mini-project report evaluating the energy inputs and co2...

Mini-project report

Evaluating the energy inputs and CO2 emissions of the nuclear cycle

Andrew Foster [email protected]

26.3.10

Evaluating the energy inputs and CO2 emissions of the nuclear cycle:

Uranium extraction

Andrew Foster

Supervisor: Dr R Hand

March 2010

Abstract

A process analysis was carried out for the Ranger uranium mine in Australia todetermine the energy input requirements of the site and the CO2 emissions associatedwith it. The analysis was then extrapolated to lower ore grades to estimate the effectthese have on the nuclear cycle. Energy inputs for Ranger were determined to liein the range 571-739GJ per tonne U3O8 with CO2 emissions of 0.75-1.08g per kWhbased on a light water reactor. The extrapolation suggested that ore grades below0.01% could play a significant role in reducing the efficiency of nuclear power if openpit mining is utilised.

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1 Introduction

One possible means of reducing anthropogenic influ-ence on the climate is to limit our dependence oncarbon-intensive fossil fuels within the global electric-ity generation mix. The associated implications forpower generating methods have engendered a changein the way in which nuclear power is marketed withthe World Nuclear Association (WNA) now stressingthe sustainable aspects of the technology [1]. Whilst itis generally accepted within the literature that nuclearpower produces lower CO2 emissions than fossil fuelsourced electricity [2, 3] the true extent of those emis-sions is still a matter for debate. Studies have shownthese to vary from a minimum of approximately 3.5gCO2-eq/kWh up to 100g CO2-eq/kWh [4, 5] or more.

A paper produced by Storm and Smith [6] in whichthe authors findings were considered excessively neg-ative by the nuclear community has found itself atthe focal point of argument over the true and poten-tial energy costs and greenhouse gas emissions (GHGs)associated with nuclear power. As part of the workthe extraction of uranium from ore bodies was consid-ered, with the results heavily criticized by the WNA. Avalue of 69PJ per tonne of uranium recovered from theRossing deposit in Namibia compared to the reportedonsite use of 1-2PJ is one particularly notable example[7, 8]. Whilst the Storm Smith value was intended toinclude indirect energy inputs, it is greater than theprimary energy consumption of the entire country ofNamibia [9]. The intention of the current work was toconduct a process analysis for a typical uranium mineand milling flowsheet using the most recent data avail-able and to compare it with the work of Storm andSmith and the statements of the WNA. The analysiswas then extrapolated as an approximate determina-tion of how decreasing ore grade could potentially af-fect the energy cost of mining and milling, as this isanother key source of disagreement between the twoparties.

2 Methodology – Ranger ProcessAnalysis

Many of the world’s current fleet of nuclear reactorsutilize the open ‘once-through’ cycle, where fuel isloaded into the reactor, burnt and discarded as waste.One outcome of this is that an input of fuel equiva-lent to demand must be sourced continually, with themajority of the uranium feedstock for enrichment cur-rently obtained from mining virgin material, the restsourced from decommissioned nuclear weapons andsome reprocessing of spent fuel and depleted uranium

tailings [10, 11]. Typically uranium ores are of fairlylow grade at 1.5% or less, with a notable exception be-ing the high grade deposits of the Athabasca Basin inCanada [12]. With this in mind, the Ranger mine inAustralia was determined to be the most suitable foruse as the subject of a process analysis based on data inthe open literature. Support for the decision included:

• The deposit has a grade of around 0.2% to 0.3%, cor-responding well with the average global ore grade,which has varied between 0.05% and 0.13% over thelast five decades [13].

• Ranger utilises open pit mining, with the conven-tional techniques (open pit plus underground) dom-inating current production [14].

• Australia is a major producer of uranium, and hasthe world’s largest known reserves [10].

• The deposit is unconformity related, which is com-mon for uranium ores.

• Ranger was considered as part of [6], providing theopportunity for comparison with and updating ofthat analysis.

Ranger

The Ranger mine, owned by Energy Resources of Aus-tralia (ERA), is located in Northern Territory, 220kmeast of Darwin. When possible, the analysis consid-ered location- and mine- specific data, although wherethis was not available the best alternatives were usedinstead. A life cycle approach based on process analy-sis was undertaken to begin with rather than the moredetailed hybrid approach. The aim was to include suf-ficient inputs such that the key factors were identifiedand their role elucidated. The mine was assumed toproduce 5,339 tonnes of U3O8 product as was the casein 2008, at a purity of 99% [15].

Excavation at Ranger began in 1980 with pit #1being mined out by 1994 [16]. This has been takenas the basis for modelling of the mining process, as atypical final design. Whilst the detailed geology of thepit was complex (see appendix), as a means of estimat-ing haulage requirements a model based on a frustumwas utilised, with the assumptions that the overburdenwas removed from the upper section and the ore fromunderneath as depicted in figure 1. The map of theRanger plant in figure 2 allowed estimation of averagehaulage distance for both overburden and ore, deter-mined to be 1km and 1.6km respectively. This is innotable contrast to the work of Storm and Smith, whoconsidered 10km to be more likely [17].

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overburden

ore

375m

175m

28.1º

Figure 1: The frustum model for pit #1.

Figure 2: Map of the Ranger mine. Pit #1 has been mined outand is therefore used as the basis for this study. After [18]

Details of the geologic conditions at Ranger led tothe consideration of quartzite sandstone as the over-burden material and quartz as the gangue within theore body [19]. With this in mind the average density ofboth overburden and ore was taken to be 2600kgm-3.

For many values in this work the source of energyinputs was unclear. In the case of thermal inputs there-fore a generic conversion factor of 75g CO2 per MJ(th)was used to determine emissions from these processeswhich corresponds with diesel fuel. For haulage themetric of tonne-km (t-km) was utilised with valuesfrom [2] for truck haulage and coastal shipping, [20]for emissions from truck haulage and [21] for inter-national shipping. These are summarised in table 1.Where possible, life cycle analyses from the literaturewere utilised to increase the value of the work, althoughthese often proved in short supply.

MJ/t-km CO2 g/t-km

Truck haulage 2.34 180Coastal shipping 0.4 30Intl. shipping 0.06 4.6

Table 1: Energy costs and CO2 emissions associated with trans-port as used in this analysis.

Mining at Ranger

Final data for the Ranger process analysis is sum-marised in table 2 in the Ranger results section. Moredetailed background of individual processes and as-sumptions can be found in the appendix. Figure 3 de-tails the simplified flowsheet for operations at Ranger.

Figure 3: The flowsheet for operations at Ranger. Chemicals ingreen are major indirect inputs identified by the author.

Mining is undertaken through bench blasting usingemulsion explosives. Quantifying the energy input ofdrilling for the placement of explosives proved difficult,due in particular to the dependence of the energy re-quirement on rock hardness, which was not known withany accuracy. As an estimate, empirical data from areview of US mines was utilised [22] with a resultingvalue of 2.26MJ per tonne rock excavated. For the ex-plosives themselves, the energy input in manufacturewas taken from Smil [23] and emissions due to deto-nation found from an average for packaged explosivessupplied by Orica mining services [24]. The quantity ofexplosive used is reported by ERA as 0.25kg per tonneof rock removed1.

Fuel consumption by excavating equipment wasestimated from the empirical data from the US, at

1This value was available at [25] until early 2010, but has since been removed. It is also referenced however in [17].

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5.95MJ per tonne of rock [22], whilst haulage of thematerial was estimated to require 0.06 litres of dieselper tonne-km [26].

Milling at Ranger

ERA operate an acid leach extraction process to pro-duce yellowcake in the form of U3O8, as depicted infigure 3. Key inputs include chemicals (H2SO4, MnO2,amines, kerosene, CaO) and diesel for electricity gener-ation. For several of these historical usage was availablein [13].

Electricity is produced on site by diesel generators,with an estimated average load of 11.5MW. It is usedin comminution (crushing and grinding) and agitationduring the leaching process, which are likely to be re-sponsible for the majority of the energy consumptionin the mill - grinding may be responsible for 50% ofenergy demand [27] whilst leaching requires 25%-33%of electrical inputs [28].

It is the inclusion of the embodied energy of chem-icals which results in large differences in energy con-sumption in uranium mining determined by the WNAand Storm and Smith. However, for H2SO4 used in theleaching process, Storm utilised an outdated techniquefor the extraction of sulphur (the Frasch process) withmost sulphur now obtained from the desulphurisationof fossil fuels, and so this was a significant update inthe present work. Further efforts were made to tai-lor haulage distances to centres of production thoughtmost likely to supply Ranger with various chemicals,whereas Storm utilised generic values [17].

Various inputs could not be sourced from the litera-ture, including the embodied energy of pyrolusite (usedas an oxidant in leaching) and amines (for solvent ex-traction) and the energy requirements of limestone pro-duction. For the embodied energies estimations wereused, in the case of pyrolusite based on typical valuesfor rock mining and chemicals and for amines basedon a precursor, NH3. Due to the high energy cost ofproducing CaO it was assumed that this was the dom-inant input in terms of embodied energy, although amore detailed analysis would require a quantificationof energy use in limestone extraction.

3 Methodology – Extrapolation

In [29] Storm and Smith calculated that a decreasein ore grade to approximately 0.01% would lead tonuclear power falling off an ‘energy cliff’, where theenergy inputs outweighed the generation capability ofburning uranium. Given that the Ranger operation istypical for uranium mining, particularly in its milling

processes, the process analysis was extrapolated to con-sider lower ore grades at Ranger to determine the effecton energy inputs and CO2 emissions. This required adetermination, and in some cases estimation, of theprocesses which would be dependent on ore grade (forinstance mining and acid leaching) and those processesunlikely to be affected (solvent extraction, calcination).The extrapolation was based on the assumption thatquantities dependent on ore grade would vary linearlywith the grade. Given that recovery of uranium fallsat lower grades this effect was also included, althoughin so doing an error was potentially introduced dueto insufficient empirical data for low grade operations.The yield curve was based on results for the five largestopen pit uranium mines at grades below 1% which usean acid leach process as determined from [14].

4 Results

Process Analysis

The process analysis results are summarised in table2. As was to be expected, the embodied energy ofyellowcake (U3O8) produced at Ranger is significantlymore than the value quoted by the WNA [8] due tothe inclusion of indirect energy inputs where possible.Table 2 also details three of the major energy inputsat Ranger. The presence of electricity is unsurpris-ing, and accounts for much of the figure reported byERA for 2008 (273GJ per tonne U3O8, or 325GJ pertonne natural uranium) [30]. The chemicals H2SO4

and CaO however have a noteworthy impact on energycosts, particularly the former, which is due in largepart to the significant quantities consumed per tonneof product. Data for sulphur production from crudeoil originated from a cradle-to-gate life cycle analy-sis from the ELCD database of the EU [31] which isnot specific to Australia but is presumably common towestern refineries, which may include those from whichERA source H2SO4. This is therefore considered oneof the most robust data points of this analysis, whichis important due to the significant effect it has on theoverall results.

The values obtained are smaller than those of theStorm and Smith analysis, which determined energycosts of 1080GJ per tonne natural uranium, or 907GJper tonne U3O8. One notable factor in this differenceis the use of 190GJ(th) per tonne of product by Stormand Smith for calcination at the end of the milling pro-cess to convert ammonium diuranate to yellowcake. Inthis study the input has not been successfully evalu-ated, but it is considered unlikely that this is correctas it would lead to an onsite energy use much greaterthan that reported by ERA, which is presumably an

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Energy use/GJ per tonne U CO2 emissions/g per kWh

Process analysis 571 – 739 0.75 – 1.08— Diesel for electricity 242 0.412— Sulphur 191 0.065— CaO up to 65 0.158 – 0.293

Process analysis + indirect inputs 654 – 822 0.89 – 1.22Storm and Smith 1080 1.75WNA/ERA 325 0.54

Table 2: Results of the process analysis for Ranger, with those of Storm and the WNA for comparison. Reported emissions for theWNA/ERA are derived from 20 tonnes CO2 per tonne U3O8.

accurate total for direct inputs. This is certainly anarea which would require further investigation, withindustry likely able to shed more light on it.

Calculation of CO2 emissions per kWh were basedon a light water reactor producing 44 million kWh grosselectricity (158TJ(e)) per tonne of natural uranium.This was the value used in the report by Storm andSmith and allows for direct comparison. The values de-termined in this work are significantly smaller, at 0.75gto 1.08g against 1.78g. A significant proportion of thisis again due to calcination, with Storm and Smith de-termining this to produce 0.39g CO2 per tonne ura-nium. The other major difference is emissions due tosulphur production, as the Frasch process consideredby Storm produces 3.1 tonnes CO2 per tonne sulphurcompared with 0.49 tonnes as found from the ELCDdatabase in this analysis. This is responsible for anextra 0.35g CO2 per kWh.

Indirect inputs associated with drilling and blast-ing, excavation and haulage and ore processing in themill as determined by Mortimer (ref. Q98 in [6]) are an-other source of variation between [6] and this analysis.Including these increases energy inputs and emissionsas seen in table 2, but as the author has not had accessto this work the veracity of these figures is unclear. Itis noted that there will certainly be such inputs asso-ciated with the mine, but their magnitude is uncertainand hence their impact is tabulated separately.

Extrapolation

As can be seen in figures 4 and 5, extrapolating theRanger process to ores of lower grade results in a sim-ilar profile graph to that of [17], but with lower emis-sions and energy inputs. The four lines other than theresult for Storm and Smith are the maxima and minimafor two situations: CaO const. refers to the situationwhere the use of lime is independent of the quantityof ore entering the mill, whilst CaO var. refers to theopposite case. This is because lime is potentially usedin several processes: neutralising tailings, treating pro-

cess water and and in part of the post-leach process-ing. The first two processes would require a quantityof lime dependent on ore grade whilst the third wouldnot, hence in reality the actual lime use will lie some-where between the curves developed in the results.

0

5000

10000

15000

20000

25000

30000

35000

40000

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

Emb

od

ied

en

erg

y /

GJ

pe

r to

nn

e U

3O

8

Percentage ore grade

Embodied energy per tonne U3O8 versus ore grade for the Ranger process analysis and the analysis of Storm and Smith

S-S soft ores

CaO const. min

CaO const. max

CaO var. min

CaO var. max

Figure 4: Embodied energy per tonne of U3O8 versus ore gradefor an extrapolation of the Ranger mine. The blue line uses datafrom [6]. For further information see text.

0

10

20

30

40

50

60

70

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

CO

2e

mis

sio

ns

/ g

pe

r kW

h


Comparison of process analysis CO2 emissions per kWh with results from Storm and Smith

S-S soft ores

CaO const min

CaO const max

CaO var. min

CaO var. max

Figure 5: CO2 emissions per kWh versus ore grade for the ex-trapolation. One tonne of natural uranium is assumed to gener-ate 44 million kWh of electricity. The blue line uses data from[6].

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The extrapolation demonstrates that for the com-mon technique used at Ranger, ore grades of lower than0.03% begin to require significant energy inputs. At agrade of 0.01%, the energy invested in production ofuranium as yellowcake accounts for up to 11.2% of thegross electricity produced by the uranium in a reactor.The CO2 emissions at this grade are 29g per kWh,which is considerably more than currently reported forhigher grade deposits but is still much less than theemissions due to burning fossil fuels.

However, there are several points regarding this ex-trapolation which should be noted. The lowest gradedeposit currently mined is 0.03% at Rossing but datacollated by the IAEA [14] highlights few deposits ofsuch low grade, with the result that extrapolatingyields for uranium to lower than this grade contains aninherent uncertainty. The yield versus grade fit usedherein was based on five data points for mines pro-ducing significant quantities of yellowcake at low oregrades, and is more optimistic than the yield curve of[6]. It is likely that as ore grade falls the size of themineralisation will decrease also, which will necessitatethe use of a smaller final grind size for efficient extrac-tion. As grinding consumes a large part of the energyrequirements of the mill, this could counter the effect ofimproved performance of the leaching circuit assumedin this work compared to that of [17].

A point worth noting is the source of electricityfor mining operations. Ranger is not connected to theAustralian electricity grid, which currently limits theowners to the use of fossil fuels (i.e. diesel poweredgenerators) for supply. Connecting to an electrical gridcould reduce the energy input required due to more ef-ficient large scale plant, and reduce carbon emissionsdepending on the generation mix. However, Australiacurrently has a heavy dependence on coal for electricitygeneration, hence these effects would not be expectedto be very significant [32]. In this work thermal inputswere found to be dominant and hence were consideredalone, but in the case of an input of electricity beingsignificant the source of that electricity would have hadto be determined.

Other factors which may affect performance at lowore grades include the possibility of using heap leach-ing (reducing grinding requirements but also lower-ing yield) and seeking deposits contained in soft oresto considerably decrease energy use in grinding, as islikely the case at Rossing. This work cannot be directlycompared to the case at Rossing due to the differencein ores at Ranger and Rossing.

5 Conclusions and Further Work

As was expected, the process analysis of the Rangermine gave results lying between those stated by theWNA and Storm and Smith, due to the inclusion ofindirect inputs and the updating of the values used forcertain inputs such as H2SO4. Due to the use onlyof data available in the open literature some valuesare not the most robust, and the use of LCA softwaresuch as SimaPro [33] could improve these due to thedatabases this gives access to. The lower value of therange of possible inputs and emissions would appear tobe an absolute lower bound however, with the use ofhybrid analysis assumed to result only in larger values.

Extrapolation to lower ore grades suggests that con-ventional open pit mining and processing of ores suchas that at Ranger with grades below ∼0.01% resultsin a large energy demand. Further work in this areamight consider the use of heap leaching, where the oreis not ground to such a fine consistency. This is donefor economic reasons, but in terms of energy inputsresults in a trade-off between energy savings from re-duced grinding and no agitation during leaching butwith decreased yield of uranium.

References

[1] World Nuclear Association, ‘Nuclear Power inthe Future and Sustainable Development’, [on-line] Available at: www.world-nuclear.org/why/sustaindevelop.html Accessed 20.3.10

[2] Bilek, M. et al. (2006) ‘Life-Cycle Energy Balanceand Greenhouse Gas Emissions of Nuclear Energyin Australia’, The University of Sydney Consul-tancy Report.

[3] Sovacool, B.K. (2008) ‘Valuing the greenhouse gasemissions from nuclear power: A critical survey’,Energy Policy 36 2940-2953.

[4] Fthenakis, V.M and Kim, H.C. (2007)‘Greenhouse-gas emissions from solar electric-and nuclear power: A life-cycle study’, EnergyPolicy 35 2549-2557.

[5] Vattenfall (2007) Certified Environmental Prod-uct Declaration of Electricity from Forsmark Nu-clear Power Plant [online] Available at: www.

environdec.com/reg/021/ Accessed 20.3.10

[6] Storm van Leeuwen, J.W and Smith, P. (2005)‘The nuclear energy balance’, [online] Available at:www.stormsmith.nl/ Accessed 15.1.10.

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[7] Rio Tinto 2004 - 2008 Performance Data Ta-ble [online] Available at: www.rossing.com/

performance.htm Accessed 19.3.10

[8] World Nuclear Association, ‘Energy Analysisof Power Systems’, (2009) Available at: www.

world-nuclear.org/info/inf11.html Accessed19.3.10

[9] U.S. Energy Information Administration (2010)‘Namibia Energy Profile’ [online] Availableat: tonto.eia.doe.gov/country/country\

_energy\_data.cfm?fips=WA Accessed 19.3.10

[10] World Nuclear Association, ‘Supply of Uranium’[online] Available at: www.world-nuclear.org/

info/inf75.html Accessed 19.3.10

[11] World Nuclear Association, ‘2009 WNA PocketGuide’ Available at: www.world-nuclear.org/

uploadedFiles/Pocket\%20Guide\%202009\

%20Uranium.pdf Accessed 10.3.10

[12] Cameco ’McArthur River’ [online] Available atwww.cameco.com/mining/mcarthur_river/ Ac-cessed 24.3.10

[13] Mudd, G.M. and Diesendorf, M. (2008) ‘Sustain-ability of Uranium Mining and Milling: TowardQuantifying Resources and Eco-Efficiency’, Envi-ron. Sci. Technol. 42, 2624-2630

[14] OECD, IAEA. (2008) ‘Uranium 2007: Resources,Production and Demand’, OECD Publishing

[15] ERA, (2008) ‘Fuelling the future’, Annual Report2008 [online] Available at: www.energyres.com.

au/media/38_reports_and_publications.asp

Accessed 19.1.10

[16] ERA, (2010) ‘History timeline’ [online] Avail-able at: www.energyres.com.au/documents/

History_timeline.pdf Accessed 24.3.10

[17] Storm van Leeuwen, J.W and Smith, P. (2007)‘Nuclear power - the energy balance’ Part D [on-line] Available at: www.stormsmith/nl/ Accessed15.1.10

[18] Supervising Scientist 2009. Annual Report 2008-2009. Supervising Scientist, Darwin. [online]Available at: www.environment.gov.au/ssd/

about/corporatedocs.html Accessed 20.2.10

[19] Hein, K.A.A (2002) ‘Geology of the Ranger Ura-nium Mine, Northern Territory, Australia: struc-tural constraints on the timing of uranium em-placement’, Ore Geology Reviews, 20 83-108

[20] Forster, D (2006) ‘Carbon footprint of the nuclearfuel cycle - Briefing note’, [online] Available at:www.british-energy.com/documents/Nucelar_

Fuel_Cycle_carbon_footprint.pdf Accessed20.2.10

[21] MacKay, D.J.C (2009) ‘Sustainable Energy - with-out the hot air’, UIT, Cambridge p95

[22] BCs, Incorporated (2002) ‘Energy and envi-ronmental profile of the U.S. mining indus-try’, [online] Available at: www1.eere.energy.

gov/industry/mining/analysis.html Accessed20.1.10

[23] Smil, V. (2008) ‘Energy in nature and society :general energetics of complex systems’, AppendixUSA, The MIT Press

[24] Orica Mining Services, Packaged Explosives [on-line] Available at: www.oricaminingservices.

com/ContentPage.aspx?SectionID=9&PageID=

46&CultureID=3&MarketID=2 Accessed 20.2.10

[25] Energy Resources of Australia [online] Availableat: www.energyres.com.au/

[26] Bilek, M. et al. (2006) ‘Life-Cycle Energy Balanceand Greenhouse Gas Emissions of Nuclear Energyin Australia’ chp. 3, The University of SydneyConsultancy Report.

[27] Wills, B.A (1992) ‘Mineral Processing Technol-ogy’, 5th ed. Exeter, Pergamon Press p275

[28] Wilson, P.D (1996) ‘The Nuclear Fuel Cycle fromore to waste’, Oxford University Press p28

[29] Storm van Leeuwen, J.W and Smith, P (2008)‘Nuclear power - the energy balance’ Part G [on-line] Available at: www.stormsmith/nl/ Accessed15.1.10

[30] ERA, (2008) ‘Sustainable Development Report’[online] Available at: www.energyres.com.au/

media/38_reports_and_publications.asp Ac-cessed 19.1.10

[31] ELCD database 2.0 and P.E.International (2009)‘Process data set: Sulphur; from crude oil;consumption mix, at refinery; elemental sulphur(en)’, [online] Available at: lca.jrc.ec.europa.eu/lcainfohub/datasets/elcd/processes/

ec450ce7-4598-4ca5-9ab3-452ff1c750a4_02.

00.000.xml Accessed 20.2.10

[32] International Energy Agency, ‘Electricity/Heatin Australia in 2007’, [online] Available at:www.iea.org/stats/electricitydata.asp?

COUNTRY_CODE=AU Accessed 25.3.10

[33] PRe consultants SimaPro software www.pre.nl/

default.htm

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Appendix

1 LCA

Whilst in industry finance is key in decision making,from a sustainability perspective the use of a tool fordetermining environmental impacts, such as life cycleanalysis (LCA), is equally desirable if not more so.Such an analysis considers the entire range of processeswhich result in a given desired outcome, consideringboth the inputs and outputs within said processes (thelife cycle inventory) and ultimately determining thenet environmental effect necessitated by the outcome(the life cycle impact assessment). The assessment maycover only a certain part of the cycle, for example in theproduction of a chemical where a cradle-to-gate analy-sis will determine the environmental effect of producingunit output of the chemical (known as the functionalunit), or the whole cycle (cradle-to-grave).

Within the field of life cycle assessment, two differ-ing techniques may be utilised. Input-output analysis(IOA) is based on an economic framework developedby the Nobel Prize winner Wassily Leontief, wherebythe monetary movements between different sectors ofthe economy are tabulated. When combined with av-erage resource consumption and emissions for each sec-tor, this can be used to determine the environmentalimpacts associated with particular goods and services.This relies however on the good or service consideredbeing well represented by the average of all goods andservices within its sector and can thus produce poorresults if this is not the case, as has been argued forthe construction of nuclear power plants [1]. The otheroption is to utilise a process-based LCA, which con-siders detailed inputs and outputs in a given process.The drawback for this methodology is the difficulty inincluding all processes, particularly those occurring farupstream — it is desirable that these have little overallimpact. A more advanced hybrid LCA technique hasbeen developed to overcome the problems associatedwith both of the key techniques — process analysis isutilised for the main processes, whilst the effects of up-stream processes are estimated using IOA [2].

In this work, a process analysis was utilised, withupstream impacts assessed where possible (typicallywhen LCA data was available in the literature). Thiswould appear to be a sensible starting point, partic-ularly as the individual impacts can be envisaged di-rectly. Where possible, values have been sourced fromlife cycle databases to enhance the value of the work, al-though in many instances no such data has been avail-able and direct inputs only have had to be used.

2 Background: Uranium mining

A mineral or metal is determined to constitute an oreif it is economically extractable, hence price can alterknown recoverable resources. Uranium ore grades aretypically given as a percentage by mass U3O8. Ura-nium may be found in the form of simple mineralssuch as uraninite (UO2) and pitchblende (UO3, U3O8)which are the least costly to process, or as more com-plex secondary minerals with an associated increase inextraction requirements. It is possible for the uraniumin a rock to be in ’solid solution’ whereby it has re-placed an atom in a silicate rather than formed mineralgrains within the rock [3]. This is the case with graniteand phosphate ‘ores’, and means the entire mass mustbe placed in solution to extract the uranium, entailingmuch greater costs. No such ores appear to be cur-rently mined, and this issue has not been consideredfurther in the current work.

Uranium mining is undertaken using several dif-ferent techniques: open cut and underground mining,in situ leaching (ISL) and by- or co- product mining,where mines produce several different valuable mate-rials. Whilst it is true that ISL has been a growingsource of uranium in the 21st century, it is currentlystill outweighed by the more traditional mining tech-niques. Furthermore, production via ISL is limited inthat the geologic conditions in which uranium miner-alisation is found must be of a specific type meaningonly a few locales can utilise it. ISL is currently usedto extract uranium from deposits in sandstone forma-tions which the WNA claims contain 18% of the world’sknown uranium resources [4]. All other forms of min-ing follow a similar technique-the ore body is excavatedeither by underground blasting or surface bench blast-ing then processed within a mill. ISL simply eliminatesthe need to remove the ore from the ground.

3 The Ranger deposit

The uranium deposit at Ranger is of the unconformitytype, which host 33% of western world uranium de-posits [5]. The deposit is hosted below the unconfor-mity, which separates overlying quartzose sandstoneof the Kombolgie formation from the schist and mi-crogneiss of the Cahill formation [6]. [6] demonstratesthat the geology of the individual pits at Ranger ismuch more complicated than the simple version statedabove, but for the purposes of this study a simplifiedversion was required to allow calculations to be made.The schist at Ranger in which the mineralisation oc-curs is partly of the quartz type, and the sandstoneoverburden is also quartzose (quartz sandstone). The

A1

approximate density of quartz, 2.6 tonnes per m3, wastherefore used in calculations for ore and overburdenremoval.

4 Overview of the Ranger Process

ERA use a conventional uranium mining method atRanger, the flowsheet for which can be seen in themain work. Overburden is removed and placed in wastestockpiles or used to construct the tailings storage fa-cility (TSF) where milling waste is later stored. Theore body is then removed through bench blasting whichcreates a staggered interior to the pit preventing land-slips. The ore is hauled using 90-150 tonne haul trucksto the mill for initial crushing. All material movedfrom the mine first passes under a radiometric discrim-inator, which determines whether the material shouldbe passed to waste stockpiles, low grade stockpiles ordirectly to the mill for processing.

Blasting to remove material from the pit requiresthe drilling of boreholes for the placement of explo-sives. The most common explosive used in open cutmining is ammonium nitrate - fuel oil (ANFO), butdue to the presence of water in boreholes at Rangeran emulsion explosive is used instead. After blasting,material is loaded onto haul trucks using an excavator.

Pit #1 had final dimensions of approximately 750macross and 175m deep at the lowest point and requiredthe removal of approximately 20 million tonnes of oreand 60 million tonnes of overburden. To approximatehaulage distances, the pit was modelled using a frus-tum, with overburden considered to be removed firstfrom the top and then ore from the lower section. Thismay not be exactly correct in reality, but without de-tailed knowledge of the ore location in the pit this wasthe most accurate method considered viable. The pitmodel can be seen in figure 1 of the main work. Thecentre of mass of each of the two sections was calculatedand used as the average depth from which overburdenor ore had to be transported to the mill. For the over-burden the depth was considered to add a relativelyminor quantity to the overall haul distance and waseffectively simply combined with the haulage distanceon the surface, as this had to be estimated anyway asthe location of waste stockpiles varies. Using satelliteimages and the map of Ranger in the main documentthe haulage distance for overburden was estimated as1km. For the ore, the haulage distance to the surfaceof approximately 600m at a slope of 10 degrees wasadded to the approximate distance to the mill of 1km.

The first part of the milling process involves thecrushing and grinding of the ore to expose the uraniummineralisation. The final size of the grind required is

determined in part by the size of the individual grainsof mineralisation and in part by the desire to disturbas little of the gangue as possible. The gangue is therock hosting the deposit and is the chief determinant ofthe quantity of acid required in the leaching of the ore,particularly in the case where the carbonate contentof the rock can neutralise significant quantities of acid[7]. At Ranger prior to the construction of the mill thenominal grind size was expected to be 74µm using rodand ball mills [8]. No more recent data has been foundfor this, and it should be noted that the grind size mayvary as ore grade varies within the pit. Also, the millat Ranger was upgraded which might have entailed achange in operating practices.

The next step is to leach the uranium from thegrind. This is achieved using dilute H2SO4 and MnO2.The manganese oxide is used to oxidize tetravalent ura-nium as typically found in the ore into the more solublehexavalent state to allow the acid to mobilise uraniumfrom the gangue. This process is possibly undertakenat slightly elevated temperatures (around 40 to 60 de-grees) and requires agitation tanks. Consequently, itcan be responsible for 25% to 33% of the mill’s energyconsumption [9] although this has not been confirmedfor Ranger specifically.

The material leaving the leaching circuit is washedto remove the ‘pregnant’ uranium-bearing liquor fromthe surface of the gangue, and is then passed througha solid-liquid separation process, where a flocculent islikely used to speed up separation along with horizontalbelt filters. The solids produced in this step constitutethe tailings of the milling process, and are neutralisedwith CaO before being pumped to the tailings storagefacility (TSF).

The next step is to extract the uranium from theliquor preferentially with respect to the other metalswhich may have been mobilised by the non-selectiveacid. Either ion exchange or solvent extraction maybe used, with the latter preferred at Ranger. Thisis undertaken using an amine in kerosene, with theamine likely being tertiary or quaternary - for exam-ple in the Caetite mine in Brazil alamine R©336 (a ter-tiary amine) is used [10]. The exact amine used atRanger is unknown hence this process has been con-sidered as a possibility. Uranium is stripped from theresulting liquor through a combination of gaseous NH3

and (NH4)2SO4, producing an acidic solution contain-ing H2UO2(SO4)2.

The final chemical step is to precipitate the ura-nium from the acidic solution. CaO may be added atthis point to raise the pH and precipitate out remain-ing impurities as an initial step, though whether thisis done at Ranger is unclear. Further ammonia is then

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added to the solution at 30 - 50 degrees resulting inthe production of (NH4)2U2O7 (ammonium diuranate,ADU). In some mills ADU is referred to as yellow-cake and is the final product. At Ranger however theproduct of the precipitation step is most likely passedthrough a centrifuge to lower the water content beforeentering a furnace such as a multiple hearth furnacewhere it is calcined at between 650 and 850 degreesfor up to two hours [11]. This has the effect of driv-ing ammonia from the product, leaving behind U3O8

at approximately 99% purity [12, 13, 14, 15, 16]. Thisis now referred to as yellowcake, despite being greenin colour, and is drummed for transport to enrichmentfacilities upon sale.

5 Mining at Ranger

The analysis of pit #1 considered the production of5,339 tonnes U3O8 per year at an ore grade of 0.24%,these figures agreeing well with those experienced atRanger (note not at the original pit #1, where oregrades were a little higher). This results in a totalpit production of 43,200 tonnes U3O8. Where annualprocess values were available in the literature, thesewere converted to per tonne product values using pro-duction for that particular year however, to minimisethe introduction of errors into the analysis.

The Northern Territory has a particularly low pop-ulation and relatively few large conurbations. Thismay partly explain why Ranger is not connected to anelectrical grid and has instead an onsite diesel genera-tor (genset) consisting of five individual engines witha maximum output of 26MW. ERA state the averageload to be 13MW, with this being shared between themine and the local mining town of Jabiru1. The au-thor deemed it reasonable to assume this to be for theyear 2008. To determine the fraction of power utilisedat the mine itself, the per capita electricity use inAustralia was used to estimate demand from Jabiru,with what remained assigned to the mine. In 2001-02the 18,769,249 citizens of Australia consumed 216,076GWh of electricity at a per capita rate of 11.51MWhper year [17, 18]. The population of Jabiru in the mostrecent census (2006) was 1,137 hence the town was pre-dicted to have an electricity power demand of 1.5MW.

A caveat to this is that the per capita consumptionincludes industrial users which will distort the valuesomewhat — the residents of Jabiru will individuallyuse less as they are not industrial users. 1.5MW wastherefore used as a conservative estimate, and meantthe estimated onsite electricity power demand of theRanger mine for 2008 was 11.5MW. This was supplied

at an efficiency of 33.5% in 2006 [19]. Assuming thiswas maintained into 2008, total thermal input for elec-tricity at Ranger was 1.08PJ, or 203GJ(th) per tonneU3O8. This constitutes a considerable percentage ofthe total energy input per year at Ranger calculated inthis study, at between 27% and 36%.

5.1 Drilling and Blasting

Energy consumption in drilling operations has provendifficult to evaluate. Various types of drill can be usedand the exact rock type also impacts on energy de-mand. Furthermore, it is unclear whether the drillsused at Ranger were powered by electricity, in whichcase the input has already been accounted for, or bydiesel. However, given that electricity is generated on-site and requires diesel to be imported anyway, it wouldseem unlikely that electricity is used in an operationwhere the use of diesel might be more efficient. As ageneral estimate for this process, a value of 2.26MJ pertonne of rock removed was used, with the assumptionthat both ore and overburden require drilling, basedon the geology of the deposit. This was taken from asurvey of US mines from 2002 and in fact applies torotary drilling of surface coal mines [20]. Clearly thisrelies on the coal being of the same drillability as therock at Ranger and the same ratio of drilling depthto rock removed being used at both coal and uraniummine. The type of input was not given, so diesel powerwas assumed. Furthermore, this value does not con-sider indirect inputs associated with drilling, althoughan attempt has been made to include these in the finaldata which includes indirect inputs.

ERA use an emulsion explosive at Ranger, withapproximately 0.25kg required per tonne of rock re-moved. No life cycle analysis for the production ofexplosives was found in the literature, so a range givenby Smil [21] of 10-70MJ/kg was used, with the upperlimit agreeing with that used in the report of Stormand Smith. With no indication of the type used, forthe detonation of the explosive data from Orica Min-ing services for their packaged explosives for open cutmetal mines was utilised [22]. An average for the CO2

emissions of five explosives (Powergel Buster, SenatelPowerpac 3000, Senatal Powersplit, Senatel Pyromex,Senatel Pyrosplit) led to a value of 171kg CO2 pertonne explosive detonated. With 80 million tonnes ofmaterial requiring removal then 20,000 tonnes of ex-plosive were required over the lifetime of the pit.

1Source no longer available due to update of website, but also referenced in [23]

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5.2 Excavation and Haulage

Data for typical energy use in the excavation of mate-rial has not been found in the recent literature, pos-sibility due to its dependence on factors such as theease with which a material may be loaded and the per-centage of time the excavator is loading as opposedto idling, with consumption typically given instead ingallons per hour, which cannot be easily converted tofuel use per tonne rock excavated. Instead, an empir-ical value from an Energy and Environmental Profileof the mining industry in the USA from 2002, fromthe Department of Energy, was used [20]. The dataconsidered was for surface coal, iron ore and limestoneexcavation, with the similarity of the values increasingconfidence in the data point, 5.95MJ per tonne exca-vated. This is indeed very similar to the value used byStorm and Smith, which was 5.56MJ per tonne assum-ing the density used in this work.

The mean haulage distance for ore and overburdenwas demonstrated earlier. Similarly to fuel use in exca-vation, reported data is often couched in terms of fueluse per unit time as opposed to per t-km, which is amore informative metric. A value of 350 litres per houron a 10 degree slope at the Rossing uranium mine inNamibia [24] with a payload of 182 tonnes may alsosupport the data point used however in the main workfor truck haulage, as at an estimated 20mph this corre-sponds to 0.06 litres diesel per t-km. Whilst this is on aslope and requires an estimate of haul speed, with themodel of the mine used in this work the haul trucksare not operating on the flat for a clear majority ofthe haul distance, and it could be assumed that theytherefore are not performing at their optimum.

6 Milling at Ranger

6.1 Comminution

Comminution, which involves the crushing and grind-ing of the ore, is the first process undertaken in themill, exposing the uranium mineralisation for leaching.Crushing reduces the products of blasting to the scaleof millimetres for grinding to a much finer consistency,50% passing 74µm in the case of the original Rangerdesign [8]. The original plan at Ranger was to utiliserod milling followed by ball milling, and whilst thismay no longer be the case due to a mill upgrade, itdoes allow estimation of the energy required in thisstage of the process through the use of the Bond workequation, which may not be valid for the more modernsemi autogenous and autogenous grinding mills. As theelectricity consumption at the mine is known there isconfidence that no electrical input into milling will be

inaccurately accounted for, but an estimation of com-minution energy use gives an idea of where the 11.5MWis utilised. The Bond work equation is

W =10Wi√P− 10Wi√

F

where W is work required in kWh per tonne, Wi theBond work index for a material in the same units, P thepassing size of 80% of the product and F the equivalentfor the feed, in microns. One difficulty with this equa-tion is that the work index Wi may be a function ofmaterial size (and so varies as ginding proceeds), hencethe value used is typically for a specific grinding circuit.Furthermore, exact data for the feed and product sizeat Ranger is unknown and neither is the most accu-rate work index for the ore. However, an assumptionthat the feed size is around 10mm (F=10,000) [25], avalue for Wi of 14.96 kWh per tonne as is the case forquartz [26] and using 74 microns as the 80% productpassing size leads to an electricity demand per tonneore of 15.89 kWh. The model used for Ranger, withproduction of 5,339 tonnes U3O8 per year, results inan average milling throughput of 226 tonnes ore perhour, hence the power draw of the grinding equipmentis around 3.6MW, thus accounting for a significant frac-tion of the average electrical load. Note this does notinclude the crushing stage, for which there appears lit-tle theoretical basis for approximating energy require-ments. It is also only the power at the mill pinion,which doesn’t take losses in the motor into account[26]. The extensive energy use in grinding processesis due to their low efficiency, with reports of only 1%of the input actually being available for size reduction[27].

6.2 Leaching

6.2.1 Sulphuric acid production and transport

Leaching at Ranger requires H2SO4 and MnO2. Theformer is to mobilise uranium from the finely groundore, with the latter acting as an oxidant, convertingtetravalent uranium of low solubility to the more solu-ble hexavalent form. As noted in the main article, theanalysis was based on the production of sulphur fromfossil fuels rather than extraction from the ground viathe Frasch process, which resulted in a lower energycost (32.7GJ per tonne sulphur as opposed to 41.5GJused in [3]). Actual production of the acid was esti-mated to require 2-3GJ per tonne of acid [21]. The acidis obtained by ERA from a storage tank at the port ofDarwin [19]. There appears to be no refinery at Dar-win, hence the acid must be brought in from elsewhere.To estimate haulage distance, it was assumed that the

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acid was sources somewhere between the Philippines(actually very close to the Northern Territory) and theMiddle East, hence a range of 1,000km to 10,000km byship, plus 260kn from Darwin to Ranger by road train.

6.2.2 Manganese oxidant

No data was found in the literature for the productionof MnO2, although in a further analysis it could po-tentially be sourced from subscription databases. Fur-thermore, it was unclear whether the oxidant used waspyrolusite (a common manganese ore) or a more re-fined form such as chemical or electrolytical grade man-ganese dioxide. An estimate for the embodied energywas therefore used, ranging from 1GJ per tonne to30GJ per tonne. The lower limit is similar to that forcrushed stone, for instance [28], with the upper limitan estimate based on values of 20-25GJ per tonne foriron ore, 30-50GJ per tonne for lead [21], 32.7GJ pertonne for sulphur and 35GJ per tonne for ammoniai.e. a rough estimate based on typical values for othermaterials including treatment of ore and production ofchemicals.

6.2.3 Oxidant transportation

The Northern Territory hosts two manganese mines[29], and it was assumed that it was from one of thesethat ERA source their oxidant. These are at GrooteEylandt and Bootu Creek. Assuming therefore thatthe product of one of these mines is directly trans-ported to Ranger, a haulage distance of between 950kmand 1,260km was estimated. The latter value includes1,000km by coastal shipping to Darwin, as Groote Ey-landt is an island.

6.3 Solid-liquid separation

This process likely utilises horizontal belt filters, andhence electricity. This is accounted for in the over-all use of the mill, and was not considered further. Aflocculent may be used to speed up the process, butat no point was this mentioned as a major input, orany values found determining its levels of use, so itwas assumed to act only as a perturbation on the finalresults.

6.4 Solvent extraction

Solvent extraction utilises an amine within extractiongrade kerosene. The exact amine used at Rangeris unknown, although at the Brazilian Caetite minealamine R©336 is used [10]. From [30] amine use for theprocess was known in litres, and so a conversion tomass was based upon alamine R©336 [31]. At 12.7 litres

per tonne U3O8 this was only a very minor input how-ever. Again due to lack of literature data an estimatefor embodied energy was required, and this was basedupon the value for ammonia (to be discussed later) asa minimum due to its status as an amine precursor,and a value of 145GJ per tonne as the upper limit, asapparently this is the largest value for any chemical inthe SimaPro database, according to [32].

For kerosene, only transportation data was in-cluded, to be consistent with, for instance, the pro-duction of diesel for electricity generation, where theembodied energy of the fuel was not included. Haulageof the 320 litres required per tonne U3O8 was consid-ered to be from Darwin only. Amines were assumed tobe sourced from the same place as ammonia (see latersection on the stripping process) and hence values be-tween 2,500km and 4,500km by sea were allowed for,plus 260km by road from Darwin.

6.5 Stripping

Stripping involves the addition of a solution of ammo-nia in ammonium sulphate [9] to the ’pregnant’ leachliquor. This analysis only considered ammonia due toinsufficient data for the sulphate, although it is as-sumed that this only gives a lower limit due to theuse of ammonia in the production of ammonium sul-phate. Energy use in the production of ammonia wasfound from [33], at 35GJ per tonne NH3. A range ofpossible emissions was found in the literature, from alow of 750kg CO2 per tonne NH3 [34] up to 1,400kg[33].

As there appears to be no manufacture of ammoniain Northern Territory, the assumption was made thatit is sourced from either Incitec in Brisbane or Kar-ratha, WA. Indeed according to [35] Incitec are one ofonly two firms manufacturing ammonium sulphate inAustralia, although the recency of this data is unclear.This led to transport distances of 2,500km to 4,500kmby sea, plus 260km by road from Darwin.

6.6 Lime

The production of lime involves extraction and com-minution of limestone (CaCO3) before calcination todrive off CO2. In [3] the quantity of lime required ap-pears to be consistent with the assumption that all ofthe sulphuric acid used must be neutralised. However,as stated in the main work lime is used for more thanthis, and some neutralisation occurs in the strippingprocess due to the addition of ammonia and ammo-nium sulphate. The former leads to a greater demand,whilst the latter reduces it. In [30] the quantity used isstated to be 5.9 tonnes of lime per tonne U3O8. This

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data was from the period 1989-1997, with no more re-cent data being available according to the same paper.Production figures were slightly lower for the periodthe data covers [36] and so an assumption is made thatthe data is still valid for higher production figures.

Data for the extraction of limestone has not beenfound in the literature, but the production of lime in-cluding final grinding is covered in an EU documentfor Best Available Techniques [37]. A range of 3.3-9.2GJ(th) per tonne of lime was found, with electric-ity inputs being negligible considering the magnitudeof the thermal requirement. CO2 emissions from thecalcination process are stated as lying between 0.987and 1.975 tonnes per tonne of lime. Note that the val-ues used therefore do not include extraction and initialcomminution or material transport, and should there-fore be considered as a lower limit. Again, more precisedata may be available in a subscription database.

7 Extrapolation

The extrapolation depended on a determination ofthose inputs thought likely to vary with ore grade i.e.the quantity of material mined and passing throughthe mill to achieve the same production level of U3O8.With reference to figure 3 in the main work (flowsheetfor Ranger operations), all processes up to the solid-liquid separation phase were deemed likely to be af-fected by ore grade, and the extrapolation consideredthem to increase linearly with decreasing ore grade, forinstance the quantity of ore that must be mined.

Electricity is used in several of these processes(namely crushing, grinding and leaching) in large quan-tities, and so the majority (10MW) was allowed to varywith ore grade. The remaining 1.5MW was consideredas an estimate of the background energy use at a minefor general use not associated directly with uraniumprocessing. Without details on exact figures this is ofcourse a very rough estimate.

As mentioned in the main text, lime is used bothin processes reliant on throughtput and possibly in apost-leach process, hence not reliant on grade. As noinformation was available to determine what fractionis used where, the results put forward consider the twoextremes, whereby all the lime use is grade dependentand non of it is. In reality, dependency on grade willlie somewhere between the two positions.

The yield curve referred to in the main work is givenin figure 1. It can be seen that at ore grades lower thanapproximately 0.08%, the yield curve used in this studyis more optimistic than that used by [3]. This is impor-tant as this is the region in which the energy require-ments predicted in [3] become considerable — the yield

used in this work predicts lower energy requirementsat low ore grades. However, the effect is the same atvery low grades (but still above 10ppm) — the energyrequirements using this yield curve and extrapolationmethodology result in geater energy inputs than onecan obtain as output from a nuclear power plant.

y = 3.4341ln(x) + 98.201

50.00

60.00

70.00

80.00

90.00

100.00

110.00

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Yie

ld/%


Yield versus grade for Storm and Smith and this report

S-S yield

Extrapolation yield

Log. (Extrapolation yield)

Figure 1: Yield versus grade graph used in the extrapolation,with yield curve of [3] for comparison. The fitted curve has anR value of 0.66 which demonstrates the difficulty in predictingyields at low ore grades. In order of increasing ore grade, thedata points are for Rossing (Namibia), Zheltye Vody (Ukraine),Stepnogorskiy Mining chemical complex (Kazakhstan), Rangerand Arlit (Niger).

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[3] Storm van Leeuwen, J.W and Smith, P. (2007)‘Nuclear power - the energy balance’ Part D [on-line] Available at: www.stormsmith/nl/ Accessed15.1.10

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[8] IAEA Technical Reports Series No. 196 (1980)‘Significance of Mineralogy in the Development ofFlowsheets for Processing Uranium Ores’, p155,Vienna

[9] Wilson, P.D (1996) ‘The Nuclear Fuel Cycle fromore to waste’, Oxford University Press pp28,34

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NEFW/documents/RawMaterials/TCBRA/

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gov/industry/mining/analysis.html Accessed20.1.10

[21] Smil, V. (2008) ‘Energy in nature and society :general energetics of complex systems’, AppendixUSA, The MIT Press

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com/ContentPage.aspx?SectionID=9&PageID=

46&CultureID=3&MarketID=2 Accessed 20.2.10

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61096.aspx Accessed 20.2.10

[25] Hukki, R.T. (1961) ‘Proposal for A Solomonic Set-tlement Between the Theories of Von Rittinger,Kick, and Bond’, Trans. AIME 220 403-408.

[26] Wills, B.A (1992) ‘Mineral Processing Technol-ogy’, 5th ed. Exeter, Pergamon pp223-224

[27] Fuerstenau, D.W. and Abouzeid, A.-Z.M. (2002)‘The energy efficiency of ball milling in comminu-tion’, International Journal of Mineral Processing67 161-185

[28] ELCD database 2.0 and P.E.International(2006) ‘Crushed stone 16/32; open pit mining;production mix, at plant; undried’, [online] Avail-able at: lca.jrc.ec.europa.eu/lcainfohub/

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mini-project report evaluating the energy inputs and co2...

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