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Assessment of quality of New Zealand coals from borecore analyses
Assessment of quality of New Zealand coals from borecore analyses* Vincent R. Gray Cod Research Association of New Zealand (Inc.), PO Box 3041, Wellngton, New Zealand
Methods are needed for predicting the properties of as-mined coals from analyses carried out on borecores. Statistical techniques are described for isolating the mean moisture, coal and mineral properties from sets of laboratory analyses carried out on borecores. Comparisons between mine and borecore samples from the same area can be used to derive general methods for predicting properties of mined coal. This Paper deals with the derivation of moisture, ash, voltaile matter, specific energy and elementary composition of coal and minerals for mined coal from borecore analysis results. (Keywords: coal; chemical analysis; borecores)
Coal prospecting in New Zealand in the past 10 years has more than doubled the estimated coal reserves-to a figure of 4600 x lo6 t. Planning for the extraction and exploitation of the newly discovered coal requires a preliminary assessment of the as-mined coal properties. Most of the available information is in the form of borecore analyses. The borecore, as recovered by drilling, is separated into plies and composites which are sent to the laboratory to be analysed. A larger number of drillholes are studied less rigorously by downhole logging methods. Some of the laboratory measurements are used to calibrate these logs. As it is difficult to know which properties of the coal will be of importance when it is finally utilized, the selection of analyses to be carried out on the borecores is as comprehensive as possible within the limitations of facilities and finance. The most useful guide to the selection of analytical procedures is Australian Standard 2519-1982 ‘Guide to the Evaluation of Hard Coal Deposits using Borehole techniques”. However, very little indication is given in this document on how analytical information from borecores should be processed to predict coal quality when it is mined, particularly for the lower rank coals which constitute >95% of the reserves in New Zealand. This Paper discusses some of the problems of attempting such predictions. There are several respects in which coal properties measured on borecore samples may differ from as-mined coal. Many coal properties as-measured or as-presented represent those of a variable mixture of coal substance, moisture and mineral components. In the absence of weathering and severe variability in maceral composition the coal substance component ofmined coal is likely to be very similar to that of the coal from the borecores. It is the amount of moisture and the amount and nature of the mineral components which are likely to show the greatest difference and thus have the greatest influence on the properties of the coal sample.
MOISTURE In this laboratory coal samples are prepared for analysis in an atmosphere of 20°C and 70% relative humidity. Analyses are determined and reported as in an air-dried condition where the moisture is a standard property from which other moisture conditions can be derived. It is possible to use equilibrium moisture isotherms such as those measured by Budge2 to make this prediction. Figure 1 gives a plot of Budge’s results relating saturation moisture (20°C 100% relative humidity) and air-dried moisture, for a range of New Zealand coals, excluding lignites, for which both equilibrium conditions are difficult to define. Thus, it is possible to predict saturation moisture (SM) from the measured air-dried moisture (ADM) using the regression equation: SM% = 0.755 + 0.811 ADM +0.0194 ADM2
Eight observations, r2 = 0.996. ‘Saturation moisture’ corresponds closely to ‘Moisture holding capacity’ as measured by BS 1016: part 213, where the moisture is measured in an atmosphere at 30°C and 96% relative humidity. Very few measurements have been made by this method in New Zealand, so Equation (1) is a useful means of predicting moisture holding capacity, which can be assumed to be the moisture condition of the coal and mineral components of an inground sample. Mine samples almost invariably contain surface moisture in addition to saturation moisture. The New Zealand Coal Research Association samples coal from all operating mines every year and publishes summaries of average properties4. Figure 1 plots the mean moisture figures (ASM) for slack coal (minus 25 mm) for all New Zealand mines against air-dried moisture (ADM). The best equation (omitting lignites) is: ASM =4.53 + 1.07 ADM%
*
This Paper was presented at the Conference ‘Analytical Methods for Coals, Cokes and Carbons’, London, UK, 28-29 April 1983 OOla-2361/83/09106244$3.00 @ 1983 Butterworth & Co. (Publishers) Ltd
1062
FUEL 1983, Vol62,
September
(1)
(2)
43 observations, r2 = 0.95, SD about regression = 1.55%.
Assessment of New Zealand coal quality: V. R. Gray
BM = bed moisture; and r2 = 0.94. The lower line is a plot of air-dried moisture (ADM) against ash%, air-dried basis (Aad), for which the equation is:
l
a 0
O-
ADM%=21.60-0_214A,,%
(4)
49 observations, r2 = 0.99. The saturation moisture for this coal, pure coal (2% ash) basis is 26.6x, so that the bed-moist figures in the upper curve indicate that the borecore samples contained free or surface moisture. This was confirmed by the geologist’s log which persistently mentioned ‘muddy coal’. It is evident that borecores may not necessarily be in saturation condition. These particular coal measures are in swampy ground and the coal itself is fissured and broken, so that in-ground coal contains free moisture. Figure 2 also includes points representing coal samples from the Kopuku mine. For 76 samples of slack coal mean moisture was 26.6% (SD 1.7%) and mean (moist) ash, 4.0% (SD 0.9%). This moisture is very close to the calculated saturation moisture, 25.7%, as Equations (1) and (2) come close to one another at this value of air-dried moisture. In this case it is evident that the coal undergoes some drying out as it is exposed for opencast mining. As will be shown, an appropriate average ash figure for substitution in Equation (4) will be calculated to dry basis (Ad,,). Equation (4) would have to be modified as follows:
l
O-
'O-
ADM%=(21.60-0.214Ad,)/(1-0.214A,,/100)
I 20 AIT--dried morsture (%) I
10
Figure 1 Plot of as-mined moisture content (0) from New Zealand mines and saturation moisture2 (0) against air-dried moisture
Samples from the mine with >30% moisture were omitted from the regression. Over most of the range covered, the mine moisture is 34% higher than the saturation moisture. Equation (2) can be used to predict mine moisture and can be improved upon by including other relevant variables into the regression. These may include type of mine envisaged (opencast, underground), size and distribution of the coal, local weather conditions, mining methods used (e.g. hydraulic methods) etc. A further improvement in accuracy is obtained by m lking an allowance for the difference in mean ash yield (dry basis) between as-mined coal and coal from borecores, on the air-dried moisture. This is done by plotting air-dried moisture (ADM) against ash (air-dried basis), A,, and deriving the regression line5. An example is given in Figure 2 for the Kopuku mine in the Maramarua coallield. The upper regression line has been drawn through the points from samples from a single borecore, 9121, as recovered from the ground. The equation for 48 observations was : BM% = 33.03 - 0.26 Abm% Where : A,,,,, = ash, bed moist;
(3)
(4a)
The described procedures work fairly well for subbituminous coals and higher ranks but they cannot be applied to lignites. Lignites display a significant moisture hysteresis so it is difficult to define an equilibrium moisture condition and it is difficult to allow the time for an apparent equilibrium to be reached or to be sure that it has been reached. Figure I shows that as-mined moisture content cannot be predicted from air-dried moisture content, even when the latter has been measured correctly. The assumption is made that the saturation moisture content of lignite is the condition in which it has been recovered from a borecore, provided care has been taken
30
;; s t 3 ‘I
x)
P 10
0
0
10
20
30
40
50
60
70
80
90
1c
Figure 2 Plot of moisture content against ash for Kopuku coal, Maramarua coalfield, showing in-ground moisture (upper line) for (0) borecore 9121, (0) air-dried moisture (lower line for borecore 9121). and (0) mine samples, Kopuku mine
FUEL, 1983, Vol62,
September
1063
Assessment of New Zealand coal quality: V. R. Gray
-
Pure coal
.--. 60L” ; 0 50>, +i zd 40: f
30-
s 20-
10-
II
1,
I
20
10
I
I
I
30
40
I
,
I 610
50
Ash (%, dry basis) Figure 3 Plot of percentage carbon (dry basis) against ash (dry basis) for Waimumu lignite
r
Examples of plots for specific energy are given in references 5 and 8 and for volatile matter in reference 5. Volatile matter shows a greater scatter about the regression line than specific energy. Any departure from linearity of the line relating specific energy to ash may indicate a change in coal maceral or mineral composition with increase of ash. With low rank coals the pure coal substance contains inorganic constituents that contribute to the ash. Therefore, there is an ash yield value which is produced entirely by coal constituents, below which no samples can be found, not even by float/sink analysis. The derivation of this ‘pure coal’ ash figure is given below and it is indicated on Figures 3-5. The substitution of this figure in the regression equations for carbon, hydrogen, nitrogen and sulphur gives figures for elementary coal consumption which can be combined from the figures by manipulation of ash constituent data to give the elementary composition of the coal substan&. An example of a plot of percentage carbon against ash (dry basis) is given in Figure 3 for Waimumu lignite. The regression equation is : %C=68.11-0.71/t,,
. .
I
0
10
I
I
20
30
I 40
e
Ash (%, dry bass) Figure 4 Plot of percentage sulphur (dry basis) against ash (dry basis) for seam 4, Mokau coalfield
against drying out or adding moisture. A relationship with ash can be obtained by the same technique to predict bed, or saturation moisture for assumed mean ash yield. COAL PROPERTIES To obtain averages and distribution information on coal properties the moisture and mineral variables must be eliminated from the analyses. A commonly used approximate method for doing this is to calculate the property on a ‘dry, ash-free’ basis. The practice is inaccurate because ‘ash’ is not the same entity as ‘minerals’, or ‘mineral matter’5 - ‘. A preferable practice is to derive ‘dry, mineral matter-free’ properties using one of the many formulae developed for the purpose. The objection here is that the formulae only apply to average coals in a country and they may not apply accurately to the particular set of samples being considered. To eliminate the moisture and ash variables of a set of coals all results are calculated on a dry basis. Then, by regressing against ash, and other relevant variables (sulphur, maceral composition, depth in ground etc.) an equation is obtained from which the value of the property at any designated value of the variables can be calculated. The moist coal property can be calculated using the moisture values derived in the previous paragraph to give an appropriate average property for the coal. Coal properties for which this technique applies are specific energy, volatile matter, carbon, hydrogen, nitrogen and sulphur.
1064
FUEL 1983, Vol 62, September
(5)
Where: r= -0.996; mineral/ash ratio = 1.043; ash yield of pure coal = 4.02 wt%; and carbon content of pure coal = 65.3 wt%. For many New Zealand coals the sulphur levels are low, fairly constant, and predominantly organic. A plot of sulphur (dry basis) against ash (dry basis) should give a means of deducing the sulphur in pure coal, the mean sulphur in the mineral fraction, and an equation for deducing mean sulphur at any ash level. The distribution of sulphur in many New Zealand coals is so irregular that considerable scatter is often shown by such a plot, although the best straight line is usually almost parallel to the ash axis. Some coals from borecores show an effect illustrated in Figure 4 (for seam 4 in the Mokau coallield) where the sulphur appears to reach a maximum figure at an intermediate ash level. Below 20% ash the regression equation is : %S = 1.30 +0.374/t,,
(6)
r=0.63.
but at > 20% ash the relation fails and a line parallel to the ash axis seems more appropriate.
5 ‘I Fwe coal
a z
4-
f 0 c
3-
100
10 Ash
(%,dry
5 4 3 basa)(rec~procal scale)
2
Figure 5 Plot of percentage boric oxide in ash against reciprocal of ash (dry basis) for Waikato coals
Assessment
Medm 50
Medm
II
Mean
Mean
a iz ,40 !F i
V. R. Gray
The regression equations relating ash composition to the reciprocal of ash yield can be used to predict ash composition for coal samples of any known ash yield. By substituting the mean ash yield of a particular mine, predicted by methods of the next section, the ash composition can be predicted. The same principles apply to trace elements. Higher rank coals also display a difference in ash composition with increasing ash yield, but correlation coelIicients are not usually high. Variability with position in a seam or in the coallield may also be significant.
B
A
of New Zealand coal quality:
30 20 10
ASH DISTRIBUTION 0
1 2
3 4
5
6
7
8 9 10 11 12 13 14+ Ash (%, dry basis)
34
5670
Figure 6 Ash histograms for Weavers coal. Comparison between A, borecore; and 8, mine samples
ASH PROPERTIES POSITION
AND
MINERAL
COM-
The composition of high temperature ash gives an indication of the amount and nature of the mineral constituents of the coal, informative analytical techniques being X-ray diffraction and FTIR spectroscopy. The amount of mineral matter present can be obtained from the ash by using the mineral matter:ash ratio deduced from regression equations involving coal propertiess. For low rank coal the ash consists of a mixture of two components, one from the inorganic portion of the pure coal substance and the other from the minerals. The proportion of the two components is a function of the total ash, such that a plot of the percentage of each component against the reciprocal of the ash should give a straight line from which the composition of the coal and mineral fractions can be deduced6T7. The ash yield of pure coal is taken to be the point on the line where percentage silica is zero and the ash yield of pure minerals is given by the previously determined mineral/ash ratio. Examples of plots for silica and calcium are given in reference 7. The degree of scatter about the straight line varies with the element or oxide considered and is an indication of its degree of uniformity in fractions of different ash yield. An example of borate content in Waikato coals, derived from Kear and Ross’ and Mackay lo is given in Figure 5. The equation of the regression line is: %B,O, = - 0.0142 + 8.113/A,,
(7)
59 observations, r = 0.85. Mean ash% of pure coal is 2.0x, so B,O, in pure coal ash is 4.04% (B in pure coal is 0.025%). B,O, in pure minerals (95% ash) is 0.07x, effectively zero. The level of correlation of this equation is such as to conclude that the boron is entirely associated with the coal. The figures for inorganic content of the coal substance obtained from these plots can be combined with the plots for carbon, hydrogen, nitrogen and sulphur to give the elementary composition of the pure coal, from which oxygen may be obtained by difference. The figures for mineral composition can be combined to give a mean composition for the mineral component from which some deductions can be made on the possible individual minerals present+‘.
A histogram of ash yield (dry basis), weighted by ply or seam thickness may be used to predict mean ash yield of a mine sample if it is possible to define how mine samples differ from bore-cores. Figure 6 shows ash histograms for 5 ft (1.5 m) borecore ply samples and mine samples from Weavers Crossing in the Huntly coalfield. It shows the main differences between the two samples. Borecore samples contain a proportion of high ash samples, usually tops and bottoms of seams, which give the distribution a long ‘tail’ and weight the mean ash, so that the mean is > the median. With mine samples (in this case, an opencast mine) there are no very high ash samples, the mean and median are almost identical, but are both greater than the median ash of the borecore sample. The mean ash of the mine sample, 4.6% (dry basis) is approximately halfway between the median (4.0%) and the mean (5.5%) of the borecore samples. By substituting the chosen mean ash value considered appropriate for mine samples into the equations relating the various coal properties to ash, deduced by previous methods, it is possible to predict mean properties of mine samples. The first step is to deduce specific energy, volatile matter, sulphur, on a dry basis, and then convert to the appropriate moist basis. CONCLUSIONS This paper has dealt with techniques for deriving only a few properties of mined coal. Further studies are required on washability characteristics, swelling and coking properties, breakage, grindability and abrasion, ash fusion temperatures and maceral and lithotypes composition. Similar techniques involving computer-based statistics can be applied. The calculations have been made on a T158 programmable calculator and on a VAX computer using the ‘MINITAB’ statistical package.
REFERENCES
5 6
8 9 10
Australian Standard 2519-1982 ‘Guide to the evaluation of Hard Coal Deposits using Borehole Techniques’, Standards Association of Australia, Sydney Budge, C. F. NZ J. Sci. 1972, 15, 39 British Standard 1016: Part 21: 1981, (IS0 1018-1975) ‘Hard Coal Determination of Moisture Holding Capacity’ Daly, T. A. ‘Analysis of Industrial Coals 197%80’, 1981 Coal Research Association of New Zealand (Inc.), Wellington Gray, V. R. Fuel 1980,59, 551 Gray, V. R. Fuel 1981,60, 362 Gray, V. R. and Daly, T. A. NZ J. Sci. 1981,24, 179 Gray, V. R. Fuel 1983,62,94 Kear, D. and Ross, J. B. NZ J. Sci. 1961, 4, 360 Mackay, M. A. and Wilson, B. I. NZ. J. Sci. 1978,21, 611
FUEL, 1983, Vol62,
September
1065
Methods are needed for predicting the properties of as-mined coals from analyses carried out on borecores. Statistical techniques are described for isolating the mean moisture, coal and mineral properties from sets of laboratory analyses carried out on borecores. Comparisons between mine and borecore samples from the same area can be used to derive general methods for predicting properties of mined coal. This Paper deals with the derivation of moisture, ash, voltaile matter, specific energy and elementary composition of coal and minerals for mined coal from borecore analysis results. (Keywords: coal; chemical analysis; borecores)
Coal prospecting in New Zealand in the past 10 years has more than doubled the estimated coal reserves-to a figure of 4600 x lo6 t. Planning for the extraction and exploitation of the newly discovered coal requires a preliminary assessment of the as-mined coal properties. Most of the available information is in the form of borecore analyses. The borecore, as recovered by drilling, is separated into plies and composites which are sent to the laboratory to be analysed. A larger number of drillholes are studied less rigorously by downhole logging methods. Some of the laboratory measurements are used to calibrate these logs. As it is difficult to know which properties of the coal will be of importance when it is finally utilized, the selection of analyses to be carried out on the borecores is as comprehensive as possible within the limitations of facilities and finance. The most useful guide to the selection of analytical procedures is Australian Standard 2519-1982 ‘Guide to the Evaluation of Hard Coal Deposits using Borehole techniques”. However, very little indication is given in this document on how analytical information from borecores should be processed to predict coal quality when it is mined, particularly for the lower rank coals which constitute >95% of the reserves in New Zealand. This Paper discusses some of the problems of attempting such predictions. There are several respects in which coal properties measured on borecore samples may differ from as-mined coal. Many coal properties as-measured or as-presented represent those of a variable mixture of coal substance, moisture and mineral components. In the absence of weathering and severe variability in maceral composition the coal substance component ofmined coal is likely to be very similar to that of the coal from the borecores. It is the amount of moisture and the amount and nature of the mineral components which are likely to show the greatest difference and thus have the greatest influence on the properties of the coal sample.
MOISTURE In this laboratory coal samples are prepared for analysis in an atmosphere of 20°C and 70% relative humidity. Analyses are determined and reported as in an air-dried condition where the moisture is a standard property from which other moisture conditions can be derived. It is possible to use equilibrium moisture isotherms such as those measured by Budge2 to make this prediction. Figure 1 gives a plot of Budge’s results relating saturation moisture (20°C 100% relative humidity) and air-dried moisture, for a range of New Zealand coals, excluding lignites, for which both equilibrium conditions are difficult to define. Thus, it is possible to predict saturation moisture (SM) from the measured air-dried moisture (ADM) using the regression equation: SM% = 0.755 + 0.811 ADM +0.0194 ADM2
Eight observations, r2 = 0.996. ‘Saturation moisture’ corresponds closely to ‘Moisture holding capacity’ as measured by BS 1016: part 213, where the moisture is measured in an atmosphere at 30°C and 96% relative humidity. Very few measurements have been made by this method in New Zealand, so Equation (1) is a useful means of predicting moisture holding capacity, which can be assumed to be the moisture condition of the coal and mineral components of an inground sample. Mine samples almost invariably contain surface moisture in addition to saturation moisture. The New Zealand Coal Research Association samples coal from all operating mines every year and publishes summaries of average properties4. Figure 1 plots the mean moisture figures (ASM) for slack coal (minus 25 mm) for all New Zealand mines against air-dried moisture (ADM). The best equation (omitting lignites) is: ASM =4.53 + 1.07 ADM%
*
This Paper was presented at the Conference ‘Analytical Methods for Coals, Cokes and Carbons’, London, UK, 28-29 April 1983 OOla-2361/83/09106244$3.00 @ 1983 Butterworth & Co. (Publishers) Ltd
1062
FUEL 1983, Vol62,
September
(1)
(2)
43 observations, r2 = 0.95, SD about regression = 1.55%.
Assessment of New Zealand coal quality: V. R. Gray
BM = bed moisture; and r2 = 0.94. The lower line is a plot of air-dried moisture (ADM) against ash%, air-dried basis (Aad), for which the equation is:
l
a 0
O-
ADM%=21.60-0_214A,,%
(4)
49 observations, r2 = 0.99. The saturation moisture for this coal, pure coal (2% ash) basis is 26.6x, so that the bed-moist figures in the upper curve indicate that the borecore samples contained free or surface moisture. This was confirmed by the geologist’s log which persistently mentioned ‘muddy coal’. It is evident that borecores may not necessarily be in saturation condition. These particular coal measures are in swampy ground and the coal itself is fissured and broken, so that in-ground coal contains free moisture. Figure 2 also includes points representing coal samples from the Kopuku mine. For 76 samples of slack coal mean moisture was 26.6% (SD 1.7%) and mean (moist) ash, 4.0% (SD 0.9%). This moisture is very close to the calculated saturation moisture, 25.7%, as Equations (1) and (2) come close to one another at this value of air-dried moisture. In this case it is evident that the coal undergoes some drying out as it is exposed for opencast mining. As will be shown, an appropriate average ash figure for substitution in Equation (4) will be calculated to dry basis (Ad,,). Equation (4) would have to be modified as follows:
l
O-
'O-
ADM%=(21.60-0.214Ad,)/(1-0.214A,,/100)
I 20 AIT--dried morsture (%) I
10
Figure 1 Plot of as-mined moisture content (0) from New Zealand mines and saturation moisture2 (0) against air-dried moisture
Samples from the mine with >30% moisture were omitted from the regression. Over most of the range covered, the mine moisture is 34% higher than the saturation moisture. Equation (2) can be used to predict mine moisture and can be improved upon by including other relevant variables into the regression. These may include type of mine envisaged (opencast, underground), size and distribution of the coal, local weather conditions, mining methods used (e.g. hydraulic methods) etc. A further improvement in accuracy is obtained by m lking an allowance for the difference in mean ash yield (dry basis) between as-mined coal and coal from borecores, on the air-dried moisture. This is done by plotting air-dried moisture (ADM) against ash (air-dried basis), A,, and deriving the regression line5. An example is given in Figure 2 for the Kopuku mine in the Maramarua coallield. The upper regression line has been drawn through the points from samples from a single borecore, 9121, as recovered from the ground. The equation for 48 observations was : BM% = 33.03 - 0.26 Abm% Where : A,,,,, = ash, bed moist;
(3)
(4a)
The described procedures work fairly well for subbituminous coals and higher ranks but they cannot be applied to lignites. Lignites display a significant moisture hysteresis so it is difficult to define an equilibrium moisture condition and it is difficult to allow the time for an apparent equilibrium to be reached or to be sure that it has been reached. Figure I shows that as-mined moisture content cannot be predicted from air-dried moisture content, even when the latter has been measured correctly. The assumption is made that the saturation moisture content of lignite is the condition in which it has been recovered from a borecore, provided care has been taken
30
;; s t 3 ‘I
x)
P 10
0
0
10
20
30
40
50
60
70
80
90
1c
Figure 2 Plot of moisture content against ash for Kopuku coal, Maramarua coalfield, showing in-ground moisture (upper line) for (0) borecore 9121, (0) air-dried moisture (lower line for borecore 9121). and (0) mine samples, Kopuku mine
FUEL, 1983, Vol62,
September
1063
Assessment of New Zealand coal quality: V. R. Gray
-
Pure coal
.--. 60L” ; 0 50>, +i zd 40: f
30-
s 20-
10-
II
1,
I
20
10
I
I
I
30
40
I
,
I 610
50
Ash (%, dry basis) Figure 3 Plot of percentage carbon (dry basis) against ash (dry basis) for Waimumu lignite
r
Examples of plots for specific energy are given in references 5 and 8 and for volatile matter in reference 5. Volatile matter shows a greater scatter about the regression line than specific energy. Any departure from linearity of the line relating specific energy to ash may indicate a change in coal maceral or mineral composition with increase of ash. With low rank coals the pure coal substance contains inorganic constituents that contribute to the ash. Therefore, there is an ash yield value which is produced entirely by coal constituents, below which no samples can be found, not even by float/sink analysis. The derivation of this ‘pure coal’ ash figure is given below and it is indicated on Figures 3-5. The substitution of this figure in the regression equations for carbon, hydrogen, nitrogen and sulphur gives figures for elementary coal consumption which can be combined from the figures by manipulation of ash constituent data to give the elementary composition of the coal substan&. An example of a plot of percentage carbon against ash (dry basis) is given in Figure 3 for Waimumu lignite. The regression equation is : %C=68.11-0.71/t,,
. .
I
0
10
I
I
20
30
I 40
e
Ash (%, dry bass) Figure 4 Plot of percentage sulphur (dry basis) against ash (dry basis) for seam 4, Mokau coalfield
against drying out or adding moisture. A relationship with ash can be obtained by the same technique to predict bed, or saturation moisture for assumed mean ash yield. COAL PROPERTIES To obtain averages and distribution information on coal properties the moisture and mineral variables must be eliminated from the analyses. A commonly used approximate method for doing this is to calculate the property on a ‘dry, ash-free’ basis. The practice is inaccurate because ‘ash’ is not the same entity as ‘minerals’, or ‘mineral matter’5 - ‘. A preferable practice is to derive ‘dry, mineral matter-free’ properties using one of the many formulae developed for the purpose. The objection here is that the formulae only apply to average coals in a country and they may not apply accurately to the particular set of samples being considered. To eliminate the moisture and ash variables of a set of coals all results are calculated on a dry basis. Then, by regressing against ash, and other relevant variables (sulphur, maceral composition, depth in ground etc.) an equation is obtained from which the value of the property at any designated value of the variables can be calculated. The moist coal property can be calculated using the moisture values derived in the previous paragraph to give an appropriate average property for the coal. Coal properties for which this technique applies are specific energy, volatile matter, carbon, hydrogen, nitrogen and sulphur.
1064
FUEL 1983, Vol 62, September
(5)
Where: r= -0.996; mineral/ash ratio = 1.043; ash yield of pure coal = 4.02 wt%; and carbon content of pure coal = 65.3 wt%. For many New Zealand coals the sulphur levels are low, fairly constant, and predominantly organic. A plot of sulphur (dry basis) against ash (dry basis) should give a means of deducing the sulphur in pure coal, the mean sulphur in the mineral fraction, and an equation for deducing mean sulphur at any ash level. The distribution of sulphur in many New Zealand coals is so irregular that considerable scatter is often shown by such a plot, although the best straight line is usually almost parallel to the ash axis. Some coals from borecores show an effect illustrated in Figure 4 (for seam 4 in the Mokau coallield) where the sulphur appears to reach a maximum figure at an intermediate ash level. Below 20% ash the regression equation is : %S = 1.30 +0.374/t,,
(6)
r=0.63.
but at > 20% ash the relation fails and a line parallel to the ash axis seems more appropriate.
5 ‘I Fwe coal
a z
4-
f 0 c
3-
100
10 Ash
(%,dry
5 4 3 basa)(rec~procal scale)
2
Figure 5 Plot of percentage boric oxide in ash against reciprocal of ash (dry basis) for Waikato coals
Assessment
Medm 50
Medm
II
Mean
Mean
a iz ,40 !F i
V. R. Gray
The regression equations relating ash composition to the reciprocal of ash yield can be used to predict ash composition for coal samples of any known ash yield. By substituting the mean ash yield of a particular mine, predicted by methods of the next section, the ash composition can be predicted. The same principles apply to trace elements. Higher rank coals also display a difference in ash composition with increasing ash yield, but correlation coelIicients are not usually high. Variability with position in a seam or in the coallield may also be significant.
B
A
of New Zealand coal quality:
30 20 10
ASH DISTRIBUTION 0
1 2
3 4
5
6
7
8 9 10 11 12 13 14+ Ash (%, dry basis)
34
5670
Figure 6 Ash histograms for Weavers coal. Comparison between A, borecore; and 8, mine samples
ASH PROPERTIES POSITION
AND
MINERAL
COM-
The composition of high temperature ash gives an indication of the amount and nature of the mineral constituents of the coal, informative analytical techniques being X-ray diffraction and FTIR spectroscopy. The amount of mineral matter present can be obtained from the ash by using the mineral matter:ash ratio deduced from regression equations involving coal propertiess. For low rank coal the ash consists of a mixture of two components, one from the inorganic portion of the pure coal substance and the other from the minerals. The proportion of the two components is a function of the total ash, such that a plot of the percentage of each component against the reciprocal of the ash should give a straight line from which the composition of the coal and mineral fractions can be deduced6T7. The ash yield of pure coal is taken to be the point on the line where percentage silica is zero and the ash yield of pure minerals is given by the previously determined mineral/ash ratio. Examples of plots for silica and calcium are given in reference 7. The degree of scatter about the straight line varies with the element or oxide considered and is an indication of its degree of uniformity in fractions of different ash yield. An example of borate content in Waikato coals, derived from Kear and Ross’ and Mackay lo is given in Figure 5. The equation of the regression line is: %B,O, = - 0.0142 + 8.113/A,,
(7)
59 observations, r = 0.85. Mean ash% of pure coal is 2.0x, so B,O, in pure coal ash is 4.04% (B in pure coal is 0.025%). B,O, in pure minerals (95% ash) is 0.07x, effectively zero. The level of correlation of this equation is such as to conclude that the boron is entirely associated with the coal. The figures for inorganic content of the coal substance obtained from these plots can be combined with the plots for carbon, hydrogen, nitrogen and sulphur to give the elementary composition of the pure coal, from which oxygen may be obtained by difference. The figures for mineral composition can be combined to give a mean composition for the mineral component from which some deductions can be made on the possible individual minerals present+‘.
A histogram of ash yield (dry basis), weighted by ply or seam thickness may be used to predict mean ash yield of a mine sample if it is possible to define how mine samples differ from bore-cores. Figure 6 shows ash histograms for 5 ft (1.5 m) borecore ply samples and mine samples from Weavers Crossing in the Huntly coalfield. It shows the main differences between the two samples. Borecore samples contain a proportion of high ash samples, usually tops and bottoms of seams, which give the distribution a long ‘tail’ and weight the mean ash, so that the mean is > the median. With mine samples (in this case, an opencast mine) there are no very high ash samples, the mean and median are almost identical, but are both greater than the median ash of the borecore sample. The mean ash of the mine sample, 4.6% (dry basis) is approximately halfway between the median (4.0%) and the mean (5.5%) of the borecore samples. By substituting the chosen mean ash value considered appropriate for mine samples into the equations relating the various coal properties to ash, deduced by previous methods, it is possible to predict mean properties of mine samples. The first step is to deduce specific energy, volatile matter, sulphur, on a dry basis, and then convert to the appropriate moist basis. CONCLUSIONS This paper has dealt with techniques for deriving only a few properties of mined coal. Further studies are required on washability characteristics, swelling and coking properties, breakage, grindability and abrasion, ash fusion temperatures and maceral and lithotypes composition. Similar techniques involving computer-based statistics can be applied. The calculations have been made on a T158 programmable calculator and on a VAX computer using the ‘MINITAB’ statistical package.
REFERENCES
5 6
8 9 10
Australian Standard 2519-1982 ‘Guide to the evaluation of Hard Coal Deposits using Borehole Techniques’, Standards Association of Australia, Sydney Budge, C. F. NZ J. Sci. 1972, 15, 39 British Standard 1016: Part 21: 1981, (IS0 1018-1975) ‘Hard Coal Determination of Moisture Holding Capacity’ Daly, T. A. ‘Analysis of Industrial Coals 197%80’, 1981 Coal Research Association of New Zealand (Inc.), Wellington Gray, V. R. Fuel 1980,59, 551 Gray, V. R. Fuel 1981,60, 362 Gray, V. R. and Daly, T. A. NZ J. Sci. 1981,24, 179 Gray, V. R. Fuel 1983,62,94 Kear, D. and Ross, J. B. NZ J. Sci. 1961, 4, 360 Mackay, M. A. and Wilson, B. I. NZ. J. Sci. 1978,21, 611
FUEL, 1983, Vol62,
September
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