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Geological Su rvey o f Fin land
Unit
Place of business
1.3.2021
Report numbe r: 16/2021
Geo lo gian tutki muskes kus | Geologiska forskningscentralen | Geolo gical Survey of Fi nland
Espoo • Kokkola • Kuopio • Loppi • Outokumpu • Rovaniemi
www.gtk.fi • Puh/Tel +358 29 503 0000 • Y-tun nus / F O-nummer / Busi nes s ID: 0244680-7
The Mining of Minerals and the Limits to
Growth
Simon P. Michaux
Geological Su rvey o f Fin land
The Mining of Minerals and the Limits to Growth
1.3.2021
Geo lo gian tutki muskes kus | Geol og iska fo rsk nin gscen tralen | Geo logic al Surv ey of F inl and
GEOLOGICAL SURVEY OF FINLAND DOCUMENTATION PAGE
Date 01/03/2021
Authors
Simon P. Michaux
Ty pe of repor t
Open File Work Report
Commission by
GTK
Title of r eport
The Mining of Minerals and the Limits to Growth
Abstract
Current industrialization has a foundation in the continuous supply of natural resources. The methods
and proces s es as s ociated with this foundation have significant momentum. This paradigm will not be
undone easily. Human nature and human his tory make it s o. Currently, our industrial systems are
absolutely dependent on non-renewable natural res ources for energy sources.
For the last 15 years , it has been apparent that the indus trial bus iness environment has been more
challenging and volatile. This report will present the thesis tha t this pers ist ent volat ility is t he for erunner
temporal markers that show the indus trial ecosystem is in the process of radically changing.
Current thinking is that European indus trial bus inesses, will replace a complex industrial ecosystem that
took more t han a century t o build. This sys tem was built with t he support of t he highe st c alorific ally dense
sour ce of energ y the world has ever know n (oil), in chea p abundant quantit ies, with eas ily ava ilable credit,
and unlimited mineral resources. This task is hoped to be done at a time when there is comparatively
very expensive energy, a fragile finance system saturated in debt, not enough minerals , and an
unprecedented number of human populations, embedded in a deteriorating environment.
It is appar ent that the goal of indust rial sc ale t rans ition away fr om foss il fuels into non-fossil fuel systems
is a much larger task than current thinking allows for. To achieve this objective, among other things, an
unprecedented demand for minerals will be required. Most minerals required for the renewable energy
trans ition have not been mined in bulk quantities before. Many of the technology metals already have
primary res ource mining supply risks
At its foundation, the current industrial ecosystem was and still is based around the consumption of
natural resources, which were considered to be infinite. The very idea that there might be system based
limits to the g lobal extraction of resources is considered foolish by the current economic market. The
volume of manufa cture was influenc ed by the c ons umption dema nd of produc ts. Growt h and expans ion
wit h no cons idered limits of any kind w as t he underlying para digm.
The majority of infrastructure and technology units needed to phase out foss il fuels has yet to be
manufactured. Recycling cannot be done on products that have yet to be manufactured. In the current
sys tem, de mand for meta ls of a ll kinds have been increa sing, jus t as the gr ade of ore s proce ssed has been
decr eas ing.
Global reserves are not large enough to supply enough metals to build the renewable non-fossil fuels
industr ial syst em or s atis fy long ter m demand in the current syst em. Miner al depos it dis covery has be en
declining for many metals. The grade of processed ore for many of the industrial metals has been
decreasing over time, resulting in declining mineral processing yield. This has the implication of the
increa se in mining energ y consumption per unit of me tal.
Mining of minerals is intimately dependent on fossil fuel based energy supply. Like all other industrial
activities, without energy, mining does not happen. A case can be made that the window of viability for
the fossil fuel e nergy s upply ecos ystem ha s been closing for 5 to 10 years.
Geological Su rvey o f Fin land
The Mining of Minerals and the Limits to Growth
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Geo lo gian tutki muskes kus | Geol og iska fo rsk nin gscen tralen | Geo logic al Surv ey of F inl and
It becomes hig hly rele vant t hen t o examine how mining ecos yste m interac ts with t he e nergy e cosys tem.
The IMF Metals Index and the Crude Oil Price Index correlates strongly. This suggests that the mining
industrial operations to meet metal demand for the future are unlikely to go as planned.
The implica tions are t hat t he ba sic pr ediction of the origina l Limits t o Growt h s yste ms s tudy (Meadows et
al 1972) wa s conc eptually correc t. Jus t s o, it s hould be considered tha t the indust rial ecos yst em and t he
society it supports may soon contract in size. This implies that the current Linear Economy sys tem is
serious ly unbalanced and is not remotely s ustainable. The Limits to Growt h conclusions sug ges t at s ome
point, the global society and the global industrial ecosystem that support it will radically change form.
It is clear that society consumes more mineral resources each year. It is also clear that society does not
really understand its dependency on minerals to function. Availability of minerals could be an issue in the
future, where it becomes too expensive to extract meta ls due t o decreas ing gra de.
This report proposes that the fundamental trans formation of the global ecosystem predicted by the
original Limits to Growth study, has been in progress since 2005, for the last 16 years. The indus trial
ecos ystem is in the process of transitioning from growth based economics to contraction based
econom ics. This will a ffect all sectors of the g lobal ecosys tem, a ll at the sa me time (in a 20 year window).
We are there now and should respond accordingly.
If t he Limit s to Growth st udy is t ruly a g ood model for pre dicting the indus tria l ecos ystem, then the current
industr ial pra ctice is inappropriat e. The continue d devel opment of the economic gr owth par adigm would
become increasingly ineffective, and a waste of valuable resources. All such efforts would be pushing in
the wrong direction with poor results.
The rules of industrialization and the sourcing of raw materials are changing into a new era of bus iness
model. Change is happening, whether we are ready for it or not.
A possible response to these structural changes is presented after conclus ions on page 52, where it was
recommended that a new resource management system
should be developed after genuinely
unders tanding the net position of long term minerals supply. Also, it was recomended that new mining
frontiers be opened, but the minerals extracted should be used differently.
Keywords
Minerals, resources, production, decreasing grade, decreasing discovery rate,
mineral te x ture,
grind size, ore hardness, mining waste, energy consumption, metals price, Limits to Growth
Othe r infor mation
N/A
Repor t seria l
16/2021
Ar chive code
Total pages
69
Language
English
Price
N/A
Confidentiality
Public Domain
Unit and section
KTR Circular Economy Solutions
IS BN Numbe r:
ISBN 978-952-217-41 3-0
Sig nature /S imon Michaux
Assoc iate P rofessor Geometallurgy
Sig natur e/S aku Vuori
Dir ector , Scie nce and Innovations
Geological Su rvey o f Fin land
The Mining of Minerals and the Limits to Growth
1.3.2021
Geo lo gian tutki muskes kus | Geol og iska fo rsk nin gscen tralen | Geo logic al Surv ey of F inl and
Contents
Documentation page
TABLE OF CONTENTS
1 Introduction 1
2 The Linear Economy and What minerals do for us 2
3 The Circular Economy is not really geared for current metric of economic growth 4
4 The mining of primary resources 4
5 Recycling 7
6 Mineral Reserves and Resources 8
7 Declining Minerals d iscove ry 10
8 Decreasing of Ore Grade 12
9 Mineral processing p lant gr ind size is decreasing 18
10 Ore is getting harder to crush and grind 23
11 Mining water consumption is increasing 24
12 Production of Mining Waste is increasing 28
13 Energy in min ing 29
14 The current industrial ecosystem is heavily dependent on fossil fuels 37
15 Limits to Growth 41
16 International Free Trade and Globalization is Under Strain 47
17 Conclusions 48
18 Possible Response to the Challenge 51
18.1 Develop a new resource management system 52
18.2 Open up new mining frontiers and use them differently 52
19 References 54
20 Appendix A – Chinese Corporate Investment & Mineral Supply Global Market Share 61
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1 INTRODUCTION
For the last 15 years, it has been apparent that the industrial business environment has been more
challenging and volatile. This report will present the thesis that this persistent volatility is the forerunner
temporal markers that show the industrial ecosystem is in the process of radically changing.
Current thinking is that European industrial bu sine sse s, w ill replace a complex industrial ecosystem that took
more than a century to build. This syste m was built with the support of the highe st calorifically de nse source
of energy the world has ever known (oil), in cheap abundant quantities, with easily available credit, and
unlimited mineral resources. This task is hoped to be done at a time when there is comparatively very
expensive energy, a fragile finance system saturated in debt, not enough minerals, and an unprecedented
number of human populations, embedded in a deteriorating environment.
Most challenging of all, this is to be done in a few short decades, with a stated target of 100% of the vehicle
fleet will be EV ’s by 2050 (Europe an Commission 2019a). It is the authors opinion that this will not go to
plan.
It is apparent that the goal of industrial scale transition away from fossil f uels into non-fossil fuel systems is
a much larger task than current thinking allows for. To achieve this objective, among other things, an
unprecedented demand for minerals will be required.
Most minerals required for the renewable energy transition have not been mined in bulk quantities before.
Many of the technology metals already have primary resource mining supply risks (Figure 1).
Figure 1. Some primary mining sources for a number of metals have clear supply risks (Source: Report On Critical Raw Materials
For The EU May 2014) (Copyright License: https://creativecommons.org/licenses/by-nc-sa/4.0/)
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In 2019, less than 0.5% of the global fleet of vehicles are EV based technology and in 2018, renewable energy
(excluding hydroelectricity) accounted for less than 5% of primary energy demand (BP Statistical Review of
World Energy 2019 & IEA 2019). The vast majority of the proposed Circular Economy support systems have
yet to be manufactured. As it is not possible to recycle something that has yet to be manufactured, the
source for this unprecedented quantity of metals will have to be sourced from mining.
Very preliminary calculations show that current production rates of metals like lithium, nickel and cobalt are
much lower than what will soon be required. It is equally apparent that current global reserves are also not
enough. This will require sharp increase in the required mines to be operating in a few short years. Just so,
a very large number of feasibility studies and pilot scale studies will be needed.
2 THE LINEAR ECONOMY AND WHAT MINERALS DO FOR US
The Circular Economy was designed to replace the Linear Economy (Figure 2). This was the system that
evolved out of the industrial revolution phases IR1, IR2 and IR3. The basic formula was the raw materials
needed for manufacture was sourced by mining of minerals only, and growth that later has been shown to
be exponential. Waste products were dumped into landfill, or simply abandoned at the point of being
discarded. Recycling was a ve ry limited activity. All energy source s were fossil fuel non-rene wable finite
natural resources (oil, gas, and coal).
Figure 2. The Linear Economy (Image: Simon Michaux)
Primary Raw
Resource
Extraction
Waste
Disposal/ Land
Fill
Metal
Smelting
Manufacture
Distribution
Consumption
Population
Growth
Growth based
economics
Supply & Demand
dynamic free market
Unit price (£, $, €, ¥) as a
metric and control mechanism
Becoming impractical due to
available land space
Becoming impractical due to rising cost
of extraction and geopolitical supply risk
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At its foundation, the Linear Economy was and still is based around the consumption of natural resources,
which were considered to be infinite. The very idea that there might be system based limits to the global
extraction of resources is considered foolish by the current economic market. Figure 2 should be put in
context of Figure 3, that shows human population growth and energy consumption growth.
Figure 3. Estimated total resource consumption by each person in American society across their lifetime, 2018 data
(Source: U.S. Mineral Education Coalition)
The volume of manufacture was influenced by the consumption demand of products. Growth and expansion
with no considered limits of any kind was the underlying paradigm. The Linear Economy was made possible
with the harnessing of fossil fuels, a cheap abundant energy source. Oil in particular was the most
calorifically dense energy resource the World had eve r known (Michaux 2019).
This system would have continued if certain limitations had not become apparent. In Europe, development
of land use made it very difficult to justify landfill waste disposal. For a short time, some waste was shipped
to the Southern Hemisphere for disposal. The catalyst for the development of a new more sustainable
system was the realization that almost all of the Critical Raw Materials was sourced outside of Europe. So,
both the primary raw material extraction and the waste disposal parts of the Linear Economy became a
perceived difficulty for the future of Europe.
From a systems point of view, the Linear Economy is showing signs of stress and strain. The logical
progression would be the transformation of the Linear Economy into something else, that was structured to
manage the limits of resource consumption, and resource stewardship more effectively (Taylor 2008).
The genius of the Circular Economy was to merge these two bottleneck points in the linear value chain,
where the output of one could be the input of the other. Just so, recycling became the strategic important
technology to develop.
Bauxite
1 001kg
Other minerals
and metals
19.8 tonne
Gold
60.34g
Coal
158 tonne
Clays
5 076kg
Cement
23.4 tonne
Natural Gas
195 952m3
Lead
393kg
Iron Ore
8.7 tonne
Salt
12 tonne
Phosphate Rock
6.97 tonne
Petroleum
2.775 billion litres
Copper
464kg Zinc
215kg
Stone, Sand & Gravel
581 tonnes
Tota l consumption over the lifetime:
1,37 million kilograms of minerals, metals and fuels
@2018 Mineral Education Coalition
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3 THE CIRCULAR ECONOMY IS NOT REALLY GEARED FOR CURRENT METRIC OF ECONOMIC
GROWTH
In the current industrial ecosystem, the underlying metric for operational success is growth. Current
economic ecosystems are geared to a growth of 2% per annum. Growth in all its forms is a metric of the
current system (The Linear Economy). Just so, the consumption of natural resources has steadily increase d.
The Circular Economy is an attempt to be sustainable. So, a fundamentally different business model must
be the foundation of whatever the Circular Economy might become. While the Circular Economy attempts
to do this, at its foundation, it still is based on market growth and uses money made as the metric f or success,
where target objectives are to still deliver 2% p.a. growth while reducing resource consumption.
4 THE MINING OF PRIMARY RESOURCES
Figure 4 shows how resource consumption has increase on a global scale between the year 2000 and the
year 2018. Consumption of most metals, minerals and energy raw materials from mining have increased in
this time frame.
Figure 4. Global annual consumption of mineral resources between the year 2000 and 2018
(Source: USGS data, World Bank data, BP Statistics 2011, BP Statistics 2019)
There is a school of thought that economic growth can be sustained with “intangible value creation”. Figure
4 shows that the industrial ecosystem and the economic growth it outputs, requires physical raw materials
to function. The system is not getting more efficient in consuming physical raw materials. For intangible
value creation to work, a fundamental restructuring of how the technology is delivered and applied would
be required. Innovations like cryptocurrencies may be virtual in nature (exist as data on the internet), but
they still have a real world physical footprint.
For example, on March 18, 2021, the annual power consumption of the Bitcoin cryptocurrency network was
estimated to be 129 terawatt-hours (TWh) (Source: Cambridge Centre for Alternative Finance, Science Mag,
96.4 %
96.4 %
40.2 %
144.3 %
26.5 %
60.3 %
66.5 %
European CRM List
Base Metals (World Bank)
Precious Metals
Industrial Minerals
Oil
Gas
Coal
Global Production Increase 2000 to 2018
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Ne w York ISO, Forbes, Facebook, Reedy Creek Improvement District, Worldometer). To put this in context,
the annual electric consumption of the nation Netherland’s in 2019 was 121.0 TWh (BP Statistical Review of
World Energy 2020). All economic activity has a footprint in the physical world in some context, with a raw
materials consumption profile.
The World Bank uses copper consumption as one of the proxies to model the global industrial ecosystem.
Figure 5 shows global production of some metals, and Figure 6 shows global copper production over the last
112 ye ars. Copper consumption between 1985 and 2008 (23 years) accounted for half of all copper ever
mined globally in a historical context. Projected world consumption between 2009 and 2030 (21 years) is
predicted to exceed all of the copper metal ever mined historical prior to 2009.
In 2019, global consumption of copper metal was 24.5 million tonnes and global copper reserves was
reported at 870 million tonnes (USGS mineral statistics). Using a straight and crude calculation, this means
that current reserves represent 35.5 years of supply at 2019 mining and recycling rates. Copper demand is
projected to increase to approximately 100 million tonnes per annum by the ye ar 2100. Just so, more copper
deposits are required to be discovered and de veloped into producing mines. This may be more difficult than
first understood (Figure 13).
Figure 5. Mining production 1825 to 2008 (Source: Mudd 2009- updated 2012, A nal yst- Gavin Mudd)
There is a current paradigm to phase out fossil fuels and all associated infrastructure. This will require an
unprecedented volume of metals of all kinds. In particular, Technology metals. Technology me tals are the
building materials needed to manufacture much of current state-of-the-art technology. Technology metals
could include: Be, B, Sc, V, Ga, Ge, Se, Sr, Y, Zr, In, Te, Cs, Ba, La, Hf, Ta, Os, Tl, Li, Ru, W, Cd, Hg, Sb, Ir, Mo
and Mg. For Europe in particular, most global supply of these metals is sourced externally and is highly
depende nt on imports (Figure 7).
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Figure 6. Global copper production 1800 – 2012 (Source: Mudd 2009- updated 2012, Analyst- Gavin Mudd)
Figure 7. Global supply of EU Critical Minerals and Metals (Source: SGU)
0
2
4
6
8
10
12
14
16
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
Annual Copper Production (Mt Cu)
USA
Australia
Canada
Chile
China
Africa
Europe
Rest
of the
World
0
0.1
0.2
0.3
0.4
0.5
0.6
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0.8
0.9
1
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
Annual Copper Production (%proportion)
USA
Australia
Canada Chile
China
Africa
Europe
Rest
of the
World
Cum. Prod to 2011 (Mt Cu):
Chile –132.2
USA –110.1
Europe –92.4
Africa –82.6
Canada –41.4
Australia –23.1
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5 RECYCLING
Base metals like Al, Cu, and Fe can be recycled with mature processes to a high degree of stream recovery.
Precious metals like Au, Ag and PGE can also be recycled through more complex process methods. This has
been developed due to the high value of the target metals. The recycling of technology metals is either not
done very well, or not done at all.
Recycling also can only be done so many times before the feedstock becomes useless. Natural laws such as
physics and thermodynamics determine the maximum achievable recycling rate as a function of the quality
of the recycling (side stream intermediate) products (Reuter et al 2006). It can be concluded that the
recyclability of a product is not only determined by the intrinsic property the different materials used, but
by the quality of the recycling streams (Reuter et al 2006). This material stream quality is determined by the
mineral classes (combination of materials due to design, shredding and separatio n), p article siz e dis tribution
and degree of liberation (multi-material particles) and the efficiency of physical separation.
This implies that waste streams cannot be recycled indefinitely before they need to be valorized by some
other form. This is something that is not included in current thinking. Figure 8 shows the recycling rates in
2011. Current recycling rates will resemble these extraction efficiencie s.
Figure 8. Recycling rates of metals (Source: United Nations Environment Programme, Recycling Rates of Metals (2011) / C&EN
May 30, 2011) (Copyright License: https://creativecommons.org/licenses/by-nc-sa/4.0/)
In 2019, there was 7.2 million Electric Ve hicles (IEA 2020). The global fleet of vehicle s was estimated to be
1.416 billion vehicles (Michaux 2021). This me ans that just 0.51% of the global fleet is currently EV
technology, and that 99.49% of the global fleet has yet to be replaced.
In 2018, the global system was still 84.7% depende nt on fossil fuels, where renewables (including solar, wind,
geothermal and biofuels) accounted for 4.05% of global energy generation. At the very least, 84.7% of the
primary energy supply is required to be replaced with non-f ossil fuel systems.
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The majority of infrastructure and technology units needed to phase out fossil fuels has yet to be
manufactured. Recycling cannot be done on products that have yet to be manufactured. The current focus
of the Circular Economy development is recycling, with the perception that mining of mineral resources is
not relevant. However, the system to phase out fossil fuels (whatever that is) has yet to be constructed, and
this will require a historically unprecedented volume of mine rals/metals/materials of all kinds.
6 MINERAL RESERVES AND RESOURCES
A use f ul way to quantify resource materials like metals in conte x t of energy consumption or embedded
energy previously consumed, is exergy. In thermodynamics, the exergy (in older usage, available work
and/or availability) of a system is the maximum useful work possible during a process that brings the system
into equilibrium with a heat reservoir. After the system and surroundings reach equilibrium, the exergy is
zero. Figure 9 and Figure 10 shows the known reserves of various metals, minerals, and energy resources,
in terms of exergy.
Much like oil extraction, once you get to the peak of production the start of difficulties to deliver product
become common place. These difficulties in production are more of an inefficiency rather than a genuine
problem, resulting in stagnation in output. Then there is the downward slide of production on the back side
of the peak. This same pattern will be observed in metal mining.
Figure 10
Figure 9. Metals and minerals raw material manufacturing landfill cycle – energy resou rces
(S ource: Val ero & Val ero 2 014 - A Thermodynamic Cradle-to-Cradle A ssessment) (copyright granted)
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Figure 10. Metals and minerals raw material manufacturing landfill cycle – mineral res ources
(S ource: Val ero & Val ero 2 014 - A Thermodynamic Cradle-to-Cradle Assessment) (copyright granted)
Figure 11 and Figure 12 shows the results of a study that examined existing reserves, deposit by deposit, in
context of predicted future copper production. As can be observed, more copper deposits will be required
to be discovered and a considerable size of copper content within a few decades.
Figure 11. Peak copper production prediction Geologic Resources Supply-Demand Model (GeRS-DeMo) all producing countries summed
(Source: Northey et al 2013)
0
5
10
15
20
25
30
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
Modlelled Production (Mt Cu)
Australia
Chile
China
FSU
Mexico
Peru
USA
Zambia
Rest of World
--
Demand
0%
20%
40%
60%
80%
100%
1900
1920
1940
1960
1980
2000
2020
2040
2060
2080
2100
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Figure 12. Peak copper production prediction Geologic Resources Supply-Demand Model (GeRS-DeMo) by country
(Source: Northey et al 2013)
7 DECLINING MINERALS DISCOVERY
Mineral deposit discovery has been declining for many metals (Figure 13 to Figure 15). As demand has
increased, all the large high grade, and easy to extract deposits have been found and mined out. It is getting
harder to find new deposits to replace the ones being consumed. The full extent of this pattern across all
industrial minerals is relatively unknown as the relevant data has not been complied into one dataset.
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Figure 13. Copper in major discoveries by year, 1990-2017 (Data as of July 18, 2018)
(Sourc e: S&P Global Market Intelligence)
Figure 14. Gold discoveries, production and pricing 1990 to 2013 (Source: SNL Metals and Mining)
0
500
1 000
1 500
2 000
2 500
3 000
3 500
4 000
4 500
5 000
0
20
40
60
80
100
120
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Copper exploration budgets (US$M)
Copper in major discoveries (Mt)
Copper in discoveries Projected copper in discoveries Copper exploraton budgets (US$M)
Gold discovered (million ounces)
Gold price ($USD/oz)
Gold
discovered
Gold
price
World mine
production
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Figure 15. Gold exploration budgets 2003 to 2017 (Source: S&P Global market Intelligence)
Gold exploration budgets were at an all-time high in 2012, while discoveries were at an all-time low. The
best gold discoveries are now years in the past.
8 DECREASING OF ORE GRADE
The grade of processed ore for many of the industrial metals has been decreasing over time (Figure 16 to
Figure 18). This has the implication of the increase in mining energy consumption per unit of metal.
Figure 16. Grade of mined minerals has been decreasing (Source: Mudd 2009- updated 2012, A nal yst- Gavin Mudd)
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Figure 17. Go ld-Barrick operations Nevada, Goldstrike & Cortez mines production & average gold yield (Source: SRSrocco Report)
Figure 18. Gold mine operating trends (Source: redra wn f rom Brook Hunt Metals Cost Service Analysis 2011)
6.0 11.7 11.6 29.6 23.9
12.04
5.63 4.6
2.34 3.02
0
2
4
6
8
10
12
14
0
5
10
15
20
25
30
35
1998 2003 2008 2013 2017
Yield (g/tonne)
Processed ore (million tonnes)
Gold-Barrick operations Nevada, Goldstrike & Cortez mines
production & average gold yield
Au Ore Processed Average Au Yield
2.3 Moz 2.1 Moz 1.7Moz 2.2 Moz 2.3 Moz
Total Annual
Au
33.0%
20.3%
50.7%
0.0%
-26.7%
-30.2%
-27.3%
-11.3%
-50% -30% -10% 10% 30% 50% 70%
Open pit ore milled
Underground ore milled
Ore heap leached
Open pit mill grade
Underground mill grade
Heap leach grade
Mill gold production
Heap leach gold production
Percentage Change between 2000 and 2009
Gold Mine Operating Trends
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Figure 18 and Figure 19 show the problem of decreasing grade from an operational context. The volume of
ore being processed increased between 20.3 to 50.7% between the years 2000 and 2009, gold production
decreased -11.3% and 0.0%. Mill gold grade had decreased between -26.7 and -30.2%. During this operating
period, an extra 12.1% of employee staff were employed. While productivity of volume of ore processed
increased by 17.6%, actual gold metal productivity declined by 18.9%.
Figure 19. Gold mine labour productivity (Source: redrawn from Brook Hunt Metals Cost Service Analysis 2 011)
The production metal yield of both gold (Figure 17) and silve r (Figure 20) has been steadily de clining.
Figure 20. D ecreasi ng ef ficien cy of silve r prod uctio n (S ource: S RSrocco Re port)
12.1%
17.6%
-18.9%
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
Employees
(thousands)
Productivity
(kg Au / man year)
Productivity
(kt ore / man year)
Percentage Change between 2000 and 2009
Gold Mine Labour Productivity
13
12,1
10,4 10,4
9,7 9,4
8,5
8,1
7,6 7,8 7,0
8,0
9,0
10,0
11,0
12,0
13,0
14,0
110
115
120
125
130
135
140
145
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
(million ounces)
Largest 7 Silver Company Production & Average Yield
(Ounces/Ton)
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Global peak silver production has already happened some time betwee n 1950 and the year 2000. 60% of all
historical volume of silver has been mined since 1950 (Figure 21). The implications of the trend shown in
Figure 16 to Figure 20 of decreasing grade is that more tonnes of ore needs to be mined for each unit of
metal extracted. This drives the cost of mining up with each associated task, from drilling and blasting,
excavation, haulage, crush and grinding and beneficiation (flotation or leaching).
Figure 21. Historical global silver production 1493 to 2017 (Source: SRS rocco Rep ort)
Figure 22. Global Copper Resources vs Grades (Source: Mudd et al 2013a)
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
1493-1600 1600-1700 1700-1800 1800-19 00 1900-1950 1950-2000 2000-2017
(millions ounces)
Historical Global Silver Production 1493 to 2017
26.34%
34.57%
20.95%
10.33%
3.71%
2.58%
1.5%
0.001
0.01
0.1
1
10
100
0.01 0.1 110
Contained Copper (Mt Cu)
Ore Grade (%Cu)
Epithermal
IOCG
Magmatic Sulphide
Orogenic Au
Porphyry
Sediment-Hosted
Skarn
VMS
Unknown / Miscellaneous
(Deposits <0.001 Mt Cu
not shown)
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Figure 22 shows a cross plot of how the different mineralogy’s and lithologies present in context of copper
grade vs. deposit size.
Figure 23 shows the current scientific thinking, how it is believed that the vast bulk of copper in mineralized
form is in ore that is ve ry low in grade, finely disseminated rock texture , with mineral grains that are very
small (Source: Mudd et al 2013b). Far smaller than current grinding technology can liberate. This highlights
the relationship between ore grade and mineral grain size.
Figure 23. Most of copper ores are low grade finely disseminated textures (Source: Mudd et al 2013b)
There is an exponential relationship between ore grade and the tons of waste that needs to be excavated,
per unit ton of metal produced (Figure 24). Again, this is driven by minerology.
Figure 24. Ore grade vs. tons of waste per ton of metal, for copper ores in South America
What this means, is the cost of mining is being driven up, as each of the higher quality deposits are extracted
and processed. In particular, the truck and shovel fleet in open pit mining is required to haul much more ore
per unit of metal, resulting in an increase in diesel fuel consumption.
To put things in appropriate context, de creasing grade does not mean that the supply of copper in the ground
is running out. It does mean that the supply of copper that is economical to extract is declining, forcing the
production cost going up. It also make s mining very reliant on the energy (die sel fue l in particular).
Mineralogical
Barrier
Current
Mining
Amount
Grade
Standard Cu
cut-off grade
~2% in 1995
Cu cut-off
grades ~0.1%
now considered
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What was considered ore in the year 2010 was considered overburden waste rock ( due to grade being be low
cutoff) in the early 1900’s. It could be argued that this was because it was not possible to extract the raw
material under economic conditions. The long-term constant real copper prices reinforce this statement by
showing that the industry have found a way to serve demand (using low grade ores) at reasonable prices.
Therefore, the ore content alone is not suitable for making a statement about the availability of raw
materials, but rather to show the enormous progress made by the technologies used (Rötzer & Schmidt
2018). That being stated, the next technological advance is required to become effective as soon as possible.
It could be shown that the ex ponential increase in the consumption of copper, for example, led to the mining
of ever larger deposits, which often have lower ore grades (Rötzer & Schmidt 2018). New technologies have
been de veloped to extract these de posits, and large shove l excavators and froth flotation, for example, have
made it possible to use ores with a low concentration of metal. Technology has been used to apply
economies of scale to meet increasing demand, while managing decreasing grades (Figure 25 to Figure 27).
Figure 25. Excavated ore, was dug out with annual labor, and delivered by horse and cart to the process mill
(Source: National Parks Survey 1972)
Figure 26. Open pit truck and shovel fleet (Image by DIEGO EFRAIN CADILLO TRUJILLO from Pixabay)
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Figure 27. Mining haul truck (Source: Dee Bradshaw)
As can be seen, the scale of the whole enterprise has gotten larger and more expensive. In 2013, a large
process plant had a capacity annual throughput of something like 50 million tonnes of ore, where a small
one had only 10 million tonnes a year. In 2013, the typical installed grinding power was of the something
like 28 MW. In 1940, the typical installed grinding power was of the something like ½ MW. The size of a
standard haulage truck had the carrying capacity of 280 tonnes of ore per load. In 1940, the standard haulage
truck was closer to 10 tonnes carrying capacity.
The industry is very far from running out of copper deposits. Large portions of the Andes mountain range in
South America is one massive copper deposit of extremely low grade. Parts of this massive system is higher
grade than others, which are economical to mine, where most of it is not. While copper market can sustain
an increasing copper price as a consequence of the cost of production, and the consumable materials are
still available (diesel fuel for example), then there will not be a shortage of copper. When the costs of mining
become too high, or supply of a vital consumable becomes unreliable, then that all changes.
9 MINERAL PROCESSING PLANT GRIND SIZE IS DECREASING
Another pattern that has been observed over a period of decades has been a decreasing grind size (also
called comminution plant closing size) in operating mines. This is related to the mineralogy of the ores being
process. Most of the easy to process ore deposits have been mined out and now it is standard practice to
process ores with more challenging rock textures.
Comminution is the process engineering term for rock breakage and is the reduction of mineralized ore from
one average particle size to a smaller average particle size, by crushing, grinding, or other processes. The
process of size reduction through comminution is important as it has economic significance. Curry et al.
(2014) found that the mill (defined as crushing, grinding and separation) typically accounts for between 35
and 50 per cent of the total mine costs. This is the particle size (expressed as a P80, or particle size that 80%
of the sample is smaller than) to which all samples for process separation a milled down in size through
grinding. The finer the required closing size, the more expensive and complex the comminution processing
plant needs to be (Figure 28).
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Figure 28. A mineral processing plant in the Southern Hemisphere (Source: Dee Bradshaw)
The comminution plant closing grind size is directly related to the mineral texture of the ore, and the average
mineral grain size containing the valuable metal. If the target mine rals are very small in grain size or are
embedded in complex rock texture, then the ore is required to subject to size reduction through grinding,
until enough of the target valuable mineral is exposed on particle surfaces for separation process like
flotation to work. Figure 29 shows the possible difference in rock texture at similar grades. Each example
in Figure 29 would have a different recovery and would need to be reduced to different grind size for full
liberation.
Figure 29. Different rock textures, each would have a different process recovery (Source and copyright: Cropp 2013)
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The process of comminution is to subject the sample to size reduction. The particle size required for the
effective liberation of the target mineral is defined by the mineralogy. For each mineral in the sample, there
would be a range of mineral grain size distribution. For process separation to economically effective, enough
of th ose particles h ave to be liberate d or partially lib erated ( Figure 30).
Figure 30. Particle size reduction through comminution and liberation of target minerals
(Image: Napier-Munn et al 1996, Copyright: JKMRC)
The size reduction to energy relationship is not linear though. The finer the grind size, the exponentially
larger energy required to comminute the ore to that size (Ballantyne & Powell 2014 and Hukki 1961) (Figure
31).
Figure 31. The Hukki energy size relationship shown as an imaginary example of the basic reduction characteristic plotted on
logarithmic paper. (Source: Hukki 1961)
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The implications of Figure 31 are that the finer the closing grind size, which is dictated by ore mineralogy and
texture, the expone ntially higher increase in energy requirements to grind that ore to that size. The tradeoff
between the cost of comminution to the target grind size and the degree of liberation and texture of the
valuable mineral particles has to be considered carefully.
A century ago, most ores being mined had mineral grains much larger than what is considered normal in
2021. In 1980, a sulfide mineral grain size requiring a plant grind closing size of 150 µm was considered
typical. Currently, a plant grind closing size of 4 to 5 µm is now economically viable. This change has been
driven by a change in ore texture regarding what has been considered economically viable (Figure 32).
Figure 32. Two different Zn-Pb-Ag mineralogy’s, resulting in two different plant grind sizes (S ource: Dee Bra dshaw)
As a broad pattern that can be seen ove r an extende d period of decades, the ore’s be ing processed have had
increasingly smaller grind sizes to be economically viable. This has been one of the factors increasing energy
consumption and the cost of mining.
Figure 33. The Australian multifactor productivity index for the mining sector has been declining
(Source: ABS 2015 Australian Bureau of Statistics)
1 mm
Target ore P80 = 150µm
10 µm
Target ore P
80
= 4µm
Biggest boom in histo
2005 to 2012
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Figure 33 shows a possible outcome of this at a regional scale. The Australian multifactor productivity index
steadily declined from the year 2001, in spite of the Australian mining industry working to reverse this trend.
The Multifactor productivity index (MFP) is defined as output per unit of combined inputs. Combined inputs
typically include labor and capital, but can be expanded to include energy, materials, and services. Figure
35 shows a 53% decre ase in Multifactor Productivity between 2001 to 2012. This means that in 11 years, as
steady increase in mining cost happened, w here 53% more measurable work had to be done to produce the
same unit mass of metal. What is interesting, is that the biggest mining boom in Australian mining history
happened between the years 2005 and 2011, yet the MFP index continued to consistently decrease. The
same pattern can be observed in South Africa and South America.
Something fundamental changed in the business model for the mining industry around the year 2001. What
this was has not been clear. It could have been the technological advancement that made fine grinding
economically viable. In 1999, there was a technological breakthrough. The IsaMill was released into the
marketplace, which was a fine grinding mill that could reliably grind ore down to 10 mm (Gao et al 2002).
It then became economically viable to extract very fine grained ore types, which were much more
commonplace. Starting in 1999, more and more mining operations procured and commissioned fine
grinding mills and ope rated mines with very complex ore textures (Figure 34). Since the n, other technologies
have been developed. There was a short transitionary time period (late 1990’s to the early 2000’s), where
conve ntional ball mills we re tried to produce very fine closing sizes. Very quickly, it became apparent this
was not very efficient and fine grinding took over.
The author hypothesizes, that from that point onwards, the business model behind mining changed, and the
costs of mining started in increase. This would not be j ust energy consumption, but quantity of ore processe d
as well. This could be why the peak in the MPF was seen in 2001, and why it steadily declined from that
point.
Figure 34. Cumulative installed p ower for commissioned IsaMill fine grinding units (Source: IsaMill)
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10 ORE IS GETTING HARDER TO CRUSH AND GRIND
Ore has also been getting harder to break over the last few decades. This has a direct outcome of requiring
more power draw (energy) to break the rock.
The mining’s industry standard to measure rock hardness is a rock breakage test called the Drop Weight Test
(or Drop Test). The Drop Test was developed by the JKMRC (Julius Kruttschnitt Mineral Research Centre) to
model the rock breakage process in comminution machines (Figure 35). JKMRC comminution models are
based on two sets of parameters (Napier-Munn et al 1996).
As the JKMRC methods aspired to model the ore characteristics separately from the processing machine
characteristics, these parameters were to be measured independently. To be useful, these parameters
needed to be experimentally measured in a way that the simulation models can exploit. The Drop Test has
been the most successful way to characterize the high energy impact of mineralized ore this to date.
Figure 35. (LHS) SAG Mill at Ministro Hales, Ch ile
(Source: Codelco F lick r http s://ww w.fli ckr.com /photo s/cod elco/ 36380 894030 /in/al bum-721576 844 523 207 42/)
(RHS) Schematic diagram of AG/SAG mill process mechanisms (Source: Napier-Munn et al 1996, copyright: JKMRC)
The objective of the Drop Test is to characterize the resistance to size reduction an ore has over a range of
applied energies by measuring an energy breakage curve used for comminution engineering. Individual
breakage events (points on the energy breakage curve) can be expressed as a specific comminution energy
level, Ecs (kWh/t), or as breakage or appearance functions.
Classification
Discharge
p
i
Breakage
New feed
f
i
Grate
High
energy
impact
Recycle
Low
energy
impact
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Figure 36. Comminution impact breakage summary of the JKTech database in 2012, of ap proxi matel y 3 0 00 DWT tests
(Source: Simon Michaux)
Figure 36 shows a summary of the measured A*b impact breakage parameter, from the JKTech data base of
approximately 3000 Drop Weight Tests. These tests were measured between 1980 and 2010. Each column
represents the average for the decade shown. The higher the number, the softer the rock that was
measured. Conversely, the lower the number, the harder the rock. As can be seen in Figure 36, ore being
processed in mines has been getting harder.
Over time, mines be ing ope ned have been processing different rock textures, which happen to be low grade
ore with fine ly disseminated target minerals (ve ry small mineral grain size ) . As it happens this kind of rock
texture happens to be much harder to break. This has been one of the contributing factors increasing ene rgy
costs, and mining costs in general.
11 MINING WATER CONSUMPTION IS INCREASING
Potable water consumption in mining has also been increasing both in volume and per unit mass of metal
produced. While mining is not the largest consumer of potable water, where industrial agriculture is the
primary application (Figure 37). Mining consumption is included into the Industrial Use category.
Nevertheless, an increase in water requirements at all will eventually become a sustainable development
problem to resolve. Global water use in the year 2000 was divide d as follow:
• 70% A griculture
• 22% Industry
• 8% Dome stic
71.5
62.3 61.6
55.0
57.0
59.0
61.0
63.0
65.0
67.0
69.0
71.0
73.0
75.0
1980's 1990's 2000's
Average A*b
Comminution Impact Breakage A*b
Harder ore
Sof ter ore
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Figure 37. World water use by economic sector (Source: Shiklomanov 2000)
The issue with any increase in water consumption is related to the perceived water scarcity that exists
already, let alone what may happen in the future with more human population and a deteriorating
environment (Figure 38 and Guppy & Anderson 2017). Without altering current levels of water consumption
and pollution, almost half of the world's population will suffer severe water stress by 2030, damaging the
well-being of millions of pe ople (UNEP 2016 and IRP 2016). Under current trends, demand for water will
exceed supply by 40 per cent in 2030, which will force governments to spend $200 billion per year on
upstream water supply as demand outstrips cheaper forms of supply.
Global water consumption is approximately 500,000 lite rs of f reshwate r per person every year (IRP 2016) .
In 2016, one billion people lacked access to safe drinking water, and 2.4 billion people did not have access
to adequate sanitation (Guppy & Anderson 2017).
Of the Wo rld’s total water supply, 97% is seawater and of the remaining, less than 0.5% is usable unpolluted
clean water. The amount of fresh water supply provided by the hydrological cycle does not increase. Water
everywhere on the planet is an integral part of the hydrologic cycle.
Many major rivers: Colorado, Ganges, Indus, Rio Grande and Yellow are so over-tapped that they now run
dry for part of the year (IRP 2016). Freshwater wetland has shrunk by about half worldwide between 1930
and 2000 ( Shiklomanov 2000).
In the Western Society, we take water for granted. Most people don’t actually think about the supply of
water. Water access is easy to ignore provided you can still turn on a tap and water comes out. We still have
the same amount of water in our ecosystem, but the supply of freshwater faces a three-pronged attack from
population growth, climate change and industrialization. As it currently stands, there’s not enough water to
go around (Figure 39).
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1930 1940 1950 1960 1970 1980 1990 1995 2000
Wat er draw (km3/ye ar )
World water use by economic sector (km
3
/year)
(Shiklomanov 2000)
Agriculture use
Municipal use
Industrial use
Reservoirs
Total (rounded)
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Figure 38. Global water consumption increase (Guppy & Anderson 2017)
(Copyright: https://www.unep-wcmc.org/terms-an d-con di ti o ns)
Figure 39. Global physical and economic water scarcity
(So urce: Wo rld W ater Develo pment Report 4. W orld Wa ter Assessment Programme (WWAP), March 2012)
The same paradigm of unawareness of potable water supply is within many parts industrial culture and is
reflected in development in the industrial ecosystem. Development of industrial sites with high potable
water volume requirements will increasingly conflict with the needs of the growing population.
Figure 40 shows a project developed to predict mining water use in Australia until the year 2050. As can be
observed potable water consumption is predicted to increase, with bulk commodities accounted for most of
the demand. The other metal ores (copper, gold, etc.) is a small proportion but will still increase.
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Figure 40. Total water required in gigalitres (109 liter) per year, in the base case scenario to 2050 for requirements of mining
(Source: Foran & Poldy 2002)
Figure 41. Water required by ore processing vs. ore grade in Australian mining industry (Source: Mudd 2011)
0
100
200
300
400
500
600
700
800
900
1,000
1,100
0 4 8 12 16 20 24 28
Ore Grade (%Cu, %Ni, %Pb ± Zn ± Cu, kg/t U
3
O
8
)
Embodied Water (kL/t Cu, kL/t Ni, kL/t Pb ± Zn ± Cu, , kL/t U
3
O
8
)
Copper
Copper-Gold
Nickel
Lead-Zinc-Silver
Zinc±Copper±Lead
Uranium
0
100
200
0 4
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Figure 41 shows how the required volume of potable water to produce a tonne of metal, compared to ore
grade. There is an inverse exponential relationship with water consumption and ore grade. What is driving
this is low grade ore is usually also disseminated very fine mineral grains. This means that the ore has to be
ground very fine (See Section 8). Grinding is a wet process and some of that water can be recycled. When
the ore has been ground to a fine size, it is much more dif ficult to re cycle the water as the slurry particle s
takes a long time to settle out in a thickener tank. This results in more water being consumed per unit of
metal produced.
Currently potable water consumption is a design cost for process plant design. In areas like Canada, or on
the Nordic Frontier (Finland, Sweden, Norway, Greenland, Denmark, and Iceland), potable water availability
is not an issue. Conversely, in parts of Africa, South America, Central Asia and Australia, potable water supply
is expensive and is managed carefully. These regions are where much of global mining is conducted. Any
increase in water demand in these regions could make mining operations unviable.
12 PRODUCTION OF MINING WASTE IS INCREASING
Demand for metals of all kinds have bee n increasing, just as the grade of ores processed has bee n decreasing.
The outcome of the combination of these two trends, is the massive increase in the generation of mining
waste, both process tailings and overburden waste rock. There will come a point when this cannot happen
in the way it has for the last 50 to 100 years. Figure 42 shows how the volume of waste rock has increased
in A ustralia betwe en 1898 and 2012.
Figure 42. Volume of waste rock produced from Australian historical mining
(Source: Mudd 2009- updated 2012, An alyst- Gavin Mudd)
In 1920, global average copper grade was 1.6%. In 2019, the average copper grade was approximately 0.5%.
Global demand for copper in 2019 was 24.5 million tonnes, which was extracted and refined, producing 4.9
0
330
660
990
1,320
1,650
1,980
2,310
0
40
80
120
160
200
240
280
1895 1905 1915 1925 1935 1945 1955 1965 1975 1985 1995 2005
Waste Rock (Gold, Black Coal)
Waste Rock (Cu, Diamonds, U, Brown Coal)
Copper (Mt)
Uranium (Mt)
Diamonds (Mt)
Brown Coal (Mm3)
Gold (Mt)
Black Coal (Mm3)
(Mm
3
)
(Mm
3
)
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billion tonnes of waste rock. The author has participated in feasibility studies for copper mines that had a
cutoff grade of 0.1%. If this became the global average by the year 2100, where copper annual demand is
projected to reach 100 million tonnes (ICSG), then 20 billion tonnes of waste rock would be generated each
year. There will come a point where this will become logistically impractical, not economically viable, or
environmentally irresponsible.
Figure 43 shows the waste plume from the Grasberg copper gold mine in Indonesia, as seen from satellite
imagery. While in operation, this mine had an annual waste plume of 80 million tonnes of process tailings
into the nearby river, and also annually produced 300 million tonnes of waste rock, placed in mullock heaps.
Total mine waste production up until the year 2011, was 1330 Mt of process tailings into the river, and 3820
Mt of waste rock.
Figure 43. Grasberg (Cu-Au) min e in Indonesia waste plume (Source: Gavin Mudd 2011 personal communication)
13 ENERGY IN MINING
Mining of minerals is an industrial activity that is highly dependent on energy (Figure 42). From diesel fuel
consumption to power the truck and shovel haulage fleet, to electricity power draw for the processing plant
to function (whe re the electricity is often ge nerated with gas or coal). Like all other industrial activities,
without energy, mining does not happen. It becomes highly relevant then to examine how mining
ecosystem interacts with the energy ecosystem.
Ene rgy is th e ma ster re sou rce. It allows and facilit ates all p hysical work don e, t he deve lopme nt of technology
and allows human population to live in such high density settlements like modern cities. The modern world
is heavily interdependent. Many of the structures and institutions we now depend upon function in a global
contex t. Energy as a fundamental resource underpins the global industrial ecosystem (Fizaine & Court 2016,
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Me adow e t al. 1972, Hall et al. 2009, Heinbe rg 2011, Marte nson 2011, Morse 2001, Ruppert 2004 and
Tverberg 2014).
Figure 44. Energy is the master resource that facilitates all industrial activities (Image: Simon Michaux)
Figure 45 shows the Metals Index and the Crude Oil Price Index (both developed and used by the
International Monetary Fund) plotted on the same chart. As can be observed, the metal’s price correlates
strongly with the oil price. Note the increase of both indexes around the year2001/2002. This correlates
with the peak shown in Figure 33. Both indexes crashed around 2008, which correlates with the Global
Financial Crisis.
Figure 45. Correlation between global metal price and crude oil
(S ource: I MF Pri mary C ommo dity Price S ystem, http://www.imf.org/external/np/res/commod/External_Data.xls)
Energy Consumption
•Petroleum products
•Power draw
Mineral Consumption
•Mining
•Refining/Smelting
Manufacture of
technology
Application of
technology
Available oil, gas
& coal deposits,
and their ERoEI
Available mineral
deposits, and their
grade, mineral grain
size & texture
30
50
70
90
110
130
150
170
190
210
230
250
270
2000M1
2000M8
2001M3
2001M10
2002M5
2002M12
2003M7
2004M2
2004M9
2005M4
2005M11
2006M6
2007M1
2007M8
2008M3
2008M10
2009M5
2009M12
2010M7
2011M2
2011M9
2012M4
2012M11
2013M6
2014M1
2014M8
2015M3
2015M10
2016M5
2016M12
Index value, Indexed to average of year 2005 = 100
Metals Price Index (PMETA)
Crude Oil Price Index (POILAPSP)
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As has been shown, the energy requirements to produce a unit metal through the mining of minerals has
been increasing for the last few decades for a number of fundamental reasons. Figure 46 shows how ene rgy
consumption in the Australian mining industry increased approximately 450% betwe e n the years 1973 and
2008.
Figure 46. Mining energy consumption 197 3 - 2007
(Source: Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) 2008 Australian Mineral Statistics)
Figure 46 shows that gas and diesel fuel (oil) provide the majority of current energy supply for mining. Future
development may be required to be operated using renewable energy supply in some form.
A challenge for the opening of new mines is their location, which is often in very remote undeveloped
geographical regions. These regions other require all necessary infrastructure (roads, rail, power supply,
etc.) to be constructed for the purpose of supporting the mine operation being proposed. For this reason ,
many new mines could be very remote from many of the proposed renewable electrical power generation
network. Moreover, these mines could be in geographical areas that will be some of the last regions to be
connected to the renewable power network. The challenge then becomes, to get a new mine opened, a
renewable power generation source would be required to be constructed at the same time, close enough to
the mine to be useful.
Future energy consumption in mining may become an increasingly sensitive design parameter and
engineering sources of energy consumption may well be optimized at a greater priority.
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Figure 47 shows how different mining and processing methods consume energy. This is a very different
concept to recovery ef ficiency. Different mineralogy's require different process paths. Understanding where
these process paths will change with lower grades and/or lower grind sizes is required.
Figure 47. Total energy consumption by process path (Source: Marsden 2008)
Figure 48 shows the energy intensity of various different process paths as a function grade, where flotation
(concentration – smelting) and leaching can be compared. The future availability of copper will also be
determined by the energy costs of its production. If there is no technological progress, geological factors
will be the main drivers of these costs. But in addition, the future development of geological parameters is
not known. However, if, for example, the ore grade falls to 0.5%, the CED will rise nearly 30% to 89 GJ-e q/t
Cu cathode in the absence of technological improvements. Figure 49 shows how different technological
events could interact the shape of the curve shown in Figure 49.
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Figure 48. Relationship between energy intensity of processing a tonne of copper vs. ore grade of copper
(Source: Norgate-Ja hans hahi, 20 10)
Figure 49. Schematic representation of the relationship between ore grade and cumulative energy demand (CED) and the
influen ce of diff erent market events (Source: Rötzer & Schmidt 2020)
0
300
600
900
1,200
1,500
00.5 11.5 22.5 3
Energy Intensity (GJ/t Cu)
Ore Grade (Cu/%)
Concentrate-Smelting (75 µm comminution)
Concentrate-Smelting (5 µm comminution)
Direct Smelting
Heap Leaching
Pressure Leaching
In Situ Leaching
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Figure 50 to Figure 52 shows how energy is partitioned up in different parts of the process flowsheet, with
some examples f rom Figure 47.
Figure 50. Energy consumed kJ per lb of copper produced, process path primary crush, SAG mill, ball mill, flotation, smelt, refine
(Image: Simon Michaux) (Source: Mars den 2 008)
Figure 51. Energy consumed kJ per lb of copper produced, process path primary crush, secondary crush, tertiary crush, HPGR, ball
mill, flotation, smelt, refine (Image: Simon Michaux) (S ource: Ma rsden 200 8)
Mining 6,000 (kJ/lb)
Primary crushing
& conveying
900 (kJ/lb)
SAG Milling
10,700 (kJ/lb)
Ball Milling
10,590 (kJ/lb)
Flotation &
regrinding
1,870 (kJ/lb)
Smelting
5,150 (kJ/lb)
Refining
2,700 (kJ/lb)
Transport to market 120 (kJ/lb)
Mining 6,000 (kJ/lb)
Primary crushing
& conveying
900 (kJ/lb)
Secondary
crushing
450 (kJ/lb)
Tertiary
crushing
450 (kJ/lb)
HPGR
1,100 (kJ/lb)
Ball Milling,
10,590 (kJ/lb)
Flotation &
regrinding
1,870 (kJ/lb)
Smelting
5,150 (kJ/lb)
Refining
2,700 (kJ/lb)
Transport to market 120 (kJ/lb)
C
V
C
V
C
V
C
V
C
V
C
V