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Exergy : A Useful Indicator for the Sustainability of
Mineral Resources and Mining
Dr Alicia Valero1, Dr Antonio Valero1, Dr Gavin M. Mudd2,#
1Centre of Research for Energy Resources and Consumption (CIRCE), University of
Zaragoza, Spain
2Environmental Engineering, Department of Civil Engineering, Monash University, Clayton,
Melbourne, Australia #Gavin.Mudd@eng.monash.edu.au
Abstract
There is active debate and research around the most suitable indicators to assess the
sustainability of mining. The most common approach is to report a range of data for a given
mine site (or less preferably, a company total), such as inputs, outputs, benefits and potential
costs. The most popular protocol in use (and growing rapidly) is the Global Reporting
Initiative (GRI). However, these measures are numerous and still do not allow a single over-
arching indicator to be developed. Other measures, such as known mineral resources over
time, do not account for critical challenges such as declining ore grades, increasing wastes
and poorer quality ores or more difficult mineralogy. By adopting a thermodynamic approach
to sustainability, through the concept of ‘exergy’, it is possible to incorporate into a single
measure the effective quality of mineral resources. Exergy involves the assessment of the
minimum energy costs involved in producing a mineral resource with a specific chemical
composition and concentration from common materials in the environment. The exergy of a
mineral resource is evaluated from mineralogic composition, concentration (or ore grade) and,
of course, quantity, by multiplying the unit exergies with the tonnes of the resource produced
(or consumed). Since exergy is a thermodynamic quantity (ie. energy or joules), it is additive
across different minerals, such as iron ore to gold to copper or even oil and gas or coal –
making it an ideal indicator to assess mineral resource sustainability at the industry scale
rather than the individual mine scale. This paper briefly outlines the theoretical basis for
exergy, and then presents a range of commodity case studies showing the application of
exergy to the Australian mining industry. Overall, the usefulness of exergy is clearly
demonstrated for use as a broad indicator of the sustainability of mineral resources at the
national or even global scale.
INTRODUCTION
The concept of ‘sustainable mining’ is a challenging area for sustainability. The very nature
of mining is the extraction of ‘finite’ mineral wealth from the earth’s natural capital or stocks
– and given that mineral or metal commodities can range in grade from >60% for iron, <0.5%
to several percent for base metals down to grams per tonne for precious metals, how can any
indicator be used to assess cumulative sustainability over time? This is no easy task, yet it is
vital to understanding and predicting the future of the mining industry at a regional or even
global scale.
It is the purpose of this paper to review the application of “exergy” accounting to mineral
resources and mining. Exergy is the use of thermodynamic accounting to assess, in one
quantity, the true energy required to produce minerals or metals from a degraded state in the
so called Reference Environment (RE; i.e. an analogue of a depleted natural environment). It
allows for the incorporation of the quality, i.e. chemical composition and concentration of a
mineral or metal, and can also allow for the state of technology to be assessed through the
exergy costs. In this way, exergy makes for a compelling way to examine the true value of
mineral resources since it is based on thermodynamics, with units of Joules (J; or equivalent
energy units such as tonnes of oil equivalent, ‘toe’). The exergy costs of gold or copper or
iron ore mining can therefore be examined in an equivalent indicator – exergy (J) – and trends
over time can give significant insights into the sustainability of mining. Thus the paper aims
to demonstrate that exergy is indeed an accurate and viable approach to quantifying
sustainability in mining at a regional or global scale, using Australia as a detailed case study.
THE THEORY OF EXERGY: A BRIEF REVIEW
This section is only a brief examination of the theoretical basis for exergy accounting. For
further details, see Valero (2008) and Valero et al. (2008).
As a result of the application of Thermodynamics to the evaluation of natural resources, and
with the support of Thermoeconomics (see a historical overview in Valero and Torres, 2005)
a rather new approach called Exergoecology was proposed by Valero (1998) as a tool for
natural resources accounting. Exergoecology is the application of the exergy analysis (Second
Law of Thermodynamics) to the evaluation of natural fluxes and resources on Earth defined
from a Reference Environment (RE). It allows to value resources, according to the physical
cost, i.e. the amount of exergy that would be required to obtain them from the materials
contained in a hypothetical environment where each element has its lowest reactivity
compatible with the mineral’s abundance on Earth (Szargut et al, 1988). A mine, like an
iceberg or a cloud has exergy with respect to this RE. If society would want to replace an
iceberg or a cloud using current available technology, immense amounts of additional exergy
would be required. Using the exergy analysis combined with the rules for exergy cost
accounting provided by Thermoeconomics, it is possible to get reasonable estimates.
Exergoecology provides this analysis, by quantifying the physical cost (J) of replacing natural
resources from a degraded state in the so called RE, to the conditions in which they are
currently presented in Nature.
Figure 1 shows in a schematic way the processes involved in the production of a certain raw
material like iron or copper. During millions of years, Nature has formed and concentrated
minerals through a large number of geological processes such as magmatic separation,
hydrothermal, sedimentary, residual, etc. (Chapman and Roberts, 1983) forming the currently
existing natural stock. The concentrated mineral deposits serve as a material and fuel reservoir
for society. The extraction of materials implies an obvious reduction of the natural stock in
terms of the minerals extracted from the mines and the fossil fuels required for the mining
processes. Those extracted minerals are concentrated and further refined to obtain the desired
raw materials, for which additional quantities of fuels and minerals are required. This way,
the natural stock stored in the Earth’s crust goes into the hands of society as technological
stock. When the useful life of products finishes, they end up as wastes – either as pollution or
disposed of in landfills – or are recycled. When materials become degraded and dispersed,
they arrive at similar conditions as in the RE. Consequently, the costs associated to obtain the
raw material from the minerals dispersed in the RE would include the natural processes of
concentrating and forming minerals into the mineral deposits (replacement costs, J) and those
associated with mining and refining the minerals (extraction and processing costs, J). In the
case of recycling, the cost to obtain the raw material is restricted to the processing of the
substance, thereby saving the natural replacement costs as well as the mining and
concentration costs.
Figure 1: Processes involved in the production of a raw-material
It is important to note the difference between extraction and replacement costs. The former
assesses the resource from the mine to market. However, the latter assess the resource from
the degraded Earth or RE to the mine. As Naredo (1987) argues, economy puts value to
natural resources considering their extraction costs and not their replacement costs. Therefore,
extraction and not recovery or recycling is fostered and optimized. This enhances the
efficiency of the extraction processes, facilitating the market availability of these substances
and further increasing their scarcity, rather than saving resources for future generations. The
Exergoecological approach shifts the anthropogenic view of the value of resources to the
Nature’s point of view based on thermodynamics. This way, the Earth is not considered as an
infinite reservoir of minerals. On the contrary, it is seen as a provider with a finite amount of
exergy resources, whose extraction implies the use of further exergy resources. The primary
objective of this field of research is thus to extend the exergy analysis until the origin of all
the natural resources at stake in a production process are accounted for.
Exergy and exergy cost assessment of minerals
The most important features that fix the value of a mineral resource are on one hand its
chemical composition and on the other hand its concentration – both characteristics which can
be assessed with the single indicator of exergy.
The chemical composition of a substance is the key factor for fixing the final use of the
resource. Furthermore, it has a direct influence on the energy required for processing the
mineral. For instance, the energy required to extract pure copper from a sulphide is
significantly smaller than from an oxide, therefore copper sulphides such as chalcopyrite
(CuFeS2) are preferred as copper ores (see Gerst, 2008). The chemical exergy can be
calculated using the following well known expression (Szargut et al., 1988):
∑∆+= mineralchkch Gbb kel
0
,
ν
(1)
where bch el,k is the standard chemical exergy of the elements that compose the mineral and
can be easily found in tables, νk is the number of moles of element k in the mineral and ΔG is
the Gibbs free energy of the mineral.
The minimum amount of energy – exergy – involved in concentrating a substance from an
ideal mixture of two components is given by the following expression (Faber and Proops,
1991):
−
−
+−= )1ln(
)1(
)ln(
0i
i
i
ic x
xx
xRTb
(2)
Where bc is the concentration exergy, xi is the molar concentration of substance i, R is the gas
constant (8.3145 J/mol•K) and T0 is the reference temperature (298.15 K). This formula is
only strictly valid for ideal gases. When there is not chemical cohesion among the substances,
it remains valid for solid mixtures. The cohesion energy is the minimum exergy needed to
break the weak binding forces among solids such as hydrogen bond, surface and hydration
forces as opposed to strong ones like crystal or chemical bonds. Notwithstanding it, they are
strong enough to require physical separation processes like crushing, grinding, or floatation.
So deviations of this formula can be expected, however it does provide a reasonable
approximation of the behaviour of bc. Further research is currently in progress to overcome
this step. The difference between the concentration exergies obtained with the mineral
concentration in a mine xm and with the average concentration in the Earth’s crust xc is the
minimum energy that Nature had to spend to bring the minerals from the concentration in the
reference state to the concentration in the mine. Note also the log-normal behaviour of this
formula. The additional exergy, Δb, required for separating an additional Δx in a mixture
depends on x, and tends to infinity when x
0. This means that complete purification is
impossible or that infinitesimal pollution is infinitely easy. The more separation we want, the
more exergy is expended per unit of additional separated material Δx. So scarcity behaves log-
normal, and each time we disperse materials, the exergy needed for recovering them from the
environment increases exponentially. Therefore, scarce materials like Au or Ag have a much
higher natural concentration exergy than common ones like Si, Al, or Fe.
This way, the total replacement exergy (bt), i.e. its natural exergy, representing the minimum
exergy required for restoring the resource from the RE to the initial conditions in the mineral
deposit, is calculated as the sum of the chemical and concentration exergy components (Eq.3).
cchtbbb += (3)
However, a study based only on reversible processes (minimum replacement exergies) would
ignore technological limits. Results show that, in general, the real energy requirements are
tens or even thousands of times greater than the exergy content of the mineral (Valero and
Botero 2002). For instance, the minimum total exergy of bauxite calculated with Eqs. 1 and 2
is 0,41 GJ/t, whereas, the actual exergy required to reproduce bauxite with the composition
and concentration found in nature with available technology is about 735 GJ/ton.
The calculation of the exergy replacement costs bt* of the resource, representing the actual
exergy required to replace the resource from the RE to its initial conditions, with current
available technology commonly have two contributions,
ccchchtbkbkb ··* +=
(4)
its chemical cost (
chch bk ·
), accounting for the chemical production processes of the substance,
and its concentration cost (
cc bk ·
), accounting for the concentration processes. Variable k
(dimensionless) represents the unit exergy replacement cost of a mineral. It is defined as the
relationship between the energy invested in the real obtaining process ( processreal
E_) for either
refining (kch) or concentrating the mineral (kc), and the minimum energy (exergy) required if
the process from the ore to the final product were reversible (
∆
bmineral).
eral
processreal
b
E
k
min
_
∆
= (5)
For instance, for the calculation of the unit replacement cost for concentrating bauxite from
the crustal to mine conditions (kc), it is assumed that the same technology for the
concentration of Al2O3 from silicate minerals in common rocks can be applied. Bravard et al.
(1972) estimated that 43170 BTU/lb of aluminium or 51.9 GJ/ton of Al2O3 is required to
produce Al2O3 from the clay. The minimum exergy required to concentrate Al2O3 from the
crustal concentration xm=0.46 to the refining concentration xr=0.90 is equal to 0.027 MJ/kg
(calculated with Eq. 2). Consequently, the unit exergy concentration cost is calculated as:
kc=51/0.027=1875
Table 1 shows the unit exergy replacement costs of the minerals considered in this paper.
These values have been updated by the authors from Valero and Botero (2002).
Table 1: Unit exergy costs of seven base-precious metals (updated from Valero and Botero, 2002)
Another very important application of exergy is the representation of the ‘Hubbert’ peak
(traditionally used for estimating the peak of production of fossil fuels) to non-fuel minerals
(eg. Hubbert, 1956). The bell-shape curve is better suited to minerals, if it is fitted with exergy
over time instead of mass over time. Oil quality keeps nearly constant with extraction,
whereas other non-fuel minerals do not (mineral concentration decreases as the mine is being
exploited). Therefore exergy is a much better unit of measure than mass, since it accounts not
only for quantity, but also for ore grades and composition. Moreover, if the Hubbert model is
applied to the exergy replacement costs explained below, the technological factor of
extracting and refining the mineral is also taken into account. In short, the well known bell-
shaped curve (presented below in Eq 6) can be fitted to the exergy or exergy replacement cost
consumption data provided, in order to estimate when mineral production will start declining.
( )
0
0
0
)( b
tt
e
b
R
tf
−
−
=
π
(6)
Where parameters b0 and t0 are the unknowns and R the economic proven reserves of the
commodity. In our case, we represented the yearly exergy replacement cost loss of the
commodity calculated with Eq. 5 vs. time, and determined the best-fit parameters for by Eq. 6
using a least squares procedure. The maximum of the function is given by parameter t0, and it
verifies that
0
0
() R
ft b
π
=
. The mathematical application used in this study is ‘cftool’ from
the software Matlab 7 (MathWorks, 2009).
The next section presents a case study of the exergy replacement costs of the main minerals in
Australia.
CASE STUDY : EXERGY AND THE AUSTRALIAN MINING INDUSTRY
The exergoecological method was applied in this study to Australian mines for two reasons:
1) a major study of Australian mining data was recently published by Mudd (2007a)
2) Australia is a major mineral producer and exports numerous commodities around the
world.
Given the availability of data, Australia is therefore an excellent case study for
exergoecological analysis of minerals and metals.
The exergy of seven important metals throughout their mining history in Australia has been
obtained: Au, Cu, Ni, Ag, Pb, Zn and Fe. Eq. 1 was used for calculating bch. The chemical
exergies of the elements generated from the RE defined by Szargut et al. (2005) were used as
the independent variables in Eq 1. The concentration exergy bc was calculated with Eq. 2. The
value of xc was taken from the latest geochemical study of the Earth’s continental crust from
Rudnick and Gao (2004).
Figures 2 and 3 show the cumulative minimum exergy consumption over time on the left axis
(in toe or ktoe) and the ore grade trend on the right axis for seven metals (Cu, Ni, Pb, Zn, Au,
Ag, Fe). The graphs reveal that consumption of all commodities has increased continuously,
following a general exponential trend. The quality of Australian mines, or in other words,
their ore grade trends, have been notably reducing throughout the last century. This implies an
even greater loss of the mine’s exergy and, importantly, increasing production of tailings.
Figure 2: Ore grade and cumulative exergy consumption of the Australian mining industry –
copper, nickel, lead, zinc, gold and silver
Figure 3: Ore grade and cumulative exergy consumption of Australian iron mines
Table 2 summarises the results obtained from this study, showing the quantity of metal lost in
terms of Mtoe, the exergy cost decrease of the economic demonstrated reserves throughout
the period of time considered, the depletion degree of the commodities (%Reserves loss) and
the number of years estimated until complete depletion occurs if the consumption rate
remains as in 2007 (reserves-to-production or R/P ratio expressed in exergy terms). The
degree of depletion is estimated by the fraction of cumulative exergy loss by 2007 and
divided by the cumulative exergy loss by 2007 plus the remaining exergy reserves in 2007.
Table 2: Reserves data and cumulative exergy losses in the Australian mining industry
It must be stressed that 2007 reserves may increase as new mines are discovered and as
technological development allows the exploitation of mines with lower ore grades.
Conversely, the future changes may lead to some reserves being reclassified as uneconomic
due to prevailing economic conditions, technological failure (eg., Cawse, Bulong; see Mudd,
2007b) or other reasons (eg. carbon trading or taxes). In fact the general trend observed in
Australia is that resources have increased over time (Mudd, 2007a,b). However, as Chapman
and Roberts (1983) argue, the world is now more developed and better explored, and it is
difficult to find regions worthy of intensive exploration efforts (eg. gold; see Mudd, 2007c).
This suggests that the process of discovery may be slowing down. Thus, although metal and
mineral reserves have been assumed to be constant for illustrative purposes in this paper, in
reality they will continue to evolve over time.
Accordingly, the most depleted commodities are in decreasing order: gold, silver and lead
experiencing a decrease of 66%, 63% and 63%, respectively. If the rate of consumption
remains the same as in 2007, the reserves will last respectively 24, 24 and 35 years. The zinc
industry has extracted about 52% of its reserves. At the same production rate, there will be
enough reserves for 30 years. Finally, copper, iron and nickel commodities are the least
depleted: 25%, 21% and 14% respectively of the present exergy reserves have been extracted.
At current extraction rates, Cu, Fe and Ni reserves would last for 68, 63 and 127 years
respectively.
Since exergy is an additive property, the total exergy cost decrease of the Australian metals
studied can be calculated. Although the quantity extracted of all commodities in terms of
mass cannot be summed up (gold and silver are extracted at rates of hundreds of tonnes per
year, whereas the other metals at rates of thousands or millions of tonnes/year), the order of
magnitude in terms of exergy cost is similar for all commodities and its sum gives valuable
information. Bt*, the energy replacement costs, obtained for all metals listed in Table 2 is
equal to 6142 Mtoe: 45.5 times the 2007 primary energy consumption of Australia at 5641 PJ
(or 135 Mtoe) (ABARE, 2008).
Additionally, the exergy replacement costs of non-fuel minerals can be compared to those of
fossil fuels. The exergy of fossil fuels can be approximated with no significant error to the
High Heating Value (HHV). In this way, one can compare with a single unit, such as exergy,
the total loss of mineral stock in a country or even in the whole world. Figure 4 shows the loss
of mineral capital in Australia due to the production of coal, oil, natural gas and the metals
discussed above. The production of fossil fuels has been obtained from BGS statistics (BGS,
various years). As can be seen, the production of iron implies a similar degradation of
Australia’s mineral capital as coal. Oil and natural gas have a slightly lower order of
magnitude, while the rest of the studied metals constitute a small fraction of the total.
Figure 4: Decrease of Australia’s mineral exergy stock, 1969 to 2007
The Hubbert peak applied to Australian minerals
The Hubbert peak model was applied to the exergy cost of the non-fuel minerals listed above
and to the exergy of the main fossil fuels produced throughout Australia’s mining industry
(coal, oil and natural gas), shown in Figure 5 (including correlation coefficients).
The application of the Hubbert peak model to the exergy reserves of the Australian minerals
considered was satisfactorily applied (correlation coefficients in brackets) to gold (86.26%),
copper (97.59%), nickel (92.05%), iron (97.10%), coal (99.48%), oil (96.23%) and natural
gas (98.94%). That was not the case for commodities silver, lead and zinc since the
correlation coefficients of the curves were slightly lower at 79.85%, 88.52% and 95.99%,
respectively. Since the production of these three metals are tightly connected (eg. Pb-Zn-Ag
ores), this implies that their production patterns do not follow the general behaviour of other
commodities. In addition, Hubbert curves assume symmetrical production behaviour which is
often not the case due to accelerated mining during boom times (as suggested by the most
recent years being significantly above their respective curves in Figure 5). Finally, economic
reserves are assumed to be constant, which recent history shows is not the case as reserves
commonly increase for most commodities (see Mudd, 2007a,b).
Using the most recent economic demonstrated reserves of the listed minerals, the Hubbert
peak model predicted that the maximum production has been already reached for zinc (2008),
gold (2006), silver (2005), lead (1996) and oil (1997). Copper will reach the peak in 2020,
natural gas in 2025, iron in 2026, nickel in 2040, and finally coal in 2048. In Figure 5, we
have plotted the annual exergy replacement costs of all mineral commodities over time and
have applied the Hubbert’s bell shape curves, including a combined cumulative curve for all
commodities analysed. This type of representation will be named here as “Exergy
countdown”, since it shows in a very schematic way the amount of exergy resources available
and the possible exhaustion behaviour that they will follow. The curves provided for lead,
zinc and silver should be noted with caution, since as stated before, the model does not
satisfactorily apply for that group of metals.
Figure 5: Exergy countdown of the main minerals produced in Australia
In Figure 5, the bell shaped curves of all fuels plus those of iron and copper are represented.
As can be seen, in irreversible exergy terms, coal is the most abundant resource, followed by
iron. Until the end of the first decade of the 21st century, both commodities will be extracted
at similar rates. However, the predicted peak of iron production in the second decade of the
21st century will slow down the extraction of the metal, while coal will clearly dominate the
mineral extraction in Australia. Figure 5 also shows the significantly lower amount of the
exergy cost reserves of natural gas and oil compared to iron and coal. Similar observations
can be seen for the rest of the metals considered. It is interesting to notice that although
copper is the most abundant commodity in exergy terms (apart from iron), the greater
extraction rate of that mineral will result in it having a faster depletion than that of nickel.
Similarly, although the exergy cost reserves of zinc and nickel are similar, the greater
extraction rate of zinc implies that the peaking year of that metal will be reached before that
of nickel. The graph also shows the smaller relative amount of the commodities of lead, gold
and silver. The exergy countdown diagram of a country allows us to predict future mineral
productions and the depletion degree of the commodities. This way, for instance, we can
forecast according to our results, that in year 2050, about 64% of the total considered mineral
reserves in Australia will be depleted in terms of exergy. Particularly, gold will be depleted at
99.9%, copper at 90.3%, lead at 87%, zinc at 97.3%, nickel at 60.4%, iron at 80%, coal at
52.4%, oil at 95.9% and natural gas at 85.2%.
It must be pointed out, that the latter minerals are not the only ones extracted in Australia.
Other minerals such as uranium, alumina, manganese, tin, diamonds and mineral sands are
also produced. The lack of historical information on ore grade trends for most of these
commodities prevents a similar thorough exergoecological analysis. Additionally, more
mineral resources could be found in the future, thereby shifting the peaking year to later dates.
However, repeating the same analysis assuming that the current proven reserves will double,
would shift the peak only by 15 to 30 years. Hence, the figures provided are reasonable to
provide a reasonable view of the magnitude of the global exergy degradation in Australia due
to mineral extraction.
CONCLUSIONS
This paper has showed that exergy analysis could be used as a tool for assessing mineral
resources on Earth. Unlike other economical or physical evaluations, the property exergy
takes into account all facets that make a natural resource valuable. Accordingly, in a single
indicator, it is possible to assess quantity, chemical composition and concentration.
Furthermore, through unit exergy costs, it is possible to assess the state of technology.
Another advantage of exergy is that it can be summed up for all minerals, whereas it is
impossible with mass: i.e. tonnes of copper plus tonnes of oil.
As a case study, we have applied the exergoecological approach to the assessment of the
degradation of gold, copper, nickel, silver, lead, zinc and iron in Australia throughout their
mining history until 2007. Analysis has shown that more than 50% of gold, silver and lead
have been mined, making the mining of these metals unsustainable in the long-term. The
mining of nickel, iron and copper is taking place in Australia at a relatively slower rate, with
significantly less than the majority mined to date and are arguably being mined at a more
sustainable rate. The sustainability of zinc can be ordered between both groups. In addition,
analysis also showed that the exergy replacement cost of the studied mineral capital extracted
in Australia is equivalent to 45.5 times Australia’s 2007 primary energy consumption. This
indicates a very significant value of lost natural capital.
The “Exergy countdown” graphs provide a practical representation of the mineral reserves
available and the possible extraction behaviour of the commodities. With the exergy
countdown, we have predicted that by the year 2050 about 64% of the main mineral
commodities produced in Australia will be depleted. Moreover, except for coal, iron and
nickel, more than 85% of the mineral reserves will be effectively exhausted by then.
The extraction of minerals produces a significant exergy decrease in the natural stock of our
planet. Conventional economics only accounts for the energy required in the extraction and
refining processes - whereas a fair accountability of resources should also take into account
the decrease of the non-fuel mineral capital endowment. This means that the true yearly
balance of the exergy decrease in the mineral endowment of the planet should account for, at
least, the exergy of fossil fuels production plus the exergy replacement costs of the extracted
non-fuel minerals as shown in Fig. 8.
The exergy analysis together with the exergy countdown of minerals could constitute a useful
prediction tool for assessing the degradation degree of non-renewable resources. However,
this technique requires world trends of natural resources production and consumption, and
trends of ore grades and mineral reserve projections which are often not readily available.
Better compilation of world mineral data would allow for more accurate accounts of natural
capital using exergoecological methods.
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TABLES
Metal
kc
kch
Ag
7041.8
1
Au
422879.0
1
Cu
343.1
80.2
Fe 97.4 5.3
Ni
431.8
58.2
Pb
218.8
25.4
Zn
125.9
13.2
Table 1: Unit exergy costs (dimensionless) of seven base-precious metals (updated from
Valero and Botero, 2002)
Mineral
Time period
R/P,
years
%Reserves
lost
Bt* lost,
Mtoe
Au
1859 - 2007
24
66
11.60
Cu
1844 - 2007
68
25
119.83
Ni
1967 - 2007
127
14
31.62
Ag
1884 - 2007
24
63
2.41
Pb
1859 - 2007
35
63
44.89
Zn
1897 - 2007
30
52
111.61
Fe
1907 - 2007
63
21
5820.34
TOTAL
6142.31
Table 2: Reserves data and cumulative exergy losses in the Australian mining industry
FIGURES
Fuels
Minerals
Natural stock Man-made stockReference
Environment
Dispersed
materials
Natural
refining
process
Recycled materials
Disposed of materials
Replacement costs Extraction and processing costs
Natural
conc.
process
Man-
made
mining
and
conc.
process
Man-
made
refining
process
Figure 1: Processes involved in the production of a raw-material
0
200
400
600
800
1,000
1,200
1844
1854
1864
1874
1884
1894
1904
1914
1924
1934
1944
1954
1964
1974
1984
1994
2004
Cumulative Total Exergy (Bt) (ktoe)
0
5
10
15
20
25
30
Ore Grade (Xm) (%Cu)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Copper
0
100
200
300
400
500
600
1967
1972
1977
1982
1987
1992
1997
2002
2007
Cumulative Total Exergy (Bt) (ktoe)
0
1
2
3
4
5
Ore Grade (Xm) (%Ni)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Nickel
0
200
400
600
800
1,000
1,200
1859
1869
1879
1889
1899
1909
1919
1929
1939
1949
1959
1969
1979
1989
1999
Cumulative Total Exergy (Bt) (ktoe)
0
14
28
42
56
70
84
Ore Grade (Xm) (%Pb)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Northampton
field only (hand-
sorted ore)
Lead
0
1,000
2,000
3,000
4,000
5,000
6,000
1898
1908
1918
1928
1938
1948
1958
1968
1978
1988
1998
Cumulative Total Exergy (Bt) (ktoe)
0
3
6
9
12
15
18
Ore Grade (Xm) (%Zn)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Zinc
0
275
550
825
1,100
1,375
1,650
1884
1894
1904
1914
1924
1934
1944
1954
1964
1974
1984
1994
2004
Cumulative Total Exergy (Bt) (toe)
0
600
1,200
1,800
2,400
3,000
3,600
Ore Grade (Xm) (g/t Ag)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Silver
0
16
32
48
64
80
96
1857
1867
1877
1887
1897
1907
1917
1927
1937
1947
1957
1967
1977
1987
1997
2007
Cumulative Total Exergy (Bt) (toe)
0
9
18
27
36
45
54
Ore Grade (Xm) (g/t Au)
Concentration Exergy (Bc)
Chemical Exergy (Bch)
Ore Grade (Xm)
Gold
Figure 2: Ore grade and cumulative exergy consumption of the Australian mining industry –
copper, nickel, lead, zinc, silver and gold
0
150,000
300,000
450,000
600,000
750,000
900,000
1907
1912
1917
1922
1927
1932
1937
1942
1947
1952
1957
1962
1967
1972
1977
1982
1987
1992
1997
2002
2007
Cumulative Total Exergy (B
t
) (ktoe)
0
15
30
45
60
75
90
Ore Grade (X
m
) (%Fe)
Concentration Exergy (B
c
)
Chemical Exergy (B
ch
)
Ore Grade (X
m
)
Assumed data only
(see Mudd, 2007)
Iron
Assumed data only
(see Mudd, 2007)
Figure 3: Ore grade and cumulative exergy consumption of Australian iron mines
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
B*
t
, ktoe
Other metals (Cu, Ni, Pb, Zn, Au, Ag)
Iron
Oil
Coal
Natural gas
Figure 4: Decrease of Australia’s mineral exergy stock, 1969 to 2007
0
100,000
200,000
300,000
400,000
500,000
1900 1950 2000 2050 2100 2150
Bt* (ktoe) - Coal, Oil, Natural Gas
Coal - peak model
Coal - actual
Oil - peak model
Oil - actual
Natural Gas - peak model
Natural Gas - actual
Coal peak: 2048
R
2
- 99.48%
Oil peak: 1997
R
2
- 96.23%
Natural Gas peak:
2025
R
2
- 98.94%
0
60,000
120,000
180,000
240,000
300,000
360,000
1900 1950 2000 2050 2100 2150
Bt* (ktoe) - Iron
0
2,000
4,000
6,000
8,000
10,000
12,000
Bt* (ktoe) - Copper, Gold
Iron - peak model
Iron - actual
Copper - peak model
Copper - actual
Gold - peak model
Gold - actual
Iron peak: 2026
R
2
- 97.10%
Copper peak:
2020, R
2
- 97.59%
Gold peak:
2025
Gold
R
2
- 86.29%
0
600
1,200
1,800
2,400
3,000
3,600
1900 1950 2000 2050 2100 2150
Bt* (ktoe) - Lead, Zinc, Silver, Nickel
Lead - peak model
Lead - actual
Zinc - peak model
Zinc - actual
Silver - peak model
Silver - actual
Nickel - peak model
Nickel - actual
Silver peak: 2005
Lead peak:
1996, R
2
- 88.52%
Zinc peak: 2025
R
2
- 95.99%
Nickel peak:
2040, R
2
- 92.05%
Silver
R
2
- 79.85%
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
1900 1950 2000 2050 2100 2150
Bt* (ktoe)
Oil
Natural Gas
Other Metals
Coal
Iron
Figure 5: Exergy countdown of the main minerals produced in Australia
