14

REFERENCES

1. Morgan, W. K. C. The Prevalence of Coal Workers’ Pneumo-
coniosis. Am. Rev. Respir. Dis., v. 98, 1968, pp. 306-310.

2. Bennett, J. G., J. A. Dick, Y. S. Kaplan, P. A. Shand, D. H. Shen-
nan, D. J. Thomas, and J. S. Washington. ‘The Relationship Between
Coal Rank and the Prevalence of Pneumoconiosis. Br. J. Ind. Med.,
v. 36, 1979, pp. 206-210.

3. Naeye, R. L., J. K. Mahon, and W. S. Dellinger. Rank of Coal
and Coal Workers’ Pneumoconiosis. Am. Rev. Respir. Dis., v. 103, 1971,
pp. 350-355.

4. Hurley, J. F., J. Burns, L. Copland, J. Dodgson, and M. Jacobsen.
Coal Workers’ Simple Pneumoconiosis and Exposure to Dust at 10 Brit-
ish Coal Mines. Br. J. Ind. Med., v. 39, 1982, pp. 120-127.

5. Baafi, E. Y., and R. V. Ramani. Rank and Maceral Effects on
Coal Dust. Int. J. Rock Mech. and Min. Sci. (& Geomech Abstr.),
y. 16, 1979, pp. 107-115.

6. Moore, M. P., and C. J. Bise. The Relationship Between the
Hardgrove Grindability Index and the Potential for Respirable Dust
Generation. Paper in Coal Mine Dust Conference (Morgantown, WV,
‘Oct. 8-10, 1984). Generic Technology Center for Respirable Dust, 1984,
pp. 250-255.

7. American Society for Testing and Materials. Standard Test Meth-
4 for Grindability of Coal by the Hardgrove Machine Method. D409-
90 in 1990 Annual Book of ASTM Standards: Volume 05.05. 1990, pp.
197-202.

8. Schlick, D. P., R. G. Peluso, and W. E. Byers. An Evaluation
of the Respirable Dust Sampling Program in United States Underground
Coal Mines. BuMines TPR 32, 1971, 20 pp.

9. Seibel, R.J., and F. E, McCall, The Dustiness of Different Coal
Scams. BuMines TPR 75, 1974, 9 pp.

10. Stecklein, G. L., R. Branstetter, R. Arrowood, D. Davidson, J.
Lankford, R. Lyle, and C, Nulton, Basic Research on Coal Fragmenta-
tion and Dust Entrainment, Volume I—Technical Information (contract
30215009, Southwest Research Inst.). BuMines OFR 215(1)-83, 1982,
121 pp.

11. Neter, J., W. Wasserman, and G. A. Whitmore. Applied Statistics.
Allyn and Bacon, 1988, pp. 329, 526.

12. Ramani, R. V., J. M. Mutmansky, R. Bhaskar, and J. Qin, Funda-
‘mental Studies on the Relationship Between Quartz. Levels in the Host
Material and the Respirable Dust Generated During Mining, Volume I:
Experiments, Results and Analysis (contract H0358031, PA State Univ.).
BuMines OFR 36-88, 1987, 179 pp.; NTIS PB 88-214325/AS.

13. National Coal Board (United Kingdom). Mining Research and
Development Review by Mining Research and Development Establish-
ment. No. 7, Apr. 1973, 12 pp.

14. Strebig, K. C., and H. W. Zeller. Effect of Depth of Cut and
Bit Type on the Generation of Respirable Dust. BuMines RI 8042,
1975, 16 pp.

15, Inculet, I. L, R. M. Quigley, and E, M. J. Beisser. Electrostatic
Charges on Clays. IEEE Trans. Ind. Appl., v. IA-21, No. 1, Jan./Feb.
1985, pp. 23-25.

16. Mukherjee, A., D. Gidaspow, and D. T. Wasan, Surface Charge
of Illinois Coal and Pyrites for Dry Electrostatic Cleaning. Am. Chem.
Soc, v. 32, No. 1, 1987, pp. 395-407.



0.005

SPECIFIC DUST, mg/ton

OO!

.003

°

DUST CONCENTRATION, mg/m?

ASH CONTENT, pet

Figure 7.—Scatter plot of ash and headgate specific (normalized) dust.

| o 4
a
— 4
a
a
= o o
o o 9
tn” a
oo
oo a a 0 oO
qo 7 Foe i 1
5 10 15 20 25 30

20

a

3

a

1
5 10 15 20
ASH CONTENT, pct

Figure 8.—Scatter plot of ash and tailgate dust concentration.


18

Table A-5.—Nonlinear model parameter table

Variable and criterion Model Parameter Parameter Standard Tetatistic Teitica
value error
Ash:
Headgate dust concentration . . aeTM a 15.726 4.968 3.166 2.042
b 0.306 0.079 3.886 2.042
DO... ee eee eee cece eee ee ax? a 29.043 8.150 3.564 2.042
b 1.407 0.226 6.231 2.042
aoTM a 0.010 0.003 3.505 2.042
b 0.529 0.093 5.709 2.042
DO. cece e eee ee ax® a 0.012 0.003 4.267 2.042
b 1.738 0.212 8.190 2.042
Tailgate dust concentration aeTM a 9.297 2.231 4.167 2.040
b 0.069 0.033 2.051 2.040
DO cece ax? a 11.959 4.273 2.799 2.040
b 0.410 0.193 2.119 2.040
Tailgate specific dust ........ aeTM* a 2.6 x10 6.1.x 104 4.320 2.040
b 0.102 0.037 2.796 2.040
DO. cee eee eee e eee ene ax® a 3.8 x 10% 1.2x 10% 3.296 2.040
b 0.603 0.177 3.412 2.040
Volatility:
Tailgate dust concentration ... a-bx + ox? a 16.350 7.500 2.180 2.042
b 1.044 0.505 2.065 2.042
° 0.019 0.008 2.425 2.042
Parameter = 0.
Parameter = 0.
When Tytatistic < Tertia C€NNOt reject Hy; if Tyeatstic > Tevtican Feject Hp.
Table A-6.—Analysis of variance and fit statistics of nonlinear models
Variable and criterion Model Source of Sum of Degrees Mean R Feeatistic Feit
variation squares _of freedom _square error
Ash:
Headgate dust aeTM Regression 297.89 2 148.95 039 31.82 3.32
concentration. Residual . . 140.44 30 4.68
Do ax? Regression 330.59 2 165.30 053 46.02 3.32
Residual 107.74 30 3.59
Headgate specific ae** Regression 2.8 x 10° 2 1.4.x 10° 0.61 49.48 3.32
dust. Residual . . 8x 10% 30 0.09
Do. ....... ax? Regression 29x 105 2 15x 10° 0.70 69.24 3.32
Residual . . 1x 10% 30 0.00
Tailgate dust aeTM* Regression 992.66 2 496.33 0.15 38.50 3.31
concentration. Residual . . 399.65 31 12.89
Do. ....... ax? Regression 987.25 2 493.62 0.14 © 37.78 3.31
Residual . . 405.07 31 13.07
Tailgate specific ae Regression 5.2x 105 2 2.6 x 10> 0.24 45.55 3.31
dust. Residual . . 1.8 x 105 31 6x 10°
Do. ....... ax? Regression 5.3 x 105 2 2.6 x 10% 0.27 47.18 3.31
Residual . . 1.7 x 10% 31 1x 10%
Volatility:
Tailgate dust a-bx + 0x? Regression 1,063.35 3 354.45 030 © 32,32 3.32
concentration. Residual . . 328.97 30 10.97
Ho! ariable = Heriterion.

H,

= Mesterion
When Fyutstic < Feria Cannot reject H,; if Fyaistic > Fertian foject Hp.

NOTE.—R? is determined from total corrected source of variation (E (y-y)").


CONTENTS

Page

Abstract 1

Introduction .. . 2

Survey strategy . 2

Identification of significant coal seam parameters 6

Seam types and dust compliance . . . ou

Discussion of coal seam parameters ....... . 13

Conclusions .. . . . 3

References .... 4

Appendix.—Survey data anc analysis. . 15
ILLUSTRATIONS

1. Percentage of U.S. longwalls in compliance with the Federal dust standard ... 2

2. USS. coal provinces 2.2.6... e cece cece cence ete tence een e ee eeeee 4

3. Frequency histogram of coal seam types sampled 5

4. Correlation matrix of seam parameters and dust criteria . 6

5. Scatter plot of ash content, volatile matter, and tailgate dust concentration . 7

6. Scatter plot of ash and headgate dust concentration 7

7. Scatter plot of ash and headgate specific (normalized) dust 8

8. Scatter plot of ash and tailgate dust concentration ...... 8

9. Scatter plot of ash and tailgate specific (normalized) dust . 9

10. Scatter plot of volatile matter and tailgate dust concentration 10

11. Scatter plot of HGI and tailgate dust concentration ..... 10

12, Average ash and volatile content of provinces sampled .. . 11

13. Average dust concentrations of provinces sampled ...... 2

14. Average dust compliance concentrations of provinces surveyed 12

15, Average ash and volatile content in two seam types sampled in the Eastern Province 12

16. Average dust concentrations in two seam types sampled in the Eastern Province ..........-+-+00+ Rn

TABLES

1. ASTM standards for coal classification 3

2. Chi-square test of sample distribution ....... 5

3. Differences in dust generation by continuous miners in 1 two different coal seams ... 1

A-1, Dust criteria measurements . ‘ 15

A-2, Coal characteristics 16

A-3. Operation parameters 7

A-4, General mine characteristics 7

A-5. Nonlinear model parameter table . . . . 18

A-6. Analysis of variance and fit statistics of nonlinear models... 18



APPENDIX.—SURVEY DATA AND ANALYSIS

Table A-1.—Dust criteria measurements

Coal pro- Dust concentration, Dust mass, mg Specific dust,
Mine Shift duced, tons mg/m? Headgate Tailgate mg/ton
Headgate Tailgate Headgate ‘Tailgate
A. 14 1,042 157 2.05 0.95 1.18 9.079E-04  1.131E-03
B. 1-4 1,148 94 94 52 49 4.512E-04 — 4.294E-04
c. 14 2,377 55 1.04 28 53 1.195E-04 2234-04
D. 15 3,067 1.51 2.36 89 1.34 2.902E-04 —4.359E-04
E. 1 2,443 241 14.54 1.09 5.47 4.458E-04 — 2.238E-03
2 2,443 78 11.83 25 3.29 1.040E-04 —1.346E-03
Fo. 1 1,305 3.22 5.24 2.41 2.89 1.618E-03 2216-03
G.. 1 2,138 1.68 3.77 73 1.40 3.410E-04 — 6.525E-04
2 1,426 ie) 3.83 te) 92 0) 6.445E-04
H. 1 751 3.09 4.21 1.40 1.68 1.860E-03  2.242-03
he. 1 3,240 3.62 7.75 1.85 3.52 5.719E-04 —1,086E-03
2 2,835 2.50 9.17 117 3.80 4.109E-04 1.339603
J. 1 3,038 3.34 8.68 1.25 2.92 4.111604 — 9.598E-04
2 2,126 3.98 4.93 2.40 279 1.131E-03 1.312E-03
K. 1 950 2.82 5.14 1.21 1.98 1.271E-03 — 2,088E-03
2 1,425 3.05 3.62 1.21 1.34 8.477E-04 —9.396E-04
L. 1 1,316 59 2.89 35 1.56 2.675E-04 —1.186E-03
2 1,053 90 5.24 24 1.40 2,.260E-04 —1.933E-03
M.. 1 826 9.30 18.12 2.03 3.88 2,454E-03  4.695E-03
2 826 14.30 8.24 3.35 1.88 4.05103 2.275E-03
N. 1 3,645 1.80 1.90 90 1.35 2,480E-04 3.701604
2 3,645 1.53 2.53 92 1.40 2.510E-04 —3.846E-04
° 1 1,786 1.54 2.81 25 114 1.417E-04 6.355E-04
2 1,786 3.81 3.94 71 1.86 3.987E-04 — 1.041E-03
P. 1 2,430 89 3.87 60 2.15 2.449E-04 — 8.844E-04
2 2,126 1.44 5.50 58 2.07 2.747E-04 — 9.732E-04
Q.. 1 1,807 59 79 38 40 2.092E-04 2,230E-04
R.. 1 1,504 70 3.31 36 1.54 2.420E-04 —1,021E-03
2 1,604 2.46 4.87 1.34 2.53 8.373E-04 — 1.579E-03
Su... 1 2,495 3.01 7.35 68 1.53 2.725E-04 — 6.128E-04
2 2,495 75 6.91 35 2.70 1.395E-04 —1.080E-03
T 1 1,382 112 3.72 25 1.04 1.780E-04 —7.540E-04
2 1,382 2.40 3.53 St 1.09 3.719E-04 — 7.916E-04
Dumped.

NOTE.—Dust measurements not in MRE equivalents.

15


Table A-3,—Operation parameters

Water Max bit Air velocity, fom Air quantity, cfm Change in
Mine Shift applied, depth, = Head- Av Tail  Head- Av Tail- quantity,”
wt pet in/rev gate face gate gate gate pet
A. 14 NA 1.42 250 295 ~——(26t 16,875 14,929 “12
B.. 1-4 NA 3.23 241 167 98 17,328 7,046 59
c.. 14 NA 3.11 418 438 450 30,430 19,845, 35
D.. 15 NA 1.97 329 285 267 20,859 22,321 7
E.. 1 0.94 5.60 230 254 228 -30,199 29,936 a4
2 93 5.07 250 261 332 32,825 43,592 33
Fo. 1 78 1.50 256 357-220 7,424 6,380 14
G.. 1 1.94 4.27 242 333 355 13,189 19,348 47
2 2.51 3.60 403 376 376 21,964 20,492 7
H.. 1 70 3.14 102 68 98 4,580 4,400 4
hen 1 1.38 4.80 249 260 248 11,180 11,135 C)
2 1.68 453 222 240 193 9,968 8,666 13
Jee 1 94 474 284 238 = 224 40,016 31,562 21
2 94 5.05 541 308 = 322, 76,207 45,370 -40
K.. 1 81 4.00 816 5244176 2,750 32,067 -49
2 88 5.64 287 474 557 19,763 42,833 117
Le. 1 4.21 2.63 340 496 490 15,266 22,001 44
2 1.18 2.49 373 433 437 16,748 19,621 7
M.. 1 6.37 2.43 408 239 228 37,903 21,181 44
2 6.45 1.95 278 239-230 25,826 21,367 17
N.. 1 8.39 3.10 258 276 = 308 31,399 37,484 19
2 7.70 3.10 258 280 292 31,399 35,536 13
o.. 1 1.47 3.82 419 313 218 34,903 18,159 48
2 2.11 3.27 416 307 181 34,653 15,077 56
P.. 1 1.45 2.27 425 336 308 43,563 31,570 -28
2 1.91 3.08 476 329 318 48,790 32,595, 33
Q.. 1 3.09 371 253 217 238 21,075 19,825 “59
R.. 1 4.98 3.20 327 316 = 308. 39,796 37,484 6
2 3.09 3.20 335 324 320 -40,770 38,944 4
S.. 1 2.00 4.13 657 50231267342 31,980 +3
2 2.73 5.33 294 330 283 30,135, 29,008 4
T 1 5.30 4.13 213 397 414 19,789 38,461 94
2 3.72 3.73 210 401 404 _19,509 37,532 92

1From headgate to tailgate.

Table A-4.—General mine characteristics

Mine Seam Height, Panel width, Cut sequence?
in ft

A... Lower Kittanning .... 66 440 BEDI

B... Eagle 72 680 Uni-Di (HT cut)

C... Pittsburgh . 65 615 (TH cut)

Di... do... 90 650 (TH cut)

E... Blind Canyon . 114 760 (H>T cut)

F... Dorchester . 50 580 (TH cut)

G... No.2gas.. 66 580 i

H... Campbell Creek 60 550 Uni-Di (TH cut)

Loo. Warfield . 60 600 Bi-Di

J... Harlan. 120 540 Uni-Di (TH cut)

K... Blue Creek . 80 660 Uni-Di (TH cut)

Li... Pratt 60 850 Bi-Di

M... | Wattis . 90 480 Uni-Di (T-H cut)

N... Eagle No. 5 (F). 408 750

0... Pittsburgh ... 84 630 (TH cut)

P.. Upper Freeport . 96 750

Q. do... 84 600

R.. 108 550 i (TH cut)

S.. 96 700 (TH cut)

T... Herrin No. 6 90 910 Uni-Di (HT cut)

1Bi-Di, bidirectional; Uni-Di, unidirectional; H+T, headgate to tailgate; T+H

tailgate to headgate.

17


concentrations from compliance sampling. Thus, the rel-
ative differences among the regional MSHA compliance

KEY
Rocky
Interior
W Eastern

Headgate

Tailgate

aa L 1

1.
o 2 4 6 8 10 [2
DUST CONCENTRATIONS, mg/m3

Figure 13.—Average dust concentrations of provinces sam-
pled.

1989 F:

Interior
CX Yesstern

1988

1987

(986

{e} | 2 3 4

DUST CONCENTRATIONS, mg/m _ —

dust data correspond to average regional seam types and
dust levels measured in this study.

Similar ash-volatility and dust relationships were also
found within the Eastern Province. Figures 15 and 16
show the ash-volatility content and dust concentrations
measured within the Eastern Province. Significantly higher
dust concentrations were observed at the four longwalls
operating in lower ash, higher volatile coal seams. Since
the secondary MSHA data concur with the data collected
in this study, seam characteristics seem to be an important
factor in the amount of dust generated and the ability to
maintain compliance.

Volatile

KEY

10 mines
4 mines
1

Ash

° fe) 20 30 40
CONTENT, pct

Figure 15.—Average ash and volatile content In two seam
types sampled In the Eastern Province.

KEY

10 mines
4 mines

Headgate

Tailgate

L 1 L

fe} 2 4 6 8
DUST CONCENTRATIONS, mg/m>

Figure 14.—Average dust compliance concentrations of prov-
Inces surveyed.

Figure 16.—Average dust concentrations in two seam types
‘sampled In the Eastern Province.


LEGEND
Lignite a
ZZ Subbituminous coal oo

Medium and high- volatile
bituminous coal

ISS Low- volatile bituminous o 600
coal
HB Anthracite and semianthracite Scale, miles

Figure 2.-U.S. coal provinces.


RELATIONSHIP OF COAL SEAM PARAMETERS AND
AIRBORNE RESPIRABLE DUST AT LONGWALLS

By J. A. Organiscak,’ S. J. Page,? and R. A. Jankowski?

ABSTRACT

The U.S. Bureau of Mines investigated the relationship of bituminous coal seam parameters and the
amount of airborne respirable dust generated at longwalls. Dust and coal samples were obtained from
20 longwalls operating in geographically representative coalfields throughout the United States.
Statistical analyses of coal seam parameters and airborne respirable dust measurements indicate a likely
causal relationship between seam type and respirable dust.

Low-ash, high-volatile coal seams were associated with higher airborne respirable dust levels. A
negative linear correlation (significant at the 95-pct confidence level) was observed between the seam’s
ash content and airborne respirable dust, explaining up to 18 pct (R? = 0.18) of headgate dust level
variation and up to 15 pct of tailgate dust level variation. Volatile matter was found to have a positive
linear correlation with tailgate dust level, explaining 16 pct of the variation. Further data examination
indicates that these relationships with dust are most likely nonlinear, because of improved R? values over
the linear correlations. However, a notable portion of longwall dust production is influenced by other
operational parameters, so additional research under more controlled conditions is needed to determine
the seam’s causative functions.

\Mining engineer.

Physicist.

3Supervisory physical scientist.
Pittsburgh Research Center, U.S. Bureau of Mines, Pittsburgh, PA.


UNIT OF MEASURE ABBREVIATIONS USED IN THIS REPORT

Btu
Btu/Ib
cfm.
fpm

in

in/rev

British thermal unit

British thermal unit per pound mass
cubic foot per minute

foot per minute

inch

inch per revolution

mg
mg/m?
mg/ton
pet

wt pet

milligram

milligram per cubic meter
milligram per short ton
percent

weight percent



1B

DISCUSSION OF COAL SEAM PARAMETERS

In this longwall study, the Bureau found that low-ash,
high-volatile bituminous coals tended to produce more air-
borne respirable dust. Although these were the chief
parameters affiliated with airborne dust generation, their
specific causal functions in airborne dust generation are
not known, The actual dust generation phenomena may
involve several interrelated coal parameters that have
chemical and/or mineral causative mechanisms of airborne
respirable dust generation. Three possible causative hy-
potheses are proposed below that could be considered for
future research on coal seam airborne dust. The first two
hypotheses were proposed by the Southwest Research In-
stitute based on its basic research on coal fragmentation
and dust entrainment conducted for the Bureau (10), and
the third hypothesis was proposed by the authors of this
report.

1. Coal fragmentation from cutting usually occurs along
planes of imperfections formed by ash material (making
the coal a more heterogeneous material), which facilitates
breakage into a larger size distribution and reduces the
amount of respirable dust generated. Note that ash con-
tent and HGI in this study have an insignificant correlation
(Gig, 4). This statistic indicates that the ash parameter has
very little association with grindability and suggests that

coal grinding properties may not be the best indicator for
airborne respirable dust formed during cutting or haulage
fragmentation,

2. Electrostatic charge on respirable coal dust, which
is partially responsible for entrainment, may arise as a
consequence of surface-air reactions (volatilization and
oxidation). Chemical and mineralogical classification re-
search on respirable-sized coal dust found an increase
in both carbon and hydrogen content and a decrease in in-
organic chemical content with increasing particle size.
This may be due to volatilization of light hydrocarbon
from the particle surface.

3. Electrostatic charge properties of ash minerals could
possibly be responsible for dust coagulation, reducing the
amount of respirable dust that becomes airborne. The
major components of ash are typically silica, clay (kaolin-
ite), and sulfur. Sulfur or iron pyrite was highly correlated
to ash content, but was not as highly associated with air-
borne dust generation as was ash. Both sulfur and clay
particles can have significantly higher electrostatic charges
than coal particles (15-16).

These three hypotheses center around chemical or min-
eralogical causes affiliated with ash and volatility param-
eters identified in this study.

CONCLUSIONS

Coal seam parameters are associated with the amount
of dust generated at longwalls. Low-ash, high-volatile
bituminous coal seams tend to experience higher res-
pirable dust levels during mining. The ash parameter
could be better described by nonlinear decay models for
both the dust concentration and specific dust criterion.
The volatile matter parameter could better describe the
tailgate dust concentrations by a polynomial growth model.
HGI was found to be indirectly related to airborne res-
pirable dust generation, contrary to the hypothesized belief
of direct association.

The ash-volatility parameters and dust measurements in
regional geographic areas (coal provinces) of the United
States relatively agreed with MSHA compliance data. The
Rocky Mountain Province averaged the highest dust levels
for both this survey and MSHA compliance data. This
province on average contains low-ash, high-volatile coal

seams, coinciding with the ash relationship found in this
study. The Eastern and Interior Provinces on average had
lower volatile, higher ash coal seams with lower MSHA
reported dust levels and higher compliance rates. This
ash-volatility and dust relationship was also observed
within the Eastern Province, which indicates that low-ash,
high-volatile seams are not located only in one province.

Additional research studies should strive to verify the
ash and volatility association with airborne respirable dust
under strictly controlled conditions by reducing the un-
explained data scatter (most likely caused by numerous op-
erational parameters). Reducing the data scatter will also
improve nonlinear model development of these coal seam
parameters. Further research efforts should target verifi-
cation of the above suggested hypotheses or any other
proposed hypotheses for developing fundamental principles
of airborne dust generation.


The criterion used for this study was to obtain a represent-
ative sample of longwalls operating in the different bi-
tuminous seam types (five bituminous classifications of
coal of the American Society for Testing and Materials
(ASTM)) and in different geographic areas of the country.
The minimum number of longwalls needed in a random
survey to obtain a representative dust sample of the long-
wall industry population was 11, based on a targeted pre-
cision of +0.5 mg/m? at the 95-pct confidence level with
a longwall industry standard deviation of 0.85 mg/m?
(from Mine Safety and Health Administration (MSHA)
data). However, 16 longwall sections were surveyed in
15 different coal seams to increase industry coverage since
a random sample could not be obtained. Two shifts of
sampling were planned throughout the study and were
achieved at 13 of the 16 sections surveyed, for a total of
29 shifts of sampling. Secondary data available from 4
other past longwall studies were also used to increase the
data base to 20 mines, 17 coal seams, and 33 data files.
Data collected for each shift included dust samples, coal
samples, ventilation measurements, production during sam-
pling, and other general mine characteristics. Multiple
respirable dust samples were collected at support 10, and

roughly 10 supports inby the tailgate of each longwall,
with personal sampling instruments, Dust sampling was
planned to take place for a minimum of four complete
mining passes or face advances. This production goal dur-
ing sampling was achieved in 70 pct of the shifts sampled,
Average airborne dust data collected at the sampling loca-
tions are shown in table A-1 of the appendix. Production
during sampling was determined from face advance, seam
height, face width, and density.

Coal samples were collected from the face conveyor
at various times during production. These samples were
combined, mixed, coned, and quartered to obtain a small
representative sample of the run-of-mine product. These
samples were packaged into small airtight containers for
transport out of the mine to the laboratory for proximate
and Hardgrove grindability analysis. Processing of these
coal samples was conducted using ASTM proximate analy-
sis and HGI classification procedures. Proximate analysis
and HGI data are shown in table A-2 of the appendix.

The sample set collected approximates a normal dis-
tribution for bituminous class coals. Figure 2 shows the
types of coals in the different coal provinces of the United
States; table 1 shows the ASTM coal classifications; and

Table 1.—ASTM standards for coal classification
Ciass and group Fixed carbon Volatile matter Calorific value ‘Agglomerating character
limits,! pet limits,’ pet limits,? Btu/Ib
‘Anthracite:
Metaanthracite . 298 <2 214,000)
Anthracite... 92-98 28 214,000} Nonagglomerating.>
Semianthracite . 86-92 814 214,000)
Bituminous:
Low-volatile 78-86 14-22 214,000)
Mediumn-volati 69-78 22:31 214,000]
High-volatile A . <69 231 214,000) Commonly agglomerating.*
High-volatile B <69 231 13,000-14,000}
<69 231 11,500-13,000,
High-volatile C . <69 231 10,500-11,500  Agglomerating.*
‘Subbituminous:
‘Subbituminous A... <69 231 10,500-11,500)
Subbituminous B ... <69 231 9,500-10,500
Subbituminous C .. . <69 231 8,300- 9,500} Nonagglomerating.
Lignitio:
Lignite A <69 231 6,300- 8,300)
Lignite B <69 231 <6,300,

‘Dry, mineral-matter-free basis.
?Moist, mineral-matter-free basis. "Moist" refers to the
visible water on the surface.

natural inherent moisture of the coal, does not include

3if agglomerating, classify in low-volatile group of the bituminous class.
There may be nonagglomerating varieties in these groups.

There are notable exceptions in this group.

NOTE—Coals having 69 pet or more fixed carbon on the dry, mineral-matter-free basis shall be classified

according to fixed carbon, regardless of calorific value.


Relationship of Coal Seam Parameters and
Airborne Respirable Dust at Longwalls

By J. A. Organiscak, S. J. Page, and R. A. Jankowski

ma

“= UNITED STATES DEPARTMENT OF THE INTERIOR 4 Chew S13

BUREAU OF MINES


IDENTIFICATION OF SIGNIFICANT COAL SEAM PARAMETERS

A correlation matrix was used to examine the inter-
dependence of coal seam parameters and to identify the
most important and independent coal seam characteristics
with respect to the airborne dust criteria (fig. 4). The
measure of association (correlation) used in this matrix is
the Pearson product-moment coefficient (r), including
sample size and level of significance (p-value) (11). The
level of significance is the probability that the variable
association is false (Type I error). The dust criterion (de-
pendent variable) is expressed in both concentrations and
airborne respirable mass measured per short ton mined
during the sampling period (specific dust) at both the
headgate and tailgate sampling locations. The actual
airborne dust generated per short ton could not be reliably
calculated and used as a criterion variable because of
notable variations between the headgate and tailgate air

quantities at many of these longwalls (see table A-3 of the
appendix), The average percent change in air quantity be-
tween the headgate and tailgate had a coefficient of varia-
tion of 1,160 pet (mean = -38 pct, standard deviation
= 44.1 pet). The wide variation of the percent change in
air quantity along the face for all the longwalls makes this
parameter unreliable for specific dust determination.

Examination of the coal seam parameter correlations
show strong associations among several parameters. Some
of the strongest and most significant correlations are
between ash and sulfur, ash and heat content, ash and vol-
atility, volatility and HGI, and volatility and moisture
content. This is not surprising since various combinations
of these parameters affect the carbon content or rank,
which is related to the heat content and hardness (HGI)
properties of the coal.

Headgate Headgate Tailgate Tailgate
Moisture Sulfur Ash_~—s Volatile © Heat «HG dust specific dust specific
content___content content content __content cone dust cone dust
1.000 0.316 --0.365 0.566 = -0.175 -0.387 0.042 -0.032 0.125 0.004 Moisture
(33) (33) 33) (33) G3) 3) 2) 32) (33) (33) content
0.000 0.074 0.037 0.001 0.330 0.026 = 0.818 0.860 0.487 0.982
1,000 0.796 -0.436 = -0.597 0.391 -0.226 = -0.232 -0.302 — -0.234 sulfur
(33) (33) (33) (33) (33) (32) (32) (33) 33) content
0.000 0.000 0.011 0.000 0.024 0.213 0.202 0.088 = 0.190
1.000 -0.531 70.767 0.296 0.404 = -0.427 -0.329 — -0.386 Ash
(33) (33) (33) (33) (32) 32) (33) (33) content
0.000 0.002 0.000 0.944 0.022 0.015 0.061 0.027
1.000 0.211 -0.857 0.199 0.051 0.405 0.201 Volatile
(33) (33) G3) Ga) (32) (33) (33) content
0.000 0.238 0.000 0.275 0.782 0.019 = 0.262
1,000 0.031 0.248 0.358 0.149 0.282 Heat
(33) G3) Gay (32) (33) (33) content
0.000 0.865 0.171 0.044 0.408 = 0.113
1.000 -0.091 0.084 -0.383  -0.099 HGI
33) 2) (32) G3) (33)
0.000 0.622 0.649 0.028 0.583
1,000 0.909 0.483 0.631 Headgate
(32) 32) (32) Gay dust cone
0.000 0.000 0.005 0.000
1.000 0.356 0.709 Headgate
(32) 32) G2) specific
0.000 0.046 0.000 dust
key 1.000 0.757 Tailgate
1,000 Correlation coefficient (r) (33) (33) dust cone
(33) Sample size 0.000 0.000
0.000 significance level (p)
1.000 Tailgate
(33) specific
0.000 dust

Figure 4.—Correlation matrix of seam parameters and dust criteria.



figure 3 shows a frequency histogram of the set of 33 sam-
ples divided into the 5 bituminous groups. Medium- and
high-volatile A bituminous coal are the most common
types of coal in the United States, and the sample data
collected correspond to a normal distribution within this
bituminous class of coal. Table 2 illustrates the use of the
chi-square (x2) statistic to test the hypothesis that the
sample frequency distribution approximates an assumed
normal distribution of bituminous coal in the U.S. coal
provinces (11). The low-volatile and high-volatile C bi-
tuminous coal groups were combined with adjacent groups
because their frequency was below the recommended
group levels for computation of a chi-square test statistic.
The hypothesis could not be rejected at the 95-pet con-
fidence level, so it was believed that a representative sam-
ple of bituminous coal seams was obtained,

Ventilation measurements and other general descriptive
data were collected from each operation. Velocity meas-
urements were made at the dust sampling locations and at
10 support intervals along the face. Headgate, tailgate,
and average face velocity and quantity data are shown in
table A-3 of the appendix. General information of the op-
erations sampled, such as mine location, seam, height, face
width, and cut sequence used, is shown in table A-4 of the
appendix.

15
>
2
& oh 4
2
3S
ied
iri my
8 fot
wo Hi Hl
>
=z
g 1
3

Ob 1,000 — 18,800 — 15,500 758 parc 820 per

Btu Btu Btu

MIDPOINT

Figure 3.—Frequency histogram of coal seam types sampled.

Table 2.—Chi-square (x) test of sample distribution

Bituminous ‘Adjusted Boundary z ‘Area Net Expected Observed
coal Midpoint midpoint &%) oz area frequency —_—frequency
€) (Oi)
10,500Btu 3.18 0.4993)
High-volatileC ... 11,000 Btu
} 12,000 Btu 11,500 Btu 2.14 4838 0.2803 9 8246)
High-volatile BB... 12,250 Btu,
13,000 Btu -58 2190,
High-volatile A... 13,500 Btu 19,500 Btu 3962 13 15
14,000 Btu, 46 A772)
69 pet C
Medium-volatile .. 73.5 pet C}
} 775 pet C 78 pet C 1.87 4693, 3216 " 106 + 4)
Low-volatile ..... 82.0 pet C,
{86 pot C 3.04 4988,
Heat content: X = 13,561 Btu Carbon content: X z= %-)/s
Ss = 962 Btu s 2? = k (Oi- Ei)°/Ei
=
i=1
ZL test H,: Oi = Ei Let a = 0.05 Test over 3 intervals:
Hy Oi # Ei n=33 df = 2, 595 = 5.99
2 2 2
x - Bat + att + font = 0.510

Since xy95 > xcatcuntea “+ Cannot reject H,


INTRODUCTION

Health researchers have strongly suspected a relation-
ship between dust generation and coal seam type, and nu-
merous studies have been conducted over the past 25 years
to identify this relationship. Several researchers have
studied the relationship between coal rank and the preva-
lence of Coal Workers’ Pneumoconiosis (CWP) (I-4).4
Some of these studies found a strong positive correlation
and others found a range of weak to very little positive
correlation. Thus, there is still some uncertainty regarding
the relationship between coal rank and CWP.

Other researchers have conducted laboratory studies on
the relationships between coal rank, macerals, grindability,
and particle size (5-6). These studies have shown conclu-
sively that there is a significant relationship between coal
rank and grindability, and there is a significant relationship
between grindability and amount of respirable-sized par-
ticles found in the product. The relationship between
grindability and particle size is not surprising since the
Hardgrove grindability index (HGI) is based on particle
sizing criteria (7). However, none of these studies actually
related airborne respirable dust to grindability.

After the enactment of the Federal Coal Mine Health
and Safety Act of 1969 in the United States, one field

study by the U.S. Bureau of Mines established mean dust
exposure differences among various occupations in the in-
dustry and another field study by the Bureau showed a sig-
nificant difference in dust exposure for the same occupa-
tions in different coal mines and/or seams (8-9). The
causes of these differences between coal seams could not
be quantified, but the differences indicated that coal seam
characteristics were one of the likely factors responsible.
Under contract to the Bureau, the Southwest Research In-
stitute extensively reviewed the present knowledge of air-
borne respirable dust generation and provided several in-
sightful hypotheses relating coal chemistry and mineralogy
(rank, volatility, and ash) to dust generation (10). Fur-
thermore, Bureau observations on prior longwall dust stud-
ies indicated notable differences in dust levels in various
seams using similar dust control technology. This report
describes a recent underground study to determine if type
of bituminous coal seam is an influential factor in airborne
dust generation. This work is part of the Bureau’s pro-
gram to improve the health of the Nation’s miners by
reducing their exposure to respirable dust.

SURVEY STRATEGY

This investigation focused on surveying longwall mining
operations. Active longwall mining (shearer) sections were
chosen because of the presumed similarities and simplicity
in the face ventilation arrangements (head-to-tail ventila-
tion) for dust sampling. Also, longwall operators’ compli-
ance with the respirable dust standard has recently started
to decline (fig. 1) with continued increases in longwall
production, Many of the traditional types of dust control
technologies are maturing, and further refinement of these
traditional technologies may not provide the additional
effectiveness needed for more advanced, higher production
longwall systems. Therefore, the Bureau is seeking funda-
mental principles relating seam parameters to airborne
dust generation in order to develop and pioneer novel
control technology for reducing the amount of respirable
dust that becomes airborne. This study was the first phase
in identifying any seam parameters associated with air-
borne respirable dust generation for future causal principle
research,

Since a randomized sample was economically impracti-
cal because of the large distances between geographical
areas of the country, a “nonprobability purposive” sampling

“{talie numbers in parentheses refer to items in the list of references
preceding the appendix.

strategy was used. This strategy encompasses drawing a
nonprobability sample that conforms to a certain criterion,

100

@Q

io}
T
L

a
3°
T
1

fe)
T
1

COMPLIANCE, pct

n
io}
T

1

fe)
1980 1982 1984 1986 1988

Figure 1.—Percentage of U.
Federal dust standard.

. longwalls in compliance with the


Table A-2.—Coal characteristics

Heat Moisture Sulfur Ash Volatile
Mine Shift content, content, content, content,! content, HGI
Btu/Ib pet pet pet pet
A.. 1-4 14,092 3.00 3.84 9.60 19.40 125
B.. 1-4 13,651 1.00 86 11.90 29.60 70
c.. 1-4 13,875 1.10 2.04 11.80 37.60 61
D.. 1-5 13,820 1.10 3.68 20.90 40.00 70
E.. 1 13,980 3.03 57 5.36 47.10 48
2 13,944 3.30 A3 4.90 46.10 49
F.. 1 14,897 92 1.06 2.97 39.50 59
G.. 1 13,189 90 1.15 15.00 32.20 59
2 13,855 93 86 10.40 33.10 62
H.. 1 15,074 89 65 2.86 33.40 62
I... 1 13,899 1.85 77 7.47 38.54 47
2 14,195 1.99 84 5.79 38.87 51
J. 1 14,390 1.81 1.17 5.14 38.58 51
2 14,687 1.69 77 3.38 39.41 53
K. 1 14,592 51 50 7.19 19.05 95
2 14,434 AB 51 7.70 19.99 97
L. 1 13,265 1.60 1.84 11.36 38.82 54
2 12,993 1.40 2.13 12.99 36.96 50
M.. 1 13,635 3.03 94 5.07 43.58 56
2 13,875 3.21 92 2.00 41.72 59
N.. 1 12,408 6.12 4 7.53 40.80 53
2 12,845 6.61 29 4.97 42.10 56
O.. 1 12,926 51 3.68 13.47 37.72 61
2 14,268 49 1.80 6.18 40.63 59
P.. 1 10,533 57 5.55 29.23 17.40 79
2 11,079 Pal 3.87 26.53 16.62 82
Q.. 1 14,240 81 441 9.08 21.63 94
R.. 1 13,464 6.19 49 4.88 46.03 49
2 13,635 5.95 51 4.89 47.19 49
S.. 1 13,535 4.31 52 6.43 43.09 43
2 13,026 3.54 AT 10.82 42.72 38
T. 1 12,694 3.72 3.98 12.23 36.76 60
2 12,530 3.44 3.07 13.52 38.65 57

1Dry basis.


Library of Congress Cataloging in Publication Data:

Organiscak, John A.
Relationship of coal seam parameters and airborne respirable dust at longwalls /
by J.A. Organiscak, S.J. Page, and R.A. Jankowski.

P. cm, — (Report of investigations; 9425)

Includes bibliographical references (p. 14).

1. Coal mines and mining—Dust control, 2. Longwall mining—Environmental
aspects—United States, 3. Bituminous coal—United States. 1. Page, Steven J. Il.

Jankowski, Robert A. III. Title. IV. Series: Report of investigations (United
States. Bureau of Mines); 9425.

TN23.U43 —[TN312] 622 s—de20_—-[622.83]_ 92-10263 CIP



0.005 T T T T T

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< .004b 4
2
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oo
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5 fe) 15 20 25 30

ASH CONTENT, pct

Figure 9,—Scatter plot of ash and tailgate specific (normalized) dust.

the scatter plots for the ash and dust data. It appears that
the ash parameter could better fit several decay models
(y = aeTM and y = ax) for both the dust concentrations
and specific (normalized) dust criteria at both the face lo-
cations. The parameters and fit statistics of these models
are shown in tables A-5 and A-6 of the appendix. Explan-
ation of the dust variation can be increased to 70 pct (R?
value) at the headgate and 27 pct at the tailgate with the
y = ax® model. Although the y = ax® model is more effi-
cient than the y = ae*, it is not a valid model because
there is no finite limit to dust generation. Therefore, cau-
tious judgment should be used with parametric modeling
analysis of the survey data because of the fair amount of
data scatter not accounted for by the ash parameter and
because of the limited amount of data at the extreme
ranges of seam types, which can enormously affect the de-
termination of model parameters. The tailgate data were
found to have much more scatter than the headgate data,
which was probably because more source contributions
were measured at the tailgate (shearer and supports).
Since too many uncontrolled and unmeasured parameters
exist in the underground mining environment, controlled
laboratory experiments are recommended to determine the
most reliable and valid model of the ash parameter.

The volatility and dust concentration relationship at the
tailgate was found to be roughly the opposite of the ash
relationship (fig. 10). The volatility data may be better de-
scribed a polynomial model (y = a - bx + cx’). However,
caution again is advised with this type of model determina-
tion because of the data scatter (more scatter than the ash
parameter data) and the low number of points for low-
volatile coals.

Since HGI is usually cited as an indicator of coal seam
dustiness, it has been examined to observe if this pa-
rameter is associated with the airborne respirable dust
measured. The only strong association found was a signifi-
cant negative correlation between HGI and tailgate dust
concentrations (r = -0.38, p = 0.03; see figure 4, the cor-
relation matrix), explaining 14 pct of the dust variation.
This HGI and tailgate dust concentration association also
coincides with the volatile parameter because HGI and
volatile matter are also highly and negatively correlated
(t = - 86, p = 0.00). Figure 11 shows the scatter plot of
HGI versus the tailgate dust concentrations. A decay non-
linear model would probably better describe the associa-
tion, but this analysis is cautioned against because of the
scatter in the data.

Although a negative correlation between HGI and dust
was observed (significant at the 95-pct confidence level),


this relationship is contrary to the speculated from rela-
tionship. The theorized relationship is a positive cor-
relation between HGI and dust generation, derived from
laboratory grinding tests. A potential reason for this dis-
crepancy is that the amount of dust entrained into the
airstream may not be directly proportional to the amount
generated in the product because some other coal seam
parameter affects airborne dust generation or entrainment,
such as ash and/or volatility.

Some other secondary data that support this hypothesis
are the data obtained at two continuous miner sections in
two different coal seams (table 3) (12). These data were
obtained from several individual cuts. The Pittsburgh Coal
Seam had a lower HGI index (61) than the No. 2 gas scam
(70) and less respirable dust measured in the mined prod-
uct. However, the Pittsburgh Seam had a significantly
higher amount of airborne dust (concentrations and per-
cent airborne per amount in product) measured in the re-
turn. Dust concentrations were 300 pet higher and the
portion of airborne dust per respirable dust in run-of-mine
product was 318 pet higher in the Pittsburgh Seam than in
the No. 2 gas seam. Although no proximate analysis was
conducted on these coal samples (not part of the original
study), the No. 2 gas seam generally has a higher ash and
lower volatile content than does the Pittsburgh Seam.
Thus, the authors believe that the amount of airborne res-
pirable dust generated from mechanized cutting may not

SEAM TYPES AND

From this study it was generally concluded that low-ash,
high-volatile coal seams produce more dust. Does this
conclusion explain regional differences found in dust com-
pliance rates throughout the MSHA districts in the coun-
try? To examine this connection, the seam parameters
and dust concentrations (primary data) collected in dif-
ferent geographic provinces were averaged with 95-pct
confidence intervals. MSHA compliance samples (second-
ary data) were also averaged for all longwall operations in
these provinces. Figures 12 and 13 show the average seam
types and dust concentrations measured for the Eastern,
Interior, and Rocky Mountain Coal Provinces in this study,
and figure 14 shows their compliance concentration av-
erages for 1986-88 from MSHA data.

These data show that the average seam parameters and
dust levels do vary between provinces. The Rocky Moun-
tain Province on average has higher volatility and lower
ash coal than the other provinces, This province also
had the highest average dust concentration measured in
this study and the highest average dust concentration
from compliance sampling. The Eastern and Interior

soy

be directly related to HGI as theorized or assumed from
laboratory studies, A National Coal Board study has also
noted, "... stronger coals produce less dust than the weak,
but break more explosively, causing a greater proportion
of the fine dust formed to be dispersed into the air" (13).
Bureau coal-cutting studies in the laboratory have indi-
cated a direct trend between measured peak cutting forces
and airborne respirable dust generation (14). The strong
association of airborne respirable dust to ash and vola-
tility observed from this longwall study indicates that
some causal entrainment phenomena linked to these seam
parameters may be responsible.

Table 3.—Differences In dust generation by continuous
miners In two different coal seams

Coal seam... Pittsburgh No. 2 gas
Seam height .. : 79 61
Number of cuts sampled. 6 4
HGI oe eee tee 61.0205 70.4220
Respirable dust generated in

product . mg/ton.. 458595 5,955879
Airborne re: dust

generated + mg/ton.. 1.32+0.59 0.30.10
Portion . ++ pet.. 0.02340.012 —_0.0055+0.0017
Air quantity. 13,467#2,190 4,121,278

DUST COMPLIANCE

Provinces on average have lower volatility and higher ash
coal seams. These provinces also had lower dust concen-
trations measured in this study and lower average dust

Volatile

KEY
Rocky
Interior
(AY Eastern

20 30 40
CONTENT, pct

Ash

° fe) 50

Figure 12.—Average ash and volatile content of provinces
sampled.


Report of Investigations 9425

Relationship of Coal Seam Parameters and
Airborne Respirable Dust at Longwalls

By J. A. Organiscak, S. J. Page, and R. A. Jankowski

UNITED STATES DEPARTMENT OF THE INTERIOR
Manuel Lujan, Jr., Secretary

BUREAU OF MINES
T S Ary, Director


Mission: As the Nation's principal conservation
agency, the Department of the Interior has respon-
sibility for most of our nationally-owned public
lands and natural and cultural resources. This
includes fostering wise use of our land and water
resources, protecting our fish and wildlife, pre-
serving the environmental and cultural values of
our national parks and historical places, and pro-
viding for the enjoyment of life through outdoor
recreation. The Department assesses our energy
and mineral resources and works to assure that
their development is in the best interests of all
our people. The Department also promotes the
goals of the Take Pride in America campaign by
encouraging stewardship and citizen responsibil-
ity for the public lands and promoting citizen par-
ticipation in their care. The Department also has
a major responsibility for American Indian reser-
vation communities and for people who live in
Island Territories under U.S. Administration.


Examination of all the seam parameters and the air-
borne dust criteria show that ash had the highest correla-
tion (significant at the 95-pct confidence level) with dust
concentration (r = -0.40, p = 0.02) and specific dust
(r = -0.43, p = 0.02) at the headgate sampling location,
explaining 16 and 18 pet (R? values) of the variation, re-
spectively. At the tailgate, volatility had the highest cor-
relation (r = 0.40, p = 0.02) with the dust concentration,
and ash had the highest correlation (r = -0.38, p = 0.03)
with specific dust, explaining 16 and 14 pct of the variation,
respectively. Ash and volatility are significantly and neg-
atively correlated with one another (r = -0.53, p = 0.00),
so the ash was also fairly correlated with dust
concentrations at the tailgate (r = -033, p = 0.06).
Therefore, it was generally concluded that high-volatile,
low-ash coal seams tend to experience higher airborne
respirable dust levels. Several operational parameters
measured (water application, maximum bit depth, etc.)
were found to have insignificant correlations with dust
concentrations, and their associations will not be included
in any further discussions. Figure 5 shows the three-
dimensional scatter plot of ash and volatility with respect
to the dust concentration at the tailgate.

Scatter plots of individual coal seam parameters and
dust (concentration and specific) indicate that indeed ash
and volatility were the parameters with the strongest re-
lationships, and these relationships could be accurately
characterized as nonlinear in nature. Figures 6 to 9 show

x
i}

a

S

o

TAILGATE DUST CONCENTRATION
mg/m?

Figure 5.—Scatter plot of ash content, volatile matter, and tail-
gate dust concentration.

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ASH CONTENT, pet

Figure 6.—Scatter plot of ash and headgate dust concentration.


10

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VOLATILE CONTENT, pct ee
Figure 10.—Scatter plot of volatile matter and tailgate dust concentration.
20 T T T T
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Figure 11.—Scatter plot of HGI and tailgate dust concentration.