IEA COAL RESEARCH

Coal classification

Anne M Carpenter

IEACR/12IEA Coal Research, LondonOctober 1988

Copyright © IEA Coal Research 1988

ISBN 92-9029-162-1

This report, produced by IEA Coal Research, has been reviewed in draft form by nominated experts in member countries andtheir comments have been taken into consideration. It has been approved for distribution by the Executive Committee of IEACoal Research.

Whilst every effort has been made to ensure the accuracy of information contained in this report, neither IEA Coal Research norany of its employees nor any supporting country or organisation, nor any contractor of IEA Coal Research makes any warranty,expressed or implied, or assumes any liability or responsibility for the accuracy, completeness or usefulness of any information,apparatus, product or process disclosed, or represents that its use would not infringe privately-owned rights.

IEA Coal Research

IEA Coal Research was established in 1975 under the auspices of the International Energy Agency (IEA) and is currentlysupported by fourteen countries.

IEA Coal Research provides information and analysis of all aspects of coal production and use, including:

- supply, mining and geosciences;- transport and markets;- coal science;- coal utilisation technology;- environmental effects;- by-products and waste utilisation.

IEA Coal Research produces:

- periodicals including Coal abstracts, a monthly current awareness journal giving details of the most recent and relevant itemsfrom the world's literature on coal, and Coal calendar, a comprehensive descriptive calendar of recently-held andforthcoming meetings of interest to the coal industry;

- technical assessments and economic reports on specific topics throughout the coal chain;- bibliographic databases on coal technology, coal research projects and forthcoming events, and numerical databanks on

reserves and resources, coal ports and coal-fired power stations.

General enquiries about IEA Coal Research should be addressed to:

Mr John TrubshawHead of ServiceIEA Coal Research14—15 Lower Grosvenor PlaceLondon, SW1W0EXUnited Kingdom

Telephone: 01-828 4661Telex: 917624 NICEBA GFax: 01-828 9508

Abstract

Literature (mainly post 1980) on coal classification is reviewed. Over the years many classification systems have beenproposed for coal. Some of the classification systems currently in use in the member countries of IEA Coal Research areexamined. These include Seyler's chart, the ASTM (used in North America), NCB (UK), Australian (including the new 1987system), German (Ruhr) and international (for both hard and soft coal) classifications. The new international codificationsystem is also covered. Reasons for the poor fit of some coals are discussed. The properties of coal (chemical, physical,mechanical and petrographic) that are used as classification parameters, and their determination, are described. A short sectionis included on potential analytical techniques. Properties of relevance in combustion, liquefaction and coking of coal and theiruse, or potential use, as classification parameters are then examined. (387 refs.)

Contents

List of figures 9

List of tables 11

Abbreviations 12

1 Introduction 131.1 Background 131.2 Scope of report 141.3 Rank 14

2 Chemical composition, properties and tests 162.1 Different bases of measurement 162.2 Carbon 182.3 Hydrogen 192.4 Oxygen 192.5 Sulphur 192.6 Volatile matter 202.7 Calorific value 212.8 Moisture 272.9 Inorganic constituents 22

3 Mechanical and physical properties and tests 243.1 Crucible swelling number 243.2 Roga index 243.3 Gray-King coke type 253.4 Audibert-Arnu dilatometer 253.5 Gieseler plastometer 253.6 Ash fusion temperatures 263.7 Hardgrove grindability index 26

4 Petrographic composition, properties and tests 274.1 Macerals 274.2 Vitrinite reflectance 294.3 Reflectograms 30

5 Potential analytical techniques 325.1 Derivative thermogravimetric analysis 325.2 Nuclear magnetic resonance 335.3 Pyrolysis-mass spectrometry 335.4 Fourier transform infrared spectroscopy 34

6 Classification systems 356.1 Seyler's classification 366.2 US (ASTM) classification 396.3 United Kingdom (NCB) classification 406.4 German (Ruhr) classification 426.5 International classifications 42

6.5.1 International classification of hard coals 426.5.2 New international codification of higher rank coals 446.5.3 International classification of brown coals 46

6.6 Modified international systems 476.6.1 Old Australian classification of hard coals 476.6.2 New Australian classification and codification 486.6.3 German international classification of hard coals 50

1 Combustion 577.1 Rank effects 527.2 Chemical composition and properties 55

7.2.1 Calorific value 537.2.2 Volatile matter 547.2.3 Ash and mineral matter 557.2.4 Moisture 577.2.5 Sulphur 577.2.6 Nitrogen 587.2.7 Chlorine 59

7.3 Mechanical and physical properties 597.3.1 Caking and swelling 597.3.2 Grindability 60

7.4 Petrographic composition and properties 607.5 Potential analytical techniques 61

7.5.1 Derivative thermogravimetric analysis 627.5.2 Pyrolysis-mass spectrometry 62

7.6 Commentary 62

8 Liquefaction 648.1 Rank effects 648.2 Chemical composition and properties 67

8.2.1 Carbon and hydrogen 678.2.2 Oxygen and nitrogen 688.2.3 Atomic ratios 698.2.4 Sulphur 708.2.5 Volatile matter 708.2.6 Moisture 718.2.7 Inorganic constituents 71

8.3 Petrographic composition and properties 728.3.1 Maceral composition 728.3.2 Reflectograms 73

8.4 Potential analytical techniques 748.4.1 Differential scanning calorimetry 748.4.2 Pyrolysis-mass spectrometry 748.4.3 Nuclear magnetic resonance 758.4.4 Fourier transform infrared spectroscopy 75

8.5 Commentary 76

9 Coking 789.1 Rank effects 799.2 Chemical composition and properties 79

9.2.1 Carbon and hydrogen 799.2.2 Oxygen 809.2.3 Atomic ratios 809.2.4 Sulphur 809.2.5 Chlorine and phosphorus 819.2.6 Volatile matter 819.2.7 Moisture 829.2.8 Inorganic constituents 82

9.3 Mechanical and physical properties 839.3.1 Crucible swelling number 839.3.2 Dilatation 839.3.3 Gieseler fluidity 849.3 A Roga index 84

9 A Petrographic composition and properties 859.5 Potential analytical techniques 87

9.5.1 Nuclear magnetic resonance 879.5.2 Fourier transform infrared spectroscopy

9.6 Commentary 88

10 Conclusions 90

11 References 92

Figures

1 Relationship of different analytical bases to various coal components 16

2 Variation of parameters with rank 18

3 Reflectogram of blend of high, medium and low volatile bituminous coals 30

4 Typical DTG burning profiles 32

5 Seyler's coal chart 37

6 Correlation of volatile yield with atomic ratio of coal 55

7 Fuel ratio as an indicator of coal reactivity 55

8 Activation energy verses burning profile peak temperature for different coal types 62

9 Variation of coal conversion with rank 65

10 Correlation of coal conversion with petrofactor 66

11 Cluster analysis on US bituminous coals 66

12 Coal conversion plotted on Seyler chart 68

13 Correlation of oil yield with oxygen and carbon 68

14 Relationship of oil yield with H/C atomic ratio 69

15 Relationship of oil yield with H/C atomic ratio, on a CO2-free basis 69

16 Relationship of coal conversion with reactivityvalues derived from the total reflectograms 73

17 Relationship of coal conversion with heat of hydrogenation (Q) 74

18 Factor spectrum for coal conversion to ethylacetate-solubles 74

19 Relationship of volatile matter with coke reactivity 81

20 Relationship of volatile matter with dilatation (bituminous coals) 84

21 Relationship of vitrinite reflectance with fluidity (MOF diagram) (bituminous coals) 85

22 Optimum ratio of reactives to inerts for each V-type 85

23 Plot of the apparent residual hydrogen content and mobile hydrogencomponent of a high volatile bituminous coal during pyrolysis at 4K/min 88

Tables

1 Huminite macerals 28

2 Vitrinite macerals 28

3 Liptinite macerals 28

4 Inertinite macerals 28

5 Main coal properties specified in some classification systems 35

6 Seyler's coal classification system 37

7 ASTM classification of coal by rank 38

8 National Coal Board classification system 41

9 Ruhr classification system 42

10 International classification of hard coals by type 43

11 International codification of higher rank coals 45

12 ECE classification of brown coals 46

13 ISO classification of brown coals and lignites 47

14 Australian classification system for hard coals 48

15 Classification and coding systems for Australian coals 49

16 Definition of traditional coal names 50

17 Effects of coal characteristics on different equipment in power plants 57

18 Indicative bituminous coal quality specifications for utilities 52

19 Strength of cokes produced from inertinite-rich and inertinite-poor coals 86

Abbreviations

ad air driedafm ash-free, moistAFT ash fusion temperaturesar as receivedAS Australian standardASTM American Society for Testing and MaterialsBS British standardCRI coke reactivity indexCSN crucible swelling numberCSR coke strength after reactionCV calorific valuedaf dry, ash-freedb dry basisDIN Deutsches Institut fur Normungdmif dry, mineral and inorganic-freedmmf dry, mineral matter-freeDSC differential scanning calorimetryDTG differential thermogravimetric analysisECE Economic Commission for EuropeEDX energy-dispersive x-ray analysisfbc fluidised-bed combustionFC fixed carbonFSI free swelling indexFT flow or fluid temperatureFTIR Fourier transform infraredHGI Hardgrove grindability indexHT hemisphere temperatureICCP International Committee for Coal PetrologyIDT initial deformation temperatureISO International Organization for StandardizationKMC King-Maries-CrossleyLTA low temperature ashmaf moist, ash-freemmf mineral matter-freemmmf moist, mineral matter-freeNCB National Coal Board (British Coal)nmr nuclear magnetic resonanceOKR Ostrava-Karvinapf pulverised fuelspy-ms pyrolysis-mass spectrometryRSI reaction strength indexSEM scanning electron microscopyVM volatile matter

1 Introduction

1.1 BackgroundCoals are of significant industrial and economic importance,both as an energy source and as industrial feedstocks.However, coals are complex, heterogeneous solids that varywidely in their properties and hence suitability for particularapplications.

Coal is a sedimentary rock composed principally of organicsubstances and inorganic minerals and moisture. It can becharacterised by its chemical composition and chemical,physical and mechanical properties. The properties andchemical composition of coal vary with the geologicalmaturity {rank) and different types or kinds of coal can bedistinguished by their inherent properties. In coal petrology,the organic fraction of coal is characterised by its maceralcomposition (see Section 4.1) and rank by the reflectance ofthe maceral, vitrinite (see Section 4.2). Coal type, to apetrographer, specifically refers to its petrographiccomposition (Ward, 1984a). The physical and chemicalproperties of each maceral differ and vary with rank, andthe proportions in which the macerals occur can also varywidely for coals of the same and different ranks. Likewise,the nature and amount of the inorganic minerals presentcan vary widely. In this report, the term grade will referto the amount of impurities, such as mineral matter, in thecoal.

The full characterisation of coal is a complex,time-consuming and expensive process. Therefore, a greatdeal of effort over the years has gone into developingsystems for classification.

The purpose of any classification is to group together thingsthat are similar and to distinguish between those that are not.The nature of a classification system will depend upon theparticular application for which the system is to beemployed. Classification systems for coal are broadly of twotypes: scientific and commercial (Marshall, 1976; van

Krevelen, 1961). These can serve different purposes.Scientific classifications can be broadly described as beingconcerned with the following aspects of coal:

- its origin;- its constitution, that is, its composition and structure;- 'fundamental' properties;- single seam coals.

Commercial classifications, on the other hand, are moreconcerned with the following aspects of coal:

- trade/market value;- its utilisation;

'technological' properties, that is, properties related fairlydirectly to the utilisation behaviour of coal;

- its behaviour;- single seam coals or blends.

It should be noted that some classification parameters can beof importance from both a scientific and commercial point ofview. In summary, commercial systems are more concernedwith the practical use of coal. The starting point of thesesystems is to identify the suitability of coals for its end uses.The majority of the established classification systems arecommercial systems that classify coals according to theirrank. Recently, systems that include both 'scientific' and'commercial' features have been developed, such as the newECE 'classification' (see Section 6.5.2). This systemincludes type (petrographic composition), as well as'technological' properties.

Some of the current classification systems in use in themember countries of IEA Coal Research will be examined.Different standards and nomenclatures are applied in thedifferent countries leading to differences in the terminologyof coal. In North America, the American Society for Testingand Materials (ASTM) classification is applied in which coalis divided into four classes: lignites, subbituminous,

Introduction

bituminous and anthracites. These terms are used genericallyin the literature. In Europe, coals are divided into two broadcategories, the hard/black coals and the soft/brown coals,with different dividing lines defined in the differentclassification systems. The terms brown coal and lignite areoften used interchangeably.

However, it has long been recognised that some coals do not'fit' existing classification systems. For example, there is awidely held view (ECE, 1976; Uribe and Perez, 1985) thatthe 'International classification of hard coals by type' doesnot cater adequately for the Gondwanan coals (that is, thePermian coals of the Southern hemisphere that weredeposited on the Gondwanaland supercontinent) on accountof their high inertinite content. Reasons for the poor fit ofsome coals will be examined.

The 'International classification of hard coals' was primarilydeveloped to assist in the international trade of coal and,when it was devised, only the Laurasian coals (that is, theCarboniferous coals of the Northern hemisphere that weredeposited on the Laurasian supercontinent) werecommercially traded. These days, with the growing trade inboth Gondwanan and Laurasian coals, there is an increasingneed for a global understanding of the relationships betweencoal characteristics and its behaviour in end-use processes.Understanding these relationships may lead to thedevelopment of a classification system that will 'fit' all typesof coal. Some of these relationships will be examined forcoal combustion, liquefaction and coking.

Some of the properties of coal that are used as classificationparameters or are used in the evaluation of coals for their enduse processes will first be discussed. Four of the neweranalytical techniques that have been used to characterisecoals will also be examined. These newer techniques mayprovide parameters that are more reproducible than some ofthe conventional empirical tests. If the determination of theclassification parameter is 'faulty' then a coal may not beaccurately classified; a classification is only as good as itsparameters. One can consider the following as the desirablecharacteristics of a test:

- reproducibility;adequate precision;

- objectivity;- reliability;- cheapness;- ability to be automated, making it less subjective and

reducing the cost;- additivity (for blending coals).

For commercial applications where blending is widespread,using parameters that are additive would have significantadvantages. How the tests meet the above requirements willbe discussed in Sections 2 to 5. It should be emphasised thatthe coal to be classified (or tested) must truly represent themass of coal from which it was taken; even the most preciseanalytical determination will be useless if the sample is nottruly representative. Various national and internationalstandards specify the procedure for collecting coal samples;following these should minimise any bias.

1.2 Scope of reportThis report examines the properties of coal that are currentlyemployed as classification parameters. In Section 2, testsconcerned with the chemical composition of coal aredescribed and, in Section 3, those concerned with themechanical and physical properties are covered. Thepetrographic tests are covered in Section 4. Since some ofthese tests are empirical, newer analytical techniques thathave been used to characterise coal are discussed in Section5. These tests may provide parameters that are morereproducible than some of the conventional empirical tests.

A number of classification systems have been proposed forcoal and some of those currently employed in the membercountries of IEA Coal Research are described in Section 6.

The significance of the various classification parameters inthe evaluation of coal for its end use is then examined.Three processes have been chosen to illustrate therelationships between coal characteristics and its behaviour:

- combustion for its commercial importance (Section 7);- liquefaction as an example of the newer technologies

(Section 8);- coking for historical reasons (Section 9).

Some additional properties that are employed by industry forthe evaluation of coals (for example, in coal specifications)that could possibly be used as classification parameters arealso considered. The report is concerned mainly with recentliterature (post 1980), although some older relevantreferences are included.

1.3 RankRank is an important concept in all classification systems.The rank of a coal is the degree or stage the coal has reachedduring its coalification, that is, its degree of metamorphismor geochemical maturity. Coalification refers to theprogressive transformation of peat through lignite/browncoal, subbituminous, bituminous to anthracitic coals (namesbased on the ASTM classification system). That is, rank is aqualitative description of the coalification sequence. It is notan objective property and therefore, opinions differ as towhich parameter would provide the best 'measure' of rank.As will be seen in Sections 2 to 4, many properties of coalchange with the degree of coalification and could thereforeprovide some measure of the rank. The ideal rank propertywould be easily and objectively measured and respondsensitively throughout the transition of plant substance toanthracite. No single property meets these criteria.

The identification of rank is important as it has a greatbearing on the properties of coal at that point of coalificationand its potential use (Falcon, 1978a; Given, 1984). Allclassification schemes use a measure of rank as one of theparameters to classify coal.

Although minerals in coal may be altered by metamorphicprocesses, it is the organic material that is most sensitive tothese processes. Therefore analyses to assess coal rank

Introduction

should be carried out on organic-rich fractions or else resultsshould be calculated to an ash-free or mineral matter-freebasis (Neavel, 1981).

There is often a tacit assumption that all coals follow asingle, though broad, band of development from the lowestto the highest rank. But it is not as simple as this, as thereare many distinct bands of coal development (Given, 1984;Valkovic, 1983). Coal is formed from a diverse set of floraand different phenomena characterised the various peatswamps and marshes from which the coal originated. Thisled to a great variety of coal types being formed throughoutthe geological ages; different coal types can be found withinone coal deposit and even within a single coal seam. That is,the properties of coal can vary both vertically andhorizontally within a coal seam. One of the most dramaticillustrations of the variations in coal properties within a seriesof related coal seams is in the Mahakam delta area ofIndonesia (Given, 1984). Coals in different areas alsoreached their present rank under widely differing sets of

conditions. Thus, one would expect many distinct bands ofcoal development. As a consequence of the many differentcoalification paths, it should not be surprising that thedifferent parameters of rank may not place coals in the samerank order.

Conflicting opinions on rank can be seen in some of the'scientific' and 'commercial' viewpoints. From a scientificviewpoint, it has been proposed that comparative rank studiesshould be carried out on the vitrinite maceral only; this willthen exclude the influence of the heterogeneity of coals asmuch as possible (ICCP, 1963, 1985; McCartney andTeichmuller, 1972; Neavel, 1981). Thus carbon content, forexample, would be measured only in the vitrinite. However,in the commercial sector, one is interested in the whole coal;properties determined on the whole coal will be an averagevalue and may well be quite different from that determinedon vitrinite alone. Thus two different measures of rank maywell be obtained.

2 Chemical composition, properties and tests

2.1 Different bases of measurementIn order to classify coals, two kinds of chemical analyses arecarried out:

- a proximate analysis which gives the relative amounts ofmoisture, volatile matter, ash and fixed carbon in coal;

- an ultimate analysis which determines the total amounts ofeach of the principal chemical elements present in coal,namely carbon, hydrogen, oxygen (usually bydifference), nitrogen and sulphur.

Most chemical analyses of coal are carried out on air-driedsamples and the percentage of the various constituents arereported to this basis. However, the analytical results can bemodified by appropriate corrections to allow expressions to anumber of different bases. Figure 1 indicates how some ofthese bases are related to various components of coal. Themost commonly-used bases in the various classificationschemes are:

(a) dry basis (db) - data are expressed as percentages of thecoal after the moisture has been removed, thuseliminating the effects of moisture, which is largelydependent on atmospheric conditions;

(b) dry, ash-free (daf) basis - the coal is assumed to be free ofboth moisture and ash;

(c) dry, mineral matter-free (dmmf) basis - the coal is assumedto be free of both moisture and mineral matter and thedata are therefore a measure of only the organiccomponent of coal;

(d) moist, ash-free (maf) basis - assumes that the coal is freeof ash but still contains moisture;

(e) moist, mineral matter-free (mmmf) basis - assumes thatthe coal is free of mineral matter but still containsmoisture.

throughout this report) is widely used, especially in Europe.It is used in this context, for example, in the 'Internationalclassification of hard coals'. However, in some countriessuch as the USA, maf can mean coal free of both moistureand ash (Elliott, 1981), that is, the same as daf. To avoidthis confusion, the term afm (ash-free and moist) hasbeen suggested (Standards Association of Australia,1987).

totalmoisture

mineralmatter

purecoal

surface moisture

inherent moisture

ash

volatilemineralmatter

volatileorganicmatter

volatilematter

fixedcarbon

ree

natte

rdr

y, m

iner

al r

i

i

dry,

ash

fre

e

>-

•a air

drie

d

as r

ecei

ved

K

There is some discrepancy over the term 'maf'. Thedefinition (d) (which is the definition that will be employed

Figure 1 Relationship of different analytical bases tovarious coal components (Ward, 1984b)

Chemical composition, properties and tests

As discussed in Section 1.3, analyses to assess coal rankshould be calculated to an ash-free or mineral matter-free(mmf) basis. The terms ash and mineral (inorganic) matterare often used interchangeably in the literature, but this canbe misleading. Coal does not 'contain' ash; ash is theresidue left after combustion. It differs both in amount andchemical composition from the mineral matter in coalbecause of the thermal decomposition of the mineral matteron heating. Callcott (1982), Gray (1987a) and Given andYarzab (1978) illustrate this in tables showing thedifferences that can occur when the elemental analysisof coal is calculated to a daf basis instead of a dmmfbasis.

Analyses calculated to the dmmf basis give a better measureof the organic portion of coal than the daf basis. Forexample, when coal is heated to determine volatile matter,volatile species will be evolved from both the organicconstituents and from the decomposition of the associatedinorganic material. This will include water from the water ofhydration of the clay minerals, carbon dioxide from thecarbonates, sulphides from pyrite and marcasite, andhydrogen chloride from the chlorides (Berkowitz, 1985;Given and Yarzab, 1978; Ward, 1984b). When volatilematter is calculated to a daf basis, no allowance is made forthis contribution from the decomposition of the minerals andthus volatile matter on a daf basis will be higher than on admmf basis. The difference will be most marked in coalshigh in pyritic sulphur, carbonates and chlorides. An ashdetermination is however, easier to perform than the analysesrequired for dmmf calculations (Scholz, 1980).

The mineral matter in coal can be estimated using variousformulae. One of the earliest formulae derived is the Pan-formula (used in the Seyler and ASTM classificationschemes), where the mineral matter is calculated from theash yield and the total sulphur content:

mineral matter — 1.08ash + 0.55sulphur

The coefficient of 0.55 indicates the proportion of sulphurthat is pyritic, but also includes a small allowance for theorganic sulphur (Gray, 1987a). However, the formula makesno specific allowance for the decomposition of carbonatesand chlorides (Given and Yarzab, 1978). The term 1.08 ashpurports to correct for the loss in weight (mass) due to theelimination of the water of hydration from the clay minerals,but the different clay minerals lose quite varying amounts ofwater on heating, with quartz losing no water at all(Berkowitz, 1985; Given and Yarzab, 1978; Valkovic, 1983).Thus to assume that a constant mean value for water loss canbe assigned to the mixtures of silicates in coals is unlikely tobe accurate for a wide range of coals. Given and Yarzab(1978) review data showing that the coefficient of the ashterm is variable for different coals (Australian and Americancoals). Lyons and Chase (1981) also found the Parr formulainappropriate for the high rank, high ash coals of theNarragansett Basin (USA).

Other formulae, which make allowances for a number ofeffects ignored by the Parr formula, have been suggested.The United Kingdom classification scheme uses a modified

form of the King-Maries-Crossley (KMC) formulawhere:

mineral matter = 1.13ash + 0.5Spyritic + O.8CO2 - 2.8Sash +2.8Ssulphate + 0.3C1

Allowances for the decomposition of the carbonates andchlorides (carbon dioxide and chlorine respectively), and forthe different forms of sulphur present (pyritic sulphur,retention of sulphate sulphur in the ash (Sash) and sulphatesulphur in the coal itself (Ssuiphate)) have been introduced.However, the equation still makes the basic assumption of aconstant water of hydration coefficient. The different formsof sulphur present and carbon dioxide present as carbonateare not generally undertaken in routine analysis (Scholz,1980). Many of the chemical treatments used in the analysisof the organic matter of coal will also solubilise part of themineral matter (Given, 1984). Errors in the chemicalanalysis will compound errors in the dmmf calculations.

The KMC formula was developed using British coals and itis therefore to be expected that the application of the formulato coals of a much more diverse origin would give lessprecise results. This has been shown to be true by Given andYarzab (1978). Neither the Parr nor the KMC formulae areapplicable to the mineral matter of lignites (Given andYarzab, 1978). The low rank coals contain inherentinorganic matter in the form of exchangeable cationsassociated with oxygen-containing functional groups(carboxyl groups). A substantial proportion of the ash isderived from these cations; that is, ash from low rank coals isnot derived solely from the coal mineral matter (Given andYarzab, 1978; Kiss and King, 1979; Perry and others, 1984).A method for expressing results for the low rank coals in amanner corresponding to the dmmf basis for the higher rankcoals has been developed, the 'dmif (dry, mineral andinorganic free) basis (Kiss and King, 1979; Perry and others,1984). This basis has not yet been included in aclassification system.

Other formulae have been suggested, but these can introduceother biases and are applicable only to the coals on whichthey were developed. An alternative is a graphical method(as described in Gray, 1980, 1983) where the coal property isregressed (using linear regression analysis) against ash andany other property likely to have an influence (such assulphur) to give an equation from which a mineral mattercorrection can be made. Although these equations will giveaverage values only, they do not require any knowledge ofthe mineral matter constituents. The technique can also beapplied to low rank coals.

Direct measurement of the mineral matter in coal can bemade (for example, AS 1038: Part 22); but the methods canbe time-consuming (Berkowitz, 1985; Given and Yarzab,1978) and so are not often carried out. When classificationparameters are corrected to a mmf basis, the accuracy of themineral matter calculation directly affects the precision ofclassifying the coals. As higher and more variable mineraland sulphur-bearing coals are mined and used, problems inmineral matter calculations can only worsen. However,corrections to a mmf basis, despite their faults, are still

Chemical composition, properties and tests

considered to reflect the organic portion of coal better thancalculations to an ash-free basis (Given, 1984; Given andYarzab, 1978; Ward, 1984b).

2.2 CarbonStandard techniques for determining carbon content (forexample, AS 1038: Part 6.1; ASTM D3178; BS 1016: Part 6;ISO 625) are similar. A weighed sample of coal is heated ina stream of dry oxygen in a closed system and undercarefully controlled conditions. The carbon content iscalculated from the amount of carbon dioxide that has beenevolved and collected in an absorption tube. Sulphur oxidesand chlorine that are also evolved are removed by thepresence of appropriate reagents. During the test, carbondioxide is also liberated from any carbonate minerals that arepresent in the coal (Neavel, 1981; Rees, 1966; Ward, 1984b),and so the analysis of 'total' carbon will include a measureof carbon from the inorganic material. Separate analyses canbe made to determine the carbonate carbon dioxide content(for example, AS 1038: Part 23; ASTM D1756; ISO 925)and correction formulae can be used to calculate the carboncontent to a mmf basis. Unfortunately, these correctionformulae can introduce their own bias, discussed in Section2.1. The carbon content is generally considered to beadditive for blending coals. The Seyler classification usesthe carbon content on a dmmf (Parr formula) as a parameter.

Although wet chemical methods for determining carbon,hydrogen, nitrogen and total sulphur are the techniquestraditionally used in classifying coals, automated instrumentalmethods are now commonly employed in laboratories. Theseinstrumental methods are fast and several elements can beanalysed in a single run (White and Whittingham, 1983).They may eventually replace the old standard methods as thepreferred technique for determining the classificationparameters.

Instead of elemental carbon content, the ASTM uses 'fixedcarbon' as a rank parameter in its classification scheme.Fixed carbon is the solid residue, other than ash, obtained bydestructive distillation of the coal under standardisedconditions. It is made up principally of carbon but maycontain appreciable amounts of sulphur, hydrogen, nitrogenand oxygen (ASTM D121; Rees, 1966). Among otherworkers, Solomon (1981) has shown that fixed carbondetermination is sensitive to the carbonisation conditions;therefore the ASTM standard (ASTM D3172) must befollowed if reproducible results are to be obtained. Unlikeelemental carbon, fixed carbon is not determined directly butis simply the difference in an air-dried coal between the sumof the volatile matter, moisture and ash contents, and 100%(ASTM D3172; Ward, 1984b). Therefore, fixed carbon willincorporate the errors, bias and scatter involved in thedetermination of volatile matter, moisture and ash, detractingfrom its reliability and accuracy. The ASTM classificationscheme calculates the fixed carbon to a dmmf basis using anequation based on the Parr formula {see Section 2.1).

Elemental carbon content is probably the chemical propertymost widely used in scientific investigations to express coalrank. During coalification, oxygen, and subsequently

hydrogen, in functional groups are removed from the coalsubstance and evolved as low molecular weight species(Neavel, 1981). As a result, carbon content increases withincreasing rank. It should be noted that carbon content of awhole coal might be different from that determined on justthe vitrinite maceral; therefore, different measures of rankmight well be obtained. (It has been proposed that, from ascientific viewpoint, rank should be assessed on only vitrinite- see Section 1.3.)

Figure 2 Variation of parameters with rank. The curvesprovide an indication only of the way in whichthe parameters change with rank (World CoalResources and Reserves Data Bank Service, 1 983)

Chemical composition, properties and tests

There are some low rank coals with a high organic sulphurcontent, such as the Illinois Basin (USA), Rasa (Yugoslavia)and Sharigh (Pakistan) coals, that have lower inherentmoisture and exhibit higher caking properties (crucibleswelling number of more than 5) than would be expectedfrom their carbon content (Elofson and Schulz, 1967). It hasbeen suggested that for these atypical coals, the carbon plussulphur contents would provide a better indication of rank asthe sum is approximately equal to the carbon content ofnormal high swelling coals.

In the ASTM classification, fixed carbon provides ameasure of rank for only the higher rank coals; one reasonis that it changes only slightly for those of lower rank(see Figure 2b).

2.3 HydrogenHydrogen content is usually determined with the carboncontent in one operation (see Section 2.2). The totalhydrogen content is calculated from the amount of watercollected in the adsorption tubes. The standardised methodmust be followed if reproducible results are to be achieved.However, this total hydrogen content will include hydrogenpresent in the moisture accompanying the sample andhydrogen present in the water of hydration in the minerals(Rees, 1966; Ward, 1984b). The moisture in coal can bedetermined experimentally and results calculated to a drybasis. Correction formulae can be used to calculate thehydrogen content to a mmf basis but, as discussed in Section2.1, these formulae can introduce their own bias. Thehydrogen content is generally considered to be additive. Ona dmmf basis (Parr formula), it is used as a parameter inSeyler's classification.

Hydrogen can be of significance in assessing the liquefactionand coking properties of coal (see Sections 8.2.1 and 9.2.1,respectively). During coalification, hydrogen in thefunctional groups in the coal substance is evolved as lowmolecular weight species (Neavel, 1981). As a result,hydrogen content decreases with increasing coalification andcan therefore be used as a rank parameter. Hydrogen contentis generally considered to provide a better indication of rankfor the anthracitic coals (Falcon, 1978a; McCartney andTeichmuller, 1972; Teichmiiller and Teichmuller, 1982),since generally, it alters only slightly for the lower rankcoals. Hydrogen content of a whole coal sample might wellbe quite different from that derived from just the vitrinitemaceral and could therefore provide a different measure ofrank.

2.4 OxygenOxygen content is probably the most significant indicator ofthe chemical properties of coal (Gray, 1983). It can be used(with other coal properties) to assess the combustion,liquefaction and coking properties of coal. Oxygen canprovide a measure of the rank (oxygen decreases with rank(Neavel, 1981)), but it is hardly ever used for this purpose.An obvious reason is that the effect of rank may beovershadowed by that of weathering. Also, there is as yet nogenerally accepted method for its direct determination.

Oxygen is generally considered to be additive for blending ofcoals.

The oxygen content is traditionally determined by subtractingthe sum of the other chemical components determined in theultimate analysis (carbon, hydrogen, nitrogen and sulphur)from 100%. Thus, this oxygen-by-difference will accumulateall the errors in the determinations of the other four elementsand especially when calculated to an ash-free or mmf basis(Given and Yarzab, 1978; Gray, 1983, 1987a; Rees, 1966).Oxygen content in a daf analysis is subject to bigger errorsthan in a dmmf analysis; that is, the discrepancy between thetwo analyses may be large, and will tend to increase withrank (Given and Yarzab, 1978).

Various methods for the direct determination of oxygenhave been proposed (Given and Yarzab (1978) review someof these methods), but no method has yet achieved wideacceptance. A simple, reliable and reproducible method forthe direct determination of oxygen is urgently required,but until such a method has been widely accepted andstandardised, oxygen-by-difference will remain thepredominant method of assessing oxygen.

2.5 SulphurSulphur can occur in coal in three main forms, as:

- organic sulphur, where it is incorporated into thehydrocarbon compounds of the coal structure;

- sulphide minerals in the inorganic fraction (pyriticsulphur);

- sulphate minerals in the inorganic fraction (sulphatesulphur).

Knowledge of the different forms of sulphur is required forcalculations to a mmf basis. As a general point, the ASTMincludes the total sulphur, that is the organic sulphur as wellas the inorganic sulphur, with the 'non-coal' (in mmf andash-free calculations). Other standards (for example, Britishstandards) include just the organic sulphur as part of the coalsubstance. Total sulphur has been proposed as aclassification parameter, as it represents a potential source ofpollution from coal use. It is generally considered to beadditive. The sulphur content of coal shows littlerelationship to rank and so cannot be used on its own as arank parameter.

The total sulphur is determined in the ultimate analysis ofcoal, as there is no standard method for the directdetermination of organic sulphur. There are two mainstandard methods for its determination. In the Eschkamethod (for example, AS 1038: Part 6.3.1; ASTM D3177;BS 1016: Part 6; ISO 334), a weighed sample of coal isoxidised at 800°C in magnesium oxide and sodiumcarbonate. Barium chloride is added, and the mass ofthe insoluble barium sulphate formed gives the total sulphurcontent of the coal. In a high temperature method (forexample, AS 1038: Part 6.3.2; ASTM D4239; BS 1016:Part 6; ISO 351), a weighed sample of coal is covered withaluminium oxide and burned in oxygen at 1350°C. Thesulphur present is converted to sulphur oxides which are

Chemical composition, properties and tests

then converted to sulphuric acid for titrimetric determination.This method is often preferred as it is quicker and has theadvantage of enabling the measurement of chlorine (ashydrochloric acid) at the same time (Gray, 1983).(Chlorine can be required for mmf and ash-free calculations.)However neither method has gone uncriticised(Markuszewski, 1988).

The amount of sulphate sulphur is determined (for example,AS 1038: Part 11; ASTM D2492; BS1016: Part 11; ISO 157)by extracting the weighed sample of coal with hydrochloricacid and precipitating the sulphur as barium sulphate forgravimetric determination. The method has been criticised asit is tedious, time-consuming and subject to error(Markuszewski, 1988).

Pyritic sulphur is determined indirectly by determining thetotal iron from a coal sample extracted with nitric acid andthe non-pyritic iron from extraction with hydrochloric acid.The difference between the two is assumed to be pyritic ironand the associated sulphur is pyritic sulphur. Somedifferences between the standard methods (specified in thesame standards as for sulphate sulphur) can give slightlydifferent results (Given and Yarzab, 1978; Gray, 1983).Also, certain coals with highly disseminated pyrite tend togive erroneously low results for pyritic sulphur, whenanalysed by these wet chemical methods (James and Severn,1967). Markuszewski (1988) discusses some of the errorsthat can occur in the ASTM standard method for pyriticsulphur determination.

There is, as yet, no standard method for the directdetermination of organic sulphur. It is deduced by thedifference between the pyritic and sulphate forms of sulphurand the total sulphur content. Thus, the calculation willaccumulate any errors in the direct determination of theseother sulphur contents, detracting from its reliability andaccuracy.

These standard wet chemical methods are being superseded.Automatic instrumental methods (often employing infraredtechniques) are now commonly used in the determinationof total sulphur. Several instrumental methods for the directdetermination of organic sulphur have also been developed;Markuszewski (1988) provides a selection. They can involvethe use of scanning electron microscopy in conjunction withenergy-dispersive X-ray analysis (SEM-EDX) (for example,as described by Maijgren and others, 1983; Straszheim andothers, 1983). SEM-EDX techniques can be time consuming.

However, an SEM-EDX procedure has been developed thatgives reproducible results on as few as20 points of observation (Burchill and others, 1987).Some of these instrumental techniques are being standardised(for example, AS 1038: Part 6.3.3 and ASTM D4239 specifyan infrared method for total sulphur determination) and mayeventually replace the standard wet chemical methods.

Any uncertainty in the organic and pyritic sulphur data couldhave implications for the postulated correlations betweenthese parameters and the liquefaction performance of coal(see Sections 8.2.4 and 8.2.7).

2.6 Volatile matterThe yield of volatile matter is one of the most commonlyemployed parameters in the classification of coal. Volatilematter can provide an indication of the combustion,liquefaction and coking properties of coal (see Sections 7.2.2,8.2.5, 9.2.6) and can be used as a rank parameter. Generally,volatile matter decreases with increasing coal rank. It isgenerally considered to be additive for blends of coal.

Volatile matter is determined by heating the coal sampleunder rigidly controlled conditions. The percentage loss ofmass less the percentage of moisture gives the proportion ofvolatile matter. The procedures are specified in variousnational and international standards (for example, AS 1038:Part 3; ASTM D3175; BS 1016: Part 3; ISO 562), butdifferences in the procedures can give slightly differentresults for the same coal, since volatile matter yield is afunction of sample size, particle size, rate of heating andmaximum temperature reached (Given and Yarzab, 1978;Gray, 1983). Therefore, the method specified in theclassification scheme must be followed or, if one is notspecified, the standard followed should be stated. The sameanalysis method should, of course, be followed for all thecoals being classified.

When coal is heated, as well as volatile matter being evolvedfrom the organic constituents, a portion will be volatilematter from the decomposition of the associated inorganicmaterial. Correction formulae are applied to calculate thevolatile matter to a mmf or ash-free basis, but, as discussedin Section 2.1, these formulae can introduce their own bias.Since the calculation of volatile matter to a mmf basisdirectly affects the accuracy of the classification of coal byrank, as higher and more variable sulphur- andmineral-bearing coals are mined and used, the problems willonly worsen.

Volatile matter is sensitive to variations in the petrographiccomposition of coal, since the macerals have differentvolatile matter yields (Pearson, 1985). Therefore, the higherinertinite content of Gondwanan coals means that volatilematter does not have quite the same relationship to rank as inthe northern hemisphere Carboniferous coals. This wouldalso be the case for other coals with low vitrinite or highexinite contents (McCartney and Teichmuller, 1972).

For coals up to about the high volatile bituminous A stage(as defined in the ASTM classification), volatile mattershows relatively little change (see Figure 2a). In mediumand low volatile bituminous coals (volatile matter of about30%-10%), volatile matter falls rapidly due to the removal ofaliphatic and alicyclic groups and increasing aromatisation ofthe humic complexes (Teichmuller and Teichmuller, 1982).Therefore, volatile matter is a better indicator of rank forthese higher rank bituminous coals.

Some methods for predicting volatile matter from ultimateanalysis have been proposed. For example Seyler (1938)used the equation:

volatile matter = 10.61 hydrogen - 1.24 carbon + 84.15

Chemical composition, properties and tests

for estimating the volatile matter for his coal chart.However, he found that the equation gave reasonable resultsfor only the vitrinite-rich coals below the anthracite rank andwith an oxygen content of less than 15%. Neavel and others(1986) found that the volatile matter of vitrinite-rich coalscould be estimated from their carbon, hydrogen, oxygen andsulphur contents. Presumably, these methods would onlyproduce reasonable results for coals of similar composition(type) to those on which they were derived.

2.7 Calorific valueCalorific value (or specific energy) is one of the most widelyemployed parameters used in classification schemes for thelower rank coals and is of obvious commercial significance,both in the trade and evaluation of coal. Generally, calorificvalue increases with increasing coal rank, largely as a resultof oxygen loss (Teichmiiller and Teichmiiller, 1982).

Gross calorific value is determined by burning a weighedsample of coal under controlled conditions, usually in acalorimeter, and correcting results for the presence of sulphurand nitrogen (Hessley and others, 1986; Ward, 1984b).Standard methods for its determination are specified in, forexample, AS 1038: Part 5, ASTM D2015, ASTM D3286, BS1016: Part 5 and ISO 1928.

Since the combustion takes place under conditions wherecondensation of water can occur, the total amount of energygiven off by the coal will be increased due to the latent heatof vaporisation. However, in an operating furnace, thecombustion products are emitted to the atmosphere beforecondensation. This net calorific value is lower than the grosscalorific value and these two values can differ significantlyfor low rank coals with high moisture content (Gray, 1983).The net calorific value is important in the commercial marketsince it gives a more accurate estimation of the calorificvalue of coal under actual operating conditions. However, itis the gross calorific value that is usually used in the variousclassification schemes. The two values can be predictedfrom each other, if the moisture and hydrogen contents of thecoal, as burned, are known.

When coal is burned, the heat of combustion will also beaffected by the mineral constituents; calorific value decreaseswith increasing mineral matter/ash (Pearson, 1985).Oxidation will also reduce the calorific value of a coal(Cudmore, 1984). The effects of moisture, however, willdepend on the basis used. To obtain the calorific value ofonly the organic portion of the coal, the contribution fromthe mineral matter will need to be taken into account.Equations for calculating the calorific value to a mmf orash-free basis can introduce their own bias, as has alreadybeen mentioned. Calorific value also varies with thepetrographic composition of the coal and is generallyconsidered to be additive.

Some classification schemes use gross calorific value on adaf basis as a classification parameter. Others use grosscalorific value on a mmmf (or maf) basis, especially whenclassifying the lower rank coals. The maf or mmmf basesare composite parameters because moisture on its own can

also be used as a rank parameter (see Section 2.8). Forprogressively higher rank coals, calorific value (mmmf)reflects both the increasing calorific value of the organicmatter and the decreasing moisture-holding capacity. Therationale for using this parameter seems to be that becausethe calorific value of moist coals depends on two differentproperties, it will be a better measure of the coal rank.Pearson (1985) showed that a coal of the same rank(measured by vitrinite reflectance) could be classified in onegroup in the ASTM classification system on the basis ofcalorific value and natural bed moisture, but in another groupwhen the coal has a slightly lower moisture content. Theproblem is that natural bed moisture of lignites can vary overextremely wide limits. Snow (1983) suggests that toovercome this problem, coals should be partially dried to auniform degree before the calorific value is determined. Infact, the ASTM standard methods determine the calorificvalue on air-dried coals.

Calorific value shows the most marked change for the lowerrank coals (see Figure 2e), where it is generally considered toprovide a good indication of the rank (Falcon, 1978a;Teichmuller and Teichmiiller, 1982). Calorific value passesthrough a maximum because hydrogen contributes more heatto combustion than carbon.

Various formulae for predicting the calorific value of coalfrom their ultimate analysis have been developed. Some ofthese formulae are reviewed by Selvig and Gibson (1945),Mason and Gandhi (1980) and Raask (1985). More recentformulae include one by Neavel and others (1986), whichuses carbon, hydrogen, oxygen, sulphur and ash (all on aweight %, dry basis). Given and others (1986) have revisedthe Mott and Spooner equation to include a term relatedexplicitly to the enthalpy of decomposition. The accuracy ofthe prediction of calorific value from these various equationsvaries for different coals.

2.8 MoistureThe moisture content of coal is of commercial interest asmoisture detracts from its value, for example, by lowering itscalorific value. Moisture is often used as a rank parameterfor the lower rank coals. Generally, it decreases withincreasing coal rank, largely as a result of decreasingporosity (Teichmuller and Teichmuller, 1982).

Moisture in coal can be determined as the equilibriummoisture, that is, the moisture content of coal that has beenleft for a time in an atmosphere of constant humidity andtemperature. Two different equilibrium moisture contents areroutinely measured on coal:

- air-dried, which is the moisture content when the samplehas reached equilibrium with the laboratory atmosphere.It can vary from one laboratory to another.

- moisture-holding capacity, that is, the equilibrium moisturecontent in an atmosphere at 30°C and 96%-97% relativehumidity. The method is specified in various standards,such as AS 1038: Part 17 (higher rank coals), AS 2434:Part 3 (lower rank coals), ASTM D1412, BS 1016:Part 21 and ISO 1018 (hard coals).

Chemical composition, properties and tests

In high rank coals, the moisture-holding capacity isconsidered to approximate to the natural bed moisture (thatis, the natural moisture content of the coal in situ, free fromsurface moisture). However, there is evidence that for thelower rank coals, the moisture-holding capacity can besignificantly lower than the natural bed moisture (Ode andGibson, 1960; Perry and others, 1984).

Bed moisture is used to classify coals in the ASTMclassification (ASTM D388). It is difficult to measure sincethe moisture content alters as soon as coal is removed fromthe seam unless careful precautions are taken (Gray, 1983).The ASTM standard discusses in some detail how thesamples should be chosen and measured. Moisture isdetermined in the proximate analysis of coal (ASTM D3173)or, if the moisture is questionable, after the sample has beenbrought into equilibrium (ASTM D1412). The newAustralian classification also uses bed moisture (determinedby a two stage drying process, AS 2434: Part 1) to classifythe lower rank coals, as these coals are generally useddirectly from the mine.

In the 'International classification for brown coal andlignites' (ISO 2950), total moisture (that is, the surface andinherent moisture) is used as the rank parameter. Surfacemoisture is the extraneous water held as films on the surfaceof the coal. The moisture present in other forms, includingthe water held in the capillaries or pores of the coal, isregarded as the inherent moisture. Total moisture can bedetermined by the method specified in ISO 1015, where thecoal is heated under reflux with toluene or xylene, and themass of water collected as a condensate is determined. Othermethods for the higher and/or lower rank coals are specifiedin, for example, AS 1038: Part 1, AS 2434: Part 1, ASTMD33O2, BS 1016: Part 1 and ISO 589.

During the proximate analysis of coal, the inherent moistureis determined on air-dried samples. It is required forcalculating fixed carbon (for the ASTM classification) andfor calculating analytical results to other bases. Variousmethods for its determination are specified in, for example,AS 1038: Part 3, ASTM D3173, BS 1016: Part 3, ISO 331and ISO 348.

Both the total and proximate inherent moisture contents ofcoal do not in fact, include the water of decomposition (thatis, water chemically combined in some of the organicconstituents) or the mineral moisture (water of hydrationassociated with the minerals). Generally, total and inherentmoisture are determined at temperatures well below thoseneeded to remove them (Hessley and others, 1986; Ward,1984b).

There is no simple and reliable method of determining thewater of hydration of mineral matter (Hessley and others,1986). In mmf calculations, an average value for the waterof hydration is assumed and this can lead to errors (discussedin Section 2.1). Thus, a coal with a high mineral contentcould give a rank measure different from other rankparameters.

Gray (1983) reviews and compares some of the methods

specified in various national and international standards thatare used today for determining the moisture content of coal.Unfortunately, the different techniques can give differentresults and are not always suitable for coals of all ranks(Gluskoter and others, 1981; Gray, 1983; Ward, 1984b). Thedetermination of moisture content of lower rank coals isespecially sensitive to oxidation and so great care is neededduring sample preparation and analysis. The techniquespecified in the classification should be followed or, if nomethod is specified, then the standard followed should bestated. Coals being classified under one classification schemeshould, of course, have all been analysed using the samemethod.

Moisture content reflects the petrographic composition of thecoal (Hessley and others, 1986; Neavel, 1981) and therefore,petrographically heterogeneous coals may not be placed inthe same order of rank as petrographically homogeneouscoals. Moisture content is generally considered to provide areasonable measure of the physical rank of coal up to thehigh volatile bituminous A stage (see Figure 2d), as moisturefalls fairly rapidly (McCartney and Teichmiiller, 1972).Changes in physical rank may be of more significance in theutilisation of brown coals than changes in the chemical rank(Higgins, 1987). For example, the effect on net calorificvalue (moist) of a 10% drop in moisture may have moresignificance in terms of utilisation than a small increase incarbon or another chemical rank parameter. One mightexpect coals with similar chemical structures to have similarproperties and behaviour. Close similarities have been foundin the organic chemical structures of Tertiary Australianbrown coals (lignites) and low rank New Zealandsubbituminous coals, when studied by I3C nmr spectroscopy(Newman and Davenport, 1986). However, these coalsappear in different classification groups under the ASTMclassification system because of their differing moisturecontent. Moisture is generally considered to be an additiveparameter.

2.9 Inorganic constituentsInorganic elements occur in coal in three principle forms(Neavel, 1981):

- dissolved in the pore water (for example, sodiumchloride);

- combined chemically with the organic materials (eitherion-exchanged or as metallo-organics);

- as discrete mineral particles.

The inorganic elements chemically combined with theorganic material are known as the intrinsic or inherentinorganic matter. However, some workers restrict the termto only those inorganic constituents that were present in thecoal-forming plants, that is, any inorganic elements whichhave become chemically or colloidally combined with thecoal after the death of the parent plants are excluded(Francis, 1954). Predominantly though, inorganic elementsoccur as discrete particles of mineral matter, the extrinsic oradventitious minerals. These were formed after the death ofthe coal-forming plants and can be of two forms (Francis,1954; Mackowsky, 1982a):

Chemical composition, properties and tests

environmental impact of coal utilisation. This is the subjectof a separate IEA Coal Research report (Smith, 1987).

For the above reasons, the mineral matter content isimportant in coal classification schemes and when theparameters used are calculated to a mmf or ash-free basis(see Section 2.1). It is generally considered to be additive.

The terms ash and inorganic (mineral) matter are often usedinterchangeably in the literature. Strictly speaking, this is notcorrect, as coal does not 'contain' ash. As discussed, ash isthe residue left after combustion and it differs both in amountand nature from the inorganic (mineral) matter in coal.

The ash yield has been used as a classification parameter. Itis generally determined by burning coal under specifiedconditions (for example, AS 1038: Part 3; ASTM D3174; BS1016: Part 3; ISO 1171), and is often referred to as the 'hightemperature ash'. The temperature chosen minimises loss ofvolatile constituents, but does not entirely succeed (Gray,1983). Also, some sulphur can be retained as sulphate in theash (Gluskoter and others, 1981; Gray, 1983).

Mineral matter can be determined directly by a number ofinstrumental techniques, including X-ray diffraction andFourier transform infrared spectroscopy. Gluskoter andothers (1981) briefly review some of these techniques.However, standard methods (for example, AS 1038: Part 22)use a low temperature ash (LTA) method. During theashing, some oxidation of the mineral matter will occur; tokeep this to a minimum and to reduce the amount of sulphurretained in the ash, the specified conditions must be closelyfollowed. The LTA method is also probably best confined tothe higher rank coals (Given and Yarzab, 1978). Automatedscanning microscopy in conjunction with energy dispersiveX-ray analysis (Huggins and others, 1980) does not requireLTA and thus oxidation is avoided. The results do notdepend on crystal structure, so the method may be moresuitable for a quantitative assessment of clay minerals thanX-ray diffraction.

— syngenetic minerals, which were deposited by water orwind, or by in situ precipitation as the coal deposits wereforming (during diagenesis). They are generallyintimately intergrown with the coal, and are difficult toremove;

- epigenetic minerals were deposited during the secondphase of the coalification process, after consolidation ofthe coal, by ascending or descending solution in cracks,fissures or cavities, or by alteration of previouslydeposited minerals. These minerals tend to be coarselyintergrown and can be separated from the coal byphysical methods, such as flotation.

The minerals found in coal are variable in both chemicalcomposition and physical properties. The major groupsinclude the clays, carbonates, iron sulphides and silicas.Other groups, which occur more rarely, include the oxides,hydroxides, other sulphides, chlorides, phosphates, othersilicates and sulphates. Associations of some minerals withmacerals can be classified in the microlithotype group,carbominerite. Mackowsky (1982a) provides a fairlydetailed review of the minerals and trace elements occurringin coal, and Gluskoter and others (1981) list some otherreferences.

Knowledge of the minerals and their distribution, and of thetrace elements in coal is of widespread interest. Forexample, the washability of coal is affected by the degree ofintergrowth of mineral matter and coal. Identification of themineral matter and controlled crushing prior to washing canresult in the removal of a high proportion of epigeneticminerals (Falcon, 1977).

Mineral matter content and properties are important incombustion, as they affect the heating value of coal, ashfusion point and the tendency for deposits and corrosion tooccur on surfaces of heating chambers {see Section 7.2.3).They are also of interest in coal liquefaction and coking(Sections 8.2.7 and 9.2.8). Knowledge of the minerals andtrace elements in coal can be important in assessing the

3 Mechanical and physical properties and tests

3.1 Crucible swelling numberThe crucible swelling number (CSN) is used in thecombustion industry (see Section 7.3.1) and is one of themost commonly used tests in the coking industry todetermine whether a coal will coke (see Section 9.3.1). Thecrucible swelling number, also called the free swelling index(FSI), measures the degree of free swelling of coal.

This relatively simple and quick test involves rapidlyheating a 1 g sample of finely ground coal in a crucibleof specified dimensions to about 820°C. The profile of thecoke button obtained is classified by comparison with a setof standard profiles and is therefore, to some extent,subjective (Falcon, 1978a). Automation, however, isremoving some of the subjectivity (Habermehl and others,1981). To obtain uniform results, the requisite standard (forexample, AS 1038: Part 12.1; ASTM D370; BS 1016: Part12; ISO 501) must be followed exactly, as different heatingrates and particle size distribution in the coal sample willgive different results (Hessley and others, 1986; Ward,1984b).

Coals are generally considered to have coking properties iftheir CSN is over four, whereas a CSN of seven or moreindicates a high quality coking coal (Blackmore, 1985).However, some coals (for example, some inertinite-richGondwanan and western Canadian Cretaceous coals) producebetter coke than is suggested by their CSN number. This isbecause the results of the test reflect variations in other coalcharacteristics. These include rank and petrographiccomposition (Alpern, 1981; Habermehl and others, 1981;Pearson, 1985), whether the coal is oxidised or weathered(Hessley and others, 1986; Pearson, 1985; Rees, 1966), andthe mineral (or ash) content (Berkowitz, 1979, 1985;Pearson, 1985). However, Moxon and others (1986) foundthat the CSN was relatively insensitive to changes in ashlevels below about 15%. Therefore, the CSN should not beused on its own for evaluating the swelling or coking

properties of coal; additional parameters would be required ina classification system that included the CSN.

The CSN cannot predict the swelling behaviour of coals atelevated pressures, which can be important for the optimumutilisation of coal in gasification processes (Beyer, 1982;Khan and Jenkins, 1986). Several coals are frequentlyblended to form the coke oven feed. The swelling propertiesof the final mixture do not depend simply on the relativeproportions of each component (Cudmore, 1984); that is,CSN is not additive. Neavel and others (1986) have derivedan equation for calculating the CSN from the oxygen contentand factors derived from the petrographic composition andmineral matter of the coal. However, the equation isprobably valid for only the vitrinite-rich coals on which itwas derived.

3.2 Roga indexThe Roga index is employed in the coking industry as itassesses the coking properties of coal. It is determined bycarbonising a mixture of known masses of the crushed coalsample and a standard anthracite (of specified properties) in acrucible at about 850°C. The resulting coke is examined in aRoga drum for its resistance to abrasion and from the resultsthe Roga index is calculated. For uniform results therequisite standard (ISO 335) must be followed. Adisadvantage of the test, particularly as regards universal use,is the requirement for a standard quality of the inertadmixture, anthracite.

The Roga index reflects variations in coal characteristicsincluding rank, petrographic composition, whether thesample is oxidised (weathered) (Falcon, 1978a) or locallyheat-altered (Smith and others, 1983) and mineral matter(ash) content (ECE, 1956). This implies that the Roga indexshould not be used in isolation for the evaluation of thecoking properties of coal, especially as some coals producebetter coke than their Roga index indicates. Unlike the CSN,

Mechanical and physical properties and tests

the Roga index is largely pressure independent (Beyer, 1984)and therefore could be used, in some cases, to predict thebehaviour of coal in processes that are carried out underpressure. The Roga indices of coals in a blend are also, tosome extent, additive (Smith and others, 1983).

3.3 Gray-King coke typeThe Gray-King coke type test is one of the most widely usedtests in the coking industry for assessing the cokingproperties of coal. In this test, the coke residue from thecarbonisation of finely ground coal in a sealed cylindricalretort tube at 600°C is classified by comparison with a seriesof standard coke types, grading from A to G. The test istherefore, to some extent, subjective. For strongly swellingcoals (coke type G1-G9), a determination is made of theproportion of electrode carbon which has to be blended withthe coal in order to obtain, on carbonisation, a strong hardcoke of the same volume as the original coal and electrodecarbon mixture; this is indicated by the subscript after theletter G. The test is specified in various standards (forexample, AS 1038: Part 12.2; BS 1016: Part 12; ISO 502)and these should be followed in order to obtain reproducibleresults.

This is a relatively time-consuming test (Habermehl andothers, 1981; Speight, 1983). Like the previous two tests, theresults reflect variations in the coal's characteristics includingthe rank and petrographic composition (Habermehl andothers, 1981; Mackowsky, 1982c), whether the coal has beenoxidised or weathered (Speight, 1983) and the mineral matter(ash) content (Moxon and others, 1986). It is probably notadditive for coal blending. Again, some coals produce bettercokes than their poor Gray-King coke number would leadone to expect (Handley and others, 1984; Pearson, 1985).Therefore, additional parameters would be desirable in aclassification system that includes the Gray-King cokenumber, especially in the evaluation of different coal types.

3.4 Audibert-Arnu dilatometerThe Audibert-Arnu dilatometer test is employed in thecoking industry. It measures the swelling properties of coals.In the test, a pencil of powdered coal is inserted in a definednarrow steel retort, topped by a steel piston and the wholeheated at a specified heating rate until the material haspassed through the plastic range and solidified (usually about450 to 500°C). A graphic plot of changes in the length of thepencil (monitored by the piston) as a function of thetemperature is obtained and the dilatation (%) calculated. If,after the initial contraction of the coal, the piston does notreturn to its original level, a negative dilatation is reported.The requisite standard (for example, AS 1038: Part 12.3; BS1016: Part 12; ISO 349) should be followed in order toobtain uniform results. The method is relativelytime-consuming (Habermehl and others, 1981). Instead ofthe Audibert-Arnu test, the Ruhr dilatometer, as specified inDIN 51739, is used in some countries. The principles are thesame, but there is some variation in equipment andprocedures.

The results of the dilatation test reflect variations in other

coal characteristics including rank and petrographiccomposition (Habermehl and others, 1981; Marshall, 1976;Pearson, 1985), mineral matter content (Marshall, 1976,Moxon and others, 1986) and whether the sample is oxidisedor weathered (Berkowitz, 1985; Marshall, 1976; Pearson,1985). It is probably not additive for coal blending. Somecoals produce better cokes than their low dilatation wouldlead one to expect, for example, some of the westernCanadian Cretaceous coals (Pearson, 1985; Price and others,1985). It has been suggested that for these high inertinitecoals, the particle size specified in the dilatation test is toofine. Fine grinding is thought to destroy the naturalintergrowth of reactive and inert constituents. Dilatometertesting of such coals using a coarse particle size and a higherpencil density can give a higher dilatation (Cudmore andHandley, 1987). Additional parameters would therefore bedesirable in a classification system that includes the dilatation.

The dilatation is also influenced by pressure (Beyer, 1982;Green and others, 1985; Khan and Jenkins, 1986; Tromp andothers, 1986) and therefore, will not accurately reflect thebehaviour of coal in, for example, gasification processes thatare carried out under pressure. Also, the behaviour of a coalin a dilatometer is not the same as its actual behaviour in acoke oven (ECE, 1982c).

3.5 Gieseler plastometerThe Gieseler plastometer test is used in the coking industry.It measures the fluidity or plastic characteristics of a coal asit is heated. The crushed coal sample is charged into a smallsteel retort containing a shaft with rabble arms (stirrer) andheated at a constant rate. A constant torque is applied to theshaft and the number of revolutions per minute is recorded.The main parameters recorded are the initial softeningtemperature, temperature of maximum fluidity,resolidification temperature, maximum fluidity (in dialdivisions per minute) and the plastic range. For uniformresults the relevant standard should be followed (forexample, AS 2137; ASTM D2639).

The results of the test reflect other coal characteristics,including rank and petrographic composition (Pearson, 1985;Ward, 1984b) and mineral matter content (Moxon and others,1986). Thus some coals, for example western CanadianCretaceous coals (Pearson, 1985), produce better coke than isindicated by their low maximum fluidity. More so than mostother properties, the degree of maximum fluidity is sensitiveto oxidation of the coal (Ward, 1984b). Therefore, care mustbe taken during storage of samples.

One of the principle uses of the fluidity data is in designingcoking coal blends. However, the maximum fluidity of thefinal blend is not additive, and calculated results can often bemisleading (Cudmore, 1984; Rees, 1966). The test may notbe reproducible from one instrument to another (Gluskoterand others, 1981). The fluidity is also influenced by pressure(Khan and Jenkins, 1986) and therefore, the behaviour ofcoal in processes carried out under pressure may not beaccurately predicted. The Gieseler test may also beinadequate for predicting the behaviour of coal in somegasification and coking processes where much higher heating

Mechanical and physical properties and tests

rates than those used in the test are employed (Habermehland others, 1981).

3.6 Ash fusion temperaturesAsh fusion temperatures (AFT) are used in combustionapplications to predict the slagging and fouling propensitiesof coal. The test provides relative information on a coalwhich is compared with similar data on coals of knownbehaviour. The empirical method for determining AFTsinvolves the gradual heating of a cone of ash at a controlledrate and in a controlled atmosphere. The ash is heated underreducing and/or oxidising conditions. Four temperatures areusually recorded, the initial deformation temperature,softening temperature, hemisphere temperature and flow orfluid temperature. However, not all these temperatures arespecified in the various standards (for example, AS 1038:Part 15; ASTM D1857; BS 1016: Part 15). Thesetemperatures are regarded as the critical design temperaturesfor a boiler. Under reducing conditions, AFTs are lower dueto the greater fluxing action (basicity) of the ferrous ioncompared to the ferric ion present under oxidising conditions.The procedure uses ash obtained under the same conditionsas the standard ashing procedure for proximate analysis.

Although AFT tests are widely used, they do not alwaysaccurately predict the performance of a coal ash. Themethod was developed when stoker-firing was thepredominant coal firing technique, and its significance andusefulness to other combustion processes, particularlypulverised coal firing application, have been questioned. Thetest uses laboratory-made ash, that is, the test is based on acoal ash chemistry that is quite different from that found inoperating boilers (Blackmore, 1985; Borio and Levasseur,1986). Laboratory-prepared ash is also usually well mixedand so fusibility problems will be underestimated becausefluxing agents in the coal itself may be irregularly distributed(Day and others, 1979).

Two ashes which have similar fusion characteristics can havemarkedly different melting and crystallisation behaviour andcould thus perform differently in a boiler (Blackmore, 1985;IEA Coal Industry Advisory Board, 1985). Generally, a lowAFT would lead one to expect possible slagging and fouling;but there are a few cases where ash with a high AFT hasresulted in significant slagging. In these cases a low ironcontent in association with silica was present in the coal(Borio and Levasseur, 1986). Wall and others (1985)consider that AFT measurements are most applicable to theformation of highly sintered or slagged deposits from iron- orcalcium-rich coals, but that even these are subject tolimitations.

AFT measurements are subjective and comparative tests haveshown poor reproducibility, especially for the initialdeformation temperature (Wall and others, 1985). The test isnot of sufficient accuracy, as the tolerance allowed between

laboratories in some national standards can make asignificant difference in the design of furnaces (Sanyal andCumming, 1985). Gray (1987a, 1987b) provides a briefcritique of the standard procedures. AFTs can be predictedfrom the ash composition (Gray, 1987b). Although AFTmeasurements can be carried out on blends of coal (Lee andWhaley, 1983), the AFTs of the blend cannot be predictedfrom the AFTs of the component coals; that is, AFT is notadditive. The IEA Coal Industry Advisory Board (1985)consider that AFT data can be misleading and that 'using ashfusion temperatures alone to predict coal fouling andslagging tendencies can be inconclusive at best'.

3.7 Hardgrove grindability indexThe Hardgrove grindability index (HGI) is widely employedin the combustion industry. It provides a measure of therelative grindability or ease of pulverisation of a coal incomparison with coals used as a standard. Generally, thehigher the HGI, the easier the coal is to grind. The method(which is specified in, for example, AS 1038: Part 20; ASTMD409; BS 1016: Part 20; ISO 5074) involves grinding 50 gof a narrow size fraction of dried coal in a standardised balland race mill for 60 revolutions, at a specified speed. Theamount of recovered material passing through the 600 jumsieve after the test is related to a series of standard coals withdesignated HGIs.

The HGI has been correlated with mill capacity for Europeancoals (Day and others, 1979) and low ash, low moisture UScoals (Wall, 1985); however, the correlation may not be validfor more petrographically heterogeneous coals (Waters,1986). The HGI reflects other coal characteristics, includingrank (Bustin and others, 1985; Juntgen, 1987a), and moistureand mineral matter (ash) contents. With increasing moisture,the index becomes less reliable (Gray, 1983; Wall, 1985;Wall and others, 1985) and the presence of even a smallproportion of hard minerals, such as quartz, with a particlesize greater than 100 p,m, will overestimate the HGI (Walland others, 1985). The repeatability and reproducibility ofthe test has also been questioned (Gray, 1983).

Grinding a vitrinite-rich coal can lead to a concentration ofvitrinite in the finer fraction (Hough and Sanyal, 1987;Sanyal and Cumming, 1985); consequently the finer fractionsof milled coal will exhibit greater combustion reactivity (seeSection 7.4). During the grinding of high inertinite, low rankbituminous coals, Jones and others (1985) found that thelargest particles (>100 |im) were enriched in vitrinite, whileinertinite was concentrated in the smaller particles, withconsequent effect on combustion.

Thus, coals of similar HGI may not, in practice, performidentically. The HGI, in general, is not additive (Sligar,1988; Waters, 1986), although Hower (1988) found that,under controlled conditions, the HGI was additive for simpleblends of US high volatile bituminous coals.

4 Petrographic composition, properties and tests

4.1 MaceralsCoal is not a homogeneous substance but contains variousconstituents analogous to the minerals of inorganic rocks.These are called macerals and are the coalified remains ofplant tissue. The term maceral describes 'the shape and thenature of the microscopically recognisable (organic)constituents of the coal' (Stach, 1982). Therefore, it can benoted at the outset that classification by maceral compositionis on a purely morphological basis, although the origin canbe important in the classification of some macerals. Eachmaceral has a distinct set of physical, chemical andtechnological properties for a given rank. The proportion ofmacerals and their characteristics (for example, reflectance)have been found to correlate with some of the properties ofcoal that are of major industrial significance.

Three groups of macerals (suffix -inite) are recognised in thehigher rank coals (bituminous and anthracites): vitrinite,liptinite (or exinite) and inertinite. The groups aredistinguished from each other by their reflectance (theproportion of directly incident light that is reflected from aplane polished surface under specified conditions). Sincethere is an overlap of reflectance between the maceralgroups, morphology is also used for identification. The termhuminite is used instead of vitrinite in the lower rank coals(lignites and subbituminous coals). These maceral groupscan be further classified into macerals which 'differ from oneanother in morphology and structure rather than reflectance'(ICCP, 1985; Stach, 1982). The internationally recognisedmacerals are listed in Tables 1 to 4.

However, there remain areas of disagreement over thedetails of maceral classification. Neavel (1981, 1986) forexample, argues that the chemical composition ofmacerals is the important factor from a technologicalviewpoint and therefore, macerals should be differentiatedonly if they are chemically distinctive. The morphologyand optical properties of macerals may not be as closely

related to their chemical properties as is sometimesassumed.

The low rank coals, being the less altered, exhibit a greatervariety of macerals than higher rank coals. The huminitesare regarded as the precursors of the vitrinites (see Table 1).However, Australia has introduced a standard (AS 2856:1986) that incorporates both the low rank and high rank coalsin the same system of maceral analysis. The huminitemacerals are distinguished from each other primarily by theirdegree of gelification (a process by which the humic (plant)matter passes through a soft plastic gel stage and takes on aswollen appearance (Teichmiiller, 1982)). The degree ofgelification has been shown to correlate with the performanceof some industrial processes, such as crushing and briquettingand in tar and char yields from carbonisation (Davis andothers, 1976; ICCP, 1985). As well as chemicalcomposition, the physical properties of macerals aresignificant in soft brown coals, such as in relation toporosity. For example, the presence of textinite caninfluence moisture content and milling characteristics(Higgins, 1987).

The vitrinite group of macerals (see Table 2) is generally themost abundant maceral group occurring in the higher rankcoals. The Carboniferous coals of the northern hemisphere(Laurasian) are usually rich in vitrinite. The reflectance ofvitrinite is often used as a measure of rank (see next section).Compared with the liptinites and inertinites in coals of thesame rank (isorank coals), the vitrinites have intermediatereflectance, hydrogen and carbon contents and volatile matteryields, but are richer in oxygen (Davis and others, 1976;Stach, 1982). Vitrinite is reactive chemically and, dependingon its rank, it is readily hydrogenated, easily oxidised andforms good coke. It should be noted that vitrinite containspetrographically heterogeneous materials (as do all themaceral groups) and therefore, differences in chemicalbehaviour within the group can occur (see Sections 7.4, 8.3and 9.4).

Petrographic composition, properties and tests

Table 1 Huminite macerals (in low rank coals) (Bustin and others, 1985; ICCP, 1985)

Maceral group Maceral subgroup Maceral Sources Equivalent maceralin hard coal

huminite humotelinite

humodetrinite

humocollinite

textiniteulminite

attrinite

densinite

gelinite

corpohuminite

woody tissuewoody tissue

finely comminutedhumic detritusfinely comminutedhumic detritus

colloidal humic gels

condensation productsof tannins

telinite

vitrodetrinite

collinite

Table 2 Vitrinite macerals (in hard coals) (Bustin andothers, 1985; ICCP, 1985)

Maceral Maceralgroup

Source Group properties

vitrinite telinite

collinite

woody tissues -leaves, bark,branches, roots etc.

humic gels

vitrodetrinite degraded fragments(of other vitrinitemacerals)

intermediate grey inreflected light(intermediatereflectivity)oxygen-richintermediate carbonand hydrogencontentsintermediate volatilematter yieldchemically reactive

Table 3 Liptinite macerals (in coals of all rank) (Bustinand others, 1985; ICCP, 1963, 1975)

Maceral Maceralgroup

Source Group properties

liptinite sporinite(or exinite)

cutinite

resinite

alginite

suberinite

spores and pollen

cuticles

resins, waxes

algae

bark tissues (cork)

dark grey in reflectedlight (lowestreflectivity)hydrogen-richhigh volatilematter yieldhigh in aliphaticschemically reactive

liptodetrinite degradation products ofliptinite macerals

The liptinite group of macerals (see Table 3) is usually aminor component of bituminous coal, although some coalsare enriched in liptinite, for example, many of the RockyMountain coals from British Columbia and Nova Scotia(Canada) (Pearson, 1985) and some sapropelic coals.Compared with the vitrinite and inertinite groups in isorankcoals, liptinite has the highest hydrogen content, highestvolatile matter yield, lowest reflectance and contains more

aliphatic groups (Stach, 1982). Depending on their rank,liptinites are highly reactive in chemical processes and,during carbonisation, liptinite enhances the fluidity of coal(Pearson, 1985). On heating, they yield high proportions oftar and bitumen, particularly in the subbituminous and lowrank bituminous coals (Neavel, 1981). They are easilyhydrogenated and so a coal rich in liptinite would bepreferred for hydrogenation.

The inertinite group of macerals (see Table 4) has a variableabundance in coal. The Permian coals of the southernhemisphere (Gondwanan) characteristically have a higherinertinite content compared with the Laurasian coals(although there are exceptions). The inertinites have thehighest reflectance, highest carbon and lowest hydrogencontents, the lowest volatile matter yield and contain morearomatic groups (relative to the vitrinite and liptinite groupsin isorank coals) (Damberger and others, 1984; Stach, 1982).Inertinites are traditionally regarded as being chemically inert(that is, compared with the other two groups of macerals).However, some of the inertinites, depending on their rank,have been shown to be chemically reactive, for example,micrinite (Stach, 1982) and semifusinite.

Table 4 Inertinite macerals (in coals of all rank) (Bustinand others, 1985; ICCP, 1963, 1975)

Maceralgroup

Maceral Source Group properties

inertinite fusinite woody tissue

semifusinite woody tissue

macrinite uncertain - probablyformed throughoxidation ofgelified plantmaterials

micrinite secondary maceral

sclerotinite fungal remains

inertodetrinite degraded fragments ofinertinite macerals

light grey to whitein reflected light

(highest reflectivity)carbon-richlow hydrogen contentlow volatile matteryieldrich in aromaticschemically inert(with exceptions, forexample semifusinite)

Petrographic composition, properties and tests

In Australian bituminous coals, semifusinite has been shownto be chemically reactive in both coking (Diessel, 1982,1983; Roberts, 1982) and coal liquefaction (Heng andShibaoka, 1983; Shibaoka and others, 1983). Usingpetrographic analyses of coal to predict the strength andreactivity of the resultant coke, one-third of the semifusiniteis conventionally treated as being reactive in the northernhemisphere Carboniferous coals. But use of the samemethods does not lead to useful predictions with mostAustralian Gondwanan coals (Diessel, 1983; Roberts, 1982)or with some western Canadian Cretaceous coals (Pearson,1985); both these coals produce better cokes than expectedfrom the results of empirical tests (CSN, Gieseler etc).Given (1984) suggests that the semifusinite in theseAustralian and western Canadian coals is different from thesemifusinite in North American and European coals.Teichmuller (1982) and Chandra and Taylor (1982) havesuggested that part of the fusinite and semifusinite maceralsin Gondwanan coals were formed by some kind ofbiochemical oxidation rather than by pyrolysis in forest fires.Semifusinite in lignite is also sufficiently reactive that it canbe converted to liquids in hydrogen donor processes (Neavel,1981).

As well as the Laurasian and Gondwanan coals, other groupsof coals of similar rank can show distinctive differences intheir behaviour. Petrographic studies of New Zealandbituminous and subbituminous Tertiary coals have indicatedsome distinctive differences between these coals andMesozoic and Palaeozoic coals of the same rank foundelsewhere (Lavill, 1988).

Although methods for maceral analysis of coals by opticalmicroscopy have been standardised (for example, AS 2856,ISO 7404/3), the analysis remains subjective, the resultsdepending on the experience of the petrographer.Comparative tests have produced widely scattered results(Anderson and others, 1985; Eidel'man, 1981), indicating thepoor reproducibility of the analysis. The method, includingsample preparation, is time-consuming and whether maceralanalysis will reach the level of precision of ultimate orproximate coal analysis is questionable (Alpern, 1987). Untilmaceral analysis has been successfully automated, most ofthese problems will remain. Provided the macerals can becorrectly identified, maceral composition is probably additivefor blending coals.

A comprehensive review of the features that characterise thevarious members of the maceral groups and standard rulesfor their microscopic identification can be found in theInternational Handbook of Coal Petrography (ICCP, 1963,1975, 1985). Stach (1982) gives an overview of the maceralsand their physical and chemical properties and bothTeichmuller (1982) and Given (1984) provide a gooddescription of the origin of macerals.

4.2 Vitrinite reflectanceVitrinite reflectance is related to the aromaticity of thevitrinite in coal (Davis, 1984; Teichmuller and Teichmuller,1982) and generally increases with increasing coal rank. It iswidely used as an index of coal rank.

The reflectance of vitrinite is the proportion of directlyincident light, usually expressed as a percentage, that isreflected from a plane polished surface, usually underoil-immersion, and under specified conditions ofillumination. Various standards (for example, AS 2486;ASTM D2798; BS 6127: Part 5; ISO 7404/5) specify themethod and the ICCP (1985) and Mackowsky (1982b)describe the equipment and procedures.

Different results are observed when using polarised andnon-polarised light. Vitrinite reflectance displays opticalanisotropy, that is, it acts as if it were a uniaxial negativecrystalline substance (Davis, 1984; Neavel, 1981). Underplane polarised light the reflectance value will vary froma minimum to a maximum during rotation of the vitrinitelayer, with the two maxima being separated by 180 degrees.However, some vitrinites act as biaxial substances andtherefore do not display a maximum reflectance value(Davis, 1978, 1984). Standard techniques generally involvedetermining the reflectance of at least 100 particles andreporting results as an arithmetic mean, the mean maximumreflectance (Rmax). The new Australian classification(AS 2096: 1987) includes this as the rank parameter. TheICCP (1985) recommends as the measure of rank, themean maximum reflectance of telecollinite (a vitrinitesubmaceral).

If vitrinite reflectance is measured under non-polarised light,the reflections from all directions on the vitrinite surface willbe integrated to give a random reflectance (Rrand) or meanreflectance (Rm) (Davis, 1978, 1984). A statistical meanof the readings is commonly reported, the mean randomreflectance (Rrand or Rm). The new international codificationof higher rank coals is using this measure as the rankparameter. The mean random reflectance will always belower than the mean maximum reflectance of vitrinite (ICCP,1985), except for basically isotropic coals (very low ranks)where they will be effectively equal.

Vitrinite reflectance measures a rank-sensitive property ononly one petrographic constituent and so is independent ofvarying maceral composition. Therefore, similar results willbe obtained on the petrographically dissimilar Gondwananand Laurasian coals (Chandra and Taylor, 1982). Vitrinitereflectance has been correlated with other rank parameterssuch as volatile matter (ICCP, 1963, 1985; McCartney andTeichmuller, 1982; Newman, 1985), carbon and hydrogencontents (McCartney and Teichmuller, 1982) and calorificvalue (Neavel, 1981). However, these correlations can varyfrom coalfield to coalfield (Jones and others, 1984), andconsequently the prediction of one property from another islikely to be imprecise.

Since it is affected only in a minor way by low temperatureoxidation, vitrinite reflectance can be used for assessing therank of weathered coals (Davis, 1978), although Gray(1987a) suggests that weathering might be expected to reducethe reflectance. When the temperature of oxidation is high(more than about 150°C) or there is some heat effect duringoxidation, vitrinite reflectance will increase, and so isinapplicable as a rank parameter for these coals (Chandra,1982).

Petrographic composition, properties and tests

Although the reflectance of vitrinite is controlledpredominantly by the stage of regional metamorphism,several other phenomena influence it. These include bothpalaeoenvironmental influences and the subsequentcoalification history. For example, some Carboniferousvitrinites from the United Kingdom had lower reflectancesthan other Carboniferous vitrinites of equivalent carboncontents, which was attributed to differences in their geologichistory (Jones and others, 1984). For the Pike River andBuller coals of New Zealand, vitrinite reflectance (Rmax) wasfound to be an unreliable rank parameter compared withvolatile matter (Newman, 1985; Newman and Newman,1982). The reflectance varied even within the same ply of acoal seam as a consequence of type variation, which wasattributed to palaeoenvironmental factors during the peatswamp deposition.

Neavel (1986) and Neavel and others (1981) have shownthat vitrinites with different elemental composition cancoincidentally have the same reflectance, that is, vitrinitereflectance is influenced by the chemical composition of thecoal. Therefore, coals with the same vitrinite reflectance canshow differences in their chemical behaviour (as observed,for example, by Kosina and Heppner, 1984).

The macerals associated with vitrinite can also influence itsreflectance. In the presence of strongly fluorescing liptinites,the reflectance of vitrinite is significantly lowered (Huttonand Cook, 1980; Kalkreuth, 1982). In these cases, vitrinitereflectance may not be an accurate indicator of rank.

Vitrinite reflectance is a time-consuming, subjective method,needing trained personnel (Eidel'man, 1981) and can beexpensive with the high cost of the instruments.Comparative tests organised by the ICCP have shown greatvariance in the reflectance values obtained, even thoughcarried out by experienced petrographers (Anderson andothers, 1985; Eidel'man, 1981). Automatic microscopicmethods are being developed which will eliminate some ofthese problems. Automation of random vitrinite reflectance(for example, Gray and Rhoades, 1984; Riepe and Steller,1984) has been successful, one reason why mean randomreflectance is preferred in the new international codification.Random reflectance is also unaffected by coals which displaybiaxial anisotropy; these coals will not display a maximumreflectance value (Davis, 1978, 1984). Correlations betweenmean and maximum reflectance have been found (Davis,1984). Vitrinite reflectance is probably not additive. Ablend of 50% each of a 0.5% Rm and a 1.0% Rm coal willnot produce a reflectance of 0.75%, but only two peaks, oneat 0.5% and one at 1.0%. One of the main uses of vitrinitereflectance as a measure of rank is that it can identify a blendof coals (see next section).

The use of vitrinite reflectance as a rank parameter is bestconfined to coals higher in rank than lignites (McCartney andTeichmiiller, 1972; Neavel, 1981), since metamorphicchanges exerted little influence on the reflectance of thehuminite (vitrinite) macerals in the lower rank coals (seeFigure 2e). However, vitrinite reflectance has been usedwith some success in the lower rank coals. For example,Marchioni (1985) found that the vitrinite reflectance

technique provided a reliable rank parameter for the ligniteand subbituminous coals in the Hat Creek (British Columbia)deposit, when the reflectance measurements were restrictedto the humotelenite subgroup. The ICCP recommends thatthe ulminite maceral should be used for reflectancemeasurements in the lower rank coals. However, parametersindicating the physical rank of soft brown coals may bepreferable (in a classification system) to vitrinite reflectanceas changes in the physical rank may be of more significancein the utilisation of these coals (Higgins, 1987).

4.3 ReflectogramsReflectograms can be constructed on the whole coal or oneach maceral group, but are more common for vitrinite. Thefollowing discussion will concentrate on vitrinitereflectograms as this is the parameter proposed in the newinternational codification (see Section 6.5.2).

A reflectogram shows the reflectance distribution of the coalsample in the form of a frequency histogram (see Figure 3).The random or maximum vitrinite reflectance of the coal ismeasured using standard techniques (see previous section)and the results reported as numbers of measurements inintervals of 0.05% reflectance (half V-step or half V-type)or intervals of 0.1 % reflectance (V-step or V-type). Forexample, V-step 8 covers the reflectance range 0.80 to0.89%; the equivalent half-steps cover the ranges 0.80 to0.84% and 0.85 to 0.89%.

<D

§20-

IDCD

coal blend: Rma, =1.245%

7 9' 11 '13' 15 17 '19'V-typeVitrinite

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 reflectance, %

Figure 3 Reflectogram of blend of high, medium and lowvolatile bituminous coals (Davis, 1984)

The new international codification uses the randomreflectance of vitrinite in the reflectogram since randomreflectance has been fairly successfully automated, forexample, with the use of image analysis (Riepe and Steller,1984). Automation has reduced the subjectivity, cost andduration of the test, but sample preparation can still betime-consuming and measurement times remain relativelylong compared with some other analytical techniques, suchas Fourier transform infrared spectroscopy (Fredericks andothers, 1987).

Reflectograms are used for analysing and monitoring thequality of coal blends, as they provide a means ofdistinguishing between single seam coals and blends of coalsof differing rank. Reflectance measurements can determine

Petrographic composition, properties and tests

the rank of the component coals, unlike traditional chemicalanalyses. These latter tests give only values representing theaverage of the mixture (Ng and Cudmore, 1987). However,reflectograms can be difficult to interpret, particularly ifcomponents of the blend are of similar rank (ECE, 1982a).They cannot identify blends unambiguously since bimodaldistribution can occur within a single coal seam (ECE, 1986).Fredericks and others (1987) suggest that the accuracy of the

determination is acceptable for only simple blends of coalswith widely differing ranks. Like vitrinite reflectance, thereflectogram is probably best confined to coals higher in rankthan lignites (see previous section) and, since it cannotdistinguish between types of anthracite, to coals of mediumrank. The reflectogram of single coals is possibly notadditive, but there appears to be little experimental evidenceto support this conclusion.

5 Potential analytical techniques

New analytical techniques have been developed over the pastcouple of decades or so to characterise coal and itsbehaviour. Parameters derived from these techniques couldpossibly be used in the classification of coal. Four of theseanalytical techniques will be discussed.

5.1 Derivative thermogravimetricanalysis

Various thermoanalysis techniques can be used tocharacterise the behaviour of coal. For example, differentialscanning calorimetry (DSC) in combination withthermogravimetry has been applied to coal combustion,pyrolysis (for example, Tromp, 1986) and liquefaction (forexample, Linares-Solano and others, 1987). Derivativethermogravimetric analysis has been chosen to illustrate theuse of thermoanalytical techniques.

A 'fingerprint' of the complete combustion process of coalcan be obtained in the laboratory using derivative (ordifferential) thermogravimetric (DTG) analysis. Thetechnique produces a burning profile curve which provides arelative evaluation of the combustion characteristics of coal(see Section 7.5.1). The test involves heating a smallquantity of powdered coal at a constant rate (generally about15°C/min) in an atmosphere of flowing air. A graphical plot(the burning profile curve or combustion profile) is producedof the rate of weight loss with time as a function oftemperature. If nitrogen is used instead of the flowing air,the profile obtained is known as the volatile release profile.

The assessment of the burning profile involves recordingseveral characteristic temperatures {see Figure 4). The DTGcurve for lignite shows two peaks, the first one beingdominated by the evolution of volatile species due topyrolysis. The order of reactivity of coal is assessedprimarily on the peak temperature (the temperature of themaximum rate of weight loss); the higher this temperature

the less reactive the coal. Coals with greater weight lossrates at lower temperatures are easier to ignite and burn.Profiles which extend into very high temperature rangesindicate slow burning coals for which longer combustiontimes are required for complete combustion. The area underthe major peak is approximately proportional to the total heatliberated (Wall, 1985).

The test has been used to identify the relative geological rankof a coal, its relative reactivity for ignition and combustionstability, for assessing burnout and to provide guidelines in

Figure 4 Typical DTG burning profiles (Sanyal andCumming, 1985)

Potential analytical techniques

the selection of mode of firing and assessment of furnaceperformance for full scale units (Morgan and others, 1986;Sanyal and Cumming, 1985). DTG data have been related tothe maceral composition (Bengtsson, 1986, 1987b; Morganand others, 1986), proximate and ultimate analysis data(Bengtsson, 1986; Ghetti, 1986) and surface area of coal,which should help optimise the combustion process (Ghettiand others, 1985). DTG has also been used to characteriseweathered coals (Bengtsson and Moilanen, 1986) and forchar reactivity measurements (Morgan and others, 1987).DTG can also assess the combustion reactivity of blends ofcoal (Sanyal and Cumming, 1985).

However, the DTG technique has not gone uncriticised. Theburning profiles depend critically upon test procedures (suchas heating rate, particle size) and on the apparatus design(Morgan and others, 1986). Standardisation of the test isrequired in order to obtain reliable, reproducible andcomparable results. The practical value of this empirical testhas been queried because of differences between the testconditions and combustion in practice (Ceely and Daman,1981: Pohl, 1988). Morgan and others (1986) however, haverelated DTG data generated at 400-600°C to combustionperformance at much higher temperatures. Blackmore(1985) believes that since DTG does not consider heat fluxfollowing ignition, during pyrolysis and char burnout, it willbe some time before the technique can be used to evaluatecoals commercially. The test, though, is rapid, reproducible(in the same apparatus), capable of being automated and costeffective (Morgan and others, 1986; Wall, 1985).

5.2 Nuclear magnetic resonanceNuclear magnetic resonance (nmr) spectroscopy enables thestructure of coal to be probed in a direct and non-destructiveway. Understanding the chemical structure of coal isimportant as the reactivity of coal is influenced by itschemical structure. A comprehensive review on nmr studiesof coal has been published by IEA Coal Research (Davidson,1986).

The technique of nmr is based on the magnetic properties ofcertain nuclei, principally protons ('H) and the carbon 13isotope, both of which occur in coal. The principal derivedparameter is the carbon aromaticity, fa, which is a measure ofthe number of carbons in aromatic ring structures. Generally,aromaticity increases with rank and therefore fa has beenproposed as a rank parameter. Newman and others (1988)have suggested that by expressing the phenolic content ofcoal as a fraction of the aromatic (fa) content, a bettermeasure of rank than either the phenolic or fa contents aloneis obtained. Phenolic contents can be estimated from the I3Cnmr spectra. However, there are problems in using nmr datadue mainly to the unstandardised nature of the test;spectrometric conditions and calculation methods vary suchthat it is not possible to compare values obtained by differentgroups of workers (Davidson, 1986). An internationalstandard is required.

The accuracy of the method has been disputed (Cookson andSmith, 1987; Davidson, 1986; Snape, 1987). For example,the cross polarisation technique, often used in solid state 13C

nmr spectroscopy to avoid long accumulation times, can giveunreliable quantitative results because an unrepresentativefraction of the coal is observed. In a low rank UKbituminous coal, it has been estimated that only about 40%of the carbon is seen. The fa values thus determined willgenerally be too low since less of the aromatic carbon isobserved. A normal accumulation may give results whichare quantitatively more valid, but at the expense of longeraccumulation times or poor signaknoise ratios. However,nmr is reproducible (in the same apparatus) (Davidson, 1986)and reasonably rapid and reliable. Nmr spectra can beanalysed by computer programs, making the method lesssubjective.

Coals of all rank have been studied by nmr spectroscopy.Nmr has been used to study coals as they are heated towardscoking temperatures (see Section 9.5.1) and coal liquefaction(see Section 8.4.3). Various coal properties have beencorrelated with the nmr spectra and could, in principle, bepredicted. These include the major elements carbon,hydrogen and oxygen (Sakurovs and others, 1987a) and theirfunctional groups, such as CH2 (Newman and Davenport,1986; Yoshida and others, 1984) and the minor butenvironmentally important species such as nitrogen andsulphur (Davidson, 1986). Correlations with petrographicproperties and volatile matter (Sakurovs and others, 1987a)and Gieseler fluidity and Audibert-Arnu dilatation (Sakurovsand others, 1987b) have also been found.

5.3 Pyrolysis-mass spectrometrySince most of the end-use processes of coal involve athermal conversion step, an analytical pyrolysis method couldoffer several advantages over conventional tests.Pyrolysis-mass spectrometry (py-ms) reflects changes in thechemical structure of coal as it is rapidly heated. Themethod generally involves rapidly pyrolysing a pulverisedcoal suspension coated on wires directly within a massspectrometer; from several consecutive scans, a compositespectrum is obtained for each coal sample.

Analysis of the spectra is however more complicated thaninterpretation of conventional tests and the equipment isexpensive. Duplicate analysis of samples suggests that thetest is reproducible and reliable (Meuzelaar and others,1984a), but presumably the same statistical packages need tobe used to allow accurate comparisons of data. The resultsmay be affected by possible secondary reactions occurringduring the pyrolysis (Winans and others, 1986). There is thequestion of whether py-ms can be applied to high rank coals,such as semianthracite, because low signal intensities wereobtained due to more pronounced char formation during thepyrolysis. This results in a less reliable spectra (Meuzelaarand others, 1984a). However, py-ms has been successfullyapplied to high rank coals by using a relatively hightemperature (1043 K) of pyrolysis (Tromp, 1987). Not allthe peaks in the mass spectra have been unambiguouslyassigned to the organic constituents of coal and further workin this direction is needed. There is also a lack of informationon the inorganic constituents (Meuzelaar and others, 1984a).

Several coal properties that are of relevance in coal

Potential analytical techniques

combustion, coking and liquefaction have been correlatedwith py-ms data and thus may, in principle, be predictedfrom pyrolysis-mass spectra. These include rank (aromaticity(fa)) (Harper and others, 1984; Meuzelaar and others, 1984a)where the latter workers suggest that a rank classificationsystem based on key structural moieties in coals couldconceivably be of more relevance to the chemical reactivityand related technological properties of coals than thecurrently used classification parameters. Correlations withcalorific value (average error was 183 kJ) (Harper and others,1984), CSN (Hill and others, 1985), organic sulphur content(Harper and others, 1984; Metcalf and others, 1987), maceralcontent (Metcalf and others, 1987; Meuzelaar and others,1984a, 1984b) and sulphur dioxide emission yield(Meuzelaar and others, 1987) have also been achieved.Schulten and others (1988) also found that a number ofpy-ms (field ionisation) peak signals correlated with coalultimate and proximate analyses data.

Curie point py-ms can be used to identify oxidised/weatheredcoals as the spectra of oxidised coals reveal a number ofmarked differences when compared with unoxidised coalsamples of the same type (Hill and others, 1985; Meuzelaarand others, 1984a). Oxidised coals have a marked effect oncoal reactivity (Tromp and others, 1987b).

5.4 Fourier transform infraredspectroscopy

The chemical structure of coal has been studied by Fouriertransform infrared (FTIR) spectroscopy. FTIR spectroscopyprovides an estimate of the aliphatic to aromatic hydrogenratios and can also provide a quantitative measure of thealiphatic and aromatic CH groups (Sobrowiak and others,1984) and OH groups (Kuehn and others, 1982; Snyder,1982) present in coal.

The method involves dispersing the coal sample in potassiumbromide (KBr) and scanning the pellet formed in an infraredspectrometer. The spectra is recorded and analysed on-lineusing minicomputers. Use of computer programs makes thetest less subjective. The technique is still evolving with newsampling methods, such as diffuse reflectance andphotoacoustic techniques, replacing the standard KBr pellets(Painter and others, 1986). These newer techniques oftenprovide a higher quality spectra than the traditional KBrpellets. They allow the raw powdered coal to becharacterised, often without the addition of other compounds.

In addition, new software with the potential for extractingadditional information from the spectrum is being developed.

Some uncertainty over the accuracy of the test has beenexpressed (for example, Painter and others, 1984; Riesser andothers, 1984; Snyder, 1982; Sobrowiak and others, 1984).With the unstandardised nature of the test, it can be difficultto compare results from different workers. There is a needfor an international standard. The technique is relatively fast;for example, diffuse reflectance FTIR with computerisedanalysis (CIRCOM program) can take less than 30 minutes,including sample preparation (Fredericks and others, 1987).However, the equipment is expensive.

From one FTIR spectrum several coal properties can bepredicted. The ratio of the intensity of the aromatic andaliphatic carbon-hydrogen bonds in the spectra correlateswith coal rank (Fuller and others, 1982). Carbon aromaticity(rank) can also be determined (Solomon, 1981). Other coalproperties (covering the rank range lignite to bituminouscoals) have been related to the spectra (for example, assuggested by Burchill and others, 1987; Senftle and others,1984; Verheyen and others, 1986, 1987) and could, inprinciple, be predicted. These include (for bituminous coals)vitrinite reflectance, calorific value and volatile matter(Fredericks and others, 1984; Kuehn and others, 1984),atomic C/H ratios (Burchill and others, 1987), the majorelements, ash, moisture, petrographic properties, maximumGieseler fluidity (log) and HGI (Fredericks and Grazier,1985; Fredericks and others, 1984). The latter workers usedfactor loadings obtained from factor analysis of the FTIRspectra (alkali halide technique) of a calibration set of coalsfor the correlations. The prediction of properties of unknowncoals will therefore be most accurate for coals withproperties similar to the calibration set. FTIR can alsoprovide a quantitative measure of the minerals present (Kisterand Dou, 1986) and information on the oxidation of coal(Donini and others, 1982; Fuller and others, 1982), althoughthe latter workers observed that the correlation was not verygood for the high volatile bituminous coals.

Coal blends have also been analysed successfully and coalblend proportions predicted by diffuse reflectance FTIR usedin conjunction with the computer program CIRCOM(Fredericks and others, 1987); for best results the unknowncoals should have similar properties to those in thecalibration set. Correlations with, for example, liquefactionyields and coke properties will be discussed in Sections 8.4.4and 9.5.2, respectively.

6 Classification systems

There are many classification systems in use today and newsystems are still being devised. This section will examinesome of the classification systems used in the membercountries of IE A Coal Research. Table 5 provides asummary of these systems. As discussed in the introduction,classification systems are broadly of two types, scientific and

commercial, each serving a different purpose. Both nationaland international classifications are in use. Each countrywith a coal industry has tended to develop its own criteria inorder to classify its domestic coals, often for a particularapplication. The classification parameters have often beenchosen for historical reasons. Since these national schemes

Table 5 Main coal properties specified in some classification systems

Seyler ASTM NCB Int - hardcoals

NewECE

Int - browncoal

AustralianOld New

Ruhr FRGInt

Chemical properties/composition

carbon xhydrogen xfixed carbon xsulphurvolatile matter 0 x xcalorific value Ox xmoistureashtar yield

Physical/mechanical properties

agglomeration xCSN 0 xRoga index xGray-King coke type x xdilatation x

Petrographic properties

liptiniteinertinitevitrinite reflectancereflectogram

0 Additional properties generally given in Seyler's chartInt International

xX X

X X

X

X X

Classification systems

were devised for specific types of coal, they are usuallyinapplicable to coals of a different type. Also, these nationalclassification schemes cannot always be used to evaluatecoals for applications other than those for which they weredeveloped.

International systems, by implication, should be able toclassify all coal types found worldwide. However, it haslong been recognised that the existing internationalclassification for hard coals does not adequately cater forsome coals, such as the Gondwanan coals. This is onereason why the new international codification has beendeveloped.

It has been suggested (for example, Alpern, 1981, 1987;Bennett and Taylor, 1970; Neavel, 1981; Uribe and Perez,1985) that both type (petrographic composition) and rankinformation should be included in a classification schemebecause they distinguish explicitly between characteristicsdeveloped at the time of seam formation (type) and thosedeveloped since as a result of the coalification processes(rank). Ideally, a classification based on these two conceptsshould be sufficient to allow one to predict the responseof a coal in any processing situation. However, limitedavailability of correlations between type and rank on onehand and the operational responses on the other hand restrictsthe application of this concept. The new ECE 'classification'includes both type and rank parameters, but also includessome of the more traditional parameters.

Traditionally, classification systems are hierarchical(Aristotelian). However, some of the newer classificationsare moving away from an hierarchy to a list of parameters ina specified order. These systems could reasonably be termed'categorisations' or 'codifications' of coals, rather thanclassifications. Examples are the new Australian and newECE systems. An information scientist would describe theseas 'faceted classifications'.

There are certain requirements (Alpem, 1981; Eidel'man,1981; Falcon, 1978b) a good classification system shouldmeet. A classification should:

categorise coals;- be able to identify the most appropriate coal for a particular

purpose/process. It should be able to assess any coaland be universally applicable to all coal types;

- allow an estimate or prediction of other properties orbehaviour of an unknown coal. This assumes thatcoals with the same basic parameters are of the sametype and will have the same properties, an assumptionthat is not necessarily true (for example, the inertiniteproblem);

- have scientifically valid parameters;- be simple to use, with legible presentation and be easily

remembered;- be for single coals;- include both raw and washed coals;- evaluate potential environmental problems.

How some of the main classification schemes in use todaymeet these requirements and how they cope with the

different types of coal will be discussed. The methodsfor determining the classification parameters and therequirements these methods should meet have been discussedin the previous sections.

There is some difference of opinion on whether aclassification should be for single coals only. More oftenthan not blends are used in the industrial applications of coaland therefore, a classification that is also applicable to blendswould be useful in the commercial sector. Mostclassifications can be applied to blends containing coals withsimilar properties. However, problems can occur whenclassifying a blend consisting of coals with widely differingproperties (Marshall, 1976). It may therefore be useful toclassify each component coal individually and to specify itsproportion in the blend separately. Classifications thatinclude parameters that are additive would be advantageous.

At the time when the traditional classifications (for exampleASTM, NCB and Ruhr) were developed, no environmentalconstraints on the use of coal were under consideration.There is increasing concern these days with theenvironmental consequences of the use of coal and therefore,parameters that can evaluate the potential environmentalproblems would be useful in an up-to-date classification.Since the majority of coal is burned, parameters (such assulphur) that indicate the likely emissions and hence thepollution control equipment required would probably be themost useful. The grade (that is, the amount of impurities suchas mineral matter) of coal can be important for tradepurposes. The commonest parameter of grade is the ashyield. Knowledge of the ash yield is also important not onlybecause of its effect on other parameters, such as volatilematter and calorific value (especially when these areexpressed on an ash-free basis), but also because of its effecton the suitability of a coal for certain industrial applications.For example, in combustion ash yield can provide anindication of the likely ash handling and disposalrequirements. However, ash and sulphur can always beconsidered separately in a coal specification.

6.1 Seyler's classificationSeyler's classification is one of the earliest scientificclassifications still in use today. It is based on the ultimateanalysis of the organic substance of coal. Although Seylerproduced a tabular form of his classification system aroundthe beginning of this century (see Table 6), it is the graphicalform that is most widely known today.

Seyler plotted the carbon content (%) (see Section 2.2) ofcoals against their hydrogen content (%) (see Section 2.3) fora wide range of coals, mainly from UK. The carbon andhydrogen contents are calculated to a dmmf basis using theParr formula, which was developed on US coals and so canlead to errors (see Section 2.1). Seyler found that the coalsplotted into a curved band, the 'coalification band', inaccordance with their degree of metamorphism (seeFigure 5). Low rank coals with their lower carbon andhigher hydrogen contents plot to the right of the graph. Forcoals that can be regarded as typical of their type (bright,vitrinite-rich coals), Seyler used the prefix ortho (typical,

Classification systems

/ ^carbonaceous

semi-anthracite

anthracite group

Brightcoalband

100 90 85 80Carbon content, %dmmf

Figure 5 Seyler's coal chart (van Krevelen, 1 961)

normal). Coals containing more carbon than those of theortho-type were given the prefix meta, and those with alower percentage of carbon are indicated by the prefix para.Furthermore, coals containing more hydrogen than thenormal, bright coals (and which plot above the coalificationband) are called per-hydrous. Similarly, coals with a lowerhydrogen content than expected are called sub-hydrous.

Seyler (1938) also succeeded in relating the elementarycomposition of normal bright coals to other technologicalproperties, such as volatile matter and calorific value. Afterthe introduction of some modifications, this has resulted inthe well-known Seyler's coal chart which:

- visually illustrates the connection between the elementarycomposition of coal and its technological properties;

- can predict the behaviour of an unknown (vitrinite-rich)coal;is rank-based;

- refers to single coals (but can be applied to blends of coalswith similar properties).

Seyler's classification is based on Regnault's first law thatstates that coals of the same kind (that is, identical in all theirproperties) have the same elementary composition withinnarrow limits. Seyler (1938) recognised that unless theconverse of this law was true, no certain inferences (orpredictions) as to the properties of coals could be based onchemical composition. He found that the converse of thislaw is true only for bright (vitrinite-rich) coals, that is, coalsof the same composition have the same volatile matterprovided they are bright coals. The formula Seyler proposed

Table 6 Seyler's coal classification system (Ward, 1984b)

Genus

Per-bituminous

Bituminous

Semi-bituminous

Carbonaceous

Anthracitic

H

%

>5.8

5.0-5.8

4.5-5.0

4.0-4.5

<4

Class, % C

Anthracite

(>93.3)

semi-anthraciticspecies(dry steamcoal)

ortho-anthracite(trueanthracite)

Carbonaceous

(93.3-91.2)

pseudo-bituminousspecies

semi-bituminousspecies(ortho-semi-bituminous)

carbonaceousspecies(ortho-carbonaceous)

pseudo-anthracite(sub-carbonaceous)

BituminousMeta-(91.2-89.0)

Per-bituminous(per-meta-bituminous)

meta-bituminous

subbituminous(sub-meta-bituminous)

pseudo-carbonaceous(sub-meta-bituminous)

pseudo-anthracite(sub-meta-bituminous)

Ortho-(89.0-87.0)

Per-bituminous(per-ortho-bituminous)

ortho-bituminous

subbituminous(sub-ortho-bituminous)

pseudo-carbonaceous(sub-ortho-bituminous)

pseudo-anthracite(sub-ortho-bituminous)

Para-(87.0-84.0)

Per-bituminous(per-para-bituminous)

para-bituminous

subbituminous(sub-para-bituminous)

pseudo-carbonaceous(sub-para-bituminous)

pseudo-anthracite(sub-para-bituminous)

LignitousMeta- Ortho-(84-80) (80-75)

Per-lignitous

lignitousmeta- ortho-

sub-lignitousmeta- ortho-

Classification systems

Table

Class

I

II

III

IV

7 ASTM classification of coal

Group

Anthracitic 1 meta-anthracite2 anthracite3 semi-anthracite!

Bituminous 1 low volatilebituminous coal

2 medium volatilebituminous coal

3 high volatile Abituminous coal

4 high volatile Bbituminous coal

5 high volatile Cbituminous coal

Subbituminous 1 subbituminousA coal

2 subbituminousB coal

3 subbituminousC coal

Lignitic 1 lignite A2 lignite B

by rank* (ASTM D388:1984)

Abbrevi-ation

maansa

lvb

mvb

hvAb

hvBb

hvCb

subA

subB

subC

ligAligB

Fixed carbonlimits,% dmmf

Equal orgreaterthan

989286

78

69

Lessthan

9892

86

78

69

Volatile matterlimits,% dmmf

Greaterthan

28

14

22 VJi~

31

Equal orless than

28

14

22

31

Calorificlimits,

value

MJ/kg mmmft

Equal orgreaterthan

32.56§

30.24§

f26.751.24.42

24.42

22.10

19.31

14.65

Lessthan

32.56

30.2426.75

26.75

24.42

22.10

19.3114.65

Agglomeratingcharacter

J1 non-lagglomerating

• commonlyagglomerating^

agglomerating

•

non-agglomerating

* This classification does not include a few coals, principally coals rich in inertinite or liptinite. In North America these coals are principallythe nonbanded varieties.

t Moist refers to coal containing its natural inherent moisture but not including visible water on the surface of the coal.$ If agglomerating, classify in low-volatile group of the bituminous class.§ Coals having 69% or more fixed carbon on the dmmf basis shall be classified according to fixed carbon, regardless of calorific value.^ It is recognised that there may be non-agglomerating varieties in these groups of the bituminous class, and there are notable exceptions in

high volatile C bituminous group.

for calculating volatile matter (see Section 2.6) is in factvalid for only certain bright coals. Chandra (1985) showedthat the converse of Regnault's law does not necessarilyfollow for all bright coals and that it was possible to havetwo bright coals of the same composition but, depending ontheir origin and the effects of alteration after their formation,showing different properties. The coals Chandra used wereregionally metamorphosed or weathered coals which wouldplot outside the coalification band. Speight (1983) considersthat elemental composition and coal behaviour do notnecessarily exist in the form of simple relationships andhence, classification by elemental composition alone isdifficult. However, simple correlations of many properties ofthe organic part of the coal with its elemental compositionhave been found (see for example, Sections 2.6 and 2.7),although these may not be applicable for all coal types.Thus, it can be said that coals with identical elementalcomposition may not behave identically and therefore theSeyler chart may not always accurately reflect the behaviourof a coal in its end use processes.

There is an implicit assumption in the coal chart that all coals

follow a single, though broad, band of development fromlignite through to anthracite (Valkovic, 1983). However,there are probably many bands of coal development (seeSection 1.3). For example, if the carbon/hydrogen contentsare plotted for the Gondwanan coals, a different'coalification band' is observed. Seyler (1938) recognisedthat some coal types plotted outside the coalification band,the per-hydrous coals (which include the sapropelic coals andother coals with a high liptinite content) and the sub-hydrouscoals (which include the inertinite-rich coals and oxidised orweathered coals). The extension of the coalification bandbelow 85% carbon is of questionable validity, as data forNorth American lignites indicate a much greater variation ofhydrogen content than the band allows (Berkowitz, 1979).

Mazumdar (1984) also found that when carbon content isplotted against hydrogen content for Indian lignites, thecoalification band is not horizontal but slopes distinctlydownwards. A number of lignites/brown coals, such as theLoy Yang (Australia) and Neyveli (India), contain less than75% carbon and so would be treated as 'peat' in Seyler'sclassification. Thus strictly speaking, Seyler's coal chart is

Classification systems

Table 7 Cont

Class

I Anthracitic

II Bituminous

III Subbituminous

IV Lignitic

Group

1 meta-anthracite2 anthracite3 semi-anthracite

1 low volatilebituminous coal

2 medium volatilebituminous coal

3 high volatile Abituminous coal

4 high volatile Bbituminous coal

5 high volatile Cbituminous coal

1 subbituminousA coal

2 subbituminousB coal

3 subbituminousCcoal

1 lignite A2 lignite B

Fixed carbonlimits,% dmmf

Equal orgreaterthan

989286

78

69

Lessthan

9892

86

78

69

Calorific valuelimits,Btu/lb mmmf

Equal orgreaterthan

14000

13000

C11500[10500

10500

9500

8300

6300

Lessthan

14000

1300011500

11500

10500

9500

83006300

Agglomeratingcharacter

J*j non-lagglomerating

commonlyagglomerating

agglomerating

non-agglomerating

applicable only to the British Carboniferous coals for whichit was developed.

Thus the main disadvantages of Seyler's coal chart are:

- applicable only to vitrinite-rich humic coals;excludes (and is inapplicable to) some lignites/brown coals;

- coals with identical elemental composition may notbehave identically in end use processes;

- not accurate enough for commercial use (Grainger andGibson, 1981);

- little information on the environmental aspects of coalutilisation (Eriksson and others, 1981);

- little information on the grade of coal.

6.2 US (ASTM) classificationThe ASTM (ASTM, 1984) coal classification system is usedextensively in North America and many other parts of theworld. It has been in use for a number of decades. Theclassification system is:

- hierarchical;- commercial;- rank-based;- for single coals;

includes coals of all rank;- easily memorable (names are widely used in the literature);

- simple and easy to use.

Two parameters are used to classify coals by rank, fixedcarbon (dmmf) for the higher rank coals and gross calorificvalue (mmmf) for the lower rank coals. The agglomeratingcharacter is used to differentiate between certain adjacentgroups. The volatile matter yield is directly related to thefixed carbon content and so can be used instead of the latter.The full classification, in SI units, is given in Table 7. Forcomparison, a simplified form of the classification isincluded in the original units, as specified in the ASTMstandard. The classification parameters are all determined bystandard techniques.

Two rank parameters are required to classify coals sinceneither the fixed carbon nor the calorific value can be usedover the entire rank range. These parameters were discussedin Sections 2.2 and 2.7. Fixed carbon is calculated to admmf basis and calorific value to a mmmf basis usingformulae based on the Parr formula (see Section 2.1).Defects in these mmf calculations are recognised, where it isacknowledged in the ASTM standard that the precision of theclassification of impure coals may be impaired by the effectsof large amounts of mineral matter.

Overlapping of the two rank parameters occur in thebituminous class, so the rule is that coals with a fixed carbonof 69% or more are classified according to this value

Classification systems

regardless of their calorific value. Two groups have thesame calorific value (10,500 to 11,500 Btu/lb or about 24.42to 26.75 MJ/kg) but are separated by their agglomeratingcharacter. The ASTM standard recognises that anomaliescan occur when using agglomerating behaviour. Itacknowledges that there can be nonagglomerating varietiesof coal in the bituminous class and that there are exceptionsin the high volatile C bituminous group. Coals with a fixedcarbon of between 86% and 92%, if they are agglomerating,are classified in the low volatile bituminous group, despitethe fact that their fixed carbon would classify them in thesemianthracite group. Some of these exceptions have beenrelated to the petrographic composition of the coal.

This classification system does not include all coals. Coalsrich in liptinite or inertinite and the nonbanded (sapropelic)coals are specifically excluded, as are weathered or oxidisedcoals. Thus the classification excludes the inertinite-richcoals of the southern hemisphere; it covers only thevitrinite-rich coals of the northern hemisphere. No cleardefinition is given of the boundary between peat and lignite.Lignite B just has a calorific value of less than 6,300 Btu/lb(14.65 MJ/kg).

The classification parameters chosen reflect the markets forcoal which were important at the time the classificationsystem was first devised, that is, the combustion and cokingmarkets. It does not effectively classify coals according totheir behaviour in the newer processes such as liquefactionand gasification (Valkovic, 1983). No explicit gradeinformation is included and there is no informationconcerning the environmental impact of coal utilisation(Eriksson and others, 1981; Valkovic, 1983). In these days,with the growing environmental concern of coal utilisationand the increasing interest in coal liquefaction andgasification, there is a need for this information to beincluded. However, additional properties can always bespecified in addition to the classification code, when buyingand selling coal.

The position of a coal in the rank series can be representedby a numeric code, enabling the classification to becomputerised. The numeric code uses a two number code,for example (62-146). The first number is the fixed carboncontent (to the nearest whole per cent) and the secondnumber is the calorific value (to the nearest 100 Btu/lb(233 kJ/kg)). The parenthesis indicates the values are on ammf basis. However, the numeric code does not contain anyinformation on the agglomerating characteristics andtherefore will not distinguish between, for example, the highvolatile C bituminous and subbituminous A coals.

There has been some criticism over the numbering system. Ithas been suggested that the class numbering system shouldbe reversed so that a high number would indicate a high rank(Speight, 1983). Since the classification system has been inuse for a number of years, some confusion may result if thenumbering system were now changed, and the coals aregenerally referred to by their group names.

Thus the main disadvantages of the ASTM classification canbe summed up as follows:

- only for vitrinite-rich humic coals (excludes Gondwanancoals);

- inadequate for coals for liquefaction and gasification;- no environmental information;- no grade information;- no clear definition of lignite/peat boundary.

6.3 United Kingdom (NCB)classification

The coal classification system in use in the United Kingdomwas first published in 1946, although it had already beenapplied for some time. Over the years it has been revised,the latest modification appearing in 1964 (NCB, 1964). Theclassification scheme (commonly known as the NCBclassification) is also given in tabular form in the BritishStandard BS 3323.

The classification is:

- hierarchical;- commercial;- rank-based;- for bituminous and anthracite coals only;- for single coals (but can be applied to some blends);- has provision for heat-altered and oxidised (weathered)

coals;- coded;- simple and easy to use.

Two parameters are used to classify bituminous andanthracite coals, namely volatile matter (dmmf) and cokingproperties (defined by the Gray-King coke type). Theseparameters are discussed in Sections 2.6 and 3.3,respectively. The different classes of coal are designated bya three figure numerical code {see Table 8). Coals with lessthan 19.6% volatile matter (dmmf) are classified by thisparameter alone and the Gray-King values shown in the tableare for information only. The classification is intended forsingle coals, but since volatile matter is additive, it can beapplied to blends of coals with less than 19.6% volatilematter. The volatile matter is calculated to a dmmf basis bya formula that uses a modified KMC equation to estimate themineral matter content (see Section 2.1).

Coals with a high ash yield (>10%) must first be cleanedbefore analysis. This implies that the classification coversonly raw coals with up to 10% ash and washed coals.

This is one of the few classification schemes that specificallyhas provision for locally heat-altered and oxidised(weathered) coals. When heat-altered coals are recognised,they are designated by adding the suffix H to the coal rankcode (for example 102H). They occur mainly in classes 100,200 and 300. Oxidised or weathered coals are distinguishedby the suffix W after the coal rank code; these coals canoccur in any class.

Lignites and brown coals are outside the range of the NCBclassification scheme. There is only a small amount of theselower rank coals in the United Kingdom (mainly in Northern

Table 8 National

Coal rank code

Main class(es) Class

Coal Board classification

Sub-class

system (NCB,

Volatile matter,%, dmmf

1964)

Gray-Kingcoke type*

Classification

Generaldescription

systems

100

200

lOlt102t

201

202203204

201a201b

6.1-9.0

9.1-19.59.1-13.59.1-11.511.6-13.513.6-15.015.1-17.017.1-19.5

A-G8A-CA-BB-CB-GE-G4G1-G8

i anthracites

low volatile steam coals

i dry steam coals

] coking steam coals

300

400 to 900:400

500

600

700

800

900

301

302

303

401402

501502

601602

701702

801802

901902

301a301b

19.6-32.019.6-32.019.6-27.527.6-32.019.6-32.0

19.6-32.0

>32.0>32.032.1-36.0>36.0

>32.032.1-36.0>36.0

>32.032.1-36.0>36.O

>32.032.1-36.0>36.0

>32.032.1-36.0>36.0

>32.032.1-36.0>36.0

A-G9 and over

j G9 and[over

\ G5-G8

G1-G4

E-G

C-D

A-B

medium volatile coals

1 prime coking coals

medium volatile, medium cakingor weakly caking coalsmedium volatile, weakly cakingto non caking coals

high volatile coalshigh volatile,very stronglycaking coals

high volatile,strongly cakingcoals

high volatile,medium cakingcoals

high volatile,weakly cakingcoals

high volatile,very weaklycaking coals

high volatile,non cakingcoals

* Coals with volatile matter of under 19.6% are classified by using the parameter of volatile matter alone; the Gray-King coke types quoted forthese coals indicate the general ranges found in practice, and are not criteria for classification.

t In order to divide anthracites into two classes, it is sometimes convenient to use a hydrogen content of 3.35% (dmmf) instead of a volatilematter of 6.0% as the limiting criterion. In the original Coal Survey rank coding system the anthracites were divided into four classes thendesignated 101, 102, 103 and 104. Although the present division into two classes satisfies most requirements it may sometimes be necessaryto recognise more than two classes.

Coals with ash of over 10% must be cleaned before analysis for classification to give a maximum yield of coal with ash of 10%.

Coals that have been affected by igneous intrusions ('heat-altered' coals) occur mainly in classes 100, 200 and 300 and when recognisedshould be distinguished by adding the suffix H to the coal rank, for example 102H, 201bH.

Coals that have been oxidised by weathering may occur in any class, and when recognised should be distinguished by adding the suffix W tothe coal rank code, for example 801W.

Classification systems

Ireland) and they are not yet commercially mined. There isno clear boundary between the bituminous and lower rankcoals. The majority of British coals have a volatile matteryield of less than 45%.

The classification was devised for the vitrinite-rich Carbon-iferous coals of the United Kingdom. It does not adequatelycater for petrographically heterogeneous coals, such as theinertinite-rich Gondwanan coals, as these coals can producebetter coke than their poor Gray-King coke number wouldlead one to expect (see Section 9.4). As with other systems,additional parameters may be required for the newer coalutilisation processes, such as gasification and liquefaction(Uribe and Perez, 1985; Valkovic, 1983). There is noexplicit grade or environmental information included(Eriksson and others, 1981; Valkovic, 1983) and a low classnumber indicates a high rank coal and vice versa. The codescan be easily computerised but no immediate impression ofthe coal rank is provided. Neither volatile matter nor theGray-King coke number can be easily ascertained from thecode number or correlates in an easily remembered form. Agood classification by its very form should reveal propertiesof coal in an easily understandable way. Names do facilitate(especially verbal) communication, one reason why they arepopular.

Thus the main disadvantages of the NCB classification canbe summed up as follows:

- only for vitrinite-rich coals (inadequate for Gondwananand other petrographically heterogeneous coals);

- inadequate for coals for liquefaction and gasification;- no environmental information;- no grade information;

no clear definition of high volatile/brown coal boundary;needs decoding.

6.4 German (Ruhr) classificationThe classification of Ruhr coals is published in theRuhrkohlen Handbuch (1969), although it had already beenin use for a number of years before this date. Coals areclassified by rank according to their volatile matter (daf) andin marginal cases, by their caking capacity (CSN). Table 9lists the rank divisions which, like the ASTM classification,are named.

The Ruhr classification is:

- hierarchical;- commercial;- rank-based;- for higher rank coals;- for single coals;- named rank divisions.

Where the rank divisions have overlapping volatile matteryields, they are distinguished by their caking capacity, whichin Table 9, is described by the appearance of the cruciblecoke yield. The crucible coke yield is the residue left in thecrucible after the volatile matter has been evolved. Theparameters are determined by the method specified in the

Table 9 Ruhr classification system (RuhrkohlenHandbuch, 1969)

Coal rank

Gasflammkohlen(gas flame coals)

Gaskohlen(gas coals)

Fettkohlen(bituminous (fat) coals)

Esskohlen(steam coals)

Magerkohlen(lean coals)

Anthrazit(anthracite)

Volatile matter,wt% daf

33-40

28-35

18-30

14-20

10-14

7-10

Nature of cruciblecoke

sintered, lightlycaked in parts

caked, fissured

strongly caked,solid

lightly caked tosintered

powdery

powdery

relevant DIN standards; the German standard for volatilematter determination (DIN 51720) should be followed asother methods can give different results (see Section 2.6).

It should be noted that in DIN 22005: Teil 2, the named rankdivisions are defined by their volatile matter only and thatthese can be different from those listed in Table 9. Forexample, Fettkohlen is defined as coal with a volatile matter(daf) from 19% to less than 28%. Thus some slightdifferences in the meaning of these terms can occur in theliterature.

As given in Table 9, the Ruhr classification covers onlythe higher rank coals. However, named divisions of thelower rank coals exist, namely Flammkohlen (flame coals),the Hartbraunkohle (hard brown coals), which are dividedinto the Mattbraunkohle (dull brown coals) and theGlanzbraunkohle (bright brown coals), and theWeichbraunkohle (soft brown coals). These terms are notdefined in the Ruhrkohlen Handbuch.

The Ruhr classification is similar to that of the NCB (Section6.3) except that the CSN is used instead of the Gray-Kingcoke number. However, most of the points discussed in thisearlier section apply. That is, the Ruhr classification:

- does not cater adequately for all coal types;- is inadequate for coals for liquefaction and gasification;- has no environmental information;- has no grade information.

6.5 International classifications

6.5.1 International classification of hardcoals

In 1949, the Coal Committee of the Economic Commissionfor Europe (ECE) set up the Classification Working Party to

Classification systems

devise an international classification of coal to assist theinternational trade. The national systems of coalclassification and methods of coal sampling and analysisused in various countries were examined and from these, the'International classification of hard coals by types' (ECE,1956) was devised. Unfortunately, despite its goodintentions, the classification has had only a limitedapplication (Eidel'man, 1981).

The international classification covers hard coals, that is,coals with a gross calorific value (maf) of more than 5,700kcal/kg (23.86 MJ/kg). Since the system has toaccommodate a larger range of coals, it is a more elaboratescheme than any one national classification system. It is:

- commercial;- rank-based;- for hard coals only;- for single coals;- coded.

A three-digit code number describes each coal. The first

further four classes. Class 1 is further subdivided intoclasses 1A and IB. The second digit represents the coalgroup, that is the caking properties of coal determined eitherby its CSN or Roga index. The last digit indicates the coalsubgroup determined by the coking properties, which arebased on the Gray-King coke type or alternatively, itsbehaviour in the Audibert-Arnu dilatometer. All theseparameters are discussed in Sections 2 and 3.

A number of subgroups have been defined that accommodatemost of the commercial coals. These subgroups have beengrouped into a relatively small number of statistical groups,represented by the Roman symbols I to VII. For example,statistical groups I and II are the anthracites, and statisticalgroup V contains the caking coals and can be furthersubdivided into statistical groups VA to VD according totheir suitability for coking. But should coals occur with acombination of caking and coking properties outside thelimits of the stated subgroups, they can still be classifiedusing the same principles.

The international classification system is a compromisedigit indicates the class of the coal (see Table 10). Coals aredivided into six classes according to their volatile matteryield (daf); however for coals with more than 33%, the grosscalorific value (maf) is used for the division of coals into a

among the various countries on the Coal Committee and assuch, suffers the problems inherent in any compromise.Not all ranks of coal are covered; there is a separateinternational classification for the lignites and brown coals

Table 10 International classification of hard coals by type (ECE, 1956)

groups(caking properties)

groupnumber

3

2

1

0

classpara-

meters

alternativeparameters

crucibleswellingnumber

> 4

2V2 - 4

1 - 2

0 - Vi

Rogaindex

> 4 5

>20 - 45

>5 - 20

0 - 5

class number

volatile matter(daf)

gross calorific valuemaf, kcal/kg (MJ/kg)30°C, 96% humidity)

code numbers

the first figure of the code number indicates the class of coal,

the second figure indicates the group,

the third figure indicates the sub-group.

0

0 - 3

100

A I B

1

>3- 1 0

>3-6.5

>6.5-10

212

211

2

>10-14

mM

332a

332b

323

322

32T

312

311

3o<y

3

>14-20

4 3 5

4 3 2

4 2 3

4 2 2

y421412

411

ioo4

>20-28

v5345 3 3

532

523

522

521

5 1 2

511

5 0 0

5

>28-33

635

634

^ 3 3

632

_623

6 2 2

- ^612

eu

6o6'

6

733

732

723A

L7l2

721

LPi2

rf1

700

7

8 3 2

823

8 2 2

821

8 1 2

811

800

8

9 0 0

9

> 3 3

>775O(32.45)

>7200(30.15)-7750(32.45)

>6100(25.54)-7200(30.15)

>57OO(23.86)-6100(25.54)

sub-groups(coking properties)

sub-groupnumber

5

4

3

2

3

2

1

2

1

0

alternative parameters

dilatationbehaviour

(%)

>140

> 50-140

> 0 - 5 0

<o

>0- 50

contraction only

^ o

contraction only

non-softening

as an indication, the followirapproximate volatile matter i

class 6: 3 3 - 4 1 %class 7: 33 - 44%class 8: 35 - 50%class 9: 42 - 50%

Gray-Kingcoke type

>G8

G5 - G8

G1 - G4

E - G

G1 - G4

E - G

B - D

E- G

B- D

A

g classes havecontents of:

classes determined by volatile matter up to 33% volatile matter and by calorific value above 33% volatile matter

notes: (i) hard coals arecoalswithagross calorific value over 5700 kcal/kg(23.26 MJ/kg)on a maf basis (30°C, 96% humidity)(ii) where ash content is >1 0%, it must be reduced to below 1 0%(iii) 332a: > 1 4 - 1 6% volatile matter

332b: >1 6 - 20% volatile matter(iv) Roman numerals represent the statistical grouping of hard coals

Classification systems

(see Section 6.5.3). There has been some criticism of thefigure chosen to define hard coals. Only part of the ASTMsubbituminous B group and all of the subbituminous A andhigher rank coals are included. Some coals, for examplefrom the Collie field in Western Australia, traditionallyregarded as hard coals would not be classified as such, sincetheir gross calorific value (maf) is less than 23.86 MJ/kg(ECE, 1985a). Some lignites are hard (for example, theHartbraunkohlen of the Federal Republic of Germany)(Alpern, 1981) and these are also not included.

Coals with more than 10% ash are required to be cleanedbefore analysis, implying that there is an ash limit of 10%(Alpern, 1981; Navale and Mistra, 1983). Alpern (1981)comments that, as well as the ash yield, the washability ofthe coal is ignored.

A choice of tests is given for determining the caking andcoking parameters that are assumed to be interchangeable, anassumption that has been shown to be inaccurate. Forexample, in a study reported by van Krevelen (1961), it wasshown that the CSN and Roga index are not alternative groupparameters for all coal types and are valid as alternativeparameters only for coals having a volatile matter of morethan 28%. The tests differ both in substance and in thetemperatures they require (see Sections 3.1 to 3.4). A coalfrom the Pechora coalfield (USSR) can have for example, acode number of 623, 633, 622 or 632 depending on which ofthe four different tests is quoted (ECE, 1976).

It has been generally recognised that the classification doesnot cater adequately for petrographically heterogeneouscoals, such as the Gondwanan coals (for example ECE, 1976;Uribe and Perez, 1985). The position of inertinite-rich coalsin the various statistical groups does not correspond to theiractual properties in end-use applications. For example, acoal from the Kuznetsk (USSR) coalfield (inertinite-rich) andanother from the Donets (USSR) coalfield (vitrinite-rich)have the same code number 311, although they producecokes with very different mechanical strengths when cokedseparately (ECE, 1976). Thus inertinite-rich coals will tendto be downgraded when compared to vitrinite-rich coals ofthe same rank.

The international classification is intended primarily toevaluate coals for combustion and coking (Eidel'man 1981)and may require supplementary parameters for the newercoal utilisation processes, such as gasification andliquefaction (Uribe and Perez, 1985). Two out of threeparameters are related to coking. No grade (Alpern, 1981) orenvironmental (Eriksson and others, 1981) information isincluded in the classification. Also, it is not easilymemorable since it uses code numbers which need decoding(Alpern, 1981). One cannot easily ascertain the value of theparameter from the relevant digit. It would be helpful if onecould determine the range of the parameter from the codewithout having to refer back to the classification system.However, the code numbers do allow computerisation of theclassification scheme.

Thus the main disadvantages of the system can besummarised as follows:

- does not cater adequately for all coal types;- inadequate for coals for liquefaction and gasification;

no environmental information;- no grade information;- choice of parameters;- needs decoding;- excludes some lower rank coals that are 'hard'.

6.5.2 New international codification ofhigher rank coals

With the increase in world coal trade in recent years, a needfor an updated international classification system for coalswas recognised. A 'classification' for the medium and highrank coals has now been developed, the internationalcodification system for medium and high rank coals (referredto as the new ECE 'classification' or internationalcodification in this report). The codification is intended toassist in the international trade in coal and replaces the 1956international classification of hard coals. Eight basicparameters (see Table 11) define the main properties of coal,represented by a 14 digit code number (ECE, 1988). Sincethe 'classification' is not hierarchical, it is termed a'codification'. The ECE is now working on an 'internationalclassification of coals', which would cover the geologicalevaluation of resources and reserves, mining and industrialuses.

The codification is an attempt to include type (petrographiccomposition), rank and grade information and marks adistinct change from the national and existing internationalclassifications. The codification is:

- commercial;- includes rank and petrographic information;- includes environmental information;- includes grade information;- for medium and high rank coals only;- for blends and single coals;- for raw and washed coals;- for all end use applications;- coded.

For the borderline between low and medium rank coals,low rank coals are defined as coals with a gross calorificvalue (maf) of less than 24 MJ/kg and a mean randomvitrinite reflectance of less than 0.6%. Medium and highrank coals are coals with a gross calorific value (maf) greaterthan, or equal to, 24 MJ/kg and those coals with a grosscalorific value (maf) less than 24 MJ/kg, provided that themean random vitrinite reflectance is equal to, or greater than,0.6%. The moisture level used for expressing the grosscalorific value on a maf basis is the 'moisture-holdingcapacity', as specified in the standard ISO 1018 (seeSection 2.8).

Some criticisms of the boundary definition have been raised.Rank changes are gradual, but it is generally accepted thatthe low/medium rank boundary occurs in the 0.4 to 0.6%vitrinite reflectance range. The calorific value is comparablewith the boundary in the existing international classificationof hard coals and is a more widely determined parameter

Classification systems

than vitrinite reflectance. With a limit of 0.6% reflectanceand 24 MJ/kg calorific value, many coals often described ashigher rank coals (for example, Collie subbituminous coalsof Western Australia) would be placed in the low rankcategory (ECE, 1982d, 1986). Also, part of some coalbedsof the same origin would be classified as low rank and partas medium rank coals (ECE, 1985b). Gray (1983) found thatthe two criteria for the boundary definition did notcorrespond for New Zealand coals.

The codification (see Table 11) uses a 14 digit code torepresent the eight basic parameters, which are (in sequence):

- mean random vitrinite reflectance (2 digits);vitrinite reflectogram characteristics (1 digit);

- maceral composition (inertinite content 1 digit, liptinitecontent 1 digit);

- crucible swelling number (1 digit);- volatile matter (2 digits);- ash (2 digits);- sulphur (2 digits);- gross calorific value (2 digits).

The parameters (discussed in Sections 2 to 4) are determinedusing techniques specified in the appropriate international(ISO) standards. The chosen parameters are a compromise

among the different requirements of the various membercountries of the ECE and as such suffers the problems of anycompromise in that the codification is unlikely to satisfyeveryone.

The rank of coal is assessed by its vitrinite reflectance (seeSection 4.2). Although generally considered to be applicableto the petrographically dissimilar Gondwanan and Laurasiancoals, identical values do not necessarily mean identicalproperties, as coals with the same reflectance do not all havethe same composition (Neavel, 1986).

The reflectogram of vitrinite (given as the standard deviationand number of gaps) provides a means of distinguishingbetween single seam coals and blends of coal of differentranks. It can identify the rank composition of blends. Otherclassifications are unable to achieve this. However, asdiscussed at the beginning of Section 6, whether aclassification should include blends and therefore, thenecessity of the reflectogram, is debatable. Using thisparameter adds complication (ECE, 1986). Results are notalways unambiguous (see Section 4.3) and this is recognisedin the note added to the code number 2 of the reflectogram.Also, little insight into the properties of coal is provided by areflectogram (ECE, 1982a, 1986). It can, however, be usefulto know if a coal is a blend; for example, the coking

Table 11 International codification of higher rank coals* (ECE, 1988)

Vitrinite

(mean

code

020304-484950

random)

Rrandom%

0.2-0.290.3-0.390.4-0.49-

4.8-4.894.9-4.99>5.0

volatile matter,§dafcode

484644

121009

0201

mass%

>4846-<4844-<46

12-<1410-<129-<10

2-<3l-<2

Characteristics of reflectogramt

code

012

34

5

standard deviation

<0.1>0.1 <0.2>0.2

ash,

code

000102

20—

no gapno gapno gap1 gap2 gaps>2 gaps

dry

type

seam coalsimple blendcomplex blendblend withblend withblend with

mass%

0-<ll-<22-<3

20-<21—

1 gap2 gaps>2 gaps

totaldrycode

000102

2930-

Maceral group composition (mmf)

inertinite^

code vol%

0 0-<101 10-<202 20-<30-7 70-<808 80-<909 >90

sulphur,

mass%

0-<0.10.1-<0.20.2-<0.3

2.9-<3.03.0-<3.1-

liptinite

code vol%

1

23-789

0-<55-<1010-<15-30-<3535-<40>40

Crucible swelling

code

012

-789

gross calorific value,dafcode

212223

373839

MJ/kg

<22

22-<2323-<24

37-<3838-<39>39

number

0-0.51-1.52-2.5-

7-7.58-8.59-9.5

* Higher rank coals are coals with: gross calorific value (maf) >24 MJ/kg and those with gross calorific value (maf) <24 MJ/kg, provided meanrandom vitrinite reflectance >0.6%

t A reflectogram as characterised by code number 2 can also result from a high rank seam coal% It should be stressed that some of the inertinite may be reactive§ Where the ash content of coal is more than 10%, it must be reduced, before analysis, to below 10% by dense medium separation. In these

cases, the cutting density and resulting ash content should be stated.

Classification systems

behaviour of a blend of coals of widely varying volatilematter yields is different from that of a single coal with thesame volatile matter as the blend.

Two parameters represent the maceral composition, theinertinite and liptinite contents. The difference between thesum of these two maceral groups and 100% gives thevitrinite content. The inclusion of the maceral compositionenables petrographically dissimilar coals, such as theGondwanan and Laurasian coals, to be distinguished.Concern however has been expressed over the inclusion of amaceral parameter. Doubts have been expressed as towhether the determination of inertinite and liptinite aresufficiently precise to be used as classification parameters(see Section 4.1). There is the question of the variability inthe make-up of inertinite and its behaviour during coalutilisation. Inertinite is generally believed to be relativelychemically inert but there is a growing body of evidenceshowing that a significant proportion of the inertinite inGondwanan and some Western Canadian coking coals isreactive in an analogous manner to the vitrinite andcontributes directly to the quality (strength) of the cokeproduced. In the absence of this knowledge, a comparison ofa Gondwanan coking coal with a Laurasian coal of similarrank and on the basis of their inertinite content will tend tounnecessarily downgrade the former because of its higherinertinite content. Therefore, it has been argued that thecodification is not truly international (ECE, 1986);Gondwanan coals could be placed at an apparentdisadvantage when compared with the Laurasian coals. Tohelp overcome this problem, explanatory notes have beenincluded with the codification pointing out that the wholepackage of parameters should be taken into account whenassessing coals for particular purposes, and not one isolatedparameter, and stressing that part of the inertinite may bereactive. The variable behaviour of macerals in coals duringtheir utilisation will be examined in Sections 7.4, 8.3 and 9.4.

The CSN, volatile matter and calorific value are ofcommercial importance and are already used as classificationparameters in various national classifications and theinternational classification of hard coals. A slight

Table 12 ECE classification of brown coals* (ECE, 1957)

complication in the coding system occurs for volatile matter,as the coding interval changes. Volatile matter (daf) is codedby intervals of 2% for coals down to 10%, but with aninterval of 1 % when the volatile matter is less than thisvalue. Some specific grade and environmental informationabout a coal is provided by the inclusion of the ash andsulphur parameters. Ash and sulphur are also of commercialimportance.

A numerical system to classify coals was chosen to avoid thedrawbacks of a descriptive system which could easily bemisinterpreted or give rise to ambiguities (ECE, 1982b).However, a named system, such as the ASTM, does have anadvantage in that it first provides a general impression of thecoal, especially its rank. Names facilitate (especially verbal)communication as it is easier to talk of say, an Australiancoking coal, than to quote the relevant code number 12 1516 24 05 04 35. The coding system devised is fairly easilydecoded as the code number for most of the parameters waschosen so that the value of each property, over a narrowrange, could easily be ascertained from the code number.However, the codification is fairly complicated.

Thus the main drawbacks of the codification can be summedup as follows:

- complicated;- needs decoding;- 'inertinite' problem;- some parameters, such as reflectogram, impart little useful

information.

6.5.3 International classification of browncoals

The existing international classification of brown coals wasdevised in the 1950s and published in 1957 (ECE, 1957). Itcovers coals with a gross calorific value (maf) of lessthan 5,700 kcal/kg (23.86 MJ/kg). Brown coals are firstdivided into six classes according to their total moisturecontent (ash-free basis of run-of-the-mine coal). Moisturewas discussed in Section 2.8. The coals are then divided

Group parametertar yield, daf %

25>20-25> 15-20>10-15<10

Class number

Class parametertotal moisturetash-free run-of-mine coal

Group number

4030201000

%

Code numbers

10401030102010101000

10

<20

11401130112011101100

I!

>20-30

12401230122012101200

12

>30-40

13401330132013101300

13

>40-50

14401430142014101400

14

>50-60

15401530152015101500

15

>60-70

Coals with a gross calorific value (maf) below 5,700 kcal/kg (23.86 MJ/kg) (30°C, 96% relative humidity). For internal purposes, coals witha gross calorific value (maf) over 23.86 MJ/kg, considered in the country of origin as brown coals but classified as hard coals for internationalpurposes, may be classified under this system, to ascertain, in particular, their suitability for processing.Total moisture refers to freshly mined coals. When total moisture content is over 30%, gross calorific value is always below 23.86 MJ/kg.

Classification systems

Table 13 ISO classification of brown coals and lignites (International Organization for Standardization, 1974)

Group parametertar yield, daf %

Group number Code numbers

25>20-25>15-20

1413121110

2423222120

3433323130

4443424140

5453525150

64636261

mClass number

Class parametertotal moisture content(ash-free) run-of-mine coal %

1

<20

2

>20-30

3

>30-40

4

>40-50

5

>50-60

6

>60-70

into a further five groups according to their tar yield (daf,from low temperature carbonisation). A four digit codenumber represents the coal, with the first two digitsindicating the class and the second two digits the group(see Table 12).

In 1974, an international standard (ISO 2950) for theclassification of brown coals and lignites by type(International Organization for Standardization, 1974) waspublished. The same two properties (total moisture and taryield) are used to divide the coal into the same six classesand five groups; but instead of a four digit code, a two digitcode is used (see Table 13).

These two classifications are:

- commercial;- for brown coals and lignites only;- for single coals;- coded;- simple and easy to use.

Both these classifications cover only the lower rank coals.Although the ECE classification covers brown coals, thecalorific value chosen as the boundary (23.86 MJ/kg) meansthat the lignites, subbituminous C and some of thesubbituminous B coals of the ASTM classification areregarded as brown coals. However, the ECE classificationdoes allow coals with a higher calorific value to be included,if the coals are regarded in the country of origin as browncoals. There is no international standard covering hardcoals. The ISO classification of brown coals and lignitesdoes not define a boundary between these coals and the hardcoals. It states that 'until reliable parameters fordifferentiation of brown and hard coals are worked out andconfirmed, coals considered in each country as brown, on thebasis of a number of other characteristics, should beclassified as brown coals regardless of their calorific value';that is, it includes cases where the calorific value is higherthan 23.86 MJ/kg.

Neither the ECE nor the ISO classifications define theboundary between peat and brown coals. Since the transitionbetween peat and brown coal (and between brown andhard coals) takes place gradually, it is difficult to fix a

precise boundary. The ECE classification considers thatthe boundary between peat and brown coal is of no majoreconomic importance, since the coal situated close to theboundary is of purely local importance and would not becommercially traded in the international market(ECE, 1957).

The ECE classification was developed for the two main usesof brown coal at that time, namely combustion (moisture)and chemical manufacture (tar yield). Moisture correlateswith calorific value for the lower rank coals and so canindicate the value of the coal as a fuel (Ode and Gibson,1960). However, brown coals with different properties andhence technological applications can be placed in the samegroup (Suess and others, 1986). Therefore additionalparameters may be required as brown coals are used moreextensively in the newer conversion processes (Berkowitz,1979). No grade or environmental information is included(Eriksson and others, 1981). Ash is of particular practicalimportance for brown coal (ECE, 1957). Finally, theclassification requires decoding and the actual moisturecontent and tar yield cannot be easily ascertained from thedigits in the code number.

The main disadvantages of the system can therefore besummarised as follows:

inadequate for liquefaction and gasification;- no environmental information;- no grade information;- no definition of peat/brown coal boundary;- needs decoding.

6.6 Modified international systems

6.6.1 Old Australian classification of hardcoals

The 'Classification system for Australian hard coals',specified in AS 2096: 1977 (Standards Association ofAustralia, 1977) is a modification of the 'Internationalclassification of hard coals by type'. It was intended to becompatible with the international classification in order tohelp the international trade in Australian coals. It has nowbeen superseded (see next section) and since most of the

Classification systems

Table 14

Coal class

Class

1234A4B56789

Australian classification system

volatile matter%, dmmf

<1010.1-14.014.1-20.020.1-24.024.1-28.028.1-33.0>33.0>33.0>33.O>33.O

gross calorificvalueMJ/kg, daf

>33.8232.03-33.8228.43-32.0227.08-28.42

for hard coals (Standards

Coal group

Group

01234

crucibleswellingnumber

0-0.51-22.5-44.5-66.5-9

Association of Australia, 1977)

Coal sub-group

Sub-group

012345

Gray-Kingcoke type

AB-DE-GG1-G4G5-G8G9

Ash number

Ashnumber

(0)(1)(2)(3)(4)(5)(6)(7)(8)

ash%, dry

<4.04.1-8.08.1-12.012.1-16.016.1-20.020.1-24.024.1-28.028.1-32.0>32.0

Hard coals are coals with a gross calorific value (daf) of 27.08 MJ/kg or more

points discussed in Section 6.5.1 are applicable, it will onlybe briefly discussed.

The classification (see Table 14) is:

- commercial;- rank-based;

for hard coals only;- for single coals;- includes some grade and environmental information (ash

number);- coded.

The Australian classification differs in several ways from theexisting international classification of hard coal. Aninteresting feature is the inclusion of an ash number andthere are no ash constraints on the coal being classified(Davis, 1970). There are some differences in the classes,presumably to suit Australian conditions. Volatile matteris given on a dmmf basis since this basis provides a moreaccurate expression of volatile matter for high ash coals thana daf basis (see Section 2.1). Australian Gondwanan coalscan have high ash yields compared to similar Laurasian coals(Synman and others, 1985; Ward, 1984b). The term 'specificenergy' (calorific value) is employed to be consistentwith the use of SI units. The gross specific energy is givenon a daf basis, instead of a maf basis. Calculation of thelatter basis requires a determination of the moisture-holdingcapacity of coal, a test that was only rarely performed inAustralian laboratories (Davis, 1970) at the time theclassification was developed. By the use of an establishedrelationship between calorific value on a maf and dafbasis, equivalent figures for the class limits of theinternational classification are used in the Australianclassification. Also, instead of a choice of parameters theAustralian system uses the CSN and the Gray-King coketype, tests which were more widely applied in the Australianlaboratories than the other two tests specified in theinternational system.

Like the international classification of hard coals, care isrequired in the interpretation of the code number when the

classification is applied to petrographically dissimilar coals tothe Australian coals, that is, when comparing coals for thesame application (by their code number) one needs to knowwhether the code number refers to a Gondwanan orLaurasian coal.

Thus the main disadvantages of the Australian classificationcan be summarised as follows:

- does not cater adequately for all coal types;- inadequate for coals for liquefaction and gasification;- no environmental (sulphur) parameter;- excludes some lower rank coals that are 'hard';- needs decoding.

6.6.2 New Australian classification andcodification

The 'Classification and coding systems for Australian coals',AS 2096: 1987 (Standards Association of Australia, 1987)has replaced the Australian classification of hard coals (seeprevious section). It was devised to conform in spirit withthe new international codification (see Section 6.5.2), butaltered to suit Australian coals. Unlike the internationalcodification, the new Australian classification covers coals ofall rank.

The Australian classification (see Table 15) is:

- commercial;- rank-based;

includes grade information;- includes environmental information;- includes whole rank range;- for single coals;- for in-situ, raw and washed coals;- for all coal utilisation processes;- coded.

Coals are classified into two classes, the higher rank coals(which are normally transported) and the lower rank coals(which are usually used or upgraded in the vicinity of the

Classification systems

deposit because of their high bed moisture). Coal is definedas higher rank if it has a gross calorific value (specificenergy, maf) of 21 MJ/kg or more and a gross calorific value(daf) of 27 MJ/kg or more. Lower rank coals are coals witheither a gross calorific value (maf) of less than 21 MJ/kg or agross calorific value (daf) of less than 27 MJ/kg. The term'afm' (ash-free, moist) is used in the standard instead of maf.

Within these two classes, separate coding systems have beendeveloped to describe the coals. The first three codingparameters are the same for each class, namely the meanmaximum reflectance of vitrinite, gross calorific value (daf)and volatile matter (daf). The fourth parameter is the CSNfor higher rank coals and bed moisture for the lower rankcoals. The last two parameters are again common to bothsystems, being the percentage of ash and total sulphur, bothon a dry basis. Each coding system for the two classescomprises eleven digits indicating the quantitative range ofthe six parameters (see Table 15). When the code number iswritten, spaces are left between the digits for each of theparameters. As a consequence, the difference between ahigher and a lower rank coal is easily recognisable as thelower rank coals have only one digit for the first parameter,whereas the higher rank coals are given two digits for thesame parameter. When some of the analytical data requiredfor coding is unavailable, a partial coding of the coal can beprovided using 'X' in place of the digits for the unknownparameter(s) (as is allowed in the international codification).All the classification parameters are determined using theappropriate Australian standard. These standards must befollowed as different methods could give different results(see Sections 2 to 4), thereby leading to a 'misclassification'

of the coal. Since some methods used for testing Australiancoals do not apply to coals of all ranks, the class of the coalmust be known before the relevant standard method can beapplied.

Two acronyms are suggested to make the coding parametersand their order easier to remember. These are REVCAS forthe higher rank coals and REVMAS for the lower rank coals,where R stands for the mean maximum Reflectance ofvitrinite, E for specific Energy, V for Volatile matter, C forthe Crucible swelling number, M for bed Moisture, A forAsh and S for the total Sulphur.

It was recognised that at times it is necessary to classifycoals in terms of the traditional names anthracite,semi-anthracite, bituminous coal, subbituminous coal andbrown coal. For these purposes the Australian standardquantitatively defines these named classes in terms of volatilematter (daf), calorific value (maf) and crucible swellingnumber, where appropriate (see Table 16).

The classification is primarily intended for commercial andindustrial purposes and in reserve estimation. Althoughbased on the international codification, there are importantdifferences between the two systems. The Australianclassification covers the whole rank range of coals. A lowercalorific value is defined for separating the lower from thehigher rank coals, a definition better suited to Australianconditions (see Section 6.5.2). Since two bases for calorificvalue are used, the reflectance is unnecessary and thus anyconflict between reflectance and calorific value for definingthe boundary or class is avoided. For example, some

Table 15 Classification and coding systems for Australian coals (Standards Association of Australia, 1987)

VitriniteRmax

(higher i

code

030405-1920-

Cruciblenumber(higheri

code

012_89

reflectance,

•ank coals)

%

0.3-0.390.4-0.490.5-0.59-1.9-1.992.0-2.09-

: swelling

rank coals)

numbers

0 or 0.51 or 1.52 or 2.5-8 or 8.59

Vitrinite (orreflectance,(lower rank

code

012345

precursor)iMnax

coals)

%

0.0-0.090.1-0.190.2-0.290.3-0.390.4-0.490.5-0.59

Bed moistureas sampled(lower rank coals)

code

2021-6465-

%

20-20.921-21.9_64-64.965-65.9-

Gross calorificvaluedaf

code

151617-3536-

Ashdry

code

0001—2930-

MJ/kg

15-15.9816-16.9817-17.98-35-35.9836-36.98-

%

0-0.91-1.9

-29-29.930-30.9-

Volatile matterdaf

code

080910—4950-

Total sulphurdry

code

0001-3132-

%

8-8.99-9.9

10-10.9-49-49.950-50.9-

%

0-0.090.1-0.19-3.1-3.193.2-3.29-

Higher rank coals are coals with gross calorific value (maf) >21 MJ/kg and gross calorific value (daf) >27 MJ/kgLower rank coals are coals with gross calorific value (maf) <21 MJ/kg or gross calorific value (daf) <27 MJ/kg

Classification systems

Table 16 Definition of traditional coal names(Standards Association of Australia, 1987)

anthracitesemi-anthracitebituminous coal

subbituminous coal

brown coal

Volatilematter%, daf

<88-13.9>14

GrosscalorificvalueMJ/kg, maf

and >26.5(>2419-23.98or19-26.48<19

Crucibleswellingnumber

provided >1)

provided 0 or 0.5

Australian coals, despite having a mean random reflectanceof 0.6%, have a gross calorific value (maf) of more than24 MJ/kg (ECE, 1986). The calorific value chosen is also inline with the previous Australian classification of hard coals.

One important difference between the two classificationschemes is that no specific type (petrographic composition)information is included in the Australian system. Sincepetrographic analysis is not sufficiently reproducible and therelationship between petrographic composition andtechnological behaviour is different for Australian (and otherGondwanan) coals compared with the Laurasian coals fromEurope and North America, it was decided not to include theinertinite content as a classification parameter. Also, theclassification is intended for single coals, not blends, and forin-situ, raw and washed coals (AS 2096: 1987). Thereforethere was no need to include the reflectogram as a parameter.

The only petrographic parameter that is included is vitrinitereflectance. Australia has opted for the mean maximumreflectance of vitrinite (as recommended by the ICCP),instead of mean random reflectance. However, the

determination of mean random reflectance is probably easierto automate {see Section 4.2), A code interval of 1% hasbeen chosen for the volatile matter compared to 1% for up to10% volatile matter and 2% for more than 10% in theinternational codification.

The coding system in the Australian classification has beenchosen so that the value of each property, over a narrowrange, can be easily ascertained directly from the codenumber. Hence, it is more easily comprehensible. Using theREVCAS and REVMAS codes enables six importantproperties of coal to be expressed in a shorthand fashion.However, the classification still:

- does not cater adequately for all coal types;requires decoding.

6.6.3 German international classification ofhard coals

The Deutsches Institut fiir Normung (1976) has published the'International classification of hard coals by type' as aGerman standard (DIN 23003). Basically no changes havebeen made, except that the calorific value has been convertedinto SI units. To avoid the problem of having a choice ofparameters, the Germans, like the Australians (Section 6.6.1)have opted for the crucible swelling number as the groupparameter. To indicate the subgroup, the Germans decided touse the dilatation behaviour instead of the Gray-King coketype test chosen by the Australians. However, the Rogaindex and Gray-King coke type are also given in the DINstandard. The various methods for determining theclassification parameters are specified in the relevant Germanstandards, which are compatible with the equivalentinternational (ISO) standards.

The international classification of hard coals has already beendiscussed in Section 6.5.1.

7 Combustion

Historically, the first main use of coal was for combustion,and this still remains the principal market for coal today.Conventional classification systems are thus often primarilyconcerned with coal combustion.

It has been suggested that combustion is the least demandingof all coal utilisation processes on the quality of coal, sincethere is such a variety of equipment and operating conditionsavailable (BCRA Quarterly, 1986). Generally, coals of allrank and types can be burned. Over the years, a number ofempirical correlations and analyses have been developed,enabling equipment to be designed to burn specific types of

coal. Table 17 lists the effects of some coal characteristicson the different equipment used in power plants. Todaythere is a need to burn coals which are different from thosefor which the equipment was designed and in anenvironmentally acceptable manner. A classification systemshould therefore be able to assess whether a coal is likely tobe suitable for a particular installation. However, it shouldbe emphasised that a classification is not the same as a coalspecification. A classification is only for the initialevaluation of a coal, whereas a specification is much moredetailed. It will specify the properties of coal (and theirvalues) that will be needed to achieve an acceptable

Table 17 Effects of coal characteristics on different equipment in power plants (Myllynen, 1988)

cv M ash VM pet.comp.

Cl N HGI ash ashanalysis fusion

coal stockpileconveyor system& coal siloscoal millsburnersfurnaceseconomiserspreheatersESPash handling systems

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

CV calorific valueM moistureash ash yieldS sulphur contentVM volatile matterpet. petrographic compositioncomp.Cl chlorine contentN organic nitrogen contentHGI Hardgrove Grindability Indexsize size distributionESP electrostatic precipitators

Combustion

Table 18 Indicative bituminous coal quality specifications for utilities

UK* Netherlands* Belgium* Sweden* Finlandt Japan*

CV, minmoisture, total,maxash, maxVM, minS, maxFuel ratio,maxN, maxCl, maxHGI, minAFT, minIDTHTFTash analysisNa20, maxsize

MJ/kg

%ad%ad%adFC/VM

%db%db

°C

°c

25.12 ar

20302.53

0.3550

1120

27.63 ad12

12251

50

107512501500

30

25.12 ar13

20251.5

dbdbdb

15250.8

60

1350 1300

1400

50

23.86 net14

1535 ar1

45

1200

50

25.12 ad10

20

12.5

1.80.0545

12001300

240

* Coal Marketing Manual (1986)t Becke(1988)Utilities can specify additional properties

combustion performance in a particular installation. It hasbeen suggested that detailed coal specifications are toorestrictive and that broader ones will open up the market.Computer programs can help evaluate the wider range ofcoals, with consequent savings (Power, 1987).

Since classification starts at the producer's end andspecification at the user's end of the market chain,classifications and specifications will need to use the sameparameters if they are to be effective tools of trade. It istherefore worth considering the properties most frequentlyrequired in coal specifications for power plants, as these canindicate which properties would be most useful in acommercial classification system. Table 18 lists theproperties most frequently required for bituminous coals.This table is only indicative; the values required will dependon the type of installation, and additional parameters can berequested by some utilities. Certainly, different values willbe specified by utilities burning low rank coals and extraparameters may also be required. This chapter will examinethe significance of these coal properties in the combustionprocess and some empirical correlations for predicting thereactivity and combustion behaviour of coal. The effect ofcoal properties on pollution control techniques, such as theresistivity of fly ash, will not be included. Mathematicalmodels for predicting coal combustion behaviour are alsooutside the scope of this review.

Combustion is a complex process. The classic modelassumes combustion takes place in three stages:devolatilisation, combustion of the volatile matter and charburnout (combustion of the devolatilised coal). Also takingplace are chemical reactions, mainly between the constituentsof the ash (Blackmore, 1985). There are three majormethods of burning solid coal, namely in fixed beds, such asstokers, in fluidised beds or as pulverised fuels (pf). Most ofthe coal used today to generate electricity is consumed as

pulverised fuels (IEA Coal Industry Advisory Board, 1985).The combustion conditions in these three processes vary,especially heating rate, burning temperature and time. Fixedbeds have a slow heating rate (a few K/s) and combustiontime varies from a few minutes to hours, depending on coalparticle size. In fluidised-bed combustion (fbc), heating ratesare generally about 103 to 104 K/s (depending on particlesize), burning temperatures between 800 and 900°C andburning time is in minutes. The heating rates quoted aretypical for pressurised fbc; lower heating rates can occur inatmospheric fbc installations. Pulverised fuel (pf)combustion has the highest heating rates (about 104 to 106K/s), burning temperatures of over 1500°C and a burningtime of fractions of a second (Essenhigh, 1981; Jiintgen,1987a). Since the combustion conditions vary considerably,the importance of certain coal properties in each process willalso vary, with consequent implications for classification.

A number of reviews have been published relating coalcharacteristics to combustion. These include reviews byEssenhigh (1981), Ceely and Daman (1981), Juntgen (1987a,1987b) and BCRA Quarterly (1986, mainly covers coals ofbituminous rank and higher). A separate IEA Coal Researchreport reviews the literature on pulverised coal combustion(Morrison, 1986).

7.1 Rank effectsIt is generally agreed that rank is important to theperformance of coal in combustion (for example, BCRAQuarterly, 1986; Blackmore, 1985; Essenhigh, 1981). Forexample, rank primarily determines combustibility andreactivity in pulverised coal combustion (IEA Coal IndustryAdvisory Board, 1985), although other properties, such ascaking capacity and petrographic composition also play apart. Many attempts have been made to establish empiricalcorrelations between rank parameters and parameters of

Combustion

combustion behaviour, such as the reactivity of coal orignition temperature. It is worth noting that particle size hasan important influence on combustion rates and that thecorrelations obtained with rank parameters are generallyvalid only for coals with similar particle size.

The combustibility or reactivity of a coal is characterised bytwo factors (Wall, 1985):

1 The volatile matter yieldThe ignition and burning of volatiles is an important stepin coal combustion. Both rank and the amount ofvolatiles present influences the ignition of volatiles. Itmight be expected that correlations exist between thecomposition of volatiles and their ignition behaviour, butunfortunately no satisfactory correlations are available.Tar yield (the main volatile product of pyrolysis),although influenced by rank, cannot be correlated withrank alone (Juntgen, 1987a; Morrison, 1986).

2 The reactivity of the charChar reactivity generally increases with decrease in rank(in pf combustion) (Cudmore, 1984; Morgan andRoberts, 1987), so that the rate of combustion issimilarly dependent on rank (BCRA Quarterly, 1986;Juntgen 1987a). However, Cumming and others (1987)found that the rank was not an accurate guide to thecombustion rate of high volatile bituminous coals.

The efficiency of combustion has also been correlated withrank. In fluidised beds, combustion efficiency (determinedfrom unburnt fuel loss) decreased with increasing rank(determined by vitrinite reflectance and carbon content)(Vleeskens, 1983a, 1983b; Vleeskens and Nandi, 1986).Blends of coals were also shown to behave additively;combustion efficiency was intermediate between those of theconstituent coals, in linear proportion to the blending ratio.However, the correlations do depend on the combustionconditions. Lee and Whaley (1983) found that in pfcombustion, the measured combustion efficiencies of coalblends were in every case, lower than the calculatedefficiencies. Vleeskens and Nandi (1986) found that in pfcombustion, the percentage of inert constituents (ash andinertinite) was of more significance than rank in predictingcombustion efficiency. However, rank had more influenceon the combustion properties of pulverised coal than maceralcomposition (for example Shibaoka and others, 1985b;Yamada and Matsuoka, 1986). Only for bituminous coalswas the influence of the inertinite content also significant.The behaviour of inertinite during pf combustion varies withrank (Jones and others, 1985), which will be discussed inSection 7.4.

From their higher reactivity, one might expect that the lowerrank coals would be the preferred feedstock for steamraising. However, bituminous coals are usually preferredbecause the lower rank coals have lower calorific values andare less efficient as an energy source. With the high risk ofspontaneous combustion during transport, handling andstorage, use of the lower rank coals is generally restricted tolocal usage (Cudmore, 1984; Dunstone, 1985; Sullivan,1986). This illustrates the fact that, when evaluating coalsfor combustion, a single classification parameter should not

be interpreted in isolation, without reference to the otherparameters.

To sum up, rank does have an important influence on thecombustion properties and behaviour of coal, suggesting thatit should be included in a classification system. A number ofproperties reflect the rank of coal and these will be discussedin the appropriate following sections.

7.2 Chemical composition andproperties

7.2.1 Calorific value

The calorific value (or specific energy) is the majorparameter in the evaluation of coals for combustionapplications (Day and others, 1979; Merrick, 1984) and is themost commonly used benchmark of coal quality and hencethe economic value of a coal. It can also be used as a rankparameter (see Section 2.7 where its determination is alsodiscussed).

The maximum theoretical amount of energy available froma coal for the production of steam is calculated from thecalorific value and consequently, the calorific value isused by boiler operators to determine the quantity of coalrequired for a boiler to achieve the desired thermal output(Black'more, 1985; Wall, 1985; Wall and others, 1985).

The calorific value is one of the more common parametersused in classification systems today, and its use is stillcontinued in the new Australian and new ECE'classifications'. Other newer classifications have excludedthe calorific value; these include a suggested classificationfor Indian coals (Tumulumi and Shrikhanda, 1985) and theVAWST classification of Chinese coals for power generation(Xu and others, 1986; Sun and Liu, 1985). Both of theseclassifications include volatile matter, ash and moistureparameters, from which the calorific value can be estimated(see Section 2.7). However, the net calorific value isrequired in the VAWST classification for the calculation ofthe 'equivalent' ash yield and sulphur content parameters.

The amount of combustible ballast (that is, the mineral (ash)and water (moisture) contents) in coal influences the calorificvalue, with high ash and moisture contents decreasing itsvalue. Therefore, if the calorific value is included as aclassification parameter, and is quoted on a daf or dmmfbasis, both total moisture and ash parameters may also benecessary. However, if the calorific value is quoted on ammmf or maf basis, then an ash parameter may be sufficient.

The calorific value is, however, not directly related to thecombustibility and reactivity of the coal. For example,although the calorific value of inertinite-rich andvitrinite-rich isorank (as measured by vitrinite reflectance)coals can differ by only a small amount (about 2 MJ/kg)(Pearson, 1985), the combustion characteristics of such coalscan be quite different (see Section 7.4). This has led toclassification systems being devised that include petrographic

Combustion

parameters, as well as the calorific value (for example,Uribe and Perez, 1985; the new international (ECE)codification).

In industrial installations the net calorific value is of moresignificance than the gross calorific value since it allows forthe loss of heat resulting as the latent heat of vaporisation ofsteam. Most classification systems however, use the grosscalorific value. Since the net calorific value can becalculated from the gross calorific value, and vice versa,either value could be used as a classification parameter,provided both the hydrogen content and total moisture, asfired, are known (see Section 2.7).

To conclude, calorific value is an important parameter incombustion. Like all classification parameters it should beinterpreted in context with other parameters, such as ash ormoisture.

7.2.2 Volatile matter

The volatile matter yield is an important property incombustion applications, providing a rough indication of thereactivity or combustibility of a coal (Blackmore, 1985;Sanyal and Cumming, 1985; Wall, 1985). It influences thedesign and operation of furnaces, boilers and fluidised-bedcombustors (for example, BCRA Quarterly, 1986; Gannonand others, 1987; Sanyal and Cumming, 1985) and thesuitability of candidate coals.

An important step in combustion is the devolatilisation,ignition and burning of the volatiles. Morrison (1986)reviews these processes in pf firing applications. The massof volatiles evolved varies with rank (as indicated by carboncontent), decreasing with increasing rank for a given set ofconditions. As the rank approaches anthracite, the ignitiontemperature rises and ignition becomes more difficult. Inorder to assist flame stability, volatile matter yield (daf)should preferably be at least 22% in pf combustion(Myllynen, 1988). However, the volatile matter (daf) ismuch less important than the volatile matter as fired,especially for high ash, high moisture coals. Volatile matteralso influences the length of a flame (Gannon and others,1987; Sullivan, 1986). No general correlations exist betweenthe volatile matter of coal and the combustion behaviour,since other properties also influence these processes. Thevolatile matter of coal cannot be directly related to flamestability or burnout (Pohl, 1988). Yields of volatiles areheavily dependent on the combustion process conditions,such as the final temperature reached, heating rate, particlesize and pressure (Jiintgen, 1987a; Morrison, 1986). Thisincreases the difficulties of finding a general correlation.

Differences in the combustion behaviour of coals with thesame volatile matter yield have been observed and attributedto differences in their maceral composition (see Section 7.4).Bengtsson (1986), for example, found that the release ofvolatile matter during combustion was related to the rank,maceral group and maceral distribution. Volatile matter isalso one of the factors governing the reactivity and burnoutefficiency of char (Eklund and others, 1987; Jiintgen, 1987a).Char reactivity is one of the main factors determining

combustion efficiency. Unfortunately, there is no standardtest for its determination; volatile matter can provide only aguide to its reactivity.

Since volatile matter is dependent on the pyrolysisconditions, the mass of volatiles evolved during combustionis not equal to that predicted by standard proximate volatilematter tests. These tests (see Section 2.6) use relatively lowheating rates and final temperatures; in pf combustion, forexample, heating rates of 106 K/s and final temperatures of1500°C or more are commonly reached.

Since it is the proximate volatile matter that is used inclassification systems, attempts have been made to relate the'true' (high temperature) volatile yield to the proximatevolatile matter. Terms such as the Q factor (Essenhigh,1981) have been developed. Work carried out at theInternational Flame Research Foundation, for example, usingan isothermal plug flow reactor showed that the ASTM testfor volatile matter underestimated the 'true' volatile yield ofcoals (Morgan and Roberts, 1987). Ratios for volatile matterat 1973 K to those from the ASTM test ranged from 1.5 to2.3 for the coals studied. Curves were derived that could beused to predict the 'true' volatile yield as a function of thefinal temperature. The prediction of the rate of volatilerelease was also investigated.

Gannon and coworkers (Gannon and others, 1987; Neoh andGannon, 1984) have correlated the 'true' volatile yields tothe elemental composition of coals (as determined instandard ultimate analysis). They found that, in terms ofvolatile yield, at high temperatures and heating rates, coalsrespond more according to their elemental composition thanto their petrographic makeup. The mass yield of volatilescorrelated best with the parameter H+2O/C+S (where H, O,C and S are the hydrogen, oxygen, carbon and sulphurcontents, respectively) (see Figure 6). This figure also showsthat volatile yield is dependent on the final temperature. Agood correlation with vitrinite reflectance was also obtained,but no apparent relationship with maceral composition forthese vitrinite-rich coals was observed. Since only a smallset of thirteen US coals, ranging in rank from lignite toanthracite was used, this parameter needs verification with alarger set of coals. If found to be valid then a classificationsystem based on the ultimate analysis of coal could beconsidered. 'True' volatile yield could be estimated usingthe appropriate regression equation for the temperature ofcombustion. Proximate volatile matter has also beencorrelated with elemental composition (see Section 2.6).Thermogravimetric methods for determining the burningprofile of coal, which is influenced by the volatile matter,will be discussed in Section 7.5.1.

Volatile matter contains both combustible andnon-combustible (for example, carbon dioxide and water)compounds. Eklund and others (1987) suggest that thecombustible volatile matter should provide a bettercorrelation with ignitibility of coal than proximate volatilematter. They have developed a method for its determinationwhich involves flash pyrolysis with flame ionisationdetection. The calorific values of volatiles can besignificantly different for coals with the same proximate

Combustion

volatile matter yield (Sanyal and Cumming, 1985), probablybecause of differing ratios of combustible to non-combustiblecomponents. This suggests that maybe combustible volatilematter would be a better parameter for a coal combustionclassification. The Chinese VAWST classification systemfor power generation coals includes such a parameter (Sunand Liu, 1985).

Current classification systems use the proximate volatilematter (generally daf) to indicate the reactivity of coals, asit can be of more significance in other applications of coal

than the combustible volatile matter. Hao (1983) found,however, that proximate volatile matter (daf) was insufficientfor evaluating the reactivity and combustion characteristicsof high ash bituminous coals and low volatile anthracites.

In industrial installations, it is more usual for blends of coalto be used than single coals. Proximate volatile matter of acoal blend may not be a reliable guide to its combustionbehaviour, if the blend contains coals with very differentvolatile matter yields. Jiintgen (1987b) discusses work whichshows that the burnout of the highly reactive coal isrelatively intensified at the beginning because the lessreactive coal consumes less oxygen. Burnout of the lessreactive coal is then inhibited because the overall oxygenconcentration is reduced by the fast burnout and high oxygenconsumption of the highly reactive coal.

Instead of volatile matter alone, the fuel ratio (that is, fixedcarbon divided by volatile matter) can be used as a measureof combustion reactivity. The fuel ratio provides anindication of the relative proportions of char to volatiles.

Figure 6 Correlation of volatile yield with atomic ratio ofcoal (Neoh and Gannon, 1984)

Although correlations between the fuel ratio and carbonburnout have been found (for example Baker and others,1986), there are exceptions (Oka and others, 1987; Smith,1985). A higher fuel ratio does not necessarily indicatea coal of lower reactivity and high carbon burnout (seeFigure 7). This is not really surprising since both volatilematter and fixed carbon determinations relate to laboratorytest conditions. As previously noted, proximate volatile yieldis generally lower than the 'true' volatile yield. Similarly,proximate fixed carbon makes no allowance for the differingreactivity of chars formed from different coals (Oka andothers, 1987; Smith, 1985). The fuel ratio can also beunsuitable for low rank coals (Kiss, 1982). Therefore, use ofthe fuel ratio as a classification parameter could be inaccurate.

Figure 70.5 1.0 2.0 4.0

Fuel ratio, fixed carbon/volatile matter.Fuel ratio as an indicator of coal reactivity(Smith, 1985)

7.2.3 Ash and mineral matter

The terms mineral matter and ash (see Section 2.9) are oftenused interchangeably in the combustion literature. Althoughash content is referred to in the literature, coal does not'contain' ash as was mentioned earlier; ash is the residue leftafter combustion and its formation is influenced mainly bythe chemical composition, thermal properties and mode of

Combustion

occurrence of the mineral matter in coal. Ash differs in bothmass and composition from the mineral matter from which itwas formed. For a more comprehensive review of thesubject of mineral matter and ash in coal see, for example,Jackson (1987), Raask (1985), Singer (1981) and Vorres(1986). Badin (1984) reviews correlations of mineral matter(ash) with coal combustion chemistry.

Mineral matter (ash) is not merely an inert diluent of coalduring combustion. It influences the reactivity of coal,lowering the calorific value and delaying ignition. It mayinfluence the amount and chemical composition of thevolatiles (see Section 2.6) and the mechanical and physicalproperties of coal, inhibiting its caking and swellingproperties (see Section 3). The burnout of char is affected ina complex way by the mineral matter composition and form(Gray, 1987a). Vleeskens and Nandi (1986) found that ashhas more influence on char burnout under pf conditions thanunder fbc conditions. Under the former conditions, unburntcarbon increased linearly with ash. A high ash coal can alsoinduce flame instability in pf boilers (Myllynen, 1988; Wall,1985).

Mineral matter also influences combustion by catalysingpyrolysis and char oxidation (Gray, 1987a). The effects areparticularly significant in low rank coals that contain a highconcentration of calcium ions, which have been identified asthe most important catalysing element (Essenhigh, 1981;Morgan and Scaroni, 1985; Morrison, 1986). Catalyticeffects of minerals in coal at the high temperatures pertainingin pf combustion are uncertain, although a reduced influenceis predicted at higher temperatures (Morrison, 1986). Thelatter review also discusses the thermal, radiation andhindrance effects of mineral matter and its influence on thechar particle size. Thus the behaviour of mineral matter incoal can influence the design of furnaces and boilers and thesuitability of a candidate coal. Therefore knowledge of themineral matter content is important in combustion.

Only limited information can be obtained from standardlaboratory analysis of coal in relation to the likelyenvironmental consequences of combustion. The bottom andfly ashes produced have to be collected and disposed of,frequently by dumping. However, the composition of theash, rather than the yield, is thought to be of moresignificance for the reuse and dumping of ash. An ashanalysis will also provide some information in relation to thelikely collectability of fly ash by electrostatic precipitators(Myllynen, 1988; Paulson and others, 1986). In general,however unless operating performance data are available, itis necessary to conduct a series of furnace tests andlaboratory analyses on the coal fly ash to evaluate therelevant properties in order to predict performance.

Instead of using the mineral matter content, the ash 'content'has been used as a classification parameter, for example inboth the old and new Australian classifications. Tumuluriand Shrikhanda (1985) also propose using ash as one of thethree parameters in their simplified classification of Indiancoals. In West Germany, it is common practice to use theamount of incombustible 'ballast' (that is, the mineral matter(ash) and total moisture content) to classify the coals.

Instead of ash, the VAWST classification of Chinese coalsfor power generation requires the 'equivalent ash content'(defined as 1000 multiplied by the ash content divided by thenet calorific value) (Sun and Liu, 1985). However, for aclassification to be applicable to other uses of coal, ash (asdetermined by proximate analysis) is probably sufficient.

Ash is commonly used as an indication of the grade orquality of a coal since it provides a measure of theincombustible material. It is used commercially to indicatethe economic value of a coal and, as such, is important in thetrading and marketing of coal. Although a number ofworkers (for example Gray, 1987a) believe that coalproperties should be expressed on a dmmf basis rather than adaf basis (see Section 2.1), recent studies of combustion tendto use a daf basis. The daf basis is also generally used in thecommercial sector in coal specifications for when theultimate analysis is given. If classification parameters aregiven on a daf basis, then it can be argued that an ashparameter is required. For example, it could help explain alow volatile matter or low calorific value. It can be notedthat, out of convenience, results quoted on a mmf basis cansometimes actually be ash-free (Lavill, 1988). This practice,that (incorrectly) assumes that the relationship of mineralmatter to ash is equal to unity, is often hidden.

From an economic point of view, low ash coals are preferred.The ash (mineral matter) yield is not so important influidised-bed combustors (Reid, 1981) and coals with up to70% ash can be burned (Cudmore, 1984). There is evidencethat some ash is needed to protect the firebars in industrialstokers (BCRA Quarterly, 1986). However, ash is morecritical in pf boilers, where a yield of below 20% is usuallypreferred (Cudmore, 1984).

It is thought that the composition of the ash, rather than theamount, is of more significance in predicting boiler operatingproblems (IEA Coal Industry Advisory Board, 1985) andextensive research has been carried out to investigate theeffect of coal ash on combustion systems. Some of this workis reviewed by Reid (1981). The principal ash-relatedproblems are corrosion, erosion, slagging and fouling.Slagging and fouling have deleterious effects on the heattransfer, heat flux and gas flow patterns in pf boilers (Reid,1981) and the deposits can plug the gas passages.

There is a need to be able to classify coals in order to predictslagging and fouling propensity. Slagging and fouling havebeen related to ash composition. Bryers and Walchuk (1985)for example, have investigated the influence of pyrite in USbituminous coals on furnace slagging. However, the meltingproperties and viscosity of molten ash are not a simplefunction of composition. A number of correlations havebeen proposed but these have had limited application. Theseinclude indices such as the base-to-acid ratio, thebase-to-acid ratio multiplied by the sodium or sulphurcontent or ratios such as the iron-to-calcium or thesodium-to-ash ratio. Borio and Levasseur (1986) and IEACoal Industry Advisory Board (1985) provide a critique ofsome of these indices. The main criticism is that the tests areperformed on laboratory-prepared ash which may be differentfrom the ash found in commercial boilers and furnaces (see

Combustion

Section 3.6). Also, the indices are not universally applicableto different coal ashes (Blackmore, 1985; IEA Coal IndustryAdvisory Board, 1985). The tests for determining the indiceswere also developed on Laurasian coals and may beinapplicable to Gondwanan coals (Sanyal and Cumming,1985).

Other tests used to predict slagging and fouling propensitiesinclude ash viscosity and ash fusion measurements. Ashfusion temperatures {see Section 3.6) are often required incoal specifications. The VAWST Chinese classification forpower station coals includes the ash softening temperature asthe slagging parameter. The tests can be carried out onblends of coal but they may not be additive. Ash fusibility isof importance in pf boilers. It is of less significance in fbcbecause the bed temperature is normally kept below the coalash fusion temperature thus avoiding bed agglomeration(Hainley and others, 1986).

To conclude, there is no single test that can adequatelydescribe coal ash behaviour. Traditional tests focus on oneparticular aspect of ash behaviour and may not be applicableto all coal ash types. An inexpensive, empirical, hightemperature test for predicting slagging and fouling potentialof ash from single or blends of coal is required (Lee andWhaley, 1983). Newer techniques which show signs ofpromise include for example, the electrical resistivity of ash(Sanyal and Cumming, 1985) and hot stage microscopy(Blackmore, 1985).

Coal ash chemistry has been related to the ash composition,but even so, no universally accepted tool for predictingslagging and fouling from the ash composition has yet beendeveloped. Also, it is difficult to see how one parameter canaccurately reflect the composition of ash; to be kept simple, aclassification system should have only one parameter topredict slagging or fouling tendencies. A classificationsystem should not include a parameter that is not universallyapplicable and reproducible and, until better predictivemethods are developed, a parameter for ash chemistry isprobably best excluded. However, the inclusion of data onash composition and behaviour, as well as 'content', wouldassist in the marketing of coal. Since the majority of coal isburnt, this would be an advantage in a commercialclassification. Many combustion problems are related toash constituents and few, if any, of these problems cancurrently be predicted by the existing traditionalclassification systems.

7.2.4 Moisture

Knowledge of the moisture content has a bearing on theeconomic value of a coal, since moisture is incombustible.Thus the moisture content is often specified during trading ofcoal. However, few classification systems use moisture as aseparate classification parameter. It is often required inclassifications for low rank coals. In the VAWSTclassification for power generation coals, the total moisturecontent is considered to be of enough importance to includeas a separate classification parameter (Xu and others, 1986;Sun and Liu, 1985). Moisture in coal and its determinationis discussed in Section 2.8.

In combustion, a high moisture content is a disadvantagesince it reduces the calorific value {see Section 2.7); heat isrequired to vaporise the moisture, heat that does little usefulwork. When determining the actual heat output from a coalin commercial boilers, the amount of total moisture, as wellas the net calorific value, needs to be taken into account(Ward, 1984b). Excessive moisture can hinder ignition and ahigh moisture content reduces the flame temperature, slowingthe rate of combustion, increasing the burnout time andresulting in a longer flame envelope and an increased risk offlame instability (Tapia, 1987). The efficiency of the boileris therefore reduced. An increase of 5% in total moistureresults in a decrease of 0.3% in boiler efficiency, assumingan initial moisture content of about 10% or more (IEA CoalIndustry Advisory Board, 1985), or a loss of about 0.07% per1% moisture (Wall, 1985).

The moisture content can also influence the handling of coaloutside the boiler. For example, a high content can causeproblems in pulverisers, freezing problems in cold weatherand clogging of hoppers and feeders (IEA Coal IndustryAdvisory Board, 1985). Spontaneous combustion problemscan also be promoted by the moisture content.

Generally, coals with a low moisture content are preferred;however a certain amount of moisture is required. In fixedbed firing, moisture is needed to bind fines and make the bedmore permeable (BCRA Quarterly, 1986). In pf combustion,a moisture content of less than 15% is usually specified(Cudmore, 1984), although the IEA Coal Industry AdvisoryBoard (1985) recommends a range of 5 to 10%. In fbc, coalswith a wide range of moisture can be burnt (Merrick, 1984).

Although moisture does affect the combustion behaviour ofcoals, it may be sufficient to include it as part of anotherclassification parameter, such as the calorific value on ammmf basis. In West Germany, the 'ballast' is commonlyused. However, if all classification parameters are on a dafbasis, then the total moisture content may be worth includingas a separate parameter. Schwarz (1986) found that ash hadmore influence than moisture on the combustibility of coals.Thus if there is a choice between moisture and ash, the latterwould be the preferred classification parameter. Howeverthe moisture content can be important when classifying thelower rank coals.

7.2.5 Sulphur

The sulphur content is nowadays almost always required in aspecification for steam coal. Its use as a classificationparameter has been proposed only in the last decade or so,mainly for environmental reasons although sulphur willaffect a boiler's performance. The older traditionalclassifications do not include a sulphur parameter. Thebehaviour of sulphur in coal during combustion is reviewedby Reid (1981) and its determination was discussed inSection 2.5.

Sulphur in coal is usually regarded as being detrimental.During combustion, the majority of the sulphur in coal istransformed to sulphur dioxide, with a proportion retained inthe ash as sulphates. The retained proportion varies; it can

Combustion

be as high as 50% in some lignites (Wall, 1985), but forbituminous coals, 5% to 10% is more usual. Taking accountof ash retention, it is therefore possible broadly to predict thelevel of sulphur dioxide which will be emitted from thecombustion of a given coal and thus whether a coal will meetthe required emission levels (Baker, 1986). For example, thesulphur content of low sulphur Australian coals has beendirectly related to sulphur dioxide emissions (Sullivan, 1986).

As sulphur dioxide emission standards are becoming stricter,the sulphur content of coal is increasingly significant.However, if the level of coal sulphur will give rise to sulphurdioxide emissions above applicable limits, a number ofoptions are available to reduce emissions. These generallyinvolve adsorption of sulphur dioxide by a reagent. Theyinclude injection of sorbents into the boiler or ducting, fluegas treatment and the use of combustion technologies wheresulphur dioxide is removed during combustion (such as fbcwith added limestone or integrated coal gasification/combined cycle).

The costs of controlling sulphur dioxide emissions varyconsiderably and are influenced by plant specific factors. Ingeneral, however, costs will increase with increased coalsulphur content. The amount of sulphur in the coal willusually determine the amount of reagent required to meet agiven emission limit. A low sulphur content is thus seen asbeneficial in environmental terms and most traded coal hasless than 1 % sulphur.

There are exceptions however to this general rule of thumbthat the less sulphur in coal the better. Very low sulphurcontents have been linked with high fly ash resistivity, whichmakes control of particulate emissions by electrostaticprecipitors more difficult (Blackmore, 1985). However,research in Australia (Paulson and others, 1986) hasindicated that the proportions of silicon, aluminium and ironin fly ash may be a more reliable indicator of resistivity thancoal sulphur alone.

Coal sulphur content can also affect boiler operation. Thereis some evidence that, particularly for coals with highchlorine content, higher sulphur levels may reduce hightemperature corrosion and fouling (Blackmore, 1985; IEACoal Industry Advisory Board, 1985). On the other hand,sulphur can contribute to low temperature corrosion.

The sulphur content can also indicate how much cleaning acoal may require before being burned. However, the totalsulphur content does not indicate the forms of sulphurpresent and hence how easily the sulphur can be removed.Organic sulphur is notoriously difficult to remove, whereaspyritic sulphur can generally be removed by mechanicalmethods of coal preparation. The form of sulphur rather thantotal sulphur is also of more interest when pulverising coal,as high pyritic sulphur can result in heavy mill componentwear (Wall, 1985).

There is a strong case for the inclusion of sulphur in aclassification system and not only for direct combustionpurposes. Sulphur can be a problem in essentially all uses ofcoal or coal-derived fuels (Reid, 1981). As concern over

environmental consequences of coal combustion (especiallyacid rain) is increasingly being translated into strict limits forsulphur dioxide emissions, a sulphur parameter is required.The VAWST Chinese classification system, which isspecifically for pulverised coal for power generation, uses the'equivalent sulphur content' (defined as 1000 multiplied bythe sulphur content divided by the net calorific value).However, for a classification to be more generally applicable,sulphur content (as determined by ultimate analysis) isprobably sufficient. Both the new Australian and new ECE'classifications' include the total sulphur content as aparameter.

7.2.6 Nitrogen

Unlike sulphur, the nitrogen content in coal has little knowneffect on boiler performance (IEA Coal Industry AdvisoryBoard, 1985; Singer, 1981) and therefore had been largelyignored. However, coal nitrogen has been found to have asignificant impact on the generation of nitrogen oxidesduring the combustion process and, in recent years, nitrogenoxide emissions from power stations have been linked with'acid rain' damage. Smith (1980), for example, reviews someof the environmental effects of nitrogen oxide emissions.Nitrogen oxide emissions are becoming subject toincreasingly strict emission limits and therefore, from anenvironmental viewpoint, coal nitrogen content becomesimportant.

There is no simple correlation between coal nitrogen contentand nitrogen oxide emissions. For example, in a studyrelating the characteristics of Laurasian and Gondwanancoals to nitrogen oxide emissions, Doolan and Knott (1985)found that the only significant association with nitrogenoxide formation was the total nitrogen content. However, thedifferences between predicted and actual nitrogen oxidelevels for coals of identical nitrogen content exceeded 20%and no compositional factors responsible for these widediscrepancies could be found. This is because nitrogen oxideemissions are somewhat unique in that, unlike sulphurdioxide, not all the nitrogen oxides come from the coal. Aproportion comes from the air introduced into the burners(thermal nitrogen). The relative contribution of coal nitrogenand thermal nitrogen to the total nitrogen oxide emissionsvaries depending on the coal and combustion conditions.However, coal nitrogen is typically the major contributor; upto about 80% of nitrogen emissions from pf boilers can arisefrom coal nitrogen (Morrison, 1980).

The formation of nitrogen oxides during coal combustion is acomplex process, dependent on a variety of interrelatedphenomena, making quantitative predictions difficult. Theprocess is still not fully understood. Jiintgen (1987b) reviewssome recent work on this subject and Morrison (1980) andSinger (1981) review some earlier work.

Some factors related to coal composition have been found toinfluence nitrogen oxide formation. Generally, as coalnitrogen content increases, total nitrogen oxide emissionincreases, while the percentage conversion of coal nitrogen tonitrogen oxide decreases (Morrison, 1980). The mode ofincorporation of the nitrogen into the coal matrix can also

Combustion

influence its fate (Burdett and Pye, 1987; Morrison, 1980).Nitrogen oxide formation may also be a function of coal rankbecause of differences in combustion characteristics for coalsof varying rank. Burchill (1987), for example, discusses thevariability of nitrogen content and functionality with coalrank. When plotted against carbon content, nitrogen contentwas found to increase during the lignite and subbituminousrank stages and then decrease during the bituminous (ataround 80%-85% carbon) rank stages. Differences innitrogen conversion data for lignite and bituminous coalshave been found, suggesting that there are significantdifferences in their coal nitrogen chemistry (Burdett and Pye,1987). Other factors related to coal composition, such ascoal oxygen and sulphur contents, can influence nitrogenoxide formation (Morrison, 1980).

Various correlations related to coal compositional factorshave been derived. For example, the kinetics of nitric oxideformation have been correlated with those of carbonmonoxide and carbon dioxide formation (Jiingten, 1987b).Pohl and others (1983) have proposed equations relatingnitrogen oxide emissions to coal nitrogen content, percentageof volatiles and percentage of fixed carbon, although therelationships vary depending on flame conditions. Nitrogencontent, when related to coal volatile matter, has also beenused to predict likely nitrogen oxide emissions, but with littlesuccess (Sullivan, 1986).

A range of other factors related to combustion conditions,particularly combustion temperature and excess oxygenlevels, have a significant effect on nitrogen oxide production.For example, the contribution of thermal nitrogen to nitrogenoxide emissions increases rapidly above 1540°C (Morrison,1980). Nitrogen oxide emissions can thus be reduced bymodifying combustion conditions, for example, by loweringflame temperature and oxygen concentration within thecombustion chamber. Nitrogen oxide reduction techniquesinclude using staged combustion (for example, Smart andWeber, 1987). Morrison (1980) reviews a number of thesecombustion modifications, and also the treatment of flue gasfor controlling nitrogen oxide emissions.

Although changing to a lower nitrogen coal will probablyreduce nitrogen oxide emissions (for a given boiler withgiven firing conditions), there are few low nitrogen coalsaround. Coals generally show little variation in theirnitrogen content; they usually contain about 0.5%-2%nitrogen (Morrison, 1980). Nitrogen oxide emissions are infact generally reduced by modifying the boiler design ratherthan by changing coals.

Since there is a general consensus that nitrogen oxideemissions are primarily influenced by combustion conditions,and because the relationship between coal nitrogen andnitrogen oxide emissions is so complex, coal nitrogen contentis probably best excluded as a classification parameter.

7.2.7 Chlorine

In combustion applications chlorine is one of the mosttroublesome components of coal, causing slagging, foulingand corrosion. There is substantial evidence that fouling and

corrosion increase as the chlorine content in coal increases(Blackmore, 1985; IEA Coal Industry Advisory Board,1985). Wall (1985) considers that chlorine contents above0.25% indicate a likelihood of fouling and corrosion,although pf boilers have been operated successfully withcoals containing over 0.5% chlorine (Day and others, 1979).

High chlorine coals are found in a number of countries. Forexample, some British coals can contain up to 1% chlorine(Given, 1984). They are generally believed to have beenformed under saline conditions. Chlorine content shows nocorrelation with rank.

Instead of using chlorine content alone, two ratios have beenapplied to predict corrosion and fouling, thesulphur-to-chlorine and chlorine-to-ash ratios. As thesulphur-to-chlorine ratio increases, coals become lesscorrosive, and an increase in ash content relative to chlorinereduces the fouling potential of a coal (Blackmore, 1985;IEA Coal Industry Advisory Board, 1985). Borio andLevasseur (1986) consider that the use of the ratios isquestionable since they do not take into account the totalquantities of the constituents present, which may be of moreimportance than their ratio. They also consider that the useof chlorine content as an index of fouling is valid only if thechlorine is present as sodium chloride and that it is thesodium that causes the fouling. Chlorine present in otherforms may or may not adversely affect fouling. Chlorine incoal occurs either associated with the organic matter (Given,1984) or as chlorides in the mineral matter. The primarycauses of fouling and corrosion is generally believed to becaused by the formation of alkali metal chlorides(Blackmore, 1985; IEA Coal Industry Advisory Board, 1985).

Neither of the two ratios (sulphur-to-chlorine orchlorine-to-ash) are currently used or have been proposed asclassification parameters, nor are they often required in acoal specification. Both ash and sulphur are used on theirown as classification parameters and both provideinformation of more technical relevance than as part of aratio. The chlorine content could possibly be used as aclassification parameter, but it is not always determined inultimate analysis. It would therefore require an additional testwhich would add to the cost and also to the complexity ofthe classification system.

7.3 Mechanical and physicalproperties

7.3.1 Caking and swelling

The combustibility or reactivity of coal is partly controlledby its caking characteristics, which influence combustion inseveral ways. As caking coals undergo pyrolysis theybecome plastic and swell and, in some cases, agglomerate sothat the effective particle size is increased. Access to air isdecreased, and pyrolysis and the subsequent char combustionare more likely to be controlled by diffusion (Gray, 1987a).As a result, chars from caking (swelling) and noncaking(nonswelling) coals behave differently during combustion(Juntgen, 1987a).

Combustion

This applies to coals burnt as lumps in fixed bed firing aswell as to pulverised coals. However, the extent of swellingis a function of the rate of heating, the final temperature andambient gas composition (Essenhigh, 1981) and so theeffects will vary in different combustion applications. Infixed bed firing, the rate of combustion at constant densitywas inversely related to the crucible swelling number (CSN)in underfeed pot combustor tests, with weakly caking coals(CSN 1 to 3.5) being the most satisfactory (BCRAQuarterly, 1986). Generally the higher the CSN, the lowerthe combustion efficiency of steam coals in most combustionprocesses. Work is discussed by Ceeley and Daman (1981)in which a nomogram was developed to predict stoker designcapacity from parameters that included the CSN.

Although caking properties are not as significant in fbcapplications (Cudmore, 1984; Merrick, 1984), knowledge ofthe caking properties of a coal can be used to avoidagglomeration problems in the fuel feeding systems (Hainleyand others, 1986). The influence of the cakingcharacteristics during pulverised coal combustion is reviewedby Morrison (1986).

The tests used to determine the caking, plasticity andswelling properties of coal and which have been variouslyused as classification parameters were discussed in Section 3.All these tests are carried out under atmospheric pressure.Since the behaviour of coals at elevated pressure cannot beaccurately predicted from their properties obtained atatmospheric pressure, these tests are probably inapplicablefor combustion processes carried out under pressure. Thiswould limit their use as classification parameters.

For typical vitrinite-rich coals, plastic and caking propertiesare principally rank-related (Neavel, 1981), with the cakingcoals being mainly of bituminous rank. However, thepetrographic composition can exert an influence (seeSection 3), leading to difficulties in the interpretation of theresults. Differences in the combustion behaviour betweenpetrographically different coals can therefore be expected(see Section 7.4).

A caking parameter may be unnecessary if it can beestimated from the other classification parameters; forexample, Neavel and others (1986) showed that forvitrinite-rich coals of low mineral matter content, the CSNcould be calculated from the oxygen, ash, inertinite andliptinite contents. However, these correlations are of limitedvalue since they are generally applicable only to the coals onwhich they were developed. Also, the Chinese do not regardthe caking characteristics to be of enough importance toinclude in their classification of coals for power generation(Xu and others, 1986; Sun and Liu, 1985).

Although caking is of some importance in combustion, it isof more significance in the coking industry and theimplications for coal classification are discussed further inSection 9.3.

7.3.2 Grindability

It is well known that the particle size and its distribution has

an important influence on combustion performance andefficiency of coal (Essenhigh, 1981; Jiintgen, 1987a). Sincethe particle size of coal can be altered by mechanicalmethods, it is not considered a suitable classificationparameter. However the grindability of coal, which helpsdetermine the particle size, will be worth considering. Thegrindability of coal is important in pf installations where thecoal is milled to a particle size below 100 |im before firing.Coal grindability will determine the capacity andperformance of pulverisers, the energy required to pulverisethe coal, as well as determining the particle size of the grindproduced (Baker, 1986; Day and others, 1979; Wall, 1985).In the combustion industry, the most frequently used index ofgrindability is the Hardgrove Grindability Index (HGI),which was discussed in Section 3.7. None of theconventional classification systems nor the newerclassifications include the HGI as a classification parameter.This is despite its importance to utilities where the HGI isfrequently required in coal specifications (Baker, 1986).

7.4 Petrographic composition andproperties

Although macerals have different combustion characteristics,Day and others (1979) believe that the combustion methodsused are relatively insensitive to the maceral assemblage inthe range of coals normally encountered. However,differences in the combustion behaviour of coals with similarproximate analyses have been related to their petrographiccomposition. For instance, when a Polish and South Africancoal (of similar proximate analyses) were fired in the same pfboiler and under the same combustion conditions, markeddifferences in furnace performance resulted (Sanyal, 1983).The difference was attributed to the different inertinitecontents of the two coals.

It is generally accepted that the vitrinite and liptinitemacerals are chemically reactive (for example. Hough andSanyal, 1987; Nandi and others, 1977; Sanyal, 1983) and thatpart of the inertinite group (mainly low reflectancesemifusinite) can also be considered as reactive (for example,Hough and Sanyal, 1987; Jones and others, 1985; Lee andWhaley, 1983).

In coals of the same rank, liptinite is the most reactive group,having the highest hydrogen content, volatile yield andheating value; inertinite is the least reactive. One importanteffect of macerals on combustion results from their influenceon the morphology of the char produced during the initialdevolatilisation stage; coals rich in vitrinite produce chars ofhigher porosity and reactivity than coals rich in inertinite(Bengtsson, 1986; Cumming and others, 1987; Jones andothers, 1985). According to Bengtsson (1986, 1987b), poreformation starts earlier in vitrinite than liptinite, but liptiniteresidues are consumed the most rapidly. The swelling ofvitrinite particles also favours rapid heterogeneouscombustion in pulverised flames.

Thus the petrographic composition of a coal can be used asan indication of the relative ease of combustion. Vitriniteand liptinite will promote good ignition and burnout and a

Combustion

coal rich in liptinite would be expected to have an especiallylow ignition temperature (Jiintgen, 1987a; Tsai and Scaroni,1987). Combustion efficiencies can also be predicted.Nandi and others (1977) found that the combustionefficiencies of two Canadian coals burnt in pf combustorswere inversely related to the inert maceral (inertinite plusoxidised vitrinite) contents.

A direct link between inertinite and unburnt carbon contentsfor Indian coals in full scale pf firing (Hough and Sanyal,1987) and for coals burnt under pf and fbc conditions(Vleeskens and Nandi, 1986) has been found. However, thelatter workers observed that in fbc, the coal with the highestinertinite content did not follow the trend and in fact showedthe smallest carbon loss. The inertinite char showed fasterburnup than vitrinite char during recycling in fbc as a resultof different attrition properties (Vleeskens and others, 1988).This indicates that the significance of petrographiccomposition will depend on the combustion process. In pfsystems, a high inertinite content will generally indicatelower reactivity and combustion efficiency (IEA CoalIndustry Advisory Board, 1985), a delay in ignition (Pearson,1985) and that flame stability may be a problem.

Thus knowledge of the maceral composition could be usefulin assessing the combustion characteristics of a coal and forpredicting burning profiles. However, the combustionproperties of different coal types cannot be predicted fromtheir petrographic composition alone (Gromulski, 1986).Therefore other classification parameters (such as rank)would be required. Two maceral groups would be required asclassification parameters to indicate the maceral composition,with the content of the third group being easily deducible.However, there is the problem that the relationship betweenpetrographic composition and combustion performance isdifferent for Gondwanan and Laurasian coals. Inertinites inLaurasian coals have been shown to be relatively unreactiveduring combustion; but inertinites with a mean randomvitrinite reflectance between 0.5% and 0.8% are reactive inGondwanan and some other inertinite-rich coals (Jones andothers, 1985). Increasingly, semifusinite is being divided into'reactive' and 'inert' portions and, with part of themacrinites, is being counted in with the vitrinite and liptinitemacerals when determining the total reactive maceral contentof coal.

Although vitrinite is considered reactive, Bengtsson (1987a)found that pseudovitrinite, like inertinite, can also increasethe quantity of unburnt carbon in the fly ash and is thereforerelatively unreactive. The high volatile US coal contained68% vitrinite (28% of which was pseudovitrinite, a lessreactive vitrinite maceral) and only 16% inertinite and 8%minerals. Thus vitrinite content is not always a reliableguide to combustion behaviour. It is interesting that neitherthe proximate nor ultimate analyses indicated anycombustion problems. Oxidised vitrinite is also considered'unreactive' (for example, Nandi and others, 1977) and maytherefore need identification. This implies that coals withsimilar maceral composition may not have identicalcombustion behaviour because of differences in the contentsof reactive macerals. Also, the different macerals in eachgroup have different chemical compositions and so the

maceral composition of each group is only an average; thatis, inertinite can have different chemical compositions andtherefore, slight differences in its behaviour can be expected.Similarly, differences in vitrinite and liptinite can also beexpected. The intergrowth of macerals (microlithotypes) canalso influence the combustion behaviour of a coal(Bengtsson, 1987b; Shibaoka and others, 1987).

A classification system based on the total reactive maceralcontent may be worth considering. However, there is as yetno widespread agreement on what actually constitutes thetotal reactive macerals or a simple method for theirdetermination. Also, a total reactive maceral parameterwould not indicate the differences in combustion behaviourof the constituent macerals.

It should be emphasised that comparative analyses of coalbased on just their petrographic composition takes no accountof design influences on combustion or that combustion issubject to many variables. The role of maceral compositionduring combustion varies with for example, furnacetemperature and particle size in pf combustors (Tsai andScaroni, 1987). Grinding a coal for a pf installation cancause maceral disproportionation (see Section 3.7) withconsequent effect on combustion. Also, maceral compositioncannot be used in isolation to assess the combustionbehaviour of a coal. The combustion properties of maceralsvary with rank; for example, the differences in morphologyof chars produced by vitrinite and inertinite decrease withincreasing rank, so that the behaviour of vitrinite andinertinite will converge with increasing rank (Jones andothers, 1985). This is another reason for including rank as aclassification parameter (see Section 7.1). In fact, rank hasbeen shown to have a larger influence on the combustionprocess than maceral composition (Jones and others, 1985;Shibaoka and others, 1985b).

The effect of maceral composition in blends of coals are asexpected for the single coals; that is, combustion reactivity ofblends increases with increasing reactive maceral content(vitrinite, liptinite and low reflectance semifusinite)(Lee and Whaley, 1983). The combustible content of the flyash decreased progressively as the reactivity of the coalblend increased. However, the combustible content of thefly ash from the coal blends could not be predicted fromthose of the constituent coals; in each case the measuredvalue was lower than that calculated. The vitrinitereflectogram can generally be used to detect coal blends (seeSection 4.3).

7.5 Potential analytical techniquesThe conventional tests used for the characterisation of coal,while still crucial for understanding combustion behaviour,do not always succeed in evaluating the characteristics to theextent warranted by the increasing use of coal from a numberof differing sources with a wide range of qualities. Also, thetests do not always relate to actual operating combustionconditions. This has led to a number of laboratory-scale testsbeing developed to improve our understanding of the effectof coal properties on combustion. Two of these tests arediscussed below.

Combustion

7.5.1 Derivative thermogravimetric analysis

Derivative thermogravimetric (DTG) analysis (see Section5.1) can provide a 'fingerprint' of the complete combustionprocess of coal. A burning profile curve is produced thatprovides a relative evaluation of the combustioncharacteristics of coal in fixed bed, fluidised bed and pfunits. The order of reactivity is assessed primarily on thepeak temperature (the temperature of the maximum rate ofweight loss); the higher this temperature the less reactive thecoal. The peak temperature could thus possibly be used in aclassification system as a measure of the combustionreactivity of a coal.

Instead of peak temperature, Smith and others (1981) haveused the temperature at which 50% of the sample has burnedaway as a measure of the combustibility (reactivity) of coals.This temperature was linearly related to the coal oxygen andcarbon contents, but with some scatter of the data points.

The use of peak temperature with other temperature pointsfor assessing the reactivity of coal can be unwieldly in thecase of multiple peak profiles and does not take into accountthe nature of the complete combustion profile. A singlemeasure for describing the reactivity or combustibility ofcoal has therefore been derived from simultaneous TG/DTGreadings - the weighted mean apparent activation energy(Em) (Cumming, 1984). This parameter encompassesvirtually the whole burning process. However, someimprovement in the data processing is necessary to simplifythe derivation of Em. There is a correlation between Em andburning profile peak temperatures.

The Em may be a more reliable tool than burning profiletemperatures for assessing coal combustibility and carbonburnout, in which case it would be the better classificationparameter. When the Em values of a wide range of coalswere plotted against their corresponding burning profile peaktemperatures, a small group of coals were distinguished thatdid not follow the general trend (see Figure 8). According totheir peak temperatures, these Gondwanan coals would beconsidered to be more reactive than the other bituminous

Figure 8 Activation energy versus burning profile peaktemperature for different coaltypes (Sanyal andCumming, 1985)

ones. In actual practice, these coals are known to give rise tohigher carbon losses in utility boilers; this is indicated bytheir higher Em values (Sanyal and Cumming, 1985).However, the DTG technique has not gone uncriticised (seeSection 5.1).

7.5.2 Pyrolysis-mass spectrometry

Since combustion includes a thermal conversion step,pyrolysis-mass spectroscopy (py-ms) could offer severaladvantages over conventional tests. As discussed in Section5.3, several coal properties show a high correlation withpy-ms data and thus may, in principle, be predicted frompy-ms data, in one test. These include rank, calorific value(average error was 183 kJ), maceral content, CSN andsulphur dioxide emission yield. However, a single measure ofcoal reactivity that can be derived directly from py-ms datawould be useful; this measure could then possibly provide aclassification parameter.

7.6 CommentaryThe difficulty of deciding which properties of coal should beincluded in order to classify a coal effectively is reflected inthe wide number of classifications in use today. To beinternational, the classification should be applicable to allcoals worldwide. A classification must be of practical valueif it is to be generally applied and should therefore includeproperties of coal that are widely accepted and used in thecombustion industry. It should be emphasised, however, thatthe requirements for a classification are not the same as thosefor a specification.

There is general agreement over the requirement for a rankparameter, but disagreement over how rank is to bedescribed. If volatile matter and calorific value are acceptedas providing an adequate reflection of coal rank, than therewould be no need to include vitrinite reflectance. Bothvolatile matter and calorific value are of more technicalsignificance in combustion. However, both the newAustralian and new ECE 'classifications' include all threeparameters.

A classification categorises coals, that is, groups similar coalstogether. As has been seen, some coals can be 'misclassified'using volatile matter and calorific value, since coals areknown to have similar volatile matter and calorific value butto show different combustion behaviour. This is a generalproblem with most classification parameters - there arealways some coals which in practice, behave as exceptions.No property of coal can be evaluated on its own.Relationships between the various properties is often asimportant as the magnitude of the characteristic itself(Blackmore, 1985).

Since the mass of volatiles evolved during combustion is notequal to that predicted by standard proximate volatile mattertests, a measure of the 'true' volatile yield may be preferredin a combustion classification. However, there is as yet nointernational agreement on the determination of thisparameter. Estimation of 'true' volatile yield from other coalproperties have been proposed, but their validity for other

coals is questionable. The combustible volatile matter hasalso been proposed as a classification parameter. However,in a general classification covering all coal uses, theproximate volatile matter would probably be preferred; thereare, at least, standard international methods for itsdetermination.

An ash parameter will provide an indication of the quality ofa coal, as well as being of technical significance. The newAustralian and ECE 'classifications' make provision for it.The inclusion of ash composition could be an advantage in acommercial classification, since many combustion problemsare related to the ash constituents. This could, however,make the classification unwieldy by increasing the number ofparameters; it would be difficult to include the ashcomposition as a single parameter.

Moisture is also frequently required in a specification, but isnot often included as a classification parameter. Its use is ofmore importance when classifying the lower rank coals. Thetrend is for classification parameters to be quoted on a daf ordmmf basis and therefore, total moisture and ash yield couldbe useful.

Standard specifications frequently require the ultimateanalysis of coal. No classification system has yet beenproposed based entirely on the ultimate analysis. The nearestis probably the Seyler chart, which is not, strictly speaking, aclassification. Oxygen content can provide a guide to thereactivity of coal and hence its rate of burnout andcombustion efficiency (Burbach and others, 1977). Butultimate analyses alone can be an unreliable guide to a coal'scombustion behaviour. Hao (1983) showed that reactivitydefined by the carbon-to-hydrogen ratio or carbon andhydrogen-to-oxygen ratio were inadequate for some Chinesecoals. A problem with rank-based correlations is that coalsof similar rank are chemically diverse and therefore,empirical correlations for coals from one geological regionmay not be valid for coals from another region (Berkowitz,1988). If a classification is based on the ultimate analysisthen other parameters, such as vitrinite reflectance, volatilematter and calorific value, could be estimated and thereforeexcluded. However, the applicability of these formulae tocoals of all types and their accuracy for industrial use isdisputed.

Only one parameter based on the ultimate analysis has beenproposed as a classification parameter in the newerclassifications. With the increasing environmental concern,there is certainly a need for a parameter to indicate possibleenvironmental consequences and sulphur, rather thannitrogen, would be the preferred parameter. Sulphuremissions correlate with the coal sulphur content, whereasthe relationship between nitrogen oxide emissions and coalnitrogen content is much less well-defined.

Some classifications systems developed in the last decade orso have included petrographic parameters. The petrographiccomposition can explain unexpected poor combustionbehaviour of some coals that have similar proximate andultimate analyses. However, inclusion of petrographic

parameters is still disputed. There is the problem ofinertinite with its different combustion behaviour inGondwanan and Laurasian coals. It also seems only to beworthwhile including a reflectogram parameter if theclassification system is intended for coal blends. Althoughblends of coal are used commercially, a reflectogram is notoften requested in a specification.

The different requirements of a classification and aspecification are illustrated by the presence or absence ofparameters such as the HGI and ash fusion temperatures,which are frequently required in coal specifications but rarelyincluded in classifications. One reason may simply be lackof space. To keep a classification simple necessitates leavingout some parameters which are required in a specification.Parameters which are relevant to several industrial uses ofcoal will have priority for inclusion in a generalclassification. Another reason may be the poor reliabilityand reproducibility of some of these tests and their poorcorrelation with the actual combustion behaviour of coal inindustrial installations. A classification that uses the same(but not all) parameters as a specification would facilitate thetrading of coal.

There is a general consensus that the current evaluative testsare inadequate and inaccurate (for example, Cumming andothers, 1987; Gray, 1987a; IEA Coal Industry AdvisoryBoard, 1985; Morgan and Roberts, 1987; Wall and others,1985) and that their interpretation into the expected full-scaleperformance of coal is unreliable. The desirablecharacteristics of a test are that it should be reproducible,reliable, objective and adequately precise, and preferablycheap and capable of automation as well. Few, if any, of theconventional tests meet all these criteria. Most of the testconditions are far removed from actual combustionconditions and the data cannot be extrapolated properly tofull-scale industrial plants. Another requirement is that thetests are global, that is, results obtained worldwide for a coalare directly comparable. Differences in standard methods invarious countries will give different results (for example,volatile matter determination by ASTM and British Standardmethods). Therefore internationally recognised methods(standards) should be followed. The widespread view thatthe only way to evaluate the suitability of a coal for a boileris for a full-scale test burn is a general indictment of theavailable tests. Improved evaluative tests based on modernanalytical techniques are urgently required. The IEA CoalCombustion Sciences is one group currently investigatingadvanced analytical techniques in the field of coalcombustion (IEA Coal Combustion Sciences, 1985).

The need for better quantitative data on coal properties and abetter understanding of combustion is seen in the number ofexpensive test facilities being built today. The comment byEssenhigh (1981) that 'to break away from the presentempiricism however, it will be necessary to establish anadequate model of coal constitution that can provideacceptable predictive correlations' is still relevant today.Until acceptable predictive correlations are achieved, thedevelopment of a practical classification that is applicableworldwide will be delayed.

8 Liquefaction

The production of liquid fuels from coal by directliquefaction involves heating pulverised coal in a solvent,with or without the presence of hydrogen, under pressure andwith or without added catalyst. Part of the coal willdecompose and dissolve in the solvent. Subsequentprocessing will separate the undissolved solids (mineralmatter and inert macerals) from the liquids, and a portion ofthe liquids may be added to the solvent and recycled. Theproducts obtained include light gases, distillate liquids andnondistillable liquids (which may be solid at roomtemperature). To assist in their characterisation, thenondistillable products are usually separated by solventfractionation into three fractions: oils (soluble in hexane,pentane or other light alkanes), asphaltenes (benzene-solubleand hexane-insoluble) and preasphaltenes (pyridine-solubleand benzene-insoluble) (Gorin, 1981).

A great deal of effort has been expended to find a singleparameter or group of parameters that will correlate thefundamental physical/chemical/geochemical properties ofcoal with its degree of conversion to liquid products. Thecorrelation of coal properties with liquefaction behaviour iscomplicated, not only because of the heterogeneity andvariability of coals worldwide and the continuous variation ofcoal properties with rank, but because, for a given coal, boththe rate and extent of conversion are heavily dependent onthe solvent, process conditions and configuration used. Thecharacteristics of coal play a more important role whenliquefaction is carried out under relatively mild conditions(for example, short residence time in the absence ofhydrogen); differences in coal conversion are generally lessevident with increasing process severity (Davis and others,1976; Gray and others, 1980a, 1980b; Snape, 1987).

It can be difficult trying to compare results from the variousresearch laboratories because of differences in experimentalconditions and methods of reporting results. Ouchi andothers (1984a) showed that if the reactivity of coal is definedin terms of pyridine-soluble material, the coal of medium

rank (83.9% carbon) gave the highest conversion. However,if the reactivity is defined as conversion to benzene- orhexane-soluble materials, the lowest rank coals (77.9%carbon) showed the highest reactivity. It would be helpful ifstandard experimental procedures were established. There isalso the difficulty in transposing some experimental results tocommercial conditions. For example, results obtained inbatch processing show markedly different trends fromcorrelations obtained in continuous flow reactors (Tomlinsonand others, 1985).

A distinction has to be made between overall conversions(determined from yields of insoluble organic matter) anddistillate yields. Coals may give similar overall conversionsin hydroliquefaction but vastly different distillate yields uponhydrocracking the primary dissolution products (Lenz andothers, 1982; Snape, 1987). Therefore laboratory studies thatwere concerned only with the overall conversion may not beparticularly relevant to commercial operations. Also, thequality of the recycle solvent can be important in potentialcommercial processes (Snape, 1987). Thus a classificationsystem developed from laboratory results may not be valid inassessing coals for commercial liquefaction plants.

Some of the parameters that are important in predicting coalreactivity and its conversion during direct liquefaction, andwhich may be helpful in developing a classification systemfor coal, will be discussed. Indirect liquefaction, in whichcoal is reacted with steam and oxygen at high temperatures,will not be covered. A recent comprehensive review of theliterature correlating coal properties to liquefaction behaviourhas been published by Snape (1987). An earlier review waspublished by Gorin (1981); the short review that appeared inthe BCRA Quarterly (1986) only covers coals of bituminousrank and higher.

8.1 Rank effectsAll classification systems use a measure of rank as one of the

Liquefaction

parameters. However, the effect of rank in coal liquefactionis not simple. Some workers have reported that the highestyields are obtained from the lowest rank coals (Derbyshireand others, 1986; Given and others, 1980; Perry and others,1982); others that optimum conversion was obtained forcoals of high volatile bituminous rank (Davis and others,1976; Gray and others, 1980a, 1980b; Whitehurst, 1980;Whitehurst and others, 1980); and yet others found nosatisfactory rank-conversion relationships (Adbel-Baset andothers, 1978; Gorin, 1981). Some of these differences willbe due to the different process conditions used. However,Whitehurst and others (1980) suggest that the 'intrinsic'reactivity of coal actually decreases with increasing rank overthe entire rank range, and that bituminous coals only 'appear'to be more reactive, until differences in rates and solubilitiesare taken into account.

There seems to be general agreement that the highest rankcoals are relatively unreactive, giving low liquefaction yields.The yield of liquid products decreases with increasing rankfor coals ranked higher than high volatile bituminous, andboth rate and yield are low for coals with more than 88%carbon (daf), even if they have a high vitrinite content(Given and others, 1975a; Whitehurst and others, 1980).These coals have little reactive hydrogen, are highly aromaticand probably contain few reactive functional groups.

Lignites, subbituminous and bituminous coals are regarded asthe potential feedstocks for liquefaction processes.Generally, US low rank (lignites and subbituminous) coalsliquefy less readily than their bituminous counterparts atshort residence times, while at longer residence timesconversions are often fairly similar for all coals (Neavel,1976; Whitehurst, 1980; Whitehurst and others, 1980). Thisobservation contrasts with the known behaviour of low rankcoals in other technological processes, such as combustionand gasification, where they are regarded as being morereactive than coals of higher rank. However, other evidencesuggests that the low rank coals are, in fact, more reactive(for example, Derbyshire and Stansberry, 1987); the low rankcoals are more sensitive to process conditions thanbituminous coals (Davis and others, 1976; Given and others,1980). Hydrogen consumption and yields of benzene-soluble products at longer residence times (>30 min) areroughly inversely proportional to rank (Gorin, 1981; Ignasiakand others, 1980; Neavel, 1976), which is in accord with thepotential of the lower rank coals to give higher distillateyields than bituminous coals under typical process conditions(Snape, 1987). Increasing distillate yields and maximumattainable oil yields with generally decreasing coal rank andincreasing H/C ratio may be related to the aromatic structureof coal becoming less condensed and to the increasingconcentration of aliphatic groups (Snape, 1987). Correlationsof aliphatic groups etc. with reactivity will be discussed inSection 8.4. Asphaltenes from lignites and subbituminouscoals are generally more aliphatic and contain less condensedaromatic structures than those from bituminous coals(Kershaw, 1985; Ladner and others, 1980).

The liquid products from the lower rank coals are morehighly oxygenated than those from bituminous coals, andfiltrate viscosity generally increases with decreasing coal

rank (Davis and others, 1976; Given and others, 1975a,1975b). Gas yields (CO, CO2, light hydrocarbons) alsoincrease with decreasing rank (bituminous rank and lower)(Berkowitz, 1985; Whitehurst and others, 1980).

The intermediate rank (bituminous) coals tend to reach theirultimate conversions very quickly. Highest yields have beenfound for the high volatile bituminous coals {see Figure 9),with coals of lower and higher rank than these giving loweryields although containing similar amounts of reactivemacerals (Given and others, 1975a; Whitehurst and others,1980). However, Strobel and others (1981) and Strobel andFriedrich (1981) found that in the Kohleol Process, themaximum oil yields occurred at a mean maximum vitrinitereflectance of between 0.5% and 0.6%. Davis and others(1976) predicted that the best coals for liquefaction wouldhave mean maximum vitrinite reflectances of between 0.49%and 1.02%, although coals outside this range are reactive andsuitable for liquefaction. In a study of mainly bituminousSouth African (Gondwanan) coals hydrogenated with orwithout anthracene oil, the highest conversion was obtainedfor coals with mean maximum vitrinite reflectance of 0.65%to 0.8% (Gray and others, 1980a, 1980b). This is within therank range predicted by Davis and others (1976) forAmerican (Laurasian) coals.

Figure 9 Variation of coal conversion with rank(Whitehurst and others, 1 980)

It appears that reactivity of coal is determined by itsstructure. For example, Whitehurst (1980) and Whitehurstand others (1980) have reported that for US (bituminous)coals containing 75-90% carbon (daf), short residence timeconversions correlated with fluidity and with pyridineextractability, all reaching a maximum at about 85% carbon(daf). At 82-88% carbon (daf), coal exhibits maximumfluidity and minimum cross-linking density in itsmacromolecular structure (Pullen, 1981; Snape, 1987). Thefact that lignite and subbituminous coals cannot be liquefiedto the same extent as bituminous coals at short residencetimes has been attributed to their sensitivity to thermaltreatment which can cause cross-linking (Derbyshire andStansberry, 1987), although other explanations are possible(Snape, 1987). The potential of low rank coals to easilycross-link could help resolve the lack of agreement on theeffect of rank in coal liquefaction. That is, low rank coals

Liquefaction

are more reactive, but how this is exploited depends on theprocess conditions. For example, the potential to cross-linkcan be removed by using a catalyst, hydrogen and lowtemperature (Derbyshire and Stansberry, 1987). Since rankdependence is process related, problems in classifying coalsindependently of the process conditions will occur. Also,structural features of the coal may need to be taken intoaccount. Structural parameters will be examined inSection 8.4.

To highlight differences in reactivity of coals and in order torank coals by their reactivity, Furlong and others (1981,1982) and Baldwin and others (1983, 1987) have proposed akinetic reactivity where coals are compared by means of rateconstants derived from conversions at a number of residencetimes, rather than by single conversion values. They foundthat whilst conversion to THF-solubles at long residence time(60 min) were fairly similar for eleven US low-pyrite highvolatile bituminous coals, conversion at short residence timeswere vastly different. No clear pattern of kinetic reactivitywith sub-rank was found, that is, the trend reported byNeavel (1976) was not followed. Given and others (1975a)also found no obvious trend of conversion with sub-rankwithin each category of the high volatile A, B or Cbituminous US coals, when liquefied using a catalyst andwith or without anthracene oil.

Instead of predicting coal behaviour from its variousproperties, this kinetically defined parameter could possiblybe used to rank coal reactivity for classification purposes.When measured by the forward rate constant, it has beencorrelated with various parameters, such as volatile matterand H/C atomic ratio (Baldwin and others, 1983, 1987;Furlong and others, 1981, 1982).

Guyot (1978a, 1978b) has suggested the use of the'petrofactor' as a means of predicting coal reactivity (seeFigure 10). This factor combines both rank and petrographiccomposition in one parameter. It is defined as:

petrofactor = 1000 x reflectance/reactive maceral content

where reflectance is the mean maximum reflectance ofvitrinite (%) and reactive maceral content is the mass percentof vitrinite plus liptinite. A correlation between thepetrofactor and conversion in tetralin for a range ofAustralian coals, as shown in Figure 10, has been found(Fletcher and Kelvin, 1980; Guyot, 1978a, 1978b). Parkashand others (1984b) also found a reasonable correlation forNorth Dakota and Texas lignites (correlation coefficient of0.67). The petrofactor could be calculated from parametersin the new international codification and so would beunnecessary as a separate classification parameter. However,the reactive maceral content does not include any of thereactive inertinites (see Section 8.3.1).

In a statistical study of the conversion of 68 US coals intetralin, Abdel-Baset and others (1978) showed that at leasttwo or three properties of coal are needed to predict coalreactivity. Cluster analysis on 15 coal characteristics hasbeen used by Yarzab and others (1980) to group over 100 UShigh volatile bituminous coals (on the basis of theirconversion in tetralin at 400°C) into three populations (seeFigure 11). Each group had markedly different liquefactionyields. Sulphur content was the major factor in separatingthe three populations, with a smaller contribution from rank.Thus cluster analysis can be used as a means of classifyingcoals. Unknown coals can be assigned to one of the threegroups using the derived discriminant analysis equations,provided the carbon and sulphur contents are known.However, only 102 out of the 104 coals were correctlyassigned, so some coals will be incorrectly 'classified'.

Multivariant analysis has been used to derive expressions topredict conversion or oil yields (for example. Hoover, 1983;

Figure 10 Correlation of coal conversion with petrofactor(Guyot, 1978b)

Figure 11 Cluster analysis on US bituminous coals(Yarzab and others, 1 980)

Liquefaction

Yarzab and others, 1980). These equations contain arank-related parameter and at least two other terms. Whenapplied by Yarzab and others (1980) on the three groupsseparated by cluster analysis, a different selection of coalproperties were derived for each group. For Group 1 (highrank (within the high volatile bituminous), medium sulphurcoals),

conversion = 34.8 Ro + 50.7 H/C + 0.16V + 30.5.

For Group 2 (medium rank, high sulphur),

conversion = 0.86 VM - 22.8 Ro + 1.39 St + 39.0

and for Group 3 (low rank, low sulphur)

conversion = 0.93 VM + 0.28 TRM - 1.7

where Ro is mean maximum vitrinite reflectance, H/C thehydrogen/carbon atomic ratio, V the total volume % vitrinite(dmmf), VM the weight % volatile matter (dmmf), St thetotal weight % sulphur (dry basis) and TRM the total reactivemacerals (volume % of vitrinite plus liptinite, dmmf).Therefore once a coal has been assigned to a group, theappropriate regression equation can be selected for predictingits conversion. Some of these parameters are included, forexample, in the new international codification and hence,coal conversion can be predicted from the relevantequation.

However, cluster analysis could not cope with all the 104coals in the sample set. Inclusion of some coals ('outliers')caused the statistical distribution to be skewed, and so thesehad to be excluded. The three groups could be distinguishedby their different geologic histories; for example Group 3comprised the Cretaceous coals from the Rocky Mountainregion. This suggests that liquefaction behaviour of any coalis directly influenced by its geologic history and sourcematerial (Berkowitz, 1988; Given and others, 1980; Yarzaband others, 1980). Thus the regression equations are validonly for the coals from the particular geologic region onwhich they were derived. Inclusion of coals from differentregions (for example Gondwanan) or of higher and lowerrank, would probably cause more groups to be discriminated,presumably each with a different regression equation forpredicting conversion. Application of this technique to allcoals found worldwide would probably become toocomplicated.

To conclude, rank on its own is a poor indicator of coalreactivity, but used with other parameters, it can be helpful inpredicting coal liquefaction behaviour. However, thecorrelations are useful only for the process conditions underwhich they were obtained. Bituminous coals are often thepreferred feedstock as lower rank coals are, in general, moredifficult to process. For example, the higher calcium contentof lignites can result in the deleterious formation anddeposition of calcium carbonate in the liquefaction reactor(Given and others, 1980). However, coals of similar rankcan display differences in their liquefaction behaviour andsome of the reasons for this will be discussed in thefollowing sections.

8.2 Chemical composition andproperties

8.2.1 Carbon and hydrogen

The correlation of carbon content with liquefaction yield waspartly covered in the previous section, as carbon content isused as a rank parameter. Generally conversion yielddecreases with increasing carbon content (for example,Ignasiak and others, 1980; Miller and Baldwin, 1985; Winansand others, 1983), with coals having a high carbon content(high rank bituminous and anthracites) giving lowliquefaction yields. However, some workers have found thatthe highest liquefaction yields were obtained from coals withabout 80 to 88 weight % carbon (Abdel-Baset and others,1978; Derbyshire and Whitehurst, 1981).

When Abdel-Baset and others (1978) used multipleregression analysis to derive a linear equation for predictingcoal conversion in tetralin from several coal characteristics, itincluded a term for total carbon content. In an extension ofthis work, Yarzab and others (1980) found that clusteranalysis partitioned a larger set of these bituminous coals intothree groups. Carbon content was one of the factors inseparating the coals, although the major factor was sulphur.However, a term for carbon content does not appear in anyof the three derived linear regression equations (seeSection 8.1). Using multivariate statistical analysis. Schultenand others (1988) derived a linear regression equation forpredicting the conversion at 60 min that does include a factorfor the coal carbon content:

conversion (%) = 80.2 - 1.1 C + 0.78 (O + N) + 1.4 VM

where C, O, N and VM are the weight % (daf) of carbon,oxygen, nitrogen and volatile matter, respectively. Only asmall sample of 20 subbituminous and bituminous Polishcoals was used. Mochida and others (1979) consider that thecarbon content is not an adequate index of liquefactionreactivity of a coal.

One would expect that a coal with a high hydrogen contentwould be the preferred feedstock for coal liquefaction (Durie,1982) since the liquid products have a higher hydrogencontent than the parent coals (Guyot, 1978b). However, notall coals with a high hydrogen content will give a highliquefaction yield. Given and others (1975b) found that oneWest Virginian (USA) lithotype with a high hydrogencontent (7%) gave essentially no conversion to oil whenreacted with a catalyst and with or without anthracene oil.Some other characteristic of the coal must be responsible forits poor conversion.

Few correlations have specifically related the hydrogencontent of coal with its liquefaction conversion. ForAustralian coals, hydrogen content provides a goodindication of their reactivity in tetralin (Fletcher and Kelvin,1980; Perry and others, 1982). Gutmann and others (1987b)found that the organic hydrogen content influenced the oilyield from brown coals (German Democratic Republic)hydrogenated in tetralin in molten salt baths at short

Liquefaction

residence time. Organic hydrogen contents had lessinfluence at a longer residence time.

One convenient way of correlating carbon and hydrogencontents with conversion behaviour is to use the Seyler chart.Figure 12 shows the extraction yields of UK coals inanthracene oil plotted on a Seyler diagram (Clarke andothers, 1980; Davis, 1978). This diagram enables thereactivity of a coal to be predicted for the same processingconditions. The extraction yields of the petrographicallydifferent Gondwanan coals in anthracene oil would probablyshow a different plot, since some Gondwanan coals plotoutside the coalification band shown in the figure (seeSection 6.1).

Figure 12 Coal conversion plotted on Seyler chart (Clarke,1980)

liquid with a low nitrogen content. Literature published upto the end of 1983 on oxygen in coal and coal liquids hasbeen reviewed by Zhou and others (1984).

Both nitrogen and oxygen contents of the extracts areinfluenced by those of the starting coal (Pullen, 1981) withthe coal extracts and distillates generally having loweroxygen and nitrogen contents than the parent coal (Guyot,1978b). Generally, both extract and distillate yields decreasewith increasing oxygen for coal liquefied in a solvent (Gorin,1981). Conversion and distillate oil yields correlated with theoxygen content of the feed coal in the Kohleol Process, withcoals with a low oxygen content having a low reactivity(Strobel and Friedrich, 1985). However, the correlation wasnot linear; maximum yield of distillate oils was achieved atabout 80% carbon (daf) and 10-12% oxygen (daf) contents(see Figure 13).

Figure 13 Correlation of oil yield with oxygen and carbon(Strobel and Friedrich, 1985)

The multiple regression equation derived by Schulten andothers (1988) for predicting conversion at 60 min includedthe oxygen plus nitrogen contents as one of the factors (seeSection 8.2.1). Winans and others (1986) found that bothorganic oxygen and sulphur can positively influence thereactivity of bituminous coal macerals under short contacttime liquefaction conditions. Solomon and others (1981)derived an expression correlating volatile matter yields forUS bituminous coals liquefied in tetralin at 400°C:

Volatile carbon has also been proposed as a parameter forcoal reactivity. It will be discussed with volatile matter(Section 8.2.5).

8.2.2 Oxygen and nitrogen

It is generally agreed that low oxygen and nitrogen contentsare preferable in coals for liquefaction. A high oxygencontent is a disadvantage because hydrogen is consumed inwater formation during the oxygen elimination processes, andthe cost of the hydrogen requirements can be a significantfactor in the operating costs of coal liquefaction plants(Durie, 1980, 1982; White, 1979). On environmentalgrounds and for ease of refining, one would prefer a coal

volatile yield = 0.8OT + 15Hai

where OT is the total oxygen content (wt% dmmf)determined by ultimate analysis and Hai is the aliphatichydrogen content (wt% dmmf) determined by Fouriertransform infrared spectroscopy. However, this equation isnot applicable to all coals.

Low rank coals (lignites and brown coals) have a highoxygen content, which could be a disadvantage duringliquefaction. However, in some processes this can be turnedinto an advantage by the in situ production of carbonmonoxide assisting in the elimination of oxygen ascarbon dioxide (Schafer, 1979). An advantage of the lower

Liquefaction

rank coals over the higher rank ones is their generally lowernitrogen content (Durie, 1982).

Although oxygen and nitrogen contents are of relevance incoal liquefaction, their importance does depend on theliquefaction process. A complicating factor for an oxygenparameter is the difficulty of its direct determination. Tokeep the classification simple, other factors may be of moreimportance and would therefore be preferred.

8.2.3 Atomic ratios

It has been suggested that diagrams based on the H/C andO/C atomic ratios can be used to classify coals (Murata,1986; Van Krevelen, 1961). Correlations of the H/C ratiowith reactivity for a variety of coals under differingliquefaction conditions have been observed. Conversions inanthracene oil or tetralin increased with increasing H/C ratiofor Gondwanan coals ranked below the medium volatilebituminous rank (Gray and others, 1980a, 1980b; Redlichand others, 1985). It gave one of the best statisticalcorrelations with conversion for Australian coals (Fletcherand Kelvin, 1980), although volatile matter gave a better one.However, Mori and others (1980) considered that thecorrelation was poor for Japanese coals liquefied in acreosote solvent. For vitrinite-rich bituminous (Laurasian)coals hydrogenated for only 3 min in a mixture of solvents,conversion to pyridine-solubles was a curve (instead of aline), with a maxima at around an H/C ratio of 0.75(Whitehurst and others, 1980).

In the regression equations for predicting coal conversionderived by Yarzab and others (1980) for the three groups ofUS high volatile bituminous coals separated by clusteranalysis, only one includes a factor for the H/C ratio (seeSection 8.1). This was for the group of highest carbon andintermediate sulphur content. However, only a fairly narrowrank range of coals was covered. They also found that underprincipal components analysis for each of the three groups,both the O/C atomic ratio and oxygen content correlatedstrongly with the first factor (rank). However, it is puzzlingthat the loadings for group 3 were of opposite sign than thosefor groups 1 and 2. No term for the O/C ratio appears in anyof the three regression equations for predicting coalconversion.

Oil yields, particularly for Gondwanan coals, have beenfound to increase with increasing H/C ratio (for example,Chaffee and others, 1986; Durie, 1980; Fletcher and Kelvin,1980; Perry and others, 1982, 1983; Redlich and others,1985, 1986). This is attributed to the increasingconcentrations of aliphatic groups (Snape, 1987). However,Gray and others (1980a; 1980b) found that the correlation forSouth African coals (hydrogenated without a solvent) was acurve rather than the straight line obtained by other workerson Australian coals liquefied in a solvent (Perry and others,1982, 1983; Redlich and others, 1985, 1986). The SouthAfrican coals did contain some anthracites which may beresponsible for the curve (see Figure 14). The correlationbetween the O/C atomic ratio and conversion or distillateyields was not statistically significant for Australian coalsliquefied in tetralin (Fletcher and Kelvin, 1980).

Figure 14 Relationship of oil yield with H/C atomic ratio(Gray and others, 1980b)

The high oxygen content of low rank coals tends to limit oilyields. Redlich and others (1985) showed that if the oilyields and H/C ratios are corrected for the carbon dioxideformed (from the carboxylic acid groups) duringhydroliquefaction, the correlation for low rank Australiancoals is improved (see Figure 15).

Figure 1 5 Relationship of oil yield with H/C atomic ratio,on a CO2-free basis (Redlich and others, 1985)

The relationships between oil yields and H/C ratio is not asstraightforward for Laurasian coals as for their Gondwanancounterparts (Snape, 1987), because distillate yields can be ata maximum for bituminous coals. Poor correlations werealso obtained on lithotypes of East German brown coalsliquefied in tetralin with a catalyst (Gutmann and others,1987a). Wolfrum (1984) found that Rhenish (West German)brown coals with a high or low H/C ratio gave a highproduct yield when reacted with hydrogen and a catalyst.Generally, Rhenish brown coals with an H/C ratio of lessthan 1.1 were suitable for hydrogenation.

Liquefaction

Thus H/C atomic ratio could provide a useful indication ofcoal reactivity during liquefaction for Gondwanan coals,although there are exceptions. One Australian subbituminouscoal (Callide) gave an anomalously high oil yield in relationto its H/C ratio (Chaffee and others, 1986; Redlich andothers, 1986). It possesses an unusually high non-acidicoxygen content and it is suggested that the distinctdepositional and coalification history of the Callide may haveresulted in different chemical and structural characteristicswhich are causing these differences. However, for Laurasiancoals more care would be needed in interpreting the H/Cparameter. The conversion trend of inertinite maceralfractions in tetralin at 6 min deviated from that of vitriniteand liptinite (King and others, 1984), suggesting that the H/Cratio is not sufficient by itself to predict reactivity of maceralfractions, and probably not for whole coals as well. Thecorrelation with O/C ratio does not appear to be significant.

8.2.4 Sulphur

In this section the effects of organic and total sulphurcontents on coal liquefaction will be discussed. Both thenew ECE and Australian 'classifications' include totalsulphur content as a parameter. Inorganic sulphur (mainlypyrite) will be covered in Section 8.2.7.

The presence of sulphur can be detrimental in combustionand coking, but there is evidence that this is not the case inliquefaction, due to its possible catalytic effect. More workhas been carried out investigating possible catalytic effects ofpyrite than on organic sulphur. However, some catalyticeffects of organic sulphur have been observed. For example,an increase in distillate yield with increasing organic sulphurand total sulphur contents was found for four Wyodak(Wyoming) subbituminous coals liquefied in two coal-derived solvents (Miller and Baldwin, 1985). However, nodefinite trend with pyritic or sulphate contents was observed,possibly because any catalytic effects may have been maskedby the use of the two high quality liquefaction solvents.Trewhella and Grint (1987) have recently reviewed the roleof sulphur in hydroliquefaction.

In the regression equation derived by Yarzab and others(1980) (see Section 8.1) for the whole data set of bituminouscoals, total sulphur content was an important factor inpredicting coal conversion. Principal component analysisindicated that the contents of organic and pyritic sulphurindependently promoted liquefaction. Total sulphur contentwas the major controlling factor that classified the coals intothe three groups separated by cluster analysis. However,only one of the regression equations derived to predictliquefaction conversion contains a factor for sulphur content,that for the highest sulphur coals of intermediate carboncontent. Further study of a subset of 26 coals from this highsulphur group by I?C nmr spectroscopy showed that thegroup was more heterogeneous than expected (Neill andothers, 1987a, 1987b). Essentially no correlation betweenaromaticity and carbon content was found, unlike variousother sets of coals for which similar data are available. It issuggested that the heterogeneity arises at least partly fromvariation in the distribution of the types of structurecontaining the organic sulphur. This could possibly be one

explanation for the observed differences in behaviourbetween coals of similar organic sulphur content.

In a study of Gondwanan coals, poor statistical correlationswere found between the organic or total sulphur contents andconversion or distillate yields, when the Australian coalswere liquefied in tetralin (Fletcher and Kelvin, 1980).Gondwanan coals generally have lower total sulphur andpyrite contents than Laurasian coals; but the reverse isgenerally the case for organic sulphur (White, 1979). Mostof the organic sulphur will end up in the liquid products.

The reactivity of 20 brown coals (German DemocraticRepublic) hydrogenated in tetralin in a molten salt bath wereevaluated by kinetic modelling by Gutmann and others(1987b). They found that in the first steps of thehydrogenation reaction, the rate constants correlated with the'combustible' sulphur content. Additional parameters wererequired for correlations at longer residence times (>60 min).

To conclude, the sulphur content could serve as a possibleindicator of the coal reactivity. However, any uncertainty inorganic sulphur determination (see Section 2.5) could haveimplications for the postulated correlations. Total sulphurcontent could prove to be a better parameter than the organicsulphur content.

8.2.5 Volatile matter

The volatile matter yield has been correlated with somesuccess with the reactivity of coal, although, like otherparameters, it is dependent on the liquefaction conditions.Generally, conversion decreases with decreasing volatilematter (Given and others, 1980; White, 1979). However, ahigh volatile matter does not necessarily mean a highconversion yield; for example a West Virginian lithotypewith a high volatile matter (52.5% dmmf) gave essentially noconversion to oil, whereas other lithotypes with lowervolatile matter gave good oil yields (under the sameexperimental conditions) (Given and others, 1975b). Thissuggests that volatile matter will need to be used inconjunction with other classification parameters.

Correlations of volatile matter with both total conversion andoil yields have been reported for brown coals (for example,Gutmann and others, 1987; Perry and others, 1982).However, for the Australian brown coals. Perry and others(1982) found that the H/C atomic ratio was a betterparameter for conversion, probably due to the elimination ofdifferences from the thermal decomposition of oxygen-containing functional groups which would be included in thecoal volatile matter.

Good correlations with both conversion and distillate yieldshave been found for Gondwanan bituminous coals (Fletcherand Kelvin, 1980; Gray and others, 1980a, 1980b). Howeverfor Laurasian bituminous coals, correlations have met withmixed success. Baldwin and others (1987) report that thevolatile matter gave one of the best correlations with coalreactivity (when reactivity was defined by the kinetic rateconstant); but Hoover (1983) did not find volatile matter tobe an important parameter for predicting coal reactivity for

Liquefaction

thirteen Kentucky subbituminous and bituminous coals(under SRC-I processing conditions). Some multipleregression equations have been derived that contain a termfor volatile matter, for example, the one derived by Yarzaband others (1980) for predicting conversion for the wholedata set of US bituminous coals and one derived by Schultenand others (1988) on Polish coals. However, not allregression equations contain a volatile matter term. Mori andothers (1980) also found no clear relationship betweenvolatile matter and conversion for Japanese Tertiary coals.

It has been suggested that volatile carbon may be a betterindicator of coal reactivity than volatile matter for coalshaving significant rank variation, since it eliminatesdifferences due to the thermal decomposition ofoxygen-containing functional groups which are normallyincluded in the coal volatile matter (Mori and others, 1980;Perry and others, 1982, 1983). Volatile carbon is defined as:

volatile carbon (wt%) = C - 100 x FC/(VM + FC)

where C is the carbon content (wt% daf), FC the fixedcarbon content (wt%) and VM the volatile matter yield(wt%). Using data from other published work and from theirown work on some Japanese coals and Australian browncoals (Morwell and Yallourn), Mori and others (1980) foundthat the characteristics of the relationship between reactivityand volatile carbon content were almost the same, despitedifferences in liquefaction conditions and different coaltypes. However, coals with a high sulphur or high inertcontent were exceptions and the effect of catalysts was largerin coals of lower volatile carbon content. Generally, coalswith a high volatile carbon content were more reactive thanthose with a lower volatile carbon content.

To conclude, volatile matter alone does not seem to correlatewell with hydrogenation behaviour for all coals and so canbe used only in conjunction with other parameters. Theobserved correlations are dependent on the liquefactionconditions and on the coal used. However, volatile matter isan easily determined parameter (see Section 2.6) and is oneof the most common properties used in current establishedclassification systems. No classification system has yetproposed the inclusion of volatile carbon as a parameter.

8.2.6 Moisture

Coals with a low moisture content are preferred inliquefaction since the presence of water can retard thehydrogenation reaction (Lenz and others, 1982; White, 1979).The high moisture content of low rank coals could be adisadvantage, since these coals would first need drying witha consequent thermal penalty. However, the moisturecontent can be turned to advantage in some processes, suchas the Costeam Process where carbon monoxide is used(Durie, 1982; White, 1979). Conversion yields ofsubbituminous coals and lignites in direct coal liquefactionprocesses are sensitive to the method and degree of coaldrying (Cronauer and others, 1984; Silver and others, 1986;Tomlinson and others, 1985). Drying lignites beforeliquefaction lowers the yield of light oil products, possiblybecause of oxidation.

Although moisture plays a part in coal liquefaction, it isprobably not of enough importance to warrant its use as aseparate classification parameter, especially if theclassification is to be kept simple.

8.2.7 Inorganic constituents

Mineral effects in coal conversion has been the subject of aseparate IEA review by Davidson (1983). Catalytic effectsduring solvent extraction of coal was also covered in anotherIEA review (Pullen, 1981) and a review by Given (1983)includes a section on the effect of mineral matter in coalliquefaction. These reviews showed that there are chemicaland/or catalytic effects associated with the inherent mineralmatter in coal. Studies have particularly implicated pyrite(and pyrrhotite) as the mineral whose presence can affectconversion yields (Trewhella and Grint, 1987), althoughsome differences in pyrite catalysis activity have beenreported.

Conversion of coals of low sulphur content have beenincreased by the addition of pyrite, which tends to reduce theviscosity of the products and to increase oil yields; however,coals differ in their response to pyrite addition (Given, 1983).Addition of pyrite to US lignite and subbituminous coalsunder SRC-II processing conditions increased the overallconversion and increased the distillate yields with decreasingrank (Tomlinson and others, 1985; Wright, 1982).Specimens of pyrite isolated from various coals havedifferent levels of effect in promoting liquefaction of lowsulphur coals (Davidson, 1983; Given, 1983).

Multiple regression equations derived for predictingconversion or oil yields often contain a term for sulphurcontent (Hoover, 1983; Yarzab and others, 1980), althoughonly the equations derived by Hoover (1983) contain a termspecific to pyritic sulphur content. However, any uncertaintyin the pyritic sulphur data (see Section 2.5) could haveimplications for the postulated correlations with liquefactionperformance. It is worth noting that the solvent compositioncan also affect the catalytic activity of the minerals(Derbyshire and others, 1981).

The role of pyrite also highlights the difference betweenmany of the Laurasian and Gondwanan coals, where theformer generally contain higher pyrite levels than the latter(Durie, 1982; White, 1979). Some high sulphur Australiancoals are known, for example the Gelliondale (Victoria)brown coals, where the catalytic effect of pyrite duringhydrogenation was recognised as early as the 1930s (White,1979).

Hoover (1983) has suggested that not only the amount butthe form (dispersion) of the pyrite in the coal is important inpromoting coal liquefaction, with the latter being the moreimportant. The majority of the catalytic activity wasprovided by the finely dispersed pyrite in US coals (underSRC-I processing conditions). Since Gondwanan coalsgenerally contain more finely disseminated syngeneticminerals than the Laurasian coals (Falcon, 1977), this couldpartly explain some of the differences in their liquefactionbehaviour.

Liquefaction

There is also evidence of possible catalytic effects ofminerals other than pyrite, such as the alumino-silicates(clays), acting as cracking catalysts (Davidson, 1983; Durie,1982; Given, 1983). However, there is not enough evidenceof their importance in promoting liquefaction for their use asclassification parameters in their own right.

Some inorganic elements (cations) are present in coal asorganometallics, chelates or absorbed species (as well as inthe mineral matter). Generally it is only in the lower rankcoals that these bound cations are of importance, principallycatalytic effects from the alkali and alkaline earth metals andiron. For example, Given and others (1975a) found thatsodium associated with the carboxyl groups had abeneficial catalytic effect with regard to quality of liquidproduct - the liquid products from sodium-rich US ligniteshad lower viscosities than those from sodium-poorlignites. These cations are covered in the review byDavidson (1983).

Whilst the presence of mineral matter and bound cations incoal can be an advantage, there are some disadvantages. Forexample, some minerals can poison added catalysts (White,1979). They can form solid deposits in the reactor which canlead to reduced conversion, enhanced abrasive rates, poorheat transfer and blockage problems (Given and others,1980). The calcium present in low rank coals (lignites andsubbituminous) can cause deposition and blockage problems(Given and others, 1980; Perry and others, 1984; Tauntonand others, 1981) due to calcium carbonate formation.However, the calcium carbonate (and possibly otherminerals) could act as a sulphur scavenger, reducing thesulphur content of the liquid products, with obviousenvironmental advantages (Davidson, 1983).

The use of parameters in a classification system to representthe inorganic portion of a coal could be an advantage in coalliquefaction, as well as in the trading of coal. However,since the catalytic effects of the mineral matter is mainly dueto pyrite, a parameter representing the pyrite content wouldprobably be sufficient. A better parameter may be the totalsulphur content, which includes pyritic sulphur.

Strobel and co-workers (Strobel and Friedrich, 1981, 1985;Strobel and others, 1981) investigated the effects of somecoal parameters on distillate oil yield in the KohleSl Process.They found that an increase in mineral matter in coal wasresponsible for the reduction in net oil yields but with noeffect on overall conversion. This resulted from what istermed the 'ballast effect'. Different optimum temperatureswere found for different mineral matter contents in coal andoptimum oil yields were also related to specific amounts ofcatalyst. Both these effects could be explained only if theballast effect was taken into account. As a result, Strobeland Friedrich (1981) propose correcting the oil yields for theballast effect by computing yields on a standard coal mineralmatter content of 4% (dry basis). Correlations with severalcoal properties were then obtained (for example oxygen andcarbon contents, see Figure 13). They also suggest that foran economical liquefaction process, one would be moreinterested in correlations with the product yield than thedegree of conversion.

8.3 Petrographic composition andproperties

8.3.1 Maceral composition

Coals of similar elemental composition can give differentextraction yields and these have been explained by referenceto their maceral composition. This has led to a number ofclassification systems being proposed that include themaceral contents as classification parameters.

Liquefaction appears to be the most sensitive of all coalconversion processes to petrographic composition (Neavel,1981), but the contribution of the various petrographicconstituents is dependent on the process conditions. It hasbeen established under a wide range of liquefactionconditions that the vitrinite and liptinite group macerals incoal of bituminous rank and lower are readily liquefied (forexample, Davis and others, 1976; Given and others, 1975a,1975b; Kalkreuth and Charnet, 1984; Parkash and others,1985). The order of reactivity of the maceral groups isgenerally accepted to be, in descending order,

liptinite > vitrinite > inertinite

(for example, Heng and Shibaoka, 1983; Parkash and others,1985). Vitrinite-rich subbituminous and bituminousCanadian Cretaceous coals liquefied in tetralin gave higherliquid and lower gas yields than the liptinite-rich coals(Kalkreuth and Charnet, 1984). An increase in liptinitecontent improved the coal conversion rate, while an increasein huminite reduced carbon conversion rates of Rhenishbrown coals liquefied in tetralin (Wolfrum, 1984). Coalswith a high bituminite content (a liptinite maceral) producedhigh oil and relatively low asphaltene yields in tetralin(Shadle and others, 1986) and so would be preferred asfeedstocks. Although pseudovitrinite is not reactive incoking, it has been shown to be reactive in liquefaction(Davis and others, 1976; Given and others, 1975b, 1980).

It is now generally accepted that part of the inertinite groupmacerals, particularly low reflectance semifusinite, arereactive and can contribute significantly to overallconversions in inertinite-rich coals (for example, Given andothers, 1980; Heng and Shibaoka, 1983; Mochida and others,1987; Parkash and others, 1985; Shibaoka and others, 1983;Snape, 1987). The inertinites produce low yields of oil andasphaltene but larger oil-to-asphaltene yields than the othertwo groups (Collin and others, 1983; Heng and Shibaoka,1983; Parkash and others, 1985; Shibaoka and others, 1984,1985a). Some of the differences in behaviour between themaceral groups have been explained by their differentreaction pathways (Shibaoka and Heng, 1984; Shibaoka andothers, 1985a).

The reactivity of coal has been correlated with some successwith its maceral composition. For vitrinite-rich bituminousand subbituminous coals, such as the Laurasian coals,correlations of vitrinite plus liptinite content with reactivitywere observed (for example, Davis and others, 1976; Givenand others, 1975b). When Furlong and others (1981) and

Liquefaction

Baldwin and others (1987) ranked US bituminous coalsaccording to their rate of liquefaction (see Section 8.1), thekinetic reactivity correlated reasonably well with the fractionof reactive macerals, defined as follows:

fraction of reactive macerals = (V + L — S)/(100 - I)

where V is vitrinite with reflectance between 0.1% and 0.6%,L liptinite, S sporinite and I inertinite, each as mass percenton a daf (or dmmf) basis. Both inertinite and sporinite aretreated as being unreactive, although most workers (such asDavis and others, 1976; Given and others, 1975b; Winansand others, 1986) consider sporinite and low reflectanceinertinite to be reactive.

Most of the multivariate regression equations for predictingconversion contain a term either for the 'total reactivemaceral' content (that is, vitrinite plus liptinite) or for thevitrinite content (Hoover, 1983; Yarzab and others, 1980).However, all these correlations and equations are valid onlyfor the coals on which they were derived or possibly forcoals with similar source materials and geologic history.They are inappropriate for Gondwanan or other inertinite-richcoals. For example, Gray and others (1980a, 1980b) foundthat when semifusinite is included in the reactive maceralcontent for South African coals, much better correlationswith conversion are obtained.

Correlations with huminite and liptinite contents have beenfound for brown coals and lignites including those from theUSA (Parkash and others, 1984b), Australia (Nomura andothers, 1982), Spain (Legarreta and others, 1987) and WestGermany (Lenz and others, 1982). However, Gutmann andothers (1987a) consider the correlation of liptinite with oilyield was poor (r = 0.78) for brown coals from the GermanDemocratic Republic. A better correlation was obtained withthe ungelified macerals.

and fusinitisation of the macerals (Parkash and others, 1984a,1984b; Shibaoka and others, 1985a).

The same macerals found in different coals may not bechemically identical. Structural differences have been foundbetween inertinites (Wilson and others, 1984) and vitrinites(Shibaoka, 1982; Stephens and others, 1985) in Laurasianand Gondwanan coals. Consequently, their liquefactionproducts are unlikely to be the same. There is also someevidence of structural differences between vitrinite withinLaurasian (British and US) coals (Mudamburi and Given,1985). Thus a classification (such as the new internationalcodification) which includes the contents of inertinite,vitrinite or liptinite may not accurately predict theliquefaction behaviour of coal. A classification based on the'reactive' and 'inert' constituents of coal could be worthinvestigating, provided agreement on the definition of'reactive' and 'inert' could be reached. Also, a simple andreliable method for this determination would be required.

8.3.2 Reflectograms

A method has been developed for predicting coal reactivityfrom its reflectogram (Riepe and Steller, 1985, 1987). Thetotal reflectance-frequency distribution (reflectogram) is usedto separate reactive and inert constituents of coal, without theneed to identify the individual macerals. An algorithm wasused that fixes the limit of reactive and inert portions in thetotal reflectogram, starting from the highest frequency, to a0.3% to 0.35% higher vitrinite reflectance value. Thereactive portions thus derived were correlated withconversion of the coal in a solvent (see Figure 16), althoughthere is some scatter in the points. The method assumes thatmacerals with the same reflectance have the same reactivity.How generally this method would work is thereforedebatable.

Problems can occur if the petrographic composition is usedfor classification purposes. Coals with the same maceralcomposition and identical reflectograms can behavedifferently during hydrogenation due to differences in theintergrowth of the macerals (microlithotypes) (Steller, 1987a,1987b). Shibaoka and others also found that themorphological properties (such as particle size andintergrowth) of macerals had an effect on their reactivity.Synergistic effects between macerals in short residence timeliquefaction have been reported (Parkash and others, 1985),suggesting that the liquefaction behaviour of whole coalsmay not always be consistent with that expected from theirmaceral analysis. However, Heng and Shibaoka (1983) andHeng and others (1983) found no sign of synergism betweenmacerals in Australian bituminous coals liquefied for longertimes.

A classification system should only include parameters thatbehave uniformly. However, the reactivity of the maceralsvaries within each group (King and others, 1984; Winans andothers, 1986). This is particularly seen within the inertinites,where not all of them are chemically 'inert'. Differences inbehaviour within the vitrinite/huminite group occur and havebeen attributed to differences in the degree of gelification

Figure 1 6 Relationship of coal conversion with reactivityvalues derived from the total reflectograms(Riepe and Steller, 1987)

73

Liquefaction

8.4 Potential analytical techniques

8.4.1 Differential scanning calorimetry

Linares-Solano and others (1987) have investigated thepossibility of using differential scanning calorimetry (DSC)to measure the heat evolved during hydrogenation of coal inhydrogen and, from this, to predict the liquefaction behaviourof coal in a solvent (tetralin). The greater the amount of heatevolved, the greater would be the conversion. A plot ofconversion against the heat of hydrogenation (Q, measuredon the basis of the coal starting weight, in J/g) gave a linearequation. However if two of the coal samples (PSOC 290and 265) are excluded, the linear equation

conversion (%) = 0.018 Q + 46.8

is obtained, with a correlation coefficient of 81% (seeFigure 17). An explanation for the behaviour of these two

outliers has not yet been found, although PSOC 290 did havethe highest volatile matter and total sulphur contents andPSOC 265 the lowest pyritic sulphur and a low total sulphurcontent. Since two out of the small sample set of 25 USbituminous coals needed to be excluded in order to obtain agood correlation, whether the heat of hydrogenationdetermined by DSC could be used to predict coalliquefaction behaviour needs further investigation.

Figure 17 Relationship of coal conversion with heat ofhydrogenation (Q) (Linares-Solano and others,1987)

8.4.2 Pyrolysis-mass spectrometry

Pyrolysis-mass spectrometry (py-ms) (see Section 5.3) hasbeen proposed as a method for rapidly screening coals topredict their performance during liquefaction (Baldwin andothers, 1983, 1987; Durfee and Voorhees, 1985; Meuzelaarand others, 1981; Voorhees and others, 1983). Py-ms datahave been correlated with the reactivity of coal and thuspossibly a parameter (or a series of parameters) could bederived that may be useful in classifying coals. For example,statistical analysis (principal component (factor) analysis

followed by stepwise regression analysis) of the compositespectra from 47 PSOC bituminous coals (from the Penn Statesample bank) enabled Durfee and Voorhees (1985) tocorrelate the peak intensities of the Curie point py-ms spectrawith conversion to the ethylacetate-solubles reported byYarzab and others (1980) (see Section 8.1). Equations formodelling and predicting coal reactivity were derived. It isinteresting to note that the reactivity of the two coalsdescribed as outliers by Yarzab and others (1980) werepredicted to within 4%. Whether the model can be appliedto other coal types needs further investigation. An attemptby Harper and others (1984) to correlate py-ms data withliquefaction yields from the same tubing bombhydroliquefaction experiments of Yarzab and others (1980)failed, possibly because of the relatively small variation inconversion yields (58.8-73.1%) in the sample set of coals.

Baldwin and others (1987) have also successfully used thesame method to correlate the conversion of USsubbituminous and bituminous coals (from the Exxon andPenn State sample banks) to THF and toluene-solubles withpy-ms. Linear correlations of py-ms data with the kineticreactivity at short conversion time was not very successful;however, conversion at 60 min is considered to be morepromising.

Pyrolysis-mass spectra have been used to trace componentsof the chemical structure of a coal which correlate with highliquefaction yield and could therefore be used to help predictthe composition of the liquids produced (Voorhees andothers, 1983). In the work discussed above by Durfee andVoorhees (1985), peaks due to phenols or aryl esters gavepositive correlations with conversion to ethylacetate-solubles,while those due to naphthalenes gave negative ones (seeFigure 18). A positive correlation of reactivity with sulphurcontent (as found by Yarzab and others (1980)) was also

Figure 18 Factor spectrum for coal conversion toethylacetate-solubles (Durfee and Vorhees,1985)

Liquefaction

observed. Whether these correlations have any real chemicalsignificance and hence their possible use as classificationparameters, needs further investigation.

Several other coal properties that are of importance in coalliquefaction have been correlated with py-ms data and thusmay, in principle, be predicted from the pyrolysis-massspectra {see Section 5.3). These include rank (aromaticity),organic sulphur content and maceral content. Schulten andothers (1988) also found that a number of py-ms (fieldionisation) peak signals correlated with conventional coalparameters (ultimate and proximate analyses data) and hencecould be used for prediction of coal conversion at 60 min.

8.4.3 Nuclear magnetic resonance

Nuclear magnetic resonance (nmr) spectroscopy {see Section5.2) has been used to investigate the chemical structure ofcoal, which influences its reactivity during liquefaction.Correlations of nmr data with reactivity have been found,offering the possibility of deriving a parameter (orparameters) that could be useful for classification purposes.

Various functional groups have been shown to influenceliquefaction. Nmr spectroscopy can provide an estimate ofthe proportion of atoms (generally, carbon, hydrogen andoxygen) in the various functional groups and so could, inprinciple, be used to predict liquefaction yields. Forexample, nmr spectra have revealed the importance ofaliphatic structures. Baldwin and others (1983, 1987) founda good correlation between aliphatic-to-aromatic ratio of theparent coal with the forward rate constant of the liquefactionreaction. Thus with increasing aliphaticity, coals areincreasingly reactive and therefore a coal with a highaliphatic content would be the preferred feedstock in someliquefaction processes. The increase in maximum attainableoil yields with generally decreasing rank is attributed to alarge extent to the increasing concentration of aliphaticgroups (Snape, 1987).

Yoshida and others (1984, 1985) investigated the reactivityof coal as reflected by the oil yield. Liquefaction was carriedout under hydrogen in the presence of a catalyst but withouta solvent. The correlation between oil yield and aliphaticcarbon content was poor; however, a better correlation wasobtained with the methylene (CH2) content (estimated byI3C nmr spectroscopy). Thus CH2 content could possibly beused to predict oil yields in a classification system.

Structural differences among coals of similar rank areimplied by their nmr spectra (Given, 1984; Newman andDavenport, 1986). For example, the latter workers found thatAustralian brown coals had weak methylene (CH2) signalswhereas New Zealand lignites had strong methylene signals;thus one could expect differences in their oil yields. Eventhough these coals had similar total oxygen contents, theirnmr spectra showed differences in the distribution of theoxygen between the various functional groups. Thereforenmr spectra can help explain why coals behave differentlyduring liquefaction although their ultimate analyses are thesame. Newman and Davenport (1986) suggest using nmrspectroscopy to classify coals as coals of similar organic

structures (and presumably similar chemical behaviour)would then be gathered together. Traditional rankingclassification schemes, such as the ASTM, classify theAustralian brown coals and New Zealand lignites in the sameclass, although their liquefaction behaviour is different.

Nmr spectra can help explain differences in liquefactionbehaviour of macerals. Inertinite has been shown to have thehighest aromaticity, followed by vitrinite and then liptinite(Pugmire and others, 1983; Wilson and others, 1984). Thespectra have also indicated that much of the material ininertinite consists of aromatic structures that are too highlycondensed to be liquefied easily (Snape, 1987), whichexplains their generally poor liquefaction behaviour. I3C nmrhas also indicated differences between the structure ofinertinite in Laurasian and Gondwanan coals (Wilson andothers, 1984), which could help explain differences in theirliquefaction behaviour.

Thus nmr spectroscopy has the potential for predicting thereactivity of coal during liquefaction and therefore, parts ofthe spectra could be used for classifying coals. H nmrthermal analysis (for example, Sakurovs and others, 1987a)may also have potential for classifying coals for liquefactionpurposes. The method is discussed in Section 9.5.1 (forcoking coals). More work, however, is needed on thedetailed characterisation of coal in order to establish othercorrelations which could be used to predict coal liquefactionbehaviour. . • -,;

8.4.4 Fourier transform infraredspectroscopy

Fourier transform infrared (FTIR) spectra {see Section 5.4)have been correlated with coal conversion and couldtherefore be used to predict liquefaction yields. For example,Senftle and others (1984) found that the liquefactionconversion (determined as the yield of ethylacetate-solubles)of US bituminous coals and vitrinite concentrates in tetralincorrelated with the intensity of the band at 2853 cm'1, ratherthan the total aliphatic CH content. This band is a measure ofthe methylene (CH2) content, which has also been correlatedwith liquefaction yield using nmr techniques {see previousSection). The liquefaction conversion was also found tocorrelate with the phenolic OH group bands. Wheninvestigating US bituminous coals using py-ms, Durfee andVoorhees (1985) also found a correlation between phenolsand conversion to ethylacetate-solubles {see Section 8.4.2).In a study of Australian coals of various ranks and theirliquefaction products, a good correlation between the 3200cm"1 band from the coal and asphaltene spectra and theatomic O/C ratio of the coal was obtained (Larkins andothers, 1986). This allowed various deductions about thenumber of phenolic groups in the coal and their role inliquefaction to be made.

Youtcheff and others (1986) have shown the importance ofthe presence of cleavable ether groups (such as -O-CH2).Therefore, presumably a coal with a high ether content wouldbe more easily liquefied than one with a lower content andwould be the preferred feedstock in some liquefactionprocesses. Solomon and others (1981) {see Section 8.2.2)

Liquefaction

derived an equation for predicting the volatile yield in coalliquefaction from the total oxygen content (determined byultimate analysis) and the aliphatic hydrogen content(determined from FTIR measurements). However, theequation is not applicable to all coals; for example, it did notapply to a group of high sulphur coals.

Supaluknari and others (1988) used FTIR to measure thealiphatic and aromatic hydrogen contents in a suite ofAustralian coals and their products after liquefaction intetralin. The aliphatic hydrogen contents showed a strongcorrelation with coal H/C values and also with oil yields andwith the total hydrocarbon products. Different trends wereobserved for the higher rank coals and for the brown coals.The authors suggest that the correlation of coal aliphatichydrogen content with total hydrocarbon product yield maybe useful in predicting the conversion reactivity of a coal.

Thus FTIR offers the potential for predicting liquefactionyields and following changes in the organic structure of coalduring liquefaction. It has also shown the possibility ofusing new parameters, such as aliphatic hydrogen ormethylene (CH2) groups, as classification parameters thatcould be used to predict liquefaction yields. Other coalproperties have been correlated with the FTIR spectra {seeSection 5.4) and could therefore, in principle, be predictedfrom the spectra. These predicted properties (such as volatilematter) could then be used to evaluate an unknown coalusing the correlations previously discussed. However, thismethod would probably not be as accurate as a directdetermination of the required property.

8.5 CommentaryThere is not yet sufficient agreement internationally on theproperties of coal that are important in its evaluation forliquefaction to allow the relevant indices for a classificationto be identified. One of the requirements of a goodclassification is that it should be able to identify the mostappropriate coal for a particular process. This is complicatedby the fact that different properties may be of more relevancein different liquefaction processes; the process chosen willalso depend on the products required. As well as the coal'sproperties, conversion is heavily dependent on the solvent,process conditions and configuration used. Liquefactionprocesses are still being developed and future processes mayhave different requirements from those of today.

Attempts to correlate individual coal parameters withconversion levels were found to be unsatisfactory; at leastthree parameters must be considered. In order for aclassification to be kept simple and easily memorable, thenumber of parameters should be kept to a minimum. Aclassification should also be able to predict the behaviour ofa coal. When restricted to specific process conditions,various correlations for predicting coal conversion from coalanalysis data have been found and these can indicate whichproperties may be useful indicators of liquefactionperformance. All the correlations include a rank-relatedparameter, such as vitrinite reflectance or volatile matter.These correlations have shown that different criteria arerequired to rationalise overall conversions and distillate or oil

yields. However, care is required in using these correlationsto predict conversion yields. Many of the correlations weredetermined on only a small sample set of coals (for example,Hoover, 1983) and whether they can be generalised for allcoals is highly questionable. The correlations will beapplicable only to the coals on which they were developed(that is, coals from the same geologic region and with asimilar geologic history) and under the same reactionconditions. Also, there could be a difficulty in transposingexperimental results (determined in small-scale apparatus) tofull-scale commercial plants.

The maceral composition can be a useful indicator ofliquefaction performance for coals from a particular geologicregion. The use of maceral composition has been proposedin several classification systems. However, there is the'inertinite problem'; the relationship between inertinite andliquefaction behaviour is different for Gondwanan coals thanfor Laurasian ones. Instead of maceral composition, aclassification based on 'reactive' and 'inert' constituentsmay be worth investigating. This will depend, of course, oninternational agreement on what constitutes the reactive andinert portions of coal, and on a simple and reliable methodfor their determination. However, it seems unlikely that adefinition suitable for all coals will be found. Variousdefinitions of reactive maceral content have been proposed(for example, Furlong and others, 1981; Yarzab and others,1980) but are not valid for all coal types. Mochida and others(1987) found that an equation (total inerts = two-thirdssemifusinite + fusinite + micrinite) that has been used withsome success to predict the coking behaviour of vitrinite-richcoals is inappropriate for coal liquefaction. They alsoshowed that maceral analysis by automatic reflectancemeasurement, a technique successful in the coking industry,is not always appropriate in coal liquefaction.

Neavel (1986) and Neavel and others (1981) however,consider the maceral composition to be unnecessary, if theultimate analysis of coal is known. Some of the fundamentalproperties of coal can be calculated from their elementalanalysis (Neavel and others, 1980, 1986) and henceliquefaction yields can be predicted. The correlations weredetermined mainly on American coals containing more than80% vitrinite; whether the same equations can be used forinertinite-rich coals needs investigating. Again, the ultimateanalysis is not always a reliable indicator as coals of similarelemental composition can give different extraction yields(Pullen, 1981).

Generally, coal with a high hydrogen content and lowoxygen, nitrogen and sulphur contents are preferred. TheSeyler chart has been used with some success for predictingliquefaction yields (Clarke and others, 1980). Newerclassifications have included the total sulphur content. Aswell as providing some environmental information, sulphurcan give some information on the reactivity of a coal.Catalytic effects from the mineral matter, mainly pyrite,occur (Davidson, 1983). However, instead of the mineralmatter, the ash 'content' is used as a parameter in a numberof classification systems; it is easily determined byconventional tests. Ash will also indicate the economic valueof the coal and can provide some environmental information.

Liquefaction

One property that is of major interest in evaluating a coal isits reactivity. It may be worth investigating using a direct,albeit empirical, measurement of reactivity as a classificationparameter. International agreement on both its definition andmeasurement would be essential. Ranking of coal based onits reactivity in different solvents has already been proposed(for example, Clarke and others, 1980). A different measureof reactivity has been proposed by Baldwin and co-workers(Baldwin and others, 1983; Shin and others, 1987); theyfound that a kinetically-defmed parameter can be used torank coal reactivity.

Some of the newer analytical techniques that have beendiscussed have indicated the importance of certain functionalgroups (such as phenols, methylene). These have beencorrelated with liquefaction yields. Some of these groupscould possibly be used for classification purposes. Theseanalytical techniques have the potential to be more objective,reliable and accurate than the conventional tests, although theaccuracy of some of the techniques has been questioned.They will, of course, need standardising. However, the

equipment is expensive and not yet widely used incommercial laboratories. There is also some evidence that itis not the total concentration but the mobility of thefunctional groups that is important, at least in the early stagesof liquefaction (Snape, 1987).

Blends of coal are likely to be used in processing since it isunlikely for a single source to be available. Therefore,for commercial purposes, a classification that is applicable toblends would be useful. Extraction yields for blendsare in agreement with those expected from the individualcoals (Clarke and others, 1980; Ouchi and others, 1984b;Sato, 1982); that is, the additivity law generally applies.However, the latter worker found that when the liquefactionis carried out without a solvent, the additivity rule was notfollowed.

Finally, a classification will provide only an indication of aparticular coal's suitability. Despite all the availablecorrelations, the final decision on a coal's suitability forliquefaction will depend on a test run.

9 Coking

Coal has been coked for several centuries; coking representsan important market for coal. Traditional classificationsystems were therefore mainly concerned with classifyingcoals for coking (and for combustion, the other main marketfor coal). Coking coals are coals that, when heated tosufficiently high temperatures in the absence of air, soften,devolatilise, swell and resolidify into a porous carbon-richsolid termed 'coke'.

There is generally some confusion over the terms 'caking'and 'coking'. Caking is the ability of a coal to melt onheating and form a coherent residue on cooling. An essentialprerequisite for a coking coal is that it should cake or fusewhen heated. However, not all caking coals are cokingcoals. Coking is used to describe those coals that aresuitable for coke manufacture. However, this explanationconflicts with the definitions in the Internationalclassification of hard coals (see Section 6.5.1) where thedefinitions of caking and coking are reversed; that is,'caking' indicates agglomeration and swelling during fastheating (CSN or Roga index) while 'coking' indicatesagglomeration and swelling during slow heating (dilatation orGray-King coke type). This is an indication of the confusionin the literature over these two terms.

Since the majority of coke (over 90%) is used in blastfurnaces (Bustin and others, 1985), this section willconcentrate on the classification of coals (often termedmetallurgical coals) for the production of blast furnace coke.In the blast furnace, coke serves essentially three roles: it actsas a fuel (heat source), as a reducing agent (reducing ironoxide to molten pig iron) and as a support for the blastfurnace charge. One important property of coke is thereforeits strength, that is, its ability to maintain its physicalintegrity as it descends with the blast furnace burden. Cokewith a high strength is preferred. A number of mechanicaltests for determining coke strength have been developed andstandardised. These include various drum tests in which thecoke is tumbled in a drum and then screened to determine its

impact strength (or stability factor) and abrasion strength (orhardness factor). The three common drum tests are theASTM tumbler test, the Micum test (Micum M40 index forimpact strength and Micum MIO index for abrasion strength)and the Japanese JIS test (DI3°i5 and DII5°i5). These testsare discussed by Zimmerman (1979) and Perch (1981).Although widely used, these drum tests are conducted underambient temperatures and so fail to take into account theactual process conditions pertaining in the blast furnace.Studies have shown that the mechanical strength of coke athigh temperatures cannot be predicted from their behaviourin tests carried out at ambient temperatures (BritishCarbonisation Research Association, 1984). However, themechanical coke strength (as determined by these drum tests)has been related, at least in some degree, to the performancein blast furnaces.

Another important property of coke is its reactivity towardscarbon dioxide in the blast furnace; coke with a lowreactivity is preferred. In Japan the I test (developed byNippon Steel Corp) is used in which two indices aredetermined: the CSR (coke strength after reaction) or RSI(reaction strength index) and the CRI or RI (coke reactivityindex). The CRI is determined from the loss in mass of cokewhen reacted with carbon dioxide under specified conditions.The sample from this reactivity test is tumbled in a specifieddrum under standardised conditions to determine the CSR(Goscinski and others, 1985a). However, these reactivitytests can give misleading information on the behaviour ofcoke since their ability to simulate conditions pertaining in ablast furnace are limited (Cudmore and Handley, 1987).New methods for coke testing, which better simulateconditions in a blast furnace, are required.

A classification system that would be able to predict cokestrength and reactivity would therefore be advantageous. Tobe of commercial value, a classification that included someof the properties commonly requested during the trade incoking coals would be an advantage. However, if a

Coking

classification is to be able to predict the behaviour of cokeand evaluate coals for coking, it should use as parametersonly those coal properties that can be closely correlated withcoke properties. This chapter will consider some of theseproperties of coal.

It should be borne in mind that, as well as the properties ofcoal, the resultant coke is also influenced by thecarbonisation conditions, such as the rate of heating, particlesize and pretreatment of the coal charge (Eisenhut, 1981;Perch, 1981). Some of these variables are within the controlof the coke-maker and so will not be discussed. The type ofcoke oven (for example, whether it is stamp-charged) willalso determine the choice of coal; a coal that meets therequirements for one coking plant may have little or no valueat another plant. Also, knowledge about how coking plantsactually operate is still quite limited.

Although the majority of traditional classifications are forsingle coals, blends of coals are generally being used atcoking plants; these blends can include non-coking coals.A classification that is applicable to both single coals andblends would be desirable for the commercial sector.However, Marshall (1976) suggests that a misleadinginterpretation of coking ability could be obtained from theclassification of a blend consisting of coals with widelydifferent properties. Therefore, it would be more useful toclassify each of the component coals of the blendindividually and to specify their proportion in the blend,provided that the additivity rules for the classificationparameters can be established. Where methods for predictingcoke properties are applicable to both single coals andblends, these will be discussed.

9.1 Rank effectsIt has been established for a considerable time that only coalswithin a specific range of rank (and type) are capable, ontheir own, of forming coke, essentially the bituminous coals(for example, Bustin and others, 1985; Cudmore, 1984).However, not all bituminous coals coke equally well; themedium volatile bituminous coals are considered to be theprime coking coals, having the optimum properties forforming good coke from single coals (Bustin and others,1985; Mackowsky, 1982c). Thus a coking coal classificationis mainly concerned with bituminous coals and this chapterwill therefore concentrate on bituminous coals. Sincenon-coking coals can be used for blending purposes, a cokingclassification system will however need to include coalsoutside the bituminous rank range. Changes in cokingtechnology are allowing a wider rank range of coals to beblended to produce high quality coke (Cudmore andHandley, 1987).

The rank of coal is one of the most important characteristicsgoverning its coking behaviour (Marshall, 1976; Perch, 1981)and the properties of the resultant coke, including itsreactivity (Cudmore, 1984; Goscinski and others, 1985b) andstrength (Bustin and others, 1985; Marshall, 1976). Cokestrength and the mechanical and physical properties of coalshow characteristic maxima when plotted against a rankparameter. Rank is also probably the most important criteria

considered in the blending of coals for coke production(Goscinski and others, 1985a). Mathematical methods forpredicting coke strength and reactivity for single coals andblends generally include a parameter that reflects the rank ofthe coal charge. These methods and the correlations ofvarious rank parameters with the resultant coke propertieswill be discussed in the following sections.

The rank of coal also influences the microstructure andmicrotexture of coke which, in turn, have been shown toinfluence the coke's reactivity and strength (Goscinski andothers, 1985b; Gray and DeVanney, 1986). This aspect willnot be discussed in this review.

However, rank alone cannot be used to evaluate a coal forcoking (no single coal property can) and it is not always areliable indicator of a coal's performance. For example, theRasa lignites from Yugoslavia are strongly coking (Given,1984), a fact that has been attributed to their high organicsulphur content (see Section 9.2.4). Coals of similar rank butdiffering petrographic composition can produce cokes withdifferent strengths (Diessel, 1983; Pearson, 1985). Whycoals of similar rank display differing coking behaviour andtherefore, what other coal properties may be required for aclassification system will be discussed in the followingsections.

9.2 Chemical composition andproperties

9.2.1 Carbon and hydrogen

Carbon and hydrogen contents can be required inmetallurgical coal specifications (Zimmerman, 1979),although they are not included as parameters in any of thetraditional classification systems (except the Seyler chartwhich is not, strictly speaking, a classification). Carbon andhydrogen contents of coke generally bear a simplerelationship with the coal's carbon and hydrogen contents.The carbon content of coke will be higher and its hydrogencontent lower, than the parent coal.

Carbon is the most important element in coal since it is thecarbon in the coke that provides the required thermal andreduction energy to produce the iron and also supports theburden, providing a permeable bed for the passage of the airblast (Perch, 1981; Zimmerman, 1979). However, not all thecarbon in the coke is available for the reduction process; aproportion is required to melt the mineral matter (ash) in thecoke and to eliminate its sulphur. The effective (or net)carbon of coke (that is, the actual carbon available forreducing the iron ore) can be calculated from an empiricalformula that combines burden and practice variables (Perch,1981). However, for classification purposes elementalcarbon should be sufficient.

The reactivity and strength of coke are related to the parentcoal's rank; carbon and hydrogen contents of coal can beused as parameters of rank (see Sections 2.2 and 2.3,respectively). However, formulae used today for predictingcoke strength and reactivity (such as the equation used by

Coking

Nippon Steel for calculating the CRI) usually includevitrinite reflectance as the coal rank parameter. Theseformulae will be discussed later (Section 9.4). The hydrogencontent of coal has also been directly related to the coke'sreactivity (Perch, 1981); the higher the hydrogen, the morereactive the coke. Correlations of the atomic ratios of carbonand hydrogen with coke properties will be covered inSection 9.2.3.

9.2.2 Oxygen

There is a direct correlation between the coal oxygen and thequality of the coke produced, with high oxygen coalsgenerally producing weak cokes (Zimmerman, 1979) anddecreased coke yields (Asakura, 1987; Cudmore andHandley, 1987). The oxygen content of the coke will belower than the coal oxygen content.

Research has indicated that the majority of the oxygen incoke is associated with its mineral matter (Cudmore andHandley, 1987). Inorganic oxides, particularly SiC>2, canreact with the coke carbon, contributing to the weight lossand degradation of coke in blast furnaces.

Oxygen is generally considered to play an important partduring pyrolysis, having a marked influence on the coal'sfluidity (Kosina and Heppner, 1984; Wilkinson, 1984).However, coals with similar oxygen contents and rank canexhibit different carbonisation properties, which have beenattributed to differences in their chemical structure (oxygenbonds). Coking coals from different areas display avariability in their oxygen bonds. Coking coals from somedeposits in the USA for example, contain as much as 50%oxygen in hydroxyl groups, whereas the strongly cokingcoals of the Donbass (USSR) have 90-95% of their oxygenin non-reactive ether bonds and heterocyclic groups (Kosinaand Heppner, 1984). Mochida and others (1984) alsoattributed differences in the carbonisation properties of twocoals with similar ultimate analyses, rank and maceralcomposition to differences in their structural features,particularly the hydroxyl groups.

Thus, oxygen content will not always provide a reliableguide to the coal's performance; other factors would need tobe taken into account. Also, the greatest impediment to theuse of oxygen as a classification parameter is the lack of anaccepted method for direct oxygen determination. Instead ofthe oxygen content, the use of the atomic ratio of oxygenwith either hydrogen or carbon has been proposed as aclassification parameter.

9.2.3 Atomic ratios

Carbon, hydrogen and oxygen contents of coal can beexpressed in terms of their atomic ratios. Correlations ofthese ratios with various coal properties, such as fluidity(which influences coke strength) and resultant cokeproperties have been found.

The H/O atomic ratio has been proposed as a classificationparameter for the Ostrava-Karvina (OKR) bituminous coals

(Kosina, 1987). Differences within the coking and cakingproperties can occur for coals with identical vitrinitereflectance (rank). This was attributed to differences withinthe vitrinite macerals; the inertinites were essentially inerteven though some of these coals are rich in inertinites (seeSection 9.4). Vitrinite reflectance (one of the proposedclassification parameters) reflects only the ordered (aromatic)part of the vitrinites; the H/O ratio is considered to reflect the'disordered' (non-aromatic) part of the vitrinites. Thevariability of the H/O ratio is caused mainly by differingoxygen contents in coals of similar rank (Kosina, 1988). TheH/O ratio was correlated with the coal's fluidity (Gieseler)(Kosina, 1984; Kosina and Heppner, 1984) and, for the lowrank bituminous OKR coals, was independent of maceralcomposition. From the H/O ratio and either the vitrinitereflectance or inertinite content (another classificationparameter), the coal's caking properties (Roga Index) andcoke strength (Micum M40 and M10 indices) could bepredicted from the appropriate regression equation (Kosinaand others, 1987). The H/O ratio, vitrinite reflectance andinertinite content together could also predict the mechanicalproperties of coke produced from binary blends of low tomedium rank bituminous OKR coals (Kosina, 1988).

The C/O atomic ratio of coal has been related to its fluidity(Gieseler) (Koba, 1980; Wilkinson, 1984). Multipleregression equations for predicting the reactivity of cokeproduced from British coals can include the C/O ratio; it wasone of the more important coal properties (along with rankand chlorine content of coal) influencing the coke reactivity(Wilkinson, 1984). Both the C/O and H/C ratios areincluded in the multiple regression equations derived byKoba (1980) for predicting the maximum Gieseler fluidity,total dilatation (Audibert-Arnu) and resultant coke strength(DI15Oi5). Graphs of H/C verses C/O can also be used topredict these properties. However, Wilkinson (1984) foundno clear relationship between either of these ratios and thedilatation for British coals. Slight but significant changes tothe equation for predicting coke strength were required for itsapplication to coal blends (Koba, 1980). All these equationswere derived on small sample sets and are probably not validfor other coal types. Wilkinson (1984) also found that, forthese British coals, the C/O ratio had more influence onresultant coke properties than the H/C ratio.

These correlations suggest that atomic ratios could help inthe evaluation of coals for coking. Use of atomic ratiosinstead of parameters based on the ultimate analysis couldreduce the number of classification parameters. Aclassification that includes one or more of these ratios maybe of use scientifically; whether it would be usedcommercially is debatable.

9.2.4 Sulphur

Sulphur in coke is detrimental in pig iron production.Although there are no absolute limits on acceptable sulphurcontents in coking coals, most commercial installationsspecify a coal with less than 1% total sulphur (Blackmore,1985; Zimmerman, 1979). However, higher sulphur coalscan be used if they are blended with low sulphur coals or if

Coking

operating conditions are adjusted accordingly. The sulphurcontent of coke is directly proportional to the total sulphurcontent of coal; typically about 80-85% of the coal sulphur isretained in the coke (Blackmore, 1985; Perch, 1981;Zimmerman, 1979).

Although most coking coals occur within the bituminousrank range, some coals of low rank show coking tendencieswhich have been attributed to their high sulphur content.The Rasa coal from Istria, Yugoslavia, can contain up to12% organic sulphur, with about one-third of the sulphuroccurring in thioethers. The ready cleavage of the thioethersis believed to be an important factor in making this apparentlignite strongly coking (Given, 1984). This could also helpexplain the coking properties of the hard black lignites fromSharigh, Pakistan (Elofson and Schulz, 1967) and why thehigh sulphur coals of the Interior Province, USA show somecoking tendency at carbon contents (dmmf) as low as 77%.Thus, although a high sulphur content is generally adisadvantage, it can contribute to the coking properties of thelower rank coals. The coal sulphur content is also one of thefactors in some of the multiple regression equations derivedby Wilkinson (1984) for predicting the reactivity of cokeproduced from British bituminous coals.

Thus the sulphur content of coal could be useful as aclassification parameter. It would provide information onboth the quality of the coke produced and on possibleenvironmental consequences from coking.

9.2.5 Chlorine and phosphorus

Both chlorine and phosphorus contents can be required inmetallurgical coal specifications (Zimmerman, 1979).Chlorine has an adverse effect in the coke ovens due to itsaction on coke oven refractories. It is generally quite low formost coals, although there are exceptions. High chlorinecoals produce cokes with a higher reactivity (Goscinski andothers, 1985b). Chlorine content is one of the factors inseveral of the multiple regression equations for predictingreactivity of coke produced from British coals (Wilkinson,1984). In fact, Wilkinson considers the chlorine content tobe one of the three more important properties influencingcoke reactivity.

Phosphorus adversely affects the iron quality. Unlikesulphur its level in the metal is difficult to control; all of thephosphorus in the blast furnace burden is reduced andretained in the hot metal product. Phosphorus in coke can bepredicted from the coal phosphorus content and coal volatilematter (Brown and others, 1982). Zimmerman (1979)suggests a safe limit of 0.05% to 0.06% for phosphorus,although even lower limits (0.03%, Cudmore, 1984;Cudmore and Handley, 1987) have been suggested.

Other properties of coal are considered to be of moreimportance in coking than chlorine and phosphorus contents.Therefore, in order to keep a classification simple, with aminimum number of parameters, chlorine and phosphoruscontents could be excluded, as they can always be specifiedseparately.

9.2.6 Volatile matter

A number of the traditional classification systems includevolatile matter as one of the parameters (see Table 5) whereit provides a measure of the rank (see Section 2.6) and sometechnical information relevant to coal utilisation. Thecorrelation of rank with the coke properties was discussed inSection 9.1.

As with all coal properties, volatile matter alone cannot beused to evaluate a coal for coking as coals with the samevolatile matter yield can show differences in their cokingbehaviour. Volatile matter influences both the swelling andshrinkage of coal during coking and helps determine theultimate coke quality, reactivity and strength (Blackmore,1985; Brown and others, 1982; Goscinski and others, 1985b).Generally, coals with between 14% and 38% volatile matter(dmmf) are considered to be possible candidates for coking(Zimmerman, 1979), although blends may include a smallproportion of coals outside this range. In order to producecoke, the volatile matter yield of coal has to be reduced; agood coke will generally have a volatile matter yield of lessthan about 1% (Cudmore, 1984; Goscinski and others,1985b). For a high yield of coke, a low volatile bituminouscoal would therefore be preferred; but since these coals arestrongly expanding, they can damage the coke oven walls ifused alone. Therefore blending comes into the picture.

The potential yield of coke, coke oven gas and coal tar canbe estimated from the coal volatile matter. Oguri and others(1987) however, suggest that subtracting a percentage of thecoal oxygen content from the volatile matter will provide abetter estimate. They also suggest using the volatile matterand H/C atomic ratio of coal to predict the heat consumptionrequired for coking (under the same operating conditions).

Coal volatile matter has been related to coke reactivity (seeFigure 19). Carbon dioxide reactivity of coke decreases from

Figure 1 9 Relationship of volatile matter with cokereactivity (Gosciniki and others, 1 985b)

Coking

the high volatile bituminous down to the medium volatilecoals and then increases for the low volatile bituminous coals(Goscinski and others, 1985b). A similar trend occurs withthe CSR index. Although several formulae have beendeveloped for predicting the CRI and CSR indices, none ofthe more notable ones listed by Goscinski and others (1985b)(such as those developed by Nippon Steel and Kobe Steel)include a volatile matter parameter. Instead, the vitrinitereflectance of coal is required.

Some methods (for example, Koba, 1980) for predicting cokestrength include the volatile matter (rank) and physicalproperties of coal. These will be discussed in Section 9.3.

Despite these correlations, some countries have moved awayfrom using volatile matter as a classification parameter. Forexample, in the 1980s the Japanese steel industry substitutedvitrinite reflectance and maximum fluidity (Gieseler) for thetwo previous classification parameters volatile matter andcoke strength (DI3°i5) (Asakura, 1987). The coke strength(DI is) can be calculated from the strength index (which iscalculated from the vitrinite reflectance distribution) andmaximum fluidity. Since volatile matter also correlates withthe strength index (Asakura, 1987), it could, presumably, beused instead of vitrinite reflectance.

Other coking coal classifications also prefer vitrinitereflectance over volatile matter. Marshall (1976) considersvitrinite reflectance to be the best single measure of rank inthe coking coal range (see Sections 2.6 and 4.2). Konev andothers (1986) found that volatile matter was of limited valuein the evaluation of blends of petrographically heterogeneouscoals; vitrinite reflectance and the sum of the 'leaning' (inert)components provided a better estimate. In a more generalclassification proposed by Kosina (1987), volatile matter isexcluded as it is dependent on a number of coal-massproperties and its faculty for prediction is considered to belimited. A number of mathematical models are in use forpredicting coke strength from vitrinite reflectance andmaceral composition, although they are limited to the coalson which they were derived (see Section 9.4).

However, volatile matter is preferred in some of the othernewer classifications, such as one for Indian coals (Tumuluriand Shrikhanda, 1985) and for Chinese coals (Wang andothers, 1986). In the latter classification, volatile matter waschosen instead of vitrinite reflectance as its determination issimpler, it is sensitive to oxidation and has practicalsignificance in industrial processes and is in common useinternationally (Chen, 1987; Wang and others, 1986).

Other recent classifications include both vitrinite reflectanceand volatile matter, such as the classification used in theUSSR (Eremin and others, 1982, 1983) and the new ECEand new Australian 'classifications'. These are more generalclassifications covering other uses of coal, besides coking.

As with all classification parameters, there are advantagesand disadvantages in the inclusion of volatile matter; whetherit is included will partly depend on what other classificationparameters are present, that is, whether the coke propertiescan be predicted from the other classification parameters.

9.2.7 Moisture

The moisture content of coal influences the coking process inseveral ways but has only an indirect effect on the cokeproperties. It influences the bulk density of the coke ovencharge which, in turn, influences the properties of the cokeproduced. A low moisture content (Blackmore, 1985;Eisenhut, 1981; Perch, 1981) will help to increase the carboncontent on a weight basis which will increase the coke ovenyield, reduce the loss of heat in the coking process requiredto drive the moisture off, help to size and blend the coalefficiently without clogging the equipment and to reducecosts associated with transportation and handling. On theother hand, the coking pressure in the coke oven is greatestfor moisture-free coal (Eisenhut, 1981), with the moisturecontent influencing shrinkage of the coal. Too dry a coal canalso present dust handling problems (Blackmore, 1985;Zimmerman, 1979). However, traditional classifications forthe higher rank coals (which include the metallurgical coals)do not include a separate moisture parameter. For lower rankcoals however, moisture is often included as a parameter (forexample, the new Australian 'classification').

9.2.8 Inorganic constituents

The mineral matter content of coal directly influences thequality of the coke produced. During coking, the bulk of thevolatile loss occurs from the organic fraction of the coal.The net result is that coke has a higher ash yield than itsparent coal (Cudmore, 1984). The ash (mineral matter) incoke is directly proportional to the ash (mineral matter) incoal and can be calculated from the ash and volatile matterof coal (as determined by proximate analysis) (Brown andothers, 1982; Neavel, 1981).

Coal with a low ash yield (that is, with a low mineral mattercontent) is preferred (generally below 10% is specified(Bustin and others, 1985)) since ash is an unwantedcomponent of coke. Coke ash reduces carbon input, lowersthe iron temperature and can increase the amount of slag in ablast furnace (Perch, 1981). Also, certain constituents in thecoke ash/mineral matter (the alkali metals) can catalyse theundesirable reaction of coke with carbon dioxide (the'solution loss reaction') (Cudmore and Handley, 1987). Anash yield of below 5%, though, is of little additionaleconomic value (Blackmore, 1985). In fact some coals withhigh vitrinite contents often need some mineral matterpresent to obtain an optimum ratio of 'reactives' to 'inerts'(Ng and Cudmore, 1987). Correlations of 'inerts' (oftendefined as 'inert' macerals plus mineral matter) with cokeproperties will be discussed in Section 9.4. For thesecorrelations, knowledge of the mineral matter content (or ashyield) would be required.

Ash is usually required in coking coal specifications (Perch,1981). Several classifications (such as the Australian)include ash as a parameter. As well as providing informationon the likely quality of the coke produced, the ash yieldprovides an indication of the economic value of the coal fortrading purposes. Ash (or mineral matter) in coal influencesother coal properties such as swelling and also influences thereactivity and strength of the resultant coke (Asakura, 1987;

Coking

Goscinski and others, 1985b; Ng and Cudmore, 1987; Oguriand others, 1987). However, not all the mineral matterconstituents are deleterious and so knowledge of the mineralmatter composition of the coal can be helpful.

The proportion of base-to-acid constituents in coal affects itsash fusion temperatures (see Section 3.6) and coke reactivityand strength. The AFT determines the melting point of thecoke ash in the blast furnace (Goscinski and others, 1985b;Zimmerman, 1979). Coke strength decreases in proportion tothe contents of minerals such as iron oxide (Fe2O3) andpotassium oxides (Oguri and others, 1987). These mineralconstituents also influence coke reactivity (Goscinski andothers, 1985b; Oguri and others, 1987). Formulae used inJapan for predicting CRI and CSR (Goscinski and others,1985b) include factors based on the mineral mattercomposition. However, these formulae are inapplicable tocoals with abnormally high or low mineral matter contents.Thus knowledge of the mineral matter constituents isrequired before these formulae can be applied. Noclassification yet includes the mineral matter composition; itwould lead to a rather complicated classification system.The ash yield is probably sufficient for the initial evaluationof a coal for coking; the mineral matter composition can bespecified separately.

9.3 Mechanical and physicalproperties

All coking coals are caking (although not all caking coals arecoking) and therefore some measure of the caking and/orcoking properties of coal have been included in most, if notall, coking coal classifications. For the classification to bekept simple it would be desirable to have only oneparameter. However, there is no universal agreement onwhich would be the 'best' parameter. Earlier traditionalclassifications (and some more recent ones) includeparameters based on the CSN or Gray-King coke number,which help determine whether a coal will coke. These testsprovide little information about the complex rheologicalbehaviour of a coal in the plastic or fluid state. Parametersbased on the Gieseler plastometer or Audibert-Arnudilatometer tests have therefore been proposed asclassification parameters in the last twenty years or so.These tests were discussed in Section 3 and their applicationin some national and international classifications in Section 6.

The mechanical and physical properties of coke helpdetermine its use. Correlations of coal properties with thesecoke properties are more complex than those relating thechemical properties of coke to the chemical properties of thecoals used. Since standard proximate and ultimate analysisof coal cannot predict the strength characteristics of theresultant coke with sufficient accuracy (Neavel, 1981), theempirical tests (CSN, Gieseler, etc) have been widelyemployed as guides for predicting coke strength.Correlations of these tests with measures of coke strengthand reactivity will be discussed in this section. As will beseen, these tests are useful for comparing coals to each otherin a qualitative way. As quantitative tools, they areapplicable for only limited ranges of coal rank and type and

under the same carbonisation conditions. A review of themechanical properties of coke has recently been published(Kirchner, 1987).

9.3.1 Crucible swelling number

A semiquantitative method for predicting the coke strength ofwestern Canadian coals from the coal CSN and volatilematter has been demonstrated (Pearson, 1980). However, themethod is probably inapplicable to other coal types. Sincethe CSN reflects other coal characteristics, such as rank andpetrographic composition (see Section 3.1), interpretation ofthe test, and hence the evaluation of a coal for coking, willdepend on what other classification parameters are present.The new ECE and Australian 'classifications' include theCSN as the only measure of the coking properties of coal;these classifications however cover other uses for coalbesides coking.

9.3.2 Dilatation

The dilatation of coal has been correlated with the resultantcoke properties. The Audibert-Amu dilatation (seeSection 3.4) of coal is one of the factors in the multipleregression equations derived by Wilkinson (1984) forpredicting the reactivity of coke produced from British coals.Several correlations of dilatometer results with coke strength(as determined in drum tests) have been demonstrated. Forexample, Koba (1980) derived multiple regression equationsfor predicting coke strength (DI 15) from the coal rank(volatile matter) and Audibert-Arnu dilatation. The equationsderived on coal blends were slightly different (but includedthe same coal properties). These equations were derived ononly a small sample set of coals; however, they do indicate acorrelation between dilatation and coke strength.

A method that has been successfully applied to theCarboniferous coals of Europe to predict coke strength againuses the dilatation and volatile matter of coal. A cokabilityindex 'G' is calculated from the Ruhr (a similar test to theAudibert-Arnu) dilatometry results and the Micum M40index is predicted from the G value, volatile matter of thecoal charge and carbonisation conditions (Simonis andothers, 1966; Perch, 1981). Thus the G factor could possiblybe used as a classification parameter. However, the methodhas some limitations, with its accuracy decreasing withincreasing coal volatile matter (Perch, 1981). Also, the Gfactor is not applicable to all coals; western CanadianCretaceous coals and some Australian Gondwanan coalsform good coke although their G values indicate otherwise(Brown and others, 1982; Cudmore, 1984). It has beensuggested that for these high inertinite coals, the particle sizespecified in the dilatation test is too fine (see Section 3.4).Fine grinding is thought to destroy the natural intergrowth ofreactive and inert constituents. Munnix (1984) considers thatthe G factor is applicable only to coals with an inert contentbelow 20%. It has been suggested that the G factor isadditive and may be determined for a blend from the valuesfor the component coals. The model has also been modified(for example, by the UK National Coal Board (BritishCoal)). However, the method and its modifications areuseful only for blends of coals with a certain range of

Coking

volatile matter and G values and under specified cokingconditions (Cudmore, 1984; Perch, 1981) and is notapplicable for some coal blends (for example, blends ofAustralian coals (Brown and others, 1982)).

The Japanese coking industry have used the relationshipbetween volatile matter and maximum dilatation to evaluatecoals for coking (see Figure 20). It can be used for blendingcoals. The ideal blend for producing coke with the requiredproperties (maximum strength etc.) is indicated by the shadedarea. However, the value of inertinite-rich coals as cokingcoal blends can be underestimated (Cudmore, 1984; Pearson,1985).

Figure 20 Relationship of volatile matter with dilatation(bituminous coals) (Zimmerman, 1979)

Examples of classification systems that include the maximumdilatation as a classification parameter are those of Marshall(1976) and Uribe and Perez (1985). Reasons given forchoosing this parameter are that dilatation is a sensitivemeasure of the coking properties of coal, reflecting coalcharacteristics such as rank, petrographic composition andoxidation. Changes in these coal properties affect theproperties of the coke produced. Dilatation also gives agreater range of values than the Roga index, CSN andGray-King coke number, and relates to measures of cokestrength in a better way than the CSN.

9.3.3 Gieseler fluidity

The maximum Gieseler fluidity of coal (see Section 3.5) isone of the factors in the multiple regression analysisequations derived by Wilkinson (1984) for predicting thereactivity of coke produced from British coals. Variousmodels for predicting coke strength based on the Gieselerfluidity have been developed. For example, Koba (1980)derived regression equations for predicting coke strength(DI 15) from coal volatile matter and maximum fluidity(correlation coefficient, r=0.96). A similar equation was

derived for coal blends. Munnix (1984) and Poos (1987)describe a method employed in Belgian coking plants forpredicting coke strength (Micum M10 and M40 indices, etc)from the coal's maximum fluidity, inert content (mineralmatter plus inert macerals) and the caking ability of thereactive matter (calculated from the maximum vitrinitereflectance). This method could also be applied to blends.

The Japanese coking industry uses two parameters to classifycoals, the maximum fluidity and maximum vitrinitereflectance. The coke strength (DI 15) can be predictedfrom the strength index (which is calculated from thevitrinite reflectance distribution) and the maximum fluidity(Asakura, 1987). An MOF diagram (see Figure 21) can beused to evaluate coals for coking. It enables coals to beblended in order to achieve a coke with the requiredproperties by assuming that the vitrinite reflectance andGieseler fluidity are additive. This is not necessarily true(Cudmore, 1984). The MOF method can underestimate thevalue of both inertinite-rich and high volatile coals as cokingblend components (Day and others, 1979). For example,most western Canadian Cretaceous coals and Gondwanancoals form better cokes than is suggested by their lowGieseler fluidities.

The fluidity of coal is also a factor in some equations (suchas one developed by Kobe Steel) for predicting the CSR(Goscinski and others, 1985b). Again, these equations areapplicable only for coals with a certain range of propertiesand carbonised under similar conditions.

Like dilatation, fluidity reflects the coal characteristics, suchas rank, petrographic composition and oxidation. Thus it issensitive to changes in coal properties which affect its cokingbehaviour. However, other classification parameters wouldbe required for the correct interpretation of the test.

9.3.4 Roga index

The Roga index (see Section 3.2) provides a measure of themechanical strength of a 'coke button' and so one mightexpect it to be fairly directly related to the strength of cokeproduced in coke ovens. However, the conditions of the testare not the same as those pertaining in actual coke ovens.

In the USSR coal 'classification' system, two parameters areused to evaluate the caking and coking behaviour of coals,the 'plastic layer thickness' and Roga index (Eremin andothers, 1983). The other classification parameters are thevitrinite reflectance, total 'fusinised' components (defined asfusinite plus two-thirds of semivitrinite and 'mixtinite') andvolatile matter (daf). From these parameters, the cokestrength (as determined in drum tests) can be predicted forsingle coals and blends of coals of differing petrographiccomposition (Eremin and others, 1982, 1983).

In China, a modification of the Roga index (the caking index,G) is used as the classification parameter for evaluating thecaking behaviour of coals (Wang and others, 1986).Advantages over the Roga index claimed includeenlargement of the useful range for strongly cakingbituminous coals and enhancement of the differentiating

Coking

30,000-

20,000-

10,000-

Japan (high volatile)

• Miike

field of blendedcoal for cokemaking

USA(high volatile)

USA (medium volatile)

Japan (high volatile)

\—Relationship between\ maximum fluidity and* rank for low inerts\ coals

\

(medium volatile)Canada

(medium volatile)

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Mean maximum vitrinite reflectance,%

Figure 21 Relationship of vitrinite reflectance withfluidity (MOF diagram)(bituminous coals)(Cudmore, 1 984; Day and others, 1 979)

ability for weakly caking coals (Chen, 1987; Wang andothers, 1986). To a certain extent the G value is additive(Chen, 1987) and so can be used for coal blends. Cokestrength (Micum M10) can be predicted from the G value (orRoga index) and volatile matter (Chen, 1987; Wang andothers, 1986).

9.4 Petrographic composition andproperties

Petrographic methods have been widely applied in the cokingindustry where routine petrographic analyses are carried outat a number of coking plants to evaluate coals for coking.The petrographic composition of coal has been used withsome success to predict the strength and reactivity of theresultant coke.

Studies have shown that coking coals consist of materialsthat, depending on their rank, will fuse on heating (reactivemacerals) and those that do not (mineral matter and inert ornon-reactive macerals). Based on the concept ofreactive/non-reactive macerals, a number of mathematicalmodels have been developed to predict coke properties,especially its strength (for example, Schapiro and others,1961; Schapiro and Gray, 1964). These models can be usedfor evaluating single coals or, more commonly, for blendingcoals for coking. They assume that, for any given rank ofcoal, there is an optimum mix of reactives to non-reactiveswhich will produce the best coke; hence the percentagesrepresenting this optimum mix will vary with rank {seeFigure 22). The models therefore include a rank parameter,usually vitrinite reflectance. In order to use these models, itwould be desirable to include vitrinite reflectance as aclassification parameter.

21-1

18-1

15-1

•& 12-1

h95.5

k93.8 1

^92.3

h-90.0

h85.7

^75.0

T3~ I s L 17 fal li5J I17T Tl9 V-type

0.4 0.6 0.8 1,0 1.2 1.4 1.6 1.8 2.0 2^2 Vitrinitereflectance, °A

Figure 22 Optimum ratio of reactives to inerts for eachV-type (Schapiro and Gray, 1 964)

However, one difficulty with using maceral groups asclassification parameters is their relationship to the reactiveand non-reactive constituents. Vitrinite and liptinite arecommonly regarded as being chemically reactive andinertinites as 'non-reactive' (depending on their rank).However, it is not as simple as this. Vitrinite, liptinite andinertinite are groups of petrographically heterogeneousmacerals and, within each group, differences in chemicalbehaviour occur. It is generally recognised that, in coking,part of the inertinites are reactive in an analogous manner tovitrinite and contribute directly to the quality of the coke (forexample, Diessel, 1983, 1986; Schapiro and others, 1961);but what constitutes the reactive inertinites is still debated.In some coals, for example Ostrava-Karvina(Czechoslovakia) coals, the inertinite appears to be almosttotally inert (Kosina and Heppner, 1984; Kosina and others,1987). Diessel (1982) found that the boundary betweenreactive and non-reactive inertinite varies with rank.

Coking

Differences among workers in the treatment of reactive andnon-reactive macerals, particularly the inertinites, can be seenin the models developed for predicting coke strength. Someof these methods have been reviewed by Bustin and others(1985), Cudmore and Handley (1987), Mackowsky (1982c)and Neavel (1981). The best known is probably the methodof Schapiro and others (1961) in which two-thirds ofsemifusinite plus the rest of the inertinites are considered toform the non-reactive macerals. One-third semifusinite plusall the vitrinites and liptinites are treated as the reactivemacerals. However, the model is inapplicable to certaincoals, such as the inertinite-rich Gondwanan (Brown andothers, 1982; Diessel, 1983, 1986) and western CanadianCretaceous (Pearson, 1985) coals; the predicted coke strengthwas consistently lower than that determined in empiricaltests. Since it is a fairly consistent error, Brown and others(1982) consider that with suitable modifications, the methodmay allow useful predictions of coke strength to be made forthese coals. It has been suggested that more than one-thirdsemifusinite is reactive in these inertinite-rich coals (Diessel,1986). The model was also inapplicable to liptinite-richcoals (Schapiro and Gray, 1964). However, the method didgive reasonable predictions for some vitrinite-rich coals fromSouth Africa (Smith and others, 1983) and Australia (Ng andCudmore, 1987).

Some anomalies also occur in the vitrinite group. In themethod of Benedict and others (1968) for predicting cokestrength, part of the vitrinites ('pseudovitrinites') areconsidered to be chemically inert and a portion of these areincluded with the non-reactives. Creaney and others (1980)attributed the variable coking behaviour of some Australiancoals with similar petrographic analyses to the presence of ahigh proportion of 'vitrinite B' (which is broadly analogousto the 'reactive vitrinite' of Benedict and others (1968)).Variability in the coking behaviour of vitrinite in isorankOstrava-Karvina coals have also been reported (Kosina,1984; Kosina and Heppner, 1984).

Stankevich and others (1981) have derived multipleregression equations for predicting coke strength (asdetermined in drum tests) of blends of petrographicallyheterogeneous coals. The equations include the followingproperties: mean vitrinite reflectance; the 'leaning' index(ratio of 'non-caking' components to the optimum quantityof 'non-caking' components in the coal charge); ash;and indices derived from differences in the rank and contentof 'caking' (vitrinite) components of the coals in thecharge. A high accuracy for Kuznets (USSR) coals isclaimed. However, only vitrinite appears to be treated asreactive.

Thus the methods for predicting coke strength appear towork provided they are applied to coals which are more orless similar in petrographic composition to the coals onwhich the models were developed and provided that the cokepotential is being evaluated on coals which will be testedunder the same experimental conditions used for the model(Bustin and others, 1985). The models may not be valid forcoals that have been oxidised or locally heat-altered (Smithand others, 1983). The same comments are probably true forthe models for predicting coke reactivity. For example, the

method used by Nippon Steel for calculating the CRIincludes a petrographic composition factor in whichtwo-thirds of the semifusinite is treated as unreactive(Goscinski and others, 1985b).

Thus one of the difficulties of using the maceral groups asclassification parameters is their non-uniform behaviour. Ahigh inertinite content does not necessarily indicate a poorcoke (see Table 19); other factors need to be taken intoaccount. Macerals are classified by their optical andmorphological features and these may not be as closelyrelated to the chemical composition and properties as issometimes assumed (see Section 4.1), leading to differencesin coking behaviour. It is possible that the composition, andhence coking behaviour, of the materials grouped under themaceral headings may differ from geologic region to regionand from geologic age to age, as they were formed fromdissimilar source materials and under differingpalaeoenvironmental conditions (Bustin and others, 1985;Diessel, 1983; Given, 1984). Certainly the semifusinite ininertinite-rich Gondwanan coals has different cokingcharacteristics from the maceral of the same name in thenorthern hemisphere Carboniferous coals. There is also thedifficulty of the correct identification of the macerals (seeSection 4.1).

Table 19 Strength of cokes produced from inertinite-richand inertinite-poor coals (Mackowsky, 1983)

VM, daf, %vitriniteliptiniteinertiniteMicum M40Micum M10

Ruhr coal

27.368

82471.4

8.5

Australian coal

25.457

14272.2

8.6

Correlations have been found of petrographic composition(percentage non-reactives or reactives) and vitrinitereflectance with various physical parameters of coke, such asthe CSN, Roga index, maximum fluidity and dilatation(Pearson, 1980, 1985; Smith and others, 1983). Therefore, inprinciple, these physical parameters could be predicted andhence excluded from a classification system. However, thecorrelations are probably applicable only to the coal types onwhich they were derived and will not be as accurate as theactual test results.

There is also evidence that other factors besides maceralcontent influence coking behaviour. The way in which themaceral groups are associated with each other can play apart. For example, the coking capacity of liptinite varies indiffering maceral associations (Mackowsky, 1983). Coals inwhich the inertinites are widely distributed within thevitrinites can exhibit poor swelling and coking capacity,although they may have similar chemical, proximate andmaceral analyses to another coal which possesses goodswelling and coking capacity (Falcon and Snyman, 1986).This inertinising effect of the coarse intergrowth of theinertinites cannot be expressed by a maceral content number.Mochida and others (1984) attribute the differentcarbonisation properties of two coals of similar rank andmaceral composition to differences in their chemical

Coking

structure. Thus, a maceral content parameter could give amisleading interpretation of the coking ability of a coal.

Information on the intergrowth of maceral groups can beobtained from a combined maceral and microlithotypeanalysis. Rentel (1987) suggests using a combinedmaceral-microlithotype analysis, along with dilatometertests, to characterise reactive inertinite and to assess the'reactive' and 'non-reactive' microlithotypes present in thecoal. He found that coke strength (Micum M40) couldbe predicted from the 'non-reactive' microlithotypes(instead of 'non-reactive' macerals) for high inertinitecoals.

Instead of using the maceral groups as classificationparameters, the total non-reactive (or reactive) maceralscould be used, provided a definition of reactivity can befound that is applicable to a majority of coals worldwide.The USSR classification includes the sum of the 'leaning' or'fusinised' components as a parameter (Eremin and others,1982, 1983). This parameter is defined as the sum of thefusinite plus two-thirds of 'semivitrinite and mixtinitegroups' and therefore may not be applicable to all coal types.Coke strength can be predicted from this 'leaning'component and the other classification parameters. In atechnological classification of brown coals that is beingdeveloped by COMECON, the sum of the gelifiedcomponents plus inertinite is proposed as a parameter (Suessand others, 1986). In both these classifications, however, thecorrect identification of the appropriate macerals is required;therefore some subjectivity will remain.

A method that does not require the direct identification ofindividual macerals would be advantageous. One possiblemethod could be the 'reactive cut off technique (Pearsonand Price, 1985). From the reflectogram of the whole coal,the proportion of noh-reactives (inertinites) that are requiredto produce a coke of known stability is calculated from thereactive cut off value. The reactive cut off is the randomreflectance value that separates reactive from inert maceralsand is calculated from the maximum reflectance of vitrinite.This indirect method was developed using Canadian coals; itsapplicability to other coals needs investigation. Diessel(1986) suggests that slightly low values may be obtained onAustralian coals.

Another method uses fluorescence to assess the fusible(reactive) and non-fusible (non-reactive) components of coal(Diessel, 1986). Reactive inertinites fluoresce. Under theexperimental conditions used, all coal macerals above 3.00%mean fluorescence intensity fused on carbonisation, thosebetween 3.00% and 1.63% partially fused and those below1.63% remained infusible. The fluorescence intensity ofnorthern hemisphere Carboniferous coals followed a similartrend to that observed in the Australian coals, but weremostly lower. When results for Permian (Australian) andCarboniferous (Ruhr) coals were treated together, cut-offvalues of 3% relative fluorescence intensity for thefused/partially fused boundary and 1.5% for the partiallyfused/non-fused boundary were obtained (Diessel andWolff-Fischer, 1987). Results also indicated that fusibilityand/or infusibility cut-offs based on fluoresence intensity

values could be applied without reference to coal rank, whichis not possible when cut-off values are based on reflectance.

Reactive and non-reactive maceral contents may be useful ina coking coal classification, allowing the prediction of cokeproperties. However, the problem of how to treat thesemi-reactive (partly reactive/fusible) macerals still remains.Also, the same definition of reactive/non-reactive may not beappropriate in other end use processes, such as liquefactionand so would be inappropriate for a general classificationsystem.

9.5 Potential analytical techniques

9.5.1 Nuclear magnetic resonance

Nuclear magnetic resonance (nmr) can provide differenttypes of information related to the chemical structure of coal(see Section 5.2). If a parameter (or set of parameters) couldbe derived from an nmr spectrum for evaluating andpredicting the coking behaviour of coal, then it couldpossibly be used as a classification parameter. For example,nmr can provide an objective chemical measure of rank (fa,although its relation to rank is disputed), an important cokingcoal parameter.

The thermoplastic property of bituminous coals is intimatelyrelated to their caking and coking behaviour. Nmr has beenused to study the chemistry of the plastic state of coal, whereit provides a continuous description of coal as it is heatedtowards coking temperatures. The parameters obtained usingthis nmr thermal analysis technique are sensitive to changesin the molecular properties of coal, particularly molecularmobility. Results are presented as a set of pyrogramsshowing the temperature variations of these parameters {seeFigure 23). For bituminous coals, these pyrograms clearlydelineate both the region of pyrolytic decomposition and theregion of thermoplasticity. Thus, this technique has adistinctly different predictive potential than conventionalcarbonisation test methods such as CSN, Gieselerplastometry and dilatometry.

However, a problem with using high temperature nmr studiesis that there is a rapid decrease in signal-to-noise ratio withincrease in temperature and techniques such as signalaveraging are required to improve the ratio (Lynch andWebster, 1979).

Using 'H nmr to study coal pyrolysis, Yokono and Marsh(1983) found a relationship between the coking properties ofcoal and the temperature dependence of the line widths athalf height (AH1/2). The temperature at which AH1/2 reacheda minimum was lower for the non-coking Taiheiyo coal thanthe coking Yubarishinko coal. However, only a smallsample set of coals was investigated.

Sakurovs and others (1987b) used 'H nmr thermal analysis tocharacterise the pyrolysis behaviour of a wide range ofAustralian bituminous coals heated at 4K/min to 875K. Thetemperatures of maximum molecular mobility (Tmm) and ofmaximum Gieseler fluidity were found to be similar and therelationship between molecular mobility and fluidity was

Coking

S5100- -100

- 0

300 500 700Temperature, K

900

mm = temperature at which the maximum extent of mobility occursmH = temperature at which the maximum rate of emission of

hydrogen in volatiles occursmm = maximum extent of molecular mobility

Figure 23 Plot of the apparent residual hydrogen contentand mobile hydrogen component of a highvolatile bituminous coal during pyrolysis at4 K/min. The differential plot of the apparenthydrogen content is shown (Sakurovs and others,1978a)

determined. Thus Tmm could possibly be used as aclassification parameter instead of the maximum Gieselerfluidity.

This technique has also been used to assess the fusibility ofthe main maceral groups of Australian Permian coals(Sakurovs and others, 1988). Liptinites were shown to becompletely fusible and vitrinites to have variable fusibilitywith no strong correlation with rank. Inertinite fusibility wasfound to be strongly correlated with rank, with significantfusibility occurring for inertinites from coals with meanmaximum vitrinite reflectance between 1.0% and 1.4%.However the inertinite fusibility assessed by this methodshows poor correlation with the reactivities estimated byeither the Schapiro-Gray (Diessel, 1982) or Diessel (1982,1983) reflectance methods (see Section 9.4). This may bedue in part to the large statistical errors associated withobtaining an inertinite reflectance histogram, and calculatingthe semifusininte fraction of inertinite (for the Schapiro-Grayestimate) (Sakurovs and others, 1988).

9.5.2 Fourier transform infraredspectroscopy

Fourier transform infrared (FTIR) spectroscopy has beenused to characterise single coals and coal blends. Variouscoal properties have been correlated with FTIR spectra (seeSection 5.4) and therefore could, in principle, be predicted.These predicted properties (for example, volatile matter)could be used to evaluate an unknown coal using thecorrelations previously discussed. From a single spectrum,several coal properties could be predicted, that is, severalclassification parameters could possibly be determined in onetest. Presumably though, these would not be as accurate as adirect determination (in conventional tests) of the requiredproperty. However, parameters derived from an FTIR

spectrum could possibly be used to evaluate an unknowncoal directly and could therefore be used as classificationparameters.

Coke properties have been predicted from the FTIR spectrumof coal. For example, from factor loadings obtained fromfactor analysis of FTIR spectra of the coals involved,Fredericks and others (1984) could predict coke strength andreactivity; seven factors were required. Since only part ofthe spectrum was analysed, the accuracy of the predictionmay be improved if more regions of the spectrum wereanalysed. It would be interesting to see if a single parametercould be derived from an FTIR spectrum that could predictthe resultant coke strength or reactivity. It could then beused as a classification parameter. Diffuse reflectance FTIRcan also monitor the degree of oxidation of coking coals(Fuller and others, 1982) and predict coal blend proportions(Fredericks and others, 1987).

9.6 CommentaryA classification system for coking coals should be able toevaluate the behaviour of coal during coking and help predictthe properties of the resultant coke. Coke properties requiredare its chemical composition, physical properties, such asstrength, and high temperature properties (reactivity). Fromthe preceding sections, it can be seen that for the properassessment of the coking potential of all coals, several coalcharacteristics should be considered; two properties areprobably insufficient to cover all coals. However, opinionsdiffer both as to the number and which properties should beincluded.

Coke strength has been related in some degree to theperformance of coke in blast furnaces. Many models forpredicting various indices of coke strength using differentproperties of coal have been developed. The accuracy of theprediction needs to be high if the models are to be ofpractical use, as even a small change in coke strength indicescan cause significant effects in blast furnace operation(Brown and others, 1982), with resultant economicconsequences. However, the accuracy of the models arelimited; they are applicable to only the coals on which theywere developed and when carbonised under the sameconditions. For an international classification, applicable tothe majority of coals found worldwide, a single model ofreasonable accuracy would be advantageous. Majordifficulties exist in developing such a model; coke strength(as determined in drum tests) reflects a number of coalcharacteristics which are interrelated in a complex manner.Some of these properties, such as pore structure andfissuration (Brown and others, 1982) are also difficult toquantify.

More recent research has been evaluating the behaviour ofcoke at high temperatures, especially its reactivity. Cokereactivity could possibly provide a better indication of cokebehaviour than strength, since the drum tests for determiningcoke strength are carried out under conditions that fail to takeinto account the actual process conditions in a blast furnace.Coke reactivity has been related semiquantitatively to certaincoal properties, such as volatile matter. Research relating

Coking

reactivity with coke structure and microtexture (for example,Coin, 1987; Goscinski and others, 1985b; Gray andDeVanney, 1986) looks promising. If the correlations withcoal properties can be quantified and parameters derived thatcan be directly determined from coal properties, then thesecould be used for classification purposes.

The chemical composition of coke can be fairly directlyrelated to the chemical composition of the coal. The ultimateanalysis of coal can provide some information on thereactivity of the resultant coke; but it provides littleinformation on the plastic behaviour of coal (Neavel andothers, 1986). Therefore, additional parameters are required.Sulphur content has been included as a parameter in some ofthe newer classifications, where it provides information onboth the environmental consequences of coking and thequality of the resultant coke. It is an important property inthe trading of coal, usually being required in coking coalspecifications. For similar reasons, ash (determined byproximate analysis) is now included in some classificationsystems. Coke strength and reactivity also vary with ash.Atomic ratios of the elements can be useful in some cases forevaluating coals for coking. Used in conjunction with otherproperties, correlations with coke strength and reactivity havebeen observed. However, atomic ratios are not yet usedcommercially, although they have been proposed in at leastone 'scientific' coal classification (Kosina, 1987).

For a commercial classification, there is probably a case forincluding coal volatile matter. It is usually required in coalspecifications and is easily determined. As well as providinga measure of coal rank, volatile matter also provides anindication of the likely yield, quality and reactivity of theresultant coke (although, as with all parameters, there areexceptions). In conjunction with other properties, such asdilatation, volatile matter has, in some cases, beensuccessfully used to predict coke strength.

Vitrinite reflectance provides a measure of coal rank only(unlike volatile matter). However, since there is quite a goodcorrelation between vitrinite reflectance and volatile matter,at least for vitrinite-rich coals, vitrinite reflectance couldprovide an indication of the resultant coke yield, quality andreactivity for these coals. There are a number of models forpredicting coke strength that include vitrinite reflectance.Inclusion of petrographic composition parameters allows theapplication of the petrographic models for predicting cokestrength. However, the usefulness of these models arelimited and there is the problem of the non-uniform

behaviour of macerals, especially inertinite. No model hasyet been derived that is applicable to all coals.

Another petrographic parameter that has been proposed as aclassification parameter is the reflectogram. Although blendsof coal are usually coked, a reflectogram cannot alwaysidentify a blend unambiguously (see Section 4.3). It hasbeen argued that a classification should be for single coals(Alpern, 1981; Marshall, 1976) as classification of blends ofcoals of widely different properties can lead tocomplications. It would probably be more useful to classifyeach of the component coals individually and to specifytheir proportions in a blend, provided that the rules foradditivity of the parameters used can be established.Reflectograms are rarely requested in coal specifications.Nevertheless, reflectograms can be useful in assessingwhether a commercial consignment is, in fact, a single coalor a blend.

Most, if not all, coking classifications and specificationsinclude a parameter for evaluating the caking or Theologicalbehaviour of coal. Used in conjunction with other coalproperties, these parameters have successfully evaluated thecoking propensity of coals and predicted coke strength(although, of course, there are exceptions). All the tests havetheir limitations; there is no clear choice on which would bethe 'better' parameter. Different classifications have optedfor different parameters. Possibly a test that better reflectsconditions pertaining in a coke oven may provide a moreaccurate prediction.

The future may lie in the newer analytical techniques (suchas nmr), that can relate coal constitution with its cokingbehaviour and could possibly predict resultant cokeproperties. These techniques would break away from theempiricism of the current tests. Although the equipment isexpensive, several classification parameters could possibly bederived from one test.

There is a general consensus that despite all the knowledgethat has been accumulated about coal properties and despitethe numerous methods for predicting coke properties, a pilotscale carbonisation run is still indispensable (especially forblends). Even though a classification is intended to provideonly a rough guide to the coking behaviour of coal, it seemsunlikely that a simple classification, suitable for commercialand scientific use, can be devised that will deal adequatelywith the variety of coking behaviour manifested among coalsof similar rank throughout the world.

10 Conclusions

The nature of a classification system will depend upon theparticular application, whether it be scientific or commercial,for which the system is to be employed. Few purely'scientific' classifications, based on the chemical compositionof coal, have been proposed that are in general use, despitecorrelations of the ultimate analysis of coal with itsbehaviour and the frequent inclusion of ultimate analysis datain research papers. Perhaps it is not therefore surprising thatthe Seyler chart, although old, is still used today.

The majority of classifications currently applied arecommercial systems. One of the main requirements of thesesystems is that they should characterise a coal and, fromcorrelations with a coal of known behaviour, be able topredict its behaviour and identify its suitability in end useprocesses. This requires identification of the properties thatare critical to the commercial performance of a coal. Thereis as yet no universal agreement on what the criticalproperties are by which a coal should be characterised.

It has been suggested that if a classification is to be ofcommercial and practical value, it should include propertiesthat are frequently required in industry, particularly in thetrade of coal. However, different properties are important inthe different end use processes; for example, calorific valueis important in the combustion industry but is of little interestin coking. Also, the correlation of coal properties with itsbehaviour is dependent on the process conditions; that is,coal properties that may be of importance in, for example,one liquefaction process may be of little value in another.The inclusion of all coal properties that are relevant to itsbehaviour in all end use processes would therefore lead to animpossibly complex classification. That a generalclassification would also deal adequately with the variety ofcoals found worldwide, and still remain simple, seemsunlikely. The essential properties for the initial evaluation ofa coal need to be identified. The lack of agreement on theseproperties is seen in the wide number of classificationsystems available. The properties required for a final

assessment of a coal for industrial use can be givenseparately; a classification cannot replace a coal specification.

The predominant approach for predicting the behaviour of acoal has been through the application of empirical tests.There is a general consensus that the majority of the currentevaluative tests are inadequate and inaccurate, and that theirinterpretation into the expected full scale performance isunreliable. Most of the test conditions are far removed fromactual process conditions. There is thus a need for betterevaluative tests, preferably based on modern analyticaltechniques. However, until the cost of the equipment (suchas mass spectrometers) has been reduced and the equipmentand methods of analysis have been standardised, thesetechniques are unlikely to be applied commercially.

Essenhigh (1981) believes that to break away from thepresent empiricism it will be necessary to establish anadequate model of coal constitution that can provideacceptable predictive correlations. Future work may lie inthis direction. One approach has been suggested by Neavel(1986), who advocates characterising coal in terms of itselemental composition (both the organic and inorganic parts)and texture (the organisation of the substances). Others (forexample, Alpern, 1981; Uribe and Perez, 1985) proposeincluding the petrographic composition (macerals) asclassification parameters. However, it has been shown thatcoals of similar elemental or petrographic composition andrank can behave differently in the same process. Also, thereis the 'inertinite problem'; inertinite in different coals candisplay differences in its behaviour. Generally, thecorrelations relating the various chemical and/or physicalproperties of coal with its behaviour are valid only for thecoals on which they were developed and, even for these,exceptions can often be found. The origin and geologichistory of a coal is reflected in the correlations. With theworldwide diversity of coals, it seems unlikely that simplecorrelations that are valid for all coals will be found. Despiteall the knowledge that has been accumulated about coal

Conclusions

properties and the numerous methods for predicting itsbehaviour in end use processes, a pilot scale test run is stillindispensable for the final evaluation of a coal.

Some of the newer analytical techniques (such aspyrolysis-mass spectrometry) have correlated variousstructural features of coal with its performance. Future workon the characterisation of coal and relationships with itsbehaviour may derive new and different classificationparameters.

Once the critical coal properties have been found, they mustbe presented in a legible and easily memorable way.

Traditionally, they have been arranged as an hierarchy.However, more recent classifications are being presented as'faceted classifications' (codifications). With the widediversity of coals, it may be easier (and of more use) toclassify them in a faceted classification than in anhierarchical system.

Thus one can conclude that since different properties of coalare important in the different end use processes and with thewide heterogeneity of coal, it seems unlikely that the desiredobjective of a simple classification that is relevant to all coaluses and for all coals, and that will be accepted worldwide,will be realised in the near future.

11 References

AdbeJ-Baset M B, Yarzab R F, Given P H (1978)Dependence of coal liquefaction behaviour on coalcharacteristics. 3. Statistical correlations of conversion incoal-tetralin interactions. Fuel; 57 (2); 89- 94 (Feb 1978)Alpern B (1981) For a universal synthetic classification ofsolid fossil fuels. Bulletin des Centres de RecherchesExploration - Production Elf-Aquitaine; 5 (2); 271-290 (30Nov 1981) (In French)Alpern B (1987) Some reflections on coal petrology andcoal classification. In: Advances in the study of the SydneyBasin, twenty- first Newcastle symposium, Newcastle, NSW,Australia, 10-12 Apr 1987. Newcastle, NSW, Australia,University of Newcastle, Department of Geology, pp 27-35(1987)American Society for Testing and Materials (1984)Classification of coals by rank. ASTM D388-84,Philadelphia, PA, USA, American Society for Testing andMaterials, 6 pp (1984)Anderson A and others (1985) Applied coal and cokepetrography. NERDDP/EG/85/407, Canberra, ACT,Australia, National Energy Research, Development andDemonstration Council, vp (Mar 1985)Asakura T (1987) Coal quality for steel mills. In: Australia-Japan coal seminar, Sydney, NSW, Australia, 5 Mar 1987.North Ryde, NSW, Australia, Australian Coal IndustryResearch Laboratories, 27 pp (1987)Badin E J (1984) Coal combustion chemistry - correlationaspects. Amsterdam, the Netherlands, Elsevier SciencePublishers, 270 pp (1984)Baker J W (1986) Technical support to thermal coalmarketing. In: Preprints, technical support for coalmarketing seminar, Brisbane, Qld, Australia, 24 Nov 1986.North Ryde, NSW, Australia, Australian Coal IndustryResearch Laboratories, 30 pp (1986)Baker J W, Bennett P A, Holcombe D, Smith G B (1986)Pilot scale combustion testing and research. In: Proceedings,second Australian coal science conference, Newcastle, NSW,Australia, 1-2 Dec 1986. Wahroonga, NSW, Australia,Australian Institute of Energy, vol 1, pp 69-74 (1986)

Baldwin R M, Durfee S L, Voorhees K J (1983)Correlation of coal liquefaction reactivity with coalproperties. American Chemical Society, Division of FuelChemistry, Preprints; 28 (5); 1-7 (1983)Baldwin R M, Voorhees K J, Durfee S L (1987)Relationship of coal characteristics to coal reactivity fordirect hydrogenation liquefaction. Fuel ProcessingTechnology; 15; 281-292 (Jan 1987)BCRA Quarterly (1986) Coal characteristics important foruses other than cokemaking. Part 1: combustion,gasification, liquefaction. BCRA Quarterly; (11); 44-62(Apr 1986)Becke H (1988) Helsinki, Finland, Imatran Vioma Oy,private communication (Jan 1988)Benedict L G, Thompson R R, Wenger R C (1968)Relationship between coal petrographic composition andcoke stability. Blast Furnace and Steel Plant; 56 (3);217-224(1968)Bengtsson M (1986) Combustion behaviour for a range ofcoals of various origins and petrographic composition.Stockholm, Sweden, The Royal Institute of Technology,Department of Heat and Furnace Technology, vp (Mar 1986)Bengtsson M (1987a) Combustion behaviour for a coalcontaining a high proportion of pseudovitrinite. FuelProcessing Technology; 15; 201-212 (1987)Bengtsson M (1987b) Combustion behaviour for a range ofcoals of various origins and petrographic compositions. In:1987 international conference on coal science, Maastricht,the Netherlands, 26-30 Oct 1987. Amsterdam, theNetherlands, Elsevier Science Publishers, pp 893-896 (1987)Bengtsson M, Moilanen A (1986) Coal characterisation -combustion properties of coal after long-term storage. Paperpresented to Finnish Flame Day's Conference, Otariemi,Finland, 3-5 Sep 1986.Bennett A J R, Taylor G H (1970) A petrographic basis forclassifying Australian coals. Proceedings of the AustralasianInstitute of Mining and Metallurgy; (233); 1-5 (Mar 1970)Berkowitz N (1979) An introduction to coal technology.New York, NY, USA, Academic Press, 359 pp (1979)

References

Berkowitz N (1985) The chemistry of coal. Amsterdam, theNetherlands, Elsevier Science Publishers, 566 pp (1985)Berkowitz N (1988) Coal aromaticity and average molecularstructure. In: Polynuclear aromatic compounds. Ebert L B(ed) ACS advances in chemistry series 217, Washington,DC, USA, American Chemical Society, pp 217-233 (1988)Beyer H D (1982) Caking and coking power of bituminouscoals under high pressures. BMFT-FB-T-82-055, Bonn,FRG, Bundesministerium fur Forschung und Technologie, 62pp (Apr 1982) (In German)Beyer H D (1984) Caking and coking power of bituminouscoals under high pressures - pressure-dependent Roga index.BMFT-FB-T-84-293, Bonn, FRG, Bundesministerium furForschung und Technologie, 93 pp (Dec 1984) (In German)Blackmore G (1985) Keynote: measuring the cost effects ofcoal quality. In: CoalTrans 84, 3rd international coal trade,transportation and handling conference, London, UK, 1 -3Oct 1984. Loth D (ed) Worcester Park, UK, CSPublications, pp 63-75 (1985)Borio R W, Levasseur A A (1986) Coal ash deposition inboilers. ACS Symposium Series; (301); 288-302 (1986)British Carbonisation Research Association (1984) Studiesof the mechanical and chemical properties of coke at hightemperatures. EUR-9045-EN, Luxembourg, Commission ofthe European Communities, vp (1984)Brown N A, Coin C D A, Gill W W (1982) Prediction ofcoke quality. BHP Technical Bulletin; 2(1); 27-30 (1982)Bryers R W, Walchuk O R (1985) Investigation of pyrite asa contributor to slagging in Eastern bituminous coals. Finalreport. DE-85014561, DOE/PC/40268-8-PU andDE-85014562, DOE/PC/40268-8-Pt.2, Springfield, VA,USA, National Technical Information Service, 2 vols, 493 pp(Mar 1985)

Burbach H E, Harris D A, Hensel R P, Martinez O,Thimot G W (1977) Compatibility between furnaces andfuels conducive to high boiler availability. Power (NewYork); 121 (12); 41-46 (Dec 1977)Burchill P (1987) Some observations on the nitrogen contentand functionality with coal rank. In: 1987 internationalconference on coal science, Maastricht, the Netherlands,26-30 Oct 1987. Amsterdam, the Netherlands, ElsevierScience Publishers, pp 5-8 (1987)Burchill P, Dunstan B, Mitchell C A, Martin T G (1987)Solid-state techniques for coal characterisation. In:Round-table meeting 'Chemical and physical valorization ofcoal', Brussels, Belgium, 10 Jun 1987. EUR-11150,Luxembourg, Commission of the European Communities, pp59-91 (1987)Burdett N A, Pye J W (1987) The effect of coalcomposition on NOx formation during combustion undercontrolled conditions. In: 1987 international conference oncoal science, Maastricht, the Netherlands, 26-30 Oct 1987.Amsterdam, the Netherlands, Elsevier Science Publishers, pp845-852(1987)Bustin R M, Cameron A R, Grieve D A, Kalkreuth W D(1985) Coal petrology - its principles, methods andapplications. St John's, Newfoundland, Canada, GeologicalAssociation ot Canada, 243 pp (1985)Callcott T G (1982) Coal systematics. In: Coal science1982, abstracts and papers, symposium on characteristics ofAustralian coals and their consequences for utilization, NorthRyde, NSW, Australia, 18-22 May 1982. North Ryde, NSW,

Australia, CSIRO, Division of Fossil Fuels, pp 19/1-19/4(1982)Ceely F J, Daman E L (1981) Combustion processtechnology. In: Chemistry of coal utilization - secondsupplementary volume. Elliott M A (ed) New York, NY,USA, John Wiley and Sons, pp 1313-1387 (1981)Chaffee A L, Liepa I, Redlich P J, Jackson W R, LarkinsF P (1986) The molecular nature of oil from coal: GC-MSanalyses of oils produced using SnO2/H2- In: Proceedings,second Australian coal science conference, Newcastle, NSW,Australia, 1-2 Dec 1986. Wahroonga, NSW, Australia,Australian Institute of Energy, vol 1, pp 369-374 (1986)Chandra D (1982) Oxidized coals. In: Stach's textbook ofcoal petrology. Stach E, Mackowsky M T and others (eds)Berlin, FRG, Gebrtider Borntraeger, pp 198-206 (1982)Chandra D (1985) Evaluation of coal characteristics. In:Proceedings, 1985 international conference on coal science,Sydney, NSW, Australia, 28-31 Oct 1985. Sydney, NSW,Australia, Pergamon Press, pp 600-603 (1985)Chandra D, Taylor G H (1982) Gondwana coals. In:Stach's textbook of coal petrology. Stach E, Mackowsky MT and others (eds) Berlin, FRG, Gebriider Borntraeger, pp177-198(1982)Chen P (1987) Caking index and new classification ofChinese coals. In: 1987 international conference on coalscience, Maastricht, the Netherlands, 26-30 Oct 1987.Amsterdam, the Netherlands, Elsevier Science Publishers, pp159-163 (1987)Clarke J W, Kimber G M, Rantell T D, Shipley D E(1980) Reactivity of British coals in solvent extraction. In:Coal liquefaction fundamentals. Whitehurst D D (ed) ACSsymposium series no. 139, Washington, DC, USA, AmericanChemical Society, pp 111-129 (1980)Coal Marketing Manual (1986) Coal marketing manual.Sydney, NSW, Australia, Australian Coal Report, 209 pp(1986)Coin C D A (1987) Coke microtextural description.Comparison of nomenclature, classification and methods.Fuel; 66 (5); 702- 705 (May 1987)Collin P J, Heng S, Wilson M A (1983) The effect oftemperature on the mean chemical composition of theproducts from hydrogenation of vitrinite and inertiniteconcentrates from Bayswater coal. In: Proceedings, 1983international conference on coal science, Pittsburgh, PA,USA, 15-19 Aug 1983. Pittsburgh, PA, USA, PittsburghEnergy Technology Center, pp 56-59 (1983)Cookson D J, Smith D E (1987) An investigation of theutility of H and C nmr chemical shift data when applied tofossil fuel products. In: Coal science and chemistry.Volborth A (ed) Amsterdam, the Netherlands, ElsevierScience Publishers, pp 31-60 (1987)Creaney S, Pearson D E, Marconi L G (1980) Anomalouscoking properties of the Wolgan seam, NSW, Australia.Fuel; 59 (6); 438-440 (Jun 1980)Cronauer D C, Ruberto R G, Silver R S, Jenkins R G,Davis A, Hoover D S (1984) Liquefaction of partially driedand oxidized coals. 3. Liquefaction results. Fuel; 63 (1);71-77 (Jan 1984)Cudmore J F (1984) Coal utilization. In: Coal geology andcoal technology. Ward C R (ed) Melbourne, Vic, Australia,Blackwell Scientific Publications, pp 113-150 (1984)Cudmore J F, Handley K (1987) Metallurgical coke

References

manufacture and factors influencing its behaviour in theblastfurnace. ACIRL-PR-87-5, North Ryde, NSW,Australia, Australian Coal Industry Research Laboratories,132pp(Sep 1987)dimming J W (1984) Reactivity assessment of coals via aweighted mean activation energy. Fuel; 63 (10); 1436-1440(Oct 1984)dimming J W, Livingston W R, Hesselmann G J (1987)Coal reactivity assessment for boiler design. In: CoalTech87, 6th international conference and exhibition on coaltechnology and coal economics, London, UK, 9-11 Jun 1987.Schiedam, the Netherlands, Industrial Presentations (Europe)BV, pp 11-30 (1987)Damberger H H, Harvey R D, Ruch R R, Thomas J(1984) Coal characterization. In: The science and technologyof coal and coal utilization. Cooper B R, Ellingson W A(eds) New York, NY, USA, Plenum Press, pp 7-45 (1984)Davidson R M (1983) Mineral effects in coal conversion.ICTIS/TR22, London, UK, IEA Coal Research, 100 pp (Jan1983)Davidson R M (1986) Nuclear magnetic resonance studiesof coal. ICTIS/TR32, London, UK, IEA Coal Research, 108PPO986)Davis A (1970) A classification for Australian coals.Queensland Government Mining Journal; 71; 204-205 (May1970)Davis A (1978) The reflectance of coal. In: Analyticalmethods for coal and coal products - volume 1. Karr C Jr(ed) New York, NY, USA, Academic Press, pp 27-81 (1978)Davis A (1984) Coal petrology and petrographic analysis.In: Coal geology and coal technology. Ward C R (ed)Melbourne, Vic, Australia, Blackwell Scientific Publications,pp 74-112 (1984)Davis A, Spackman W, Given P H (1976) The influence ofthe properties of coals on their conversion into clean fuels.Energy Sources; 3 (1); 55-81 (1976)Davis G O (1978) Coal refining by solvent extraction andhydrocracking. Chemistry and Industry; 5 (115); 560-566 (5Aug 1978)Day J C, Jones R H, Belcher C B (1979) Evaluation ofcoals for the metallurgical and power industries. BHPTechnical Bulletin; 23 (2); 11-18 (Nov 1979)Derbyshire F, Stansberry P (1987) Comments on thereactivity of low-rank coals in liquefaction. Fuel; 66 (12);1741-1742 (Dec 1987)Derbyshire F J, Whitehurst D D (1981) Study of coalconversion in polycondensed aromatic compounds. Fuel; 60(8); 655-662 (Aug 1981)Derbyshire F J, Varghese P, Whitehurst D D (1981) Thepromotion of coal liquefaction by mineral matter catalysis.In: Proceedings, international conference on coal science,Dusseldorf, FRG, 7-9 Sep 1981. Essen, FRG, VerlagGliickauf, pp 356-361 (1981)Derbyshire F J, Davis A, Lin R, Stansberry P G, TerrerM -T (1986) Coal liquefaction by molybdenum catalyzedhydrogenation in the absence of solvent. Fuel ProcessingTechnology; 12; 127-141 (Mar 1986)Deutsches Institut fur Normung (1976) Internationalclassification system for hard coals. DIN 23003, Berlin,FRG, Beuth Verlag GmbH, 4 pp (Apr 1976)Diessel C F K (1982) Reactive inertinite.NERDDP/EG/82/46, Canberra, ACT, Australia, National

Energy Research, Development and Demonstration Council,49 pp (Jan 1982)Diessel C F K (1983) Carbonization reactions of inertinitemacerals in Australian coals. Fuel; 62 (8); 883-892 (Aug1983)Diessel C F K (1986) Fusible and non-fusible componentsof coal. In: Proceedings, second Australian coal scienceconference, Newcastle, NSW, Australia, 1-2 Dec 1986.Wahroonga, NSW, Australia, Australian Institute of Energy,vol l ,pp 327-332 (1986)Diessel C F K, Wolff-Fischer E (1987) Coal and cokepetrographic investigations into the fusibility ofCarboniferous and Permian coking coals. InternationalJournal of Coal Geology; 9; 87-108 (1987)Donini J C, LaCourt S A, Lynch B M, Simon A (1982)Determination of surface and bulk oxidation of coals byFourier transform infrared spectroscopy using photoacousticdetector. In: Coal - phoenix of the '80s, 64th CIC coalsymposium, Halifax, Nova Scotia, Canada, 31 May-3 Jun1981. Al Taweel A M (ed) Ottawa, Ontario, Canada,Canadian Society for Chemical Engineering, vol 1, pp132-134(1982)Doolan K J, Knott A C (1985) Characterisation of coalsrelative to NOx emissions. NERDDP/EG/86/512, Canberra,ACT, Australia, National Energy Research, Development andDemonstration Council, 59 pp (Jun 1985)Dunstone R H (1985) Commercial implications of coalproperties. Geological Society of Australia Abstracts; (17);191-198(1985)Durfee S L, Voorhees K J (1985) Pyrolysis-massspectroscopic prediction of liquefaction reactivity andstructural analysis of coal. Analytical Chemistry; 57 (12);2378-2384 (Oct 1985)Durie R A (1980) The characteristics of Australian coals andtheir implications in coal liquefaction. In: Coal liquefactionfundamentals. Whitehurst D D (ed) ACS symposium seriesno. 139, Washington, DC, USA, American Chemical Society,pp 53-73 (1980)Durie R A (1982) Coal properties and their importance inthe production of liquid fuels - an overview. Fuel; 61 (10);883- 888 (Oct 1982)Economic Commission for Europe (1956) Internationalclassification of hard coals by types. E/ECE/247,E/ECE/COAL/110, New York, NY, USA, United Nations, 54pp (Aug 1956)Economic Commission for Europe (1957) Mining andupgrading of brown coal in Europe: developments andprospects. E/ECE/297, E/ECE/COAL/124, New York, NY,USA, United Nations, vp (1957)Economic Commission for Europe (1976) Comparison ofsystems of classification of hard coals by type, as used inparticular countries, with the ECE internationalclassification. COAL/GE.3/R.16/Rev.l, Geneva,Switzerland, United Nations, Economic Commission forEurope, 9 pp (21 May 1976)Economic Commission for Europe (1982a) Preparation ofan industrial classification of medium-rank coals.COAL/GE.3/R.49/Add.ll, Geneva, Switzerland, UnitedNations, Economic Commission for Europe, 3 pp (21 Jan1982)Economic Commission for Europe (1982b) Report of thethird ad hoc meeting on the preparation of a new ECE

References

classification of coals. COAL/AC.5/6, Geneva, Switzerland,United Nations, Economic Commission for Europe, 13 pp(4 Mar 1982)Economic Commission for Europe (1982c) Preparation ofan industrial classification of medium-rank coals.COAL/GE.3/R.49/Add.l4/Rev.l, Geneva, Switzerland,United Nations, Economic Commission for Europe, 4 pp(7 May 1982)Economic Commission for Europe (1982d) Preparation ofa new ECE classification of coals - general classification.COAL/R.88, Geneva, Switzerland, United Nations,Economic Commission for Europe, 4 pp (25 Aug 1982)Economic Commission for Europe (1985a) Preparation ofa new ECE classification of coals. COAL/GE.3/R.76/Add.2,Geneva, Switzerland, United Nations, Economic Commissionfor Europe, 3 pp (31 Oct 1985)Economic Commission for Europe (1985b) Report ofeighty-first session of the Coal Committee. ECE/COAL/88,Geneva, Switzerland, United Nations, Economic Commissionfor Europe, 35 pp (1 Nov 1985)Economic Commission for Europe (1986) Preparation of anew ECE classification of coals.COAL/GE.3/R.76/Add.2/Supp.l, Geneva, Switzerland,United Nations, Economic Commission for Europe, 16 pp(10M 1986)Economic Commission for Europe (1988) Internationalcodification system for medium and high rank coals.ECE/COAL/115, New York, NY, USA, United Nations, 28PP(1988)EidePman E Ya (1981) On coal classification. Coke andChemistry USSR (English translation ofKoks i Khimiya);(6); 108-111 (1981)Eisenhut W (1981) High temperature carbonisation. In:Chemistry of coal utilization - second supplementary volume.Elliot M A (ed) New York, NY, USA, John Wiley and Sons,pp 847-917 (1981)Eklund G, Pedersen J R, Striiomberg B (1987)Determination of combustible volatile matter in fuels. Fuel;66(1); 13-16 (Jan 1987)Elliott M A (1981) Preface. In: Chemistry of coal utilization- second supplementary volume. Elliot M A (ed) New York,NY, USA, John Wiley and Sons, pp xiii-xv (1981)Elofson R M, Schulz K F (1967) Some spectralobservations on two coking lignites. American ChemicalSociety, Division of Fuel Chemistry, Preprints; 11 (4);259-263 (1967)Eremin I V, Tsikarev D A, Bronovets T M (1982)Petrological-genetic classification and cokability of coals.Solid Fuel Chemistry (English translation of KhimiyaTverdogo Topliva); 16 (3); 1-5 (1982)Eremin I V, Bronovets T M, Ol'shanetskii L G, Kaftan YS (1983) A uniform industrial-genetic classification for hardcoals of the USSR. Coke and Chemistry USSR (Englishtranslation of Koks i Khimiya); (5); 1-8 (1983)Eriksson S, Nord B, Persson K (1981) Coal classification.KHM- TR-14, Vallengby, Sweden, Statens Vattenfallsverk,Projekt Kol-Halsa-Miljo, 26 pp (Dec 1981) (In Swedish)Essenhigh R H (1981) Fundamentals of coal combustion.In: Chemistry of coal utilization - second supplementaryvolume. Elliott M A (ed) New York, NY, USA, John Wileyand Sons, pp 1153-1312(1981)Falcon R M S (1977) Coal in South Africa - Part 1: the

quality of South African coal in relation to its uses and worldenergy resources. Minerals Science and Engineering; 9 (4);198-217 (Oct 1977)Falcon R M S (1978a) Coal in South Africa, Part II. Theapplication of petrography to the characterization of coal.Minerals Science and Engineering; 10 (1); 28-53 (Jan 1978)Falcon R M S (1978b) Coal in South Africa. Part III -Summary and proposals - the fundamental approach to thecharacterization and rationalization of South Africa's coal.Minerals Science and Engineering; 10 (2); 130-153 (Apr1978)Falcon R M S , Snyman C P (1986) An introduction to coalpetrography: atlas of petrographic constituents in thebituminous coals of Southern Africa. Johannesburg, SouthAfrica, Geological Society of South Africa, vp (1986)Fletcher I, Kelvin N V P (1980) Influence of coalcharacteristics on hydrogenation performance.ACIRL-PR-80-12, North Ryde, NSW, Australia, AustralianCoal Industry Research Laboratories, 34 pp (Oct 1980)Francis W (1954) Coal: its formation and composition.London, UK, Edward Arnold (Publishers) Ltd., 575 pp (1954)Fredericks P M, Grazier P E (1985) Quality control of coalby Fourier transform infrared spectroscopy. In: Proceedings,1985 international coal science conference, Sydney, NSW,Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 815-817 (1985)Fredericks P M, Osborn P R, Swinkels D A J (1984)Rapid coal characterization by FT-ir spectroscopy. Fuel; 63(1); 139-141 (Jan 1984)

Fredericks P M, Kobayashi R, Osborn P R (1987) Rapidanalysis of coal blends by diffuse reflectance FT-irspectrometry. Fuel; 66 (11); 1603-1608 (Nov 1987)Fuller M P, Hamadeh I M, Griffiths P R, Lowenhaupt DE (1982) Diffuse reflectance infrared spectrometry ofpowdered coals. Fuel; 61 (6); 529-536 (Jun 1982)Furlong M W, Baldwin R M, Bain R L (1981) Reactivityof coal towards hydrogenation: ranking by kineticmeasurements. In: Proceedings, international conference oncoal science, Dusseldorf, FRG, 7-9 Sep 1981. Essen, FRG,Verlag Gliickauf, pp 374-379 (1981)Furlong M W, Baldwin R M, Bain R L (1982) Reactivityof coal towards hydrogenation - ranking by kineticmeasurements. Fuel; 61 (2); 116-120 (Feb 1982)Gannon R E, Abichandani J S, Neoh K G (1987) Coalcharacteristics important to pulverized coal processes. FuelProcessing Technology; 15; 189-199 (Jan 1987)Ghetti P (1986) DTG combustion behaviour of coal.Correlations with proximate and ultimate analysis data.Fuel; 65 (5); 636-639 (May 1986)

Ghetti P, De Robertis U, D'Antone S, Villani M, ChielliniE (1985) Coal combustion. Correlation between surface areaand thermogravimetric analysis data. Fuel; 64 (7); 950-955(Jul 1985)Given P H (1983) The dependence of liquefaction behavioron coal characteristics. Final technical report for theperiod March 1981 to February 1984. Part 1: dependenceof liquefaction behavior on coal characteristics: a selectiveand critical review of the literature. DOE-40784-FR-1,Springfield, VA, USA, National Technical InformationService, 92 pp (May 1983)Given P H (1984) An essay on the organic geochemistry ofcoal. In: Coal science, volume 3. Gorbaty M L, Larsen J

References

W, Wender I (eds) Orlando, FL, USA, Academic Press, pp63-252(1984)Given P H, Yarzab R I (1978) Analysis of the organicsubstance of coals: problems posed by the presence ofmineral matter. In: Analytical methods for coal and coalproducts - volume 2. Karr C Jr (ed) New York, NY, USA,Academic Press, pp 3-41 (1978)Given P H, Cronauer D C, Spackman W, Lovell H L,Davis A, Biswas B (1975a) Dependence of coal liquefactionbehaviour on coal characteristics. 1. Vitrinite-rich samples.Fuel; 54 (1); 34-39 (Jan 1975)Given P H, Cronauer D C, Spackman W, Lovell H L,Davis A, Biswas B (1975b) Dependence of coal liquefactionbehaviour on coal characteristics. 2. Role of petrographiccomposition. Fuel; 54 (1); 40-49 (Jan 1975)Given P H, Spackman W, Davis A, Jenkins R G (1980)Some proved and unproved effects of coal geochemistry onliquefaction behaviour with emphasis on US coals. In: Coalliquefaction fundamentals. Whitehurst D D (ed) ACSsymposium series no. 139, Washington, DC, USA, AmericanChemical Society, pp 3-34 (1980)Given P H, Weldon D, Zoeller J H (1986) Calculation ofcalorific values of coals from ultimate analyses: theoreticalbasis and geochemical implications. Fuel; 65 (6); 849-854(Jun 1986)Gluskoter H J, Shimp N F, Ruch R R (1981) Coalanalyses, trace elements, and mineral matter. In: Chemistryof coal utilization - second supplementary volume. Elliott MA (ed) New York, NY, USA, John Wiley and Sons, pp369-424 (1981)Gorin E (1981) Fundamentals of coal liquefaction. In:Chemistry of coal utilization - second supplementary volume.Elliott M A (ed) New York, NY, USA, John Wiley andSons, pp 1845-1918 (1981)Goscinski J S, Gray R J, Robinson J W (1985a) A reviewof American coal quality and its effect on coke reactivity andafter reaction strength of cokes. Journal of Coal Quality; 4(1); 35-43 (May 1985)Goscinski J S, Gray R J, Robinson J W (1985b) A reviewof American coal quality and its effect on coke reactivity andafter reaction strength of cokes. Journal of Coal Quality; 4(2); 21-29 (Nov 1985)Grainger L, Gibson J (1981) What is coal? In: Coalutilization: technology, economics and policy. London, UK,Graham and Trotman, pp 3-30 (1981)Gray D, Barrass G, Jezko J, Kershaw J R (1980a) SouthAfrican coals and their behaviour during liquefaction. In:Coal liquefaction fundamentals. Whitehurst D D (ed) ACSsymposium series no. 139, Washington, DC, USA, AmericanChemical Society, pp 35-51 (1980)Gray D, Barrass G, Jezko J, Kershaw J R (1980b)Relations between hydroliquefaction behaviour and theorganic properties of a variety of South African coals. Fuel;59(3); 146-150 (Mar 1980)Gray R J, DeVanney K F (1986) Coke carbon forms:microscopic classification and industrial applications.International Journal of Coal Geology; 6 (3); 277-297 (Sep1986)Gray R J, Rhoades A H (1984) Zonax automaticmicroscope for monitoring coal quality and blendproportioning for cokemaking. Ironmaking Proceedings,Metallurgical Society ofAIME; 43; 189-196 (1984)

Gray V R (1980) Graphical methods for determination ofthe mineral-matter-free properties of coal and the mineralmatter/ash ratio. Fuel; 59 (8); 551-556 (Aug 1980)Gray V R (1983) Coal analysis in New Zealand.NZERDC-97, Auckland, New Zealand, New Zealand EnergyResearch and Development Committee, 78 pp (Sep 1983)Gray V R (1987a) The effect of coal properties oncombustion. Paper presented at international symposium onmultiphase flows, China, Apr 1987.Gray V R (1987b) Prediction of ash fusion temperature fromash composition for some New Zealand coals. Fuel; 66 (9);1230- 1239 (Sep 1987)Green P D, Patrick J W, Thomas K M, Walker A (1985)Some aspects of the role of coal thermoplasticity and cokestructure in coal gasification. 2. The effects of pressure andheating rate on dilatometric parameters and opticalanisotropy development. Fuel; 64 (10); 1431-1437 (Oct1985)Gromulski J (1986) Combustion properties for Polish andRussian coals: a literature review. Report SUF-215,Stockholm, Sweden, Stiftelsen for Varmeleknisk Forskning,74 pp (Feb 1986) (In Swedish)Gutmann M, Keil G, Klare H, Konig M, Radeck D(1987a) Hydrogenation of brown coals - relations betweenselected lithotypes and liquid products. Fuel ProcessingTechnology; 15; 327-339 (Jan 1987)Gutmann M, Konig M, Radeck D, Keil G (1987b)Correlation between parameters of lignite and hydrogenationreactivity from experiments in a batch reactor. In: 1987international conference on coal science, Maastricht, theNetherlands, 26-30 Oct 1987. Amsterdam, the Netherlands,Elsevier Science Publishers, pp 187-192 (1987)Guyot R E (1978a) Influence of coal characteristics on theyields and properties of hydrogenation products.ACIRL-PR-78-8, North Ryde, NSW, Australia, AustralianCoal Industry. Research Laboratories, 33 pp (Jun 1978)Guyot R E (1978b) Relationship between coal propertiesand liquefaction potential. ACIRL-PR-79-1, North Ryde,NSW, Australia, Australian Coal Industry ResearchLaboratories, 28 pp (Dec 1978)Habermehl D, Orywal F, Beyer H D (1981) Plasticproperties of coal. In: Chemistry of coal utilization - secondsupplementary volume. Elliott M A (ed) New York, NY,USA, John Wiley and Sons, pp 317-368 (1981)Hainley D C, Yavuzkurt S, Scaroni A W (1986) Effect ofcoal properties on fluidized bed combustor performance. In:Technical, economics, synfuels and coal energy - 1986, ninthannual energy sources technology conference, New Orleans,LA, USA, 23-27 Feb 1986. Dicks J B (ed) New York, NY,USA, American Society of Mechanical Engineers, pp 43-54(1986)Handley K J, Burke L O, Naylor P, Stumm M, Roberts OC, Clough S, Cudmore J F (1984) Carbonising propertiesof Australian coals and blends. NERDDP/EG/85/387,Canberra, ACT, Australia, National Energy Research,Development and Demonstration Council, 252 pp (Dec 1984)Hao L (1983) The combustion of anthracites and low gradebituminous coals. In: Proceedings, 1983 internationalconference on coal science, Pittsburgh, PA, USA 15-19 Aug1983. Pittsburgh, PA, USA, Pittsburgh Energy TechnologyCenter, pp 561-564 (1983)Harper A M, Meuzelaar H L C, Given P H (1984)

References

Correlations between pyrolysis mass spectra of RockyMountain coals and conventional coal parameters. Fuel; 63(6); 793-802 (Jun 1984)Heng S, Shibaoka M (1983) Hydrogenation of the inertinitemacerals of Bayswater coal. Fuel; 62 (5); 610-612 (May1983)Heng S, Collin P J, Wilson M A (1983) Hydrogenation ofmaceral concentrates from Bayswater coal: effect oftemperature on the yield and mean chemical composition ofthe product. Fuel; 62 (11); 1359-1368 (Nov 1983)Hessley R K, Reasoner J W, Riley J T (1986) Coalscience: an introduction to chemistry, technology andutilization. New York, NY, USA, John Wiley and Sons, 279pp(1986)Higgins R S (1987) Richmond, Vic, Australia, StateElectricity Commission of Victoria, Herman ResearchLaboratory, private communication (1987)Hill G R, Jakab E, Hoesterey B, Meuzelaar H L C (1985)Oxidative weathering phenomena in coals from the WesternUnited States. In: Proceedings, 1985 internationalconference on coal science, Sydney, NSW, Australia, 28-31Oct 1985. Sydney, NSW, Australia, Pergamon Press, pp459-462(1985)Hoover D S (1983) Correlation of coal quality to coalliquefaction. American Chemical Society, Division of FuelChemistry, Preprints; 28 (5); 48-57 (1983)Horie H (1987) Coal manual 1987. Japan, Tokyo, TexReport Ltd, 532 pp (1987)Hough D C, Sanyal A (1987) The role of petrography in theclassification and combustion of coal. Energy World; (146);7-10 (Apr 1987)Hower J C (1988) Additivity of Hardgrove grindability. acase study. Journal of Coal Quality; 7 (2); 68-70 (Apr/Jun1988)Huggins F E, Kosmack D A, Huffman G P, Lee R J(1980) Coal mineralogies by SEM automatic image analysis.Scanning Electron Microscopy; 1980 (I); 531-540 (1980)Hutton A C, Cook A C (1980) Influence of alginite on thereflectance of vitrinite from Joadja, NSW and some othercoals and oil shales containing alginite. Fuel; 59 (10);711-714 (Oct 1980)IEA Coal Combustion Sciences (1985) First annual reportof the IE A implementing agreement for a programme ofresearch, development and demonstration of coal combustionsciences: annex 1, cooperation on investigation intoadvanced analytical techniques and basic and appliedresearch in the field of coal combustion sciences, 31December 1985. Available from International EnergyAgency, Paris, France.IEA Coal Industry Advisory Board (1985) Coal qualityand ash characteristics. Paris, France, OECD/IEA, 63 pp(1985)Ignasiak B, Carson D, Szladow A J, Berkowitz N(1980) Studies on noncatalytic liquefaction of WesternCanadian coals. In: Coal liquefaction fundamentals.Whitehurst D D (ed) ACS symposium series no. 139,Washington, DC, USA, American Chemical Society, pp97-110(1980)International Committee for Coal Petrology (1963)International handbook of coal petrography. Second edition.Paris, France, Centre National de la Recherche Scientifique,vp(1963)

International Committee for Coal Petrology (1975)International handbook of coal petrography. Supplement tothe second edition. Paris, France, Centre National de laRecherche Scientifique, vp (1975)International Committee for Coal Petrology (1985)International handbook of coal petrography. Edited reprintof 1971 supplement to the second edition. Murchison D G,Smith A H V (eds) Newcastle upon Tyne, UK, University ofNewcastle upon Tyne, vp (1985)International Organization for Standardization (1974)Brown coals and lignites - classification by types on thebasis of total moisture content and tar yield. ISO2950-1974, Geneva, Switzerland, International Organizationfor Standardization, 2 pp (1974)Jackson P J (1987) Mineral matter in pulverized coalcombustion. In: Fundamentals of the physical-chemistry ofpulverized coal combustion, proceedings of NATO advancedresearch workshop, Les Arcs, France, 28 Jul-1 Aug 1986.Lahaye J, Prado G (eds) Dordrecht, the Netherlands,Martinus Nijhoff, pp 269-287 (1987)James R G, Severn M I (1967) Effect of particle size on thedetermination of pyritic sulphur. Fuel; 46; 476-478 (1967)Jones J M, Davis A, Cook A C, Murchison D G, Scott E(1984) Provincialism and correlations between someproperties of vitrinites. International Journal of CoalGeology; 3 (4); 315-331 (Apr 1984)Jones R B, McCourt C B, Morley C, King K (1985)Maceral and rank influences on the morphology of coal char.Fuel; 64 (10); 1460-1467 (Oct 1985)Jiintgen H (1987a) Coal characterization in relation to coalcombustion. Part I: structural aspects and combustion. ErdolKohle, Erdgas, Petrochemie vereinigt mit Brennstoff-Chemie;40 (4); 153-165 (Apr 1987) (In English)Jiintgen H (1987b) Coal characterization in relation to coalcombustion. Part II: environmental problems of combustion.Erdol Kohle, Erdgas, Petrochemie vereinigt mitBrennstoff-Chemie; 40 (5); 204-208 (May 1987) (In English)Kalkreuth W (1982) Rank and petrographic composition ofselected Jurassic-Lower Cretaceous coals of BritishColumbia, Canada. Bulletin of Canadian PetroleumGeology; 30 (2); 112-139 (1982)Kalkreuth W, Charnet G (1984) Liquefactioncharacteristics of selected vitrinite and liptinite rich coalsfrom British Columbia, Canada. Fuel ProcessingTechnology; 9(1); 53-65 (Jul 1984)Kershaw J R (1985) Variation in the chemical nature ofasphaltenes with the process, the coal and the reactionconditions. Liquid Fuels Technology; 3 (2); 205-228 (1985)Khan M R, Jenkins R G (1986) Swelling and plasticproperties of coal devolatilized at elevated pressures: anexamination of the influence of coal type. Fuel; 65 (5);725-731 (May 1986)King H -H, Dyrkacz G R, Winans R E (1984) Tetralindissolution of macerals separated from a single coal. Fuel;63 (3); 341-345 (Mar 1984)Kirchner A T (1987) Evaluative report on the mechanicalproperties of coke. IEACR/04, London, UK, IEA CoalResearch, 25 pp (1987)Kiss L T (1982) Chemistry of Victorian brown coals. In:Proceedings, symposium on coal resources: origin,exploration and utilization in Australia, Melbourne, Vic,Australia, 15-19 Nov 1982. Mallett C W (ed) Melbourne,

References

Vic, Australia, Geological Society of Australia, Coal Group,pp 153-168 (1982)Kiss L T, King T N (1979) Reporting of low-rank coalanalysis - the distinction between minerals and inorganics.Fuel; 58 (7); 547-549 (Jul 1979)Kister J, Dou H (1986) Global characterization of thechemical constituents of coal by x scanner, uv fluorescencespectroscopy and FTIR spectroscopy. Fuel ProcessingTechnology; 12; 19-29 (Mar 1986)Koba K (1980) Statistical analyses and prediction of cokingproperties of coal. Fuel; 59 (6); 380-388 (Jun 1980)Konev N L, Sobolev S Ya, Blokhin V S, Kilonenko Yu A,Makarov G N (1986) Effect of coal genetic properties oncoke quality. Koks i Khimiya; (12); 15-17 (Dec 1986) (InRussian)Kosina M (1984) Possibilities of the utilization ofmicropetrographic parameters in the scientific classificationof bituminous coals. International Journal of Coal Geology;4 (3); 263-280 (Dec 1984)Kosina M (1987) Scientific classification of bituminouscoals. International Journal of Coal Geology; 8 (3); 233-246(Sep 1987)Kosina M (1988) Effects of the properties and compositionof coal blends on coke mechanical properties. Fuel; 67 (3);431-436 (Mar 1988)Kosina M, Heppner P (1984) Macerals in bituminous coalsand the coking process. Part 1: effect of basic coal propertieson the process of thermal degradation. Fuel; 63 (6); 838-846(Jun 1984)Kosina M, Heppner P, Ruzicka I (1987) Importantproperties of bituminous coals influencing the carbonizationprocess. In: 1st international cokemaking congress -preprints, Essen, FRG, 13-18 Sep 1987. Essen, FRG, VerlagGliickauf, vol 1, Paper D5, 18 pp (1987)Kuehn D W, Snyder R W, Davis A, Painter P C (1982)Characterization of vitrinite concentrates. 1. Fouriertransform infrared studies. Fuel; 61 (8); 682-694 (Aug 1982)Kuehn D W, Davis A, Painter P C (1984) Relationshipsbetween the organic structure of vitrinite and selectedparameters of coalification as indicated by Fourier transformir spectra. In: Chemistry and characterization of coalmacerals. Winans R E, Crelling J C (eds) ACS symposiumseries no. 252, Washington, DC, USA, American ChemicalSociety, pp 99-119 (1984)Ladner W R, Martin T G, Snape C E, Bartle K D (1980)Insights into the chemical structure of coal from the nature ofextracts. American Chemical Society, Division of FuelChemistry, Preprints; 25 (4); 67-78 (1980)Larkins F P, Supaluknari S, Thomas R, Jackson W R,Redlich P (1986) Structural characterization of Australiancoals by FTIR and the relationship with liquefaction data.In: Proceedings, second Australian coal science conference,Newcastle, NSW, Australia, 1-2 Dec 1986. Wahroonga,NSW, Australia, Australian Institute of Energy, vol 1, pp357-362(1986)Lavill D (1988) Wellington, New Zealand, Ministry ofEnergy, private communication (Apr 1988)Lee G K, Whaley H (1983) Modification of combustion andfly-ash characteristics by coal blending. Journal of theInstitute of Energy; 56 (429); 190-197 (Dec 1983)Legarreta, J A, Arias P L, de Marco I (1987) Chemicaland petrographic characterization and liquefaction yields of

Spanish coals. Fuel Processing Technology; 15; 293-305(Jan 1987)Lenz U, Dolkemeyer W, Ritter G, Weiner B, Wolfrum E(1982) Effects of brown coal quality and process parameterson the hydroliquefaction of brown coal. Fuel; 61 (10);947-952 (Oct 1982)Linares-Solano A, Mahajan O P, Weldon D, Walker P L(1987) Coal liquefaction yields in tetralin - their predictionfrom heat measurements of coal hydrogenation in H2 byDSC. Fuel; 66 (5); 715-717 (May 1987)Lynch L J, Webster D S (1979) Plasticity of coal studiedwith nuclear magnetic resonance. Fuel; 58 (3); 235-237(Mar 1979)Lyons P C, Chase H B (1981) Rank of coal bed of theNarragansett basin, Massachusetts and Rhode Island.International Journal of Coal Geology; 1 (2); 155-168 (Jun1981)Mackowsky M T (1982a) Minerals and trace elementsoccurring in coal. In: Stach's textbook of coal petrology.Stach E, Mackowsky M T and others (eds) Berlin, FRG,Gebriider Borntraeger, pp 153-171 (1982)Mackowsky M T (1982b) Methods and tools ofexamination. In: Stach's textbook of coal petrology. StachE, Mackowsky M T and others (eds) Berlin, FRG, GebriiderBorntraeger, pp 295-348 (1982)Mackowsky M T (1982c) The application of coal petrologyin technical processes. In: Stach's textbook of coalpetrology. Stach E, Mackowsky M T and others (eds)Berlin, FRG, Gebriider Borntraeger, pp 413-481 (1982)Mackowsky M T (1983) The application of coal petrology.Special Publication, the Geological Society of South Africa;7; 97-109 (1983)Maijgren B, Hiibner W, Norrgard K, Sundvall S -B(1983) Determination of organic sulphur in raw andchemically cleaned coals by scanning electron microscopyand energy dispersive X-ray spectrometry. Fuel; 62 (9);1076-1078 (Sep 1983)Marchioni D L (1985) Reflectance studies in brown coal: anexample from the Hat Creek deposit of British Columbia. In:Neuvieme congres international de stratigraphie et degeologie du carbonifera, compte rendu, volume 4. Ninthinternational conference on Carboniferous stratigraphy andgeology, Champaign-Urbana, IL, USA, 17-26 May 1979.Cross A T (ed) Carbondale, IL, USA, Southern IllinoisUniversity Press, pp 590-599 (1985)Markuszewski R (1988) Some thoughts on the difficulties inthe analysis of sulfur forms in coal. Journal of Coal Quality;7 (1); 1-4 (Jan 1988)Marshall R J (1976) Classification of coking coals. Fuel;55 (10); 346-348 (Oct 1976)Mason D M, Gandhi K (1980) Formulas for calculating theheating value of coal and coal char: development, tests anduses. American Chemical Society, Division of FuelChemistry, Preprints; 25 (3); 235-245 (1980)Mazumdar B K (1984) Genetic development of coal andcoal behaviour. URJA; 15 (6); 437-444 (Jun 1984)McCartney J T, Teichmiiller M (1972) Classification ofcoals according to degree of coalification by reflectance ofthe vitrinite component. Fuel; 51 (1); 64-68 (Jan 1972)Merrick D (1984) Coal combustion and conversiontechnology. London, UK, Macmillan Publishers, 413 pp(1984)

References

Metcalf G S, Windig W, Hill G R, Meuzelaar H L C(1987) Characterization of US lignites by pyrolysis massspectrometry and multivariate analysis. InternationalJournal of Coal Geology; 7 (3); 245-268 (Mar 1987)Meuzelaar H L C, McClennen W H, Tomlinson J H, PopeD L (1981) A multimode Curie-point ms system for rapidcharacterization of fossil fuels and their liquefactionproducts. In: Proceedings, international conference on coalscience, Dusseldorf, FRG, 7-9 Sep 1981. Essen, FRG,Verlag Gluckauf, pp 816-821 (1981)Meuzelaar H L C, Harper A M, Hill G R, Given P H(1984a) Characterization and classification of RockyMountain coals by Curie-point pyrolysis mass spectrometry.Fuel; 63 (5); 640-652 (May 1984)Meuzelaar H L C, Harper A M, Pugmire R J, Karas J(1984b) Characterization of coal maceral concentrates byCurie-point pyrolysis mass spectrometry. InternationalJournal of Coal Geology; 4 (2); 143-147 (Sep 1984)Meuzelaar H L C, Hoesterey B L, Windig W, Hill G R(1987) Prediction and modeling of coal conversion reactionsby pyrolysis mass spectrometry and multivariate statisticalanalysis. Fuel Processing Technology; 15; 59-70 (1987)Miller R L, Baldwin R M (1985) Effect of Wyodak coalproperties on hydroliquefaction reactivity. Fuel; 64 (9);1235-1241 (Sep 1985)

Mochida I, Takarabe A, Takeshita K (1979) Solvolyticliquefaction of coals with a series of solvents. Fuel; 58 (1);17-23 (Jan 1979)Mochida I, Shimohara T, Korai Y, Fujitsu H (1984)Carbonisation of coals to produce anisotropic cokes. 5.Structural factors of coals influencing carbonizationproperties. Fuel; 63 (6); 847-853 (Jun 1984)Mochida I, Kishino M, Sakanishi K, Korai Y, TakahashiR (1987) Liquefaction reactivities of three subbituminouscoals in tetrahydrofluoranthene as a hydrogen donor. Energyand Fuels; 1 (4); 343-348 (Jul/Aug 1987)Morgan B A, Scaroni A W (1985) Pulverized lignitecombustion. In: Proceedings, 1985 international conferenceon coal science, Sydney, NSW, Australia, 28-31 Oct 1985.Sydney, NSW, Australia, Pergamon Press, pp 347-350 (1985)Morgan M E, Roberts P A (1987) Coal combustioncharacterisation studies at the International Flame ResearchFoundation. Fuel Processing Technology; 15; 173-187 (1987)Morgan P A, Robertson S D, Unsworth J F (1986)Combustion studies by thermogravimetric analysis. 1. Coaloxidation. Fuel; 65 (11); 1546-1551 (Nov 1986)Morgan P A, Robertson S D, Unsworth J F (1987)Combustion studies by thermogravimetric analysis. 2. Charoxidation. Fuel; 66 (2); 210-215 (Feb 1987)Mori K, Taniuchi M, Kawashima A, Okuma O,Takahashi T (1980) The relationship between coalcharacteristics and its reactivity on hydroliquefaction. In:Coal liquefaction fundamentals. Whitehurst D D (ed) ACSsymposium series no. 139, Washington, DC, USA, AmericanChemical Society, pp 75-96 (1980)

Morrison G F (1980) Nitrogen oxides from coal combustion- abatement and control. ICTIS/TR11, London, UK, IEACoal Research, 86 pp (Nov 1980)Morrison G F (1986) Understanding pulverised coalcombustion. ICTIS/TR34, London, UK, IEA Coal Research,46pp(Dec 1986)Moxon N T, McLellan J, Warbrooke P R (1986) The

effect of ash on the laboratory carbonization properties ofcoal. Journal of Coal Quality; 5 (2); 76-78 (Apr 1986)Mudamburi Z, Given P H (1985) Some chemical structuralfeatures of coals of differing maceral distributions andstratigraphy. Organic Geochemistry; 8 (6); 441-453 (1985)Munnix R (1984) Coke strength prediction based on coalpetrography and fluidity. Ironmaking Proceedings,Metallurgical Society of AIME; 43; 19-27 (1984)Murata T (1986) Types of coal and their effectiveutilization: obtaining the right methodology (II). KagakuSochi; 28 (3); 111-117 (1986) (In Japanese)Myllynen H (1988) Which thermal coal? In: CoalPower '87conference, Dusseldorf, FRG, 27-29 Oct 1987. WorcesterPark, UK, C S Publications, pp 37-42 (1988)Nandi B N, Brown T D, Lee G K (1977) Inert coalmacerals in combustion. Fuel; 56 (4); 125-130 (Apr 1977)National Coal Board (1964) The coal classification systemused by the National Coal Board. London, UK, NationalCoal Board, Scientific Control, 10 pp (1964)Navale G K B, Misra B K (1983) Status of Indian coals inuniversal classification of solid fossil fuels. Geophytology;13(2); 214-218(1983)Neavel R C (1976) Liquefaction of coal in hydrogen-donorand non-donor vehicles. Fuel; 55 (7); 237-242 (Jul 1976)Neavel R C (1981) Origin, petrography, and classification ofcoal. In: Chemistry of coal utilization - secondsupplementary volume. Elliott M A (ed) New York, NY,USA, John Wiley and Sons, pp 91-158 (1981)Neavel R C (1986) Coal science: an idiosyncratic view.Fuel; 65 (12); 1632-1637 (Dec 1986)Neavel R C, Hippo E J, Smith S E, Miller R N (1980)Coal characterization research: sample selection, preparationand analyses. American Chemical Society, Division of FuelChemistry, Preprints; 25 (3); 246-257 (1980)Neavel R C, Smith S E, Hippo E J, Miller R N (1981)Optimum classification of coals. In: Proceedings,international conference on coal science, Dusseldorf, FRG,7-9 Sep 1981. Essen, FRG, Verlag Gluckauf, pp 1-9 (1981)Neavel R C, Smith S E, Hippo E J, Miller R N (1986)Interrelationships between coal compositional parameters.Fuel; 65 (3); 312-320 (Mar 1986)Neill P H, Given P H, Weldon D (1987a) A search forsystematic relations between aromaticity and rank of highsulphur coals. Fuel; 66 (1); 92-95 (Jan 1987)Neill P H, Maciel G, Given P H, Weldon D (1987b)Aromaticity of some high sulphur coals: surprising degree ofheterogeneity. Fuel; 66 (1); 96-98 (Jan 1987)Neoh K G, Gannon R E (1984) Coal volatile yield andelement partition in rapid pyrolysis. Fuel; 63 (10); 1347-1352(Oct 1984)Newman J (1985) Relationships between vitrinite reflectanceand volatile matter in West Coast bituminous coals: 1. Theeffect of isorank type variations on coal properties. In: Coalresearch conference - proceedings, Wellington, NewZealand, 15-17 Oct 1985. Wellington, New Zealand, CoalResearch Association of New Zealand, vol 1, Paper 2.2, 10PP (1985)Newman R H, Davenport S J (1986) Comparison ofAustralasian Tertiary coals based on resolution-enhancedsolid state 13C nmr spectra. Fuel; 65 (4); 533-540 (Apr 1986)Newman J, Newman N A (1982) Reflectance anomalies inPike River coals: evidence for variability in vitrinite type

References

with implications for maturation studies and 'Suggate rank'.New Zealand Journal of Geology and Geophysics; 25 (2);233-243 (1982)Newman R H, Sim M N, Johnston J H, Collen J D (1988)Comparison of aromaticity and phenolic content asparameters for characterization of coal by C n.m.r.spectroscopy. Fuel; 67 (3); 420-425 (Mar 1988)Ng N, Cudmore J F (1987) Applied coal and cokepetrography in ACIRL. ACIRL-PR-87-1, North Ryde, NSW,Australia, Australian Coal Industry Research Laboratories, 72pp (Feb 1987)Nomura M, Yoshida T, Kikkawa S, Philp P (1982) Effectsof petrographic constituents in three Yallourn brown coallithotypes on hydroliquefaction processes. Fuel; 61 (5);472-473 (May 1982)Ode W H, Gibson F H (1960) International system forclassifying brown coals and lignites and its application toAmerican coals. BM-RI-5695, Washington, DC, USA,Bureau of Mines, 23 pp (1960)Oguri K, Kitahara A, Hijiriyama M, Nishida S, Akita K(1987) Evaluation of coking coal. In: 1st internationalcokemaking congress -preprints, Essen, FRG, 13-18 Sep1987. Essen, FRG, Verlag Gliickauf, vol 1, Paper El, 12 pp(1987)Oka N, Murayama T, Matsuoka H, Yamada S, YamadaT, Shinozaki S, Shibaoka M, Thomas C G (1987) Theinfluence of rank and maceral composition on ignition andchar burnout of pulverized coal. Fuel ProcessingTechnology; 15; 213-224 (Jan 1987)Ouchi K, Ibaragi S, Kobayashi A, Makino K, Itoh H(1984a) Reactivity of coals in hydrogenation. Fuel; 63 (3);427-430 (Mar 1984)Ouchi K, Ibaragi S, Kobayashi A, Tanimoto K, MakabeM, Itoh H, Matsubara K, Takekawa T (1984b) Effect ofblending on liquefaction of coals. Fuel; 63 (1); 78-83 (Jan1984)Painter P, Starsinic M, Riesser E, Rhoads C, Bartges B(1984) Concerning the calculation of coal structuralparameters from spectroscopic data. American ChemicalSociety, Division of Fuel Chemistry, Preprints; 29 (4); 29-35(Apr 1984)Painter P, Bartges B, Plasezynski D, Plasczynski T,Lichtus A, Coleman M (1986) Novel methods for FTIRanalysis of coal. American Chemical Society, Division ofFuel Chemistry, Preprints; 31 (1); 65-69 (Apr 1986)Parkash S, Lali K, Moluszko M, du Plessis M P (1984a)Contribution of vitrinite macerals to the liquefaction ofsubbituminous coals. Fuel Processing Technology; 9 (2);139-148 (Oct 1984)Parkash S, du Plessis M P, Cameron A R, Kalkreuth WD (1984b) Petrography of low rank coals with reference toliquefaction potential. International Journal of CoalGeology; 4 (3); 209-234 (Dec 1984)Parkash S, Lali K, Moluszko M, du Plessis M P (1985)Separation of macerals from subbituminous coals and theirresponse to liquefaction. Liquid Fuels Technology; 3 (3);345-375 (1985)Paulson C A J, Potter E C, Vale J S (1986) Correlation ofsome readily measured parameters of coal and fly ash withelectrostatic precipitator performance. In: Seventh worldclean air congress, Sydney, NSW, Australia, 25-29 Aug

1986. Eastwood, NSW, Australia, Clean Air Society ofAustralia and New Zealand, vol 3, pp 420-427 (1986)Pearson D E (1980) The quality of Western Canadiancoking coal. CM Bulletin; 73 (813); 70-84 (Jan 1980)Pearson D E (1985) The quality of Canadian coal - apetrographic approach to its characterization andclassification. In: Coal in Canada. Patching T H (ed)Montreal, Quebec, Canada, Canadian Institute of Mining andMetallurgy, pp 21-30 (1985)Pearson D E, Price J T (1985) Reactivity of inertinite(coal-typing) of Western Canadian coking coal. In:Proceedings, 1985 international conference on coal science,Sydney, NSW, Australia, 28-31 Oct 1985. Sydney, NSW,Australia, Pergamon Press, pp 907-908 (1985)Perch M (1981) Solid products of pyrolysis. In: Chemistryof coal utilization - second supplementary volume. Elliot MA (ed) New York, NY, USA, John Wiley and Sons, pp919-981 (1981)Perry G J, Allardice D J, Kiss L T (1982) Variation inVictorian brown coal characteristics and hydrogenationpotential. Fuel; 61 (10); 1058-1064 (Oct 1982)Perry G J, Allardice D J, Kiss L T (1983) Thecharacteristics of Victorian brown coal in relation tohydrogenation performance. In: Proceedings, 1983international conference on coal science, Pittsburgh, PA,USA, 15-19 Aug 1983. Pittsburgh, PA, USA, PittsburghEnergy Technology Center, pp 44-47 (1983)Perry G J, Allardice D J, Kiss L T (1984) The chemicalcharacteristics of Victorian brown coal. American ChemicalSociety Symposium Series; (264); 1-14 (1984)Pohl J H (1988) Volatile matter and flame stability. In: Aworkshop on steaming coal: testing and characterisation,Newcastle, NSW, Australia, 17-19 Nov 1987. Newcastle,NSW, Australia, University of Newcastle, Institute of CoalResearch, ppL5.1-L5.21 (1988)

Pohl J H, Chen S L, Heap M P, Pershing D W (1983)Correlation of NOx emissions with basic physical andchemical characteristics of coal. In: Proceedings of the 1982joint symposium on stationary combustion NOx control,Dallas, TX, USA, 1-4 Nov 1982. EPRI-CS-3182-vol.2,Palo Alto, CA, USA, Electric Power Research Institute,pp 36.1-36.30 (Jul 1983)Poos A (1987) Eighteenth carbonization science lecture:constitution and monitoring of coking coal blends. Yearbookof the Coke Oven Managers' Association; 223-254 (1987)Power (1987) Do we need highly detailed coal specs?Power (New York); 131 (10); 121-123 (Oct 1987)Price J T, Gransden J F, Silveston P L, Readyhough P J,Newman A, Ramachandran P (1985) Factors affecting therheology of Cretaceous coal. In: Proceedings, 1985international conference on coal science, Sydney, NSW,Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 969-972 (1985)Pugmire R J, Woolfenden W R, Mayne C L, Karas J,Grant D M (1983) Application of 2-D and dipolar dephasing' C nmr techniques to the study of structural variations in

coal macerals. In: Proceedings, 1983 internationalconference on coal science, Pittsburgh, PA, USA, 15-19 Aug1983. Pittsburgh, PA, USA, Pittsburgh Energy TechnologyCenter, pp 667-670 (1983)

Pullen J R (1981) Solvent extraction of coal. ICTIS/TR16,London, UK, IEA Coal Research, 124 pp (1981)

References

Raask E (1985) Mineral impurities in coal combustion -behavior, problems, and remedial measures. Washington,DC, USA, Hemisphere Publishing, 506 pp (1985)Read D C, Minchener A J (1984) The low temperaturecombustion characteristics of various coals in a fluidised bedcombustor. In: Fluidised combustion: is it achieving itspromise?, 3rd international fluidised conference, London,UK, 16-17 Oct 1984. London, UK, Institute of Energy,vol 1, DISC/26/224-DISC/26/231 (1984)

Redlich P, Jackson W R, Larkins F P (1985)Hydrogenation of brown coal. 9. Physical characterizationand liquefaction potential of Australian coals. Fuel; 64 (10);1383-1390 (Oct 1985)

Redlich P, Jackson W R, Larkins F P (1986) The effect ofchemical composition and structure of coal on its reactivityunder liquefaction conditions. In: Proceedings, secondAustralian coal science conference, Newcastle, NSW,Australia, 1-2 Dec 1986. Wahroonga, NSW, Australia,Australian Institute of Energy, vol 1, pp 346-356 (1986)Rees O W (1966) Chemistry, uses and limitations of coalanalyses. Report of Investigations, Illinois State GeologicalSurvey; (220); 55 pp (1966)Reid W T (1981) Coal ash - its effect on combustionsystems. In: Chemistry of coal utilization - secondsupplementary volume. Elliott M A (ed) New York, NY,USA, John Wiley and Sons, pp 1389-1445 (1981)Rentel K (1987) The combined maceral-microlithotypeanalysis for the characterization of reactive inertinities.International Journal of Coal Geology; 9; 77-86 (1987)Riepe W, Steller M (1984) Characterisation of coal and coalblends by automatic image analysis. Use of the Leitz textureanalysis system. Fuel; 63 (3); 313-317 (Mar 1984)Riepe W, Steller M (1985) Relationship between totalreflectance and behaviour of coal in conversion processes.In: Proceedings, 1985 international conference on coalscience, Sydney, NSW, Australia, 28-31 Oct 1985. Sydney,NSW, Australia, Pergamon Press, pp 681-683 (1985)Riepe W, Steller M (1987) Relationship between reflectancedistribution and hydrogenation behaviour of hard coals.Fuel; 66 (1); 83-85 (Jan 1987)

Riesser B, Starsinic M, Squires E, Davis A, Painter P C(1984) Determination of aromatic and aliphatic CH groups incoal by FT-ir. 2. Studies of coals and vitrinite concentrates.Fuel; 63 (9); 1253-1261 (Sep 1984)Roberts O C (1982) Coke strength prediction methodsapplied to Australian coals. ACIRL-PR-82-8, North Ryde,NSW, Australia, Australian Coal Industry ResearchLaboratories, 25 pp (Oct 1982)Ruhrkohlen Handbuch (1969) Ruhrkohlen-Handbuch:Anhaltszahlen, Erfahrungswerte und praktische Hinweise furindustrielle Verbraucher. Essen, FRG, Verlag GltickaufGmbH, 495 pp (1969) (In German)Sakurovs R, Lynch L J, Maker T P, Banerjee R N(1987a) Molecular mobility during pyrolysis of Australianbituminous coals. Energy and Fuels; 1 (2); 167-172 (1987)Sakurovs R, Lynch L J, Webster D S, Maher T P (1987b)Relationships between thermally-induced molecular mobilityand macroscopic fluidity of Australian bituminous coals. In:7987 international conference on coal science, Maastricht,the Netherlands, 26-30 Oct 1987. Amsterdam, theNetherlands, Elsevier Science Publishers, pp 625-628 (1987)Sakurovs R, Lynch L J, Webster D S, Maher T P,

Banerjee R N (1988) Fusibility of maceral groups inAustralian bituminous coals. Paper presented to the 3rdAustralian coal science conference, Adelaide, SA, Australia,16-18 May 1988.Sanyal A (1983) The role of coal macerals in combustion.Journal of the Institute of Energy; 56 (427); 92-95 (Jun 1983)Sanyal A, Cumming J W (1985) Steam coal quality. In:Coaltech '85, fifth international conference and exhibition oncoal utilization and trade, London, UK, 11-13 Dec 1985.Schiedam, the Netherlands, Industrial Presentations (Europe)BV, vol l,pp 121-152(1985)Sato Y (1982) Liquefaction of blended coal. Fuel; 61 (9);875-876 (Sep 1982)Schafer H N S (1979) Pyrolysis of brown coals. 1.Decomposition of acid groups in coals containing carboxylgroups in the acid and cation forms. Fuel; 58 (9); 667-672(Sep 1979)Schapiro N, Gray R J (1964) The use of coal petrographyin cokemaking. Journal of the Institute of Fuel; 37 (281);234-242 (Jun 1964)Schapiro N, Gray R J, Eusner G R (1961) Recentdevelopments in coal petrography. Proceedings - BlastFurnace, Coke Oven and Raw Materials Committee ofAIME; 20; 89-112(1961)Scholz A (1980) Correlation between the content of volatilematter and mineral matter in hard coals. Fuel; 59 (3);197-200 (Mar 1980)Schulten H -R, Simmleit N, Marzec A (1988) Liquefactionbehaviour of coals: a study by field ionization massspectrometry and pattern recognition. Fuel; 67 (5); 619-625(May 1988)Schwarz V (1986) Method for classifying coal consideringits combustibility. Energetika; 36 (7); 309-311 (Jul 1986) (InCzech)Selvig W A, Gibson F H (1945) Calorific value of coal. In:Chemistry of coal utilization. Lowry H H (ed) New York,NY, USA, John Wiley and Sons, vol 1, pp 132-144 (1945)Senftle J T, Kuehn D, Davis A, Brozoski B, Rhoads, C,Painter P C (1984) Characterization of vitrinite concentrates.3. Correlation of FT-ir measurements to thermoplastic andliquefaction behaviour. Fuel; 63 (2); 245-250 (Feb 1984)Seyler C A (1938) Petrology and the classification of coal.Proceedings of the South Wales Institute of Engineers; 53(4); 254-327 (Jan 1938)Shadle L J, Jones A D, Deno N C, Given P H (1986)Multifacetted study of a Cretaceous coal with algal affinities.3. Asphaltenes from liquefaction and a comparison withsome hydrogen-rich Texas coals. Fuel; 65 (5); 611-620(May 1986)Shibaoka M (1982) Characteristics of Australian coalresources. In: Coal science 1982, abstracts and papers.Symposium on characteristics of Australian coals and theirconsequences for utilization, North Ryde, NSW, Australia,18-22 May 1982. North Ryde, NSW, Australia, CSIRO,Division of Fossil Fuels, pp 1/1-1/4 (1982)Shibaoka M, Heng S (1984) Model for the coalhydrogenation process and its application. Fuel; 63 (2);174-177 (Feb 1984)Shibaoka M, Heng S, Okada K (1983) Microscopicinvestigation of hydrogenation behaviour of inertinite fromsome Australian coals. In: Proceedings, 1983 internationalconference on coal science, Pittsburgh, PA, USA, 15-19 Oct

References

1983. Pittsburgh, PA, USA, Pittsburgh Energy TechnologyCenter, pp 699-702 (1983)Shibaoka M, Wilson M A, Heng S (1984) Hydrogenation ofinertinite rich Australian coals. NERDDP/EG/84/322,Canberra, ACT, Australia, National Energy Research,Development and Demonstration Council, 71 pp (Jun 1984)Shibaoka M, Heng S, Okada K (1985a) Response ofinertinites from some Australian coals to non-catalytichydrogenation in tetralin. Fuel; 64 (5); 600-605 (May 1985)Shibaoka M, Thomas C G, Young B C, Oka N, MatsuokaH, Tamaru K, Murayama T (1985b) The influence of rankand maceral composition on combustion of pulverized coal.In: Proceedings, 1985 international conference on coalscience, Sydney, NSW, Australia, 28-31 Oct 1985. Sydney,NSW, Australia, Pergamon Press, pp 665-668 (1985)Shibaoka M, Thomas C G, Heng S, Mackay G H (1987)Significance of morphological features of macerals in coalutilization research. In: 1987 international conference oncoal science, Maastricht, the Netherlands, 26-30 Oct 1987.Amsterdam, the Netherlands, Elsevier Science Publishers, pp107-110(1987)Shin S -C, Baldwin R M, Miller R L (1987) Coal reactivityin direct hydrogenation liquefaction processes: measurementand correlation with coal properties. Energy and Fuels; 1(4); 377-380 (Jul/Aug 1987)Silver H F, Hallinan P J, Frazee, W S (1986) Effect ofwater on liquefaction reactivity of low rank coals. AmericanChemical Society, Division of Petroleum Chemistry,Preprints; 31 (3); 755-760 (1986)Simonis W, Gnuschke G, Beck K -G (1966) The influenceof coking capacity on the mechanical strength of coke.Gluckauf-Forschungshefte H; 27; 105-113 (Jun 1966) (InGerman)Singer J G (1981) Combustion - fossil power systems.Windsor, CT, USA, Combustion Engineering Inc, vp (1981)Sligar J (1988) Grindability of coal. In: A workshop onsteaming coal: testing and characterisation, Newcastle,NSW, Australia, 17-19 Nov 1987. Newcastle, NSW,Australia, University of Newcastle, Institute of CoalResearch, pp L4.1-L4.9 (1988)Smart J P, Weber R (1987) Advanced NOx reductiontechniques. In: 1987 international conference on coalscience, Maastricht, the Netherlands, 26-30 Oct 1987.Amsterdam, the Netherlands, Elsevier Science Publishers, pp861-864(1987)Smith G B (1985) Laboratory studies to support themarketing of Australian coals. In: Proceedings, Coalresearch conference, Wellington, New Zealand, 15-17 Oct1985. Wellington, New Zealand, Coal Research Associationof New Zealand, vol 2, Paper 34.2, 15 pp (1985)Smith I (1980) Nitrogen oxides from coal combustion -environmental effects. ICTIS/TR10, London, UK, IEA CoalResearch, 97 pp (Oct 1980)Smith I M (1987) Trace elements from coal combustion:emissions. IEACR/01, London, UK, IEA Coal Research, 87PP(1987)Smith S E, Neavel R C, Hippo E J, Miller R N (1981)DTGA combustion of coals in the Exxon coal library. Fuel;60 (6); 458-462 (Jun 1981)Smith W H, Roux H J, Steyn J G D (1983) Theclassification of coal macerals and their relation to certainchemical and physical parameters of coal. In: ICAM 81,

proceedings of the first international congress on appliedmineralogy, Johannesburg, South Africa, 1981. de Villieres JP R, Cawthorn P A (eds) South Africa, Geological Societyof South Africa, pp 111-115(1983)Snape C E (1987) Characterisation of organic structure forliquefaction. Fuel Processing Technology; 15; 257-279 (Jan1987)Snow D (1983) Physical and chemical characteristics of coal.In: Coal development: collected papers, Coal developmentworkshops, Grand Junction, CO, USA, 1982. Fisher S,Books D and others (eds) Billings, MT, USA, Montana StateOffice, Bureau of Land Management, vol 1, pp 159-200 (Jul1983)Snyder R W (1982) Development and application of Fouriertransform infrared spectroscopic techniques to thecharacterization of coal and oil shale. Ph.D. Thesis,University Microfilms Order no. 82-28938, University Park,PA, USA, Pennsylvania State University, 163 pp (1982)Snyman C P, van Vuuren M C J, Barnard J M (1985)The chemical and petrographical characteristics of SouthAfrican coals: a practical approach. In: Proceedings, 1985international conference on coal science, Sydney, NSW,Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 604-607 (1985)Sobrowiak M, Riesser E, Given P, Painter P (1984)Determination of aromatic and aliphatic CH groups in coalby FT-ir. 1. Studies of coal extracts. Fuel; 63 (9); 1245-1252(Sep 1984)Solomon P R (1981) Relation between coal aromatic carbonconcentration and proximate analysis fixed carbon. Fuel; 60(1); 3-6 (Jan 1981)Solomon P R, Hobbs R H, Hamblen D G, Chen W -Y, LaCara A, Graff R S (1981) Correlation of coal volatile yieldwith oxygen and aliphatic hydrogen. Fuel; 60 (4); 342-346(Apr 1981)Speight J G (1983) The chemistry and technology of coal.New York, NY, USA, Marcel Dekker, 540 pp (1983)Stach E (1982) The macerals of coal. In: Stach's textbook ofcoal petrology. Stach E, Mackowsky M T and others (eds)Berlin, FRG, Gebruder Borntraeger, pp 87-104 (1982)Standards Association of Australia (1977) Classificationsystem for Australian hard coals. AS 2096-1977, NorthSydney, NSW, Australia, Standards Association of Australia,6pp(1977)Standards Association of Australia (1987) Classificationand coding systems for Australian coals. AS 2096-1987,North Sydney, NSW, Australia, Standards Association ofAustralia, 8 pp (1987)Stankevich A S, Zolotukhin Yu A, Kalinina G I, AleshinV A, Chemerko V A (1981) Relationship between themechanical strength of coke, the chemical and petrographicparameters of Kuznets coal charges and their coking regimes.Coke and Chemistry USSR (English translation of Koks iKhimiya); (2); 15-22(1981)Steller M (1987a) Hydrogenation behaviour of coal maceralasssociation. International Journal of Coal Geology; 9(1) ;109-127 (Nov 1987)Steller M (1987b) The influence of maceral intergrowth onthe hydrogenation of coal. In: 1987 international conferenceon coal science, Maastricht, the Netherlands, 26-30 Oct1987. Amsterdam, the Netherlands, Elsevier SciencePublishers, pp 115-118 (1987)

References

Stephens J F, Leow H M, Gilbert T D, Philp R P (1985)Aqueous sodium dichromate oxidation of Australian vitriniteconcentrates. Fuel; 64 (11); 1531-1536 (Nov 1985)Straszheim W E, Greer R T, Markuszewski R (1983)Direct determination of organic sulphur in raw andchemically desulphurized coals. Fuel; 62 (9); 1070-1075(Sep 1983)Strobel B, Friedrich F (1981) Effects of some less obviousparameters in hydroliquefaction of coal. In: Proceedings,international conference on coal science, Diisseldorf, FRG,7-9 Sep 1981. Essen, FRG, Verlag Gluckauf, pp 556-561(1981)Strobel B O, Friedrich F (1985) Experiences fromcontinuous hydrogenation of various coals. In: Proceedings,1985 international conference on coal science, Sydney,NSW, Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 7-10 (1985)Strobel B, Friedrich F, Rolling G, Liphard K G, Romey I(1981) Coal hydrogenation at Bergbau-Forschung. Erdol undKohle, Erdgas, Petrochemie vereinigt mit Brennstojf-Chemie;34 (9); 391-396 (Sep 1981) (In German)Suess M, Kuenstner E, Schneider W and others (1986)Present state and problems of establishing internationalbrown coal classifications for technological uses. Zeitschriftfur Angewandte Geologic; 32 (2); 29-33 (Feb 1986)Sullivan K M (1986) Evaluation of coals for pulverised fuelfiring. In: Preprints, technical support for coal marketingseminar, Brisbane, Qld, Australia, 24 Nov 1986. NorthRyde, NSW, Australia, Australian Coal Industry ResearchLaboratories, 8 pp (1986)Sun Yilu, Liu Wenzhen (1985) Research on classification ofChinese coal for power generation. In: Proceedings, 1985international conference on coal science, Sydney, NSW,Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 379-382 (1985)Supaluknari S, Larkins F P, Redlich P, Jackson W R(1988) An FTIR study of Australian coals: a comparison ofstructural and hydroliquefaction data. Fuel ProcessingTechnology; 18 (2); 147-160 (Apr 1988)Tapia N (1987) Spanish experience firing wide range ofcoals in utility boilers. In: Coaltech 87 - Coaltrade 87, sixthinternational conference on coal technology and coaleconomics, London, UK, 9-11 Jun 1987. Schiedam, theNetherlands, Industrial Presentations (Europe) BV, pp199-218(1987)Taunton J W, Trachte K L, Williams R D (1981) Coalfeed flexibility in the Exxon Donor Solvent coal liquefactionprocess. Fuel; 60 (9); 788-794 (Sep 1981)Teichmiiller M (1982) Origin of the petrographicconstituents of coal. In: Stach's textbook of coal petrology.Stach E, Mackowsky M T and others (eds) Berlin, FRG,Gebriider Borntraeger, pp 219-294 (1982)Teichmuller M, Teichmiiller R (1982) The geological basisof coal formation. In: Stach's textbook of coal petrology.Stach E, Mackowsky M T and others (eds) Berlin, FRG,Gebruder Borntraeger, pp 5-86 (1982)Tomlinson G, Gray D, Neuworth M (1985) The impact ofrank-related coal properties on the response of coals tocontinuous direct liquefaction processes. In: Proceedings,1985 international conference on coal science, Sydney,NSW, Australia, 28-31 Oct 1985. Sydney, NSW, Australia,Pergamon Press, pp 3-6 (1985)

Trewhella M J, Grint A (1987) The role of sulphur in coalhydroliquefaction. Fuel; 66 (10); 1315-1320 (Oct 1987)Tromp P J J (1987) Coal pyrolysis: basic phenomenarelevant to conversion processes. Ph.D. Thesis, Amsterdam,the Netherlands, University of Amsterdam, 188 pp (1987)Tromp P J J, Karsten P J A, Jenkins R G, Moulijn J A(1986) The thermoplasticity of coal and the effect of K2CO3addition in relation to the reactivity of the char ingasification. Fuel; 65 (10); 1450-1456 (Oct 1986)Tromp P J J, Kapteijn F, Moulijn J A (1987a)Characterization of coal pyrolysis by means of differentialscanning calorimetry. 1. Quantitative heat effects in an inertatmosphere. Fuel Processing Technology; 15; 45-57 (Jan1987)

Tromp P J J, Kapteijn F, Boon J J, Moulijn J A (1987b)Low-temperature pre-oxidation of coals; the effects on thechar gasification reactivity. In: 1987 internationalconference on coal science, Maastricht, the Netherlands,26-30 Oct 1987. Amsterdam, the Netherlands, ElsevierScience Publishers, pp 537-541 (1987)Tsai C -Y, Scaroni A W (1987) Pyrolysis and combustionof bituminous coal fractions in an entrained-flow reactor.Energy and Fuels; 1 (3); 263-269 (May-Jun 1987)Tumuluri S G, Shrikhanda K Y (1985) Studies onclassifying Indian coals. 1. A new classification system.Fuel Science Technology; 4 (2); 57-60 (Apr 1985)Uribe C A, Perez F H (1985) Proposal for coalclassification. Fuel; 64 (2); 147-150 (Feb 1985)Valkovic V (1983) Trace elements in coal. Boca Raton, FL,USA, CRC Press, vol 1, 218 pp (1983)van Krevelen D W (1961) Coal. Typology - chemistry -physics - constitution. Amsterdam, the Netherlands, ElsevierPublishing, 532 pp (1961)

Verheyen T V, Perry G J, Osborn P R, Fredericks P M(1986) FTIR characterization of the significant properties ofVictorian brown coal. In: Proceedings, second Australiancoal science conference, Newcastle, NSW, Australia, 1 -2Dec 1986. Wahroonga, NSW, Australia, Australian Instituteof Energy, vol 1, pp 392-397 (1986)Verheyen T V, Heng S, Perry G J, Fredericks P M (1987)Rapid analysis of brown coal properties by statisticalcorrelation of their infrared spectra. In: 1987 internationalconference on coal science, Maastricht, the Netherlands,26-30 Oct 1987. Amsterdam, the Netherlands, ElsevierScience Publishers, pp 127-130 (1987)Vleeskens J M (1983a) Effect of coal properties on thefluidized bed combustion efficiency of single coals andblends. ECN-133, Petten, Netherlands, ECN-NetherlandsEnergy Research Foundation, 36 pp (May 1983)Vleeskens J M (1983b) Combustion efficiency andpetrographic properties. In: Proceedings, 1983 internationalconference on coal science, Pittsburgh, PA, USA, 15-19 Aug1983. Pittsburgh, PA, USA, Pittsburgh Energy TechnologyCenter, pp 599-602 (1983)

Vleeskens J M, Nandi B N (1986) Burnout of coals.Comparative bench-scale experiments on pulverized fuel andfluidized bed combustion. Fuel; 65 (6); 797-802 (Jun 1986)Vleeskens J M, van Haasteren T W M B, Roos M, GerritsJ (1988) Behaviour of different char components in fluidizedbed combustion: a char petrography study. Fuel; 67 (3);426-430 (Mar 1988)Voorhees K J, Durfee S L, Baldwin R M (1983)

References

Liquefaction reactivity correlations using pyrolysis/massspectrometry pattern recognition procedures. In: Polymercharacterization - spectroscopic, chromato-graphic andphysical instrumental methods. Craver C D (ed) Advancesin chemistry series 203, Washington, DC, USA, pp 677-691(1983)Vorres K S (ed) (1986) Mineral matter and ash in coal.American Chemical Society Symposium Series; (301); 1-537(1986)Wall T F (1985) Coal characterisation for combustion. In:Characterisation of steaming coals, Newcastle, NSW,Australia, 20-22 May 1985. Wibberley L (ed) Newcastle,NSW, Australia, University of Newcastle, Institute of CoalResearch, pp 1.1-1.19(1985)Wall T, Wibberley L, Stewart I M (1985) Thecharacterisation of steaming coals - limitations of thestandard laboratory and pilot scale tests. In:Characterisation of steaming coals, Newcastle, NSW,Australia, 20-22 May 1985. Wibberley L (ed) Newcastle,NSW, Australia, University of Newcastle, Institute of CoalResearch, pp 11.1-11.26(1985)Wang Y, Yang J, Chen P (1986) Study on technicalclassification of Chinese lignites, bituminous coals andanthracites. Energy (Oxford); 11 (7); 671-676 (Jul 1986)Ward C R (1984a) Introduction. In: Coal geology and coaltechnology. Ward C R (ed) Melbourne, Vic, Australia,Blackwell Scientific Publications, pp 1-39 (1984)Ward C R (1984b) Chemical analysis and classification ofcoal. In: Coal geology and coal technology. Ward C R (ed)Melbourne, Vic, Australia, Blackwell Scientific Publications,pp 40-73 (1984)Waters A (1986) The additive relationship of the Hardgrovegrindability index. Journal of Coal Quality; 5 (1); 33-34(Jan 1986)White A, Whittingham J (1983) Ultimate analysis of coalsand cokes using instrumental techniques. Fuel; 62 (9);1058-1061 (Sep 1983)White N (1979) Coal properties for conversion - a review.BHP Technical Bulletin; 23 (2); 70-78 (Nov 1979)Whitehurst D D (1980) A new outlook on coal liquefactionthough short-contact-time thermal reactions: factors leadingto high reactivity. In: Coal liquefaction fundamentals.Whitehurst D D (ed) ACS symposium series no. 139,Washington, DC, USA, American Chemical Society, pp133-164(1980)Whitehurst D D, Mitchell T O, Farcasiu M (1980) Coalliquefaction - the chemistry and technology of thermalprocesses. New York, NY, USA, Academic Press, 393 pp(1980)Wilkinson H C (1984) Correspondence between thecomposition and plastic properties of British coals and thestructural properties and reactivity of the correspondingcokes. Fuel; 63 (1); 101-108 (Jan 1984)Wilson M A, Pugmire R J, Karas J, Alemany L B,Woolfenden W R, Grant D M, Given P H (1984) Carbondistribution in coals and coal macerals by crosspolarization/magic angle spinning carbon-13 nuclearmagnetic resonance spectroscopy. Analytical Chemistry; 56(6); 933-943 (May 1984)

Winans R E, King H -H, McBeth R L, Botto R B (1983)Characterization of short contact time dissolution productsfrom a series of vitrinite-rich coals. American ChemicalSociety, Division of Fuel Chemistry, Preprints; 28 (5); 8-16(1983)Winans R E, Scott R G, Neill P H, Dyrkacz G R, HayatsuR (1986) Characterization and pyrolysis of separated coalmacerals. Fuel Processing Technology; 12; 77-88 (Mar 1986)Wolfrum E A (1984) Correlations between petrographicalproperties, chemical structure, and technological behavior ofRheinish brown coal. American Chemical SocietySymposium Series; (264); 15-37 (1984)World Coal Resources and Reserves Data Bank Service(1983) Concise guide to world coalfields. London, UK, IEACoal Research, vp (1983)Wright C H (1982) Coal rank effects in the SRC II Process.American Chemical Society, Division of Fuel Chemistry,Preprints; 27 (3/4); 43-52 (1982)Xu Xuchang, Mao Jianxiong, Zen Rudiang (1986) Thecoal characteristics used for power and heating system inChina and the new technology on coal combustion. In:Pacific Rim coal: consumption, production, trade andtechnology, Hong Kong, 12-14 Feb 1986. Arlington, VA,USA, Pasha Publications, 9 pp (1986)Yamada S, Matsuoka S (1986) The effect of coal rank andmacerals on the combustibility of pulverised coal. IdemitsuSekiyu Gijutsu; 29 (2); 199-204 (1986) (In Japanese)Yarzab R F, Given P H, Spackman W, Davis A (1980)Dependence of coal liquefaction behaviour on coalcharacteristics. 4. Cluster analyses for characteristics of 104coals. Fuel; 59 (2); 81-92 (Feb 1980)Yokono T, Marsh H (1983) Annmr study of hydrogentransfer reactions during carbonization of coals and pitches.In: Coal liquefaction products, volume J. Schultz H D (ed)New York, NY, USA, John Wiley and Sons, pp 125-138(1983)Yoshida T, Hasegawa Y, Maekawa Y (1984) Chemicalstructure and hydroliquefaction reactions of coal. In:Magnetic resonance - introduction, advanced topics andapplications to fossil energy. Petrakis L, Fraissard J P (eds)NATO ASI series C, volume 124, Dordrecht, theNetherlands, D Reidel Publishing, pp 677-688 (1984)Yoshida T, Tokuhashi K, Maekawa Y (1985) Liquefactionreaction of coal. 1. Depolymerization of coal by cleavagesof ether and methylene bridges. Fuel; 64 (7); 890-896 (Jul1985)Youtcheff J, Painter P, Given P (1986) FTIR spectroscopicstudies of coal liquefaction products. American ChemicalSociety, Division of Fuel Chemistry; Preprints; 31 (1);318-322 (Apr 1986)Zhou P, Dermer O C, Crynes B L (1984) Oxygen in coalsand coal-derived liquids. In: Coal science, volume 3.Gorbaty M L, Larsen J W, Wender I (eds) Orlando, FL,USA, Academic Press, pp 253-300 (1984)Zimmerman R E (1979) Evaluating and testing the cokingproperties of coal. San Francisco, CA, USA, Miller FreemanPublications, 144 pp (1979)

Related publications

Further IEA Coal Research publications on coal science are listed below:

Catalysts for fuels from syngas: new directions for researchG Alex Mills, IEACR/09, ISBN 92-9029-159-1, 62 pp, Aug 1988, £60

Catalysis in coal liquefaction: new directions for researchFrank J Derbyshire, IEACR/08, ISBN 92-9029-158-3, 69 pp, Jun 1988, £60

Understanding pulverised coal combustionG F Morrison, ICTIS/TR34, ISBN 92-9029-138-9, 46 pp, Dec 1986, £20

Nuclear magnetic resonance studies of coalR M Davidson, ICTIS/TR32, ISBN 92-9029-126-5, 108 pp, Jan 1986, £20

Catalytic coal gasificationJ R Pullen, ICTIS/TR26, ISBN 92-9029-105-2, 57 pp, Jun 1984, £20

Mineral effects in coal conversionR M Davidson, ICTIS/TR22, ISBN 92-9029-086-2, 100 pp, Jan 1983, £20

Solvent extraction of coalJ R Pullen, ICTIS/TR16, ISBN 92-9029-078-1, 124 pp, Nov 1981, £20

Methanation catalystsG H Watson, ICTIS/TR09, ISBN 92-9029-053-6, 56 pp, Feb 1980, £20

Molecular structure of coalR M Davidson, ICTIS/TR08, ISBN 92-9029-049-X, 86 pp, Jan 1980, £20

Other IEA Coal Research publicationsReviews, assessments and analyses of:

supply, mining and geosciencestransport and marketscoal utilisationenvironmentby-products and waste utilisation

Coal abstractsCoal calendarCoal research projectsCoal data base user aidsReference works on coal resources

Details of all IEA Coal Research publicationsare available from:IEA Coal ResearchPublications Department14-15 Lower Grosvenor PlaceLondon SW1W0EXUnited Kingdom

Tel: 01-828 4661Telex: 917624 NICEBA GFax: 01-828 9508