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Clarkes for Carbonaceous biolithes

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Estimations of Clarkes for Carbonaceous biolithes: World averages for trace
element contents in black shales and coals
Article in International Journal of Coal Geology · April 2009
DOI: 10.1016/j.coal.2009.01.002
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International Journal of Coal Geology 78 (2009) 135–148
Contents lists available at ScienceDirect
International Journal of Coal Geology
j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / i j c o a l g e o
Estimations of Clarkes for Carbonaceous biolithes: World averages for trace element
contents in black shales and coals
M.P. Ketris, Ya.E. Yudovich ⁎
Institute of Geology, Komi Scientific Center, Ural Branch of the Russian Academy of Sciences, 167023 Syktyvkar, Morozova st., 100, ap. 49, Russia
a r t i c l e
i n f o
Article history:
Received 27 October 2008
Received in revised form 1 January 2009
Accepted 6 January 2009
Available online 14 January 2009
Keywords:
Metalliferous black shales
Coal
Geochemistry
Trace elements
World average contents (black shale and coal
Clarke values)
a b s t r a c t
Black shale and coal Clarke values are the average trace element contents in the World black shales and coals.
These calculations are made in Russian geochemistry but up to now are poorly known in the West.
Modern tables of black shale and coal Clarkes are presented, based on comprehensive calculations using very large
amount of information (thousands analyses of black shales, coals, and coal ashes for trace elements). In black shale
geochemistry, three figures were calculated for each main lithologies: terrigenous (+tuff), chert, and carbonate.
Two Clarke estimations are presented, named “lithological” (K1) and “lithostratigraphical” (K2). In coal
geochemistry, seven figures were calculated for each trace element: average content in hard coals and their
ashes; average content in brown coals and their ashes; average content in all coals and their ashes; and coal
affinity index (or “coalphile index”) = average content in all ashes/Clarke values of sedimentary rocks.
The black shale and coal Clarkes presented here provide an important scientific base for many geochemical
comparisons and issues.
© 2009 Elsevier B.V. All rights reserved.
1. Introduction
1.2. Some history
In 1923, the famous Russian geochemist A.E.Fersman1 introduced the
term “clark” (= Clarke, in English), in honor of the prominent American
scientist, one of the founders of geochemistry, F.W.Clarke (who worked
many years as Chief Chemist at U.S. Geol. Survey), who first calculated
average composition of various rocks, and later, the Earth's crust.
In black shale geochemistry, a well-known estimation of average
contents of trace elements in black shales was made by Vine and
Tourtelot (1970). Their calculations, using 20 U.S. Phanerozoic black
shale units, have been widely cited (by many researchers) because
there were no other estimations.
But, it is desirable to use more comprehensive world-wide data for
more accurate conclusions. Our calculations are based on tens of
thousands of analyses employing hundreds of sample mean values.
Statistical processing of the data supported new Clarke estimations
which seem to be more plausible.
In coal geochemistry, there are known some attempts to calculate
coal Clarkes for several trace elements. The first calculations were
made by the Norwegian-German geochemist, another founder of
geochemistry3, Goldschmidt (1935), at start of the 1930s. Goldschmidt
organized systematical analyses of some European coals for trace
elements, using modern (for that time) analytical methods – emission
spectrographic and X-ray fluorescence analyses. Goldschmidt's estimations of trace element average contents for “ordinary” (common)
and “enriched” coal ashes were, for many consequent years, the
“compass” for geochemists dealing with coal.
Later, we find some averages in studies by Krauskopf (1955) and
Bethell (1962). The first wide (including most trace elements and most
1.1. Meaning of the Russian term Clarke
Fersman defined “Clarke” as the average content of given chemical
element in the Earth's crust and also in the hydrosphere. This term very
soon took root in Russian literature, but, up to now, is nearly unknown
to Western researchers2. With time, however, a sense of the term was
strongly extended: many other geochemical averages were named as
“Clarkes”, for example, “Clarkes of granites”, “Clarkes of basalts”,
“Clarkes of sedimentary rocks”, etc., including “coal Clarkes”, i.e.
average trace element contents in the World coals. For example, coal
Clarke of Ge is 3.0 ± 0.3 ppm (hard coals) and 2.0 ± 0.2 ppm (brown
coals) (Yudovich and Ketris, 2004).
⁎ Corresponding author. Tel.: +7 821 31 19 24.
E-mail addresses: yudovich@geo.komisc.ru, EYuYa@yandex.ru (Y.E. Yudovich).
1
Fersman was the first, who gave a lecture course “Geochemistry” (Moscow, 1912).
Later, he created many fundamental proceedings on geochemistry, for example,
“Pegmatites” (1931), “Geochemistry” (4 volumes, 1933–1939), etc.
2
That is why, in our articles in As or Hg in coal (Yudovich and Ketris, 2005a,b), the
terms like “coal Clarke of As” need obligatory the special explanation for the Western
reader.
0166-5162/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.coal.2009.01.002
3
Two other founders of geochemistry, new science of 20th century, were Russian
scientists, V.I.Vernadski and his follower, A.E.Fersman.
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Fig. 1. Structure of the scientific field in black shales geochemistry. The areas with neighboring overlaps are shaded (Yudovich and Ketris, 1994, p. 4; 1997, p. 5).
World coals) calculation of coal Clarkes was performed in the USSR
(Yudovich et al., 1972). Later, Valkovič's (1983a,b) estimations (based
on U.S. figures, but including some others) were developed.
Valkovič (1983a,b) used frequency histograms for statistical
evaluations of averages. It is a very useful working procedure, and it
was independently widely used in our new calculations (Yudovich
et al., 1985). The estimations based on thousands of analyses, were
made as four figures for each trace element: (1, 2) for hard coals and
their ashes, and (3,4) for brown coals and their ashes. These new coal
Clarke figures (with detailed explanation of stepped calculation
procedure), were cited in Russian, East European, Indian, and Chinese
studies for many years.
Unfortunately, it was in a Russian-language book, and for this
reason, our figures remained practically unknown to the most
Western researchers. Swaine (1990) published his excellent outline
on trace elements in coal. He tried to embrace all the World coals, but
his outline had large omissions of the East (Soviet) Block coals. It is of
note, Swaine's world estimation were, as a rule, rough interval values;
for example, as 10–40 ppm (and not, say, as 16 ± 5 ppm, where ±5 ppm
means statistical standard deviation).
In last decades of 20th century, great changes appeared in coal
geochemistry due to environmental problems caused by wider
consumption of coal in electric power plants. This enlarged demand
for coal created abundant new geochemical studies, with analyses of
coal on toxic elements, such as Be, Hg, Cd, Pb, As, Sb, Se, Cr, Mn, U, and
some others. In addition, coal mining sharply increased in developing
countries, such as Spain, Turkey, Greece, China, India, Brazil, Peru, and
Nigeria, among others. These coals have been analyzed using wide
international cooperation, for example, with U.S. Geological Survey,
using modern analytical equipment.
Therefore, the amount of coal-trace-element figures has greatly
increased. The U.S. Geological Survey created their “Coal Quality
(COALQUAL) Database” (Bragg et al., 1998), with more than 13,000
analyses for most trace elements. Finally, in recent decades, due to
mostly Russian researchers (V.V. Seredin, S.I. Arbuzov and some
others), the old problem became again actual: coal as industrial
resource of trace elements (Sc, Ge, REE, Nb, Ta, Re, Au, and platinum
group elements, PGE) (Arbuzov et al., 2000, 2003; Zharov et al., 1996;
Seredin and Shpirt, 1995; Seredin and Finkelman, 2008).
All the latter work necessitates new coal Clarkes calculation.
2. Estimation of trace elements Clarkes for black shales
The so called “black shales” (sedimentary rocks enriched in Corg)
are of great interest to geochemists, lithologists, paleontologists,
mineralogists, ore prospectors, and oil geologists, chemists, and
technologists in the field of oil shale industry (Fig. 1).
For a geochemist, black shales are anomalous rocks enriched in P,
U, Mo, V, Re, Se, Zn, Hg, and some other trace elements. For a
lithologist, they are unusual sedimentary rocks, mixtures of organic
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and inorganic matter at varying ratios. The inorganic matter may be of
almost any composition: clay, silt, sand, carbonate, chert, phosphate,
tuff, and may be deposited in nearly any facies. For a stratigrapher and
paleontologist, in general, black shales present special stages in the
history of sedimentary shell. For an ore prospector, black shale (or oil
shale) species are the most likely oil-productive source beds. Finally,
so called oil shales are also black shales containing “shale oil”, which
can be extracted by means of pyrolysis. World “oil shale” reserves
exceed petroleum reserves.
All the topics above mentioned account for abundant references on
black shale (and oil shale) geochemistry and geology. Many scientific
congresses, symposiums, and workshops took place on these
problems. For example, a symposium “Geochemistry, Mineralogy
and Lithology of Black Shales” was held in 1987 in Syktyvkar (Russia)
under the direction of the second author. Of special note was the
UNESCO International Geological Correlation Program Project 254,
entitled “Metalliferous Black Shales”.
As a result, two of our Russian monographs were published
(Yudovich and Ketris, 1988, 1994), and also short English outline with
huge bibliography (Yudovich and Ketris, 1997). In the 1994-monograph, Clarke estimations for more than 60 trace elements in black
shales were first calculated. Such calculations are difficult because of
lithological diversity of black shales, among other reasons.
137
2.1. An “ideal” information file
Such a file should include answers to the following questions:
-
where were the samples taken from?
what is the correct name of the rock?
what is the correct stratigraphic position of the rock samples?
what are the analytical errors and accuracy?
how many rock samples were analyzed?
Such informational “ideal” is hardly achievable in most cases; as a
rule, some information is not available in literature. As an example,
information about Corg content was often lacking, although it is crucial
for geochemical conclusions. As there are no Corg data, rough Corg
estimation may be made using chemical analysis data (Yudovich and
Ketris, 1988, p. 29).
2.2. Calculation method
All calculation procedures may be divided into several stages
(Yudovich and Ketris, 1994):
1) formation of so called “primary statistical samples”; 2)
calculation of common median and its standard deviation; 3)
estimation of geochemical background and geochemical anomalies;
Fig. 2. Common median calculation (± standard deviation, shaded column): the example is for uranium in black shales (Yudovich and Ketris, 1994, p. 44; 1997, p. 31). Each point
represents one “primary statistical sample”. Q1 and Q2 are first and third quartilies of frequency distribution. Black shale lithologies: 1 – carbonate, 2 – clay, 3 – silt and sand, 4 – chert,
5 – tuff, 6 – phosophate, 7 – shale of unclear lithology.
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4) formation of so-called “second statistical samples”; 5) “lithological
Clarke K1” estimation; 6) “lithostratigraphic Clarke K2” estimation.
2.2.1. “Primary statistical samples” and common median calculations
As a base (the “elementary unit”) for calculations, “a primary
sample” was used. The primary sample is a group of analyses of
lithologies representing to certain stratigraphic unit of some region.
For example: “Lower Carboniferous (=Mississippian) black cherts of the
Pai-Khoi”. We dealt with two different situations.
First: primary samples were already available from the literature as
average values. Such samples were sometimes heterogenous; for
instance, “carbonates + claystones”, although such rocks are known to
widely differ in trace elements content. Further, some data recorded in
Soviet references were average values for entire sedimentary
sequences, the so called “carbonaceous formations” (Sozinov et al.,
1988).4 The term itself is not clearly defined and the averages cannot
geochemical applications.
Second: primary statistical samples were not found in the
literature, but analyses were available for statistical processing.
Recalling the above mentioned information about geological age,
lithologies etc., the primary sample averages may be obtained. Given
considerable data dispersion, we applied mean median calculations,
while at small dispersions simple arithmetic means were calculated.
Then “common medians” were graphically estimated. Each point
of such graph represents one primary sample mean. The points are
plotted on horizontal lines representing a certain stratigraphic level
each (Fig. 2).
The following step is a common median standard deviation
calculation:
pffiffiffiffiffi
δMe = ðQ3 − Q1 Þ=2 N;
ð1Þ
where:
- N is number of points (=primary samples),
- Q1 and Q3 are the first and the third quartiles of frequency
distribution.
The median was tabulated in the form of Me ± δMe. The standard of
the primary frequency distribution, δx, was calculated as:
δx = Q3 − Me
ð2Þ
The geochemical background value (GB) is a frequency distribution
part limited by the first and the third quartiles:
GB = Q3 − Q1
ð3Þ
Hence, 50% of primary sample means constitute a geochemical
background. Positive geochemical anomalies (A) are determined by
adding standard deviations to the common median:
A0 = Q3 = Me + 1δx ðqanomalyqÞ
A1 = Q3 + 1δx = Me + 2δx ðqstrong anomalyqÞ
A2 = Q3 + 2δx = Me + 3δxðqvery strong anomalyqÞ
ð4Þ
ð5Þ
ð6Þ
Common median and quartiles values allow estimation of “true”
element distribution in black shales. The median is particularly con-
venient because its value is little influenced by individual extreme
values, when a data population is large enough.
It is clear, however, that common median cannot be used for Clarke
estimations because it is dependent on the available set of data. Some
black shales have been studied in detail and described in numerous
geochemical publications. Others, on the contrary, are poorly known,
hence they are represented only as few points (=primary samples
means) on the graphs. For this reason, the common median value is
more affected by better studied black shales than by less studied ones.
A good example is Goldschmidt's reports on average values for
West Europian coals. They had been cited for a long time as Clarke
values for coals worlwide. But, as was subsequently shown, the
average values proved inflated since geochemistry of West European
coals is sharply anomalous (Yudovich et al., 1985).
2.2.2. “Second statistical samples” and “lithostratigraphic subclarkes”
The following calculation step is averaging primary sample means
belonging to a given age, region, and lithology. Several primary
samples thus grouped make up a “secondary sample”, giving an
opportunity to calculate “lithological subclarkes”. Unfortunately,
scantiness of lithological information, typical for many geochemical
reports, brought us to employ it in a very rough form: lithologies were
restricted to the following three: carbonates, cherts, and terrigenous
rocks, even without classifying the latter into clastic and clayey ones.
The rocks of volcanic-sedimentary origin were grouped within one of
the three types, more, however, with terrigenous rocks. Phosphate
rocks needed to be distinguished for some elements (P, Sr, U).
“Lithological subclarkes” were calculated for the following stratigraphic levels:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Recent + Holocene
Paleogene + Neogene
Cretaceous
Jurassic
Triassic + Permian
Carboniferous (Mississippian + Pennsylvanian)
Devonian
Silurian
Ordovician
Cambrian
Vendian
Riphean = Upper Precambrian
Karelian (Aphebian) = Middle Precambrian
Upper Archean and 15. Lower Archean = Lower Precambrian
These 15 units constitute four larger stratons: Phanerozoan
(including Vendian, or “Eocambrian” according to Salop, 1982),
Upper, Middle, and Lower Precambrian.
It is necessary to average the means of the litologies (=second
statistical samples) in order to obtain “lithostratigraphic subclarkes”.
For example, data set named “Carboniferous Black Shales” consists of:
two carbonate samples (20 analyses),
five chert samples (143 analyses),
19 terrigenous (+volcanic-sedimentary) samples (950 analyses).
Obviously, calculation of arithmetic mean by lithologies would be
incorrect since of Carboniferous subdivisions are different in thickness. Hence, straton means must be “weighted” for abundance of
lithologies. For weight coefficients we used values recommended by
A.I. Yeliseev (1997, oral communication)5:
cherts : carbonates : terrigenous rocks = 0:2 : 0:3 : 0:5
4
It is necessary to note, that the term “formation” in Russian geological literature
has a different meaning than in the West. “Formations” as understood in Russia are
nearly equal to “assemblages”; they denote much thicker stratigraphic units than
implied by American usage. What is meant by “formation” in the USA is close to
“member” in Russia (“sveeta” or свита in Russian).
ð7Þ
5
These values are based on an extended study of the Russian plate/the Urals
boundary zone [Eliseev, 1978, 1982; Puchkov, 1979].
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If phosphate rocks are present, carbonates make up 0.29 and phosphates 0.01.
For example, mean Zn contents for Carboniferous carbonates,
cherts, and terrigenous rocks make up 440, 400, and 160 ppm
respectively. As a result, the weighted mean for Carboniferous black
shales (“lithostratigraphic subclarke”) may calculated as follows:
K2 ðCarboniferousÞ = 0:3 × 440 + 0:2 × 400 + 0:5 × 160 = 280 ppm:
ð8Þ
2.2.3. “Lithological Clarke K1” estimation
Having lithologic averages for each straton (for example, “mean Zn
content in Carboniferous cherts”), one may calculate “common
lithological Clarke K1” as shown in Fig. 3, left.
First, lithologic subclarkes are calculated using 15 (or fewer)
stratons (i is a straton's number):
K1 ðCaÞ½carbonate rocks = Median KiCa
K1 ðSiÞ½cherts = Median KiSi
ð9Þ
ð10Þ
K1 ðAlÞ½terrigenous + volcanicsedimentary rocks = Median KiAl ð11Þ
Second, “lithological Clarke K1” is calculated as a weighted mean:
K1 ¼ 0:2K1 ðSiÞ þ 0:3K1 ðCaÞ þ 0:5K1 ðAlÞ
ð12Þ
In this type of calculation, preference is given to black shale
lithologies; in spite of uncertainty in rock names, the Clarke values
obtained provide comparisons which arrive at unexpected conclusions. For example, for Zn we have:
K1 ðCaÞ ¼ 140 43; K1 ðSiÞ ¼ 160 30; and K1 ðAlÞ ¼ 140 20 ppm:
ð13Þ
Similar subclarke values for Zn in chert and carbonate black shales
indicate mostly hydrogenic Zn-origin. Moreover, enriched Zn content
139
in black cherts has untrivial implications suggesting its biogenic origin
(Yudovich and Ketris, 1994, 1997).
2.2.4. “Lithostratigraphic Clarke K2” estimation
First, stratone subclarkes are grouped as follows:
K1(Ph) – for Phanerozoic including Vendian, mean of 11 stratones;
K1(pЄ3) – for Upper Precambrian (=Riphean);
K1(pЄ2) – for Middle Precambrian (=Karelian);
K1(pЄ1) – for Lower Precambrian, mean of two stratons.>
Second, “lithostratigraphic clarke K2” is calculated by averaging the
values:
K2 ¼ 1=4½K1 ðPhÞ þ K1 ðpЄ3 Þ þ K1 ðpЄ2 Þ þ K1 ðpЄ1 Þ
ð14Þ
The procedure is aimed at considering the relative duration of
geochrones, consequently, to some extent, corresponding black shale
masses for each straton. It is obvious that K2 is 75% composed of prePhanerozoan stratons (3:1), whereas, for K1 estimations the corresponding ratio is 4:11. This is why, K2-values strongly depend on old
metamorphic schists subclarkes. If the schists are enriched in any element
as compared with Phanerozoan, K2-values will be higher than K1 and vice
versa. Besides, if qtrueq black shale distribution in the sedimentary shell is
different from 3:1, K2-estimation would be also invalid.
2.3. Some words about “true” Clarkes
It is hard to say which of the estimations, K1 or K2, is more relevant.
For this reason both the estimations are tabulated (see Tables 1 and 2).
The closer are K1 and K2 values, the more reliable is the “true”
Сlarke value, which is a mathematical expectation of a random value.
Besides, similar K1, K2 and common median values are an important
Fig. 3. Calculation of the qlithologicalq and qlithostratigraphicq Clarkes K1 and K2 (Yudovich and Ketris, 1994, p. 47; 1997, p. 34). See the text for comments.
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Table 1
Some statistics of trace elements distribution in black shales, ppm
Me ± δMe
Geochemical background
A0
A1
K1 ± δK1
K2
KCa
1 ±δ
KSi
1 ±δ
KAl
1 ±δ
74 ± 4
31 ± 2
4.7 ± 0.4
2.0 ± 0.9
190 ± 10
500 ± 20
40–120
15–50
2–7
0.5–10
100–300
270–800
120–170
50–70
7–10
10–15
300–400
800–1000
170–200
70–100
10–12
15–25
400–500
1000–1400
68 ± 5
33 ± 3
4.8 ± 0.6
2.5 ± 0.7
290 ± 10
590 ± 40
76
37
4.2
2.2
230
630
39 ± 4
24 ± 10
4.1 ± 0.8
0.7 ± 0.8
480 ± 40
540 ± 90
44 ± 6
19 ± 2
3.0 ± 1.6
4.8 ± 2.1
140 ± 20
740 ± 70
93 ± 9
44 ± 2
5.9 ± 1.0
2.6 ± 1.1
200 ± 10
560 ± 60
Cation- and anion-forming lithophiles with constant valency
Be
127
7810
2.0 ± 0.1
1–3
Sc
140
6880
12 ± 1
7–20
Y
142
8620
26 ± 1
15–40
Yb
110
5640
2.8 ± 0.1
2.0–3.5
La
128
4495
28 ± 1
20–40
Ce
75
2800
58 ± 3
35–80
Eu
40
1500
1.2 ± 0.04
1.0–1.4
Lu
32
950
0.4 ± 0.01
0.30–0.45
Nd
50
1300
33 ± 2
15–45
Sm
44
1270
5.4 ± 0.3
2.5–7.0
Tb
45
1160
0.75 ± 0.03
0.5–0.9
Pr
15
375
4.2 ± 0.5
2.5–6.0
Gd
25
400
4.7 ± 0.4
2.5–6.0
Dy
15
340
3.0 ± 0.4
1–4
Er
15
375
1.9 ± 0.1
1–2
Ho
5
330
0.52 ± 0.09
0.2–0.6
Tm
14
33
0.40 ± 0.04
0.3–0.55
Ga
249
10400
16 ± 1
9–25
Ge
60
4630
2.4 ± 0.2
1.2–3.0
3–4
20–25
40–50
3.5–4.0
40–50
80–110
1.4–1.6
0.45–0.50
45–55
7.0–8.5
0.9–1.1
6.0–8.0
6.0–7.5
4–5
2–3
0.6–0.7
0.55–0.65
25–35
3.0–4.0
4–5
25–30
50–65
4.0–5.0
50–60
110–130
1.6–1.8
0.50–0.60
55–65
8.5–10
1.1–1.3
8–10
7.5–9.0
5–6
3–4
0.7–0.8
0.65–0.80
35–45
4.0–5.0
2.1 ± 0.1
11 ± 0.5
23 ± 1
2.6 ± 0.1
28 ± 2
58 ± 6
1.0 ± 0.4
0.35 ± 0.02
26 ± 2
4.6 ± 0.3
0.60 ± 0.03
4.3 ± 0.3
3.8 ± 0.4
2.7 ± 0.2
1.6 ± 0.1
0.38 ± 0.02
0.26 ± 0.02
17 ± 1
2.4 ± 0.1
2.6
12
23
2.8
26
55
1.0
0.35
29
4.5
0.66
4.4
4.3
2.9
1.8
0.50
0.35
17
2.5
1.6 ± 0.4
5.9 ± 0.5
12 ± 3.4
1.7 ± 0.2
22 ± 2
50 ± 12
0.47 ± 0.09
0.29 ± 0.02
12 ± 4.7
2.5 ± 0.3
0.28 ± 0.06
4.7 ± 1.6
2.7
1.2 ± 0.3
1.0 ± 0.25
0.07
0.20
13 ± 1
1.2 ± 0.2
2.2 ± 0.2
11 ± 1.1
25 ± 2
2.9 ± 0.2
29 ± 1
53 ± 22
1.5 ± 0.1
0.33 ± 0.05
36 ± 3
6.5 ± 0.4
0.84 ± 0.05
4.3 ± 0.3
1.4 ± 1.7
1.8 ± 0.3
1.5 ± 0.2
–
–
14 ± 1
3.0 ± 0.3
2.4 ± 0.2
14 ± 1
29 ± 1
2.9 ± 0.2
31 ± 2
61 ± 6
1.1 ± 0.1
0.40 ± 0.01
25 ± 3
4.5 ± 0.5
0.60 ± 0.02
4.1 ± 0.5
5.5 ± 0.5
3.9 ± 0.4
2.0 ± 0.1
0.57 ± 0.04
0.30 ± 0.03
20 ± 1
2.8 ± 0.2
Cation- and anion-forming lithophiles with variable valency
Ti
466
17700
3000 ± 100
1500–4600
Zr
251
13300
120 ± 5
60–190
Hf
49
1290
4.2 ± 0.2
2.5–6.0
Th
99
6310
7.0 ± 0.4
4–11
Sn
170
8040
3.9 ± 0.3
2–10
V
653
25200
205 ± 15
100–400
Nb
39
1800
11 ± 1
7–15
Ta
40
680
0.7 ± 0.04
0.5–1.0
Mo
495
18480
20 ± 1.5
6–60
W
36
1380
2.9 ± 1.0
0–15
U
240
8400
8.5 ± 0.8
4–25
Re
48
670
0.9 ± 0.3
0.2–3.5
4600–6200
190–260
6.0–7.5
11–15
10–15
400–600
15–20
1.0–1.3
60–100
15–25
25–40
3.5–6.0
6200–7800
260–330
7.5–9.0
15–19
15–20
600–800
20–25
1.3–1.6
100–140
25–35
40–55
6–9
2700 ± 100
120 ± 5
3.5 ± 0.3
7.2 ± 0.4
5.6 ± 0.3
180 ± 10
10 ± 0.7
0.66 ± 0.06
20 ± 3
7.8 ± 1.4
13 ± 2
0.4 ± 0.3
2800
200
4.5
7.8
5.7
180
15
0.8
14
2.7
9.9
0.8
1200 ± 100
74 ± 6
2.2 ± 1.6
3.9 ± 0.6
5.0 ± 0.7
99 ± 23
2.9 ± 1.0
0.17 ± 0.14
16 ± 7
8.1 ± 1.2
10 ± 1.9
0.5 ± 0.5
2100 ± 200
120 ± 10
2.9 ± 0.3
5.0 ± 0.6
4.0 ± 0.4
250 ± 30
17 ± 2
0.55 ± 0.22
29 ± 3
21 ± 5
13 ± 2
1.0 ± 0.2
3900 ± 100
150 ± 10
3.8 ± 0.5
7.4 ± 0.6
6.6 ± 0.4
200 ± 10
12 ± 1
0.8 ± 0.1
18 ± 3
2.4 ± 1.9
14 ± 3
0.2 ± 0.1
Metals-thiophiles
B
196
P
364
F
47
Cl
25
Br
23
I
12
Cu
580
Ag
220
Au
148
Zn
489
Cd
57
Hg
54
In
7
Pb
436
Bi
20
Elements
N
n
Typical cation-forming lithophiles
Rb
80
5790
Li
57
4520
Cs
33
3170
Tl
18
2710
Sr
304
16650
Ba
314
15100
Non metals-thiophiles
As
130
Sb
82
Se
94
Te
7
Fe-group elements
Cr
562
Mn
534
Co
517
Ni
638
9460
14,900
1630
450
1070
310
25,740
9000
9120
18,540
2260
1420
176
20,520
2740
56 ± 3
1400⁎ ± 160
660 ± 70
300 ± 100
13 ± 3
1.6 ± 0.2
70 ± 3
1.0 ± 0.1
7.0 ± 1.0
130 ± 10
5.0 ± 0.6
0.27 ± 0.03
0.7
21 ± 1
1.1 ± 0.3
30–120
930–220
400–1500
100–1000
2–30
–
35–150
0.4–2.4
3–20
60–300
2–12
0.2–0.6
–
10–40
0–4
120–165
2200–3000
1500–2000
1000–2000
30–50
–
150–230
2.5–4.0
20–35
–
300–470
12–19
0.6–0.8
–
40–60
165–220
3000–3800
2000–3000
2000–3000
50–70
–
230–310
4.0–5.5
35–50
470–640
19–26
0.8–1.1
–
60–85
6–10
71 ± 5
1800⁎ ± 100
830 ± 70
420 ± 90
9.8 ± 1.7
1.3 ± 0.2
87 ± 9
1.6 ± 0.2
7.6 ± 3.9
140 ± 20
6.9 ± 1.4
0.23 ± 0.03
2.4
26 ± 1
2.0 ± 0.5
65
1300⁎
760
380
12
1.3
140
1.7
9.7
160
6.2
0.32
–
25
1.8
4.3 ± 8
710 ± 70
640 ± 70
340 ± 80
13 ± 3
0.8 ± 0.1
55 ± 26
1.7 ± 0.6
4.9 ± 2.1
140 ± 43
8.3 ± 3.3
0.29 ± 0.07
0.3
26 ± 2
2.5 ± 0.6
87 ± 17
1200 ± 100
720 ± 130
400 ± 190
12 ± 4.6
–
100 ± 16
1.0 ± 0.3
8.5 ± 1.3
160 ± 30
9.0 ± 3.3
0.18 ± 0.03
0.01
17 ± 2
3.4 ± 0.7
81 ± 6
1200 ± 100
780 ± 100
470 ± 160
7.0 ± 4.3
1.6 ± 0.2
100 ± 8
1.8 ± 0.2
8.8 ± 7.7
140 ± 20
5.3 ± 1.3
0.22 ± 0.03
4.6 ± 3.2
29 ± 2
1.1 ± 0.8
4190
1930
1650
110
30 ± 3
5.0 ± 0.5
8.7 ± 1.4
2.0 ± 0.3
10–80
2–11
3–30
1.3–3.0
80–130
11–17
30–50
3–4
130–180
17–23
50–70
4–5
30 ± 3
5.6 ± 0.8
7.8 ± 1.0
2.1
58
5.3
9.3
1.8
34 ± 6
6.8 ± 0.8
8.0 ± 0.8
4.2
30 ± 11
8.8 ± 3.9
12 ± 2
0.3
27 ± 3
3.6 ± 0.4
6.6 ± 1.7
1.7
21,900
19,600
21,000
23160
96 ± 3
400 ± 20
19 ± 1
70 ± 2
50–160
200–800
10–30
40–140
160–220
800–1200
30–40
140–210
220–280
1200–1600
40–50
210–280
81 ± 5
440 ± 30
14 ± 1
67 ± 4
93
1100
18
67
45 ± 6
500 ± 50
11 ± 1.1
41 ± 6
86 ± 12
250 ± 30
11 ± 1.5
63 ± 7
100 ± 7
470 ± 30
17 ± 2
84 ± 6
(N – number of primary samples, n – number of analyses).
Calculations by Marina P. Ketris, 1990.
⁎ The asterisk means that calculation was made with including 0.01 phosphate contribution, as: chert:carbonate:terrigenic (+tuff):phosphate = 0.20:0.29:0.50:0.01.
Author's personal copy
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
Table 2 (continued)
Table 2
Subclarkes for the black shale lithologies, ppm
Elements
Carbonate shales,
m
n
KCa
1
Me ± σMe
Elements
Chert shales,
m
n
Typical cation-forming lithophile elements
Li
9 1580 24 ± 10
8
930
Rb
11 1720 39 ± 4
11 1700
Cs
5 1550 4.1 ± 0.8
5
490
Tl
5 1440 0.7 ± 0.8
3
380
Sr
11 2210 480 ± 40
12 4870
Ba
12 2740 540 ± 90
12 4760
KSi
1
Terrigenous and
volcanic-sedimentary
shales, KAl
1
Me ± σMe
m
19 ± 2
47 ± 6
3.0 ± 1.6
4.8 ± 2.1
140 ± 20
740 ± 70
13
14
10
6
15
15
2010
1660
1140
890
8560
7630
44 ± 2
93 ± 9
5.9 ± 1.0
2.6 ± 1.1
200 ± 10
560 ± 60
3900
3650
4860
2350
1740
340
780
660
990
370
630
340
330
340
32
2820
550
5880
1870
2.4 ± 0.2
14 ± 1
29 ± 1
31 ± 2
61 ± 6
4.1 ± 0.5
25 ± 3
4.5 ± 0.5
1.1 ± 0.06
5.5 ± 0.5
0.60 ± 0.02
3.9 ± 0.4
0.57 ± 0.04
2.0 ± 0. 1
0.30 ± 0.03
2.9 ± 0.2
0.40 ± 0.01
20 ± 1
2.8 ± 0.2
Cation- and anion-forming elements
Be
10 1420 1.6 ± 0.4
Sc
10 1750 5.4 ± 0.3
Y
10 2230 12 ± 3.4
La
10 1080 22 ± 3
Ce
8
660 37 ± 12
Pr
2
5 4.7 ± 1.6
Nd
4
260 12 ± 5
Sm
4
260 2.4 ± 0.3
Eu
3
260 0.42 ± 03
Gd
1
4 2.7
Tb
3
250 0.27 ± 0.03
Dy
2
2 1.2 ± 0.3
Ho
1
1 0.07
Er
2
5 1.0 ± 0.25
Tm
1
1 0.2
Yb
8 1790 1.8 ± 0.2
Lu
3
260 0.28 ± 0.01
Ga
12 1880 13 ± 1
Ge
9 1820 1.2 ± 0.2
with stable valency
9 2490 2.2 ± 0.2
11 1350 12 ± 2
10 1530 25 ± 2
9
710 31 ± 3
8
340 41 ± 48
2
29 4.3 ± 0.3
4
57 40 ± 10
4
200 5.0 ± 1.2
3
41 1.3 ± 0.3
3
27 1.4 ± 1.7
4
66 0.72 ± 0.21
2
36 1.8 ± 0.3
Cation- and anion-forming elements
Ti
13 3750 1200 ± 100
Zr
11 2690 74 ± 6
Hf
3
260 2.2 ± 2.8
Th
8 1440 3.9 ± 0.6
Sn
10 1930 5.0 ± 1.3
V
14 4790 99 ± 23
Nb
6 1170 2.9 ± 1.0
Ta
3
3 0.17 ± 0.12
Mo
13 3770 16 ± 7
W
4
690 8.1 ± 1.2
U
10 1230 10 ± 1.9
Re
4
440 0.5 ± 0.5
with variable
11 4100
10 4470
3
41
8 1890
10 1660
12 6550
7 1750
3
41
12 6220
2
70
11 3480
3
110
n
Me ± σMe
2
29
1.5 ± 0.2
8
910
2.8 ± 0.3
10
7
2640
930
14 ± 1
3.0 ± 0.3
13
14
15
13
12
6
9
9
8
7
8
6
4
6
3
13
7
15
10
valency
2100 ± 200
140 ± 10
3.1 ± 2.4
4.2 ± 0.7
4.0 ± 0.4
250 ± 30
17 ± 2
0.55 ± 0.06
29 ± 3
21 ± 5
13 ± 2
1.0 ± 0.2
15
15
8
14
13
15
11
5
15
10
15
4
9810
6040
780
2470
4480
13870
1880
430
8490
530
3700
120
3900 ±100
150 ± 10
3.8 ± 0.5
7.4 ± 0.6
6.6 ± 0.4
200 ± 10
12 ± 1
0.83 ± 0.09
18 ± 3
2.4 ± 1.9
14 ± 3
0.2 ± 0.1
87 ± 17
1200 ± 100
720 ± 130
400
12 ± 5
14
15
13
9
7
5
4560
8200
600
290
460
270
81 ± 6
1200 ± 100
780 ± 100
470 ± 160
7.0 ± 4.3
1.6 ± 0.2
100 ± 16
1.2 ± 0.2
8.5 ± 1.3
160 ± 30
9.0 ± 3.3
0.18 ± 0.03
0.01
17 ± 2
3.4 ± 0.7
15
14
10
15
8
9
5
15
8
13730
4810
6050
11030
1470
460
220
10280
1450
100 ± 8
1.9 ± 0.3
8.8 ± 7.7
140 ± 20
5.3 ± 1.3
0.22 ± 0.03
4.6 ± 3.2
29 ± 2
1.1 ± 0.8
Typical anion-forming lithophile elements
B
9 1970 43 ± 8
10 2930
P
13 2980 710 ± 70
12 3490
F
9
820 640 ± 70
6
210
Cl
6
100 340 ± 80
2
58
Br
3 600 13 ± 3
2
11
I
4
39 0.77 ± 0.04
Metals-sulfophiles
Cu
14 5840
Ag
9
730
Au, ppb
6
650
Zn
14 4130
Cd
5
680
Hg
8
560
In
1
3
Pb
13 4580
Bi
5 1140
55 ± 26
11
1.7 ± 0.6
12
4.9 ± 2.1
5
140 ± 43
12
8.3 ± 3.3
4
0.29 ± 0.07 5
0.3
1
26 ± 2
12
2.5 ± 0.6
2
Nonmetals-sulfophiles
As
9
840
Sb
7
610
Se
9
370
Te
1
25
34 ± 6
6.8 ± 0.8
8.0 ± 0.8
4.2
10
9
9
1
900
480
730
2
30 ± 11
8.8 ± 3.9
12 ± 2
0.03
14
12
11
2
2460
840
550
80
27 ± 3
3.6 ± 0.4
6.0 ± 1.7
1.7
Elements-siderophiles
Cr
13 3820
Mn
13 4540
45 ± 6
500 ± 50
12
12
5090
4970
86 ± 12
250 ± 30
15
15
13040
10100
100 ± 7
470 ± 30
6170
3320
2420
3390
110
400
1
5670
150
141
(continued on next page)
Carbonate shales, KCa
1
m
n
Elements-siderophiles
Co
11 3540
Ni
13 4290
Chert shales, KSi
1
Terrigenous and
volcanic-sedimentary
shales, KAl
1
Me ± σMe
m
n
Me ± σMe
m
n
Me ± σMe
11 ± 1.1
41.6
12
12
5410
5460
11 ± 1.5
63 ± 7
15
15
12010
13400
17 ± 2
84 ± 6
Calculations by Marina P. Ketris, 1990.
m - number of stratons, n - number of analyses, Me - straton median, σMe – standard
deviation of straton median.
controlling factor. At any rate, it seems likely that they must not
exceed the double-standard median limits:
ðK1 ; K2 Þ b Me F 2δMe
No doubt, all the preceding errors affect the final “true” estimation.
Among them are:
- incorrectly defined original lithologies;
- inaccurate weight coefficients, both lithologic (0.2:0.3:0.5) and
stratigraphic (1:3);
- number of lithological subclarkes different from each other;
- number of Phanerozoic black shales different from pre-Phanerozoic ones.
For example, assumed weight coefficients for carbonate (0.3) and
terrigenous shales (0.5) may differ for Paleozoic platforms (more than
0.3) and Mesozoan geosynclines (more than 0.5), respectively.
As follows from the above discussion, we are very well aware of all
the inaccuracy of the Сlarke values we propose. It should be noted,
however, that they are no less accurate than the Clarke values for the
Earth's crust and the ocean widely referred to in literature. From all
the variety of strongly diverging values, Vinogradov (1962) simply
chose the figures he thought adequate. No doubt our Clarke values will
be revised in the not so distant future. Nevertheless, the Clarkes
proposed here are presently quite useful.
3. Estimation of trace elements Clarkes for coals
As was mentioned above, such calculations were made by several
researchers, but there are many difficulties in the calculation.
3.1. Coal-basis and ash-basis Clarkes
Up to 1970–1980, coal was mostly not directly analyzed for trace
elements but through an analysis of coal ash. Standard coal ashing was
performed at 750 °C (in USA and many West countries), or at 850 °C
(in former USSR and now in Russia)6. It is well known that some
elements may be almost fully (Hg, I, Br), or partly (Ge, Mo, etc.)
volatilized by high-temperature ashing. Trace element loss may be
minimized by low-temperature ashing (~130–150 °C) by means of
radio-frequency exposure in oxygen plasma (Gluskoter, 1965). This
excellent method, is, however, time-consuming and for this reason is
not widely acceptable.
So, up to end of 1980s, the content of trace element in coal (coalbasis content) was obtained by recalculation from the content in ash
(ash-basis content). Such recalculation may lead to underestimation of
coal-basis figures, and, as a result, to underestimation of coal-basis
Clarkes.
During the last decades of 20th century, several direct methods of
coal analysis were introduced in coal geochemistry, and first of all –
INAA, instrumental neutron activation analysis. So, many directly
6
Nonstandard ashing (550 °C, with an air access) used in USSR and USA for special
intent – following analyses of ash for trace elements.
Author's personal copy
142
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
obtained coal-basis figures appeared in the literature. Now a new
opportunity appears – to recalculate coal-basis figures to ash-basis
ones.
If the analysis of coal ash was earlier simply “a technical tool”
(because a direct analysis of coal was too hard and unreliable
procedure), have we any need for the “ash Clarkes” today? Yes, we
have such need: for the calculation of important geochemical values,
“coal affinity indexes” (or “coalphile coefficients), as we will discuss
below.
3.2. “Coal-affinity” (coalphile) indexes
Goldschmidt (1935) first calculated the “enrichment coefficients”
of coal ash by comparison of element content in coal ash and Earth's
crust Clarke value. For example: the Earth's crust-As Clarke value was
assumed to be 5 ppm, and As content in As-rich ashes was determined
as 500 ppm; so, enrichment coefficient was 500/5 = 100.
Later Yudovich (1978) used coal ash Clarke values (instead of
“enriched ashes”) and Clarkes of sedimentary rocks for such
calculation. These figures (enrichment coefficients) were named as
“typomorph coefficients”, and were widely cited in Russian and
Bulgarian literature7. More recently, this poor term was substituted
for coalphile coefficient (index), or coal affinity index (Yudovich and
Ketris, 2002).
What does a coal affinity index mean? – It shows, how efficiently coal
acted as a geochemical barrier for trace elements, during all its geologic
history. The more coal concentrated trace elements from environment
compared with sedimentary rocks, the greater would be the coal affinity
index. A researcher could compare coal affinity indexes for different
elements in given coal field, given coal basin, or province; for the coals of
different rank; and for the same coal field (basin, province) but for
different elements. For example, As coal affinity index is 50 ppm/
11 ppm= about 5 (Yudovich and Ketris, 2005a,d), and Hg coal affinity
index is 0.75 ppm /0.05 ppm = 15 (Yudovich and Ketris, 2005b,c,d). So,
Hg is threefold more coalphile element than As.
3.3. Calculation method
All calculation procedures may be divided into several stages
(Ketris and Yudovich, 2002):
1) analytical data collection; 2) preliminary data processing and
formation of basic tables; 3) using basic tables, formation of
sufficiently homogeneous statistical data samples (data assemblages),
and calculation of sample-averages; 4) using sample-averages,
plotting of frequency histograms and evaluation of the Clarke value,
as median.
3.3.1. Analytical data collection
This is very time-consuming and the hardest part of all the work.
We collected coal-analyses data nearly 45 years. From the literature, it
is necessary to extract the following data: (a) coal locality (country,
basin, coal field (deposit), coal seam; (b) coal rank and geological age;
(c) ash yield on dry matter (Ad, %); (d) how units are used (%, ppm, mg/g
etc.), and basis – coal or ash; (e) number of coal specimens (analyses).
Unfortunately, only in few instances we could obtain all the
information! Often, a part of information needed was lacking. For
example, if the coal locality was lacking, such analytical data have to be
rejected.
The stratigraphic data were needed in order to not include
different-age coals within an united statistical sample. We need also
to know: if the data collected belong to coal beds or coal inclusions?
The latter may be extremely enriched in trace elements (Yudovich,
7
See numerous papers published by Greta Eskenazy, Jordan Kortensky, Stanislav
Vassilev, and some others.
Fig. 4. A sketch showing a procedure of stepped averaging (Tkachev and Yudovich, 1975,
p. 124). The steps (levels): a – initial, the analyses of coal specimens; b – coal beds; c –
coal fields; d – coal areas (basins, provinces), e – final totality of the areas (= global
totality of statistical samples). 1 – anyone object of the given step (level); 2 – specific
object of this step (level), for which are shown its lower (composing) components.
1972, 2003), and the use of such figures may sharply change the
sample average. The other important question arises: was the given
coal influenced secondary processes? Such data may also distort a
homogeneity of the statistical sample.
In literature prior to 1980, a simultaneous analysis presentation on
an ash- and on a coal basis was rare; so, we needed to know an ash
yield in order to obtain the lacking figure by recalculation. If an ash
yield was lacking, we tried to evaluate it using all the available
information sources (reference books, special monographs, etc.).
In many Soviet papers (where in fact, many thousand spectrographic analyses were averaged), the number of analyses was lacking.
In such instances, we needed to get only some “conditional” number
Author's personal copy
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
143
Fig. 5. An example of the “appropriate" plot: zirconium (Yudovich, Ketris, 2006a,b,c, p. 285). N – number of analyses, n – number of statistical samples, Me – the median of statistical
samples.
of analyses. This means that our “number of analyses” sometimes did
not contain enough accurate information (tends to be underestimated).
3.3.2. Preliminary data processing and formation of basic tables
Preliminary data processing may start even during data collection:
the individual figures (belonging to each coal specimen) being
averaged – if such average is lacking in original text. As elemental
information units, we assumed a coal bed- or coal-field averages. For
example, if there were several figures for one coal bed, we calculated
the coal-bed average and put it in the basic table. If there were the
figures for three coal beds, these three figures were put in basic table,
etc. If the set of analyses had very sharp anomalies (for example, one
to two order-of-magnitude more than coal geochemical background),
such figures, as a rule, were not included in average calculation.
As a result, for each element we created two basic tables, for brown
and hard coal, as following:
Hard (brown) coals
Country Coal basin
(province,
region, area)
Coal
field,
bed
Geologic n Ad E, ppm
age
on coal
basis
E, ppm
on ash
basis
Reference
(source of
data)
In such a table, n means the number of analyses, Ad – ash yield, %, E –
a chemical element.
3.3.3. Stepped averaging and final median calculation
After basic tables were formed, we could obtain the assemblage of
statistical samples (and their averages), which would be used for the
final Clarke calculation. Each statistical sample embraces the analyses
of a coal basin or large coal area (region). All the analyses included are
to be averaged. If the collected data allowed, we constructed two to
four statistical samples for big coal basins (provinces) – for example,
for some industrial regions (within Donets basin, Ukraine), coal fields,
or other geographical units. The number of such “intra-basinal”
statistical samples nearly corresponded with coal geological resources
of the given basin.
The full concept involves stepped (successive) averaging, from
minor to large: one coal bed ⇒ several coal beds ⇒ coal field (deposit)
⇒ coal area (several coal fields) ⇒ coal basin or province ⇒ totality of
the coal basins (=assemblage of statistical samples), i.e. Clarke value
totality, comprising several dozen random (statistical) samples
representing many thousands of analyses (Fig. 4).
For example, coal Clarke value of As was calculated using totality,
consisting of 119 statistical samples (and about 21,000 analyses) – for
hard coals, and 66 statistical samples (and about 21,000 analyses) – for
brown coals (Yudovich and Ketris, 2005a). On the steps, the averages
were calculated as arithmetic mean (if the sample was more
homogeneous), or as median (if the sample was less homogeneous).
Following our good experience in black shale geochemistry
(Yudovich and Ketris, 1994), we use a sample totality median (Me)
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144
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
as a Clarke value estimation. As an estimation of the median accuracy
(σMe) we use the value
pffiffiffiffiffi
σ Me = ðQ3 − Q1 Þ=2 n;
ð16Þ
where Q1 and Q3 – two distribution quartiles, corresponding 1/4 and
3/4 of the cumulative frequency.
Although a Clarke value (a median) is estimated analytically, it is
very instructive to plot a frequency histogram. The distribution of
trace element contents in coal is, as a rule, log-normal; that is why, for
plotting the logarithmic scale is often used. The plot character could
suggest: how “good” is the totality studied. If the histogram is “right”
(for example – near to log-normal), the totality could be attested as a
“good” one (Fig. 5); in opposite case, we can think the totality is too
small and not representative of natural coals (Fig. 6). In such a case, we
need to get some new analyses for a better Clarke estimation. In fact,
the elements with “right” histograms nearly “do not react” upon new,
supplementary analyses – their Clarke value could only little vary (as a
rule – not more than within accuracy range of median, i.e. ±1σMe). On
the contrary, some rare, poorly studied elements (such as Au, Pd, Tl, In,
Te, Cl, I, and some others) may, in future, change their Clarkes more
appreciably.
The other (well known) histogram characteristic is its σMe value
compared with Me value. If these figures are comparable (very large
variance of the statistical distribution), the Clarke value is, of course,
not very reliable; if σMe bb Me, the opposite is true. For example,
average content of Pd in brown coal ashes was estimated only over
eight statistical samples (nearly 50 analyses) as 0.066 ± 0.027 ppm.
Such a figure appears to be too high and dubious, accounted for
Chinese Pd-rich coals contribution. There is no doubt, as the sample
assemblage is extended, the Pd Clarke in coal will be changed.
For the REE, one other criterion exists: the picture of the
standardized (normalized) curve. As example, Tm has some peak on
such curve, that distinguishes Tm from the neighboring REE. It may
mean that the Tm coal Clarke is now overestimated, and may be
amended in future, as more information would be available.
3.3.4. Calculation results
The results of the calculations are shown in Table 3 and 4.
The last column in Table 3 represents coal affinity indexes,
calculated using our coal Clarkes and modern weighed Clarkes for
sedimentary rocks, calculated by Grigoriev (2003) using the Ronov's
sedimentary shell model (Ronov, 1980; Ronov et al., 1990). It is of note,
the coal affinity indexes are calculated on the base of averaged ash
Clarkes, i.e. (element Clarke in hard coal ash + element Clarke in brown
coal ash)/2. For example, lithium: (49 ppm + 82 ppm)/2 ≈ 66 ppm;
66 ppm/33 ppm = 2 (coal affinity index).
It should be noted that some Clarkes in Table 3 are based on small
statistical samples or/and not very reliable analyses. Such (preliminary)
Fig. 6. An example of the irregular plot: iodine.
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M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
145
Table 3
Coal Clarke values for trace elements
Elements
Coals
Brown
Typical cation-forming lithophile elements
Li
10 ± 1.0
Rb
10 ± 0.9
Cs
0.98 ± 0.10
Tl
0.68 ± 0.07
Sr
120 ± 10
Ba
150 ± 20
Coal ashes
Hard
All
Brown
Hard
All
Clarke value of
sedimentary rocks
14 ± 19
18 ± 1
1.1 ± 0.12
0.58 ± 0.04
100 ± 7
150 ± 10
12
14
1.0
0.63
110
150
49 ± 4
48 ± 5
5.2 ± 0.5
5.1 ± 0.5
740 ± 70
900 ± 70
82 ± 5
110 ± 10
8.0 ± 0.5
4.6 ± 0.4
730 ± 50
980 ± 60
66
79
6.6
4.9
740
940
33
94
7.7
0.89
270
410
Cation- and anion-forming elements with stable valency
Be
1.2 ± 0.1
2.0 ± 0.1
Sc
4.1 ± 0.2
3.7 ± 0.2
Y
8.6 ± 0.4
8.2 ± 0.5
La
10 ± 0.5
11 ± 1
Ce
22 ± 1
23 ± 1
Pr
3.5 ± 0.3
3.4 ± 0.2
Nd
11 ± 1
12 ± 1
Sm
1.9 ± 0.1
2.2 ± 0.1
Eu
0.50 ± 0.02
0.43 ± 0.02
Gd
2.6 ± 0.2
2.7 ± 0.2
Tb
0.32 ± 0.03
0.31 ± 0.02
Dy
2.0 ± 0.1
2.1 ± 0.1
Ho
0.50 ± 0.05
0.57 ± 0.04
Er
0.85 ± 0.08
1.00 ± 0.07
Tm
0.31 ± 0.02
0.30 ± 0.02
Yb
1.0 ± 0.05
1.0 ± 0.06
Lu
0.19 ± 0.02
0.20 ± 0.01
Ga
5.5 ± 0.3
6.0 ± 0.2
Ge
2.0 ± 0.1
2.4 ± 0.2
1.6
3.9
8.4
11
23
3.5
12
2.0
0.47
2.7
0.32
2.1
0.54
0.93
0.31
1.0
0.20
5.8
2.2
6.7 ± 0.5
23 ± 1
44 ± 3
61 ± 3
120 ± 10
13 ± 2
58 ± 5
11 ± 1
2.3 ± 0.2
16 ± 1
2.0 ± 0.1
12 ± 1
3.1 ± 0.3
4.6 ± 0.2
1.8 ± 0.3
5.5 ± 0.2
1.10 ± 0.10
29 ± 1
11 ± 1
12 ± 1
24 ± 1
57 ± 2
76 ± 3
140 ± 10
26 ± 3
75 ± 4
14 ± 1
2.6 ± 0.1
16 ± 1
2.1 ± 0.1
15 ± 1
4.8 ± 0.2
6.4 ± 0.3
2.2 ± 0.1
6.9 ± 0.3
1.3 ± 0.1
36 ± 1
18 ± 1
9.4
23
51
69
130
20
67
13
2.5
16
2.1
14
4.0
5.5
2.0
6.2
1.2
33
15
1.9
9.6
29
32
52
6.8
24
5.5
0.94
4.0
0.69
3.6
0.92
1.7
0.78
2.0
0.44
12
1.4
Cation- and anion-forming elements with stable valency
Ti
720 ± 40
890 ± 40
Zr
35 ± 2
36 ± 3
Hf
1.2 ± 0.1
1.2 ± 0.1
Th
3.3 ± 0.2
3.2 ± 0.1
Sn
0.79 ± 0.09
1.4 ± 0.1
V
22 ± 2
28 ± 1
Nb
3.3 ± 0.3
4.0 ± 0.4
Ta
0.26 ± 0.03
0.30 ± 0.02
Mo
2.2 ± 0.2
2.1 ± 0.1
W
1.2 ± 0.2
0.99 ± 0.11
U
2.9 ± 0.3
1.9 ± 0.1
800
36
1.2
3.3
1.1
25
3.7
0.28
2.2
1.1
2.4
4000 ± 200
190 ± 10
7.5 ± 0.4
19 ± 1
4.7 ± 0.4
140 ± 10
18 ± 1
1.4 ± 0.1
15 ± 1
6.0 ± 1.7
16 ± 2
5300 ± 200
230 ± 10
9.0 ± 0.3
23 ± 1
8.0 ± 0.4
170 ± 10
22 ± 1
2.0 ± 0.1
14 ± 1
7.8 ± 0.6
15 ± 1
4650
210
8.3
21
6.4
155
20
1.7
14
6.9
16
Typical anion-forming lithophile elements
B
56 ± 3
P
200 ± 30
F
90 ± 7
Cl
120 ± 20
Br
4.4 ± 0.8
I
2.3 ± 0.4
52
230
88
180
5.2
1.9
410 ± 30
1200 ± 100
630 ± 50
770 ± 120
32 ± 5
13 ± 2
260 ± 20
1500 ± 100
580 ± 20
2100 ± 300
32 ± 9
12.2 ± 5.4
335
1350
605
1440
32
12.6
Metals-sulfophiles
Cu
Ag
Au, ppb
Zn
Cd
Hg
In
Pb
Bi
47 ± 3
250 ± 10
82 ± 6
340 ± 40
6.0 ± 0.8
1.5 ± 0.3
3740
170
3.9
7.7
2.9
91
7.6
1.0
1.5
2.0
3.4
72
670
470
2700⁎
44
1100
CAI
2.0
0.84
0.86
5.5
2.7
2.3
4.9
2.4
1.8
2.2
2.5
2.9
2.8
2.4
2.7
4.0
3.0
3.9
4.3
3.2
2.6
3.1
2.7
2.8
11
1.2
1.2
2.1
2.7
2.2
1.7
2.6
1.7
9.3
3.5
4.7
4.7
2.0
1.3
0.53
0.73
0.01
15 ± 1
0.090 ± 0.020
3.0 ± 0.6
18 ± 1
0.24 ± 0.04
0.10 ± 0.01
0.021 ± 0.002
6.6 ± 0.4
0.84 ± 0.09
16 ± 1
0.100 ± 0.016
4.4 ± 1.4
28 ± 2
0.20 ± 0.04
0.10 ± 0.01
0.040 ± 0.020
9.0 ± 0.7
1.1 ± 0.1
16
0.095
3.7
23
0.22
0.10
0.031
7.8
0.97
74 ± 4
0.59 ± 0.09
20 ± 5
110 ± 10
1.10 ± 0.17
0.62 ± 0.06
0.11 ± 0.01
38 ± 2
4.3 ± 0.8
110 ± 5
0.63 ± 0.10
24 ± 10
170 ± 10
1.20 ± 0.30
0.87 ± 0.07
0.21 ± 0.18
55 ± 6
7.5 ± 0.4
92
0.61
22
140
1.2
0.75
0.16
47
5.9
31
0.12
6.0
43
0.80
0.068
0.043
12
0.26
3.0
5.1
3.7
3.3
1.5
11
3.7
3.9
23
Nonmetals-sulfophiles
As
Sb
Se
7.6 ± 1.3
0.84 ± 0.09
1.0 ± 0.15
9.0 ± 0.7
1.00 ± 0.09
1.6 ± 0.1
8.3
0.92
1.3
48 ± 7
5.0 ± 0.4
7.6 ± 0.6
46 ± 5
7.5 ± 0.6
10.0 ± 0.7
47
6.3
8.8
7.6
1.2
0.27
6.2
5.3
33
Elements-siderophiles
Cr
Mn
Co
Ni
Pd
15 ± 1
100 ± 6
4.2 ± 0.3
9.0 ± 0.9
0.013 ± 0.006
17 ± 1
71 ± 5
6.0 ± 0.2
17 ± 1
0.001 ± 0.002
16
86
5.1
13
0.0074
82 ± 5
550 ± 30
26 ± 1
52 ± 5
0.066 ± 0.027
120 ± 5
430 ± 30
37 ± 2
100 ± 5
0.007 ± 0.011
100
490
32
76
0.037
58
830
14
37
1.7
0.59
2.3
2.1
(continued on next page)
(continued on next page)
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146
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
Table 3 (continued)
Elements
Elements-siderophiles
Ir
Pt
Coals
Coal ashes
Brown
Hard
0.002 ± 0.006
0.065 ± 0.018
0.001 ± 0.0003
0.005 ± 0.003
All
0.002
0.035
Brown
Hard
0.013 ± 0.031
0.22 ± 0.04
0.007 ± 0.003
0.038 ± 0.018
Clarke value of
sedimentary rocks
All
CAI
0.010
0.13
Calculations by Marina P. Ketris, 2005.
CAI – coal affinity indexes (“coalphile indexes”).
CAI = average element concentration in coal ash/Clarke value in sedimentary rocks.
⁎ Cl Clarke value in sedimentary rocks – according to (Ronov et al., 1990).
⁎⁎The brackets mean that calculated Clarke value (based on small statistical samples or not very reliable analyses) is of minor adequacy (reliability). Such values could be strong
changed in future.
9
The ± figures mean ±1σMe
Clarkes could be strong changed in future; corresponding figures are
shown in the brackets.
4. Discussion in coal geochemistry
The data in Table 3 allow us to make some comparisons and raise
issues.
4.1. The values from 1985 and 2005: a comparison.
Due to new analytical methods and the great information gain, the
2005 Clarke estimations for some elements were appreciably changed
compared with 1985 estimations. Among these elements:
Li, Rb, Ag, Ti, Nb, As, Cl – for all coals; Cu, Be, B, Sc, Th – for brown
coals; Hg – for hard coals.
Other Clarke estimates also changed but less, only within 20–40%:
Ga, Y, Yb, Р – for all the coals; Ba, B, Cd, Co – for brown coals; Zn, Sc, Mo,
Mn – for hard coals.
Finally, many Clarke values have kept within the calculation
accuracy range: Sr, Ge, Zr, Sn, V, F, Cr, Ni – for all the coals; Hg, Zn, Mo,
Mn – for brown coals; Rb, Be, В, Cu, Th – for hard coals.
4.2. Comparison of brown and hard coal Clarkes
Such a comparison allows analysis of coal rank influence on coal
geochemistry. Coal “metamorphism” is the thermal epigenetic
process, involving hot brines and fluids influencing coal beds. These
processes not only changed coal organic matter, but may greatly
change the trace element contents by means of their input or output
(Yudovich, 1978; Yudovich and Ketris, 2002). However, this (obvious)
issue is far from universal. It is known that, in general, hard coals are
Paleozoic, and brown coals are Mesozoic and Cenozoic. This means
that in some instances the geochemical difference “brown coals vs.
hard coals” may be primary, accounted for the large initial difference
of Paleozoic and Mesozoic-Cenozoic coal-forming flora.
As seen from Table 3, brown coals are enriched in B, U, and Mn. For
all three elements, one can suggest their output during thermal
metamorphism of the coal organic matter. More elements are
enriched in hard coals compared with brown ones. Weak enrichments
include Co, Ge, V, Pb, Se, and strong ones include Rb, Be, Zn and Ni.
Only for the evident sulfophile elements (such as Pb, Se, and Zn), such
enrichments could be caused by hydrothermal input related to coal
metamorphism. However, for litho- and siderophile elements (such as
Be, Cr, Co, Ni) such explanation appears to be dubious. It is not
excluded that primary coal-formed flora acted here as actual factor of
difference (Yudovich, 1978). Such (non-trivial) conclusion could
highlight some problems dealing with the biosphere evolution.
4.3. Coal affinity indexes
By analyzing ranges of the coalphile indexes (the last column in
Table 3), one can divide the elements in four groups:
(a) non-coalphile elements (coal affinity indexes are b1): I, Cl, Mn,
Br, Rb, Cs;
(b) weakly or moderate coalphile elements (coal affinity indexes
range from 1 to 2): Ti, Zr, F, Cd, V, Ta, Cr, Y, Li, P;
(c) coalphile elements (coal affinity indexes range from 2 to 5): Ni,
Hf, Sn, La, Co, Ba, Sc, Nb, Sr, Th, Ga, Cu, REE, Zn, W, Au, In, Pb, U, B,
Be;
(d) highly coalphile elements (coal affinity indexes N5): Ag, Sb, Tl, As,
Mo, Ge, Hg, Bi, Se.
The greater is the coal affinity index, the greater is the contribution
of an authigenic fraction of given trace element (represented by
organic or micro-mineral forms), and the less is one of a clastogenic
fraction (represented by macro-mineral forms (for example, silicatic).
Due to the new (weighed) Clarkes of sedimentary rocks (Grigoriev,
2003), some earlier estimations of coal affinity have drastic changed.
So, after the calculation of real evaporites contribution in sedimentary
shell (Ronov, 1980; Ronov et al., 1990), the weighted Clarkes of
halogens Cl, Br, and I in sedimentary rocks increased. This results in a
corresponding sharp decrease in their coal affinity indexes: halogens
“have transformed” from highly coalphile elements (Yudovich et al.,
1985; Yudovich and Ketris, 2006b) to non-coalphile ones8. Also, the
coalphile indexes of Au, Cd, Y, V, U, Cr have unexpectedly decreased,
and, in turn, indices of Tl, Zn, Hf, and In have unexpectedly increased.
The extreme coalphile indices of Bi and Se appear to be very
doubtful. Such strange figures could be accounted for errors in the
Clarke values for sedimentary rocks (and not for coal Clarkes errors?).
It is of note, these elements are often not analyzed; due to analytical
difficulties; see, for example, for Se (Yudovich and Ketris, 2006a). This
may be a factor.
5. Conclusion
Black shale Clarke values are the average trace element contents in
the World black shales. It is well known that black shales (carbonaceous, mainly marine sedimentary rocks) often are metalliferous and/
or bituminous: enriched in U, V, Mo, Re, many other trace elements,
and “shale oil”. That is why the Clarke values for black shale are very
important for each researcher dealing with oil- or ore-bearing black
shales. The tables of black shale Clarkes calculated by the authors in
1994 are presented here; these calculations are based on huge
information.
Coal Clarke values are the average trace element contents in the
World coals. The modern table of coal Clarkes is presented here,
calculated by the authors based on a very large amount of information
(thousands analyses of coal and coal ashes for trace elements).
The coal Clarkes are the scientific tool for many geochemical
comparisons and issues. First of all, coal Clarkes allow to compare
given (studied) coal with World geochemical background, and to
conclude: is the coal “normal” (near to the Clarke level), enriched or, in
8
However, J.C.Hower believes [personal communication, December 2008] that
halogens are coalphile on lithotype basis; vitrains have high Cl and Br where these
elements are high. But, Cl (or Br) are not universally high, so averaging takes in low-Cl
coals.
Author's personal copy
M.P. Ketris, Y.E. Yudovich / International Journal of Coal Geology 78 (2009) 135–148
Table 4
Number of analyses for coal Clarkes calculated
Elements
Li
Rb
Cs
Tl
Sr
Ba
Be
Sc
Y
La
Ce
Pr
Nd
Sm
Eu
Gd
Tb
Dy
Ho
Er
Tm
Yb
Lu
Ga
Ge
Ti
Zr
Hf
Th
Sn
V
Nb
Ta
Mo
W
U
B
P
F
Cl
Br
I
Cu
Ag
Au
Zn
Cd
Hg
In
Pb
Bi
As
Sb
Se
Cr
Mn
Co
Ni
Pd
Ir
Pt
Brown coals (lignites)
Hard (bituminous) coals
n
N
n
N
44
47
40
28
78
76
80
73
72
57
44
16
30
35
35
18
34
26
25
19
18
61
32
86
84
88
74
38
52
69
97
43
33
80
45
63
65
52
37
39
27
8
90
63
31
84
40
48
7
78
26
66
43
39
95
82
95
93
8
4
6
4914
2898
1808
1588
16,335
16,108
48,001
40,358
59,505
44,689
4196
243
1203
1875
1913
453
1468
989
719
436
365
31,120
1525
41,801
32,186
26,528
49,087
10,932
3586
66,318
83,964
28,961
1626
71,606
8591
7561
5800
5127
3149
1410
1061
52
69,855
13,248
1180
78,908
2251
3623
193
67,744
2196
21,092
5220
2323
46,136
23231
69,660
70,560
52
7
44
84
79
70
49
113
127
118
112
106
105
80
35
58
71
73
42
64
49
41
37
35
94
65
127
127
126
112
65
97
103
139
80
65
131
69
110
103
105
77
83
65
18
139
96
43
137
75
94
15
136
53
124
92
81
141
134
142
143
17
9
18
11866
12742
11765
6105
27,052
18,433
114,256
118,155
117,643
22,232
12,200
4871
6828
11,440
11,578
5625
8640
5663
5298
5272
4792
95,812
10,290
121,820
128,060
28577
101,390
10,376
18,356
90,502
99,450
10,588
8224
104,901
8817
19,282
13,834
14,812
11,249
9981
6807
264
75,121
11,799
2037
103,924
15,079
34,775
648
93,983
6739
22,466
13,662
16478
64,442
29,521
125,023
135,952
431
146
201
n – number of statistical samples, N – number of analyses.
turn, impoverished in given trace element. Such comparisons are
known of great importance for toxic elements (such as Hg, As, Se, Be
etc.), as well for valuable elements, having industrial potential (such as
Ge, Ga, Sc, Re, REE, PGE, etc.).
Other important values have the “coal affinity indexes” (coalphile
indexes) of trace elements (average element content in coal ash/
element Clarke in sedimentary rocks). These indexes show how
147
efficiently coal acted as a geochemical barrier for trace elements
during all its geologic history. A comparison of coalphile indexes with
each other allow to display a contribution of coal authigenic matter
(organics, sulfides etc.) in coal inorganics. On the other hand, the
comparison of the coalphile indexes of the same element, but in
different coals, allow to see some non-obvious peculiarities of the coal
fields or coal basins. See, for example, numerous Bulgarian papers for
reference, such as on the coal geochemistry of In, W (Eskenazy, 1980,
1982); REE, Zr and Hf (Eskenazy, 1987a,b); Ta, Au (Eskenazy, 1990,
1992); As and Sb (Eskenazy, 1995); Be (Eskenazy, 2006); B (Eskenazy
et al., 1994), Sr (Eskenazy and Mincheva, 1989), REE, U and Th
(Kortenski and Bakardjiev, 1993); on coal inclusions with unique
contents of trace elements (Vassilev et al., 1995), etc.
Acknowledgements
James Hower kindly and selflessly edited the original Russian-toEnglish translation of this manuscript. Greta Eskenazy and Vladimir
Seredin (the reviewers) made some valuable notes and corrections.
We are very appreciative to Editor-in-Chief and our reviewers.
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