\ 

Anthracite and semianthracite 

low-volatile bituminous coal 

Medium-and high-volatile 

bituminous coal 

Subbituminous coal 

~ 

~ 

lignite 

SYMPOSIUM PROCEEDII'IGS: 

A National Agenda 

For Coal-Quality Research 

Symposium convened by the 

United States Geological Survey 

SYMPOSIUM PROCEEDINGS: 

A National Agenda For Coal-Quality 

Research April 9-11, 1985 

Edited by Susan Garbini and Stanley P. Schweinfurth 

U.S. GEOLOGICAL SURVEY CIRCULAR 979 

Symposium convened by the 

United States Geological Survey 

1986 
DEPARTMENT OF THE INTERIOR 

DONALD PAUL HODEL, Secretary 

U.S. GEOLOGICAL SURVEY 

Dallas L. Peck, Director 

Library of Congress Cataloging-in-Publication Data 

Symposium proceedings : a national agenda for coalquality research, April 9-11, 1985. 

(U.S. Geological Survey circular ; 979) 

"Symposium convened by the United States Geological 

Survey." 

Supt. of Docs. no.: I 19.4/2:979 

1. Coal--Congresses. I. Garbini, Susan. 

II. Schweinfurth, Stanley P. III. Geological Survey 

(U.S.) IV. Series. 

TP32S.S96 1986 662.6'22973 86-600093 

Any trade names in the publication are used for descriptive purposes only and 

do not constitute endorsement by the U.S. Geological Survey. 

Free on application to Distribution Branch, Text Products Section, 

U.S. Geological Survey, 604 South Pickett Street, Alexandria, VA 22304 
PUFACE 

On April 9 to 11, 1985, the U.S. Geological Survey, along 

with cosponsors, the Association of American State Geologists, tbe 

U.S. Department of Energy, the Electric Power Research Institute, 

and the U.S. Environmental Protection Agency, convened a symposium 

on coal quality at the headquarters of the U.S. Geological Survey 

in Reston, Virginia. 

The purpose of this symposium was to provide a forum for th£ 

exchange of information pertaining to coal-quality research and 

related activities. The goals for the meeting were to consider 

data analysis and research priorities and to recommend an agenda 

for research on coal quality to enable the Nation to take the 

fullest possible advantage of its vast inventory of coal resourc£~. 

The approach at the symposium was to discuss all aspects of 

coal-quality research from the characterization of coal in the 

ground to the coal-research needs of the struggling synfuels 

industry. The framework for these discussions consisted of a dar 

of overview talks, a day of workshops, and a half day of workshop 

reports. 

The cosponsors of the symposium were enlisted to provide th~ 

widest possible coverage and the best possible balance to the 

meeting. We wish to express our gratitude to them for their 

generous and enthusiastic support and most particularly to the 

members of the coordinating committee of the symposium for their 

help in planning the meeting and organizing the panels for the 

workshops. These are: Donald L. Koch, Association of American 

State Geologists (AASG), Paul C. Scott, U.S. Department of Energ:' 

(DOE), Jeremy Platt, Electric Power Research Institute (EPRI), 

George Rey, U.S. Environmental Protection Agency (EPA), and Jack A. 

Medlin, U.S. Geological Survey (USGS). In addition to these, many 

other individuals from the cosponsoring organizations participated 

directly in the symposium as speakers and panelists and an even 

larger number participated actively in the proceedings from the 

floor. We also wish to thank the many individuals from private 

operating and consulting firms who participated as speakers and 

panelists and as active audience. 

iii 

CONTENTS 

Preface •••••••••••••••••••••••••••••••••••••••••••••••••••••• iii 

Introduction ••••••••••••••••••••••••••••••••••••••••••••••••• 1 

PART I •. OVERVIEW 

Perspectives on U.S. Coal Industry Development 

Richard L. Gordon •••••••••••••••••••••••••••••••••• 5 

Barriers and Opportunities in the Application of 

Coal-Quality Geoscience 

Jeremy Platt ••••••••••••••••••••••••••••••••••••••• 39 

Coal Quality and Power-Plant Performance 

Michael P. Heap •••••••••••••••••••••••••••••••••••• 83 

The Why and How of Coal-Quality Research in the 

u.s. Department of Energy 

Richard E. Harrington •••••••••••••••••••••••••••••• 95 

Coal Quality as It Relates to Air Policy Analysis 

Paul Schwengels •••••••••••••••••••••••••••••••••••• 103 

Predicting Coal Product Quality and Its Effect on 

Marketability 

James Pinta, Jr. ••••••••••••••••••••••••••••••••••• 123 

A National Agenda for Geologically Related Coal Research 

Donald C. Haney •••••••••••••••••••••••••••••••••••• 155 

U.S. Geological Survey Coal-Quality Research 

Terry W. Offield, Susan Garbini, and 

Stanley P. Schweinfurth •••••••••••••••••••••••••• 165 

PART II. WORKSHOPS 

An Analysis of the Proceedings of the Symposium Workshops 

Stanley P. Schweinfurth •••••••••••••••••••••••••••• 187 

Recommendations presented by the workshop panels: 

Workshop I: Characterization of the Quality of Coal 

Resources and Reserves •••••••••••••••••••• 199 

Workshop II: Coal Utilization and Procurement ........... 201 

Workshop III: Coal Mining and Coal Cleaning 

(Beneficiation) ••••••••••••••••••••••••• 203 

v 
Uorkshop IV: Environmental Issues and the Role of 

Coal-Quality Research •••••••••••••••••••• 206 

Workshop V: Advanced Technologies for Coal 

Utilization •••••••••••••••••••••••••••••• 207 

PART III: POSTER SESSIONS 

Abstracts •••••••••••••••••••••••••••••••••••••••••••••••••• 211 

PART IV: SUPPLEMENTARY PAPERS 

Some Thoughts on Future Needs for the Characterization 

of Coal Resources 

Alan Davis ••••••••••••••••••••••••••••••••••••••••• 267 

Problems with Estimating Coal-Quality Characteristics 

of Tonnage Reserves 

John c. Ferm ••••••••••••••••••••••••••••••••••••••• 273 

Effects of Coal Quality on Production Cost --

A Utility's Perspective 

Rick A. Mancini •••••••••••••••••••••••••••••••••••• 279 

Coal Reserve Characterization for Emission Control 

Francis Martino and Susan L. Latimer ••••••••••••••• 285 

Comments on Characterization of the Quality of Coal 

Resources and Reserves 

David Mathew ••••••••••••••••••••••••••••••••••••••• 299 

Prepared Statement for Panel I: Characterization of the 

Quality of Coal Resources and Reserves 

H. L. Retcofsky •••••••••••••••••••••••••••••••••••• 305 

PART V. PARTICIPANTS 

Overview Speakers •••••••••••••••••••••••••••••••••••••••••• 315 

Panelists and Recorders .................................... 316 

List of Attendees •••••••••••••••••••••••••••••••••••••••••• 321 

vi 
INTRODUCTION 

The U.S. Geological Survey (USGS) has been doing research on 

coal quality for almost a century (Averitt and Lopez, 1972). Most 

of the work of the USGS regarding coal went into efforts to assess 

the quantity of coal in the United States, not the quality. 

Proximate and ultimate analyses were published with the resource 

numbers, but only a limited amount of research went into understanding the origin of coal, the chemistry of coal, or whether it 

might be possible to predict coal quality downdip and away from 

existing information. Because of the complexities of modern 

industrial society, the USGS and cosponsors have become increasingly 

aware of a growing need to understand coal from the standpoint of 

quality as well as quantity. Consequently, we have been expanding 

our research in coal quality over the past 10 years and are 

planning further increases. The perception that greater attention 

needs to be given to coal quality led to the convening of a 

symposium on this topic in April 1985. 

The opportunity to discuss coal-quality research in a 

holistic sense apparently struck a responsive chord in the coal 

community. The workshop panels were quickly oversubscribed, s~d 

the participants--approximately 250--came from all corners of the 

coal community and even included staff members of congressionc-1 

committees. Judging from the extent to which the objectives e-nd 

goals of the symposium were achieved, we may consider it a success. 

SYMPOSIUM FORMAT 

The first day of the meeting consisted of a keynote speech 

and overview talks on the needs and applications of coal-qualfty 

research from the perspectives of the cosponsors and coal-min1.ng 

and coal-utilization industries. 

On the second day of the symposium, five workshops met 

concurrently. Each of the five workshops was given a separate 

topic area to discuss with the understanding that there would 

probably be some overlap among the five topics. Each workshop was 

led by a panel of experts on the topic consisting of two coleaders 

and five or six working members. The structure of the workshop 

included active audience participation. Each workshop was to 

address its topic from the point of view of current research on 

coal quality within the topic area and recommendations for 

research and related activities that need to be done. 

Workshop topics were as follows: 

1 
I - Characterization of the quality of coal resources and 

reserves. 

II - Coal utilization and procurement 

III - Coal mining and coal cleaning 

IV - Environmental issues 

V - Advanced technologies for coal utilization 

On the final half-day, reports were presented on individual 

workshop proceedings and their recommendations for coal-quality 

research agendas and related activities. 

The following Proceedings present the written versions of the 

keynote and overview speakers, together with summaries and lists 

of workshop discussions and recommendations. Appendices include 

additional information relevant to the meeting. 

REFERENCE 

Averitt, Paul, and Lopez, Lorreda, 1972, Bibliography and ind~x of 

U.S. Geological Survey publications relating to coal, 18r2-

1970: U.S. Geological Survey Bulletin 1377, 73 p. 

2 
PART I. OVERVIEW 

PERSPECTIVES ON U.S. COAL INDUSTRY DEVELOPMENT 

by 

Richard L. Gordon 

The Pennsylvania State University 

Discussion of coal is habitually marred by rhetorical 

excesses. The usual inability to maintain a proper perspectivn on 

complex issues is at least as prevalent in coal discussions as in 

other policy debates. Attitudes about coal have fluctuated widely 

in the past decade. We started with suggestions that explosive 

growth would occur. When growth proved merely steady and regionally disparate, disappointment set in. Today, it appears that the 

proper view of coal has become better recognized. 

Typically, viewers have deplored the present but envision a 

glowing future. Concerns rarely arise about how, other than by a 

miracle, the situation will change so abruptly. The realistic 

view rejects both these attitudes. The present is much better 

than industry grumblings and press stories would suggest. In 

particular, the prevailing situation includes the basis for sustaining industry growth. The result will be a future less bright 

than enthusiasts hoped for. However, this will occur because the 

dreams were based on defective logic. No golden opportunities 

will have been missed. 

This discussion begins with a survey of coal-market conditions. I next turn to questions of the critical regulatory 

influences on the situation. Then, I treat the role of scientific 

and technical developments, such as are being considered at this 

conference, in affecting the coal industry. 

Coal Resources Versus Coal Economics 

In dealing with coal, a critical problem is avoiding being 

overly impressed by the ample amounts of known coal resources. 

Writers on coal insist on proclaiming that it is the most abundant 

fuel. Such statements are irrelevancies. For many reasons, the 

comparative known or estimated physical endowments of fuels are 

not useful indicators of prospects. The basic problem is the 

ultimate translation of minerals in the ground into reserves end 

this is an economic, not a technical, process. Neglect of th1s 

point has led many, including even some distinguished economists, 

into serious error. 

5 
The practical concern is the economi.c availability of different fuels over our planning horizon. One particularly obvious 

objection to considering only physical endowments is that it will 

take many decades before we can consume all the oil, gas, coal, 

and uranium that is known to exist. It would be infeasible and 

unwise to devote significant efforts now to meet pP.Oblems that 

might arise several generations from now. We need the time to 

learn more about what will really happen. 

The relevant consideration is the optimum pattern of fuel nse 

in the next decade or two. Experience has shown that perceived 

relative physical endowment is, for good reason, a poor criterion 

for choice. At the very least, the perceptions could be very 

wrong. More critically, the radical differences in the economics 

of using different fuels must be considered when appraising 

immediate prospects. The economically sensible route is the one 

we have been and will be taking of stressing oil and gas use first. 

The costs of forcing increased saving of oil and gas for future 

use prove to far exceed the benefits. 

Electricity-Based Growth 

Because of these economic forces, the health of the coal 

industry in the United States and elsewhere has increasingly 

centered on the economic attractiveness of coal as an electricutility fuel. Electric utilities have been the only growing 

market for coal (fig. 1). In most major countries belonging to 

the Organization for Economic Cooperation and Development (OECD), 

most coal consumption has been by electric utilities (figs. 2 and 

3). The U.S. coal industry demonstrates a particularly high level 

of dependence on the electric-utility market--85 percent of 

domestic tonnage coal use in 1983 (fig. 4 for the United States 

and figs. 5-10 for other countries). On a Btu basis, the share 

was 83 percent; preliminary 1984 Btu figures set the share at 82 

percent. 

This U.S. growth has actually outpaced expectations of the 

middle 1970's for U.S. electric-utility coal use. In 1985, we 

should use about 700 million short tons or 15 quadrillion Btu of 

coal for electricity generation. In contrast, seven of the eight 

1974 Project Independence scenarios called for much lower 1985 

consumption in that market. The eight projections range from 417 

to 769 million short tons. Four cases were between 417 and 492 

million; two at 620 and 630 million; another at 664 million. In 

Btu, the range was 9 to 16 quadrillion. 

Overestimates of electricity output growth were more than 

compensated for by failure of nuclear power to develop as strongly 

as expected. The 1985 Energy Information Administration (EIA) 

forecasts for electric power in 1985 project 4 quadrillion Btu of 

nuclear power out of total electric-utility fuel use of 27 

6 
,.. ..... 

aetdc 

tea8 

-....! 

500000 

450000 

400000 

350000 

300000 

250000 

200000 l USA 

150000 ~ .. -·-

1000 00 ... 

50000 

0 

1 1 1 1 1 

9 9 9 9 9 

5 5 5 5 5 

0 2 4 6 8 

OBCDB.,. .. e .. ·· ... , . 

_,.·· -·--..... ···----- -----·- "· .-· . ·-·---" .. .. , 

1 1 I 1 

9 9 9 9 

6 6 6 6 

0 2 4 6 

Yeu 

1 1 

9 9 

6 7 

8 0 

1 

9 

7 

2 

1 1 I 

9 9 9 

7 7 7 

4 6 8 

Figure 1. Electric-Utility Coal Consumption. 

... ·· . -- .. 

1 1 

9 9 

8 8 

0 2 
000000 

I ih 1 I I 

lffil Nonindustrial 

500000 ~ I m Other industry 

.00000 .. I. Coking 

00 1'llouM..a I 1 • Electricity generation 

IIIW'tC tiM 300000 

£& • £& 

200000 

100000 

0 

USA OECOE.._ ..... Aultl'alll 

Figure 2. Coal Use by Sector, 1982. 
\0 

120000 

100000 

n..... eoooo 

••vic 

tea• 

60000 

40000 

20000 

0 

Britain Germany France 

Iilli Nonindustrial 

II Coking 

II Other industry 

• Electricity generation 

Italy 

Figure 3. Coal Use in OECD Europe, 1982. 
...... 

0 

9'1 

1'1 

Figure 4. U.S. Coal Consumption,1983. 

• Electricity genratfon 

• Coking 

1111 Other Industry 

(liT) Nonindustrial 
1-' 

1-' 

2971 

6X 

58" 

Figure 5. OECD Europe Coal Consumption,1982. · 

• Electricity generatlan 

B Coke pl1nts . 

B Energy Industries 

[iJ Gasworks 

0 Other Industry 

~ Nonlndustry 

m Transportation 
9'1 

12'1 

• Electricity generalton 

Ill Coking 

t; 111 Other industry 

Iilli] Nonlndustry 

Figure 6. UK Coal Consumption,l982. 
61 271 

• Electricity Generation 

• Coking 

~': :.i :. ::~ ~:: t lJfU: j:l·l~l :: :~: ll( 1-' 521 I 0!1 other Industry w 391 [Til Nonindustrial 

Figure 7. German Coal Consumption,l982. 
f-." 

..,.. 

3UC 

51 

551 

• Electricity generation 

Ill Coking 

II Other industry 

(iili) Nonindustrial 

Figure 8. French Coal Consumption,l982. 
1-' 

lJ1 

Ul 

Figure 9. 

36JC 

• Electricity generation 

Ill Coktng 

II Other industry 

liilil Nontndustrta1 

Italian Coal Consumption,1982. 
,_... 

0\ 

111 

HI 

671 

Figure 10. Japanese Coal Consumption,1982. 

• Electricity generalton 

II Coking 

0 Energy industries 

lililJ Gasworks 

0 Other industry 

~ Nonindustrial 
quadrillion. Project Independence projected at least 12.5 

quadrillion Btu of nuclear power out of a 36-41 quadrillion total. 

(Subsequent forecasts, however, were better about 1985 prospects 

in this market.) 

The current prognosis for growth from EIA and Data Resources 

tends to call for consumption of around 800 million tons in 19~~, 

900 to a billion by 1995, and 1.1 to 1.2 billion by the year 2000. 

Energy Ventures' Coalcast service set 1995 levels 100 million tons 

below Data Resources which, in turn, has a forecast at the low end 

of the EIA range. This is a scaling back. The Department of 

Energy (DOE) published its first estimates of 1995 coal use in 

1979 (in its annual report covering 1978). It set a range of 1.2 

to 1.5 billion tons (Table 1). 

Similarly, in western Europe, coal use for electricity 

generation has been rising for more than three decades, and growth 

was greater in the 1970's than in the 1960's. This growth should 

continue. However, because of strong commitments to nuclear 

power, a severe limit exists to further growth of coal consumption 

in western Europe and Japan. Tables 2 and 3 summarize various 

coal forecasts for 1990 and 2000. 

As several different regional groupings are used for western 

Europe, data comparison is more complex than in the case of Japan. 

Japanese forecasts have been scaled back markedly. Reduced expectations about steel industry needs have been a major influence. 

Projections for 1990 coal use in electricity generation have b~en 

fairly stable, but this is not the case for the year 2000. 

The main distinction in western Europe is between the full 

region and the group of leading countries belonging to the 

European Communities. (The definition of the full region used by 

the United Nations includes Yugoslavia, which is not a member of 

the OECD, a major source of energy studies. The OECD operates an 

International Energy Agency [lEA] which France, Iceland, and 

Finland refused to join.) Again, in forecasts of Europe, sca1edback expectations are evident. Coking use is expected to dec1ine. 

In the European Economic Community (EEC), electric power coal use 

might easily have little or no increase by the year 2000. Nor-EEC 

countries, such as Spain, Portugal, Turkey, and Sweden, might 

increase coal use more. 

The expansion in electric-utility coal use has sufficed to 

permit an increase in total U.S. consumption of coal. In 

contrast, total coal use in western Europe was declining thro\•gh 

the late 1970's. By 1982, consumption was still well below 

post-World War II peaks. Japanese consumption, in which cokirg 

coal dominates, had a more complex pattern growth in the fift1.es 

and sixties, something of a downturn in the seventies, and a 

recovery in the early eighties. 

17 
Source 

OOE1979A-HS/tl) 

DOE 19798-LSIHD 

DOE 1979C-t1S/MD$23.5001L 

DOE 19790-HS-LD 

DOE 1979E--LSJLD 

DOE 1979CLow-t1SII1D$16.SOOIL 

I 979CHigh t1SIMD$31.5001L 

DOE 1 979~*f1Siti0$23.SOOIL 

DOE I 979C*Nut1Moratortltm 

DOE 1 979C H1 gh CeptteiCost 

DOE 1980LOW 

DOE 1980Med1um 

DOE 1 980 High 

DOE 1981Low 

DOE 1981 MediUm 

DOE 1981Htgh 

DOE 1982 $49 011 

DOE 1982$67011 

DOE 1982$88011 

DO£ 1 98411ecnum on Pr1ce 

DOE. I 984LOW 011 Price 

DOE 1 984Htgh 011 Pr1ce 

DOE I 985A Mecllwn 011 

DOE 19858 Low GNP Growth 

DOE 198SC HtgftGNPGrowth 

·-OOE 19850low World011 

DOE 198SEH1gft World011 

DRI 11ey 1 979 

ORI June 1980 

ORI W1nter82/83 

DRI summer 1984 

DR I Winter 1 9&.4/85 

toelcost 1985 

S.lectedFoncHte of 199SU.S. CoeiTonnegM * 

f11111onlh0rt tons 

Production Exports Electr1c1ty Coking Other Synthetics Tote1Use 

2.113.9 134.0 1.509.5 98.9 292.0 n.4 1.960.3 

2,.119.5 134.0 1.301.1 97.8 331.8 250.3 1.943.7 

1.999.0 89.0 1.375.7 95.6 306.7 128.2 1.876.8 

1,.699.2 89.0 1,.226.9 93.5 241.0 45.2 1,.595.2 

1.871.1 69.0 1.231.2 92.7 304.5 149.5 1.741.8 

... 771.0 89.0 1.271.8 96.3 258.1 52.0 1,.649.6 

2.055.9 89.0 1.370.1 94.7 304.8 193.5 1.935.8 

1.986.0 89.0 1.377.8 95.6 291.4 128.3 1,~~863.5 

2.122.8 89.0 1.502.4 95.6 297.9 136.9 2.006.1 

1 ... 822.8 89.0 1 ~6.3 95.6 304.6 123.4 1 ... 706.3 

1.592.0 143.0 1.055.0 80.0 268.0 50.0 1.452.0 1,~~71 s.o 143.0 1,11 s.o 79.0 280.0 10 1.0 1,~~575.0 

'· 718.0 143.0 1.136.0 79.0 258.0 105.0 1.577.0 

1 ... 847.0 143.0 1jl160.0 77.0 257.0 208.0 1,~~702.0 

1.878.0 143.0 1.167.0 75.0 249.0 266.0 1.757.0 

1 ... 895.0 143.0 1 .. 160.0 74.0 235.0 298.0 1.767.0 

l,e5.9 171.0 1.037.3 85.0 168.6 24.0 1.314.5 1,~~568.5 171.0 1 jl034.5 82.7 I 92.3 88.0 1,~~397.5 

1 .. 615.5 171.0 I ,0 19.1 79.6 205.3 140.5 1,444.5 

1.-191.0 116.0 916.0 52.0 93.0 7.0 1.061.0 

1.205.0 I 16.0 924.0 54.0 97.0 6.0 1.076.0 

1 .. 174.0 116.0 905.0 50.0 89.0 6.0 1jl044.0 

1.221.0 1 06.0 951.0 49.0 1 05.0 6.0 1.110.0 

1 .. 172.0 1 06.0 909.0 47.0 98.0 6.0 1 .. 060.0 

1 .. 259.0 106.0 982.0 51.0 109.0 6.0 1.140 

1..234.0 106.0 961.0 49.0 107.0 6.0 1 .. 122.0 

1.202.0 1 06.0 936.0 49.0 I 0 1.0 6.0 1.09 I .0 

1,~~558.5 88.6 1.1 46.9 I 09.0 191.5 22.5 1,11169.9 

1.575.0 121.7 1.065.1 96.1 177.7 121.0 1.453.3 

1,389.9 192.8 959.7 64.3 136.5 28.0 ..... 88.4 

1..284.2 133.4 969.8 53.6 110.9 0.4 1,134.7 

1.164.4 85.41 908.2 52.6 1 11.1 0.3 1,.071.8 

1.030.0 65.0 819.0 56.0 90.0 965.0 

Notes: DOE rromrepons1nueca1n yeenl1steca--rrom 1979to 1982. the Annuol 

Report to Congren;subeequently the Annuel Energy Outlook 

Dote Resources from 11sted 11sues or Its coat R8Y1ew 

Coelcest: oral communtcet1on 

* See Sources and Notes on the Tables 

18 
Tablt2 

S.llctN Forecasts of~l Conunption .and Output W. Dffferent R.pns m 1990 * 

Mi1Hon Coal Equvalent Tons 

Total Ntt Total Sttn Colmg Sttn Colmg Otbtr 

CoclrtnJ OUtput Import ~ OUtput OUtput Imports Import! E1fctr1c Nucltar Colmg Sttn 

FortoaSts of EEC 

EA Sttn Coi178 274.0 114.1 388.1 195.2 78.8 93.8 20.3 232.8 192.6 99.1 56.2 

UNECE 1983 285.9 133.7 419.6 "'" HIA "'" .,.,,. 

EA CQl ftformation 248.7 101.6 350.7 183.8 &S.O 73.5 28.1 "'" 212.6 1SS.S "'" "'" 93.1 "'" 45.0 

EEC 1984 ~.8 81.7 336.8 N/A N/A N/A N/A 206.6 196.4 N/A N/A 

E£C 198S 250.0 95.7 b45.7 "'" HIA "'" N/A 228.6 207.1 N/A 

s-wro 1985 190.0 91.0 281.0 N/A N/A ·N/A N/A 171.0 214.0 62.0 "'"' 48.0 

Fonoasts of OECD Ecropt 

EAStNmCoa178 332.2 132.9 48S.1 246.5 85.7 111.9 41.0 270.6 241.5 126.7 87.8 

EA 1982 'w'orld Enlrgv 360.0 189.0 549.0 "'" "'" "'" "'"' 297.0 294.3 119.0 1!3.0 

lltECE 1983 399.3 193.2 592.5 N/A N/A N/A N/A N/A N/A "'" N/A 

EA Coallnformatton 334.7 1~.6 470.4 2642 70.4 94.1 41 !5 261.0 230.8 111.9 97!5 

Calarco 1985 499.6 133.6 633.2 4~.9 45.7 95.5 §.1 468.8 0.0 83.9 80.2 

Forteasts of Japan 

EA Swn Coa178 19.0 123.0 142.0 8.9 10.1 33.1 89.9 32.1 ~.1 100.0 9.9 

'w'orld Coa1 Cu. A 18.0 101.0 119.0 11.0 7.0 24.0 77.0 10.0 92.0 84.0 5.0 

Yorld Coal CaM 8 18.0 112.0 137.0 11.0 7.0 33.0 79.0 37.0 98.0 86.0 14.0 

EA 81 Coal Polic9 18.9 140.9 159.7 12.3 6.6 S6.6 84.3 50.6 128.6 90.9 68.9 

EA 1982 Yorld EnlrCJIJ 18.0 139.0 157.0 'N/A N/A N/A N/A 37.0 0.0 101.0 19.0 

EAPoltcV 83 ,,,7 88.6 102.9 10.0 ,,7 HIA N/A 38.6 N/A 77.1 -11.4 

EA Cot11nformation 15.0 88.0 10J.O 10.0 5.0 22.0 66.0 §.7 66.6 71.0 -6.7 

Cararco 1985 18.4 89.9 108.3 15.3 2.9 ~.9 64.0 27.8 HIA 66,9 13.6 

Fortcasts of North Amtr1ci 

EA St.am Coal 78 1,()6i.J -88.0 97S.3 sn.1 179.6 -10.0 -78.0 776.7 J26.7 101.6 97.0 

,_.orld Coal ea. A 850.0 -82.0 768.0 692.0 158.0 -25.0 -57.0 570.0 307.0 101.0 97.0 

'w'orld Coal C.. 8 11152.0 -125.0 1 JJ27 .0 986.0 166.0 -60.0 -65.0 788.0 373.0 101.0 138.0 

EA 81 Cut Po~Dj 987.0 -127.7 859.3 814.3 149.9 -54.7 -73.0 597.6 281.6 7,.9 766.7 

tit ECE 1983 986.9 -127.7 ~92 N/A N/A N/A N/A N/A N/A N/A N/A 

EA1982 ,_.orld Entr9J 987.0 -127.0 860.0 N/A N/A HIA "'"' S97.0 251.4 71.0 186.0 

lEA 83 Coal Polbj 992.9 -132.9 861.4 84S.7 147.1 "'"' N/A 618.6 N/A 67.1 174.3 

EA CoallnfonMtton m.3 -132.4 860.9 846.7 146.6 -~.4 -79.0 618.6 270.0 67.6 174.7 

Calaroo 1985 967.4 -89.8 m.6 856.4 111.0 -21.4 -68.4 747.8 0.0 4~.6 83.7 

Fortcasts of MlstraHa 

lEA Steam Coa118 150.9 -90.0 60.9 83.2 67.7 -36.0 -54.0 44.0 5.0 17.7 3.2 

'World Coal Case A 1".0 -H~.O ,.,2 11:5.0 80.0 -37.0 -68.0 642 0.0 122 13.8 

'iorldCoal CaH B 195.0 -105.0 90.2 115.0 eo.o -~.0 -68.0 64.2 0.0 12.2 1J.8 

EA 81 Coal Polbj 188.0 -111.6 76.3 112.3 72.1 -55.3 -56.3 52.4 0.0 15.9 56.9 

lit ECE 1983 205.0 110.0 95.0 HIA N/A HIA HIA N/A -N/A N/A N/A 

EA1982 'World Entr9J 188.0 -112.0 76.0 HIA N/A lt/A N/A 53.0 0.0 16.0 7.0 

lEA 83 Coal PoJicq 148.6 -85.7 62.9 92.9 57.1 N/A HIA 44.3 N/A 14.3 7.1 

lEA Coal klfonnation 149.1 -86.0 63.1 92.0 57.1 -42.8 -43.2 43.7 0.0 13.9 5.5 

~brco 1985 190.3 -88.1 102.2 132.6 'S7.7 -38.2 -49.9 82.3 0.0 7.8 12.1 

* See Sources and Notes on the Tables N/A ~ Not Available 

19 
Tablt 3 

S.llcted Foreoasts o1 Coal CORSinption .t Output ;n Dtfftnnt Regions In 2000 * 

Million Coal Equivalent Tons 

Total Ntt Us. Sttam Comg Sttam Comg Othtr 

eotmtrv Output Import Total Output Output Imports Imports E1tctr1c Nuoltar Coki'; Sttam 

FortcaSts o1 E£C 

lEA Sttam Coal 78 292.4 248.9 541.3 211.7 80.7 219.3 29.6 35:5.8 413.0 11~.,3 7S.2 

UNECE83 302.1 207.3 ~.3 Hilt Hilt Hilt Hilt Hilt Hilt Hilt Hilt 

EA Co~l Information 248.3 162.3 410.7 184.0 64.3 136.7 25.6 252.2 278.3 89.9 68.6 

EEC 1m 2~.7 131.4 377.1 HIA N/A N/A HIA Z54.3 307.1 NIA NIA 

Saarberg 1985 175.0 1~.0 312.0 Hilt 'HI A HIA HIA 198.0 314.0 53.0 61.0 

FortcaSts o1 OECD EtrG~» 

lEA St•.n CN1 78 i64.0 310.7 674.7 276.J 87.7 254.2 56.5 419.0 529.5 144.2 111.5 

'&'orld Coal Cas. A 373.0 179.3 555.5 296.0 79.0 143.8 36.7 313.2 N/A 115.7 125.7 

'Yorld Co.al Cu. B 426.6 386.3 812.9 343.0 83.6 332.5 53.8 431.4 HIA 136.8 243.8 

lEA S2 Yorld EMrw 379.0 410.0 789.0 0.0 0.0 0.0 0.0 450.0 422.9 147.0 192.0 

UNECE83 40'9.6 281.9 691!5 N/A N/A N/A N/A N/A N/A N/A N/A 

lA Coal Information 354.0 222.2 574.8 284.0 70.0 178.1 44.0 m.9 m.1 114.0 126.9 

Calarco 1985 506.7 166.1 672.8 469.8 36.9 128.8 37.3 509.6 N/A 74.2 88.6 

F orteaSts o1 Japan 

lEA St..n ~~ 78 19.0 180.9 199.9 9.3 9.7 76.5 104.4 7S.7 147.1 114.1 10.1 

'w'or1d Coal Cas. A 18.0 158.0 224.0 11.0 7.0 73.0 ss.o 72.0 199.0 92.0 60.0 

'w'orld Coal Cas. B 18.0 132.0 150.0 11.0 7.0 53.0 ~JJ S7.0 188.0 86.0 7.0 

lEA Co~J Policy 83 15.7 140.0 155.7 10.0 5.7 N/A N/A 67.1 HIA 84.3 4.3 

lEA Coal Information 1~.9 140.0 1~.9 10.6 ~.3 70.0 70.0 67.6 129.6 ~.3 13.0 

C.arco 1985 17.6 111.3 128.8 16.0 1.6 49.7 61.6 51.0 N/A 63.1 14.7 

Foncasts of North Nntr1ca 

lEA Stt.n ~178 1~.0 -143.0 1,109.0 1,056.8 19S.2 -50.0 -93.0 845.0 632.8 102.2 161.8 

Vorld CoaJ Cast A 1,281.0 -124.0 1,157.0 1,098.0 183.0 -56.0 -68.0 850.0 345.0 115.0 192.0 

'w'orld CNl CaM B 2,042.0 -221.0 1,821 JJ 1,839.0 203.0 -143.0 -78.0 1,235.0 688.0 125.0 461.0 

I.JIJ EC£ 83 1,463.7 -211.4 1,254.3 N/A N/A N/A N/A N/A N/A HIA N/A 

lEA 82 'l'orld Energy 1 ,693.0 -296.0 1,397.0 N/A N/A N/A HIA 1,036.0 ~.7 96.0 26:5.0 

lEA 83 Coal Policy 1P1.4 -225.7 1,145.7 1,198.6 172.9 Hilt Hilt 838.6 Hilt 75.7 231.4 

lEA Coa1 Information 1,372.0 -225.7 1,146.3 1 ,198.7 173.3 -128.2 -97.6 837.9 377.0 75.7 232.7 

~Jarco 1~ 1;1:23.7 -110.1 1,113.7 1,11~.6 108.1 -37.9 -72.2 977.1 N/A !6.0 97.0 

Forecasts of Australia 

EA St•n CNJ 78 28S.1 -19SJJ 90.1 192.8 92.3 -120.0 -7S.O 69.7 10.0 17I !.1 

'Yorld ~1 Cas. A 18.0 132.0 150.0 t 1.0 7.0 53.0 79.0 57.0 188.0 86.0 7.0 

~orld Coal cast B 326.0 -160.0 1~.4 224.0. 102.0 -~.0 -~.0 107.3 0.0 16.f 41.3 

UNECE SJ 300.0 -160.0 140.0 0.0 0.0 0.0 0.0 0.0 0.0 0.(' 0.0 

lEA 83 Coal Po1icv 242.9 -154.3 88.6 171.4 71.4 'N/A N/A 67.1 N/A 21A 2.9 

EA Coal Information 242.9 -1~!5 88.4 171.4 71.4 -104!5 ~.0 66!5 0.0 21A 0.~ 

Calarco 1985 239.3 -101.4 137.9 178.9 60.4 -49.0 -52.4 114.5 N/A 8.C 15.3 

* See Sources and Notes on the Tables N/A = Not available 

20 
Malaise about coal, then, is discontent with this situation. 

The coal industry naturally would like more markets and a better 

situation in the markets it serves. Here in the United States, 

the primary concerns about extant markets relate to the slower 

growth of electricity generation and the resistance of regulators 

to allow creation of new capacity. Regions producing high-sulfur 

coal (particularly the Illinois basin and Ohio) are worried abo•.tt 

present and proposed regulations limiting sulfur emissions. Th~se 

parts of the coal industry, such as Pennsylvania and parts of w~st 

Virginia, .that were major suppliers to the steel industry are 

upset by the collapse of the U.S. market for coking coal. Coking, 

the only market in which coal has a technological advantage, has 

proven one in which demand has shifted from stagnation to decline. 

Because of what I consider unfortunate developments, the 

threat of nuclear power to coal in the U.S. market is limited to 

the impacts of such plans from the early 1970's that will 

ultimately be realized in the next few years. However, much of 

the rest of the world has chosen to continue nuclear developmer.t. 

Nuclear power expansion deprives the coal industry of a sales rise. 

Weaknesses in Other Markets 

Beyond these difficulties is the failure of other industrial 

markets or synthetic fuels markets to develop as forecast. Th~ 

synfuels situation is less surprising. The case for synfuels r~as 

based on dubious projections about oil prices. It was feared that 

such prices would rise continually and that it would become 

economic to develop oil shale and various synthetics from coal to 

compete with high-priced oil. The primary failing of such analyses 

was an excessive pessimism about oil. In addition, synthetic fuel 

production started to appear far more expensive than its advocates 

initially claimed. 

The experience with other industrial markets is trickier. A 

standard forecast for over a decade has been for coal to absorb 

much of the growth in industrial fuel use. The 1974 Project 

Independence scenarios call for total industrial coal use (including coking) to hit 215-230 million tons by 1985. Numerous armchair 

calculations were published purporting to prove that coal was the 

cheapest fuel source for new boilers. (The maturity of fluidized 

bed reactor technology is creating some optimism that the prol'lem 

is close to solution. This remains to be seen.) 

Actual consumption through 1983 was stagnant in the "oth~r 

industry" portion of the market. Sales never returned to 1973 

levels (fig. 11). With sales of more than 70 million tons in 

1984, we saw the first signs of a comeback. Current 9 month 

figures are at an annual rate of 72 million tons. The Energy 

Information Administration's forecasts, issued in early 1985, set 

21 
. ~ 

C"' 

(''1 

~H 

It) 

G) ('I 

CD 

-

CDO 

0\G) 

,.._ G3 

"" 

"'- . .0 GJ 

Q. 

an~ 0 

~ 

~ ... :s ~ 

t')~ ~ 

u ~ 

~ ~ 

I" ., ,.._ - ~ ~ < ~""' til 

0\ I:) 

• .OM GJ 

.c a. ·~ ~ a ...... .. c:= 0 :1 ·~ ..-4 

1.1.1 ·~ d 

~ Ul 0 

G~ ..-4 

u ~ 

1.1.1 ·~ § c:::a t') 

~ g) 

N d 

0 

·~ u 

-

G M 

"' 0 0 

0\ .~ u 

lnM M 

"' "' . .., ..... 

~ 

.u 

an g) 

·~ :s 

., 

II) • .., d 

t-f 

U')~ 

It) ,.., . 

~ 

~ 

an GJ ("• 

,.., ~ 

:s 

- C)() 

an ..-4 

ra.. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ' ' ' ' ' ' ' ' ' ' 8 8 2 ~ ~ ~ ~ ~ ~ 0 - -

22 
the 1985 levels for total industry coal use at 130 million (58 

coking and 72 other). 

Similarly, in neither western Europe nor Japan has there be~n 

a major shift to coal in other industrial uses. Japan has raisei 

coal use for this purpose from only slightly more than a million 

metric tons in 1973 to about 11 million in 1982. The long decline 

in European industrial coal consumption did not end until 1979. 

By 1982, consumption was still below the levels of 1974. Cokingcoal demand has tended to collapse (fig. 12). 

The Underlying Forces 

The central consideration in all appraisals of coal is the 

amount of coal that can be produced at costs significantly below 

the prevailing prices of oil and gas. No one would use coal 

unless the delivered price were below the delivered price of oil. 

Every coal user endures extra nonfuel costs in receiving, stori~g, 

and burning coal. These costs involve both a higher investment 

and greater nonfuel operating costs. 

The extent of coal markets depends upon the interaction of 

user size and location. Location is critical for the usual reaFon 

that it greatly affects transportation costs. Transportation, fn 

turn, is a major influence on costs. Thus, those with access to 

coal that is cheaper to mine and transport and farther from 

sources of oil and gas are more likely to use coal. 

User size is critical in that the disadvantage of using coal 

can be materially reduced with large-scale burning. The most 

obvious advantages are the ability to receive coal in trainload 

(or, internationally, in large shipload) lots and the lower unit 

costs of large-scale pollution control equipment and its operation. 

The advantage of large-scale use is lower unit nonfuel costs at 

almost every stage of the coal-consumption process. 

As far as the relative importance of size and location, 

experience has been that coal sales have gained far more from 

selling to electric utilities more distant from coal mines than 

from selling to other types of users nearer the mines. The 

available evidence suggests that the scale effect has been both 

increasing in importance and of greater impact than location in 

affecting coal use. On the first score, the two considerations 

already stressed seem the critical forces for increasing the 

advantage of large scale employment of coal. Bulk shipping has 

become an increasingly important influence. The sixties saw the 

rise of unit train rates in the United States; the seventies saw 

the rise of ports in South Africa and Australia to handle larger 

colliers. 

23 
en 

~ 

0 

4-J 

(.) 

•r-1 

J.-1 

4-J 

QJ 

s 1\.) 

.r;:... "0 

~ 

cu 

en 

;::3 

0 

..c: 

H 

180,000 

160,000 

140,000 

120,000 

100,000 

80,000 

60,000 

40,000 

20,000 

0 

OECD Europe 

51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 Year 

52 54 56 sa so 62 6.4 6~ 68 10 1~ ?4 ?.; 7, ~., ~~ 

Figure 12. Coking-Coal Consumption in OECD Europe, the USA, and Japan. 
Air-pollution regulation since the 1977 move to a best 

available control technology (BACT) approach has also significantly increased the advantage of large-scale use. Not only are tr~ 

unit costs of constructing pollution-control devices lower for 

large-scale users, but important economies of scale arise in 

operation. The close controls and frequent cleanings required to 

keep stack gas scrubbers operational are less burdensome for l~rge 

operations. 

I suspect that inadequate appreciation of these points is the 

source of the many expressions of surprise over the lack of co~l 

conversion by nonutility boilers. The forecasts alluded to before 

seem to underestimate the magnitude of the nonfuel costs of fu~l 

use at levels well below those of large power plants, as well E'S 

overestimating the price of oil. The converse of this argument is 

that in a large part of the world, coal, at least from the low·· 

cost suppliers, is a cheaper fuel than oil and gas for new 

electric power plants. As noted, a critical further question is 

the comparative economics of coal and nuclear power. 

The regulatory uncertainties in the United States have 

guaranteed that no more nuclear plants will be ordered in the 

foreseeable future. Nuclear regulation has the dubious reputation 

of being universally damned as both inordinately slow and expensive 

and incapable after all that of ~nsuring nuclear safety. The 

situation is aggravated by the reluctance of public utility 

commissions to allow new investments in facilities. The only open 

question is whether the death would have occurred even with 

different regulation. 

The experience abroad strongly indicates that the intrinsic 

economics do make nuclear power an attractive option. The Fre~ch, 

Germans, and Japanese, using U.S.-developed technologies, have 

proceeded with extensive nuclear developments. The one major 

country that has faltered is Britain, which insisted on developing 

its own technology. To be sure, there are alternative explanations. Most of these countries have less access to low cost coal 

than does the United States. However, Ontario is as well placed 

to receive U.S. coal as many parts of the United States, and 

Ontario Hydro is going heavily nuclear (using a successful 

Canadian technology). 

Similarly, it is not clear that foreign nuclear and electricutility industries are better organized and better coordinated. 

The much cited example of the coordinated French effort appears to 

be an exception rather than a typical case. A more plausible, but 

still dubious, defense of the U.S. outcome is that regulation in 

those countries is too lax. If my views that nuclear power was 

killed predominantly by unwise public policy are correct, coal 

analysts must recognize that in the very long run with which this 

conference is concerned nuclear power may revive. 

25 
With all this in mind, we can return to the question of the 

prospects for coal. Expectations for the United States are that 

by 1995 use will reach 1.1 billion tons. This contrasts with a 

1979 DOE forecast range of 1.6 to 2.0 billion short tons. By 

2000, we might reach 1.4 or 1.5 billion. The reductions reflect 

both the cuts already noted in estimates for electric utilities 

and slashing of all the other estimates. Both coking· coal and 

nonutility steam coal forecasts were more than halved; forecasts 

for synthetic fuels went from substantial to negligible. The 

range of views on European and Japanese prospects as noted is eve~ 

wider and rapidly changing. 

Production Impacts 

Coal-production trends follow the fundamental economic 

principle of reflecting the interaction of demand and supply. 

Thus, consumption trends have interacted with world-supply 

conditions to produce diverse production developments. The United 

States shares with China, South Africa, India, Australia, and 

Canada the maintenance of growth and nontrivial production levels 

(figs. 13-16). (Soviet coal production, in contrast, has tended 

to stagnate in recent years.) At the other extreme, the controlled 

contraction of western European coal production continues to 

stumble onward. Here the more interesting cases are Britain and 

Germany. They have the largest coal industries in western Europe. 

Both have shut down larger amounts of capacity than elsewhere, but 

this was mainly because there was more capacity to begin with. 

The percent declines were much greater in other western European 

countries (fig. 17). 

More than slightly perversely, it is the Germans who have 

preserved the largest fraction of prior coal-producing capacity. 

In 1957, at the start of the European recognition of its coal 

problems, Britain was producing about 225 million metric tonnes; 

West Germany, 155 million. The respective 1983 levels were 116 

and 90 million. Such differences conflict with the vision of 

Britain as a more protectionist, lower coal-cost country. 

Presumably, the availability of North Sea oil and gas put more 

pressure on British coal protectionism than was experienced in 

Germany. 

The biggest influence on coal production in the United States 

has been the interaction among rapid growth in the West, rising 

natural gas prices, and the availability of low-cost coal in the 

West. Within the United States, the production rises have been 

predominantly in the West. The great bulk of the growth of 

western coal output has been to serve new markets, especially in 

the West South Central States. A second major force has been 

air-pollution regulations that encourage the use of low-sulfur 

coal. This has brought significant amounts of western coal.into 

Minnesota, Wisconsin, Illinois, Indiana, Michigan, and Ohio. 

26 
(I) 

s:: 

0 

-1-J 

(.) 

-M 

,... 

-1-J 

Q) 

N s 

"' "'0 

s:: 

Cll 

(I) 

=' 0 

..c 

E-< 

900,000 

BOO,OOO 

700,000 

600,000 

500,000 

400,000 

300,000 

200,000 

100,000 

0 

46 4B 50 52 54 se 5e 60 62 64 66 6B 10 12 74 76 76 eo e2 B4 

47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 61 63 

Figure 13. U.S. Coal Production by Region. 

Year 
500,000 

450,000 

400,000 

350,000 

(/) 300,000 ~ 

0 

+J 

u 

·ri 

!-< 250,000 +J 

Q) 

s N 

00 "0 

~ 200,000 Cll 

(/) 

;::l 

0 

..c: 150,000 E--1 

100,000 

50,000 

0 

Appelechte 

West~ 

I 

I

. 

~; 

Illinois bestn 

'»·=- · ................. ·-· ··~ ......... ,.-.-.. ~·->»<·· _/ 

46 48 50 52 54 56 56 60 62 64 66 66 70 72 74 76 78 80 62 64 Year 

47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 61 83 

Figure 14. U.S. Coal Production by Region. 
(/) 

{:l 

0 

-1-J 

(.) 

•r-i 

1-1 

-1-J 

(1) 

N s 1..0 "0 

{:l 

cO 

(/) 

::l 

0 

.c 

E-i 

eoo,ooo 

700,000 

600,000 ¥ \ U.S.A. 

500,000 ..... 

400,000 

300,000 I ~- I \ /\ / Chine 

200,000 

100,000 

0 I i I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 

46 4B 50 52 54 56 se 60 62 64 66 68 70 72 74 76 7B eo 62 64 Year 

17 1~ 51 53 55 57 5~ ~1 ~3 ~~ ~7 ~q 71 7~ 7~ 77 7Q e1 e~ 

Figure 15. Coal Production USA, USSR, China. 
Cll 

~ 

0 

.j..J 

C) 

"M 

J..l 

.j..J 

Q) 

s w 

0 "t:: 

~ 

Clj 

Cll 

==' 0 

.c: 

E-t 

250,000 

200,000 

150,000 

1 Poland 

100,000 

50,000 

0 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 

~ ~~ CS() cs~ ~4 c;,c; -;~ .;~ 'i~ 'i4 'i'i ~~ 7() '?~ 7 4 '?~ ?'~ ~t) ~~ ~1 Year 

47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 61 63 

Figure 16. Coal Production in India, Poland, South Africa, and Australia. 
Cll 

j:l 

0 

~ 

() 

or-t 

1--1 

~ 

QJ 

w a ,_. '"d 

j:l 

ctl 

Cll 

::s 

0 

..c:: 

E-1 

250,000 

Britala 

200,000 

Germaay 

I __.,-......, 

150,000 

100,000 

Praace 

50,000 

_,___,_.--------------.... ... , 

.,..z-'~----,. -------------------. ___ __ 

.. 1_.... ~--~------~----------------- 0 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 1 a 

46 4B 50 52 54 56 58 60 62 64 66 66 70 72 74 76 76 60 82 64 Year 

47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 61 63 

Figure 17. Western European Coal Production. 
Within the East, several forces have been at work. Some 

regions, notably eastern Kentucky, have waxed while others wa~ed. 

Eastern Kentucky has benefited from many influences. It is a 

source of low sulfur fuel; it is well located to serve growing 

markets in the Southeast; it has better labor relations and a more 

favorable regulatory climate Uhan in some other eastern State~. 

The international situation is even more complex. As already 

suggested, government intervention has allowed the gradual 

reduction of coal output in high-cost areas such as western E'1rope 

and Japan. The decline in Japanese production coupled with rising 

consumption has resulted in sharply higher imports, with the 

United States, Australia, Canada, and South Africa as key 

suppliers. 

Each of these countries has a different role in the world 

market. The United States is the long-time but challenged leader. 

Its advantages are availability of particularly high quality 

coking coals and experience in export markets. Its drawbacks are 

higher costs, especially for low sulfur steam coals. Australia 

has large amounts of cheap surface mineable coking and steam coals 

in regions fairly close to port. South Africa has low-cost 

surface mineable coals, predominantly steam coals. Canada's coals 

are in the West; they compete best as coking coals for Japan. 

Other competitors may arise. Exxon's large Colombian venture has 

a minimum export target (15 million) close to current Canadian 

levels (18 million in 1982). Hopes are for output double the 

minimum. 

How the world market actually is shared is not readily 

forecast and depends upon the underlying economics and the wisdom 

of public policies. It is to be hoped that the strong industries 

will not be hampered by excessive controls or the weak ones overly 

protected by continued heavy subsidies. 

The Policy Climate 

All this has occurred and continues to occur despite the 

existence of a mass of government policies that restrict the 

production and use of coal. These policies differ radically in 

the wisdom of their purported 'intents. However, they suffer 

uniformly from unsatisfactory implementation. All countries l'ave 

become concerned with the environmental impacts of coal produ~tion 

and use. Those countries with expanding coal industries are also 

interested in ensuring an equitable sharing of the bounties of 

production. Those countries with contracting industries have 

tried to ease the pains. 

In every situation, an argument can be made for some action. 

Serious environmental damages are a burden on the society that. 

should be alleviated. A long tradition exists in the theory and 

32 
practice of public finance of taxing the economic rents--the 

profits in excess of a reasonable return on capital--from minercl 

exploitation. Modern governments believe that assistance should 

be provided to the innocent victims of economic change. 

The mildest criticism of all these policies is that they are 

very badly designed. A vast literature has arisen suggesting t1'~t 

environmental regulations seek to attain their goals through 

inordinately expensive, time-consuming rules. The evidence also 

suggests that policymakers have set their objectives on the basis 

of flimsy, exaggerated estimates of damages (particularly to 

health) and a poor idea of what causes them. The Lave and Seskin 

(1977) estimates of health damages from air pollution have been 

severely criticized, particularly by Ramsay (1979), as far too 

high; nevertheless, they are still widely used in policy debates. 

The Office of Technology Assessment used them in 1984 to justify 

action on acid deposition.* The damages to lakes are too small to 

justify massive control outlays, so a health rationale is needen. 

We appear to be seeking too much abatement and possibly 

emphasizing the wrong problems. 

Similarly, efforts to tax economic rents are severely flaw~d. 

Generally, the drawback again is reliance on undesirable instruments. A standard exercise in elementary economics is to show 

that sales taxes and percentage royalties cause undesirable 

decreases in production. Nevertheless, sales taxes and royalties 

are the favorite way of transferring economic rents to governme~t. 

In the United States, we behave like an underdeveloped country and 

are overly obsessed with avoiding inadequacy of payment. For 

various reasons, we demand a ridiculously high level of proof that 

sufficient payment is received. Many different motives inspire 

these attacks; some are sincerely concerned with rent taxation, 

others, such as environmentalists and those using coal-bearing 

lands for other purposes, view high charges as a good way to 

discourage mining. Institutional peculiarities make State 

governments desire vigorous efforts to get high prices for Federal 

minerals. Under present law, the States enjoy the benefits of 

*For the fullest statement of the Lave and Seskin views, 

see Lester B. Lave and Eugene P. Seskin, Air Pollution and Humcn 

Health, Baltimore, Md.: Johns Hopkins University Press for 

Resources for the Future, 1977. See William Ramsay, Unpaid Cost 

of Electric Energy: Health and Environmental Impacts from Coal and 

Nuclear Power, Baltimore, Md.: Johns Hopkins University Press for 

Resources for the Future, 1979. Ramsay sets the deaths from coal 

pollution at much lower levels than Lave and Seskin. Finally, see 

U.S. Congress, Office of Technology Assessment, Acid Rain and 

Transported Air Pollutants: Implications for Public Policy, 

Washington, D.C.: U.S. Government Printing Office, 1984. 

33 
higher payments for Federal minerals without bearing the costs of 

producing such incomes. 

I believe this is extraordinarily shortsighted policy an~ 

that everyone, including tax collectors, would be better off if 

land were put into its socially most valuable use as soon as 

possible. An action system of disposal is desirable as the 

administratively most satisfactory way of choosing among clairqnts. 

The problem is the insistence on vainly waiting for higher offers 

that will never emerge. 

Finally, however much one wants to ease transitions, the 

prolongation since 1958 of efforts to assist western European coal 

seems excessive. The facts reinforce this view. Policy has 1'~en 

and continues to be guided by incorrect visions of the prospects. 

This experience is the quintessence of the drawbacks of the 

argument that coal is a plentiful fuel. 

The coal industry has done remarkably well given these 

adversities. Even though the industry has managed to lessen the 

impacts, the policies should be reformed. I would argue that 

policy reform may be by far the most critical need in the coal 

realm. 

Implications for Research 

Thus, the perspective provided as a preliminary to discussions 

of research needs is an emphasis on the critical role of intrinsic 

market forces and regulation in affecting coal developments. 

Those suggesting increased research should be more realistic about 

what can be accomplished. 

The research community loses credibility when it makes performance claims that cannot be realized. Such a loss has occurre~ in 

energy research. To a large extent, the failure was based on 

excessive reliance on the incorrect views of coal that I criticized. 

Another influence, however, has been the inability to meet the 

technological promises. A decade or so ago, the impression was 

created, by at least some of the more flamboyant and thus more 

publicly known advocates, that several alternative technologies 

for coal utilization would soon be economically available. 

Opportunistic politicians, particularly in the Carter administration, used these ideas to create ill-advised energy research a~d 

development programs, particularly the Synthetic Fuels Corporation, 

as a substitute for policy reform. The refusal to remove a morass 

of price controls was rationalized by invalid claims that only new 

technologies would solve the problem. The result has been drastic 

deterioration of the climate for energy research. 

This, of course, denotes neither a failure to effect 

technological advances nor the undesirability of careful effor~s 

34 
to formulate a better research program. I merely suggest that we 

should practice the much advocated and inadequately implementerl 

concept of learning from experience. The new research agenda that 

is proposed here should not suffer from the defects already noted 

of past .efforts. We should not repeat the discredited notion t.hat 

we must use coal for everything. There are, nevertheless, many 

opportunities for coal. The problem is not to obscure them in the 

all too traditional hyperboles of coal advocacy. 

35 
Sources and Notes on the Tables 

Table 1 - DOE 1979-1982 

U.S. Department of Energy, Annual Report to Congress. 

Energy Information Administration, Annual Report to 

Congress. 

In some years the forecasting volume was supplemented by 

another volume tabulating results. 

DOE 1983 to date, Energy Information Administration, Annual 

Energy Outlook. 

DR!: Data Resources, Coal Review. 

Tables 2 and 3 - World Coal: lEA Steam Coal 1978 

International Energy Agency, Steam Coal Prospects to 2000. 

Paris: Organization for Economic Co-operation and 

Development, 1978. 

World Coal: Carroll L. Wilson, Project Director, 

Coal--Bridge to the Future. Report of the World Coal Study, 

Cambridge: Ballinger Publishing Company, 1980. 

lEA Coal Policy, 1981, International Energy Agency, Coal 

Prospects and Policies in lEA Countries, 1981 Review. 

Paris Organization for Economic Co-oper at ions and De,Telopment 

1982. 

lEA World Energy 1982: International Energy Agency, World 

Energy Outlook, Paris Organization for Economic Co-operation 

and Development, 1982. 

UN ECE 1983: United Nations Economic Commission for Europe, 

Working Party on Coal Trade, World Coal Trade Up to the Year 

2000. Geneva Economic Commission for Europe. 

EEC 1984: European Economic Community Commission, Review of 

Member States' Energy Policies, Brussels, 1984. 

EEC 1984: European Economic Community Commission, Ero.rgy 

2000. A reference projection and its variants for tl'e 

European Community and the World to the year 2000. 

lEA Coal Information, International Energy Agency, Coal 

Information 1984. Paris: Organization for Economic 

Co-operation and Development, 1984. 

Saarberg 1985: Saarberg, Market Perspectives in 198:. 

Saarbruchen: Saarberg, 1985. 

Note: Certain figures are inferred. lEA Coal Policy 1981 and 

1983 and the two EEC reports report in oil equivalent tons (OET). 

Conversion to coal equivalent tons (CET) was by multiplication by 10/7, 

the standard lEA relation between OET and CET. lEA Coal Policy 1981 

and 1983 and lEA Coal Information do not report steam use as such. It 

was calculated as production plus net imports and other steam was 

computed as total steam consumption less electric power. In sc~e 

cases, a negative number results. This could occur if production or 

trade estimates report as coking coal, coking quality coal used for 

electric power. lEA 1978 does not report coking and steam outp1t and 

they are calculated as consumption less imports. 
World Coal contains two page summaries of forecasts for thr. 

participating countries. These provide figures for 1990 and 2000 

corresponding to all the categories listed in the table. Howevr.r, only 

partial forecasts are given for the rest of the OECD. In particular, 

an "other western Europe" number is available on total use, stet'1Q. use, 

steam imports, coking coal imports, electricity coal use, industrial 

coal use, and case B production but only for the .year 2000. These 

numbers were manipulated to yield all the year 2000 other OECD Furope 

categories needed for the tables. These were added to data on 

separately reported countries to yield the OECD Europe numbers Ehown. 

Calarco shows actual coal tons so his steam coal figures are not 

comparable with those in other studies. 

37 

BAIRIBRS AND OPPORTUNITIES IN THI APPLICATION 

OP COAL-QUALITY GBOSCIBNCB 

by 

Jeremy Platt 

Electric Power Research Institute 

Coal-quality geoscience means different things to differert 

people. For most, even including many people in the geologic 

community and mining indus try, it undoubtedly means the esoteri.c 

study of boring, black rocks. Yet for a growing number of 

electric-utility fuel managers and plant operators, coal-compary 

mining engineers and coal marketers, policy analysts, and others, 

coal-quality geoscience is developing a decidedly practical flevor. 

The promise of cost savings, beginning with exploration and 

extending to combustion and environmental management, is exciting 

the interest of these "newcomers." 

Misconceptions about coal-quality geoscience and poor comD"'1 tnication among the mining industry, utility industry, coal-research 

community, and government are the principal obstacles to more 

widespread application of coal-quality geoscience in policymaklng, 

mining operations, and utility fuel management. These same 

obstacles stand in the way of a rigorous and timely nationwide 

research effort into coal-quality geoscience. The approach taken 

in this paper is to examine nine of these misconceptions. They 

are presented as a series of "myths." Although I may overstat~ 

some of them, they illustrate the important role of attitudes, and 

not merely scientific fact or technological readiness, in deteJ~ining the many possible applications of coal-quality geoscience. 

MYTH NO. 1: COAL GEOLOGY IS AN ANTIQUATED SCIENCE 

Most casual observers might assume that the science of coel 

geology has its roots in the Industrial Revolution. In the Unjted 

States, we might suppose that the great strides in understandir~ 

coal geology and resources took place well before the 1950's, when 

coal gave way to oil as the principal energy source to the ecor<)my. 

Although this is largely true, reflected in the work of White r~d 

Thiessen (1913), Campbell (1903, 1906, 1912, and 1917), Cady 

(1915, 1933, 1939, and 1942), and others, the irony is that mot~rn 

developments in petroleum geology have been responsible for muc.h 

of the change and growth in coal geology over the past 15 years·. 

39 
(For additional references to early publications on coal, see 

Eyster and others, 1980.) 

The modernity and dynamic nature of the current state of 

coal geology can be illustrated in many areas, all having an 

important bearing on our understanding of coal quality. Three are 

discussed here: depositional environment concepts, geochemistry 

of coal quality, and coal geostatistics. 

Deposi.tional Environment Concepts 

The 1960's was a period of growth in the understanding of 

depositional environments, stratigraphy and sedimentology. No 

doubt an important driving force was the need to better delineate 

oil reservoir beds and to extract more information from individual 

drill holes and core samples. Interpretation of sedimentary facies 

in terms of their environments of deposition gave geologists a 

powerful predictive tool. Moreover, it provided a framework for 

explaining otherwise discrete and seemingly unrelated lithologies 

in vertical and lateral succession (fig. 1). In the 1960's, t~ese 

concepts were advancing the state of the art, and they had only 

just begun to be applied to coal. 

The sedimentary deposits of the Mississippi Delta and Gulf 

Coast were the cradle for the development of these concepts, particularly with respect to the geometry and sedimentology of the 

full range of deltaic deposits extending from the upper delta plain 

to the lower delta plain and beyond. It is no accident that an 

understanding of the distribution and characteristics of lignites 

has enabled the Texas Bureau of Economic Geology to show a close 

analogy between these lignite-bearing sequences and the now-classic 

Mississippi-delta depositional models. A case in point is their 

study, conducted between 1979 and 1981, of four densely drilled 

lignite properties, each representing a different paleogeographic 

environment (Tewalt and others, 1983). Examples of cross sections 

are presented in figure 2. The authors calculated the number of 

holes required to estimate the ~esources in each property to the 

same level of precision (20 percent) (table 1). The pattern of 

results confirms their prior notions at least in its general 

direction. 

Obviously, if one could calibrate characteristics of seam 

thickness variation and continuity to particular environments a~d 

then identify these same environments in the rock record, one 

would have a powerful tool for exploration and resource assessm~nt. 

Actually, this hasn't been possible. The rocks provide their o~·~ 

record of depositional environments which has defied simplification. Consequently, geologists are not all of one mind concerning 

the applicability of depositional-environment concepts. A retreat 

in scale can be seen in the work of John Ferm (for example, Hor~e 

and others, 1978, Ferm and Mathew, 1981, and Ferm and Staub, 

40 
A 

BAR-I 

RIER I 

I 

BACK- I 

BARRIER 1 

I 

I 

~ORTHOQUARTZITE 

~SANDSTONE 

0 GRAYWACKE 

SANDSTONE 

LOWER ITRANSITIONA~ 

DELTA PLAIN 1 LOWER 1 

I DELTA PLAIN 1 

SCALES 

= ::::E METE~ F;:Oo 

0 ..... 

KILOMETERS 

==::;10____ 20 O ~ MILES lO 

Figure 1. Depositional model for peat-forming (coal) environment~ 

in coastal regions. Upper part of figure is plan view 

showing sites of peat formation in modern environments; 

lower part is cross section (AA') showing, in relative 

terms, thickness and extent of coal beds and their 

relations to sandstones and shales in different 

environments (from Horne and others, 1978). 

41 
~ 

ALLUVIAL PLAIN DEPOSIT 10,000 FT 

r =~ 

t., ..... ~·I 

Dip Section 

l-=~- Dip Section 

~ 

UPPER DELTA PLAIN 10,000 FT 

Strike Section 

LOWER DELTA PLAIN 10,000 FT 

E- ~ = I 

S.trike Section 

r~- ~ -~~ . ~-· ==-===r 

___ ------------- Dip Section 

STRAND PLAIN/LAGOONAL 10,000 FT 

_;:;....-

-------

......._. 

II em 

~j:p: 20 600 

. 

...,... -~ "Y" 

. 

-. Strike Section II em 

; ! !l -~l 

20 

1:1:er 600 ==~ 800 30 

Dip Seqtions 

.I 

::= 

·~ 

Figure 2. Cross sections of Texas lignite deposits (modified fro~ 

Tewalt and others, 1983). 

42 
1984), who after dissecting many sites in the Central and Southern 

Appalachians from a depositional-environment perspective, has 

turned to a more descriptive and less interpretive approach to 

coal seam geometry--the concept of platforms and transition zones 

(fig. 3). Nevertheless, his evolution by no means condemns the 

usefulness of depositional-environment concepts as an explanatory 

and predictive tool in local applications and in supporting the 

detailed analysis of coal quality through paleobotanical and other 

means. 

Not to be misleading, perhaps it should be said that in many 

applications the routine payoff from depositional concepts comes 

not so much from what they say about the coal itself, but from 

allowing an improved interpretation of the facies of the non-coal 

rocks within coal-bearing sequences. This is of great importanc~ 

to correlation using geophysical logs and cores. 

When we consider the extent to which depositional-environm£nt 

concepts have penetrated the practice of coal geology, it is 

surprising how very short the history of these concepts are. Tl'e 

number of research studies is quite small, and the progress that: 

has been made owes more to the perseverance of a relatively small 

number of individuals working in selected areas of opportunity 

(that is, good outcrops or good company cooperation) than to any 

widespread market shift in coal price, consumption, or public 

coal-quality consciousness. 

Geochemistry of Coal Quality 

The association of marine beds with higher sulfur coals is 

now widely recognized. The example given in figure 4 is typical 

of this association, where the coal underlying marine roof rocks 

has a high sulfur content and the coal that had been shielded f~om 

marine influences by an intervening wedge of terrigenous clasti~s 

has a low sulfur content. This association has been observed 

frequently enough that roof lithology has gained status as a predictive indicator of underlying coal quality. Another practical 

benefit is that the introduced sulfur is commonly in a form more 

amenable to cleaning; for example, that in the example in figure 4 

is mostly disseminated framboidal pyrite. Although less practical, 

another use of this association is as an indicator of the depositional environment of the roof rocks where the sulfur content of 

the underlying coal is known. 

So far, so good. In the intervening years since Williams and 

Keith's pivotal study in 1963--which is pointed to as the first 

statistical and definitive documentation of this roof-rock/coalquality association--it would appear that these ideas have been 

proven by the test of time. The time, just as for depositionalenvironment concepts, has been quite short. But more alarming is 

the next chapter of the story, and how it illustrates ongoing 

43 
STUDY AREA 

DEPOSITIONAL SETTING 

ALLUVIAL PLAIN 

UPPER DELTA PLAIN 

LOWER DELTA PLAIN 

STRANDPLAIN/LAGOONAL 

NO. OF BOREHOLES 

(PRECISION 20%) 

33 

9 

5 

7 

Table 1. Borehole data requirements for reserve estimation in 

differing depositional settings (modified from Tewalt 

and others, 1983). 

PLATFORM PLATFORM 

TRANSITION TRANSITION 

MINABLE SEAM 

Figure 3. Model of Appalachian coal beds (from Ferm and Mathew, 

1981). 

44 
A. 

B. 

c. 

J 

N SCALES 

0 I M Mil•• 

0 lcilomet.,, 

~ ~~t:~~T~::L:ND 

m Olt·IOit 

D IOit · lOft 

0 ,,_,..,._20, 

- lhw ofcrou 111etSCALES 

0..., M miM 

0 

- 5 ki'--n 

DEPOSITIONAL 

ENVIRONMENTS 

OF ROOF ROCK 

~ N 

j 

0 

SCALE 

I 2 J ~ Miles N 

--- j 0 5 ki'-tw• 

SULFUI I'EICENT 

Dl-"-1 

EJI 2 

tz3 2 3 

OJ 4 

r::.::le-,.."-4 

Figure 4. Roof-rock/coal-quality association. A. Distance to 

overlying marine rocks. B. Interpretation of 

immediately overlying rock. C. Sulfur content of coal 

(from Horne and others, 1978). 

45 
change in our understanding of the geologic factors controlling 

coal quality. 

Cecil and others (1982), largely on the basis of detailed 

geochemical analysis of the Upper Freeport coal bed in 

Pennsylvania, have proposed that the primary control of both 

sulfur and ash in coal (with the exception of clearly indisputable 

terrigenous clastics) is the geochemistry of the peat-forming 

swamp. This might seem a minor distinction from the geochemical 

conditions present during deposition of the roof rocks, but it 

significantly changes one's view of the marine-roof/high-sulfur 

coal association to "a special case of the pH model" (Cecil and 

others, 1982) ••• 11a special case within a more encompassing 

geochemical model" (Cecil and others, 1983). 

The basic argument is that, under highly acidic and wet 

conditions, the dissolved mineral content of fresh water is very 

low and bacterial activity capable of either degrading the peat or 

reducing any sulfate present is low. These conditions produce 

low-ash, low-sulfur coal. Under drier freshwater conditions, the 

residual ash content is increased in proportion to oxidation of 

the organic matter. And under the more alkaline conditions 

characteristic of brackish and marine waters, bacterial activity 

is enhanced, simultaneously degrading the peat and reducing the 

sulfates present. These conditions produce high-ash, high-sulfur 

coal. 

Support for these new theories is seen in the exceptions to 

the traditional roof-rock/coal-quality associations and in the new 

associations of ash and sulfur. For example, exceptions to a 1:1 

roof-rock/coal-quality relationship have been found not only in 

Williams and Kei.th's work on the Lower Kittanning, but also in 

recent work on the upper Elkhorn No. 3 and Fire Clay coal beds by 

Currens (1981). This led Currens to propose a model linking the 

sulfur and ash distributions during peat formation (fig. 5), and 

to propose further that the association of marine rocks with highsulfur coal is more of a coincidence than a consequence. 

It is too early to tell where these new ideas may lead. 

Their relevance to finding low-sulfur and low-ash coals or coals 

that can be cleaned to compliance levels is readily suspected but 

remains to be demonstrated in a significant number of case studies. 

One direction that Cecil and others have taken (1983, 1985) is to 

examine the broad paleoclimate changes that have ultimately 

controlled local pH and coal quality. In turn, notions of what 

constitute properly analogous depositional environments have been 

expanded. 

46 
PERCENT TOTAL SULFUR 

PERCENT ASH 

w<6% o6-12%E:312-18%E2J>18% 

Figure 5. Speculative relationship of coal quality to contemporaneous peat-forming environment (from Currens, 1981). 

47 
Coal Geostatistics 

Coal geostatistics is another, perhaps more clearcut, example 

of the modernity of the tools of coal geoscience. As far as I 

know, no applications of mining geostatistics--itself a relatively 

new discipline--to coal were made before 1978 in the United States. 

Now, several mining companies have become conversant with geostatistical techniques. As Rendu (1982) pointed out, "There are 

strong indications that geostatistics is going to play an increasing role in the evaluation of coal projects." Unfortunately, the 

adoption of these techniques has been impeded by the lack of 

thorough yet readable demonstrations, such as that provided by 

Buxton (1982). The mining industry's use and the utility industry's 

acceptance of geostatistical coal-reserve assessments will probably 

require many more examples of practical success before the mystique 

of coal geostatistics is overcome and the backlash from snake-oil 

applications, which can be anticipated, has subsided. 

In our own studies of coal geostatistics (for instance, Tewalt 

and others, 1983, and Journel, in press), we have found that these 

techniques are hardly necessary for devising gross property 

tonnage estimates. Their promise, instead, is in how they can 

account for the varying degrees of uncertainty surrounding 

estimates of coal characteristics at specified locations anywhere 

in the coal property. This information can be of considerable use 

in optimizing drilling campaigns (Kim and others, 1980), as well 

as in simulating the quality of run-of-mine coal so as to assure 

continued compliance with emissions regulations or coal contract 

quality specifications (Knudsen and others, 1980). 

The appealing thing about geostatistical techniques is that 

they don't superimpose an arbitrary weighting scheme on how the 

existing data on quality or thickness will be used to estimate 

characteristics away from the known data points. Instead, the 

available data for a particular property are analyzed to derive a 

"customized" weighting scheme. This is done by constructing a 

variogram, which shows the waning influence of a sample point at 

increasing distances from that sample point. An example of a 

variogram for coal thickness is given in figure 6. Other products 

of geostatistical analysis are more familiar, such as a map of 

sulfur distribution, (fig. 7). Their greatest practical value is 

probably in better understanding mined coal quality over time 

(fig. 8). 

Given the paucity of studies to date, the future of coal 

geostatistics will be dynamic. 

MYTH NO. 2: THE GEOLOGY OF COAL IS SIMPLE AND STRAIGHTFORWARD 

Most geologists have had a brief exposure to coal geology 

during their education, although their careers have led elsewhere. 

48 
~ (h) 

(112, 

10~--------------r-------------~--------------~-------------, 

700 

100 

500 

400 

300 

_, 

e, ~ (h)• 140•475(2(1fi)-2(t1

3

)3) 

lf (h)-140+475 

~ (h)•O 

II) 11 

nugget (Col 

----range(a) [ I 

-------------------- I 

Figure 6. 

I 100 

~--------------~-------------T ~~---------,1~5--------------roVariogram: variation in seam thickness measurements at 

increasing separation of sample points (from Pierce i'nd 

others, 1982). 

49 
0 

Figure 7. Contour map of Kriged sulfur values (in percent) plus 

two times standard deviation (from Kim and others, 

1981). 

50 
The fact that there routinely has been more money in other fields 

explains a lot; but another reason for the lack of glamour of coal 

geology may be simply that it is viewed as intellectually barren. 

What better example of the monotonous nature of layer-cake geology 

than coal? A localized version of this layer-cake perception is 

illustrated by a road cut in figure 9; a regional version is the 

sketch in figure 10. Although only schematic, figure 10 leaves 

one with the impression of a single coal bed extending from West 

Virginia to Kansas! Under such conditions, it wouldn't seem that 

exploration takes much creativity. 

In fact, the geology of coal-bearing sequences, although 

conforming to certain regularities, is anything but simple. The 

sedimentologic complexity of modern depositional environments, 

such as the views of the Mississippi Delta in figure 11 and the 

streamcourses of the Mississippi in figure 12, make this abundantly 

clear, as do many of the previous figures. The models of depositional environments, (figs. 1 and 2), do not eliminate this 

complexity--they simply make it a little easier to deal with. 

Whereas most of the work to date has been aimed at the 

geometry of coal beds and intervening sequences, the variation in 

coal quality characteristics is no less complex and, for want of 

data, more poorly understood. An example of a much smaller scale 

of variation than illustrated in previous figures is that of ash 

within an 8-foot-thick coal bed over a 10-acre mine site in West 

Virginia (fig. 13). Needless to say, very few pictures of coalquality variation are available at a scale anything like this. 

Yet, it is at this scale of fine-tuning where paleobotanical 

concepts and coal petrography are likely to yield important 

insights into the distribution and variation of ash, sulfur, and 

other characteristics, all having potentially tremendous 

commercial significance. (For a western example of a coal seam 

dissected at this scale of inquiry, see Warwick and others, 1984.) 

MYTH N0.3: BY NOW, USEFUL APPLICATIONS OF COAL GEOSCIENCE HAVE 

BEEN EXHAUSTED 

From an abstract perspective, once we recognize that much of 

the growth in the tools of coal geoscience has taken place so 

recently that not even the geologic community is fully aware of 

these developments, it is a short leap to conclude that applications of coal geoscience in mining, quality control, and resource 

assessment must certainly be in their earliest stages. 

A less abstract way of demonstrating this is to turn to 

anecdotes from mining and utility companies about some of their 

recent experiences, most of which are less than 7 years old. I 

have kept the company names confidential partly out of ignorance, 

but also not to scare away others from coming forth with other, 

hopefully more detailed, examples. 

51 
•s 

Figure 8. 

LEGEND 

m:!J ..... .. ~Elll ..... _ 

E§J-Io ~-­ ~~~ IIMIII ...... erOOM 

~ C.kw .... •AIMhtOM 

1!3 Tft"' -..tOM bed 

.... u ....... • .., ....... 

ililill•-... ~ ...... , .. .... '::af::;:) .............. . 

ll1l A.·--·· v ........... . 

3.6-·r---------------------------------~ 

3.2 

3.8 

2.a 

2.6 

8 18 

Run·of·the ~line ••••• 

Siallation 

38 

DAVS 

s0 68 

Simulated versus actual run-of--mine sulfur values (from 

Knudsen and others, 1980). 

Figure 9. Sketch of a roadcut that could lead to a "layer-cake" 

interpretation of coal- bed stratigraphy on a local 

scale (from Kentucky Geological Survey, 1981, pl. 15). 

52 
Ll THOLOGIC SYMBOLS 

CONCLOW[OAT[ rn lHALY LIWCSTOHC ~ SAHO.S TON( c::;:] liiiii(STQN( ~ 

SHAlt ~ CL AY ~ 

SANOY SHALt ~ CONCIJI[ fiOHS [QJ CAIUOHACCOU$ $HAL[~ IJt OK!TOH( ~ 

Figure 10. Diagrammatic regional cross section that could lead to 

the interpretation that coal-bed stratigraphy is 

"layer-cake" over large areas (from Wanless, 1950). 

53 
Vl 

~ 

~ PLEISTOCENE 

lr~ SWAMP 

~:::] FRESH WATER MARSH 

II BRACKISH WATER MARSH 

I I SALT WATER MARSH 

II SAND 

0 10Mi. 

............ 

~ 

0 10 Km. 

../) 

Figure 11. Mississippi Delta complex showing distribution 

patterns of channel sands to peats associated with 

marsh and swamp environments (from Frazier and Osanik, 

1969). 

~ 

~ 

~ f 

, 

r 

N 
t 

N 

______ _,s Mi. 

NO SAND I Levee, 

Aood Basin Deposits I 

SAND (Channel· 

Point Bar Deposits! 

Figure 12. Modern and ancient stream courses of the Mississippi 

River as indicated by fluvial sand (point bar) 

deposits (from Fisk, 1944). 

55 
ASH CONTENT OF WAYNESBURG COAL 

STRIP MINE NEAR MORGANTOWN, W.V. 

0 COAL WITH < 20% ASH 

II COAL WITH > 20% ASH 

OSHALE 

• SAMPLES .BASEMENT 

Figure 13. Small-scale variation in ash illustrated by a block 

diagram of a strip mine area displaying the lowtemperature ash content for the Waynesburg coal near 

Morgantown, West Virginia. Seven units including the 

middle shale parting (Unit 4) represent subdivisions 

of seam based on ash content. Dots on surface are the 

23 sampling locations. Percent dominant category 

refers to the persistence each unit extends throughout 

the strip mine area. T-8 represents an arbitrary plane 

constructed through Unit 7 so as to suggest the 

ash-peat accumulating simultaneously (an interpreted 

time horizon) (from Donaldson and others, 1979). 

56 
o A major coal company was willing to sell one-half of a 

western coal property to a utility. At the time, the cc41 

company used essentially no geologists. The utility weut 

to the trouble to map the property and located a major 

sand channel. In subsequent negotiations, the utility 

acquired the good half and the coal company was left with 

the channel. 

o A coal company was investing in an eastern property that 

had been sparsely drilled. On adjacent property, a majcr 

sand channel and severe slumping problems had been 

encountered. Without making any observations on the 

adjacent property, the coal company developed the mine c~d 

ran into the same problems. 

o Engineering consultants had drilled a western undergrourd 

property. By coincidence, three holes intersected sandstone 

roof, leading to an estimate that 80 percent of the roof 

would be good, solid sandstone. Once the coal company r~t 

underground, they found that only 5 percent of the roof 

was sandstone. A look at electric logs revealed the 

sandstones were fluvial, not blanket. As a consequence of 

rotten-roof conditions, the company routinely had to t~:e 

1/2 to 1 foot of roof, diluting the mined coal. Safety 

problems were aggravated, and at the channel margins, up 

to 6 feet of roof came down. Ash ranged from 5-7 percert 

to as much as 30-40 percent. 

o One member of a coal-company partnership wanted the oth~r 

to put up $20 million for longwall development of a new 

western property. The other wanted to do more geology 

first. After driving the entry 200 feet, the coal 

disappeared in a meander-bend channel scour. This was the 

first of many geologic problems encountered as mining 

proceeded. 

o An eastern coal company was selling a property showing 

8-foot coal with 30 million tons recoverable resources. 

Reinterpretation of logging reduced this estimate to 10 to 

15 million tons. 

o A coal company projected run-of-mine quality from a 

western property on the basis of drilling cuttings. Black 

shale was misinterpreted as coal. The mined product wa~ 

unacceptable, the property had to be redrilled and logged, 

and selective mining procedures with blending had to be 

introduced. 

o In a similar eastern case, unsupervised coring operations 

resulted in incomplete measurement of the partings in tl'e 

57 
seam. The ash was understated, and the coal company had 

to build a coal-cleaning plant. 

o Unanticipated underground conditions nearly doubled the 

cost of supplying coal from an eastern mine over a 4-year 

period. Roof falls at another mine cost more than $1 

million in cleanup and lost production. And because of 

these kinds of problems with quantity and also quality, a 

local utility buyer had to drastically reduce the amount 

of coal it could expect from these sources. 

o An eastern utility found that no suppliers could actually 

deliver coal in the required sulfur range. This was after 

$4-1/2 million had been spent to improve precipitator 

performance and after seven bids had been accepted from a 

field of 30 producers. 

These examples, I am told, are a small sample. By their very 

recent vintage, they warn us not to assume that all possible 

mistakes have been made and that the lessons from these have been 

learned. 

MYTH NO. 4: GEOLOGY AND COAL MINING DO NOT MIX 

This attitude reflects the traditional barriers between 

geologic functions and mining operations--barriers that lie behind 

many of the lost opportunities in the previous examples. Traditionally, the proper role of the geologist is to find the coal in 

the first place or, if this has already been done, to serve as a 

"land man" handling leasing activities and keeping up with the 

competitors. Mining operations have been described as a sort of 

"men's club" of tradition among the operators, engineers, and so 

on, where the geologist is only brought in when things get really 

bad, as in some of the previous examples. 

Certainly the fundamental orientations of operations and 

geology are different. The mining engineering approach to a 

problem is to mine through it or around it and keep producing. 

The approach is "can do"; one that geologists call "exploring w1.th 

a continuous miner." In this environment, geologic analysis is a 

luxury, probably irrelevant, and what's more, a safety headache. 

Yet the blame does not rest entirely with the engineers and opel·ators. Some mining engineers have accepted, and even instigated, 

geologic analysis as an adjunct to operations. The exacting 

nature of the mine environment is not one that tolerates geolog1.c 

imprecision. A mining college professor pointed out to me that 

one of the obstacles was the legacy of bad mining geology. 

As bad as this situation sounds, it now appears that a mix of 

geology and mining is occurring at an increasing rate. The phr~qe 

"coal mining geologist" need no longer be considered a simple 

58 
contradiction in terms. Much of the leadership in this must be 

attributed to recent oil-company involvement in western mining. 

Not only have oil companies had a different approach to the role 

of geologists and a higher tolerance of overhead costs, but also 

the scale of quality variation and seam discontinuities has 

required a tighter control than in the principal midwest and 

eastern seams. 

The contribution of geology to mining operations is most 

apparent in roof control. As several of the previous examples 

illustrated, the impact of bad roof on mine dilution can be severe. 

Examples of roof conditions related to different types of roof rock 

are shown in figure 14, an Illinois mine in the Herrin (No. 6) 

coal bed and in figure 15, a Utah mine. The coming of age of 

geology in mining is indicated by recent activities of the U.S. 

Bureau of Mines (USBM) (for instance, Jeran and Jansky, 1983) and 

by the remarks of a USBM geologist in a mining trade journal 

(Moebs, 1985). He writes: 

Studies directed toward increasing the utilization of 

geologic methods in coal mine ground control are becoming 

more important. It is commonly recognized that geology is 

the key to effective ground control. That is, a sound 

knowledge of the character and structure of rock provides a 

sound basis for mine planning and selection of appropriate 

roof-support methods. 

For example, studies by the U.S. Bureau of Mines have identified geologic structures in mine roof rock that contribute to 

many roof falls in Appalachian coal mines. These structures, 

including paleo-channels, kettlebottoms, scours, pinchouts, 

slickensides, clay veins, crevasse splays, and joints, can 

often be identified during, and sometimes before, mine 

development. Mine projections can be revised to reduce the 

adverse effects of discontinuities in roof structure, large 

roof areas of laminated sandstone or incompetent strata 

generally can be delineated or inferred from exploratory 

drill-hole data, and the need for supplementary support can 

be anticipated. Accurate descriptions of roof geology also 

provide some indication of optimum length and type of roof 

bolts that should be installed. 

An instructive example of the geologist's role was described 

by Horne and others (1978). A coal bed was found to be split 

above and below by a channel sand. Mining followed the lower and 

thicker split, where the roof was composed of channel-margin 

sediments and severe roof falls were encountered. Advances were 

made three different times before a geologist was consulted, 

recommending driving through the upper split because of better 

roof conditions and in spite of the mining engineer's deeply 

rooted aversion to mining rock. 

59 
9 

8 

5 

4 

3 

2 

A u 

A 8 c D 

E F 

::::== IIOPeclll of Anna Shale; numbers 

indicate thickn- in f"t 

~ Major roof falls 

~ Minor roof falls 

• • • Crib 

rv-v-~ Floor heave 

E F 

G 

G 

Figure 14. Distribution of roof falls and their relation to the 

immediate roof strata in west-central Illinois. No 

roof falls occur where Brereton Limestone directly 

overlies the Herrin (No. 6) Coal, although some 

shallow flaking of "clod" may occur locally. Grid 

interval is 200 feet (61 m). (From Krausse and 

others, 1979). 

60 

9 

8 

7 

4 

3 

2 
_,o-

... 

Jll!lllll 

,...... 

• 

0 

ISOSAND CONTOUR("'.) 

FLUVIAL CHANNEL SANDSTONE 

ZONE OF DIFFERENTIAL 

COMPACTION 

PALEOCURRENT DIRECTION 

SIGNIFICANT ROOF FAILURES 

500 1000 1500 

Figure 15. Roof-rock/roof-fall relationships, Utah (from Mercier 

and Lloyd, 1981). 

61 
MYTH NO. 5: FOR UTILITIES, COAL GEOSCIENCE IS THE MINING 

COMPANIES' BUSINESS 

The only generality one can make about utility attitudes 

toward, and technical involvement with, coal geoscience is that 

they span a broad spectrum. The degree of involvement certainly 

swings with market conditions. There is a tendency toward locking 

up supplies through long-term contracts and captive operations 

under sellers'-market conditions and a tendency toward short-term 

contracts and spot purchases, along with selling captive operations 

that have suddenly become bad business, under buyers'-market 

conditions. Accompanying these swings in purchasing patterns is 

an ebb and flow in utilities' involvement with geoscience. 

Vaninetti (1981) has characterized the tradeoffs between 

different purchasing patterns and the associated risks as seen by 

utilities (fig. 16). Individual circumstances have had a lot to 

do with how sensitive utilities are to these different sources of 

risk. For utilities that have long-term contracts and few hitches 

resulting from adverse mining conditions or coal-quality changes, 

coal geoscience is a distant memory, accounted for at the time of 

initial contract selection and negotiation. The situation is not 

quite the same for utilities that have many sources of coal, as in 

much of the midwest, east, and south. Although it is much easier 

for them to replace one supplier with another, there are costs in 

doing so. One utility executive summed up this situation with the 

comment, "You can't burn coal contracts!" Nevertheless, these 

utilities' involvement in applications of coal geoscience is by no 

means uniform or intense. Finally, there are examples in the east 

and west where making do with existing sources of coal--either 

contract, equity or captive--has required much more geoscientific 

information to be developed than was initially envisioned. Once 

the need for this information has been demonstrated (often 

painfully) to these utilities, their expertise and knowledge of 

the value of this information is carried forward into their future 

purchasing activities even as they shift toward shorter term and 

more flexible coal-supply arrangements. 

Institutional considerations also influence utilities' extent 

of involvement in coal geoscience. Knowledge of geologic conditions is much more important to the buyer in a cost-plus contract 

where the costs will automatically be passed through than it is in 

a fixed-price contract where the seller carries the risk (as well 

as the reward). In the latter case, knowledge by the utility of 

geologic conditions may even prove detrimental to their own 

interests, as one utility planner suggested, because it muddies up 

the question of who has knowledge of the risks and, consequently, 

incurs the responsibility for any remedies. Yet, even in this 

case, a minimum of geologic knowledge on the part of the buyer is 

essential when i.nterpretations have to be made about whether 

62 
UTILITY RISK 

SUPPLY AVAILABILITY 

SUPPLY INFLEXIBILITY 

CAPITAL REQUIREMENT 

PRICE INSTABILITY 

· LIABILITY 

LABOR INVOLVEMENT 

INFLATION SENSITIVITY 

MARKET SENSITIVITY 

UTILIZATION UNCERTAINTY 

ENVIRONMENTAL EXPOSURE 

TECHNICAL INVOLVEMENT 

CONTRACT EQUITY OWNERSHIP 

Figure 16. Risks associated with different coal procurement 

methods (from Vaninetti, 1981). 

63 
certain conditions encountered during mining are "acts of God" 

or--another example--whether clauses that pass through the 

unanticipated costs of compliance with regulatory requirements are 

properly invoked. Such clauses might be a convenient mechanism to 

fund more costly mining practices in response to adverse geologic 

conditions. 

The combination of market forces, individual purchasing 

circumstances and experiences, and contractual styles leads to the 

diversity of utilities' current attitudes toward, and awareness 

of, coal geoscience. These factors alone do not lead to any 

particular trend. Another consideration, however, does portend 

continued erosion of the attitude that coal geoscience is just 

mining companies' business: plant performance. 

To an increasing extent, utilities and their regulatory 

agencies are attempting to improve power-plant performance. 

Generating more power, longer, and with lower maintenance costs 

from existing units pays off in postponing costly additions of new 

generating capacity and in holding the lid on rising costs of plant 

operations. The trick has been to achieve desired performance 

levels without sacrificing these economic gains to the higher 

costs of better quality coals. At the same time, utilities have 

been under pressure to hold down their fuel costs, but not at the 

expense of degrading plant performance through using lower quality 

coals and incurring a higher net generation cost. Consequently, 

utilities are in the midst of a revolution, going from purchasing 

coal on a simple basis of dollars per ton or dollars per million 

Btu to determining the appropriate cost in terms of cents per 

kilowatt-hour. There is no simple formula for doing this given 

the variabilities of coal quality, the idiosyncrasies of complex 

engineering systems, and the human dimension. Yet it is easy to 

see how this trend places a premium on thoroughly understanding 

and being able to anticipate coal-quality characteristics. 

What cost savings might come from this? 

o Five years ago an eastern utility estimated that better 

control of sulfur and ash content of coal would improve 

boiler availability by 5 percent. At that time, this 

translated to a savings of $1,500,000 per year on a 

typical 650 MW unit. 

o A western utility estimated 2-3 years ago that for every 

1 percent increase in the coal-ash content above the 

design levels, there was a 1 percent reduction in plant 

availability. This translated to a cost of approximately 

$1 million per percentage point. 

o An eastern utility spokesman pointed out that the cost 

savings on their system from improved coal quality are not 

64 
reflected in any clear-cut changes in operating conditions. 

Rather, he suggested they may be reflected in extended 

plant life. 

o An eastern utility estimates that each point loss in tr~ir 

coal supplies' grindability index is equivalent to a 2(0 

Btu loss in heat content. This is because of curtailments 

due to the inability to feed coal to their boilers at e 

sufficient rate. Systemwide, their use of nondesign g1·ind 

coals is costing them a 10 percent loss in generating 

capacity. Although this loss is currently offset by tl'~ 

lower cost of these coals, the value of that capacity vill 

increase significantly in coming years. 

MYTH NO. 6: UTILITIES KNOW WHAT COALS ARE BEST FOR THEM 

This statement is basically true with a few exceptions. One 

industry-wide exception already mentioned is the difficulty in 

making extremely fine-tuned evaluations of the engineering and 

economic impacts of small changes in the many dimensions of coal 

quality. Other recent and notable exceptions concern the use of 

coals with which the industry has a relatively short track record 

and/or the performance of environmental control technologies with 

which the industry has accumulated much less experience than with 

the basic operations of coal combustion. The reason for citing 

examples of these exceptions is twofold: (1) to demonstrate that 

utilities, boiler manufacturers, and electrostatic precipitator 

manufacturers are fallible (the geology and mining professions do 

not have the only corner on uncertainty); and (2) to suggest that 

there may yet be further change in our understanding of the 

identity of important coal characteristics (some of which we may 

have come to take for granted), particularly as newer technologies 

come into play. 

o An eastern utility purchasing premium low-sulfur coal 

found that the sulfur content was too low to impart a 

necessary charge to the fly ash particles for them to be 

captured effectively by the electrostatic precipitators. 

A higher sulfur coal had to be purchased and blended ~ith 

the premium supplies to achieve acceptable precipitatcr 

operation. 

o A southern utility's first experience with a new coal 

source was that the sodium content was too low, causir~ 

much the same problems as in the previous example. A 

higher sodium coal was obtained from a new mine for a new 

power plant and it was delivered on spec. This time, the 

sodium content was too high and caused serious, unanticipated fouling on the precipitator plates and wires. To 

mitigate the problem, only a fraction of the original coal 

could be accepted and detailed analysis of the sodium 

65 
distribution was required to maintain an acceptable blen1 

of coals. 

o An eastern utility's coal units were designed to burn soft 

coal. In broadening the geographic range of their coal 

supplies over the past 10 years, the Hardgrove Grindability 

Index proved to be an inaccurate guide to coal-milling 

characteristics because of its poor reproducibility. Nor~ 

the utility must perform test burns on all their serious 

candidate coal sources. 

MYTH NO. 7: WITH THE RIGHT TECHNOLOGY, QUALITY VARIATION DOES NOT 

MATTER 

Whatever breakthroughs we may have already made or will yet 

make in combustion technologies, it is clear we will be using th~ 

technologies we've got now for a long time to come. In every 

case, an understanding of coal quality and variation is important 

to designing these technologies at an economic optimum. With 

sufficient knowledge, we might even be able to forego or postponn 

the investment in a technological fix. 

An extreme example of this, which illustrates the role of 

geoscientific techniques and the criterion of economics in 

ultimately justifying a technology, was a coal-cleaning plant 

evaluation for a western underground mine. This evaluation 

involved preparing detailed maps of seam thickness, ash content, 

faulting, roof and floor lithologies, and the mine design (fig. 

17). Mine dilution corrections were calculated and an integrate~ 

picture of run-of-mine ash developed (fig. 18). After all this, 

it was decided a preparation plant was not necessary--at least net 

for the present. A detailed knowledge of the run-of-mine coal 

quality was critical to this determination. 

MYTH NO. 8: THE RESEARCH ISSUES BEHIND ACID RAIN REGULATION 

CONCERN THE ENVIRONMENTAL SCIENCES, NOT COAL-QUALITY 

GEOSCIENCE 

A prodigious amount of research into acid rain, its causes 

and effects is taking place around the country. A hint of the 

mind-boggling complexity of this issue, particularly for determining the payoff of specific mitigation measures, is given in figure 

19. Figure 19 is based on calculations of where an oxygen molecule 

would arrive if released every 2 hours from a central location 

over the course of 1 year. Obviously, source-receptor relationships are difficult to determine, and as a result, a vast effort 

is going into the very tedious job of taking many measurements of 

wet and dry deposition at many sites mainly in the eastern United 

States. 

66 
Figure 17. 

26 ..... ,·: 

rl an.~ 

····· 

ROOF 

ROCKS 

Geologic information contributing to run-of-mine 

coal-quality assessment (proprietary mining-company 

data; details undisclosed). 

67 
Figure 17. (Continued) Geologic information contributing to 

run-of-mine coal-quality assessment (proprietary 

mining-company data; details undisclosed). 

68 
27 

77-27·1 

• 

75·27-1 

• 

74·26·2 • 

74-26·3 • 

26 

76-;(3-2 • 

76·23·1 

• 

ROM 

ASH % 

EC·: 

• 

Figure 18. Expected run-of-mine (ROM) ash content of coal. 

Expected ash content reported in percent to two 

decimal places in the center of each block. 

(proprietary mining-company data.) 

69 
Figure 19. 48-hour destinations of oxygen molecules released 

every 2 hours from a central U.S. location. (R. Husar, 

Washington University, written communication, 1985.) 

70 
Although this research is central to developing the scientific 

rationale for acid-rain mitigation measures, the other side of th~ 

equation--the costs of reducing sulfate and other emissions--has 

not been as thoroughly investigated. Here, geoscientific 

information in the form of a sound understanding of the extent, 

quality, recoverability and costs of low-sulfur coal supplies is 

badly needed. 

The compliance strategy decision dilemma facing utilities 

looks something like the sketch in figure 20. They face a 

choice--exaggerated and simplified in this figure--between 

switching from higher to lower sulfur or cleaned-to-compliance 

coals and installing scrubbers or other, newer technologies. A 

1983 survey of utilities revealed a wide range in their perceptions of how high the premium for low-sulfur coal might go under 

acid-rain legislation (figure 21). Since then, several studies 

focusing on eastern low-sulfur coal availability have indicated 

that a more optimistic view of the low-sulfur coal premium may be 

warranted (table 2). The strongest indicator was the procurement 

experience of Detroit Edison last year, which smoked out bids th~t 

totaled a production of 75 million tons per year of low-sulfur 

coal. All of this came from the Central Appalachian region. 

As encouraging as this experience was, it could reflect a 

number of factors that would undermine its reliability as an 

indicator of long-term supply potential. However, little other 

information is available to resolve this important question other 

than second-hand analyses of earlier studies. 

MYTH NO. 9: THE GOVERNMENT IS PROVIDING FOR PUBLIC INFORMATION 

NEEDS ON THE NATION'S COAL SUPPLIES 

This attitude obtains some support from the fact that the 

coal resources of the United States are enormous. An estimate as 

high as 11.6 trillion tons has been published (Ferm and Muthig, 

1982). A pessimistic estimate of 120 billion tons of steam coal 

recoverable by mining has also been published by Schmidt (1979). 

However, even this very low estimate, an improbable number by all 

accounts, is high enough that neither cries of impending shortage 

nor a call for Congressional scrutiny are likely to emerge in the 

foreseeable future. If having enough resources were all that 

mattered, then a negligible government role would appear 

justified. 

The problem is that the adequacy and urgency of understanding 

coal quality are quite different from concerns over raw tonnage 

levels. Apathy over the latter has no place rubbing off onto the 

former. The significance of coal-quality information to public 

policy became apparent relatively recently with passage of the 

Clean Air Act of 1970. Responding to this need, the U.S. Bureau 

of Mines and the Environmental Protection Agency conducted analyses 

71 
B 

$ 

Figure 20. Example of compliance strategy, decision dilemmas 

facing electric utilities as illustrated by 

probability distributions for two events--A and B. 

The cost of building a flue-gas scrubber might be 

high, but fall into a narrow range, such as event B, 

whereas the costs of switching to a lower sulfur coal 

are less well known giving them a much wider range 

such as event A. In this example there is a finite 

possibility that the costs of switching could exceed 

the costs of scrubbing, although the probabilities 

favor the opposite. 

72 
UTILITIES' ESTIMATES OF LOW-SULFUR COAL PREMIUM 

1983 EEl SURVEY OF ACID RAIN COMPLIANCE STRATEGIES 

15,000 ,...---------------------::::S~cr-ub----, 

12,000 II :~~~~~: ;· .• , .. ,. 

Scrub 

Scrub 9,000 

6,000 

3,0000 , L...----&.;.So!!.;:.cr~u:.;.J.b ____ _......:....:..=...a....&...c..~..__-~~.__.~ :;~~7:~~~- ....... :~ ... ; S.IIC.ow~itc.LL.h __ _..·..::..····; -.. :_i_~:.:· ...... ·_ 

~ 

.. :,:i __-~ .. 'l,.:_.~-_:_-,.i ~ .. 

-

·.· ..... S~w'"'it"c:4.._h__. -$5-$10 -$10-$15 -$15-$20 - $2Q-$30 

Figure 21. Wide range of views of price premium for low-sulfur 

coal provided by 24 utilities responding to Edison 

Electric Institute (EEl) survey, as interpreted by the 

author. 

73 
~ 

~ 

Table 2. CHANGING VIEWS OF LOW-SULFUR COAL AVAILABILITY IN THE CENTRAL APPALACHIAN REGION 

Central Appalachia Production Increases for Coal-Switching Scenarios 

(Estimates in this part of table not comparable because developed for different regulatory assumptions.) 

S02 rollback. 6 8 10 10 

(million tons) 

Production change +34 +51 +78 +35 to 50 

(million tons per year) (Klein, (ICF, Inc., (Klein, (Parker & Thompson, 

1984) 1985) 1984) 1984) 

Conflicting Evidence of Low-Sulfur Coal Availability 

Source 

---

SOHIO, 1981 (Keady and Rimstidt, 1983) 

ICF, Inc, 1981-82 (Klein and Meany, 1984) 

Electric Power Research Institute Workshop, 1983 

(Tennican, Wayland, and Weinstein, 1984) 

Edison Electric Institute Survey, 1983 (National Economic 

Research Assoc., 1983) 

Informal Survey, 1983-84 (Platt, 1985) 

Congressional Research Service, 1984 (Parker and Thompson, 1984) 

Detroit Edison, Bids, 1984 (Tennican, Wayland, and Weinstein, 1984) 

Temple, Barker, and Sloane, Inc., 1984 (Tennican, Wayland and 

Weinstein, 1984) 

Skelly & Loy, Mining block studies, 1984 (Hughes, Gunnett, and 

Rathbun, in press) 

Boulder Exploration Group, Inc., Production capacities, 1984 

(Hughes, Gunnett, and Rathbun, in press) 

12 

+49 

(ICF, Inc, 

1985) 

Outlook 

Pessimistic 

Unclear 

Optimistic 

Mixed, Pessimistic 

Mixed 

Optimistic at mine; 

Pessimistic delivered 

Optimistic 

Optimistic 

Pessimistic, Mixed 

Optimistic 
of the sulfur distribution and washability characteristics of U.S. 

coals in the mid-1970s; and the U.S. Geological Survey (USGS) 

initiated a program of coal sampling and chemical analyses to 

address many of the deficiencies in the existing, coal-quality 

data. Ten years later, it is appropriate to ask what we have 

learned. 

The situation appears to be that current knowledge about 

coal-quality parameters as they relate to coal resources is 

limited by a small number of samples, incomplete characterization 

of coal quality, and an unrepresentative distribution. Most data 

on coal quality refer to mined-out areas, and there is little data 

on the quality of deeper coals yet to be mined. This paucity of 

coal-quality data is reflected in estimates that have been made of 

the number of existing coal-quality samples per billion tons of 

resource (one to five samples), the number of years the USGS 

analytical program would have to continue before the desired 

number of analyses is reached (20 to 40 years), and the number of 

coal samples tested for washability characteristics (600 samples 

by 1981, not many more today) (J.H. Medlin, USGS, oral 

communication, 1984). 

In light of these facts, it is sobering to reflect on the 

course of government programs to characterize coal quality and 

recoverability. This symposium appears to be poised, not at the 

beginning of a Federal and State effort to characterize coal 

resources, but at its end: 

o Historically, the USGS has been the primary source of 

information on in-place coal resources. The Bureau of 

Mines estimated the recoverable resource portion of 

in-place coal. With the creation of the Department of 

Energy, all coal-resource-related work at the Bureau of 

Mines ceased. In the Department of Energy, coalresource-related work dwindled to negligible levels by 

1981. Before that, modest funds had been directed to 

updating resource numbers for several States in 

cooperation with the USGS and State surveys. 

o Historically, the Bureau of Mines carried out a coalwashability testing program. The work maintained momentum 

after the creation of the Department of Energy, largely 

due to the support of the Environmental Protection Agency 

which reached a peak during the 1977-79 period. The 

funding for this program effectively ceased at the end of 

FY 1984. 

Reinstatement or expansion of government's role in characterizing the Nation's coal resources is as much a responsibility cf 

the mining and utility industries as it is of government. The 

private sector's responsibility is to convey to government its 

75 
needs for research and information.1/ These needs do not stop at 

preliminary assessment of coal quantity and quality. They exte:"ld 

to information about coal marketability, recoverability, and 

recovery costs. To communicate these needs constructively, mi~ing 

and utility companies will have to overcome some of their 

traditional distrust of and sense of irrelevance of government 

programs. This symposium is an excellent start to this process. 

CONCLUSION 

The preceding myths span a broad spectrum of activities. No 

group is immune to their influence. Recognizing that these and 

similar myths are real obstacles to the application of coalquality geoscience is important, not only in designing a national 

coal-quality research agenda, but also in winning the public a~d 

private support and cooperation crucial to implementing such an 

agenda. 

REFERENCES 

Buxton, B. E., 1982, Coal reserve assessment--a geostatistical 

case study: Stanford, Calif., Stanford University, MS 

thesis, 150 p., to be published in Vaninetti, G., ed., 

Geostatistics in the coal industry: Electric Power Resear~h 

Institute (in press). 

Cady, G. H., 1915, Coal resources of District I, Illinois: 

Illinois Coal Investigations, Bulletin 10, 149 p. 

______ 1933, The physical constitution of Illinois coal and its 

significance in regard to utilization: Illinois Mining 

Institute Proceedings, p. 95-111, 19 figs. 

1939, Nomenclature of the megascopic description of Illinois ------coals: Economic Geology, v. 34, no. 5, p. 475-494. 

----~1942, Modern concepts of the physical constitution of coal: 

Journal of Geology, v. 50, no. 4, p. 337-356. 

1/several recent reports highlight some of these needs 

through illustrating the deficiencies of existing information. 

Examples are a nationwide overview of coal-supply uncertainties 

that impede determination of future coal price and availability 

(Klein and Meany, 1984); an evaluation of the critical research 

issues underlying the coal market outlook (Tennican, Wayland, and 

Weinstein, 1984); and a methodology for making regional coal 

recoverability and cost estimate,,s (Hughes, Gunnett and Rathbun, 

1985). 

76 
Campbell, M. R., 1903, Recent work in the bituminous coal field of 

Pennsylvania: U.S. Geological Survey Bulletin 213-G, 

p. 270-275. 

1906, Survey work on coal during 1905: U.S. Geological ------Survey Bulletin 285-F, p. 203-210. 

1912, Miscellaneous analyses of coal samples from various ----~ fields of the United States: U.S. Geological Survey Bulletin 

471-J, p. 629-655, tables. 

1917, The coal fields of the United States; general ------introduction: U.S. Geological Survey Professional Paper 

100-A, p. 1-33, illus., tables, map. 

Cecil, C. B., Stanton, R. W., Dulong, F. T., Neuzil, S. G., 

Ruppert, L. F., and Pierce, B. S., 1985, Paleoclimate 

controls on late Paleozoic sedimentation and peat formatior 

in the Central Appalachian Basin: International Journal of 

Coal Geology, v. 5, p. 195-230. 

Cecil, C. B., Stanton, R. W., Dulong, F. T., and Renton, J. J., 

1982, Geologic factors that control mineral matter in coal, 

in Filby, R. H., Carpentry, R. S., and Ragain, R. C., eds., 

Atomic and nuclear methods in fossil energy research: New 

York, Plenum, p. 323-335. 

Cecil, C. B., Stanton, R. W., Neuzil, S. G., Dulong, F. T., and 

Ruppert, L. F., 1983, Paleoclimatic controls on the 

occurrence and quality of coal, in Cronin, T. M., Cannon,~. F., 

and Poore, R. Z., eds., Paleoclimate and mineral deposits: U.S. 

Geological Survey Circular 822, p. 40-42. 

Currens, J. C., 1981, Quality characteristics of the Upper Elkhorn 

No. 3 and Fire Clay coal beds, in Coal and coal-bearing rocks 

of Eastern Kentucky--Annual Geological Society of America 

Coal Division Field Trip, November 5-7, 1981: Lexington, ry., 

Kentucky Geological Survey, p. 94-105. 

Donaldson, A. C., Renton, J. J., Kimutis, Robert, Linger, Daniel, 

and Zaidi, Mohammed, 1979, Distribution pattern of total 

sulfur content in the Pittsburgh coal, in Donaldson, A. C.,. 

Presley, N. M., and Renton, J. J., eds,-carboniferous Coal 

Guidebook: West Virginia Geological and Economic Survey, 

Bulletin B-37-3, v. 3, p. 143-183. 

Eyster, J. M., Klein, D. E., and Walton, D. R., 1980, Coal 

resource information--bibliography: Electric Power Research 

Institute EA-673, v. 2, part 3. 

77 
Ferm, J. C., and Muthig, P. J., 1982, A study of the United States 

coal resources: Jet Propulsion Laboratory Publication 82-14 

and DOE publication DOE/ET-12548-15. 

Ferm, J. C., and Mathew, D., 1981, Impact of new geologic concerts 

on resource and reserve estimates: paper presented at 

Electric Power Research Institute Workshop on Applied Coal 

Geoscience and the Electric Utilities, Austin, Texas 

(unpublished manuscript). 

Ferm, J. C., and Staub, J. R., 1984, Depositional controls of 

mineable coal bodies: Spec. publs. International Association 

of Sedimentology, 7, p. 275-289. 

Fisk, H. N., 1944, Alluvial valley of the lower Mississippi River: 

Vicksburg, Miss., Corps of Engineers, U.S. Army, 89 p., 

33 pl. 

Frazier, D. E., and Osanik, A., 1969, Recent peat deposits Louisiana 

coastal plain, in Dapples, E. C., and Hoskins, M. E., eds., 

Environments of-coal deposition: Geological Society of 

America Special Paper 114, p. 63-83. 

Horne, J. C., Ferm, J. C., Caruccio, F. T., and Baganz, B. P., 

1978, Depositional models in coal exploration and mine 

planning in Appalachian Region: American Association of 

Petroleum Geologists Bulletin, v. 62, no. 12, p. 2379-2411. 

Hughes, W. R., Gunnett, J. W., and Rathbun, L. S., Reserves and 

potential supply of Appalachian low-sulfur coal: Electric 

Power Research Institute RP2369-50, in press. 

ICF, Inc., 1985, Analysis of sulfur dioxide and nitrogen oxide 

emission reduction alternatives with electricity rate 

subsidies, for Acid Rain Roundtable, 230 p. 

Jeran, P. W., and Jansky, J. H., 1983, A guide to geologic 

features in coal mines in the Northern Appalachian Coal 

Basin: U.S. Bureau of Mines Information Circular 8918, 16 p. 

Journel, A. G., 1986, Geostatistics for the coal industry--the 

state of the art, [22 p.], ~ Vaninetti, G., ed., Geostatistics 

in the coal industry: Electric Power Research Institute, in 

press, 250 p. 

Keady, F. D., and Rimstidt, D. L., 1983, Prospects for coal 

development, in Selected papers on fuel forecasting and 

analysis: Electric Power Research Institute Report EA-301~, 

284 p. 

78 
Kentucky Geological Survey, 1981, Coal and coal-bearing rocks of 

eastern Kentucky--Annual Geological Society of American Coal 

Division Field Trip, November 5-8, 1981: Lexington, Ky., 

Kentucky Geological Survey, 169 p. 

Kim, Y. C., Martino, F., and Chopra, I. K., 1980, Application of 

geostatistics in a coal deposit: Paper presented at American 

Institute of Mining·, Metallurgical, and Petroleum Engineer"' 

(Society of Mining Engineers) Annual Meeting, Reno, Nevada, 

Preprint 80-90. 

Klein, D. E., 1984, Lower sulfur coals as a means of reducing 

sulfur-dioxide emissions: First International Conference on 

Acid Rain, Regulatory Aspects and Engineering Solutions, 

28 p. 

Klein, D. E., and Meany, D. P., 1984, Effects of resource 

depletion on future coal prices: Electric Power Research 

Institute Report EA-3733, 116 p. 

Knudsen, H. P., Baafi, E. Y., and Kim, Y. C., 1980, Use of 

conditional simulation in underground coal mine planning: 

Paper presented at American Institute of Mining, Metallurgical, 

and Petroleum Engineers (Society of Mining Engineers) Fall 

Meeting, Minneapolis, Minn., October 22-24. 

Krausse, H.-F., Damberger, H. H., Nelson, W. J., Hunt, S. R., 

Ledvina, C. T., Treworgy, C. G., and White, W. A., 1979, &~9f 

strata of the Herrin (No. 6) coal member in mines of 

Illinois--their geology and stability: Illinois State 

Geological Survey Minerals Note 72, 54 p. 

Mann, Charles, Manning, Susan, Hogan, William, Smith, D., 1985, 

Integrated fuels and investment planning: Electric Power 

Research Institute Report EA-4166, 108 p. 

Mercier, J. M., and Lloyd, T. w., 1981, Geologic evaluation of a 

central Utah coal property, Wasatch Plateau, Emery County, 

Utah: Utah Geological and Mineralogical Survey, Special 

Studies, 54, p. 33-44. 

Moebs, N. N., 1985, Mine design and ground control: World Mining 

Equipment, v. 9, no. 1, p. 10-13. 

National Economic Research Associates, 1983, A report on 

the results from the Edison Electric Institute study of the 

impacts of the Senate Committee on the Environmental and 

Public Works Bill on acid rain legislation S-768: Edison 

Electric Institute, Washington, D.C. 

79 
Parker, L. B., and Thompson, D. A., 1984, Acid rain legislation 

and the future of the eastern low-sulfur coal industry: U.S. 

Congress, Congressional Research Service Report 84-89, 104 p. 

Pierce, F. W., Kent, B. H., and Grundy, W. D., 1982, 

Geostatistical analysis of a 113-billion ton coal deposit, 

central part of the Powder River basin, northeastern Wyoming, 

in Gurgel, K. D., ed., Proceedings, fifth symposium on the 

geology of Rocky Mountain coal: Utah Geological and 

Mineralogical Survey Bulletin 118, p. 262-272. 

Platt, Jeremy, 1985, Informal survey of fuel concerns of 24 utilities, 

December 1983 - January 1984, in Mann, Charles, Manning, Susan, 

Hogan, William, and Smith, D.,-eds., 1985, Integrated fuels and 

investment planning: Electric Power Research Institute Report 

EA-4166, 108 p. 

Rendu, J. M., 1982, Application of geostatistics to coal evaluation, 

in Gurgel, K. D., ed., Proceedings, fifth symposium on the 

geology of Rocky Mountain coal: Utah Geological and 

Mineralogical Survey Bulletin 118, p. 251-261. 

Renton, J. J., and Donaldson, A. C., 1979, Prediction model for 

compositional changes within coal from core data, 12th 

Quarterly Report, DOE Contract EY-76-5-05-5065, 58 p. 

Schmidt, R. A., 1979, Coal in America--An Encyclopedia of 

Reserves, Production and Uses: N.Y., McGraw-Hill, 458 p. 

Tennican, M. L., Wayland, R. E., and Weinstein, D. M., 1984, 

Agenda of critical issues--coal price and availability: 

Electric Power Research Institute Report EA-3750, 50 p. 

Tewalt, S. J., Bauer, M.A., Mathew, David, Roberts, M.P., 

Ayers, W. B., Jr., Barnes, J. W., and Kaiser, W. R., 1983, 

Estimation of coal resources in Texas Gulf Coast, Ohio 

Northern Appalachian, and Wyoming Powder River Basins--a 

comparison of statistical approaches: Texas Bureau of 

Economic Geology Report of Investigations 136, 137 p. 

Vaninetti, G. E., 1981, Technical considerations of coal supply 

procurement: paper presented at Electric Power Research 

Institute Workshop on Applied Coal Geoscience and the 

Electric Utilities, Austin, Texas: Electric Power Research 

Institute (in press). 

Wanless, H. R., 1950, Late Paleozoic cycles of sedimentation in 

the United States: International Geological Congress, 18th, 

Great Britain, 1948, Report, pt. 4, p. 17-28. 

80 
Warwick, P. D., Flores, R. M., and Ferm, J. C., 1984, Alluvial 

model for Eocene Wasatch Formation Coal, Power River Basin, 

Wyoming [abs.]: American Association of Petroleum GeologiFts 

Bulletin 68,7, p. 953. 

White, D., and Thiessen, P., 1913, The origin of coal: U.S. 

Bureau of Mines Bulletin 38, 390 p. 

Williams, E. G., and Keith, M. L., 1963, Relationship between 

sulfur in coals and the occurrence of marine roof beds: 

Economic Geology, v.58, p. 720-729. 

81 

COAL QUALITY AND POWER-PLANT PERFORMANCE 

by 

Michael P. Heap 

Energy and Environmental Research Corporation 

INTRODUCTION 

Coal is a generic term referring to a family of solid fuels 

that varies widely in both composition and physical characteristics. Although it does contain hydrocarbons, sulfur, nitrogen, 

oxygen, and most inorganic elements, these are not distributed 

uniformly. Ideally, the suitability of a coal for use in power 

generation should be based upon its type and rank. However, the 

correlation between coal rank, type, and combustion properties is 

tenuous, necessitating the use of empirical relationships which 

apply to specific applications and are based upon the "quality" of 

coal. Rank and type are fundamental properties of coal, but 

quality is an economic value established by the relationship 

between these fundamental properties and the specific process 

application. For example, a high-quality coal for power 

generation need not, and most probably will not, be a high-quality 

coal for coke production. 

High interest rates, increased construction costs, and 

reduced demand for power emphasize the need for the utility 

industry to maximize the utilization of existing emhedded capital. 

Consequently, any reduction in power-plant availability because of 

coal quality must be avoided. However, Blackmore (1980), Anson 

(1977), and Phillips and Cole (1980) have presented evidence 

indicating that the performance of existing power plants has 

deteriorated steadily in recent years. Nationally, the availability of generating units fell from 78 to 63 percent over the 

10-year period from 1968 to 1978. Blackmore argues that this 

deterioration is linked to coal quality because the average Btu 

level of coal delivered also decreased from approximately 11,750 

Btu to 10,600 Btu. Blackmore used an 800 MW unit in the American 

Electric Power system to demonstrate that this national trend 

applies to specific units. Figure 1 shows that the availability 

of this unit parallels closely the Btu content of the coal being 

fired. However, as illustrated in figure 2 (also due to 

Blackmore), Btu content is not the sole coal-related factor 

affecting availability. A comparison of two units of the same 

size, design, and age indicates that the unit fired with a coal 

83 
94 

88 

~ 

-·-

·-

~ 82 ttl 

-·-

ttl 

> 

<C 

~ 76 

70 

~ 

-·-

·-~ 

ttl 

-·-

ttl 

> 

< 

~ 

100 

95 Unit A 

90 

85 

80 

75 

70 

1971 1972 1973 1974 1975 

Year 

13~000 

12,500 

12,000 

11,500 ~ 

-

""" ::s 

.j..) 

11,000 c:c 

10,500 

10,000 

Figure 1. Availability versus heat content of one 800 MW Unit in 

the American Electric Power system (Blackmore, 1980). 

Unit A versus Unit 8 

1971 - 1975 

Unit A Unit B 

Ash and 

sulfur 15.2% 19.7% 

Heat 11,810 11,460 

index Btu/lb Btu/lb 

Slagging Low to Ver:· high 

index medium 

Ash fusion More than Les~ than 

temperature 2700°F 2501°F 

Figure 2. Comparison of coal properties and the availability 

of two similar 800 MW Units (Blackmore, 1980). 

84 
which had a greater tendency to slag (lower ash-fusion temperature 

and higher slagging index) had a lower availability. It has been 

estimated (Budder et al., 1981) that a loss of 1 percent availability could cost in excess of $1.5 million per thousand MWe per 

year or approximately 0.4 mills per kWh (averaged over 30 years). 

Consequently, there is considerable incentive to establish which 

properties of coal reduce availability and thereby establish the 

real cost of coal. 

This paper discusses the impact of coal quality on powerplant performance and costs and the influence of coal properties 

on the heat-release processes. 

COAL-QUALITY IMPACTS 

Several investigations of the relationship of coal quality to 

power-plant performance have been conducted by utility companies 

and other organizations. Table 1 shows the results of an analysis 

conducted by Blake and Robin (1982) to evaluate the impact of 

increasing coal-ash content from 15 to 20 percent. The analysis 

was based on a detailed review of internal records as well as 

published reports correlating coal quality with power-plant 

performance and assumed no change in the delivered cost of the 

coal. The largest cost factors were maintenance and ash-pond 

costs, followed by availability loss. The cost impacts on boiler 

efficiency and operation and auxiliary power are much smaller. 

The following sections discuss the methods which can be used to 

calculate the cost impacts of coal quality on the following 

power-plant performance factors: 

o Heat Rate - This includes boiler efficiency and auxiliary 

power. 

o Availability Loss - This includes capacity limitations a~ 

well as component failures leading to partial or full 

outages. 

o Maintenance and Operational Costs - These costs include 

routine repair following equipment failures, and costs for 

scrubber reagents, ash disposal, and so on. 

Coal Quality and Heat Rate 

Coal quality can affect heat rate by changing the boiler · 

thermal efficiency, ,auxiliary power consumption, and turbine cycle 

efficiency (via changes in steam conditions). The key boiler heat 

losses affected by coal composition are the dry flue gas loss, 

losses due to moisture in the flue gas, and losses due to 

incomplete combustion. All are dependent on coal quality. Dry 

flue gas loss is calculated easily given the excess air. However, 

excess air requirements depend on flame stability, carbon burnout, 

85 
Table 1. Evaluation by Southern Company Services (SCS) of tl'~ 

cost impact of increasing coal ash content from 15 to 20 

percent on a utility boiler. The cost impact 

corresponds to 7 percent of the coal cost. (From Flake 

and Robin, 1982). 

Boiler efficiency 

Operation and auxiliary power 

Maintenance 

Availability loss 

Ash pond cost 

Total 

86 

Cost 

($1000) 

148 

67 

957 

529 

905 

2,605 
slagging, and heat-transfer patterns in the furnace and convect1ve 

pass and are difficult to predict with existing correlations. 

Moisture losses are calculated easily by means of standard 

engineering relationships. Incomplete combustion is manifested 

primarily by carbon in the bottom and fly ash. The carbon 

remaining in the bottom and fly ash is due to incomplete oxidation 

of coal char remaining after devolatilization. The dynamics of 

char combustion depend on the coal composition and particle-size 

distribution, the rate of fuel/air mixing, the furnace thermal 

environment, and the amount of excess air. 

Power-plant auxiliaries consume power for coal handling, 

feeding, pulverizing, ash removal, precipitation/scrubbing, and 

air moving (fans). Coal quality affects power consumption for 

most of these components in a straightforward manner (given the 

excess air level), with the exception of the pulverizer. The 

parameter used most often to link coal quality to pulverizer 

performance is the Hardgrove Grindability Index (HGI). Manufacturers have developed empirical relationships which relate coal 

characteristics to pulverizer capacity and power consumption. 

Normally, turbine-cycle efficiency is not considered to be 

affected by coal quality as the steam-cycle components do not 

contact the coal. However, the steam conditions depend on the 

heat-absorption pattern in the furnace and convective pass which 

is affected by coal composition and excess air requirements. 

Changes in the heat distribution may result in an inability to 

achieve superheat or reheat temperatures or require excessive 

attemperation, which can degrade turbine-cycle efficiency 

significantly. 

Coal Quality and Availability 

The costs of availability losses due to coal-quality 

degradation can be many times larger than costs of heat-rate 

increases, depending on a utility's economic situation. In the 

short term, an availability loss at one unit requires the utility 

to operate another unit with a higher net power generating cost. 

In some cases the differential costs will be small; for example, 

if a sister unit can be brought on line. In other cases, the 

utility may need to purchase power or use peaking gas turbines at 

significantly increased cost. In the long term, chronic availability loss will require construction of new units. Thus, the net 

cost of availability loss expressed as the cost of differential 

power can range from essentially zero to several mills/kWh. 

Availability losses are related to many factors including 

plant design, operating and maintenance procedures, and, of 

course, coal quality. Availability losses can be divided into two 

major categories: capacity limitations which are related to 

87 
specific input conditions (such as a mill capacity limitation rlue 

to a low-heating-value coal); and failures which can reduce 

capacity (partial outage) or cause a shutdown (full outage). 

Ideally, capacity limitations should be predictable based on tl'@ 

specific coal characteristics. However, there is considerable 

uncertainty in calculations of capacity limitations, especiallr 

due to an inadequate understanding of the mineral-matter effects 

on phenomena such as slagging and fouling. Availability loss rlue 

to failures includes a certain degree of randomness. For example, 

the specific locations and times of tube failures due to erosion 

or corrosion cannot be predicted currently. Because of the 

probabilistic nature of such availability loss, at present the 

only effective way to correlate it with coal properties is to 

evaluate a data base using statistical techniques. 

Coal Quality and Maintenance Costs 

The relationships between coal quality and maintenance coRts 

are difficult to assess because of three factors: the records 

maintained by utilities, the impact of non-coal-related factor~, 

and plant-design variations. Utilities use a variety of 

procedures to account for maintenance costs in coal-fired units. 

Although these procedures generally meet utility needs, they often 

make it difficult to evaluate coal-quality impacts. For example, 

although the maintenance cost resulting from a tube failure ma:r be 

identifiable, it may not be possible to determine whether the tube 

failure was related to coal quality, water quality, structural 

problems, or other effects. Maintenance costs depend on the 

utility's specific situation as well. If a unit is required for 

power generation, routine maintenance may be bypassed, reducing 

maintenance cost and vice versa. Power-plant components of 

varying design have different maintenance requirements. 

COAL PROPERTIES AND COMBUSTION 

During combustion, chemical energy in the coal is converted 

to thermal energy. The function of the radiant section of the 

steam generator is to provide the equipment to ensure that this is 

accomplished in a safe and efficient manner and the volume to 

ensure that heat is transferred from the combustion products so as 

to reduce ash-particle temperatures to some "safe" level, thereby 

preventing problems due to ash deposition. The fates of three 

coal components during the combustion process have a significant 

impact on efficiency and availability and, therefore, upon the 

cost of power generation. These are carbon, mineral matter, and 

trace organic species (nitrogen and sulfur). 

Coal Char Combustion 

Char is that fraction of the coal which remains after the 

volatiles have evolved from the coal particle. Char burnout is 

88 
usually greater than 99 percent in boilers operated in the United 

States. However, the rate of char combustion influences the 

properties of the fly ash, heat-release patterns, heat-absorption 

patterns, and boiler efficiency. The carbon content of ash 

influences fly ash precipitability because the presence of carbon 

lowers the fly ash resistivity and increases the solids loading. 

The rate of char oxidation affects heat release and absorption 

patterns, primarily because of its impact on ash properties. The 

melting point of most ashes is lower under reducing conditions. 

Thus, an ash particle containing significant quantities of carbon 

will have more probability of producing molten ash particles. In 

addition, if carbon is present on wall deposits, depletion of 

available oxygen promotes the formation of a molten deposit 

(slagging). 

Mineral Matter 

Mineral matter in the coal is converted to ash during the 

combustion process. Many of the availability problems associated 

with coal quality in the steam generator relate to the fate of 

coal mineral matter and involve three closely related phenomena: 

slagging, fouling, and corrosion. The mechanism of slag formation 

is not well understood. A simple heat-transfer analysis shows 

that heat flux to the walls of a typical modern utility furnace 

covered by a thin layer (on the order of 1 mm) of powdery ash can 

result in a temperature drop of approximately 1000°F. If conditions are such that ash particles reach the furnace wall in a 

molten or sticky state, and if they wet the wall surface or 

otherwise adhere, the temperature of the surface exposed to the 

flame will increase. Thus, for slagging to occur, it is necessary 

that ash particles of the appropriate composition be transported 

and adhere to the furnace wall. If the surface temperature rise~ 

beyond the melting point, then the deposit layer begins to flow. 

The formation of fouling deposits on superheater tubes also 

requires that particles of particular composition be transported 

to the tube surface and adhere. The difference between slagging 

and fouling is that fouling is normally considered to take place 

because of a build-up of dry deposits. However, both phenomena 

are associated with the composition of the coal ash contacting tl'~ 

solid surface. 

Many indices based upon coal properties have been calculated 

to assess the potential of coals to slag, foul, and corrode 

furnaces and superheater tubes. The Electric Power Research 

Institute (EPRI) is currently conducting a study to develop an 

improved understanding of the knowledge of slagging and fouling as 

affected by coal characteristics, boiler design, and operating 

conditions. As part of this study, a 24-page questionnaire was 

circulated to utilities to solicit information on the frequency of 

problems resulting from slagging and fouling. During the initial 

statistical analysis, the relationships commonly used for slagging 

89 
and fouling were examined. Figure 3 compares the frequency of 

slagging by plotting slagging indices as a function of steam 

generation per unit plan area for the coal being fired. The 

slagging factor is that used by Babcock and Wilcox and is defined 

as the base to acid ratio (calculated based upon American Society 

for Testing and Materials ash properties} multiplied by sulfur 

content. The boundaries between the regions were drawn 

empirically to maximize the number of points located with corre~t 

areas. Using the boundaries shown, 61 percent of the data points 

are located within the correct areas. However, it should be noted 

that for any given steam flow per plan area, there are examples of 

boilers with rare and frequent problems with very similar slagging 

factors. The initial results from this EPRI study indicate that 

the slagging frequency of many boiler/coal combinations can be 

accurately categorized using almost any of the parameters reported 

in the literature. Also, some combinations appeared to be 

impossible to categorize properly using any of the recognized 

parameters. 

The limited success of slagging, fouling, and corrosion 

indices in correlating coal performance in field-operating systems 

is probably due to the comple~ity of the process. As the indices 

used to assess slagging, fouling, and corrosion potential are 

based upon analysis of coal samples, they fail to take account of: 

o The heterogeneity of the coal and mineral-matter mixture 

that is being fired. 

o The relationship of mineral forms to each other and the 

variation in mineral composition of the individual coal 

particles. 

o The mechanism of particle transport. 

o Selective deposition within the furnace. 

o Variation of compositio~ of the deposit as a function cf 

time. 

o The strength of the deposits and the ease of removal by 

soot blowing. 

o The influence of operating and design variables on 

properties other than furnace exit temperature. 

o Reactions of ash particles with vaporized mineral mattE.r 

which could occur prior to deposition on the walls. 

o Interaction of ash particles in the free stream, which 

could form low-melting point eutectics. 

90 
3~------~------~~~--~~------~------~--

0 Rare 

6 I 0 Occas iona 1 

0 Eb 0 

l:::l Frequent 

2 

S- 6 :::::5 X4- 6 (]).....-

""0:::::5 

CV) 

......... 

X 

0~0 6 en 

c-o 0 •r- .,... 

cnu 0 0 

C')c:( 

~ .......... 1..0 r-(]) lr- 1--J (/)VI 

~ 0 

co 

Q]\o~ 0 

0 

Ol ~ I .o Q) ....,- I~ .. , 

0.8 1 1. 2 1. 4 1. 6 1.8 

Steam Flow Per Plan Area 

in 103 lbs/hr-ft2 

Figure 3. Slagging frequency (Barrett, 1983). 
Efforts have been made to overcome some of these difficulties 

by evaluating the characteristics of portions of the mineral 

matter and coal ash. This involves separating the coal into 

several specific gravity fractions and examining the character~ 

istics of the various gravity sink fractions. Research at 

Combustion Engineering indicates that the slagging potential of 

coals can be correlated with the iron content of ash for the 2.9 

specific gravity sink fraction. Iron (as Fe203) contents of mere 

than 70 percent indicate a coal that has severe slagging potential. 

American Electric Power, on the other hand, correlates the 

slagging potential of run-of-mine and washed coal based on the 

following whole coal characteristics: 

o Pounds of ash per 106 Btu, as received, base to acid 

ratio, and 

o Ash softening temperature. 

There is some disagreement as to whether the total quantity 

of ash influences the slagging potential. Intuitively, it would 

appear that problems due to ash deposition would be greater for 

larger quantities of ash. 

Nitrogen and Sulfur 

Two of the organic trace species present in coal create 

environmental problems and thereby influence power costs. An 

efficient combustion process converts nitrogen and sulfur present 

in the coal to nitrogen and sulfur oxides. Sulfur is contained 

both in the organic matrix and as part of the mineral matter and 

is readily converted to S02, which is normally removed from the 

combustion products by flue gas scrubbing equipment. However, if 

the coal mineral matter contains alkalies, some of the sulfur 

forms alkali-metal sulfates and is retained in the fly ash. 

Nitrogen contained in the coal can be oxidized to nitric oxide. 

However, the conversion efficiency to nitric oxide is dependent 

upon the availability of oxygen, particularly in the early stages 

of combustion, because under fuel-rich conditions, nitrogen 

species can be converted to N2. Those coals containing higher 

quantities of volatile nitrogen are most likely to produce higher 

levels of NO under normal conditions. 

SUMMARY 

Coal quality can have a profound impact on the performance of 

coal-fired power plants and there is a need to establish 

relationships which allow coal quality to be related to the cost 

of power. Improved methods of coal characterization are required 

that define the fate of mineral matter during combustion as a 

function of plant design and operating conditions. 

~2 
REFERENCES 

Anson, D., 1977, Availability pattern in fossil-fired steam pow~r 

plants: Electric Power Research Institute Special Report 

FP-583-SR. 

Barrett, R. E., Murin, J. M., Mack, G. A., and Dimmer, J.P., 

1983, Evaluating slagging and fouling parameters: presented 

at the Fall Meeting of the American Flame Research Committee, 

October 4, 1983, Akron, Ohio. 

Blackmore, G., 1980, Some current comments on coal by an electric 

utility: presented at American Electric Power Service 

Company Conference, February 8, 1980, Lancaster, Ohio. 

Blake, M. W., and Robin, T. T., 1982, Coal quality influence on 

operating plant cost: 1982 Conference on Reliability for the 

Electric Power Industry, Portland, Oregon. 

Budder, M.K., Folz, D.J., Goodman, T.O., and Sybert, L., 1981, An 

impact of coal-cleaning cost of new coal-fired power 

generation: Electric Power Research Institute Report 

CS-1622. 

Phillips, P. J., and Cole, R. M., 1980, Economic penalties 

attributable to ash content of steam coals: Mining 

Engineering, v. 32, no. 3, p. 297-302. 

93 

THE WHY AND HOW OF COAL-QUALITY RESEARCH 

IN THE U.S. DEPARTMENT OF ENERGY 

by 

Richard E. Harrington 

U.S. Department of Energy 

I'm very pleased at the opportunity to participate in thir 

Symposium on Coal Quality. There is a close scientific relatic~­

ship between the work of the U.S. Geological Survey and the U.f. 

Department of Energy (DOE}, and this is particularly true in tre 

area of fossil energy. Here we are dealing with the same fossjl 

energy materials, and we have mutual interest and concern about 

the properties that determine their quality. 

I have been asked to talk about the DOE research relating-to 

coal quality. I could easily use all my time telling you about 

what we are doing to clean and prepare coal to optimize its 

performance in combustion equipment, minimize its impact on th~ 

environment, and extend its application. But, most of you knolT 

all that. Besides, you will be hearing later from specialists in 

these areas. Let me instead talk to you about one specific aspect 

of our work that, by its nature, requires major coal quality 

research. I'll start with the "why" of this research area. 

During the latter half of the 19th century, coal graduall:r 

displaced wood as the major energy form fueling the industrial 

revolution. By the turn of the century and for nearly three 

decades into the 20th century, coal reigned as the major fuel form 

supplying all of the major energy use sectors. It was not until 

the mid-1920's that petroleum, spurred primarily by the advent of 

the automobile, began to capture a significant percentage of 

the total energy market. As oil production increased and prices 

fell to as low as 10 cents per barrel in the following years, coal 

began to seriously lose ground in all but the electric utility 

sector. With the concurrent growth of natural gas usage and the 

convenience of both oil and gas, coal sales in the nonutility 

markets plummeted. The result was that over the past 50 years, 

the coal industry has gone from a position of being the Nation's 

energy-supply industry to the current position of being the 

utility industries' primary energy supplier. No longer is coal 

used to heat water, homes, apartment buildings, offices, 

warehouses, stores, hospitals, and the like. In short, coal has 

lost out in the residential, commercial, and light industrial 

95 
sectors. In retrospect, this loss of market was a major factor, 

along with growing transportation fuel requirements, that has led 

to our current dependence on oil (much of it foreign) and our 

major imbalance in fuel use as compared with our resource base. 

However, it also defines an opportunity for the coal industry. 

It is an opportunity to recapture a major fraction of over 2S 

quads (excluding transportation) of the Nation's 80 quads of 

energy consumption. If coal could capture 2S percent of this 2.S 

quad fraction, it would represent a SO percent increase in the 

U.S. coal consumption. Any movement in this direction would 

improve our national security and fuel-use balance. 

Let's take a closer look at the anatomy of this opportunity. 

First, it is made up of a multitude of small users who use energy 

in a relatively limited number of ways, and it is far different 

from the electric utility supply sector. The two most important 

opportunities for coal in this sector are for use in water heating 

and space heating. 

In order for coal to penetrate the light industrial, commercial, and residential markets, four conditions are required: 

1. An assured supply of coal. 

2. A desire by the customer to use coal rather than oil or 

gas; that is, a financial incentive and adequate fuel 

quality. 

3. A coal delivery and ash management infrastructure. 

4. A catalog of competitive coal-use technologies, primarily 

furnaces and water heaters. 

The first condition, an assured coal supply, is no problem. 

The capability to supply almost any increased demand up to the 

full requirement of these sectors now exists. The second 

requirement, a customer desire to use coal, that is, primarily an 

economic incentive, is satisfied by the fact that a major 

advantage of coal over oil and gas is that it can be delivered to 

most places at a cost of from 30 percent to SO percent of its 

competitors. Environmental-quality requirements must also be m~t 

by either improved coal quality or applicable pollution-control 

technology. The third condition, the need for a fuel supply and 

ash management infrastructure, is not likely to be a problem. If 

the economic demand develops, this infrastructure will appear. 

Here again, coal quality could be a factor in relation to ash 

management. 

The main problems arise with the last item. Coal-use 

technology has not kept pace with oil, gas, and electric-use 

96 
technology. As a result, there are almost no modern technologier 

in the fuel-use areas required by these use sectors. Even more 

important, there is practically no technology base or cadre of 

expertise in this area. It will take time to build a competitivn 

position for coal. It is possible, however, to translate much of 

the gas and oil technology directly to coal systems and possibly 

take advantage of some of the foreign expertise that has continu~d 

to develop. Nevertheless, a great opportunity exists for coal to 

get back into areas now dominated by gas and oil--successful 

penetration could easily double the use of coal in the United 

States. This is the "why" DOE is pursuing research in this area, 

and why coal quality is an important part of that R&D. 

Now let's consider the "how." 

A good description of the U.S. reaction to the energy crisis 

of the early 1970's was that we "jumped on our technological horse 

and rode off in all directions." After a decade and several 

billion dollars later, I'm afraid the world changed around us more 

than we have changed the world--but we are much smarter. 

Among the things we learned is that, technically, we can make 

synthetic natural gas and liquids from coal, but we can't afford 

the products. They cost from two to five times the price of 

naturally occurring gas and petroleum. Another thing we learned 

was that the quality and performance specifications for coalderived gas and liquids are set by the-petroleum-based products 

they are trying to emulate. This is because our energy-conversion 

machines, such as gasoline and diesel engines, turbines, boilers, 

furnaces, water heaters, and so on, have been developed to use 

petroleum products. 

If we are to make progress in the area of developing coalderived fuels, we must first recognize that there is nothing 

sacred about the petroleum-based fuel forms. The quality and 

specifications of these petroleum fuels are as they are only 

because they have been optimized to fit their energy-conversion 

machines and, conversely, the energy-conversion machines have been 

optimized to the unique properties of the available petroleum 

fuels. Couldn't these petroleum-based fuels and their energyconversion machines just as well have been optimized to different 

specifications? Of course they could and they were. This has 

given rise to such fuel and machine combinations as highcompression gasoline engines; diesel-fueled diesel engines; 

turbines that use fuels that range from distillate through 

residual fuels; gasoline heaters/lights; kerosene heaters/lights; 

and so on. Why, then, couldn't coal-derived fuels and machines be 

developed if it were economically and strategically desirable tc 

do so? Again, the answer is, not only is it possible, it has b€~n 

done. Coal-oil fractions and even powdered coals were used for 

97 
all kinds of heating and engine systems long before petroleum 

forced them from the marketplace. 

Of course it can be done, technically, but can it be done 

economically now that the price of oil is several times the price 

of coal? Again the answer is yes. We recently did a study in 

which we compared the life-cycle cost of various coal-derived f·,el 

forms. Costs for a number of processes ranging from the direct 

use of coal through coal liquefaction were adjusted to a common 

basis. When we compared the results (fig. 1), there were really 

no surprises--the general rules applied that (1) the higher the 

process capital cost, and (2) the more work that is done on the 

coal, the more costly the product. Because of our inability to 

put all studies on a common basis, the absolute values of the cost 

of products should not be taken too seriously. What is important 

is that the trends and relative costs are about right and that 

clearly some of the coal-based products are much less costly than 

the "premium" petroleum-based products. If energy-conversion 

machines were developed and optimized to the specifications of 

coal-derived fuel forms, it is likely that they could economically 

displace the petroleum products. This is not an argument for a 

return to coal stoves, coal pyrolysis, and coal-oil products 

(although many of these need to be reconsidered). Rather, it is a 

call to the scientific and coal community to recognize that ver~r 

little new work has been done during the past 50 or so years in 

the coal-science areas except for that which has been directed 

toward trying to make coal-derived fuel forms look like petroleumbased products. It is also a reminder that coal is capable of 

producing an almost infinite variety of products, many at low 

costs that could potentially be used as unique fuel forms. 

Coal liquid mixtures (CLM) are an example of a new commercf.al 

form of coal fuel which has achieved a level of acceptance and 

success when used in appropriate energy-conversion machines. 

In its current application as a boiler fuel, CLM quality 

requirements need not be very high because most applications will 

be equipped with dust collectors to control ash. To expand the 

application of CLM to the nonutility sectors such as commercial 

and residential applications, however, will require much higher 

quality or highly beneficiated coal. In its extreme applicatior, 

CLM would be used as a fuel for internal combustion engines. 

Quality standards for these fuels must approach those of petroleum 

fuels. Obviously, as the quality of CLM fuels improves, the coFt 

of their preparation increases, approaching the price of petrol€~.m 

products. 

As we have already observed, fuel-use machines have been 

optimized to the quality and specifications of existing petroleum 

products. And, as we have also observed, different machines caD 

accommodate fuels of different quality levels and different 

98 
.... 

z 

w 

~ 

w 

cc 

5 

0 

w 

a: 

w 

0 

a: 

Q. 

13 

:::l 

0 

0 

a: 

Q. 

a: 

<t 

w 

> 

.... 

Cl) 

a: 

u: 

20 

18 

16 

14 

12 

10 

I 

• 

2 

0 CWNING PLANT PRODUCT 

0 LIQUID PYROLYSIS PLANT PRODUCT 

A GASIFICATION PLANT PRODUCT 

• LIQUEFACTION PLANT PRODUCT 

CLIANINO 

LIQUEFACTION 

0 ____ ._ __ ~--~----._--~--------~--~--_.----~--~--,--'----

0 2 • 8 10 12 14 16 11 20 22 24 

PLANT CAPITAL COST ESTIMATE (1982 t/MMBTU INPUT/YEARl 

Figure 1. Cost of various coal-derived fuel forms. 

99 
specifications. The job then becomes one of adapting the 

appropriate machine to accommodate the different fuel forms and 

different operating conditions. Fortunately, most of our machires 

are readily adaptable over wide ranges of fuel and operating 

conditions. Examples include diesels that run on powdered coal 

(the fuel which diesels were originally invented to use); 

distillate, residual, vegetable, and other oil; as well as natu1·al 

and coal gas. 

The key point that we should keep in mind is that we are not 

bound to energy-conversion machine designs or operating conditions 

that are the results of their having been optimized with 

petroleum-based fuels. Our research and development objectives in 

this area, therefore, are to adapt and optimize energy-conversion 

machines to permit the use of coal-derived fuel forms, thereby 

displacing oil and gas with coal. 

It is important that we keep in mind that we will not 

displace oil and gas with coal quickly even when we have 

attractive technical alternatives in hand. This is probably a 

blessing in disguise. As scientists, politicians, suppliers, 

processors, and users, we would like to see developments adopte~ 

quickly, but this is almost never achieved without great cost. We 

cannot afford to lightly scrap the national inventory and capital 

investment we have in our energy-conversion machines in favor of a 

new technology. So we see that the timeframe for the introduct:f.on 

of new technologies is consistent with the timeframe that will 1'~ 

required for stepwiseevolutionary development with the necessary 

attention to coal and product quality. While this helps provid~ 

perspective regarding the patience we will need once options ar~ 

in hand, it also gives rise to a sense of urgency for getting or 

with the job of developing these options. 

There is no reason why coal must be dirtier than oil for tl'o. 

u~er, or why it should be more difficult to use, less safe, more 

complex, or require a more costly first investment. The proble~ 

is that there has been very little R&D support in the United 

States to make it otherwise. Attention to the quality of coal ~nd 

coal-derived products is essential if we are ever to realize th~ 

opportunity for coal to regain some of its position as an energy 

source in the nonutility market. It will take a positive 

commitment and action by government and the people who stand to 

gain by these technologies--the coal industry itself. 

The rationale for DOE's coal-research program is derived, 

at the highest level, from the National Energy Policy Plan whicr 

calls for a balanced and mixed-energy resource system and data c~ 

a suite of technologies from which the private sector, based upc~ 

market forces, can make demonstration and commercialization 

decisions suiting their needs. The program further derives fro~ 

the Office of Fossil Energy strategy which calls for, among other 

100 
things, the increased utilization of coal in an environmentally 

acceptable manner and the development of technological options for 

the utility use of coal if needed to meet the potential electricutility-capacity shortfall of the 1990's. 

On the basis of this guidance, technological options 

representing significant advances to conventional systems are 

identified, research programs defined and costed for the life of 

the programs and competed against other programs for research 

monies on a year-to-year basis. The competition involves 

consideration of factors such as compliance with national energy 

policies and fossil-energy program objectives, resource require-· 

ments, private cost-sharing available, potential for moving coaJ. 

in new market areas, stage of development, and so on. Of coursn, 

DOE works closely with other Federal agencies, the private sector, 

and the international energy community to ensure that our progrrms 

are potentially useful and do not duplicate the work of others. 

Coal liquid mixtures are clearly in our immediate commercial 

future. This product is a significant step in allowing coal to 

again move into the light industry, commercial, and residential 

markets. But this is only a start. Many more coal and coalderived fuel forms are needed to realize coal's fair share of tl·~ 

energy market. Coal characteristics and quality, as well as thP. 

quality of the coal-derived products, are keys to success of th~se 

energy forms. Some, perhaps most, of the return on these R&D 

investments will be a little (but just a little) beyond today's 

commercial horizon. But we must not forget that the future has an 

insistent way of becoming our tomorrow, our today, and then 

history before we know it. 

101 

COAL QUALITY AS IT RELATES TO 

AIR POLICY ANALYSIS 

by 

Paul Schwengels 

Environmental Protection Agency 

I appreciate the opportunity to participate in this symposium 

on coal-quality data and related research. I will try to provide 

a view of coal-quality data issues from the perspective of airquality policy concerns. This is not a comprehensive overview of 

all the coal-quality research issues of concern to the Environm~ntal 

Protection Agency. I am not technically competent to do that a~d 

am not sure that it would be particularly helpful. What I would 

like to do instead is to briefly discuss the environmental 

policy-making process and illustrate how coal-quality information 

is or could be used in the process. 

I will use the particular policy issue with which I am most 

directly involved--acid deposition--as an example. This policy 

debate is very likely the most important current environmental 

issue related to coal use. I will review the major policy 

questions related to acid deposition and potential control 

measures. To the extent possible, I will suggest where these 

policy questions imply need for coal data. My hope is that these 

suggested general data needs will then be addressed in greater 

detail in the subsequent workshop sessions. 

Before turning specifically to the acid-deposition debate, I 

would like to briefly review the general relationship between coal 

use and environmental concerns. Figure 1 is a graph of historic 

U.S. energy consumption by fuel type. It illustrates that during 

the first half of this century coal was the dominant fuel nationally. In the post World War II period it was rapidly displaced by 

oil and natural gas. However, since the early 1960's, coal use 

has begun to increase again, and this trend is expected to continue. 

Figure 2 is taken from a Department of Energy forecast 

published in October 1983. It clearly shows the expectation of 

significant increases in coal use in the future. The reasons for 

this turn-around have been analyzed widely. Coal is a domestically abundant fuel, and since the oil price shocks of the 197C's, 

it has become attractive relative to oil and gas for both economic 

103 
-en 

-~ 

.w 

= 

z 

0 

-.... 

.... 

~ -· .... 

-

! 

-.... 

! 

V') 

z 

0 

u 

>-

CoO 

a:: 

""' z 

L.W 

.... 

~ 0 

.... -

< z 

80~----------------------------------------

70 ~ 60 l NATURAL 

GAS 

50 

40 

30 

ANTHRACITE 

20 

10 

BITUMINOUS COAL 

WOOD 

o~,~~~~~~~~~~~~~~~~~~~~~~~~~ 

1900 1910 1920 1930 1940 1950 , 960 t 970 1980 

YEAR 

Figure 1. U.S. historic energy consumption by fuel type. 

(Source: Gschwandtner et a1, Historic emissions of 

sulfur and nitrogen oxides in the United States from 

1900 to 1980, U.S. EPA Report No. EPA-600/7-85-009, 

April 1985.) 

104 
U.S. INDIGENOUS ENERGY PRODUCTION 

(Scenario Bl 

1~~------------------------------------------~ 

1 u 90 

, = 

2 

a. 

" 

~ 60 

c 

~ ·c 

, 

ca a 30 

History I Projected 

1960 1966 1970 1975 1980 1985 1990 1995 2000 2006 ~10 

Year 

~Oil C Nuclear 

t:J Gas l:ZI Renewables 

• Coal Solids 

Figure 2. Projected energy production by fuel type. (Sourc~: 

Energy projections to the year 2010, U.S. Dept. of 

Energy Report No. DOE/PE-0029/2, October 1983.) 

105 
and national policy reasons. Clearly, we should be prepared for 

coal use to increase. 

Coal is, in many ways, a more difficult fuel to use, alth~ugh 

technologies are available to deal with its problems. These 

difficulties include a range of potential environmental proble~s 

associated with coal mining, preparation, transportation, and 

utilization. Figure 3 (taken from a 1979 report by the Office of 

Technology Assessment) illustrates the range and complexity of 

environmental issues associated with coal and its impacts on air, 

land, and water resources. 

Coal-quality data or assumptions are important inputs to 

forecasting cost and market penetration of coal in the future. In 

addition, virtually all of the potential environmental impacts of 

coal are sensitive to coal characteristics. Thus, there is a 

close relationship between environmental-quality concerns and the 

need for accurate data on coal quality. As coal use increases in 

the future, the data requirements for environmental analysis will 

no doubt also increase. 

The cnrrent policy debate over acid rain (or acid depositfon) 

provides a good example of the relationship between coal quality 

and environmental analysis. Figure 4 is a simplified diagram 

designed to illustrate the major components of the extremely 

complex acid-deposition phenomenon. Concerns about acid deposJtion are, of course, directly related to possible adverse effects. 

In addition to possible effects on forests and surface waters 

shown in the diagram, acid deposition may cause damage to man-rr~de 

materials, agricultural crops, and human health. 

Problems related to concentrations of acid deposition precursors in the atmosphere, such as visibility degradation, are also 

closely linked with the acid deposition scientific phenomenon and 

its possible policy solutions. In addition, other pollutants, 

such as ozone and heavy metals, may also play a role in the 

potential adverse effects of concern related to acid deposition. 

Thus, a variety of possible effects and causes must be considered 

in evaluating the acid deposition phenomenon. 

Many of these effects are dependent on regional or local 

environmental characteristics such as meteorology or soil type. 

The possibility of adverse effects is greatest in specific 

locations which are environmentally sensitive to acid depositio~. 

To understand the cause of adverse effects and their possible 

remedies, it is necessary to understand the atmospheric transport, 

transformation, and deposition processes, occurring both locally 

and over large regions, which lead to acid deposition in sensitive 

receptor regions. Our understa~ding of the science of acid 

deposition must include a range of emissions of relevant chemical 

substances from both natural and man-made sources. In addition to 

106 
AIR 

Dust 

l 

Polycyclic organic material 

t 

Particles 

\ 

co 

\ 

Sulfur 

compounds 

/ 

Polycyclic 

organic material 

t 

LAND 

I J 

Slurry pipeline 

Home 

Figure 3. Environmental disturbances from coal-related 

activities. (Source: Office of Technology AssessmeDt, 

The direct use of coal, Washington, D.C. 1979.) 

107 

Waste 

disposal 

problem 
TRANSPORT & 

2. TRANSFORMATION 

1. EMISSIONS 4. EFFECTS 

Figure 4. Schematic diagram illustrating major components of the 

acid deposition phenomenon. 

108 
sulfur dioxide (SOz) and nitrogen oxides (NOx), which are the 

principal precursors of acid deposition, other relevant substan~es 

include natural emissions of reduced sulfur compounds, volatile 

organic compounds (or hydrocarbons) from both natural and man-m~de 

sources, heavy metals such as lead and mercury, alkaline dust, and 

ammonia. Volatile organic compounds (VOC) are important precursors 

of ozone and other oxidants, which in turn play a role in converting sulfur and nitrogen oxides to acidic sulfate and nitrate 

in the atmosphere. Also, ozone and its precursors are important 

as alternative or synergistic causal agents for some categories of 

effects, as is the case for heavy metals. Alkaline dust and 

ammonia can act to neutralize acidity in the atmosphere or aftEr 

deposition on land or surface waters. 

Virtually all parties in the policy debate agree that acid 

deposition is related to man-made emissions, particularly in 

eastern North America. Great uncertainty exists over the extent 

of acid deposition, its effects on various categories of receptors 

and the detailed processes which result. The broad policy 

decisions which must be made are whether to control precursor 

emissions, how much and of what pollutants, when to implement a 

control program, where to control, and who should pay for 

controls. 

The current widely varying positions on these issues exist 

for two basic reasons. First, there are very large technical or 

scientific uncertainties about key aspects of the acid-deposition 

phenomenon. In particular, the magnitudes of current and 

potential effects and cause and effect relationships are very 

poorly understood. Second, major economic and regional interests 

would be heavily affected by any control policy (including a 

policy of no control). 

Table 1 summarizes some of the major interests which aff~~t 

the politics of acid rain. In general, Congressional delegations 

quite legitimately represent the major interests of their con~tituents. Regions which have actual or potential adverse impacts are 

in favor of emission controls as soon as possible. Regions ard 

industries which have high emissions are naturally opposed to 

"hasty control action" and sympathetic to cost-sharing optionf', 

whereas regions with few large sources favor a "polluter pays'~ 

approach. 

Within this context of scientific uncertainty and competing 

political interests, several alternative proposals have emerged. 

The range of proposals which have emerged in the Congress is 

illustrated by table 2. Most proposals fall within one of the 

four categories ranging from no controls to reductions on the 

order of 10 million tons. The most recent bill (S. 52) and an 

earlier bill (H.R. 3400) illustrate the major alternatives for 

implementing major reductions. 

109 
Table 1. Congressional positions on acid rain control. 

If coostjtueocy cootajos· 

*Affected areas-lakes, 

forest damage 

* No large emitters 

*No large emitters but 

anticipated high growth 

*Large emitters 

*High sulfur coal producers 

* Low su J fur co a J producers 

110 

Congress ion a 1 de 1 egat ion fav~ 

* Contra l soon, freedom to choose 

expeditious control altern~t1ve, 

po 11ut~r pays 

*polluter pays 

*no emissions cap 

*geographically constrainec 

program 

*More justification through 

research 

*Federal financing of controls 

*Mandatory scrubbing 

*freedom of choice on control 

alternative (i.e.,swltching) 
Table 2. Summary of major legislative alternatives. 

A) ADDITIONAL RESEARCH AND EFFECTS t11TIIATION 

*SEN. BYRD ( S. 454) 

- calls for further resolution of scientific uncertainties through·research before contr1ls 

- provides grants to the states for lake liming and other effects mit1gat1on 

B) LAAlE REDUCTION - FREE TO CHOOSE CONTROLS 

* SEN. STAFFORD ( S.52) 

- 10 million ton 502 control program within 1 0 years within 31 eastern states - allows sources to choose least-cost control measures - likely to result in significant coal switching - polluter pays, requires study of fee system 

C) LAAlE REDUCTION - t1ANDATOAY SCAUBBINI 

*CONe. WAXMAN/SIKORSKI ( H.R. 3400) 

- 10 million ton 502 and 4 million ton NOx control program within 10 years in 48 f•.ates 

- str1kes a comprom1se by requiring scrubb1ng for the 50 largest emitters - allows the remaining sources to choose the least-cost control measure 

-fee system to subsidize scrubbing 

D) PHASE I - EVALUATION - PHASE II 

*SENATORS HUMPHRY AND PROXMIRE ( S. 503 ) 

- reflects the National Governors Association's compromise approach 

- requires an initial 5 mllhon ton reduction within 6 years 

- a three year evaluation period for EPA to assess the results 

- an additional 5 million ton reduction during Phase II, if warranted 

111 
S.52 allows for affected States and industries to choose 

among available control measures to meet their targeted emiss1on 

reductions with the assumption that this will allow for the l€astcost economic solution. The costs are to be borne by the sour~es 

and presumably passed on to their customers. 

H.R. 3400, although calling for roughly equivalent sulfur 

reductions, differs in other ways. To protect mining employme~t 

in the high-sulfur coal regions of Appalachia and the Midwest, 

this bill would require technological controls for most reductions. 

In addition, the bill would spread the cost of controls more 

broadly, using a national tax on electricity generation to help 

pay for the controls. The proposal introduced recently by 

Senators Humphrey and Proxmire adds the concept of spreading 

emission reductions out over two phases. This is a compromise 

approach which has been endorsed by the National Governor's 

Association. 

Another, somewhat different approach has been discussed b·~t 

not yet formally introduced in the Congress. This is the concept 

of requiring emissions reductions from large utility sources as 

they reach a specified age, such as 30 or 40 years. This appr,ach 

is based on a recognition that most sulfur dioxide emissions 

associated with acid deposition come from plants which started up 

prior to the introduction of New Source Performance Standards in 

1971 and that the current trend is toward extending the service 

lives of these high-emissions plants. This control approach w,uld 

require each unit or plant to either retire or meet a more 

stringent standard upon reaching the specified age. 

Major components of the present Administration's policy o~ 

acid rain are outlined in table 3. Acid deposition is recognized 

as a serious environmental problem. Decision on appropriate 

additional action, if any, has been postponed until more info~~ation becomes available. This does not imply that acid rain 

controls are unnecessary or that they are too expensive, but only 

that it is premature and unwise to make a decision limited by our 

current understanding. Additional scientific information is 

needed to make a prudent choice regarding the best course of 

action. As stated in recent Congressional testimony, "when the 

fundamental scientific uncertainties have been reduced, this 

Administration will craft and support an appropriate set of 

measures to solve the acid rain problem." 

Considerable evolution in the details of this policy over the 

past year and a half has been due to intensified policy analysis 

efforts within EPA and the Cabinet Council on Natural Resources 

and the Environment. A thorough review of the problem and issues 

has been conducted in an effort to reach a consensus on control 

options which might be considered. This process allowed for more 

112 
Table 3. Administration position on acid deposition control. 

POSTPONE CONTROL DECISION PENDING 

IMPROVEMENTS IN SCIENTIFIC INFORMATION 

ACCELERATE RESEARCH T ARGETTED ON KEY 

POLICY QUESTIONS 

SURFACE WATER ACIDIFICATION 

FOREST EFFECTS 

DRY DEPOSITION 

ATMOSPHERIC MODELING 

ONGOING POLICY ANALYSIS 

IMPLEMENTATION PLANNING 

STAR PROGRAM 

CONTROL TECHNOLOGY RESEARCH 

113 
explicit identification of the critical uncertainties affecting 

policy development. On the basis of this experience, several new 

activities have been initiated. The following are the key points 

of the Administration's current acid-rain policy: 

1. The question of adopting an emissions reduction progr~m 

for acid rain control has been deferred without prejudice. The 

deferral is based on uncertainties in two general areas (a) what 

is the nature and magnitude of the problem, and (b) how effective 

are the proposed solutions in solving these current or potential 

problems? Definitive answers to these questions will not be forthcoming in the near or middle term. Therefore, decisions about 

acid rain will have to be made in an environment of scientific 

uncertainty. The goal of deferring the decision is an opportunity 

to make some interim gains in knowledge that can significantly 

improve the chances that correct choices will be made. 

2. To allow for a decision as expeditiously as possible, 

major new or expanded research efforts are being targeted toward 

the key questions. To address the question of the nature and 

magnitude of effects, the EPA has begun an extensive survey of 

current and potential surface-water acidification across the 

Nation. In addition, a major survey of current and potential 

forest and vegetation effects is now being designed. To respond 

to the effectiveness question, there are accelerated programs to 

produce dose-response information for various types of effects, to 

improve our ability to monitor dry deposition, and to model th~ 

atmospheric processes which relate emissions sources to deposition 

in sensitive regions. 

3. It is impossible to predict when enough will be known to 

make a decision, as it is very much dependent on the kinds of 

answers which come from the research. Establishing when enougl' is 

known to make a decision is not a research or scientific question, 

it is a policy question. Consequently, policy analysis is an 

ongoing and high-priority function. Two major objectives of tl'is 

effort are 1) to assimilate the results of the research and re~Tise 

the possible options accordingly, and 2) to identify additional 

policy-relevant information needed from the research program. In 

the meantime, we are beginning to evaluate possible results in 

advance, thus reducing response time once the results are in. 

4. The policy calls for beginning to plan for possible 

implementation without waiting for final Congressional or 

Executive Branch action on a control program. By starting the 

implementation planning and analysis effort now, we can ensure 

that any program adopted in the future would be more effective 

than if implementation were an afterthought. In addition, thi~ 

program could save a year or more in actual implementation tim~ 

should a control program be adopted. One aspect of the implem~ntation effort is the State Acid Rain (STAR) grant program whic1: 

114 
provides funds to State agencies to support detailed analysis of 

implementation problems and issues which would face each 

particular State should a major control program be enacted. 

Another aspect of implementation planning is embodied in tl'~ 

Administration's commitment to a program of control technology 

research being carried out by EPA and DOE. As a result of thes~ 

efforts, a broader range of cost-effective control technology 

options should be available in the future, including some designed 

specifically for the retrofit requirements of an acid-rain control 

program. Should major reductions actually be required, the 

availability of alternative control technologies could substantially reduce the total cost and/or associated economic disruption. 

5. Critical to the position of waiting for more information 

before deciding, is the premise that we are not facing an 

ecological emergency. Although there is a general consensus am~ng 

EPA scientists and policy analysts that current evidence does n~t 

indicate such a crisis, the evidence is not conclusive. Consequently, a major priority of the near-term research effort is to 

confirm or disprove this conclusion. If research shows that an 

emergency does exist, a control decision will be made based upon 

whatever information is available at the time. 

The largest and most critical scientific uncertainties related 

to acid rain revolve around the actual and potential effects and 

the atmospheric processes by which acid deposition is created. 

However, there are important uncertainties and issues concernir~ 

the man-made emissions, and the cost and other impacts of posslble 

control actions. These uncertainties can affect the distributional and equity aspects of a policy; that is, which regions, 

industries, consumer groups, etc. are affected. For this reason, 

they may be extremely important in the policy debate, although of 

lesser significance from a purely scientific point of view. 

In the remainder of my time, I would like to focus on the 

man-made sources of emissions relevant to acid rain, especially 

S02, and the control options and issues associated with reducing 

these emissions. These are the policy questions which relate to 

the need for coal-quality data. 

As indicated in figure 5, there is considerable uncertainty 

about the baseline levels of S02 emissions to be expected over the 

next 25 years or more in the absence of acid-rain control 

legislation. These alternative projections were presented by the 

Secretary of Energy in recent Congressional testimony. For 

several reasons, it seems that the high end of this range is more 

likely. The Administration is forecasting strvng and sustained 

economic growth, lifetimes of coalfired power plants are being 

extended, and we do not yet see evidence that new technology ~ill 

cause emissions standards for new plants to be reduced further. 

115 
SCENARIO 

HIGH 

LOW 

GRownt 

HIGH 

LOW 

RETIRI 

60YR 

41YR. 

NSPS 

CONST. 

UPOATI 

(1) Strategic Environmental Assessment System 

(2) Environmental Trends Analysis Model 

(1) 

(2) 

--

----

Figure 5. Projections of future national so2 emissions with 

alternative input assumptions. (Source: Donald P. 

Hodel, U.S. Secretary of Energy, Testimony before the 

Subcommittee on Health and the Environment, Committee 

on Energy and Commerce, U.S. House of Representatives, 

March 29, 1984.) 

116 
All of this would argue for a future in which SOz emissions may be 

expected to remain high or to increase for some time. 

Whatever baseline projection one uses, there is the real 

possibility that a major reduction of emissions will be required 

in the 1990's to alleviate acid rain and other air-pollution 

effects. Given our current understanding of the economics of the 

coal and electric utility industries and available control 

technologies, it appears that alternative approaches to implementing such reduction could have markedly different impacts on 

industries and regions. Figures 6 through 8 show results of scme 

analyses conducted for EPA by ICF, Incorporated. This analysi~ 

compared the Waxman-Sikorski Acid Rain Bill (H.R. 3400) with a 

"cost-effective equivalent." The cost-effective equivalent wa~ 

developed using a computer model of the utility industry to 

achieve the same level of emission reduction while minimizing the 

total direct cost to electric utility companies. It should be 

emphasized that only direct costs to the utilities are included in 

this calculation. The analysis also assumes that coal and 

electric-utility industries respond smoothly to economic market 

forces. In reality, there are probably many constraints which 

limit the operation of these markets. However, the comparison of 

the two fairly extreme cases--mandated scrubbers versus least-~ost 

market response is an informative analytic effort. 

Figure 6 shows that the cost-effective equivalent can 

substantially reduce direct utility costs and almost eliminate the 

need for capital expenditures. This is because the model finds 

shifting to low-sulfur coal to be the least-cost option for nearly 

all affected plants. As shown in figure 7, this has dramatic 

effects on regional coal markets causing high-sulfur regions, 

especially the Midwest, to decline while increasing low-sulfur 

coal production from Central Appalachia and the West. As show~ in 

figure 8, this translates into large reductions in employment in 

the high-sulfur coal regions although net national employment 

changes very little. 

These two cases clearly illustrate one of the major dilem,as 

facing policy-makers in the acid-rain area. If and when there is 

a consensus that major control action is required, there is still 

a tradeoff to be made in implementation. The available options 

are (a) costly or (b) very disruptive to some regions. This is 

the area in which the development of more cost-effective technology 

can make a contribution. This is where there are current policyrelated needs for coal-quality research. Several key policy 

questions in the acid-rain area appear to be closely connected 

with coal data. Examples are: 

1) What is likely to happen to the cost of producing cocl 

under future levels of demand--by regions, by sulfur content? 

117 
I 

INCREASE IN PRESENT VALUE OF COSTS 

(iD 1982 Dollars) 

~~--------------------------~==~~~~ SUD .. dy/Taa 

- lnauatrtal c::::::J Utility 

30 

'S 20 11.2 

j 

25 

20 

• .. 

.! 

0 

Q 15 

-

0 

• I 10 ii 

5 

0 

10 

0----------------~------~--------------~------' 

INCREASE IN CUMULATIVE CAPITAL COSTS - 1995 

(in 1982 Dollars) 

21.5 c:::l UtiHty I 

rza Subaidy/Tax. 

1.5 

Cost-Effective 

E&:J,ivalent 

Figure 6. Comparison of Waxman-Sikorski Acid-Rain Bill (H.R. 3400) 

with a cost-effective equivalent. (Source: ICF, Inc., 

Analysis of the Waxman-Sikorski Sulfur Dioxide Emission 

Reduction Bill (H.R. 3400), April 1984.) 

118 
300 

! 200 

'I 

I 100 

800 

800 

J 

'I 400 

I -

I 

200 

1880 

HIGH SULFUR COAL PRODUCTION 

213 

Baae 

1885 

1~=--1 

Waxman-Sikcnkl Coat-Effective 

1885 ecpv .... 

1885 

LOW SULFUR COAL PRODUCTION 

1~=-~1 878 

1880 

585 

Sue 

1895 

Waxman-Sikorski Cost-Eftectlvt' 

1885 EcPvalent 

1885 

Figure 7. Effect on regional coal markets of alternative 

approaches to acid rain control legislation. (Source: 

ICF, Inc., Analysis of the Waxman-Sikorski Sulfur 

Dioxide Emission Reduction Bill (H.R. 3400) April 1984.) 

119 
TOTAL COAL MINING AND TRANSPORTATION EMPLOYMENT 

~~~====~-----------------------, 

1~=---1 

300 

; 

i j200 

100 

100 

75 

; 

i 

j 50 

25 .... 

1880 ... 

188& 

WaxmM-SikcnKI Coet-Effectlw 

188& Eqaavelent 188& 

H IGH·SUL.FUR COAL MIN lNG EMPLOYMENT 

l~=~adn, 

1880 Waxman-Sikorski Cost-Effective 

1885 Eq&ivalent 

1885 

Figure 8. Effect on employment of alternative approaches to acid 

rain control legislation. (Source: ICF, Inc., 

Analysis of the Waxman-Sikorski Sulfur Dioxide Emission 

Reduction Bill (H.R. 3400) April 1984.) 

120 
2) How accurately can we estimate current and future 

emissions of SOz at a given facility based on coal-quality data? 

3) What are the technical constraints/costs associated with 

fuel switching--to western low-sulfur sub-bituminous coal, to 

eastern low-sulfur coal? 

4) How can new technologies modify the cost, employment, and 

other economic impacts of major control programs? 

5) Can physical coal washing play a larger role in aciddeposition control programs than currently projected? 

Answers to these questions are limited by available data o~ 

distribution of coal reserves, sulfur content in coals and its 

variability, etc. In all cases better data would be desirable. 

Because of the importance of coal in the Nation's future, we 

need a continued long-term effort to ensure that the coal-quality 

data required to support energy and environmental research is 

available and as accurate as possible. The extreme complexity and 

magnitude of such a long-term research effort is beyond the 

resources of the EPA and probably of any single agency of 

government. What is needed is a coordinated effort involving 

cooperation of many governmental agencies and affected industries. 

In addition to the long-term needs, there are short-term 

policy information needs which change frequently as different 

policy issues dominate the national debate. The current emphasis 

on acid rain has caused EPA's engineering research program to 

focus heavily on a limited number of control technology optionE 

for SOz and NOx which have potential for retrofit in the near to 

medium terms. These include wet flue-gas desulfurization (scrubbing) with enhancements, improved dry scrubbing technologies, 

limestone injection with multistage burners (LIMB), and coal 

washing. Coal-quality data is an important input to developmert 

and evaluation of these technologies. Improvements in these dcta 

could make important contributions to the success of these 

technological efforts if they can be achieved within time and funding limitations. Short-term needs such as these must be caref\•lly 

integrated and balanced, however, with long-term program needs. 

This seminar offers an important opportunity to further 

cooperative efforts and to move toward consensus on the appropriate 

allocation of scarce resources among competing short-term·and longterm research needs in the coal-quality area. It is my hope tl1~t 

the panel sessions on subsequent days of this seminar will be 

successful in identifying and organizing these competing needs and 

in moving toward a coordinated comprehensive program. 

121 

PREDICTING COAL PRODUCT QUALITY AND ITS EFFECT 

ON MARKETABILITY 

by 

James Pinta, Jr. 

Chevron Oil Field Research Company 

INTRODUCTION 

Assessment of a resource is a dynamic process consisting of 

several phases that begins with exploration and continues throughout subsequent phases in developmental evaluation and exploitation 

(fig. 1). The goal of resource assessment is to provide a tec~nical 

basis on which to make an economic evaluation of resources, whe:ther 

for project financing, purchasing or selling, accounting purposes 

such as depletion or tax calculations, or final mine planning. 

Required input includes coal tonnage, quality, and mineability 

estimates to determine the economics of extraction and preparation, 

and marketability estimates of the resulting coal products to 

determine profitability. 

Ideally, each phase produces information permitting 

"go/no-go" decisions on future exploration, development, and 

exploitation work to be made with greater and greater confidence. 

Resource-assessment budgets are established to gather information 

necessary to achieve a desired confidence level in mineability and 

marketability estimates. Amounts invested in each phase of the 

assessment must be balanced against the benefits to be realized 

from the information gathered or, alternatively, against the risks 

involved in not gathering the additional information required. 

The resource assessment necessary in opening a coal property 

is fundamentally different from that of oil and gas exploratio~. 

In exploring for oil and gas, there is nearly always a significant 

"value of discovery." In other words, there is an immediate 

market for oil and gas at a price which would yield an attractive 

return on investment. The point at which a coal property has an 

equivalent value is reached only after a resource has been characterized and the mining project has been engineered sufficiently to 

predict with reasonable confidence the cost of production, and 

when a buyer has committed to purchase the mine production at a 

price level that results in an attractive investment for the mine 

construction. Unlike oil, coal is a user-constrained commodity. 

123 
• DYNAMIC PROCESS; SEVERAL ITERATIONS 

• SEVERAL PHASES 

- EXPLORATION 

-DEVELOPMENTAL EVALUATION 

- EXPLOITATION 

• GOAL: 

- PROVIDE A TECHNICAL BASIS ON WHICH TO MAKE AN 

ECONOMIC EVALUATION OF RESOURCE EXPLOITATION 

POTENTIAL 

i) PROJECT FINANCING 

ii) PURCHASING OR SELLING 

iii) ACCOUNTING (DEPLETION, TAX, ET~ 

iv) FINAL MINE PLANNING 

• GET INFORMATION TO PERMIT GO/No-GO DECISION ON 

FUTURE PHASES AND ACTIONS 

Figure 1. Coal resource assessment process. 

124 
RESOURCE-ASSESSMENT STRATEGY FOR PREDICTING COAL QUALITY 

Several phases of assessment are usually used to determine 

the potential profitability of a resource (fig. 2). Initial 

phases are necessarily broad, with each successive phase becoming 

narrower in scope and more detailed in nature (figs. 3-9). Data 

gathered in the initial phases of resource assessment establist~s 

a foundation on which each successive phase must be based. 

Ideally, each phase produces information required to decide 

whether or not to go on to the next phase. 

Figure 10 represents an algorithm for combining data from all 

completed stages to assess the potential profitability of a giv~n 

resource in a given market at any stage of evaluation. 

Economic constraints limit the amount of sample obtainable 

from a reserve, especially in deep reserves. Thus, exploratior 

programs for coal-reserve evaluations must be designed to gather 

the greatest possible amount of geologic information (for the 

allotted budget) in order to permit prediction of anticipated 

mining conditions and coal-product quality over the area of the 

reserve. 

MINING CONSIDERATIONS 

The first step in evaluating the mineability of a particular 

reserve is to determine the geologic factors that affect mininr 

costs (fig. 11). During the initial phases, these factors can be 

ranked from highest to lowest in importance to identify the pieces 

of information that are essential to reserve evaluation. Durir.g 

later phases, the impact of these geologic factors on mining c0sts 

must be quantified on a $/ton basis. Figure 12 illustrates th~ 

methodology used to optimize the selection of mining methods for 

an underground reserve. Costs for various geologic conditions 

existing at given localities are overlaid to prepare an estimate 

of anticipated mining costs for a particular m1n1ng method. Maps 

of mining costs are compared and the optimum method or combination 

of methods is selected. Often, in the early phases of resourc~ 

assessment, areas will be identified where additional geologic 

information is required to select the optimum method of mining for 

that area. This information provides input into the types of 

information and, therefore sampling program, needed to complet~ 

the next phase of resource assessment. 

COAL PRODUCT QUALITY 

Figure 13 indicates where particular coal-characterization 

parameters are important to a utility power plant; however, no 

quantitative information is available at this time. It is quite 

probable that individual power plants have very different "use 

costs" associated with a particular parameter. 

125 
PHASE TO ACCOMPLISH INPUT REQUIRED Ff'~M 

PHASE I MARKET OPTIONS MARKETING 

REGION OF INTEREST REGIONAL COAL GEOL01Y 

PHASE II SELECT MOST FAVORABLE MARKETING 

SITES REGIONAL COAL GEOL01Y 

MARKETING 

COAL GEOLOGIST 

RECONNAISSANCE OF AREAS PHOTO GEOLOGIST 

PHASE Ill FEASIBILITY STUDIES & FIELD GEOLOGIST 

OPTION LAND MINING ENGINEERING 

LAWYERS FOR OPTIONS 

DRILL HOLES 

CONCEPTUAL MINE PLANNING COAL GEOLOGIST 

PHASE IV • DEVELOP MODEL FIELD GEOLOGIST 

MINING ENGINEERING 

MARKETING 

PRELIMINARY MINE DESIGN DRILL HOLES 

• USE MODEL TO LAY OUT COAL GEOLOGIST 

PHASE V ADDITIONAL SAMPLES FIELD GEOLOGIST 

REQUIRED MINING ENGINEERS 

• REFINE MINE DESIGN EQUIPMENT MANUFACTURERS 

• REFINE MODEL MARKETING 

ECONOMISTS 

DRILL HOLES 

PHASE VI FINAL PREMINING DESIGN COAL GEOLOGIST 

FIELD GEOLOGIST 

• USE MODEL TO AVOID MINING ENGINEERS 

PROBLEMS WHICH MAY EQUIPMENT MANUFACTURERS 

CAUSE DELAYS IN GOING ECONOMISTS 

TO FULL PRODUCTION 

PHASE VII IN SITU MONITORING MINING ENGINEERS 

COAL GEOLOGIST 

Figure 2. A coal resource assessment strategy. 

126 
PHASE I 

SELECT REGION OF INTEREST 

• MARKET OPTIONS 

-MARKET OPPORTUNITIES 

- COAL SPECIFICATIONS 

-TRANSPORTATION REQUIREMENTS 

-OTHER 

i) ENVIRONMENTAL CONCERNS 

ii) OWNERSHIP CONSTRAINTS 

iii) PREFERRED MINING METHODS, ETC. 

• REGION SELECTION 

Figure 3. 

PHASE II 

PRELIMINARY INVESTIGATION OF A REGION 

• OBTAIN MORE DETAILED INFORMATION 

- REGIONAL TRENDS OF COAL CHARACTERISTICS 

- TRANSPORTATION 

-CUSTOMERS 

- REGULATIONS 

- LAND AVAILABILITY 

-MANPOWER AVAILABILITY 

• SELECT THE MOST PROMISING SITES FOR MORE 

DETAILED EVALUATION 

Figure 4. 

127 
PHASE Ill 

RECONNAISSANCE/FEASI Bl LITY STUDIES 

• GENERAL SITE EVALUATIONS 

- REVIEW LITERATURE & EXISTING DATA 

i) GEOLOGY 

ii) GROUNDWATER 

-STUDY NEARBY OPERATIONS 

i) IDENTIFY POTENTIAL PROBLEMS 

ii) IDENTIFY POTENTIAL SOLUTIONS 

-SATELLITE IMAGERY AND AERIAL PHOTOGRAPHY 

-RECONNAISSANCE 

i) FLY OVER 

ii) DRIVE THROUGH/WALK THROUGH 

- OPTION PROMISING PROPERTIES 

Figure 5. 

PHASE IV 

CONCEPTUAL MINE/PREPARATION PLANT PLANNING 

• EXPLORATION PROGRAM TO OBTAIN SAMPLES 

-PERMITS 

- DRILLING & SAMPLING PROGRAM 

• DEVELOP MODEL OF DEROSIT (GEOSTATISTICS) 

• ESTIMATE COAL MINEABILITY 

• ESTIMATE COAL QUALITY ATTAINABLE 

• PRIORITIZE SITES; PURCHASE DESIRED PROPERTIES 

Figure 6. 

128 
PHASE V 

PRELIMINARY MINE/PREPARATI~N PLANT DESIGN 

• REFINE EXISTING DATA 

- USE MODEL TO HELP IDENTI ~V WHERE ADDITIONAL 

DATA IS REQUIRED 

• ACQUIRE ADDITIONAL DATA 

- REFINE MINE DESIGN 

i) STRATIGRAPHY 

ii) STRUCTURE 

iii) IN SITU STRESSES 

iv) GROUNDWATER COND~TIONS, ETC. 

- REFINE COAL PRODUCT QUA~ITY ESTIMATE/ 

PREPARATION PLANT DESIG~ 

i) ASH AND SULFUR DIS1RIBUTION 

ii) MINING DILUTION CO~TRIBUTION 

• MARKET PRODUCT(S) 

Figure 7j 

PHASE VI I 

FINAL PREMINING 9ESIGNS 

• FINALIZE PREPARATION-PLANT/ DESIGN 

• FINALIZE MINE DESIGN 

• GOAL IS TO PROCEED DIRECTL t FROM CONSTRUCTION 

WITH A MINIMUM OF DELAYS I 

Figure 8t 

PHASE V~l 

IN SITU MONI10RING 

• MAINTAIN GOOD RECORDS 

• PERFORMANCE EVALUATIONS! 

• CORRECTIVE ACTIONS TAKEN ~HERE NECESSARY/FEASIBLE 

Figure ~. 

129 
PROFIT-ORIENTED MINE PLANNING 

COST.SENSITIVE MINE PLANNING COST .SENSITIVE PLANT PLANr'•NO 

GIOLOGIC, HYDROGEOLOGIC, COAL THICKNESS, COAL QUALITY ] AND PARTING, RIDERS, AND 

CULTURAL DATA BONE, TOP, ETC. WASHABILITY DATA 

I I 

ISOPACH MAP GENERATION PRODUCTION LEVEL ISOPACH MAP GENERA nON 

AND AND AND 

GEOSTATISTICALANALYSIS . MINING METHOD GEOSTAnSTICAL ANALYSIS . 

I I 

PREPARATION PLANTMINING EQUIPMENT- OPERATION & OWNING COST, ~ OPERATING & OWNING COST, MARKET PENAL TiE(' oUALITY & 

ETC. --

CONVERT MAPS 

TO 

PRODUCTION COSTS 

ADD MAP 

FOR 

FINAL PRODUCTION COSTS 

PROFIT 

SALE PRICE 

MARKET 

_PRODUCTIQN LEVEL 

.SEOVENCE OF MINING 

TYPE OF MINING 

QUANTITY NEEDS, ETC. 

I 

PROFIT MAP 

PRELIMINARY OR FINAL 

MINE PLAN 

LAYOUT OF MINE. 

Figure 10. 

130 

CONVERT MAPS 

TO SALES PRICE 

MINUS PREPARATION COST 

ADO MAP 

FOR FINAL SALES PRICE 

MINUS PREPARATION COST 

FUTURE BORING 

It EXPLORATION PROGRAM 

ENVIRONMENTAL DATA 

REFUSE AREA LOCATION 

SPECIFIC GRAVITY OF PLANT 

DESIGN REQUIREMENTS 

SLOPE II BOTTOM LOCATION 
IIIWNt'BIIMCI HAULAOI 

LONGWALL 

MINING ... 

z CONDITIONS 0 en z ... "' 2 

> a: "' ~ ..1 > c 0 "' i (,J a: z ... lA. ::I ... 0 0 c )o 

PARAMETERS 0 en z j: z ... en Q ..1 ... ..1 z 0 "' i z )o )o t z 0 0 (,J c z "' "' c a: ..1 c ... :::& "' a "' • :::& a: :::& en a: ... j: .. a: c .. 0 0 :: c 

a ..1 "' "' :::& "' z c 0 z ... 5 • ::I ~ ... i z 0 0 ..1 "' "' "' c ! i 0 (,J ..1 lA. > :::& Q "' % lA. Q,. "' 

BASE ELEVATION • • • • • • • • • • • • • 

COVER THICKNESS • e • • • • • • • • • • • 

ROOF SHALE THICKNESS • • • • • • • • • • • • • 

NUMBER OF STRATA IN FIRST 50 FEET • • • • • • • • • • • • • 

SANDSTONE THICKNESS IN 50 FEET • • • • • • • • • • • • • 

LIMESTONE THICKNESS IN So FEET • • • • • • • • • • • • • 

DISTANCE TO FIRST THICK SANDSTONE • • • • • • • • • • • • • 

DISTANCE TO FIRST THICK LIMESTONE • • • • • • • • • • • • • 

TOTAL SEAM THICKNESS • • • • • • • • • • • • • 

COAL THICKNESS • • • • • • • • • • • • • 

PERCENT ASH • • • • • • • • • • • • • 

PERCENT SULFUR • • • • • • • • • • • • • 

BTU CONTENT • • • • • • • • • • • • • 

GROUNDWATER PRESSURE • • • • • • • • • • • • • 

LINEAMENTS • • • • • • • • • • • • • 

FLOOR INTEGRITY • • • • • • • • • • • • • 

SURFACE FACILITIES • • • • • • • • • • • • • 

OIL AND GAS WELLS • • • • • • • • • • • • • 

SURFACE HYDROLOGY • • • • • • • • • • • • • 

GROUNDWATER HYDROLOGY • • • • • • • • • • • • • 

Figure 11. Effect of geologic factors on mining conditions. 

circle indicates degree of importance. 

131 

! 

iii g "' t; ..1 Q c en ... a: j: 

"' ~ "' z ... ... c· "' (,J 

a: i .. c 

! a: 

! c 

j: "' % j: (,J ~ g c "' a: "' Q c 0· Q,. ! 0 i "' lA. 

a: a: "' ::I Q,. Q,. a: en 

• • • • 

• • • • 

• • • • 

• • • • 

• • • • 

• • t' • 

• • t' • 

• • (' • 

• • (' • 

• • 4' • 

• • f' • 

• • r • 

• • f" • 

• • • • 

• • • • 

• • • • 

• • 4' • 

• • • • 

• • • • 

• • • • 

Size of 
1~ 

w 

1\.) 

A c D 

GEOLOGIC NIIO IICTITUTIONAL 

PARAMETERS CONVERTED TO 

DOLLARS PER TON 

• LONGWALL MINING ROOM AND PILLAR 

CCONTINUOUS MINING) 

COAL MARKETABILITY 

OF CLIAN COAL 

1. LINEAMENT DISTRIBUTION------

2. OYERIURDEN THICKNESS--------- --~ 

3. DISTANCE TO FIRST THICK SANOSTONE---

4. DISTANCE TO FIRST THICK LIMESTONE--- ---~----s:::::3 ~ l.mVAT ... OHH<WAT<OT..._,_____ ::: s ~ ~ 6. THICKNESS OF THE SHALE-------- ----~ ~ ----...........5 ~ 

I. 

7.NUMilEROFSTRATAIN50FEET-----

SA!ilDSTONE THICKNESS IN 50 FEET-----

--........,, 

.... 

~ . ~ 

I. LIMESTONE THICKNESS IN 50 FEET----- -------------------

:~·.~~::::KO~~:~~:;K-:..::~:~~~ ==~-=--~--=- ----- 12. THICKNESS OF THE COAL---------

13. MINEABLE COAL THICKNESS------- ---- -----""~,...------.....,~-----::: 

14. PERCENT ASH------------- -------------------~"!_"'-3_-_-_-_-_-~------~- 15. PERCENT SULPHUR------------

16. BTU CONTENT-------------

17 FREE SWELLING INDEX----------

18. INSTITUTIONAL CONSTRAINTS------

18. LAW AND ENVIRONMENTAL CONSTRAINTS-

-----------------------------------------------

-------~------~ :!: :'£ - -------- 1 ------~ 

"'~ ""la~ ""~"'- Figure 12. Methodology used to optimize selection of mining methods 

for an underground reserve. 
SUMMARY TABLE OF WHERE PARTICULAR COAL-cHARACTERIZATION 

PARAMETERS IMPACT UTILITY BOILER SYSTEMS 

COAL HANDLING 

PROXIMATE (ASH AND MOISTURE) 

ULTIMATE (OXYGEN) 

BTU/POUND 

BULK DENSITY 

BURNERS 

PROXIMATE (MOISTURE AND VM) 

ULTIMATE (N) 

BURNING PROFILES 

VOLATILE-RELEASE PROFILES 

AIR HEATERS 

PROXIMATE (MOISTURE, VM) 

ULTIMATE (ASH, S) 

PRECIPITATORS 

ULTIMATE (MOISTURE, S, AND 

GAS DENSITY) 

ASH ANALYSIS 

VM=Volatile matter 

FSI=Free swelling index 

FC=Fixed carbon 

HGI=Hardgrove grindability index. 

PULVERIZERS 

PROXIMATE (ASH, MOISTURE, VM) 

ULTIMATE ( 1; S) 

BTU/POUND 

FORMS OF SULFUR 

FSI 

HGI 

ABRASIVENESS (QUARTZ CONTENT) 

FURNACE DESIGN 

PROXIMATE (MOISTURE, ASH, VM, FC) 

ULTIMATE (C, H, N, S) 

FORMS OF SULFUR 

ASH ANALYSIS 

ASH FUSION TEMPERATURES 

ASH VISCOSITY 

GRAVITY FRACTIONATION 

BURNING PROFILES 

VOLATILE RELEASE PROFILES 

CONVECTION PASS DESIGN 

PROXIMATE (ASH, MOISTURE) 

FORMS OF SULFUR 

ASH ANALYSIS 

ASH FUSION TEMPERATURES 

TOTAL ALKALI ON COAL 

ASH SINTERING STRENGTH 

ACETIC ACID SOLUBLE ALKALIS 

GAS SCRUBBER 

PROXIMATE (MOISTURE, ASH) 

ULTIMATE (SAND GAS DENSITY) 

ASH ANALYSIS 

S=Sulfur 

N=Nitrogen 

C=Carbon 

H=Hydrogen 

Figure 13. 

i33 
To accurately assess the variability of each of these 

parameters over a 100 million ton reserve would require a ver~ 

large number of very large samples. It is not feasible to collect 

such a suite of samples, thus indirect methods of assessment must 

be used to infer coal quality {and therefore, coal-product 

quality) obtainable from a particular reserve. Some of these 

methods are illustrated in the following discussions. 

Figure 14 illustrates the results of attempting to correlate 

the ash content of various raw and clean-coal fractions with 

various other coal-quality parameters. It should be emphasized 

that although the ash content shows good correlation with Btu/lb, 

percent total sulfur, percent pyritic sulfur, percent organic 

sulfur, percent A1203, percent Si02, acid/base ratio, and per~~ent 

volatile matter, these results are applicable only to this 

particular reserve. In fact, these correlations may not even 

exist for other deposits. By using the percent volatile matter 

value obtained from figure 14 and the correlations illustrated in 

figure 15, estimates of percent carbon, percent hydrogen, percent 

nitrogen, and percent oxygen can be obtained. Thus, one can infer 

a large amount of quality data by simply measuring one characteristic {that is, ash content) if enough data is available to 

generate these types of interrelationships among coal-quality 

parameters. Once a coal-characterization parameter is selected as 

important in evaluating a resource, it becomes necessary to 

project this quality parameter across the extent of the resource. 

Figure 16 indicates the type of data on mineral-matter size 

distribution required to assess the grind necessary to liberate 

various amounts of this material. This type of information is 

useful for fine coal cleaning and essential if extremely low ash 

products {<1 percent) are to be produced. 

It is thought that cleaning may remove some of the epigenetic 

"overprinting" {for instance, cleat pyrite, and so on) masking 

syngenetic relationships among coal-quality parameters. These 

parameters are less variable in the clean coal than observed in 

the raw coal; hence, fewer samples are required using the cleancoal data. Figures 17, 18, and 19 indicate the differences in 

variability observed in raw versus clean-coal fractions for the 

quality parameters ash, sulfur, and Btu for a particular reserve. 

Two relatively new areas of characterizing coal deposits {and 

variability expected) are studies on depositional modeling and 

geostatistics. Figure 20 illustrates idealized models for 

environments of deposition for coal. Data from the literature 

indicates that correlations exist between geologic hazards that 

have an impact on mining costs {fig. 21) and coal quality {fig. 

22). Thus, by determining the environment of deposition in which 

a particular coal resource was deposited, one can estimate the 

134 
'1 7 

15 

... ,. 0 13 

0 

0 11 

: ... ~ 

,~ llC 9 •• -

= 7 ... 

CD 5 

3 

-26 

0 

;: 2 2 ~ 

·,~~ a: • 

>18- ,, a. ,, -14- , 

a: ,"" ~10-

en 

u. 

::l 

...J 6 - /~ 2~ • 

if ..J..a-ft, I I I I I 

0 8 18 24 32 40 48 

WEIGHT " ASH 

if 

0 8 18 24 32 40 48 

WE.IGHT " ASH 

3.0P---------------------------------~ 

2 2.5 ... 

< 

a: 2.0 

w 

en 1 5 < . CD Q 1.0 

0 

< 0.5 

0 

' '.. .. . . ·~. • • 

8 16 24 

WEIGHT " 

48 

30 

-.... 28 

< 

1- 22 0 

t: 18 

a: 

= 

14 ~ 

..1 10 

= co • 

-,2 

a 

-0 2.4 

z 

< 2.0 ~ ·':-;· a: 

0 1.8 • - 1.2 

a: 

::) 

u. 

..I 

::) '',,~ 

• 

- 0 8 18 24 32 4(l 48 

WEI~HT "·ASH 

80 

w 

Q 50 

>< 

~ 40 • 

Q 

z 30 

0 

CJ 20 ..I 

,CI) 

10 

'If 

0 8 18 24 32 40 48 

WEIGHT " ASH 

80P-------------------------------~ 

a: 

~:::~ .. w '-.. ~.~ 

..I 30 1- •....--_._. ____ _. . 

.... 

~ 201-

0 

> 10 1-

if 

0 

I 

8 

I I I 

16 24 32 

WEIGHT " ASH 

I I 

40 48 

Figure 14. Correlation between ash content and other coal properties. 

135 
I ...I 

w 

"' 

80 

70 

60 

z 50 

0 

ID 

a: 40 

< 

0 

'll- 30 

20 

# 

o~----~~~~--~~--~~~~--~~--~ 

z 

w 

<!' 

1.5 

0 1.0 

a: 

t: 

z 

'll0.5 

0 10 20 30 40 

«JfJ VOLA TILE MATTER 

/

. 

• 

• 

• 

• 

50 60 

0.0' I I I I- I I I I I I I I p 

0 10 20 30 40 50 60 

~ '!Ol!\ T'U: ~,1!\ TT~~ 

6 

5 

z 

w 4 <!' 

0 

a: 

Q 3 

>-

l: 

'll-. 2 

1 

z 9 

w 

CJ 

>-

)( 

0 

'll0 

0 

10 20 30 40 

«JfJ VOLA TILE MATTER 

10 20 30 40 

~ '!Ol~T!l~ ~.&.TT~~ 

Figure 15. Correlation between volatile matter content and coal properties. 

50 60 

50 60 
100 •liTo rr- 0 

I ~ I 'l'l 

e/ I ~ I I /·'!rt.e 

• I ~' / q~ . I , I /_CI~ "' • 

I / e<:' I 

• t) I / 

10 I I ~ :I 

CD ~. I c ;; e" / u.. 

,.e. r:l ~j6 

~ 

!I 4: 

.c .!.I .,. lbf a; <:' 

~ fl 

CD I. 0 

> llJI 1 

- I I .! 

:;, 

E I I. 

(.) = • I I I 

I • I 

I 

l I ol I I I I tl 

10 100 1000 10,00( 

Average Diameter (Microns) 

Figure 16. Pyrite and mineral-matter size distribution for three 

benches of a coal core. 

137 
~ 

w 

00 

::z: 

fl) 

c 

25.0 

Y COORDINATE 

------

18000 

24000 

36000 

42000 

RAW COAL 

• • 

-x-• 

CLEAN COAL -b0 

/:). 

--x--

~ 15.0--

~ 

... 

X~~ ---- I 

R~="o--........___~ . _4 

.......... ---------· ~-X-::~~~~~ -- --0--- --L.:l " ---- = --=--=-= ==-... -- :=-

9 ~-~ . ------------ - - c.---- 0 --- -

-=--- ---- ----:.0 - --=----.... ------ ---= --~ ---~ --~ ~ A ----x 

I-; •-

' 

o.oL-----~----~------~----~------~----~------~----~~----~-----:~ 0 50 10 15 20 25 30 35 40 45 50 

X COORDINATES (x 1000) 

Figure 17. Ash variability in the raw and clean coal. (X andY coordinates relate to an 

arbitrary map grid used during evaluation of a particular coal reserve.) 
J--1 

w 

1..0 

a: 

::a 

_, 

&I. 

::a 

en 

~ 0 

s.s ·"· • ·"· » X 

Y COORDINATE 

-----

18000 

24000 

36000 

42000 

RAW COAL CLEAN COAL 

• -0-

• 0 

A ~ 

• -x- --x--

--- -------0-----------0 ' -- ' 0 .-0----- _...... X ,. 

0 ..... "' - - - - .. -------- ><' , _,.___ ......... -- ---o 

cs. .... ........ -.... -- ---~ "----------e:.---

x' .. ----IIZI --- --x------ __ ... x--------- ------ ---x----

15 20 25 35 45 50 

X COORDINATE ( X1000) 

Figure 18. Sulfur variability in the raw and clean coal. (X and Y coordinates relate to an 

arbitrary map grid used during the evaluation of a particular coal reserve.) 
I-I 

~ 

0 

Y COORDINATE 

18000 

24000 

36000 

RAW COAL 

• • 

-x-• 

CLEAN COAL 

0 

0 

~ --x--

o0 ,-o----- 42ooo 

.1\ - --- ____ ,.,-,, __ .. 6------------------

...... '-" 

... <->- ---,. ,,-. "' ,, --.,.eX------- ,---"" ~ -_____ .., ____ 

--- ------" . ___ -D -tJ .. --.. ___ 

------- ,.. ....... s ---------~ ~ 0 --u--~ 'x---"'-' - --u-:.-..-..~.:- ---c' -----><-- ...... 0 

·-------

12000 

0 5 15 20 25 30 35 

X COORDINATE 

Figure 19. BTU variability in the raw and clean coal. (X and Y coordinates relate to an 

arbitrary map grid used during the evaluation of a particular coal reserve.) 
I-' 

.s::-

1--' 

. .-..;.· ORTHOQUARTZITE 

• !."~"..t:: SANDSTONE . 

>·;,;.·:···. ~f:l GREYWACKE :.-· ;,,",.,>;; SA.NDSTONE J 

::~0A SHALE 

• COAL . 

100 

FEET 

0 

i .< .. ·, 

SCALE .. . -. . ·; . . - . ., ·:... _;: --~ . 

-

"fiS*"h,;itr . .ewk;:e A;:; ,; · · ·· -· ~.. -h~~.t.J~; ,,>,.. .. ::,.:~ i'-..t~f __ ~· .... :,• ., . -·- -·~ M... . ......... _ _: .: '-~-- ·;.., ............... ,.::~~,. ~..;,.~ r ;~ ·,_ ., ?.::;.:;i-f =- .~ /,. · ~'k -.. A':.. :: -::wi~*tdittnti 

Figure 20. Idealized models for environments of deposition of coal deposits. 
Roof Problems Back-Barrier Lower Delta Transitional Lower Fluvial and Upper 

Plain Delta Plain Delta Plain 

Clay-rich Rooted Zones 3-2 2 2-1 1 

Slump Blocks 1-2 3-2 2-1 1-2 

Rider Coals within 20 ft. 3-2 2-1 1-2 1 

(6 meters) of Mined 

Coal (Intervening 

Material Fine-grained) 

Kettles (Upright Stumps) 2 2 2-1 1-2 

in Fine-grained Rock 

Sandstone Channels 1 1-2 2 2-3 

Enclosed in Shales 

~ 

~ Jointed Orthoquartzitic 2-1 3 3-4 4 

N Sandstones 

Cube Rock (Non-bedded 2 2-1 1 3-2 

Black Claystones) 

Conglomerate and Plant 3-2 2-3 2-1 1 

Debris Lags 

Fine-grained Burrowed 1-2 1-2 2-1 3-2 

Zones 

1. Abundant 2. Common 3. Rare 4. Not present 

Figure 21. Abundance of potential roof problems related to depositional environments. 
1-' 

~ 

w 

Environment 

Barrier Bar/ 

Lagoon 

Lower Delta 

Plain 

Transitional 

Upper Delta 

Plain 

Thickness 

Thin 

Thin 

Thick 

Thick 

Locally 

Areal Extent 

Discontinuous 

3-15 Hiles 

Widespread; 

5-70 Miles 

Wide 

Widespread; 

Continuous 

Discontinuous; 

May Pinch Out 

in 500' 

Sulfur 

High 

Framboidal 

Irregular 

Low 

Low 

Roof Mini Deltas 

Problems Crevasse Splays 

Severe 

40' Thick 

100'-5 Mi. Wide Few Usually 

3-4,000' in Dia. 

Some 

Best 

Proximity to 

Marine Environment 

Close !It 

Farthest 

Figure 22. Characteristics of coal quantity, quality, and mineability expected in coals 

deposited in selected environments. 
variability anticipated. In this manner, a logical exploratory 

drilling program can be devised to obtain samples for coal-quality 

analyses to both test and refine the model and predict with so,e 

degree of certainty the range of mining conditions and coal 

quality anticipated (fig. 23). 

Geostatistics is another powerful tool that can be used in 

reserve evaluation. The advantage of a geostatistical approach is 

that it permits you to place a confidence level on your estimates 

of quality, variability, and so on. However, when applied indiscriminately, geostatistics can lead the unwary astray. Figure 24 

is an idealized example of an attempt to construct a semi-variogram 

from a set of coal-quality data from a hypothetical coal resource 

in northern Appalachia. Any interpretation of the data would be 

suspect. However, when the data is broken down into two separate 

sets, each consisting of data within an interpreted environment of 

deposition (based on geologic data), the semi-variograms becom~ 

more meaningful (figs. 25 and 26). After a structural study 

(figs. 27 and 28), the semi-variograms indicate the variability 

expected in different directions within each environment of deposition found in the deposit. Thus, drilling patterns required to 

obtain additional samples can be logically established to maximize 

information at the minimum exploration cost. 

MARKETABILITY 

Once the resource has been evaluated in terms of mineability 

(that is, production cost) and range of coal-product qualities 

producible (that is, coal-preparation costs), a curve of product 

cost versus coal quality (fig. 29) can be generated. The 

Marketing Department must then gather information to permit 

generation of a curve showing anticipated market price versus coal 

quality (fig. 30). Combining these curves gives an indication of 

where coal-product qualities producible will be uneconomic to 

produce and market (fig. 31, Areas A, B, and C). This curve 

permits evaluation of the profitability anticipated when marketing 

particular coal-product qualities. 

SUMMARY 

Coal-resource assessment is a dynamic, phased process requiring input from geologists, mining engineers, preparation engineers, 

marketing departments, and corporate management. Early input from 

the marketplace is essential in identifying opportunities for 

coal-product penetration. Predicting the range of mining conditions expected to be found as well as the range of coal qualities 

found and coal-product qualities producible requires extrapolation 

of data on less than 10 tons of material to a reserve that may 

have over 100 million tons of recoverable coal. Because this 

sample is so small and the results of the exploration program and 

engineering evaluation affect a $100 million corporate decisio~ on 

144 
t-' 

~ 

VI 

1000' Radius 

8 

Parallel to 

Shoreline 

m 

Back 

Barrier 

Swamp 

1320' Radius 

0 

Lower 

Delta 

Transitional 

Lower 

Delta 

Plain 

2000' Radius 

Parallel to 

Stream and River Direction 

m n 

Upper 

Delta 

Plain 

--

Alluvia 

Plain 

~ 

1000-500' Radius 

8 0 

ErraticNot Predictable 

Environment 

Plan view 

Cross section 

Consistency of seams 

is controlled by paleoenvironments which dictates 

"radius" of influence. 

in 

~ 

General Terms} 

~ Suggested Trend 

~ =fR= of Grid 

Figure 23. Use of depositional models to reduce costs of exploration drilling. 
f--4 

+:---

0"1 

0 

I 

~ 

<( 

2 

~ 

<{ 

C> 

COMPOSITED EXPERIMENTAL AND THEORETICAL 

SEMI-VARIOGRAMS OF GENERALIZED COAL QUALITY 

IDEALIZED RESERVE, NORTHERN APPALACHIA all data 

I 

·-

-

-

-

-

00 o o 

0 00 ooo o 

0 () 0 

0 0 0 0 

00 0 0 

0 0 Go 0 

0 oOO 0 0 

0 °0oo 0 0 00 ° 

0 0 

0 ° 0 aD 0 

0 0 00 

0 

0 

0 

0 0 0 00 

0 0 

o·<Q o o o o o 

0 

0 

0 0 0 0 

0 

0 0 

0 

-1 0 0 

~0 

-

0 I I I I I I I I I I I I I I 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

FEET x 1000 

Figure 24. 
J-1 

-l:'-

......, 

0 

I 

!<{ 

<( 

~ 

::E 

<( 

" 

COMPOSITED EXPERIMENTAL AND THEORETICAL 

SEMI-VARIOGRAMS OF GENERALIZED COAL QUALITY 

IDEALIZED RESERVE, NORTHERN APPALACHIA zone 1 

oo o o o ooooo o 

0 0 

0 0 

0 00 

0 

0 

0 

0 0 

0 0 

o~~~--~~~~~--~~~~~~~~-

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

FEET x 1000 

Figure 25. 
1-' 

.&::--

(X) 

0 

I 

~ 

<( 

~ 

~ 

<( 

(!) 

COMPOSITED EXPERIMENTAL AND THEORETICAL 

SEMI-VARIOGRAMS OF GENERALIZED COAL QUALITY 

IDEALIZED RESERVE, NORTHERN APPALACHIA zone 2 

onoooo o 0 .u 

oo 

00 

0 

Bo 

0 

o~--~~----~~~~~--~~~~----

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

FEET x 1000 I I 

Figure 26. 
1-' 

.,1::-o 

\.0 

COMPOSITED EXPERIMENTAL AND THEORETICAL 

DIRECTIONAL SEMI~VARIOGRAMS OF GENERALIZED COAL QUALITY· 

IDEALIZED RESERVE, NORTHERN APPALACHIA zone 1 

0 

I 

~ 

<( 

~ 

~ 

<( 

" 

-

-

-

-

-

-I .-

0 

-

-

(N-S DIRECTIONJ .Q····O········O··.:.:.:.li·.:.·-·ts ... O~A-.o- 6---6. 

.0 A .... -

£f ... .a' 0 ~, ... 

. 45. ~A f,...E---W....,D-IR....,E-C-TI-0-NI 

{;) ty . A' 

, 

, 

o· ,'if 

I , 

d f1 • I 

I 

6 

I 

I 

I 

Legend 

o N-S DIRECTION 

6 E-W DIRECTION 

0 I I I I I I I I I I I I I I 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

FEET x 1000 

Figure 27. 
~ 

tJ1 

0 

COMPOSITED EXPERIMENTAL AND THEORETICAL 

DIRECTIONAL SEMI-VARIOGRAMS OF GENERALIZED COAL QUALITY 

IDEALIZED RESERVE, NORTHERN APPALACHIA zone 2 

0 

I 

~ 

<{ 

~ 

~ 

<( 

~ 

-

-

Legend - o NW-SE DIRECTION --·--·--

X NE-SW DIRECTION - -----

-1 INE-SW btRECTtONI 

. Q <>-·-o 

-1 

)fo 

--1~~-SE DiRECTiONI 

-

Q I I I I I I I I I -~-r I I I 

0 2 4 6 8 10 12 14 16 18 20 22 24 26 

FEET x 1000 

Figure 28. 
w 

> Ck: 

::> 

u 

>- J-

_J 

<( 

:::::> 

0 

__) 

<( 

0 

u 

(/) 

::::> 

(/) 

0::: 

w 

> 

r--

(/) 

0 

u 

z 

0 

B 

::::> 

0 

0 

0::: 

a_ 

··o·--······0 

0 

·. 

·o ..... -e 

I 

~--------------------------~0 0 

(J S3SV3CJ:>NI AlllVnO l:>naO~d lVO:> 

151 

0 

(f) 

w 

(f) 

<( 

w 

0:: 

u 

z 

1-

lf) 

0 

u 

z 

0 

t-· 

c 

--. 

...... 

c 

c 

Ct:: 

(L 
....... 

V1 

N 

ANTICIPATED MARKET PRICE VERSUS COAL QUALITY CURVE 

0 

Vl 

w 

(11 

<( 

w 

a::: 

u 

z 

>- 1-

....J 

<( 

::> 

0 

-

: 

p 

: 

d 

.. 0······0··· 

~···········0· 

O·~····O·······O·······O 

.0 

_J (]}······0··0' 

<( 

0 

u 

0~----------------------------~ 

0 

ANT!C!PATE11 ~AARKET PR!CE !!'!CREASES r'\ 

Figure 30. 
1-' I V1 

w 

CURVES COMPARING PRODUCTION COST AND ANTICIPATED MARKET PRICE 

VERSUS 

0 

(f) 

w 

(/) 

<( 

w 

~ 

u 

z 

>- .--

::J 

<( 

=> 

a 

_J 

<( 

0 

u 

COAL PRODUCT QUALITY 

1 

I 

I 

I 

.....a- --e---~J 

c er · 

/ 

Vl pr Ji .. 6 ...... --l:l·· ·······ll 

I B. ---.:-e-::::t-~ ....---------, 

I ;~--~· Legend 

o PRODUCTION COST 

I /" ..... 

1 fD f1 

~~~-~/ 

6 ANTICIPATED MARKET PRICE 

0-+-1----· 

0 

PR0l1l JCT!t1N coc;T ANn MARKET PRI~E INCREASES L> 

Figure 31. 
mine development, it is important that resource assessment te.ams 

(a) interact at all levels, and (b) use all ·the "tools" (that is, 

depositional modeling, geostatistics, geologic interpretation, and 

so on) available, and use them properly. 

Only when the resource has been characterized and the project 

engineered sufficiently to predict with reasonable confidence the 

cost of production, and when a buyer has committed to purchase the 

mine production at a price level that results in an attractive 

investment for the mine construction, will a company commit 

capital to open the mine. 

154 
A NATIONAL AGENDA FOR GEOLOGICALLY RELATED COAL RESEARCH 

by 

Donald C. Haney 

Kentucky Geological Survey 

Why do we need to know more about coal quality? This Nation 

has billions and billions of tons of coal, so why the concern? I 

truly wish it could be so simple. 

Sometimes I think coal researchers and developers have a very 

narrow view of the subject about which they are supposed to be the 

experts. It may be caused by isolation or ignorance or apathy--

who knows? So, for the next few minutes I am going to talk about 

coal in general, and then finish my presentation by mentioning 

research areas I consider important. 

Even though I represent the coal-producing States of the 

Association of American State Geologists, what I say today 

reflects my own opinions, but not necessarily those of the entire 

group. 

From coal, this Nation produces 55 percent of its electrical 

needs. In 1984, the United States produced nearly 800 million 

tons of coal valued at $26 per ton, and that alone contributed $22 

billion to the national economy. Together with its related goods 

and services, coal is a very major contributor to our national 

economic well-being. Coal is as valuable to this Nation's economy 

as are all metallic and nonmetallic minerals combined. Coal 

constitutes 70 percent of the known fossil fuels on earth. But 

coal has a bad name. Who is interested in coal? I am, you are, 

and others should be. 

Figure 1 demonstrates that our ability to produce oil at the 

pace of current world consumption and population growth is in 

jeopardy. For the near and possibly distant future, coal will be 

our principal source of electricity, and in time, coal will 

probably be our principal transportation fuel. We once had 

coal-fired steamships and trains, and we may see their return in 

the future. 

Even though coal and the services it generates are very 

important to our national economy, very few dollars are earmarked 

for research on coal. The present administration is, through the 

155 
I-' 

Vl 

0\ 

World Crude Production vs. 

50 

~"'1 

~ ~40 

~' ...... 

~ ~ 30 

i:CI) (..) <: 20 ~ ~0 

Q~ 

g ::::! 10 G:=~==· 

a..S 

Population 

10 

:c: 

0 

8 i: 

q:Ci) 

6 s :c: a..O 

0~ 

4 a.. ::::! 

oe 

...... l&a .. n..,.a\1- 2 ~ 

3;: 

0 ·- 0 

1900 1925 1950 1975 2000 2025 2050 2075 2100 

YEARS 

~ 

Cumulative Production 

489 x 109 BBL 

Proved Reserves 

679 x 109 BBL 

AFTER OIL & GAS JOURNAL, 12/24/84 

Figure 1. 

~ 

Still To Be Discovered 

832 x 109 BBL 
Environmental Protection Agency (EPA), talking about putting 

several millions of dollars into acid-rain research, but I would 

like to point out to you that new money is not being appropriated. 

That money will come out of someone's budget, and it may be thet 

of the U.S. Geological Survey. 

Why has coal-related research fallen on such hard times? For 

example, at the Federal level why do we have to hide coal-related 

research by calling it something else such as Regional Geology or 

Evolution of Sedimentary Basins? Do we hide oil and gas research, 

uranium-thorium research, volcano research, or earthquake research? 

Why coal? 

Why does the U.S. Office of Surface Mining spend millions of 

dollars on regulating mining, reclaiming abandoned mine lands, 

pumping grout into the bottomless pits of old underground coal 

mines, and allocate only pennies for research? 

Whether it pleases us, the EPA, the Sierra Club, Common 

Cause or anyone else, coal will have to provide most of this 

Nation's and the world's near-future energy needs. By the year 

2000, the portion of the world's energy supplied by coal will 1'ave 

grown from 19 percent to 32 percent. 

So why are the press, public, special interest groups, and 

government putting so much pressure on coal? It's almost like 

shooting yourself in the foot. Why are we putting so little 

research effort into coal? Why is our government deserting coal? 

I realize that the people in Alaska, California, Missouri, 

southern Illinois and Indiana and western Kentucky are concerned 

about earthquakes. I know the people in the Cascades of the 

Northwest and in Alaska are concerned about volcanoes. But, does 

that concern warrant or justify a particular research organization 

spending approximately six times as much money on those areas last 

year as on coal from which 55 percent of our electricity is 

generated? 

In recent times, we've had only one volcanic eruption in the 

continental United States, and that was in a very remote area. If 

better judgment had been shown, possibly no lives would have b~en 

lost. I am not necessarily suggesting that we spend less on 

earthquake and volcano research, but I do declare an urgent ne~d 

to increase spending for coal research. 

Do the special interest groups and Congress realize what they 

are saying when they advocate raising clean air standards? Do 

people from noncoal-producing States which use electricity generated from coal realize what is happening? Do regulators who h~lp 

set policy and advise Congress acknowledge or consider the impqct 

157 
of certain pieces of legislation on our population? By law the; 

are supposed to. 

It is easy to sit in an office in Washington and formulate 

rules and regulations for the coal industry and related industri.es 

if one is not held responsible for the impact of such rules and 

regulations on society, individuals, States or the Nation. If 

Congressmen, overzealous environmentalists or overbearing reguletors could be held responsible for the adverse impact of poorly 

conceived, unreasonable, and unnecessary rules and regulations c~ 

people or the Nation, maybe they would be more objective. If 

these same people had to be responsible for providing adequate 

coal supplies at reasonable costs when the temperature is -20 

degrees, then they might take a more objective approach in 

formulating rules and regulations for others to live by. 

Let us consider one State, one with which I am very 

familiar--Kentucky. Kentucky produced approximately 150 million 

tons of coal last year, having a mine-mouth value of $4.5 billion. 

Twenty-seven percent of Kentucky's tax revenue comes from coal. 

The value of coal production in Kentucky is about twice that of 

agriculture and livestock combined, including tobacco. 

What happens if Kentucky's coal production drops significantly? Who takes the responsibility for feeding displaced people? 

Who keeps the children in school? Who is responsible for the lost 

dignity of once-proud families? The Sierra Club? EPA? Congress? 

Who is responsible, or better yet, who will assume responsibility? 

If you think electricity is high now, just wait. 

In Kentucky, we already have a public debate and a split 

between some western Kentucky coal operators and eastern Kentuck:? 

coal operators. The problem concerns low-sulfur coal. Eastern 

Kentucky has a significant amount of low-sulfur coal. Western 

Kentucky has very little (figs. 2 and 3). 

It is obvious that most of Kentucky's compliance coal is in 

eastern Kentucky, but only 40 percent of it is in compliance at 

1.2 pounds of sulfur dioxide per million Btu. In western Kentucky 

only 2.5 percent is in compliance at 1.2 pounds of sulfur dioxide 

per million Btu. Should the emission standard be changed to 0.8 

pounds of sulfur dioxide per million Btu, only 5 percent of 

eastern Kentucky coal would be in compliance, and none of the 

western Kentucky coal would meet this standard. 

It is unlikely that the utility companies will devise new or 

improved combustion technology to comply with clean-air standards 

if they can get low-sulfur coal. By high-grading, we can providP. 

low-sulfur coal from eastern Kentucky, but at what cost, and for 

how long? In fact, most of the low-sulfur coal in eastern North 

America is within a 100-mile radius of Pikeville, Kentucky. 

158 
Histogram of Frequency Distributior 

For Potential S02 Emissions for 

Eastern Kentucky Coal Resources 

33 

30 

27 

STANDARD FOR 

• COMPLIANCE COAL 

3 

0 I = 

11.2 2 3 4 5 6 

POTENTIAL S02 EMISSIONS 

(S02 LB. PER 106 BTU} KGS 1985 

Figure 2. 

159 
~ 

0'\ 

0 

~ (.) 

§ 12 

0 

~ 9 

a: 

g, 6 

f-.., 

~ 3 

(.) ffi 0--

a... 

Histogram of Frequency Distribution 

For Potential S02 Emissions for 

Western Kentucky Coal Resources 

STANDARD FOR 

~COMPLIANCE COAL 

4 5 

POTENTIAL S02 EMISSIONS 

(S02 LB. PER 106 BTU) KGS 1985 

Figure 3. 
What does all this have to do with a conference on coal 

quality? Everything. We must burn coal and we must do it 

responsibly; also, we must zealously preserve and protect our 

resources. We must find ways to do both. 

If our coals are not clean enough to burn and at the same 

time protect our air quality, then we must clean them. If we 

cannot clean them using known technology, then we must improve 

known technology and devise new technology. To devise new 

technology for cleaning requires us to learn everything we can 

about coal. Its composition affects cleaning and combustion. 

Much research is needed in the area of combustion. We cannot 

expect our mining industry to bear all the burden of providing 

clean coal. The utilities are part of our system, and they tc':l 

must accept a fair share of the burden. 

Attitudes must change. Government must help. Industry D',\St 

help. We do not have unlimited natural resources as we once 

thought we had. We can no longer afford to mine and use our 

mineral resources in a helter-skelter fashion as we have in t~e 

past. Our resources must be managed and used responsibly. 

For example, how would high-grading affect marginal coal~? 

It would render many unmineable. Already some of the higher 

sulfur coals are being put on spoil piles in order to meet 

competitive market demands. How would high-grading affect the 

energy supply of future generations? It would deprive them of a 

resource that I think we are obligated to share with them. ~'at 

is our responsibility to future generations? Obviously some 

people think there is none, and others don't care. Still others 

are very concerned. Nonrenewable resources should be guarded with 

zeal and consumed with discretion. We are all responsible; the 

miner, the utility company, the consumer, the regulator--it's a 

responsibility that we all must assume. 

I am not an expert on water chemistry or the physics and 

chemistry of air. However, I do know that lakes and other bo~ies 

of water are dynamic systems, and that the chemistry of these 

systems depends on many things such as rocks, development of both 

flora and fauna, and the age of the water body. They are very 

much a part of nature's evolutionary scheme. I also know that 

rainfall is not the only thing that determines the water chemistry 

of a body of water. Therefore, is sulfur from the combustion of 

coal the only contributor to acid rain or acid lakes, or is it 

just an obvious contributor and one that is easy to attack? 

Are we sure? Are we willing to use our precious low-sulfur 

coal while at the same time we destroy millions of tons of 

marginal coals because of a possible misconception or mistake? 

We've done similar things before. What about other nations cf the 

161 
Earth with which we share a common atmosphere? Are they willing 

to go to the necessary expense to meet the same high clean-air 

standards that are being proposed? The answer right now is no. 

If they are not, then what will be the impact of our efforts-on 

the world's atmosphere? What impact does the added expense of 

mining coal in the United States have on the world coal market 

where we are already competing with subsidized mining? What is 

the impact on our balance of trade? 

Colombia is shipping coal into the southeastern United States 

cheaper than Appalachian coal can be produced. There are many 

reasons why they can do this. One is that their industry is State 

owned and regulated. 

The coal industry in the United States is one of the most 

regulated industries we have, and it is also a very essential one 

for our present and future welfare. I truly hope that we do not: 

shackle the industry with regulations. It is indeed one of the 

industries that has helped make this Nation great and one that ~as 

helped us attain the highest standard of living in the world 

today. 

If we assume that the government, industry, concerned citizens, 

and people in general acknowledge the need, we can achieve much 

toward our goals through research. In my opinion, the national 

agenda for geologically related coal research should include: 

1. Characterization of major coal beds - All major coal beds 

should be characterized by representative sampling and 

analysis by chemical, physical, maceral, and mineral methods. 

2. Geologic mapping - Geologic mapping is the foundation of all 

geologic and resource studies. Resource estimates are not 

possible without outcrop mapping. Nationally, we are not 

doing much in this research area. 

3. Thickness mapping - Thickness mapping is also essential for 

resource estimates and for geologic modeling. 

4. Coal-quality mapping - Coal-quality mapping is important for 

determining trends in coal quality and resource availability, 

and for geologic modeling. 

5. Resource estimates - Resource estimates are important for 

public policy decision making, revenue predictions, 

utility-fuel projections, transportation projections, 

financial planning, and geologic studies. · 

6. Modeling of coal-forming environments - Modeling of coalforming environments is vital for interpolations and 

extrapolations of coal thickness and quality data, and it is 

162 
also valuable for predicting mineability. Understanding of 

the modern analogues so often referred to, Mississippi River 

Delta, Okefenokee Swamp, and Everglades, is not sufficient; 

further research into modern swamp environments should be 

encouraged. 

7. Characterization of sulfur- Characterization of sulfur is 

important because sulfur is the most notorious contaminant in 

coal; it is also important in geologic modeling and resource 

classifications. Sulfur occurs in a variety of forms in coal, 

and much of it has unknown origins. We must characterize 

these forms and study the sulfur isotopes to determine the 

sources of sulfur in coal. 

8. Geostatistical methods for coal study - It is important that 

we improve our quantitative methods for studying coal; these 

include resource calculations, measure of variability and 

uncertainty, and coal-quality predictions and variability. 

9. National Coal Resources Data System - This Nation needs a 

centralized and uniform coal resources data system. Currently, the U.S. Department of Energy, Energy Information 

Agency; U.S. Geological Survey, National Coal Resource Data 

System; and Bureau of Land Management all maintain separate 

coal-resource data bases. Efforts should be made to 

coordinate these separate, and sometimes conflicting, data 

bases. 

Work is going on in these areas now, but not at levels equal 

to the need; therefore, the levels of funding must be raised. 

Overlap among various governmental agencies wastes research 

dollars through duplication. Overlap should be eliminated. 

The major research agencies for coal are performing many 

tasks that might be better done by local agencies. Perhaps the 

efforts of major agencies would be more effective if directed 

toward more basic research which often involves highly specialized 

analytical tools. 

Finally, we need cooperation between Federal, State, and 

private agencies before research is initiated and after it is 

underway. This doesn't always happen today. If we don't chanre 

this situation, then improvement in the effectiveness of coal 

research, which,is so sorely needed, will be much slower in 

becoming reality. 

163 

U.S. GEOLOGICAL SURVEY COAL-QUALITY RESEARCH 

by 

Terry W. Offield, Susan Garbini, and Stanley P. Schweinfurth 

U.S. Geological Survey 

INTRODUCTION 

The U.S. Geological Survey (USGS) coal program consists of 

three major parts: 

1. Studies of the sedimentary rocks containing the Nation's 

coal resources and their environments of deposition. This 

involves geologic mapping and delineation of stratigraphic relationships and sedimentologic character, leading to interpretation 

of the original conditions of peat deposition, and the subsequent 

geologic history involved in coalification of the peat. 

2. Characterization of peat, lignite, and coal according to 

the type and composition of their organic and inorganic materials. 

The nature and composition of the macerals, including their 

original botanical character, and the chemistry and mineralogy of 

the inorganic components define the quality of the fuel material 

and prefigure much of the utilization process. This work, 

together with the studies of the enclosing rocks, is intended as a 

basis for models that will be useful in assessing the Nation's 

coal resources and predicting the character of coals out acrc~s 

basins long in advance of actual exploration or mining. 

3. The National Coal Resources Data System (NCRDS), a 

computerized bank of information on more than 100,000 drill l'':lles 

and measured sections and 10,000 coal and rock samples. Coalquality data consist of the usual data from proximate and ultimate 

analyses, ash-fusion temperature, and so on, and also comprel'~nsive multielement chemical data. Data and samples are provirled to 

NCRDS by 20 State organizations; analyses are performed by tlv~ 

USGS and by contract laboratories. Much of the analytical work 

has been supported by the Department of Energy and the 

Environmental Protection Agency. 

Coal quality is a vital issue in the Nation's energy and 

future. This meeting was conceived and organized with the 

cosponsors in order to survey a broad array of Government, 

165 
industry, and academic concerns and ideas having to do with coal 

quality. It is expected that the symposium results will be u~eful 

in planning USGS research efforts, especially in gauging new 

directions, and assigning priorities. Conversation among such a 

variety of coal experts as are gathered here can provide a wh~le 

field of coal knowledge and insights into its optimal utilization. 

Background 

There is no argument today about whether the United States 

has enough coal. In 1974, the USGS estimated the country's coal 

resources as about 4 trillion tons--a lot of coal by anyone's 

standards. It should be noted that much of the estimated resource 

is in the "hypothetical" category; that is, it has not been tested 

by the drill and is simply projected by geologic reasoning to be 

out there underlying sedimentary basins. Much of the stated 

resource will prove to be unavailable for recovery--overlain b:? 

roads or towns, too deep or too thin by today's economics, or 

perhaps of too poor or too variable quality to permit economic use. 

However, there is still a lot of coal, and developing new technologies of coal utilization might well expand the range of coals 

that can be used economically. The successful design and use of 

such technologies, however, will rest on better knowledge of coal 

quality and how it varies within coal beds, from bed to bed in the 

same sequence and from area to area. Such knowledge will also be 

the undergirding of an appropriate structure for regulation of 

coal use and determination of environmental standards. 

Whether our vast coal resources will serve us in environmentally and socially acceptable ways will depend to a large 

extent on the physical nature or quality of that coal. Coal i~ a 

complex and heterogeneous mixture of organic and inorganic 

constituents whose composition may vary significantly between coal 

beds or even over short distances within a single bed, as sho~ by 

the real example of sulfur and ash contents in two coal beds 

illustrated in figure 1. Because of this kind of variability in 

coal quality, particularly with regard to constituents that affect 

the environment, much more basic and applied research is required 

to determine the most efficient and least environmentally harmful 

ways in which to utilize coal. 

Horror stories abound concerning multimillion-dollar mistakes 

or problems that arise because of too little awareness of coal 

quality. In mining, a recent reported example showed a large 

western mine operation losing 4 million tons of production because 

of unacceptable sodium content in the coal--an unforeseen change 

in the reserve that might have been predicted with better understanding of the local geologic setting of the coal. 

Plans and procedures for blending and cleaning coal to meet 

consumer standards often go awry because of unexpected variation 

166 
f-.' 

0'1 

'-J 

COAL 8 

UPPER 25 BENCH 

PARTINGS 

MIDDLE 1 BENCH 

PARTINGS 1 

LOWER 

BENCH 22 

VARIABILITY OF 

SULFUR & ASH 

WITHIN A MINE (%) 

Figure 1. An example of the variability of coal 4uality as demonstrated by the variations 

in sulfur and ash within a single coal bed (bed B) and between coal beds (beds A 

and B), based on an actual situation. The vertical lines within the block 

diagram represent cored drill holes. (Source: P.C. Lyons, U.S. Geological 

Survey, written commun., 1984.) 
in the delivered coal. Many such procedures focus on sulfur 

content in coal, but other chemical and physical components, 

commonly not even analyzed for, also cause problems in the utilization of coal. Mineral matter in coal is a major cause of 

slagging and fouling of equipment when coal is burned or gasified, 

and it causes myriad problems with filtration, catalysis, and 

abrasion when coal is converted as in liquefaction and solvent 

coal refining. Similar problems arise in the design of pollutioncontrol equipment, where the interactions between pollutants and 

their effect on the operation of control equipment complicate 

design and make it difficult for operators of coal-fired boilers 

to select the optimum control method. (For instance, the 

properties of ash are a significant determinant of collector 

performance when an electrostatic precipitator is used for ash 

removal.) Attributes of coal that will be relevant to the 

fledgling synfuels industry are still poorly understood, but 

billions of dollars almost certainly will be spent on new technologies, and their effectiveness and success and breadth of 

applicability will be inextricably tied to the character of the 

coal put into the technological processes. 

Efforts are being made to find solutions to the problems 

associated with coal use, but it is possible that the fixes 

designed for currently perceived problems may give rise to a host 

of new or previously unrecognized problems. For example, if a 

solution to the problems of SOx and NOx emissions were achieved, 

resulting in increased use of coal, other noxious materials in 

coal such as arsenic, lead, cobalt, chlorine, and fluorine might 

reach harmful levels of concentration in the environment. In 

order to avoid a pattern which might lead to the ramification 

rather than the mitigation of environmental damage, it is essential to establish a comprehensive understanding of the complex 

nature of coal as the foundation for wise and economic coal 

utilization. 

Current knowledge about coal-quality parameters as they 

relate to coal resources is limited by a small number of samples, 

incomplete characterization of coal quality, and an unrepresentative distribution (fig. 2). Most data on coal quality refer to 

mined-out areas; there are very little data on the quality of 

deeper coals yet to be mined (fig. 3). As high-quality coal is 

depleted (we always mine the best of the most accessible coal 

first), it will be necessary to understand and predict in advance 

the nature of the deeper coals farther out in the basins. It 

cannot be assumed that those coals will be of poorer quality than 

coals along the outcrop--the original depositional environment 

controls on coal character may just as well have produced better 

coals downdip--but we won't know until we have enough information 

to make predictive models of coal regions and coal types. 

168 
,.... 

"' 1.0 

.. 

z 

0 

... 

,__ 8 

~~ e ::c: • .. -. z 

0 

:::; 

..J 

i 

2 

.. 10 z 

0 

... 8 

... a: • - e 0 ~ ::c: • .. -. z 

0 

:::; 

..J 

i 

DEMONSTRATED RESERVE BASE OF COAL 

ACCORDING TO TOTAL SULFUR CONTENT 

POWDER RIVER BASIN 

... 

.. 

<# 

~ .. .. .... • ~ ~. ~ ' ····-·· ~ 

... ... \ 

... 

• • . ... 

... .. .... . 

;I 

... 

• • I ~ • I . ~ 

c;. ... ... 0 

. 

0 

. \ 

.... ... 

... ' \ .. 

.. . ·., . ~ ·.... 0-i. 

... TOTAL SULFUR CONTENT I"') 

.. .. 

• 

WESTERN INTERIOR 

. • .. 

BASIN 

~ ~~~ . ..~ . :-'~ .. •J 

c:>. "~ ~ ... . ~~ 

. .... !~. ·~ .. ~ .. _ ~ &..~ ~~ ~ 

... 0 

. ... \ ....... ~ 

~ -~ ! ~ .. 0 \ ... ... ... . ~~"oi. ~ , .. TOTAL IULFUR CONTENT 1-.1 

.. 

z 30" 

0 

.... 2 5 

;..-

et• 20 oo 

; :;u5 

z-1o 

2 s -' -' 

i 

SOUTHERN APPALACHIAN 

BASIN 

0 

... 

0 

. 0 

~ 

... 

.. 

0 ~ -' ... 

.. \ 

.. 

. .. .. 

... 

... 

~ 

• 

\ 

.. .. ... ~ ~.. ~ .,.'So 

~ "- oi:. ... ... TOTAL SULFUR CONTENT 1-.1 

.. 2 z 

0 

... 

,__ 

~! 1 

:z: • .,_ 

.. 

z 

NORTHERN APPALACHIAN 

8 

.. ~ 

. .. 

... 

0 

. 

0 

. \ 

... 

... \ 

... 

. .. ... 

... \ 

.. . 

.. .. \ • ., 

~ \ ~ ...... 0 

i... 

TOTAL SULFUR CONTENT 1"'1 

CENTRAL APPALACHIAN 

BASIN )"" 0 1• ~::~ ... S .. ~ ,__ 

a:" 1 00 l:;; 

.,_ 

z 

0 

-' 

-' 

i 

.. 

~. 

... 

,. 

0 

. 

!I"~ s-~ k ..~~ .• 

~· 

~~\ ~ ~ '~~. 

"., rTI ~: 0 ~ .... 

!., ~:--~ ~~~ ~:..~ 

0 , , ., .. ~ 

. ', -~ ~ ~ .,..,. \ -~ .., f# , 0 , .• ., -i. 

... TOTAL SULFUR CONTENT 1"'1 

Figure 2. For most U.S. coal basins large amounts of coal resources have not been sampled and analyzed for 

total sulfur content. This is shown by the large amount of coal in the unknown category for 

each basin. The Central Appalachian Basin, where there is a much higher level of certainty 

about sulfur distribution, is an exception because of the long history of mining of 

high-quality, low-sulfur coal in that area. Sulfur data are on an as-received basis. (Source: 

J.H. Medlin and F.O. Simon, U.S. Geological Survey, written commun., 1984.) 
t-' 

....... 

0 

SAMPLE LOCATIONS 

AND OUTLINE OF THE 

PITTSBURGH 

COAL BED 

OH 

• 

wv 

fl1d 

~ 

PA 

• 

VA 

• SAMPLE LOCATIONS 

Figure 3. The Pittsburgh coal bed serves as a typical example of the distribution of coal samples from 

coal beds in the United States. Most samples for which data are available for public purposes 

are from the edges of the main deposit and from isolated pockets, or outliers, of the main 

deposit. These are areas that have been mined out or are being mined currently. Few or no 

samples are available from the more deeply buried parts of deposits. (Source: J.H. Medlin and 

F.O. Simon, U.S. Geological Survey, written commun., 1984.) 
Because of the general paucity of up-to-date coal-quality 

information, one frequently hears such statements as: Appalachian 

coal is medium-sulfur; midcontinent coal is high-sulfur; western 

coal is low-sulfur. These generalizations are misleading and oversimplified and do not provide a correct basis for decisionmaking 

concerning coal utilization. 

For example, such discussion of the pollution-control issue 

revolves around the misperception that a switch to low-sulfur 

western coal would solve the problem of acid precipitation related 

to stationary sources. However, most low-sulfur western coal is 

also much lower in Btu content than midwestern and eastern cocl, 

so in order to obtain equivalent heat value more coal would hcve 

to be mined and burned. Thus, a lot of sulfur would be releaEed 

into the environment as the overall amount of coal burning 

increase~, and other important environmental disruptions and 

economic side effects of the switch to western coal would come 

into play as well. 

Figure 4 shows the average sulfur content of coals by major 

coal basins with respect to existing and suggested limits on 

pounds of S02 per million Btu. Although the dots on the grapl' 

represent basin-wide averages of available data on sulfur, th1,s 

figure suggests that there are few areas that could maintain 

sustained production of coal to meet current new-source perfoJ~­

ance standards, and none that could meet a suggested lower le~el 

of allowable sulfur input of 0.6 lb of S02 per million Btu. Preor post-use cleaning could change this, but only at increased 

costs. 

There also are difficulties in the presumption of an easy fix 

to the S02 emission problem by using eastern low-sulfur coals 

(locally available but not regionally abundant) because: (1) 

these coals are nearing depletion along the outcrop belt, which 

means that future mining must be at increasing depths and exp~nse; 

(2) reliable identification and characterization of large remaining quantities of this type of coal are lacking; and (3) there is 

competition for this type of coal for domestic metallurgical uses 

and for export. Careful and systematic characterization of all 

U.S. coal resources may reveal more low-sulfur, high-Btu coal that 

can directly meet the requirements for S02 reduction or that can 

be cleaned or blended to meet proposed tightened standards, but it 

will require substantial additional work to either prove or 

disprove this possibility. 

A further point of concern is secondary pollution associated 

with the burning of coal. Removing pollutants by pre-use cleaning 

or from smokestack emissions may simply transfer them to the solid 

wastes and water emerging from the coal-use processes. For 

example, if sulfur is removed during coal conversion and disp~sed 

of with the ash or waste pile, water percolating through the waste 

Ul 
5.0 

4.0 

ILLINIOS 

BASIN WESTERN 

'- JMIERIOR 

BASIN ::J 

..... • ::J 

tn 3.0 :::::> 

J~ 

ro 

- c c NORTHERN • :::::> APPAl.ACHIAN Q) 

0 ~ 

~ 1-

'- BAStN m 

Q) ... c Q. • a. ~ 

2.0 N 

0 ~ (f) ... 

C) ,_ a. 0 

N 

.a • 0 

FORT 

UNION 

WAR ~lOR .... en 

SAN JUAN ~ -0 BAS hN 

R BASIN 1.0 LIGNITE 

=~~~~E ~ . ~-- - -:~.- ~------

T 

BASIN 

---- .. ------- RATON ME ~-A- - - - - - - - . ------- ------------- 0.0 

10 11 12 13 14 

BTU per Pound (thousands) 

+ :9 --- _ ... CD SOUTHER 0 

HIAN + 

N 

APPALAC 

I-BASIN_ ---

15 

Figure 4: On the basis of the data in the U.S. Bureau of Mines 

Demonstrated Reserve Base of Coal, very few areas can be 

expected to contain large quantities of coal that will meet 

current new-source performance standards (NSPS) for so2. 

Even fewer areas can be expected to contain large amounts of 

coal that will meet the stricter level of SOz input that has 

been suggested by some groups without some kind of pre-, 

syn-, or post-utilization modification. (Major coal basins 

are shown in figure 2.) The dots on the chart represent the 

means and the bars represent one standard deviation about 

those means for Btu and total elemental sulfur content from 

the data available for the coals of each area. Analytical 

data are on an as-received basis. (Source: F.T. Dulong, 

U.S. Geological Survey, written commun., 1985.) 

172 
material may be acidified, mobilizing and transporting a vari~ty 

of polluting chemical elements into the local environment. Coal 

cleaning does not eliminate any elements. The trace-element 

content of the cleaning water is tremendously enriched, which can 

cause serious pollution problems. The chemical composition of fly 

ash is influenced by the composition of source coal and by plant 

operating conditions. If scrubbers are used, a proportion of the 

contaminants will end up in the scrubber sludge, causing disposal 

and potential ground-water problems. Little information is 

available on the potential emissions of trace pollutants from coal 

combustion or conversion processes. More data on coal quality are 

needed to evaluate and improve control options. 

If we are to rely on increased use of coal to meet our future 

energy needs, without allowing the quality of the environment to 

deteriorate, we must conduct research that will provide us with an 

adequate information base for predicting and controlling the 

effects of emissions and effluents from coal, and for optimizfng 

the development of technology for coal cleaning, burning, and use 

in synfuels production. In the long run, and perhaps even in the 

near term, research focused in these directions will be much less 

costly than mistakes in design of processes or equipment or ir 

setting policies and regulations. 

Coal Research Activities 

For decades, the USGS has had at least a few individual 

researchers working on coal-quality topics. Prominent among these 

were David White, who wrote classic papers on the origin of cc~l; 

Reinhart Thiessen, founder of coal petrography in the United 

States; Taisia Stadnichenko and Peter Zubovic, who developed the 

concept of elemental affinities in coal and began defining the 

distribution of minor and trace elements in coals of the Unite~ 

States; James Schopf, continuing the basic research on the or1gin 

of coal; and Irving Breger, with advances on a broad front in 

organic geochemistry of fossil fuels. An irony of some of thjs 

forefront research is that it was not done for the sake of coFl, 

but rather because of short-term major interest in trace elements 

like uranium and germanium. 

Today coal-quality research is well recognized as a 

critically important aspect of the overall coal program, and the 

research is expanding to serve the needs described in the preceding section. Coal-quality work at the USGS comprises: 

o Basic and applied research into the physical and chemical 

nature and cycling of the organic and inorganic constit.'.tents of coal, focusing on the rapid identification and 

quantification of sulfur-bearing components and other 

noxious and deleterious components. 

173 
o Basic research into the geologic aspects of deposition and 

formation of coal that also control the petrographic a~d 

chemical variability of coal beds. 

o Investigations of the nature and modes of occurrence of 

chemical contaminants in the rocks that surround and are 

interbedded with coal. 

o Studies of the occurrence, distribution, and accessibility 

of coal deposits that have specific chemical and physical 

properties. 

o Development of field and laboratory methods, instruments, 

and techniques to analyze, examine, interpret, and pre4ict 

coal-quality parameters that can be related to coal cleaning or feedstock characteristics, and to determine the 

distribution of these parameters in coal deposits in 

relation to geologic and geochemical factors. 

o Routine, reliable, and credible analyses of coal samples 

for calorific value, ash, moisture, and sulfur, and 70 

major, minor, and trace elements. 

o Maintenance of a computer-based system for the storage, 

retrieval, and manipulation of data on coal quality and 

quantity. 

Because coal typically is such complex material, the key to 

understanding it is in petrographic and chemical analysis using an 

array of increasingly sophisticated techniques. It is necessary 

to characterize the macerals as telinite, fusinite, cutinite, 

sporinite, and other such components, and to determine their 

paleobotanical origins, in order to establish the origins of coal. 

It is necessary to identify inorganic components of coal beds, to 

ascertain their depositional or diagenetic origins, and to 

determine the partitioning of significant trace elements betwnen 

the inorganic and organic materials of the coal. It also is 

necessary to decipher the effects of coalification on the starting 

materials, and the nature of the coalification process. Furt1'~r, 

it is important to relate the coal to its enclosing rocks in order 

to understand the precise geologic environment in which peat-~wamp 

deposition, coalification, and diagenetic changes took place. 

This requires an understanding of the nature of the swamps, tl'~ir 

vegetation, and paleoclimates. 

Selected examples of current USGS research results may s~rve 

to illustrate some of the avenues being followed: 

o In addition to standard megascopic field descriptions and 

conventional microscopic petrographic analysis of pellet 

U4 
mounts to describe the average compositions of coals, 

quantitative descriptions of coal beds from top to bottom 

are produced by means of modal analyses of continuous 

columnar or core samples utilizing an automated image 

analysis system. Lithologic units determined by microscopic analysis with this system are in turn described in 

terms of microscopically determined percentages of 

vitrinite, exinite, inertinite, and optically resolvable 

mineral content to give a quantitative quality profile of 

the given coal bed (Chao and others, 1980). This provides 

a partial basis for interpretation of coal origin (for 

instance, peat materials deposited in place or transported), depositional environment, diagenetic changes, 

burial history, and so on, and identified points for more 

detailed studies by other techniques. 

o To define the distribution of mineral matter, determine 

its origins (depositional or diagenetic), and identify 

actual residence of important chemical elements, microscopic petrography commonly is followed by scanning 

electron microscopy (SEM) and microanalytic techniques. 

When mineral grains are identified, they are examined by 

electron microprobe to establish chemical contents. Thus, 

the presence of zinc known from multielement chemical 

analysis can be shown to be precisely related to the 

presence of sphalerite, and the character of the 

sphalerite may reveal diagenetic origin. In one recent 

study, pyrite grains were found to have smooth areas and 

pitted areas: microprobe traverses across the grains 

showed arsenic in the pyrite to be confined to the pitted 

portions (figs. Sa, b). As these portions also were 

characterized by fractures, the arsenic is interpreted as 

having been made available from epigenetic solutions 

moving through the coal after it originally formed. 

o Routine electron microprobe analysis of chemical contents 

of individual maceral grains has the capability of 

detection of elements of atomic number 11 and greater and 

a minimum detection limit of 0.01-0.05 percent for most 

elements. Important extensions of microprobe capability 

now are available with PIXE, (proton-induced X-ray 

emission) and LAMMA (laser microprobe mass analysis) 

instruments. With PIXE, quantitative analysis is carried 

out for elements of atomic number 11 or higher at concentrations as low as 1 to 10 ppm (Minkin and others, 1982), 

while LAMMA can be used for qualitative analysis of all 

elements from H to U at sensitivities as low as 1 ppm. 

Although not yet quantitative, LAMMA "fingerprints" both 

175 
1-' 

'-1 

CJ\ 

a. Photomicrograph in reflected light, showing 

both smooth and fractured massive pyrite. 

Center areas of the pyrite are smooth whereas 

areas adjoining fractures are pitted. The 

series of spots across the center of the field 

mark the sequence of electron microprobe 

analyses of arsenic concentration at 6 pm 

intervals. Bar scale = 0.25 mm. 

.H 

... 

·" 

... 

(/)50 

<( 

'#. .... 

~ 

.30 

.21 

.It 

CONCENTRATION PROFILE : levels of arsenic present in outer (pitted) and 

inner (smooth) areas of a pyrite grain in 

fractured Upper Freeport coal, H2-42P.1 

, .. Electron microprobe traverse, 611 m steps 

b. Profile of arsenic concentration along the 

path of the electron microprobe traverse 

shown in a. 

Figure 5. Photomicrograph and arsenic concentration profile of a pyrite grain from the Upper 

Freeport coal bed, Indiana County, Pennsylvania (modified from Minkin and others, 1984). 
the mineral and maceral components of coal, and is 

especially powerful for detection and characterization of 

certain organic fragments that may vary with maceral 

variety as well as rank of coal (Lyons, P.C., written 

commun., 1985). 

o Studies of concretions found in coal ("coal balls") show 

that coalification is identical inside and outside the 

concretions, even though the woody-material cell structure 

inside the concretion shows none of the compaction undergone by the material of the surrounding coal. The nature 

of the chemical changes in the process of coalification of 

woody tissue is studied using NMR (Nuclear Magnetic 

Resonance). This shows that, initially, wood is diagenetically altered, primarily with loss of cellulose and 

other carbohydrates and with concomitant selective 

preservation of lignin-like components. These are also 

altered but with retention of some structural character of 

lignin, as evidenced by NMR spectral peak. From these 

observations, a new hypothesis has been derived for the 

loss of oxygen during coalification (Hatcher and others, 

1982): humic acids, soluble and readily mobilized 

components rich in oxygen-containing chemical structures, 

are mostly oxidation products of the chemical alteration 

from peat to lignite. Loss of humic acids during compaction and expulsion of water explains the observed loss of 

oxygen content during coalification to higher rank. As 

rank increases up to high-volatile bituminous coal, 

changes in the spectra imply significant loss of oxygenrich functional groups. With additional increase in rank, 

the primary change is loss of aliphatic peaks, as is 

expected from pyrolitic breakdown of the chemical 

structure. High-rank coal is essentially entirely 

aromatic in structure. 

o Quartz grains in upper Freeport coal have been studied 

using the electron microprobe and cathodoluminescence 

(Ruppert and others, 1985). Nonluminescence of quartz 

connotes that it is authigenic (formed in place by 

diagenetic process). Quartz grains in this coal bed are 

83 percent authigenic; 17 percent of the quartz is 

detrital. In the roof shale, 7 percent of the quartz is 

authigenic. 

o Calcite deposited in cleat in the upper Freeport coal has 

been characterized by means of carbon-oxygen-isotope 

analysis (Dulong and others, 1985). Its isotope content 

is very different from that of calcite from freshwater 

limestone a short distance below the coal. It may be said 

177 
that the cleat calcite is not derived from solution of the 

underlying limestone, but rather was produced in a process 

of isotopic fractionation caused by methanogenic bacteria. 

Calcite in macerals was produced by both biotic and 

abiotic processes. A practical benefit is the knowledge 

that the two kinds of calcite have different specific 

gravities and respond differently in sink-float treatment 

during coal beneficiation. 

o Studies of modern swamps as early-stage analogs of coal 

beds are revealing details of plant-community distribution 

and associated chemical processes that appear directly 

applicable in interpreting the nature of coal facies. 

Peat swamps show directly the variations in plant 

materials, admixing of in-place and transported materials 

(both organic and inorganic), and changes resulting froo 

natural events such as alternating wet and dry periods or 

fires. Observation of differing peat-accumulation 

morphologies and the associated differences in water 

supply and the chemistry of the peats has led to an 

important distinction that may be made between two 

fundamental types of peat deposits (fig. 6): ombrogenous 

or rainfall-dependent peats and topogenous or ground-water 

fed peats (Cecil and others, 1985). As a general rule, 

ombrogenous peat deposits tend to be domed and can be 

expected to produce low-ash, low-sulfur coal deposits, 

whereas topogenous peats tend to be planar and can be 

expected to produce relatively high-ash and high-sulfur 

coal deposits. Because each type of peat has a different 

type of water supply, each would be very different in 

chemistry. This distinction results in different chemical 

make-up of the original peats and the resulting coals. 

o In related studies of the coals of the Pennsylvanian 

sequence in the central Appalachian basin, ash and sulfur 

variations are linked to type of coal deposit. This in 

turn relates to both local settings and to interpreted 

paleoclimate (fig. 7). It is construed that lower to 

middle Pennsylvanian coals were derived from ombrogenous 

peats that formed in wet climates, and upper Pennsylvanian 

coals were derived from topogenous peats that formed in 

more seasonally dry conditions (Cecil and others, 1985). 

o In other swamp studies, the primary distribution of coal's 

sulfur and its forms and the genesis of its pyrite have 

been documented in Everglades peats in a regional study of 

peat stratigraphy and chemistry. A prominent finding is 

that pyrite forms at the expense of organic sulfur in the 

178 
J--1 

........ 

1.0 

PEAT TYPE 

A 

B 

~ ~<:'­ ~fl> 

u 

DOMED PEAT 

Peat Swamp Forest 

Zoned Phasic Plant Communities 

b ·~0 b ~oq , ~v -,..0 

v'lf r-0 ~q oq ~ /'< 0 '&~ 4.0 -~ ~ /v 

0 I ~ +01 

PLANAR PEAT 

Spatially Heterogeneous Plant Communities 

O:J' 0 ,o .... ~ ~<:'­ ~qj. 

u 

~ ~<:'­ -:<::-qj. 

u 

71gure 5. GenerallzeJ cross-sectlons oZ JomeJ anJ planar peat Jeposlts. DomeJ peat Jeposlts are 

ombrogeneous and generally have zoned plant communities (A). Planar peat deposits are 

topogeneous and contain spatially heterogeneous plant commmunities (B) (modified from Cecil and 

others, 1985). 
Series 

c L.. as 

Q)·-

~E~ OL..""""' 

...JQ) a. 

c 

-~ c L.. as 

Q) > 

a.-

c.~ 

:::)~ c 

Q) 

a. 

c 

~ 

c 

Q) as 

- > "0-

'0~ 

·- f/) 

~ c 

c 

Q) 

a. 

c 

-~ c L.. as 

Q) > 

0 ~-~ 

_,~ c 

Q) 

a. 

as 

0 

0 

L.. 

::::s 

== ::::s

f/) 

I 

.c 

-~ J: 

.c 

f/) 

as 

I 

.c 

-~ J: 

t 

+ 

as 

0 

0 

L.. 

::::s 

-::::s 

en 

I 

~ 

0 

__, 

.c 

en 

as 

I 

~ 

0 

__, 

Everwet 

Dry-seasonal 

Low High 

Rainfall 

Evapotranspiration 

Figure 7. The ratios of rainfall to evapotranspiration 

interpreted from stratigraphic changes in lithologies 

and coal quality in the Mississippian and Pennsylvanian 

Series in the central Appalachian basin (modified from 

Cecil and others, 1985). 

180 
lower part of the peat column across the Everglades. This 

is a significant diagenetic change occurring early in the 

coal-forming process. It involves the bacterial reduction 

of organic oxy-sulfur compounds to sulfides that react 

with ferrous iron to form pyrite. These findings explain 

the tissue- and cell-bound status of the framboidal and 

microglobular pyrite in coal, and the basal accumulation 

of pyrite that is noted in many coal beds. (See figs. 8 

and 9 from Altschuler; Schnepfe, Silber, and Simon, 1983.) 

o The detailed character of the coals and their enclosing 

rocks are brought together in models of the coal-forming 

environments in order to interpret the precise geologic 

settings and/or subsequent diagenetic processes associated 

with coal facies. Examples of this modeling include: 

central Appalachian Pennsylvanian coals (particularly the 

Freeport); coals from the barrier-beach swamp settings 

along the margin of the western seaway of Cretaceous time; 

and a 200-foot-thick coal bed, known as "Big George," in 

Tertiary rocks of the Powder River Basin. 

Conclusions 

All this work needs to be intensified and expanded, preferably 

through the development of consortia of government (Federal and 

State), academic, and industry researchers of diverse talents and 

interests. In this way, studies can span the necessary range of 

concerns from understanding the field setting of the raw material 

through insights into the mineralogy and chemistry that affect 

coal cleaning, combustion, and pollution potential. In addition, 

an ultimate goal of the USGS is to accumulate enough data-bank 

information along with modeling insights so that coal resources 

throughout the Nation can be estimated and characterized in terms 

of coal quality and optimal-use potential. 

ACKNOWLEDGMENTS 

The ideas and activities described here involve many USGS 

researchers and have been clarified for the authors in many 

diverse conversations and presentations. Thanks are particularly 

due to Blaine Cecil, Jack Medlin, Edward Chao, Ron Stanton, 

Patrick Hatcher, Paul Lyons, Sam Altschuler, and their coworkers. 

181 
~ 

00 

N 

Core locations 

13 12 11 10 8 8 7 8 5 4 3 2 

ilHJiJ; 

IJ1m¥I ··· . rnii!'I"Ji[r · •. J !~Y!TrJrrrr ~~frrpHrrcl}!l':'if[~''<~ . . "lj'['lfnnlti1 ·.,JI~Ijk' ... ;.· ~ ·: .. -.~:::· : .. ::::·.·· · 1:: .. '~~~~~ . n11 :rll!lfJ· [IIlli,! i!.JJ, 11 1 li .... ;: .. • • • • • llJ 1 . , ", 1 ~ · u, 11 II p: J..l, 11 :: • 

)u . . .:.~jjl:'!·?i~-?; ~:·~~~. l'~·r , 111111111 11illlilllllllllllli!lllliiiiJIIIJJJjrljj]]JIIIllll111r.ll'· 1111 :":'' 111 11111 ~::Hii!!li !![i!ji]!!Jflj] i !iti~:· ··" .·;'1]!111U1 • ::.: .;:: ·r-

[1 .IJ ·~ ·.!!I!J!t ''llilllilll!!lilllllllii!JIIIlllll:::;;iiilll11 iH . ~!lmmg!!TIIIIIIIIIIIII:ti' II 1

' :r.[J· Ill ' ,. r11 1 111 ·M1:: .. :;.: I I Peat .. .. I .. IIJ .... qnJIJII' ..• . ~· •..••. 

11/ · )~l~n" ' , ).·;=:· · 

·~ .. :~~lli.fl!~! ~~.~:[~'!.~.'.' !.~.L~J.~!:~ !.11 ~.~~ ~~.~w~ u.u~.~! ~ ~~~!\~~~.l'~u ... , . I . ~ ,; d Y ~~ ~ ~ :~~=~~ !~.~~!:'!i ilL:~.· .. 

· · · · ··=:· .. }.~~~~vu ~! !_~ 11 ~~~ :.t il'r\:· .. · · · · 0 4 ml 

0 4 km 

3 

.... 2 E 

• '0 

:I 

.:: 

c 

Sea level •· 0 

B Lake \,~ "( 

Okeechobee'-' ' Palm 

Beach'"' 

Figu~2 S. 

• (A) Core lithology and stratigraphic profile of 

Holocene deposits across the southern Everglades along 

the Tamiami Trail. Average depth to Pleistocene Miami 

oolite basement is shown by the general profile where 

cores penetrate solution pits in the basement. Thus the 

actual basin extends from cores I to 9, and major peat 

deposition from I to 8. (B) The profile in (A) follows the 

horizontal line through the Everglades in the area map. 

St~3ti;~3phic p~ofile of u~qt bqqin, s~1th~rn ~v~r~l~d~~, 

Florida (from Altschuler and others, 1983). 
e 

u 

-

1: 

~ 

• 0 

Core 2 

0-

A 

25 

50 

75 

100 I 

Core 5 

0 ,--

25 

( 50 

75 L 

~ 

I 

i 

; 

I 

I 

J 

I _____ j 

0 ------------

25 

50 

I 

75L_ __ .. __ _ 

0 1.0 2.0 

Absolute weight ('If.) 

I 

N 

~ 

0 

fl) 

I 

~ 

. ~ 

:; 

Ill 

.. I 

I 

I L__ ---------' 

;r-;---~ 

i I ~ \ ~ Cl 

~~ 0 ; I 1 I j U ""• = 0 I ;:_ "l .. -~- r--~ --------- ~ 

:; 

Ill 

I 

l __ _ j 0 50 100 

l---------' 

0 

~ :; 

Ill 

fl) 

II 

(,) 

I 

, 

'I 

--------

50 

I. 

100 

Relative weight ('!rt) 

Figure 9. Sulfur and its forms in representative cores across the 

Everglades peat basin showing the vertical distribution of 

(A) total sulfur, (B) its mineral and organic forms, and 

(c) the relation of pyritic sulfur to forms of organic 

sulfur. Note the decline in organic S (B) and particularly 

of reducible organic S (C) as pyrite increases. (From 

Altschuler and others, 1983.) 

183 
REFERENCES 

Altschuler, Z.S., Schnepfe, M.M., Silber, C.C., and Simon, F.O., 

1983, Sulfur diagenesis in Everglades peat and origin of 

pyrite in coal: Science, v. 221, p. 221-227. 

Cecil, C.B., Stanton, R.W., Neuzil, S.G., Dulong, F.T., Ruppert, 

L.F., and Pierce, B.S., 1985, Paleoclimate controls on Late 

Paleozoic sedimentation and peat formation in the Central 

Appalachian Basin (U.S.A.), in T.L. Phillips and C.B. Cecil, 

eds., Paleoclimate controls on coal resources of the 

Pennsylvanian System of North America: The International 

Journal of Coal Geology, v. 5, p. 195-230. 

Chao, E.C.T., Minkin, J.A., and Thompson, C.L., 1980, Application 

of automated image analysis to coal petrography, in Carter, 

L.M., ed., Proceedings of the Fourth Symposium on~he Geology 

of Rocky Mountain Coal-1980: Colorado Geological Survey 

Resource Series 10, Denver, Colorado, p. 50-54. 

Dulong, F.T., Spiker, E.C., Cecil, C.B., and Stanton, R.W., 1985, 

Calcite genesis in the Upper Freeport coal bed as indicated 

by stable isotope geochemistry: Geological Society of 

America, Abstracts with Programs, v. 17, no. 7, p. 569. 

Hatcher, P.G., Breger, I.A., Szeverenyi, N.M., and Maciel, G.E., 

1982, Nuclear magnetic resonance studies of ancient buried 

wood. II. Observations on the origin of coal from lignite to 

bituminous coal: Organic Geochemistry, v. 4, p. 9-18. 

Minkin, J.A., Chao, E.C.T., Thompson, C.L., Nobiling, Raines, and 

"Blank, Herma, 1982, Proton microprobe determination of 

elemental concentrations in coal macerals: Scanning Electron 

Microscopy 1982, I, 175-184. 

Minkin, J.A., Finkelman, R.B., Thompson, C.L., Chao, E.C.T., 

Ruppert, L.F., Blank, Herma, and Cecil, C.B., 1984, 

Microcharacterization of arsenic- and selenium-bearing pyrite 

in Upper Freeport coal, Indiana County, Pennsylvania: 

Scanning Electron Microscopy 1984, IV 1515-1524. 

Ruppert, L.F., Cecil, C.B., Stanton, R.W., and Christian, R.F., 

1985, Authigenic quartz in the Upper Freeport coal bed, 

west-central Pennsylvania: Journal of Sedimentary Petrology, 

v. 55, no. 3, p.334-339. 

184 
PART II. WORKSHOPS 
• 
AN ANALYSIS OF THE PROCEEDINGS OF THE SYMPOSIUM WORKSHOPS 

Background 

by 

Stanley P. Schweinfurth 

U.S. Geological Survey 

The five workshops described in the Introduction met 

concurrently on the second day of the symposium and then presented 

their findings and recommendations to a plenary session of the 

meeting on the morning of the third day. Panel coleaders and 

panelists had done much advance work in preparation for their 

workshop sessions. 

The discussions of each workshop were recorded by particfpating scientists whose notes form the basis for the analysis 

presented in this chapter. The recorders' notes were reviewec by 

the panelists for general agreement as to the substance, form, and 

content of the workshop's deliberations before they were inclr.fed 

as part of the final record of the symposium.* The formal 

recommendations of each workshop are presented following this 

paper. 

The purpose of this analysis is to provide a substantive 

summary of the detailed discussions of the individual workshor~. 

Discussion in each workshop was devoted to a variety of subjects 

that cut across all of the workshop topics and that were universally viewed as major problem areas. Each workshop recommend€;{ 

that priority attention should be given to one or another of these 

problem areas in their formal recommendations. This paper 

summarizes the workshop proceedings as they relate to major 

problem areas and only briefly touches on other, less well-covered 

topics. 

The major problem areas as inferred from the discussion ~f 

the five workshops on coal-quality research are discussed bel~v. 

*The names of the recorders are included with the names of the 

panelists for each workshop in Part V. Workshop notes will be 

available for inspection by appointment, for 1 year from the (ate 

of publication of these proceedings at the U.S. Geological Survey, 

Reston, Virginia. 

187 
The topic of each major problem area and the sequence for 

discussion of each of these topics were selected as the best 

reading of the intent of the workshop participants. 

Major Problem Areas in Coal Quality Research and Related 

Activities 

Analysis of the workshop proceedings indicates that the 

discussions, suggestions, and recommendations of the participants 

with regard to major problems in coal quality and related topics 

can be grouped into seven major areas. Analysis and discussion of 

these major problem areas, which require either research or 

institutional attention or both to provide needed answers and 

results, is presented in approximate order of priority. 

The priority assigned to each of the major problem areas 

is based on the amount of discussion recorded for that topic in 

each workshop, averaged across all five workshops. In some cases 

the differences in the amount of discussions between these major 

problem areas are very slight and the rankings of several of the 

topics might easily be reversed if ranked by another analyst. For 

example, sulfur was identified as a separate topic because of its 

perceived relation to major environmental problems, with the 

result that it received a lower priority relative to some other 

topics. If, however, sulfur had been included with the general 

problem area that seemed to hold the highest priority in the 

workshop discussions--the need for new analytical procedures and 

more data on coal composition in general--it would have been 

included in a topic that appears to rate a much higher priority in 

the views of the symposium participants. 

Analytical procedures and results. Specific interest was 

registered in certain kinds of analyses that are not now available 

as the direct result of an existing analytical procedure. Interest 

was also expressed in obtaining more and better analytical data on a 

variety of specific inorganic elements, other than sulfur, that 

affect coal use or that may cause environmental problems. A~ong the 

elements and properties for which there are no direct methods of 

analysis, oxygen and inherent moisture were identified (organic 

sulfur is included under sulfur in coal below); whereas among those 

elements for which more analytical data are needed, silicon, 

aluminum, iron, calcium, sodium, potassium, arsenic, chlorine, 

boron, fluorine, lead, magnesium, mercury, titanium, and certain 

other trace elements such as selenium, that may cause environmental 

concerns, were identified. Several participants questioned whether 

enough is known about the fate of some of these potentially harmful 

~8 
elements when they are released from mines, preparation plants, and 

scrubber sludges. Additional research on the occurrence, pathways, 

and ultimate resting places of potentially harmful trace elements 

was recommended. 

Participants explained that better data on oxygen, oxidation 

of coal surfaces, and moisture are needed with regard to advancerl 

uses of coal, especially gasification and coal-water slurries or 

mixtures. Research into ways to prevent or slow surface oxidation 

was recommended. Calcium, iron, silicon, and aluminum primarily 

control slag viscosity. A large amount of iron causes wall 

corrosion in boilers. Sodium is useful in small quantities, but 

too much causes fouling (although this apparently depends to some 

extent on how the sodium is bound in the coal). Halides cause 

corrosion, and lead, mercury, and selenium may cause environmental 

problems. 

There was a general call for research into methods to improve 

predictability of the slagging and fouling properties of coal and 

coal blends. Several participants suggested that detailed analyses 

should be made of washed and/or pulverized coal because that is what 

is fed into boilers. In both of these cases, the inorganic chemistry may be expected to be different from the chemistry of either 

run-of-mine (ROM) coal or face or core samples. Others advised that 

analyses should be performed on both low- and high-temperature ashes 

of the same sample. One participant reported good results for some 

elements with electron-probe microanalysis of raw coal. Development 

of better analytical techniques for ultrafine coal was singled o~lt 

as an important area for additional research. 

With respect to the organic constituents and structures of 

coal, concern was expressed that although much is known, opportu,-

ities still exist for research because of inadequacies in ultimate 

analyses (C, H, N, 0, S) as currently performed, and because a 

better understanding of organic functionalities and the structure 

of coal is needed. This was reported to be especially true with 

regard to advanced uses of coal such as coal-water mixtures, 

advanced combustion, and liquefaction. 

Participants who deal with coal handling, coal beneficiatio~, 

and advanced uses of coal indicated that there is a need to devise 

better methods to study the surface chemistry of coal and to 

better understand the electrical properties of coal. The surface 

properties and effects of different coals apparently have significant impacts on such things as the beneficiation potential of 

coals, reactivities of coal with the various media used in beneficiation, how well different coals can be made into coal-water 

slurries or coal-water fuels, and how well they can withstand long 

periods of storage. A general appeal was made to devise better 

methods for nondestructive testing, automated testing equipment, 

and especially cost-effective equipment that could continuously 

~9 
analyze wet coal streams because so much of coal gets wet during 

transportation, storage, and preparation. 

It was also generally concluded that more attention should be 

given to the chemistry and physical properties of the rocks 

adjacent to coal beds because they frequently contribute to the 

mineral matter mixed with the ROM coal. A better understanding of 

the geochemistry of these rocks may also contribute to a better 

understanding of the geochemistry of coal. 

In summary, the participants requested more chemical data on 

coal. As one participant stated: "With policy decisions, there 

is so much to gain if there are good data. With a poor data base 

one makes bad decisions." Another participant recommended that 

the chemical data called for would be much more generally useful 

if it were reported by mole percent rather than by weight percent 

as is current practice. 

Standards and samples. The consensus on standards seems to 

be that although there are standards (ASTM, institutional), they 

do not cover the full range of needs of coal users and they are 

inconsistently applied. Greater care in the application of existing standards was urged so that the results of analytical wor,~ on 

one body of samples will be comparable with work on any other. 

Recommendations were made that new kinds of analyses and standards 

need to be developed. However, it is necessary to be sure that 

new data will be comparable to old data. 

Because in most cases only limited funds are available to 

obtain samples and because samples are the basis for coal-quality 

research at all steps in the process of characterizing and using 

coal, the following actions were recommended with regard to 

standards: 

1. Devise new ASTM standards for particle sizes, ash and 

washability analyses, and for slagging and fouling 

indices for ultrafine coals (UFC) because existing 

standards are only useful for coal greater than 30 

microns (38 mesh) in particle size (separate standaris 

need to be developed for both eastern and western co~ls), 

and also for chemically cleaned coals. 

2. Devise new ASTM standards for mineral forms in coal and 

for describing coal quality versus coal rank. 

3. Devise ASTM standards for the analysis of sulfur for~s 

that do not result in errors for organic sulfur. 

4. Devise ASTM standards for coal products that contain very 

small amounts of sulfur and ash. 

190 
5. Devise standards for analytical procedures for coal ash 

released under reducing conditions. 

6. Devise uniform standards for geophysical methods being 

used to estimate coal-quality data. 

7. Prepare standardized samples and make available. 

8. Devise standards for ROM coal sizes. 

9. Devise standards for use in blending coals. 

Considerable debate was focused on where and how coal samples 

should be taken. For example, it was pointed out that tests on 

core samples do not accurately predict the washability of ROM coal. 

One attendee from a major energy company remarked that there are 

significant problems in writing specifications. For instance, 

even weighing a ton of coal produces disagreement. The coal 

company takes measurements at the loading of the car and the 

utility company takes measurements at arrival, and the numbers 

don't mesh. Even when numbers and sampling procedures are 

specified, the numbers for coal Btu, sulfur, and ash content 

differ. The need is for more information on the natural 

variability of a given coal in the ground and for acceptable 

limits over which a given coal may be expected to vary (with 

reasonable care in handling) after it is mined. If these limits 

are generally understood and accepted, then some variation within 

the limitsought to be acceptable to all concerned. 

The consensus on sampling seems to be that: 

1. Samples should be taken at each point where coal undergoes a major change, beginning with prospecting cores, or 

wherever a major decision about its use needs to be made, 

such as after long periods of storage. 

2. Coal in the ground should be sampled by bench or natural 

break, letting the user composite the results if so 

desired. 

3. Only coal of "mineable" thickness should be sampled. 

Other recommendations for sampling procedures and standards 

and other concerns expressed were: 

1. Greater attention should be given to describing why a 

sample was taken and what the sample represents. 

2. Larger samples should be collected at individual sampling 

points to improve the representativeness of each sample. 

191 
3. Partings are part of coal beds and should be include1 in 

a sample, no matter how thick, if they are going to be 

mined along with the coal. 

4. Those who sample coal should receive adequate training. 

5. Mechanical sampling is preferable to manual sampling. 

6. The entire issue of sampling and sampling standards 

should be reviewed at a special workshop. 

7. "Top-of-car" sampling should be avoided because it is not 

representative. 

8. Samples for which data are stored in any data system 

should be especially carefully documented. 

One indication of the size of the problem of reliable samples 

and analyses is that some utilities reportedly drill for their own 

coal samples on suppliers' properties. This is a kind of insurance, 

no doubt, but expensive. Should it be necessary? One attendee 

commented that "coal preparation plants are operated, not controlled," implying that little attention is given to sampling and 

analytical standards at many coal preparation facilities. 

Specific recommendations on sampling and analytical standards 

were made by all of the workshops. 

Communications. Every workshop indicated large and 

continuing problems with the level, and sometimes with the very 

existence, of communications among the various members of the coal 

community. It was recognized that there are numerous meetings 

where coal-research results are presented, but a general complaint 

was that too few opportunities exist for specialists to discuss 

problems in a workshop/roundtable atmosphere. Another general 

complaint was that communication and coordination are lacking 

among Federal agencies and between Federal and State agencies with 

regard to coal research and coal research needs. Private industry 

was faulted for being too proprietary with the results of work 

that is of a general nature and that could be shared without 

harmful impact on profits. It was recognized that some competition in research activities is' healthy and productive, but that 

poor communication can result in needless duplication of effort, 

wasted money, and missed opportunities. 

Other problems and suggested solutions with regard to conmunications and data bases that were voiced by a large number of 

attendees were: 

1. It is often unknown, or at best unclear, to researchers 

and coal suppliers just what the coal-quality data n~eds 

192 
of utilities and other coal users are, so that a greater 

effort should be made to communicate those needs 

throughout the coal community. 

2. Some attendees commented that coal-quality research c~d 

characterization should be done only on problems of 

immediate concern, whereas others suggested that it 

should be the responsibility of public agencies to try to 

determine what might materialize in terms of future 

problems and begin working on them and including the 

results in a "national" data system. It appears that 

this issue requires further discussion and clarification. 

3. More communications and "technology transfer" need to be 

carried out with coal researchers and users in foreir;n 

countries. It was recommended that an official U.S. 

delegation to the International Standards Organization 

(ISO) should be sponsored. 

4. In the coal-quality data systems community it was 

recommended that a thorough review of the content, 

direction, and addressability of computer data bases be 

conducted and that a single publication be prepared ''hich 

describes each system so that a single reference would be 

available for coal researchers and users. One major 

consulting firm reported that it uses only publicly 

available data in its coal demand/supply analyses, but 

that it encounters great difficulties in trying to 

integrate data on coal quality, quantity, and accessibility into complete coal-demand/coal-supply scenarios 

because these data are not adequately related or integrated within their source data systems. 

A general recommendation on communications and data systems 

was that user groups should be organized and should meet on a 

regular basis to compare and exchange information on coal quality 

and related issues. 

Ash properties, coal cleaning, slagging, and fouling. M·,ch 

of the discussion on these topics relates in some way to coal-ash 

mineral forms and inorganic chemistry. However, there was also 

discussion of ash as a separate, complete entity in coal in terms 

of amounts, kinds (that is, alkaline versus acid), and properties 

as they relate to coal use, cleaning, blending, and slagging and 

fouling. It seemed appropriate, therefore, to discuss 11 ash11 under 

its own heading. For example, the eutectics of ash fusion are 

important, especially with coals of different grindabilities, 

because mills process softer coal before harder coal and, 

therefore, ash can become concentrated in some parts of the feed 

stream resulting in "flameouts. 11 It was pointed out that the. 

ash-fusion eutectics of blends are different than the average~ for 

193 
the individual coals making up the blend and that the same is true 

for the swelling indices of blended coals. Furthermore, the 

slagging and fouling behavior of blends cannot now be predict~d 

from the properties of the separate coals. 

Participants expressed considerable dissatisfaction with 

current methods and standards for predicting ash fusion, 

viscosity, slagging and fouling, and these areas were identified 

as requiring more research. One panelist indicated that much of 

this research would have to be done in boilers rather than 

laboratories. In the case of slagging gasifiers, it was reported 

that the amount of ash is not very important but that the 

chemistry is. The gasifier requires ash that will fuse at 

relatively low temperatures. At least one firm is conducting 

research on methods to lower ash-fusion temperatures and on tl~~ 

relation between ash-fusion temperatures and viscosity. One 

attendee stated that the problem of ash-fusion is not conduci,•e to 

solution by modeling. In response to this, several suggested that 

ash-fusion problems may well be addressed through knowledge gained 

from ceramics, metallurgy, and igneous petrology. Another 

attendee requested research to identify the temperatures of 

formation of slags, sinters, and calcines from coal mineral matter. 

Another problem area is that coal washing changes the 

chemistry of the ash in the washed coal, but there is little rlata 

on what the resultant changes might be. Research to perfect the 

predictability of techniques for cleaning coal that are not based 

on specific gravity was identified as an important need in 

advanced uses of coal: more float/sink data for small particlesized coal was also requested. 

Fly-ash resistivity was identified in the workshops as 

another problem needing research. 

Petrography is a technique for sample analysis that may 1'~ 

required to accomplish other recommended research objectives 

outlined above, but this technique was discussed in a unique 

perspective which could lead to some productive research in coal 

cleaning and coke production. It was reported that there has been 

promising petrographic research indicating the relationship 

between coal macerals and the response of a coal to grinding and 

washing, as some macerals are more friable and lighter than others. 

It was also reported that no petrographic work is being done on 

coke in the United States, although research on coke and coking 

coal is necessary to improve the worldwide marketability of U.S. 

coals suitable for making coke. 

Modeling, geostatistics, and prediction of coal quality. 

These topics received much discussion in the workshops at the 

symposium and especially in Workshops I, II, and III. It was 

generally agreed that we need the capability to predict what vill 

194 
happen under a given set of circumstances, but how to get there? 

It was suggested that the proper approach is to develop models, 

test them against the real world, and then, if they survive, to 

apply them. One way to test the performance of models against the 

real world is through the use of geostatistics. 

Some participants expressed the opinion that geostatistics is 

a mature subject and available for use for any purpose, whereas 

others thought that additional research is required before geestatistical methods could become universally applicable. Most 

participants seemed to agree that most existing models for 

predicting coal quality and quality variations at all stages of 

the coal business--from characterizing the quality and quantity of 

coal resources to predicting ash composition and ash behavior--

leave much to be desired. The consensus seemed to be, however, 

that good models will save time and money and deserve a reasor..=ible 

amount of research effort. Nevertheless, statistical process 

control is currently used by only a very few coal producers au~ 

users. 

Specific areas identified as needing additional research and 

related activities were: (1) methods for locating minimumvariance samples; (2) inclusion of post-depositional history fn 

developing coal-deposit models; (3) methods to relate coalwashability data from large and small diameter cores; (4) mor~ 

education and training on the use of geostatistics; and (5) 

publication of more modeling and geostatistical "case histori~s" 

in a timely manner. 

Sulfur in coal. Sulfur in coal continues to be a problen. 

Whether there is too much or too little sulfur, whether it oc~urs 

as pyrite, organic sulfur, or sulphate, and how entrained, were 

all subjects of discussion at the symposium. Additional reseRrch 

needs were identified as: 

1. Methods to identify the forms of sulfur in coal, 

especially organic sulfur. 

2. Methods to extract organic sulfur before using coal. 

3. Methods to predict where and in what form sulfur will 

occur in coal in the ground. 

4. Determination of the "true" size of pyrite grains in 

coal. 

5. Development of models to predict the formation of acid 

mine waters. 

6. Development of selective mining methods to reduce th~ 

level of pyrite in ROM coal. 

195 
Several attendees commented that it would be very beneficial 

if the agencies that prepare coal-resource maps would include data 

on sulfur content and forms on their coal maps. 

Minerals in coal. This topic took up much discussion time in 

most of the workshops and especially in Workshop V with regard to 

UFC (ultrafine coal). Apparently, it is as important to know l~hat 

the mineral forms are that are present in coal as it is to knol~ 

what the inorganic chemical composition is. The consensus was 

that too little is currently known about minerals in coal. 

Minerals such as quartz and pyrite cause erosion in coal handling 

and utilization equipment, whereas clay affects coal handling; if 

feldspar is present, it may be of the sodium variety. There w~s 

agreement that much more research needs to be done on mineral 

forms in coal. Some attendees suggested that data on mineral 

forms in coal would be far more valuable for steam coals than e. 

maceral analysis would be because bottom and fly-ash characteristics will depend, to some extent, on the minerals present in the 

feed coal. 

It was reported that there is evidence that mineral grain 

sizes tend to be smaller in coals of lower rank, but that this 

tendency requires more research for corroboration. If true, ttis 

tendency has important implications for coal beneficiation. 

Opportunities for research on mineral forms appear to be in 

devising rapid, improved, and inexpensive analytical methods for 

determining mineral forms; determining origin, sizes, and distribution of mineral forms in coal and how the mineral matter 

interfaces with coal; determining the relationships of different 

mixes of minerals to ash-fusion and fouling characteristics; and 

making minerals liberation measurements (separation of coal fro~ 

mineral matter) for finely ground coals. 

Additional Recommendations 

Some of the workshops at the symposium provided recommendations for research on coal quality and related activities that 

were unique to that group. These recommendations are presented by 

workshop: 

Workshop I - Complete geologic mapping in all coal basins and 

expand research on the geology and geochemistry of low-rank 

coals--most research is being done on bituminous coals; change the 

manner in which coal resources are characterized to meet the needs 

of the mining and utilizing industries within the next decades; 

and study the physical characteristics of overburden for use in 

mine planning. 

Workshop II - Make a greater effort to extend the classification of resource data into reserves data with associated 

196 
production costs. The focus of this effort should be to provide 

better data on coal reserves by sulfur categories, and perhaps 

other quality criteria, for use in strategic planning by 

government and industry. Study the chemical reactions of coal 

blends during combustion. Initiate research to simplify the 

evaluation of the coal-handling factor (HF); HF is mainly a 

function of moisture, particle size, and clay content. Provide 

data on coal accessibility as well as on total resources. 

Workshop III - Devise new technology for reserve characterization such as the following: a borehole miner, thickness of seam 

using radar, and directional underground drilling. Devise new 

technologies for mine operation such as coal preparation at th~ 

face, underground disposal of preparation waste, ash analyzers to 

detect partings, methods to reduce ROM sulfur, and methods to 

minimize contamination and variability of ROM coal. Devise a 

relative spontaneous-combustion potential index. Determine th~ 

fate of various pollutants in typical disposal situations from 

mines and preparation plants. Study methods to provide analyses 

of geologic hazards and risks involved with coal mining. 

Workshop IV - Do research on biological and combined 

biological physical methods to clean coal and on methods to 

recover coal fines (fines may include as much as 10 percent of the 

combustibles) from preparation-plant waste streams. Study the 

effects of toxic substances derived from coal mining on ground 

water. 

Workshop V - Initiate or expand research on atomization 

characteristics of coal-water fuels, particle-size distributic~ in 

ultrafine coals and standardization of these particle sizes, e~d 

comminution properties to aid in ultrafine grinding of coal: the 

Hardgrove test is not representative for other high-moisture coals 

or for ultrafine grinding. Study the details of the coal-water 

fuel-combustion process. Initiate research on collection of t:he 

very fine dust resulting from coal burning. Perform long-ten' 

research on coals that do not liquefy well and be able to 

correlate the variables important in various liquefaction 

processes. 

Afterward 

The five workshops at the Symposium on Coal Quality have 

provided a massive amount of material on the kinds of researcl' and 

related activities that are needed in the field of coal quality in 

order to facilitate expansion in the use of coal in an 

environmentally sound and cost-effective manner. These workshops 

provided what is truly a "national agenda" for research on coal. 

In general, the participants called for a systematic, multidisciplinary approach to coal research which they indicated should 

consist of all parts of the coal community, including geologists, 

197 
chemists, engineers, and economists, from Federal and State 

agencies, industry and academia in order to be most effective and 

incorporate the special abilities of each in the research prop,ram. 

The U.S. Geological Survey (USGS) is in agreement with this 

approach and is presently analyzing what its role can be in tl'is 

national agenda for coal-quality research; it will describe its 

proposed program in the near future. In part, the planning 

process in the USGS will depend on the response of industry to the 

recommendations of these workshops. The USGS must depend heavily 

on the willingness of the coal industry to share information ith 

the USGS on coal occurrence and quality. The general concept~ 

that the USGS formulates will be more credible if industry data 

are available and these concepts will be of greater benefit ir 

return to the entire coal community: details of shared data can 

be kept confidential by USGS. Industry has shared data with the 

USGS in the past on an ad hoc basis to the mutual benefit of l.'>th 

sides. If this relationship could be broadened and institutionalized, the mutual benefits could be even greater. As steps 

toward this end, the USGS may enter into cooperative research with 

industry if the results may be made publicly available. 

Industrial Research Associateships are also available at the rsGS 

whereby someone from industry may conduct research with Survey 

equipment at Survey facilities under the same conditions as fer 

USGS/industry cooperative research. 

The challenge has been made. Will we rise to it? We have in 

the past; we can in the future. 

198 
WORKSHOP AND PANEL I 

CHARACTERIZATION OF THE QUALITY OF 

COAL RESOURCES AND RESERVES 

The more significant issues considered by this workshop were 

(1) characterization of coal in place, (2) assessment of coal 

resources by quality, (3) methodologies and uses of predictive 

models, (4) uses and availability of data in the public domain, 

and (5) information dissemination and technology transfer. 

Recommendations: 

o Develop and quantify geologic models. Rates of change and 

interdependence of variables must be expressed in quantitat1ve 

and probabilistic terms to have the greatest utility to the 

coal industry. 

o Promote the use of statistical and geostatistical methods for 

coal-quality characterization. Nonparametric statistics are 

recommended and Kriging is a useful technique but other metl'~ds 

may be useful if properly applied. 

o Standard procedures for coal analyses should be followed 

"without deviation." New analyses must be comparable with 

older analyses. If new techniques are developed, they must 

produce results that are comparable with older techniques. 

o Give special attention to sampling of low-rank coals, 

standardize sampling practices not currently covered by 

standards, and develop statistical methods for determining the 

variabilities in quality parameters caused by sampling 

practices. 

o Develop geophysical methods for coal-quality analysis. 

o Improve communications between Government agencies, and provide 

inventories of increased access to Federal data bases. 

o Convene workshops to consider each of the items listed in more 

detail. 

Panel I recommended that the following topics should receive 

special attention for research: 

o Studies of modern swamps as analogs of coal deposits should be 

expanded to understand process relationships in time and srace 

and the relationships between dependent and independent 

variables to aid in the development of predictive models. 

o Geologic mapping should be completed in all coal basins. 

199 
o Studies of the geology and geochemistry of low-rank coals 

should be expanded. Most research is being done on bituminous 

coals. 

o Forms of sulfur should be investigated by modern techniqu€~ and 

the sources and mobility of. sulfur compounds should be 

investigated. 

o The variability of important coal-quality characteristics 

should be documented and reported by statistical parameters. 

200 
WORKSHOP AND PANEL II 

COAL UTILIZATION AND PROCUREMENT 

The objective of the panel was to identify the technical 

information needs of coal producers and consumers for developir.g 

effective procurement relationships, for producing the lowest 

electric generating costs at the bus bar with reliable system 

operations, and for strategic planning. Once the needs were 

identified, a set of research recommendations was derived to 

satisfy the objective of the symposium. 

Output·of the panel is a set of recommendations for 

coal-quality research and improved communication. Four broad 

categories identified are (1) a set of target topics, (2) assessment of existing data bases, (3) improved identification of 

economic reserves, and (4) better communication. 

Target topics include: 

A. Sampling - Assess current techniques and their 

representativeness. 

B. Blending - Conduct research on the ash fusion, 

grindability, and handling characteristics of various 

coal blends in order to develop criteria for blending; 

C. Coal petrography/petrology 

1. Identify petrographic relationships associated with 

coal utilization/combustion parameters. 

2. Determine the usefulness of data from experimental 

petrology, combined with coal analyses, in predicting 

ash fusion and other combustion characteristics. 

3. Assess the predictability of combustion characteristics of coal blends and coals mixed with other 

compounds in order to modify those characteristics. 

D. Applied Coal Geology/Geostatistics - Conduct additional 

research on the use of these tools in evaluating in-place 

resources, recoverability, and quality variations and in 

developing exploration and mining plans. 

E. Develop data relating drill-core coal quality to 

run-of-mine and cleaned coal quality, including an 

assessment of the impact of coal cleaning processes on 

how coal should be characterized. 

201 
We recommend that existing data bases be reevaluated. 

Available data should be assessed for their reliability based ~~ 

sampling and measurement techniques employed. We support the 

concept of the National Coal Resources Data System and consolidation of the various coal quality data bases. 

It is suggested that a greater effort be extended to the 

classification of resource data into reserves data with associated 

production costs. The focus of this effort should be to provide 

better data on coal reserves by sulfur categories, and perhaps 

other quality criteria, for use in strategic planning considerations of Government and industry. 

Finally, we propose that some resources be expended in 

improving communication among coal quality researchers and the 

users of their product. Some possible approaches might include: 

A. Topic-user groups composed of data development and user 

personnel in target subjects; 

B. Online newsletter identifying who is doing what in 

specific areas (emphasis should be on who to contact for 

information); and 

C. Regional technical meetings on subjects of interest. 

202 
WORKSHOP AND PANEL III 

COAL MINING AND COAL CLEANING (BENEFICIATION) 

The consensus of the Panel discussions is as follows: 

I. Mine Planning 

A. Develop predictive techniques to provide better 

definition of individual coal reserves with regard to the 

following aspects: 

1. Minor anomalies (utilizing high-resolution seismic 

methods) 

2. Geological features 

3. Selected coal constituents 

4. Mineability 

5. Adjacent rock properties (natural radiation levels, 

sparking tendencies) 

B. Minerals in Coal 

1. Investigate the amounts, particle sizes, and type~ of 

minerals as they exist in coal and correlate these 

variables with the performance of the coal in various 

utilization unit operations. New or modified 

analytical techniques may be required 

2. Predict distribution of utilization "bad-actors" 

C. Core and Channel-Sample Treatment 

1. Develop a method for treatment of core and channel 

samples to improve estimates of plant yield and 

permit an optimum plant design. 

2. Determine target-size distribution for ROM 

(run-of-mine) coal 

3. Determine the relationship between coal propertie~ 

and particle-size distribution 

4. Develop a method to simulate a particle-size 

distribution of preparation-plant feed and ROP 

(run-of-plant) material 

D. New Technology Development 

1. Develop new technology for reserve characterization 

a. Bore-hole miner 

b. Bore-hole elemental analyzer 

c. Thickness of seam using radar 

d. Directional underground drilling 

II. Mine Operation 

A. Develop New Technology 

1. Coal preparation at the face 

2. Underground disposal of preparation waste 

3. Ash analyzers to detect partings 

203 
4. Control ROM coal sizing 

a. Investigate bit spacing and design 

b. New fragmentation methods 

5. Run-of-mine sulfur reduction 

a. Improved cutting 

b. Mining strategies 

c. Improved control by automation 

6. Minimize contamination and variability of ROM coal 

III. Coal Cleaning (Beneficiation) - Above Ground 

A. General 

1. Develop an improved data base of coal-preparationplant performance 

2. Develop an on-line coal-slurry analyzer 

a. Moisture and other pertinent parameters 

3. Determine the separation capacity relative to trace 

elements and mineral species, such as quartz 

a. Determine environmental concern of trace eleme~ts 

at utilization level, and removal strategy at 

preparation plant 

4. Fate of chemicals used in coal-preparation processing 

5. Develop off-line control of preparation plants using 

ROM quality estimates based on geostatistics 

a. Compare with on-line control based on elemental 

analysis 

B. Ultrafine Coal 

1. Develop new test methods to replace washability tests 

presently used on +28 mesh material 

2. Develop new ASTM analytical methods where existing 

methods are either inapplicable or inaccurate, sucl' 

as for ash and sulfur 

3. Develop new measures of beneficiation potential, a~ 

maceral/mineral liberation 

C. Chemical Cleaning 

1. Quantitatively and qualitatively identify organic 

sulfur-containing molecules 

2. Develop measurement of physico-chemical surface 

properties to control surface-chemistry-based 

processes 

IV. Coal Marketing 

A. Develop relationships to quantify differences in coal 

quality as they affect the value of steam coal 

1. Constituents that cause abrasion and erosion 

2. Ash properties correlated with combustion behavior 
B. Develop relationship to quantify differences in coal 

quality as they affect the value of metallurgical coal 

C. Develop relationships to quantify differences in coal 

quality as they affect the value of coal used in ceme~t 

kilns 

D. Develop blending techniques to produce desirable coal 

characteristics 

1. Steam coal 

2. Metallurgical coal 

3. Cement-kiln coal 

V. Ancillary Operations 

A. Develop a relative spontaneous-combustion potential 1ndex 

B. Fate of various pollutants in typical disposal situations 

from mines and preparation plants 

VI. Technology Transfer 

A. Foreign Information 

1. Greater involvement in international organizations 

such as ISO (Standards) 

B. Domestic Information 

1. Collected by U.S. Government from foreign source~ 

2. Collected by Federal and State agencies 

a. Central data base 

C. Domestic Industry 

1. Workshops and seminars 

a. Further the application of existing, powerful 

tools, such as geostatistics and geographical 

logging 

In summary, the following four issues among those delineated were 

considered most significant for future research and developme~t 

investigations. 

o Characterization of minerals 

o Estimation method for plant performance from core/channel 

data 

o National coal-mining/preparation-plant performance data 

base 

o Coal properties as they relate to value of coal for 

specific utilization purposes 

205 
WORKSHOP AND PANEL IV 

ENVIRONMENTAL ISSUES AND THE ROLE OF COAL-QUALITY RESEARCH 

Workshop IV concluded that: 

o Additional research is needed to establish important 

coal-quality parameters that are related to major 

environmental issues and to establish the limits over which 

certain coal-quality parameters vary in nature. 

o Coal-industry technology needs to be upgraded and the 

methodologies used by the industry need to be reexamined. 

Panel IV recommended that additional research be conducted on: 

o Sulfur and its forms 

o Particulate matter with regard to the fusion tendency of fly 

ash, mineral species in coal, and ash resistivity 

o Physical properties of coal such as grindability, 

washability, and the viscosity of slag 

o Properties of the organic constituents of coal and ranges of 

moisture content 

o Specific trace elements--arsenic, selenium, mercury, boron, 

fluorine, and chlorine 

o Nitrogen in whole coal and in the volatiles produced during 

coal use 

2~ 
WORKSHOP AND PANEL V 

ADVANCED TECHNOLOGIES POR COAL UTILIZATION 

Summary of the conclusion and recommendations were: 

1. Initiate or expand research on: 

o Understanding the mineral species present in coal and the 

reactivities and size distribution of mineral-matter grairs 

in coal 

o Develop a direct method to determine the oxygen content of 

coal 

o Improvements in coke petrography (very little is currently 

being done in the United States) 

o Atomization characteristics of coal-water mixtures (CWM) 

o A high-shear viscosity test related to coal quality and to 

atomization of CWM 

o The properties of coal-ash slags under both reducing and 

oxidizing conditions 

o The chemistry of organic-sulfur compounds in coals 

o Particle-size distributions in ultra-fine coal (UFC) and 

standardization of particle sizes in UFC 

o New techniques to measure the chemistry of surface 

oxidation of coal and of specific chemical groups in coal 

o Understanding of trace-metal associations in coal and 

trace-metal release patterns 

o Comminution properties to aid in ultra-fine grinding of 

coal 

2. Improve coordination and cooperation among Federal agencies 

engaged in coal-quality research and in dissimination of resear~~h 

results by: 

o Providing better access to coal-quality data in the 

National Coal Resources Data System (NCRDS) of the USGS, 

holding workshops on NCRDS, and publishing a brochure(s) 

describing NCRDS 

o Provide computerized lists of coal-research projects and 

findings and mailing lists of appropriate personnel to 

207 
receive notice of relevant reports on research result~. 

Greater interaction is needed between the various 

subdisciplines working on coal quality 

o USGS should publish an annual report on projects and 

results of its coal-quality research 

o Establishing an intergovernmental task force to coordinate 

coal-quality research objectives 

Panel V recommended that priority should be given to researcb on 

mineral species and mineral-grain size distribution in coal, on 

coal grindability, and on improving communications among 

coal-quality researchers and between them and the general 

community of coal users. 

200 
PART III: POSTER SESSION ABSTRACTS 

LIST OF ABSTRACTS 

Affolter, R.H., and Stricker, G.D., Geochemistry of some Tertiary 

alluvial lowland coals from the Capps and Chuitna coal 

fields, Cook Inlet Region, Alaska. 

Allcock, J.B., and others, An interdisciplinary geoscientific 

approach to modeling coal-quality variations in a Texas 

lignite deposit: Implications for mine planning and use. 

Ashton, K.C., and others, Ash-fusion study of West Virginia coals. 

Campbell, Frank, Occurrence of sulfates discriminates oxidized 

from unoxidized coals in western New Mexico. 

Carlton, R.W., Image analysis of pyrite in Ohio coal: Relatic~ 

between pyrite grain-size distribution and pyrite sulfur 

reduction. 

Chao, E.C.T., and others, Petrographic documentation and 

interpretation of principal mineral occurrences in coal. 

Chao, E.C.T., and others, Upgraded quantitative petrologic and 

facies characterization of coal based on modern methodology. 

Coleman, D.D., and others, The use of stable isotope ratios for 

monitoring the behavior of organic and pyritic sulfur du~ing 

desulfurization of Illinois coals. 

Currens, J.C., and others, Applications of a coal-quality data 

base: Geology and quality of the fire clay coal in eastern 

Kentucky. 

Dulong, F.T., and others, Elemental variability and characterization by physical coal cleaning: Arsenic, a case study. 

Dulong, F.T., and others, Stable isotope geochemistry of calcite 

in the Upper Freeport coal bed. 

Eggert, D.L., and others, Composition and energy content of coal 

wastes and water chemistry of Green Valley-Wabash Mine Area, 

Vigo County, Indiana. 

Englund, K.J., and Thomas, R.E., Geologic setting of thick, lowsulfur coal in the Lower Pennsylvanian Pocahontas Formation, 

Virginia and West Virginia. 

211 
Friedman, S.A., A geochemical study of bituminous coal resources 

of Middle Pennsylvanian age in eastern Oklahoma: Part 1: 

maps showing distribution of fixed carbon and sulfur, and 

lead, zinc, and manganese. 

Golightly, D.W., and others, Current analytical methods for 

determining the inorganic composition of coals. 

Grady, W.C., and others, Relationships of palynology, petrography, 

and coal quality in some Upper Kanawa Formation coal beds of 

West Virginia. 

Harvey, R.D., and DeMaris, P.J., Size and maceral associations of 

pyrites in some Illinois coals and their float-sink 

fractions. 

Hatcher, P.G., and Spiker, E.C., Diagenesis of fossil-fuel 

precursors. 

Hickman, R.E., and Osterkamp, W.R., Sediment yields in watershP.ds 

draining the Appalachian coalfields and surrounding areas. 

Hildebrand, R.T., and Affolter, R.H., Influences of volcanism on 

coal quality--examples from the Western United States. 

Kotra, R.K., and Hatcher, P.G., Laser microprobe analysis and 

pyrolysis of geopolymers. 

Lyons, P.C., and others, Laser microprobe characterization of 

vitrinites from the Lower Bakerstown coal bed. 

Medlin, A.L., and others, Coal-quality analysis utilizing the 

National Coal Resources Data System (NCRDS) 

Mikesell, J.L., and others, In-situ elemental analysis of coal by 

neutron activation. 

Miller, E.V., The use of the National Coal Resources Data Syst~~ 

in coal quality studies. 

Neuzil, S.G., and Cecil, C.B., Modern analogs illustrating 

controls on coal quality. 

Nuelle, L.M., and others, Reducing and predicting sulfur content 

of Missouri coal through beneficiation and geologic modeling. 

Oman, C.L., and Meissner, C.R., Jr., Comparisons of the chemical 

characteristics of Gulf Coast lignite samples. 

Palmer, C.A., The assessment of modes of occurrence of trace 

elements in coal minerals using size and density separation 

procedures. 

212 
Pierce, F.W., and others, A geostatistical approach to assessing 

coal-quality data. 

Ruppert, L.F., and others, Cathodoluminescent properties of qnartz 

in coal: A method for determining variation in coal quality. 

Senftle, F.E., and others, Magnetic properties of coal. 

Senftle, F.E., and others, High-technology fuel. 

Smith, C.J., and King, H.M., Computer mapping of quality data for 

coals in West Virginia--an aid in matching a specific co~l 

grade to a specific end use. 

Stanton, R.W., and others, Physical and chemical variables related 

to coal washability: Upper Freeport coal bed facies. 

Stanton, R.W., and others, Quality and extent of facies within the 

Upper Freeport coal bed: West-central Pennsylvania. 

Tewalt, S.J., and Jones, C.M., Chemical and petrologic 

characteristics of deep-subsurface Wilcox lignites (Eoc~ne) 

from east and east-central Texas. 

Tice, J.H., and others, Coal reserve characterization for emission 

control. 

Trent, V.A., and Oman, C.L., Sulfur content of coal in the 

Appalachian and Illinois Basins. 

Vorres, K.S., and Marianelli, R.L., The premium coal sample 

program. 

Whelan, J.F., and others, Stable-isotope and inclusion-fluid 

composition shades of epigenetic pyrite and sphalerite from 

Illinois Basin coals. 

Windolph, John, Jr., and others, Comparative geochemistry of two 

coal beds from contrasting depositional environments of Late 

Cretaceous age in the western part of the Wind River Basin, 

Wyoming. 

213 

GEOCHEMISTRY OF SOME TERTIARY ALLUVIAL LOWLAND COALS 

FROM THE CAPPS AND CHUITNA COAL FIELDS, 

COOK INLET REGION, ALASKA 

by 

R.H. Affolter and G.D. Stricker 

U.S. Geological Survey 

The Capps and Chuitna coal fields, Beluga coal-resource area, 

are located approximately 90 km west of Anchorage in the upper 

Cook Inlet Region of south-central Alaska. Forty-three core 

samples from these fields, representing eight coal beds (Capps, 

Waterfall, M, 0, Q, and three unnamed beds), were collected from 

the lower Oligocene to middle Miocene Tyonek Formation. The coalbearing section of the Tyonek Formation is believed to have 

accumulated in poorly drained alluvial lowlands adjacent to 

tectonically active highlands. 

Statistical summaries of proximate and ultimate analyses, 

heat-of-combustion, forms-of-sulfur, and contents of 40 major-, 

minor-, and trace-elements were compiled and evaluated along with 

the low-temperature-ash mineralogy for each sample. Analyses show 

an apparent rank that ranges from subbituminous B to subbitumjnous 

C, with a variable ash content of 4.7 to 46.5 percent and one of 

the lowest reported sulfur ranges for any United States coal 0f 

0.08 to 0.33 percent. 

Nearly half of the elements analyzed (Si, Al, K, Ti, Be, Cr, 

Cu, F, Ga, La, Sc, Th, U, V, Y, Yb, and Zr) show a variation f.n 

concentration that is directly related to the ash content of the 

coal (linear correlation coefficients )0.8). Mineral composition 

of the low-temperature ash is predominantly kaolinite and 

mica-type clays with varying amounts of quartz. These data 

suggest that many of the elements that vary with ash content may 

also be associated with the clay minerals. The M bed has the 

lowest ash content and the lowest concentration of ash-correlated 

elements, whereas the Capps bed has the highest ash content and 

therefore, the highest concentration of these elements. The 

variability of ash content is probably a direct result of the 

proximity of the original peat swamp to nearby tectonically active 

highlands. The peat is thought to have accumulated in non-marine 

swamps as indicated by the low average forms-of-sulfur for all 

eight coal beds (0.13 percent organic sulfur, 0.02 percent sulfate 

sulfur, and only 0.01 percent pyritic sulfur). Trace elements 

that normally show positive correlation with sulfur in most U.S. 

coals, such as As, Cd, Co, Fe, Mo, Ni, Pb, and Zn, are low in 

concentration for coal from the Tyonek Formation. 

215 
AN INTERDISCIPLINARY GEOSCIENTIFIC APPROACH 

TO MODELING COAL-QUALITY VARIATIONS IN A 

TEXAS LIGNITE DEPOSIT: IMPLICATIONS 

FOR MINE PLANNING AND USE 

by 

J.B. Allcock, S.W. Beckman, D.A. Juckett, 

J.A. Luppens, N.H. Moster, K.S. Schorno, M.A. Waldrop 

Phillips Research Center 

Geologists, mining engineers, geophysicists and geochemist~ 

from Phillips Coal Company and Phillips Petroleum Company are 

working together to determine the best way to mine a lignite seam 

to meet quality standards for a potential client. The program 

combines existing whole-seam quality data from more than 60 cor~d 

holes and geophysical logs from more than 600 uncored holes witl' 

analyses and logs from three cores that were sampled in 0.2-0.5~ 

foot intervals and analyzed in detail. Standard analyses were 

done by an independent laboratory and mineralogical, petrographic, 

infra-red and pyrolysis studies were done by Phillips and the 

University of Utah. We used this information to interpret the 

earlier data and develop an environment of deposition model. 

The seam, as much as 5.5-feet thick and covering an area 

about 5 miles by 7 miles, formed in lower Wilcox (Eocene) times in 

an upper-delta-plain, freshwater hardwood swamp between two 

regional distributary channels. Sulfur content is (0.8 percent 

(dry basis) except in the extreme southwest of the prospect. 

Sediment supply was mostly from the north, so the overall ash 

content decreases southwards, although it increases near smaller 

channels. The overall energy level increased through time 

{upwards) with four recognizable higher energy pulses. 

These pulses were traced by density logs to predict ash 

distribution when designing a selective mine plan for part of the 

prospect. The plan increases as-mined calorific value by 350-600 

Btu/lb and reduces ash content by 3-5 percent while losing only 8 

percent of the original tonnage and increasing the strip ratio 

from 12.4 to 13.4. 

Groundwater-driven redistribution of organically bound 

calcium has increased the Ca:S ratio, and thus the potential 

natural sulfur retention, in the proposed mine area. 

Vertical maceral zoning, partly correlatable with the 

sedimentary cycles, can be traced by resistivity log signatures. 

The zones have different pyrolysis yields and the relationship 

could be used to evaluate synfuel potential of lignite seams. 

216 
ASH-FUSION STUDY OF WEST VIRGINIA COALS 

by 

K.C. Ashton, C.J. Smith, and M.E. Hohn 

West Virginia Geological and Economic Survey 

As more industries and utilities convert to coal, ash-fusion 

information becomes more important for boiler design (wastedisposal systems). For example, burning a low-fusion-temperature 

coal can cause slagging--the buildup of molten ash on boiler 

waterwall tubes. This not only lowers boiler efficiency but also 

can increase downtime. 

Recently, potential buyers of West Virginia coal have frequently inquired about ash-fusion. However, the amount of 

information in the West Virginia Geological and Economic Survey's 

database is limited to data from about 800 samples, 50 percent of 

which are collected in five counties. Thus, the Survey is 

conducting a study of ash-fusion temperatures for the State's 

coals, to increase available data and its geographic coverage. 

A Leco AF-500 automated ash-fusion analyzerl is used in this 

study. This presentation addresses: 

(1) operation of an automated ash-fusion analyzer; 

(2) repeatability of results from an automated analyzer; 

(3) comparison of automated with conventional data; 

(4) preliminary research developments. 

The goal of this project is to do research on ash fusion cf 

West Virginia coals. The research seeks to develop for West 

Virginia coal a statistical-correlation model relating ashelemental data with fusion data, and to investigate the relatic~ship 

between ash color and fusion temperature. (Light-colored ashe~ 

tend to have higher fusion temperatures than darker ashes.) 

The ash-fusion project adds vital user-needed information to 

our computer database. With this addition, the Survey can offer a 

more complete, unbiased source of information about West Virginia 

seams to prospective buyers of West Virginia coal. 

2ll 
OCCURRENCE OF SULFATES DISCRIMINATES OXIDIZED FROM 

UNOXIDIZED COALS IN WESTERN NEW MEXICO 

by 

Frank Campbell 

New Mexico Bureau of Mines and Mineral Resources 

Knowledge of the depth and distribution of oxidized coals can 

allow for better development of the coal resource of an area, as 

well as increased accuracy in prediction of trends in coal quality. 

Sulfates, usually in the form of gypsum, tend to be found in 

near surface coals whereas organic and sulfide sulfur are fou~d in 

coals at all depths. The formation of sulfates is a product of 

oxygen-bearing surface water, which percolates through a coal bed 

converting sulfides to sulfates. Thus the presence of sulfates 

can be useful in identifying oxidized coals. 

Twenty-two commonly run combustion analyses including nine 

major oxides (Si, Al, Fe, Ti, Ca, Mg, Na, K, P) were run on 50 

coal samples from western New Mexico; the coals were from the 

Upper Cretaceous Moreno Hill and Fruitland Formations. Both 

proximate and ultimate analyses show significant differences Phen 

separation is based on whether or not sulfates are present in the 

sample. Parameters, such as Btu, carbon and hydrogen, in the 

sulfate-bearing samples have a lower average value and a highP.r 

standard deviation in range of values and lower means. In those 

samples containing sulfates both moisture and oxygen are incr~ased, 

along with their standard deviations. Downhole profiles show 

these changes in combustion parameters with depth at a single 

location. Of the nine major oxides, four, (Ca, Na, Mg, K) showed 

change in oxidized coals. Ca and Na are decreased in both th~ 

mean value, as well as their standard deviations. An increas~ in 

mean and standard deviation are found for Mg and K. This results 

in a slight reduction in the silica ratio for unoxidized coal~. 

The depth at which the sulfates form, indicating an oxidized c?al, 

is reasonably uniform throughout an area, but differs in area~ of 

different climatic and geologic conditions. 

The accuracy of some calculated values, such as rank and 

relation of hydrogen to volatile matter are affected. The calculated rank will vary depending on whether or not sulfates are 

present. In the case of the Moreno Hill coals, the rank range.s 

from subbituminous A to high-volatile bituminous C for coal from 

the same area coal bed. Hydrogen has a direct relationship to 

volatile matter in non-sulfate-bearing coals making estimates of 

volatile matter from hydrogen content more accurate. 

218 
IMAGE ANALYSIS OF PYRITE IN OHIO COAL: 

RELATION BETWEEN PYRITE GRAIN-SIZE DISTRIBUTION 

AND PYRITE SULFUR REDUCTION 

by 

R.W. Carlton 

Ohio Geological Survey 

The size characteristics of pyrite in coal have long been 

known to influence the amount of pyrite sulfur reduction that will 

occur when a coal is washed by float-sink methods. However, 

manual microscopic methods of determining the size characteristics 

of pyrite embedded in coal are tedious and time consuming, and, as 

a result, practical application of this knowledge has been ver:T 

limited. Modern automated image analysis offers a potentially 

rapid, nontiring method of determining the size distribution of 

pyrite associated with coal. 

Linear-regression analysis of data collected on 14 X 28-m~sh 

coal indicates a strong correlation between the cumulative per~ent 

pyrite in certain pyrite size ranges determined by image analy~is 

and pyritic sulfur reduction of washed coal. Using two different 

magnifications and slightly different operating conditions for the 

image analyzer, correlation coefficients of r = -0.95 (high magnification), and r = -0.90 (low magnification) were obtained between 

pyritic sulfur reduction and cumulative percent pyrite in the less 

than 24 micron and less than 66 micron size range, respectively. 

Two factors which appear to work against these strong relatio~ships 

in this study are poor precision of the pyrite-size-distribution 

data and the unpredictable clustering of pyrite grains in some 

coal particles. The equations defining the sulfur reduction/~ize 

distribution correlation should be applied only under the 

conditions in effect when the relationship was established. 

219 
PETROGRAPHIC DOCUMENTATION AND INTERPRETATION OF 

PRINCIPAL MINERAL OCCURRENCES IN COAL 

by 

E.C.T Chao, J.A. Minkin, J.M. Back, and S.S. Crowley 

U.S. Geological Survey 

In order to understand and interpret the sulfur and ash 

contents and variations in coal, it is necessary to document the 

crystal habit, modes of occurrence, distribution, and abundances 

of the principal minerals in coal. These minerals include iron 

sulfides (pyrite and marcasite), quartz, clays (illite, kaolinites, 

smectites, and chlorites), carbonates (calcite, siderite, ankerite, 

and so on) and other accessory minerals such as feldspars, rutile, 

and zircon. Some of these minerals, whether of primary (syngenetic), secondary (epigenetic), or diagenetic origin, may be 

important indicators of the paleogeochemical and paleodepositional 

environment of the precursors of the coal in which they occur. 

The modes of occurrence, distribution, and abundance of types 

of minerals in coal seem to have close association and correlation 

with the relative abundance of either vitrinite, or exinite and 

inertinite groups of macerals in coal. High mineral contents 

generally correlate with high exinite- and/or inertinite-bearing 

coals and low mineral contents generally correlate with high 

vitrinite coals. These observations are important to our understanding of coals of allochthonous versus autochthonous origin. 

Principal minerals in coal, and their occurrences in partings 

associated with coal bed, may also be correlated with the tra~eelement characteristics of particular coals. Hence, the minerals 

may be key indicators of the source of the organic and inorganic 

detritus that may contribute to the high or low sodium, chlorf.ne, 

or fluorine contents of particular coals. 

220 
UPGRADED QUANTITATIVE PETROLOGIC AND FACIES 

CHARACTERIZATION OF COAL BASED ON MODERN METHODOLOGY 

by 

E.C.T. Chao, J.A. Minkin, J.M. Back, and S.S Crowley 

U.S. Geological Survey 

Our principal research objectives are the development and 

application of modern techniques and procedures for the establishment of an upgraded, quantitative coal-quality and description 

data base with emphasis on petrologic and facies characterization 

of autochthonous and allochthonous coals. (Autochthonous coals 

develop from plants which after death form peat in place. 

Allochthonous coals form from plant remains which were transported 

considerable distances from their original site to site of 

deposition and peat formation). 

Coals of autochthonous origin generally have a uniform 

thickness (commonly less that 15 feet). Coals of allochthonous 

origin are generally very thick (more than 50 feet) and show 

pronounced coal-bed thickness variations. They may be distinguished petrologically on the basis of structural and textural 

characteristics of the coal. Autochthonous coals are usually well 

banded or finely laminated and layered. Allochthonous coals are 

typically poorly to irregularly banded or lenticular. The bands 

may be steeply dipping and contain rounded to irregular-shaped 

chunks of vitrite or vitrain. 

The data obtained with the modern techniques we use include: 

1. Macroscopic and microscopic quantitative characterization 

of coal-bed profiles in terms of coal lithotypes and total VEl~ 

(V-vitrinite group, E-exinite group, !-Inertinite group, M-mineral 

group), using high-resolution binocular microscopes, research 

petrographic microscopes and an automated image-analysis systerr. 

2. Characterization of the modes of occurence, assemblages, 

distribution, and abundance of the principal minerals in coal t:hat 

contribute to the ash content in a coal bed. These minerals 

include pyrite-marcasite, quartz, clay minerals, carbonate, and 

accessory minerals. Such specific mineral data require the 

combined use of optical petrographic microscopy, interference 

microscopy, X-ray diffraction, automated image analysis, scannfng 

electron microscopy, electron-probe microanalysis, and scanninr, 

transmission electron microscopy. The mineral distribution and 

abundance data so obtained are also essential for establishing a 

coal-bed formation curve. 

221 
3. Direct determination of trace-element content in coal 

macerals and minerals by electron-probe microanalysis and by 

proton-induced X-ray emission microprobe methods. The traceelement data may be used to establish a geochemical profile of 

the coal bed as a basis for interpreting the paleogeochemical 

environment of deposition of the coal precursor. 

The new and upgraded quantitative coal-quality data base is 

essential and vital to both the characterization of the coal 

quality and to the interpretation of coal facies with respect to 

a particular depositional environment. 

222 
THE USE OF STABLE ISOTOPE RATIOS FOR MONITORING 

THE BEHAVIOR OF ORGANIC AND PYRITIC SULFUR 

DURING DESULFURIZATION OF ILLINOIS COALS 

by 

D.D. Coleman, C.L. Liu, and K.C. Hackley 

Illinois State Geological Survey 

Naturally occurring differences in the sulfur isotopic 

compositions of organic and pyritic sulfur in some coals make it 

possible to monitor the fate of these two different species during 

desulfurization. Once the isotopic compositions of the individual 

species are established, one can analyze the sulfur removed during 

desulfurization (or the residual sulfur remaining in the treate~ 

coal) and calculate the proportion of each species removed. 

Previous research at the ISGS has shown that a significant 

amount of sulfur can be removed from coal by low-temperature 

charring (pyrolysis). Furthermore, the sulfur which remains in 

the char is rendered more subject to chemical attack than that in 

the feed coal. Pyrolysis experiments have been conducted on three 

different samples of Illinois No. 6 coal at temperatures rangin~ 

from 350° to 750°C under a nitrogen atmosphere. The sulfur 

released with the volatile products and the sulfur remaining in 

the char were quantitatively collected and their respective 

isotopic compositions measured. The isotopic data showed that for 

all three samples tested, the sulfur released with the volatiles 

was predominantly organic in origin; pyritic sulfur was not 

volatilized until the temperature exceeded 4500 to 5oooc. This is 

in agreement with thermogravimetric analysis (TGA) and 

differential thermogravimetric analysis (DTG) which suggests tt·.~t 

organic sulfur and pyritic sulfur are liberated at different 

temperatures. Further testing has shown that during charring ct 

65ooc, some of the pyritic sulfur becomes incorporated into the 

organic structure. There does not, however, appear to be any 

migration of sulfur in the reverse direction (from the organic 

phase to the pyritic phase). 

Low-temperature pyrolysis coupled with other processes shows 

technical and economic promise as a method for producing a 

compliance fuel from high-sulfur Illinois coal. Stable isotope 

monitoring has proven to be very helpful in understanding the 

reactions which are involved during desulfurization of Illinoi~ 

coal--a requirement if process efficiency is to be improved. ~he 

method is unique in that it uses an inherent characteristic of the 

coal as a "tracer"; no additives or chemical treatments of the 

coal are necessary prior to desulfurization. 

223 
APPLICATIONS OF A COAL-QUALITY DATA BASE: 

GEOLOGY AND QUALITY OF THE FIRE CLAY COAL 

IN EASTERN KENTUCKY 

by 

J.C. Currens, J.C. Cobb, and R.A. Brant 

Kentucky Geological Survey 

The Fire Clay coal is one of the leading compliance coals in 

the eastern United States. This coal has been mapped on more than 

120 7.5-minute quadrangles in eastern Kentucky. Resource estimates 

show 5.9 billion tons of original coal resources and 5.2 billion 

tons of remaining resources. The Fire Clay occurs in a terrigenous 

clastic wedge between two marine units in the Breathitt Formation 

of Middle Pennsylvanian age. An extensive data base for this coal 

consisting of 1,569 measured sections and 200 analyses of channel 

samples has been developed by the Kentucky Geological Survey. 

Applications of this data base include geologic and coal-quality 

modeling. 

Geologic investigations of Fire Clay include mapping the coal 

thickness and various quality characteristics such as sulfur, ash, 

moisture, and calorific content. Analysis of the overlying strata 

provides information about potential influences on the coal from 

fresh, brackish, and marine depositional systems. Coal-resource 

maps serve as the foundation for geologic and coal-quality morleling. The geometry of coal-thickness contours gives information 

about paleoslope and drainage patterns, and the isopach maps ~erve 

as an appropriate base for plotting sulfur and ash values. 

Patterns and trends in geology and coal quality which arise from 

these constructions are useful for predicting coal-quality 

characteristics in areas of less data. 

The use of cluster analysis has been attempted on an expnrimental basis to classify areas of the coal bed according to similar 

geologic parameters such as coal thickness, parting thickness, 

number of partings, sulfur content, and ash content. A princi.palcomponent analysis gives a ranking of the importance of each 

parameter in influencing the clustering. As more information 

becomes available and statistical relationships are better 

understood, the ability to extrapolate coal-quality 

characteristics will improve. 

The abundance of compliance-quality coal in the Fire Clay has 

been estimated using probability modeling based upon the frequency 

of results of paired sulfur and Btu analyses. A cumulative 

frequency distribution was constructed to show the potential 

sulfur dioxide emissions per million Btu. This cumulative 

frequency distribution yields the percent of coal resources that 

224 
satisfy any given sulfur dioxide standard. In the case of the 

Fire Clay coal, 68 percent of resources are in compliance at a 

standard of 1.2 pounds of sulfur dioxide per million Btu, 54 percent are in compliance at 1.0 pound of sulfur dioxide per millio, 

Btu, and only 3 percent are in compliance at 0.8 pound of sulfur 

dioxide per million Btu. 

225 
ELEMENTAL VARIABILITY AND CHARACTERIZATION BY PHYSICAL 

COAL CLEANING: ARSENIC, A CASE STUDY 

by 

F.T. Dulong and C.B. Cecil 

U.S. Geological Survey 

J.D. Kilgroe 

U.S. Environmental Protection Agency 

Six hundred thirteen complete channel samples representing 

34 coal beds of the Pennsylvanian and Permian (?) periods in the 

central Appalachian basin were analyzed for major, minor, ana 

trace elements. The average arsenic concentration on a whole.-coal 

basis is 14.0 ppm (standard deviation= 14.9). The ranking cf the 

average arsenic concentration by formation is: Kanawha (mean = 

5.04 ppm), is less than New River (mean = 10.1 ppm), which is 

equal to Pocahontas (mean= 10.9 ppm), which is equal to 

Monongahela (mean= 12.4 ppm), and all are less than Allegheny 

(mean = 18.1 ppm). 

An analysis of the Upper Freeport coal bed of the Allegheny 

formation was undertaken to evaluate the regional (western 

Pennsylvania) versus local (within mine) arsenic variation. The 

arsenic concentration and variation are greater on the regional 

scale (mean = 40.8 ppm with a standard deviation = 30.6 for n = 

21) than within mine (mean = 23.8 ppm with a standard deviation = 

18.7 for n = 19). 

Nine samples of the Upper Freeport coal bed were subjected to 

a 21-part washability study. This float-sink testing verifien an 

inorganic affinity of arsenic and indicated an associative 

relationship between arsenic and pyritic sulfur for the Upper 

Freeport coal bed. There is an average 47 percent reduction in 

the arsenic concentration in utilizing the coal floated at a 

specific gravity of 1.6, which represents approximately 86 weight 

percent of the coal. The remaining 14 weight percent of the coal 

shows a seven-fold increase in the arsenic concentration relative 

to the original sample. On the basis of these results, arsenic in 

the Upper Freeport coal bed se!ems to be associated with largesized, removable pyrite. High concentrations of both arsenic 

()19 ppm) and pyritic sulfur ()1.3 percent) indfcate a strong 

potential for their reduction by physical coal-cleaning methods. 

However, samples containing comparably high pyritic sulfur but 

moderate arsenic contents (<9 ppm) show very little potential for 

removal by physical processing. This is attributed to the smrll 

size (<30 um and dispersed) of the pyrite. 

226 
STABLE ISOTOPE GEOCHEMISTRY OF CALCITE IN THE 

UPPER FREEPORT COAL BED 

by 

F.T. Dulong, E.C. Spiker, C.B. Cecil, and R.W. Stanton 

U.S. Geological Survey 

At least two, and possibly three, stages of calcite formation 

are indicated by the isotopic composition of calcite samples from 

the Upper Freeport coal bed. Samples of calcite from cleat were 

compared to sink 1.8 gravity fractions and -100 mesh size fractions 

from size-gravity separates. All are enriched in 13c relative to 

the PDB standard for carbon. The relatively constant 18o values 

for these samples may indicate a constant temperature of formation. 

The positive enrichment in 13c is indicative of C02 derived frc, 

fermentation processes. In contrast, calcite in float 1.275 

gravity fractions tends to be depleted in 13c. The 18o values in 

the float 1.275 samples have a wide range, indicating possible 

variation in the temperature of formation. 

Comparison of calcite from coal samples with samples of 

associated limestone suggests that calcite in coal resulted from 

biotic and abiotic processes within the peat/coal. Some of th~ 

calcite in the float 1.275 fraction from the Upper Freeport coal 

bed may have been formed very early as the result of bacterial 

sulfate reduction. The cleat calcite, sink 1.8 calcite, and -100 

mesh calcite formed during a second stage, apparently as a resnlt 

of fermentation and methanogenesis. Part of the calcite in float 

1.275 samples may have formed in a third and still higher 

temperature stage which was probably abiotic and the result of 

thermally generated C02 during coalification. The origin of 

calcite in the coal controls its segregation during grinding, 

sizing, and float-sink testing. 

227 
COMPOSITION AND ENERGY CONTENT OF COAL WASTES AND WATB~ 

CHEMISTRY OF GREEN VALLEY-WABASH MINE AREA, 

VIGO COUNTY, INDIANA 

by 

D.L. Eggert, J.G. Haller, P.N. Irwin, and L.V. Miller 

Indiana Geological Survey 

The site of the abandoned Green Valley-Wabash Mine, Vigo 

County, Indiana, contains an estimated 5 million tons of wastes 

distributed over about 60 acres to depths of as much as 55 feet. 

The wastes, from a coal-preparation plant, are composed of 

silicate and sulfide minerals and coal in gob piles and tailings 

ponds. 

Analyses of coal tailings were as follows: ash (750°C), 

13.1 - 35.5 percent; total sulfur, 3.5 - 9.3 percent; and heat 

content, 8,000 - 11,750 Btu/lb. Analyses of gob ranged, respectively, from 38.8 to 79.4'percent; 4.9 to 23.8 percent; and 1,360 

to 5,470 Btu/lb. Washability tests on gob samples indicated that 

some beneficiation might permit recovery of about 1 million tons 

of coal. 

Five water samples were taken and analyzed: (1) West Little 

Sugar Creek above the site; (2) West Little Sugar Creek down~tream 

from the mine-waste area; (3) a small stream that drains the site; 

(4) a well in a waste pile; (5) a tailings pond. The pH of ~~st 

Little Sugar Creek decreased from 7.8 above the site to 4.2 t~low. 

Concentrations of 10 of the 16 elements determined in samples from 

West Little Sugar Creek increased significantly below the minedrainage area: iron, 0.2 mg/L above and 380 mg/L below (86 

percent was ferrous iron); sulfate, 66 mg/L above and 1,600 m~/L 

below; aluminum, 0.06 mg/L above and 74 mg/L below. The highest 

total dissolved solids (118,000 mg/L), predominantly as ferrous 

sulfate, was in the ground water from the well in the waste pile. 

Mine wastes at this site are a source of contaminants that 

adversely affect the quality of water in West Little Sugar Creek. 

Reclamation of this site would mitigate a significant source of 

acid mine drainage and provide coal for energy use. 

228 
GEOLOGIC SETTING OF THICK, LOW-SULFUR COAL IN THE 

LOWER PENNSYLVANIAN POCAHONTAS FORMATION, 

VIRGINIA AND WEST VIRGINIA 

by 

K.J. Englund and R.E. Thomas 

U.S. Geological Survey 

Economically important deposits of thick, low-sulfur coal are 

intercalated with a sequence of stacked delta lobes in the 

Pocahontas Formation of southwestern Virginia and southern West 

Virginia. The ancestral peat beds and associated clastic sediments were part of a northwestward - prograding terrestrial wedge 

that began to encroach on the southeastern shoreline of a 

regressive Carboniferous seaway in Late Mississippian time. 

During Early Pennsylvanian time, the northwestward progradation of delta lobes was interrupted by periodic stillstands and, 

along the delta front, sand was reworked and segregated by coastal 

currents and waves to form a system of curvilinear barrier-bar~. 

Extensive swamps developed behind these protective barriers and 

vegetation flourished on platforms created by the abandoned delta 

lobes. Plant growth and plant debris accumulated on the inactive, 

sand-dominated delta lobes and formed domed deposits of ombrogenous 

peat that were low in ash and sulfur. In contrast, high-ash m'lcks 

consisting of organic-rich clay and silt were deposited in the 

interlobe areas. As in modern analogous peat-forming environm~nts 

on the north coast of Borneo, the accumulation of thick deposits 

of low-ash and low-sulfur peat on the slightly elevated platform 

areas was dependent on high rainfall which contributed little, i.f 

any, mineral matter to the peat. The ombrogenous nature of the 

Pocahontas coal beds is demonstrated by the occurrence of thick, 

low-sulfur and low-ash coal over the central part of the sandstone 

lobes whereas, thin, impure, and discontinuous coal beds occur in 

the shale-dominated interlobe areas. This analysis demonstrates 

that the geometry, thickness, and orientation of delta lobes 

correlate strongly with coal quality and thickness--a relationship 

that can be a useful exploration tool. 

229 
A GEOCHEMICAL STUDY OF BITUMINOUS COAL RESOURCES 

OF MIDDLE PENNSYLVANIAN AGE IN EASTERN OKLAHOMA: 

PART 1: MAPS SHOWING DISTRIBUTION OF FIXED CARBON 

AND SULFUR, AND LEAD, ZINC, AND MANGANESE 

by 

S.A. Friedman 

Oklahoma Geological Survey 

More than 600 chemical analyses of channel and core samples 

of coal resources of Middle Pennsylvanian age from eastern 

Oklahoma, performed by The University of Oklahoma, the Oklahoma 

Geological Survey, the U.S. Geological Survey, and the U.S. Bureau 

of Mines since 1928 were tabulated and evaluated. These analyses 

provided 450 selected data points showing dry, ash-free (daf) 

fixed carbon and total sulfur and zinc, manganese, and lead in 

trace amounts that were plotted on four preliminary maps. The 

maps represent data from a combination of 17 coal beds. Some 

results and tentative conclusions follow. 

Although the typical coal is high-volatile B bituminous in 

rank, an area in northeastern Le Flore County contains coal of 

semi-anthracite rank, and an area in Coal County contains coal of 

high-volatile C bituminous rank. Daf fixed carbon (coal rank) 

decreases from east ()85 percent) to west (<45 percent). "Hot 

spots" ()60 percent daf fixed carbon) are present northeastward 

from Tulsa to within a few miles of Kansas. These areas are n~t 

related to present depth of burial of coals but may be related to 

a heat source in shallow basement rocks. 

The 7.8 million short tons of identified resources of 

bituminous coal in Oklahoma contains a weighted average sulfur 

content of 2.3 percent. Sulfur within individual coal beds ra~ges 

from (1 percent to )6 percent. Four of the 17 coal beds constituting the identified resources contain most of the low-sulfur 

(<1 percent) coal. Most medium- to low-volatile bituminous coal 

contains < 3 percent sulfur. In most areas near the Ouachita 

Mountains-and south of Tulsa near the Ozark Plateau, coals contain 

<3 percent sulfur. 

Whole-coal analyses indicate that positive anomalies exist 

for lead, zinc, and manganese near the Ozarks lead-zinc mining 

district, near the southern Ozarks, and near the Ouachita 

Mountains in the eastern part of the Arkoma Basin in Oklahoma. 

The lead anomaly in the southeastern area is small in areal ex~ent 

and in quantity. 

Coal rank shows no correlation with the proximity of the 

Ozark Plateau, the Ouachita Mountains, or the Arbuckle Mountains. 

230 
Low-and medium-volatile bituminous coals are believed to have been 

affected by a deep-seated heat source associated with the 

Mississippi Embayment. Most sulfur in coals was deposited during 

their peat-swamp stage, and the quantity of sulfur was due to 

depositional environments in and adjacent to paleo-swamps. The 

origin of trace elements is believed to be related to late 

Paleozoic emplacement of lead-zinc ores in the Ozark and Ouachita 

regions. 

231 
CURRENT ANALYTICAL METHODS FOR DETERMINING THE INORGANIC 

COMPOSITION OF COALS 

by 

D.W. Golightly, A.F. Dorrzapf, Jr., R.R. Larson, 

P.J. Aruscavage, and C.A. Palmer 

U.S. Geological Survey 

Information on the concentrations of inorganic elements in 

coals is essential to a complete description of coal quality. 

Concentrations of more than 70 elements important to an assessment 

of coal quality are determined by methods established in U.S. 

Geological Survey laboratories for the chemical and instrumental 

analysis of whole coal and of coal ash. This group of diverse 

methods results from the application of generally complementary 

measurement approaches that account for the capabilities of 

individual techniques, the quality of information sought, and the 

cost of this information. Methods are described for the determination of major-, minor-, and trace-elements in coal and coal ash. 

The principal measurement techniques used include atomic emission 

spectography (AES), atomic absorption spectrometry (AAS), x-ray 

fluorescence spectrometry (XRF), instrumental neutron activation 

analysis (INAA), and specific ion electrode (SIE). 

For the routine quantitative analysis of whole coal: Hg is 

determined by cold-vapor AAS; Pis measured by XRF; and As, Ba, 

Br, Ce, Co, Cr, Cs, Eu, Fe, Hf, Hg, K, La, Lu, Na, Nd, Rb, Sb, Sc, 

Se, Sm, Sr, Ta, Tb, Th, U, W, Yb, and Zn are determined by INAA. 

Recently developed direct-current arc AES methods enable the 

determination of 28 elements in whole coals. 

For the routine quantitative analysis of coal ash (500 

degrees Celsius ashing temperature): Cd, Cu, Li, Pb, and Zn are 

determined by flame AAS; Al, Ca, Fe, K, Mg, Mn, Na, P, S, Si, and 

Ti are determined by XRF. After a special ashing procedure and 

fusion of the resulting ash with NaOH, F concentrations are 

measured by SIE. An automated, semiquantitative direct-current 

arc AES method is applied to the analysis of all coal ashed for 

the determination of 64 elements. 

232 
RELATIONSHIPS OF PALYNOLOGY, PETROGRAPHY, AND COAL QUALITY 

IN SOME UPPER KANAWHA FORMATION COAL BEDS OF WEST VIRGINIA 

by 

W.C. Grady and C.F. Eble 

West Virginia Geological and Economic Survey 

W.H. Gillespie 

U.S. Geological Survey 

Twenty-nine samples from three Upper Kanawha Formation co~l 

beds (Stockton-Lewiston, Coalburg, and Winifrede) may be divided 

into two groups, based upon their coal-quality, petrographic, and 

palynologic characteristics. The first group contained 11 highash samples (average 17.5 percent) with moderate vitrinite 

abundances (V=61.6 volume percent), moderate exinite {E=7.4 percent) and moderate inertinite contents {1=13.1 percent). The 

second group of 18 samples contained moderate ash (8.7 percent), 

moderate vitrinite {V=57.4 percent), high exinite {E=9.2 percent), 

and high inertinite (22.6 percent) abundances. The first group of 

high-ash samples contained high percentages (average, 61.8 percent) 

of spores assignable to arborescent lycopods (Lycospora spp.). 

The second group contained high percentages (average 56.2 percent) 

of marrattiaceous tree fern spores (Laevigarosporites globosus, 

Punctatosporites minutus, and Punctatisporites minutus). 

Petrographic results suggest that the tree ferns occupie~ 

raised, well-drained portions of the swamps in areas of high-r~at 

oxidation, minor detrital influx, and minor early syngenetic 

mineral formation, which resulted in a lower ash content. The 

arborescent lycopods appear to have been the dominant vegetat1.on 

in areas of more-or-less standing water, which were less susceptible to peat oxidation. These areas were more susceptible to 

early syngenetic mineral formation and detrital influx, resulting 

in a higher ash content. 

These petrographic, palynologic, and coal-quality differences 

were observed between full-thickness channel samples (19 included 

in this study) and within a single coal bed sampled in 10 6-inch 

increments. 

233 
SIZE AND MACERAL ASSOCIATIONS OF PYRITES IN SOME 

ILLINOIS COALS AND THEIR FLOAT-SINK FRACTIONS 

by 

R.D. Harvey and P.J. DeMaris 

Illinois State Geological Survey 

Density-based processes are commonly applied to coal 

preparation and the amount of pyrite and other sulfides removed 

from coal varies considerably from one deposit to another. Some 

variation is due to the design and operation of the preparation 

plant, but some of it is due to the physical properties of th~ 

coal material. The influence of the physical properties, which 

are primarily thought to be the size and maceral associations of 

the pyrites, have not been sufficiently evaluated. The objectives 

of this project were to devise a microscopic procedure for 

assessing these properties, and to compare the results with 

float-sink tests for a few samples. 

Microscopic measurements were made on polished specimens of 

samples crushed to less than 840 um in size. The apparent diameter 

of pyrites was measured in micrometers along a line superpose~ on 

the grain so as to bisect the grain (Martin's Statistical 

Diameter). Precision tests indicated that at least 1000 grains 

selected at random must be measured to obtain a reproducible mean 

diameter characteristic of the sample. The maceral-mineral 

association of each measured grain was classified as one of seven 

different types (modified micro-lithotypes). 

The procedure used was to study three feed samples and six to 

seven float-sink fractions from each. The mean diameter of all 

pyrites in the specimens ranged from 6 to 30 um. Pyrites in lowdensity fractions were almost entirely associated with maceralrich particles, and these averaged 6 to 10 um in diameter. The 

largest grains were associated with other pyrite grains in pyritic 

coal particles. 

The characteristic found most useful for evaluating the 

float-sink behavior of coal was the percentage of the grain 

diameters within the various associations. Pyrite grains judged 

easy to remove were free grains, and grains enclosed in carbominerite or pyritic coal particles; pyrite grains judged hard to 

remove were those enclosed in vitrite, inertite, liptite, and hiand trimacerites. The ratio of the percentage diameters within 

these two groups of association gave a value we have defined as 

the pyrite cleanability index (PCI). PCI correlated very closely 

with pyritic sulfur content, measured chemically, and it may 

provide a useful means to evaluate and compare the cleanability of 

feed coals to various preparation plants. · 

234 
DIAGENESIS OF FOSSIL-FUEL PRECURSORS 

by 

P.G. Hatcher and E.C. Spiker 

U.S. Geological Survey 

Studies of the diagenesis of wood in anoxic sediments by 

solid-state 13c nuclear magnetic resonance (NMR) and stable 

isotopes show that microbiologically resistant components (lignin 

and resins) are selectively preserved whereas labile components 

(carbohydrates) are decomposed and lost. The selective degradation occurs with little alteration of cellular morphology. 

Coalification alters the lignin as the remnant cells coalesce to 

form a structureless mass (vitrinite). Similar studies of the 

diagenesis of algae in anaerobic sediments show that precursors of 

algal coal and kerogen evolve by a process of selective preservation and suggest that these precursors exist in algae and other 

microfloras. NMR spectra identify the chemical structure of the 

precursors as complex paraffinic macromolecules. Diagenesis 

essentially degrades microbiologically labile components such as 

carbohydrates, proteins, and lipids. 

235 
SEDIMENT YIELDS IN WATERSHEDS DRAINING 

THE APPALACHIAN COALFIELDS AND SURROUNDING AREAS 

by 

R.E. Hickman and W.R. Osterkamp 

U.S. Geological Survey 

Large amounts of sediment leaving a watershed can have 

undesirable effects downstream. Deposition in downstream channels 

can result in increased flood peaks, and deposition in reservoirs 

reduces reservoir capacity. Deposition in streams can destroy 

benthic plants and animals, and high suspended-sediment concentrations in the water column can stress and produce undesirable 

changes in water-column biota. In addition, some plant nutrients 

and toxic materials in rivers are more likely to move as materials 

associated with sediment particles rather than as dissolved load. 

The amount of sediment leaving a mine's watershed can be far 

greater than that leaving an undisturbed watershed because surface 

mining greatly disturbs the landsurface. Undisturbed, foreste1 

watersheds in the eastern United States have a mean annual sediment 

yield of about 30 megagrams (metric tons) per square kilometer. 

Annual yields as much as 7300 megagrams per square kilometer have 

been measured in small, mined watersheds. The amount of sedim~nt 

leaving any mined watershed depends not only upon mining activities, but also upon vegetation, soil characteristics, topograp~y, 

rainfall, watershed size, and the use of sediment controls. 

Preliminary results of work quantifying the sediment yields 

in watersheds draining the Appalachian coalfields and surrounding 

areas are presented in two maps. Mean annual suspended-sedime~t 

yields for the study area are given in one map. The second map 

indicates whether the sediment loads and concentrations in 

selected rivers have been increasing or decreasing. These two 

maps are based upon a compilation of available sediment-yield 

data. 

236 
INFLUENCES OF VOLCANISM ON COAL QUALITY--EXAMPLES 

FROM THE WESTERN UNITED STATES 

by 

R.T. Hildebrand and R.H. Affolter 

U.S. Geological Survey 

Several small Tertiary coal deposits in Idaho, Nevada, and 

Washington formed in fresh-water basins located near active 

continental (salic) volcanic centers. Metastable glassy material 

(tephra) ejected during volcanic eruptions was introduced into the 

coal-forming environment of these basins as ash falls. This 

tephra contributed to the high ash content of many of the coal 

beds, formed laterally persistent partings ("tonsteins") in the 

coal, and constitutes a large part of the strata enclosing the 

deposits. 

In order to study the possible relationships between the 

presence of tephra and coal quality, chemical data for 65 coal 

samples from 12 of these deposits were compiled and statistically 

analyzed. The results indicate that, in addition to the high ash 

content, coal from Tertiary deposits containing appreciable 

amounts of tephra generally is enriched in many elements compared 

to 460 coal samples from 11 deposits of similar ages remote from 

volcanic activity. Amounts of some elements, notably Co, Cr, C·t, 

F, Mo, Nb, Ni, U, V, Y, Zn, and Zr, are significantly higher in 

the tephra-containing deposits, and are not related to ash content 

(12.3 to 56.1 percent) or apparent rank (lignite to high-volatile 

A bituminous coal). Amounts of some other elements, particularly 

As and Sb, appear to be directly related to the sulfur content of 

the coal. Many of the coal samples from deposits influenced by 

volcanism also contain unusually high amounts of some less comm~n 

trace elements, including Ge, rare-earth elements (Ce, La, Nd, 

Yb), and W. 

Tephra in the coal beds and enclosing strata is the probable 

source of most of the elements enriched in these deposits. 

Volcanic glass deposited in the coal-forming environment remains 

largely unaltered during coal formation. Diagenetic alteration of 

the glassy material in the surrounding tuffaceous strata and 

subsequent leaching by groundwater mobilizes soluble oxides of 

such elements as Mo, U, and V. These oxides are transported in 

solution from the surrounding rocks and introduced into the coal 

deposit, where they precipitate in the reducing environment of the 

organic-rich sediments. 

237 
LASER MICROPROBE ANALYSIS AND PYROLYSIS OF GEOPOLYMERS 

by 

R.K. Kotra and P.G. Hatcher 

U.S. Geological Survey 

Laser microprobe mass spectrometry was used to examine 

chemical structural components of plant biopolymers, coal, ard 

related substances. The new Laser Micropobe Mass Analyzer (I.AMMA 

1000, Leybold-Heraeus Inc.) utilizes a neodymium-YAG laser tc 

desorb, photolyze, pyrolyze, and subsequently ionize organic and 

inorganic components. The system is capable of detecting orranic 

and inorganic species in both the positive and negative ion ~~des 

and has the potential of serving as an organic microprobe. 

However, it cannot analyze neutral species which, in some caEes, 

may be produced in greater abundance than charged species. 

Results indicate that characteristic organic ions, some molec·1lar 

ions, elemental ions as well as some recombination ions are 

produced by the laser ionization process. The interpretation of 

the LAMMA spectra of the complex geopolymers is a difficult task 

at this stage due, in part, to the lack of a sufficient LAMMI 

spectral data base. A systematic study of the laser-induced 

spectra of plant biopolymers and geopolymers with various laser 

energies, sample preparation methods, reproducibility, and sc on, 

is required before attempting fingerprinting. In our evaluation, 

the commercial system available presents certain limitations, 

especially in data processing, and further development of this new 

technique may facilitate routine use. 

Chemical structural information may also be obtained with 

related alternate microprobe techniques. Neutral species prc1uced 

by laser interaction can be directed to a gas chromatograph for 

identification. A laser microprobe gas chromatograph system has 

been built to analyze trapped volatiles and contents of fluid 

inclusions in a variety of materials. Volatiles are swept into a 

chromatograph equipped with a helium ionization detector. Laser 

pyrolysis of bulk organic geopolymers followed by detection with 

suitable detectors such as flame ionization, alkali flame 

ionization and so on, is an approach that is currently being 

pursued. 

In addition to the laser techniques, flash thermal pyrolysis 

techniques on samples also yield structural information. 

Kerogens, coals, humic substances, separated plant fragments, 

and so on, have been analyzed by pyrolysis gas chromatography. 

Information obtained from bulk analysis as well as by microprobe 

will provide specific knowledge on the origin, conditions of 

formation, and transformation of coal and related substances. 

238 
LASER MICROPROBE CHARACTERIZATION OF VITRINITES 

FROM THE LOWER BAKERSTOWN COAL BED 

by 

P.C. Lyons, G.A. Sellers, and F.W. Brown 

U.S. Geological Survey 

D.M. Hercules and J.J. Morelli 

University of Pittsburgh 

M.A. Millay 

University of Maryland 

The Laser Microprobe Mass Analyzer (LAMMA 1000) is a stateof-the-art microprobe system capable of analyzing mineral and 

maceral components in coal. All elements and isotopes (including 

hydrogen) and organic fragments up to m/z 2000 can be detected by 

this system. Our research group has been "fingerprinting" various 

minerals and macerals in bituminous coal. We have succeeded in 

"fingerprinting" iron sulphide (probably pyrite) and different 

types of vitrinites within the Lower Bakerstown coal of medium 

volatile bituminous rank. 

The spectra for the banded and nonbanded vitrinite show the 

elements Na, Mg, Al, K, Ca, and Fe. However, the banded vitrinite 

is characterized by Li, Ti, Sr, Ba, F, ±.Cl, and an organic mass 

peak at m/z 65 amu, probably representing the aromatic ion, CsHs+· 

These latter components are absent or lacking in spectra of the 

nonbanded vitrinite. These differences in elemental chemistry 

possibly indicate chemical variations in tissues or other organic 

components from which the banded and nonbanded vitrinites were 

derived and/or elements entrapped from fluids mobilized during 

diagenesis. 

239 
COAL-QUALITY ANALYSIS UTILIZING THE NATIONAL 

COAL RESOURCES DATA SYSTEM (NCRDS) 

by 

A.L. Medlin, K.K. Krohn, and P.T. Kerr 

U.S. Geological Survey 

Coal quality, the thermal, physical, and chemical properties 

of coal, has become an increasingly important issue with changing 

technology and legislative usage restraints. There are many 

aspects to this issue today and many more developing with changes 

in economic and technologic requirements of coal usage. Some of 

these aspects are: boiler design related to proposed feedstock 

chemical composition, potential emissions from coal consumption, 

effectiveness of coal cleaning in reducing chemical components and 

emissions, beneficial components that can be used to optimize 

certain coal-utilization processes, and definition of sufficient 

coal resources that meet specific quality criteria. Both computer 

techniques and adequate coal-quality data are ess~ntial components 

in responding to the current needs for synthesis and identification of problems and solutions as well as meeting further 

analytical requirements. 

NCRDS provides users with a national data base of documented 

coal-quality data and the computer-analysis tools to study the 

data in a variety of ways. The USCHEM data base contains the 

results of several thousand analyses of coal samples collected 

according to U.S. Geological Survey standards. The analytical 

data include: proximate and ultimate values, oxides, and 61 najor 

and minor trace elements. Some of the current capabilities and 

applications include: trends in coal quality for individual or 

combined chemical elements within coals, calculation of potential 

emissions from coal consumption, delineation of coal resource~ 

with defined coal quality characteristics. In addition, the 

system is designed to be flexible and useful in future applications by providing general graphic and tabulation functions. 

System users can continue to use the system capabilities for their 

particular analysis or application as technology and constraints 

change. 

240 
IN-SITU ELEMENTAL ANALYSIS OF COAL BY NEUTRON ACTIVATION 

by 

J.L. Mikesell, F.E. Senftle, and A.B. Tanner 

U.S. Geological Survey 

The U.S. Geological Survey (USGS) has worked to develop 

neutron techniques for the borehole measurement of the elemental 

composition of ores since 1969, and first demonstrated a borehole 

ultimate analysis of coal in 1977. Borehole measurements such as 

these permit real-time evaluation of coal quality without the 

expense of coring or the delays associated with laboratory 

analyses. Two technological innovations make such measurements 

possible: the availability, from Savannah River Operations 

Office, DOE, of small californium-252 (252cf) fission neutron 

sources, and the development, by USGS and Princeton Gamma-Tech, of 

the melting-cryogen-cooled high-purity germanium borehole gammaray detector. A technique of relating mass fractions to measured 

gamma-ray intensities, which eliminates the need for detailed 

knowledge of the geometry of the neutron distribution, is used to 

calculate elemental compositions without resorting to the test 

pits or computer borehole modeling. In coal, all of the major 

constituents (C, H, N, S, Si, Al, Fe, Ti) except oxygen can be 

determined quantitatively by thermal neutron capture gamma-ray 

spectroscopy. The newest innovation in this field is the replacement of the 252cf neutron source with a neutron generator, a type 

of ion accelerator. These generators, used for many years by the 

petroleum logging industry, produce neutrons having an energy of 

14 MeV. The neutron generator is a safer tool than is californium, 

as no radiation is emitted by the device until it is turned on,c 

after it has been lowered into the borehole. The coupling of a 

neutron generator with a high-resolution detector to form a 

borehole measuring system was pioneered by workers at Sandia 

National Laboratories. USGS has built and put into service a 

neutron generator based on the Sandia design, and has a second 

under construction. This new device enables the experimenter to 

use higher energy (n,n'), (n,p), (n,2n), and (n,a) reactions as 

well as the (n,y) thermal neutron capture reaction. Both the 

(n,n') and the (n,p) reactions on 16o permit quantitative measurement of oxygen in coal, and the inelastic scattering excitation of 

carbon provides increases sensitivity over that of the (n,y) 

reaction. 

241 
THE USE OF THE NATIONAL COAL RESOURCES DATA 

SYSTEM IN COAL QUALITY STUDIES 

by 

E.V. Miller 

Virginia Division of Mineral Resources 

The Virginia Division of Mineral Resources, in cooperation 

with the U.S. Geological Survey and the U.S. Bureau of Mines, has 

collected and analyzed 849 coal samples from 122 coal beds in the 

southwestern Virginia coal fields. The analytical data were 

entered into the National Coal Resources Data System (NCRDS). 

The Dorchester coal bed in Wise County was selected to 

demonstrate the capability of potential users of NCRDS to access 

this data for coal-quality studies. The analytical information 

was entered into the USCHEM and USTRAT data bases. PACER was used 

to extract the data from USCHEM and USTRAT. The data were maripulated with GARNET to produce county maps showing the outcrop cf 

the coal bed and the sample localities. GARNET was also used to 

create isopach maps of the coal bed and of the overburden and to 

produce isoline maps illustrating the distribution of the BTU's 

and a variety of elements, such as sulfur, in the coal bed. 

Coal analyses of the Dorchester coal bed were transferre~ 

from USCHEM to the local Tektronix 4054 terminal, where they were 

manipulated by Micro GRASP to produce ternary plots of ash, 

volatile matter, and fixed carbon. X-y plots were also made to 

characterize the distribution of sulfur and BTU's in the sampl.es 

of Dorchester coal. 

The isopach maps, isoline maps, ternary plots, and x-y plots 

are useful both to industry and in geologic research. Use of the 

NCRDS enables these maps and plots to be produced quickly and 

easily. 

242 
MODERN ANALOGS ILLUSTRATING CONTROLS ON COAL QUALITY 

by 

S.G. Neuzil and C.B. Cecil 

U.S. Geological Survey 

Modern analogs of coal deposits (peat) can provide valuable 

information on the geologic factors that control coal quality. 

Modern peat-forming environments may be categorized into topogenous 

or ombrogenous deposits representing two different chemical/ 

physical depositional systems. Topogenenous peat deposits are 

dominated by mesotrophic to eutrophic ground and surface water; 

thus they are confined to topographic depressions. Thickness of a 

topogenous peat deposit is limited by the water table resulting in 

a relatively flat (planar) upper surface. Floral distribution, 

dependent on water depth, forms random mosaic patterns. Varying 

vegetal-production and peat-accumulation rates cause shifts in 

water depth and floral-distribution patterns both laterally and 

vertically within peat deposits. The quality of planar-peat deposits may be influenced by 1) influx of dissolved load and suspended 

sediments and 2) significant levels of microbial degradation wnich 

can develop in the mildly acid environment. The mineral-matter 

content of the peat tends to be relatively high and variable. 

Ombrogenous peat deposits are dominated by oligotrophic 

precipitation which maintains a raised water table within the 

peat, independent of the local water table, resulting in 

domed-peat deposits that are not necessarily flooded. Peat 

thickness is dependent on the rate of peat accumulation. The 

flora show diminishing stature and even complete changes in flcral 

assemblages in concentric zones from the periphery to the cente:r 

and horizontal stratification from the bottom to the top of a r~at 

dome. Highly acid conditions, net hydrologic flushing, absence of 

dissolved and detrital influx, and limited microbial activity 

generally result in a low mineral matter content in ombrogenous· 

peat. 

Our studies in the Appalachian Basin suggest that the more 

variable and higher mineral matter content in coal beds of the 

upper Middle and Upper Pennsylvanian series is primarily the 

result of topogenous peat deposition. The coal beds of the Lo~er 

and lower Middle Pennsylvanian series are more uniform and lower 

in mineral-matter content because they were derived form 

ombrogenous peat. 

243 
REDUCING AND PREDICTING SULFUR CONTENT OF MISSOURI COAL 

THROUGH BENEFICIATION AND GEOLOGIC MODELING 

by 

L.M. Nuelle and J.L. Bostic 

Missouri Department of Natural Resources 

Division of Geology and Land Survey 

M.H. Erten 

University of Missouri-Rolla Mining Engineering Department 

Economic coal seams of northern and western Missouri are in 

Middle Pennsylvanian rocks of the Western Interior coal basin, and 

are high volatile A to bituminous C. More than half contain 4 -

5 percent S, one-fourth contain 3 - 4 percent S, and most of tl'e 

others contain )5 percent S; only a small fraction contain <3 

percent S. Missouri coal averages 4.27 percent S: 2.52 percent 

pyritic, 0.08 percent sulfate, 1.67 percent organic material. 

Because of increasing concern about S02 emissions in burning 

high-sulfur coals, the Missouri Department of Natural Resources, 

Division of Geology and Land Survey is sponsoring research on 

desulfurization through beneficiation, combustion with lime, and 

geologic modeling. 

Missouri coal desulfurization is being evaluated at the 

University of Missouri-Rolla Mining Engineering Department. 

Research consists of beneficiation and combustion- zone and 

flue-gas desulfurization. Beneficiation (such as heavy-media 

separation, tabling, and floatation) shows that most coals can be 

cleaned to produce acceptable ash content and that considerable 

quantities of nonorganic sulfur can be removed. Combustion-zone 

and flue-gas desulfurization experiments indicate that flue-gas 

desulfurization is more effective when lime and lime~tone are used 

as S02 absorbing agents. 

A southwest Missouri coal-field evaluation shows that 

geologic modeling can help predict sulfur content. The thicker 

portions of Riverton coal were formed in a lake-margin environ~ent. 

Detrital material, transported along drainages, added clay to the 

coal. The clay was probably a source of ferrous iron and it also 

formed a parting which apparently prevented H2S from escaping the 

decaying peat. A combination of these factors would be conducive 

to pyrite formation. The lower coal bench contains twice as much 

sulfur as the upper; they average 8.96 percent S and 3.25 percent 

S, respectively. Field relations indicate that the bog at 

Sylvania was elevated, thereby escaping much detrital influx. A 

southeastward-prograding delta deposited Warner Formation sediments 

in erosional scours. The elevated bog escaped inundation by muddy 

prodelta sediments; instead, it is largely covered by cleaner, 

244 
fluvial sandstones. The latter are more conducive to peat-bog 

oxidation, which is unfavorable for pyrite formation. The coal in 

the elevated Sylvania bog contains the least sulfur, averaging 

1.59 percent S. 

245 
COMPARISONS OF THE CHEMICAL CHARACTERISTICS 

OF GULF COAST LIGNITE SAMPLES 

by 

C.L. Oman·and C.R. Meissner, Jr. 

U.S. Geological Survey 

Proximate and ultimate analyses, calorific values, forms of 

sulfur, and concentrations of 10 minor and 29 trace elements, l'ave 

been determined for 116 lignite samples from the lignite beds of 

the Gulf Coast. The lignite beds sampled range in age from 

Paleocene to Upper Eocene, are from the Wilcox Group in Texas, 

Arkansas, Mississippi, and Alabama; the Claiborne Group in 

Arkansas, Mississippi, and Tennessee; the Jackson Group in 

Arkansas; and the Midway Group in Alabama. 

On a whole-coal basis, elements such as Ga (5-13ppm}, Hg 

(.08-.4ppm}, Mo (1.3-2.6ppm}, Sc (2.9-6.8ppm}, U (1.5-2.8ppm}, V 

(22-48ppm}, andY (8-18ppm} exhibit very little variation among 

samples over the entire area. In contrast, Co (3-19ppm}, Cr 

(13-73ppm}, La (9-52ppm), Mn (39-330ppm}, Se (1.6-8ppm}, Zn 

(5-30ppm}, and Zr (24-290ppm} show the greatest regional variation 

among samples. 

The lignite samples contain 4 to 5 times the concentrations 

of B, and 5 to 7 times the concentrations of Mn and Nb, found in 

Appalachian bituminous coal samples, whereas the levels of other 

elements are comparable to bituminous coal. 

Geometric means for lignite ash (525°C} range from 12.5 

percent in the Calvert Bluff Formation of the Wilcox Group in 

Texas to 38.2 percent in the Claiborne Group in Tennessee. Th~ 

geometric mean of the ash for all lignite samples is 20.3 percent 

compared to 10.0 percent for the Appalachian bituminous coal 

samples. 

Geometric means for major ,and minor oxides in the lignite ash 

indicate that Si02 is highest in the lignite beds from the 

northern part of the Gulf Coast embayment. 

Comparing arithmetic means of proximate with ultimate 

analyses reveals that moisture, oxygen, and sulfur are highest in 

the eastern part of the Gulf Coast embayment and volatile matt~r, 

fixed carbon, carbon and calc~ific value are highest in the 

western part. 

246 
THE ASSESSMENT OF MODES OF OCCURRENCE OF TRACE 

ELEMENTS IN COAL MINERALS USING SIZE AND 

DENSITY SEPARATION PROCEDURES 

by 

C.A. Palmer 

U.S. Geological Survey 

The growing concern over the environmental hazards associated 

with coal utilization has produced a need for a detailed understanding of the occurrence and distribution of trace elements in 

coal. Previous attempts to determine the distribution of trace 

elements among coal components have yielded only a partial 

understanding of this problem. Many elements are difficult to 

detect because they exist in minor or trace quantities in minerals 

or are found in minerals that are extremely fine grained, Becau~e 

of this, it is often difficult to determine the relative 

concentrations in various components. 

A procedure has been developed to determine the associatioD 

of major and trace elements in the minerals found in coal. 

Low-temperature-ashed bituminous coal is separated into six sizE 

fractions ranging from (0.08 um to )20 um. The four fractions 

)0.2 um are further subdivided into heavy (specific gravity )2.~6) 

and light (specific gravity (2.96) fractions. These fractions and 

the unseparated low-temperature ash are analyzed by X-ray diffraction analysis to determine major mineral concentrations. The 

concentration of trace elements are determined in each of these 

fractions and the whole coal by instrumental neutron-activation 

analysis. Mass balance calculations are made to account for the 

distribution of 28 elements among the various size and density 

fraction of the low-temperature ash. Elemental concentrations of 

the various fractions are compared with the mineral concentrations 

in the fractions determined by X-ray diffraction analysis. 

This approach provided both quantitative and qualitative 

information of the modes of occurrence of the trace elements in 

coal, the size distributions of the minerals, and concentrations 

of the major minerals in the coal. In addition, the presence of 

trace minerals and their effect on the trace-element content of a 

coal are considered. 

247 
A GEOSTATISTICAL APPROACH TO ASSESSING COAL-QUALITY DATA 

by 

F.W. Pierce, W.D. Grundy, and G.T. Spanski 

U.S. Geological Survey 

A demonstration of kriging as an estimation technique has 

been done with a database for a coal bed in the San Juan Basin, 

New Mexico. The study was made of an area that includes both 

densely spaced and sparsely distributed data and excludes suspect 

data near outcrops and channels. 

Contour maps of thickness, feet-percent sulfur, and feetpercent ash were prepared from grid values estimated by point 

kriging. Variance maps, showing relative measures of the accnracy 

of the contour maps, were constructed from variance values 

calculated along with the estimates. Coal quantity and quality 

were estimated by block kriging for a square-mile block withir the 

study area. 

Properties that are often estimated for coal are thicknePs, 

elevation, and sulfur, ash, moisture, or Btu values. These, like 

most other geologic variables are spatially autocorrelated, wl'ich 

means values close together are more similar than values at pcints 

farther apart. The semi-variogram, the basic tool of geostati.stics, is used to model the physical and statistical structure of a 

spatially correlated variable. The kriging algorithms calculcte a 

set of weights to be assigned to data points used in estimating 

blocks or grid nodes. Values for the nugget, range, and sillr 

which quantify the relation between distance between sample values 

and the variation of the geologic variable, are computed from the 

theoretical semi-variogram and are used in the calculation of the 

estimation variance. The advantage of kriging is that it yields 

unbiased estimates that have minimum error variances; also the 

estimation variances provide a measure of the reliability of the 

estimates. 

248 
CATHODOLUMINESCENT PROPERTIES OF QUARTZ IN COAL: 

A METHOD FOR DETERMINING VARIATION IN COAL QUALITY 

by 

L.F. Ruppert, C.B. Cecil, and R.W. Stanton 

U.S. Geological Survey 

Cathodoluminescent (CL) properties of quartz grains in the 

Upper Freeport coal bed were measured to determine their origin. 

CL (the emission of visible light during electron bombardment) is 

useful in genetic studies of minerals; quartz, in particular, tas 

definitive luminescent characteristics that are apparently relzted 

to the temperature of crystallization. Analyses of quartz grains 

taken from representative samples of the Upper Freeport coal be1 

show that 77 percent of the quartz are nonluminescent and therefore 

are inferred to be authigenic in origin. In contrast, the remaining 23 percent are luminescent and are inferred to be detrital in 

origin. These CL data are in agreement with other data from lowtemperature ash, maceral, and major, minor, and trace-element 

analyses that suggest a plant-derived origin for most mineral 

matter, exclusive of calcite and pyrite, in the Upper Freeport 

coal bed. 

The luminescent properties of quartz in a coal bed can gi~re 

information that may be directly related to the variation in coal 

quality. Plant-derived mineral matter predominates in interior 

portions of the paleoswamp of the Upper Freeport coal bed where 

sediment influx was limited. The percentage of luminescent or 

detrital quartz is expected to increase because of the increased 

sediment supply along the margins of the paleoswamp and 

approaching contemporaneous stream channels that cut through the 

peat body. 

249 
MAGNETIC PROPERTIES OF COAL 

by 

F.E. Senftle, A.N. Thorpe, and C.C. Alexander 

U.S. Geological Survey 

A study has been made of the magnetic susceptibility of coal 

and coal constituents. As the ferromagnetic component of the bulk 

magnetic susceptibility of coal is small, the measured susceptibility is made up of diamagnetic and paramagnetic components. The 

diamagnetism resides in the organic part of the coal whereas t1'e 

paramagnetism originated (1) in the mineral inclusions and (2) in 

the unpaired electron spins in the organic structure. The 

fundamental information acquired in this study has been used to 

investigate several practical problems. 

Coal Grinding. It has been found that when coal is ground in 

a steel grinder, the pulverized coal is contaminated with abraFion 

particles from the grinder. Because coal is a soft material, 

these particles are extremely small (< 30 um) and we have showr 

them to be superparamagnetic. In pulverized coal, these particles 

tend to agglomerate and the clusters so formed take on 

ferromagnetic properties. 

The concepts learned in this study can be directly applied to 

coal cleaning. One of the methods of industrial coal cleaning is 

density separation using a slurry of finely powdered magnetite as 

the heavy liquid. There are two problems with this method: (1) 

there is a significant loss of magnetite, which is expensive, and 

(2) the magnetite trapped in the coal adds to the ash. The larger 

magnetite particles can be recovered magnetically because magnetite 

is ferromagnetic. However, the very fine particles lose their 

ferromagnetism and become superparamagnetic. Proper processing of 

the magnetite to eliminate the supermagnetism can reduce the 

losses substantially. 

Magnetic Separation of Pyrite. Pyrite is a very weakly 

magnetic mineral, and cannot be practically separated using 

conventional low-field magnetic separation. By heating coal in a 

vacuum or an inert atmosphere to about 3SOOC the pyrite can be 

converted to pyrrhotite, a slightly magnetic mineral. By using a 

relatively expensive high-gradient magnetic-separation (HGMS) 

method, the pyrrhotite content, and hence the sulfur concentration, can be reduced. The USGS is currently experimenting with an 

alternative method. The coal is heated to about 400°C in an inert 

gas containing a carefully measured trace of oxygen. Under these 

conditions, the pyrite grains are coated with a thin layer of 

magnetite, a strongly magnetic mineral. By this technique, 60-80 

250 
percent of the pyrite can be removed using ordinary low-field 

magnetic separators. 

By standardizing the heating and anoxic gas flow, the change 

in magnetization can be used to measure the pyrite concentratio~ 

in the coal. 

The chemical reactions and mechanism of formation of magnetite 

from pyrite under these conditions is not yet completely clear. 

Further work is being done to more fully understand the reactions 

and reaction rates. 

251 
HIGH-TECHNOLOGY FUEL 

by 

F.E. Senftle, D.B. Wright and P.I. Hackney 

U.S. Geological Survey 

High-technology fuel has been defined as coal or other 

organic solid fuel from which the inorganic ash-producing phases 

have been nearly completely removed. Because much of the mineral 

inclusion in coal is extremely finely divided and disseminated 

throughout the coal material, the production of high-technology 

fuel generally involves complete solution of coal, removal of the 

insoluble mineral matter, and reconstitution of the organic matter. 

The organic source materials should be low-grade or high-ash coals 

that are unsuitable for fuel application, and are relatively 

inexpensive to obtain. An alternative to natural organic sources 

might be the ever-increasing amount of human and industrial waste, 

such as sewage sludge. 

Coal as a Source Material. Coal is insoluble in aqueous 

solutions primarily because of its aromatic nature. If the 

aromatic rings are opened, a large fraction of the coal becomes 

soluble. Certain elements, because of their electronegative 

properties, are strongly electrophilic and can open aromatic rings. 

Experiments with the electronegative elements tellurium and gold 

have opened the aromatic rings and caused the coal to go into 

solution. Once in solution, the insoluble fraction ~ontaining 

many of the ash-forming components is removed by filtration. Tl'~ 

organic fraction in solution is reconstituted into a solid by 

polymerization. NMR measurements indicate that the polymer is 

highly condensed and in this respect resembles anthracite. The 

chemical reactions leading to the polymers are very complex and 

further work needs to be done before a full-scale application can 

be proposed. Laboratory experiments utilizing benzene as a simple 

starting material are currently being performed in an effort to 

understand the process. 

Sewage Sludge as a Source Material. Sewage sludge is becomfng 

a valuable national resource. Approximately 40 percent of most 

sludge is organic material. Concentrated sulfuric acid attacks 

the aliphatic compounds in the organic fraction of the sludge ard 

renders them soluble in acid. The insoluble matter containing the 

aromatic compounds is treated similarly to the coal discussed 

above, so that it becomes soluble in acid. After filtration, tl'~ 

solutions containing the converted aliphatic and aromatic compo~nds 

are polymerized using separate techniques to reconstitute the 

organic materials into a solid coal-like material. The heat 

content of this material is variable; however, a product with a 

252 
heating value as high as 6000 BTU/lb (1.396 x 104 kJ/kg) has b~en 

obtained. 

This work is still in a development stage, but the results 

look very promising for using coal and sewage sludge as fuels and 

hydrocarbon sources for the chemical industry. 

253 
COMPUTER MAPPING OF QUALITY DATA FOR COALS 

IN WEST VIRGINIA--AN AID IN MATCHING A SPECIFIC 

COAL GRADE TO A SPECIFIC END USE 

by 

C.J. Smith and H.M. King 

West Virginia Geological and Economic Survey 

In 1907, the first studies of the State's coal reserves ~~re 

initiated as part of the West Virginia Geological and Economic 

Survey's Statewide geological mapping program. Since then, 

extensive work has been conducted to map and characterize the 

State's 62 minable seams. This effort has shown that the coals 

have a wide diversity of quality, and this diversity provides the 

coal-user with a choice of grades to meet specifications for 

varied applications. Approximately 6,000 coal samples have been 

analyzed, and a computer data base of coal-quality information is 

now maintained and continues to grow. An extensive coal-quality 

mapping project makes this information convenient to use. 

The objective of coal-quality mapping is to produce a series 

of contour maps showing the variations in coal quality for the 

most important seams. Parameters being mapped include sulfur, 

ash, Btu, fuel ratio, Hardgrove grindability, volatile matter, 

fixed carbon, and kilocalories per kilogram. This type of information is extremely valuable for someone interested in buying, 

selling, evaluating, or developing West Virginia coal. 

The maps are computer-generated at a scale of 1:500,000 and 

show the trends of coal-quality parameters for individual seams. 

The maps are supplemented by a computer program which searches the 

database and generates a printout of geographical areas within the 

State where coal has been sampled that meets the desired specifications. These computer techniques go a long way in helping the 

user find target areas within the State to match the right coal to 

the desired end use. 

254 
PHYSICAL AND CHEMICAL VARIABLES RELATED TO COAL 

WASHABILITY: UPPER FREEPORT COAL BED FACIES 

by 

R.W. Stanton and C.B. Cecil 

U.S. Geological Survey 

Francis Martino 

Pennsylvania Electric Company 

J.D. Kilgroe 

U.S. Environmental Protection Agency 

Stratigraphic analyses of a coal bed (chemical, physical and 

descriptive analyses by facies) show that variability in quality 

and washability characteristics is related to variation in coalbed facies. The washability characteristics of a coal bed can be 

inferred from the stratigraphic analysis of the bed. In addition, 

certain petrographic, physical, and chemical values of coal-bed 

facies can be related to washability characteristics such as w0ight 

percent recovery and pounds of sulfur/million Btu's recovery at a 

particular specific gravity of separation. 

The most significant variables measured on the head (unpr~­

cessed) sample that can be used to estimate the weight percent of 

coal recovered from size-gravity separation of coal include sample 

density, inertodetrinite content, certain trace-element contents 

such as lanthanum, niobium, cesium, and selenium, and illite 

content. The best estimates for sulfur recovery for Upper 

Freeport coal-bed samples can be calculated from petrographic 

characterization of pyrite form and association, weight percent 

pyrite, and density. 

Sulfur variability, within a profile of the Upper Freeport 

coal bed, is commonly greatest in the uppermost facies and res'tlts 

from differences in the forms of pyrite. Specifically, pyrite 

that replaced organic matter is more highly variable than other 

forms. This variability is probably the result of the origin of 

the pyrite, which may be related to the lithology of the roof 

rock, in particular sandstone. This variability of minerals other 

than pyrite and calcite is related primarily to detrital surges 

which are superimposed on predominant amounts of authigenic 

minerals that originated from plant degradation. 

255 
QUALITY AND EXTENT OF FACIES WITHIN THE UPPER 

FREEPORT COAL BED: WEST-CENTRAL PENNSYLVANIA 

by 

R.W. Stanton, B.S. Pierce, and C.B. Cecil 

U.S. Geological Survey 

Francis Martino 

Pennsylvania Electric Company 

Coal-bed facies within the Upper Freeport coal bed were 

identified and correlated using core and mine face descriptions. 

In addition, relative coal quality was determined by comparing 

x-ray radiographs and in-mine visual descriptions. The facies are 

relatively uniform in thickness and less variable in quality than 

the whole bed because the whole bed is not composed of the sam~ 

number of facies throughout the deposit. Mapping of facies can be 

used in conjunction with chemical and petrographic data to areally 

delimit the shape and quality variability of the bed and to infer 

geologic factors that control coal-bed quality. Recognition of 10 

or more Upper Freeport coal bed facies is based on visual descriptions of the bed underground and descriptions obtained from x-ray 

radiographs of core. These facies are interpreted to have res·,tlted 

from three different stages of peat formation: (1) topogenous, 

low-lying, widespread peat formation, which included depositio~ of 

detrital sediments and formation of attritial-rich banded coal-bed 

facies; (2) sediment-starved peat formation which resulted in 

vitrain-rich banded coal-bed facies; and (3) peat-island formation 

which resulted in facies of cannel/splint and banded coal. 

Isopleth maps indicate trends in concentrations of ash and sulfur 

data in the first stage (lowest coal-bed facies) which contrast 

with the more random distribution of ash and roof-related variability of sulfur in the second stage (the middle coal-bed facies). 

Additional points of control are required to construct isopleths 

of ash and sulfur data of stage three. 

Correlation of coal-bed facies provides coal-quality data 

which is more reliable in the assessment of quality than comparison 

of whole-bed analyses and should become useful in mine planning. 

In addition, the stratigraphic data (facies characteristics, 

quality, and extent) of a bed can aid in mining and preparatio, 

evaluation and can be used to interpret the conditions of paleopeat formation and the shape and composition of the paleo-peat 

body. 

256 
CHEMICAL AND PETROLOGIC CHARACTERISTICS OF 

DEEP-SUBSURFACE WILCOX LIGNITES (EOCENE) FROM 

EAST AND EAST-CENTRAL TEXAS 

by 

S.J. Tewalt and C.M. Jones 

Bureau of Economic Geology 

The University of Texas at Austin 

Seven cores from the deep-subsurface Wilcox Group in East and 

east-central Texas provided samples from 18 lignite seams representing five stratigraphic intervals. The seams occur at major 

facies transitions at depths ranging from 240 to 1,040 ft (70 to 

315m). Complete chemical and petrographic analyses of the 

lignites provide new data for comparison with near-surface seams. 

On a moisture-free basis, the deep East Texas seams are low 

in ash and high in calorific value (11.4 percent and 11,300 

Btu/lb, respectively) compared to near-surface seams (23 percent 

ash and 9,550 Btu/lb). In east-central Texas, deep seams average 

18.7 percent ash and 10,185 Btu/lb on a moisture-free basis, 

whereas near-surface seams average 21 percent ash and 9,722 Btu/lb. 

Most of the deep-basin samples from both areas are borderline 

subbituminous, estimating rank from dry, ash-free carbon values. 

The average Na20 content of ash from the deep East Texas 

seams is more than 6 percent; in east-central Texas it is only 

1.3 percent. Na20 content is highest in the deepest seams in both 

areas and is related to sodium content in the ground water. In 

both areas, deep-basin lignite ash contains greater percentages of 

S03 and Na20 than near-surface lignites 

Whole-coal trace-element concentrations are widely variable .• 

Average uranium content falls below, and selenium and arsenic 

concentrations equal or exceed, average values for these elements 

in other U.S. lignites. 

Petrologic examination of the deep-basin seams reveal limited 

well-preserved plant material. Many huminities have undergone 

partial or complete gelification. Liptinite content is high an~ 

can exceed 30 percent; higher liptinite correlates with lower 

inertinite. Comparison between petrographic and chemical data 

shows that seams with larger percentages of liptinite have high~r 

hydrogen contents and calorific values. 

Current characterization work is focused on near-surface 

Jackson Group (Eocene) lignites to complement the existing data on 

Wilcox coals. 

257 
COAL RESERVE CHARACTERIZATION FOR EMISSION CONTROL 

by 

J.H. Tice, S.L. Latimer, and Francis Martino 

Pennsylvania Electric Company 

R.W. Stanton 

U.S. Geological Survey 

The objective of the Coal Reserve Characterization (CRC) 

Study is to develop models to optimize mine planning and operation, coal preparation and utilization while complying with 

performance standards for specific flue gas emissions. The CRC 

Study is being conducted at Homer City Generating Station, located 

in Indiana County, Pennsylvania, and owned by Pennsylvania 

Electric Company and New York State Electric and Gas Corporation. 

The presentation shows the interrelationship of techniques 

for coal-reserve characterization, mine planning, coal preparation 

and ultimately prediction and control of as-burned coal quality 

without Homer City owners sacrificing either economic or environmental concerns. 

The result is a series of computerized geologic and engineering models that will enable the user to model a reserve, predict 

in-seam and ROM quality, project the effect of feed blending to a 

coal-cleaning plant, and the subsequent emission level from 

clean-coal utilization. 

258 
SULFUR CONTENT OF COAL IN THE APPALACHIAN 

AND ILLINOIS BASINS 

by 

V.A. Trent and C.L. Oman 

U.S. Geological Survey 

The U.S. Geological Survey has submitted samples of coal from 

beds in 11 States for chemical analysis to the Coal Analysis 

Section, Department of Energy (formerly of the U.S. Bureau of 

Mines). The amounts of the total sulfur, organic sulfur, and 

pyritic sulfur are shown on a series of panels. The first panel 

shows the location and number of coal samples by State and County. 

The coal analyses are presented on a second panel as arithmetic 

mean values for ash, Btu-content, total sulfur, and for the three 

forms of sulfur, by State. Additional panels show computergenerated trend maps of the distribution of the total sulfur, 

pyritic and organic sulfur. 

The amount of sulfur that potentially can be recovered from 

coal is estimated using the published State coal-resource data and 

the mean sulfur concentrations. The area that has the greatest 

potential for recovery of sulfur is Ohio. The total sulfur co~tent 

is 3.51 percent, the highest of the 11 States sampled; most of 

that is pyritic sulfur, 2.09 percent, which is easier to remove 

from the coal because organic sulfur is locked in coal consti t·tents (molecular). The second- and third-ranked potential sulfurfrom-coal resource areas are western Kentucky and Alabama where 

the coals contain 1.75 and 1.74 percent pyritic sulfur, respectively. 

259 
THE PREMIUM COAL SAMPLE PROGRAM 

by 

K.S. Vorres 

Argonne National Laboratory 

R.L. Marianelli 

U.S. Department of Energy 

The Premium Coal Sample Program at Argonne National 

Laboratory will provide the coal-science research community with 

long-term supplies of a small number of premium coal samples that 

can be used as standards of comparison. These samples will be 

as chemically and physically identical as possible, have wellcharacterized chemical and physical properties, and will be stable 

over long periods of time. Coals will be selected, collected, 

transported, and processed into the desired particle and sample 

sizes, and sealed in environments as free of oxygen as possible. 

The samples will be checked for homogeneity, characterized in ~1 

extensive interlaboratory program, and then periodically monitored 

for stability. Samples will be distributed to researchers after 

the samples are characterized. 

260 
STABLE-ISOTOPE AND INCLUSION-FLUID COMPOSITION SHADES OF 

EPIGENETIC PYRITE AND SPHALERITE FROM ILLINOIS BASIN COALS 

by 

J.F. Whelan and G.P. Landis 

U.S. Geological Survey 

J. C. Cobb 

Kentucky Geological Survey 

Kaolinite-pyrite-sphalerite-calcite mineralization occurs in 

cleats and clay dikes of mid-Pennsylvanian coals in Illinois. crD 

and alSo values of inclusion fluids in this pyrite range from -137 

to -61 and -12.3 to -5.2, respectively. These compositions are nand 18o-depleted with respect to any depositional or diagenetic 

fluid previously known to have existed in these rocks. If, as we 

believe, these fluids reflect coal-pore water at the time of 

pyrite formation, then such waters must have exchanged with or 

been generated from organic compounds in the coal. Gases in 

pyrite-hosted inclusions contain C02, CO, or N2, Ar, H2S, S02, 

abundant hydrocarbons (CH4, C2H2, C2H6, C3Hs, C4H1o, and so on), 

and exhibit alkene:alkane ratios )1. The predominance of alkenes 

probably reflects the differing solubilities of saturated and 

unsaturated hydrocarbons in aqueous fluids. 

a34s values of pyrite concretions, nodules, bedding-plane 

concentrations, and cleat fillings from Nos. 2, S, and 6 coals in 

Illinois range from -12.4 to -0.1; within individual mines the 

range is much smaller, often <4. Pyrite a34s values do not 

reflect the different pyrite morphologies. Bacterial sulfate 

reduction is the widely accepted source of pyritic A in high-S 

coals. However, the comparatively small range of o34s values 

observed contrasts with the large ranges characteristic of 

bacterial activity. High-S peat and lignite may contain 10 

percent or more total S, of which 1-2 percent is pyrite. High-S 

coals of Illinois also may contain 10 percent or more total S, but 

with more than half contained in pyrite. We propose that this 

increase in the proportion of pyritic S in sub-bituminous-(and 

higher ?) rank coal reflects the formation of coarse pyrite in 

epigenetic settings (cleat, and so on), from S released during the 

post-lignite-rank breakdown of S-hearing organic compounds. Tl'e 

isotopic and gas compositions of the fluids, and sulfide o34s 

values, suggest that coal-pore fluid chemistry was controlled, at 

times, by coal devolatilization. 

Sphalerite in the coals was deposited at 90-100°C from brines 

chemically similar to those that formed the Upper Mississippi 

Valley Zn-Pb district. However, crD and o18o data from the 

sphalerite inclusion fluids trend toward the isotopic composition 

261 
of pyrite inclusion fluids, which suggests mixing between the 

coal-pore water and the Zn-transporting brines. o34g values of 

sphalerite are close to those of associated pyrite. This suggests 

that sphalerite also precipitated from S derived from organics, or 

that sphalerite inherited S by replacing pyrite. Gases trapped in 

sphalerite-hosted fluid inclusions are less hydrocarbon enriched 

than those of pyrite-hosted inclusions. 

262 
COMPARATIVE GEOCHEMISTRY OF TWO COAL BEDS FROM 

CONTRASTING DEPOSITIONAL ENVIRONMENTS OF LATE CRETACEOUS 

AGE IN THE WESTERN PART OF THE WIND RIVER BASIN, WYOMING 

by 

John Windolph, Jr., R.C. Warlow, N.L. Hickling, 

and L.J. Bragg 

U.S. Geological Survey 

Coal-bearing rocks in the Wind River Basin record a transition 

from marine deltaic (paralic) to non-marine intermontane (limnic) 

depositional environments. The coal-bed geochemistry indicated 

changes in source and nature of sedimentation during this evolutionary period. Samples from two thick coal beds, the Signor in the 

Mesaverde Formation and the Welton in the Meeteetse Formation, 

exhibit significant differences in the quality of coal from 

contrasting environments. 

Preceding and during deposition of the Mesaverde Formatio~., 

peat accumulation coincided with extensive marine regressive 

cycles. These peat deposits accumulated in coastal swamps that 

overlay former seaward-prograding linear-shoreline and lobatedeltaic sand bodies. The Signor coal bed, which formed in this 

environment, was influenced by post-depositional marine and 

brackish-water incursions. Proximity to the sea is indicated by 

the high content of sulfur, boron, phosphorous, and other 

marine-related elements. 

Extensive air fall of volcanic ash accompanied sedimentation 

throughout Late Cretaceous time and was a significant component of 

the Meeteetse Formation. During deposition of the Meeteetse 

Formation, emergence to the north and subsidence to the east, 

coupled with tectonically active source areas to the west 

transformed this area into an intermontane basin. The Welton coal 

bed formed in this setting and was subject to the influx of 

volcaniclastic terrigenous sediment. Silicon, rare earth, and 

chalcophile-related elements are concentrated in the ash residue 

of the Welton coal bed and are indicative of the restrictive 

terrestrial conditions. Subsequent episodes of intensified 

tectonic deformation in the area of the Wind River Basin gradt·ally 

shifted the depocenter eastward into the Power River Basin where 

enormous deposits of peat accumulated. The geochemical signatures 

of coal beds in this region corroborate this change in patterns of 

deposition that began to the west in the Green River Basin during 

evolution of the Frontier Formation and ended to the east wit\', 

basin filling during the Eocene Period. 

263 

PART IV: SUPPLEMENTARY PAPERS 

SOME THOUGHTS ON FUTURE NEEDS FOR THE 

CHARACTERIZATION OF COAL RESOURCES 

by 

Alan Davis 

The Pennsylvania State University 

Changes in the manner in which and extent to which our coal 

resources are characterized must conform to the constraints which 

will be imposed upon the coal-mining and utilizing industries 

within the next decades. Failure to do so will result in industry 

being unprepared to provide the assurances that mine safety and 

health and environmental standards would be met. Major 

constraints will be limits on emission of sulfur oxides and 

possibly of toxic volatile elements from coal-burning plants, the 

risk of curtailment or abandonment of operations which endanger 

the health or safety of personnel, and the threat of closure of 

mining operations which detrimentally affect the quality of 

surface or ground waters. 

Some of the special requirements and opportunities will b~ 

considered in this talk, from energy policy formulation through 

resource assessment and mining to major end uses. 

Energy Policy 

The time may come when indigenous oil and gas resources, 

because of their limited availability, will be earmarked for 

certain priority uses such as transportation, fertilizers and 

other chemicals. Coal and nuclear energy might have to satisfy 

the lion's share of utility and industrial demand. Coal, however, 

is likely to have to meet exacting specifications for a diverse 

market that will be both pollution-shy and able to pick and choose 

from a wealth of potential suppliers, foreign as well as domestic. 

The formulation of a comprehensive energy policy involving 

coal could depend upon the availability of tried and true 

predictive methods which can be used on in situ data to gaze into 

the future of, for example, mine safety, potential for acid 

mine-water production, preparatory-plant behavior, sulfur, and 

trace-element emissions from utilities, the type of slagging, 

267 
operating and fouling potential in utilities, and suitability as a 

blend component in metallurgical coking or as a feedstock for 

conversion.· 

The kinds of national resource data presently reported may be 

insufficient for future policy purposes. Previously, resources 

were characterized by quantity, depth, thickness, sulfur, rank, 

and a few other physical characteristics. However, the current 

National Coal Resource Data System (NCRDS) could be the means of 

storing and providing the variety of other data which may be 

needed, including information on the enclosing strata. So, for 

example, instead of just resource quantities, we could include 

qualifications such as "highly faulted" or "potentially dangero•,\s 

roof conditions" or "coal capable of meeting the specifications 

for utility plants A, B, and so on, if cleaned at specific gravity 

X in prep plants C, D, and so on." Such an approach might render 

the current distinction between resources and reserves redundant. 

Exploration 

Coal is a bulk commodity of relatively low value. So, an 

ability to estimate quantities of a reserve to the nearest several 

hundred tons may not be critically important to the feasibility of 

opening a large mine. One might therefore question whether the 

greater precision of complicated geostatistics is always a 

worthwhile effort. However, geostatistics could be a valuable aid 

in treating those coal qualities which are highly variable, 

especially where these variables are important considerations for 

the end use. Sulfur in eastern coals and sodium in western coals 

are two good examples. 

In evaluating coal, we often have been concerned with the 

accuracy of analyses, but precision often is ignored. What is 

needed is the proper usage of appropriate statistical methods. 

The danger is that our understanding of statistics frequently is 

inadequate. For example, factor analyses have been used to 

produce factors from coal data on the assumption of linear 

interrelationships among properties, although coal is notorious 

for its curvilinear relationships. Also, several geostatistical 

methods require that data points be random, our coal data points 

rarely are. In fact, for practical exploration purposes, it is 

preferable that data points are not random. 

Another aspect of precision relates to our selection of 

samples for large-scale testing. We are all aware of reports of 

testing performed on, for example, "Illinois No. 6," "Wyodak11 coal 

or "Pittsburgh No. 8." One gets the impression that almost any 

old coal would do; such a seam designation pays only token lip 

service to the idea that one coal might behave differently from 

another. Another aspect of the same problem is that coal for 

testing from bore cores has cost as much as $40,000/ton. In all 

268 
these cases it should be essential to know what the samples 

represent. When the testing itself is so expensive and the 

implications of that testing are financially staggering, then the 

effort must be expended to ensure that the sample represents an 

average composition, a best case or worst case, or that it 

provides an indication of the expected range of results. 

A statistical approach might provide some interesting 

alternatives to the present means of classifying reserves into 

measured, indicated and inferred categories based on circular 

areas of influence around data points. For example, probability 

distribution curves plot probability against quantity of reserves. 

They enable categories of reserves to be established; for examrle, 

"proved" (say greater than 95 percent probability), "probable, •r 

and "possible." The shapes of the curves reflect the reliability 

of estimates. 

Special consideration needs to be given to the estimation of 

reserves of anthracite in silt dams and culm banks. Here, the 

variability is different in kind and magnitude from that of in 

situ coals. 

The application of geophysical methods for estimating quality 

data is established, although the use of standards and calibration 

tests apparently is not uniform. Possibly some minimum 

requirement for the number of logging techniques needed to 

establish individual coal parameters might be expected, as migl·t 

the number of calibration holes run and the length of interval~ of 

coal core analyzed in such calibration tests. The effectivene~s 

of these techniques, of geophysical prediction should be detaiJ.ed 

following the actual mining of several prospects. 

Coal Mining 

In situ analysis of coal and geophysical interpretations of 

roof and floor rocks will be used to predict mining conditions and 

mine production not only for current mining methods, but possil,ly 

also for future methods. Models have been developed to predict 

roof and floor problems and for reconnaissance of possible gas and 

rock blowouts ahead of mining. In the future, explorationists may 

have to examine the feasibility of large-scale open-pit mining for 

anthracite, hydraulic mining, and of telechiric mining. In th~ 

last, both automation and remote handling could be used to avoid 

the need for mine ventilation, roof support, accidents and health 

hazards. Input for modeling this type of mining could include not 

only depth, thickness and simple structure, but also seam 

continuity, cleat measurements, strength and friability. Models 

to predict the formation of acid mine waters could include sulfur 

levels and forms in the coals and associated strata, pyrite size 

distributions and estimates of available carbonate to buffer the 

269 
acidity. Many of these parameters might even be interpreted from 

down-hole logging techniques. 

Power Generation 

Better methods of estimating and making uniform the moisture 

contents of as-fired coal are likely to be sought. This 

particular property could be critical in the case of low-rank 

coals. 

Improved methods of predicting slagging and fouling 

properties of coals are being sought. It is revealing that the 

predictions seem to improve as the level of sophistication of the 

analyses goes up. So, although acid/base ratios are essential as 

a first step, a clearer picture can emerge if one also has 

information on the oxidation/reduction state of the iron, on 

whether or not the alkalies are water soluble or ion exchangeable, 

and on the distribution of inorganic matter through the coal 

particles. Possibly, still better interrelationships could be 

obtained if mineralogical analyses were used to relate to fusion 

and slagging behavior. Consequently, for this and many other 

investigations, it would be useful to have improved methods for 

obtaining mineralogical analyses of coals. Can this be done? At 

least more standards for X-ray identification of coal minerals 

should be made available. 

Concern about inefficient combustion resulting in high levels 

of unburnt carbon in the fly ash is one reason why the 

petrographic composition of coals should not be ruled out as a 

useful quality parameter for coal combustion. Although a 

petrographic analysis may not be a required analysis in the same 

way that it is necessary for characterizing metallurgical coal, 

knowing the reflectance, maceral composition and level of 

oxidation have helped to identify the source of problems in 

problem coals. 

Pertinent data for the production of coal/water fuels would 

include those related to the stability of the suspension. These 

could include such properties related to hydrophobicity as maceral 

composition, rank index, mineralogy, mineral levels, and oxidation 

levels. 

Some Other Special Directions for Coal Science 

There appear to be some special needs in the following areas: 

o Investigations of the detailed crystal chemistry of coal 

pyrite and marcasite and of the organic structures in 

which sulfur occurs. 

210 
o Programs to characterize the size distribution of iron 

sulfide forms in in situ coals in order to predict the 

liberation of pyrite in improved cleaning processes. 

o Studies of the provincialism of coal properties. Coals of 

different basins formed from different starting materials 

in different environmental settings, and underwent 

different thermal and burial histories with high and low 

heating rates for long and short times. The differences 

in the relationship between properties, although only 

recognized in recent years, are not necessarily subtle; 

for example, the anomalous porosity, reflectance, and 

coking characteristics of Illinois coals. Provincialism 

is not just a topic for scientific investigation; there 

could be important implications for utilization. 

271 

PROBLEMS WITH ESTIMATING COAL-QUALITY CHARACTERISTICS 

OF TONNAGE RESERVES 

by 

John C. Ferm 

University of Kentucky 

Estimating coal-quality characteristics of tonnage reserves 

is a complex and difficult problem. It is one, however, of 

substantial importance in evaluation of coal lands and establishment of public policy dealing with resource utilization. In order 

to make such estimates, two basic approaches appear necessary. 

The first is establishment of an organized bank of extant data 

that is generally and rapidly accessible. Such an approach should 

lead to evaluation of the existing data base and recommendatioqs 

for upgrading. The second approach amounts to a re-examinatioq of 

concepts and procedures now used in estimation of coal quality and 

essentially is a series of research problems directed to ratio~alization of quality measurements. It is to this second approach 

that this paper is directed. 

Parameter Specification 

The first step, either for organization of extant data or 

re-examination of basic concepts, is definition of parameters that 

make up "coal quality." The difficulty here arises from the fact 

that coal is a commodity and that many of the well-established 

parameters have arisen more or less ad hoc to meet a specific need 

at a specific time. As a result, the number of parameters, for 

instance, ash fusion, grindability, sulfur forms, maceral composition, etc., continues to grow, and can be expected to increase as 

coal utilization becomes more sophisticated due to operational or 

environmental constraints. Although each quality parameter will 

doubtless be needed, the question arises whether coal characterization is not in the same position as the study of minerals prior 

to the discovery of atomic structure. Most geologists have 

memories of qualities of "hardness," specific gravity, color, 

crystal form, and refractive index of mineral species which can 

now be related to the basic properties of atomic structure. 

Mineral identification today proceeds using both basic and 

derivative criteria, but the relationships between them are, for 

the most part, known and understood. The question then is: "l1hat 

273 
are the basic properties of coal that are analogous to atomic 

structure in minerals and which will explain other derivative 

properties?" Resolution of this question should lead to a better 

understanding, if not a simplification, of existing quality 

parameters. 

Sampling Units 

Once specific quality parameters--basic or derived--can be 

decided upon, the next question is definition of the object or 

sampling unit upon which measurements or observations are to be 

made. Measurements such as the height of men, weight of pigs, or 

wheelbase of automobiles are relatively straightforward as the 

sampling unit is obvious. With coal (or wheat or sand), however, 

the problem is more difficult and the definition is more or lePs 

operational. In the case of much "in place" coal, the sampling 

unit is a column of varying width or diameter from the top to the 

bottom of the seam, obtained by coring or direct removal. MeaPurements of properties from columns averaged across the areal extent 

of the seam represent the characteristics of the entire body. 

Samples from belts, cleaning plants, railroad cars and stockpiles 

are defined by a volume increment which presumably represents e 

volume of coal from the "in place" seam. As these systems are 

designed, there should be a predictive link from "in place" to 

delivered product, and past experience shows that this is ofter 

the case. There are examples, however, of rejected carloads or 

barges that indicate that the system does not always work. However, 

it is generally not known whether this failure is one of procedural 

error or a failure of the system to accurately represent the 

quality of the coal body. 

Precision of Estimates 

Once the parameter and sampling units have been defined, 

methods for attaching statements of precision of estimates have 

been well established by both sampling theory and practice. In 

general, the level of precision of the estimate is inverse to the 

variation found among the samples and proportional to the number 

of samples. If variation is great, the level of precision is low; 

if the number is large, precision is increased. If the level of 

precision is stated in advance, then the number of samples 

required to attain this given level of precision is dependent upon 

variation of the parameter found in sampling units; large variation requires a greater number of samples than small variation. 

Practical application of this relationship is found in volume 

increment samples of loose, broken coal on belts and stockpiles 

(ASTM D-2234-82 1984). In such cases, the size of the increment 

is dependent on the size of the coal particles relative to the 

total volume of the sample. If too few particles are included, 

they will bias tl1e results toward their particular qualities. 

Clearly, the sampling system anticipates variation between coal 

274 
particles, and in loose increment type samples efforts are being 

made to include particles that have varying properties in proportion to their occurrence in the sampled material. The point is 

that variation is expected between coal particles, but because 

there is no known physical relationship between pieces on a stockpile or belt, the only alternative is to assure that variation 

among particles is proportionally included in the sample. 

Coal columns from either cores or channels cut into the seam 

can be considered in different ways depending on the treatment of 

the sample. If the entire column is treated as a single sample, 

it does not differ in substance from a belt or stockpile sample in 

that all variation in the seam is aggregated into a single sample 

in proportion to its occurrence in the seam. Such a procedure, 

however, does not identify and locate specific parts of the seam 

that may have desirable or undesirable characteristics which are 

amenable to isolation during preparation. In addition, such 

procedures ignore the advantages of stratified sampling, which 

minimizes sample variance by selection of subsamples which are 

characterized by variance that is smaller than for the entire 

sample. In the case of a coal column, utilization of this methc1 

requires identification of strata suspected of having minimum 

variance before the subsample is taken. 

This form of subsampling is attempted in some cases by 

sampling individual coal benches which upon analysis have shown 

substantial differences. Some recent experiments, however 

(Esterle, 1984; Miller, 1984), have shown that there is almost as 

much variation in ash, sulfur, and maceral content within benches 

as there is between them. This suggests that there is a major 

sampling problem in which it is known that variance can be 

partitioned, but that there is no clear physical procedure for 

identification of relatively homogenous strata in advance of 

subsampling. Moreover, it is not known at what practical level 

subsampling with minimum variance occurs. Some experiments by 

Stanton and others (1983) suggest that radiography may assist in 

identification of subsampling units, and the previously cited 

studies of Esterle and Miller suggest that subsampling based on 

purely megascopic criteria may be useful. But the number of such 

studies is small, and it is obvious that much experimental work 

will be required if efficient descriptive and subsampling 

procedures are to be devised. 

Quality Per Ton 

Definitions and procedures of sampling quality parameters 

represent one set of problems. Projection of quality parameters 

onto estimated tonnages categorized by seam thickness, depth of 

burial, and structural attitude combine problems of quality 

estimates with those of reserve (resource) estimates. Estimates 

of tons are products of area and thickness, and as currently 

275 
practiced, require knowledge of seam continuity and rate of 

thickness variation. As indicated elsewhere, there are no 

standard procedures for expressing a degree of confidence in 

either of these estimates and substantial effort will be required 

to bring these areas under control (Tewalt and others, 1983; Ferm, 

1983). One of the more hopeful aspects of this problem is 

represented in the results of some recent studies by Cecil and 

others (1981), Esterle (1984), and J.R. Staub (personal communication, 1985). These studies suggest that quality parameters of 

ash, sulfur, and maceral content are associated to some degree 

with variation in thickness and partings of some coal seams. 

Should such relationships be firmly established, they could 

greatly simplify estimation of quantity per quality. It is also 

clear that investigations of this type are still small in number, 

the results preliminary, and substantial effort will be necessary 

to bring this information to the application stage. 

Summary 

It is certain that estimates of quality parameters of coal 

reserves will require substantial efforts in standardizing existing testing methods for known quality properties and establish~ent 

of workable and efficient data bases for absorbing extant information about them. It is also obvious that substantial effort will 

be required in the area of research. One of these areas is 

concerned with the establishment of basic coal parameters to w~ich 

other operationally defined properties can be related. Such a 

system would permit not only clear conceptual notion of coal 

quality but would also enhance the large body of extant quality 

data. Another area is the development of a system of description 

of raw, in-place coal that will allow for more efficient sampling 

in advance of analysis. Finally, considerable effort should be 

devoted to establishment of relationships of morphologic properties of minable coal bodies--thickness, area and character of 

adjacent strata--to quality parameters. Controlled experiments 

and hypothesis testing of relationships between coal-body 

morphology and quality properties should ultimately lead to 

rational estimates of quality attributes of coal reserves or 

resources. 

REFERENCES 

Cecil, C. B., Stanton, R. W., and Dulong, F. T., 1981. Geology of 

contaminants in coal: Phase I, Report of investigations: 

U.S. Geological Survey Open-File Report 81-0953-A, 101 p. 

Esterle, J. S., 1984. The Upper Hance coal seam in southeastern 

Kentucky - a model for petrographic and chemical variatior in 

coal seams: Lexington, Kentucky, University of Kentucky, 

unpub. M.S. Thesis, 104 p. 

276 
Ferm, J. C., 1983. [A revision of] "Coal resource classificatio~ 

system of the U.S. Geological Survey," by Gordon H. Wood, 

Jr., and others, 1983, U.S. Geological Survey Circular 891: 

American Association of Petroleum Geologists, v. 67, no. 12, 

p. 2266-2267. 

Miller, T. R., 1984. The chemical variation in the Upper Hance 

coal seam, southeastern Kentucky: Lexington, Kentucky, 

unpub. M.S. thesis, 130 p. 

Stanton, R. W., Moore, T. A., Rupert, L. F., and Cecil, C. B., 

1983. X-ray radiographic description of coal core as an aid 

for estimating coal quality: Geological Society of America, 

Abstracts with Programs, v. 15, no. 6, p. 695. 

Tewalt, S. J., and others, 1983. Estimation of uncertainty in 

coal resources: EA-3133 Research Project 1267-1, Final 

Report prepared by the University of Texas at Austin, Bure~u 

of Economic Geology for Texas Energy and Natural Resources 

Advisory Council; prepared for EPRI, Palo Alto, California, 

137 p. 

277 

EFFECTS OF COAL QUALITY ON PRODUCTION COST--

A UTILITY'S PERSPECTIVE 

by 

Rick A. Mancini 

New York State Electric and Gas Corporation 

The philosophy or procedure a utility uses in the procurement 

of fuel is influenced by many factors. To understand these, you 

must understand the utility itself and its environment. 

The New York State Electric and Gas Corporation (NYSEG) is an 

investor-owned utility located in central New York State. Our 

service area covers 34 percent of the State. NYSEG operates si:r:. 

steam-generating plants in New York State and co-owns with the 

Pennsylvania Electric Corporation (PENELEC), Homer City Station, 

which PENELEC operates. Our total capacity is 2,400 megawatts, 98 

percent of which is coal fired. If we exclude Homer City Station, 

NYSEG's coal burn is 3.2 million tons/year. It is important to 

note that although 98 percent of NYSEG's generation is coal fir~d, 

56 percent of the installed generating capacity in New York State 

is oil fired. Our generating station production cost is the 

lowest in the State with any surplus generation marketable to our 

neighboring utilities. 

Because of NYSEG's location in the State, our generating 

stations are very close to the outer edges of the northern 

Pennsylvania coal fields. This coal, however, tends to be of 

lower quality and can cause an assortment of operating problems at 

the generating stations. This situation has posed an interesting 

problem to our management through the years. Do you purchase this 

lower quality fuel at a favorable purchase price, or do you go 

deeper into Pennsylvania or West Virginia for the higher quality, 

generally higher cost coals? Items which influence this decision 

are the F.O.B. mine costs, freight rates, generating-station 

design, handling and maintenance costs, ash-disposal costs, 

environmental limitations and replacement power costs. 

To understand the total cost of operation of a generating 

unit based on the cost and quality of a fuel, NYSEG developed a 

computer model of each unit to simulate the burning of coal in the 

unit and to predict its production cost. Figure 1 illustrates the 

parameters modeled in the program and the influence each has on 

the resulting electric production cost. The boxes highlighted on 

279 
~ 

w 

40 

COAL QuALITY ·vs-PRODUCTION COST 

ELECTRIC 

'---~~------~--------~--------~----~~--~--~,p:rf~J~~ 

S/MWH 

Figure 1. Coal quality versus production cost. 

~ 30-+--+--

<( 

I 

0 

t- 20 

(f) 

0 

0 

6 10 ---

t0 

=> 0 

0 

-o 

0:: 

0... 

~10~~----------+---------~--------~-----

10,000 11,000 1 2,000 13,000 

BTU/LB 

Figure 2. Coal quality versus production cost. 

280 
this figure are the coal-quality parameters used by our models. 

These models also predict deratings which will be illustrated in 

figure 3. 

Figure 2 presents an example of how the production cost on a 

unit might vary with the fuel quality. The top curve illustrates 

the change in production cost as the quality varies for coal 

purchased on a dollar-per-ton base. The lower curve uses the same 

fuel quality information, but is determined by pricing the fuel on 

a cents-per-MBTU base. It is assumed in this example that coal 

represented by the various qualities will not cause any generating 

deficiencies. 

I'd like now to give some examples of how the model could be 

used. 

Figure 3 illustrates the effect that coal from three different vendors has on the operation of a unit. The information 

presented in this example actually occurred in the NYSEG system. 

The lower histogram illustrates the effect that the coal from 

three different vendors has on the ability of a unit to meet full 

capacity. The two plots shown for each vendor represent the 

average quality and the quality at one standard deviation based on 

the variability of the coal received. In this example, the average 

quality of the coal received from Vendor 1 would burn with no 

deficiencies in generation whereas the swings in quality on the 

low side could derate the unit 25 percent. Vendor 2's coal causes 

derates in both the average and low quality, whereas vendor 3 

causes no derates in either case. Derates or generating deficiencies in this model would result from the inability of the 

pulverizers to handle enough material for steam generation or from 

exceeding the opacity limits through precipitator limitations. 

The upper histogram illustrates the relative production cost 

associated with these coals. It is interesting to note that the 

component is virtually the same for the three products; yet, the 

total cost to the corporation differs significantly. These 

examples were specifically taken to illustrate the variation that 

could exist for the same coal cost. 

This may cause one to conclude that only fuels of high 

quality should be bought that do not cause any generating deficiencies. This is true up to a point. Figure 4 illustrates an 

evaluation made by NYSEG for a long-term coal contract. All of 

the coals supplied by these vendors would allow the unit to 

achieve full generating capability; yet, each affords a different 

production cost. Would it be prudent for a utility to purchase 

from Vendor C when supplies from Vendor G or Vendor A are readily 

available? 

281 
c:::J-PRODUCTION COMPONENT 

~-REPLACEMENT POWER COMPONENT 

0.0 ......... --'---'-----l~---L--.L...--.L.---""-----'----J...-

> 100 .... 

u 

<( 

Q. 

<( 

(.) 

LL.. 50 

0 

rz 

I.J.J 

(.) 

0: 

(.!) 3; 

> 0 

<( ...I 

(.!) 3: 

> 0 

<( ...I 

~ o.....L..~--._~-----~-~~----~-.1..--~-

1-

(f) 

0 

0 

z 

0 

1-

0 

~ 

0 

0 

0:: 

a.. 

VENDOR "I" VENDOR ''2'' 

AVG- AVERAGE QUAL! TY FUEL 

LOW- ONE STANDARD DEVIATION 

REDUCTION IN FUEL QUALITY 

Figure 3. Production cost versus coal quality. 

r VENDOR"c' 

. rVENDOR "D" 

~VENDOR"E" rVENDOR"F'' 

• VENDOR's' 

[i VENDOR"s'' ! WASHED 

RUN OF MINE . · rVENDOR ''A" ,, , <!5 WASHED 

[

VENDOR G \\ II 

0VENDOR A ci RUN OF MINE 

12poo 

HEATING VALUE 

13,000 

BTU/LB 

Figure 4. Production cost versus heating value. 

282 
Other observations that can be made from this figure are: 

1. Vendor A Run of Mine and Vendor G have similar productfon 

costs, yet their quality varies significantly. What risks are 

associated with purchasing Vendor G over Vendor A or the reverse? 

2. Also, notice the difference between Vendor A Run of Mire 

versus Vendor A washed. This suggests there is no incentive to 

purchase the washed product over the Run of Mine. 

3. However, for Vendor B, the production cost for the Run of 

Mine is slightly more expensive than the washed product. Obviovsly, 

the washed product in this case would be a better buy. 

My intent is to present a concept. Some of the informatior 

presented in these examples would not result in the same conclu~ 

sions if applied to other utilities. Also, our model does not 

include all of the parameters or variables that could or should 

be looked at in understanding the effect of coal quality on 

production cost. Our model provides insight to support our fuel 

procurement policies and long-term strategies. I believe this is 

only the "tip of the iceberg" on what challenges we may face in 

the cost of service. This is one utility's perspective. 

283 

COAL RESERVE CHARACTERIZATION 

FOR EMISSION CONTROL 

by 

Francis Martino and Susan L. Latimer 

Pennsylvania Electric Co. 

The state-of-the-art in Coal Reserve Characterization (CRC) 

methods has undergone a major change as a result of a combination 

of factors including, but not limited to, the ever-changing energy 

requirements and science. Therefore, any comprehensive coalreserve characterization study should incorporate the technology 

advancements currently available in the areas of exploration, 

mining engineering, processing, and combustion. The mineability 

and utilization of a coal reserve is to be assessed to determine 

if it will be environmentally and commercially economic over its 

productive life. This is because major planning and economic 

decisions are made based on the results of a coal-reserve study 

with the following considerations in mind: 

o Most of the coal used by utilities is purchased under 

long-term contracts. 

o Utilities require decision-making in all aspects from 

power-plant design to coal-procurement strategies. 

o A coal reserve's quality and usability must be determined 

within environmental constraints. 

o The uncertainty of whether a mine's coal product is of 

sufficient quantity and quality for the life of a contra~t 

must be reduced. 

o New advances in coal combustion and coal-cleaning 

technology require a higher level of accuracy. 

Inadequate or improper reserve data assessment may have a 

disastrous impact on a utility's coal procurement and utilizatior 

program. In many instances, utilities, although making huge 

financial commitments, have relied on mining consultants and 

mining companies for assurances of coal-reserve assessment withot·t 

particular regard to the methods used to project or predict the 

information. If the expected conditions do not materialize, the 

285 
coal company will appeal to the utility for relief and the utility 

will be faced with a number of difficult alternatives, such as: 

(1) providing additional financial compensation, (2) taking over 

the mine and seeking another operator, or (3) acquiring alternative sources of supply. In any of these circumstances, the 

utility may still have a problem with quality and/or high-cost 

coal, and may be forced to acquire new reserves in an unfavorable 

economic atmosphere. Thus the coal reserve must be used in the 

most effective and efficient manner. Because today's coal-mine 

development costs often exceed $100 million and power generation 

$1 billion, it is only logical that technology advancements to 

identify the degree of confidence (risk) associated with a coalreserve's utilization should be sought. 

I will now explain some aspects of Pennsylvania Electric 

Company's (PENELEC) and New York State Electric and Gas 

Corporation's (NYSEG), coal reserve characterization (CRC) use~ at 

the Homer City Generating complex. 

PENELEC is one of three operating companies of the General 

Public Utilities Corporation (GPU). About 85 percent of the 

electricity PENELEC produces comes from coal-fired power plants 

which burn approximately 17-20 percent of all the coal produced in 

the State of Pennsylvania. The primary reason for this is that 

PENELEC sits right in the heart of the eastern coal field. Coal 

is our primary fuel source, but does not always provide satisfactory results because the quality varies; the quantity fluctuates; 

or cost varies despite carefully planned mines and crafted 

contracts. 

Because of these factors, the primary question raised when 

the management looks at a coal reserve is, "can we utilize it to 

our advantage?" If we develop better qualifying capabilities t:o 

evaluate a coal reserve, the true utilization potential can be 

quantified and the optimum utilization of coal will be realized. 

For example, a Pennsylvania utility spent approximately 

$4.5 million to improve precipitator efficiency. The upgraded 

facilities worked with some coals and not with others, primarj.ly 

because of an inability to obtain the precise quality of coal 

necessary to meet, both particulate and sulfur dioxide standards 

at the same time. This utility diligently sought bids from 

approximately 60 coal producers and accepted seven who promised 

to deliver coal within the necessary, stringent sulfur range. The 

suppliers didn't live up to their promises, because they didn't 

have the knowledge (or perhaps the desire) to develop their mines 

in a way which would produce a uniform product, and the utility 

did not have the tools to determine the fact in advance. 

All of the points I have made are known to coal producers and 

utilities. However, most are slow to make use of them. Because 

286 
of the fragmentation of the industries and the relatively modest 

size of many operations, few are actively seeking a better way. 

Although we may do a bit more than go out with a divining rod, 

many of us have not adopted data-collecting technology and computer analysis which the miners of other minerals are using 

successfully. 

The CRC is a method to delineate the particular qualities, 

features, and peculiarities of a given coal reserve. We envision 

it as a tool to meet present and future requirements for supplying 

a uniform quality fuel to coal burning and cleaning facilities 

within the best environmental and economical manner possible. 

The CRC program should include: 

o Information analysis utilizing computers and other 

advanced technology, equipment, and procedures. 

o Mathematical modeling to interpret information gained. 

o Scientific projections to guide and improve mine 

development procedures. 

Underground coal-mine planning traditionally focused on the 

mine design aspects concerning safety and efficiency in the quest 

to produce low-cost coal. Very little attention has been given to 

predetermination of coal qualities and surrounding geologic 

characteristics. Yet, voids, sandstone washout, unstable roofs, 

high-water seepage, and quality transitions are conditions found 

underground, usually unexpectedly, and then overcome only by br,te 

force at substantial cost. In the past, it was not uncommon for 

an operator to abandon a work place when any of these things 

occurred, because it was relatively easy to start another heading 

or even start mining some distance away, ignoring the resource 

potential or the bottom-line cost. Now, with practically all of 

the easily accessible reserves mined out or being mined, and with 

development costs of deeper mines soaring, it is an economic 

requirement that once mining is underway, it should continue along 

the original plan. 

Some predetermination of coal qualities and surrounding 

geologic characteristics could have easily reduced the impact of 

those ills just mentioned. For example, it has been discovered 

that a strong relationship exists between underground fractures 

and surface water courses. Knowledge of the exact location of 

probable faults prior to deciding upon the final layout of a mine 

offers an opportunity to reduce development and operating costs 

with improved coal-quality control. 

Advance knowledge will also help work around the problems 

caused by the undulating nature of a coal seam whose high point 

287 
is referred to as the anticline and low point as the syncline. 

A work area at the syncline sustains pressure from both sides and 

top resulting in the need for stronger roof supports and larger 

pillars to lessen the vertical pressure, and escapes the high 

horizontal tectonic forces which makes mining along the syncline 

more difficult and expensive. Of course, to maximize the coal 

recovery, it is necessary to work the syncline areas; but the 

problems and cost can be mitigated by orienting the main heading 

in a different direction with prudent mine planning to help offset 

poor roof and bottom conditions. 

Another important reason to predetermine coal qualities and 

geologic characteristics of any given coal reserve is the proliferating number of environmental regulations. 

To comply with State and Federal clean-air regulations, the 

quality of coal must be carefully controlled within narrow limits. 

At each coal burning station, stack emissions generally fluct·tate 

in tandem with coal quality. Emission violations can be caused by 

mechanical malfunctions, but a constant fluctuation in coal 

quality also makes it very difficult for the operator to keep his 

stacks clean. It is a known fact that coal delivered to a geTterating station can vary as much as +100 percent in sulfur 

content and +70 percent in ash content. This occurs in spite 

of the best efforts of the coal buyers and the coal producers to 

obtain a consistent supply of contract compliance coal. 

The reason coal varies so much in chemical characteristics is 

that it is a heterogeneous material whose composition varies 

substantially along the vertical and horizontal planes of any 

specific coal seam. This variation is graphically depicted in 

figure 1. Figure 2 shows sulfur content ranging from 2 to 

6 percent in a particular coal seam. 

If we are to control the coal quality, we must be able to 

first predict with a certain degree of accuracy and confidence. 

This is where geostatistics can be applied to predict the shortterm coal qualities. 

The first historical (as well as present-day) step in 

answering the question as to whether a prospective reserve is 

acceptable and should be mined is the collection of data from the 

geophysical and chemical characteristics of the reserve body. 

Traditionally, the core drilling is done at random locations, 

analyzed, and isopleths drawn. A CRC program identified more 

scientifically the selection of drill sites and the use of 75 

percent air drilling with 25 percent coring of the coal along 

with electric logging to more economically explore the coal ffeld. 

A reduction in the number of drill holes, while increasing 

the confidence of the findings, is made possible by the use of 

288 
N 

00 

1.0 

V( AY Ollll AND HARD 

COAl·I'ANOEO FAACIUA(S E:ASilY·ClEAT PYAIT[ 

CANNEl 

MEDIUM GRAY PAAflfiC. 

IUHTTL£ BUI0£0 COAL-EASilY FRACTURED 

f'YRI TE l[NS£5 AT TOP AND BAS£ AND IN 

ClEAT 

HARD ljAG( BLOCKY BAN0£0 COAl 

Figure 1. 

4 ,. 11 sut run I ASH 

~~1·'7~~(1- ~ -- -~-~-~ ,~-~- ---- -"'-,-_:--- -~-: .· ..... :;j.) ~~:! I I I 4 ·' 'r.••l I 7. 6 

- ..-- -- -- -- -·- -· --{ ~::i) 41 . s - •· ft:S.-: ___ ,_• - - -- -- .. -- ~ ----- ~: .:1 ll. 1 

c-=.-__ - __ [_;bmr) ,,_, 

l 0 

-- --- - -~ 

l ' 

Illustration of typical coal qualities. 

10.4 

17.0 

A5tl SULfUR 

67.1 -,-o7. I 4. '' 

Jl. f I '0 

14 ' I 7' 

"'·2 1.60 

SULfUR 

l 7 

4. 9S 

1.10 

Z .IS 

] 05 

I '' 

l&S 

on 
' 

-......._-- / 

I 

Figure 2. sulfur variation in a coal seam as snown by total 

percent sulfur contours· 

290 
geostatistics. This technique mathematically optimizes the 

information, location, and number of cores necessary to define the 

geology, ash, sulfur, BTU's, and thickness of a coal reserve with 

the least possible variance and costs. Now, by formula, it is 

possible to calculate the probable error of the predicted value of 

any geologic feature and from this probable error, it is possible 

to calculate the probability that the predicted value will fall 

within a certain range of the mean value. 

In a process called Kriging, a series of maps defining tbe 

average thickness, ash, sulfur, BTU, or other characteristic along 

with their associated error limits can be constructed in blocks of 

any dimension desired. A section of a mine is shown in figure 3 

consisting of nine of the 1,000-foot-square blocks used in a 

Kriging exercise. The upper number in each block is the avera~e 

value of total sulfur, in percent, in that block; the lower number 

is the associated probable error. 

In contrast, the traditional method of translating core cata 

to isopleths produces varying results. For example, figure 4 

shows two sets of sulfur isopleths of a mine. Both the solid and 

the dashed lines were drawn by highly respected consulting fir~s 

and followed accepted procedures in arriving at contradictory 

predictions. 

Geostatistics was applied to sulfur, ash, and thickness 

values of drill holes in the Upper Freeport ("E") seam. The 

deposit was then Kriged on 1,000 by 1,000 foot panels and ther 18 

new holes were drilled to validate the predictions. More thar 

one-half of the Kriged values predicted were within 2 percent of 

the actual values. Six predictions came within 11 percent of the 

actual values and two were within 14 percent. These are consldered 

very good results in the mining industry. They are clearly b~tter 

than other estimates. 

A short-term quality prediction model was developed to b~tter 

predict in-situ coal qualities from the immediate working areas in 

the mine. This model is designed to utilize both existing diamonddrill holes and other sampling information during its quality 

prediction. The geostatistical technique of linear Kriging iv 

used to make the best estimate of the characteristics of futur·e 

production areas. 

From an optimal mine-planning and emission-control standpoint, 

accurate characterization (or prediction) of in-site coal qualities 

is a must simply because this prediction is the basic input to all 

subsequent processes. This fact can be further emphasized by 

figure 5, which shows schematically an overall emission-control 

strategy available to a typical utility company. 

291 
N 

\0 

N 

19 

.3 

22 

.3 

2.6 

A 

2.9 

.3 

2.5 

.3 

2.9 

.a 

Figure 3. Expanded view of a coal property showing results of a 

Kriging exercise for total sulfur in one coal bed. 

~l~~k~ ~~2 l,OOO-f22t square; upper numbers ln each 

block are percent total sulfur; lower numbers are 

probable errors. 

2.3 

.3 

2.6 

.3 

32 

4 
Figure 4. Map showing two contrasting interpretations (solid v~. 

dashed isopleths) of sulfur distribution in a coal b€i 

as produced by traditional methods by different 

interpreters. Isopleths are percent total sulfur. 

2~ 
Process #1 

lnsltu 

Coal 

Process Process 

#3 #4 

Cleaning 

Plant 

Run of 

Mine 

Power 

Plant 

Process 

#2 

Figure 5. Schematic of an overall emission-control strategy. 

294 
Each process shown does provide the possibility of emission 

control. For example, different working areas can be schedulecl so 

as to minimize the sulfur variability of run-of-mine (ROM) coal 

qualities in Process No. 1. In Process No. 2, the use of Bradford 

breaker and air table eliminate coal partings and out-of-seam 

dilution material. Another possible control is the temporary 

stockpiling of high-sulfur coal for future blending with lowsulfur coal. 

Coal cleaning as depicted by Process No. 3 (fig. 5) is 

perhaps the most readily available emission-control strategy for 

the coal-fired utility companies, whereas Process No. 4 can be the 

installation of sulfur removal devices or external purchasing of 

low-sulfur coal for further blending. 

All this information can be displayed either in map form or 

in contour plots. Figure 6 shows a contour map of the Kriged 

sulfur, ash or any quality values for a coal reserve. In the same 

figure, the projected working areas are also laid out so that the 

computer programs can be run interactively to obtain the desired 

scheduling of mining faces during any given planning period. 

The prediction results of the 6 months in-situ coal qualities 

of those areas that were actually worked from January through June 

1982 are given in Table 1. Using the Kriging variance information 

given in Table 1, the 95 percent error found can be computed for 

each prediction in order to assess the relative reliability of the 

prediction. 

In Table 2, the 6 months prediction results of the run-of-mine 

sulfur quality were compared with the actual "as-received" figures. 

Unfortunately, it was learned through the current research effort 

that little information is available for performing either an 

out-of-seam dilution computation or a material balance across our 

Bradford breakers. Therefore, a new research program was started 

to better quantify the available information. 

Again, experience indicates that we all will benefit 

financially, environmentally, and operationally from having a 

better coal-reserve characterization program by developing: 

o A methodology on which to base decisions for coal 

purchases. 

o Assurance that suppliers will be able to live up to 

contract terms. 

o Ability to predict, with a high degree of confidence, the 

quality and quantity of coal in a specific mine so as to 

properly design boilers, cleaning facilities, and 

emission-control devices. 

295 
Figure 6. Map showing Kriged iso-sulfur values (total sulfur in 

percent) and projected coal-mine face advances. 

296 
Table 1. Predicted values for the quality of the coal mined from 

the areas shown in figure 6 during a 6-month period. 

Thiclmess Variance Ash Variance Sulfur Variance 

Month inch inch2 % (%)2 % (%)2 

January - 82 51.84 1.29 18.22 0.461 2.54 0.033 

February - 82 51.80 1.37 18.19 0.445 2.54 0.033 

March- 82 51.66 1.72 17.88 0.657 2.43 0.044 

April- 82 51.67 0.91 17.25 0.281 2.51 0.025 

May- 82 51.66 1.01 17.80 0.246 2.50 0.020 

June- 82 51.37 1.46 17.71 0.422 2.38 0.033 

Table 2. Actual average sulfur values for the coal mined during a 

6-month period from the mine in figure 6 compared with 

the predicted values given in table 1. 

Sulfur 

Actual Deviation 

Predicted Reported From 

Month (lnsitu) (As-Received) ".ctual 

% Ofo % 

January - 82 2.54 2.74 -7.30 

February - 82 2.54 2.67 -4.87 

March- 82 2.50 2.62 -4.58 

April- 82 2.51 2.86 -12.24 

May- 82 2.50 2.81 -11.03 

June- 82 2.38 2.63 -9.51 

297 

~ 
o Confidence in a degree acceptable to regulatory 

authorities and stockholders that its coal-purchasing 

program is cost effective, efficient, and productive. 

o Knowledge of the mineability of a coal seam. 

To summarize, I have shown that there are many variables to 

be considered in deciding where and how to mine coal and explained 

why it is time to get away from the prevalent exploratory type of 

mining and develop a scientific procedure. 

I offer the CRC program as a design tool which will save 

money and provide confidence that the coal will be mined in a safe 

and commercial manner. But, most importantly, the flames in the 

boilers will continue producing electricity in a reliable, costeffective manner from existing and future generating stations 

while complying with performance standards for specific flue gas 

emissions only if research is continued in the areas of: 

o Determining the correlation of drill cores and channel 

samples to estimate coal-cleaning plant yield and permit 

optimum plant design through the use of quality control in 

prudent mine planning. 

o Determining the fine-coal-cleaning (-100 mesh) potential 

of coals that can be accomplished using dense medium 

cyclones. 

o Determining the fine coal-cleaning (less than -100 mesh) 

potential of coals utilizing various flotation devices. 
COMMENTS ON CHARACTERIZATION OF THE 

QUALITY OF COAL RESOURCES AND RESERVES 

by 

David Mathew 

Utah International 

I start with a question--what is the one major issue affecting 

the coal industry in the United States today? From the standpoint 

of business planning and decision making, the answer is the everchanging regulation picture. I would like to see this meeting 

develop an agenda for priorities in basic applied research on the 

quality of coal resources and reserves that will aid in developing 

regulations to ensure that we take advantage of the Nation's vast 

coal resources in a cost-effective and environmentally acceptable 

way. 

For those of you not involved on a day-to-day basis with 

mining and selling coal, let me offer some insights into the 

effects that changing regulations have on our business. I will 

limit the discussion to those regulations directly linked to coal 

quality, that is emissions regulations. 

The Clean Air Act of 1970, the New Source Performance 

Standards (NSPS) set by the Environmental Protection Agency (FPA) 

for coal-fired utilities, required all plants constructed after 

1971 to meet an emissions limit of 1.2 pounds of S02 per milljon 

BTU's. The rule allowed plants to choose between technologiccl 

emissions controls (such as scrubbers) and fuel controls (sucl' as 

burning low-sulfur coal. The rule caused considerable turmoil in 

our business. Many utilities chose low-sulfur coal over scrulbers 

partly because they regarded scrubbers as an unproven technology; 

also, few wanted to bother with operating them. However, the 

primary reason for coal switching was that the utilities' 

commission resisted price increases to cover pollution controJ,s, 

whereas fuel adjustment clauses made it a simple matter to pa~s 

along the increased cost of lower sulfur coal without the approval 

of the utilities' commission. 

The most significant impact of the act was the shift in 

regional production. Over the period 1971-1983, coal producerl in 

the low-sulfur fields of the western United States moved into the 

eastern U.S. marketplace. Western production increased 40 percent 

during this period, whereas eastern U.S. production only incrP.ased 

299 
5 percent. A similar and perhaps more revealing trend can be 

observed in the State of Kentucky which has a region of highsulfur coal reserves (western Kentucky) and a region of mediumto-low-sulfur coal reserves (eastern Kentucky). Over the same 

period, western Kentucky production decreased 25 percent and 

eastern Kentucky increased 30 percent. 

The fear that utilities would cease buying locally available 

coal had its effect on Congress. In 1977, Congress passed the 

Clean Air Act Amendments under the guise of preventing the 

degradation of existing air quality. EPA required sulfur 

reduction for all coals high or low in sulfur. Under the rule, 

all plants built after 1978 would have to have a scrubber or 

equivalent technology. Not surprisingly, low-sulfur producers 

thought that they had been legislated out of the market. In fact, 

the amendments, driven by economics and politics, did for the 

first time recognize the legitimacy of protecting the Nation's 

coal resources. This, I believe, should be the cornerstone of 

this meeting: the protection and judicious use of the Nation's 

coal resources. A policy that allows or favors fuel switching 

could have important consequences for the conservation and 

judicious use of the country's coal resources. The encouragemP.nt 

of the use of the highest quality coal first (in this case lowsulfur coal) is very short-sighted given the finite nature of the 

resource. 

The pendulum of changing regulations is by no means 

stationary; the trend seems to be towards tightening air-emissions 

standards. In fact, several current environmental issues are 

being considered, including acid rain, fugitive dust from coal 

mining, tall stack regulations, revision to the NSPS for coal-fired 

power plants, and maybe, later, the greenhouse effect. 

Briefly, pending acid-rain legislation would require 

midwestern States to reduce emissions by as much as 80 percent. 

Two approaches are being considered. One, the no-cost-sharing 

flexible approach, would establish each State's emissions 

reduction, direct the States to devise methods of achieving the 

reduction, and offer no financial assistance for achieving the 

reductions. The second type, the cost-sharing, forced-technology 

approach, would require that some of the reduction be achieved by 

retrofitting certain plants with scrubbers and would establish a 

trust fund for distributing the costs. Each approach would reFult 

in a shift in regional production and employment. The forcedtechnology approach would be somewhat more costly in dollars, l'•tt 

would involve less disruption. However, as long as there are 

market advantages to be gained under the guise of environmental 

legislation, industry believes that the acid-rain debate will 1?. 

long. In the meantime, the country's coal resources are being 

"highgraded." 

300 
Turning now to the quality of coal resources and reserves, 

what is the status of existing information on coal quality and of 

the methodologies for predicting the quality of coal in place, and 

where should research monies be spent? To answer the question, 

let us isolate the steps from exploration to utilization (fig. 1). 

Step 1 

The distribution of coal resources displays a distinctive 

difference between regions. Take, for example, the eastern anrl 

western United States. Eastern U.S. reserves are defined as 

medium-to-high sulfur and western U.S. reserves are low in sulfur. 

Quantification of this distribution, especially at the State 

level, has not been completed. Currently, only a few States are 

working on this task. We need to devise a method of defining the 

coal quality of a region's coal resource. The precision of the 

distribution should be sufficient for policy issues only. 

Step 2 

The characterization of coal quality of a reserve at the 

property scale is normally the responsibility of the mining 

company and is directed at mine planning and marketing. Monies 

spent at this step will have limited impact on government regulations because data are often held confidentially by industry. 

Experience has proven that given the density shown on the map, 

tonnage calculations don't change very much with additional 

drilling. However, it is our experience that coal-quality definition often changes with additional drilling. What might have been 

sufficient drilling to market a coal may not be sufficient to sell 

it on a day-to-day basis. This is a long-standing problem in the 

coal business, but especially now with tighter specifications of 

utility contracts. 

Step 3 

Coal washing can remove modest amounts (15-30 percent) of 

sulfur at reasonable costs ($5 to $10 per ton of coal), but co8ts 

increase dramatically as more sulfur removal is sought. Washing 

is currently limited to the removal of coarse forms of mineral 

matter and inorganic sulfur. Most of the research on washing is 

being conducted on the engineering technology front. We need to 

ascertain what parameters of coal quality are important in this 

new research and make sure they are presented at the regional 

level. 

Step 4 

Coal slurry fuels could be a near-term solution to making 

coal competitive with oil and would allow coal to be burned in 

facilities currently designed for oil. As in step 3, most of the 

301 
STEP 1 

r·J 

--.. ,J-• .--. •• .-.J r------------

STEP3 

WASH PLANT 

\ 

STEP 4 

TRANSPORTATION 

\ 

UTILITY 

STEP 5 

,.... 

/ 

_ilr_==-----==-== 

POWER GRID 

Figure 1. Five steps from exploration to utilization of coal 

where coal-quality research is needed. 

302 
research is on the engineering front. Again, coal-quality 

parameters of importance to the new research should be ascertained 

and documented at the regional level. 

Step 5 

The issue with the greatest potential to affect the coal 

industry is related to coal utilization. Regulations controlling 

the utility industry will dictate how we mine and process coal in 

the future. Utilities are searching for the most economically 

efficient way to produce power. Research is underway to develop 

fluidized bed combustion, flue gas desulfurization, coal water 

slurry fuels and synthetic fuels. 

As already pointed out, information on coal quality by region 

will be essential for rational legislation to take advantage of 

the Nation's vast coal resources. This workshop should devise a 

plan of attack to document the distribution of the quality of coal 

resources by region. 

300 

PREPARED STATEMENT 

by 

H. L. Retcofsky 

U.S. Department of Energy 

PANEL I - CHARACTERIZATION OF THE QUALITY OF 

COAL RESOURCES AND RESERVES 

As Director of the Pittsburgh Energy Technology Center's 

(PETC) Division of Coal Science, I have two major responsibilities 

relevant to the characterization of coal that pertain to the 

subject matter of this meeting. The first responsibility is for 

the routine characterization of coal using standard methods of 

analyses as described by the American Society for Testing and 

Materials (ASTM). In this capacity, PETC laboratories determine 

whether or not selected coal purchases by government agencies meet 

contractual specifications regarding the quality of the coal. The 

second responsibility is to perform coal-characterization research 

designed to elucidate the basic chemistry and physics of coal 

conversion processes and coal-utilization technologies. This 

second responsibility frequently involves the use of highly 

sophisticated and often very expensive scientific instruments 

including, but not limited to, magnetic-resonance spectrometers, 

X-ray diffractometers, surface-sensitive instruments, and optical 

spectrophotometers. In the remarks that follow, my distinct 

preference for the use of standardized methods for characteri~ation of coal quality for the purposes of this discussion will 

become apparent. I wish to assure the audience and the readers of 

these proceedings that my recommendations are based on some 27 

years of experience in coal research in which both standardiz~d 

and nonroutine methods for coal characterization have been us~d 

extensively. 

In addition to the issue of the use of standardized versus 

nonstandardized methods of coal analyses, I also wish to call 

attention to the need for a better defined statement of the 

purposes for which measurements of quality are required and to 

remind the audience that the site chosen for the measurements may 

also influence the results. I would also point out that prob~bly 

no absolute answers to the various issues before this panel exist, 

and, perhaps more important, that the novice coal researcher (and 

305 
even the experienced one) will face a number of perils and 

pitfalls should he fail to appreciate this fact. 

One of the objectives stated in the announcement of this 

meeting is "to identify research and information needs about coal 

quality for application to resource assessment, coal mining and 

preparation, coal utilization, and pollution control technologies." 

Missing from this list are several coal technologies that not very 

long ago were considered as emerging technologies; coal liquefaction and coal gasification are two examples that immediately 

come to mind. It should be noted that a high-quality coal for one 

technology may not be a high-quality coal for another. For 

example, low-sulfur coals are considered high-quality coals for 

combustion. Nevertheless, sulfur in the form of pyrite appears to 

promote the conversion of coal to liquid products (fig. 1). The 

question for consideration is, then, to what extent and for what 

purposes should existing coal reserves be characterized? What is 

needed is a series of tests that will provide good general information at a reasonable cost. Coal samples earmarked for a specific 

technology cou1d then to subjected to more specific characterization techniques consistent with the end use of the coal. 

Although certain characterization needs, for instance, sulfur 

and nitrogen contents, mineral matter or ash "content," may be 

common to each of the applications cited above, others may be of 

importance to only one or two. It would appear that basic characterization needs, especially for coal resource assessment, include 

ultimate and proximate analyses, calorific values, Hardgrove 

grindability index, ash-fusion temperature, and sulfur forms. 

More sophisticated needs, such as trace-element determinations, 

although of great significance for environmental concerns, may 

prove too expensive to be performed on every sample that will 

eventually be included in a data base. Furthermore, data of this 

type simply will not be available for samples from depleted mines, 

whereas ultimate and proximate analyses will very likely be 

available. The obvious questions are whether or not data on 

mined-out portions of a seam are important and whether or not old 

data are still useful. The answer from the coal geology community 

is a resounding yes to each! Certainly, data from mined-out areaF 

have considerable value in projecting continuity of a seam over 

lateral distances. 

Another issue for consideration is the use of standardized 

methods of analyses. Debate on this issue is usually heated, witl' 

the "standard methods" community defending its approach on groundssuch as the test of time, that is, that the use of standard 

methods has provided analytical data to assess the quality of coal 

reserves since (or before) the turn of the century. The believer 

in modern, mainly instrumental techniques responds with equal 

vigor, claiming superiority in chemical speciation, laboratory 

306 
80 

..,_ • c 

Q) 

0 

'- • Q) 

Q. 

.. 0 60 

...J 

LaJ 

-

>-

z 

0 

-

1-

(..) 40 ~ LaJ • Low-pyrite coal 

::::> • Coal with added pyrite 0 

-...J 

200 I 2 3 

LIQUEFACTION CYCLES 

Figure 1. The effect of pyrite on liquefaction. 

307 
efficiency, and so on. Clearly, neither side has all the answ~rs, 

and the merits of each must be considered. 

The current and future usefulness of existing data bases is 

an important factor in this debate. As mentioned above, most of 

the early data bases relied on the use of standardized methods of 

analyses to ensure the quality of the data. Although standardized 

methods are sometimes criticized with respect to precision, 

accuracy, sensitivity, efficiency, and speciation, the methods 

have nevertheless survived the test of time and have stood up 

under litigation. Additionally, thousands of tons of coal are 

bought and sold each day based on contractual agreements in which 

the quality of the coal is identified by results obtained by 

standard methods. This is not to underestimate the power of 

modern instrumental techniques. Indeed, the use of such 

techniques in coal-structure investigations is an area of intense 

coal activity and is well under way in several laboratories. 

Measurements of such parameters as the carbon aromaticity (solfdstate nuclear magnetic resonance), the number and nature of fr~o. 

radicals (electron spin resonance), and the quantity of hydroxyl 

groups (chemical derivation and infrared spectroscopy) can now be 

made, and techniques to determine other coal parameters at the 

molecular level are on the horizon. Whether or not any coal data 

base can afford such analyses is sure to be a limiting factor. 

Research into correlations between coal behavior and molecular 

parameters is worthy of continued support and may very well 

influence the choice of analytical measurements. Once that choice 

is made, it becomes prudent to standardize the methods to ensure 

the integrity of the resulting data. Once an analytical method is 

standardized, it is critical that standardized procedures be 

followed without deviation. 

Naturally, new adventures into coal technologies will place 

new demands on the analyst. These demands must not be ignored. 

For example, new and much more sensitive techniques will be 

required to determine low levels of sulfur and ash (and perhaps 

mineral matter) in "ultraclean" coal, and enhanced efforts to 

characterize coal surfaces, especially with respect to oxidation, 

are desirable. 

The lack of certified standard coal samples is a problem of 

some significance. Several coal-sample banks capable of providing 

so-called pristine samples for coal research are now or soon will 

be in existence. Nevertheless, only a few government-certified 

coal standards (for instance, Hardgrove grindability standards ~nd 

sulfur standards) are now available. The need for such standarcls 

is underscored by the current entry of commercial laboratories 

into this market. The issuance of standard samples is traditionally the role of government, and existing government agenci~s 

should be designated to fulfill that role in coal research. 

308 
Where should a measurement on coal be made? Ordinarily, 

samples are characterized in laboratories that are remote to tl'~ 

mine or to the reserves. Recent interest in portable analyzerF 

and in-seam analyzers deserve some comment. The question as to 

where the measurements should be made--in the seam? in the mine? 

in the laboratory? at the site of use?--must be considered. 

Sometimes, however, such discussions ignore more fundamental 

issues of coal stability. Although most coal scientists will 

readily concur that the sample analyzed at the site of use is not 

likely to be identical to that same sample as it existed in the 

mine, few realize the rapidity with which coal samples undergo 

change. Rapid oxidation that occurs within the first several 

minutes of exposure of coal to air even at ambient conditions was 

vividly demonstrated by Japanese scientists in the late 1960's. 

The experiment involved the measurement of spin centers (presu~­

ably organic free radicals) in coal by electron spin resonance 

spectrometry. Briefly, the samples of coal 

"were taken from coal seams deep from the working faces 

without exposure to air. The coals were immediately 

covered with deoxygenated water at the working places of 

the coal face before being taken to the laboratory. The 

coals were powdered in a glove-box filled with nitrogen 

gas in the laboratory, and the powdered coals were 

placed in the ESR (electron spin resonance) sample 

tubes ... " 

The increase in the number of spin centers after exposure of the 

samples to air, that is, after breaking the tips of the evacuated 

ESR tubes, is shown in figure 2. Note that changes occur witl'in 

the first few minutes of exposure to air, and that the rate of 

change is dependent on rank. Please be aware that the actual 

phenomenon itself may be of little importance from a practical 

point of view; I know of no influence of the number of existing 

spin centers in coal on its behavior during utilization or 

conversion. The point I make is simply that a measurement made 

under ordinary laboratory conditions may not yield the same 

results as a measurement made in the mine or in the seam. 

The purpose of these remarks is to bring the following issues 

and recommendations to the attention of the panelists and 

audience: 

o When assessing the quality of a coal, the ultimate use(s) 

of that coal should, if possible, be specified. Coals 

earmarked for specific technologies will most likely 

require specialized characterization in addition to the 

more generalized characterization that will probably be 

performed on all coals for entry into data banks. 

309 
I 

0 

... en 

LLI 

a:: 

.... 

z 

LLI 

0 

z 

Q. 

en 

LL. 

0 

z 

0 

-.... 

<t 60 a:: 

.... 

z 

LLI 40 

0 

z 

0 

0 20 

0 2 4 6 8 10 12 14 

AERIAL OXIDATION TIME, h 

Figure 2. The relation between the concentration of spin centers 

and aerial oxidation time for virgin coals (reprinted 

from Ohuci. et al., Fuel, 48, 189 (1969)). 

310' 
o Potential, as well as current uses of coal should be 

considered in coal-quality assessment. 

o Standard methods should be utilized wherever possible tc 

ensure the quality of data, and such methods should be 

followed without deviation to allow proper comparison of 

the data. 

o Research into the use of modern instrumental techniques to 

assess coal quality should be continued with emphasis on 

precision, accuracy, and standardization of procedures. 

o The need for certified coal standards should be addressed, 

preferably with the aid of appropriate government 

agencies. 

o The coal community should be made aware of rapid changes 

in coal characteristics that may occur immediately after 

removal of the coal from the seam. 

311 

PART V. PARTICIPANTS 

OVERVIEW SPEAKERS 

Richard L. Gordon (Keynote Speaker) 

Professor of Mineral Economics 

The Pennsylvania State University 

Donald c. Haney 

Director and State Geologist 

Kentucky Geological Survey 

Richard E. Harrington 

Deputy Assistant Secretary, 

Coal Utilization 

u.s. Department of Energy 

Michael P. Heap 

Vice President 

Energy and Environmental 

Research Corp. 

Terry w. Offield 

Chief, Office of Energy and Marine Geology 

u.s. Geological Survey 

James Pinta, Jr. 

Research Geologist 

Chevron Oil Field Research Co. 

Jeremy Platt 

Project Manager, Energy Resources Program 

Electric Power Research Institute 

Paul Schwengels 

Program Analyst 

Office of Air and Radiation 

Environmental Protection Agency 

315 
Panel I - Characterization of the Quality of 

Coal Resources and Reserves 

Harold J. Gluskoter, Co-Leader 

Senior Exploration Supervisor 

(Present affiliation u.s. Geological Survey) 

James c. Cobb, Co-Leader 

Head, Coal Section 

Kentucky Geological Survey 

David Matthew 

Regional Exploration Manager 

Utah International 

John Ferm 

Professor of Geology 

University of Kentucky 

H. L. Retcofsky 

Director, Division of Coal Science 

Pittsburgh Energy Technology Center 

Alan Davis 

Assistant Director, Coal Research Section 

College of Earth and Mineral Sciences 

The Pennsylvania State University 

Dennis P • Meany 

Project Manager 

ICF, Incorporated 

Recorders 

Kenneth J. Englund, u.s. Geological Survey 

M. Devereau Carter, u.s. Geological Survey 

316 
Panel II - Coal Utilization and Procurement 

Louis J. Petrovic, Co-Leader 

President 

Resource Engineering, Inc. 

Edward L. Julian, Co-Leader 

Fuels Economist 

Tennessee Valley Authority 

Homer E. Harris 

Director of Research 

Eastern Associated Coal Corporation 

S. Frank Smith 

Executive Vice President 

ANR Coal, Inc. 

James A. Monk, Jr. 

Coordinator, Fuel and Transport 

Boston Edison Coal Conversion Group 

Rick A. Mancini 

Supervisor of Performance 

and Fuel Engineering 

New York State Electric 

and Gas Corporation 

Peter Calvert 

Manager, Coal Procurement 

New England Electric 

Recorders 

Jean A. Minkin, u.s. Geological Survey 

Judith M. Black, u.s. Geological Survey 

317 
Panel III - Coal Mining and Coal Cleaning (Beneficiation) 

P. Stanley Jacobsen, Co-Leader 

Senior Coal Preparation Engineer 

Burns and Roe Services Corp. 

Robert w. Row, Co-Leader 

Project Manager, Fuel Quality 

Electric Power Research Inst. 

Richard E. Hucko 

Project Manager, Coal Preparation 

Pittsburgh Energy Technology Center 

Francis Martino 

Project Manager, EPA Coal Reserve 

Characterization Program 

Pennsylvania Electric Co. 

Mel J. Laurila 

Senior Coal Preparation Engineer 

Norton, Hambleton, Inc. 

Richard D. Pick 

Manager of Coal Processing 

Anaconda Minerals Co. 

Randy M. Kosky 

Group Supervisor 

CONOCO, Inc. 

Recorders 

Ronald Stanton, u.s. Geological Survey 

Bion H. Kent, u.s. Geological Survey 
Panel IV - Environmental Issues and the Role of Coal-Quality Research 

Jerry Pell, Co-Leader 

Manager, Coal Preparation Program 

Office of Fossil Energy 

u.s. Department of Energy 

George Rey Co-Leader 

Senior Staff Engineer, Air and 

Energy Research 

Office of Research and Development 

u.s. Environmental Protection Agency 

Julian w. Jones 

Chemical Engineer, Emissions Technology Branch 

Air Environmental Energy Research Laboratory 

u.s. Environmental Protection Agency 

Seth Schwartz 

Economist 

Energy Venture Analysis, Inc. 

Zigmund J. Frompovicz 

Fuel Specialist, Combustion Systems 

Babcox and Wilcox Co. 

Robert Statnick 

Senior Environmental Scientist 

Coal Research Division 

CONOCO 

Gerald Hollinden 

Chief, Process Engineering Branch 

Tennessee Valley Authority 

Fred c. Belsak 

Vice President, Technical Services 

Island Creek Coal Co. 

Recorders 

Frederick 0. Simon, u.s. Geological Survey 

Eleanora I. Robbins, u.s. Geological Survey 

Wayne Sigleo, u.s. Geological Survey 

319 
Panel V - Advanced Technologies for Coal Utilization 

Karl S. Vorres, Co-Leader 

Program Manager 

Premium Coal Sample Program 

Chemistry Division 

Argonne National Laboratory 

J. Warchol, Co-Leader 

Group Supervisor, Fuels Technology Group 

Research and Development Division 

Babock and Wilcox 

Fred Simmons 

Chief Chemist 

OTISCA Industries 

Arthur M. Squires 

University Distinguished Professor 

Department of Chemical Engineering 

Virginia Polytechnic Institute and 

State University 

Gary J. Goetz 

Supervisor of Fuels Research 

Combustion Engineering, Inc. 

Warren G. Schlinger 

Associate Director of Gasification 

Texaco, Inc. 

Recorders 

John 0. Maberry, u.s. Geological Survey 

Jack H. Medlin, u.s. Geological survey 

320 
SYMPOSIUM ON COAL QUALITY 

April 9-11, 1985 

List of Attendees 

Mark L. Adkins 

Getty Mining Company 

5697 S. Bree Street 

Salt Lake City, UT 84118 

Ronald Affolter 

U.S. Geological Survey 

P.O. Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

John B. Allcock 

Phillips Research Center 

253 GB 

Bartlesville, OK 74003 

Z. S. Altschuler 

Consulting Geologist 

10201 Grosvnor Place 

Rockville, MD 20852 

Noel C. Balthasar 

U.S. Department of Energy 

1000 Independence Avenue, S.W. 

Washington, DC 20585 

Brian Arkell 

New Mexico Bureau of Mines 

Campus Station 

Socorro, NM 87801 

Kenneth C. Ashton 

West Virginia Geological Survey 

P.O. Box 879 

Morgantown, WV 26505 

Gleason Avery 

Tennessee Valley Authority 

307 Krystal Building 

Chattanooga, TN 37401 

321 

Judy Back 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

William C. Banks 

Aticoal Services, Ltd. 

P.O. Box 1516 

Newport News, VA 23601 

H. H. Barker 

Virginia Power 

P.O. Box 26666 

Richmond, VA 23219 

Fred C. Belsak 

Island Creek Coal Co. 

P.O. Box 12029 

Lexington, KY 40579 

Donald Bieniewicz 

Office of Policy Analysis 

U.S. Department of the Interior 

18th & C Streets, N.W., Rm. 4453 

Washington, DC 20240 

Perry Bissell 

Resource Dynamics 

1340 Old Chain Bridge Road 

McLean, VA 22101 

Alan E. Bland 

Kentucky Center for Energy 

Research Laboratory 

P.O. Box 13015 

Lexington, KY 40512 

Fred Block 

Office of Surface Mining 

U.S. Department of the Interior 

1951 Constitution Avenue, N.W 

Washington, DC 20240 
Rich Bonskowski 

U.S. Department of Energy 

Energy Information Administration 

Coal Division, EI-521 

Washington, DC 20585 

Joy Bostic 

Missouri Geological Survey 

P.O. Box 250 

Rolla, MO 65401 

Paul Boswell 

Export-Import Bank 

811 Vermont Avenue, N.W. 

Washington, DC 20571 

Clyde Boykins 

U.S. Department of Energy 

Energy Information Administration 

1000 Independence Avenue, S.W. 

Washington, DC 20585 

Lawrence L. Brady 

Kansas Geological Survey 

1930 Constant Avenue, Campus West 

Lawrence, KS 66046 

Russell A. Brant 

Kentucky Geological Survey 

University of Kentucky 

311 Breckinridge Hall 

Lexington, KY 40506 

James R. Brooks 

Maryland Geological Survey 

711 W. 40th Street, Suite 440 

Baltimore, MD 21211 

Michael Brownfield 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

Peter Calvert 

Manager, Coal Procurement 

New England Electric 

25 Research Drive 

Westborough, MA 01581 

322 

Frank Campbell 

New Mexico Bureau of Mines 

Socorro, NM 87801 

Thomas M. Campbell 

Savannah Electric and Power Go. 

600 E. Bay Street 

P.O. Box 968 

Savannah, GA 31402 

David W. Carey 

New York State Electric 

and Gas 

P.O. Box 29 

Homer City, PA 15748 

Richard W. Carlton 

Ohio Department of Natural 

Resources, Geological Survey 

Fountain Square, Bldg. B. 

Columbus, OH 43224 

Donald D. Carr 

Indiana Geological Survey 

611 N. Walnut Grove 

Bloomington, IN 47405 

M. D. Carter 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

C. Blaine Cecil 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Edward C. T. Chao 

U.S. Geological Survey 

929 National Center 

Reston, VA 22092 

Don Chestnut 

Kentucky Geological Survey 

University of Kentucky 

311 Breckinridge Hall 

Lexington, KY 40506 
I. K. Chopra 

New York State Electric 

and Gas Corp. 

4500 Vestal Parkway East 

Binghamton, NY 13903 

John B. Clardy 

Florida Power Corp. 

P.O. Box 14042 

St. Petersburg, FL 33733 

James C. Cobb 

Kentucky Geological Survey 

University of Kentucky 

311 Breckinridge Hall 

Lexington, KY 40506 

Wendell Cochran 

American Association of 

Petroleum Geologists 

4812 30th Street South 

Arlington, VA 22206 

Dennis D. Coleman 

Illinois State Geological 

Survey 

615 E. Peabody Drive 

Champaign, IL 61821 

S . Lynn Coleman 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Aureal T. Cross 

Department of Geological 

Sciences 

Michigan State University 

East Lansing, MI 48824 

Sharon Crowley 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

James C. Currens 

Kentucky Geological Survey 

University of Kentucky 

311 Breckinridge Hall 

Lexington, KY 40502 

323 

Heinz H. Damberger 

Illinois Geological Survey 

615 E. Peabody Drive 

Champaign, IL 61820 

Alan Davis 

Assistant Director, Coal 

Research Section 

Pennsylvania State University 

513 Deike Bldg. 

University Park, PA 16802 

John Demchalk 

Appalachian Regional Commission 

1666 Connecticut Avenue, N.W. 

Washington, DC 20235 

Jim Democker 

U.S. Environmental Protectior. 

Agency 

401 M Street, S.W. 

Washington, DC 20460 

Kevin DeVanney 

U.S. Steel Corp. 

Technical Center 

One Tech Center Drive 

Monroeville, PA 15146 

John H. DeYoung, Jr. 

U.S. Geological Survey 

920 National Center 

Reston, VA 22092 

Leonard F. Dow 

Boston Edison Co. - P220 

800 Boylston Street 

Boston, MA 02199 

Frank T. Dulong 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Cortland Eble 

West Virginia Geological Survey 

P.O. Box 859 

Morgantown, WV 26503 
Greg E. Eddy 

BDM Corp. 

7915 Jones Branch Drive 

McLean, VA 22102 

J. James Eidel 

Illinois State Geological 

Survey 

615 E. Peabody Drive 

Champaign, IL 61820 

George Engelke 

Commercial Testing & 

Engineering Co. 

Suite 210B 

1919 S. Highland Avenue 

Lombard, IL 60148 

Kenneth D. Englund 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Robert Eynon 

U.S. Department of Energy 

MS 2F-021 

1000 Independence Avenue, S.W. 

Washington, DC 20585 

Ralph Eicher 

Terra Information Processing 

Services 

P.O. Box 17261 

Dulles Intn'l. Airport, VA 20041 

Sharon Falcone 

University of North Dakota 

Energy Research Center 

University Station, Box 8213 

Grand Forks, ND 58202 

John Ferm 

Department of Geology 

University of Kentucky 

Lexington, KY 40512 

Doyle G. Frederick 

Associate Director 

U.S. Geological Survey 

102 National Center 

Reston, VA 22092 

324 

Samuel A. Friedman 

Oklahoma Geological Survey 

830 Van Vleet Oval, Room 163 

Norman, OK 73019 

Z. J. Frompovicz 

Babcock & Wilcox 

20 S. Van Buren Avenue 

Barberton, OH 44203 

Rodger C. Fry 

Utah Power & Light Co. 

P.O. Box 899 

Salt Lake City, UT 84110 

Alexander Gakner 

Federal Energy Regional 

Commission, RB-507 

825 N. Capitol Street 

Washington, DC 20426 

Susan Garbini 

U.S. Geological Survey 

915 National Center 

Reston, VA 22092 

Jean Gleason 

Arthur D. Little, Inc. 

35 Acorn Park 

Cambridge, MA 02140 

Harold J. Gluskoter 

Exxon Production Research Co. 

P.O. Box 2189 

Houston, TX 77001 

Gary Goetz 

Combustion Engineering 

1000 Prospect Hill Road 

Windsor, CN 06095 

Danold W. Golightly 

U.S. Geological Survey 

957 National Center 

Reston, VA 22092 

Claude A. Goode 

U.S. Bureau of Mines 

Box 18070 

Bruceton, PA 15236 
John S. Gordon 

American Institute of 

Chemical Engineers 

600 Maryland Avenue, S.W. 

Washington, DC 20024 

Richard L. Gordon 

Department of Mineral Economics 

Pennsylvania State University 

State College, PA 16802 

John S. Goscinski 

Massey Coal Sales Company 

P.O. Box 26765 

Richmond, VA 23261 

Bill Grady 

West Virginia Geological Survey 

P.O. Box 879 

Morgantown, WV 26507 

Kathleen M. Groff 

Wyoming Geological Survey 

P.O. Box 3008 

University Station 

Laramie, WY 82070 

Robert W. Hall 

U.S. Bureau of Land Management 

350 S. Pickett 

Alexandria, VA 22304 

Robert M. Hamilton 

Chief Geologist 

U.S. Geological Survey 

911 National Center 

Reston, VA 22092 

James E. Handsborough 

Exxon Coal Resources, Inc. 

P.O. Box 2180 

Houston, TX 77001 

Donald C. Haney 

Director and State Geologist 

Kentucky Geological Survey 

University of Kentucky 

311 Breckinridge Hall 

Lexington, KY 40506 

325 

Sherie C. Harding 

109 Argyle Court 

California, MD 20619 

R. E. Harrington 

Deputy Assistant Secretary for 

Coal Utilization, Advanced 

Conversion and Gasification 

U.S. Department of Energy 

Washington, DC 20545 

Homer E. Harris 

Eastern Associated Coal Corp. 

Research & Technical Center 

P.O. Box 70 

Beckley, WV 25802 

Robert E. Harris 

Coal Division 

Energy Information Administration 

U.S. Department of Energy 

1000 Independence Avenue 

Washington, DC 20585 

Richard Harvey 

Illinois State Geological 

Survey 

615 E. Peabody Drive 

Champaign, IL 61820 

Patrick G. Hatcher 

U.S. Geological Survey 

923 National Center 

Reston, VA 22092 

Michael P. Heap 

Energy and Environmental 

Research Corp. 

18 Mason 

Irvine, CA 92714 

Charles C. Heath 

Director, Coal Division 

Energy Information Administration 

U.S. Department of Energy 

Washington, DC 20585 
William T. Henshaw 

Southern Company Services 

P.O. Box 2625 

Birmingham, AL 35202 

Nelson Hickling 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Rick T. Hildebrand 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

Robert G. Hobbs 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

Gerald A. Hollinden 

Tennessee Valley Authority 

1130 Chestnut Street Tower 

6th Chestnut Street 

Chattanooga, TN 37343 

Charles W. Holmes 

U.S. Geological Survey 

Box 6732 

Corpus Christi, TX 78411 

John S. Hoover 

U.S. Department of Energy 

Energy Information Administration 

1000 Forrestal Bldg. 

Washington, DC 20585 

Jeffrey L. Horton 

Virginia Power 

Box 26666 

Richmond, VA 23261 

Donald Hoskins 

Pennsylvania Geological Survey 

Department of Environmental 

Resources 

P.O. Box 2357 

Harrisburg, PA 17120 

326 

Richard E. Hucko 

U.S. Department of Energy 

Pittsburgh Energy Technolog~' 

Center 

P.O. Box 10940 

Pittsburgh, PA 15236 

P. Stanley Jacobson 

Burns & Roe Services Corp. 

P.O. Box 18288 

Pittsburgh, PA 15236 

Thomas Jake 

West Virginia Geological Sur·vey 

P.O. Box 879, Mont Chateau 

Morgantown, WV 26505 

Daniel A. Jobin 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

John L. Jobling 

Southern Illinois University 

5227 South Kenton Way 

Englewood, CO 80111 

John E. Johnston 

President, Johnston & 

Associates 

15905 Berkeley Drive 

Haymarket, VA 22069 

Julian W. Jones 

U.S. Environmental Protection 

Agency 

Air & Energy Engineering 

Laboratory (MD-61) 

Research Triangle Park, NC 27711 

Richard W. Jones 

The Geological Survey 

of Wyoming 

P.O. Box 3008 

University Station 

Laramie, WY 82071 
Jean Juilland 

U.S. Bureau of Land Management 

Washington, DC 20240 

Edward L. Julian 

Tennessee Valley Authority 

307 Krystal Bldg. 

Chattanooga, TN 37401 

Thomas M. Kehn 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Bion H. Kent 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

James D. Kilgore 

U.S. Environmental 

Protection Agency 

Air & Energy Engineering 

Research Lab 

Research Triangle Park, NC 27711 

Rich Killmeyer 

U.S. Department of Energy 

P.O. Box 10940 

Pittsburgh, PA 15236 

Hobart King 

West Virginia Geological Survey 

P.O. Box 879 

Morgantown, WV 26507 

Jeffrey G. Klapheke 

Institute for Mining and 

Minerals Research 

University of Kentucky 

P.O. Box 13015 

Iron Works Pike 

Lexington, KY 40512 

William A. Kneller 

Geology Department 

University of Toledo 

Toledo, Ohio 43606 

327 

Jeffrey C. Knight 

Rochester and Pittsburgh Coal 

Box 729 

Indiana, PA 15701 

Donald L. Koch 

Director and State Geologist 

Iowa Geological Survey 

123 N. Capitol 

Iowa City, IA 52242 

John F. Kohut 

Public Service Electric 

& Gas Co. 

Fuel Supply Department, T14B 

P.O. Box 570 

Newark, NJ 07101 

Randy M. Kosky 

CONOCO Inc. 

Coal Research Division 

4000 Brownsville Road 

Library, PA 15129 

R. K. Kotra 

U.S. Geological Survey 

923 National Center 

Reston, VA 22092 

Kathleen Krohn 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

John K. Kuhn 

Director, Research Applications 

and Development 

Kentucky Center for 

Energy Research 

P.O. Box 13015 

Lexington, KY 40512 

L. R. Ladwig 

Colorado Geological Survey 

Room 715 

1313 Sherman Street 

Denver, CO 80203 
Susan Latimer 

Pennsylvania Electric Co. 

1001 Broad Street 

Johnston, PA 15907 

Mel J. Laurila 

Norton Hambleton Inc. 

3135 Professional Drive 

Ann Arbor, MI 48104 

D. H. Lee 

4 No. 4th Street 

Richmond, VA 23261 

R. K. Leininger 

Indiana Geological Survey 

611 N. Walnut Grove 

Bloomington, IN 47405 

J. Robert Lewis 

Tennessee Valley Authority 

1060 Commerce Union Bank Bldg 

Chattanooga, TN 37402 

Ray List 

Norton Hambleton Inc. 

Suite 400 

2301 M Street, N.W. 

Washington, DC 20037 

Tom Loomis 

U.S. Department of the Interior 

Washington, DC 20240 

Wayne C. Love 

Florida Power Corp. 

P.O. Box 14042 

St. Petersburg, FL 33733 

James A. Lovett 

Virginia Division of 

Mineral Resources 

Johnson Center, Room 100 

468 E. Main Street 

Abingdon, VA 24210 

Paul C. Lyons 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

328 

John 0. Maberry 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Ian D. MacGregor 

National Science Foundation 

1800 G Street, N.W. 

Washington, DC 20550 

Jules A. MacKallon 

U.S. Bureau of Land Management 

Room 348 

18th and E Streets, N.W. 

Washington, DC 20240 

Rick A. Mancini 

New York State Electric 

and Gas Corp. 

4500 Vestal Parkway East 

Binghamton, NY 13903 

Charles D. Masters 

U.S. Geological Survey 

955 National Center 

Reston, VA 22092 

Francis Martino 

Pennsylvania Electric Co. 

1001 Broad Street 

Johnstown, PA 15905 

David Matthew 

Utah International 

9111 Cross Park Drive, Bldg. B 

Knoxville, TN 37923 

Douglas E. Matyas 

Federal Energy Regulatory 

Commission 

825 N. Capitol Street, N.E. 

Washington, DC 20426 

Gayle H. McColloch, Sr. 

West Virginia Geological 

Economic Survey 

Box 879 

Morgantown, WV 26507-0879 
Dennis P. Meany 

ICF Inc. 

Suite 950 

1850 K Street, 

Washington, DC 

Jack H. Medlin 

N.W. 

20006 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Arun K. Mehta 

Electric Power Research Inst. 

3412 Millview Avenue 

Palo Alto, CA 94303 

Jon L. Mikesell 

U.S. Geological Survey 

990 National Center 

Reston, VA 22092 

Michael A. Millay 

Botany Department 

University of Maryland 

College Park, MD 20742 

Elizabeth V. Miller 

Virginia Division of Mineral 

Resources 

Box 3667 

Charlottesville, VA 22903 

Ralph L. Miller 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Robert C. Milici 

Virginia Division of Mineral 

Resources 

P.O. Box 3667 

Charlottesville, VA 22920 

Jean A. Minkin 

U.S. Geological Survey 

929 National Center 

Reston, VA 22092 

329 

Carol Molnia 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

James A. Monk, Jr. 

Boston Edison Co. - P276 

800 Boylston Street 

Boston, MA 02199 

Shelley Moore 

P.O. Box 7868 

Madison, WI 53707 

Sandra G. Neuzil 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

E. A. Noble 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Laurence M. Nuelle 

Missouri Department of 

Natural Resources 

Division of Geology and Land 

Survey 

P.O. Box 250 

Rolla, MO 65401 

J. T. O'Connor 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Terry W. Offield 

U.S. Geological Survey 

915 National Center 

Reston, VA 22092 

Charles Oman 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 
W. F. Outerbridge 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Curtis A. Palmer 

U.S. Geological Survey 

990 National Center 

Reston, VA 22092 

Jerry Pell 

U.S. Department of Energy 

Office of Coal Utilization 

Systems 

Fossil Energy, FE-23 

Washington, DC 20545 

William C. Peters 

U.S. Department of Energy 

P.O. Box 10940 

Pittsburgh, PA 15236 

D. B. Peterson 

House Subcommittee on Fossil 

Fuels 

H2-331, Annex 112 

Washington, DC 20515 

Louis J. Petrovic 

President 

Resource Engineering, Inc. 

80 Bacon Street 

Waltham, MA 02154 

Richard D. Pick 

Anaconda Minerals Company 

Technology Department 

555 17th Street 

Denver, CO 80202 

Brenda Pierce 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Frances W. Pierce 

U.S. Geological Survey 

Box 25046, Mail Stop 937 

Denver Federal Center 

Denver, CO 80225 

330 

James Pinta, Jr. 

Gulf Research & Development Co. 

P.O. Box 2038 

Pittsburgh, PA 15230 

Jeremy Platt 

Electric Power Research 

Institute 

P.O. Box 10412 

Palo Alto, CA 94306 

John Pyrdol 

Federal Energy Regulatory 

Commission, Rm. 507 

400 First Street, N.W. 

Washington, DC 20426 

Marshall Rehm 

Pennsylvania Power & Light Co. 

2 N. 9th Street 

Allentown, PA 18049 

Herbert L. Retcofsky 

Pittsburgh Energy Technology 

Center 

P·.o. Box 10940 

Pittsburgh, PA 15236 

George Rey 

U.S. Environmental Protection 

Agency 

ORO 681 

Washington, DC 20460 

Ed Rhodehomel 

14621 Baugher Drive 

Centreville, VA 22020 

Charles L. Rice 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Robert L. Rioux 

U.S. Geological Survey 

915 National Center 

Reston, VA 22092 
Eleanora I. Robbins 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Henry W. Roehler 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

Robert W. Row 

Project Manager, Coal Quality 

Electric Power Research Institute 

P.O. Box 10412 

Palo Alto, CA 94303 

Terry L. Rowland 

The Coteau Properties Co. 

2000 Schafer Street 

Bismark, ND 58501 

Leslie Ruppert 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

George W. Sall 

U.S. Department of Energy 

FE-13 

Washington, DC 20545 

J. David Sanchez 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

John Sanfilipo 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Warren G. Schlinger 

Texaco, Inc. 

3350 Wilshire Boulevard 

Los Angeles, CA 90010 

331 

Craig R. Schmit 

North Dakota Mining and Mineral 

Resources Research Institute 

Box 8103, University Station 

Grand Forks, ND 58202 

Robert Schnapp 

U.S. Department of Energy 

Energy Information Administration 

Mail Stop 2F-021 

Washington, DC 20585 

Robert 0. Schrott 

U.S. Bureau of Land Management 

Code 690 

18th and C Streets, N.W. 

Washington, DC 20240 

Seth Schwartz 

Energy Ventures Analysis, Inc. 

1111 N. 19th Street, Suite 505 

Arlington, VA 22209 

Kenneth A. Schwarz 

Maryland Geological Survey 

The Rotunda 

711 W. 40th Street, Suite 440 

Baltimore, MD 21211 

Stanley P. Schweinfurth 

U.S. Geological Survey 

915 National Center 

Reston, VA 22092 

Paul Schwengels 

U.S. Environmental 

Protection Agency 

ANR 445 

401 M Street, S.W. 

Washington, DC 20467 

Paul C. Scott 

U.S. Department of Energy 

FE-14 

Washington, DC 20545 

Frank E. Senftle 

U.S. Geological Survey 

990 National Center 

Reston, VA 22092 
Wayne R. Sigleo 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Fred Simmons 

Otisca Industries 

501 Butternut Street 

Syracuse, NY 13208 

Frederick 0. Simon 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Carl J. Smith 

West Virginia Geological and 

Economic Survey 

P.O. Box 879 

Morgantown, WV 26507 

S. Frank Smith 

ANR Coal, Inc. 

P.O. Box 1871 

Roanoke, VA 24008 

Barry Solomon 

Federal Energy 

Commission 

825 N. Capitol 

Washington, DC 

Samuel Spadone 

Regulatory 

Street, N.E. 

20426 

Office of Coal Utilization 

Systems 

U.S. Department of Energy 

Germantown, MD 20545 

Arthur M. Squires 

Virginia Polytechnic Institute 

and State University 

Department of Chemical 

Engineering 

Blacksburg, VA 24061 

Robert M. Statnick 

CONOCO, Coal Research Division 

4000 Brownsville Road 

Library, PA 15129 

332 

Ben Stothart 

Pennsylvania Power & Light Co. 

2 North 9th Street 

Allentown, PA 18101 

Raymond W. Strom 

NERCO Coal Company 

4225 Malsbary Road 

Cincinnati, Ohio 45242 

Daniel Talmo 

Wisconsin Division of Energy 

P.O. Box 7868 

Madison, WI 53707 

Allan B. Tanner 

U.S. Geological Survey 

990 National Center 

Reston, VA 22092 

Nancy Teaford 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Susan J. Tewalt 

Bureau of Economic Geology 

University of Texas 

University Station, Box X 

Austin, TX 78713 

Duane A. Thompson 

Library of Congress 

ENR-CRS 

Washington, DC 20540 

Arthur N. Thorpe 

Department of Physics and 

Astronomy 

Howard University 

Washington, DC 20059 

Jim Tice 

Pennsylvania Electric Co. 

1001 Broad Street 

Johnstown, PA 15907 

Dave Traudt 

U.S. Bureau of Land Management 

350 S. Pickett Street 

Alexandria, VA 22304 
Virgil A. Trent 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Karl S. Vorres 

Argonne National Laboratory 

CHM 211, Chemistry Division 

Argonne, IL 60439 

Kevin P. Walek 

Committee on Energy and 

Commerce 

H2-331 House Annex II 

U.S. House of Representatives 

Washington, DC 20515 

James J. Warchol 

Babcock & Wilcox 

Alliance Research Center 

1562 Beeson Street 

Alliance, OH 44601 

R. C. Warlow 

12601 Pinecrest Road 

Herndon, VA 22070 

William Watson 

U.S. Geological Survey 

105 National Center 

Reston, VA 22092 

Russell G. Wayland 

4660 N. 35th Street 

Arlington, VA 22207 

Jean N. Weaver 

U.S. Geological Survey 

Box 25046, Mail Stop 972 

Denver Federal Center 

Denver, CO 80225 

Paul K. West 

The Falkirk Mining Company 

P.O. Box 1087 

Underwood, ND 58576 

333 

Joseph F. Whelan 

U.S. Geological Survey 

Box 25046, Mail Stop 963 

Denver Federal Center 

Denver, CO 80225 

William Whitlock 

Virginia Division of Mineral 

Resources 

Johnson Center, Room 100 

468 E. Main Street 

Abingdon, VA 24210 

Gerry Wilkes 

Virginia Division of Mineral 

Resources 

Box 3667 

Charlottesville, VA 22920 

Richard N. Wilson 

U.S. Bureau of Land Management 

P.O. Box 1449 

Sante Fe, NM 87505 

John F. Windolph, Jr. 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Christopher Wnuk 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Larry D. Woodfork 

West Virginia Geological Survey 

Morgantown, WV 26507 

Zeno R. Wright, Jr. 

Potomac Electric Power Company 

1900 Pennsylvania Avenue, N.W. 

Washington, DC 20068 

Doug Young 

Virginia Power 

P.O. Box 26666 

Richmond, VA 23261 
Valentine Zadnik 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

Peter Zubovic 

U.S. Geological Survey 

956 National Center 

Reston, VA 22092 

334 *U.S. GOVERNMENT PRINTING OFFICE: 1986-491-405:20114