in sluiceways 

may alter, resulting in plugging or erosion. 

Ash composition effects the resistivity of an ash, impacting on ESP performance. Blending of coals is 

one method of overcoming poor ash resistivity. Decreasing the proportion of Fe2O3, K2O and Na2O, or 

increasing the proportion of MgO, CaO and SiO2, would be expected to improve the performance of 

the ESP. 

Coals containing large proportions of pyrite generally are considered abrasive, causing high wear 

rates in mills. Blending a high pyrite coal with a coal with little or no pyrite will reduce the wear in a mill 

but will not reduce the wear linearly with blend proportion because hard minerals are often retained in 

the grinding zone. Other hard minerals, such as quartz, will also cause abrasion in mills. 

Issue Property Impact on performance 

Blending 

Australian coal 

with low rank 

coals 

Moisture Improved handling properties. 

Less air requirements for mills. 

Lower flue gas volume, resulting in a change in efficiency of 

boiler, altered SO4 dewpoint, improved ESP performance and 

better de-NOx performance. 


Blending with 

high sulphur 

coals 

Blending coals 

with different 

mineral matter 

Volatile matter Low NOx burners produce less NOx, but are often accompanied 

by increased carbon in ash. 

Changing the volatile content will change the flame temperature. 

SOx emissions Increasing the proportion of low sulphur coal in a blend will 

decrease the SOx emissions. 

Greater reduction in SOx emissions can result when sulphur is 

fixed in the ash, as the sulphate, by Ca and Mg. 

Blending to reduce SOx in the gas stream will decrease the 

efficiency of ESP’s and de-SOx equipment. 

Pyrite Slagging has long been associated with pyrite; also abrasion in 

mills. 

Fe species Iron species can result in slagging when reducing environments 

exist (eg low NOx burners). 

Chlorine Chlorine is associated with corrosion but can be reduced with 

blending. 

Silica Quartz can be abrasive to mills and erosive to boilers. 

Fine quartz is reflective and can impede boiler performance. 

This is overcome with blending. 

Poor resistivity Decreasing the proportion of Fe2O3, K2O and Na2O or increasing 

ash 

MgO, CaO and SiO2 may improve ash resistivity and ESP 

performance. 

Table 12: Summary of the issues associated with blending Australian coals with indigenous coals. 


6 TECHNOLOGY TRANSFER ACTIVITIES 

The work completed in this report has been outlined in a paper presented at the Fourth Annual 

Participants Conference of the Cooperative Research Centre for Black Coal Utilisation, attended by 

many industrial personnel. Further information transfer will be completed when this report is circulated 

widely. The authors also strongly recommend that members of the coal industry who receive a copy 

of this report be surveyed to determine if the issues outlined in this study represent the same issues 

identified by industry personnel when selling or using coals as blends in general. Such a survey is 

believed to be a necessary step in the identification of issues associated with blending within the 

Australian coal industry but was not completed as it was not allotted funding in this project. 


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APPENDIX 1 

SUPPLEMENTARY 

REFERENCE 

TABLES 


APPENDIX 1 SUPPLEMENTARY REFERENCE TABLES 

PROPERTY 

Coal 

Handling 

Milling & 

Firing 

Boiler 

Ash 


Flue Gas 

Cleaning Other 

Coal and ash properties and plant systems affected 

SYSTEMS AFFECTED 

PLANT 

ENVIRONMENTAL 

Moisture Holding Capacity at x 

Inherent Moisture 

Proximate analysis (as fired) 

x x *1 

Moisture x x x x x 

Ash x x x x x x 

Volatile Matter x x 

Fixed Carbon x x 

Specific Energy x x 

Sulphur - Total x *2 

Pyritic x x x x 

Sulphate x x 

Organic x x 

Phosphorus x x 

Chlorine 

CO2 or Cm 

x 

x 

x 

Arsenic 


x 

Carbon x x 

Hydrogen x x 

Nitrogen x x 

Sulphur x x x *3 

Oxygen x x 

Hardgrove Grindability Index x *4 

YGP Abrasiveness Index x 

B.S. Index x 

Relative Density 

Ash fusibility temps 

x 

Oxidising x 

Reducing x 

Ash Analysis x x x x *5 

Trace elements - coal x 

Trace elements - ash x 

Flyash resistivity x 

Coal flow properties x 

Size distribution - coal x x 

Size distribution - flyash x x x x 

Ignition temp. - coal x 

Burning profile - coal x 

Comments 

*1 i.e. air-dry moisture, Mad 

*2 See also Sdaf in ultimate analyses 

*3 See also Sulphur - Total 

*4 Result does not relate to the sample, but to a specially prepared, sized, dedusted fraction. 

*5 SiO 2, Al 2O 3, Fe 2O 3, TiO 2, Mn 3O 4, CaO, MgO, Na 20, K 2O, Li 2o, P 2O 5, SO 3 

Table 13: Wall's table of the impact of coal properties on plant performance (Wall, 1988). 


PROPERTY 

Summarization of the additivity of various properties of blended coals * 

References for 

additive 

References for nonadditive 

Our conclusion 

Heating Value 

Proximate analysis 

6, 12 n/a Additive 

Moisture 5, 12 n/a Additive 

Volatile Matter 5, 6, n/a Additive 

Ash 6, , n/a Additive 

Fixed Carbon 

Ultimate analysis 

6 n/a Additive 

Carbon 12 n/a Additive 

Hydrogen 12 n/a Additive 

Nitrogen 12 n/a Additive 

Sulphur 12 n/a Additive 

Oxygen 

Ash analysis 

12 n/a Additive 

SiO2 n/a n/a 

Al2O3 n/a n/a 

TiO2 n/a n/a 

Fe2O3 n/a n/a 

CaO n/a n/a 

MgO n/a n/a 

Na2O n/a n/a 

K2O n/a n/a 

SO3 n/a n/a 

P2O5 n/a n/a 

Chlorine 5 n/a n/a 

Free Swelling Index n/a 12, 17, 18 Non-additive 

Ash Fusion Temperatures Non-additive 

Initial deformation n/a 12, 19, 20 Non-additive 

Softening n/a 12, 19, 20 Non-additive 

Hemispherical 12, 19, 20 Non-additive 

Fluid 12, 19, 20 Non-additive 

HGI 14, 15, 21, 22, 23, 24 12, 25, 26, 27 

< > means that some care in the application of the additivity/non-additivity rule for the corresponding 

parameter is required. For example, the measured dry ash contents for the blend were generally higher 

than the calculated ash values (reference 12). 

* Information from reference 5 is considered in the table. 

Table 14: Su’s table of additivity of properties for coal blends (Su, 1999). 

Su’s references: 

5 Carpenter, M A, "Coal blending for power stations", IEA/81, IEA Coal Research, London, 1995. 

6 Su S, Pohl J, "Combustion behaviour and ash deposition of blended coals in power station boilers", 2nd 

Asian Pacific Conference on Sustainable Energy and Environmental Technology, Gold Coast, 14-17 June 

1998. 

12 Riley J T, Gilleland S R, Forsythe R F et al, "Nonadditive analytical values for coal blends", 7th 

International Coal Testing Conference, pp 32-38, Charleston, WV, 1989. 

13 Artos V, Scaroni A W, "T.g.a and drop-tube reactor studies of the combustion of coal blends", Fuel 

1993, 72(7), pp 927-933. 

14 Hower J C, Wild G C, "Relationship between hardgrove grindability index and petrographic composition 

for high-volatile bituminous coals from Kentucky", Journal of Coal Quality, 1988, 7(4), pp 122-126. 

15 Conroy A P, Juniper L A, Phong-Anant D, "The impact of coal pulverizing characteristics on power 

plant performance", International Conference on Coal Science, Tokyo, Japan, 23-27 Oct 1989, pp 1003- 

1006. 

17 Cudmore J F, "Coal Utilization", in Ward C R, editor, "Coal geology and coal technology", Melbourne, 

Blackwell Scientific Publications, 1984, pp 113-150. 

18 Lowe A J, McCaffrey D J A, Richards D G, "PMRTA investigation into the non-additive swelling 

behaviour of coal blends", Coal Sci. Technol., 24 (Coal Science, Vol. 1), 1995, pp 343-346. 

19 Askew H, Lief H I, "Blending coals to meet ash fusion temperature specification", 5th Australian Coal 

Science Conference, Melbourne, 30 November-2 December 1992, pp 257-264. 

20 Lloyd W G, Riley J T, et al, "Ash fusion temperatures under oxidising conditions", Energy & Fuels, 

1993, 7, pp 490-494. 

21 Juniper LA, Smith B. “Research achievements in defining the combustion characteristics of Australian 

coals”. Coal Handling and Utilization Conference, Sydney, Australia 19-21 June 1990. p. 129-134. 

25 Waters A, "The additive relationship of the hardgrove grindability index", Journal of Coal Quality, 1986, 

5(1), pp 33-34. 

26 Sligar J, "Grindability of coal", Workshop on steaming coal: testing and characterisation, Newcastle, 

Australia, 17-19 Nov., 1987. 

27 Hower J C, "Additivity of Hardgrove Grindability: A case study", Journal of Coal Quality, 1988, 7(2), pp 

68-71. 


PROPERTY 

Summary 

Power station component performance 

Environmental control 

# of the impacts of coal quality on power station performance 

Ash 

manage 

ment 

Coal 

cleaning 

require 

ment* 

SOx 

control 

require 

ment* 

NOx 

control 

require 

ment* 

Overall power station performance 

Quality & 

quantity of 

waste 

products* Capacity Heat rate 


Mainte 

nance 

require 

ment* 


Steam 

Fly ash 

Availa 

& storage Mills Burners generator 

collection 

bility 

Ash content ▼▲ ▼▲ ▼▲ ▼▲ ▼▲ ▲▲ ▼▲ ▲▲ ▼▲ ▼▲ ▲▲ ▼▲ 

Heating Value ▲▼ ▲▼ ▼▲ ▲▼ ▼▲ ▼▲ ▼▲ ▼▲ ▼▲ ▲▼ ▲▼ ▲▼ ▲▼ 

Sulphur content ▼ ▼▲ ▼▲ ▲▼ ▲▼ ▲▼ ▲▼ ▲▼ ▼▲ 

Moisture ▼▲ ▼ ▼▲ ▼▲ ▼ ▼▲ ▼▲ ▲▼ ▼▲ 

Hardgrove Grindability ▲▼ ▼ ▲▼ ▼ ▼▲ ▼▲ ▼▲ ▲▼ 

Volatile Matter ▼▲ ▼▲ ▲▼ ▼▲ ▼▲ 

Ash fusion temperature ▲▼ ▲▼ ▲▼ ▼▲ ▲▼ 

Ash resistivity ▼▲ ▼▲ 

Sodium content ▼ ▲ ▼▲ 

Chlorine content ▼▲ ▼▲ ▼▲ ▲▼ ▼▲ 

Fuel ratio ▲▼ ▲▼ ▼▲ ▲▼ 

Free Swelling Index ▼▲ ▼▲ 

Size consist ▲▼ ▲▼ ▲▼ ▲▼ ▲▼ ▲▼ ▲ ▲▼ ▲▼ ▲▼ 

# 

compiled from observations from literature and the IEA Coal Research survey 

value of the property increases 

value of the property decreases 

▼ worsened (or decreased for components marked *) 

▲ improved (or increased for components marked *) 

Table 15: Skorupska’s table for the impact of coal quality on power station performance (Skorupska, 1993).

APPENDIX 2 

POWER STATION 

PERFORMANCE INDICES 


APPENDIX 2 POWER STATION PERFORMANCE PREDICTION INDICES 

Several indices have been developed to assist operators to determine the impact of coal and coal 

blends on plant performance. Listed below is a selection of the most widely used indices. These 

indices are derived from experience with a limited number of coals, and are unlikely to be applicable 

to other coals with different geological or geographical histories. They are based on the properties of 

laboratory prepared ashes produced under conditions different to those of pf fired boilers, and reflect 

the average composition of the coal blend, taking no account of the variability which exists within the 

blend (or coal). Also, they have been calibrated in boilers under baseline conditions that may differ 

depending on operation and advances in technology. 

A2.1 Fuel ratio as a predictor of burnout efficiency 

Fuel ratio (i.e. (fixed carbon)/(volatile matter)) is typically used as an indicator of burnout efficiency. 

Figure 24 shows the results of pilot scale combustion test work for several unblended and blended 

coals, determined in the ACIRL combustion test facility. As the figure shows, there is a general trend 

of decreasing burnout efficiency (as indicated by increasing levels of unburnt combustibles) with 

increasing fuel ratio. 

Unburnt Combustibles (%) 

10.00 

1.00 

0.10 

Unblended Coals 

0.01 

Blended Coals 

0.0 1.0 2.0 3.0 4.0 5.0 

Fuel Ratio (FC/VM) 

Figure 24: Unburnt combustibles as a function of fuel ratio for unblended and blended coals 

The figure also shows that the blended coals follow the same general trend as the unblended coals. 

There is, however, substantial anecdotal evidence to support the proposition that not all coals blended 

for fuel ratio (or volatile matter content), report burnout behaviour even approximating that of 

unblended coals of the same fuel ratio. The factors, which contribute to this, include the following: 

• The differences in fuel ratios of the blend components. Anecdotal evidence indicates that the 

burnout performance of blends made up of components with vastly different fuel ratios is more 

heavily influenced by the presence of the lower volatile or higher fuel ratio material (i.e. the least 

reactive material) and, because of this, will be inferior to the performance suggested by the prorated 

fuel ratio. 

• The extent to which particle size impacts burnout efficiency. As previously discussed, blend 

components with different HGI values will preferentially report to different size fractions in the 


pulverised coal product. Increased particle size adversely affects burnout efficiency, and this may 

impact on the overall performance of the blend depending on the other properties of the coal. 

A2.2 Sintering temperature for predicting fouling behaviour of coal ash 

The sintering temperature of an ash is the temperature when strength will begin to develop within a 

deposit due to sintering or bonding of ash particles. This temperature is simply determined by 

experimentation (Al-Otoom, 2000), but infrequently completed, as the sintering temperature of coal 

ash can be as low as 600 o C. Such temperatures are disturbing to operators who see no value in a 

temperature of 600 o C, which is significantly lower than the operating temperature of a boiler. 

However, these temperatures represent the starting point for sintering, or the temperature at which 

slight sintering will occur if enough time has elapsed. When compared to a coal with a sintering 

temperature of 1000 o C, it is clear that any deposition from ash with a sintering temperature of 600 o C 

will form strong and difficult to remove deposits in a shorter time frame at the operating temperatures 

of the boiler. 

A2.3 Sodium in ash to predict fouling behaviour 

Many empirical results have shown that the sodium content of ash can be used to predict boiler 

fouling, as sodium can initiate deposit formation. Table 16 shows the fouling expected from the 

proportion of sodium in ash. This index will work well when deposition is governed by sodium 

condensation. Deposition by other mechanisms can only be predicted with other indices. 

Na2O in ash (wt%) Boiler fouling 

2.5 Severe 

Table 16: The boiler fouling predicted by ash sodium content (Raask, 1985). 

A2.4 Alkali metal content for prediction of fouling 

Sintered deposits have been reported to have a layered structure resulting from the immiscibility of 

silicates and sulphates formed from the ash. Alkali metals generally form these sulphates species, 

which transport through the porous deposit as a vapour phase, depositing on the metal surface and 

producing a very strong adhesion of the deposit to the tube. Decomposition of sodium and calcium 

sulphates by silicates at temperatures in excess of 1100°K produce a glassy silicate with a low 

sintering temperature, which will increase the strength of bonds between particles (Raask, 1985). 

For bituminous coal, the index for alkali metals is defined as: 

⎛ % ash( 

db) 

⎞ 

( % Na 2O 

+ 0. 

6589% 

K2O) 

⎜ 

⎟ , 

⎝ 100 ⎠ 

where, %Na2O and %K2O represent the percentage of alkali metals present in the ash of a coal, as 

measured by XRF analysis and reported as oxides. Table 17 shows the values of this index which 

correspond to fouling propensity. 


Alkali index of coal Fouling 

0.6 Severe 

Table 17: The value of the alkali metal content of coal with corresponding boiler fouling (Raask, 1985). 

The value of the index should be additive for coal blends as it is based on the ash analysis. Note, 

however, the comments in sections 3.1.3 and 3.11 regarding sulphur fixation. The value of this index 

to Australian coals is dubious as Su (1999) found no significant correlation between fouling propensity 

of Australian coal blends and this index. 

A2.5 Viscosity of laboratory ash for predicting slagging behaviour 

Estimation of the ash viscosity at given temperatures provides an indication of the relative stickiness 

of particles, or the likelihood that particles will form deposits due to inertial impaction. Particles initially 

become “sticky” and are likely to form a deposit at viscosities between 10 6 to 10 8 Poise (Srinivasachar 

et al., 1990). Below this viscosity, particles are dry and will not collect on a surface. Above this 

viscosity the particles very quickly form a strong deposit that is difficult to remove, as shown in Figure 

25. 

Capture efficiency (uncorrected) 

1.0 

0.8 

0.6 

0.4 

0.2 

0 

Soda-lime glass 

53/74 μm 

1m/s 

8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 

1/T x 10 4 (K -1 ) 

Figure 25: The capture efficiency, or formation of deposit of soda-lime glass and the corresponding 

particle viscosity. 

To determine the viscosity of an ash at a particular temperature, most researchers use Urbain’s 

correlation (Urbain, 1981). Unfortunately, this correlation is only valid for homogeneous Newtonian 

slags, outside the regime of sticky particles. Another index, T25, gives the temperature at which slags 

have a viscosity of 25 Pas., again generally a molten flowing slag. Ultra-Systems Technology (1997) 


Transition 

8 

7 

6 

5 

4 

3 

Log 10 Viscosity (Pa.S)

found that T25 was inappropriate for Australian coals as there was no correlation with their slagging 

behaviour. The temperature of critical viscosity, the minimum temperature at which the slag behaves 

in a Newtonian manner, is also used but again this describes a liquid, homogeneous slag. 

A2.6 The iron/calcium ratio to predict coal ash slagging propensity 

The ratio of iron (%Fe2O3) and calcium (%CaO) in ash is recommended by Su as a good indicator for 

slagging behaviour for Australian coals and coal blends. A ratio near 1 was found empirically to 

produce severe slagging, and ratios near 0.3 and 3.0 produced some slagging. This index assumes 

strong interaction of iron oxide and calcium species, which could be expected in sideritic coals where 

iron is substituted by calcium. However, when sideritic iron is not replaced by calcium, the calcium 

must be closely associated with iron bearing minerals for this index to be valuable. The Fe2O3/CaO 

ratio of 3 is close to the eutectic found on the CaO, FeO, MgO phase diagram of 1160°C, shown in 

Figure 26, indicating that if CaO and FeO combine in these proportions a sticky phase will form in a 

boiler (Bailey, 1998). The other ratios assume interaction of iron and calcium along with other 

elements. Interaction of iron and calcium in a blend, when each mineral is present in separate coals, 

may still produce such slagging behaviour. However, study of the test data of Australian coal blends 

presented by Su does not seem to indicate any value of this index. 

Figure 26: The FeO-CaO-MgO equilibrium phase diagram showing the eutectic at 1160°C 

A2.7 Base to acid ratio for predicting slagging behaviour: 

The base to acid ratio is commonly used to predict the slagging propensity of a coal. It is defined as: 

% Fe2O3 

+ % CaO + % MgO + % Na2O 

+ % K 2O 

% SiO + % Al O + % TiO 

2 

2 

3 

2 

A value of the base to acid ratio between 0.4 and 0.7 indicates a high slagging propensity. Values 

outside this range indicate a lesser likelihood to slag. 


.

The base to acid ratio assumes that the addition of acidic components to an ash increases the ash 

melting temperature. Addition of basic components therefore decreases the melting temperature of 

the ash and the likelihood of severe slagging. In general, this principle is true for coal ashes. 

However, the basic components of the ash will effect the melting temperature of the ash in different 

ways and to different degrees, making comparison of coal ashes of significantly different composition 

impossible. As the index is based solely on the ash oxide analysis it ignores the impact of particle 

size, which can effect the deposition in a furnace, or the impact of particular minerals in coal, which 

are usually responsible for initiating deposition. Su (1999) found no correlation between slagging in 

test furnaces and the base to acid ratio of Australian coals or blends of Australian coals. 

A2.8 B/A x %S(db) to predict slagging propensity 

An index for slagging that multiplies the base to acid ratio with the sulphur content of the coal, on a 

dry basis, is sometimes used when the proportion of iron in the ash, as measured by XRF, is greater 

than the combined proportions of calcium and magnesium. This index assumes all sulphur is present 

as pyrite, which is inappropriate for Australian coals. 

Slagging deposits will often form from a deposit produced by particles collecting on a surface and 

then melting to produce a slag. Once molten, most particles that impact on the deposit will adhere to 

the deposit. But the composition of the slag may not be equivalent to the ash composition, depending 

on the deposition mechanism, ensuring that indices such as those presented here provide an 

inadequate comparison of slagging propensity. 

A2.9 Emission index: 

This is the amount of SO2 produced per MJ of energy input into a burner (measured on an 

experimental scale). It is non-linear in respect of blending ratio. 

A2.10 Erosion indices 

Two theories have been proposed to explain the erosion observed in PF boilers. Erosion by hard 

particles, consisting mainly of quartz, is based on the micro-machining theory, where impacting 

particles are believed to cut into the surface. The second theory is the platelet theory that suggests 

that the metal deforms when the hard particles impact into it. Continual deformation eventually causes 

some the surface to break away. In both theories, particle size, density and hardness strongly 

influence the degree of erosion caused by mineral species in the ash. Larger, denser particles carry 

more momentum, which results in more energy that can cause the particle to cut into the surface. The 

hardness of the material will determine whether the particle deforms the surface on which it is 

impacting, or whether it will deform itself. Materials softer than the tube walls will deform rather than 

affect the surface. Particles that have softened due to their temperature (i.e. have begun to melt) will 

be less likely to abrade any surface. Quartz, especially unfused quartz, is extremely hard. 

Aluminosilicates are also hard materials and are denser than quartz. They may therefore play a role in 

erosion. 

Particles of quartz encapsulated in coal will experience higher temperatures than particles not 

included in the coal matrix. Therefore particles in the coal matrix are more likely to be softer and react 

with other minerals which are also included in the coal, resulting in soft or molten particles that will not 

abrade a surface. 


As the erosion indices are generally predicted from an ash analysis, based on the proportion of hard 

materials in the coal, the indices are additive for blends. The following erosion indices are commonly 

used (Gupta, 1998, Raask, 1985): 

Silica: SiO2 content as per the standard ash analysis. This index assumes all silica is erosive and 

therefore will over-predict the erosive nature of many coals. 

Conventional erosion index: E=SiO2-1.5*Al2O3. This index assumes a set proportion of SiO2 is locked 

in clays (in a ratio of 1.5 to 1). The remainder is assumed to be free quartz. This proportion was based 

on British coal samples and has been show to represent American coals relatively well, though it has 

not been compared with Australian coals. 

Effective silica: The amount of silica SiO2 (wt.%) not included in the coal matrix. This is often 

expressed as a percentage of the total SiO2 content (based on the ash analysis). 

The Black Coal CRC Ash Effect Predictor uses CCSEM analysis to characterise the coarse excluded 

quartz, and therefore erosion.

a review of the state-of-the-art in coal blending for power ... - CCSD

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