VOLUME 119 NO. 3 MARCH 2019

The Southern African Institute of Mining and Metallurgy

!+! ! + + ++ !  +! !  + !  *Deceased * H. Simon (1957–1958)  !! !""  * M. Barcza (1958–1959) Mxolisi Mgojo * W. Bettel (1894–1895) * R.J. Adamson (1959–1960) President, Minerals Council South Africa * A.F. Crosse (1895–1896) * W.R. Feldtmann (1896–1897) * W.S. Findlay (1960–1961) * D.G. Maxwell (1961–1962)  !! " !""  * C. Butters (1897–1898) * J. de V. Lambrechts (1962–1963) Gwede Mantashe * J. Loevy (1898–1899) * J.F. Reid (1963–1964) Minister of Mineral Resources, South Africa * J.R. Williams (1899–1903) * S.H. Pearce (1903–1904) * D.M. Jamieson (1964–1965) Rob Davies * W.A. Caldecott (1904–1905) * H.E. Cross (1965–1966) Minister of Trade and Industry, South Africa * W. Cullen (1905–1906) * D. Gordon Jones (1966–1967) * P. Lambooy (1967–1968) Mmamoloko Kubayi-Ngubane * E.H. Johnson (1906–1907) * R.C.J. Goode (1968–1969) Minister of Science and Technology, South Africa * J. Yates (1907–1908) * R.G. Bevington (1908–1909) * J.K.E. Douglas (1969–1970) !""  * A. McA. Johnston (1909–1910) * V.C. Robinson (1970–1971) * D.D. Howat (1971–1972) A.S. Macfarlane * J. Moir (1910–1911) * C.B. Saner (1911–1912) * J.P. Hugo (1972–1973) !""  " * W.R. Dowling (1912–1913) * P.W.J. van Rensburg (1973–1974) M.I. Mthenjane * A. Richardson (1913–1914) * G.H. Stanley (1914–1915) * R.P. Plewman (1974–1975) " ! " !""  * J.E. Thomas (1915–1916) * R.E. Robinson (1975–1976) Z. Botha * J.A. Wilkinson (1916–1917) * M.D.G. Salamon (1976–1977) * G. Hildick-Smith (1917–1918) * P.A. Von Wielligh (1977–1978)  ! " !""  * H.S. Meyer (1918–1919) * M.G. Atmore (1978–1979) V.G. Duke * J. Gray (1919–1920) * D.A. Viljoen (1979–1980) * J. Chilton (1920–1921) * P.R. Jochens (1980–1981)     ! " !""  * F. Wartenweiler (1921–1922) G.Y. Nisbet (1981–1982) I.J. Geldenhuys * G.A. Watermeyer (1922–1923) A.N. Brown (1982–1983) * R.P. King (1983–1984) ""  !""  * F.W. Watson (1923–1924) J.D. Austin (1984–1985) S. Ndlovu * C.J. Gray (1924–1925) * H.A. White (1925–1926) H.E. James (1985–1986) H. Wagner (1986–1987)  "  " "!"! * H.R. Adam (1926–1927) * B.C. Alberts (1987–1988) R.T. Jones * Sir Robert Kotze (1927–1928) * J.A. Woodburn (1928–1929) * C.E. Fivaz (1988–1989)  !! !"!"! * H. Pirow (1929–1930) * O.K.H. Steffen (1989–1990) V.G. Duke * J. Henderson (1930–1931) * H.G. Mosenthal (1990–1991) * A. King (1931–1932) R.D. Beck (1991–1992) ! ! ""!    * V. Nimmo-Dewar (1932–1933) * J.P. Hoffman (1992–1993) I.J. Geldenhuys S.M Rupprecht * P.N. Lategan (1933–1934) * H. Scott-Russell (1993–1994) C.C. Holtzhausen N. Singh * E.C. Ranson (1934–1935) J.A. Cruise (1994–1995) D.A.J. Ross-Watt (1995–1996) W.C. Joughin A.G. Smith * R.A. Flugge-De-Smidt N.A. Barcza (1996–1997) G.R. Lane M.H. Solomon (1935–1936) * R.P. Mohring (1997–1998) E. Matinde D. Tudor * T.K. Prentice (1936–1937) * R.S.G. Stokes (1937–1938) J.R. Dixon (1998–1999) H. Musiyarira A.T. van Zyl * P.E. Hall (1938–1939) M.H. Rogers (1999–2000) G. Njowa E.J. Walls * E.H.A. Joseph (1939–1940) L.A. Cramer (2000–2001) * J.H. Dobson (1940–1941) * A.A.B. Douglas (2001–2002)  !""  "!
     * Theo Meyer (1941–1942) S.J. Ramokgopa (2002-2003) N.A. Barcza J.L. Porter * John V. Muller (1942–1943) T.R. Stacey (2003–2004) R.D. Beck S.J. Ramokgopa * C. Biccard Jeppe (1943–1944) F.M.G. Egerton (2004–2005) J.R. Dixon M.H. Rogers * P.J. Louis Bok (1944–1945) W.H. van Niekerk (2005–2006) R.P.H. Willis (2006–2007) M. Dworzanowski D.A.J. Ross-Watt * J.T. McIntyre (1945–1946) * M. Falcon (1946–1947) R.G.B. Pickering (2007–2008) H.E. James G.L. Smith * A. Clemens (1947–1948) A.M. Garbers-Craig (2008–2009) R.T. Jones W.H. van Niekerk * F.G. Hill (1948–1949) J.C. Ngoma (2009–2010) G.V.R. Landman R.P.H. Willis * O.A.E. Jackson (1949–1950) G.V.R. Landman (2010–2011) C. Musingwini * W.E. Gooday (1950–1951) J.N. van der Merwe (2011–2012) * C.J. Irving (1951–1952) G.L. Smith (2012–2013) G.R. Lane–TPC Mining Chairperson * D.D. Stitt (1952–1953) M. Dworzanowski (2013–2014) Z. Botha–TPC Metallurgy Chairperson * M.C.G. Meyer (1953–1954) J.L. Porter (2014–2015) K.M. Letsoalo–YPC Chairperson * L.A. Bushell (1954–1955) R.T. Jones (2015–2016) C. Musingwini (2016–2017) G. Dabula–YPC Vice Chairperson * H. Britten (1955–1956) * Wm. Bleloch (1956–1957) S. Ndlovu (2017–2018) !   ! "!  Botswana Vacant DRC S. Maleba Johannesburg Vacant %#%*$*+ )$+ "(&)*& Namibia N.M. Namate Scop Incorporated Northern Cape F.C. Nieuwenhuys "('%*& Pretoria R.J. Mostert Genesis Chartered Accountants Western Cape L.S. Bbosa )*)'$*()& Zambia D. Muma The Southern African Institute of Mining and Metallurgy Zimbabwe C. Sadomba Fifth Floor, Minerals Council South Africa Building 5 Hollard Street, Johannesburg 2001 • P.O. Box 61127, Marshalltown 2107 Zululand C.W. Mienie Telephone (011) 834-1273/7 • Fax (011) 838-5923 or (011) 833-8156 E-mail: [email protected] 9 1 0 2 H C R A ...... iv M

3

 
. O N

9 ...... v–vi 1 1

E M U L O V VOLUME 119 NO. 3 MARCH 2019 ...... 290          ...... 243 ...... 229 ...... 217 ...... 253      McGill University, Canada PROFESSOR DICK MINNITT SPECIAL EDITION PROFESSOR DICK MINNITT SPECIAL NIOSH Research Organization, USA University of British Columbia, Canada Murdoch University, Australia Curtin University, Australia McGill University, Canada , University of Exeter, United Kingdom T.J. Otto and C. Musingwini. . . . V. Maseko and C. Musingwini. . . . E. Topal, D. Vogt R. Dimitrakopoulos, D. Dreisinger, E. Esterhuizen, H. Mitri, M.J. Nicol, #')*#$'(%#$+ "(&%*+%$*" A spatial mine-to-plan compliance approach to improve alignment of short- and long-term A spatial mine-to-plan compliance approach to improve alignment of short- and mine planning at open pit mines by Application of geometallurgical modelling to mine planning in a copper-gold mining Application of geometallurgical modelling mineral processing efficiency operation for improving ore quality and by C. Beaumont and C. Musingwini . . . . by J. Githiria and C. Musingwini. . . . range for Mineral Reserve declarations to An empirical long-term commodity price mines minimize impairments in gold and platinum by Journal Comment by W. Assibey-Bonsu ...... model to incorporate uncertainty for improved A stochastic cut-off grade optimization project value Contents Due to a lack of proper integration between technical and functional areas that form the mine Due to a lack of proper integration between technical and functional areas that form value chain at Kansanshi, the ore classification system that was being used unintentionally misclassified ore. A geometallurgical analysis was therefore undertaken to review the classification system and a new geometallurgical ore classification system was developed, which led to a decrease in the waste tons mined and an increase in the ore tons. President’s Corner: Treating the mineral asset like an asset Treating Corner: President’s by A.S. Macfarlane ...... – Author registration The ORCiD initiative The development and implementation of a spatial mine-to-plan compliance reconciliation The development and implementation of a spatial mine-to-plan compliance reconciliation of an open approach for an open pit mine is described. Applying this approach to a case study mine-to- pit iron ore mine in South Africa indicated a significant improvement in the spatial plans, plan compliance, thus improving the alignment between short-term plans, long-term and life-of-mine plans. An assessment of modifying factors for converting Mineral Resources to Mineral Reserves An assessment of modifying factors for converting sensitive to long-term commodity prices. The findings revealed that Mineral Reserves were most that long-term commodity price assumptions from the analysis of the assessment suggests Reserve declarations and minimize impairments. within ±5% improve confidence in Mineral A stochastic cut-off grade optimization model that extends Lane’s deterministic theory for A stochastic cut-off grade optimization model life of mine (LOM) is presented. The model uses calculating optimal cut-off grades over the price distribution to account for uncertainty. realistic grade-tonnage realizations and commodity optimization approaches was demonstrated. An improved project value by using stochastic ,   
  

    

 



   

   (&)"+  

*)&)#'$'()  )#+ )&&  

  




   B. Genc  M. Tlala D. Tudor  S. Ndlovu R.D. Beck R.T. Jones  + T.R. Stacey

P. den Hoed   W.C. Joughin

J.H. Potgieter H. Lodewijks N. Rampersad  C. Musingwini  

!"('%*($+%$*"

M. Dworzanowski !"('%*($+%#&'$#' )&)'+$#"+ ii  

   for resale. purposes, for creating new collective works, or Schenectady, New Yorkconsent 12301, does U.S.A. not This copying, extend to such otherdistribution, kinds as for of advertising copying or promotional for general paid through the Copyright Clearance Center, Inc., Operations Center, P.O. Box 765, 108 of the U.S. Copyright Law. The fee is to be paper beyond that permitted by Section 107 or copier pays the stated fee for each copy of a copyright holder consentscopies to of the the makinguse. article This of for consent is personal given or on internal condition that the by any meansthe publishers. without the prior permission of U.S. Copyright Law applicable to users In the U.S.A. The appearance of the statement of copyright at the bottomappearing of in the this first journal page indicates of that an the article a retrieval system, or transmitted in any form or     of this publication may be reproduced, stored in purposes of research or private study. No part an article may be supplied by a library for the THE INSTITUTE, AS A BODY, IS NOT RESPONSIBLE FOR THE STATEMENTS AND OPINIONS ADVANCED IN ANY OF ITS PUBLICATIONS. of the Republic of South Africa, a single copy of Copyright© 2018 by The Southern African Institute of Miningreserved. and Multiple Metallurgy. copying Allthis of rights publication the or contentspermission of parts is thereof inpermission breach without is of hereby copyright,titles given but and for abstracts theauthors. of copying Permission papers of to andshort copy names extracts illustrations of from and contributions the is text usually ofapplication given individual to upon the written source Institute, (and provided where thatis appropriate, the acknowledged. the Apart copyright) for from the any purposes fair of dealing review or criticism under E-mail: [email protected] %*#$& (*)'%*+%
+ ")*'(&(#+) *(#')"+ The Southern African Institute of The Southern African Institute Mining and Metallurgy P.O. Box 61127 Marshalltown 2107 Telephone (011) 834-1273/7 Fax (011) 838-5923 E-mail: [email protected]  ISSN 2225-6253 (print) ISSN 2411-9717 (online) Camera Press, Johannesburg Barbara Spence Avenue Advertising Telephone (011) 463-7940 L VOLUME 119 NO. 3 MARCH 2019

Evaluation of government equity participation in the minerals sector of Tanzania from 1996 to 2015 by P.R. Lobe, A.S. Nhleko, and H. Mtegha ...... 261 The Tanzanian government’s equity participation in the minerals sector was evaluated for the period 1996 to 2015. The study highlights a number of challenges faced by the government, and recommends measures to be taken to ensure a more effective government equity role. Benefits of including resistivity data in a resource model – an example from the Postmasburg Manganese Field by J. Perold and C. Birch ...... 271 The manganese resources determined by using drilling data exclusively were compared to those determined from a combination of drilling and resistivity data. The results showed that including resistivity data can reduce exploration costs significantly due to the more accurate siting of boreholes, which decreases the number of boreholes, samples, and analyses required. Furthermore, a better forecast of the net present value of an operation can be obtained due to the more accurate estimation of manganese resources and stripping ratios. Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data from Landsat by M.A. Mahboob, B. Genc, T. Celik, S. Ali, and I. Atif ...... 279 The unique spectral reflectance and absorption characteristics of remotely sensed Landsat data in the visible, near- infrared (NIR), shortwave-infrared (SWIR) and thermal -infrared (TIR) regions of the electromagnetic spectrum were used in different digital satellite image processing techniques. The methodology developed in this study, based on reflectance spectroscopy of satellite data, is cost-effective and time saving, and can be applied to inaccessible and/or new areas where on-the-ground knowledge is limited. The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery, South Africa by M. Katuruza and C. Birch ...... 291 An unmanned aircraft system (UAS) was used at Isibonelo Colliery to conduct highwall mapping using a digital photogrammetry technique. The collected data was rapidly processed and a 3D model of the mapped pit area produced. The results showed a good correlation between the resource model and the UAS data model.

PAPERS OF GENERAL INTEREST

Optimization of conditions for the preparation of activated carbon from olive stones for application in gold recovery by M. Louarrat, G. Enaime, A. Baçaoui, A. Yaacoubi, J. Blin, and L. Martin ...... 297 The purpose of this study was to produce an activated carbon from olive stones to be used for the recovery of gold. The effect of four process parameters on the production of the activated carbon was studied in order to optimize the yield, gold recovery capacity, and mechanical strength. The activated carbon produced under the optimal conditions had a gold adsorption capacity similar to that of commercial activated carbon and performed well in CIL tests. Improved ultrafine coal dewatering using different layering configurations and particle size combinations by M.E.C. Snyman and N. Naudé...... 307 Major problems with belt-filter dewatering operations are caused by the presence of ultrafines in the feed stream. This work examined the effect of coal particle size and layering during super-fines belt-filter dewatering using a range of blends. This was determined in practise using a vacuum filter to simulate belt filtration. The best layering configuration was with fine material at the bottom and coarse material on top. Contributors to fatigue at a platinum smelter in South Africa by J. Pelders and G. Nelson ...... 313 This study assesses the associations between demographic, work, living and socioeconomic conditions, and lifestyle characteristics and fatigue at a platinum smelter. Information was gathered from interviews and questionnaires. Various demographic, lifestyle, and wellness-related factors were found to be associated with fatigue. Both work and non-work contributors should be addressed in fatigue management plans. South Africa’s options for mine-impacted water re-use: A review by T. Grewar ...... 321 Large volumes of treated mining-impacted water are produced, often with no end use in mind other than discharge or disposal. The most suitable option for re-using treated mining-impact water is within agriculture, specifically the irrigation of crops (food, forage, or energy crops), which currently and unnecessarily uses the majority of South Africa’s high-quality resources of potable water.

         
   
 iii L  
 W. Assibey-Bonsu   
          Group Geostatistician and Evaluator, Gold Fields Limited    recognizes the immense contribution of Professor Dick Minnitt, of contribution of Professor Dick Minnitt, recognizes the immense   Journal short-term spatial mine reconciliation and compliance. versus is volume of the h one of their four NRF-rated academics and one of only three Professor Emeritus academics and one of only three Professor one of their four NRF-rated the School of Mining Engineering at the University of the Witwatersrand (Wits), where he is Engineering at the University of the Witwatersrand the School of Mining T insights and inputs for ongoing mineral resource research to both industry and academia. insights and inputs for ongoing mineral resource Institute of Mining and Metallurgy (SAIMM). Though ‘retired’, he continues to provide valuable Institute of Mining and Metallurgy (SAIMM). contributed to, but also supported and maintained a close association with, the Southern African contributed to, but also supported and maintained mineral economics and mineral resource evaluation. Over the years he not only materially mineral economics and mineral resource evaluation. courses in geostatistics and mineral economics for mining investment in his specialized fields of courses in geostatistics and mineral economics postgraduate (MSc/PhD) candidates and publishing his own research, but also presenting candidates and publishing his own research, postgraduate (MSc/PhD) appointments in the School. He spent most of his career at Wits, supervising not only He spent most of his career at Wits, appointments in the School.

  


Comment Journal , deserves mention, from aspects that include mine planning (36%), geology and resource estimation (21%), , deserves mention, from aspects that include It is hoped that readers will benefit from this volume, which recognizes the immense contributions that Professor It is hoped that readers will benefit from this volume, which recognizes the immense The technology, metallurgy, and environmental topics range from the use of unmanned aircraft systems for The technology, metallurgy, and environmental topics range from the use of unmanned The policy papers present some interesting contributions including an evaluation of government participation in The policy papers present some interesting contributions including an evaluation of government This volume also highlights how geology and resource modelling underpin economic block modelling and This volume also highlights how geology and resource modelling underpin economic Mine planning aspects cover subjects including stochastic cut-off grade derivation aimed at quantifying uncertainty Mine planning aspects cover subjects including Professor Minnitt has published some 65 technical papers both locally and overseas. Professor Minnitt has published some 65 technical Professor Minnitt was appointed as the JCI Professor of Mineral Resources and Reserves in Professor Minnitt was appointed as the JCI Dick Minnitt has made to both research and industry. highwall mapping in open pits to environmental dust controls. the mineral sector in Tanzania and South Africa, as well as the role of women in the mining sector. the mineral sector in Tanzania and South Africa, as well as the role of women in the further show the advantages of accessing additional information for geological modelling, including resistivity data for further show the advantages of accessing additional information for geological modelling, minerals. manganese resource modelling and reflectance spectroscopy for mapping hydrothermal could reduce the risks in resource/reserve and mine financial evaluation. The geology and resource modelling papers could reduce the risks in resource/reserve and mine financial evaluation. The geology demonstrates how stochastic processes, which quantify uncertainty pertaining to geology and economic parameters, demonstrates how stochastic processes, which quantify uncertainty pertaining to geology regards to long-term/life-of-mine with regards to input parameters for cut-off grade modelling, assessment of modifying factors for reserve declaration, with regards to input parameters for cut-off practitioners’ challenge with and spatial mine planning reconciliation. The latter provides possible solutions to the the balance of the papers from industry. government and mining policy (21%), to technology, metallurgy, and environmental papers that make up the final government and mining policy (21%), to technology, are from Wits University, showcasing ongoing research at Wits, with 22% of this volume. Most of the contributions Journal The variety and diversity of his contributions to research and industry as reflected in this The variety and diversity of his contributions organizing committee for the 35th International Geological Conference. organizing committee for the 35th International still finds time to go above and beyond, as shown in 2016 through his membership of the still finds time to go above and beyond, as are indeed numerous, illustrating both dedication and much sacrifice of his private life, yet he are indeed numerous, illustrating both dedication Geostatistical Association of South Africa (GASA). His accolades, awards, and contributions Geostatistical Association of South Africa (GASA). the Geological Society of South Africa (GSSA), and a life member and past president of the the Geological Society of South Africa (GSSA), Sampling and Blending 2017. He is a Fellow of the SAIMM, a Fellow of the AusIMM and Sampling and Blending 2017. He is a Fellow in 2017, awarded for excellence in teaching and application of the Theory of Sampling by in 2017, awarded for excellence in teaching at the Eighth World Conference on the World Conference in Sampling and Blending, the SAIMM in 2008, 2014, and 2016, and most recently the Pierre Gy Sampling Gold Medal the SAIMM in 2008, 2014, and 2016, and 2001, and over the years has received many merit awards, including three silver medals from 2001, and over the years has received many iv L President’s Treating the mineral asset like an asset Corner

he papers in this edition are all related to Mineral Resource Management, the field in which Professor Richard Minnitt practised for many years in the Chair in Mineral Resources at the University of the TWitwatersrand. Professor Minnitt has followed the great luminary, the late Danie Krige, in pioneering many aspects of this field, especially in the areas of geostatistics and mineral evaluation. It is most fitting that this special edition be dedicated to this area, and to Professor Minnitt. The field of Mineral Resource Management is one which has developed over the last two decades, with its initial development (in a South African context) finding its roots in what was then the Gold Division of Anglo American. The initial premise was that work in the fields of geology, evaluation, mine surveying and mine planning was conducted in ‘silos’, and was normally seen as a ‘service’ function to mining. This relegation to a service function meant that the work done by these departments was seen as purely technical and carried out at a low level in the organization. Work in rock engineering, ventilation, and safety was similarly subordinated. The result of this perspective was that these departments submitted reports on observations, and made recommendations, which all too often went unheeded, rendering these departments ineffective. The advent of value chain thinking, coupled with the application of Levels of Work Theory, as developed by Elliott Jaques in his book entitled Requisite Organization (Cason Hall & Co., 1989) and developments in mining technical information systems created the idea that Mineral Resource Management (MRM) as a concept would on the one hand break down the functional silos and create an integrated approach to technical services, and on the other hand would elevate the profile and accountability of MRM. Benchmarking against international operations indicated that in technical services departments such integration already existed, and the levels of competence and professionalism were considerably higher than had been the case traditionally in South African operations. Companies such as Codelco and BHP Billiton populated these departments with competent senior mining engineers and general managers, and focused on areas aligned to the full value chain, such as business planning, mine design, optimization, metal accounting, and geometallurgy. It was also observed that these departments were considered as the ‘brains trust’ of the operations, with mining departments having little discretion in terms of ‘where to mine’. These observations and conclusions were the basis for establishing MRM at mines and creating MRM departments in South Africa. At the same time, academic research and developments resulted in the establishment of postgraduate courses in MRM at the University of the Witwatersrand, and in Mineral Throughput Management at the University of the Free State. As all of this work progressed, so it started to give direction to the further development of MRM technical systems, with an increasing emphasis on economics and optimization. So where is MRM now? It is my opinion that while good progress was made in developments in MRM, and excellent studies and research have been done in various areas of technical focus (as illustrated by the papers in this edition), there is much work still to be done. The concept of MRM may have reached its limit, and a transition to Mineral Asset Management would seem to be appropriate. It is obvious that the principal asset of a mining company is the Mineral Resource over which the company has rights. Within this asset is the metal or commodity that should be identified, scheduled, extracted, and beneficiated in order to realize optimum value from the underlying asset. This focus on ‘treating the asset like an asset’ leads one in the direction of asset management principles, wherein one would apply the same asset management principles to this principal asset as one would to an asset such as a haul truck. Let us consider some of these. Assets should be the subject of life cycle costing. When applied to the mineral asset, this should cover the entire process of discovery, feasibility, design, scheduling, development, operation, and closure. A life cycle costing approach seeks to derive the maximum value from the asset over its life through the optimal combinations of capital, operating levels, operating costs, and profitability, under constantly varying revenue conditions. This approach recognizes that the old ‘cradle to grave’ approach to the life of mine through a once-a-year rework is obsolete, and that a more dynamic approach is required which constantly re-evaluates whether the extraction strategy is still appropriate, and when the asset should be either sold or replaced. This approach should also ensure that the right metrics are applied at the appropriate stage of the life of the mine. Clearly, long-term measures are not appropriate when the asset is in a harvesting or closure phase.

         
  
 v L of o  
(SME. 2001) A.S. Macfarlane President, SAIMM          Management of Mineral Resources (continued) , Chamber of Mines, 1977). The pay limit has been used as a , Chamber of Mines, 1977). The pay limit has   .   , Mining Journal Books, 1988) extended the use of cut-off grades to long- , Mining Journal Books, 1988) extended the  South African Mine Valuation President’s Corner President’s   
 The Economic Definition of Ore all relevant data related to the asset and its use. all relevant data related to the asset and its measures indicate the appropriate levels of flexibility required. measures indicate the appropriate levels of interruption due to seismicity, potential for the loss of the asset as it is extracted and transported, and the reliability of interruption due to seismicity, potential for to ensure that short- and medium-term plans can be realized. to ensure that short- assets. failures due to geological interferences such as dykes, potholes and washouts, and other unwanted events. These failures due to geological interferences such aspects that make the asset unreliable are addressed. This could include the level of geological uncertainty, the risk of aspects that make the asset unreliable are resulted in sufficient mineable face length being available, and that sufficient flexibility has been created in the orebody, that sufficient flexibility has been created in mineable face length being available, and resulted in sufficient includes a holistic approach covering capital, people, systems, and indicators of productivity. In this case, productivity What is the mean time between failures? This involves the development of controls that monitor the mean time between What is the mean time between failures? This Is the asset optimized? Is the asset reliable? Answering such a question requires that sufficient work has been done to ensure that those Is the asset reliable? Answering such a question Is the asset available? This means the development of appropriate metrics and controls to ensure that planning has metrics and controls to ensure that planning This means the development of appropriate Is the asset available? will place focus on the mining process, mining efficiency, and all the leading Is the asset being utilized optimally? This In each phase, critical asset management value-adding questions should be asked, such as: asset management value-adding questions In each phase, critical The question arises as to whether the traditional metrics applied to the life of mine, in terms of net present value (NPV) to the life of mine, in terms of net present to whether the traditional metrics applied The question arises as These initiatives should all help to contribute towards restoring confidence of investors, who have seen a paucity of These initiatives should all help to contribute towards restoring confidence of investors, These opportunities, as well as the establishment of new Mineral Asset Management metrics, are easier to develop now These opportunities, as well as the establishment of new Mineral Asset Management Third, these should become important tools in the toolbox of the modern Mineral Asset Manager. Third, these should become important tools in the toolbox of the modern Mineral Asset Secondly it provides a fascinating problem for a postgraduate study, to identify the missing link between dynamic cut-off Secondly it provides a fascinating problem for a postgraduate study, to identify the missing So, what does this mean? relies on an iterative, manual It creates an opportunity, in that the use of an EVA/MVA based optimization tool currently This two-stage, iterative optimization process intuitively suggests another important link, which is that to real option This two-stage, iterative optimization process intuitively suggests another important This created a very important linkage between cut-off grades, EVA, MVA, and optimization. Kenneth Lane ( The issue of optimization is where the topic becomes really exciting. One of the tools in the toolbox of the Mineral Asset The issue of optimization is where the topic ® ® ® ® ® making, and incorporating risk and volatility. making, and incorporating (MVA) (long term), combines short-term cash flow optimization with long-term value, based on value-adding decision- with long-term value, based on value-adding short-term cash flow optimization (MVA) (long term), combines valuation is done. Alternatively, an economic value added (EVA) approach (short term), coupled with market value add approach (short term), coupled with market an economic value added (EVA) valuation is done. Alternatively, ‘constant’ in that they rely on a set of considerations that are static rather than dynamic, unless constant re-planning and rather than dynamic, unless constant rely on a set of considerations that are static ‘constant’ in that they and internal rate of return (IRR), are still appropriate. This consideration leads to a conclusion that these metrics may be to leads to a conclusion that these metrics (IRR), are still appropriate. This consideration and internal rate of return dividend returns from local mining stocks over many years because of the greater level of real-time data that is possible and available. grades, EVA and MVA, and real option analysis. grade/tonnage curve and asset management. calculation. Thus, the need to develop this into a useable model provides an opportunity to link this directly to the calculation. Thus, the need to develop this into a useable model provides an opportunity the remaining asset and the capitalization required to be applied to it. analysis. This is because the Black-Scholes formula for real option evaluation splits the value of a real option into the value analysis. This is because the Black-Scholes formula for real option evaluation splits the volumes, grades etc.) and optimizing the value of the remaining life of the asset. volumes, grades etc.) and optimizing the value equation. He used this equation to perform optimization by maximizing the cash flow of short-term extraction (by varying equation. He used this equation to perform examined the work of Lane, and realized that Lane’s dynamic cut-off grade optimization was actually based on the EVA examined the work of Lane, and realized that term optimization and dynamic optimization. Juan Camus in his book term optimization and dynamic optimization. available reserves and mining mix, under varying price conditions. available reserves and mining mix, under mining areas where costs can be accurately allocated. This has been used for short-term optimization through estimating mining areas where costs can be accurately This does not serve as an optimization tool. Cut-off grades, on the other hand, allow more focused application to specific This does not serve as an optimization tool. measure to define Mineral Resources and Mineral Reserves, usually on an annual basis and mainly for shareholder reporting. measure to define Mineral Resources and Mineral pay limit, as espoused by Storrar ( Manager is the grade-tonnage curve and the use and application of cut-off grades. Traditionally, mines have worked with the Manager is the grade-tonnage curve and the vi L http://dx.doi.org/10.17159/2411-9717/2019/v119n3a1 A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value by J. Githiria1 and C. Musingwini1

rock must provide a certain minimum profit per ton processed. $78-5=5 Later in the 1960s, work on cut-off grade Cut-off grade is a decision-making criterion often used for determining the calculation again appeared, including that quantities of material (ore and waste) to be mined, ore processed, and published by Henning (1963), Lane (1964), saleable product. It therefore directly affects the cash flows from a mining operation and the net present value (NPV) of a mining project. A series of and Johnson (1969). Lane (1988) different cut-off grades that are applied over the life of mine (LOM) of an subsequently published an updated version of operation defines a cut-off grade policy. Due to the complexity of the his 1964 work as a comprehensive book on calculation process, previous work on cut-off grade calculation has mostly the use of cut-off grade to economically define focused on deterministic approaches. However, deterministic approaches ore using NPV as a proxy for value. To date, it fail to capture the uncertainty inherent in input parameters such as is Lane’s work on value-based cut-off grade commodity price and grade-tonnage distribution. This paper presents a optimization that has received the most stochastic cut-off grade optimization model that extends Lane’s attention among the mining fraternity. Lane’s deterministic theory for calculating optimal cut-off grades over the LOM. work placed more emphasis on optimizing cut- The model, code-named ‘NPVMining’, uses realistic grade-tonnage off grade in order to improve the economic realizations and commodity price distribution to account for uncertainty. viability of mining projects and operations. NPVMining was applied to a gold mine case study and produced an NPV ranging between 7% and 186% higher than NPVs from deterministic The cut-off grade algorithm developed by Lane approaches, thus demonstrating improved project value from using (1964, 1988) was more elaborate than others stochastic optimization approaches. as it took into account constraints associated with the capacities of the mine, mill, and @<$"8965 market, resulting in the derivation of six optimization, cut-off grade policy, deterministic approach, heuristic approach, stochastic approach, grade-tonnage realization, uncertainty. potential cut-off grades from which an optimal cut-off grade could be selected. Three of the six cut-off grades are described as limiting cut- off grades while the other three are denoted as balancing cut-off grades. Limiting cut-off grades are derived by assuming that each of
;3298476>87>34:#8//>29;6<>3;.34.;:=87 the three stages (mining, processing, and ;76>8-:=1=;:=87 refining) is an individual and independent Cut-off grade is a decision-making criterion constraint on throughput due to production that is generally used in mining to distinguish capacity limitations, operating costs, and price ore from waste material. Consequently, it is attributable to the output product. Balancing used to determine the quantities of material cut-off grades are determined by assuming (ore and waste) to be mined, ore processed, that two out of the three stages are and saleable product. A series of different cut- concurrently operating at their capacity limits. off grades that are applied over the life-of- Despite its fairly comprehensive structure, mine (LOM) of a mining operation defines the Lane’s cut-off grade optimization algorithm cut-off grade policy for that particular had some shortcomings. For example, it could operation. The cut-off grade therefore directly not be used to determine cut-off grades for affects the cash flows to be produced and the polymetallic deposits. This shortcoming is now net present value (NPV) of a project at the addressed through the concept of net smelter mine planning or feasibility study stage. Pioneering work on cut-off grade calculation can be attributed to Mortimer’s (1950) work on grade control for gold mines in South Africa. Although Mortimer’s work is given relatively little recognition, it established 1 University of the Witwatersrand, South Africa. the fundamental principle that not only must © The Southern African Institute of Mining and rock at the lowest grade cover its cost of Metallurgy, 2019. ISSN 2225-6253. Paper received extraction, but that the average grade of the Aug. 2018.

VOLUME 119          
  
 217 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value return (NSR) for evaluating polymetallic deposits, as for paper therefore extended Lane’s algorithm to develop a example in the work of Shava and Musingwini (2018) who stochastic cut-off grade model by concurrently considering developed an NSR model for a zinc, lead, and silver mine. variability in both commodity price and grade-tonnage Shava and Musingwini (2018) then related the NSR values to distribution. The model that was developed is code-named the applicable cut-off grades for each of the three constituent ‘NPVMining’. metals. Table I summarizes some studies that have attempted to address different shortcomings in Lane’s cut-off grade 86=/=3;:=875>:8>;7<5>34:#8//>29;6<>:0<89$>/89>:0< theory. 5:830;5:=3> 186<. Despite making improvements to Lane’s original cut-off Lane’s theoretical framework is premised on a schematic grade theory, the models in Table I are deterministic and material flow as illustrated in Figure 1. Depending on the therefore fail to capture the economic, technical, and applicable cut-off grade, material from the mine can be geological uncertainties that mining operations continually classified as waste and sent to the waste dump; as ore and face. The uncertainties include those associated with sent for milling in the processing plant; or as low-grade commodity price and grade-tonnage distribution. Due to this material and sent to a stockpile for processing later during shortcoming, the NPVs generated from these models are sub- the LOM. The milling process produces a concentrate which is optimal. There is, therefore, a need for a stochastic cut-off sent to the refinery to produce the final saleable product, grade optimization approach that can capture uncertainty in which is then marketed. parameters such as commodity price and grade-tonnage The production capacities of the different stages in the distribution. This challenge had been long-recognized in mining complex are denoted by M, C, and R, for the mining, other studies not related to Lane’s framework, but which milling, and refinery capacities, respectively. Lane’s attempted to use other stochastic and/or dynamic framework uses the notations in Table III. The input programming (DP) approaches to address the challenge. parameters in Table III were then modified to account for variability as explained in the following sections. :830;5:=3>;76>6$7;1=3>-9829;11=72>;--98;30<5>:8 Given a set of equally probable grade-tonnage curves (w), 34:#8//>29;6<> the stochastic approach develops a cut-off grade policy by Several studies that have applied stochastic and/or DP determining the cut-off grade (G) from time periods 1 to N. approaches in the calculation of cut-off grades have The NPV of future cash flows is maximized subject to mining, incorporated the dynamic nature of input parameters. Table II processing, and refining capacity constraints. The objective summarizes some studies that have attempted to address function for the cut-off grade optimization remains uncertainty in parameters for cut-off grade determination. unchanged from Lane’s original formulation, as represented The studies summarized in Table II, except for the model by Equation [1]. by Asad and Dimitrakopoulos (2013), were not based on Lane’s framework and tended to consider only one input [1] parameter as being stochastic. The study presented in this

Table I ;1-.<5>8/>5:46=<5>;669<55=72>581<>5089:381=725>=7>;7<5>34:#8//>29;6<>:0<89$

:46$ 411;9$>8/>=1-98<1<7:

Taylor (1972) Taylor’s approach for balancing cut-off grades used statistical parameters to describe the grade distribution of the orebody, since grade is variable throughout an orebody. Taylor (1985) The approach incorporated a stockpiling stage into Lane’s framework so that instead of dumping low-grade material as waste, it is kept as stockpiles as future ore feed to the mill. Dagdelen (1992, 1993) Dagdelen developed an analytical method for finding balancing cut-off grades which was more efficient than Lane’s graphical. Whittle and Wharton (1995) The approach, which is incorporated in the open-pit mining software Geovia Whittle 4-X®, added linear programming (LP) optimization into Lane’s theory to simultaneously incorporate stockpiling of mined material, ore blending, and account for multiple minerals. Asad (1997, 2005) Asad developed a cut-off grade optimization algorithm based on Lane’s work, but with a stockpiling option for open-pit mining operations with two economic minerals. King (2001) King modified Lane’s approach by incorporating variations in throughput for different ore types in order to cater for polymetallic deposits. Dagdelen and Kawahata (2008) The approach applied mixed-integer linear programming (MILP) to improve the efficiency of the calculation process in Lane’s algorithm and was used develop the OptiPit®.mining software package Gholamnejad (2008, 2009) Gholamnejad modified Lane’s algorithm to cater for the trade-off between an increase in the average mill grade and a concomitant increase in rehabilitation costs. As the cut-off grade is increased, the amount of material mined and dumped as waste also increases, leading to increased rehabilitation costs. Osanloo, Rashidinejad, and Rezai (2008) The study incorporated environmental requirements into Lane’s cut-off grade optimization by incorporating waste and tailings disposal costs. King (2011) King modified the earlier (King, 2001) version by incorporating operating and administrative costs. Githiria, Muriuki, and Musingwini (2016) The study developed a computer-aided application based on Lane’s algorithm and improved the efficiency of the cut-off grade calculation process. L 218   
 VOLUME 119          
A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

Table II ;1-.<5>8/>5:46=<5>;669<55=72>473<9:;=7:$>=7>34:#8//>29;6<>6<:<91=7;:=87

:46$411;9$>8/>5:830;5:=3>89> >;--98;30

Dowd (1976) The approach was based on DP to optimize cut-off grade. It incorporated the interaction of cut-off grades and fluctuating commodity prices, but ignored variability in costs. Krautkraemer (1988) Krautkraemer analysed the effect of stochastic metal prices on the selection of cut-off grades, depending on the rate of metal price change relative to the discount rate, and concluded that fluctuations in metal prices critically affect the selection of cut-off grades. Cetin and Dowd (2002, 2013, 2016) The approach applied genetic algorithms (GAs) and DP to optimize cut-off grades for polymetallic mines, while assuming a constant grade-tonnage distribution for the entire orebody. Cetin and Dowd (2016) compared GA, the grid search method, and DP when deriving optimal cut-off grades for deposits with up to three constituent minerals and concluded that GAs are more robust in optimizing cut-off grade for multi-mineral deposits under technical and economic constraints only. Asad (2007) Asad optimized cut-off grade for an open-pit mining operation through an NPV-based algorithm that considered metal price and cost escalation but ignored geological uncertainty. Li, Yang, and Lu (2012) The approach optimized cut-off grade using stochastic programming in open-pit mining but considered commodity price as the only dynamic variable. Asad and Dimitrakopoulos (2013) Asad and Dimitrakopoulos modified Lane’s approach into a heuristic cut-off grade model to account for geological uncertainty in ore supplied to multiple processing streams. However, the approach was limited to a single mine. Thompson and Barr (2014) The approach optimized cut-off grade using stochastic programming in open-pit mining, but considered commodity price as the only dynamic variable. Myburgh, Deb, and Craig (2014) The approach was a hybrid heuristic approach to maximize NPV through cut-off grade optimization. It is incorporated in the software package, Maptek Evolution®. The approach employs an evolutionary GA to optimize cut-off grade and extraction sequence by managing two lower-level algorithms. The first one is LP-based and determines the optimal flow of material through multiple processing streams and manages stockpiles. The second is a local search technique for deriving the best production schedule.

However, the cash flow equation changes to incorporate the uncertainty of both the metal price and grade-tonnage distribution in the orebody, as indicated in Equation [2].

[2] !=249<>(> >30<1;:=3>.;$84:>8/>1;:<9=;.>/.8">=7>;>1=7=72>381-.< *,=:0=9=;)>'%(&+

Table III Using the optimum cut-off grades obtained in the algorithm for the given grade-tonnage curve w, a yearly 8:;:=875>45<6>=7>;7<5>;.289=:01>*;6;-:<6>/981 production schedule that shows the cut-off grade, quantity ,=:0=9=;)>'%(&+ mined (Qmw), quantity processed (Qcw), quantity refined 8:;:=87 -.;7;:=87 7=: (Qrw), profit, and NPV is calculated. Figure 2 illustrates the steps involved in the algorithm used in this research study. i Year - The algorithm developed from Figure 2 was coded using N Mine lifeYears CC Capital cost $ million the C++ programming language in Microsoft Visual Studio s Selling price $/g 2017 Integrated Development Environment (IDE) on a r Refining cost $/oz standard computer to produce the application code-named m Mining cost $/ton ‘NPVMining’. The code for NPVMining is given in Appendix c Milling cost $/ton 1. The application is an executable file and will run on f Annual fixed costs $/year computers that run applications with .exe extension. The y Recovery % d Discount rate % computer must have Visual Studio 2017 and Microsoft Office M Mining capacity t/a 2013 installed on it. C Milling capacity t/a Microsoft Visual Studio 2017 (VC++) supports two R Refining capacity t/a versions of the C++ programming language, which are the Qm Material mined t/a ISO/ANSI standard C++, and C++/CLI (Common Language Qc Ore processed t/a Qr Concentrate refined t/a Infrastructure). C++/CLI has a highly-developed design capability that enables the assembly of the entire graphical user interface (GUI), and the code that creates it being where d is the discount rate and Pwi is the cash flow generated automatically (Githiria, Muriuki, and Musingwini, generated in period i by extracting the orebody based on a 2016). The C++ programming language was used in the grade-tonnage curve w. implementation of the algorithm to enable the execution of

VOLUME 119          
  
 219 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value the application on Windows-based computers with different (m), milling cost (c), refining cost (r), recovery (y), architectures and/or platforms. This compatibility aspect annual fixed costs ( f ), and discount rate (d ). enables easy portability of the application to make it usable 3. Introduce variability in the input parameters (metal by mine planners working on different computing platforms. price and grade-tonnage). The output from the model is easily exported to Microsoft 4. Determine the optimum cut-off grade to be used in year Excel 2013 for comparison and analysis. i using the cut-off grade equations. If the initial NPVi is The flow diagram in Figure 2 was then modelled as not known set the NPVi to zero. follows: 5. Determine the tons of ore (qow), tons of waste (qww), i. Identify the methods of data entry for the grade-tonnage and average grades of the ore associated w the optimum curves, commodity price, and costs. cut-off grade (gavg). Set: Qcwi = C if qow is greater than ii. Develop software to input the grade-tonnage curves, the milling capacity (C), otherwise Qcwi = qow. Using commodity price, and costs variations and run tests for Equations {3]–[7], calculate the quantity to be mined validation. (Qm) and refined (Qr). Find the limiting capacity and the iii. Implement the algorithm for calculating cut-off grade and mine life (N) from the following: NPV using the inputs provided. iv. Test and validate the output and provide the output in a [3] format that will display the results appropriately. Mathematical functions of commodity price against time [4] were applied in the above procedure. A random number generator was developed to generate values within a [5] specified range so that input values are stochastic but within realistic ranges. [6] ,<7<9;.>5:<-5>=7>:0<> 5:830;5:=3>;.289=:01 The steps to determine a cut-off grade policy as outlined by Lane (1964), but modified as illustrated in Figure 2 to [7] incorporate uncertainty in NPVMining, are as follows (Githiria, 2018): 6. Determine the yearly profit using Equation [8]. 1. Formulate multiple realizations of grade-tonnage [8] distribution for the entire deposit. 2. Input the parameters to be used in the cut-off grade policy, such as the mining capacity (M), milling capacity (C), refining capacity (R), selling price (P), mining cost 7. Compute the NPV using the formula below by discounting the profits at a given discount rate (d) for the time calculated as the LOM.

[9]

This value of V becomes the second approximation of V (the first was V=0) for use in the formulae to calculate the optimum cut-off grade. 8. Repeat the computation from step 5 until the value, V, converges. 9. Adjust the grade-tonnage distribution by subtracting the ore tons from the grade-tonnage distribution intervals above the optimum cut-off grade (G) and the waste tons (Qmw – Qcw) from the intervals below the optimum cut-off grade (G) in proportionate amounts. This is to ensure that the distribution remains unchanged, otherwise it will change to a different grade-tonnage distribution. For each of the multiple realizations of the grade-tonnage distribution the current grade-tonnage curve being used at that specific period will be altered simultaneously. This will cater for the intertemporal dependencies that alter the grade- tonnage distribution with time. 10. If it is the first iteration then, knowing the profits obtained in each year, find the yearly NPV by !=249<>' !.8">6=;29;1>8/>:0<>186=/=<6>34:#8//>29;6<>;.289=:01 discounting back those profits and go to step 4. If it is *,=:0=9=;)>'%(&+ the second iteration, then stop. L 220   
 VOLUME 119          
A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

11. Use the net present values obtained in step 10 as the initial NPV for each of the corresponding years for the second iteration.

9=6<539=-:=87>8/> NPVMining caters for: (i) economic and operational parameters, (ii) grade-tonnage distribution, and (iii) the cut- off grade policy or production schedule as shown in Figure 3. One of the source files, NPVMiningDlg.cpp, contains the code that executes the algorithm through the user interface. Appendix 1 contains the code for NPVMining. The input parameters (price and costs) used in the calculations are uploaded to the application using Microsoft Excel® spreadsheets. Other parameters are entered into the user !=249<> ,9;6<>3;:<289$>"=768">*,=:0=9=;)>'%(&+ interface via the dialog boxes. The metal price variability is obtained from factoring either a fixed or geometric range. After calculating the optimum cut-off grade, a cut-off grade policy is generated showing the three main economic indicators: annual profit, NPV, and LOM. The NPVMining user interface has five dialog boxes: (i) grade category window (Figure 4), (ii) price criteria window (Figure 5), (iii) other parameters window (Figure 6), (iv) limiting capacity selection window (Figure 7), and (v) cut-off grade calculation window (Figure 7). The grade-tonnage distribution, economic and operational parameters are the input data used in the computer-aided application. The grade-tonnage distribution is entered into the grade category window as shown in Figure 4. The grade category input window has several dialog boxes describing the lower grade limit, upper grade limit, and !=249<> 9=3<>39=:<9=;>"=768">*,=:0=9=;)>'%(&+ quantity of ore per increment for the multiple realizations. The economic and operational parameters are keyed on the user interface using the price criteria and other parameters window as shown in Figures 5 and 6. This data is uploaded using Microsoft Excel® worksheets containing technical data, while other data is entered in the dialog box as required. This process simplifies data entry, which is tiresome if done manually. The two input windows in Figures 5 and 6 have several dialog boxes that represent economic and operational parameters such as metal price, mining cost, milling cost, refining cost, mining capacity, processing capacity, refining capacity, recovery, discount rate, and fixed !=249<> :0<9>-;9;1<:<95>*<38781=3>;76>8-<9;:=87;.>-;9;1<:<95+ cost. "=768">*,=:0=9=;)>'%(&+

!=249<>  45<9>=7:<9/;3<>*,=:0=9=;)>'%(&+

VOLUME 119          
  
 221 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

The break-even cut-off grade and Lane’s limiting cut-off grade are selected and calculated as shown in Figure 7, and the output is displayed in the output window as shown in Figure 8. The main economic indicators of the project (annual profit, NPV, and LOM) are displayed on the user interface. After clicking the ‘calculate’ button, the results of the cut-off grade policy calculations are displayed in the output window and generated on an Microsoft Excel® spreadsheet as shown in Figure 8. The spreadsheet consists of seven main columns: optimum cut-off grade, quantity of material to be mined (Qm), quantity of ore to be milled (Qc), quantity of product refined (Qr), mine life, annual profit, and NPV. The resultant cut-off grade policy is exported to Microsoft Excel® for ease of use and interpretation. The NPVMining application was tested on the data-set for a case study of the McLaughlin gold mine, which is a defunct gold mine in northern California, USA. The data-set was obtained from the mining library compiled by Espinoza et al. (2012) for research purposes. This data-set was selected because it has previously been used in other cut-off grade optimization studies, therefore allowing comparison of the output from NPVMining with those studies. !=249<>& 4:-4:><-89:<6>:8>;>=39858/:>3<. 5-9<;650<<:> <539=-:=87>8/>:0<>3;420.=7>28.6>1=7<>3;5<>5:46$ *,=:0=9=;)>'%(&+ 6;:;#5<:> Tables IV and V provide the simulated grade-tonnage Table V distribution and the economic, design, and operational parameters, respectively, for the McLaughlin gold mine case 38781=3)>6<5=27)>;76>8-<9;:=87;.>-;9;1<:<95 45<6>=7>:0<>186<.>*,=:0=9=;)>'%(&+

8:;:=87 -.;7;:=87 7=: 1847:>

CC Capital cost $ million 105 000 000 m Mining cost $/ton 1.20 c Milling cost $/ton 19.00 r Refining/Selling cost $/oz 655.00 f Annual fixed costs $/year 8,350,000 y Recovery Decimal 0.90 d Discount rate Decimal 0.15 M Mining capacity t/a Unlimited C Milling capacity t/a 1 050 000 !=249<> <.<3:=87>8/>:0<>.=1=:=72>3;-;3=:$>;76>34:#8//>29;6<>-8.=3$ R Refining capacity t/a Unlimited 45<6>>*,=:0=9=;)>'%(&+

Table IV =14.;:<6>29;6<#:877;2<>6=5:9=4:=87>8/>:0<>3;420.=7>28.6>6<-85=:>*,=:0=9=;)>'%(&+

4;7:=:$>8/>1;:<9=;.>=7>:0<>5=14.;:<6>89<86$>9<;.=;:=87>*:+> ,9;6<>*8:+ ,( ,' , , , ,

0.000-0.020 70 000 70 022 70 081 70 003 69 640 70 900 0.020-0.025 7 257 7 263 7 257 7 364 7 890 7 000 0.025-0.030 6 319 6 325 6 332 6 405 6 860 5 700 0.030-0.035 5 591 5 595 5 616 5 632 6 100 5 200 0.035-0.040 4 598 4 603 4 628 4 608 4 950 4 600 0.040-0.045 4 277 4 279 4 306 4 318 4 570 4 300 0.045-0.050 3 465 3 466 3 488 3 502 3 680 3 000 0.050-0.055 2 438 2 439 2 468 2 438 2 630 2 200 0.055-0.060 2 307 2 309 2 335 2 318 2 520 2 100 0.060-0.065 1 747 1 748 1 754 1 740 1 900 1 500 0.065-0.070 1 640 1 643 1 647 1 637 1 770 1 400 0.070-0.075 1 485 1 488 1 494 1 481 1 560 1 200 0.075-0.080 1 227 1 229 1 237 1 246 1 270 800 0.080-0.100 3 598 3 598 3 625 3 636 3 810 3 300 0.100-0.358 9 574 9 578 9 579 9 641 10 330 9 800 Total 125 523 125 585 125 847 125 969 129 480 123 000 L 222   
 VOLUME 119          
A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value study. Table VI provides the price variations used in the NPV for six equally probable grade-tonnage curves and a calculations. range of metal prices is generated as shown in Table VII. The Six grade-tonnage curves (GTC1 to GTC6) for the resultant cut-off grade policies from the model shows a McLaughlin deposit, as illustrated in Table IV, were used to significant difference between the minimum and maximum determine balancing cut-off grades as described in Lane’s NPV generated through the equally probable grade–tonnage cut-off grade theory (Lane, 1964, 1988). The grade-tonnage curves. The resultant cut-off grade policies generate the curve data was used to calculate the ratios and cumulative optimal NPV in approximately 9 years for the six grade- values in relation to the different stages in a mining complex. tonnage curves. The application (NPVMining) also generates Over-estimation or under-estimation of the grade, volume, or possible outcomes in relation to the change in gold price. The tonnage and other parameters related to a deposit is common six possible outcomes for each price category generate in most conventional and deterministic orebody models. This different outcome as shown in Table VII. The resultant cut- is detrimental to the planning of the mining operation, which off grade policies are generated by varying the grade–tonnage consequently leads to loss of profits. There are several curves for all mineable ore in every grade interval and the statistical methods for measuring uncertainty of the orebody metal prices against time. The solution was generated in in relation to the geological characteristics. Stochastic 14.45 seconds after running the NPVMining code on approaches are employed to characterize the geological Microsoft Visual Studio 2017. uncertainty by modelling and estimating the orebody more The relationship between NPV and the metal price was reliably. This study employed the Monte Carlo method to modelled using a linear regression approach (Figures 9 and simulate the grade-tonnage distribution of the orebody. It 10). The linear regression model shown in Figure 9 is applied used statistical and graphical techniques, including linear to identify the relationship between NPV and the response and nonlinear modelling, to simulate the probable variables (metal price) when all the other variables in the distribution of the data. It is evident from the simulated model are held fixed. The correlation coefficient in the multiple realizations of the orebody that the tonnages relationship between metal price and NPV is about 0.97, decrease with increasing grade ranges. indicating that metal price variation has a high significance The McLaughlin mining operation case study for the NPV. incorporates a mine, processing plant, and waste dump, following the three main stages presented in Figure 1, excluding the stockpiling option. The mine produces sulphide Table VII and oxides ores mixed with waste material in controlled <:>-9<5<7:>;.4<5>2<7<9;:<6>45=72> quantities. The ore goes through several processing stages such as gravity concentration, flotation, and leaching. In the "0<7>;9$=72>-9=3<>;76>29;6<#:877;2<>6=5:9=4:=87 subsequent refining step, the gold is recovered from solution *<5: 3;5<>53<7;9=8+>*,=:0=9=;)>'%(&+ and the waste material is sent to the waste dump. The operation is assumed to have an unrestricted potential to  >* +> 9=3<>*8:87+ ,9;6<#:877;2<>*:+> mine and refine/market the annual gold production, while 467 172 060.50 1250 125 523 the processing capacity is set to be at 1.05 Mt/a of ore (Table 467 172 060.49 1250 125 585 466 990 510.59 1250 125 847 V). Gold price uncertainty applied in this study was assumed 468 922 686.82 1250 125 969 to have a range (2% per period) that is increasing yearly, as 488 180 335.90 1250 129 480 shown in Table VI, to be within the generally accepted long- 475 864 529.70 1250 123 000 487 959 524.30 1270 125 523 term gold price of around US$1300 per ounce. 487 959 524.30 1270 125 585 487 777 974.39 1270 125 847 A<54.:5>/981>:0<>;--.=3;:=87>8/> :8>:0< 489 777 241.30 1270 125 969 509 740 604.86 1270 129 480 3;420.=7>28.6>1=7<>3;5<>5:46$> 496 886 282.14 1270 123 000 508 746 988.10 1290 125 523 The stochastic cut-off grade model (NPVMining) is used to 508 746 988.10 1290 125 585 calculate the optimum cut-off grade that maximizes NPV in 508 565 438.18 1290 125 847 510 631 795.78 1290 125 969 the shortest mine life possible using the price variations in 531 300 873.82 1290 129 480 Table VI and the grade-tonnage curves in Table IV. A 517 908 034.58 1290 123 000 summary of the best-case scenario showing the calculated 529 534 451.90 1310 125 523 529 534 451.88 1310 125 585 529 352 901.98 1310 125 847 531 486 350.25 1310 125 969 552 861 142.78 1310 129 480 Table VI 538 929 787.03 1310 123 000 550 321 915.70 1330 125 523 550 321 915.68 1330 125 585 9=3<>;9=;:=875>45<6>=7>:0<>186<.>*,=:0=9=;)>'%(&+ 550 140 365.78 1330 125 847 552 340 904.73 1330 125 969 9=3<>3;:<289$>7;1< ;.4<>* 8+ 574 421 411.74 1330 129 480 559 951 539.47 1330 123 000 Year 1Range1 1250 571 109 379.50 1350 125 523 Year 2 Range2 1270 571 109 379.47 1350 125 585 Year 3 Range1 1290 570 927 829.57 1350 125 847 Year 4 Range2 1310 573 195 459.21 1350 125 969 Year 5 Range1 1330 595 981 680.69 1350 129 480 Year 6 Range2 1356 580 973 291.91 1350 123 000

VOLUME 119          
  
 223 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

® 7% better than the Cut-off Grade Optimiser ® 35% better than OptiPit® ® 13% better than Maptek Evolution®. The superior NPV generated by NPVMining can be attributed to its incorporation of stochasticity of input parameters, which is not incorporated in the other models. This demonstrates that superior results are obtained by incorporating uncertainty into Lane’s cut-off grade theory.

873.45=87 The stochastic NPVMining model was applied to a gold mine case study data-set to ascertain its benefits in an operational !=249<> =7<;9>9<.;:=8750=-><:"<<7>1<:;.>-9=3<>;76> > *,=:0=9=;)>'%(&+ mine. NPVMining was used to generate six cut-off grade policies, indicating that a change in grade-tonnage distribution has an overall effect on NPV. A comparison between NPVMining and other cut-off grade optimization The relationship between NPV and the other parameter models demonstrated and validated the efficiency of the (grade-tonnage distribution) when all the other variables in model. Using an Intel dual-core processor running at the model are held fixed is shown in Figure 10. The 3.00GHz and with 4.00GB RAM, the model generated results correlation coefficient in the relationship between grade- for each simulation within 5 seconds. The improvements in tonnage distribution and NPV is about 0.13, indicating that NPV generated by NPVMining ranged between 7% and 186%, grade-tonnage distribution has a low impact on NPV. demonstrating the value of using stochastic approaches to cut-off grade optimization. Ignoring the commodity price and 81-;9=587>8/> :8>8:0<9>34:#8//>29;6< geological uncertainties in daily mining operations may have ;--98;30<5 very serious negative economic implications for a mining project. In deterministic cut-off grade optimization approaches applied in the mining industry, the outcomes are determined 378".<621<7:> through known parameters without any room for random variation. This limits the flexibility of a mine plan in cases The work reported in this paper is part of a PhD research where commodity price and operational costs fluctuate study in the School of Mining Engineering at the University through the LOM. However, the self-adaptation in stochastic of the Witwatersrand. The financial support obtained from algorithms contributes greatly to their ability to address the Julian Baring Scholarship Fund (JBSF) for the PhD study successfully most complex real-world problems. This is due is greatly acknowledged. to their strategic outlook on mining problems that allows them to be easily applied to complex mining situations. Table VIII summarizes the results of a comparison conducted between NPVMining and the following cut-off grade approaches: (i) Break-even cut-off grade model (Githiria and Musingwini, 2018) (ii) Cut-off Grade Optimiser (Githiria and Musingwini, 2018) (iii) OptiPit® (Dagdelen and Kawahata, 2008) (iv) Maptek Evolution® (Myburgh, Deb, and Craig, 2014). Table VIII shows that NPVMining generated the highest NPV. Compared to the other cut-off grade approaches, NPVMining produced results that were: !=249<>(% =7<;9>9<.;:=8750=-><:"<<7>29;6<#:877;2<>6=5:9=4:=87> ® 186% better than the break-even cut-off grade model ;76> >*,=:0=9=;)>'%(&+

Table VIII 81-;9=587>8/>:0<>1=7<>.=/<)>3;50>/.8")>;76> >/981>6=//<9<7:>34:#8//>29;6<>186<.5>*,=:0=9=;)>'%(&+

<:<91=7=5:=3>34:#8//>29;6<>;--98;30<5 :830;5:=3>34:#8//>29;6<>;--98;30<5
9<;#<<7>34:#8//>29;6<>186<. 4:#8//>,9;6<>-:=1=5<9 -:= =: ;-:<>8.4:=87 

LOM (years) 35 10 18 10 9.12 Profits/cash flow ($ million) 863 825.44 885.60 760.10 887.09 NPV($ million) 163.42 435.52 347.08 413.84 467.17 L 224   
 VOLUME 119          
A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

A KING, B. 2011. Optimal mining practice in strategic planning. Journal of Mining Science, vol. 47, no. 2. pp. 247–253. ASAD, M.W.A. 1997. Multi mineral cut-off grade optimization with option to KRAUTKRAEMER, J.A. 1988. The cut-off grade and the theory of extraction. stockpile, MSc thesis. Colorado School of Mines, Golden, CO. Canadian Journal of Economics, vol. 21, no. 1. pp. 146–160. ASAD, M.W.A. 2002. Development of generalized cut-off grade optimisation http://doi:10.2307/135216 algorithm for open pit mining operations. Journal of Engineering and LANE, K.F. 1964. Choosing the optimum cut-off grade. Colorado School of Applied Sciences, vol. 21, no. 2. pp. 119–127. Mines Quarterly, vol. 59, no. 4. pp. 811–829. ASAD, M.W.A. 2005. Cut-off grade optimisation algorithm with stockpiling LANE, K.F. 1988. The Economic Definition of Ore: Cut-off Grade in Theory and option for open pit mining operations of two economic minerals. Practice. Mining Journal Books, London. International Journal of Surface Mining, Reclamation and Environment, LI, S., YANG, C., and LU, C. 2012. Cut-off grade optimization using stochastic vol. 19, no. 3. pp. 176–187. programming in open-pit mining. Proceedings of the Sixth International Conference on Internet Computing for Science and Engineering, Henan, ASAD, M.W.A. 2007. Optimum cut-off grade policy for open pit mining China. IEEE, New York. pp. 66–69. doi:10.1109/ICICSE.2012.24 operations through net present value algorithm considering metal price MORTIMER, G. 1950. Grade control. Transactions of the Institution of Mining and cost escalation. Engineering Computations, vol. 24, no. 7. and Metallurgy, vol. 59. pp. 1–43. pp. 723–736. MYBURGH, C.A., DEB, K., and CRAIG, S. 2014. Applying modern heuristics to ASAD, M.W.A. and DIMITRAKOPOULOS, R. 2013. A heuristic approach to stochastic maximising net present value through cut-off grade optimisation. cut-off grade optimisation for open pit mining complexes with multiple Proceedings of Orebody Modelling and Strategic Mine Planning processing streams. Resources Policy, vol. 38. pp. 591–597. Symposium, Perth, WA. Australasian Institute of Mining and Metallurgy, CETIN, E. and DOWD, P.A. 2002. The use of genetic algorithms for multiple cut- Melbourne. pp. 155–164. off grade optimisation. Proceedings of the 32nd International Symposium OSANLOO, M., RASHIDINEJAD, F., and REZAI, B. 2008. Incorporating environmental on Application of Computers and Operations Research in the Mineral issues into optimum cut-off grades modeling at porphyry copper deposits. Industry (APCOM). Society for Mining, Metallurgy & Exploration, Resources Policy, vol. 33, no. 4. pp. 222–229. Littleton, CO. pp. 769–779. SHAVA, P. and MUSINGWINI, C. 2018. A net smelter return model for a CETIN, E. and DOWD, P.A. 2013. Multi-mineral cut-off grade optimization by grid polymetallic deposit. Proceedings of the 6th Regional Conference of the search. Journal of the Southern African Institute of Mining and Society of Mining Professors: Overcoming Challenges in the Mining Metallurgy, vol. 113, no.8. pp. 659–665. industry through Sustainable Mining Practices, Johannesburg, South Africa, 12-13 March 2018. Southern African Institute of Mining and CETIN, E. AND DOWD, P.A. 2016. Multiple cut-off grade optimization by genetic Metallurgy, Johannesburg. pp. 279–291. algorithms and comparison with grid search method and dynamic TAYLOR, H.K. 1972. General background theory of cut-off grades. Transactions programming. Journal of the Southern African Institute of Mining and of the Institution of Mining and Metallurgy, Section A: Mining Metallurgy, vol. 116, no.7. pp. 681–688. Technology, vol. 81. pp. A160–A179. DAGDELEN, K. 1992. Cut-off grade optimisation. Proceedings of the 23rd TAYLOR, H.K. 1985. Cut-off grades – some further reflections. Transactions of International Symposium on Application of Computers and Operations the Institution of Mining and Metallurgy, Section A: Mining Technology, Research in the Minerals Industry (APCOM). Society for Mining, vol. 96. pp. 204–216. Metallurgy & Exploration, Littleton, CO. pp. 157–165. THOMPSON, M. and BARR, D. 2014. Cut-off grade: a real options analysis. DAGDELEN, K. 1993. An NPV optimisation algorithm for open pit mine design. Resources Policy, vol. 42. pp. 83–92. Proceedings of the 24th International Symposium on Application of WHITTLE, J. and WHARTON, C. 1995. Optimising cut-offs over time. Proceedings Computers and Operations Research in the Mineral Industry, Montreal, of the 25th International Symposium on the Application of Computers and Quebec, Canada. Canadian Institute of Mining, Metallurgy and Petroleum, Mathematics in the Mineral Industries, Brisbane, Australia. Australasian Montreal. pp. 257–263. Institute of Mining and Metallurgy, Melbourne. pp. 261–265. DAGDELEN, K. anD KAWAHATA, K. 2008. Value creation through strategic mine planning and cut-off grade optimization, Mining Engineering, vol. 60, --<76=>(?>86<>/89> *,=:0=9=;)>'%(&+ no. 1. pp. 39–45.  !  DOWD, P.A. 1976. Application of dynamic and stochastic programming to optimise cut-off grades and production rates. Transactions of the double CNPVMiningDlg::determineStripRatio(double Institution of Mining and Metallurgy, Section A: Mining Technology, dCutoff_grade, int iPos) vol. 85, no. 1. pp 22–31. { ESPINOZA, D., GOYCOOLEA, M., MORENO, E., and NEWMAN, A. 2012. MineLib: a library of open pit mining problems. Annals of Operations Research, //determine breakeven cutoff grade policy vol. 206. pp. 93–114. double dSRatio; int g = 0; GHOLAMNEJAD, J. 2008. Determination of the optimum cut-off grade considering double dCurrentPrice = dValArray[iPos]; //getCurrentPrice(); environmental cost. Journal of International Environmental Application POSITION pos = listGradeCat.GetHeadPosition(); and Science, vol. 3, no. 3. pp.186–194. dTotalWaste = 0.0; GHOLAMNEJAD, J. 2009. Incorporation of rehabilitation cost into the optimum cut- off grade determination. Journal of the Southern African Institute of dTotalOre = 0.0; Mining and Metallurgy, vol. 108, no. 2. pp. 89–94. while (pos) GITHIRIA, J.. 2018. A stochastic cut-off grade optimisation algorithm. PhD { thesis, University of the Witwatersrand, South Africa. GradeCategory sGradeCat = listGradeCat.GetNext(pos); GITHIRIA, J., MURIUKI, J., and MUSINGWINI, C. 2016. Development of a computer- if (sGradeCat.dLowerLimit < dCutoff_grade) dTotalWaste aided application using Lane’s algorithm to optimise cut-off grade. Journal of the Southern African Institute of Mining and Metallurgy, vol. 116, += sGradeCat.dQuantity; no. 11. pp. 1027–1035. else dTotalOre += sGradeCat.dQuantity; GITHIRIA, J. and MUSINGWINI, C. 2018. Comparison of cut-off grade models in } mine planning for improved value creation based on NPV. Proceedings of dTotalOre -= dMinedOre; the 6th Regional Conference of the Society of Mining Professors (SOMP), Johannesburg, South Africa. Southern African Institute of Mining and dSRatio = dTotalWaste / dTotalOre; Metallurgy, Johannesburg. pp. 347–362. dSRatio = round(dSRatio*100)/100; HENNING, U. 1963. Calculation of cut-off grade. Canadian Mining Journal, return dSRatio; vol. 84, no. 3. pp. 54–57. } JOHNSON, T.B. 1969. Optimum open-pit mine production scheduling. A Decade of Digital Computing in the Mineral Industry. Weiss A. (ed.). AIME, New  !  York, pp. 539–562. double CNPVMiningDlg::average_grade(double dCutoff_grade) KING, B. 2001. Optimal mine scheduling policies. PhD thesis, Royal School of { Mines, Imperial College, London University, UK.

VOLUME 119          
  
 225 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

double dResult = 0.0; else if (m_boolRefCap == true) { POSITION pos = listGradeCat.GetHeadPosition(); dResult = (cObj->get_refiningCost() + ((dAFixedCost + while (pos) (cObj->get_discountedRate() * dNPV)) / dRefCapacity)) / { ((dPrice - cObj->get_refiningCost()) * cObj- GradeCategory sGradeCat = listGradeCat.GetNext(pos); >get_recovery()); if (sGradeCat.dLowerLimit >= dCutoff_grade) { } dResult += sGradeCat.dMidpoint * dResult = round(dResult * 100) / 100; sGradeCat.dQuantity; return dResult; dResult = round(dResult * 1000) / 1000; } }  
 !!  } double CNPVMiningDlg::breakevencutoff_grade(int iPos) dResult /= dTotalOre; { dResult = round(dResult * 1000) / 1000; double dResult = 0.0; return dResult; double dPrice = 0.0; } //using the first value in the array   !!  dPrice = dValArray[iPos]; void CNPVMiningDlg::determineOptimumGrade() dResult = cObj->get_millingCost() / ((dPrice - cObj- { >get_refiningCost()) * cObj->get_recovery()); dTotalWaste = 0.0; dResult = round(dResult * 100) / 100; POSITION pos = listGradeCat.GetHeadPosition(); return dResult; while (pos) } { GradeCategory sGradeCat = listGradeCat.GetNext  !   (pos); bool CNPVMiningDlg::checkGradeCatDuplicate(double lowerlimit, double upperlimit) sGradeCat.dOreQty = dTotalQty - dTotalWaste; { sGradeCat.dWasteQty = dTotalWaste; bool bFound = false; dTotalQty -= sGradeCat.dQuantity; for (int g = 0; g < m_listGradeCat.GetItemCount(); g++) dTotalWaste += sGradeCat.dQuantity; { sGradeCat.dmc = sGradeCat.dOreQty / (sGradeCat.dOreQty if (_wtof(m_listGradeCat.GetItemText(g, 1)) == lowerlimit + sGradeCat.dWasteQty); || upperlimit == _wtof(m_listGradeCat.GetItemText(g, 2))) sGradeCat.dG = determineGSum(pos) / { sGradeCat.dOreQty; bFound = true; sGradeCat.dmr = (sGradeCat.dOreQty * sGradeCat.dG) / (sGradeCat.dOreQty + sGradeCat.dWasteQty); break; sGradeCat.dcr = sGradeCat.dG; } } } } return bFound; }  !!  double CNPVMiningDlg::limitingcutoff_grade(int iPos) !   { bool CNPVMiningDlg::checksubCatDuplicate(CString cat, CString double dResult = 0.0; subcat) double dPrice = 0.0; { double dNPV = cObj->get_NPV(); bool bFound = false; double dAFixedCost = cObj->get_annualFixedCost(); for (int g = 0; g < m_listPriceCat.GetItemCount(); g++) double dMillCapacity = cObj->get_millingCapacity(); { double dMineCapacity = cObj->get_miningCapacity(); if (m_listPriceCat.GetItemText(g, 1) == cat && subcat == double dRefCapacity = cObj->get_refiningCapacity(); m_listPriceCat.GetItemText(g, 2)) //using the first value in the array { dPrice = dValArray[iPos]; bFound = true; break; if (m_boolMillCap == true) { dResult = (cObj->get_millingCost() + ((dAFixedCost + } (cObj->get_discountedRate() * dNPV)) / dMillCapacity)) / } ((dPrice - cObj->get_refiningCost()) * cObj- return bFound; >get_recovery()); } } else if (m_boolMineCap == true) {   ! ! !! !  dResult = (cObj->get_millingCapacity() + ((dAFixedCost + int CNPVMiningDlg::factorial(int n) (cObj->get_discountedRate() * dNPV)) / dMineCapacity)) { / ((dPrice - cObj->get_refiningCost()) * cObj- return (n == 1 || n == 0) ? 1 : factorial(n - 1) * n; >get_recovery()); } } int CNPVMiningDlg::combinationcount(int n, int r) L 226   
 VOLUME 119          
A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

{ { return (factorial(n) / (factorial(r)*factorial(n - 1))); if (iArrayCatSubItems[d] > 1) } { int CNPVMiningDlg::getusedcategoriesList() iArrayCatSubItemsCmb[d] = { combinationcount(iArrayCatSubItems[d], 1); int iTotal = 0, iLast = 0; } int iCat = m_listPriceCat.GetItemCount(); else if (iArrayCatSubItems[d] == 1) for (int v = 0; v < 30; v++) szUsedCatItems[v] = L""; { for (int t = 0; t < iCat; t++) iArrayCatSubItemsCmb[d] = 1; { } CString szTempCat = m_listPriceCat.GetItemText(t, 1); } for (int k = 0; k < 30; k++) //get the summation of all the combinations { for (int j = 0; j < iCatCmb; j++) if (k == iLast) { { for (int i = 0; i < iCatCmb; i++) if (szTempCat == szUsedCatItems[iLast - 1]) { break; iCurrVal = iArrayCatSubItemsCmb[iCurrPos]; else { if (i <= iCurrPos) continue; szUsedCatItems[iTotal] = szTempCat; else iArrayCatSubItemsCmbTotals += iTotal += 1; iCurrVal*iArrayCatSubItemsCmb[i]; iLast += 1; } break; iCurrPos += 1; } } } return iArrayCatSubItemsCmbTotals; else if (k < iLast) continue; } } void CNPVMiningDlg::fillcombinationlist(COleSafeArray } *m_combinationList) return iTotal; { } long index1[2]; int CNPVMiningDlg::combinationtotals() int iArrayCatLastSubItems[20] = { 0 }; { int iLastPosArray[20] = { 0 }; CString szArrayVals[100][2]; //get a list of the category combinations CString szArrayCat[20]; int iCat = iUsedCatNum; int iArrayCatSubItems[20] = { 0 }; for (int r = 0; r < 100; r++) int iArrayCatSubItemsCmb[20] = { 0 }; { int iArrayCatSubItemsCmbTotals = 0; for (int e = 0; e < 2; e++) int iCurrVal = 0, iCurrPos = 0; { //determine how many categories exist szArrayVals[r][e] = L""; int iCat = m_cmbPriceCat.GetCount(); } for (int u = 0; u < iCat; u++) } { for (int b = 0; b < 20; b++) iLastPosArray[b] = -1; m_cmbPriceCat.GetLBText(u, szArrayCat[u]); int iItemCount = m_listPriceCat.GetItemCount(); } for (int t1 = 0; t1 < iItemCount; t1++) //determine the number of combinations expected { int iCatCmb = combinationcount(iCat, 1); CString szCatItem = m_listPriceCat.GetItemText(t1, 1); //loop through all the data and identify the subcategories in szArrayVals[t1][0] = szCatItem; each category and store them in an array CString szSubCatItem = m_listPriceCat.GetItemText(t1, 2); for (int t = 0; t < m_listPriceCat.GetItemCount(); t++) szArrayVals[t1][1] = szSubCatItem; { for (int k = 0; k < iCat; k++) szArrayVals[t][0] = m_listPriceCat.GetItemText(t, 1); { szArrayVals[t][1] = m_listPriceCat.GetItemText(t, 2); if (szArrayVals[t1][0] == szUsedCatItems[k]) for (int k = 0; k < iCat; k++) { { iArrayCatLastSubItems[k] = t1; if (szArrayVals[t][0] == szArrayCat[k]) } iArrayCatSubItems[k] += 1; } } } } int iCurrRow = 2, iCurrCol = 1; //determine the number of combinations for each category int i = 0; for (int d = 0; d < iCat; d++) while (1)

VOLUME 119          
  
 227 L A stochastic cut-off grade optimization model to incorporate uncertainty for improved project value

{ } for (int j = 0; j < iCat; j++) } { else //no number on its right for (int t = 0; t < iItemCount; t++) { { if (iLastPosArray[j] != if (szArrayVals[t][0] != szUsedCatItems[j]) iArrayCatLastSubItems[j]){ continue; if (t <= iLastPosArray[j]) continue; if (j == 0)// has a number on its right } { } if (iLastPosArray[j] != index1[0] = iCurrRow + i; iArrayCatLastSubItems[j]) { index1[1] = iCurrCol + j; int iTemp = j; if (j == 0) bool bTemp = true; { loopj: long numpos[2]; if (iLastPosArray[iTemp + 1] == numpos[0] = index1[0]; iArrayCatLastSubItems[iTemp + 1]) numpos[1] = 0; if (iTemp + 1 == iCat - 1) CString szNum; szNum.Format(L"%d", { numpos[0] - 1); if (t <= iLastPosArray[j] && bTemp == BSTR bstr = szNum.AllocSysString(); true) { m_combinationList->PutElement(numpos, bstr); continue; SysFreeString(bstr); } } } BSTR bstr1 = szArrayVals[t][1].AllocSysString(); else { m_combinationList->PutElement(index1, bstr1); iTemp += 1; SysFreeString(bstr1); if (iLastPosArray[iTemp + 1] < iLastPosArray[j] = t; iArrayCatLastSubItems[iTemp + 1]) bTemp = false; break; goto loopj; } } } } i++; if (t < iLastPosArray[j]) continue; } } } else { if (t < iArrayCatLastSubItems[j])  !  continue; double CNPVMiningDlg::dgetAnnualProfit(int iPos) else { { int iTemp = j; double dResult = 0.0; bool bTemp = true; double dPrice = 0.0; loopj1: //using the first value in the array if (iLastPosArray[iTemp + 1] == dPrice = dValArray[iPos]; iArrayCatLastSubItems[iTemp + 1]) { dResult = ((dPrice - cObj->get_refiningCost()) * cObj- if (iTemp + 1 == iCat - 1) >get_refiningCapacity()) - (cObj->get_millingCapacity() * { cObj->get_millingCost()) - (cObj->get_miningCapacity() * if (t <= iLastPosArray[j] && cObj->get_miningCost()) - cObj->get_annualFixedCost(); bTemp == true) { dResult = round(dResult * 100) / 100; //start from the first sub item return dResult; if (j > 0) t = } iArrayCatLastSubItems[j - 1] + 1;  else return; double CNPVMiningDlg::dgetNPV(double dMinelife, double } dAnnualProfit) } } else { double dResult = 0.0; iTemp += 1; dResult = (dAnnualProfit * ((round(pow(1 + cObj- if (iLastPosArray[iTemp + 1] < >get_discountedRate(), dMinelife) * 1000) / 1000) - 1)) / iArrayCatLastSubItems[iTemp + ((round(pow(1 + cObj->get_discountedRate(), dMinelife) * 1]) bTemp = false; 1000) / 1000) * cObj->get_discountedRate()); goto loopj1; dResult = round(dResult * 100) / 100; } } return dResult; } } N L 228   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a2 An empirical long-term commodity price range for Mineral Reserve declarations to minimize impairments in gold and platinum mines by V. Maseko1 and C. Musingwini2

(the JORC Code), a Mineral Reserve is synonymous with an Ore Reserve. The ('DB5;C; conversion of Mineral Resources to Mineral When considered collectively, Mineral Resources and Mineral Reserves are Reserves involves applying modifying factors, arguably a key asset for any mining company. Mineral Reserves are the which are non-resource considerations. The economically mineable portions of Mineral Resources. They therefore modifying factors used in the Mineral Reserve provide a good indication of the economic prospects in the short to estimation process include mining, medium term and associated non-financial impairments for mining metallurgical, processing, infrastructure, companies, hence a focus on Mineral Reserves. An assessment of economic, marketing, legal, environmental, modifying factors for converting Mineral Resources to Mineral Reserves social, and governmental factors. Each of these revealed that Mineral Reserves were most sensitive to long-term modifying factors consists of several commodity prices, hence the focus on long-term commodity prices. The components which require due consideration justification for selecting gold and platinum mines is that they collectively in the estimation of Mineral Reserves. Table I make a significant contribution to South Africa’s earnings from mining. The introduction of the South African Code for the Reporting of shows some of the components typically Exploration Results, Mineral Resources and Mineral Reserves (SAMREC considered for each of the modifying factors. Code) in 2000 informed the basis for analysing long-term commodity price It can be argued that, considered assumptions for major South African gold and platinum mining companies collectively, Mineral Resources and Mineral between 2000 and 2016. The analysis revealed that the least number of Reserves are the single most significant asset non-financial impairments occurred when long-term commodity prices or among the most significant assets for any were within ±5% of spot prices. This finding suggests that this range is the mining company (Njowa and Musingwini, ideal range for long-term commodity price assumptions to improve 2018). International reporting codes provide confidence in Mineral Reserve declarations and minimize impairments. the minimum standards and guidelines for the @' B>8; estimation, declaration, and public reporting of modifying factors, long-term commodity prices, spot prices, impairment, Exploration Results, Mineral Resources, and reporting codes. Mineral Reserves. The reporting of Exploration Results, Mineral Resources, and Mineral Reserves serves the needs of governments, international organizations, investors and potential investors and their advisors (SAMREC, 2016). International organizations D=>B867=CBD are interested in the in situ estimates of The South African Code for the Reporting of mineral inventories to inform world Exploration Results, Mineral Resources and perspectives on strategic and critical minerals, Mineral Reserves (SAMREC Code) defines a while governments rely on these estimates to Mineral Resource as ‘a concentration or design policies for safeguarding their mineral occurrence of solid material of economic endowments and ensuring that their citizens interest in or on the Earth’s crust in such can benefit from the exploitation of those form, grade or quality and quantity that there minerals (Musingwini, 2018). Investors are are reasonable prospects for eventual economic extraction’ (SAMREC, 2016, p. 18). Mineral Resources are categorized according to increasing levels of geoscientific confidence or knowledge, from Inferred to Indicated and lastly, Measured categories. The SAMREC Code 1 defines a Mineral Reserve as ‘the economically Ernst & Young Advisory Services Limited, South mineable part of a Measured and/or Indicated Africa. 2 School of Mining Engineering, University of the Mineral Resource’ (SAMREC, 2016, p. 25). In Witwatersrand, South Africa. some of the other reporting codes such as the © The Southern African Institute of Mining and Australasian Code for Reporting of Exploration Metallurgy, 2019. ISSN 2225-6253. Paper received Results, Mineral Resources and Ore Reserves Aug. 2018; revised paper received Jan. 2019.

VOLUME 119          
  
 229 L An empirical long-term commodity price range for Mineral Reserve declarations

Table I '5C7A;E/A8A5=@8E,>B:E*55<@'A>8EAD8E(:C=#2E9??3.

+B8C,'CD4E,A7=B>'5C7A@8

Mining Mining method, dilution and mining recovery, production rates, operating and capital costs, the degree of selective mining, grade control, geotechnical influences, ventilation, use of stope fill, mode of access to underground mines, overall mining sequence. Metallurgical Test sample representativeness, product specification, metallurgical recovery and throughput, ore characteristics, operating and capital costs, variable ore characteristics and their potential impact on process performance, overall economics. Economic Commodity price forecasts (including the impact of hedging), royalties, operating and capital costs. Marketing Sales projections, analysis of demand trends and estimates for off-site treatment terms and costs, product quality and blending abilities (for commodities such as iron ore, coal, and industrial minerals). Legal Political risk and security of tenure, environmental factors. Social Sustainable development and social license to operate. Governmental Government regulatory framework.

interested in the economically extractable portion of the :5B>=AD7@EB,E:E7B::B8C='E5>C7@;ECD mineral deposit as this is a good indicator of the economic @;=C:A=CD4E+CD@>A@; prospects for mining companies in the short to medium term. Commodity prices are very important in the Mineral Reserve Securities exchanges worldwide have an overarching estimation process. For example, as Appleyard (2001, p. 8) principle of protecting investors and so require transparent argued, ‘the most sensitive inputs to a mine valuation are and consistent reporting of Mineral Resources and Mineral those which relate to revenue. While metallurgical recovery Reserves for easier decision-making by investors. The directly relates to revenue, the factors which are usually national reporting code in South Africa is the SAMREC Code. subject to most variation are the price for the commodity’. The SAMREC Committee (now SAMCODES Standards Conducting a valuation is a critical step in establishing the Committee or SSC) first published the SAMREC Code in economic viability of Mineral Reserves. Therefore, the March 2000 and later that year the Johannesburg Stock statement by Appleyard (2001) indicates that although all Exchange (JSE) adopted the Code, requiring compliance with other modifying factors are important in the estimation of the Code as part of the Listing Requirements for mining Mineral Reserves, commodity price assumptions are the most companies. important modifying factor. However, commodity prices The reporting codes are principles-based and therefore fluctuate over time as dictated by market forces and not prescriptive. This gives the Competent Person (CP) some international reporting codes do not require the revision of discretion in estimating and reporting Mineral Resources and Mineral Reserve estimates due to short-term commodity price Mineral Reserves, if their approaches and methodologies are movements. Another revenue driver, which is critical to the reasonable and defendable. The discretion includes mine valuation process, is grade, as grade (together with assumptions on modifying factors. The 2016 Edition of the production volumes and metallurgical recovery) is a key SAMREC Code attempted to address the shortcomings driver of saleable product volumes to which commodity prices associated with the discretion exercised by CPs by are applied to estimate revenue. The reporting codes provide introducing the ‘if not, why not’ reporting principle. This guidance on the use of long-term price assumptions for principle requires that CPs must report on every aspect as Mineral Reserves estimation. The arguments put forward by specified in Table I of the SAMREC Code, otherwise they need authors such as Appleyard and Smith (2001), and Baker and to provide reasonable justification for not reporting on certain Giacomo (2001) are in agreement with these guidelines of elements (Lomberg and Rupprecht, 2017). This principle the reporting codes. makes it more difficult for a CP to be selective when Appleyard and Smith (2001, p. 327) argued that the reporting, thus enabling the CP to include all the information ‘failure to recognise that a price decrease means that a that stakeholders, investors, potential investors, and advisors previous Ore Reserve is now a body of uneconomic would reasonably expect to find in a public report (Lomberg mineralisation, can cause a company to continue operating and Rupprecht, 2017). One of the modifying factors for until it is in a position where it can fail’. This argument which a CP needs to exercise reasonable discretion is long- indicates that in a volatile commodity market, commodity term commodity prices. Long-term commodity prices are one price decreases significantly affect the quantum of Mineral of the most important modifying factors used in Mineral Reserves and can impair the economic viability of a mining Reserve estimation. Mineral Reserves are the economically operation if they persist in the long term. Baker and Giacomo mineable portions of Mineral Resources; hence, they provide (2001, p. 669) also argued that commodity prices are critical a better indication of the economic prospects for mining in that ‘fundamental to the determination of reserves (and to companies in the short to medium term. In order to minimize a lesser extent resources) is the underlying metal price variations in long-term commodity price assumptions, this assumptions used in the estimation. Contained metal can be research study undertook to estimate an ideal range of long- highly sensitive to metal price assumptions employed, term commodity prices relative to spot prices. By minimizing especially where the margin between cost and revenue is variations, it should be possible to improve confidence in the small. At best, a company could consider providing reporting of Mineral Reserves. sensitivities of tonnes and grade to commodity price L 230   
 VOLUME 119          
An empirical long-term commodity price range for Mineral Reserve declarations assumptions. At the very least we are of the view that The third step involved evaluating correlations between companies should disclose the price at which the the long-term commodity price assumptions and the other determinations are made (in appropriate currencies)’. This modifying factors, and the Mineral Reserve declarations of argument indicates that Mineral Reserve estimates are very the major South African gold and platinum mining companies sensitive to commodity prices. It was therefore, necessary to from 2000 to 2016 to determine if long-term commodity explore the impact that commodity price assumptions have prices had the most significant impact on the Mineral Reserve on Mineral Reserves, but also simultaneously evaluating the estimates. Lastly, it was necessary to make an estimation of impacts of other modifying factors on Mineral Reserves to the ideal range for the long-term commodity price obtain a balanced view. assumptions for the Mineral Reserve estimates for South African gold and platinum mining companies based on the +@=#B8B

Table II D7B:@E7BD=>C!6=CBDE!'E=#@EA>CB6;E:CDCD4E;@7=B>;ECDE(B6=#E*,>C7AE,B>E9?39EAD8E9?3E/;B6>7@ E(=A=C;=C7;E (B6=#E*,>C7A2E9?3.

'5@EB,E:CDCD4 9?39 9?3 "E:C<C!6=CBD "E:C<C!6=CBD

Coal and lignite 96 097 24.4 117 958 28.1 Gold and uranium ore 66 957 17.0 63 674 15.2 Iron ore 68 061 17.3 60 699 14.5 Chrome ore 11 412 2.9 16 383 3.9 Manganese ore 10 254 2.6 17 093 4.1 Platinum group metal ore 106 555 27.1 91 099 21.7 Dimension stone (granite, marble, slate and sandstone) 630 0.2 1 146 0.3 Limestone and limeworks 2 398 0.6 2 717 0.6 Other stone quarrying, including stone crushing and clay and sandpits 10 289 2.6 16 584 4.0 Diamonds (including alluvial diamonds) 8 694 2.2 15 055 3.6 Other chemical and fertilizer minerals 3 330 0.8 5 976 1.4 Extraction and evaporation of salt 280 0.1 215 0.1 Other mining activities and service activities incidental to mining 7 822 2.0 10 295 2.5 Other minerals and materials n.e.c. 582 0.1 639 0.2 Total 393 361 100.0 419 533 100.0

VOLUME 119          
  
 231 L An empirical long-term commodity price range for Mineral Reserve declarations are considerably higher than prevailing spot commodity commodity basket price for a multi-metal deposit is obtained prices, an impairment may be triggered since the recoverable by considering the recoverable proportions of the individual value of the non-financial assets may be exceeded by the metals found in the deposit and their respective prices, taking carrying value, in line with the provisions of IAS 36. into account market considerations. Impairments can also be recorded when long-term Figure 2 shows that for the period 2008 to 2014, Lonmin commodity prices are considerably lower than prevailing consistently assumed long-term PGM basket prices that were prices, as the perceived recoverable value (as represented by considerably higher than the spot prices. This optimistic long-term commodity price assumptions) may be lower than long-term price outlook would probably have contributed to current carrying values. Therefore, impairments can occur the poor investment choices made by Lonmin in bringing the under conditions of either excessive optimism or K4 shaft into production in 2011. Persistent weak PGM prices conservatism in long-term commodity price assumptions. rendered the project financially unviable and Lonmin had to place the K4 shaft on care and maintenance in November (B6=#E*,>C7ADE4B<8EAD8E5:E5>C7@EA;;6:5=CBD; Impala adopted a long-term PGM basket price closer to spot prices in 2016, its Mineral Reserves would have halved, It was necessary to assess the long-term commodity price although the long-term PGM basket price assumed by Impala assumptions relative to spot prices, as this would assist in was 30% above spot prices (Impala, 2016). This shows the evaluating how these assumptions influenced Mineral significant effect of long-term commodity price assumptions Reserve declarations. An analysis by Barclays Bank plc on Impala’s Mineral Reserve estimates. (2015) concluded that 65% of the South African platinum Figure 4 illustrates the 2015 South African gold mining industry was cash flow negative at 2015 spot prices, production cost curve, which explains why South African compared to only 22% of the South African gold mining gold mines were mostly cash flow positive in 2015 (Barclays industry. The better performance by the gold mining sector is Bank plc, 2015). It was mostly operations owned by probably attributable to a better performing gold price Harmony Gold (indicated as ‘HAR’ in Figure 4) which were compared to the platinum price pre- and post-2015. in the upper quartile of the cost curve. This is partly the However, the quality of investment and operational decisions reason why Harmony Gold mines were loss-making in 2015, between the two sectors (based on their long-term although this could also have been due to fact that the mines commodity price assumptions) could also have partly have some of the lowest grades in the South African gold contributed to differences in their financial performance. mining sector. The global PGM cost curve in Figure 5 Figure 1 indicates that South African gold mining companies adopted more conservative long-term price assumptions for their Mineral Reserve estimations relative to the 2015 gold average spot price, with the exception of Harmony Gold, which assumed a long-term price which was higher than the average spot price (Barclays Bank plc, 2015). As argued earlier, these conservative assumptions would have informed the operational and investment decisions of the South African gold mining companies, which may have contributed to their better cash flow positions compared to platinum mining companies. Figures 2 and 3 illustrate the platinum group metals (PGMs) basket price assumptions relative to average spot prices between 2006 and 2016 for Lonmin plc (Lonmin) and C46>@E9%&+E!A;@=E5>C7@;E7B:5A>@8E=BE:E5>C7@ Impala Platinum Holdings Limited (Impala), respectively. A A;;6:5=CBD;E,B>E$BD:CDE!@= @@DE9??1EAD8E9?3E/;B6>7@ EA>7

C46>@E:5AA@E%&+E!A;@=E5>C7@;E,B>E9?31E/CD C46>@E3$BD4 =@>:E7B::B8C='E5>C7@;E6;@8ECDE+CD@>A7@EAD8 (B6=#E*,>C7ADE>AD8;E5@>[email protected]:5A>@8E=BE:E!A;@=EAD8 +CD@>A@E@;=C:A=CBD;E,B>E(B6=#E*,>C7ADE4B<8E:CDCD4E7B:5ADC@; 7BD;@D;6;E5>C7@;E/;B6>7@ E:5A7@ EA>7

C46>@E(B6=#E*,>C7ADE4B<8E5>B867=CBDE7B;=E76>@ECDE9?3E/;B6>7@ EA>7

C46>@E&@2ECD7<68CD4E7A5@2ECDE9?3E/;B6>7@ EA>7

Table III &B<8EAD8E%&+E5>C7@;E,B>E=#@E5@>CB8E9???E=BE9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E C=7B2ED-8-0E+@=A'2ED-820 6AD8<2ED-8.

@A> &B<8E %C8C6:E "6=#@DC6:E &B<8E %C8C6:E "6=#@DC6:E /(B. /(B. /(B. /(B. /(EB. /(B. /*"B. /*"B. /*"B. /*"B. /*"B. /*"B.

2016 1 249 987 613 663 575 40 18 367 14 525 9 020 9 750 8 460 588 2015 1 160 1 052 692 919 544 42 14 798 13 421 8 826 11 731 6 936 536 2014 1 266 1 384 803 1 128 556 58 13 731 15 009 8 710 12 237 6 027 629 2013 1 411 1 485 725 1 075 826 57 13 618 14 339 7 002 10 377 7 975 550 2012 1 669 1 549 644 1 270 1 070 90 13 699 12 720 5 290 10 425 8 786 739 2011 1 572 1 719 733 1 990 1 036 110 11 417 12 488 5 328 14 455 7 527 799 2010 1 226 1 611 526 2 384 642 180 8 977 11 792 3 854 17 451 4 702 1 318 2009 973 1 205 264 1 442 425 160 8 249 10 211 2 235 12 218 3 605 1 356 2008 872 1 571 352 6 455 450 110 7 203 12 980 2 909 53 321 3 718 909 2007 697 1 305 355 6 076 447 415 4 909 9 192 2 499 42 805 3 149 2 924 2006 604 1 142 321 4 442 350 610 4 093 7 733 2 172 30 086 2 368 4 131 2005 445 897 202 2 002 169 87 2 832 5 705 1 282 12 732 1 078 553 2004 410 846 230 904 186 68 2 648 5 464 1 485 5 839 1 204 439 2003 364 692 199 475 93 41 2 753 5 233 1 508 3 596 704 310 2002 310 540 337 768 294 40 3 272 5 688 3 548 8 095 3 095 422 2001 271 529 604 1 582 413 80 2 334 4 557 5 199 13 623 3 556 689 2000 279 545 743 1 993 415 160 1 937 3 780 5 155 13 832 2 880 1 110

indicates that South African platinum mines were mostly trends in US dollar terms. The US dollar-denominated gold cash flow negative in 2014 (Barclays Bank plc, 2014). These and PGM prices have shown a general downward trend from observations suggest that there is a relationship between 2012 to 2016, while the South African rand- (ZAR)- financial performance and long-term commodity price denominated commodity prices have shown a general assumptions. positive trend from 2000 to 2016. The general depreciation of Commodity prices fluctuate due to supply and demand the rand against the US dollar in periods of weak US dollar- dynamics. In the case of gold and PGMs, the period from denominated commodity prices is the major reason for this . 2000 to 2008 was marked by a general upward trend in the South African gold and platinum mining companies have prices of these precious metals. However, following the 2008 therefore made their long-term commodity price assumptions Global Financial Crisis, the precious metal prices that had in an increasing rand-price environment between 2000 and peaked crashed rapidly in 2009, followed by marginal 2016. recoveries in 2010 to 2012. Table III and Figure 6 indicate South Africa’s major gold mining companies have that precious metal prices continued to experience downward generally reported on the long-term gold price assumptions

VOLUME 119          
  
 233 L An empirical long-term commodity price range for Mineral Reserve declarations

C46>@E1&B<8EAD8E%&+E5>C7@;E,B>E=#@E5@>CB8E9???)9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E C=7B2ED-8-0E+@=A'2ED-8-0E6AD8<2ED-8-.

used in their Mineral Reserve declarations. Table IV shows Table IV that by 2001, a year after the introduction of the SAMREC Code, the three major South African gold producers started *@>A4@E;5B=E4B<8E5>C7@;EAD8E:E4B<8E reporting their long-term gold price assumptions. Table IV 5>C7@EA;;6:5=CBD;E,>B:E9???E=BE9?31E/;B6>7@; E and Figure 7 also show that between 2000 and 2016, South African gold mining companies assumed long-term gold ($E+@=A<;EE+CDCD42ED-8-0E*D4:BD'E&B<82E9???)9?310E&B<8EC@<8;2 either lower than or in line with prevailing spot prices. This 9???)9?3120E(C!AD'@E&B<82E9?3 9?31. suggests that South African gold mining companies had a lower probability of reporting unprofitable ounces as part of @A> (5B=E4B<8E5>C7@ $BD4 =@>:E4B<8E5>C7@EA;;6:5=CBD;E/*"4. their Mineral Reserves in the period from 2000 to 2016. The *D4:BD'E &B<8EE (C!AD'@ abbreviation ‘NR’ means ‘not reported’ and ‘N/A’ means ‘not /*"4. *;#AD=C &B<8 C@<8; &B<8 applicable’. For example, in Table IV, Sibanye Gold did not 2016 590 506 530 000 475 107 550 000 490 000 exist as a gold mining company hence ‘N/A’ is used between 2015 475 767 431 000 450 026 500 000 430 000 2000 and 2011. 2014 441 465 398 452 425 064 400 000 420 000 The history of South African platinum mining companies 2013 437 828 360 252 400 148 400 000 410 000 2012 440 417 290 064 339 833 380 000 380 000 as regards reporting long-term price assumptions in Mineral 2011 367 051 269 841 279 888 310 000 N/A Reserve declaration between 2000 and 2016 has been less 2010 288 628 238 028 250 149 265 000 N/A detailed than that of the gold mining companies. Implats and 2009 265 204 227 627 224 975 230 000 N/A 2008 231 573 200 698 179 883 150 000 N/A Northam began reporting on long-term platinum prices only 2007 157 820 148 536 115 022 100 000 N/A in 2003, followed by Lonmin in 2005; while Anglo American 2006 131 587 114 939 104 972 92 000 N/A 2005 91 065 86 807 91 996 92 000 N/A Platinum (Amplats) did not report its long-term price 2004 85 121 94 764 91 996 90 000 N/A assumptions in the period under review, as shown in Table V. 2003 88 522 78 769 92 948 95 000 N/A Figure 8 and Table V show that between 2003 and 2016, 2002 105 194 94 041 94 845 95 111 N/A 2001 75 056 71 262 67 388 69 992 N/A South African platinum mining companies generally reported 2000 62 279 NR 60 033 NR N/A long-term platinum prices that were higher than prevailing spot prices. Implats’ long-term platinum prices have often been the most bullish throughout the period under review, NR Not reported N/A Not applicable while Northam’s long-term prices have been relatively conservative. Figure 9 shows that for the other PGMs, South African platinum mining companies have generally reported long-term prices higher than spot prices for palladium between 2000 and 2016 and more optimistic long-term prices (relative to spot) for rhodium between 2009 and 2016. However, for gold and iridium, South African platinum mining companies have generally reported long-term prices that were lower than spot prices. The reporting trends of South African platinum mining companies suggest that between 2000 and 2016, they were more likely than gold mining companies to report uneconomic ounces as part of their Mineral Reserves. Persistent reporting of uneconomic ounces can trigger impairment.

B>>@;EAD8E>@5B>=@8 C46>@E$BD4 =@>:E4B<8E5>C7@EA;;6:5=CBD;E>@C7@; ,>B:E9???E=BE9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E*D4A@; *;#AD=C2E9???)9?310EA>:BD'E&B<82E9???)9?310E&B<8EC@<8;2E9???)9?310 As discussed earlier, Appleyard (2001) suggested that (C!AD'@E&B<82E9?3)9?31. L 234   
 VOLUME 119          
An empirical long-term commodity price range for Mineral Reserve declarations

Table V C;=B>C7AA4@E;5B=E5C7@;EAD8E:E5C7@EA;;6:5=CBD;E,>B:E9???E=BE9?31E/;B6>7@; ($E+@=A<;EE+CDCD42ED-8-0E:5A=#A:E%C7ADE%

@A> (5B=E5C7@E $BD4 =@>:E5C7@EA;;6:5=CBD;E/*"B. /*"B.E :5A=#A:E%C7ADE%

2016 14 525 18 648 20 291 20 729 NR 15 500 2015 13 421 17 718 19 357 18 632 NR N/A 2014 15 009 26 760 13 455 16 785 NR N/A 2013 14 339 18 778 15 925 16 785 NR N/A 2012 12 720 16 080 11 963 14 875 NR N/A 2011 12 488 22 560 12 866 15 200 NR N/A 2010 11 792 27 716 12 360 14 904 NR N/A 2009 10 211 20 879 9 450 14 400 NR N/A 2008 12 980 24 083 14 391 12 000 NR N/A 2007 9 192 11 085 6 670 9 208 NR N/A 2006 7 733 7 850 5 850 7 700 NR N/A 2005 5 705 6 700 4 950 4 940 NR N/A 2004 5 464 6 100 4 347 NR NR N/A 2003 5 233 6 100 5 004 NR NR N/A 2002 5 688 NR NR NR NR N/A 2001 4 557 NR NR NR NR N/A 2000 3 780 NR NR NR NR N/A

NR: Not reported N/A Not applicable

C46>@E $BD4 =@>:E5C7@EA;;6:5=CBD;E>@C7@;2E9???)9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E:5A=#A:E%C7ADE%

C46>@E$BD4 =@>:E%&+E5>C7@EA;;6:5=CBD;E>@C7@;E9???)9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E C=7B2ED-8-0E+@=A'2ED-8-0E6AD8<2ED-8-0 :5A=#A:E%C7ADE%

VOLUME 119          
  
 235 L An empirical long-term commodity price range for Mineral Reserve declarations

Mineral Reserves are most sensitive to commodity prices is being tested on the y and x axes, with the dependent among the modifying factors. However, other modifying variable on the y-axis and the independent variable on the x- factors are also important for Mineral Reserve estimation. It axis. The best fit or regression line is then fitted to the data- was therefore necessary to establish the relationship between points, followed by a horizontal line representing the mean of the Mineral Reserve estimates of South African gold and the dependent variable (y). SSR and SSTO are then calculated platinum mining companies and their reported modifying based on the original data points and points on the mean and factors. The coefficient of determination (R2) was used to regression lines to allow the calculation of R2 (Penn State assess the relationship between Mineral Reserve estimates Eberly College of Science, n.d.).Table VI shows a rating scale and modifying factors. R2 measures the correlation between for the R2 values for ranking the strengths of the correlations two variables by determining how changes in the between the Mineral Reserves and modifying factors. Tables independent variable affect the dependent variable. R2 uses VII and VIII provide a summary of R2 values between regression to determine the fit between two sets of variables reported modifying factors and declared Mineral Reserves. and indicates the strength of the relationship between the Tables VII and VIII show that the reported Mineral Reserves variables. R2 values typically range between 0 and 1, with of South African gold and platinum mining companies values closer to 1 indicating a stronger relationship. R2 is measured using the formula: Table VI Regression sum of squares (SSR) 9 R2 = "A=CD4E;7A<@E,B>E" A<6@;E,B>E=#@EE>@A@;EAD8E:B8C,'CD4E,A7=B>; where SSR is a measure of the sum of the squared differences /+A;@B2E9?3 . between the regression line and the mean line of data-points B@,,C7C@D=EB,EE8@=@>:CDA=CBDE/"9.?)E?- ?-)?-1 ?-1)3-? and SSTO is a measure of the squared differences between data-points and their mean line. The process for estimating Correlation rating Poor Moderate Good Colour Red Orange Green R2 involves first plotting the two variables whose relationship

Table VII "9 A<6@;E,B>E>@5B>=@8E+CD@>A@;EAD8E:B8C,'CD4E,A7=B>;E,B>E:A B>E4B<8 :CDCD4E7B:5ADC@;ECDE(B6=#E*,>C7AE!@= @@DE9???EAD8E9?31E/+A;@B2E9?3 . L 236   
 VOLUME 119          
An empirical long-term commodity price range for Mineral Reserve declarations

Table VIII "9 A<6@;E,B>E>@5B>=@8E+CD@>A@;EAD8E:B8C,'CD4E,A7=B>;E,B>E:A B>E5C7AE!@= @@DE9???EAD8E9?31E/+A;@B2E9?3 .

between 2000 and 2016 were mostly sensitive to long-term 2003 and 2016, as shown in Table X. Northam assumed commodity prices as the R2 (on average) values are generally conservative long-term platinum prices (relative to spot higher than those of the other modifying factors. prices) in the earlier part of the period and higher prices in the latter part, resulting in an average variance of zero over :5AC>:@D=;EAD8EC8@AAD4@E,B>E: the period. Since Amplats did not report its assumed long- 7B::B8C='E5>C7@; term platinum price, a comparison with spot prices could not be undertaken. The major South African platinum mining An assessment of the non-financial asset impairments of companies have also recorded significant non-financial asset South African gold and platinum mining companies from impairments in the period from 2000 to 2016, with Northam 2000 to 2016 gives an indication of the relationship between recording the least impairments (Table X). Figure 11 shows asset carrying values as represented by long-term commodity that of the several impairments recorded by the major South prices and recoverable values as represented by prevailing African platinum mining companies from 2000 to 2016, very spot prices. few occurred in the ±5% long-term platinum price to spot The major South African gold mining companies mostly price ratio range. The historical long-term commodity prices assumed rand-denominated long-term gold prices lower than used for impairment testing purposes would have been in line spot prices between 2000 and 2016. However, these with the long-term prices used for Mineral Reserve companies recorded significant non-financial asset estimation. The use of long-term commodity prices that were impairments in this period, as shown in Table IX. This within 5% of prevailing spot prices resulted in reporting of indicates that having a conservative view on long-term prices ounces that were economically mineable (Mineral Reserves) does not prevent the incurring of impairments. However, under the prevailing conditions, as evidenced by the limited Figure 10 shows that when long-term gold price assumptions number of impairments incurred within this commodity price of the South African gold mining companies were within ±5% range. This suggests that this range is ideal for long-term of spot prices, then minimal impairments were recorded. The platinum prices to minimize impairments for South African majority of impairments were recorded outside the ±5% long- platinum mining companies. term gold price to spot price range, which suggests that this could be an ideal long-term gold price assumption range in Mineral Reserve declarations for South African gold mining BD7<6;CBD; companies. This study evaluated the impact of modifying factors on the Among South Africa’s major platinum mining companies, Mineral Reserve estimates reported by the major South Implats and Lonmin have on average assumed long-term African gold and platinum mining companies from 2000 to platinum prices that were higher than spot prices between 2016. Among the modifying factors used in Mineral Reserve

VOLUME 119          
  
 237 L An empirical long-term commodity price range for Mineral Reserve declarations

Table IX $BD4 =@>:E4B<8E5>C7@;EAD8EC:5AC>:@D=;E,B>E:A B>E4B<8E:CDCD4E7B:5ADC@;ECDE(B6=#E*,>C7AE!@= @@DE9??? AD8E9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-80E*D4:BD'E&B<82E9???)9?310 &B<8EC@<8;2E9???)9?310E(C!AD'@E&B<82E9?3)9?31.

C46>@E3?$BD4 =@>:E4B<8E5>C7@;EAD8E4B<8E:CDCD4E7B:5AD'EC:5AC>:@D=;E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E*D4:BD' &B<82E9???)9?310E&B<8EC@<8;2E9???)9?310E(C!AD'@E&B<82E9?3)9?31.

estimation, the Mineral Reserves of South African gold and and 2016. The South African gold mining companies reported platinum mining companies appeared to have been most long-term rand-denominated gold prices that were lower than sensitive to changes in long-term gold and platinum prices prevailing spot prices over the 2000 to 2016 period. The between 2000 and 2016. The study further noted that South platinum mining companies, however, reported long-term Africa’s major gold mining companies consistently reported platinum price assumptions that were mostly higher than the long-term gold prices used in their Mineral Reserves from prevailing spot prices. Therefore, South African platinum 2001, a year after the introduction of the SAMREC Code. mining companies were most likely to have reported ounces Mineral Reserve reporting by South Africa’s major platinum that were uneconomic as part of their Mineral Reserves and mining companies was less detailed than that by gold mining would have been more prone to impairments between 2000 companies. The reporting of long-term platinum prices used and 2016. An assessment of long-term gold and platinum in Mineral Reserve estimation by platinum mining companies prices relative to historical spot prices and their impact on the only started between 2003 and 2005. Amplats did not report number of non-financial asset impairments recorded by its long-term platinum prices over the period between 2000 South Africa’s gold and platinum mining companies revealed L 238   
 VOLUME 119          
An empirical long-term commodity price range for Mineral Reserve declarations

Table X $BD4 =@>:E5C7@;EAD8EC:5AC>:@D=;E,B>E:A B>E5C7AE!@= @@DE 9???EAD8E9?31E/;B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E:5A=#A:E%C7ADE%

C46>@E33$BD4 =@>:E5C7@;EAD8E5:@D=;E/B6>7@; E($E+@=A<;EE+CDCD42ED-8-0E:5A=#A:E%@D7@; long-term commodity prices were within ±5% of prevailing ANGLO AMERICAN PLC. 2000. Annual Report 2000. spot prices. This suggests that if South Africa’s gold and http://www.sharedata.co.za/Data/000238/pdfs/ANGLO_ar_00.pdf platinum mining companies keep their long-term commodity [accessed 14 October 2017]. prices within ±5% of rand-denominated spot prices, it could ANGLO AMERICAN PLC. 2002. Annual Report 2002. https://core.ac.uk/download/pdf/33158338.pdf [Accessed 14 October result in more reliable Mineral Reserve estimates, which 2017]. could clearly demonstrate economic viability as evidenced by ANGLO AMERICAN PLC. 2003. Annual Report 2003. a potentially limited number of impairments incurred in the http://www.angloamerican.com/~/media/Files/A/Anglo-American-PLC- future. V2/investors/a-reports/2004rep/annual_review_2003.pdf [Accessed 14 October 2017]. ANGLO AMERICAN PLC. 2004. Annual Report 2004. *7DB <@84:@D=; http://china.angloamerican.com/~/media/Files/A/Anglo-American- China/reports-and-publications/2004/annual-report-2004.pdf [accessed The work reported in this paper is part of an MSc research 14 October 2017]. study in the School of Mining Engineering at the University ANGLO AMERICAN PLC. 2005. Annual Report 2005. of the Witwatersrand. http://china.angloamerican.com/~/media/Files/A/Anglo-American-

VOLUME 119          
  
 239 L An empirical long-term commodity price range for Mineral Reserve declarations

China/reports-and-publications/2005/angloamericanreport05.pdf ANGLOGOLD ASHANTI LIMITED. 2008. Mineral Resource and Ore Reserve Report [accessed 14 October 2017]. 2008. https://www.anglogoldashanti.com/archive/ ANGLO PLATINUM LIMITED. 2006. Annual Report 2006. miningreserves/Mineral%20resource%20and%20ore%20reserve%20repor http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- ts%20(2002%20-%202012).zip [accessed 14 October 2017]. American-Platinum/annual-reports/2006.pdf [accessed 14 October 2017]. ANGLOGOLD ASHANTI LIMITED. 2009. Mineral Resource and Ore Reserve Report ANGLO PLATINUM LIMITED. 2007. Annual Report 2007. 2009. https://www.anglogoldashanti.com/archive/miningreserves/ http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- Mineral%20resource%20and%20ore%20reserve%20reports%20(2002%2 American-Platinum/annual-reports/2007.pdf [accessed 14 October 2017]. 0-%202012).zip [accessed 14 October 2017]. ANGLO PLATINUM LIMITED. 2008. Annual Report 2008. ANGLOGOLD ASHANTI LIMITED. 2010. Mineral Resource and Ore Reserve Report http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- 2010. https://www.anglogoldashanti.com/archive/miningreserves/ American-Platinum/annual-reports/2008.pdf [accessed 14 October 2017]. Mineral%20resource%20and%20ore%20reserve%20reports%20(2002%2 ANGLO PLATINUM LIMITED. 2009. Annual Report 2009. 0-%202012).zip [accessed 14 October 2017]. http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- ANGLOGOLD ASHANTI LIMITED. 2011. Mineral Resource and Ore Reserve Report American-Platinum/annual-reports/ar2009.pdf [accessed 14 October 2011. https://www.anglogoldashanti.com/archive/miningreserves/ 2017]. Mineral%20resource%20and%20ore%20reserve%20reports%20(2002%2 ANGLO PLATINUM LIMITED. 2010. Annual Report 2010. 0-%202012).zip [accessed 14 October 2017]. http://www.angloamerican.com/~/media/Files/A/Anglo-American-PLC- ANGLOGOLD ASHANTI LIMITED. 2012. Mineral Resource and Ore Reserve Report V2/investors/a-reports/2011rep/angloplatinumltd_2010.pdf [accessed 14 2012. https://www.anglogoldashanti.com/archive/miningreserves/ October 2017]. Mineral%20resource%20and%20ore%20reserve%20reports%20(2002%2 ANGLO AMERICAN PLATINUM LIMITED. 2011. Integrated Annual Report 2011. 0-%202012).zip [accessed 14 October 2017]. http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- ANGLOGOLD ASHANTI LIMITED. 2013. Mineral Resource and Ore Reserve Report American-Platinum/AA%20Plat%20- 2013. https://thevault.exchange/?get_group_doc=143/1502781082- %20INTEGRATED%20ANNUAL%20REPORT%202011.pdf [accessed 14 MineralResourceandOreReserveReport2013.pdf [accessed 14 October October 2017]. 2017]. ANGLO AMERICAN PLATINUM LIMITED. 2012. Annual Report 2012. ANGLOGOLD ASHANTI LIMITED. 2014. Mineral Resource and Ore Reserve Report http://www.angloamericanplatinum.com/~/media/Files/A/Anglo- 2014. https://thevault.exchange/?get_group_doc=143/1502780826- American-Platinum/annual-reports/anglo-american-platinum-ar-2012.pdf MineralResourceandOreReserveReport2014.pdf [accessed 14 October [accessed 14 October 2017]. 2017]. ANGLO AMERICAN PLATINUM LIMITED. 2013. Ore Reserves and Mineral Resources ANGLOGOLD ASHANTI LIMITED. 2015. Mineral Resource and Ore Reserve Report Report 2013. http://www.angloamericanplatinum.com/~ 2015. https://thevault.exchange/?get_group_doc=143/1502780767- media/Files/A/Anglo-American-Platinum/documents/aap-rr-2013.pdf MineralResourceandOreReserveReport2015.pdf [accessed 14 October [accessed 14 October 2017]. 2017]. ANGLO AMERICAN PLATINUM LIMITED. 2014. Ore Reserves and Mineral Resources ANGLOGOLD ASHANTI LIMITED. 2016. Mineral Resource and Ore Reserve Report Report 2014. http://www.angloamericanplatinum.com/~/ 2016. https://thevault.exchange/?get_group_doc=143/1502779473- media/Files/A/Anglo-American-Platinum/annual-reports/anglo-american- platinum-r-and-r-2014.pdf [Accessed 14 October 2017]. 2016MineralResourceandOreReserveReport.pdf [accessed 14 October 2017]. ANGLO AMERICAN PLATINUM LIMITED. 2015. Ore Reserves and Mineral Resources Report 2015. http://www.angloamericanplatinum.com/~/ APPLEYARD, G.R. 2001. An overview and outline, mineral resource and ore media/Files/A/Anglo-American-Platinum/documents/amplats-mr-2015- reserve estimation. The AusIMM Guide to Good Practice. Edwards, A.C. final.pdf [accessed 14 October 2017]. (ed.). Monograph 23, Australasian Institute of Mining and Metallurgy, Melbourne. pp. 3–12. ANGLO AMERICAN PLATINUM LIMITED. 2016. Ore Reserves and Mineral Resources Report 2016. http://www.angloamericanplatinum.com/~/ APPLEYARD, G.R. AND SMITH, C.L. 2001. Non-resource inputs to estimation of ore media/Files/A/Anglo-American-Platinum/annual- reserves - The modifying factors. Mineral Resource and Ore Reserve reporting/downloads/ore-reserves-and-mineral-resources-2016.pdf Estimation: the AusIMM Guide to Good Practice. Edwards, A.C. (ed.). [Accessed 14 October 2017]. Monograph 23, Australasian Institute of Mining and Metallurgy, ANGLOGOLD LIMITED. 2000. Form 20-F for the Financial Year Ended December Melbourne. pp. 325–332. 31, 2000. https://www.anglogoldashanti.com/investors/annual- BAKER, C.K. and GIACOMO, S.M. 2001. Resources and Reserves Their uses and reports/form-20-f-form-6-k-us-gaap/ [accessed 14 October 2017]. abuses by the equity markets. Mineral Resource and Ore Reserve ANGLOGOLD LIMITED. 2001. Form 20-F for the Financial Year Ended December Estimation: the AusIMM Guide to Good Practice Edwards, A.C., 31, 2001. https://www.anglogoldashanti.com/investors/annual- (e.d.)Monograph 23. The Australasian Institute of Mining and Metallurgy, reports/form-20-f-form-6-k-us-gaap/ [accessed 14 October 2017]. Melbourne. pp.666–676. ANGLOGOLD LIMITED. 2002. Supplementary Information: Ore Reserves and BARCLAYS BANK PLC. 2014. Lonmin Plc Is this the time for change? - An equity Mineral Resources 2002. research report by African Precious Metals. 7 November 2014. https://www.anglogoldashanti.com/archive/miningreserves/Mineral%20re BARCLAYS BANK PLC. 2015. Built for today’s environment An equity research source%20and%20ore%20reserve%20reports%20(2002%20- report by African Precious Metals. 3 September 2015. %202012).zip [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2001. Annual Report 2001. ANGLOGOLD LIMITED. 2003. Supplementary Mineral Resource and Ore Reserve https://www.goldfields.com/pdf/investors/integrated-annual- information 2003. reports/2001/booklet.pdf [accessed 14 October 2017]. https://www.anglogoldashanti.com/archive/miningreserves/Mineral%20re Gold Fields Limited. 2002. Annual Report 2002. source%20and%20ore%20reserve%20reports%20(2002%20- https//www.goldfields.com/pdf/investors/integrated-annual- %202012).zip [accessed 14 October 2017]. reports/2002/booklet.pdf [accessed 14 October 2017]. ANGLOGOLD ASHANTI LIMITED. 2004. Supplementary Information: Mineral GOLD FIELDS LIMITED. 2003. Annual Report 2003. Resources and Ore Reserves 2004. https://www.goldfields.com/pdf/investors/integrated-annual- https://www.anglogoldashanti.com/archive/miningreserves/Mineral%20re reports/2003/booklet.pdf [accessed 14 October 2017]. source%20and%20ore%20reserve%20reports%20(2002%20- GOLD FIELDS LIMITED. 2004. Annual Report 2004. %202012).zip [accessed 14 October 2017]. https://www.goldfields.com/pdf/investors/integrated-annual- ANGLOGOLD ASHANTI LIMITED. 2005. Supplementary Information: Mineral reports/2004/booklet.pdf [accessed 14 October 2017]. Resources and Ore Reserves 2005. https://www.anglogoldashanti.com/archive/miningreserves/Mineral%20re GOLD FIELDS LIMITED. 2005. Annual Report 2005. source%20and%20ore%20reserve%20reports%20(2002%20- https://www.goldfields.com/pdf/investors/integrated-annual- %202012).zip [accessed 14 October 2017]. reports/2005/booklet.pdf [accessed 14 October 2017]. ANGLOGOLD ASHANTI LIMITED. 2006. Supplementary Information: Mineral GOLD FIELDS LIMITED. 2006. Annual Report 2006. Resources and Ore Reserves 2006. https://www.goldfields.com/pdf/investors/integrated-annual- https://www.anglogoldashanti.com/archive/miningreserves/Mineral%20re reports/2006/booklet.pdf [accessed 14 October 2017]. source%20and%20ore%20reserve%20reports%20(2002%20- GOLD FIELDS LIMITED. 2007. Annual Report 2007. %202012).zip [accessed 14 October 2017]. https://www.goldfields.com/pdf/investors/integrated-annual- ANGLOGOLD ASHANTI LIMITED. 2007. Supplementary Information: Mineral reports/2007/booklet.pdf [accessed 14 October 2017]. Resources and Ore Reserves 2007. https://www.anglogoldashanti.com/ GOLD FIELDS LIMITED. 2008. Annual Report 2008. archive/miningreserves/Mineral%20resource%20and%20ore%20reserve% https://www.goldfields.com/pdf/investors/integrated-annual- 20reports%20(2002%20-%202012).zip [accessed 14 October 2017]. reports/2008/iar-2008.pdf [accessed 14 October 2017]. L 240   
 VOLUME 119          
An empirical long-term commodity price range for Mineral Reserve declarations

GOLD FIELDS LIMITED. 2009. Annual Report 2009. HARMONY GOLD MINING COMPANY LIMITED. 2015. Mineral |Resources and Mineral https://www.goldfields.com/pdf/investors/integrated-annual- reserves 2015. http://www.har.co.za/15/download/HAR-RR15.pdf reports/2009/iar-2009.pdf [accessed 14 October 2017]. [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2010. Mineral Resources and Mineral Reserves 2010. HARMONY GOLD MINING COMPANY LIMITED. 2016. Mineral Resources and Mineral https://www.goldfields.co.za/reports/annual_report_2010/minerals_overvi Reserves 2016. http://www.har.co.za/16/download/HAR-RR16.pdf ew.php [accessed 14 October 2017]. [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2011. Mineral Resources and Mineral Reserves 2011. IMPALA PLATINUM HOLDINGS LIMITED. 2000. Mineral Resources and Mineral https://www.goldfields.co.za/reports/ar_dec_2011/minerals/downloads_pd Reserves 2000. http://implats-reports.co.za/reports/2000/pdfs/Impala_ f.php [accessed 14 October 2017]. plat.pdf [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2012. Mineral Resources and Mineral Reserves 2012. IMPALA PLATINUM HOLDINGS LIMITED. 2001, Annual Report 2001, https://www.goldfields.com/pdf/investors/mineral-reserves-and- http://www.implats.co.za/pdf/annual-reports/archive/2001/implats- resources-reports/2012/mrr-2012.pdf [accessed 14 October 2017]. ar2001.pdf [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2013. Mineral Resources and Mineral Reserves 2013. IMPALA PLATINUM HOLDINGS LIMITED. 2002. Annual Report 2002. https://www.goldfields.com/pdf/investors/mineral-reserves-and- http://www.implats.co.za/pdf/annual-reports/archive/2002/implats- resources-reports/2013/mrr-2013.pdf [accessed 14 October 2017]. ar2002.pdf [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2014. Mineral Resources and Mineral Reserves 2014. IMPALA PLATINUM HOLDINGS LIMITED. 2003. Annual Report 2003. https://www.goldfields.com/pdf/investors/mineral-reserves-and- http://www.implats.co.za/pdf/annual-reports/archive/2003/implats- resources-reports/2014/mrr-2014.pdf [accessed 14 October 2017]. ar2003.pdf [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2015. Mineral Resources and Mineral Reserves 2015. IMPALA PLATINUM HOLDINGS LIMITED. 2004. Annual Report 2004. https//www.goldfields.com/pdf/investors/mineral-reserves-and-resources- http://www.implats.co.za/pdf/annual-reports/archive/2004/implats- reports/2015/mrr-2015.pdf [accessed 14 October 2017]. ar2004.pdf [accessed 14 October 2017]. GOLD FIELDS LIMITED. 2016. Mineral Resources and Mineral Reserves 2016. IMPALA PLATINUM HOLDINGS LIMITED. 2005. Annual Report 2005. https://www.goldfields.com/pdf/investors/mineral-reserves-and- http://www.implats.co.za/pdf/annual-reports/archive/2005/implats- resources-reports/2016/mrr-2016-hires.pdf [accessed 14 October 2017]. ar2005.pdf [Accessed 14 October 2017]. HARMONY GOLD MINING COMPANY LIMITED. 2000a. Annual Report 2000. IMPALA PLATINUM HOLDINGS LIMITED. 2006. Annual Report 2006. http://implats- https://www.harmony.co.za/assets/investors/reporting/annual- reports.co.za/reports/2006/default.htm [accessed 14 October 2017]. reports/harmony_ar2000.pdf [accessed 14 October 2017]. IMPALA PLATINUM HOLDINGS LIMITED. 2007. Annual Report 2007. http://implats- HARMONY GOLD MINING COMPANY LIMITED. 2000b. Form 20-F for the fiscal year reports.co.za/reports/2007/default.htm [accessed 14 October 2017]. ended June 30, 2000. https://www.harmony.co.za/downloads/send/23- IMPALA PLATINUM HOLDINGS LIMITED. 2008. Implats Mineral Resource and Mineral form-20-f/368-form-20-f-2000 [accessed 14 October 2017]. Reserve Statement 2008. http://www.implats.co.za/pdf/annual- reports/mr-mr-statement/2008/implats-mrmr-2008.pdf [Accessed 14 HARMONY GOLD MINING COMPANY LIMITED. 2001a. Annual Report 2001. https//www.harmony.co.za/assets/investors/reporting/annual- October 2017]. reports/2001/landing.htm [accessed 14 October 2017]. IMPALA PLATINUM HOLDINGS LIMITED. 2009. Implats Mineral Resource and Mineral Reserve Statement 2009. http://www.implats.co.za/pdf/annual- HARMONY GOLD MINING COMPANY LIMITED. 2001b. Form 20-F for the fiscal year ended June 30, 2001. https://www.harmony.co.za/downloads/send/23- reports/mr-mr-statement/2009/implats-mrmr-2009.pdf [Accessed 14 form-20-f/367-form-20-f-2001 [accessed 14 October 2017]. October 2017]. IMPALA PLATINUM HOLDINGS LIMITED. 2010. Implats Mineral Resource and Mineral HARMONY GOLD MINING COMPANY LIMITED. 2002. Annual Report 2002. Reserve Statement 2010. http://www.implats.co.za/pdf/annual- https//www.harmony.co.za/assets/investors/reporting/annual- reports/mr-mr-statement/2010/implats-mrmr-2010.pdf [accessed 14 reports/harmony_ar2002.pdf [accessed 14 October 2017]. October 2017]. HARMONY GOLD MINING COMPANY LIMITED. 2003. Annual Report 2003. IMPALA PLATINUM HOLDINGS LIMITED. 2011. Implats Mineral Resource and Mineral https://www.harmony.co.za/assets/investors/reporting/annual- Reserve Statement 2011. http://www.implats.co.za/pdf/annual- reports/harmony_ar2003.pdf [accessed 14 October 2017]. reports/mr-mr-statement/2011/implats-mrmr-2011.pdf [accessed 14 HARMONY GOLD MINING COMPANY LIMITED. 2004. Annual Report 2004. October 2017]. https://www.harmony.co.za/assets/investors/reporting/annual- IMPALA PLATINUM HOLDINGS LIMITED. 2012. Implats Mineral Resource and Mineral reports/harmony_ar2004.pdf [accessed 14 October 2017]. Reserve Statement 2012. http://www.implats.co.za/pdf/annual- HARMONY GOLD MINING COMPANY LIMITED. 2005. Mineral Resources and Ore reports/mr-mr-statement/2012/implats-mrmr-2012.pdf [Accessed 14 Reserves 2005. https//www.harmony.co.za/assets/investors/ October 2017]. reporting/annual-reports/2005/Harmony_ar2005_res.pdf [accessed 14 IMPALA PLATINUM HOLDINGS LIMITED. 2013. Implats Mineral Resource and Mineral October 2017]. Reserve Statement 2013. http://www.implats.co.za/pdf/annual- HARMONY GOLD MINING COMPANY LIMITED. 2006. Annual Report 2006. reports/mr-mr-statement/2013/implats-mrmr-2013.pdf [accessed 14 https://www.harmony.co.za/assets/investors/reporting/annual- October 2017]. reports/2006/files/Harmony_AR2006.pdf [accessed 14 October 2017]. IMPALA PLATINUM HOLDINGS LIMITED. 2014. Implats Mineral Resource and Mineral HARMONY GOLD MINING COMPANY LIMITED. 2007. Annual Report 2007. Reserve Statement 2014. http://www.implats.co.za/pdf/annual- https://www.harmony.co.za/assets/investors/reporting/annual- reports/mr-mr-statement/2014/implats-mrmr-2014.pdf [accessed 14 reports/2007/files/Harmony_AR07.pdf [Accessed 14 October 2017]. October 2017]. HARMONY GOLD MINING COMPANY LIMITED. 2008. Annual Report 2008. IMPALA PLATINUM HOLDINGS LIMITED. 2015. Implats Mineral Resource and Mineral https://www.harmony.co.za/assets/investors/reporting/annual- Reserve Statement 2015. http://www.implats.co.za/pdf/annual- reports/2008/files/Harmony_AR2008.pdf [accessed 14 October 2017]. reports/mr-mr-statement/2015/implats-mrmr-2015.pdf [accessed 14 HARMONY GOLD MINING COMPANY LIMITED. 2009. Annual Report 2009. October 2017]. https://www.harmony.co.za/assets/investors/reporting/annual- IMPALA PLATINUM HOLDINGS LIMITED. 2016. Implats Mineral Resource and Mineral reports/2009/files/Harmony_AR09.pdf [accessed 14 October 2017]. Reserve Statement 2016. http://bastiongraphics.co.za/bastion- HARMONY GOLD MINING COMPANY LIMITED. 2010. Annual Report 2010. ir/2016/Implats-2016/Implats-MRR-2016/downloads/Implats%20MR% https://www.harmony.co.za/assets/investors/reporting/annual- 202016.pdf [accessed 13/04/2017]. reports/2010/f/HAR_AR2010.pdf [accessed 14 October 2017]. IFRS FOUNDATION, (n.d.). International Accounting Standard 36 Impairment of HARMONY GOLD MINING COMPANY LIMITED. 2011. Annual Report 2011. Assets. http://www.frascanada.ca/international-financial-reporting- http://www.financialresults.co.za/2011/harmony_ar2011/downloads/har standards/resources/unaccompanied-ifrss/item45641.pdf [accessed mony_integrated_ar2011.pdf [accessed 14 October 2017]. 02/06/2018]. HARMONY GOLD MINING COMPANY LIMITED. 2012. Annual Report 2012. KITCO, (n.d.). Daily Palladium Charts. http://www.kitco.com/scripts/hist_charts/ http://www.financialresults.co.za/2012/harmony_ar2012/integrated- yearly_graphs.plx [accessed 10/02/2018]. report/downloads/Harmony%20AR_Lo-Res_new.pdf [Accessed 14 KITCO, (n.d.). Daily Rhodium Charts. http://www.kitco.com/scripts/hist_charts/ October 2017]. yearly_graphs.plx [accessed 10/02/2018]. HARMONY GOLD MINING COMPANY LIMITED. 2013. Mineral Resources and Mineral LOMBERG, K. and RUPPRECHT, S.M. 2017. The 2016 SAMREC Code. Journal of the Reserves 2013. http://www.financialresults.co.za/2013/harmony_ir2013/ Southern African Institute of Mining and Metallurgy, vol. 117, no. 12, harmony_mr2013/index.php [accessed 14 October 2017]. pp.1095–1100. HARMONY GOLD MINING COMPANY LIMITED. 2014. Form 20-F for the fiscal year LONMIN PLC. 2000. Annual Report 2000. https://thevault.exchange/?get_ ended June 30, 2014. https://www.harmony.co.za/downloads/send/23- group_doc=166/1449150925-AnnualReportAccounts.pdf [accessed 14 form-20-f/1038-2014-harmony-20f [accessed 14 October 2017]. October 2017].

VOLUME 119          
  
 241 L An empirical long-term commodity price range for Mineral Reserve declarations

LONMIN PLC. 2001. Annual Report 2001. https//thevault.exchange/?get_ http://www.northam.co.za/images/publications/ar/ar_2001/resources_and group_doc=166/1449150754-AnnualReportAccounts.pdf [accessed 14 _reserves.html [accessed 14 October 2017]. October 2017]. NORTHAM PLATINUM LIMITED. 2002. Annual Report 2002. LONMIN PLC. 2002. Annual Report 2002. https://thevault.exchange/?get_ http://www.northam.co.za/downloads/send/39-2002/495-annual-report- group_doc=166/1449150530-AnnualReportAccounts.pdf [accessed 14 2002 [accessed 14 October 2017]. October 2017]. NORTHAM PLATINUM LIMITED. 2003. Annual Report 2003. LONMIN PLC. 2003. Annual Report 2003. https//thevault.exchange/?get_group_ http://www.northam.co.za/downloads/send/38-2003/494-annual-report- doc=166/1449150320-AnnualReportAccounts.pdf [accessed 14 October 2003 [accessed 14 October 2017]. 2017]. NORTHAM PLATINUM LIMITED. 2004. Annual Report 2004. LONMIN PLC. 2004. Annual Report 2004. https://thevault.exchange/?get_group_ http://www.northam.co.za/downloads/send/37-ar-2004/493-annual- doc=166/1449149849-AnnualReportAccounts.pdf [accessed 14 October report-2004 [accessed 14 October 2017]. 2017]. NORTHAM PLATINUM LIMITED. 2005. Annual Report 2005. LONMIN PLC. 2005. Mineral Resources and Reserves 2005. http://www.northam.co.za/downloads/send/36-2005/492-annual-report- https://thevault.exchange/?get_group_doc=166/1449149275- 2005 [accessed 14 October 2017]. MineralResourceMineralReserveStatement.pdf [accessed 14 October NORTHAM PLATINUM LIMITED. 2006. Annual Report 2006. 2017]. http://www.northam.co.za/downloads/send/35-2006/491-annual-report- LONMIN PLC. 2006. Mineral Resources and Reserves 2006. 2006 [accessed 14 October 2017]. https://thevault.exchange/?get_group_doc=166/1449148329- NORTHAM PLATINUM LIMITED. 2007. Annual Report 2007. MineralResourceMineralReserveStatement.pdf [accessed 14 October http://www.northam.co.za/downloads/send/34-2007/490-annual-report- 2017]. 2007 [accessed 14 October 2017]. LONMIN PLC. 2007. Mineral Resources and Reserves 2007. NORTHAM PLATINUM LIMITED. 2008. Annual Report 2008. https://thevault.exchange/?get_group_doc=166/1449145281- http//www.northam.co.za/downloads/send/33-2008/489-annual-report- MineralResourceMineralReserveStatement.pdf [accessed 14 October 2008 [accessed 14 October 2017]. 2017]. NORTHAM PLATINUM LIMITED. 2009. Annual Report 2009. LONMIN PLC. 2008. Mineral Resources and Reserves 2008. http://www.northam.co.za/downloads/send/32-2009/488-annual-report- https://thevault.exchange/?get_group_doc=166/1449142943- 2009 [accessed 14 October 2017]. MineralResourceMineralReserveStatement.pdf [accessed 14 October NORTHAM PLATINUM LIMITED. 2010. Annual Report 2010. 2017]. http://www.northam.co.za/downloads/send/31-2010/487-annual-report- LONMIN PLC. 2009. Mineral Resources and Reserves Statement 2009. 2010 [accessed 14 October 2017]. https://thevault.exchange/?get_group_doc=166/1449141739- NORTHAM PLATINUM LIMITED. 2011. Annual Integrated Report 2011. MineralResourceMineralReserveStatement.pdf [accessed 14 October http//www.northam.co.za/downloads/send/30-2011/486-annual-report- 2017]. 2011 [accessed 14 October 2017]. LONMIN PLC. 2010. Mineral Resources and Reserves Statements 2010. NORTHAM PLATINUM LIMITED. 2012. Annual Integrated Report 2012. https://thevault.exchange/?get_group_doc=166/1449140716- http://northam.integrated-report.com/2012/download/NHM-IR2012.pdf MineralResourceMineralReserveStatement.pdf [accessed 14 October [accessed 14 October 2017]. 2017]. NORTHAM PLATINUM LIMITED. 2013. Annual Integrated Report 2013. LONMIN PLC. 2011. Mineral Resources and Reserves Statements 2011. http://www.northam.co.za/downloads/send/25-2013/483-annual- https://thevault.exchange/?get_group_doc=166/1449138821- integrated-report-2013 [accessed 14 October 2017]. MineralResourceMineralReserveStatement.pdf [accessed 14 October NORTHAM PLATINUM LIMITED. 2014. Annual Integrated Report 2014. 2017]. http://northam.integrated-report.com/2014/downloads/NHM-IR14.pdf LONMIN PLC. 2012. Mineral Resources and Reserves Statements 2012. [accessed 14 October 2017]. https://thevault.exchange/?get_group_doc=166/1449136164- Northam Platinum Limited. 2015. Annual Integrated Report 2015. MineralResourceMineralReserveStatement.pdf [accessed 14 October http://northam.integrated-report.com/2015/downloads/NHM-IR15.pdf 2017]. [accessed 14 October 2017]. LONMIN PLC. 2013. Mineral Resources and Reserves Statements 2013. NORTHAM PLATINUM LIMITED. 2016. Annual Integrated Report 2016. https://thevault.exchange/?get_group_doc=166/1449133312- http://northam.integrated-report.com/2016/download/NHM-AIR16.pdf MineralResourceMineralReserveStatement.pdf [accessed 14 October [accessed 14 October 2017]. 2017]. PENN STATE EBERLY COLLEGE OF SCIENCE, (Not dated). 1.5 - The coefficient of LONMIN PLC. 2014. Mineral Resources and Reserves Statements 2014. determination, r-squared, https://newonlinecourses.science.psu.edu/ https://thevault.exchange/?get_group_doc=166/1449131677- stat501/node/255/ [accessed 14/01/2019]. MineralResourceMineralReserveStatement.pdf [accessed 14 October QUANDL, (Not dated). Ruthenium prices. 2017]. https://www.quandl.com/data/JOHNMATT/RUTH-Ruthenium-Prices LONMIN PLC. 2015. Mineral Resources and Reserves Statements 2015. [accessed 10/02/2018]. https://thevault.exchange/?get_group_doc=166/1453806485- SIBANYE GOLD LIMITED. 2013. Mineral Resources and Mineral Reserves 2013. 2015_RR_Statement.pdf [accessed 14 October 2017]. http://reports.sibanyegold.co.za/2013/download/SGL-RR13.pdf [accessed LONMIN PLC. 2016. Mineral Resources and Reserves Statements 2018. 14 October 2017]. https://thevault.exchange/?get_group_doc=166/1507013512-Lonmin- SIBANYE GOLD LIMITED. 2014. Mineral Resources and Mineral Reserves 2014. Resource-Statement-2016.pdf [accessed 14 October 2017]. http://reports.sibanyegold.co.za/2014/download/SGL-RR14.pdf [accessed MACDIARMID J., THOLANA, T., and MUSINGWINI, C. 2018. Analysis of key value 14 October 2017]. drivers for major mining companies for the period 2006–2015. Resources Sibanye Gold Limited. 2015. Mineral Resources and Mineral Reserves 2015. Policy, vol. 56, pp.16–30. http://reports.sibanyegold.co.za/2015/download/SGL-RR15.pdf [accessed MASEKO, V. 2018. An assessment of the long-term commodity price 14 October 2017]. assumptions on the Mineral Reserve estimates of South African gold and Sibanye Gold Limited. 2016. Mineral Resources and Mineral Reserves Report platinum mining companies from 2000 to 2016. MSc research report, 2016. http://reports.sibanyegold.co.za/2016/download/SGL-RR16.pdf University of the Witwatersrand, South Africa. [Accessed 14 October 2017]. METALARY, (Not dated). Iridium price. https://www.metalary.com/iridium-price/ SNL Metals & Mining. (Not dated). Gold price chart. [accessed 10 February 2018]. https://www.snl.com/web/client?auth=inherit#industry/priceChart MUSINGWINI, C. 2018. Keynote Address: The importance of teaching mineral [accessed 10/02/2018]. reporting and valuation codes in mine planning and valuation discourses SNL Metals & Mining. (Not dated). Gold price chart. within a mining engineering curriculum. Proceedings of Society of Mining https://www.snl.com/web/client?auth=inherit#industry/priceChart Professors 6th Regional Conference, Johannesburg, South Africa, 12–13 [accessed 10/02/2018]. March 2018, Southern African Institute of Mining and Metallurgy, STATISTICS SOUTH AFRICA. 2017. Mining Industry 2015 Report no. 20-01-02. Johannesburg. pp. 237–244. http://www.statssa.gov.za/publications/Report-20-01-02/Report-20-01- NJOWA, G. AND MUSINGWINI, C. 2018. A framework for interfacing mineral asset 022015.pdf [accessed 25/07/2017]. valuation and financial reporting. Resources Policy, vol.56. pp. 3–15. SAMREC. 2016. South African Mineral Resource Committee. The South African NORTHAM PLATINUM LIMITED. 2000. Resources and Reserves 2000. Code for the Reporting of Exploration Results, Mineral Resources and http://www.northam.co.za/images/publications/ar/ar_2000/resources_and Mineral Reserves (the SAMREC Code). 2016 Edition. _reserves.html [accessed 14 October 2017]. http://www.samcode.co.za/codes/category/8-reporting- NORTHAM PLATINUM LIMITED. 2001. Resources and Reserves 2001. codes?download=120:samrec N L 242   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a3 Application of geometallurgical modelling to mine planning in a copper-gold mining operation for improving ore quality and mineral processing efficiency

by C. Beaumont1 and C. Musingwini2

to support geostatistical estimations of copper grade continuity. The model has been colour- &38,272 coded based on total copper (TCu) grade Kansanshi mine, located in northwestern Zambia, uses conventional open- ranges. The model also has mineralogical pit mining to produce primarily copper, with gold as a by-product. The ore domains defined by ranges of oxidation is extracted from a deposit with highly complex mineralogical suites that intensity and associated mineralogy. are difficult to process, sometimes leading to poor recoveries. The mine The Kansanshi deposit comprises a series was using an ore classification system called ‘Mat-Type’, which classified of complex mineralogical suites that were various ore types into 22 different quality categories, ranging from poor to good quality. Ore with poor recovery was classified as ’poor quality’ ore formed through the interaction of geological, and directed to long-term stockpiles. Due to a lack of proper integration weathering, and oxidation processes. between the technical and functional areas forming the mine value chain, Geophysical and geochemical processes Mat-Type unintentionally misclassified ore. A geometallurgical analysis resulted in the mineralization in the upper was therefore undertaken to review Mat-Type and a new geometallurgical portion of the ore deposit being oxidized from ore classification system, called ‘OXMAT ’, was developed to replace Mat- a predominantly chalcopyrite, pyrrhotite, and Type. pyrite assemblage to a suite of secondary When implemented, OXMAT eliminated nine of the 22 ore categories copper sulphide minerals and primary copper and the remaining 13 ore categories could now be more accurately and oxide minerals, including bornite, digenite, consistently defined, leading to a significant change in the quantity of ore chalcocite, malachite, tenorite, and chrysocolla. being mined. OXMAT demonstrated that within a defined test volume of the geological model, waste tonnes could be reduced by 19% while ore Where large subvertical fault structures cut tonnes could be increased by 17%. This paper therefore demonstrates the across the deposit, these processes have value created through integrated geometallurgical modelling. affected the host rock and mineralization at much deeper levels. There is a high degree of 9&$8402 variability in the composition of the mineral acid-soluble copper, total copper, gangue acid consumption, geometallurgical modelling, oxidation ratio, weathering domains. assemblages over short ranges, both laterally across the deposit and vertically within mineralized structures. The mine has a complex metallurgical processing plant which is designed to primarily recover copper from different ore types. In ;35480)*5783 order to treat the different ore types, there are Kansanshi mine is located in northwestern three main metallurgical processes, all of Zambia, approximately 10 km north of the which are served by a dedicated crusher and provincial capital Solwezi and about 160 km set of mills. These metallurgical processes are west of Nchanga mine in the Central African (Beaumont, 2016): Copperbelt (Broughton and Hitzman, 2002). ® Sulphide ore flotation The location of Kansanshi mine relative to ® Mixed ore flotation other major copper deposits in the Copperbelt ® Oxide ore flotation followed by is indicated in Figure 1. atmospheric acidic leaching, solvent Kansanshi mine uses conventional open- extraction, and electrowinning (SX-EW). pit mining methods to exploit copper- and gold-bearing veins hosted in a structurally- controlled mineral deposit. Mining is carried out in two areas of the deposit, the Northwest and Main pits. A third area of the deposit, called Southeast Dome, is currently not being 1 Kansanshi Mining Company PLC, Solwezi, exploited (Figure 2). Zambia. 2 School of Mining Engineering, University of the Figure 3 illustrates an east-west cross- Witwatersrand, South Africa. section of the Kansanshi mine grade control © The Southern African Institute of Mining and model through the Main Pit area of the Metallurgy, 2019. ISSN 2225-6253. Paper received deposit, created using assay and logging data Aug. 2018; revised paper received Oct. 2018.

VOLUME 119          
  
 243 L Application of geometallurgical modelling to mine planning in a copper-gold mining operation

(7+)49:'%6,:8.:-6 84:09,82752:73:5/9:935461:.47*63:8,,94915:$75/:5/9:18*65783:8.:632632/7:-739:*74*190:73:490: 06,590:.48-:717589:   !:" '

(7+)49:"%9818+7*61:-6,:8.:5/9:632632/7:849:09,8275: 606,590:.48-:880!:" ''

(7+)49:%4822:29*5783:5/48)+/:5/9:673:75:,845783:8.:5/9:632632/7:-739:+4609:*835481:-8091!:188 73+:3845/

The sulphide flotation plant utilizes a standard flotation concentrate for smelting. Tailings from the oxide ore flotation method to produce a copper and gold concentrate for plant report to an atmospheric leach plant. Copper is leached smelting. The mixed flotation plant utilizes controlled from the oxide ore using concentrated sulphuric acid, and the potential sulphidization (CPS) to improve the recovery of pregnant solution is subjected to solvent extraction and secondary copper sulphide minerals or partially oxidized electrowinning to produce a final copper cathode product. copper bearing minerals, also to produce a copper- and gold- Gold is also recovered from all metallurgical circuits by bearing concentrate for smelting. The oxide ore plant utilizes centrifugal concentrators. The gold concentrate is upgraded a standard flotation method producing a copper and gold by tabling and smelted to produce doré bars. L 244   
 VOLUME 119          
Application of geometallurgical modelling to mine planning in a copper-gold mining operation

Some of the mineralogical suites are difficult to process in modelling has been used in the mining industry to overcome the metallurgical plant, leading to poor recoveries. A material challenges arising from ore variability and to generate type ore classification system called ‘Mat-Type’ was used to significant value-add. Bye (2011) and Chibaya (2013) classify the various ore types based on a number of control broadly explained the concept of geometallurgy as a technical parameters that would manage ore quality and ensure approach that integrates geology, mine design and planning, efficient and economic recovery of copper and gold. Ore metallurgy, and environmental analysis with the aim of containing mineral assemblages considered to be of ‘poor improving the understanding of available mineral resources quality’ were directed to long-term stockpiles, which are for better extraction of the minerals of interest. scheduled for processing towards the end of the life of mine. In the case of Kansanshi mine, the Mat-Type system was In 2015 a smelter was commissioned on the Kansanshi used for classifying the various ore types, ranging from ‘poor mine site. A by-product of the smelting process is sulphuric quality’ to ‘good quality’, into 22 different quality categories. acid, which is a reagent that is critical to the oxide ore It was found that due to poor integration between the leaching process. The production of sulphuric acid from the technical operating silos that form the mine value chain, the smelter flue gas reduces the impact on local air quality. In Mat-Type ore classification system did not adequately addition, the cheap acid produced has a significant impact on consider geological, mineralogical, or metallurgical processes the economic viability of some of the ‘poor quality’ oxide ore in an integrated way. that was previously considered to be too expensive to process due to its high acid consumption in the leaching process.
#94#79$:8.:5/9:
 849:*16227.7*65783:2&259- It was therefore imperative that a review of the Mat-Type The Mat-Type ore classification system was first introduced ore classification system be undertaken to determine how it at Kansanshi mine in 2009. The system was designed with could be improved through the application of the following objectives (Beaumont, 2016): geometallurgical modelling principles. The ultimate goal of ® Separating oxide ore from sulphide ore and the review was to establish if the value of the ‘poor quality’ categorizing anything that was not sulphide or oxide as ore could be realized sooner through better ore classification mixed float ore so that ore could be fed to the process plant directly rather ® Applying a set of cut-off grades to categorize waste, than being stockpiled and reclaiming it at a later date. Better marginal grade, low grade, and high grade for both ore classification could potentially be achieved through an sulphide ore and oxide ore improved geometallurgical understanding that is integrated ® Improving the ’quality’ of the sulphide ore mill feed across the overall mine value chain. product by reducing the acid-soluble copper (ASCu) content to <0.05% 95/80818+& ® Improving the ’quality’ of the mixed float ore product The review of the Mat-Type ore classification system required by increasing the quantity of acid-insoluble copper an understanding of holistically integrating multiple technical (AICu) in the ore feed and functional areas across the entire mine value chain. It ® Improving the ‘quality’ of the oxide ore product by was therefore, important to develop a research methodology increasing ASCu grades to >0.6% ® that would systematically address each of these areas in a Managing the consumption of sulphuric acid (H2SO4), manner that would maintain focus on the relevant data in the which is an important yet costly reagent used in the context of the overall project goal. To this end, the literature oxide ore processing circuit was reviewed for information on how geometallurgical ® Directing any ore that did not conform to the above investigations had been undertaken on other mineral quality control factors to appropriate long-term deposits. This review demonstrated the need to investigate stockpiles. each aspect of the problem in a systematic manner, starting Based on the objectives listed above, the Mat-Type ore with the ore deposit characteristics and working forward, classification system used a series of ‘IF’ statements to apply through each stage of the mine value chain to establish how fixed grade limits and quality control parameters to determine each stage impacted consecutive stages. ore that would be suitable to feed each of the three mineral This required mapping out the Mat-Type system as a flow processing circuits: sulphide flotation, mixed flotation, and chart to identify each of the decision-making points and the oxide leach. Anything that was not suitable for the factors or assumptions applied at each of those points. Work processing plant would be directed to a long-term stockpile. could then be carried out to determine if any particular Figure 4 illustrates the calculation logic of the Mat-Type decision point, factor, or assumption was still relevant given system, where, each of the 22 hexagonal boxes represents a the current, more thorough understanding of the deposit and specific ore type. mineral processing system. Through an iterative process, the modified decisions, factors, and assumptions were built into /845*8-73+2:8.:5/9:
 849:*16227.7*65783 a separate flow chart which was code-named ‘OXMAT ’. This 2&259- allowed comparisons to be made between the Mat-Type and Through a systematic review of the Mat-Type ore OXMAT systems to enable the determination of the scale of classification system a number of key shortcomings were change caused by each modification as it was applied at each identified (Beaumont, 2016): stage of the ore classification system. ® A lack of ownership and management of the input data, and the absence of a formalized review process to 98-95611)4+7*61:-8091173+ ensure that data inputs remain fit-for-purpose under Bye (2011) described case studies where geometallurgical ever-changing circumstances

VOLUME 119          
  
 245 L Application of geometallurgical modelling to mine planning in a copper-gold mining operation

(7+)49: (18$:*/645:49,49293573+:5/9:65 &,9:849:*16227.7*65783:2&25&9-:*61*)1651783:18+7*: 96)-835!:" '

® Lack of application of geological data to support the system also needed to be reviewed in the context of the definition of certain ore categories improved understanding of the geology and mineralization of ® Application of inconsistent ’quality control’ factors at the deposit and of the metallurgical process. various stages of the ore classification process. A cross-functional team composed of geologists, mining engineers, and metallurgists was tasked to complete a 9#918,-935:8.:63:7359+46590:6,,486*/:58:849 thorough review of the entire Mat-Type ore classification *16227.7*65783: system to ensure that it remained fit-for-purpose. Detailed The Mat-Type ore classification system was developed by a technical discussions were promoted between stakeholders consultancy firm in conjunction with the technical services across the functional areas of the mine value chain, allowing team at Kansanshi mine. The key objective of the the free flow of ideas and improved understanding of the classification system was to direct the best quality and orebody, the mining process, and the metallurgical process. highest grade ore to the process plant in order to increase This integration of knowledge and understanding between copper production. Once the system was developed it was the key technical areas allowed for improved decision- handed over to the technical services team on site and making based on all of the available data. A cross-functional implemented in early 2009. Given the simplistic approach to the systematic review of available data was understanding of the ore deposit at that time, there was no critical in supporting the development of a geometallurgical process to rigorously validate the Mat-Type ore classification ore classification method. system and fully understand how it was categorizing ore into the different types. 939461:7-,46*57*6175& From 2010 to 2013, a large-scale mineral resource The Mat-Type system was extremely complicated to use. definition drilling programme was completed and a number Only four out of the 22 available ore categories could be used of capital projects to upgrade and increase the throughput consistently on a daily basis to feed the process plant. Each capacity of the metallurgical plant were also commissioned. day the mine geologist on duty would have to manually re- During this time, operating costs, mineral royalties, and direct ore from the digging face to the crusher based on a commodity prices changed. Following the publication of an visual assessment of the characteristics of the material being updated Mineral Resource and Mineral Reserve statement mined. These manual re-directions were subjective. The and Life of Mine Optimization (LOM) plan in December 2012, intention of the Mat-Type system was to provide greater the Kansanshi mine technical services team was asked to control over the quality of the ore reporting to the mineral review the cut-off grades applied to the grade control model processing circuit. However, the day-to-day reality was that by the Mat-Type system. During this review it emerged that a there were so many quality control factors applied to the number of other data inputs to and assumptions in the system that its consistency in application was questionable. L 246   
 VOLUME 119          
Application of geometallurgical modelling to mine planning in a copper-gold mining operation

/9:7-,6*5:8.:$965/9473+:630:87065783:83:5/9:
  These domains could be defined as: 849: ® Ratio range <0.10: Fresh sulphide mineralization composed of chalcopyrite The Mat-Type ore classification system used in situ ® Ratio range between >0.10 and <0.15: Secondary weathering domains as a primary broad-scale criterion for copper sulphide mineralization composed of bornite, grouping types of ore. The assumption was that each of the with minor amounts of covellite, digenite, and following three groups could be linked to a metallurgical chalcopyrite process. ® Ratio range between >0.15 and <0.50: Secondary ® Mineralization in highly weathered saprolite zones was copper sulphide mineralization composed of chalcocite, considered to be suitable for the oxide process plant with minor covellite, digenite, and copper oxides such ® Mineralization in saprock zones was considered to be as tenorite and chrysocolla suitable for processing in the mixed ore flotation plant ® Ratio range >0.50: Oxidized mineralization ® Mineralization contained in the fresh rock predominantly composed of malachite and chrysocolla (unweathered areas) was considered to be suitable for with minor chalcocite, tenorite, cuprite, and native the sulphide ore flotation plant. copper. However, the weathering process was not responsible for A pit wall mapping campaign undertaken in conjunction the chemical modification of ore minerals from the original with re-logging of selected diamond drill core confirmed the chalcopyrite assemblage to secondary sulphide or primary spatial presence of these mineral groupings within the ranges oxide assemblages. This was the result of oxidation. The of oxidation ratio specified above. This analysis intensity of weathering and oxidation across the Kansanshi demonstrated that it would be more appropriate to categorize deposit is highly variable. Typically, in areas of intense ore types according to oxidation intensity and associated weathering there is also intense oxidation. However, it was mineralogy rather than by weathering characteristics, as was also observed that in deep-seated fault structures, where then the practice in the Mat-Type ore classification system. weathering was limited and the host lithology still remained largely intact, pods of moderately to highly oxidized 8,,94:49*8#94&:-8091173+:6361&272 mineralization could be found. Metallurgical recovery modelling for each of the process plant Through statistical analysis of raw sample data gathered routes had typically been done in isolation owing to the view from diamond drilling and reverse circulation drilling that each ore product and each mineral processing route was programmes a series of oxidation domains was defined. An separate. The accepted logic was that higher ASCu grades in oxidation ratio was calculated using Equation [1] and applied the sulphide flotation system led to poor recovery. A fixed to the raw geological sample data. Assay values below 0.20% cut-off grade of 0.05% ASCu was used to manage the quality TCu were removed from this analysis to aid in interpretation. of the sulphide ore in order to obtain the maximum copper These results were plotted on a log histogram as presented in recovery in the sulphide flotation plant. Ore with an ASCu Figure 5. >0.05% would be directed to the mixed float circuit or a long- term stockpile. [1] Analysis was conducted to compare the recovery profiles of the sulphide and mixed float processes. The results of this This exercise demonstrated that there were four distinct analysis are presented in Figure 6. The analysis oxidation domains within the Kansanshi mineral deposit. demonstrated that while ASCu values >0.05% reduced

(7+)49:%8+:/7258+46-:8.:87065783:465782:.84:46$:26-,19:0656:.48-:5/9:632632/7:849:09,8275: 96)-835!:" '

VOLUME 119          
  
 247 L Application of geometallurgical modelling to mine planning in a copper-gold mining operation

The cross-over points at 10% and 36% oxidation ratio, as indicated in Figure 7, for the metallurgical recovery models were well aligned with the same ratio groupings derived from the analysis of raw geological sample data. It was found that the two separate analyses of separate data sources were aligning well to support the overall hypothesis that oxidation was the key factor in ore classification and metallurgical efficiency. Further analysis of the available metallurgical data demonstrated two significant opportunities to recover additional copper from the mixed float and oxide ore. The first required a modification to the oxide flotation circuit, incorporating CPS technology to increase the recovery of minor secondary sulphide minerals such as chalcocite and (7+)49:%8-,647283:8.:*8,,94:.18565783:49*8#94&:,48.7192:62:6 covellite. The second required the mixed float ore tailings to .)3*5783:8.:):-711:/960:+4609: 96)-835!:" ' be directed through the oxide leach circuit. A comparison of the oxidation ratio of mixed float mill head grade (prior to flotation) with the oxidation ratio of the mixed float tailings recovery in the sulphide circuit, the mixed float process still (after flotation) is presented in Figure 8. It was found that as returned a lower recovery for this ore type. Therefore, using a copper-bearing sulphide minerals were recovered in the fixed ASCu cut-off grade of 0.05% to direct sulphide ore to flotation process, the ASCu/TCu ratio of the remaining the mixed float process was not reliable. tailings was increased, indicating that the minerals remaining From the analysis and understanding of the oxidation in the mixed float tailings were more amenable to leaching. domains, discussions between the geology and metallurgical By directing the mixed float tailings through the oxide leach teams revealed that each of the mineral groupings identified circuit the oxidized minerals could be leached and processed was more or less amenable to a specific mineral processing through to the SX-EW circuit. method employed at the Kansanshi metallurgical plant. A hypothesis was presented stating that copper recovery in each 63+)9:6*70:*832)-,5783 mineral processing circuit is a function of the ratio of ASCu to Across the industry, managing the consumption of sulphuric TCu grade. To investigate this hypothesis, head grade and acid in an oxide leach plant has always been a serious issue recovery data for the sulphide and mixed float processing for most metallurgical operations. Typically at Kansanshi the circuits spanning a four-year period was analysed to compare highest grade oxide ore was found in close proximity to a the recovery profiles for each circuit as a function of the lithological unit termed the ‘upper marble’, composed of calculated oxidation ratio (Figure 7). Through the recovery calcium carbonate (CaCO3) which is a gangue acid- modelling process three key trends were identified: consuming (GAC) component of the oxide ore. To limit the ® Ore with an oxidation ratio <10% would produce more acid-consuming properties of oxide ore fed to the copper through the sulphide plant compared to the metallurgical plant, a limit of 50 kg/t GAC was applied by the mixed and oxide plants Mat-Type ore classification system. With an abundance of ® Ore with an oxidation ratio of >10% but <36% would cheap sulphuric acid being generated from the smelting be most effectively treated in the mixed float plant process, the oxide ore processing strategy could be changed ® Ore with an oxidation ratio >36% would produce the because acid consumption had become less of a constraint. It highest recovery through the oxide plant. was therefore important to understand the geological range of

(7+)49:%48*922:,1635:49*8#94&:$75/:492,9*5:58:87065783:46578 L 248   
 VOLUME 119          
Application of geometallurgical modelling to mine planning in a copper-gold mining operation

(7+)49:%8-,647283:8.:/960:+4609:630:56712:+4609:87065783:465782:8#94:57-9:.84:5/9:-790:.1865:849:-95611)4+7*61:,48*922: 6$283:630:96)-835!:" '

gangue acid-consumers occurring naturally in the deposit Equation [2] assumes that oxide ore with a high ASCu and how best to control the feed of high-GAC ore types to the grade and a GAC greater than 50 kg/t could still be fed to the oxide circuit. oxide process plant if the AOR was below a nominal value set A review of the available geological assay data showed a at five. However, if the AOR was above five the Mat-Type ore highly skewed bimodal population of GAC data across the classification system indicated that the ore should instead be deposit (Figure 9). There are two distinct domains of GAC- fed to the mixed float circuit. bearing ore within the Kansanshi deposit. These can be An analysis of GAC and ASCu grade data demonstrated geologically defined as: that there was no statistical relationship between GAC and ® High-GAC domain, >110 kg/t, dominated by marble ASCu grade. Furthermore, the application of the AOR at ® Low-GAC domain, <110 kg/t, dominated by clastic various stages of the Mat-Type ore classification system was rocks composed of schists and phyllites. directing oxide ore to either the wrong metallurgical process (mixed float) or to long-term stockpiles. The unintentional This analysis demonstrated that the limit of 50 kg/t GAC effect of this was to artificially increase the ASCu grade of the currently applied to oxide ore in the Mat-Type classification mixed float ore feed by changing the dominant mineralogical system was suboptimal, as it lay in the middle of one suite from secondary sulphide minerals to oxide minerals. population of the GAC data. By raising the oxide ore GAC Oxide minerals are less amenable to the CPS process than limit from 50 kg/t to 110 kg/t the acid consumption could be secondary sulphide minerals, thus while the factor was more appropriately managed through the application of assisting in reducing the GAC content of the oxide circuit, geological controls. The net effect of this was that a there was a negative impact on the recovery of copper in the significant quantity of oxide ore was now available for mixed float circuit. processing that would have previously been directed to stockpiles. With this increased quantity of oxide ore at a higher GAC content, a larger quantity of acid produced from 790:.1865:;):46578 the smelting process could be utilized. After the implementation of the Mat-Type ore classification system in 2009 a drop in the recovery performance of the *70:58:849:46578 mixed float process was noted. Metallurgical test work by Further investigation into the application of GAC Paquot (2009) had demonstrated that the recovery in the management methods in the Mat-Type ore classification mixed float process could be improved by controlling the system revealed that it was possible to take advantage of the quantity of AICu in the feed. AICu is defined by Equation [3]: acid to ore ratio (AOR) factor. The AOR is a metallurgical [3] factor developed to further define and manage the gangue acid consumption in the oxide ore metallurgical process, and AICu is effectively the portion of a primary or secondary is defined by Equation [2]. sulphide mineral that has not been fully oxidized to become acid soluble. To improve and maintain recovery of the mixed [2] float ore the ‘mixed float acid insoluble copper ratio’ (MF_AICu_Ratio) was developed as given by Equation [4].

VOLUME 119          
  
 249 L Application of geometallurgical modelling to mine planning in a copper-gold mining operation

(7+)49:%7258+46-:8.::#61)92:.84:5/9:632632/7:09,8275: 96)-835!:" ':6.594:
+71#79!:" '

[4] 9#918,-935:8.:6:39$:849:*16227.7*65783:2&259- 6290:83:+98-95611)4+7*61:-8091173+ The work by Paquot (2009) had demonstrated that a As a result of the analysis of oxidation ratios, plant recovery MF_AICu_Ratio of >70% in the mixed float ore feed would models, gangue acid consumption, AOR, MF_AICu_Ratio, and improve the recovery. A revision was made to the Mat-Type cut-off grades it was necessary to overhaul the Mat-Type ore ore classification system in 2010 to apply the MF_AICu_Ratio classification system in order to develop a more optimal ore to the classification criteria of mixed float ore. Mixed float ore classification methodology. The ‘OXMAT’ system was that did not meet the MF_AICu_Ratio criterion was directed to developed with the goal of applying it to the ore control long-term stockpiles. process at Kansanshi to supersede the Mat-Type system. A Despite the MF_AICu_Ratio being determined through a flow chart detailing the newly developed ‘OXMAT’ ore logical analysis of available metallurgical data, its application categorization methodology is provided in Figure 10. to the Mat-Type ore classification system was done in The first step in revising the ore classification method and isolation from other factors applied to the same ore types. creating the OXMAT system was to group ore into Therefore, it did not account for the varied range of representative geological domains. Oxidation ratios were mineralogy in the mixed float ore feed, nor the calculated based on the estimated TCu and ASCu block grades misclassification and redirection of high-GAC oxide ore to the of the geological model. Ratio ranges were then applied to the mixed float circuit through the application of the AOR factor. grade control block model, creating three main mineralization While the MF_AICu_Ratio minimized the impact of poorly categories as follows: classified oxide ore entering the mixed float process, it was a ® Sulphide float ore: oxidation ratio <0.1, fresh, reactive solution that did not prevent oxide ore from being unweathered, un-oxidized chalcopyrite incorrectly classified at source in the pit. ® Mixed float ore: oxidation ratio >0.1 and <0.5, secondary sulphides minerals, partial or weak )58..:+46092 weathering, localized moderate oxidation During the review of the Mat-Type ore classification system it ® Oxide leach ore: oxidation ratio >0.5, moderate to was found that a series of fixed grade limits was applied to intense weathering, moderate to intense oxidation. each of the 22 ore types as part of the process of determining The second step was to define more appropriate cut-off whether the ore should be processed or stockpiled. These grades for each of the three categories. These cut-off grades grade limits were linked to the perceived capabilities of the would be required for separating waste from marginal ore, metallurgical process plant at a specific point in time. A low-grade ore, and high-grade ore in each of the three broad mechanism was required to ensure that strategic decisions ore categories. The cut-off grades derived from the Mineral taken in the long-term planning environment would translate Resource to Mineral Reserve conversion process were applied to short-term mine planning and execution. This would allow to the new grade-control ore classification system. This for economic cut-off grades determined in the Mineral brought alignment to the various levels of business planning Resource to Mineral Reserve conversion process to be and assisted in day-to-day ore production and blending updated as and when they changed, thus gaining alignment requirements. Critical to the management of cut-off grades between all of the different technical facets of the business. was the development of a formalized periodic review process L 250   
 VOLUME 119          
Application of geometallurgical modelling to mine planning in a copper-gold mining operation

(7+)49:' %(18$:*/645:49,49293573+:5/9:*61*)165783:18+7*:8.:5/9:39$1&:09#918,90:  849:*16227.7*65783:2&259-

that would allow necessary adjustments to the cut-off grades mined from the deposit between January 2013 and December based on changing economic parameters. 2015 was analysed to determine the quantities of ore and The final development in the new OXMAT ore waste classified by Mat-Type and by OXMAT. Figures 11 and classification methodology was to place an appropriate limit 12 present the results of this analysis, which indicated the on gangue acid consumption in the oxide leach plant by following. using a geological limit that distinguished ore within the ® Tonnes of waste defined by the OXMAT method were marble lithology from ore hosted in the clastic lithologies. Ore 19% less than the tons of waste defined by ‘Mat-Type’ with a GAC >110 kg/t would be directed to the long-term ® Within the volume analysed only 8% of the material stockpiles and recovered as and when there was sufficient was considered as ore suitable for direct feed to the acid available from the on-site smelter, while oxide ore with a process plant using the Mat-Type method. However, GAC <110 kg/t was directed straight to the oxide float/ leach when it was classified using the OXMAT method, ore plant and processed. The resulting ore classification method suitable for direct feed to the process plant increased by now contained only 13 categories compared to the 22 25% categories originally created in the Mat-Type system. ® Despite the substantial increase in the quantity of ore 92)152:.48-:6,,1&73+:5/9:49#7290:849:*16227.7*65783 available for direct feed to the process plant using the 2&259- OXMAT system, the quantity of ore directed to long- term stockpiles remained nearly the same as with Once all the revisions had been incorporated in the ore classification using the Mat-Type method. classification methodology it looked very different to the Through the application of the OXMAT ore classification original Mat-Type classification system. A total of nine ore categories could be completely removed, making the new method, further possible benefits were identified: OXMAT system far more manageable and easy to ® Less material would need to be mined to provide the understand. The remaining 13 ore categories were redefined same quantity of ore feed to the process plant, leading to classify ore more optimally at source, for feeding to the to the opportunity to reduce mining costs metallurgical process plant. A testing process was ® The ore feed was now consistently classified, thus implemented to compare the ore and waste volumes defined removing the need for manual re-directions to be made by the two very different systems. on a daily basis The OXMAT ore classification system was applied to a ® Improved ore quality for all three metallurgical circuits copy of the geological model in conjunction with the Mat- would lead to higher copper recoveries, increasing the Type system. Using survey data, the volume of material value derived from the deposit.

VOLUME 119          
  
 251 L Application of geometallurgical modelling to mine planning in a copper-gold mining operation

mineral processing efficiencies. It is therefore important to have a good understanding of the variability in ore characteristics. Geometallurgical modelling is an integrated approach that assists in overcoming these challenges and generates value-add for an operation. In this paper we presented a case study on geometallurgical modelling for a copper mine producing by-product gold, and provided a review of an ore classification system that was modified through geometallurgical modelling to improve process efficiencies and unlock value. The ore classification system called Mat-Type initially classified the various ore types ranging from ‘poor quality’ to ‘good quality’ into 22 different quality categories. Due to a lack of proper integration between the technical operating silos that formed the mine value chain, the Mat-Type system did not adequately (7+)49:''%91657#9:,48,8457832:8.:849:630:$6259:09.7390:&:5/9:
consider geological, mineralogical, or metallurgical processes  2&259-:$75/73:5/9:#81)-9:8.:-6594761:6361&290 in an integrated way. The system was modified to produce a new geometallurgical ore classification system called OXMAT. Through the application of geometallurgical modelling, nine of the 22 ore categories in the original Mat-Type ore classification system were eliminated. The remaining 13 ore categories were re-defined in the OXMAT system in order to more appropriately classify the ore. By determining a more accurate and consistent set of ore definitions, it was possible to significantly increase the quantity of ore available for direct feed to the process plant, thus demonstrating the value-creating opportunities that can arise out of proper implementation of geometallurgical modelling.

* 38$190+-9352 The work reported in this paper is part of an MSc research study by the first author undertaken in the School of Mining Engineering at the University of the Witwatersrand. (7+)49:'"%91657#9:,48,8457832:8.:849:630:$6259:09.7390:&:5/9 Permission by the management of First Quantum Minerals   2&259-:$75/73:5/9:#81)-9:8.:-6594761:6361&290 Ltd to publish the paper is greatly acknowledged.

Within the volume of ore that was analysed the change in 9.9493*92 BEAUMONT, C. 2016. A geo-metallurgical strategy for improving ore quality and classification method did not directly reduce the quantity of mineral processing efficiency at Kansanshi mine in Zambia. MSc Research ore going to long-term stockpiles, as was originally intended. Report, University of the Witwatersrand. It is, however, reasonable to assume that less ore would be BEAUMONT, C. 2017. Analysis of oxidation ratios in RC and diamond drilling data, a revision in the context of the current OXMAT ore classification. directed to long-term stockpiles in the future if the overall Internal company report. First Quantum Minerals Ltd., October 2017. annual mining volume is reduced. BROUGHTON, D. and HITZMAN, M. 2002. Exploration history and geology of the Kansanshi copper (minor gold) deposit Zambia. Economic Geology Special The implementation of a geometallurgical methodology Publication no. 9. pp. 141–153. Society of Economic Geologists. for ore classification and mine planning promoted the BYE. A.R., 2011. Case studies demonstrating value from geometallurgy development and integration of knowledge between different initiatives. Proceedings of GeoMet 2011: The First AusIMM International Geometallurgy Conference, Brisbane, QLD, Australia, 5-11 September, technical disciplines across the mine value chain. Problems 2011. David, D. (ed.), Australasian Institute of Mining and Metallurgy, and challenges that arise during day-to-day operations can Melbourne. pp.9–30. now be quickly understood and discussed within a large CHIBAYA, A. 2013. Geo-metallurgical analysis - Implications on operating flexibility (A case for geometallurgy for Orapa A/K1 deposit). MSc multi-disciplinary team, leading to effective decision-making Research Report, University of the Witwatersrand. which maximizes the flow of value along the mine value DAWSON, P. and BEAUMONT, C. 2014. Defining variable recovery models using oxidation ratios. Internal company report. First Quantum Minerals Ltd. chain. Through this more collaborative approach that crosses December 2014. traditional technical boundaries, the OXMAT system assists DAWSON, P. and BEAUMONT, C. 2017. A review of Mixed Float tails processing in achieving a more effective mine planning process, and its impact on oxide leach efficiency. Internal company report. First Quantum Minerals Ltd. August 2017. informed by geometallurgical analysis of the available data OGILVIE, J. 2014. Spatial analysis of GAC assay data for the Kansanshi deposit. and centred on the overall mine value chain from the Internal company report. First Quantum Minerals Ltd., November 2014. geological resource through mining, mineral processing, and PAQUOT, F. 2009. The influence of sulphidisation, the addition of dispersant and de-sliming of oxidised ore, on the recovery of the AICu component of smelting. mixed float ores. Internal company report. First Quantum Minerals Ltd., May 2009. 83*1)27832 SILLITOE, R.H., PERELLO, J., CREASER, R.A., WILTON, J., WILSON, A.J., and DAWBORN T. 2017. Age of the Zambian Copperbelt. Mineralium Deposita, vol. 52, Variable ore characteristics pose a challenge in the mining no. 8. pp. 1245–1268, industry as they have a direct impact on the mine-to-mill WOOD, D. 2011. Geological mapping and interpretation of the Kansanshi Dome, Solwezi, North-western Province, Zambia. Internal company report. First design, planning, and operation by reducing the mining and Quantum Minerals Ltd. October 2011. N L 252   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a4 A spatial mine-to-plan compliance approach to improve alignment of short- and long-term mine planning at open pit mines by T.J. Otto1 and C. Musingwini2

term planning processes (McCarthy, 2015). '% ) According to Steffen (1997), most open pit mining operations follow a systematic and The objective of any mining company is to sustainably maximize the net present value (NPV) throughout the life-of-mine (LOM). The expected NPV disciplined mine planning process involving over the LOM is calculated based on a mine plan, yet the actual value three distinct levels of mine planning in realized by the mining company depends greatly on the level of developing the Mineral Reserves. These levels intertemporal execution against the mine plan. Consequently, a major key are the: performance indicator (KPI) that is often overlooked in open pit mining, ® LOM plan due to a greater focus on temporal KPIs, is the degree of spatial compliance ® Long-term plan (LTP), which follows to the mine plan. Such focus sometimes leads to short-term actions being from the LOM detrimental to long-term plans. In this paper we describe the development ® Short-term plan (STP), which in turn and implementation of a spatial mine-to-plan compliance reconciliation approach for an open pit mine. Application to a case study open pit iron follows from the LTP. ore mine in South Africa indicated a significant improvement in the spatial Each of these stages of planning represents mine-to-plan compliance, from 69% to 94% over a three-year period from different levels of risk and has different 2014 to 2016. These results indicate that implementation of the proposed objectives. The planning horizons for the spatial mine-to-plan compliance reconciliation approach can contribute different stages are also broadly referred to as positively to improving the level of spatial execution and assists in the strategic, tactical, and operational planning improving the alignment between short-term, medium-term, and levels (Tholana and Neingo, 2016). LOM plans. Literature on mine planning generally -(%$
 focuses on ways of improving mine plans by intertemporal compliance, spatial compliance, short-term plan, long-term incorporating the analysis and evaluation of plan, LOM plan. risk into the planning process, thereby improving the expected NPV and/or risk- adjusted NPV of the mine. The literature deals ,'"$%
!")%' mainly with the strategic level of mine The objective of any mining company is to planning. Various studies have been devoted maximize the net present value (NPV) to improvements in the mine planning process throughout the life of mine (LOM). However, with the aim of developing optimal mine plans. this objective needs to be fulfilled in a These include advances in mine planning sustainable manner that considers the needs of software and related systems that are various stakeholders, including employees, employed in mine planning (Gurgenli, 2011) shareholders, and local communities where the and the application of orebody flexibility to mines operate. The expected NPV is calculated ensure maximum mineral asset utilization in using a mine plan as a basis. Mine planning underground mining applications (Tholana broadly involves identifying a strategy to and Neingo, 2016), as well as the progression exploit the mineral resource in a way that of stochastic mine planning techniques. Where maximizes value at an acceptable level of risk stochastic approaches have been applied, they have proven to be able to add higher value in throughout the LOM (Tholana and Neingo, production schedules – in the order of 25%, 2016). The mine planning process is a well- recognized component in the mining value chain of an open pit mine. Figure 1 reflects the relative position of mine planning within a typical open-pit mining value chain from the 1 Anglo American Kumba Iron Ore, Corporate mineral resource to the market. Office, Centurion South Africa. 2 School of Mining Engineering, University of the The mine planning process begins with a Witwatersrand, South Africa. sequence of increasingly detailed feasibility © The Southern African Institute of Mining and studies and continues throughout the life of Metallurgy, 2019. ISSN 2225-6253. Paper received the mine through several long-term and short- Sep. 2018.

VOLUME 119          
  
 253 L A spatial mine-to-plan compliance approach to improve alignment

)$(*)')'* &#(*!&)'*$% *$(%$!(*"%* &$ (" with consequent improvements of up to 30% in the NPV operate a large open pit mine two major areas need to be compared to conventional approaches to mine planning managed; namely the quality and integrity of the mine (Dimitrakopoulos, 2011). planning process and the execution of the mine plan. The Despite significant improvements in the mine planning importance of execution against the mine plan is also process and the resultant mine plans, open pit mining highlighted by Musingwini (2016); operations are measured remains a high-risk business (Sabour and Dimitrakopoulos, against planned targets in order to evaluate operational 2008). There are numerous sources of risk, and these can be performance. grouped as: The level of execution or compliance against a mine plan ® External uncertainties such as volatile commodity can be measured in two ways – time-based or temporal prices and exchange rates measurements, and area-based or spatial measurements. The ® Internal uncertainties such as geology, chemical quality measurement of performance against temporal metrics is predictions, operational uncertainties, and input cost. common practice in the open pit mining industry and these Open pit mines are dynamic environments that are time-based targets are typically short-term focused. The characterized by a continuous displacement of the working measurement of performance against spatial metrics is faces both in time and space (Halatchev and equally important in an open pit mine. These area-based Dimitrakopoulos, 2003). The existence of risk (and metrics provide insight into the long-term aspects of opportunity) in open pit mining is evident when considering execution against the mine plan. The development and the differences between the expected and actual outcomes implementation of a spatial mine-to-plan compliance process achieved by mining projects and operating mines. This was is important to ensure: noted from benchmark studies considering mainly Australian ® Long-term sustainable ore supply mining operations. A survey of 48 Australian mining projects ® That key issues adversely impacting on mine showed that the actual tonnages extracted for 46% of these production are identified (e.g. ramp establishment, mines were more than 20% higher or lower than those dewatering, drill-and-blast quality, pre-split and buffer expected (Sabour and Dimitrakopoulos, 2008). Benchmark blocks) studies of 21 open pit mines by AMC Consultants evaluating ® The achievement of planned mining flexibility. the monthly variability between the mine budget and actual Previous studies on spatial mine-to-plan compliance have production over a 12-month period showed an average been done in mining environments other than open pit variability of 29% for ore tonnes mined (McCarthy, 2015). mining and have mainly focused on short-term plans. For Ramazan and Dimitrakopoulos (2004) indicated that about example, Angelov and Naidoo (2010) described a two- 60% of the mines surveyed had an average rate of production dimensional (2D) spatial mine-to-plan compliance approach in the early years of operation that was less than 70% of the that determines the degree of deviation from the original designed production capacity. The failure to have actual short-term mine plans in underground coal mines by outcomes close to or the same as planned targets is widely comparing actual mined areas to initially planned mining acknowledged in the mining industry as a top risk areas. Morely and Arvidson (2017) proposed a spatial mine- (Musingwini, 2016). to-plan compliance approach that determines spatial Ultimately, the actual value realized by the mining comparison of volumes measured monthly against the short- company (as opposed to the expected value) is not only term plan. The purpose of this paper is to describe the dependent on the quality and integrity of the mine plans; it development and implementation of a standardized spatial also depends greatly on the level of execution against the mine-to-plan compliance reconciliation approach at an open mine plan. The effective execution of the agreed-upon mine pit mine by comparing planned and actual tonnages in three plan is therefore critical to the successful operation of an dimensions (3D) instead of just comparing volumes and open pit mine (Hall and Hall, 2006). In order to sustainably aligning short-term plan execution to long-term plans. L 254   
 VOLUME 119          
A spatial mine-to-plan compliance approach to improve alignment

.*"$&! * &")&#* )'("% #&'*!% #)&'!(+ KPIs that mining companies track on a weekly, monthly, quarterly, and annual basis and the long-term value expected To achieve the goal of creating long-term value, mining by (and often promised to) stakeholders. companies (with operational mines) typically develop short- term measures of value against which operational and )'("% #&'*!% #)&'!(* %
(# financial performance are tracked. As a result, many time- based or temporal key performance indicators (KPIs) are The spatial mine-to-plan compliance at an open pit mine can developed and tracked by mining companies. be measured effectively when the following major One grouping of KPIs is concerned with reconciling components are in place: a quality mine plan, a process of planned activities with what actually happened. Conducting capturing and analysing actual mining progress spatially, and reconciliation across the mining value chain ensures that the definitions or categories for reconciling the actual areas mining process occurs in a progressively more predictable mined with the planned mining areas. These aspects are manner (Bester et al., 2016). Reconciliation in the open pit explained in the following sections. mining industry is a broad subject and is usually associated  
  with comparing the results of planned versus actual activities As a start, it is important to define ‘the plan’ against which for temporal KPIs such as the waste production, plant spatial mine-to-plan compliance is measured. The tactical production, and chemical and physical qualities of the horizon of mine planning normally involves the development product for the specific time period under review. The main of annual tactical plans (also referred to as budget plans, reason for undertaking these reconciliations is performance business plans, or medium-term plans). These plans are tracking with the purpose of operational improvement. successors of feasibility studies and LOM plans, and Consequently, a major KPI that is often overlooked in the predecessors of operation plans (Phillis and Gumede, 2011). open pit mining industry is the level of spatial compliance to These annual production schedules are a critical factor in the the mine plan, which measures how well the mine plan is planning of open pit mines. They deal with the effective executed spatially. This requires considering not only what is management of a mine’s production and cash flows in the being mined and when, but also where the mining activities order of millions of dollars (Ramazan and Dimitrakopoulos, are taking place in the open pit. This is important because 2004). The reason for focusing on the tactical mine plan is mining in areas outside of the planned areas can affect future that this plan is typically the basis for annual budgets and, as waste stripping or advance into future production areas too such, it sets annual operational and financial performance early. targets. Management is expected to deliver against annual Hall and Hall (2015) stated that the major focus of high- mine plans – these plans are a form of contract between a performing open pit mines should be on delivering the mine and its stakeholders (Phillis and Gumede, 2011). The operational and financial targets according to the tactical tactical plan provides the bridge between strategic mine mine plan, without compromising the mine’s ability to deliver planning and operational planning and translates the on its future KPIs. The difference (if any) between planned expected long-term value (often expressed as NPV) into and actual performance should therefore be regularly operational and financial targets such as monthly production measured and monitored. The monitoring of compliance with tonnes, product quality, unit cost, and revenue projections. the mine plan should also consider spatial aspects. It is Importantly, it remains a mining plan and therefore also important to identify where material has been mined to prescribes the spatial development of the open pit mine. ensure that the progress of mine development is adequate to For these reasons, the annual tactical plan produced for meet long-term strategic targets such as timely access to an open pit mine is used as the basis for tracking the spatial future ore (Hall and Hall, 2015). An unbalanced focus on mine-to-plan compliance. The minimum output required from short-term temporal KPIs such as productivity improvements the tactical plan is stage plans for the agreed-upon measuring or unit cost reduction at the expense of spatial compliance period (typically monthly) per mining area (or pushback) and with the mine plan could lead to the prioritization of mining bench. The stage plans are typically provided in the inappropriate mining activities in the wrong mining areas. format of a digital terrain model (DTM) indicating the areas The development and implementation of a spatial mine- planned for mining per month. In addition, ore and waste to-plan compliance reconciliation approach is of critical tonnages for these areas are calculated from the applicable importance in an open pit mine, as it ensures that short-term mining model, which contains the appropriate geological KPIs are achieved by identifying key factors negatively information for these areas. These outputs are typically impacting on mine production while giving adequate generated using mine scheduling software and a suitable consideration to long-term KPIs such as sustainable ore general mining package (GMP). supply and the achievement of planned mining flexibility. An evaluation of the operational performance of an open    pit mine that considers only temporal KPIs, such as monthly In an open pit mine the survey department is typically ore and waste tonnages mined, can provide a false sense of responsible for capturing and analysing actual spatial mining security to mine management as performance against these progress. Best practice in data acquisition involves the use of KPIs could be positive while mining activities are not laser scanners to conduct month-end ex-pit production occurring in the correct spatial areas in the open pit, to the measuring surveys. Riegl and Maptek scanners exceed the detriment of long-term KPIs such as timely exposure of minimum requirements for the spatial accuracy of surveyed future ore. Spatial mine-to-plan compliance is therefore a data-points and are currently considered industry-leading critical KPI as it provides a bridge between the short-term technologies. Scanners and associated global positioning

VOLUME 119          
  
 255 L A spatial mine-to-plan compliance approach to improve alignment system (GPS) equipment are checked and calibrated on a envisaged in the tactical plan and the incremental (or weekly basis to ensure their spatial accuracy is within 50 monthly) areas within the bigger tactical plan. This mm. Although Total Stations are also still utilized, laser introduces the concepts of in-sequence and out-of-sequence scanning technology is preferred due to its speed, accuracy, mining as subsets of mining within the tactical plan. Actual density of survey points captured, and the ability to work mining is deemed to be in sequence when it took place within effortlessly in a 3D environment. the areas indicated in the tactical plan up to the date of The laser scanning process involves the continuous measurement. Actual mining is deemed to be out of sequence scanning of open pit working areas during the production when it took place within the areas indicated in the tactical month and again at month-end. The working areas are plan but after the date of measurement. For example, for the typically scanned in a ‘stop-and-go’ mode from three reconciliation process done at the end of month six of a positions to ensure accurate spatial registration of the specific year, all actual mining activities that took place in scanned data as well as complete coverage of the working areas planned for months one to six are deemed in sequence, areas. These working area scans are then registered and a while actual mining activities that took place in areas report is generated which states the spatial accuracy achieved planned for months seven to twelve are deemed out of for the scans. A survey DTM of the pit is then generated by sequence. The categories used for reporting spatial mine-to- combining all the individual scans. The survey DTM plan compliance are described in Table I and illustrated in represents the actual pit surface at the time of measurement. Figure 2. By comparing the latest survey DTM with the DTM developed Compliance measurement per category is calculated as a at the start of the measuring period (month), areas where tonnage compliance and expressed as a percentage of mining took place during the month under evaluation, can be planned tonnes for ore, waste, and total material mined. identified. )'("% #&'*!% #)&'!(*$(!%'!)#)&")%'* $%!(        The components of the mine-to-plan compliance model  described above provide the basis from which the The spatial data can now be analysed in order to reconcile the reconciliation process can be managed. The detailed steps of actual mined areas with the planned areas in 3D space. the reconciliation process are presented in the following Actual and planned mining areas are then divided into three sections. categories: ‘mined in plan’, ‘mined out of plan’, and the resultant ‘planned areas not mined’. The reconciliation is   done by considering both the total (or annual) area The spatial compliance against the tactical mine plan is

Table I &"(%$)(*%$*!&#!#&")'* &")&#* )'("% #&'*!% #)&'!(

&"(%$ (!$) ")%'%#%$*!%
(

Planned and mined in sequence Areas that were planned to be mined and were mined in sequence. Green Planned and mined out of sequence Areas that were planned to be mined but were mined out of sequence. Yellow Mined out of plan Areas that were mined completely outside of the tactical plan. Red Planned not mined Areas that were planned to be mined but not mined. Brown

)$(*&"(%$)(*%$*!&#!#&")'* &")&#* )'("% #&'*!% #)&'!( L 256   
 VOLUME 119          
A spatial mine-to-plan compliance approach to improve alignment

)$(* ( %$")'*%*! #&") (* &")&#* )'("% #&'*!% #)&'!(*"($('* 

reported on a monthly basis using the categories described in considering how these areas should be prioritized in future Table I. The reporting format consists of graphs in which the operational plans. The plans also assist in understanding the spatial compliance is expressed as a percentage of planned reasons for adverse outcomes with the aim to improve future tonnes mined. This allows for evaluation of the year-to-date mine-to-plan compliance. compliance as well as the assessment of trends in the spatial mine-to-plan compliance over a given period of time. Figure 3 illustrates an example of the reporting of spatial mine-to-plan compliance on a cumulative monthly basis. From the information provided in Figure 3 the following interpretation can be made using the mine-to-plan compliance data. 1. The actual tonnes mined for the seven month period is 102% of the planned tonnes 2. 79% of the mining took place in the areas planned to date (mined in sequence) 3. 14% of actual mining took place within the areas planned in the tactical plan but after the date of measurement (mined out of sequence) 4. 9% of mining took place outside of the tactical plan (mined out of plan). In addition, the monthly trend provides further insight into month-on-month changes in compliance to the tactical mine plan. The major implication of below-targeted spatial mine-to-plan compliance is the fact that planned areas are not mined (i.e. mining capacity is not applied spatially in line with the tactical plan). This impacts negatively on the open pit mine’s ability to achieve operational (production and product quality) and financial targets. The reporting is further enhanced with plans per mining area illustrating the reconciliation between areas planned and areas where actual mining took place (Figure 4) by using the categories in Figure 2. Although these plans allow for further analysis of the areas actually mined, the real value lies in )$(* #&'*%)'* &")&#* )'("% #&'*!% #)&'!( evaluating the areas that were planned but not mined and $(!%'!)#)&")%'*$(#"*&"*)('*)$%'*%$(* )'(*' &'* 

VOLUME 119          
  
 257 L A spatial mine-to-plan compliance approach to improve alignment

It is important to note that the mine-to-plan compliance iron ore Mineral Reserve was approximately 500 Mt and the reconciliation results should not be considered in isolation. LOM stripping ratio approximately four times. The Sishen pit These results should be included in a consolidated is a conventional open pit, truck-and-shovel operation. In performance dashboard for an open pit mine that provides a 2017, a total of 162 Mt of waste material was mined at holistic view of the mine’s technical and financial Sishen, making it the single biggest open pit mine in performance against temporal and spatial short-term and southern Africa on a tonnes per annum basis. Both dense long-term KPIs. medium separation and jig processing plants are employed and the annual product output in 2017 was 31.1 Mt.  The spatial mine-to-plan compliance methodology was Target setting is of paramount importance for the successful introduced at Sishen during 2013. The focus of the mine-to- management of spatial mine-to-plan compliance. It is plan compliance reconciliation model and process is to track important to select targets that reflect industry best practice spatial compliance against the annual business plan (tactical while taking account of historical performance, levels of plan) agreed upon as part of the annual business planning flexibility in the open pit mine, as well as practical cycle. considerations. For the purpose of explaining the process and Spatial mine-to-plan compliance reconciliation takes place based on acceptable results achieved, the target for spatial through a well-established monthly management routine mine-to-plan compliance against the tactical plan is set at a using the model and process discussed in this paper. At minimum of 85% in-sequence mining and a maximum of Sishen, the mine-to-plan compliance results form part of a 15% mining outside of the tactical plan. The targets should technical key success factor (TKSF) dashboard that is used to be refined as the mine-to-plan compliance process is measure and manage the technical health of the mine. embedded. The effectiveness of the proposed approach is demonstrated in Figure 5, which shows the Sishen spatial    mine-to-plan compliance reconciliation results for 2014, Spatial deviations from the mine plan (positive and negative) 2015, and 2016. occur when either the quality of the mine plan is not on Figure 5 demonstrates that, using the approach discussed standard or the execution against the mine plan is not in this paper, the spatial mine-to-plan compliance at Sishen adequate. In an open pit mine, spatial deviations from the improved from 69% to 94% over the three-year period up to mine plan typically occur for two main reasons. Firstly, when 2016. This illustrates the benefits of implementing spatial the assumptions used as input to the development of the mine-to-plan compliance reconciliation and incorporating this tactical mine plan are not achieved in practice (or are KPI into the TKSF dashboard of an open pit mine. incorrect). Examples include assumptions on the vertical rate of advance, loading and hauling equipment productivity, and %'!#)%' assumptions regarding equipment allocated to critical An approach for measuring and managing the spatial mine- secondary tasks. Actual mining therefore remains spatially to-plan compliance against the tactical mine plan has been on plan but takes place at a different rate from the planned presented. The approach incorporates a model providing rate. This normally manifests as actual in-sequence mining mine-to-plan reconciliation categories as well as a spatial being higher or lower than planned. If not managed, it could reconciliation process focusing on reporting, target setting, lead to actual mining activities taking place out of sequence and analysis of the reasons for deviations. The aim of the and out of plan. Secondly, this occurs when short-term approach is to improve the spatial execution against the technical or financial objectives are prioritized at the expense tactical mine plan in an open pit mine. Application of the of the spatial execution of the tactical mine plan. Examples approach will contribute to the achievement of an open pit include cutting back on waste stripping to improve short-term mine’s operational and financial targets (derived from the unit cost and targeting an unplanned mining area to reduce tactical mine plan) while maintaining the mine’s ability to short-term hauling distances. Here, actual mining is not deliver on its future KPIs, thereby contributing towards spatially honouring the tactical plan. If not managed properly, meeting the ultimate objective of maximizing the NPV then out-of-sequence and out-of-plan mining takes place and throughout the LOM in a sustainable way. the areas planned and not mined increase as a result. A case study at the Sishen iron ore mine, South Africa Adverse outcomes are highlighted as part of the monthly illustrated how the implementation of the spatial mine-to- reporting routines and should be viewed as opportunities for plan compliance approach contributed positively to improving the quality of mining plans and to an improved improvement of either the quality of the next tactical mine understanding of the major reasons for non-compliance. This plan or the quality of spatial mining execution against the led to a significant improvement in the spatial mine-to-plan plan. The operational or short-term planning horizon is compliance from 69% to 94% over the three-year period from utilized to manage improved spatial compliance by directing 2014 to 2016, inclusive. mining to areas planned and not yet mined. /! '%#(
( ('" / #)!&")%'*)'*&'*% ('* )"*)$%'*%$(* )'( The work reported in this paper is part of a current PhD The spatial mine-to-plan compliance approach discussed research study in the School of Mining Engineering at the above was implemented at the Sishen iron ore mine in the University of the Witwatersrand. The permission granted by Northern Cape Province of South Africa. Sishen is operated the management of Anglo American Kumba Iron Ore to by Anglo American Kumba Iron Ore. At the end of 2017 the publish the paper is greatly appreciated. L 258   
 VOLUME 119          
A spatial mine-to-plan compliance approach to improve alignment

)$(* &")&#* )'("% #&'*!% #)&'!(* ($%$ &'!(*)('*)$%'*%$(* )'(*' &'* 

(($('!( operation. Proceedings of Metallurgical Plant Design and Operating Strategies (MetPlant 2015), Perth, WA, 7–8 September 2015, ANGELOV, A.A. and NAIDOO, K. 2010. Plan compliance process for underground Australasian Institute of Mining and Metallurgy, Carlton, Victoria. coal mines. Journal of the Southern African Institute of Mining and pp. 35–45. Metallurgy, vol. 110, no. 5. pp. 241–250. MORLEY, C. and ARVIDSON, H. 2017. Mine value chain reconciliation - BESTER, M., RUSSELL, T., VAN HEERDEN, J., and CAREY, R. 2016. Reconciliation of demonstrating value through best practice. Proceedings of the Tenth the mining value chain - mine to design as a critical enabler for optimal International Mining Geology Conference, Hobart, Tasmania, 20–22 and safe extraction of the mineral reserve. Journal of the Southern African September 2017. Australasian Institute of Mining and Metallurgy, Carlton, Institute of Mining and Metallurgy, vol. 116, no. 5. pp. 407–411. Victoria. pp. 279–292.

DIMITRAKOPOULOS, R. 2011. Stochastic optimisation for strategic mine planning: MUSINGWINI, C. 2016. Presidential Address: Optimization in underground mine A decade of developments. Journal of Mining Science, vol. 47, no. 2. planning - developments and opportunities. Journal of the Southern pp. 138–150. African Institute of Mining and Metallurgy, vol. 116, no.9. pp. 809–820.

ESTERHUYSEN, W.D. 2013. Progress update on mine planning reconciliation in PHILLIS, R.C.D. and GUMEDE, H. 2011. Annual mine planning and execution Kumba. Kumba Iron Ore, internal memo, June 2013. pp. 1-8. buffering - a safety imperative. Journal of the Southern African Institute GURGENLI, H. 2011. Implementing an efficient mine planning system. of Mining and Metallurgy, vol. 111, no. 8. pp. 565–572.

Proceedings of the SME Annual Meeting, 27 February - 2 March 2011. RAMAZAN, S. and DIMITRAKOPOULOS, R. 2004. Uncertainty-based production pp. 1–3. scheduling in open pit mining. Transactions of the Society for Mining, HALATCHEV, R. and DIMITRAKOPOULOS, R. 2003. On the dynamics of mining Metallurgy and Exploration, vol. 316. pp. 106–112.

operations in open pit mines. International Journal of Surface Mining, SABOUR, A. and DIMITRAKOPOULOS, R. 2008. Mine design selection under Reclamation and Environment, vol. 17, no. 4. pp. 246–263. uncertainty. Mining Technology, vol. 117, no. 2. pp. 53–64.

HALL, A. and HALL, B. 2006. Doing the right things right - Identifying and SNYMAN, W.J. 2017. Mine-to-plan compliance improvement journey. Internal implementing the mine plan that delivers the corporate goals. Proceedings presentation, Kumba Iron Ore Company, July 2017. pp. 1-6. of the International Mine Management Conference, Melbourne, Victoria, STEFFEN, O.K.H. 1997. Planning of open pit mines on a risk basis. Journal of 16-18 October 2006. Australasian Institute of Mining and Metallurgy, the South African Institute of Mining and Metallurgy, vol. 97, March/April Carlton, Victoria. pp. 119–128. 1997. pp. 47–56. HALL, A. and HALL, B. 2015. The role of mine planning in high performance. THOLANA, T. and NEINGO, P.N. 2016. Extending the application of PAS 55/ISO AusIMM Bulletin, August 2015. pp. 68–71. 55 000 to mineral asset management. Journal of the Southern African MCCARTHY, P.L. 2015. Integrated mining and metallurgical planning and Institute of Mining and Metallurgy, vol. 116, no. 11. pp. 1043–1050. N

VOLUME 119          
  
 259 L We strive to offer you the lowest cost of ownership

Weir Minerals is a leading designer and manufacturer of mine dewatering solutions, slurry pumps, hydrocyclones, valves, screens, centrifuges, crushers, feeders, washers, conveyers, rubber lining, hoses and wear- resistant linings for the global mining and minerals processing, sand and aggregate, and power and general industrial sectors. For more information contact us on +27 11 9292600

Minerals www.minerals.weir www.weirafricastore.com

Copyright © 2016, Weir Slurry Group, Inc.. All rights reserved. http://dx.doi.org/10.17159/2411-9717/2019/v119n3a5 Evaluation of government equity participation in the minerals sector of Tanzania from 1996 to 2015 by P.R. Lobe1, A.S. Nhleko1, and H. Mtegha1

It is important to note that the establishment of mines depends on the (0?<29@9 mineral resources being economically viable. Government’s equity role in the minerals sector is one of the nationalist Mines provide local citizens with secure measures implemented in order to ensure greater control and management employment and local content opportunities, of a country’s mineral resources. This paper evaluates the Tanzanian government’s equity participation in the minerals sector from 1996 to raising their income and quality of life. Mineral 2015. The research methodology included determination of the number of exploitation is also a source of government mineral rights, minimum allowable exploration expenditures in revenue when mines produce or recover prospecting licences (PLs), and forms of equity role of the government. minerals resources through their value chains Data was collected and analysed for PLs, mining licences (MLs), and to the selling points. special mining licences (SMLs). Production and selling of mineral products The study revealed a number of challenges faced by the Tanzanian enable government to collect revenue through government as regards its equity strategy in the mineral sector. One of the royalties, corporate income taxes, and other major challenges was the secrecy surrounding agreements and contracts legal means (Otto et al., 2006; Wise and entered into between the government and private sector investors, which Shtylla, 2007). Where there are good were concluded via various business ownership and mineral development government policies, the minerals sector can projects. This secrecy resulted in non-transparency and lack of accountability in the mining industry. integrate with other sectors of the economy to The financial benefits accruing to the government were inadequately establish downstream industries (Highley, realized, evident through inconsistent payments of corporate income tax Chapman, and Bonel, 2004; Ministry of Energy and mining royalties by the mining companies. Furthermore, the and Minerals, 2009). Good government government does not have solid mechanisms and frameworks for policies are defined as implementable plans or assessing non-financial benefits, thus it is difficult to measure the impact courses of action to influence and determine of these factors. decisions, actions, and other matters in the It is recommended that the Tanzanian government review the Mining interest of the country (Businessdictionary, Act and Regulations of 2010 to include the provision of solid mechanisms 2017; Free Dictionary, 2017; Bendiola, 2013). and frameworks for all forms of government equity role. Since the inception of the Mining Act of This paper is based on an MSc research study undertaken at the University of the Witwatersrand. 2010 and the Tanzanian government’s mandate to the State Mining Corporation CA0 <=39 (STAMICO) to oversee government interests in Tanzania, minerals sector, government participation, equity role, joint prospecting, and medium- and large-scale venture. mining, there has been no study to evaluate the equity role of the government in the minerals sector. A mining operation with a capital investment between US$100 000 and US$100 million or the equivalent amount in ?:=<367:@

VOLUME 119          
  
 261 L Evaluation of government equity participation in the minerals sector of Tanzania equity role performance of the Tanzanian government in Tanzania plays a significant role in the global mining prospecting, and medium- and large-scale mining been since industry, supplying: the enactment of Mining Act of 2010?’ In order for this ® 1.6% of the world’s gold, making it the 15th largest research study to make a meaningful contribution, the period producer (Yager, 2013; Mineweb, 2015) from 1996 to 2015 was investigated. ® 166 500 carats of diamond in 2013/2014, making it 13th in the globe (US Geological Survey, 2015). This ->?>?@>?B8@?A=>;9BA?3< 8A?:B>?3B8@?A9 production was 0.23% of the annual total average This section discusses the nature, quality. and quantity of production of 72.35 million carats ® mineral resources and quantity of known mineral reserves. Tanzanite – the only producer in the world (Ihucha, Tanzania’s minerals endowment includes gold, tanzanite, 2014; Yager, 2013). diamonds, coal, uranium, iron ore, gemstones, and copper. These mineral deposits exist in stratigraphic formations such as Cenozoic volcanics, the Ubendian Belt, greenstone belts, and Archean cratons, to mention a few (Figure 1). According to the Ministry of Energy and Minerals (2010), there are five groups of commodities that exist in Tanzania. These comprise: ® Metallic minerals such as gold, nickel, tin, rare earth elements, iron ore, copper, lead, and the platinum group metals (PGMs) ® Gemstones such as diamonds, tanzanite, ruby, emerald, and sapphire ® Industrial minerals such as phosphate, gypsum, limestone, kaolinite, graphite. and bauxite ® Building materials such as stone, sand, aggregates, gravel, and fireclay ® Energy minerals, including uranium and coal. In Tanzania, information pertinent to geology and geophysics useful for assisting investors in selecting areas for prospecting is available from the Geological Survey of Tanzania (GST) Dodoma. Geological mapping has covered 90% of the country (Ministry of Energy and Minerals, 2015). According to the Ministry of Energy and Minerals (2015), mineral prospecting operations carried out between 1990 and 2015 have revealed reserves of approximately 2200 t of gold and 5 Gt of coal (see Figure 2a). Other mineral reserves are depicted in Figure 2b. $@46=AB&!)@?A=>;B=A9A=.A9B@?B->?>?@>

$@46=AB%!A<;<4@7>;B:A==>?A9B>?3B9A;A7:A3B8@?A=>;B<776==A?7A9B@?B->?>?@>B*)9>/>1>B&,,+ L 262   
 VOLUME 119          
Evaluation of government equity participation in the minerals sector of Tanzania

The tanzanite industry has not flourished in Tanzania has declared closure of the corporation, while de-specification despite its long history. This is due to the following reasons refers to the reversal of the order to close a public (Ihucha, 2014; Rimoch and Cherng, 2013; Dodgson, 2016): corporation. After the companies under government holding ® The continuing practice of exporting rough tanzanite corporations had been placed in receivership or liquidated, ® Inadequate and inefficient jewellery cutting centres STAMICO was listed in August 1997 as a specified public ® High rate of tanzanite smuggling corporation under PSRC. This was after its closure in April ® Tax evasion 1996 (Ministry of Finance and Planning, 1992; Ngonyani ® Lack of political will for implementing regulations in 2014). As STAMICO became a specified public corporation, the tanzanite sector. all its rights, privileges, powers, duties, or functions were vested in the board of directors. The board of directors then In Tanzania, from 1996 to 2015, there were nine active waited for STAMICO’s shares to be allotted or sold by the mines (Mwihava and Masanja, 2015; Tanzania Minerals government (Ministry of Finance and Planning, 1992). Audit Agency, 2016a). These included six large-scale mines However, the government delayed the decision to allot or sell and three medium-scale mines (Table I). STAMICO, causing it to survive from 1996 until 2008. During this period, STAMICO concentrated on the provision of .<;6:@?>?@>?B8@?A=>;B9A7:<= contract drilling services, consultancy work, property rental income, acquisition of mineral rights, and joint venturing %#(!$'($($'!& '&#(%&(#'( %&'!"(' #$! (Ngonyani, 2014). Furthermore, during the same period, '$!'(  there were recommendations in 2008 from the Justice Mark In 1992, the Tanzanian government enacted the Public Bomani Commission’s Report favouring restoration of Corporations Act of 1992 to replace the Public Corporations STAMICO rather than its closure. The government then Act of 1969 (Ministry of Finance and Planning, 1992). This decided to restore STAMICO (Bomani, 2008). De-specification action was due to the underperformance of parastatals during of the corporation took place in April 2009 with the socialism and the self-reliance policy between 1967 and the publishing of a de-specification order in the Government late 1980s. Underperformance of parastatals was attributed Gazette (State Mining Corporation, 2014). to lack of local expertise, lack of managerial skills, "&'(%&(#'("& "&%"&( %&'!"(' #$!(!$ (  embezzlement, bureaucracy, capacity underutilization, loss- making, reliance on government subsidies, non-payment of #$(  taxes, overemployment and monopolistic behaviour of the In 1996, the government realized that the Mining Act of 1979 operation, and huge debts (Muganda, 2004; Ngowi, 2009). had failed to attract local and foreign mining investment. In 1993, the Tanzanian government established the This, coupled with economic reforms undertaken by the Presidential Parastatal Sectoral Reform Commission (PSRC) government between the late 1980s and early 1990s, to be in charge of privatization of state-owned organizations prompted the government to change the legislation (Tanzania (Twaakyondo, Bhalalusesa, and Ndalichako, 2002; Muganda, Minerals Audit Agency, 2016b; Muganda, 2004; Ngowi, 2004). Under the Public Corporations Act of 1992, all 2009; Weir, n.d.). The aim was to attract investors and bring companies under government holding corporations were into the country capital, technology, and expertise (Tanzania transferred to the Treasury Registrar (TR) for privatization Minerals Audit Agency, 2016b). This resulted in the through the PSRC. This action affected all companies under government endorsing the Minerals Policy of 1997 and the State Mining Corporation (STAMICO), which were Tanzania Mining Act of 1998 (State Mining Corporation, transferred to the TR and were kept under receivership or 2016; Ministry of Energy and Minerals, 2009). Other notable liquidated (Muganda, 2004; Ngonyani, 2014). Consequently, changes were the formulation of fiscal incentives aimed at STAMICO was closed in April 1996. attracting both local and foreign investors, and the opening of six large-scale mines as indicated in Table II. ' %% "#%$&("&('' %% "#%$&($(
This development brought about an increase in gold Specification of a public corporation means that the minister production from less than 1 t/a in 1998 to over 45 t/a in

Table I >=4AB>?3B8A3@68B97>;AB8@?A9B@?B->?>?@>B>9B<5BA7A8/A=B&,%

'<82>?0 2=<A7: (7>;AB =<367: @9:=@7: '<88@99@=

Merelani tanzanite mine (MTM) also known as TanzaniteOne tanzanite mine (TTM) Medium Tanzanite Simanjiro 2001 Ngaka coal mine (NCM) Medium Coal Mbinga 2012 New Luka gold mine (NLGM) Medium Gold Chunya 2012 Bulyanhulu gold mine (BGM) Large Gold Kahama 2001 Buzwagi gold mine (BZGM) Large Gold Kahama 2009 Geita gold mine (GGM) Large Gold Geita 2000 North Mara gold mine (NMGM) Large Gold Tarime 2002 Stamigold Biharamulo Mine (SBM) formerly known as Tulawaka Gold Mine (TGM) Large Gold Biharamulo 2005 Williamson diamonds mine (WDM) Large Diamond Kishapu 1940

Source: Mwihava and Masanja (2015); Tanzania Minerals Audit Agency (2016a)

VOLUME 119          
  
 263 L Evaluation of government equity participation in the minerals sector of Tanzania

Table II ® Inadequate capacity to administer the sector ® Inadequate infrastructure such as roads, reliable power )@?A9BA9:>/;@91A3B@?B->?>?@>B/A: AA?B% B>?3 supply, and communications to support the sector &,, ® Low level of value addition ® Growing negative public perception of the minerals )@?A 2=<A7: A>= (:>:69 sector. This is a result of the low contribution in both 7<88@99@;B=@41:9B< ?A3B/0B:1AB->?>?@>?B4<.A=?8A?: US$2.5 billion in 2007 (Ministry of Energy and The analysis of all mineral rights owned by the government Minerals, 2009) focused on prospecting licences (PLs), mining licences, (MLs) ® Increased mineral exports value from US$26 million and special mining licences (SMLs) partially and wholly in 1997 to US$420 million in 2002, as indicated in owned by STAMICO and NDC and TR. Figure 4 indicates that Figure 3 (Msabaha, 2006). STAMICO has 17 partially owned and 20 wholly owned Despite these achievements, Msabaha (2006) and the mineral rights from 1996 to 2015. STAMICO’s partially Ministry of Energy and Minerals (2009) highlighted major owned mineral rights comprised 13 PLs, 2 MLs, and 2 SMLs challenges as: while wholly owned rights included 19 PLs and 1 SML. The ® Low level of integration of the minerals sector with targeted minerals were gold, tanzanite, phosphate, rare earth other sectors of the economy elements (REEs), gypsum, kaolinite, feldspar, and coal.

$@46=AB !->?>?@>9B8@?A=>;BA2<=:9B5=<8B%,B:/>1>B&,,+ L 264   
 VOLUME 119          
Evaluation of government equity participation in the minerals sector of Tanzania

$@46=AB!)@?A=>;B=@41:9B2>=:@>;;0B>?3B 1<;;0B< ?A3B/0B(-)'

Companies that owned mineral rights from 1996 in relation to the government equity role in the mining industry are presented in Figure 7. Each indicator in Figure 7 comprises the mineral type, type of mineral right, and percentage of ownership by the shareholder(s). It is deduced

$@46=AB!)@?A=>;B=@41:9B2>=:@>;;0B>?3B 1<;;0B< ?A3B/0B'

Figure 5 shows that NDC had 46 partially owned and 33 wholly owned mineral rights from 1996 to 2015. The partially owned mineral rights consisted of 43 PLs, one ML, and two SMLs and wholly owned rights were 22 PLs. The targeted minerals included coal, iron ore, dolomite, soda ash, $@46=AB!(1>=A1<;3A=9B<5B- B>?3B-')B2=@.>:AB<@?:B.A?:6=AB*
+ 7<82>?@A9B>?3B8@?A=>;B=@41:9 and all minerals other than building materials and gemstones (AOBG) and gold. NDC played its role in the minerals industry by entering into joint ventures with Intra Energy Tanzania Limited (IETL) and Sichuan Hongda Group (SHG) of China through Tancoal Energy Limited (TEL) and Tanzania China International Mineral Resources Limited (TCIMRL), respectively. TEL was awarded 10 coal prospecting licences and one coal mining licence. In addition, TCIMRL acquired 10 coal, 17 iron ore, and 7 dolomite prospecting licences and one coal special mining licence (Figure 6). TR partially owned one diamond SML, SML 216/2005. The TR’s percentage of ownership of a mineral right vis-a-vis the private investor was 25%. The private investor that owns the diamond SML with TR is Petra Diamonds Ltd, with a 75% shareholding. Under the government equity role from 1996 to 2015, coal was the most sought-after commodity, followed by gold and iron ore. This was presumably due to high granting of coal mineral rights by the Ministry of Energy and Minerals. From 1996 to 2015, the Ministry of Energy and Minerals granted 36 coal, 28 gold, and 19 iron ore mineral rights in $@46=AB!)@?A=>;B:02A9B8@?A=>;B=@41:9B>?3B/69@?A99B< ?A=91@29B/0 line with the government equity role in the minerals industry. 4<.A=?8A?:

VOLUME 119          
  
 265 L Evaluation of government equity participation in the minerals sector of Tanzania that, out of 106 mineral rights, 60 were owned through joint investor’s money spent as government contribution in an ventures (JVs) between the state and private companies; 42 investment would be through government-foregone (39.6%) were fully owned by STAMICO and NDC as sole dividends with interest. Free equity is when the company commercial entities, and four (3.8%) were owned through grants a portion of its shares to the government at no cost partnerships. (Heller, 2011; Cottarelli, 2012). Free-carry equity has the features of both free and carried equity (Kaba, 2017). It is ?>;09@9B<5B=A7A@.>/;AB>??6>;B;A.@A9B5<=B;@7A?7A9 when a percentage of mining company’s shares is offered to During the period under study the government received levies the government by the company, and the company also for licences issued under prospecting, mining, and special carries the costs and expenses for the government. According licence categories. Figure 8 presents annual levies payable by to Kaba (2017), the government may contribute in kind by STAMICO, NDC, and TR to the government from 2011 to granting the mining licence and/or mining rights. 2015 for holding licences issued by the government. Although the Mining Act, 2010 defines free-carry equity From Figure 8, the annual payable levies of STAMICO in terms of the free-carried interest (FCI), this equity role from 2011 to 2015 on its wholly and partially owned mineral approach is not yet practiced in Tanzania. In 2014, TZGT rights exceeded those of NDC and TR. This was because planned to execute free-carry equity in the Nachu graphite STAMICO owned more MLs and SMLs than NDC and TR, with project (NGRP) and Mkuju River uranium project (MRUP). greater ownership shares. It should be emphasized here that Negotiations for free-carried interest (FCI) for each project the annual levy rates for MLs and SMLs, expressed in US were conducted between the TZGT and project owners from dollars per square kilometre per annum, are much higher 2014, but were concluded unsuccessfully in 2015 as the than for PLs, which caused higher payable annual levies on parties could not reach consensus on FCIs. This consequently mineral rights under STAMICO to the tune of approximately impeded the signing of MDAs, which also limited execution US$0.9 million. of the free-carry equity role by the government. However, Whereas STAMICO had more shares of ownership in the government is negotiating with various stakeholders to mineral rights than NDC and TR, a rationale that mostly implement free-carry equity. Table III summarizes the results necessitated its self-commitment in settling of annual levies, for forms of government equity role in prospecting and NDC was deemed to have relied on the private sector medium- and large-scale mining. Most of the prospecting investors in settling the same. However, it seemed that the licence agreements were concluded under carried and paid parastatal contribution of payable annual levies on partially equity types, comprising 56 and 41 PLs respectively. These and wholly government-owned PLs exceeded the private agreements may lead to meaningful government participation sector investors’ contribution. This was attributed to many in the mining industry since the government has paid in one partially owned mineral rights issued to NDC having higher way or another for the shares held in an entity. This shareholding ownerships than private sector investors. participation will allow government to promote the mining industry as an invested party. (688>=0B<5B:1AB5<=89B<5B:1AB4<.A=?8A?:BA6@:0B=<;A $'!& '&#('%#(!$'(%&(!$' #%&( @?B:1AB8@?A=>;9B9A7:<= Table IV depicts the financial benefits of the government There are four main types of government equity role, namely equity role in 89 prospecting licences through STAMICO and paid or full equity, carried equity, free equity, and free-carry NDC from 2011 to 2015. The total derived benefits amounted equity. Paid equity is the equity capital financing or buying of to US$251 839.60. shares in enterprises by government, as a private investor would do (Heller, 2011; Natural Resource Governance $'!& '&#('%#(!$'(%&( '%  "'( %&%& Institute, 2015; Cottarelli, 2012). Carried equity is when the % '& ' private sector investor meets all capital costs and expenses in an investment without any financial contribution from STAMICO and NDC are involved in carried equity in three government (Natural Resource Governance Institute, 2015; medium-scale mines. The government did not earn any Cottarelli, 2012; McPherson, 2008). However, according to dividends from these mines during the period under review. Heller (2011) and McPherson (2008), the recovery of an STAMICO could not pay dividends as it was classified as a going concern and later reclassified; however, it was operating at a loss from 2013 to 2014 (Controller and Auditor General, 2015). NDC may not have paid an amount to the government because no dividends were declared for NDC based on the carried equity principle. It is expected that when STAMICO is profitable, dividends will be paid. Furthermore, once NDC has paid its debt of acquiring shareholding in full, dividends may be paid to the State provided that at least the mine is profitable.

$'!& '&#('%#(!$'(%&("!' "'( %&%&(% '& ' The government was involved in large-scale mining through exercising paid and carried equity roles. The paid equity role is through Stamigold Biharamulo mine and Kiwira coal mine, $@46=AB ! >0>/;AB>??6>;B;A.@A9B5<=B;@7A?7A9B1A;3B5=<8B&,%%&,% while carried equity is through Buckreef gold mine, L 266   
 VOLUME 119          
Evaluation of government equity participation in the minerals sector of Tanzania

Table III $<=89B<5B->?>?@>?B4<.A=?8A?:BA6@:0B=<;AB@?B69A

=A>B<5B2>=:@7@2>:@?3B8@?@?4B2=<A7:9B*8@?A9+BAA=7@9@?4B=A92A7:@.AB5<=89B<5BA6@:0B=<;A -<:>; A6@:0B=<;A (-)' ' -

Prospecting Carried 13 PLs 43 PLs None 56 PLs Paid 19 PLs 22 PLs None 41 PLs Medium scale mining Carried Merelani Ngaka Coal Mine None 3 medium TanzaniteOne scale mines Mining Ltd and Kigosi gold mine Large-scale mining Carried Buckreef gold mine Liganga Iron ore Mine and Williamson Diamonds 4 large Mchuchuma Coal Mine Mine scale mines Paid Kiwira coal mine and None None 2 large Stamigold Biharamulo mine scale mines Free carry Will apply in Nachu graphite project and Mkuju River uranium project pending meeting first of agreeable FCIs (through negotiations between government and projects owners) and signing of Minerals development agreements. Negotiations deemed to continue after 2015.

Table IV A=@.>:@?7@>;B/A?A5@:9B<5B:1AB4<.A=?8A?:BA6@:0B=<;AB@?B2=<92A7:@?4

>0>/;AB>??6>;B;A.@A9B=A:[email protected] '>:A4<=0B<5B5@?>?7@>;B/A?A5@:B5=<8B&,%%B:

STAMICO Payable annual levies from 13 PLs partially owned 21 941.70 Payable annual levies from 19 PLs wholly owned 33 504.30

NDC Payable annual levies from 37 PLs partially owned 89 365.10 Payable annual levies from 20 PLs wholly owned 107 028.50 Total 251 839.60

Mchuchuma coal mine, Liganga iron ore mine, and activities through STAMICO and NDC were analysed to Williamson diamond mine. The parastatals tasked with assess the non-financial benefits they generated. heading and protecting the role of government are STAMICO, Performances were analysed vis-a-vis three set of non- NDC, and TR (the government agent). The government did financial benefit indicators in prospecting, namely geo- not receive any earnings from these roles. This may be knowledge, government confidence in undertaking mining, explained by the fact that some operations can only begin and national capacity-building. Areas of non-financial after certain infrastructure is in place, such as construction of benefits include greater control of the minerals sector, Mchuchuma coal mine, the thermal power station, and a employment equity, human resource development, transmission line from Mchuchuma to Liganga. procurement, and enterprise development and community  "!($(%&"& %"('&'%#(#$(#'($'!& '&#( development (see Table VI). There were two major challenges (shortcomings) faced by Table V summarizes the financial benefits to the government the Tanzanian government in prospecting, medium-, and from 2006 to 2015. Based on the data collected and analysed large-scale mining. Firstly, STAMICO had financial in this paper, the financial benefits stood at US$53.39 million constraints from 2013 to 2014 after it was reclassified from against exploration costs of US$2.06 million (for all PLs) and being a going concern. In this case, as highlighted by the payable annual levies of US$1.76 million (for all mineral Controller and Auditor General (2015), STAMICO had rights) respectively. In the economics context, minimum suffering a recurrence of losses, for instance losses of allowable exploration expenditures and payable annual levies approximately US$450 293 in 2013 and US$632 452 in would be regarded as operating costs. These two costs may be incorporated in the income statements together with 2014. It is important that the government make interventions mineral sales revenues, cost of sales, other operating in STAMICO’s operations with workable strategic solutions to costs/expenses, depreciation expenses, etc. Then, the prevent the parastatal from dwindling. projects’ net profits before and after taxes would be Lastly, the secrecy in agreements or contracts in determined for payments of corporate income taxes to the partnerships, private JV companies, and mineral government and dividends to the shareholders (Correia et al., developments between the government and the private sector 1993). investors. Secrecy contributed to non-transparency and poor accountability in the prospecting, medium-, and large-scale  "!($(&$&%&"& %"('&'%#(#$(#'($'!& '&# mining projects under the government equity role. In The government carried and paid equity roles in prospecting addition, non-transparency and poor accountability in these

VOLUME 119          
  
 267 L Evaluation of government equity participation in the minerals sector of Tanzania

Table V (688>=0B<5B5@?>?7@>;B/A?A5@:9B<5B:1AB4<.A=?8A?:B5=<8B&,,B:

)@?A=>;B=@41: '<9:9B@?76==A3B@?B8@?A=>;B=@41:9B $@?>?7@>;B/A?A5@:9B5=<8B8@?A=>;B=@41:9 )@?@868 >0>/;AB -<:>;B A7A@.>/;AB '<=2<=>:A )@?@?4 A7A@.>/;A :1A=B -<:>;B >;;< >/;A >??6>; 7<9:9 >??6>; @?7<8AB =<0>;:0 2=<5@:9B<= :>A9 5@?>?7@>; A2;<=>:@ *#("B8@;;@

13 PLs partially owned 0.22 0.02 0.24 0.02 - - - - 0.02 by STAMICO 19 PLs wholly owned 0.23 0.03 0.26 0.03 - - - - 0.03 by STAMICO 37 PLs partially owned 0.76 0.09 0.85 0.09 - - - - 0.09 by NDC 20 PLs wholly owned 0.85 0.11 0.96 0.11 - - - - 0.11 by NDC Subtotal US$) 2.06 0.25 2.31 0.25 - - - - 0.25 ML 490/2013 of Merelani - 0.05 0.05 0.05 2.60 1.38 - 8.64 12.67 tanzanite mine (MTM) ML 496/2013 of Kigosi - 0.06 0.06 0.06 - - - - 0.06 gold mine (KGM) ML 439/2011 of Ngaka - 0.12 0.12 0.12 - 1.11 - - 1.23 coal mine (NCM) Subtotal US$) - 0.23 0.23 0.23 2.60 2.49 - 8.64 13.96 SML 04/92 of Buckreef - 0.16 0.16 0.16 - - - - 0.16 gold mine (BKGM) SML 533/2014 of Liganga - 0.15 0.15 0.15 - - - - 0.1 iron ore mine (LIOM) SML 534/2014 of Mchuchuma - 0.13 0.13 0.13 - - - - 0.13 coal mine (MCM) SML 216/2005 of Mwadui - 0.31 0.31 0.31 0.11 9.44 - 25.92 35.78 diamond mine (WDM) SML 233/2005 of Kiwira - 0.23 0.23 0.23 - - - - 0.23 coal mine (KCM) SML 157/ 2003 of Stamigold - 0.30 0.30 0.30 - 0.82 - 1.61 2.73 Biharamulo (SBM) Subtotal US$) - 1.28 1.28 1.28 0.11 10.26 - 27.53 39.18 Total (US$) 2.06 1.76 3.82 1.76 2.71 12.75 - 36.17 53.39

projects placed the Tanzanian government at risk of entering business ownerships that government and private sector unfair and/or objectionable agreements or contracts. investors pursued. In addition, sole commercial entities, The legislation states that public single (completely partnerships, and private JV companies adopted in the owned) or JV (partially owned) companies are required to government equity role are secretive in nature and this release public certified copies of their annual financial results in counter-productivity. statements to the Registrar of Companies (Correia et al., The Tanzanian government inadequately realized 1993; Marx et al., 1999). In addition, they are obliged to financial benefits through its equity role in prospecting, furnish their shareholders with mid-yearly interim reports medium-, and large-scale mining. Inadequacy in financial and audited annual financial statements (Correia et al., 1993; benefits was characterized by inconsistent payments of Marx et al., 1999). These two requirements are a reflection of corporate income tax, mining royalties, and other taxes by how transparent and accountable public single and JV the mining companies. Another reason for this problem was companies are as compared to businesses such as sole the non-realization of profits and receipt of dividends from commercial entities, partnerships, and private JV companies. mining enterprises in which the government is sole commercial entity (via parastatals) or a shareholder with '?3B=A7<88A?3>:@

Table VI ?7@>;B/A?A5@:9B<5B- -BA6@:0B=<;AB@?B8A3@68B>?3B;>=4A97>;AB8@?@?4

(7>;AB<5B )@?A =A>:A=B7?B=A9<6=7AB =<76=A8A?:B>?3B '<886?@:0B3A.A;<28A?: 8@?@?4 :1A8@?A=>;B9A7:<=B A6@:0 3A.A;<28A?:BA?:A=2=@9A *)'+ *5<=B- -B1>.@?4BBB 3A.A;<28A?: < ?A=91@2B91>=A9B @?B:1AB8@?@?4B91>=A+

Medium MTM Fairly achieved 1,166 locals were cumulative Fairly achieved despite Local procurement at Mine supplied water, employed from 2009 to 2015 lack of monitoring and 91.6%from 2012 and constructed school compared with 23 enforcement mechanisms. 2014 at the value of classrooms and roads from expatriates value of US$11.6 2010 to 2014 at the cost of million. US$427, 967 to zero respectively. KGM Fairly achieved No data in public domains. No data in public No data in public None. domains. domains. NCM Fairly achieved No data in public public Fairly achieved despite No data in public No data in public domains. domains. lack of monitoring and domains. enforcement mechanisms. Large BKGM Fairly achieved No data in public domains Fairly achieved despite No data in public No data in public domains. lack of monitoring and domains. enforcement mechanisms. LIOM Fairly achieved LIOM together with MCM Fairly achieved despite No data in public No data in public domains. will employ 32 000 locals. lack of monitoring and domains. enforcement mechanisms. MCM Fairly achieved MCM together with LIOM will Fairly achieved despite No data in public No data in public domains. employ 32 000 locals. lack of monitoring and domains. enforcement mechanisms. WDM Fairly achieved 558 locals were cumulative Fairly achieved despite Local procurement of Mine supplied water, employed from 2009 to 2015 lack of monitoring and goods was at 80.5% of constructed school compared with 11 enforcement mechanisms. total procurement from classrooms and roads from expatriates. 2012 to 2014 at a value 2010 to 2014 at the cost of of US$98.91 million. US$381 813 to US$125 323 respectively. KCM Fairly achieved No data n public domains No data in public No data in public No data in public domains. domains. domains. SBM Fairly achieved Only locals, 340 skilled and Fairly achieved despite Mine spent From 2011 to 2015, the 43 non-skilled employed at lack of monitoring and US$63 076.92 in local mine spent a total of the mine from 2014 to 2015. enforcement mechanisms. procurement of food US$101 238.47 on CSR stuffs from 2011 to 2015. activities including supplying of desks to pupils, renovations of water storage facilities, feeder roads as well as classrooms.

development as well as community development. However, in A5A=A?7A9 Tanzania there are no solid mechanisms and frameworks for BENDIOLA, I. 2013. Characteristics of a good policy & overall view of planning overseeing of non-financial benefits. and its relationship to the management process. It is recommended that the following issues be considered https://www.slideshare.net/IvanBendiola/characteristics-of-a-good-policy in order to improve the government’s effective performance [accessed 30 July 2017]. in the equity role strategy. BOMANI, M. 2008. Report of the Tanzanian presidential mining review ® Government to review the Mining Act of 2010 to committee to advise the government of the mining sector. include solid mechanisms and frameworks for all forms http://www.policyforum-tz.org/sites/default/files/BomaniReport- English_0.pdf [accessed 2 February 2016]. of government equity role, and assessing and measuring performance in equity role BROWN, M. 2013. Mining in Kenya – the start of new era? https://www.mayerbrown.com/files/uploads/Documents/PDFs/Mining_in_ ® Government should develop oversight mechanisms to Kenya2.pdf [accessed 9 September 2016] ensure that the effectiveness of its equity participation is monitored and its entities account to Parliament BUSINESSDICTIONARY 2017. Policy. ® http://www.businessdictionary.com/definition/policy.html [accessed 10 Government to review the Mining Act of 2010 and August 2017]. Regulations of 2010 to include frameworks for Controller and Auditor General. 2015. Report of the Controller and Auditor derivation, validation, and auditing of operating and General on the financial statements of the state mining corporation for the capital costs used in mining projects where the State six months period ended 30th June 2014. National Audit Office, Dar es holds equity interest. Salaam, Tanzania.

VOLUME 119          
  
 269 L Evaluation of government equity participation in the minerals sector of Tanzania

CORREIA, C., FLYNN, D., ULIANA, E., and WORMALD, M. 1993. Financial MUGANYIZI, K.T. 2012. ICTD Research 1: Mining sector taxation in Tanzania. Management. Par Print, Cape Town, South Africa. https://opendocs.ids.ac.uk/opendocs/bitstream/handle/123456789/2311/I CTD%20Research%20Report%201_0.pdf?sequence=1&isAllowed=y COTTARELLI, C. 2012. Fiscal regimes for extractive industries: Design and [accessed 13 December 2016]. implementation. http://www.greenfiscalpolicy.org/wp- content/uploads/2016/11/IMF-2012-Fiscal-Regimes-for-Extractive- MWIHAVA, C.X.N. and MASANJA, M. P. 2015. Annual Report July 2014 – June Industries-Design-and-Implementation.pdf [accessed 5 December 2016]. 2015.https://mem.go.tz/wp-content/uploads/2015/11/17.11.15annual- report-minerals-division.pdf [accessed 12 May 2016]. DODGSON, L. 2016. Tanzanite: How Tanzania can profit from mining its rare stone. http://www.mining-technology.com/features/featuretanzanite-how- NATURAL RESOURCE GOVERNANCE INSTITUTE. 2015. State participation in oil, gas tanzania-can-profit-from-mining-its-rare-stone-4698401/ [accessed and mining. https://resourcegovernance.org/sites/default/ 3 January 2017]. files/nrgi_StateParticipation_20150311.pdf [accessed 16 February 2016].

EAST AFRICAN COMMUNITY. 2011. Promotion of extractive and mineral processing NATURAL RESOURCE GOVERNANCE INSTITUTE. 2015. State participation in oil, gas industries in EAC- United Republic of Tanzania status. and mining. https://resourcegovernance.org/sites/default/ http://industrialization.eac.int/index.php?option=com_docman&task=cat_ files/nrgi_StateParticipation_20150311.pdf [accessed 16 February 2016]. view&gid=80&Itemid=70 [accessed 9 February 2016]. NGONYANI, E.A. 2014. Strategic Plan 2014/15–2018/19. FREEDICTIONARY 2017. Policy. https://www.thefreedictionary.com/ http://www.stamico.co.tz/wp-content/uploads/2014/12/STAMICO- Government+policies [accessed 18 May 2017]. STRATEGIC-PLAN-201415-201819.pdf [accessed 9 June 2016].

HELLER, P. 2011. National participation in oil and mining. NGOWI, H.P. 2009. Economic development and change in Tanzania since http://www.eisourcebook.org/cms/August%202013/National%20Participa independence: The political leadership factor. Proceedings of the tion%20in%20Oil%20&%20Mining.pdf [accessed 19 November 2016]. Conference on Political and Managerial Leadership for Change and Development in Africa, Mbabane, Swaziland, September 2009. pp. 1–23. HIGHLEY, E.D., CHAPMAN, R.G., and BONEL, A.K. 2004. The economic importance http://www.academicjournals.org/article/article1379789169_Ngowi.pdf of minerals to the UK. https://www.bgs.ac.uk/downloads/ [accessed 19 May 2016]. start.cfm?id=1301 [accessed 11 July 2016]. OTTO, J., ANDREWS, C., CARWOOD, F., DOGGETT, M., GUJ, P., STERMOLE, F., STERMOLE, IHUCHA, A. 2014. How Kenya and India plunder tanzania's blue gem. J., AND TILTON, J. 2006. Mining royalties: A global study of their impact on https://empirevoice.blogspot.co.za/2014/12/how-kenya-and-india- investors, government, and civil society. plunder-tanzanias.html [accessed 31 October 2016]. http://siteresources.worldbank.org/INTOGMC/Resources/336099- US GEOLOGICAL SURVEY. 2015. Mineral commodity summaries 2015. 1156955107170/miningroyaltiespublication.pdf [accessed 28 September https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf 2016]. [accessed 20 November 2016]. OTTO, J.M. Not dated. Mineral policy, legislation and regulation. KABA, D. 2017. Free carried interests in Francophone Africa mining legislation - https://commdev.org/userfiles/files/1217_file_UNCTAD_Otto.pdf [accessed Is there such a thing as a free lunch? http://www.fasken.com/en/free- 2 April 2016]. carried-interests-in-francophone-africa-mining-legislation---is-there- RIMOCH, D. AND CHERNG, S. 2013. A rare and beautiful stone fails to shine: such-a-thing-as-a-free-lunch-01-26-2017/ [accessed 5 February 2017]. Tanzania’s missed opportunity. MCPHERSON, C. 2008. State participation in the natural resource sector: http://knowledge.wharton.upenn.edu/article/rare-beautiful-stone-fails- Evolution, issues and outlook. http://www.imf.org/external/np/seminars/ shine-tanzanias-missed-opportunity/ [accessed 12 November 2016]. eng/2008/taxnatural/pdf/mcpherson.pdf [accessed 17 February 2016]. STATE MINING CORPORATION. 2014. State Mining Corporation. MINEWEB. 2015. Gold’s Top 20 – Mines, miners and countries. http://www.stamico.co.tz/wp-content/uploads/2014/09/CORPORATE- http://www.mineweb.com/news/gold/golds-top-20-mines-miners-and- PROFILE1.pdf [accessed 18 June 2016]. countries/, [Accessed 7 October 2016] STATE MINING CORPORATION. 2016. Corporate profile. MINING ACT. 2010. No. 14 Mining 2010. http://extwprlegs1.fao.org/docs/ http://www.stamico.co.tz/corporate-profile/ [accessed 25 December 2016]. pdf/tan97360.pdf [accessed 1 March 2019]. TANZANIA MINERALS AUDIT AGENCY. 2016a. Annual Report 2015. MINISTRY OF ENERGY AND MINERALS. 2009. The Mineral Policy of Tanzania. http://www.tmaa.go.tz/uploads/TMAA_Annual_Report_2015-4.pdf https://mem.go.tz/wpcontent/uploads/2014/02/0014_11032013_Mineral_ [accessed 13 June 2016]. Policy_of_Tanzania_2009.pdf. [accessed 29 March 2016]. TANZANIA MINERALS AUDIT AGENCY. 2016b. History of the Agency. MINISTRY OF ENERGY AND MINERALS. 2010. Mining Act, 2010. http://www.tmaa.go.tz/tmaa/about/category/history [accessed 29 July https://mem.go.tz/wp-content/uploads/2014/02/0013_ 2016]. 11032013_Mining_Act_2010.pdf [accessed 7 April 2016]. TWAAKYONDO, M.H., BHALALUSESA, P.E., and NDALICHAKO, L.J. 2002. Factors MINISTRY OF ENERGY AND MINERALS. 2015. Tanzania mining industry investor’s shaping successful public private investorship in the ICT sector in guide.http://www.tanzania.go.tz/egov_uploads/documents/TANZANIA_M developing countries the case of Tanzania. ining_Industry_Investor_Guide_-_June_2015_-1_sw.pdf [accessed 11 http://tanzaniagateway.org/docs/ICT_sector_in_developing_countries_the_ October 2016]. case_of_Tanzania.pdf [accessed 11 June 2016].

MINISTRY OF FINANCE AND PLANNING. 1992. The Public Corporations Act of 1992. WEIR, A. Not dated. Development in post-independence Tanzania. http://faolex.fao.org/docs/pdf/tan142173.pdf. [accessed 16 June 2016]. http://www.fastonline.org/CD3WD_40/HDLHTML/EDUCRES/DEP18E/EN/ CH04.HTM [accessed 15 June 2016]. MSABAHA, I.S. 2006. Tanzanian minerals sector- performance, fiscal benefits and challenges. World Bank Fiscal Issues Workshop, Washington DC, WISE, H. AND SHTYLLA, S. 2007. The role of the extractive sector in expanding USA, October 2006. pp. 1-15. economic opportunity. https://www.hks.harvard.edu/m- http://siteresources.worldbank.org/INTOGMC/Resources/3360991160575 rcbg/CSRI/publications/report_18_EO%20Extractives%20Final.pdf 823247/tanzaniaminister.ppt [accessed 31 January 2016]. [accessed 8 October 2016].

MUGANDA, A. 2004 Tanzania’s economic reforms — and lessons learned. YAGER, R.T. 2013. The mineral industry of Tanzania. http://www.tanzaniagateway.org/docs/tanzania_country_study_full_case. https://minerals.usgs.gov/minerals/pubs/country/2013/myb3-2013-tz.pdf pdf [accessed 26 May 2016]. [accessed 12 October 2016]. N L 270   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a6 Benefits of including resistivity data in a resource model — an example from the Postmasburg Manganese Field by J. Perold1 and C. Birch1

(1996), mining of manganese ore from the PMF ceased during 1989 in favour of the +7:.6;6 superior quality of manganese ore from the Due to the challenging geological environment of the Postmasburg KMF. Manganese Field (PMF), a study was conducted to determine if any Gutzmer (1996) also stated that the benefits would derive from the inclusion of resistivity data during three- irregular size and shape of the deposits, dimensional (3D) modelling of the manganese resource. This was achieved shortage of remaining reserves, and ore by estimating manganese resources from 2011/2012 drilling data and composition, are the chief factors that stopped comparing them with manganese resources estimated from the same the exploitation of the PMF orebodies. The drilling data and resistivity data collected during 2013 and 2017. shortage of remaining ore reserves might be Both models were adjusted to limit their extent to the same 3D modelling space. Significant volume and tonnage differences were ascribed to insufficient geological input, observed for all lithological units. The greatest differences were noted in resulting in incorrect geological understanding the manganiferous zones of alteration – 7.200 Mt for the geological model and modelling of these orebodies. This versus 3.700 Mt for the geoelectric model. likelihood is based on the findings of McCarthy This study showed that the inclusion of resistivity data can reduce (2003), who identified problem areas with exploration costs significantly, as a direct consequence of the resistivity associated error frequencies from 105 data allowing more accurate siting of boreholes. This decreases the completed mine feasibility studies analysed number of boreholes, samples, and analyses required due to the 3D (Table I). A significant portion of identifiable electrical delineation of mineralized areas prior to drilling. errors is directly linked to insufficient An additional benefit is the ability to more correctly forecast the net geological input, resulting in incorrect present value of an operation due to more accurate estimation of geological understanding and modelling of manganese resources and stripping ratios. This is clearly demonstrated by the estimated gross profit estimation of R409 million for the geological orebodies. Mine design and scheduling using resource model versus R264 million for the geoelectric resource model. incorrect orebody models will surely contribute The addition of resistivity data can, therefore, reduce exploration costs to business risks, negatively impacting on and can increase confidence in geological and financial modelling. It would potential profitability. be reasonable to conclude that this approach could also be used for karst- The critical role of manganese in the global hosted massive sulphide deposits. economy and the fact that mining in the PMF ><+:8/6 ceased prior to the development of current resource estimation, manganese, resistivity data, financial modelling. levels of geophysical prospecting techniques and 3D modelling software are sufficient reason to apply these technologies during prospecting in the PMF. The purpose of this paper is to highlight the impact of resistivity data on the accuracy of PMF mineral resource @798:/219;:7 estimation. This was established by comparing According to Corathers (2014) and Gajigo, differences in geological interpretation by Mutambatsere. and Adjei (2011), South Africa constructing two 3D resource models; one with holds between 75–80% of global manganese and one without resistivity data. reserves, followed by Ukraine (10%), Australia (3%), India (3%), and Gabon (2%). The known, land-based, manganese resources located elsewhere are estimated at 2%. The majority of economically important sedimentary manganese ore deposits in South Africa are situated in the Northern Cape Province (Gutzmer, 1996). Manganese ores of 1 School of Mining Engineering, University of the the Postmasburg Manganese Field (PMF) were Witwatersrand, South Africa. discovered in 1922, and the Kalahari © The Southern African Institute of Mining and Manganese Field (KMF) in 1940. According to Metallurgy, 2019. ISSN 2225-6253. Paper received Astrup and Tsikos (1998) and Gutzmer Sep. 2018; revised paper received Feb. 2019.

VOLUME 119          
  
 271 L Benefits of including resistivity data in a resource model

Table I an arc to the north, east and south’ (Cairncross, Beukes, and Gutzmer 1997). Rocks of the Transvaal Supergroup, ;37;,;1579=,<56;;4;9+=692/+=<88:86=
=$5890+)=( Griqualand West Basin, were deposited onto the basement rock of the Maremane Dome. 8:4<-=58<5 88:8=,8<2<71+=& ( The study area is underlain by manganese ore of the Geology, resource and reserve estimation 17 Western Belt (Gutzmer, 1996) of the PMF. The orebody is Geotechnical analysis 9 associated with shale, overlain by quartzite and basaltic lava Mine design and scheduling 32 of the Gamagara Formation, Olifantshoek Supergroup. The Mining equipment selection 4 Metallurgical test work, sampling scale-up 15 irregular size and shape of the orebodies (Gutzmer, 1996) Process plant equipment design and selection 12 resulted primarily from deposition onto a weathered, Reivilo Cost estimation 7 Formation dolomite paleosurface. The Reivilo Formation is a Hydrology 4 subdivision of the Ghaap Group, Campbell Rand Subgroup, Total 100 Transvaal Supergroup. Dolomite that resisted weathering formed unevenly spaced pinnacles when the softer rocks were eroded away. Accurate delineation of the dolomitic floor ?0<=:69-56283=#57357<6<=";<4/=&#"( topography and manganese orebody is of utmost importance The PMF is situated on the Maremane Dome (Eriksson, for precise geological modelling and mineral resource Altermann, and Hartzer; 2006), and is located immediately to estimation. the north of the town of Postmasburg, extending northwards A clear understanding of the mineral content and textural towards Sishen (Figure 1). The Maremane Dome (Figure 2) is relationships within the rocks of the Western Belt of the PMF a ‘domed anticline with strata dipping at less than 1:100 in is also required prior to constructing a 3D geological model as

";328<='!:159;:7=:,=90<=:69-56283=#57357<6<=";<4/)= :890<87=$5.<=8:*;71<)=:290=,8;15

";328<=! :890 6:290=18:66 6<19;:7=908:230=90<=#58<-57<= :-<=&$5;8718:66)=<2<6)=57/=%29-<8)=' ( L 272   
 VOLUME 119          
Benefits of including resistivity data in a resource model shown in Figure 3. Gutzmer (1996) and Gutzmer and Beukes publications concluded that the inclusion of resistivity data (1997) suggest that the ferruginous manganese ores formed can result in much greater detail than is usually assimilated through the following sequence of events: from drilling and sampling alone. 1. Deposition of a mixture of aluminous clay and To construct a 3D geoelectric model, the relationship ferruginous manganiferous wad in depressions in the between identified geological domains and georeferenced karst topography of the paleodolomite surface of the resistivity values has to be defined. Identification of Reivilo Formation. consistent apparent resistivity ranges depends entirely on the 2. The deposition of haematite pebbles, shale, and quartzite order of magnitude of the variability in electrical conductivity of the Gamagara Formation. for a specific rock domain (Oldenburg and Jones, 2007). 3. Low-angle thrusting causing lower level greenschist Guidelines used to determine apparent resistivity ranges were facies metamorphism, resulting in the formation of based primarily on their research. 2+ 3+ braunite (Mn ,Mn6 SiO12) and partridgeite (Mn2O3), Oldenburg and Jones’s (2007) generalized comparison for 3+ as well as coarse crystalline bixbyite-rich (Mn2 O3) different rock types (Figure 4) clearly indicates that the ferruginous ores (Mindat, 2017). expected resistivity ranges for metallic minerals (0.01 to 4. Exposure and erosion producing: 1  .m) should differ significantly from that for shale (7 to (a) Supergene mineralization resulting from 50  .m), sandstone (60 to 10 000  .m) and dolomite (1000 2+ 3+ secondary karstification, slumping, and to 100 000  .m). Braunite (Mn Mn 6[O8|SiO4]), bixbyite brecciation, leading to the formation of (Mn,Fe)2O3, partridgeite (Mn2O3), haematite (Fe2O3), and 4+ 3+ romanechite ((Ba, H2O)2(Mn ,Mn )5O10) specularite (Fe2O3) are the economically important ore (Mindat, 2017) crusts and wad minerals associated with the PMF (Gutzmer, 1996; Gutzmer (b) Placer (canga) deposits resulting from and Beukes, 1997). Smith (2002) records the resistivity of accumulation. haematite as 3.5 × 10-3 – 107  .m. and that of specularite averaging 6 × 10-3  .m. Srigutomo, Trimadona, and ..4;159;:7=:,=8<6;69;*;9+=628*<+=/595 Prihandhanu (2016) concluded that manganese ore of a Research results related to the findings of resistivity studies mudrock-hosted manganese deposit is associated with conducted on the rocks of the PMF are not available in the resistivity values less than 5  .m and that the resistivity of public domain. Research by Ramazi and Mostafaic (2012) on the mudrock rarely exceeds 100  .m. The 2D resistivity manganese deposits associated with the Uremich-Dokhtar surveyed conducted comprised 70 lines, each 550 m in volcanic belt in the northwest of Iran showed that resistivity length. results can be used to accurately differentiate between Differences between project-specific selected resistivity manganese interbeds and limestone. The manganese ranges and the published resistivity ranges cited are mainly mineralization underlying their study area correlated well ascribed to differences in conductivity. Oldenburg and Jones with areas of low resistivity. Moreira et al. (2014) used low (2007) stated that conductivity is mainly dependent on clay resistivity values to accurately differentiate between content, moisture content, hydraulic permeability, porosity, manganese mineralized zones, soil, and saprolite associated temperature and phase of pore fluid, and the concentration of with supergene manganese deposits in southern Brazil. Both dissolved electrolytes.

";328<=!#:/<4=,:8=90<=:8;3;7=:,=90<=,<8823;7:26=-57357<6<=:8<6=:,=90<=<69<87=<49=&%29-<8)=' =%29-<8=57/=<2<6)=' (

VOLUME 119          
  
 273 L Benefits of including resistivity data in a resource model

";328<=!%<7<854;

";328<=!%<:8<,<8<71

@79<8.8<959;:7=57/=-:/<44;73 areas with low manganese concentrations when iron concentrations were close to or higher than 21%. Additional The impact of resistivity data on the accuracy of PMF mineral zones of higher grade Mn mineralization, [Mn]
24% and resource estimation was tested by constructing two 3D [Mn]
28%, were then delineated within the manganore resource models, for comparison in Geovia Surpac 6.7. A zone. primary geological model was created from data gathered during geological mapping, drilling, and sampling within the  
  study area. A second 3D geoelectrical model was created by using resistivity data to guide the interpretation of the data The resistivity data was imported into Geovia Surpac 6.7. used during construction of the primary model. Care was taken to ensure that the resultant dispersion patterns compared favourably with the inverse model      resistivity sections, which accompanied the data. This is Construction of the geological model commenced (Turner and evident when comparing the georeferenced, measured Gable, 2006), by creating 15 west-east geological cross- apparent resistivity pseudo-section for line 11 (Figure 5) sections perpendicular to the strike of the orebody. with the graphical resistivity section presented for line 11 Interpretation of the geology was limited to the sectional (Figure 6). Georeferencing of the data resulted in the actual areas between boreholes drilled. The range of influence of 3D orientation of each data-point, thus ensuring that it data from individual holes was limited to half the distance represents its physical location. between holes unless geological contacts could be accurately When constructing the 3D geoelectrical model, recognized on the surface. relationships between identified geological domains Delineation of manganiferous zones of alteration underlying the project area and the georeferenced resistivity (manganore) was restricted to areas with reported Mn values values had to be defined (Loke, 2000). Table II summarizes equal to or greater than 11% and/or combined Mn and Fe the resistivity ranges selected for identified lithological units values of 21% or greater. This resulted in the inclusion of underlying the project area. This was achieved by draping the L 274   
 VOLUME 119          
Benefits of including resistivity data in a resource model

";328<=! ;,,<8<79=385.0;154=8<6;69;*;9+=6<19;:76)=4;7<=''=& :7)='(

Table II geological model. The differences observed are significant and relate to: <6;69;*;9+=8573<6=6<4<19 170 Surface dumps Unknown > 370 insufficient geological and chemical data Dolomite [Mn] < 11% > 170 ® The shape, position, and orientation of the overlying Dolomite [MnFe] ≥ 21% > 370 quartzite ® The shape, position, and orientation of the unaltered shale. georeferenced resistivity data over borehole geological logs The principal reason for the volumetric differences is the and analytical data contained in the project database. high resolution of the sectional resistivity data, which allows Resistivity ranges were found to be fairly constant but detailed modelling on a very small scale. Results obtained showed some variation between lines. Two lines showed from the resistivity data and associated geoelectrical model reduced resistance, approximately 50  .m, for mineralized resemble the model of origin proposed by Gutzmer (1996) areas compared to the other lines surveyed. and Gutzmer and Beukes (1997) more closely than the The resolution of the resistivity values is unfortunately geological model derived from drilling results alone. not high enough to conclusively deduce whether ferruginous shale with low concentrations of manganese is associated with areas of low resistivity (< 50  .m). As Mn and Fe mineralization are uncorrelated, zones of alteration (Table II) were subdivided into mostly manganiferous (50–100  .m) Table III and mostly ferruginous (< 50  .m). Solid models were 6<8*

;90:4:3+ #:/<44;73=<88:86 <62496=57/=/;61266;:7 %<:4:3;154= %<:<4<198;154= $0573<

   :42-<=&-( Table III compare volumetric differences for lithological Quartzite 0.438 0.566 26.9 domains that resulted from the modelling regimes employed, Dolomite 1.368 1.425 4.2 based on geological interpretation as shown in Figure 7. The Shale 2.189 1.333 39.1 Ferruginous zone - 1.586 Undefined differences are expressed as percentage change, based on the Manganiferous zone 1.869 0.954 49.0 modelled volume of individual lithological units of the

VOLUME 119          
  
 275 L Benefits of including resistivity data in a resource model

";328<=!<19;:754=1:-.58;6:7=:,=3<:4:3;154=;79<8.8<959;:7=;90=57/=;90:29=8<6;69;*;9+=/595

     Table IV Applying a cut-off grade (Pittuck, 2015) to the created $:-.58;6:7=:,=698;..;73=859;:6=566:1;59

Table V $:-.58;6:7=:,=<.4:859;:7=<.<7/;928<

.4:859;:7=<.<7/;928< ;90:29=8<6;69;*;9+ ;90=8<6;69;*;9+ $0573< =-;44;:7

Resistivity survey - 0.151 Undefined Core drilling 0.948 0.515 45.7 Chemical analysis 0.211 0.102 51.7 Total cost estimate 1.159 0.767 46.8

Table VI ,,<19=:,=698;..;73=859;:=:7=-:7904+=.8:/219;:7=1:696=57/=38:66=.8:,;9=&42-.=:8<=.8:/219(

.<859;:7 ;90:29=8<6;69;*;9+ ;90=8<6;69;*;9+ $0573< =-;44;:7 '

RoM ore feed 1.488 1.488 0.0 Waste mining 1.269 3.919 208.8 Crushing and screening 1.129 1.129 0.0 Secondary breaking (20% of feed) 0.031 0.031 0.0 Lump ore cost of production (LCOP) 3.917 6.568 67.7 Gross sales revenue (DAP) 11.070 11.070 0.0 Gross profit after LCOP (DAP) 7.153 4.202 41.3

geochemical contacts during 3D modelling of the mineral averaged above 28% Mn. The average in situ manganese deposit. grade of the area drilled during 2017 is 8% higher than the average grade of the project estimated from the 2011/2012      drilling data. The average estimated iron grade is 6.5% The effect of different stripping ratios, from the created higher than in 2011/2012, while the total average metal resource models, on monthly gross profit is illustrated in concentration (MnFe) increased by 14.5%. Table VI. Stripping ratio is the only variable considered when A similar grade comparison confined to the area drilled the cost of production (lump ore product) is calculated. If the during 2017 showed that the average in situ manganese stripping ratios for the created models were the same, the grade estimated from the 2017 data is 2.54 % higher than estimated costs would have been equal. This caused the cost that estimated from the 2011/2012 drilling data. The average of waste mining associated with the geoelectrical model to be estimated iron grade is 4.49% higher than in 2011/2012, 209% higher than that estimated for the geological model. while total average metal concentration (MnFe) increased by Gross profit for the geoelectrical model reduces by 41% 7.03%. compared to the geological model based on drilling data alone. $:71426;:76 Assuming that the geoelectrical model is more accurate, The aim of this study was to determine if any benefits will the monthly estimated gross profit of the geological model is derive from the inclusion of resistivity data in a manganese overestimated by R3 million. This equates to R409 million for resource model for the PMF. This was achieved by estimating the declared mineral resources. manganese resources from 2011/2012 drilling data for comparison with resources estimated from the same drilling 54;/59;:7=:,=90<=0+.:90<6;6 data plus resistivity data collected during 2013 and 2017. To confirm the conclusions drawn and endorse the It was established that the addition of resistivity data can recommendations made, 16 core boreholes were drilled in the reduce exploration costs significantly in this challenging study area during November/December 2017, the first geological environment. The reduction in costs is a direct drilling since completion of the initial prospecting phase consequence of the application of resistivity data allowing (without resistivity data) during 2011/2012. Boreholes were more accurate placing of boreholes. This lessens the number sited on an approximate 50 × 50 m grid covering an area 150 of boreholes, samples, and analyses required due to the 3D m by 175 m in extent. Boreholes were deliberately placed on electric delineation of mineralized areas prior to drilling. resistivity lines surveyed earlier during 2017 or 2013. An additional benefit is the ability to more correctly The area chosen showed continuity of resistance levels forecast the net present value of an operation due to more <150  .m over distances exceeding 120 m. accurate estimation of manganese resources and stripping The results of the 2017 drilling campaign were very ratios. This is clearly demonstrated by the estimated gross encouraging. All 16 boreholes drilled intersected manganese profit difference of R409 million for the geological resource mineralization. The ore intersections in 15 of the boreholes model and R264 million for the geoelectrical resource model.

VOLUME 119          
  
 277 L Benefits of including resistivity data in a resource model

The addition of resistivity data can, therefore, reduce LOKE, M.H. 2000. Electrical imaging surveys for environmental and engineering exploration costs and can increase confidence in geological studies. A practical guide to 2-D and 3-D surveys. http://www.heritagegeophysics.com/images/lokenote.pdf and financial modelling. It would be reasonable to conclude MC CARTHY, P. 2003. Managing technical risk for mine feasibility studies. that this approach could also be used for karst-hosted Proceedings of the Mining Risk Management Conference. Australasian massive sulphide deposits. Institute of Mining and Metallurgy, Melbourne, Australia. Mindat.org. 2017. https://www.mindat.org/
   MOREIRA, C.A., BORGES, M.R., VIEIRA, G.M.L., FILHO, W.M., and MONTANHEIRO, M.A.F. 2014. Geological and geophysical data integration for delimitation This paper is based on the MSc research project by Perold of mineralized areas in a supergene manganese deposit. Geofisica (2018), supervised by C. Birch from the School of Mining Internacional, vol. 53, no. 1. pp. 199–210. Engineering, University of the Witwatersrand. OLDENBURG, D.W. and JONES, F.H.M. 2007. Inversion for applied geophysics; Learning resources about geophysical inversion. Geophysical Inversion Facility, University of British Colombia. https://www.eoas.ubc.ca/    ubcgif/iag/foundations/properties/resistivity.htm ASTRUP, J. and TSIKOS, H. 1998. Manganese. The Mineral Resources of South PITTUCK, M. 2015. Cut-off grades for mineral resource reporting: going the extra Africa. Wilson, M.G.C. and Anhaeusser, C.R. (eds). Handbook 16. Council rare earth mile. SRK Consulting International Newsletter, no. 51. for Geoscience, Pretoria. pp. 450–460. http://www.srk.com/files/File/newsletters/srknews51-MRE_A4-LR.pdf CAIRNCROSS, B., BEUKES, N.J., and GUTZMER, J. 1997: The Manganese Adventure: RAMAZI, H. and MOSTAFAIC, K. 2012. Application of integrated geoelectrical The South African Manganese Fields. Associated Ore & Metal Corporation methods in Marand (Iran) manganese deposit exploration. Arabian Limited, Johannesburg. 236 pp. Journal of Geosciences, vol. 6. pp. 2961–2970. doi 10.1007/s12517-012- CORATHERS, L.A. 2014. Manganese. US Geological Survey Mineral Commodity 0537-2. Summaries. February 2014. SAMREC. 2016. South African Mineral Resource Committee. The South African http://minerals.usgs.gov/minerals/pubs/commodity/manganese/ Code for the Reporting of Exploration Results, Mineral Resources and ERIKSSON, P.G., ALTERMAN, W., and HARTZER, F.J. 2006. The Transvaal Mineral Reserves (the SAMREC Code. 2016 Edition. Supergroup and its precursors. The Geology of South Africa. Johnson, http://www.samcode.co.za/codes/category/8-reporting- M.R., Anhaeusser, C.R., and Thomas, R.J. (eds.). Geological Society of codes?download=120:samrec South Africa, Johannesburg and Council for Geoscience, Pretoria. SMITH, R.J. 2002. Geophysics of iron oxide copper-gold deposits. Hydrothermal pp. 237–260. Iron Oxide Copper-Gold & Related Deposits: A Global Perspective. Volume GAJIGO, O., MUTAMBATSERE, E., and ADJEI, E. 2011. Manganese industry analysis: 2. Porter, T.M. (ed.). PGC Publishing, Adelaide. pp 357–367. Implications for project finance. Working Paper Series no. 132. African Development Bank Group. https://www.afdb.org/en/documents/ SRIGUTOMO, W. TRIMADONA, and PRIHANDHANU, M.P. 2016. 2D resistivity and document/working-paper-132-manganese-industry-analysis- induced polarization measurement for manganese ore exploration. implications-for-project-finance-24162/ Proceedings of the 6th Asian Physics Symposium, Bandung, Indonesia, GUTZMER, J. 1996. Genesis and alteration of the Kalahari and Postmasburg 19–20 August 2015. Journal of Physics: Conference Series, vol. 739, no. 1. manganese deposits, Griqualand West, South Africa. PhD thesis, Faculty 0121385. IOP Publishing. https://iopscience.iop.org/article/10.1088/1742- of Science, University of Johannesburg. 6596/739/1/012138/pdf GUTZMER, J. and BEUKES, N.J. 1997. Mineralogy and mineral chemistry of oxide TURNER, A.K. and GABLE, C.W. 2006. A Review of Geological Modeling. Colorado facies manganese ores of the Postmasburg manganese field, South Africa. School of Mines, Golden, CO. https://pdfs.semanticscholar.org/5777/ Mineralogical Magazine no. 61. pp. 213–230. c2b949527397ac42ac9be64e5bb4fe7e8c7e.pdf N L 278   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a7 Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data from Landsat by M.A. Mahboob1, B. Genc1, T. Celik2, S. Ali3, and I. Atif3

properties of rocks and weathering soils, such %*:6.585 as mineralogy, landforms, geochemical signatures, and the spatiall distribution of Mapping of hydrothermally altered areas, which are usually associated with mineralization, is essential in mineral exploration. In this research, lineaments (Bhattacharya et al., 2012). open source reflectance spectroscopy data from the multispectral A fundamental principle of mineral moderate-resolution Landsat 8 satellite was used to map altered rocks in exploration is that it is quite possible that the Gauteng and Mpumalanga provinces of South Africa. The unique undiscovered deposits will be located in the spectral reflectance and absorption characteristics of remotely sensed close vicinity of discovered ones. For example, Landsat data in the visible, near-infrared (NIR), shortwave-infrared if mining is taking place in a particulat area, (SWIR) and thermal infrared (TIR) regions of the electromagnetic then similar minerals will be more likely found spectrum were used in different digital image processing techniques. The nearer to the discovered deposit, and as the band ratios (red/blue, SWIR 2/NIR, SWIR 1/NIR), spectral band distance increases, the likelihood of new combinations (Kaufmann ratio, Sabins ratio) and principal component discoveries will decrease. In that situation, analysis (Crosta technique) were applied to efficiently and successfully map hydrothermal alteration minerals. The results showed that the before drilling exploratory boreholes at new combination of spectral bands and the principal component analysis locations, remote sensing can be used method is effective in delineating mineral alteration through remotely effectively to identify regions with higher sensed satellite data. The validation of results by using the published chances of mineralization, mainly through mineral maps of the Council for Geoscience South Africa showed a good multi- or hyperspectral remote sensing images relationship with the identified zones of mineralization. The methodology (Gholami, Moradzadeh, and Yousef, 2012; developed in this study is cost-effective and time-saving, and can be Ciampalini et al., 2013). The use of reflectance applied to inaccessible and/or new areas with limited ground-based spectroscopic information derived from remote knowledge to obtain reliable and up-to-date mineral information. sensing data allows effective localization of <*$6945 mineral exploration and reduces the cost and remote sensing, mineral mapping, reflectance spectroscopy, Landsat, time spent on fieldwork for geological, mineral exploration, hydrothermal alteration. geophysical, and geochemical studies (Short and Lowman Jr, 1973; Tedesco, 2012; Marjoribanks, 2010). Several remote sensing studies for mineral exploration and lithological mapping have been done in arid and semi-arid :7964,2786: regions. In areas with good geological Many developing nations depend on exposure, satellites in orbit are capable of exploration and exploitation of mineral acquiring spectral reflectance data directly resources to sustain their economic growth. from rock or/and soils (Sabins, 1999; Di Usually, the traditional mineral exploration Tommaso and Rubinstein, 2007; Zhang et al., techniques require enormous finances, 2007; Pour and Hashim, 2012; Mahboob, prolonged time, and tremendous manpower, Iqbal, and Atif, 2015). particularly in areas that are not easily reachable (Maduaka, 2014). Furthermore, mineral exploration required state-of-the-art techniques and expertise along with 1 School of Mining Engineering, University of the geological, geochemical, and geophysical data- Witwatersrand, South Africa. sets, which may not be easily available or may 2 School of Computer Science and Applied be lacking where access is problematic (Kaiser Mathematics, University of the Witwatersrand, et al., 2002; Bemis et al., 2014). Modern South Africa. 3 remote sensing technology has proved to be School of Advanced Geomechanical Engineering, National University of Sciences and Technology one of the highly efficient and robust (NUST), Pakistan. techniques used for mineral exploration. The © The Southern African Institute of Mining and use of remote sensing satellite images for Metallurgy, 2019. ISSN 2225-6253. Paper geological mapping and mineral exploration received Sepc. 2018; revised paper received Mar. usually involves studying the physicochemical 2019.

VOLUME 119          
  
 279 L Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

Hydrothermal alteration minerals with diagnostic spectral ;7<98;3=;:4=/<71645 absorption properties in the visible and near-infrared through the shortwave length infrared regions can be identified by   multispectral and hyperspectral remote sensing data as a tool The study areas for this research were Roodepoort and for the initial stages of porphyry copper and epithermal gold Westonaria in Gauteng Province and Witbank and Kriel in exploration (Di Tommaso and Rubinstein, 2007; Zhang, Mpumalanga Province, as shown in Figure 2. Pazner, and Duke, 2007; Ramakrishnan and Bharti, 2015). Gauteng's name is derived from the Sotho, ‘Gauta’ which In general, porphyry copper deposits are formed by means ‘gold’, with the local suffix ‘-eng’. Gauta has been hydrothermal alteration of fluids. These altered rocks can be taken from the Dutch word for gold, ‘goud’. The main identified through their spectral characteristics in the visible economic sectors are financial services, business services, and infrared wavelengths (Pour and Hashim, 2012). Many logistics, communications, and mining. The most significant minerals have unique and characteristic spectral properties, geological formation in Gauteng is the Witwatersrand with a specific amount of electromagnetic (EM) energy Supergroup. Gold in this region was derived from granite- reflected and/or absorbed at a particular wavelength, which greenstone terranes and transported to and concentrated in can be used to identify them with a high degree of the Witwatersrand Basin by fluvial activity. Gauteng was confidence. The portion of the electromagnetic spectrum from built upon the wealth of gold found deep underground, i.e. 0.4 to about 2.5 μm (the visible, near-infrared, and almost 40% of the world’s reserves (Durand, 2012). shortwave-infrared region) is useful to sense the geological Mpumalanga is another mineral-rich province of South features with moderate and low-temperature properties Africa. The general geology of of this area consists of because most of the sunlight is reflected in this portion of the mudrock, siltstones, sandstones, conglomerate, and several spectrum (Mahboob, Iqbal, and Atif., 2015a). coal seams. Mpumalanga accounts for 83% of South Africa's Usually, Iron oxides, oxyhydroxides, and ligands can be coal production. Ninety per cent of South Africa's coal mapped very well in this range of the electromagnetic consumption is used for electricity generation and the spectrum because of their high- or low-temperature alteration synthetic fuel industry (Dabrowski et al., 2008). characteristics (Clark et al., 1990). This portion of the spectrum can also be used for differentiation between silicate   (clay) minerals and other features. This spectral differentiation of minerals has been the basis for the use of Usually, ASTER is the most commonly used satellite data for this technique in mineral exploration (Calvin, Littlefield, and hydrothermal mineral mapping and exploration. However, Kratt, 2015). The thermal infrared (TIR) portion of the since 2008, ASTER’s six SWIR sensors have not been spectrum, usually from 7 to 14 μm, senses the energy emitted operational because of malfunctioning (Wessels et al., 2013). from the Earth's surface. In addition to water, carbonates, Landsat data is also free and is used in mapping and and sulphates, this region of the electromagnetic spectrum is exploration of hydrothermally altered minerals and rocks. In also sensitive to Si-O bonds in silicates (Repacholi, 2012; this research, the cloud-free level 1T (L1T) data from the Udvardi et al., 2017; Manley, 2014). The spectral signatures Landsat 8 satellite (path 170 / row 78) recorded in August of some typical minerals (calcite, orthoclase feldspar, 2017 was used. Landsat images are processed in units of kaolinite, montmorillonite, and haematite) that can be clearly absolute radiance using 32-bit floating-point calculations. and confidently mapped using reflectance spectroscopy data These values are then converted to 16-bit integer values in (i.e. hyperspectral data) are shown in Figure 1. the finished Level 1 product (Chander and Markham, 2003). In this study, the identification of hydrothermally altered Landsat 8 is equipped with the Operational Land Imager rocks and features associated with hydrothermal mineralization in South Africa’s Gauteng and Mpumalanga provinces is examined using Landsat 8 (originally known as Landsat Data Continuity Mission (LDCM)) remote sensing reflectance spectroscopy.

(80,9<='&<-3<27;:2<=5.<279;=6-=56/<=7*.82;3=/8:<9;35=8:=71<=!858+3<) :<;9 8:-9;9<4)=;:4=51697$;!< 8:-9;9<4=9<086:5=6-=71<=<3<2796/;0:<782 5.<279,/=;3<)="'  (80,9<="&;.=6-=;,7<:0=;:4=.,/;3;:0;=.96!8:2<5=6-=%6,71=-982;= L 280   
 VOLUME 119          
Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

(OLI) and the Thermal Infrared Sensor (TIRS); their spatial based methods. In the empirical approach, the spectral and spectral characteristics are shown in Table I. A single properties of the ground features are used for transforming Landsat 8 image covers an area of 170 km (north-south) by the spectral data from the sensor’s radiance to ground 183 km (east-west). reflectance. Empirical methods are simple but do not incorporate the pixel-to-pixel variation in atmospheric effects,  whereas the physical-based methods, such as The pre-processing of raw satellite images is necessary to Atmospheric/Topographic CORrection or ATCOR (Richter, obtain geometrically and atmospherically corrected images so 1997), MODerate resolution atmospheric TRANsmission or that the spectral information can be extracted and analysed. MODTRAN (Berk et al., 1998), and the Satellite Signal in the The raw satellite images of the study areas are shown in Solar Spectrum (6S) code (Vermote et al., 1997), incorporate Figure 3. the heterogeneity of the atmosphere but require several The geometric correction entails the georeferencing of complicated and manual procedures, which make it difficult satellite images with respect to ground control points in order to process large amounts of satellite data. On the other hand, to obtain pixels with the same dimensions. For atmospheric the Landsat Ecosystem Disturbance Adaptive Processing corrections there are two different approaches: relative System (LEDAPS) software (Masek et al., 2006), which has normalization (Schroeder et al., 2006) and absolute implemented the 6S code, made atmospheric correction for correction (Chavez, 1996; Song and Woodcock, 2003). Landsats 4–7 fully automated. Recently, Vermote et al. Relative normalization includes radiometric correction of the (2016) derived an improved atmospheric correction algorithm Landsat data-sets with respect to a reference image based on for Landsat 8 (L8SR), which has shown an improvement the correlation between pseudo-invariant objects from multi- over the ad-hoc Landsat 5–7 LEDAPS product. The modified date images (Song et al., 2001). Absolute correction can be LEDAPS product was applied in this study for atmospheric subdivided into two more categories: empirical and physical- corrections as shown in Figure 4.

  As OLI band 1 (coastal aerosol) is useful for imaging shallow Table I waters and band 9 (cirrus) for detecting high-altitude clouds ;:45;7= =5;7<3387<=5.<279;3=;:4=5.;78;3=4<7;835 and tracking fine particles like dust and smoke, these two bands were not included in further analysis. Moreover, %.<279;3== %.<279;3= ;!<3<:071= %.;78;3= according to the literature, for mineral exploration mapping +;:4= +;:4= 
/ 9<563,786: the most appropriate bands are located in the visible, NIR, :,/+<9 :;/< / and SWIR regions. In this research study, OLI bands 2–7 and 1 Coastal aerosol 0.43 - 0.45 30 TIRS bands 10–11 were used for advanced processing. All 2 Blue 0.45 - 0.51 30 these bands were stacked as a single image using the layer 3 Green 0.53 - 0.59 30 4 Red 0.64 - 0.67 30 stacking digital image processing technique (Mahboob, Atif, 5 Near-Infrared (NIR) 0.85 - 0.88 30 and Iqbal, 2015). 6 Shortwave-Infrared (SWIR) 1 1.57 - 1.65 30 7 Shortwave-Infrared (SWIR) 2 2.11 - 2.29 30     8 Panchromatic 0.50 - 0.68 15 9 Cirrus 1.36 - 1.38 30 Usually, the L1T images of Landsat 8 consist of the digital 10 Thermal-Infrared (TIRS) 1 10.60 - 11.19 100 numbers (DNs), which cannot be used due to lack of 11 Thermal-Infrared (TIRS) 2 11.50 - 12.51 100 physically meaningful information and should be converted

(80,9<=&7/65.1<982;33*=2699<27<4=;:4=<:1;:2<4=;:45;7=5;7<3387< (80,9<=&;$)=,:.962<55<4=;:45;7=5;7<3387<=8/;0<5=6-=71<=57,4* 8/;0<5=6-=71<=57,4*=;9<;5=,58:0=:<;9 8:-9;9<4)=9<4)=;:4=09<<:=5.<279;3 ;9<;5= +;:45=26/+8:;786:

VOLUME 119          
  
 281 L Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data to surface reflectance. This conversion is required for (Sabins, 1999). Usually, minerals like iron oxide and quantification of different features in remote sensing data as sulphate have low and high reflectances in the it incorporates solar conditions (geometry, illumination, and ultraviolet/blue and near-infrared portion of the EM spectrum intensity) when the images were captured. In this study, the respectively (Johnson et al., 2016), hence these minerals data was converted to Top of Atmosphere (TOA) reflectance have a rusty shade in a natural colour image. using radiometric coefficients as recommended by Roy et al. (2016), whereby DNs were converted to reflectance
  representing the ratio of the radiation reflected from a surface Band-ratioing is a digital image-processing technique that to the radiation striking it (Han and Nelson, 2015), as shown enhances the contrast between features by dividing a in Figure 5. measure of reflectance for the pixels in one band by that of Equation [1] was used to convert DN values to TOA the pixels in another band of the same satellite image. This reflectance (Zanter, 2016): technique has been widely used for visualizing and mapping hydrothermally altered rocks. For example, Han and Nelson [1] (2015) efficiently used the image ratios of Landsat Thematic Mapper (TM) band 5 (1.55–1.75 μm) over band 7 (2.09– where 2.35 μm) to differentiate areas with high concentrations of alunite and clay, where pixels in the satellite image appear  = Top of Atmosphere Planetary Reflectance (dimensionless) bright. Another study, conducted by van der Meer (2004), used the ratio image of band 3 (0.63–0.69 μm) over band M = Reflectance multiplicative scaling factor for the band 1 (0.45–0.515 μm) to highlight areas with rich iron ores. In the current research work different band ratios, as shown in A = Reflectance additive scaling factor for the band Table II, were developed and applied in order to enhance Qcal = Level 1 pixel value in DN
= Solar elevation angle (degrees). hydrothermally altered rocks and lithological units. The selection of bands is related to the spectral reflectance and   position of the absorption bands of the mineral or The data captured by Landsat 8 represents the reflected assemblage of minerals to be mapped. and/or emitted spectral energy, which can be further used Even though the band-ratioing technique works very well based on the absorption characteristics of spectra to detect for visualization, it is not capable of mapping or different materials and features of the Earth’s surface. Some quantification of the land features. One of the reasons for minerals and mineral groups in hydrothermally altered rocks this limitation is that most of the optical multispectral remote have unique absorption characteristics in the EM spectrum. sensing instruments use the bandwidths > 0.05 μm, which is For example, some alunite and clay ores have unique too wide to explicitly differentiate the unique spectral absorption features at approximately 2.1 μm, and their absorptions related to specific alteration minerals (van der spectral responses are much higher at approximately 1.7 μm Meer, 2004). Furthermore, many band-ratioing techniques use only two or (sometimes) three bands, whereas multispectral remote sensing instruments offer many more bands than that. Based on these limitations, there is a need to adopt another advanced digital satellite image analysis approach which can utilize all available satellite bands together, as described in the following sections.

    The spectral band combination technique, also known as red-

Table II ;:4=9;7865=-69=<:1;:2

%9#=:6# %.<279;3= ;!<3<:071 *.<=6-=/8:<9;3 +;:4=:;/< :/ <:1;:2<4

1 Red 640–670 Iron oxide Blue 450–510

2 Shortwave-Infrared (SWIR) 1 1570–1650 Hydroxyl- Shortwave-Infrared (SWIR) 2 2110–2290 bearing rock

3 Shortwave-Infrared (SWIR) 2 2110–2290 Clay minerals Near-Infrared (NIR) 850–880

4 Shortwave-Infrared (SWIR) 1 1570–1650 Ferrous Near-Infrared (NIR) 850–880 mineral (80,9<= &%.<279;3=+;:45=6-=;:45;7= =5;7<3387<= L 282   
 VOLUME 119          
Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data green-blue (RGB) combination, is a very useful image strata, etc. (Grunsky. Mueller, and Corrigan, 2014). enhancement technique which offered powerful means to Generally, the spectral properties of different features present visually interpret multispectral satellite data (Novak and in the area, i.e. vegetation, rocks, and soils, are responsible Soulakellis, 2000). The band combinations of satellite data for the statistical variance mapped into each PC, which can be true (natural) or false-colour composites (FCC) using becomes the basis of the Crosta technique (Tangestani and individual bands or band ratios. For this purpose, several Moore, 2001). In this study, the same technique has also band ratios and bands combinations have been developed been applied based on highly variable non-correlated satellite over time to differentiate lithologies in a satellite image. A bands for hydrothermally altered rocks. few examples are given in Table III. In this research, the Kaufmann and Sabins ratios were <5,375=;:4=4852,5586: applied to highlight the hydrothermally altered rocks The effectiveness of remote sensing-based hydrothermal associated with the minerals present in the study areas. Most minerals identification and mapping depends on the clear research studies have applied these two ratios for the differentiation of the reflected spectra of altered bedrock from identification of altered areas and their associated minerals. those of the other objects. The true colour composite of bands For example, Mia and Fujimitsu (2012) and Abhary et al. 3, 2, and 1 as red, green, and blue respectively highlighted (2016) applied the Kaufmann ratio for the mapping of the textural characteristics of the igneous rocks, which could minerals containing hydroxyl and iron ions using Landsat be separated from those of sedimentary rocks. Pournamdari, satellite data. Similarly, da Cunha Frutuoso (2015) used the Hashim, and Pour (2014) tested the same satellite band Sabins ratio for the identification of sulphide deposits associated with the alteration areas of iron oxides. combinations and found them to be effective for differentiating igneous rocks in south Iran. The false-colour   composite was assigned to bands 4, 3, and 2 as red, green, Principal component analysis (PCA) is an advanced and blue respectively as shown in Figure 6 to analyse the information extraction technique and is frequently used in reflected satellite spectroscopy. The false-colour composite is the Earth sciences (Cheng et al., 2011, El-Makky, 2011). PCA important to enhance the regional geological and is a well-known multivariate statistical method and has been geomorphological features, as also reported by Bedini generally used to study associations between variables. By (2009). Vegetation appeared in red shades because of the orthogonal transformation, several correlated variables can near-infrared (0.7–1.2 μm) band, which was highlighted with be transformed into uncorrelated combinations (eigenvector a red colour and vegetation reflects the maximum in this loadings) of principal components (PCs) based on their band. covariance or correlation matrix (Horel, 1984; Loughlin, Hydrothermally altered clay and carbonate minerals are 1991). Generally, the first few PCs highlight the most recognizable as yellow areas in crystalline igneous rocks in variability in the original data-set (Panahi, Cheng, and the Gauteng and Mpumalanga districts as shown in Figure 7. Bonham-Carter, 2004). Therefore, PCA reduces the This may be due to clay and carbonate minerals having dimensionality and redundancy of data-sets and is commonly absorption in the 2.1–2.4 μm range (band 7 of Landsat 8) applied to enhance information interpretability (Cheng et al., and reflectance at 1.55–1.75 μm (band 6 of Landsat 8) 2011; Horel, 1984; Jolliffe, 2002). According to the algorithm properties. Van der Meer (2004) also reported the same for PCA, PCs are linear combinations of the original variables, absorption and reflectance bands for the clay minerals using whereas each PC incorporates the input variable uniquely and NASA’s Airborne Visible/Infrared Imaging Spectrometer signifies only limited information within the complete data- (AVIRIS) data. Another study, conducted by Zaini et al. set (Abdi and Williams, 2010). Due to its handling of (2016), concluded that clay and carbonates have the same multivariate data-sets, PCA has been extensively used in absorption and reflectance bands and these can be effectively remote sensing for geological mapping of ores, igneous rocks, used to map them using reflectance spectroscopy.

Table III ;:45;7==5.<279;3=+;:4=26/+8:;786:5)==26/+8:;786:5=-69=<:1;:2

%9#=:6# :;3*585=7*.< %.<279;3=+;:45 *.<=6-=/8:<9;3=<:1;:2<4= <-<9<:2<5

1 Kaufmann ratio 7 : 4 : 5 Red represents minerals containing iron ions; green (Kaufmann, 1988) 4 3 7 represents vegetated zones, and blue represent hydroxyl-bearing minerals.

2 Chica–Olma ratio 5 : 5 : 3 Red depicts clay; green represents iron ions; blue represents ferr in colour. (Mia and Fujimitsu, 2012b) 7 4 1

3 Sabins ratio 5 : 3 : 3 Yellow represents hydrothermal alteration areas; black identifies (Sabins, 2007) 7 1 5 water; dark green indicates vegetation, lighter green signifies clay-rich rocks; blue shows sand; red, pink or magenta indicates iron oxides.

4 Sultan’s ratio 5 : 5 : 5 × 3 Deep violet represents the hydroxyl minerals; (Gad and Kusky, 2006) 7 1 4 4 green ferric ions, and blue the ferrous oxides.

5 Abrams ratio 5 : 3 : 4 Hydrothermally altered iron- oxide represented as green and clay minerals as red. (Pour and Hashim, 2012) 7 1 5

VOLUME 119          
  
 283 L Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

in dark blue represent the iron deposits in Gauteng and Mpumalanga. In addition, the research conducted by Holmes and Lu (2015) supported the results of this study and highlights the potential of iron ore deposits in Gauteng and Mpumalanga. Gold cannot be ‘seen’ directly in any remotely sensed satellite image. However, the presence of this precious metal can be mapped through its association with several other minerals based on their spectral reflectances (Kotnise and Chennabasappa, 2015). The group of minerals present in the alteration zones related to gold deposits generally includes the clay minerals illite-1M and illite-2M1, dioctahedral smectite, and kaolinite (Drews-Armitage, Romberger, and Whitney, 1996). These minerals have characteristic spectral signatures mostly in the shortwave infrared portion of the electromagnetic spectrum. These spectral signatures can be used to map the sites that are most favourable for the occurrence of gold deposits, which is very cost- and time- (80,9<=&=26/+8:;786:=-69=+;:45=)=)="#= :1;:2<4=8/;0<5=$1<9< effective for mineral exploration programmes. The band 6,7296.=85=9<.9<5<:7<4=8:=51;4<5=6-=09<<:=;:4=!<0<7;786:=8:=4;9=9<4= combination of shortwave infrared 2 with spectral band 2.11– 2.29 μm and near infrared with spectral band 0.85–0.88 μm

(80,9<= &*.82;3=5.<279;3=9<-3<27;:2<=2,9!<=6-=896:=684<=8:=36;/=56835 ;7164=#)="'=

(80,9<= &=26/+8:;786:=-69=+;:45=)=)='#= :1;:2<4=8/;0<5=$1<9< 6,7296.=85=9<.9<5<:7<4=8:=51;4<5=6-=*<336$=

The iron oxides present within the study areas were highlighted by the spectral band ratio of red and blue bands as discussed in Table II. The soils rich in iron oxides reflect more in the red band of the spectrum, i.e. 0.64–0.67 μm and have absorption characteristics in the blue band i.e. 0.45– 0.51 μm (Schwertmann, 1993). The typical reflectance curve of iron oxide-rich soils is shown in Figure 8. Pour and Hashim (2015) have also shown the importance of the red and blue bands of Landsat data for mapping of iron oxides in Iran. In 2017, Pour et al., also identified the iron-rich mineralized zones of remote Antarctica from Landsat imagery by using spectral band ratio techniques. The map of potential iron oxides present in the study areas derived from the band ratio of the red and blue wavelengths of the spectrum is shown in Figure 9. This map showed a good agreement with the Council for Geoscience (CGS) map of iron deposits of (80,9<=&;:4=9;786=6-=9<4 =;:4=+3,< +;:4=<:1;:2<4=56835=$871 South Africa, as indicated in Figure 10. The areas highlighted .67<:78;3=896:=684<5=9<.9<5<:7<4=8:=51;4<5=6-=.,9.3<= L 284   
 VOLUME 119          
Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

(80,9<='&96:=4<.65875=6-=%6,71=-982;=6957<9)="'"+=

in Figure 11 shows the areas which have the potential to host clay minerals in shades of red to yellow. Liu et al. (2018) applied various image-processing techniques, including false-colour composite, band ratios, and matched filtering, to process ASTER satellite data and map the distribution of hydrothermal minerals associated with gold deposits, and concluded that the SWIR and NIR bands are the most effective for this purpose. In general, clay minerals, which are associated with gold mineralization potential, are more widespread in Gauteng Province compared to Mpumalanga Province (Durand, 2012; Sutton et al., 2006; Sutton, 2013). The approach that was applied to map potential gold mineralization in this study has also been applied by several other researchers. Safari, Maghsoudi, and Pour (2017) used a similar approach to identify gold mineralization and concluded that the integration of remote sensing data with other information led to the definition of locations possibly suitable for hosting Sn- W and Au-Ag occurrences. Another study, conducted by (80,9<=''&;:4=9;786=-69=<:1;:2

VOLUME 119          
  
 285 L Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

(80,9<='"&634=4<.65875=6-=%6,71=-982;=6957<9)="'";=

(80,9<='& ;,-/;::=;:4=%;+8:5=9;7865=9<.9<5<:78:0=1*49671<9/;3 /8:<9;35=8:=;,7<:0#=:=71<= ;,-/;::=9;786=/;.)=9<4=9<.9<5<:75 (80,9<='&;:4=9;786=-69=<:1;:2

(80,9<='==*49671<9/;3=/8:<9;35=/;.=0<:<9;794=+*=71<= 9657; (80,9<=' & ;,-/;::=;:4=%;+8:5=9;7865=9<.9<5<:78:0=1*49671<9/;3 7<21:8,<#=37<9;786:=6:<5=;9<=180138017<4=;5=+98017=9<086:5= /8:<9;35=8:=.,/;3;:0;#= 636,9=2648:0=;5=-69=(80,9<='= distinguished by bright pixels in PC6. PC5 can be used to paper, virtual verification, i.e. visual interpretation of map the hydroxyl-bearing minerals because of the positive absorption of spectral bands and comparison with the and negative eigenvalues of bands 7 and 5 respectively, and published maps by the CGS was used to evaluate the results these minerals appeared as dark. These selected PCs were of hydrothermal mineral exploration, along with the several further used in the Crosta technique; the hydroxyl (H) and similar research studies done by different researchers. Good iron oxide (F) images are combined with selected PCs to qualitative agreement was observed for the results of PCA produce a map revealing the pixels indicating abnormal and the spectral reflectance of the satellite data. concentrations of both hydroxyls and iron oxides. The PCs having positive eigenvalues from both input bands are selected for the analysis. Figure 16 shows the Crosta images 6:23,586:5 of hydroxyl (H), hydroxyl plus iron oxide (H+F), and iron This study confirms that Landsat reflectance spectroscopy oxide (F) as an RGB composite. This band combination data can be used easily and efficiently to map hydrothermal returns a dark bluish composite image on which alteration minerals. Different digital image processing algorithms and zones are highlighted as bright regions, as also discussed by techniques were applied to assess their significance for Ciampalini et al. (2013). hydrothermal mineral exploration. The principal component analysis (PCA)-based Crosta technique and band ratio    techniques like the Kaufmann and Sabins ratios proved to be The most common method to evaluate the results of this sort more significant and efficient for hydrothermal mineral of mineral mapping is by spectrometer and/or spectral testing exploration. Several researchers have also concluded that of samples in the laboratory. According to Clark (1999) there advanced image processing techniques like those applied and are two types of method for authentication of information tested in the current study are quite efficient in terms of extracted from remotely sensed imagery: virtual and in situ. mineral mapping through remote sensing data (Manuel et al., If the spatial and/or spectral resolution of remotely sensed 2017; Liu et al., 2018). The maps produced in this study are satellite data is fine and accurate then virtual verification can not only appropriate for any spatial queries and analysis, but be done by inspecting the remote sensing data directly and also for environmental modelling such as assessing the comparing it with already published reports or data. In this impacts of mining activities on environmental features such

Table IV 98:28.;3=26/.6:<:7=;:;3*585=6-=;:45;7=5;7<3387<=+;:45=-69=;,7<:0=;:4=.,/;3;:0;=

:.,7=+;:45  '  "       

Band 2 0.360613 -0.149047 -0.473757 0.642169 -0.156241 -0.431860 Band 3 0.346576 0.127976 0.409188 0.052900 -0.093199 0.827397 Band 4 -0.352093 -0.273256 0.602391 0.608503 0.463980 -0.352654 Band 5 -0.489315 0.846570 -0.302391 -0.155955 -0.127694 0.055763 Band 6 0.484542 0.143013 0.471431 0.321111 0.435239 -0.037414 Band 7 -0.389437 0.386786 -0.256332 0.295141 0.738839 0.005991 Eigenvalues (%) 94.53 7.93 3.67 0.08 0.04 0.001

VOLUME 119          
  
 287 L Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data as the forest, farmland, and urban areas. The hydrothermal CIAMPALINI, A., GARFAGNOLI, F., ANTONIELLI, B., MORETTI, S., and RIGHINI, G. 2013. minerals identified in this study are only the estimation Remote sensing techniques using Landsat ETM+ applied to the detection of iron ore deposits in Western Africa. Arabian Journal of Geosciences, vol. based on literature-cited, proven algorithms for remotely 6. pp. 4529–4546. sensed data, and should be treated as a preliminary CLARK, R.N. 1999. Spectroscopy of rocks and minerals, and principles of assessment of the study areas. The other important point to spectroscopy. Manual of Remote Sensing, vol. 3. pp. 2.2–2.4. consider is the resolution of the satellite data used in this CLARK, R.N., KING, T.V., KLEJWA, M., SWAYZE, G.A., and VERGO, N. 1990. High study; Landsat 8 has a 30–100 m spatial and moderate spectral resolution reflectance spectroscopy of minerals. Journal of Geophysical Research: Solid Earth, vol. 95. pp. 12653–12680. spectral resolution. Data-sets with this kind of resolution may DA CUNHA FRUTUOSO, R.M. 2015. Mapping hydrothermal gold mineralization suffice for regional work but not for detailed mineral using Landsat 8 data. A case of study in Chaves license, Portugal. mapping. Using satellite data with higher spatial and spectral https://sigarra.up.pt/fcup/pt/pub_geral.show_file?pi_doc_id=44053 resolutions, such as that from Worldview 3 satellite (Kruse, DABROWSKI, J.M., ASHTON, P.J., MURRAY, K., LEANER, J.J., and MASON, R.P. 2008. 2015) or aerial drones, may be more suitable for detailed Anthropogenic mercury emissions in South Africa: Coal combustion in power plants. Atmospheric Environment, vol. 42. pp. 6620–6626. minerals mapping. Nevertheless, the maps developed in this DI TOMMASO, I. and RUBINSTEIN, N. 2007. Hydrothermal alteration mapping using research are a valuable data source for comprehensive studies ASTER data in the Infiernillo porphyry deposit, Argentina. Ore Geology to be conducted in the future. The methodology developed in Reviews, vol. 32. pp. 275–290. this study is cost-effective and time-saving, and can be DREWS-ARMITAGE, S., ROMBERGER, S., and WHITNEY, C. 1996. Clay alteration and applied to inaccessible and/or new areas with limited ground- gold deposition in the Genesis and Blue Star deposits, Eureka County, Nevada. Economic Geology, vol. 91. pp. 1383–1393. based knowledge where reliable and up-to-date minerals DUCART, D.F., SILVA, A.M., TOLEDO, C.L.B., AND ASSIS, L.M.D. 2016. Mapping iron information is desired. oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil. Brazilian 2:6$3<40/<:75 Journal of Geology, vol. 46. pp. 331–349. Durand, J. 2012. The impact of gold mining on the Witwatersrand on the rivers The work presented in this paper is part of a PhD research and karst system of Gauteng and North West Province, South Africa. study in the School of Mining Engineering at the University Journal of African Earth Sciences, vol. 68. pp. 24–43. of the Witwatersrand. The authors would like to acknowledge EL-MAKKY, A.M. 2011. Statistical analyses of La, Ce, Nd, Y, Nb, Ti, P, and Zr in the administrative and financial support provided by School bedrocks and their significance in geochemical exploration at the Um Garayat gold mine Area, Eastern Desert, Egypt. Natural Resources of Mining Engineering, as well as the School of Advanced Research, vol. 20. pp. 157. Geomechanical Engineering (SAGE), at the National GABR, S., GHULAM, A., and KUSKY, T. 2010. Detecting areas of high-potential University of Sciences and Technology (NUST) Risalpur gold mineralization using ASTER data. Ore Geology Reviews, vol. 38. Campus, Pakistan. pp. 59–69. GAD, S. and KUSKY, T. 2006. Lithological mapping in the Eastern Desert of Egypt, the Barramiya area, using Landsat thematic mapper (TM). Journal <-<9<:2<5 of African Earth Sciences, vol. 44. pp. 196–202. ABDI, H. and WILLIAMS, L.J. 2010. Principal component analysis. Wiley GALE. 2017. Education, learning and research resources. https://www.gale.com/ Interdisciplinary Reviews: Computational Statistics, vol. 2. pp. 433–459. [accessed 15 November 2017]. ABHARY, A. and HASSANI, H. 2016. Mapping hydrothermal mineral deposits GHOLAMI, R., MORADZADEH, A., and YOUSEFI, M. 2012. Assessing the performance using PCA and BR methods in Baft 1: 100000 Geological Sheet, Iran. 2. of independent component analysis in remote sensing data processing. http://www.academia.edu/28268172/Mapping_Hydrothermal_Mineral_De Journal of the Indian Society of Remote Sensing, vol. 40. pp. 577–588. posits_Using_PCA_and_BR_Methods_in_Baft_1_100000_Geological_Sheet GRUNSKY, E.C., MUELLER, U.A., and CORRIGAN, D. 2014. A study of the lake _Iran sediment geochemistry of the Melville Peninsula using multivariate BEDINI, E. 2009. Mapping lithology of the Sarfartoq carbonatite complex, methods: applications for predictive geological mapping. Journal of southern West Greenland, using HyMap imaging spectrometer data. Geochemical Exploration, vol. 141. pp. 15–41. Remote Sensing of Environment, vol. 113. pp.1208–1219. HAN, T. and NELSON, J. 2015. Mapping hydrothermally altered rocks with BEMIS, S.P., MICKLETHWAITE, S., TURNER, D., JAMES, M.R., AKCIZ, S., THIELE, S.T., Landsat 8 imagery: A case study in the KSM and Snowfield zones, and BANGASH, H.A. 2014. Ground-based and UAV-based photogrammetry: northwestern British Columbia. British Columbia Geological Survey. A multi-scale, high-resolution mapping tool for structural geology and HOLMES, R. and LU, L. 2015. Introduction: Overview of the global iron ore paleoseismology. Journal of Structural Geology, vol. 69, no. 1. pp. 63–178. industry. Iron Ore. Elsevier. BERK, A., BERNSTEIN, L., ANDERSON, G., ACHARYA, P., ROBERTSON, D., CHETWYND, J., HOREL, J. 1984. Complex principal component analysis: Theory and examples. and ADLER-GOLDEN, S. 1998. MODTRAN cloud and multiple scattering upgrades with application to AVIRIS. Remote Sensing of Environment, Journal of Climate and Applied Meteorology, vol. 23. pp. 1660–1673. vol. 65. pp. 367–375. JOHNSON, J.R., BELL III, J.F., BENDER, S., BLANEY, D., CLOUTIS, E., EHLMANN, B., RAEMAN ASNAULT INCH E OUÉLIC BHATTACHARYA, S., MAJUMDAR, T., RAJAWAT, A., PANIGRAHI, M., and DAS, P. 2012. F , A., G , O., K , K., and L M , S. 2016. Constraints Utilization of Hyperion data over Dongargarh, India, for mapping on iron sulfate and iron oxide mineralogy from ChemCam visible/near- altered/weathered and clay minerals along with field spectral infrared reflectance spectroscopy of Mt. Sharp basal units, Gale Crater, measurements. International Journal of Remote Sensing, vol. 33. Mars. American Mineralogist, vol. 101. pp. 1501–1514. pp. 5438–5450. JOLLIFFE, I.T. 2002. Principal component analysis and factor analysis. Principal CALVIN, W.M., LITTLEFIELD, E.F., and KRATT, C. 2015. Remote sensing of Component Analysis. Springer. pp. 150–166. geothermal-related minerals for resource exploration in Nevada. KAISER, P.K., HENNING, J.G., COTESTA, L., and DASYS, A. 2002. Innovations in Geothermics, vol. 53. pp. 517--526. mine planning and design utilizing collaborative immersive virtual reality CHANDER, G. and MARKHAM, B. 2003. Revised Landsat-5 TM radiometric (CIRV). Proceedings of the 104th CIM Annual General Meeting. CIM, calibration procedures and postcalibration dynamic ranges. IEEE Montreal. Transactions on Geoscience and Remote Sensing, vol. 41. pp. 2674–2677. KAUFMANN, H. 1988. Concepts, processing and results. International Journal of CHAVEZ, P.S. 1996. Image-based atmospheric corrections-revisited and Remote Sensing, vol. 9. pp. 1639–1658. improved. Photogrammetric Engineering and Remote Sensing, vol. 62. KOTNISE, G. and CHENNABASAPPA, S. 2015. Application of remote sensing pp. 1025–1035. techniques in identification of lithological rock units in southern extension CHENG, Q., BONHAM-CARTER, G., WANG, W., ZHANG, S., LI, W., and QINGLIN, X. of Kolar Schist Belt from Chigargunta, Chittoor District, Andhra Pradesh to 2011. A spatially weighted principal component analysis for multi-element Maharajagadai, Krishnagiri District, Tamil Nadu. International Journal of geochemical data for mapping locations of felsic intrusions in the Gejiu Innovative Science, Engineering Technology, vol. 2, no. 11. mineral district of Yunnan, China. Computers & Geosciences, vol. 37. https://pdfs.semanticscholar.org/6015/c9bc313ed49aff69eace093634eeb2 pp. 662–669. b978e2.pdf L 288   
 VOLUME 119          
Mapping hydrothermal minerals using remotely sensed reflectance spectroscopy data

KRUSE, F.A. 2015. Comparative analysis of airborne visible/infrared imaging SABINS, F. F. 1999. Remote sensing for mineral exploration. Ore Geology spectrometer (AVIRIS), and hyperspectral thermal emission spectrometer Reviews, vol. 14. pp. 157–183. (HyTES) longwave infrared (LWIR) hyperspectral data for geologic SABINS, F.F. 2007. Remote Sensing: Principles and Applications, Waveland mapping. Proceedings of Algorithms and Technologies for Multispectral, Press. Hyperspectral, and Ultraspectral Imagery XXI. International Society for SAFARI, M., MAGHSOUDI, A., and POUR, A.B. 2017. Application of Landsat-8 and Optics and Photonics. 94721F. doi: 10.1117/12.2176646 ASTER satellite remote sensing data for porphyry copper exploration: a LIU, L., LI, Y., ZHOU, J., HAN, L., and XU, X. 2018. Gold-copper deposits in case study from Shahr-e-Babak, Kerman, south of Iran. Geocarto Wushitala, Southern Tianshan, Northwest China: Application of ASTER International, May 2017. pp. 1–16. data for mineral exploration. Geological Journal, vol. 53. pp. 362–371. SCHROEDER, T. A., COHEN, W.B., SONG, C., CANTY, M.J., and YANG, Z. 2006. LOUGHLIN, W. 1991. Principal component analysis for alteration mapping. Radiometric correction of multi-temporal Landsat data for characterization Photogrammetric Engineering and Remote Sensing, vol. 57. of early successional forest patterns in western Oregon. Remote Sensing of pp. 1163–1169. Environment, vol. 103. pp. 16–26. Maduaka, A.C. 2014. Contributions of solid mineral sectors to Nigeria’s SCHWERTMANN, U. 1993. Relations between iron oxides, soil color, and soil economic development. Eastern Mediterranean University (EMU) and formation. Soil Color. Bigham, J.M. and Ciolkosz, E.J. (eds.). Soil Science Doğu Akdeniz Üniversitesi (DAÜ). Society of America. pp. 51–69. MAHANDANI, S., PUTA, I., HIRAWAN, A., ABBAS, R., and TITISARI, A. 2018. SHORT, N.M. and LOWMAN JR, P.D. 1973. Earth Observations from Space: Integrated remote sensing and geological mapping to identify landslide Outlook for the Geological Sciences. Goddard Space Flight Center, prone zone in Loano, Purworejo, Central Java. Proceedings of EAGE-HAGI Greenbelt, MD. 1st Asia Pacific Meeting on Near Surface Geoscience and Engineering. doi: SONG, C. and WOODCOCK, C.E. 2003. Monitoring forest succession with 10.3997/2214-4609.201800372 multitemporal Landsat images: Factors of uncertainty. IEEE Transactions MAHBOOB, M.A., ATIF, I., and IQBAL, J. 2015. Remote sensing and GIS on Geoscience and Remote Sensing, vol. 41. pp. 2557–2567. applications for assessment of urban sprawl in Karachi, Pakistan. Science, SONG, C., WOODCOCK, C.E., SETO, K. C., LENNEY, M.P., and MACOMBER, S.A. 2001. Technology and Development, vol. 34. pp. 179–188. Classification and change detection using Landsat TM data: When and MAHBOOB, M.A., IQBAL, J., and ATIF, I. 2015. Modeling and simulation of glacier how to correct atmospheric effects? Remote Sensing of Environment, avalanche: A case study of gayari sector glaciers hazards assessment. vol. 75. pp. 230–244. IEEE Transactions on Geoscience and Remote Sensing, vol. 53. SUTTON, M., WEIERSBYE, I., GALPIN, J., and HELLER, D. 2006. A GIS-based history pp. 5824–5834. of gold mine residue deposits and risk assessment of post-mining land MANLEY, M. 2014. Near-infrared spectroscopy and hyperspectral imaging: non- uses on the Witwatersrand Basin, South Africa. Proceedings of Mine destructive analysis of biological materials. Chemical Society Reviews, Closure 3006. Fourie, A. and Tibbett, M. (eds.) Australian Centre for vol. 43. pp. 8200–8214. Geomechanics, Perth pp. 667–678. MANUEL, R., BRITO, M.D.G., CHICHORRO, M., and ROSA, C. 2017. Remote sensing SUTTON, M.W. 2013. Use of remote sensing and GIS in a risk assessment of for mineral exploration in Central Portugal. Minerals, vol. 7. p. 184. gold and uranium mine residue deposits and identification of vulnerable https://pdfs.semanticscholar.org/9b8a/8073aadc6d19c5e4f14f517fe4450 land use. MSc dissertation, University of the Witwatersrand. 96b8465.pdf http://wiredspace.wits.ac.za/handle/10539/12692 MARJORIBANKS, R. 2010. Geological mapping in exploration. Geological Methods TANGESTANI, M. AND MOORE, F. 2001. Comparison of three principal component in Mineral Exploration and Mining. Springer. analysis techniques to porphyry copper alteration mapping: a case study, MASEK, J.G., VERMOTE, E.F., SALEOUS, N.E., WOLFE, R., HALL, F.G., HUEMMRICH, Meiduk area, Kerman, Iran. Canadian Journal of Remote Sensing, vol. 27. K.F., GAO, F., KUTLER, J., and LIM, T.-K. 2006. A Landsat surface pp. 176–182. reflectance dataset for North America, 1990-2000. IEEE Geoscience and TEDESCO, S.A. 2012. Surface Geochemistry in Petroleum Exploration. Springer Remote Sensing Letters, vol. 3. pp. 68–72. Science & Business Media. MIA, B. and FUJIMITSU, Y. 2012. Mapping hydrothermal altered mineral deposits UDVARDI, B., KOVÁCS, I.J., FANCSIK, T., KÓNYA, P., BÁTORI, M., STERCEL, F., FALUS, using Landsat 7 ETM+ image in and around Kuju volcano, Kyushu, Japan. G., and SZALAI, Z. 2017. Effects of particle size on the attenuated total Journal of Earth System Science, vol. 121. pp. 1049–1057. reflection spectrum of minerals. Applied Spectroscopy, vol. 71. NOVAK, I. and SOULAKELLIS, N. 2000. Identifying geomorphic features using pp. 1157–1168. LANDSAT-5/TM data processing techniques on Lesvos, Greece. VAN DER MEER, F. 2004. Analysis of spectral absorption features in Geomorphology, vol. 34. pp. 101–109. hyperspectral imagery. International Journal of Applied Earth Observation PANAHI, A., CHENG, Q., and BONHAM-CARTER, G.F. 2004. Modelling lake sediment and Geoinformation, vol. 5. pp. 55–68. geochemical distribution using principal component, indicator kriging and VERMOTE, E., JUSTICE, C., CLAVERIE, M., and FRANCH, B. 2016. Preliminary analysis multifractal power-spectrum analysis: A case study from Gowganda, of the performance of the Landsat 8/OLI land surface reflectance product. Ontario. Geochemistry: Exploration, Environment, Analysis, vol. 4. Remote Sensing of Environment, vol. 185. pp. 46–56. pp. 59–70. VERMOTE, E. F., TANRÉ, D., DEUZE, J. L., HERMAN, M., and MORCETTE, J.-J. 1997. POUR, A.B. and HASHIM, M. 2012. The application of ASTER remote sensing Second simulation of the satellite signal in the solar spectrum, 6S: An data to porphyry copper and epithermal gold deposits. Ore Geology overview. IEEE Transactions on Geoscience and Remote Sensing, vol. 35. Reviews, vol. 44. pp. 1–9. pp. 675–686. POUR, A.B. and HASHIM, M. 2015. Regional hydrothermal alteration mapping VORSTER, C. 2012a. Simplified geology and gold deposits, South Africa Lesotho using Landsat-8 data. Proceedings of Space Science and Communication and Swaziland. Council for Geoscience, Pretoria, South Africa. (IconSpace) 2015. IEEE. pp. 199–202. http://www.geoscience.org.za/images/Maps/gold.gif POURNAMDARI, M., HASHIM, M. and POUR, A.B. 2014.Spectral transformation of VORSTER, C. 2012b. Simplified geology and iron deposits, South Africa Lesotho ASTER and Landsat TM bands for lithological mapping of Soghan and Swaziland. Council for Geoscience, Pretoria, South Africa. ophiolite complex, south Iran. Advances in Space Research, vol. 54, no. 4. http://www.geoscience.org.za/images/Maps/iron.gif pp. 694–709. WESSELS, R L., VAUGHAN, R.G., PATRICK, M.R., and COOMBS, M.L. 2013. High- RAMAKRISHNAN, D. AND BHARTI, R. 2015. Hyperspectral remote sensing and resolution satellite and airborne thermal infrared imaging of precursory geological applications. Current Science, vol. 108. pp. 879–891. unrest and 2009 eruption at Redoubt Volcano, Alaska. Journal of RATHOD, P.H., MÜLLER, I., VAN DER MEER, F.D., and DE SMETH, B. 2016. Analysis Volcanology and Geothermal Research, vol. 259. pp. 248–269. of visible and near infrared spectral reflectance for assessing metals in ZAINI, N., VAN DER MEER, F., VAN RUITENBEEK, F., DE SMETH, B., AMRI, F., and soil. Environmental Monitoring and Assessment, vol. 188. pp. 558. LIEVENS, C. 2016. An alternative quality control technique for mineral REPACHOLI, M. 2012. Clay Mineralogy: Spectroscopic and Chemical chemistry analysis of Portland cement-grade limestone using shortwave Determinative Methods. Springer Science & Business Media. infrared spectroscopy. Remote Sensing, vol. 8. p. 950. RICHTER, R. 1997. Correction of atmospheric and topographic effects for high ZANTER, K. 2016. Landsat 8 (L8) data users handbook. spatial resolution satellite imagery. International Journal of Remote https://landsat.usgs.gov/landsat-8-l8-data-users-handbook [accessed 20 Sensing, vol. 18. pp. 1099–1111. January 2018]. ROY, D.P., KOVALSKYY, V., ZHANG, H., VERMOTE, E.F., YAN, L., KUMAR, S., and ZHANG, X., PAZNER, M., and DUKE, N. 2007. Lithologic and mineral information EGOROV, A. 2016. Characterization of Landsat-7 to Landsat-8 reflective extraction for gold exploration using ASTER data in the south Chocolate wavelength and normalized difference vegetation index continuity. Mountains (California). ISPRS Journal of Photogrammetry and Remote Remote Sensing of Environment, vol. 185. pp. 57–70. Sensing, vol. 62. pp. 271–282. N

VOLUME 119          
  
 289 L Learn more: www.geobrugg.com/rockfall

GBE rockfall barriers made of high-tensile steel wire FOR AN ECONOMICAL SOLUTION TO ROCKFALL

Geobrugg Southern Africa (Pty) Ltd | Unit 3 Block B Honeydew Business Park | 1503 Citrus Street | Honeydew 2170 | South Africa | T +27 11 794 3248 | [email protected] | www.geobrugg.com

THE ORCID INITIATIVE – AUTHOR REGISTRATION

The SAIMM has joined the ORCiD initiative, and from 2019 authors (and co-authors) of papers submitted to the Journal or conferences will need to include their ORCiD identifiers (ORCiD iDs). An ORCiD is a persistent digital identifier that distinguishes authors from every other researcher, using a 16-digit code, e.g. https://orcid.org/0000-0002-3843-3472. ORCiD (Open Researcher and Contributor ID) is a is an open, not-for-profit organisation with the aim of providing a persistent and unique digital identifier – an ORCiD (pronounced ORC-iD) – to any individual who is involved in research, scholarship, and innovation activities, similar to the way in which the digital object identifier (DOI) constitutes a persistent identity for documents on digital networks. The ORCID record can be enhanced with the registrant’s professional information and linked to other identifiers (such as Scopus, ResearcherID, or LinkedIn). The National Research Foundation (NRF) in South Africa requires that all researchers and students ap- plying for funding and rating at the NRF have an ORCiD identifier. This allows them to uniquely identify themselves as the author of their work across all systems integrated with the ORCID registry. Unique identification is particularly import when a researcher’s citations are assessed. If there is any confusion about an author’s details then the citations are separated, e.g. JA Smith, John Smith, J Smith. Citation counters will interpret these formats as three different people. Using an ORCiD will automatically group all this individuals research together. There are currently 1025 ORCiD member organisations, including publishers, research institutes, universities, professional associations, and funding agencies, and around 6 million registrants. To obtain your unique ORCiD identifier, register now at https://ORCiD.org/register The process is simple and takes less than a minute. http://dx.doi.org/10.17159/2411-9717/2019/v119n3a8 The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery, South Africa by M. Katuruza1 and C. Birch2

the absence of a short-term geological model that could be used for short-term mine &%.5+/1/ planning. Short-term models are built by mine The purpose of this study was to demonstrate unmanned aircraft system geologists, when they take the latest release of (UAS) technology in opencast highwall mapping using the experience at the resource geological model and add in data Isibonelo Colliery in Mpumalanga Province of South Africa. In opencast as it becomes available from progressive mines, geological mapping has evolved over time and there have been challenges in extracting valuable information from exposed highwalls due mining. The data includes surveyed highwall to restricted access for safety reasons. A UAS was used at Isibonelo seam-roof and/or seam-floor contacts, faults, Colliery to conduct highwall mapping, using drone-based digital dykes, blast-hole data, grade control hole data, photogrammetry techniques. A demonstration survey was undertaken and any other measurements deemed during February 2018. The highwall flyover demonstration was planned necessary for modelling. Highwall mapping for two areas (North and South pits) where field control points were with a survey total station is standard practice placed by the mine survey department. A contractor used a DJI Phantom 4 at Isibonelo Colliery. Recent technological (Pro) for the highwall mapping. Raw data was processed within 48 hours advances have made new digital and a 3D model of the mapped pit area was produced. Further data photogrammetry techniques available for extraction included obtaining updated weathering and lithological contact mapping, with a camera being carried by a elevations and thicknesses for use in short-term planning. The results UAS which does highwall mapping. The showed a good correlation between the resource model and the UAS data model. The project was considered a success and highwall flyover mapping process of short-term geological modelling and is now standard practice at Isibonelo Colliery. allows for the incorporation of small-scale features, such as seam rolls and previously 6%54*/ unidentified faults, which may not be obvious geological model, highwall mapping, coal mining, unmanned aircraft from broadly spaced exploration drill-hole systems, UAS, drone, photogrammetry. data.

'67&726!'.5-5)%73.* +'525)43,,6241!7+45!6//1.) .245*0!215.7 UAS technology has developed rapidly in Detailed geological mapping is crucial to the South Africa in the last 6 years, following the understanding of the structure of any mineral regularization of its use by the country’s deposit. Several mapping methods may be controlling body, the South African Civil applied depending on the available Aviation Authority (SACAA). These aircraft exposure/outcrop and nature of the orebody; are also referred to as unmanned aerial for example, coal deposits typically suboutcrop vehicles (UAVs) or remotely piloted aircraft only, therefore an opencut highwall provides (RPAs). (Bucalo et al., 2015). The latest data the best exposure for mapping the geology. from Business Insider indicates that there are Mapped information, when incorporated into a 686 operators with remote pilot licences resource model (generated from exploration (RPLs) in South Africa. (Caboz, 2018). borehole data), improves the understanding of the orebody or coal seam. This research paper focused on the use of unmanned aircraft system (UAS) technology for pit highwall mapping to generate data for updating geological models and avail the latest information to mine planning to improve the 1 Geology Manager–Production, Isibonelo Colliery, short-term plans. Anglo American Coal, South Africa. 2 School of Mining Engineering, University of the The Isibonelo Colliery’s geological model is Witwatersrand, South Africa. updated annually and is termed a resource © The Southern African Institute of Mining and geological model, from which the mining Metallurgy, 2019. ISSN 2225-6253. Paper received model is built. This research was motivated by Oct. 2018; revised paper received Feb. 2019.

VOLUME 119          
  
 291 L The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery

UASs are used for geological and topographic mapping, matched image pairs. The result of the triangulation process coastal control, landslide inspections, and are capable of is initially a sparse point cloud. Finally, a dense point cloud integrating geophysical instrumentation like magnetic, was produced for the highwall map. The greater the amount electromagnetic, infrared, radar, and natural gamma ray of collected high-resolution images, the more detailed the sensors (Bucalo et al., 2015). Therefore, UASs have become model produced, a dense 3D image of the pit. a very important tool in the field of geoscience. The UAS The generated drone data model was validated against discussed here uses a high-resolution camera that provides the resource model and actual survey data. CloudCompare, a excellent ground coverage. The aircraft are generally 3D point cloud manipulation software package, was used to inexpensive, with small commercial systems like the DJI extract geological mapping data from the drone data model, Phantom 4 costing a few thousand rands. UASs are good at which was then exported to Stratmodel (the geological focusing on specific areas and do not require excessive flight modelling software used at Isibonelo) for update of the short- lines to cover an area of interest. term geological model. UASs are a useful tool for extracting geological information from inaccessible areas. Data is generated '67/15.6-57&7'1)'3--7,3++1.)769+6416.!677 rapidly; an area that takes three days of physical mapping Isibonelo Colliery is situated near the northern margin of the may take only an hour or less to capture with a UAS. On Highveld Coalfield of Mpumalanga Province (Figure 2). The completion of the UAS survey, the captured data is processed area is underlain by sedimentary strata of the Karoo to produce a 3D surface model. In an open pit setting. The Supergroup, which was deposited in the Permian period lithological contacts can then be mapped from the 3D model. (248–290 Ma) (Anhaeusser and Maske, 1986). The Karoo Figure 1 shows one of the most modern UAS platforms used sequence is made up predominately of sediments and is in South Africa, the DJI Phantom 4. capped by a sequence of volcanic strata. Three stratigraphic The DJI Phantom 4 has a camera with the capability of units define the sedimentary succession of the Karoo recording in RAW image format, which makes editing even Supergroup. From oldest to youngest, these are the Dwyka, easier. (Caboz, 2018). It is fitted with a 1-inch 20-megapixel Ecca, and Beaufort groups (Cadle, 1995). Coal seams of the sensor capable of shooting 4K/60fps video. Previously, the perspective gained from the UAS could only be attained from a manned aircraft, such as a helicopter. With the UAS it is possible to obtain digital images of the highwall as well as a multitude of digital terrain points, all in 3D space. ‘Structure from Motion or SfM is a photogrammetric method for creating three-dimensional models of a feature or topography from overlapping two-dimensional photographs taken from many locations and orientations to reconstruct the photographed scene.’ (Ullman, 1979). Thus, the software processes digital photographs, forming a 3D surface image or point cloud that can be compared against the 3D geological model. Software packages like Agisoft, 3-D Rippler, and Geo Arc use algorithms (mathematical descriptors of each feature on the images) to create a 3D image through triangulation of (1)0467# 7'3.25,77457&7"35$7# 7

(1)0467 5!3215.7,3+757/15.6-575--164%7"32040373.*7 61.)/$7# L 292   
 VOLUME 119          
The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery

Highveld Coalfield are hosted within the Vryheid Formation of the Middle Ecca Group (270 Ma). Sediments of the Vryheid Formation represent coal-capped upward-fining cycles of clastic sediments deposited in a fluviodeltaic/shallow marine environment. After considering several options for highwall mapping (e.g. total station survey) at Isibonelo, so that geological data could be produced for the short-term geological modelling, a UAS flyover was eventually given a trial in February 2018. The demonstration was carried out by Vidblast (Pvt) Ltd and Premier Mapping. Permissions and flight planning were needed before the survey could be undertaken. The planning included delineation of the mapping area and determining the position of the surveyed marker pegs, which serve as ground control points (GCPs) for the survey. The coordinates (in .csv format) of the control pegs were sent to the service provider for flight (1)0467 /15.6-575--164%7/046%7*6,5./243215.73463/7"%6--5 planning purposes. 46!23.)-6/ The demonstration was planned to cover selected areas in both the North and South pits. Figure 3 is an overview reference map of the survey areas. Highwall mapping focused on delineation of the weathering horizons, namely the base horizon of ‘softs’, which include soils and sands (BHSO), the base horizon of friable weathering (BHFW), the base horizon of weathering (BHWE), and finally the interburden and the coal seams (no. 5 and no. 4 seams). Figure 4 illustrates typical weathered horizons of a highwall where the UAS flyover mapping project was conducted at Isibonelo Colliery. The South pit survey covered the furthest southern area between the S5 and S6 ramps, through to the end of the cut. For the North pit, the survey was between the N1 and N2 ramps (strip 31 and strip 32). Figure 5 illustrates the UAS flyover focus area in the North pit, as planned in the survey office in conjunction with the author The UAS demonstration flight was planned for both pits (1)0467 %+1!3-7'1)'3--7/52/
7,3++1.)7327/15.6-575--164% on the same day. The area delineated in yellow in Figure 5 "320403$7# was defined by control points pegged on the ground by the surveyor prior to the flight. control points if required. Additional control points were Since this was the maiden flight, the process required a pegged on the day of the flight to ensure optimal surveyor on site on the day of the flight to provide additional georeferencing of the final 3D model.

(1)0467 &7-%5647542'7+127"&046%76+342,6.2$7/15.6-575--164%

VOLUME 119          
  
 293 L The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery

The demonstration flight was conducted by a licenced and is shown in Figure 9. There is a good correlation UAS pilot using the DJI Phantom 4. The UAS was flown from between the model contact and the results from the UAS a mini-pad at the back of a utility vehicle parked on the data. dragline walkway bench on the low wall (spoils) side of the The highwall UAS mapping technique is quick in pit. The flight height was 50 m above the pit, with six flight generating geological data for updating geological models lines being flown, each 500 m in length with a spacing of (short-term modelling) compared to the total station highwall 60 m between lines. mapping technique, which is time-consuming and prone to human error. &7*3237+45!6//1.) The data resolution is exceptionally high, with a point cloud density of 13 million over an area of 120 000 m2 for The data produced during the highwall mapping consisted of the South pit demo area. 3D point clouds comprising 13 million data-points over the South pit and 11 million data-points over the North pit. These were produced from digital photographs with a 60% 5.!-0/15./73.*746!5,,6.*3215./77 overlap between images in the series. The UAS captured finer The spatial accuracy of the UAS data is high and eliminates structures along the highwall with its high-resolution human error when mapping the lithological contacts. The camera. The data was processed using Agisoft, a 3D geological contacts are well defined in the 3D point cloud photogrammetry software package for drone data processing. data, with the contacts already in a 3D coordinate system Agisoft builds a 3D point cloud using SfM. The data points compatible with the geological model at Isibonelo Colliery. were first cleaned out to remove any anomalies, especially A UAS flyover generates data within minutes (e.g. 35 the machinery that was working in the pit during the flyover, minutes over an area 500 m × 240 m) over a very large area as this can distort the model. The GCPs assisted in of the open pit. Furthermore, the digital photographs provide georeferencing of the model within the surveyed area. The a usefull reference tool during the 3D modelling process. The control points pegged on the ground are visible in the image turnaround time, from survey to completion of data of the model (Figure 6). processing, including a 3D model of the flown highwall area, The software also processed the digital photos to form a can be as little as 48 hours, which is needed for decision- 3D surface image, or textured mesh. making in mining. CloudCompare was used to compare the data provided by There is also the scope for zooming into specific problem this survey to 3D data from the resource model. The UAS areas and extracting additional information without model was further validated by a surveyor and geologist who mapped the no. 4 and no. 5 seam top and bottom contacts in selected places, using a total station. The total station observations are shown on the 3D mesh model in Figure 7.

.3-%/1/75746/0-2/77 Figure 8 illustrates a comparison of the bottom and top contacts of the sandstone (as derived from drone data) to the BHFW from the resource model. The sandstone contacts are currently not modelled in the resource model (using the defined weathering surfaces only from borehole data). This is the reason for the short-term model intervention. The no. 4 seam top contact from the UAS data was compared to the geological model at the same point in space (1)0467 (347&502'7+12$7&7 7,6/'7,5*6-7"*6740%.$7#

(1)0467 (347&502'7+127,3++6*7.577/63,73.*7.57 7/63,7!5.23!2/712'72523-7/23215.7+51.2/7,346*7"32040373.*74625410/$7# L 294   
 VOLUME 119          
The use of unmanned aircraft system technology for highwall mapping at Isibonelo Colliery

(1)0467 (347&502'7+127/3.*/25.6746/504!67!5,+346*712'7&7*3237,5*6-7"4625410/$7#

(1)0467 &241+#7.577/63,74557&7!5,+346*712'746/504!67,5*6-7"320403$7#

compromising the safety of man and machinery. This is not Technology. http:// www.adamtech.com.au/3dm/goonyella% possible with conventional highwall mapping, which is 20report%20(abridged).pdf limited by access. The UAS highwall mapping technique BUCALO, F., D'ALLESANDO, A., COLTELI, M., and MARTORANA, R. 2015. Drones: new technologies for geophysics? Near Surface Geoscience 2015. Proceedings proved it can generate large volumes of useful geological data of the 21st European Meeting of Environmental and Engineering over a short period of time, something not achievable Geophysics, Turin, Italy. European Association of Geoscientists & through physical mapping. Engineers, The Netherlands. pp. 6–10. The availability of new UAS technologies coupled with CABOZ, J. 2018. Business Insider South Africa. photogrammetry software to process data has improved the https://www.businessinsider.co.za/sas-most-popular-drone-remains-way- ahead-of-its-competitors-here-are-the-5-reasons-why-2018-3 speed and accuracy of geological data acquisition and CADLE, A.B. 1995. Depositional systems of the Permian Vryheid Formation, interpretation at Isibonelo Colliery. Highveld Coalfield, South Africa, Their relationship to coal seam occurence Geologists should be equipped with this new technology and distribution. PhD thesis, University of the Wistwatersrand, to update short-term geological models timeously. Training Johannesburg on software for building 3D models and extrapolation of data DE BRUYN, D. 2018. Drone hole identification. Johannesburg. Unpublished is also recommended for geologists using UAS for highwall report. mapping. KATURUZA, M. 2017. Competent Person Report, Resources Isibonelo Colliery. Unpublished meport In addition to highwall mapping, UAS technology is KATURUZA, M. 2017. Competent Person's Report for Isibonelo Colliery. exceptionally useful in a mining environment, having Unpublished, mine internal document. numerous other applications which include blast monitoring, KATURUZA, M. and LEVINGS, S. 2017. Isibonelo Colliery CPR presentation. stockpile reconciliations, in-pit coal reconciliation, and Unpublished internal presentation. inspection of mine infrastructure. KATURUZA, M. and PRETORIUS, D. 2018. Improving short term modelling using drone data at Isibonelo Colliery. Unpublished internal document. PRETORIUS, D.J. 2018. Isi drone data. Unpublished internal report. 86646.!6/ ULLMAN, S. 1979. Structure from motion (SfM) photogrammetry. Proceedings ANHAEUSSER, C.R. and MASKE, S. 1986. Mineral Deposits of South Africa (Vols. the Royal Society B, vol. 203, no. 1153. The Royal Society, London: 1-2). Geological Society of South Africa, Johannesburg. pp. 405–426. : https://royalsocietypublishing.org/doi/abs/10.1098/ BIRCH, J. 2004. 3DM Analyst 2.1 trial at BMA Coal’s Goonyella Mine. ADAM rspb.1979.0006 N

VOLUME 119          
  
 295 L Hydrometallurgy Colloquium Impurity removal in hydrometallurgy 21–22 May 2019

Glenhove Conference Centre, Melrose Estate, Johannesburg

BACKGROUND WHO SHOULD ATTEND Removal of impurity metals plays a very important role in > Process engineers (chemical, metallurgical) who would like the fi nal grade and quality of the target metals recovered in a refresher course or enhance their knowledge on techniques hydrometallurgical processes. From base to precious metals, a used for impurity removal in hydrometallurgy. proper consideration of a metal separation and impurity removal > Graduates from other disciplines such as chemistry or circuit can have a huge impact on the success of an operation. Th is environmental science, who are involved in related work. course aims to enhance knowledge in the separation and removal > Plant operators who wish to enhance their skills and of metal ions in solution, with focus being on solvent extraction, knowledge. ion exchange, precipitation cementation, membrane separation. Selected current practice and new technologies applicable to base > University postgraduate students. metals, precious metals, uranium etc. will be considered.

TOPICS Day 1 — Fundamentals

> Precipitation > Cementation > Membrane separation > Solvent extraction > Ion exchange Day 2— Case Studies

> Practical — Case studies FOR FURTHER INFORMATION CONTACT: Yolanda Ndimande, Conference Co-ordinator, SAIMM P O Box 61127, Marshalltown 2107 · Tel: +27 (0) 11 834-1273/7 E-mail: [email protected] · Website: http://www.saimm.co.za

Conference Announcement http://dx.doi.org/10.17159/2411-9717/2019/v119n3a9 Optimization of conditions for the preparation of activated carbon from olive stones for application in gold recovery by M. Louarrat1, G. Enaime1, A. Baçaoui1, A. Yaacoubi1, J. Blin2, and L. Martin2

(Yalcin and Arol, 2002; Gratuito, 2008), palm shells (Sumathi, 2009), cherry stones .BC6?F? (Jaramilloa, Gomez-Serrano, and A´lvareza, The purpose of this study is to prepare a new activated carbon from olive 2009), macadamia nut shells (Eddy, 2011), stones for use in gold recovery by carbon-in-leach (CIL) and carbon-in- apricot stones (Soleimani and Kaghazchi, pulp (CIP). The preparation method chosen was physical activation using 2008), and bagass (Syna and Valix, 2003). steam. The effect of four process parameters: the residence time for There are basically two methods of carbonization, the activation temperature, the residence time for preparing activated carbon: physical or activation, and steam flow, were studied by the mean of response surface chemical activation. Physical activation is most method (RSM) in order to optimize the yield, iodine index, and attrition commonly used. This thermal gas process is a characteristics. These two last responses were used as primary indicators two-step process. The production of activated of gold recovery capacity and mechanical strength. The results obtained show that optimal activated carbon can be prepared under the following carbon by the thermal route starts with conditions: a carbonization time of 157 minutes, activation at 921°C for 53 carbonization, followed by activation. During minutes, and a water vapour flow of 0.18 mL/min. This optimum carbon activation the carbonized product develops an has an iodine value greater than 1100 mg/g and an attrition index in the extended surface area and a porous structure order of 0.74%. These values reflect the quality of the precursor (olive of molecular dimensions. Activation is stones) as a raw material for the development of an effective new generally conducted at temperatures between activated carbon for the gold mining industry. 800 and 1100°C in the presence of a suitable E.&CA>? oxidizing agent such as steam, air, or carbon olive stones, activated carbon, response surface method (RSM), physical dioxide. activation, gold recovery. Activated carbon has had a tremendous impact on the technology and economics of gold recovery. The main advantages of activated carbon are: its high selectivity towards gold relative to base metals, its ease of elution, and its large particle size (Arriagad $BDAC>;@DFCB and Garcia, 1997). It should be noted that the Activated carbon is an effective adsorbent physical and chemical properties of the widely used in industry due to its high surface activated carbon used can strongly affect the area, well-developed reproducible microporous amount of gold adsorption. The primary structure, and high degree of surface reactivity criteria for activated carbon intended for use in and adsorption capacity. World consumption of a gold adsorption process are as follows activated carbon is steadily increasing. It is (Yalcin and Arol, 2002; Gergova, Petrov, and primarily used in industrial wastewater and Minkova, 1993): gas treatment. and also for silver and gold ® High adsorption capacity recovery from cyanide solutions (Syna and ® High adsorption rate Valix, 2003; Soleimani and Kaghazchi, 2008; ® Good resistance to abrasion. Buah and Williams, 2010; Eddy et al., 2011). However, activated carbon is expensive and it needs to be regenerated after each adsorption cycle. In order to decrease the cost of manufacturing activated carbon, low-cost forest and agricultural wastes are considered promising new materials. In recent years considerable research has been reported on 1 Laboratory of Applied Chemistry, Department of activated carbon from agricultural wastes, Chemistry, Morocco. 2 Centre for International Cooperation in Agronomic such as olive stones (Yavu et al., 2010), acorn Research for Development (Cirad), France. shells (Sahin and Saka, 2013), peanut shells © The Southern African Institute of Mining and (Wu, Guo, and Fu, 2013), grape seeds Metallurgy, 2019. ISSN 2225-6253. Paper received (Jimenez-Cordero, 2014), coconut shells Jun. 2018; revised paper received Aug. 2018.

VOLUME 119          
  
 297 L Optimization of conditions for the preparation of activated carbon from olive stones

In gold recovery plants, activated coconut-shell carbons and fixed carbon) allows prediction of certain behaviours in have been the preferred adsorbent for many years, due to the pyrolysis processes based on a standard method (Norme their resistance to abrasion and selectivity for gold. However, AFNOR XP CEN/TS 14 774-3). increasing gold production necessitates the exploitation of other sources. Many research investigations published *')#* * recently used low-cost precursors such as apricot stones, The thermogravimetric analyses of olive stones were peach stones, hazelnut shells, bagasse, and macadamia nut conducted by a simultaneous TGA-DTA instrument (Setaram shells (Yalcin and Arol, 2002; Syna and Valix, 2003; Souza et Instrumentation) in an air atmosphere at a heating rate of al., 2004; Mansooreh Soleimani et al., 2008; Gerrard Eddy et 10°C/min to attain a maximum temperature of 930°C. al., 2011; Raminez-Muniz, 2010; Mpinga et al., 2014) to FTIR spectroscopy provides information about chemical produce an adequate activated carbon. characterization of the functional groups in olive stones and The aim of this study was to evaluate olive stones as an the resulting activated carbon. The FTIR spectra were alternative raw material to coconut shells for the production recorded between 400 and 4000 cm−1 using a PerkinElmer of activated carbon used in gold metallurgy. The spectrometer. characteristics of the activated carbon prepared under optimal conditions were compared with those of the commercial &!&"&
*')'" %+% carbon (GoldSorb). To our knowledge, this is the first time The morphology of the activated carbon prepared under the that olive stones have been used as a precursor for the optimal conditions was observed using scanning electron preparation of activated carbon for gold applications. microscopy (VEGA3 TESCAN instrument).

GDEAFGH=ED1C>?H &#+)$*)$! ! "! #! The iodine number of the prepared activated carbon was Olive stones from Marrakech Province in Morocco were used. measured by titration based on the standard method ASTM D The material was crushed to between 3.15 and 4 mm, rinsed 4607-94 (ASTM. 2006). with water to remove traces of olive pulp, and dried in the ((!+(+&) drying oven overnight at 105°C. Activated carbon hardness was determined using a wet ! #! # "!"! # ! # " attrition test as described by Toles et al. (2000). The fraction of granular activated carbon between 0.5 and 2 mm was used Carbonization was carried out in a Carbolite type CTF for the attrition tests. One gram of granular activated carbon 12/65/650 programmable electrical furnace. A mass of 30 g was added to 100 mL of acetate buffer in a 150 mL beaker. of olive stones was introduced into the reactor, which was The solution was stirred for 24 hours at 25°C on an IKA heated to the desired temperature of 500°C and maintained magnetic stirrer at 500 r/min using 0.500 stir bars. The for different residence times in a nitrogen flow. samples were then poured onto a 0.3 mm screen and the The activation process was carried out in the same retained carbon was washed with 250 mL distilled water. furnace. The activation time was between 30 to 120 minutes, After washing, the retained carbon was dried at 110°C for 2 and the activation temperature was between 800 and 950°C hours. The sample was removed and allowed to cool in a in a steam flow of 0.1 to 0.2 mL/min. desiccator and weighed. The percentage attrition was The resulting activated carbon was rinsed for 30 minutes calculated as: with distilled water and dried. A portion was ground and sifted to obtain a powder with a particle size smaller than % Attrition=([(initial wt (g)–final wt (g)))⁄ 45 μm, and the powder was then dried and kept in a hermitic (initial wt (g)]) × 100 bottle for iodine testing. The rest of granular activated carbon was used for attrition, bulk density, and kinetic activity "*#$)%+( testing. Apparent or bulk density is a measure of the weight of the The activated carbon mass yield was determined from the material that is contained in a given volume under specified following equation: conditions. A 10 mL cylinder was filled to a specified volume (Yield = (Activated carbon weight)⁄(Raw material with activated carbon that had been dried in an oven at 80°C weight)) × 100 for 24 hours. The cylinder was weighed. The bulk density was then calculated according to the method of Snell and !! #! # " Ettre (1968): Bulk density = (weight of dry material(g))⁄ "$$)('"*')'" %+% (volume of packed of dry material(ml)) The determination of the total content of carbon, hydrogen, and nitrogen for the raw material (in our case olive stones) is #%&!(+&)*($%( based on the standard method (XP CEN/TS 15104, Afnor Essentially, all procedures used to determine the kinetic Group, 2005), but for activated carbon the determination is activity involve contacting a known mass of carbon with a based on the standard method ASTM D5373 (ASTM, 2016). solution of known initial gold concentration, collecting and analysing samples of the solution over a period of time, and )+(+'"*')'" %+% then calculating the activity of the carbon sample based on The initial analysis (moisture, ash content, volatile matter, the data obtained. L 298   
 VOLUME 119          
Optimization of conditions for the preparation of activated carbon from olive stones

In this study, the activated carbon activity was usually individual and interaction effects of various parameters. Four determined based on the Mintek method (Staunton, 2016). variables were investigated in this study: residence time for The activated carbon was separated from the solution by carbonization (X1), temperature of activation (X2), residence filtering, and the gold concentration of the solution was time for activation (X3), and steam flow (X4). Table I shows measured by atomic absorption spectrophotometry (AAS) the ranges and levels of the four independent variables with (Unicam model 939 instrument) using an air-acetylene flame actual coded values of each parameter. The independent and absorbance peak at a wavelength of 242.8 nm. The variables are coded to two levels, namely low (–1) and high quantity of gold absorbed onto the activated carbon was (+1). The yield of activated carbon (Y1), iodine number (Y2), calculated from the difference between the initial and final and attrition (Y3) were analysed as responses. gold concentration in the solution. For this study, response surface methodology based on empirical mathematical modeling was used. More precisely, a * ')+#'(+&)*($%(% second-order polynomial model was postulated to capture the The cyanidation tests using the CIL technique were carried possible nonlinear effects and curvature in the domain: out according to the experimental methodology used by various authors (Staunton, 2016). The gold ore used in this study was a residue from cobalt extraction, containing 24% moisture. The samples were pulped with water. Cyanidation was carried out in beakers at a pulp density of 1.24, stirring for 12 hours in the presence where Y is predicted response, Xi ( i = 1,2…n) the of a solution of 0.8 g/l free cyanide at a pH of 10.5 adjusted unidimensional variables. with quicklime. Periodic checks of free cyanide and pH were The Doehlert experimental design and the corresponding carried out and the desired values were maintained by the experimental conditions and responses are given in Table II. addition of cyanide and quicklime. For adsorption of the gold cyanide complex, activated carbon of particle size between 1.4 and 2 mm was added at a dosage of 20 g per litre of solution. The pulp was then screened at 1 mm to recover the Table I activated carbon. The solution was filtered and the solids !)6EAF=EBDGHE6EB>EBD dried. Samples of the solution, solids, and activated carbon were taken to determine the gold concentration by AAS. 8GAFG9

    " " # !"# %C>E +GAFG9

The carbonization and activation optimization were studied X1 Carbonization time min 0 120 240 using response surface methodology and multi-criteria X2 Activation temperature °C 800 875 950 optimization with a Doehlert design and desirability function X3 Activation time min 30 75 120 X4 Steam flow mL/min 0.10 0.15 0.20 (Doehlert, 1970). This method helps to optimize the

Table II

CE1E?F7B"HE)6EAF=EBDGFDFCB?"HGB>HAE?6CB?E?,H-2H.FE<>"H-0HFC>FBEHG>?CA6DFCB @G6G@FD."H-*HGDDAFDFCB

!)6EAF=EBDHBC, 2 0 *  5(4 -2 5=7#74 -0 5(4 -*

1 1.0000 0.0000 0.0000 0.15 15.19 922.00 1.72 2 -1.0000 0.0000 0.0000 0.15 19.75 823.60 0.11 3 0.5000 0.8660 0.0000 0.15 15.26 992.90 1.59 4 -0.5000 -0.8660 0.0000 0.0000 25.33 599.52 0.02 5 0.5000 -0.8660 0.0000 0.0000 19.83 666.37 2.01 6 -0.5000 0.8660 0.0000 0.0000 17.05 976.25 2.12 7 0.5000 0.2887 0.8165 0.0000 12.16 922.00 2.94 8 -0.5000 -0.2887 -0.8165 0.0000 23.21 747.10 0.17 9 0.5000 -0.2887 -0.8165 0.0000 23.03 743.09 0.11 10 0.0000 0.5774 -0.8165 0.0000 20.50 951.59 0.19 11 -0.5000 0.2887 0.8165 0.0000 13.25 1097.62 2.65 12 0.0000 -0.5774 0.8165 0.0000 17.70 958.62 1.28 13 0.5000 0.2887 0.2041 0.7906 15.11 1042.79 1.93 14 -0.5000 -0.2887 -0.2041 -0.7906 19.31 867.70 1.86 15 0.5000 -0.2887 -0.2041 -0.7906 22.50 733.12 0.51 16 0.0000 0;5774 -0.2041 -0.7906 17.57 939.40 2.39 17 -0.5000 0.0000 0.6124 -0.7906 18.06 915.24 2.27 18 0.0000 0.2887 0.2041 0.7906 13.98 1090.28 2.53 19 0.0000 -0.5774 0.2041 0.7906 20.08 866.02 0.92 20 0.0000 0.0000 -0.6124 0.7906 20.04 889.80 0.34 21 0.0000 0.0000 0.0000 0.0000 19.36 800.97 1.12 22 0.0000 0.0000 0.0000 0.0000 18.26 889.79 0.43 23 0.0000 0.0000 0.0000 0.0000 18.80 818.72 0.66 24 0.0000 0.0000 0.0000 0.0000 19.03 755.62 0.77 25 0.0000 0.0000 0.0000 0.0000 17.86 874.98 0.32

VOLUME 119          
  
 299 L Optimization of conditions for the preparation of activated carbon from olive stones

The centre points are repeated five times in order to calculate vibration at 1463, 1425, 1380, 1330 cm–1 can be allocated to the variance of experimental error and to test the the asymmetric and symmetric bending (C-H) due to the reproducibility of the data. The experiments were carried out bands of methylene and methyl groups (Sundqvist, Karlsson, in a random order to minimize the effect of systematic errors. and Westermark, 2006). The band at 1253 cm–1 can be The models were validated using analysis of variance attributed to (C-O) asymmetric stretching of aromatic ethers, (ANOVA). They were also checked by the correlation esters, and phenols. The stretch vibration from acids, coefficient (R2) and the adjusted determination coefficient alcohols, phenols, and esters are observed in the relativity 2 (R A) in order to measure the proportion of the total intense bands at 1157 and 1041 cm–1. The deformation of observed variability described by the model (Bacaoui et al., the (C-H) bond in aromatic compound gives rise to the last 1998, 2001; Hameed, Tan, and Ahmad, 2009). band at 603 cm–1. The FT-IR and TG/DTA spectra of olive stones are similar E?;H>F?@;??FCBH to those of other lignocellulosic materials such as coconut shell (Sahin and Saka, 2013). The high fixed carbon, volatile !! #! # " "! "! #!" content, and carbon concentration (Table IV) indicate that this material a good precursor for preparing a hard activated The TG/DTA curves for olive stones are shown in Figure 1. carbon to be used in gold adsorption. The first endothermic event was due to water loss, and the second to loss of mass. The mass loss curves make it  !! # " " " " possible to visualize and decouple different phenomena distinguished as a function of the temperature level in the  (+'($#* '!&)* +$"#* reactor. Two losses of mass are shown: the first is a loss of The carbon yield varied between 12.16 and 25.33% (Table 5.59% in the drying phase from 43.9°C to 161°C, during II). These high yields are due to the nature of olive stones, which time the residual moisture is driven off. The second is which are very rich in carbon and volatiles materials as noted a loss of 67.4% in the range from 162°C to 801.4°C. In this in Table IV, which in turn favours the production of pores phase several zones may be associated with the degradation during carbonization by the volatilization of volatile matter in of the principal constituents of olive stones (hemicelluloses, the form of gas and tar. cellulose, lignin) (Guinesi and Cavalheiro, 2006; Aigner et The total yield in carbon can be described as follows: al., 2012). This process begins with the most thermally Y1 = 18.57 – 1.931 X1 – 3.786 X2 – 4.275 X3 – 0.361 X4 unstable compound. Hemicelluloses degrade between 162°C The coefficients of correlation (R2= 0.939, R2 = 0.832) and 325°C, followed by celluloses between 325°C and 375°C. A between the theoretical and experimental response, The change in the slope of the curve reflects a change in calculated by the model, are satisfactory. chemical kinetics. Lignin degrades between 375°C and 500°C; Analysis of the results shows, as expected, that the its kinetics of degradation are slower than those of other activation temperature (X ) and the activation time (X ) have compounds. Finally, the end of degradation is located at 2 3 a very negative influence on yield. 500°C and above. The FT-IR spectrum of olive stones is shown in Figure 2. #%&!(+&)* '' +( *&!*+&#+)$*  The broad band observed at 3425 cm–1 corresponds to the It is known that the iodine number is a reliable measurement stretch vibration of hydroxyl groups involved in hydrogen of the microporosity of activated carbons, with higher iodine bonding (O-H), possibly due to absorbed water. A small number defining a higher microporosity and higher internal band located at 2920 cm–1could be assigned to the (C-H) surface area (Eddy et al., 2011). The adsorption capacity of stretch vibration in methyl and methylene groups, and the iodine (Y2) can be described by the model: band at 1739 cm–1 is ascribed to the vibration of (C=O), Y2 = 846.116 – 77.348 X1 + 164.326 X2 + 109.336 X3 + mainly from the esters, carboxylic acids, or aldehydes derived 2 2 2 76.581 X4 – 100.107 X1 – 72.962 X2 + 129.363 X3 + from cellulose and lignin (Saidatul, Jamari, and Howse, 2012, 2 Sevilla and Fuertes, 2009). The vibration stretching (C=C) 129.009 X4 – 127.206 X1X2 – 110.279 X2X3 + 147.090 from the aromatic rings present in lignin caused the X1X4 + 86.287 X2X4 + 131.671 X3X4 emergence of the bands at about 1639 and 1508 cm–1. The

3F7;AEH2/1EA=G

2 2 The coefficients of correlation (R = 0.976, R A = 0.950) and lower temperatures for longer activation times. An between the maximum capacities of adsorption calculated by increase in the activation time increases the porosity and the model and those determined experimentally are modifies the pore structure, and also promotes the formation satisfactory. of active sites within the activated carbon (Lua and Guo, Analysis of this response (Y2) shows that the activation 2000). temperature (X2) and the time of activation (X3) have a Figure 6 shows the combined effects of activation time strong impact on the development of the porous texture and steam flow on the iodine adsorption capacity. It seems during activation. These factors therefore influence the that the maximum iodine number was achieved when the adsorption behaviour of the activated carbon. Moreover, time of activation and the steam flow were increased. temperature seems to be more influential during a long Physical activation is a process in which the carbonized activation time. It seems that more micropores are opened product develops a porous structure of molecular dimensions with increased activation temperature and activation time. The iodine adsorption test is normally used as a performance indicator for gold adsorption, with the minimum recommended iodine number required for activated carbons for use in the gold industry being 1000 mg/g (Buah and Williams, 2010). Figures 3–6 illustrate the interaction between the variables in contour plots. Figure 3 shows the combined effect of time of carbonization (X1) and temperature of activation (X2) on the iodine number. The highest iodine number (>1000 mg/g) was achieved at approximately 940°C and 60 minutes of carbonization time. The figure shows that the iodine number increased with increasing temperature and decreasing time of carbonization. The increased temperature causes an increase in the release of low molecular weight volatiles from the matrix structure, which in turn causes pore 3F7;AEH/+GAFGDFCBHC:HFC>FBEHB;=9EAH5-04HC:HG@DF8GDE>H@GA9CBHG?HG development. The numbers of pores and porosity will :;B@DFCB?HC:H@GA9CBF GDFCBHAE?F>EB@EHDF=EHGB>H?DEG=H:FBEHB;=9EAH5-04HC:HG@DF8GDE>H@GA9CBHG?HG obtained at high temperatures with short activation times, :;B@DFCBHC:HG@DF8GDFCBHDE=6EAGD;AEHGB>HG@DF8GDFCBHDF=E

3F7;AEH*/+GAFGDFCBHC:HFC>FBEHB;=9EAH5-04HC:HG@DF8GDE>H@GA9CBHG? 3F7;AEH/+GAFGDFCBHC:HFC>FBEHB;=9EAH5-04HC:HG@DF8GDE>H@GA9CBHG?HG :;B@DFCB?HC:H@GA9CBF GDFCBHAE?F>EB@EHDF=EHGB>HG@DF8GDFCBHDE=6EAGD;AE :;B@DFCBHC:HG@DF8GDFCBHDF=EHGB>H?DEG=H:

VOLUME 119          
  
 301 L Optimization of conditions for the preparation of activated carbon from olive stones and an extended surface area. At high temperature in the be improved by reducing the activation time. Indeed, a long presence of a steam activating agent, the loss of mass activation time leads to the weakening of the carbon structure increases proportionally to the reactivity of the carbon atoms and increases the surface area by opening up the micropores, with the activating agent. This causes the unblocking of the as indicated by a higher iodine number. pores, which makes the activated carbon structure more open. Subsequently, the carbon of the aromatic ring  ## #!"  ##! # "#"#!## " #  structures starts burning, producing active sites and wider The aim of this study was to identify the optimal conditions pores (Sahin and Saka, 2013) for preparation of activated carbon with good characteristics for use in gold adsorption. The comparison of optimal  # # "
  conditions for responses Y1, Y2, and Y3 shows that the Another parameter that is important for assessing the maximization of each response was not obtained at the same suitability of the activated carbon for gold adsorption is conditions. To determine an acceptable compromise zone, resistance to attrition. This response is described by the responses were simultaneously optimized by using the following equation: desirability functions approach (Derringer and Suich, 1980) Y3 = 0.633 + 0.574 X1 + 0.601 X2 + 1.193 X3 – 0.647 X4 included in the NEMROD software (Mathieu et al., 2000). + 0.976 X 2 + 1.729 X 2 – 1.455 X X + 1.281 X X + 2 4 1 2 2 3 $%+!'+"+( *) (+&)*'!&'  1.285 X3X4. This method first converts each estimated response Y into an The coefficients of correlation (R2= 0.945, R2 = 0.848) i A individual scale-free desirability function d that ranges from between the attrition responses calculated by the model and i zero (outside of the desired limits, if Y ≤ Y ,min) to unity, the those determined experimentally are satisfactory. i i target (desired) value (if Y ≥ Y ,max), where Y ,min and The activation residence time (X ) has a strong positive i i i 3 Yi,max are the lower and upper acceptability bounds for correlation with attrition resistance, the temperature of response i, respectively. activation (X ) also has a positive effect on this parameter, 2 The lower and upper acceptability bounds were set at the and the steam flow (X ) has a negative one. 4 extreme values, which were selected according to quality Figsures 7, 8, and 9 demonstrate the relationships criteria for the activated carbon used in the gold industry. between the variables in contour plots. Figure 7 shows the Since the response surface had been reasonably explored in combined effects of carbonization time and activation the range of studied variables, the weights for the first two temperature on attrition resistance of the activated carbon, the lowest attrition value (0.5%) being achieved at approximately 850°C and 60 minutes. A brittle activated carbon was obtained when both variables were increased. When the activation temperature is average and the carbonization residence time is minimal, a rigid activated carbon was obtained. The effect of activation temperature and activation time on attrition of the activated carbon is shown in Figure 8. The lowest point of attrition (0.2%) was determined. It seems that at the average activation temperature and the minimal activation time, the resistance to attrition increases. Furthermore, Figure 9 shows that the lower attrition value is obtained when the steam flow is increased and the activation time decreased. The attrition test is a critical performance indicator for activated carbon, with resistance to attrition depending 3F7;AEH /+GAFGDFCBHC:HGDDAFDFCBH5-*4HC:HG@DF8GDE>H@GA9CBHG?H:;B@DFCB?HC: mainly on preparation conditions. Resistance to attrition can G@DF8GDFCBHAE?F>EB@EHDF=EHGB>HG@DF8GDFCBHDE=6EAGD;AE

3F7;AEH/+GAFGDFCBHC:HGDDAFDFCBH5-*4HC:HG@DF8GDE>H@GA9CBHG?H:;B@DFCB?HC: 3F7;AEH /+GAFGDFCBHC:HGDDAFDFCBH5-*4HC:HG@DF8GDE>H@GA9CBHG?H:;B@DFCB?HC: @GA9CBF GDFCBHAE?F>EB@EHDF=EHGB>HG@DF8GDFCBHDE=6EAGD;AE G@DF8GDFCBHAE?F>EB@EHDF=EHGB>H?DEG=H:

(++$#* &)#+(+&)% 3F7;AEH2/+GAFGDFCBHC:H>E?FAG9F It was necessary to establish domains of variation of each DE=6EAGD;AEH response in relation to the material characteristics required. The activated carbon should have a yield mass between 12 and 30%, the iodine number should be greater than 1000 mg/g, and the attrition should be lower than 2%. To optimize all responses under the same conditions was difficult, because most of the regions of interest are different. For example, if the iodine number (Y2) increases the attrition number (Y3) also increases, which is unsatisfactory. Therefore, in order to find a compromise, we have resorted to the function of desirability. The compromise domain for the preparation of activated carbons with a high yield level, high iodine number, and low attrition number is depicted in Figures 10, 11, and 12. As can be observed in Figure 10, the maximum value of the desirability function was obtained when the activation time was less than 60 minutes and the activation 3F7;AEH22/+GAFGDFCBHC:H>E?FAG9F ?DEG=H:E?FAG9FHG@DF8GDFCBHDF=EH values agree well with those calculated from the model. significant reduction was observed for many bands in the FT- #!"!"#!"  #" " "  # IR spectrum. For example, in the spectrum of activated !  carbon (Figure 13), a significant decrease in the intensity of The immediate and elemental analyses of the olive stones the band located at 3425 cm-1, assigned to the reduction of and activated carbon prepared under the optimum conditions hydrogen bonding, was observed. Due to the dehydrating are given in Table IV. effect of activation, the decrease of the bands at about 2374 As can be seen, the fixed carbon content was greater in and 2923 cm-1, ascribed to asymmetric (C-H) stretching, activated carbon (97.3%) than in the raw material (20.2%), indicated that the hydrogen content decreases, which is due to the release of volatile components during the confirmed by the elemental analysis given in Table IV. The activation step, as shown by the decrease in volatile content decrease of the band at 1700 cm-1 corresponding to C=O in the activated carbon sample (1.9%). After activation, a may be due to the decomposition of these groups during

VOLUME 119          
  
 303 L Optimization of conditions for the preparation of activated carbon from olive stones

Table III C&EAHHDGA7EDH8G<;E?HGB>HD1EH6GADFGE?FAG9FH&FD1HEG@1HAE?6CB?E

E?6CB?E C&EAHF 5(4 >F =FB,H5(4 >F =G),H5(4 %G<@,H8G<;E !)6,H8G<;E

Y1 12 30 1 36.51 29.18 43.84 18.57 17.67 Y2 1000 1500 1 5.39 0 16.39 1026.93 1009.23 Y3 0 2 2 81.76 62.94 100 0.36 0.74 Desirability 33.86 0 51.78

di: partial desirability of response Yi, di min: minimal partial desirability of response Yi, di max: maximal partial desirability of response Yi calc. value: calculated value, exp. value: experimental value

Table IV $==E>FGDEHHGB>HEHG@DF8GDE>H@GA9CB

$==E>FGDEHHGBG<.?F?H5(4 !H@GA9CB %HHHHHHHHHHHHHHHHHHHHHHHHHHH

Olive stones 7.3 0.5 79.3 20.2 47.8 6.4 0.19 Activated carbon 3.3 0.7 1.9 97.3 90.8 0.93 0.67

presented in Figures 14 and 15 show the morphologies of the two activated carbons (GoldSorb and the optimal activated experimental carbon). A porous surface can be seen, with mainly a microporous and mesoporous structure, which will provide the maximum number of possible gold loading sites for both activated carbons. The textural characteristics of the activated carbon obtained from olive stones are similar to those of the commercial activated carbon GoldSorb, which is used extensiveily in the gold industry (Table V). It was found that the prepared activated carbon has a high iodine number, very low ash content, low attrition, and a strong affinity for gold. From Table VI it can be seen that the particle size and the size 3F7;AEH2*/3$H?6E@DA;=HC:HG@DF8GDE>H@GA9CBH6AE6GAE>H;B>EAHC6DF=G< distribution of the activated carbon prepared from olive @CB>FDFCB? stones were lower than those of the commercial activated carbon. Consequently, the size of granules of the raw material activation. The disappearance of the band located at during the crushing stage must be increased. 1639 cm-1 corresponding to olefines, and the appearance of Figure 16 illustrates the percentage gold recovery in the the band at 1569 cm-1 attributed to the aromatic C=C bond, cyanidation test (CIL) after having recycled the activated can be explained by the fact that the structure of activated carbon six times. It can be seen that the prepared activated carbon becomes richer in aromatics. The vibration at carbon based on olive stones performs comparably to the 1433.79 cm-1 is assigned to the asymmetric and symmetric commercial carbon (GoldSorb). The percentage gold recovery bending of (C-H). A significant reduction was observed for with commercial activated carbon decreases from the third the bands located between 850 and 1300 cm-1, which include cycle and reaches 79.2% at the last cycle. The activated (C-O) in carboxylic acids, alcohols, and esters. The intense carbon based on olive stones achieved a 100% gold recovery band at 592 cm-1 was ascribed to the stretching vibration in cycles 1 to 5, and 96% in the sixth. This result was (C-C). confirmed by analysis of the carbon after each cycle. Figure FT-IR and chemical analysis demonstrate that during this 17 shows the gold loading per gram of activated carbon. It is study, an activated carbon with good properties was prepared concluded that the adsorption capacity of the activated carbon from olive stone. prepared from olive stones is superior to that of the The porous nature and surface structure of the activated commercial carbon. carbon were examined using scanning electron microscopy %CB@<;?FCBH (SEM). The specific surface area (SBET) was determined from the adsorption-desorption isotherm of N2 at 77K (Brunauer, The response surface method (RSM) was used to optimize the Emmett, and Teller, 1951). The activated carbon produced process conditions for the preparation of activated carbon under the optimal conditions had a specific surface area of based on olive stones and its affinity for gold. 1073 m2/g with an average pore size of 1.4 nm. The specific ® Olive stones are a good precursor for producing surface area of our activated carbon is similar to that of efficient activated carbon with high performance for commercial activated carbon (1100 m²/g). The SEM images use in the gold industry. L 304   
 VOLUME 119          
Optimization of conditions for the preparation of activated carbon from olive stones

3F7;AEH2/ !H=F@AC7AG61?HC:HG@DF8GDE>H@GA9CBH6AC>;@E>H;B>EAHD1EHC6DF=;=H@CB>FDFCB?,H5G4H0H=H?@G

3F7;AEH2/ !H=F@AC7AG61?HC:H@C==EA@FGH@GA9CBHC<> CA9,H5G4H0H=H?@G

Table V 1.?F@GH@1E=F@GHD1EH@C==EA@FGH@GA9CB

'@DF8GDE>H@GA9CB $C>FBEHB;=9EAH5=7#74 ;A:G@EHGAEGH5=0#74 'DDAFDFCBH5(4 '?1H5(4 H5(4 H5=7H';#7H',%4 ;<H>EB?FD.H57#=*4

Optimum 1009.23 1073 0.74 0.7 57.25 28.72 495 Commecial (GoldSorb) 1090.45 1100 0.28 1.6 59.48 30.75 500

Table VI ® Experimental design and the response surface methods were used to determine the acceptable compromise GADF@H?F EH>F?DAF9;DFCBHC:HD1EHC6DF=;= zone of preparation conditions. Analysis of the effects E)6EAF=EBDGHD1EH@C==EA@FGH@GA9CB of carbonization time, activation temperature, activation time, and steam flow showed that the most '@DF8GDE>H@GA9CB H2,H== 2,0H== 0*,2H== H*,2H== important factors affecting the iodine number and Optimum 5% 35% 55% 5% attrition are the activation temperature and the Commecial (GoldSorb) 3% 15% 74.48% 7.5% activation time. ® Doehlert design, response surface methodology, and multi-criteria optimization using desirability functions

3F7;AEH2HHC<>HFB7H6EAH7AG=HC:HG@DF8GDE>H@GA9CBHC8EAH?F)H@.@HAE@C8EAFE?H5(4HC8EAH?F)H@.@GDFCBHDE?D?H5%$4 C:[email protected]>GDFCBHDE?D?H5%$4

VOLUME 119          
  
 305 L Optimization of conditions for the preparation of activated carbon from olive stones

were used to determine the acceptable compromise Journal of Hazardous Materials, vol. 164. pp. 1316–1324. doi: 10- 1016/j.hazmat.2008.09.042 zone for yield, iodine number, and attrition. The JAMARI, S.S. and HOWSE, J.R. 2012. The effect of the hydrothermal carbonization optimal conditions were identified as a carbonization process on palm oil empty fruit bunch. Biomass & Bioenergy, vol. 47. residence time of 157 minutes, an activation pp. 82–90. doi: 10.1016/j.biombioe.2016.09.061 JARAMILLIO, J., GOMEZ-SERRANO, V., AND A´LVAREZA, P.M. 2009. Enhanced temperature of 921°C, an activation time of 53 minutes, adsorption of metal ions onto functionalized granular activated carbons and a steam flow of 0.18 mL/min. prepared from cherry stones. Journal of Hazardous Materials, vol. 161. ® The activated carbon produced under the optimal pp. 670–676. doi: 10/1016/j.jhazmat2008.04.009 https://www.sciencedirect.com/science/article/pii/S030438940800530X conditions had a high iodine number and a low JIMENEZ-CORDERO, D., HERAS, F., ALONSO-MORALES, N., GILARRANZ, M.A., and attrition rate. The gold adsorption capacity was similar RODRÍGUEZ, J.J. 2014. Preparation of granular activated carbons from grape seeds by cycles of liquid phase oxidation and thermal desorption. Fuel to that of the commercial activated carbon and the Processing Technology, vol. 118. pp. 148–155. doi: carbon performed well in CIL tests. 10.1016/j.fuproc.2013.08.019 The studies suggest that olive stones can serve as a LUA, A.C. and GUO, J. 2000. Activated carbon prepared from oil palm stone by one-step CO2 activation for gaseous pollutant removal. Carbon, vol. 38. precursor for activated carbon to be used as an alternative to pp. 1089–1097. doi: 10.1016/S0008-6223(99)00231-6 the imported commercial activated carbon (coconut-shell MATHIEU, D., NONY, J., and PHAN-TAN-LUU, R. 2000. NEMROD-W software. Société LPRAI, Marseille, France. based) used in the Moroccan gold extraction industry. MPINGA, C.N., BRADSHAW, S.M., AKDOGAN, G., SNYDERS, C.A., and EKSTEEN, J.J. 2014. The extraction of Pt, Pd, and Au from an alkaline cyanide simulated '@BC&7=EBD? heap leachate by granular activated carbon. Minerals Engineering, vol. 55. The authors gratefully acknowledge the Higher Education pp. 11–17. doi: 10.1016/j.mineng.2013.09.001 Ministry of the Kingdom of Morocco, the Center for NORME. AFNOR XP CEN/TS 14 774-3. POINERN, G.E.J., SENANAYAKE, G., SHAH, N., THI-LE, X.N., PARKINSON, G.M., AND International Cooperation in Agronomic Research for FAWCETT, D. 2011. Adsorption of the aurocyanide, Au(CN)2- complex on Development (CIRAD), and the Department of Chemistry, granular activated carbons derived from macadamia nut shells – A preliminary study. Minerals Engineering, vol. 24. pp. 1694–1702. doi: Science Faculty, Semlalia Marrakech, Cadi Ayyad Marrakech 10.1016/j.mineng2011.09.011 University. RAMINEZ-MUNIZ, K., SONG, S., BERBER-MENDOZA, S., and TONG, S. 2010. Adsorption of the complex ion Au(CN)2- onto sulfur-impregnated E:EAEB@E? activated carbon in aqueous solutions. Journal of Colloid and Interface Science, vol. 349. pp. 602–606. doi: 10.1016/j.cis.2010.05.056 AIGNER, Z., BERKESI, O., FARKAS, G., and SZABO-REVESZ, P. 2012. DSC, X-ray and FTIR studies of a gemfibrozil/dimethyl-beta-cyclodextrin inclusion SAHIN, O. and SAKA, C. 2013. Preparation and characterization of activated complex produced by cogrinding. Journal of Pharmaceutical and carbon from acorn shell by physical activation with H2O–CO2 in two-step Biomedical Analysis, vol. 57. pp. 62–67. pretreatment. Bioresource Technology, vol. 136. pp. 163–168. doi: 10.1016/j.biortech.2013.02.074 AFNOR GROUP. 2005. Biocombustibles solides - Détermination de la teneur totale en carbone, hydrogène et azote - Méthodes instrumentals. Paris. SEVILLA, M, and FUERTES, AB. 2009. The production of carbon materials by ARRIAGAD, R. and GARCIA, R. 1997. Retention of aurocyanide and thiourea–gold hydrothermal carbonization of cellulose. Carbon, vol. 47. pp. 2281–2289. complexes on activated carbons obtained from lignocellulosic materials. doi: 10.1016/j.carbon.2009.04.026 Hydrometallurgy, vol. 46. pp. 171–180. doi: 1016/S0304- SNELL, F.D. and.ETTRE, L.S. 1968. Encyclopedia of Industrial Chemical Analysis. 386X(97)00010-8 vol. 8. Interscience, New York. p. 179. ASTM. 2006. D 4607-94. Standard test method for determination of iodine SOLEIMANI, M. and KAGHAZCHI, T. 2008. Adsorption of gold ions from industrial number of activated carbon. ASTM International, West Conshohocken, PA. wastewater using activated carbon derived from hard shell of apricot ASTM. 2016. D5373-16. Standard test methods for determination of carbon, stones – An agricultural waste. Bioresource Technology, vol. 99. hydrogen and nitrogen in analysis samples of coal and carbon in analysis pp. 5374–5383. doi: 10.1016/j.biortech.2007.11.021 samples of coal and coke. ASTM International, West Conshohocken, PA, SOUZA, C., MAJUSTE, D., DANTAS, M.S.S., and CIMINELLI, V.S.T. 2014. Selective BAÇAOUI, A., YAACOUBI, A., DAHBI, A., BENNOUNA, C.. AYELE, J., and MAZET, M. adsorption of gold over copper cyanocomplexes on activated carbon. 1998. Characterization and utilization of a new activated carbon obtained Hydrometallurgy, vol. 147–148. pp. 188–195. doi: from Moroccan olive wastes. Journal of Water Supply: Research and 10.1016/j.hydromet.2014.05.017 Technology, vol. 47, no. 2. pp. 68–75 STAUNTON, W.P. 2016. Gold recovery (carbon-in-pulp). Development in Mineral BAÇAOUI, A., YAACOUBI, A., DAHBI, A., BENNOUNA, C., PHAN-TAN-LUU, R., MODANO- Processing, vol 15, chapter 30. Elsevier. HODAR, F.J., RIVER-UTRILLA, J., and MOREO-CASTILLA, C. 2001. Optimization SUHAS, G.V.K. CARROTT, P.J.M., and RIBEIRO CARROTT, M.M.L. 2007. Lignin - from of conditions for the preparation of activated carbons from olive-waste natural adsorbent to activated carbon: a review. Bioresource Technology, cakes. Carbon, vol. 39, no. 3. pp. 425–432. vol. 98. pp. 2301–2312. doi: 10.1016/j.biortech.2006.08.008 BANSAL, R.C., DONNET, J.B., and STOECKLI, F. 1988. Active Carbon. Marcel Dekker, New York. SUMATHI, S., BHATIA, S., LEE, K.T., and MOHAMED, A.R. 2009. Optimization of microporous palm shell activated carbon production for flue gas BRUNAUER, S., EMMETT, P.H., and TELLER, E. 1938. Journal of the American desulphurization: Experimental and statistical studies. Bioresource Chemical Society, vol. 60. p. 309 . Technology, vol. 100. pp. 1614–1621. doi: BUAH, W.K. and WILLIAMS, P.T. 2010. Activated carbons prepared from refuse 10.1016/j.biortech.2008.09.020 derived fuel and their gold adsorption characteristics. Environmental Technology, vol. 31, no. 2. pp. 125 137. doi: SUNDQVIST, B., KARLSSON, O., and WESTERMARK, U. 2006. Determination of 10.1080/09593330903386741 formic-acid and acetic acid concentrations formed during hydrothermal treatment of birch wood and its relation to colour, strength and hardness. DERRINGER, G. and SUICH, R. 1980. Simultaneous optimization of several Wood Science and Technology, vol. 40. pp. 549–561. doi: response variables. Journal of Quality Technology, vol. 12. pp. 214–219. 10.1007/S00226-006-0071-z DOEHLERT, D.H. 1970. Uniform shell design. Applied Statistics, vol. 19, no. 3, pp. 231–239. doi: 10.1155/2103/549729. SYNA, N., and VALIX, M. 2003. Modelling of gold (I) cyanide adsorption based on the properties of activated bagasse. Minerals Engineering, vol. 16. GERGOVA, K., PETROV, N., and MINKOVA, V. 1993. A comparison of adsorption pp. 421–427. doi: 10.1016/S0892-6875(03)00053-0 characteristics of various activated carbon. Journal of Chemical Technology & Biotechnology, vol. 56. pp. 77–82. doi: 10.1002/jctb.280560114 TOLES, C.A., MARSHALL, W.E., JOHNS, M.M., WARTELLE, L.H., and ALOON, A.M. 2000. Acid-activated carbons from almond shells: physical, chemical and GRATUITO, M.K.B., PANYATHANMAPORN, T., CHUMNANKLANG, R.-A., SIRINUNTAWITTAYA, N., and DUTTA, A. 2008. Production of activated carbon adsorptive properties and estimated cost of production. Bioresource from coconut shell: Optimization using response surface methodology. Technology, vol. 71. pp. 87–92. doi: 10.1016/S0960-8524(99)00029-2 Bioresource Technology, vol. 99. pp. 4887–4895. doi: WU, M., GUO, Q.J., and FU, G.J. 2013. Preparation and characteristics 10.1016/j.biortech.2007.09.042 ofmedicinal activated carbon powders by CO2 activation of peanut shells. GUINESI, L.S. and CAVALHEIRO, E.T.G. 2006. The use of DSC curves to determine Powder Technology, vol. 247. pp. 188–196. doi: the acetylation degree of chitin/chitosan samples. Thermochimica. Acta, 10.1016/j.powtec.2013.07.013 vol. 444. pp. 128–133. doi: 10.1016/j.tca.2006.03.003 YALCIN, M. and AROL, A.I. 2002. Gold cyanide adsorption characteristics of GUINESI, L.S. and CAVALHEIRO, E.T.G. 2006. The use of DSC curves to determine activated carbon of non-coconut shell origin. Hydrometallurgy, vol. 63. the acetylation degree of chitin/chitosan samples. Thermochimica. Acta, pp. 201–206. doi: 10.1016/S0304-386X(01)00203-1 vol. 444. pp. 128–133. doi:10.1016/j.tca.2006.03.003 YAVUZ, R., AKYILDIZ, H., KARATEPE, N., and ÇETINKAYA, E. 2010. Influence of HAMEED, B.H., TAN, I.A.W., and AHMAD, A.L. 2009. Preparation of oil palm preparation conditions on porous structures of olive stone activated by empty fruit bunch-based activated carbon for removal of 2,4,6- H3PO4. Fuel Processing Technology, vol. 91. pp. 80–87. doi: trichlorophenol: Optimization using response surface methodology. 10.1016/j.fuproc.2009.08.018 N L 306   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a10 Improved ultrafine coal dewatering using different layering configurations and particle size combinations by M.E.C. Snyman1 and N. Naudé1

of finer and coarser materials has been proposed to deliver better dewatering !31'040 efficiency and improved the quality of the Coal fines produced during processing are difficult to dewater and result in a recycled water (Kenney, 1994). lower quality product and consequent lower value. A South African coal This project aimed to solve belt filter mine experiences severe difficulties with belt filter dewatering operations problems associated with ultrafine materials at due to the presence of fines reporting from the thickener underflows. Plant 2 currently handles super-fine particles of size −34 μm and has low belt filter a South African coal mine. The plant operates efficiency: excessive moisture retention lowers the product quality and two belt filter plants: the thickener underflow strains downstream processing. It was necessary to determine an alternative solids feed to Plant 1 is relatively coarse, method for dewatering these fines. Blending of fine material with coarser having a particle size of approximately 75 μm, material was proposed as a solution. The effect of coal particle size and while that of Plant 2 is fine, approximately 34 layering during ultrafines belt filter dewatering was evaluated using various μm. The optimum blend proportions and blends of the fine Plant 2 material with coarser Plant 1 material. The best layering arrangements of the two materials on layering arrangement of the two materials and its optimum blend required a belt filter were assessed to compare to achieve reduced filter cake moisture content was determined in practise dewatering efficiency and the quality of the using a vacuum filter to simulate belt filtration. A blend of the two materials filter cake and filtrate produced. Factors gave improved dewatering efficiency for the belt filters compared with that influencing the final moisture content of a of the Plant 2 material alone. The best layering configuration was with Plant 2 material at the bottom and Plant 1 material on top. The optimum blend for filter cake generated by layering super-fine industrial applications comprised 48% fines from Plant 2. and coarser material on a belt filter to maximize water removal efficiency were :7! 12+0 experimentally determined using different ultrafine coal, dewatering, belt filter, vacuum filter, moisture content. layering configurations. The optimum fines content of the blend was then determined.

86* ,21-3+ 93521+-*5413  "#!%$ #% # Fines are produced during the processing of Insufficient dewatering influences the quality coal. It is estimated that 2 to 3% of run-of- of the final coal product, especially in the mine coal reports to the ultrafine portion thermal coal industry. The moisture content of (−100 μm) (le Roux, 2005). The particle size coal is strongly governed by the quality of coal is inversely proportional to the amount specifications and economic possibilities for a of water adsorption, so smaller particles plant. A lower moisture content results in a adsorb more moisture. Moisture removal higher quality product and hence a higher requires either mechanical processes or sales price, so it is essential that continuous thermal drying: mechanical processes are less improvement of dewatering technologies is expensive, but the fines still have high undertaken (de Korte, 2008). A previous study moisture retention. Discarding of fines leads to showed that the proportion of −75 μm material economic losses, so it is essential that they be in the belt filter feed exhibited a linear dewatered so that they can then be sold as a product: fines need to be treated for both resource management and conservation reasons (Kenney, 1994). Removal of free surface moisture from ultrafine coal particles using a belt filter therefore remains a process 1 Department of Materials Science and Metallurgy that needs to be continuously improved. Engineering, University of Pretoria, South Africa. 2 School of Mining Engineering, University of the Ultrafine coal originating from a thickener Witwatersrand, South Africa. underflow is known to be difficult to dewater © The Southern African Institute of Mining and owing to factors such as filter cloth blockage Metallurgy, 2019. ISSN 2225-6253. Paper received and moisture retention due to clogging. Mixing Jun. 2018; revised paper received Aug. 2018.

VOLUME 119          
  
 307 L Improved ultrafine coal dewatering using different layering configurations relationship with the product surface moisture content specified by ASTM 2234 (ASTM, 2017a) for gross sample (Arnold, 1999). The final filter cake moisture is influenced by collection from the coal mine Plant 1 and Plant 2 thickener modification of the coal surface, type of surfactant, type of underflow materials. Plant 1 provided the coarse material and dewatering device, conditioning time, and the pH value of the Plant 2 the fine material. The sampling position was selected system (Nkolele, 2004). to avoid any mixing of added reagents (such as flocculants) Modelling of water and coal particle interactions is that would be present if samples were taken from the belt continually evolving to enable a better understanding of the filter. The collected coal samples were dried at 105°C for 24 interactions that occur during dewatering. Tests have proven hours to remove all moisture. The samples were then broken that the densest packing of spherical particles results in a down using a roller pin and divided into the appropriate total void volume of 26%, due to the comparable densities of sample masses required for testing by means of a rotary coal and water (Nkolele, 2004). For smaller coal particle splitter. sizes, the voids form capillary cavities filled by water. An increased attraction between the water and the coal surface !#"%$"%$"#!"#" results, leading to mechanical dewatering mechanisms not The particle size distribution (PSD) of each material sample being able to adequately remove this water (Nkolele, 2004). was determined. Wet sieving, using the ASTM D4749 Decreasing particle size causes an increased water-exposed (ASTM, 2017b) procedure, was employed to obtain an surface area. The particle size of the coal is inversely accurate representation of size. Each test employed three proportional to the final moisture content of the filter cake: 500 g samples from each plant. The PSD analyses were finer coal sizes have larger moisture retention (i.e., are more carried out in triplicate to obtain representability. The size difficult to dewater) than coarser particle sizes (Basim, distribution ranged from −1000 to −53 μm. 1997). %!" $ "!#"   "#!%$!%#" $#! $% "  Figure 1 shows the layering configurations and their The coal industry often reduces the moisture content of the descriptors used in this study. The samples from Plants 1 and filter cake by blending high-moisture fine coal with low- 2 had different material size distributions and the drainage moisture coarse coal. The blending proportions differ would differ for different layering configurations. For each of depending on the materials used in the colliery. The optimum the five layering possibilities, three tests were conducted to blend must therefore be individually determined for each determine the relative error. Different layering set-ups were plant. Blending increases the permeability of the cake, tested to determine the configuration that gave the best leading to reduced blinding of the belt filter cloth. dewatering results. This optimum layering set-up was then used for further test work. Each test required a combined !#%!"#"$ $%#$"#%!$#% mass of 200 g. The appropriate amount of water was then Belt filter systems are specifically designed for a high solids added to obtain the typical underflow solids density of the capacity. The concentration of solids for the system is industrial thickeners of 44%; thus, for 200 g solids, 454 mL determined by the concentration of the primary solids in the water was added. feed and further solids that may precipitate during treatment, Industrial AP520 C flocculant (Pathlochem) was mixed hence a varying feed solids concentration is experienced. For with the water at 0.05 mass percentage, as used in industry. most sludges fed to belt filter presses, the feed dry solids Filter paper (Econofilt, 240 mm diameter) was placed on a concentration falls in the range of 1–10% and the resulting Buchner vacuum filter, after which the slurries of the various moisture content of the filter cake is the range of 12–50%. materials were layered in the filter according to the required The input solids loading depends on the sludge type and the configuration in such a way as to not disturb the layering. filter media used. This input to the belt filter press is The vacuum filter was switched on and the mass of water generally measured as the mass of dry solids per unit time removed from the slurries was measured every second for a per unit belt width. For lower ranges of solids, the feed is period of 300 seconds using a load cell (ZEMIC model H3-C3- normally 40–230 kg/h/m belt width; for higher solids’ 100kg-3B). ranges, the feed increases to 300–910 kg/h/m belt width. #"$% $%#%!" #" Dilute feed solids concentrations result in a cake of higher Once the most efficient layering configuration was moisture content, while a higher feed solids concentration established, this was used to determine the optimum blend yields an improved solids filtration rate and a drier end for the most efficient moisture removal. The slurries product. The thickness of the cake formed should also be comprised 0, 10, 25, 50, 75, and 100% Plant 2 material. All considered when selecting the percentage of solids in the tests were carried out in triplicate feed. Cake thickness affects the permeability of the filtration mix and thus the filtration rate. Generally, the minimum design discharge cake thickness is 3–5 mm. This size ensures that the cake is thick enough to discharge and easy to remove from the belt (Schonstein, 2008).

75 1+1/1,!

%$!%!#" 4,-27
#6!7243,
*13.4,-2654130
57057+
727
)/635
#
(657246/ Sampling was carried out in accordance with the procedure 27'2707350
5 7
*16207
'6254*/70
63+
)/635
&
(657246/
5 7
.437
'6254*/70 L 308   
 VOLUME 119          
Improved ultrafine coal dewatering using different layering configurations

 "#!%$ #% #$ "$ $"#%!$ % In addition to using load cell measurements to determine the mass of water removed by filtering, the moisture retention of the filter cake was measured by removing the surface moisture by drying, according to the procedure described by ASTM D3302 (ASTM, 2017c). This entailed spreading the sample into tared pans and weighing the pans, after which the sample was dried in an oven at 30ºC with intermittent stirring until the sample appeared dry. The pan was then removed and the new mass recorded before it was placed back in the oven. This procedure was repeated at 2-hour intervals until the mass change between the intervals was 4,-27
)6254*/7
047
+40524-54130
1.
)/635
#
63+
)/635
&
5 4* 7372 less than 0.1%. The sample was then cooled to ambient -3+72./1
(657246/0
60
06('/7+ temperature, the final mass measured, and the moisture change calculated.

 %!"% #$%#
 Table I A stand was designed and built, in which the load cell could "26!
+4..26*5413
270-/50
be placed and connected to the ceramic head of the vacuum filter. A water distribution system was designed to distribute )/635
# )/635
& water evenly over the entire layered sample at a low enough 600 

72212 600 

72212 rate to prevent mixing of the layers. The experimental Calcite 2.04 0.51 Calcite 2.21 0.57 equipment and configuration are shown in Figure 2. Dolomite 7.81 1.17 Dolomite 8.91 1.2 Kaolinite 38.17 1.35 Kaolinite 43.09 1.38 Magnetite 3.76 0.42 Magnetite 10.49 0.57 70-/50
63+
+40*-00413 Pyrite 3.79 0.39 Pyrite 2.75 0.39 Quartz 39.89 1.29 Quartz 27.44 1.11 !#"%$"%$"#!"#" Siderite 4.54 0.63 Siderite 5.13 0.66 The PSD was used to characterize the materials used for the experiments. The wet sieving results are shown in Figure 3. The D50 values (particle size at which 50% of the material Table II passed through the sieve) for Plant 1 (coarse) and Plant 2 (fine) materials were 75 μm and 34 μm, respectively. "26!
./-1270*73*7
270-/50

%$! %!#"% 
 )/635
# )/635
& Samples were also split out, ground, and subjected to X-ray 7254.47+ 36/!07+ diffraction (XRD) and X-ray fluorescence (XRF) analysis. SiO2 99.6 99.70 17.90 18.40 XRD indicated that the higher percentage clay phase in the TiO2 0.01 0.00 0.40 0.60 Plant 2 material was kaolinite. The XRD and XRF results are Al2O3 0.05 0.01 7.01 8.69 given in Tables I and II, respectively. Fe2O3 0.05 0.01 2.54 5.97 MnO 0.01 0.00 0.06 0.08 MgO 0.05 0.01 0.53 0.65 %" $ $% %!"% # CaO 0.01 0.01 1.36 1.74 To best illustrate the layering set-up for the experiments. Na2O 0.05 0.02 0.04 <0.01 K2O 0.01 0.01 0.39 0.28 labels were used that referred to the order in which the P2O5 0 0.03 0.09 0.10 Cr O 0 0.00 0.01 0.02 samples from Plant 1 (D50 of 75 μm) and Plant 2 (D50 of 2 3 NiO 0 0.01 0.01 0.03 34 μm) were configured. Table III shows an explanation of V2O5 0 0.00 0.01 0.02 the labelling system used. ZrO2 0 0.01 0.02 0.03 SO3 0 0.00 0.08 0.06 BaO 0 0.00 0.04 <0.01 CuO 0 0.00 <0.01 <0.01 ZnO 0 0.00 <0.01 0.01 SrO 0 0.00 0.02 0.02 LOI 0 0.10 69.50 63.20 Total 100 99.93 100.00 99.91

 "#!%$!%#% #" $ $!" %$!#% The results for the amount of water removed for the different layering configurations are shown in Figure 4. Some noise in the data occurred due to vibration of the vacuum filter motor on the laboratory bench. For the specified filtration time of 300 seconds, higher drainage values were achieved when the 4,-27
&'724(7356/
075"-'
Plant 2 (fine) material was placed first on the filter paper. The

VOLUME 119          
  
 309 L Improved ultrafine coal dewatering using different layering configurations

Table III '/6365413
1.
7'724(735
/67/0

67/ '/6365413

Plant 1 Only Plant 1 sample used Plant 2 Only Plant 2 sample used Plant 1-2 Plant 1 sample on top with Plant 2 sample layered at the bottom Plant 2-1 Plant 2 sample on top with Plant 1 sample layered at the bottom Plant 1-2-1 Plant 1 sample on top with Plant 2 sample in the middle and Plant 1 sample layered at the bottom Plant 2-1-2 Plant 2 sample on top with Plant 1 sample in the middle and Plant 2 sample layered at the bottom

4,-27
16+
*7//
(760-27(7350
0 1 43,
2657
1.
(600
/100
1.
6572
-3+72
+4..72735
.4/5265413
/6!7243,
*13.4,-2654130

Plant 2-2 configuration gave the highest drainage rate. The When Plant 2 (fine) material was layered at the bottom, drainage rates decreased when Plant 1 (coarse) material was most water seeped quickly through the gaps formed in the layered at the bottom on the filter. As expected, using only Plant 1 material to the Plant 2 layer. The Plant 1 material did Plant 2 (fine) material resulted in a very slow drainage rate. not settle into the Plant 2 layer because the gaps between the The data shown in Figure 4 followed an exponential latter particles were too small. The water then became decay trend for the drainage rates. The Plant 1-2-1 trapped in the bottom Plant 2 layer. The fine material did not configuration showed an initial increase in moisture trap the water in the Plant 2 layer that was placed directly on drainage. It is theorized that the water drained through the the filter paper, and the force of the vacuum was strong upper Plant 1 (coarse) layer and was then trapped in the enough to extract more of this water. The best layering middle Plant 2 (fine) layer, which prevented further draining configuration was therefore to use Plant 2 (fine) material at until the force from the vacuum became sufficient to drain the bottom. Both the Plant 2-1 and Plant 2-1-2 the water through the bottom Plant 1 coarse layer; the configurations offered improvement; however, to minimize drainage rate then started increasing. Table IV details the complications in industrial application, it would be easier to final results. The Plant 2-1 and Plant 2-1-2 layering have a single layer of each particle size range. The Plant 2-1 configurations gave the best drainage rates, while those in configuration was therefore selected as optimum. which the Plant 1 material was placed at the bottom gave the least-desired results. Layering of Plant 2 (fine) material at the bottom of the Table IV filter cake resulted in 22% moisture retention; layering Plant 70-/50
1.
/6!7243,
7'724(7350 1 (coarse) material at the bottom gave 30% moisture retention. This large difference can be explained by the size 6!7243,
156/
(600
1.
26436,7
2657
1405-27
2756437+ differences between the two materials. When Plant 2 material *13.4,-265413 6572
27(17+
$,% $(0% $% was at the top, it started to settle in the gaps formed by the coarser Plant 1 material. The finer material then trapped the Plant 2 337.83 1.13 26 Plant 1 339.3 1.13 25 water and formed a layer of fine wet material. This layer did Plant 2-1 356.08 1.19 22 not settle to the bottom of the filter cake and the suction Plant 1-2 317.07 1.06 30 Plant 2-1-2 341.13 1.14 25 power of the vacuum filter was not adequate to extract this Plant 1-2-1 323.61 1.08 29 trapped water. L 310   
 VOLUME 119          
Improved ultrafine coal dewatering using different layering configurations

It is worthy of note that the 25% and 26% moisture equation was obtained and the Microsoft Excel Solver retentions reported for the individual Plant 1 and Plant 2 function was used to determine the optimum percentage of materials, respectively (Table I), were close to the values Plant 2 fines that should be employed in this layering currently measured on an industrial scale. The experimental configuration. results are therefore considered to be comparable to projected Using the best-fit quadratic relationship indicated in industry performance. Figure 7, it was determined that the optimum Plant 2-1

"#%!$ %$#""# The quality of the filter cake after dewatering is very important with regard to its further processing. If the cake is too wet, it will be heavy and have the characteristics of sludge, making it difficult for the dewatered material to be transported on the mine conveyor systems. Figures 5a to 5c show considerable differences in the final filter cakes: the cake from the Plant 1-2 configuration still had water lying on the top; the cake resulting from the Plant 2 configuration did show moisture retention and a tendency to be sludgy; that resulting from the Plant 2-1 configuration was much sturdier and had a visually drier appearance.

#%!$"#$ $%! 4,-27
156/
6572
27(16/
60
6
.-3*5413
1.
'72*7356,7
.4370
73 Water extracted from the belt filter is recycled to the process -043,
5 7
)/635
&"&
.4/5265413
*13.4,-265413 plant so its quality is important. Figures 6a to 6c show large differences in the water qualities produced from the Plant 2, Plant 1-2, and Plant 2-1 configurations. For the Plant 1-2 Table V configuration, a large amount of fines washed through the filter paper with the water, which resulted in poor water 70-/50
.12
'72*7356,7
.4370
6++45413
-043,
)/635
&" quality and would cause a build-up of ultrafine material in &
*13.4,-265413 processes where the recycled water is utilized. )21'125413
1.
)/635
& 156/
(600
1.
26436,7
1405-27
 % %$ $!  !#" $ $" %$ $ #%!$!%  $.437%
(657246/
$% 6572
27(17+
$,% 2657
$(0% 2756437+
$% To determine the optimum blend of the two materials, the 0 339.3 1.13 25 Plant 2-1 layering configuration was employed with different 20 353.75 1.18 22 proportions of fines in the bottom layer. The amount of water 50 356.08 1.19 22 60 357.44 1.19 21 removed was plotted against the percentage fines, as shown 100 337.83 1.13 26 in Figure 7. The data is given in Table V. A fitted linear

4,-27
) 151,26' 0
1.
.436/
.4/572
*6 70
'21+-*7+
-043,
$6%
)/635
&
$%
)/635
#"&
63+
$*%
)/635
&"#
.4/5265413
*13.4,-2654130

4,-27
-6/45!
1.
.4/5727+
6572
'21+-*7+
!
$6%
)/635
&
$%
)/635
#"&
63+
$*%
)/635
&"#
.4/5265413
*13.4,-2654130

VOLUME 119          
  
 311 L Improved ultrafine coal dewatering using different layering configurations layering required that 48% by mass of Plant 2 material should be used for the bottom layer. This is expected to give 21% water retention in the final cake, as proven in this test work. However, as shown in Table II, there is a range of percentage fines – from 20% to 60% – for which moisture removal would be efficient. Industrial applications will therefore have some leeway if the process parameters fall within this range. A comparison of the PSD for the optimum blend with those of Plants 1 and 2 is presented in Figure 8. The optimum Plant 2-1 blend has a D50 of 53 μm. 4,-27
 1('624013
1.
'6254*/7
047
+40524-54130
1.
.77+0
51
)/635
# 13*/-04130
)/635
&
63+
1'54(47+
)/635
&"#
/6!72
*13.4,-2654130 A South African coal mine suffers from poor belt filtration performance when treating fine material originating from the Plant 2 thickener underflow. This study evaluated the 7.7273*70 filtration characteristics and water quality produced using ARNOLD, B. 1999. Simulation of dewatering devices for predicting moisture various blends and layering configurations of coarser Plant 1 content of coal. Coal Preparation, vol. 20. pp. 35-54. material with the fine Plant 2 material. The experimental ASTM. 2017a. D2234. A. Standard practice for collection of a gross sample of results showed that mixing Plant 1 and Plant 2 materials coal. ASTM International, West Conshohocken, PA. gave improved dewatering efficiency compared with Plant 2 ASTM. 2017b. D4749. Standard test method for performing the sieve analysis material alone. A layering configuration with the fine of coal and designating coal size. ASTM International, West Conshohocken, PA. material placed directly on the filter cloth and the coarse ASTM. 2017c. D3302. A. Standard test method for total moisture in coal. material layered above gave the best filtration characteristics. ASTM International, West Conshohocken, PA. The optimum blend for this industrial application contained BASI, G. 1997. Fine coal dewatering. Master's thesis, Virginia Tech State 48% of the Plant 2 fines. The existing Plant 1 and Plant 2 University. https://vtechworks.lib.vt.edu/handle/10919/35680 arrangements can be retained, but the materials currently fed DE KORTE, G. 2008. Dewatering of ultra-fine coal with filter presses. Coaltech, Pretoria. to the two plants should be appropriately split to ensure KENNEY, M.E. 1994. Coal dewatering. US patent 5.346.630. sufficient dewatering and plant capacity. Laboratories, E.G. 2016. PSD of GG8 and GG2. Exxaro GG, Lephalale, South Africa.. * 31 /7+,7(7350 LE ROUX, M.E.A. 2005. The optimization of an improved method of fine coal This work was financially supported by EXXARO. This dewatering. Minerals Engineering, vol. 18, no. 9. pp. 931–934. manuscript was edited for publication by Dr Kathryn Sole NKOLELE, A. 2004. Investigations into the reduction of moisture in final coal by plant tests with surfactants. Journal of the South African Institute of (University of Pretoria). Mrs J. Dykstra carried out the XRF Mining and Metallurgy, vol. 104, no. 3. pp. 171–176. analyses and Mrs W. Grote the XRD at Stoneman (University SCHONSTEIN, P. 2008. Horizontal vacuum belt filters in the mining and chemical of Pretoria). industries. Filtration and Separation, vol. 28, no. 2. pp. 121–122. N

4–5 July, 2019 SMART MINING, SMART ENVIRONMENT, SMART SOCIETY Implementing change now, for the
mine of the future For further information contact: Yolanda Ndimande · Conference Co-ordinator · SAIMM Tel: +27 (0) 11 834-1273/7 · E-mail: [email protected] · Website: http://www.saimm.co.za Background Society in general, and the economy in particular, is evolving at breakneck speed. Old jobs are being lost and new ones are constantly being created. It is likely that mines developed in the next ten years will have a very different staff complement to those currently in production. It is also clear that we are at tipping points for climate systems and for biodiversity: the challenges facing the extractive sector in the coming decades are likely to be much greater than anything in the past century. What does this mean for environmental management? How should we be planning mines to reduce environmental footprints? What skills do we need to do this? Which energy sources will be available and will they have an impact on production? Can we close mines in a way that ensures that viable post-mining economies can be established? This conference bridges the gap between practitioners and decision-makers and managers in both the public and private sectors. The intention is to transfer knowledge and to debate the big issues facing regulators, mining companies, labour, and communities in a way that identifies solutions. The conference will consist of a number of invited keynote speakers who will focus on strategic issues, with the possibility of a workshop included. Accolades Boutique Venue, Midrand L 312   
 VOLUME 119          
http://dx.doi.org/10.17159/2411-9717/2019/v119n3a11 Contributors to fatigue at a platinum smelter in South Africa by J. Pelders1,2 and G. Nelson2

Kantola, 2007; Minkel et al., 2011; Schwarz et .%#$($ al., 2013). It is a significant concern in the mining industry as it is commonly identified as Fatigue is a significant concern in the mining industry as it is a causal or contributing factor in many incidents and accidents. Fatigue can be caused a causal or contributing factor in many by work- and non-work-related factors. There is a lack of information accidents and injuries (Schutte, 2009). Fatigue about associations between demographic and other non-work factors, and can also lead to long-term health problems, fatigue. This study aimed to assess associations between demographic, including digestive problems, heart disease, work, living, and socioeconomic conditions, and lifestyle characteristics, stress, and mental illness (Shaw, 2003). and fatigue at a platinum smelter in South Africa. Eight interviews with Fatigue can be caused by both work- management and two focus groups with production workers were related and non-work-related factors. Work- conducted, and 75 questionnaires were completed by production and other related causes include work schedules and workers. Both work- and non-work-related factors were considered to be design, task requirements at work, and the causes of fatigue. These factors included overtime, shift work, high work environment conditions. Work workloads, activities performed outside of work, age, race, housing tenure, diet, sleep disorders, stress, and job satisfaction. In general, higher levels scheduling factors include the number and of fatigue were reported by younger participants, those who rented pattern of hours worked, time of day, shift accommodation, ate less healthily, had a sleep disorder, and those with work, and night work (Di Milia et al., 2011; high levels of stress and low job satisfaction. As various demographic, NSW, 2009; Schutte and Maldonado, 2003; lifestyle, and wellness-related factors were associated with fatigue, both Shaw, 2003). Task requirements associated work and non-work contributors should be addressed in fatigue with fatigue include high mental and physical management plans. demands, especially monotonous tasks or -'#"$ tasks requiring sustained attention (Åkerstedt Sleepiness, living conditions, lifestyle, fatigue management, mining et al., 2014; Jing-Gang and Lei, 2013; NSW, industry. 2009; Schutte and Maldonado, 2003; Shaw, 2003; Williamson et al., 2011). Work environment factors include noise, temperature extremes, or the psychosocial environment ,) "#% (Jing-Gang and Lei, 2013; NSW, 2009; Shaw, Fatigue may be defined as ‘a state of impaired 2003). mental and/or physical performance and Individual and non-work contributors to lowered alertness arising as a result of, or a fatigue include aspects such as sleep, health, combination of, hard physical and mental fitness for work, lifestyle factors, and work, health and psychosocial factors or commuting time (Åkerstedt et al., 2014; Di inadequate restorative sleep’ (BHP Billiton, Milia et al., 2011; Horrey et al., 2011; NSW, 2005). Williamson et al. (2011) define fatigue 2009). Age, diet, drug and alcohol use, as a biological drive for recuperative rest. medical conditions, quality and quantity of rest Sleepiness and fatigue are related, and the before a work period, circadian rhythm (‘body terms are often used interchangeably. clock’), sleep disorders, strenuous activities However, sleepiness, more specifically, can be outside of work (e.g. a second job), family defined as sleep propensity, or a person’s commitments, and psychological issues such tendency to fall asleep (Hossain et al., 2003; Shen, Barbera, and Shapiro, 2006). Increasing levels of fatigue and sleepiness are associated with lapses in attention, errors, response slowing, fluctuations in alertness and 1 Mining and Mineral Resources, Natural Resources effort, and impaired attention, working and the Environment, CSIR, South Africa. 2 School of Public Health, Faculty of Health memory, long-term memory, decision-making, Sciences, University of the Witwatersrand, and creativity (Alhola and Polo-Kantola, 2007; South Africa. van Dongen and Dinges, 2000). Fatigue is also © The Southern African Institute of Mining and associated with adverse effects on mood and Metallurgy, 2019. ISSN 2225-6253. Paper received impulsive behaviours (Alhola and Polo- Oct. 2017; revised paper received Aug. 2018.

VOLUME 119          
  
 313 L Contributors to fatigue at a platinum smelter in South Africa as stress also play a role in the levels of fatigue experienced Closed-ended questions were used to gather information (Åkerstedt et al., 2014; Molarius et al., 2006; ORR, 2012; about participant demographics, work, living and Schutte and Maldonado, 2003; Shaw, 2003). In addition, socioeconomic conditions, lifestyles, health and wellness, and living conditions are likely to influence the levels of fatigue fatigue. Four questions were used to assess levels of fatigue, experienced by mineworkers due to poor conditions in which namely (1) whether participants thought they received to sleep, long commuting times between work and home, and enough sleep, (2) general sleepiness using the Karolinska poor health arising from a lack of access to services and Sleepiness Scale (KSS) (Åkerstedt and Gillberg, 1990), (3) a amenities (Åkerstedt et al., 2014; Galobardes et al., 2006). subjective rating of fatigue at work, adapted from the Samn- Horrey et al. (2011) reported that many demographic, Perelli fatigue scale (Samn and Perelli, 1982), and (4) personality, and workplace factors can impact the levels of whether the participant had unintentionally fallen asleep at fatigue experienced and their consequences. De Milia et al. work in the past 12 months. For the KSS, participants were (2011) noted that the interaction between demographic asked to rate how sleepy they generally felt on a scale from 1 factors and fatigue is a neglected area of research and that, (‘extremely alert’) to 9 (‘very sleepy, great effort to stay apart from age and sex, the influence of many demographic awake’). Subjective fatigue at work was recorded on a five- factors is largely unknown. There is a lack of information point Likert scale from ‘fully alert, wide awake’, to about associations between demographics, living conditions, ‘completely exhausted.’ The participants completed the and various other non-work factors and fatigue (Di Milia et questionnaires under the guidance of researchers who were al., 2011; Horrey et al., 2011). Living and socioeconomic fluent in local languages. conditions have been highlighted as a particular concern in Data from the voice recordings was downloaded and the South African mining industry. Further study on these transcribed. Thematic content analysis was used to factors is warranted to assist in broadening the summarize responses from the interviews and focus groups. understanding of their effects on fatigue so that they might Data from the questionnaires was captured electronically be considered in fatigue management programmes in order to using Excel software. A binomial fatigue variable was created implement appropriate interventions. The aim of this study using data from the four questions in the questionnaire that was to assess associations between demographic, work, were designed to assess fatigue. If data from two or more of living and socioeconomic conditions, and lifestyle these questions indicated high levels of fatigue (i.e. not characteristics, and fatigue in the South African Mining receiving enough sleep, a KSS score of over 5, a fatigue Industry. rating of more than ‘a little tired’, and/or falling asleep at work unintentionally in the past year), a positive fatigue
'&##!# score was indicated for the participant. In addition to The study design was cross-sectional. Although most data descriptive analyses, Pearson chi-squared and Fischer’s exact collected was quantitative, qualitative data was also gathered, tests were conducted using Stata 13 software to determine and methodological triangulation was used to verify the whether there were significant associations between each of results. Participants were recruited from a platinum smelter the demographic, work, living and socioeconomic condition, located in Limpopo Province in South Africa, in 2016. and lifestyle variables, and the summary fatigue variable. To Semi-structured interviews were held with eight improve the integrity of the inferential statistics, data was individuals in management positions or their representatives. grouped or omitted, where appropriate, to increase the These individuals were selected based on their positions at number of responses per category. Fisher’s exact test was the smelter, namely those from human resources, finance, used in cases where the number of participants per cell was health and safety, laboratory, production, engineering, and less than five. Statistical significance was set at 95% (p < protection services. Two focus group discussions were held 0.05). with groups of 11 (9 male and 2 female) and 13 (7 male and Ethical approval to conduct this study was obtained prior 6 female) production workers, respectively. Convenience to data collection from the CSIR Research Ethics Committee sampling was used to select these participants. The interview (reference number: 158/2015) and the University of the and focus group participants were asked about fatigue experienced at the smelter and its potential causes, both at Witwatersrand Human Research Ethics Committee (certificate work and outside of work, and were requested to make number: M140222). Necessary permission to conduct the recommendations for reducing it. The interviews and focus study was obtained from the company. group discussions were held in the language most readily understood by the participants which, in this case, was /'$!&$ English. The interviews and discussions were voice-recorded.  
      Quantitative data was collected using questionnaires that were completed by workers employed at the smelter.  Participants were selected using convenience sampling. The Participants in the interviews and focus groups generally felt smelter employed 188 permanent employees in the that fatigue was a problem at the smelter, especially for those workgroups included in the study, and around one-third of working in hazardous occupations. However, it was these were sampled. The study focused on production considered to be relatively well managed. Those in workers, such as those working at the furnace, as it was management identified various work-related causes of assumed that they would be at a high risk of fatigue and its fatigue, including overtime, shift work, repetitive and effects. However, other groups of workers, such as those monotonous work, and work that required high levels of working in engineering departments and in laboratories, were concentration. Overtime work was a particular concern for also included. engineering personnel as they worked on ‘standby’ in L 314   
 VOLUME 119          
Contributors to fatigue at a platinum smelter in South Africa addition to working normal day shifts. Production and Table I laboratory workers, on the other hand, worked 12 hour shifts that included night shift work. The production workers noted ' #")( * )") &'"($&( $*)%*&'*)$$# ()&(#%$ short staffing, including that resulting from absenteeism, as (&*)&(' the main concern relating to fatigue, as this led to increased workloads. )"()!' )"&( ()%&$ )&(' )!' Activities outside of work were also considered to %* '$*%* #*%* contribute to fatigue by both those in management positions Sex and the production workers. These included family Male 50 (68.5) 21 (42.0) 29 (58.0) 0.641 (P) responsibilities, part-time studies, and social activities. Female 23 (31.5) 11 (47.8) 12 (52.2) Personal differences such as age, intrinsic sleeping rhythms, Age ≤35 years 36 (51.4) 21 (58.3) 15 (41.7) 0.015* (P) and stress were also linked to fatigue. The socioeconomic >35 years 34 (48.6) 10 (29.4) 24 (70.6) conditions (e.g. income, education, transport, and housing) Race of the smelter workers were seen to be relatively good, and Black 64 (87.7) 32 (50.0) 32 (50.0) 0.004* (F) Other 9 (12.3) 0 (0.0) 9 (100.0) the daily commuting times were not generally excessive; as Marital status such, these factors were not of particular concern for fatigue. Married 37 (50.7) 16 (43.2) 21 (56.8) 0.918 (P) Not married 36 (49.3) 16 (44.4) 20 (55.6)  Home province A total of 75 questionnaires were completed. The average Limpopo 58 (79.5) 25 (43.1) 33 (56.9) 0.804 (P) Elsewhere in South Africa 15 (20.5) 7 (46.7) 8 (53.3) response rate to each of the questions was 98%, ranging Highest level of education from 95% to 97%. Grade 12 or less 31 (43.1) 10 (32.3) 21 (67.7) 0.070 (P) Table I shows the demographic profile of the study Higher than Grade 12 41 (56.9) 22 (53.7) 19 (46.3) participants. The majority of the participants were male (68.5%) and the average age was 37 (±7) years, with a range *Indicates significance at p < 0.05. (P) Pearson’s chi-square test performed. (F) Fisher’s exact test performed. of 22–60 years. Most of the participants were Black Africans (87.7%). All were South African, and most (79.5%) came from Limpopo, the province where the smelter was located. The participants were relatively well educated: 56.9% had a Table II post-Grade 12 qualification and only 5.6% had not completed #"*)"()!'$*)%*&'*)$$# ()&(#%$*(&*)&(' secondary school.

Selected work-related variables are shown in Table II. The )"()!' )"&( ()%&$ )&(' ( majority of the participants (53.4%) worked in the furnace %* '$*%* #*%* )!' section, 17.8% in the engineering department, 15.1% in the regional laboratory, and 13.7% in the process laboratory. Work area Furnace 39 (53.4) 20 (51.3) 19 (48.7) 0.318 (F) Most (86.3%) were permanent employees, and 67.1% worked Process laboratory 10 (13.7) 5 (50.0) 5 (50.0) shifts. In general, those working in the furnace section and in Regional laboratory 11 (15.1) 4 (36.4) 7 (63.6) the process laboratory worked shifts, while those in the Engineering 13 (17.8) 3 (23.1) 10 (76.9) engineering department and the regional laboratory did not. Work status Permanent 63 (86.3) 29 (46.0) 34 (54.0) 0.497 (F) The shifts were 12 hours long, and included night shifts. Contract 10 (13.7) 3 (30.0) 7 (70.0) About one-third (34.2%) of the participants reported that Shift work they often worked overtime. Yes 49 (67.1) 25 (51.0) 24 (49.0) 0.077 (P) No 24 (32.9) 7 (29.2) 17 (70.8) Findings relating to the living and socioeconomic Overtime conditions of the sample are included in Table III. Access to Yes 25 (34.2) 12 (48.0) 13 (52.0) 0.605 (P) services was relatively high, and most (97.2%) had electricity No 48 (65.8) 20 (41.7) 28 (58.3) in their dwellings. Most of the participants lived within a 50 km radius of the smelter, and the majority (84.7%) had *Indicates significance at p < 0.05. (P) Pearson’s chi-square test commuting times of less than 30 minutes. Most used their performed. (F) Fisher’s exact test performed. own vehicles to travel to and from work. The median number of people that relied on the participants’ incomes was four. Over a quarter (27.4%) reported always or often finding it difficult to pay for all the things they needed, and 39.7% 11.1%, 16.7%, and 72.2%, respectively, prior to days off reported owing money to someone. work. Participants also generally reported having better With regard to lifestyle, 32.9% reported exercising in quality sleep before a day off work than before a work day. their leisure time more than once a week, 15.7% smoked, Table V shows that 21.4% of the participants reported and 41.1% drank alcohol more than once a month (Table IV). having a medical condition and 23.3% reported taking In terms of nutrition, 76.7% considered the food they ate to medication. Most (86.3%) considered their health to be good be healthy or very healthy; none reported it to be unhealthy or very good, and 34.7% had not taken any sick leave in the or very unhealthy. Over a quarter of the participants (26.0%) previous year. While some of the participants were unsure if reported usually having fewer than 6 hours of sleep in the 24 they had a sleep disorder or not, 15.9% reported having one. hours before a work shift; 27.4% slept for 6–7 hours, and Around 4.2% of the sample reported having a work-related 46.6% slept for 7 or more hours. These values compare to injury, and 2.8% had been involved in a work-related

VOLUME 119          
  
 315 L Contributors to fatigue at a platinum smelter in South Africa

Table III ((%*)%*$# (#' #%# ( * #%(&(#%*)"()!'$*)%*&'*)$$# ()&(#%$*(&*)&('

)"()!' )"&( ()%&$ )&(' ( %* '$*%* #*%* )!'

Location of dwelling Mine (smelter) property 8 (11.3) 5 (62.5) 3 (37.5) Suburban area 34 (47.9) 15 (44.1) 19 (55.9) 0.230 (F) Township 18 (25.3) 9 (50.0) 9 (50.0) Rural area 11 (15.5) 2 (18.2) 9 (81.8) Housing tenure status Owned and fully paid off 6 (8.7) 1 (16.7) 5 (83.3) Owned but not yet paid off 25 (36.2) 10 (40.0) 15 (60.0) 0.037* (F) Rented 33 (47.8) 19 (57.6) 14 (42.4) Occupied rent-free 5 (7.3) 0 (0.0) 5 (100.0) Level of crowding (number in room) One 17 (23.6) 9 (52.9) 8 (47.1) Two 40 (55.6) 15 (37.5) 25 (62.5) 0.415 (P) More than two 15 (20.8) 8 (53.3) 7 (46.7) Piped water in dwelling Yes 60 (87.0) 26 (43.3) 34 (56.7) 0.724 (F) No 9 (13.0) 3 (33.3) 6 (66.7) Flush toilet Yes 64 (88.9) 31 (48.4) 33 (51.6) 0.068 (F) No 8 (11.1) 1 (12.5) 7 (87.5) Commuting time Less than 15 minutes 9 (12.5) 3 (33.3) 6 (66.7) 15 to less than 30 minutes 52 (72.2) 25 (48.1) 27 (51.9) 0.598 (F) 30 minutes to less than an hour 11 (15.3) 4 (36.4) 7 (63.6) Difficultly affording necessities Always/often 20 (27.4) 11 (55.0) 9 (45.0) Sometimes 24 (32.9) 13 (54.2) 11 (45.8) 0.076 (P) Occasionally/never 29 (39.7) 8 (27.6) 21 (72.4) Indebtedness Yes 29 (39.7) 15 (51.7) 14 (48.3) 0.270 (P) No 44 (60.3) 17 (38.6) 27 (61.4)

*Indicates significance at p < 0.05. (P) Pearson’s chi-square test performed. (F) Fisher’s exact test performed.

Table IV ('$&!'*)"()!'$*)%*&'*)$$# ()&(#%$*(&*)&('

)"()!' )"&( ()%&$ )&(' ( %* '$*%* #*%* )!'

Exercise Once a week or less 49 (67.1) 24 (49.0) 25 (51.0) 0.206 (P) More than once a week 24 (32.9) 8 (33.3) 16 (66.7) Smoke Yes 11 (15.7) 6 (54.5) 5 (45.5) 0.394 (P) No 59 (84.3) 24 (40.7) 35 (59.3) Drink alcohol Less than once a month 43 (68.9) 15 (34.9) 28 (65.1) 0.065 (P) More than once a month 30 (41.1) 17 (56.7) 13 (43.3) Healthiness of diet Healthy or very healthy 56 (76.7) 21 (37.5) 35 (62.5) 0.048* (P) Neither healthy nor unhealthy 17 (23.3) 11 (64.7) 6 (35.3) Average hours of sleep – before work <7 hours 39 (53.4) 20 (51.3) 19 (48.7) 0.170 (P) ≥7 hours 34 (46.6) 12 (35.3) 22 (64.7) Average hours of sleep – before off-days <7 hours 20 (27.8) 8 (40.0) 12 (60.0) 0.745 (P) ≥7 hours 52 (72.2) 23 (44.2) 29(55.8)

*Indicates significance at p < 0.05. (P) Pearson’s chi-square test performed. (F) Fisher’s exact test performed. L 316   
 VOLUME 119          
Contributors to fatigue at a platinum smelter in South Africa

Table V ')!&*)%*'!!%'$$*)"()!'$*)%*&'*)$$# ()&(#%$*(&*)&('

)"()!' )"&( ()%&$ )&(' (

%* '$*%* #*%* )!'

Medical condition Yes 15 (21.4) 6 (40.0) 9 (60.0) 0.801 (P) No 55 (78.6) 24 (43.6) 31 (56.4) Sleep disorder Yes 11 (15.9) 8 (72.7) 3 (27.3) 0.024* (P) No 58 (84.1) 21 (36.2) 37 (63.8) Medication Yes 17 (23.3) 10 (58.8) 7 (41.2) 0.155 (P) No 56 (76.7) 22 (39.3) 34 (60.7) Self-reported health Good or very good 63 (86.3) 27 (42.9) 36 (57.1) 0.740 (F) Not good 10 (13.7) 5 (50.0) 5 (50.0) Sick leave in previous year 0 days 25 (34.7) 8 (32.0) 17 (68.0) 1–9 days 34 (47.2) 16 (47.1) 18 (52.9) 0.202 (P) More than 10 days 13 (18.1) 8 (61.5) 5 (38.5) Stress Not at all / a little stressed 48 (67.6) 13 (27.1) 35 (72.9) 0.000* (P) Very stressed 23 (32.4) 18 (78.3) 5 (21.7) Job satisfaction Not satisfied 39 (54.9) 26 (66.7) 13 (33.3) 0.000* (F) Satisfied 32 (45.1) 5 (15.6) 27 (84.4) Quality of life Good 57 (79.2) 23 (40.4) 34 (59.7) 0.366 (P) Not good 15 (20.8) 8 (53.3) 7 (46.7)

*Indicates significance at p < 0.05. (P) Pearson’s chi-square test performed. (F) Fisher’s exact test performed.

Table VI )&('*")&(%$*

)"()!' )"&( ()%&$ )&(' ( %* '$*%* #*%* )!'

Enough sleep Yes 49 (67.1) 11 (22.5) 38 (77.6) 0.000* (P) No 24 (32.9) 21 (87.5) 3 (12.5) KSS ratings of general sleepiness 1 – 5: Not sleepy 38 (53.5) 8 (21.0) 30 (79.0) 0.000* (P) 6 – 9: Sleepy 33 (46.5) 24 (72.7) 9 (27.3) Fatigue rating – in general while at work Fully alert, wide awake 9 (12.7) 0 (0.0) 9 (100.0) Somewhat fresh, lively 18 (25.4) 5 (27.8) 13 (72.2) A little tired 29 (40.8) 11 (37.9) 18 (62.1)  * Moderately or very tired 9 (12.7) 8 (88.9) 1 (11.1) Completely exhausted 6 (8.5) 6 (100.0) 0 (0.0) Fallen asleep unintentionally at work in past year Yes 38 (52.1) 30 (79.0) 8 (21.1) 0.000* (F) No 35 (47.9) 2 (5.7) 33 (94.3) Summary fatigue variable Fatigued 32 (43.8% 32 (100.0) 0 (0.0) N/A Not fatigued 41 (56.2) 0 (0.0) 41 (100.0)

*Indicates significance at p < 0.05. (P) Pearson’s chi-square test performed. (F) Fisher’s exact test performed.

accident in the previous 12 months. Almost half of the A summary of the fatigue ratings of the participants can participants (45.1%) reported being satisfied with their jobs, be found in Table VI. Two-thirds (67.1%) thought that they 23.9% were neither satisfied nor dissatisfied, and 31.0% received enough sleep. The average level of sleepiness were dissatisfied. Most (79.2%) considered their quality of recorded in the KSS was 5 (‘neither alert nor sleepy’); 46.5% life to be good. One-third (32.4%) reported being very reported some degree of sleepiness, as indicated by a score of stressed. 6 or higher. When the participants were asked to rate how

VOLUME 119          
  
 317 L Contributors to fatigue at a platinum smelter in South Africa fatigued they usually felt while at work, 21.2% reported contributed to fatigue. The factors that were significantly feeling moderately tired or completely exhausted. Over half associated with fatigue were age, race, housing tenure status, (52.1%) reported having unintentionally fallen asleep while healthiness of diet, sleep disorders, stress and job at work in the past year. From the summary variable based satisfaction. on the results for these four fatigue-related items, 43.8% of The higher levels of fatigue reported by the younger the participants were classified as fatigued. A summary workers could be a result of the ‘healthy worker effect’, as variable could not be calculated for two participants, as a those that can best handle the work demands are most likely result of missing data, reducing the sample size for the chi- to remain in the job. It might also be a result of social square and Fisher’s exact tests to 73. activities that the younger participants are involved in outside of work. This was mentioned in the focus groups. Reasons   for the non-black group reporting lower levels of fatigue Results of the Pearson chi-square and the Fisher’s exact tests could be because they were, on average, older than the black are shown in Tables I to VI, together with the percentage of participants, and because a lower percentage of them did shift participants in each category that were identified as fatigued. work. However, only nine (12.3%) of the participants were Both age and race were associated with fatigue (p<0.05, non-black, which could have biased the results. Table I). A higher proportion of those aged 35 years or It was unexpected that none of the work-related variables younger reported to be fatigued than those older than 35. were significantly associated with fatigue. It was anticipated Black participants reported fatigue more frequently than that factors such as working shifts and working overtime those of other race groups. The proportion of participants that would be associated with higher levels of fatigue. However, it was not black was small, which could influence the validity of is noteworthy that the participant groups generally either this result. Most of the non-black participants (89.9%) were worked shifts (i.e. production and laboratory workers) or over 35 years and only 22.2% of this group did shift work. commonly worked overtime (e.g. those in engineering). As No statistically significant associations with fatigue and sex, such, it is possible that these factors counteracted the marital status, home province, or education were seen. associations, as shift work and overtime would both affect None of the recorded work-related variables were fatigue in the different groups. significantly associated with fatigue (Table II). However, Those who rented accommodation or were paying some trends were evident, such as higher levels of fatigue in housing debts reported higher levels of fatigue than those those working at the furnace and the process laboratory than who lived rent-free or had paid off their housing. The latter in those working in the regional laboratory and the group might be less stressed and under less pressure to work engineering department. Higher levels of fatigue were also harder or longer hours to earn production bonuses. As the reported by those that did shift work, those that worked overtime, and permanent employees, although the differences living conditions, commuting times, and socioeconomic were not statistically significant. conditions of the participants were generally not seen to be Housing tenure was associated with fatigue (p<0.05, problematic, this could explain the lack of association of Table III). Those who owned and had fully paid off their these factors with fatigue in this sample. homes and those who occupied dwellings rent-free reporting Those who considered their diets to be healthy reported lower levels of fatigue than those who rented or owned but lower levels of fatigue. Healthier diets might lead to better or had not yet paid off their dwellings. Area of dwelling, level of more sustained energy levels. Reports of healthy eating might crowding, access to piped water and flush toilets, commuting also be linked to personality or psychosocial states or traits, time, difficulty affording necessities, and indebtedness were with those who are more optimistic reporting better health not significantly associated with reported fatigue. and lower fatigue. Those who considered their diets to be healthy or very As might be expected, those who reported having a healthy reported less fatigue (p<0.05), but exercise, alcohol sleeping disorder experienced higher levels of fatigue, likely use, smoking, and sleep received were not significantly due to inadequate restorative sleep. It was unexpected that associated with fatigue (Table IV). hours of sleep obtained were not significantly associated with Sleep disorders, stress, and job dissatisfaction were fatigue. This could point to the importance of sleep quality in positively associated with fatigue (p<0.05) (Table V). Those relation to fatigue, including the ability to adapt to shift work, reporting as having a sleep disorder, high stress levels, and rather than sleep length alone. It could also be that the 7- poor job satisfaction reported higher levels of fatigue. Having hour cut-off used in the study as an indicator of insufficient a medical condition, taking medication, self-reported health sleep was too high. conditions, sick leave, and quality of life were not statistically Higher stress levels and poorer job satisfaction were both associated with the fatigue variable in this study. The four strongly associated with fatigue. Stress and job variables that were used to predict fatigue were significantly dissatisfaction could be either causes or consequences of associated with the summary fatigue variable (p<0.001, fatigue. Workers might be stressed and dissatisfied because Table VI). they are fatigued, or fatigue may result from high levels of stress and dissatisfaction (e.g. because of impaired sleep ($ $$(#% quality). Stress and fatigue have commonly been considered Fatigue was identified in 44% of the study participants, as to be associated, and fatigue has been associated with indicated by subjective responses and reports of falling asleep impairments in mood (Åkerstedt et al., 2014; Republic of unintentionally while at work. From the interviews and focus South Africa, 2014; Shaw, 2003). Stress and job groups conducted, both work- and non-work-related factors dissatisfaction have also been linked (e.g. Coomber and L 318   
 VOLUME 119          
Contributors to fatigue at a platinum smelter in South Africa

Barriball, 2007). Extraneous variables, such as high ALHOLA, P. and POLO-KANTOLA, P. 2007. Sleep deprivation: Impact on cognitive workloads or challenging work conditions, might contribute performance. Neuropsychiatric Disease and Treatment, vol. 3, no. 5. to the experience of stress, job dissatisfaction, and fatigue, pp. 553–567. simultaneously. Although some research has shown fatigue BHP Billiton. 2005. Fit for Work/Fit for Life. Issue 1, May 2005. to be associated with increased sick leave or absenteeism and COOMBER, B. and BARRIBALL, K.L. 2007. Impact of job satisfaction components poor health (e.g. Åkerstedt et al., 2014), the current study on intent to leave and turnover for hospital-based nurses: A review of the failed to demonstrate these associations. Nevertheless, some research literature. International Journal of Nursing Studies, vol. 44, no. 2. pp. 297–314. trends were evident in the data, such as correlation of increased fatigue with increased sick leave, poorer subjective DI MILIA, L., SMOLENSKY, M.H., COSTA, G., HOWARTH, H.D., OHAYON, M.M., and PHILIP, P. 2011. Demographic factors, fatigue, and driving accidents: An health, and poorer quality of life examination of the published literature. Accident Analysis and Prevention, A limitation of the study is the small sample size, which vol. 43, no. 2. pp. 516–532. might have reduced the statistical significance of the GALOBARDES, B., SHAW, M., LAWLOR, D.A., LYNCH, J.W., and SMITH, G.D. 2006. findings. The use of convenience sampling was a further Indicators of socioeconomic position (Part 1). Journal of Epidemiology and limitation, as it could result in sampling bias. The study Community Health, vol. 60, no. 1. pp. 7–12. participants might not have represented the workforce, being HORREY, W.J., NOY, Y.I., FOLKARD, S., POPKIN, S.M., HOWARTH, H.D., and COURTNEY, healthier and less fatigued workers, as they were not absent T.K. 2011. Research needs and opportunities for reducing the safety from work or on sick leave at the time of the study. Another consequences of fatigue. Accident Analysis and Prevention, vol. 43, no. 2. limitation is that the study made use of self-reported data. pp. 591–594.

Factors such as personality, mood, and understanding could HOSSAIN, J., REINISH, L., KAYUMOV, L., BHUIYA, P., and SHAPIRO, C. 2003. have affected the responses. Furthermore, as the focus of the Underlying sleep pathology may cause chronic high fatigue in study was to gather more information about non-work shift workers. Journal of Sleep Research, vol. 12, no. 3. pp. 223-230. contributors to fatigue, only basic data about work-related Minkel, J., Htaik, O., Banks, S., and Dinges, D. 2011. Emotional expressiveness factors was gathered. The inclusion of more detailed work- in sleep-deprived healthy adults. Behavioral Sleep Medicine, vol. 9, no. 1. related information, such as work design, scheduling, and pp. 5–14. environmental factors, would have allowed for a more MOLARIUS, A., BERGLUND, K., ERIKSSON, C., LAMBE, M., NORDSTRÖM, E., ERIKSSON, complete understanding of contributors to fatigue at these H.G., and FELDMAN, I. 2006. Socioeconomic conditions, lifestyle factors, operations. It should also be noted that as the study was and self-rated health among men and women in Sweden. European conducted at a single workplace, the findings may not be Journal of Public Health, vol. 17, no. 2. pp. 125–133. generalizable. Notwithstanding these limitations, we believe NSW (New South Wales, Australia). 2009. Department of Primary Industries, that the results provide an indication of levels of fatigue and Fatigue Management Plan: A practical guide to developing and contributors to them. implementing a fatigue management plan for the NSW mining and extractives industry. Version 1.0. www.dpi.nsw.gov.au/__data/assets/ pdf_file/0017/302804/Guide-to-the-Development-of-a-Fatigue- #% !$(#%*)%*"' # '%)&(#%$ Management-Plan-Amended-17-6-10.pdf Several demographic, living condition, lifestyle, health, and ORR (Office of Rail and Road). 2012. Managing rail staff fatigue. January wellness variables were associated with fatigue in this group 2012. London, UK.http://orr.gov.uk/__data/assets/pdf_file/0005/ of smelter workers. Generally, factors within the work 2867/managing_rail_fatigue.pdf environment receive most attention when it comes to fatigue REPUBLIC OF SOUTH AFRICA. 2014. Guideline for the Compilation of a Mandatory management. It is recommended that mining workplaces also Code of Practice for Risk-Based Fatigue Management at Mines. take factors outside of the workplace into consideration in Department of Mineral Resources. Government Gazette, vol. 32, their fatigue management programmes. Further study in no. 38339, 19 December 2014. different settings and with larger sample sizes would be SCHUTTE, P.C. 2009. Fatigue risk management: Charting a path to a safer worthwhile in order to confirm these findings, and to workplace. Proceedings of the Hard Rock Safety Conference. Southern generate recommendations relating to non-work contributors African Institute of Mining and Metallurgy, Johannesburg. pp. 245–250. to fatigue that can be applied more broadly. SCHUTTE, P.C. and MALDONADO, C.C. 2003. Factors affecting driver alertness during the operations of haul trucks in the South African mining industry. + %#!'' '%&$ Report no. SIM 02 05 02. CSIR Mining Technology, Pretoria, South Africa. SCHWARZ, J.F., POPP, R., HAAS, J., ZULLEY, J., GEISLER, P., ALPERS, G.W., This paper arises from a project conducted by the CSIR. We OSTERHEIDER, M., and EISENBARTH, H. 2013. Shortened night sleep impairs would like to thank Sophi Lestoalo, who was a research facial responsiveness to emotional stimuli. Biological Psychology, vol. 93, assistant for this study, and Sizwe Phakathi and Schu no. 1. pp. 41–44. Schutte for acting as co-supervisors. We are also grateful to SHAW, A. 2003. Guideline on fatigue management. Shaw Idea Pty Ltd,. the participating smelter and each of the participants involved Mt Egerton, Victoria, Australia. in the study. SHEN, J., BARBERA, J., and SHAPIRO, C.M. 2006. Distinguishing sleepiness and fatigue: Focus on definition and measurement. Sleep Medicine Reviews, /''"'% '$ vol. 10, no. 1. pp. 63–76.

ÅKERSTEDT, T., AXELSSON, J., LEKANDER, M., ORSINI, N., and KECKLUND, G. 2014. Do VAN DONGEN, H.P. and DINGES, D.F. 2000. Circadian rhythms in fatigue, sleep, stress, and illness explain daily variations in fatigue? Journal of alertness, and performance. Principles and Practice of Sleep Medicine, Psychosomatic Research, vol. 76, no. 4. pp. 280–285. vol. 20. pp. 391–399.

ÅKERSTEDT, T. and GILLBERG, M. 1990. Subjective and objective sleepiness in WILLIAMSON, A., LOMBARDI, D.A., FOLKARD, S., STUTTS, J., COURTNEY, T.K., and active individuals. International Journal of Neuroscience, vol. 52, no. 1–2. CONNOR, J.L. 2011. The link between fatigue and safety. Accident Analysis pp. 29–37. and Prevention, vol. 43, no. 2. pp. 498–515. N

VOLUME 119          
  
 319 L  
   Skills for the future – yours and your mine’s



Glenhove Conference Centre, Melrose Estate, Johannesburg

BACKGROUND Previous SAIMM Mine Planning forums have clearly highlighted deficiencies in mine planning skills. The 2012, 2014, and 2017 colloquia all illustrated developing skill-sets with a variety of mine planning tools in a context of multiple mining methods. Newer tools and newer skills for the future of mining will feature in 2019.

OBJECTIVES WHO SHOULD ATTEND Using a backdrop of a generic description of the multidisciplinary mine ­ Mine planners and practitioners planning process, the forum provides a platform for the mine planning ­ Mine designers fraternity to share mining business-relevant experiences amongst ­ Technical support staff peers. While different mining environments have their specific ­ Cost and financial modellers information requirements, all require the integration of inputs from ­ Chief planners different technical experts, each with their own toolsets. ­ The forum’s presentations will highlight contributions from a series Mineral resource managers of technical experts on current best practice, and will be augmented by ­ Mine managers responsible for planning displays of state-of-the-art mine planning tools in order to create a ­ Consultants learning experience for increased planning competencies. ­ Independent mine planning consultants

FOR FURTHER INFORMATION CONTACT: Camielah Jardine • Head of Conferencing • SAIMM Tel: +27 11 834-1273/7 • Fax: +27 11 833-8156 E-mail:[email protected] •Website: http://www.saimm.co.za http://dx.doi.org/10.17159/2411-9717/2019/v119n3a12 South Africa’s options for mine- impacted water re-use: A review by T. Grewar1

a 40% water shortfall by 2030, which may *7916:6 affect up to 1.8 billion people based on current water demand trajectories (Zhuwakinyu, South Africa is a water-scarce country, rated as one of the 30 driest countries in the world. Worryingly, government expects water demand to 2017). outstrip supply as early as 2025. The South African government believes Currently, South Africa is experiencing the that substantial volumes of water can be made available through the re- worst drought since 1904, which has triggered use of treated mining-impacted water. Currently, however, large volumes severe water shortages, negatively affecting of treated mining-impacted water are produced, often with no end use in agricultural output in all sectors (News24, mind other than discharge or disposal, when these treated effluents may 2016). The potential exists for nation-wide have further uses in applications which are currently and unnecessarily ‘water-shedding’ initiatives, similar to the using high-quality water. Treating the wastewaters to levels that meet electrical load-shedding programme initiated ’fitness-for-use’ guidelines for alternative applications such as agriculture, by Eskom, being implemented for homes and sanitation, or industrial processes will reduce the treatment cost burden businesses in the near future if the situation compared to potable water production. The primary conclusion of this review is that the most suitable option for re-using treated mine-impacted continues to decline. Currently, water water is in agriculture, for irrigation of crops (food, forage, or energy restrictions are in place country-wide with the crops), which currently and unnecessarily makes use of the majority of Western Cape being the worst affected South Africa’s high-quality resources or potable water. Other findings province. In 2016, eight of the nine provinces, include the realization that although guidelines and legislation for water with the exception of Gauteng, were declared re-use in South Africa exist and are readily available, they tend to be drought disaster areas. The country’s total contradictory and confusing in many cases. It is imperative that these water supply is currently estimated at ambiguities and incongruities in the available guidelines and legislation 14.6 km3/a, of which surface water is the main for water re-use be clarified and updated swiftly. source. The current demand is estimated to be =*'98.6 between 15 km3/a and 16 km3/a, and it is water re-use, mining-impacted water (MIW), agriculture, acid mine expected that South Africa will experience a drainage (AMD). 17% water supply and demand gap by 2030 (Webb, 2015; News24, 2016; Zhuwakinyu, 2017). The UN World Water Development Report (2017) argues that improved wastewater 7;89.-2;:97 management could facilitate the achievement South Africa is a water-scarce country and is of the UN’s 2030 Sustainable Development currently rated as one of the 30 driest Goals (SDGs). SDG-6 specifically has a target countries in the world, with an average rainfall to reduce the proportion of untreated of 490 mm/a, approximately half of the global wastewater by half by 2030. while sustainably average. As an indicator of the degree of increasing water recycling and safe re-use regional variability in South Africa’s water (WWAP, 2017). The report also suggests that supply, it has been shown that 70% of all wastewater which is traditionally discarded runoff is from approximately 20% of the land could be treated to provide a non-potable area. Regardless of the water scarcity faced in water resource for use in agriculture and South Africa, our water conservation track energy production. According to the Water record is poor, with an average consumption of 2017 Report, more than 50 countries 280 L/d per person, almost 60% more than the global average of 175 L/d per person. Around 40% of this allocation is utilized in watering lawns and gardens (Zhuwakinyu, 2017). The South African government predicts water demand to outstrip supply as early as 1 Biotechnology Division, Mintek South Africa. 2025. On an international scale, the situation © The Southern African Institute of Mining and appears just as dire, with the United Nations Metallurgy, 2019. ISSN 2225-6253. Paper received High Level Panel on Water (HLPW) expecting Jan. 2018; revised paper received Oct. 2018.

VOLUME 119          
  
 321 L South Africa’s options for mine-impacted water re-use: A review worldwide are already making use of treated wastewater for treating minewater to potable standards, with the treatment irrigation, accounting for approximately 10% of all irrigation costs estimated to be between R12 and R18 per cubic metre water world-wide. (Annandale et al., 2007; Webb, 2015). The question, A number of proposals have been put forward by the however, remains whether it is necessary to treat the South African government to increase water supply. These minewater to potable levels, thereby incurring high treatment include; rainwater harvesting; desalination; increasing the costs, when activities like irrigation of crops, flushing of yield from surface water; and promoting the use of toilets, and washing of clothes do not require potable water. groundwater on a larger scale (Webb, 2015). Currently, Does it not make sense to reduce the treatment burden and surface water comprises about 79% of the total water supply subsequent cost by treating the water only to levels that are of the country while groundwater, mainly used in rural areas, suitable for these or similar activities? comprises only about 14%, with the balance (7%) comprising Minister Mokonyane reaffirmed the South African re-used water. Government believes that substantial volumes government’s stance on water re-use and recycling while of water can be made available through the increased re-use speaking at the launch of the United Nations World Water of return flows, especially in some coastal cities where Development Report 2017 in March 2017. She stated that potentially re-usable wastewater is currently discharged into ’recycling water for industrial and agricultural purposes the sea, as well as the re-use of treated acid mine drainage would go a long way towards ensuring the country’s water (AMD) in particular or mine-impacted water (MIW) in security’ (Zhuwakinyu, 2017). To help incentivize water re- general (Webb, 2015). use, the DWS announced in May 2016 that government In the context of this review, AMD is defined as an acidic would provide R600 million every year towards treating MIW, effluent with high sulphate and metal concentrations with the funds allocated directly by the National Treasury. emanating from abandoned or ownerless mines, and MIW is Some of these funds will be recovered from users of the defined as any wastewater of varying pH that has in some treated water (33%) while the balance of 67% will be way been affected by mining or a mining-related process, and recovered from the polluting mining operations through a hence can encompass AMD among other effluent types. For proposed environmental levy (Zhuwakinyu, 2016). this reason, these two terms will be used interchangeably. Government’s short-term intervention for MIW treatment The goal of this review was to perform an overview of the in the Witwatersrand Basin in Gauteng have included the literature to determine the current state of MIW re-use in installation of three high-density sludge (HDS) treatment South Africa and to provide a central resource of information plants in Krugersdorp, Germiston, and the most recent regarding legislation, available guidelines, and potential commissioned in Springs during February 2017. These plants options for re-using treated MIW. can treat 50 ML/d, 82 ML/d, and 110 ML/d of decant respectively, after which it is released into nearby water ":7:70:51<2;=.>'<;=8>:7>9-;)>(38:2<> resources (Zhuwakinyu, 2017). The major problem with this solution, however, lies in the fact that water treated by HDS The impacts of mining range from initial exploration through has sulphate levels that are well above those allowable for the life-cycle of the mine to beyond mine closure. Mining- discharge, in addition to a number of issues surrounding impacted water disposal poses serious problems globally, and storage and disposal of the sludge produced. the quality of the impacted water depends greatly on the chemical and mineralogical characteristics of the orebody. Owing to its salinity, minewater generally cannot be &-88=7;>;8=<;5=7;>;=2)79490:=6 discharged into river systems unless diluted with good Since this reviews’ focus is not on MIW treatment quality water to reduce the salinity to within acceptable technologies but rather on uses for the treated water, this limits. For this reason, the Department of Water and section will merely highlight the more mainstream treatment Sanitation (DWS) is assessing the installation of desalination options currently in use, along with some of the newer plants to treat MIW to levels that will enable safe discharge; technologies that are becoming available. These include however, the long-term view on MIW treatment includes Mintek’s passive biological sulphate reduction (BSR) process desalination to potable standards to augment fresh water and SAVMINTM, both of which address salinity issues. These supply. A number of coal mines in Mpumalanga are already technologies are summarized in Table I.

Table I -55<8*>93><<:4<4=>" >;8=<;5=7;>;=2)79490:=6

=2)79490* 8=<;5=7;>5=;)9.  >296; <6;=>:66-=6> 9;<4=79719;<4=

1Reverse osmosis (RO) Membrane High (R12-18/m3) Brines Potable 2High-density sludge (HDS) Precipitation 3Low (R1-2/m3) Sludges Non-potable/high-sulphate

4SavminTM Precipitation Med/high (R10/m3 for 2 g/L SO4) Metal hydroxides, gypsum 5Potable and non-potable 6Passive biological sulphate Biological dissimilatory 7Low/med (R3-5/m3) 8Sulphide Non-potable/fit-for-use reduction (BSR) sulphate reduction

1Greenlee et al. (2009) 5Potable water is possible depending on inlet feed composition 2Zhuwakinyu (2017) 6Grewar (2017) 3Van Zyl et al. (2001) 7Mintek (2018) 4Van Rooyen (2017) 8Potential to include a polishing step where sulphide can be recovered as biosulphur (value-added product) L 322   
 VOLUME 119          
South Africa’s options for mine-impacted water re-use: A review

<;=8>8=-6= cooling, washing), non-potable urban uses such as fire protection, air conditioning, sanitation (toilet flushing), and The Department of Water and Sanitation is the custodian of potable re-use. South Africa's water resources and is responsible for Re-use and recycling within industrial processes is fast ensuring that water resources remain fit for recognized uses becoming the norm as regulations and laws regarding and are maintained and protected (DWAF, 1996). environmental protection and water security are becoming Four broad categories of water use are recognized in the increasingly stringent. However, there are still large volumes South African National Water Act (Act 36 of 1998), namely of treated effluent being produced with no end use in mind domestic, industrial, agricultural, and recreational use. These categories can each be subdivided into a number of other than discharge or disposal. These treated effluents subcategories, all of which may have vastly different water could be re-purposed for other applications that are quality requirements. The minimum contaminant limits unnecessarily using high-quality water resources. By simply (MCLs) for a variety of constituents have been defined for the adopting the ‘water quality cascade’ approach (Stoakley, recognized water use categories in the South African Water 2013), which refers to the linking of the quality of a Quality Guidelines (volumes 1 through 8) produced by the wastewater source to an appropriate subsequent activity, all Department of Water Affairs and Forestry (1996). ’Water use’ available water would be put to its most beneficial use even characterization involves investigating various characteristics as the quality decreases after each re-use. For example, of a specific water use (i.e. costs, socio-economic benefits, minewater may be suitable for a number of alternative volume of use), which assists in determining the applications (agriculture, sanitation, industry) provided that consequence thereof. In addition, various legislated it is treated to acceptable levels for various contaminants. guidelines are considered in conjunction with risk-based Advantages of this approach include the resultant capex and factors to determine the water quality required for a particular opex cost savings from a reduced treatment burden as well as use. The water quality requirements for water use are usually the identification of an alternative water resource. determined on a site- or case-specific basis (DWAF, 1996). The aim of this re-use ‘philosophy’ would ultimately be to The traditional ‘once-through’ centralized water reduce potable water consumption and subsequently increase management system is being re-thought due to growing water conservation. The practice of using reclaimed water scarcity owing to population growth, urbanization, and wastewater is, however, not risk-free, hence proper planning climate change. This has become a global problem that has and risk analysis are essential to mitigate the risks applicable triggered renewed interest in water recycling and re-use. An to the re-use application identified. array of ecological and financial benefits can be generated by        decentralized water re-use systems, in addition to the supplementing of existing stressed water supplies (Stoakley, There are a number of South African Acts that are applicable 2013). when water is used and effluent is discharged. Although the Water Services Act (No. 108 of 1997) (WSA) and the     National Water Act (Act 36 of 1998) (NWA) form the The National Water Resources Strategy (NWRS) first edition foundation for the legislative framework within the sector, (2011) identified water re-use as one of a number of other Acts which are also important include the Environment important strategies to balance water availability and Conservation Act (Act 73 of 1989) (ECA) and the National requirements in the future. One of the commitments of the Environment Management Act (Act 107 of 1998) (NEMA), NWRS is, ‘DWA [now the DWS], with sector partners will where recent amendments would also be applicable. In some explore the use of new technologies for re-using waste water instances specific municipal bylaws may also be relevant and for using treated mine water’. With the 2013 NWRS2 an (South Africa, 1989, 1997, 1998a, 1998b). annexure (D) was released specific to the national strategy The NWA (Act 361 of 1998), however, is the primary for water re-use. It stated that water re-use can be classified legislation governing the use and discharge of ‘wastewater’. as direct or indirect, planned or unplanned, on a large or a The Act aims to ensure that the nation’s water resources are small scale irrespective of location. It may involve a variety of protected and managed to reduce and prevent pollution and treatment options or none at all, with the reclaimed water degradation of water resources. The Act also promotes the being used for a number of activities, each with its own re- ‘polluter pays’ principle, and the stringent Wastewater use strategy. There is, however, an associated risk that water Discharge Standards Guidelines proposed by the then re-use may be unplanned, unregulated, and/or result in Department of Water Affairs in 2010 will force industries to unintended or undesirable consequences. develop their own cleaner production systems. The Act Water quality and security of supply, water treatment requires that any person using wastewater for irrigation technology, cost relative to other water supply alternatives, purposes, discharge, or disposal must register with the social and cultural perceptions, and environmental responsible authority as a registered water user and must considerations are the five key considerations that affect ensure that the wastewater does not impact other water choices related to water re-use as an option for water supply sources, property, or land and that the wastewater is not augmentation (South Africa, 2013). detrimental to the health of the public. The inclusion of planned water reclamation, recycling, In South Africa, the WSA (Act 108 of 1997) relates more and re-use schemes in water resource systems reflects the to the management of human drinking water and directs bulk increasing scarcity of water sources as a whole. Some of the water suppliers to the compulsory national standards in the categories of potential wastewater re-use are agricultural, form of SANS 241-1:2015. The SANS 241 standard is landscape irrigation, industrial recycling and re-use (i.e. specifically designed with bulk water suppliers in mind and is

VOLUME 119          
  
 323 L South Africa’s options for mine-impacted water re-use: A review aimed at safe water provision for domestic drinking use, and which will most likely also be applicable to the re-use of thus focuses on life-long safety for all types of users and treated minewater. Several surveys completed more recently aesthetic acceptability (South Africa, 1997). have revealed numerous additional factors that appear to Currently the re-use of effluent streams requires influence the perceptions, acceptability, and overall successful environmental authorization in terms of the NEMA implementation of recycled water regardless of the source (107:1998), and in some cases requires water use licences within a community. Some of these factors include the (WULs) in terms of the NWA (36:1998). Specifically, all new sources of the water to be re-used, trust in and knowledge of and existing mines are required, in terms of the NWA the treatment processes producing the water for re-use, the (36:1998), NEMA (107:1998), and the Mineral and specific activities related to water re-use, and the cost of Petroleum Resources Development Act (Act No. 28 of 2002) water reuse (Bruvold and Ward, 1972; Stoakley, 2013). (MPRDA), to optimize water re-use and reclamation (DWA, Stoakley (2013) conducted surveys among South African 2013). university students to determine their perceptions around Other regulations relevant to the use of water for mining water re-use. The results showed a high degree of and related activities in South Africa, aimed at the protection acceptability for non-potable uses such as watering gardens of water resources, are published in terms of the NWA and toilet flushing, which increased with the premise that (36:1998) in the Government Notice 704 of 4 June 1999, either the individual would personally not have access to known as GN704, which states that mines must collect, clean water without re-use or it would benefit the confine, and take reasonable measures to prevent water environment. Reluctance appeared greater in the potable use resource contamination as well as ensure that water used in category, with concerns surrounding health and safety being any process at a mine or activity is recycled as far as paramount. practicable (Munnik and Pulles, 2009). Water re-use projects in the past have, however, shown Although it is unfortunate that much of South Africa’s that the level of community acceptance and perceptions water-quality woes stem from a lack of coordination in around elements such as cost, risk, and necessity are vital indicators of a planned project’s eventual success or failure addressing the water contamination issue, this concern is (Stoakley, 2013). For these reasons, the benefits of expected to be addressed when the Mine Water Management proactively providing opportunities for public participation in Policy (MWMP) comes into effect. The draft proposal was the development process should be carefully considered and approved by Cabinet in 2017 and later gazetted by the DWS will far outweigh the perceived administrative burdens of in July 2017, allowing a 60-day period for public comment. such a task by ensuring a smoother, more successful The MWMP policy is aimed at (a) ensuring improved water implementation phase. quality management and reduction of water pollution, including through AMD treatment, (b) strengthening the :;7=66>398>-6= protection of water resources from mine water contamination The South African Water Quality Guidelines, volume 3 from short to long term, and (c) providing a basis for holding (DWAF, 1996), sums up ‘fitness for use’ as a judgement of parties potentially liable for negative effects and damages how suitable the quality of water is for its intended purpose through AMD-related pollution (DWS media statement, 14 or for protecting aquatic ecosystems. However, with modern July 2017; Zhuwakinyu, 2017). technology water of nearly any quality can be produced for a        specific purpose provided it can be treated to the required specifications. Therefore, how fit a particular water source is    for use depends also on the design specifications for the Bruvold and Ward (1972) conducted one of the earliest process and how much the user is prepared to invest in studies on public perceptions of recycled water usage. They treating the water to comply with these specifications. Hence, identified ‘psychological repugnance’, also known as the ‘fitness for use’ is largely defined by the use of water quality ‘yuck factor’, as the main reason for opposition to the use of guidelines. Table II provides a summary of a number of treated water originating from municipal wastewater and different categories of water re-use.

Table II &<;=098:=6>93>19;=7;:<4>8=-6=>398>;8=<;=.>(" >,<.<1;=.>3895> (>$/#%+

&<;=098*>93>8=-6= =628:1;:97>93>2<;=098*

Urban use Unrestricted irrigation Landscape irrigation of parks, playgrounds, school yards, golf courses, cemeteries, residential areas, green belts Restricted irrigation Irrigation of areas with infrequent and controlled access Other uses Fire protection, disaster preparedness, construction Agricultural use Food crops Irrigation for crops grown for human consumption Non-food crops and crops consumed after processing Irrigation for fodder, fibre, flowers, seeds, pastures, commercial nurseries, instant lawn Other use Industrial re-use Cooling system water, process water, toilets, laundries, air-conditioning, wash-down water Residential re-use Cleaning, laundries, toilets, air-conditioning Potable re-use Blending with municipal water supply, pipe-to-pipe supply L 324   
 VOLUME 119          
South Africa’s options for mine-impacted water re-use: A review

Both locally and internationally, a number of limits and ® MCL levels for Ca and Mg have not been set for the guidelines for different contaminants are available in the select group of activities where re-use is possible, not literature. However, many of these deviate significantly from even for human consumption one another in terms of approaches and methodologies used ® SO4 MCL levels are more stringent for discharge to a to arrive at the specified criteria. For this reason, the DWAF sewer than for human consumption, with none set at (now DWS) South African Water Quality Guidelines all for discharge to a watercourse (SAWQG) volumes 1 to 8 (1996) were developed to provide a ® MCL for SO4 for irrigation is not set in any of the single set of guidelines and criteria for water quality and formal guidelines or legislation fitness for use that is appropriate for recognized water uses ® Allowable EC levels for irrigation differ in the NWA in a South African context. guidelines (South Africa, 2013) compared to the DWAF Based on the definitions, concepts, and guidelines above, irrigation guidelines (1996) an assessment was performed in order to determine the most ® Fe MCL for discharge to a water resource is more suitable uses for treated MIW. Using available data, which in stringent than that for human consumption, and the some cases was limited, we directly compared the maximum same applies in the case of Mn contaminant limits (MCLs) of the more relevant elements in ® Allowable pH levels differ in the DWAF irrigation MIW for potentially feasible re-use activities, including crop guidelines (1996) from those in the NWA guidelines irrigation (DWAF Volume 4; 1996), discharge to a sewer for (South Africa, 2013). sanitation (City of Johannesburg Metropolitan Municipality These incongruities and the absence of set limits in some Water Services By-laws, 2008), discharge to a watercourse cases within the available guidelines and legislation for water (South Africa, 1998b), and drinking water (SANS 241:2015). re-use pose a potential hindrance to the technology and R&D These are compared in Table III. framework, which requires clear and unambiguous guidelines It should be noted here that although industrial re-use is upon which new technology is designed and developed. an option and is being considered in some respects, it was These guidelines therefore need to be clarified and updated not considered in this review to be a viable option. This was timeously so as to not adversely affect technology primarily due to the results from a study performed by the development in this sector. DWA (2013) that determined that although there are a large The various options for treated MIW reuse are discussed number of industries located within the Rand Water supply in more detail below. area affected by AMD decant, 67% of the industrial water demand is required by only three individual super-factories,   all of which are distant from the AMD generation points and The success of the eMalahleni Water Reclamation Plant require very high-quality water (above potable water (EWRP) in Witbank has demonstrated the viability of using standards), which is not provided by neutralized or MIW treated to potable levels for residential human minimally treated AMD. consumption. Potable water, however, comes at a hefty Interestingly, this direct comparison in Table III treatment price and depending on the treatment process, highlighted a number of incongruities in the available significant amounts of wastes (brines) are produced that guidelines and legislation used to compare the MCLs: present a costly disposal dilemma.

Table III &951<8:697>93>;)=>5<:5-5>297;<5:7<7;>4:5:;>,"&!+><4-=6>398><><8:=;*>93>8=-6=><2;::;:=6>':;)>8=61=2;>;9 18:5<8*>" >295197=7;6>

"<:5-5>297;<5:7<7;>4:5:;6>,"&!6+>,50!+ &97;<5:7<7; &891>:88:0<;:97>> #/ :62)<80=>>6='=8> ## :62)<80=>>'<;=829-86=>,0=7=8<4>4:5:;6+> #$ 8:7:70> <;=8

SO4 - 250 - 500 Cl-(a)700 1000 - 300 Mg (b)-- - - Al (c)20 - - 0.3 Ca - - - - Mn (d)10 50 0.1 0.4 Fe 20 200 0.3 2 Na (e)460 - - 200 SAR (sodium adsorption ratio) (f)15 - - - EC (mS/m) (g)540 (13150–200) 500 <150 170 pH 6.5-8.4 (135.5–9.5) - 5.5-9.5 5.0-9.7

Notes: (a) May exceed, depending on crop tolerance, target 100 mg/L; (b) Limits not set or not available; (c) May exceed, only acceptable over short term, target 5 mg/L; (d) May exceed, only acceptable over short term, target 0.02 mg/L; (e) May exceed, depending on crop tolerance, target 70 mg/L; (f) May exceed, some economically important crops can be irrigated without developing sodium toxicity, target 2.0 (g) May exceed, requires sound irrigation management, target 40 mS/m.

9DWAF 1996. South African Water Quality Guidelines for Agriculture: Irrigation (Volume 4) 12SANS 241:2015 Drinking water specification 10City of Johannesburg. 2008. Metropolitan Municipality Water Services By-laws 13South African National Water Act (No. 36 of 1998) 11South Africa (2013)

VOLUME 119          
  
 325 L South Africa’s options for mine-impacted water re-use: A review

As mentioned previously, potable water is not necessary the increased demand in this sector, which is expected to for a number of domestic activities. Hence MIW treated to the grow from 8.9 km3/a currently to 9.7 km3/a by 2035 (Webb, lowest requirements for such activities could provide 2015; Zhuwakinyu, 2017). significant savings in terms of treatment costs while The South African National Water Act (No. 36 of 1998), simultaneously having a positive impact on the environment specifically the revision of general authorization in terms of and our highly stressed water resources. This partial Section 39 of the National Water Act (Act no. 36 of 1998), treatment should, however, not only focus on neutralization published under Government Notice 665 in Government and the removal of metals, which in the past have been the Gazette 36820 dated 6 September 2013, classifies irrigation, primary focus of treatments options, but also on reducing the specifically irrigation with biodegradable industrial sulphate content as the salt load of the partially treated MIW wastewater and domestic wastewater, as a controlled activity would still present a contamination risk to resources via in terms of Section 21(e) that can be practiced only under domestic sewerage systems. license. Biodegradable industrial wastewater is defined in the Act  
 as wastewater that contains predominantly organic waste arising from industrial activities including, but not limited to, Agriculture accounts for around 70% of fresh water milk processing, abattoirs, manufacture of animal feed, and withdrawals from rivers, lakes, and aquifers worldwide with production of alcohol or alcoholic beverages in breweries, approximately 1000 L of water required to produce 1 kg of wineries, or malthouses. Although the Act specifies cereal grain, and 43 000 L to produce 1 kg of beef (Pimentel biodegradeable wastewater, all wastewater regardless of et al., 2004; Webb, 2015). source may be used for irrigation provided the water quality Irrigated agriculture is the largest consumer of available remains within the set guidelines. Permission is granted only water in South Africa. However, the abstraction rate related if the location of the water use complies with the guidelines to irrigation has decreased dramatically from 80% of that aim at preventing pollution of other water sources such available water resources 45 years ago to around 63% as aquifers, boreholes, watercourses, or wetlands. The Act currently (Zhuwakinyu, 2017). This downward trend has also details precautionary practices to ensure that the water continued, with irrigators experiencing increasing pressure to user follows acceptable construction, maintenance, and reduce their water use. Since many irrigation schemes are operational activities. In addition, sampling and monitoring is situated at the lower end of drainage basins they often also required to be performed on a regular basis and the receive poor quality water due to the influence of upstream results reported to the relevant authority. activities (DWAF: Volume 4, 1996). Wastewater limit values for a variety, albeit limited list, of Irrigators may experience a range of adverse effects as a contaminants are described in the Act (36:1998) for the result of variable water quality that may include reduced crop irrigation of any land or property specific to areas of (a) up to yield and quality, and soil degradation and damage to 2000 m3, (b) up to 500 m3, and (c) up to 50 m3 with equipment from scaling or corrosion. These effects can be domestic or biodegradable waste water (Table IV). mitigated by switching to a more tolerant crop or simply This list is unfortunately far from comprehensive and changing the irrigation method (DWAF, 1996, vol.). does not cover contaminants such as metals and sulphates. The South African government is planning a 33% However, guidelines for some of these are available in the increase in irrigated land by 2030 due to anticipated South African Water Quality Guidelines - Volume 4: increasing demand from the agricultural sector. This is being Agricultural Use: Irrigation (1996), produced by the DWAF driven by the National Development Plan (NDP), which has (summarized in Table III), and these need to be used in identified agriculture as a key element in food security, job conjunction with the Act to determine the quality of water creation, and social capital in rural communities as it has required for irrigation purposes. been recognized as having significant employment-creation potential due to the labour-intensive nature of the industry.   Other factors such as climate change, drought, and Pulles (2006) describes management options for saline MIW population growth are also expected to contribute heavily to in South Africa as (1) pollution prevention at source, (2) re-

Table IV <6;='<;=8>4:5:;><4-=6>398>:88:0<;:97>93><7*>1891=8;*>98>4<7.>-1>;9>$///>5% ,<.<1;=.>3895>9-;)>(38:2<>$/#%+>

<8:<4=6 !:5:;6>>>>>>>,$///>5%+ !:5:;6>, //>5%+ !:5:;6>, />5%+

pH 5.5-9.5 6-9 6-9 Electrical conductivity (mS/m) 150 200 200 Suspended solids (mg/L) 25 - - Chloride as free Cl (mg/L) 0.25 - - Fluoride (mg/L) 1 - - COD (mg/L) 75 400 5000 Ammonia (ionized and un-ionized) as N (mg/L) 3 - - Nitrate, nitrite as N (mg/L) 15 - - Orthophosphate as P (mg/L) 10 - - L 326   
 VOLUME 119          
South Africa’s options for mine-impacted water re-use: A review use and recycling of water to minimize the volume of polluted In summary, it is clear that using treated MIW for crop water that could also be treated, (3) treatment of effluents if irrigation confers a number of notable advantages, including the problem cannot be solved through prevention, re-use, the facts that (a) MIW requires a low level of treatment prior and recycling, and (4) discharge of treated effluent, which is to re-use in irrigation, resulting in substantial treatment cost considered the last resort. In addition, he also mentions the savings, (b) large portions of irrigated land are located near potential for using gypsiferous or lime-treated minewater for MIW sources, which would limit the collection and agricultural irrigation as a re-use strategy, particularly post distribution costs if MIW was utilized, (c) the treatment and mine closure. re-use of MIW could operate as a single financial initiative, A number of opportunities are provided by using with income from the MIW-irrigated crops funding the MIW gypsiferous mine wastewater in irrigation, including the treatment and/or creating jobs and food security for the local potential to enable dry season production as well as community, (d) treatment and re-use of MIW in crop stabilizing dryland crop production. Simultaneously, it would irrigation would relieve the environmental and health provide a relatively cheap method of reducing the volumes of liabilities of the mines producing the MIW, while minewater decant being produced unchecked. By irrigating simultaneously stimulating agriculture in the vicinity, and (e) with gypsiferous wastewater, a large percentage of the salts would make more high-quality or potable water available for present can be removed from the mine effluent through more pressing needs (van Zyl et al., 2001). gypsum precipitation into the soil profile (Annandale et al., The potential for linking mining with agriculture has been 2007). recognized by some in the industry, although it will need Several studies have been published around the widespread adoption to make a significant impact on the treatment of MIW within the upper Olifants River catchment status quo. A recent article in Mining Weekly Online (14 area which identified a number of advantages to irrigation September 2016) quoted Exxaro CEO Mxolisi Mgojo as with treated MIW. While the quantities, MIW treatment saying that ’I really think the land around our coal mines technologies, flow sheets, and the corresponding costs would should be developed into agricultural hubs’. The same article have changed since these studies were done, it can be reports that Sibanye Gold is rolling out a modern approach to expected that the advantages identified would still be relevant ensure community development in the areas in which it today, and these are explored in more detail below. operates, with the aim to leave an agricultural economy in its Grobbelaar et al. (2004) reported estimates of the place when operations cease in 30–40 years’ time. It was volumes of minewater stored and generated for various reported that 640 people are already employed and the mines in the central Witbank coalfields in Mpumalanga. They community has been benefitting from the sale of produce to state that after closure of the entire Mpumalanga coalfields, the Spar retail group. approximately 360 ML/d of mine-impacted water may be generated, while for the Olifants catchment area a volume of  170 ML/d was estimated. These enormous volumes, acting as Over the last 30 years various studies have been performed an alternative water resource, could potentially support over in South Africa on the potential of using minewater for 6 000 ha of irrigated land. On a more site-specific scale, the irrigation, with varying levels of success (du Plessis, 1983, Kleinkopjé Colliery in Witbank, which has an estimated daily Jovanovic et al., 1998; Annandale et al., 1999, 2001, 2002, water make of around 14 ML with a further 120 000 ML of 2006, 2007, 2009; Pretorius et al., 1999; Jovanovich et al., water stored underground could, depending on the crop 2002, 2004; van der Laan et al., 2014). A few examples are system chosen, sustain irrigation of 500–700 ha, alone. discussed below. In addition, van Zyl et al. (2001) reported that simply In 1983 Du Plessis (1983) was the first to investigate the treating minewater decant to irrigation standards, rather than use of gypsiferous minewater for irrigation purposes. He for urban or industrial applications, would reduce capital and found that lower soil and percolate salinity was achieved by running costs by 87% and 78%, respectively. Similarly, irrigating with gypsum-rich water instead of chloride-rich Annandale et al. (2007) compared the capital costs of several water of similar composition and attributed this to the treatment options, and showed treatment for irrigation to be precipitation of gypsum in the soil. Furthermore, the increase lower in cost by an order of magnitude. In addition, and of in sodium caused by gypsum precipitation did not particular importance in the post-closure period of a mine, the significantly affect the physical properties of the soil or crop income generated from the sale of the water could be offset yield. against the running costs. Further benefits include job Lime-treated MIW has been used successfully in the creation and protection of water resources, which are aligned irrigation of crops at the Landau Colliery Kromdraai Opencast to the government’s NDP. Section (Witbank, Mpumalanga). A field screening trial of 20 Currently, mine land post mine closure is rehabilitated, agronomic and pasture crops, including maize, soybean, rye, but usually not to the advantage of the local communities. wheat, lucerne, and kikuyu was investigated for irrigation by Mines in South Africa tend to be located in water-scarce lime-treated MIW on a sandy acidic soil. The results indicated areas, and use of the land for agricultural purposes would that considerable yield increases of irrigated crops could be require fresh water to be provided from further afield, which realized compared with rain-fed cropping, provided that is not economically viable. However, as explained above, the irrigation and fertilization practices were managed correctly treatment of MIW provides a water source on site or nearby, (Jovanovic et al., 1998). which then allows agriculture on the mine land to become a In 1997–1998, Annandale et al. (2001) undertook a field realistic opportunity for the surrounding community on a trial at Kleinkopjé Colliery in Witbank (Mpumalanga) to year-round basis (Jovanovich et al., 2002). determine the effect of using gypsiferous minewater for

VOLUME 119          
  
 327 L South Africa’s options for mine-impacted water re-use: A review irrigation of crops of sugar bean and wheat on rehabilitated In general, crop production under irrigation with opencast mine land. They found considerable increases in minewater rich in Ca and sulphate was found to be feasible yields of sugar beans and wheat under irrigation with and sustainable, if properly managed. The same team also gypsiferous minewater compared with rain-fed cropping. investigated the sustainability of irrigation with gypsiferous Specifically, yields of sugar beans on virgin land were higher coalfield minewater on a commercial scale and found that compared to those on the rehabilitated land. They attributed crops like sugar beans, wheat, maize, potatoes, and pastures this to a number of reasons, including late planting date, soil were very successfully produced with no significant impact compaction, low soil pH, and nutrient deficiencies, and not on the soil or surface and groundwater resources being necessarily the quality of the irrigation water. Excellent wheat observed, at least in the short to medium term (eight years). yields were obtained on both virgin and rehabilitated land, In 2014, van der Laan et al. reported on the potential for which was attributed to the fact that wheat is more tolerant to goldfield minewater from the Witwatersrand area to be used salinity than beans. In addition, no symptoms of foliar injury as an alternative irrigation water resource. The minewater due to overhead irrigation with gypsiferous water were was either pre-neutralized, as was the case for prior studies observed. performed on coalfield minewater described above, or raw Annandale et al. (2007, 2009) carried out a long-term minewater was applied to soils or mine tailings that had been study at three mines, namely Kleinkopjé Colliery near preconditioned with slaked lime or limestone. The Witbank, New Vaal Colliery near Vereeniging, and preconditioning of the soils was expected to facilitate in situ Syferfontein near Secunda. The average water qualities used neutralization and sequestration of many of the contaminants are summarized in Table V. All sites were centre-pivot present in the raw minewater. The results illustrated that irrigated with gypsiferous minewater, and some had begun goldfield minewater could be used as a cost-effective solution irrigation with minewater as far back as 1997. They found for the irrigation of salt-tolerant crops on agricultural land or that the maize yield from irrigation with minewater was vegetation on mine tailings. The researchers calculated that lower than dryland-produced crops, particularly on 60% of the salts from the neutralized minewater would be rehabilitated land, but attributed this to the poor drainage of retained within the soil profile, compared to 75–90% salt the site and the rapid rise in the electrical conductivity (EC) removal achieved from the raw water when irrigating observed over the irrigation period. However, wheat yield pretreated mine tailings or clay soils. was unaffected by similar water quality. They also The work described above is significant as it highlights determined that potatoes were successfully produced using the potential for the use of coal or gold minewater to be used gypsiferous minewater, and that pasture crops like lucerne for the production of various types of crops ranging from and fescue were unaffected by irrigation with Na2SO4-rich food for human consumption to forage and pasture crops for minewater at Syferfontein. No symptoms of foliar injury due livestock consumption and even for energy crops for biofuel to centre-pivot sprinkler irrigation with gypsiferous production. This is where the re-use strategy for MIW within minewater were observed for all crops. They did, however, agriculture specifically fits within the framework of the note that potassium (K) uptake was suppressed by the Water-Energy-Food (WEF) nexus, which is rapidly becoming presence of high calcium (Ca) and magnesium (Mg) in the a strategic area of importance, globally. water, and suggested that this could be corrected by regular application of K-containing fertilizer and following proper irrigation management. Some crop failures were noted but <7:;<;:97 these were attributed to poor site selection, resulting in About 40% of the water consumed by South African waterlogging of crops, rather than the water quality. households is used to flush toilets, and about 60% of the total water and sanitation costs are used to fund the treatment of this contaminated wastewater. On average, 200 g/d of human waste per person is flushed down the toilet, while 6–9 L of drinking quality water is used for each flush Table V (Webb, 2015). Potable water is, however, not necessary for (=8<0=>:88:0<;:97>'<;=8>-<4:;:=6><;>;)=>.:33=8=7; sanitation purposes and this represents a major 5:7=6>,<.<1;=.>3895>(77<7.<4=>et al>$//>$//+ mismanagement of our limited water resources. Unfortunately in South Africa, unlike other countries (7<4*;= (7<4*6=6>,50!+ such as Japan and Australia, dual reticulation systems which 4=:791> 4=:791> *3=8397;=:7 ='><<4 allow for the use of treated wastewater for sanitation are rare. ,"<98+ ,'==397;=:7+ These would be required in order to make use of wastewater for sanitation purposes in residential homes. The lack of Al 0.3 0.01 0.1 - Ca 513 405 32 93 these dual reticulation systems therefore currently prevents Mg 158 196 88 31 the use of wastewater for any purpose, be it sanitation or K--165otherwise, in the majority of residential homes in South Na 51 47 796 132 Fe 0.3 0.08 0.1 0.32 Africa. However, Dr Jo Burgess from the WRC (26 May 2016) Mn 6 0.01 0.03 0.08 explained in a personal communication that wastewater re- SO4 2027 1464 1647 430 use may be permitted in a commercial building such as a Cl- 18 32 17.8 42 TDS 2917 2212 2435 1120 business or separate ablution facilities as in schools or pH 6.4 7.0 9.2 7.5 camping grounds, provided adequate signage is put up to EC (mS/m) 294 205 372 132 alert users to the fact that wastewater is in use for sanitation L 328   
 VOLUME 119          
South Africa’s options for mine-impacted water re-use: A review and should not be consumed. The wastewater would also required for the majority of processes, especially mineral need to meet various limits for discharge to the sewer system processing and cooling, where some mining operations are in order to prevent scaling of the pipelines and not making use of treated residential waste/sewage in an effort to overburden the treatment facilities. reduce their water footprint. With proper water management The sanitation system would also need to be situated procedures in place, the mining industry would be able to nearby a decant point or MIW source in order to make logical save up to 40% of its fresh water intake. However, it is and economic sense, since transporting ‘dirty’ water large recognized that an acceptable water quality is not the only distances is not economically viable. These limitations consideration when determining the re-use of MIW (treated unfortunately reduce the volume of treated MIW that could be or otherwise). The primary concern is the removal of salts feasibly utilized, thereby making the overall impact of from the system so that there would be no need to use sanitation as an alternative activity for MIW re-use somewhat dilution water on eventual discharge (DWA, 2013; Toledano insignificant under the current circumstances. Going forward, and Roorda, 2014). however, re-use of MIW in sanitation should be revisited Four different categories are defined in the DWAF Volume once legislation is amended and infrastructure improved to 3: Industrial Use (1996) for industrial processes according to allow for this option to be more widely utilized. the purity of water required, and these are summarized in Table VI.      From the DWA (2013) report, it was concluded that only Although the re-use of MIW in industry was not considered Category 4 industrial processes might be capable of using during this comparative study, the option is still available neutralized MIW, and the options for this are limited. Raw and was therefore included in the overall review discussion MIW cannot be considered for any of the industrial use surrounding options for MIW re-use. categories listed in Table VI. Desalinated MIW, if treated to a Significant amounts of water are used (both consumed high enough standard to be considered domestic quality, will and non-consumed) in almost all aspects of mining, although be suitable for Category 3 processes while Categories 1 and 2 the most intensive areas of water use are for cooling of require a higher water quality than domestic (potable) water. drilling machinery, dust suppression, and minerals The extra costs associated with attaining the higher quality processing. However, these are case-specific and can vary water required for Categories 1, 2, and 3 will outweigh the greatly depending on factors such as water chemistry, benefits of supplying users in these categories, in which case climate, water availability, mine management and practices, only select Category 4 users could benefit depending on their geology, ore mineralogy, and the commodity being mined. proximity to an AMD decant point. Generally, lower grade ores require more water for A few case studies of water re-use strategies by various processing. This water is abstracted either directly (from mines are discussed in more detail below. boreholes, dams, streams, or rivers) or indirectly (via a water services provider) from water resources (surface water and      
groundwater). Due to water scarcity becoming more In South Africa, the Witbank coalfields, located in the widespread, governments around the world are becoming eMalahleni Municipality, contain many mines, some of which increasingly aware of the importance of safeguarding water are closed or abandoned and contain significant volumes of resources, which is forcing mining companies to revisit their polluted groundwater which contaminates groundwater and processes with a view of reducing their water footprint. surface water sources. The eMalahleni Municipality is Many mining companies are investing heavily in new struggling to meet the water demand of its burgeoning water infrastructure and management systems to re- population and was coping with this by removing 60% more use/recycle water as well as improving metal recovery than it was licensed to (75 ML/d) from the Witbank Dam by processes and treating effluent prior to discharge. Over 90% abstracting approximately 120 ML/d, with predictions of this of minewater can be re-used if treatments such as reverse increasing to 180 ML/d by 2030 (ICMM, 2012). In 2007, osmosis and microfiltration are employed. An often- Anglo American's AngloCoal division partnered with BHP overlooked aspect of mining is that potable water is often not Billiton and the eMalahleni Local Municipality in an effort to

Table VI &<;=098:=6>93>1892=66=6>;)<;>)<=>==7>.=3:7=.><2298.:70>;9>8=-:8=.>'<;=8>-<4:;*>, (># >94>%+

Category 1 Processes that require a high-quality water with relatively tight to stringent specification of limits for most or all of the relevant water quality constituents. Standard or specialized technology is essential to provide water conforming to the required quality specifications. Consequently, costs of in-house treatment to provide such water are a major consideration in the economics of the process. Category 2 Processes that require water of a quality intermediate between the high quality required for Category 1 processes and domestic water quality (Category 3 processes). Specifications for some water quality constituents are somewhat tighter or more stringent than for domestic water quality. Standard technology is usually sufficient to reach the required water quality criteria. Cost for such additional water treatment begins to be significant in the economics of the process. Category 3 Processes for which domestic water quality is the baseline minimum standard. Water of this quality may be used in the process without further treatment, or minimum treatment using low to standard technology may be necessary to reach the specifications laid down for a desired water quality. Costs for further in-house treatment are not significant in the economics of the process. Category 4 Processes that within certain limitations can use water of more or less any quality without creating any problems. No additional treatment is usually required and there is therefore no further cost.

VOLUME 119          
  
 329 L South Africa’s options for mine-impacted water re-use: A review overcome the problems of AMD pollution and water scarcity this review is that the most suitable option for re-using in the city. They built the flagship eMalahleni Water treated mine-impacted water is in agriculture, namely Reclamation Project (EWRP), mentioned previously in this irrigation of crops (food, forage, or energy crops), which review, which utilizes treatment technologies including currently and unnecessarily makes use of the majority of ultrafiltration and reverse osmosis, at a cost of US$100 South Africa’s high-quality resources or potable water. This million. The EWRP produces potable water from the mine is due to a number of facts. effluent and currently supplies around 12% of eMalahleni’s ® Using MIW for irrigation would make substantial water. Pipelines were constructed from the participating volumes of high-quality or potable water, that was mines (Kleinkopjé, Greenside Colliery, and South Witbank previously reserved for irrigation, available for more Colliery) to a central water storage facility, a water treatment pressing needs (e.g. drinking water). plant, and two reservoirs. Part of the plant is financed by the ® Treating minewater decant to irrigation levels, rather selling of potable water back to the municipality at the than for urban/industrial use, would lead to a 87% and operating costs (Toledano and Roorda, 2014). 78% reduction in capital and running costs, Anglo Platinum’s Modikwa Mine, located in the mineral- respectively. rich Bushveld Complex region in South Africa, originally ® Irrigated farm areas are often located near MIW extracted all its process water from the Olifants River, much sources, limiting the need for collection and distribution to the ire of the Kruger National Park and surrounding of treated MIW for crop production. communities. In an effort to reduce its overall water usage ® The treatment and use of the MIW could operate as a and the subsequent costs involved in transportation and single financial initiative, with income from the MIW- handling, the mine installed two separate dewatering plants, irrigated crops (energy/forage/food crops) funding the including high-rate clarifiers and a filter press, on the north MIW treatment and/or creating jobs and providing and south shafts. The plants recover over 98% of the process food/energy security for the local community. water, and the clarified water is stored for re-use during ® This option would relieve the environmental and health mining operations (Talbot and Talbot, 2012). liabilities of the mines producing the MIW, while      stimulating agriculture in the vicinity. ® This option fits well within the WEF nexus, which is The National Water Act (Act 36 of 1998) also governs the becoming increasingly prominent on the international discharge of domestic and industrial wastewater to a water agenda that continues to focus on collaborative resource through a pipe, canal, sewer, or other conduit. The initiatives on solving the numerous limitations user must register as a water user with the relevant surrounding water, energy, and food provision to a authority. The Act provides a list of wastewater limit values growing global population. that must be adhered to during discharge. These limits are compared, among others, to the limits set by the City of Another important finding of this review includes the Johannesburg (2008) bylaws for discharge to sewers in realization that although guidelines and legislation relating to Table III. water re-use in South Africa exist and are readily accessible, The Act governs the discharge of up to 2 000 m3 of they tend to be contradictory and confusing in many cases, wastewater on any given day provided that the discharged which will have the unintended consequence of negatively water complies with the general wastewater limit values set affecting technology development in the sector. For this out in Table III, does not alter the natural ambient water reason, it is imperative that these ambiguities and temperature of the receiving water resource by more than 2 incongruities within the available guidelines and legislation or 3°C, depending on the water source as listed in the Act, for water re-use be clarified and updated swiftly. and is not a complex industrial wastewater. Similarly to irrigation with wastewater, the Act details (279'4=.05=7;6 precautionary practices in addition to the requirements for The author would like to acknowledge Mintek for permission sampling and monitoring on a regular basis and the reporting to publish this work. of results to the relevant authority. ?=3=8=72=6 &9724-6:976><7.>8=2955=7.<;:976 ANNANDALE, J., BELETSE, Y., DE JAGER, P., JOVANOVIC, N., STEYN, J., BENADE, N., The re-use of treated mine-impacted water is not currently a LORENTZ, S., HODGSON, F., USHER, B., VERMEULEN, D., and AKEN, M. 2007. priority in South Africa. Although the discharge of effluent to Predicting the environmental impact and sustainability of irrigation with water resources should be the option of last resort, it is often coal mine water. Report no. 1149/01/07, Water Research Commission the first choice of many in the mining industry and industry (WRC), South Africa. as a whole due to its simplicity and low cost. Unfortunately, ANNANDALE, J.G., BELETSE, Y.G., STIRZAKER, R.J., BRISTOW, K.L., and AKEN, M.E. the discharge option in many instances requires the use of 2009. Is irrigation with coal-mine water sustainable?. Proceedings of the high-quality water to dilute the treated effluent to within International Mine Water (IMWA) Conference, Pretoria, South Africa. allowable discharge limits for TDS in particular (600 mg/L) International Mine Water Association. pp. 337–342. and salinity in general. In addition, many activities are using ANNANDALE, J.G., JOVANOVIC, N.Z., PRETORIUS, J.J.B., LORENTZ, S.A., RETHMAN, N.F.G., and TANNER, P.D. 2001. Gypsiferous mine water use in irrigation high-quality or potable water unnecessarily (e.g. sanitation, on rehabilitated open-cast mine land: Crop production, soil water and salt crop irrigation). balance. Ecological Engineering, vol. 17, no. 2–3. pp. 153–164. Throughout this report, various options for re-using ANNANDALE, J., JOVANOVICH, N., BENADE, N., and TANNER, P. 1999. Modelling the treated MIW were investigated. The primary conclusion of long-term effect of irrigation with gypsiferous water on soil and water L 330   
 VOLUME 119          
South Africa’s options for mine-impacted water re-use: A review

resources. Agriculture, Ecosystems and the Environment, vol. 76, Munnik, R. AND Pulles, W. 2009. The Implementation of the recently developed no. 109–119. pp.109–119. best practice guidelines for water resource protection in the South African ANNANDALE, J., JOVANOVICH, N., HODGSON, F., USHER, B., AKEN, M., VAN DER mining industry. Proceedings of the International Mine Water (IMWA) WESTHUIZEN, A., BRISTOW, K., and STEYN, J. 2006. Prediction of the Conference, Pretoria, South Africa, 19 - 23 October 2009. International environmental impact and sustainability of large-scale irrigation with Mine Water Association. pp. 22–28.

gypsiferous mine-water on groundwater resources. Water SA, vol. 32, SOUTH AFRICA. 2011. National Water Resources Strategy (NWRS). 1st edn. no. 1. pp. 21–28. SOUTH AFRICA. 2013. National Water Resources Strategy 2 (NWRS2). 1st edn. ANNANDALE, J., JOVANOVICH, N., TANNER, P., BENADE, N., and DU PLESSIS, H. 2002. NEWS24. 2016. State of drought disaster declared in 8 provinces. News24, 9 The sustainability of irrigation with gypsiferous mine-water and June 2016. https://www.news24.com/SouthAfrica/News/state-of-drought- implications for the mining industry in South Africa. Mine Water and the disaster-declared-in-8-provinces-20160609 Environment, vol. 21, no. 2. pp. 81–90. PIMENTEL, D., BERGER, B., FILIBERTO, D., NEWTON, M., WOLFE, B., KARABINAKIS, E., BRUVOLD, W. and WARD, P. 1972. Using reclaimed wastewater: Public opinion. CLARK, S., POON, E., ABBETT, E., and NANDAGOPAL, S. 2004. Water resources: Water Pollution Control Federation, vol. 44, no. 9. pp. 1690–1696. Agricultural and environmental issues. BioScience, vol. 54, no. 10. CITY OF JOHANNESBURG. 2008. Metropolitan Municipality Water Services By-laws, pp. 909–918. published under notice no 835 in Gauteng Provincial Gazette extraordinary no 179 dated 21 May 2004 and as amended by notice 1455 PRETORIUS, J., DOYER, O., ANNANDALE, J., and JOVANOVICH, N. 1999. Managing the in Provincial Gazette no 162 dated 20 June 2008. environmental impact of irrigation with gypsiferous mine water. Agrekon, vol. 38, no. 4. pp. 567–584. DEPARTMENT OF WATER AFFAIRS (DWA). 2013. Feasibility study for a long-term solution to address the acid mine drainage associated with the East, PULLES, W. 2006. Management options for mine water drainage in South Africa. Central and West Rand underground mining basins. Study Report no. 5.3: Proceedings of Mine Water Drainage - South African Perspective, 19-20 Options for use or discharge of water – DWA Report no. P RSA October 2006. Water Institute Southern Africa, Johannesburg: 000/00/16512/3. SOUTH AFRICA. 1989. Environment Conservation Act (Act 73 of 1989) and DEPARTMENT OF WATER AFFAIRS AND FORESTRY (DWAF). 1996. South African amendments. Water Quality Guidelines (2nd Edition). Volumes 1–8. Pretoria. SOUTH AFRICA. 1997. Water Services Act (No. 108 of 1997) and amendments.

DEPARTMENT OF WATER AND SANITATION (DWS). 2017. Media statement: DWS SOUTH AFRICA. 1998a. National Environment Management Act (Act 107 of draft mine water management policy 2017 gazetted for public comment. 1998) and amendments. 14 July 2017. Pretoria. SOUTH AFRICA. 1998b. National Water Act (Act 36 of 1998) and amendments. DU PLESSIS, H. 1983. Using lime treated acid mine water for irrigation. Water SOUTH AFRICA. 2002. Mineral and Petroleum Resources Development Act (Act Science and Technology, vol. 15. pp. 145–154. No. 28 of 2002) and amendments. GREENLEE, L., LAWLERB, D., FREEMAN, B., MARROT, B., and MOULIN, P. 2009. SOUTH AFRICA. 2013. National Water Act revision of general authorisations in Reverse osmosis desalination: Water sources, technology, and today’s terms of section 39 of the NWA (36:1998). Published under Government challenge. Water Research, vol. 43. pp. 2317–2348. Notice 665 in Government Gazette 36820, dated 6 September 2013 GREWAR, T. 2017. How South Africa’s acid mine drainage dilemma can STOAKLEY, A. 2013. Alternative water management in Pretoria, South Africa: An positively impact the water-energy-food nexus. Proceedings of the investigation into public perceptions of water recycling. Proceedings of SAIMM/MMMA Water 2017 Conference, Emperor's Palace, Johannesburg, People and the Planet 2013 Conference: Transforming the Future. James, South Africa. Southern African Institute of Mining and Metallurgy, Johannesburg. P., Hudson, C., Carroll-Bell, S., and Taing, A. (eds). Global Cities Research Institute, RMIT University, Melbourne, Australia . GROBBELAAR, R., USHER, B., CRUYWAGEN, L., DE NECKER, E., and HODGSON, F. 2004. Long term impact of intermine flow from collieries in the Mpumalanga TALBOT & TALBOT. 2012. Water recovery in platinum mines. Inside Mining, 3 area. Report no. 1056/1/04. Water Research Commission (WRC), South December 2012. Africa. TOLEDANO, P. and ROORDA, C. 2014. Leveraging mining investments in water

JOVANOVIC, N.Z., BARNARD, R.O., RETHMAN, N.F.G., and ANNANDALE, J.G. 1998. infrastructure for broad economic development: Models, opportunities and Crops can be irrigated with lime-treated acid mine drainage. Water SA, challenges. Columbia Center on Sustainable Investment, Columbia vol. 24, no. 2. pp. 113–122. University. https://academiccommons.columbia.edu/doi/

JOVANOVICH, N., ANNANDALE, J., VAN DER WESTHUIZEN, A., and STEYN, J. 2002. 10.7916/D8BK1MZC/download Monitoring the soil water and salt balance under irrigation with WEBB, M. 2015. Water 2015: A Review of South Africa’s Water Sector. Creamer gypsiferous mine wastewater. Proceedings of Surface Mining 2002 – Media, Johannesburg. Modern Developments for the New Millennium. Southern African Institute WWAP (United Nations World Water Assessment Programme). 2017. The of Mining and Metallurgy, Johannesburg. United Nations World Water Development Report 2017: Wastewater, The JOVANOVICH, N., ANNANDALE, J., VAN DER WESTHUIZEN, A., and STEYN, J. 2004. Untapped Resource. UNESCO, Paris. Monitoring the effect of irrigation with gypsiferous mine wastewater on VAN DER LAAN, M., VENN FEY, M., VAN DER BURGH, G., DE JAGER, P., ANNANDALE, J., crop production potential as affected by soil water and salt balance. and DU PLESSIS, H. 2014. Feasibility study on the use of irrigation as part Journal of the Souh African Institute of Mining and Metallurgy, vol. 104, of a long-term acid mine water management strategy in the Vaal Basin. no. 2. pp. 73–81. Report no. 2233/1/14, Water Research Commission (WRC), South Africa. INTERNATIONAL COUNCIL ON MINING AND METALS (ICMM). 2012. Environmental VAN ROOYEN, M. 2017. Evolution of the SAVMIN process for treatment of teport: Water management in mining: a selection of case studies. London, TM AMD. Proceedings of the SAIMM/MMMA Water 2017 Conference, UK. Emperor's Palace, Johannesburg, South Africa.10–11 July 2017. Southern KEW, J. 2017. Shoprite wins as consumers seek cheap food to beat inflation. African Institute of Mining and Metallurgy, Johannesburg. Fin24, Bloomberg News, 19 January 2017. VAN ZYL, H.C., MAREE, J.P., VAN NIEKERK, M., VAN TONDER, G.J., and NAIDOO, C. https://www.fin24.com/Companies/Retail/shoprite-wins-as-consumers- seek-cheap-food-to-beat-inflation-20170119 2001. Collection, treatment and re-use of mine water in the Olifants River Catchment. Journal of the South African Institute of Mining and MINING WEEKLY. 2016. Mine land, water should be used for agriculture – Exxaro Metallurgy, vol. 101, no. 1. pp. 41–46. CEO. Mining Weekly, 14 September 2016. http://www.miningweekly.com/article/mine-land-water-should-be-used- ZHUWAKINYU, M. 2016. Water 2016: A Review of South Africa’s Water Sector. for-agriculture-exxaro-ceo-2016-09-14 Creamer Media, Johannesburg.

MINTEK. 2018. Biological sulfate reduction - Value proposition. Mintek ZHUWAKINYU, M. 2017. Water 2017: A Review of South Africa’s Water Sector. Technology Demonstration, Randfontein, South Africa Creamer Media, Johannesburg. N

VOLUME 119          
  
 331 L Embracing the Fourth Industrial Revolution in the Minerals Industry Driving competitiveness through people, processes and technology in a modernised environment

5–6 JUNE 2019 | THE CANVAS RIVERSANDS | FOURWAYS | SOUTH AFRICA

BACKGROUND The SAIMM ran a very successful conference in 2017, which was called ’New Technology and Innovation in Mining’. Now, two years on, it is time to update ourselves on the latest developments, both in the digital world as well as the physical world of the minerals industry. 2XULQGXVWU\VWHHSHGLQJUHDWWUDGLWLRQDQGLQQRYDWLRQQRZ¿QGVLWVHOIIDFLQJQHZFKDOOHQJHVDQGPDQ\RSHUDWLRQV have already embraced these challenges and introduced people-centric technologies that are truly at the cutting edge of innovation. Besides showcasing many exciting innovations and case studies, the conference will be supplemented with a trade show where many of these technologies will be featured.

TOPICS hData mining h$UWL¿FLDOLQWHOOLJHQFH hNew equipment hAutomation hRemote operation hInformation management hCommunications technology h1HZHI¿FLHQWHTXLSPHQW hRenewable energy/energy HI¿FLHQF\ FOR EXHIBITION AND SPONSORSHIP OPPORTUNITIES CONTACT THE CONFERENCE CO-ORDINATORW

*VU[HJ[!@VSHUKH5KPTHUKL࠮*VUMLYLUJL*VVYKPUH[VY࠮;LS!  -H_!  VY   ࠮,THPS!`VSHUKH'ZHPTTJVaH >LIZP[L!O[[W!^^^ZHPTTJVaH NATIONAL & INTERNATIONAL ACTIVITIES 2019 2–3 April 2019 — Global Mining Guidelines Group 2019 31 July–1 August 2019 —Entrepreneurship in the Minerals Wits Club, University of the Witwatersrand, Johannesburg, Industry Conference 2019 South Africa ‘Bringing ideas to life’ Contact: Yolanda Ndimande The Canvas Riversands, Fourways, Johannesburg, South Africa Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 Contact: Camielah Jardine E-mail: [email protected], Website: http://www.saimm.co.za Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 8–10 May 2019 — 22nd International Conference on Paste, E-mail: [email protected], Website: http://www.saimm.co.za Thickened and Filtered Tailings 5–7 August 2019 —The Southern African Institute of Mining The Westin, Cape Town, South Africa and Metallurgy in collaboration with the Zululand Branch is Email: [email protected] organising The Eleventh International Heavy Minerals Website: www.paste2019.co.za Conference 18–25 May 2019 — ALTA 2019 Nickel-Cobalt-Copper ‘Renewed focus on Process and Optimization’ Uranium-REE, Gold-PM, In Situ Recovery, Lithium Processing The Vineyard, Cape Town, South Africa Conference & Exhibition, Perth, Australia Contact: Yolanda Ndimande Contact: Allison Taylor Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 Tel: +61 411 692 442, E-mail: [email protected] E-mail: [email protected], Website: http://www.saimm.co.za Website: https://www.altamet.com.au/conferences/alta-2019/ 18–21 August 2019 — Copper 2019 21–22 May 2019 — Hydrometallurgy Colloquium 2019 Vancouver Convention Centre, Canada ‘Impurity removal in hydrometallurgy’ Contact: Brigitte Farah Glenhove Conference Centre, Melrose Estate, Johannesburg Tel: +1 514-939-2710 (ext. 1329), E-mail: [email protected] Contact: Yolanda Ndimande Website: http://com.metsoc.org Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 19–22 Augusts 2019 — Southern African Coal Processing E-mail: [email protected], Website: http://www.saimm.co.za Society 2019 Conference and Networking Opportunity Graceland Hotel Casino and Country Club, Secunda 22–23 May 2019 — SA Mining Supply Chain Conference and Contact: Johan de Korte Strategy Workshop Tel: 079 872-6403 Bateleur Conference Venue, Nasrec, Johannesburg E-mail: [email protected] Contact: Yolanda Ndimande Website: http://www.sacoalprep.co.za Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 28–29 August 2019 — International Mine Health and Safety E-mail: [email protected], Website: http://www.saimm.co.za Conference 2019 22–23 May 2019 — Mine Planner’s Colloquium 2019 ‘Beyond Zero Harm’ ‘Skills for the future – yours and your mine’s’ Johannesburg Glenhove Conference Centre, Melrose Estate, Johannesburg Contact: Camielah Jardine Contact: Camielah Jardine Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 E-mail: [email protected], Website: http://www.saimm.co.za E-mail: [email protected], Website: http://www.saimm.co.za 28–30 August 2019 — IFAC MMM 2019 Symposium 27–29 May 2019 — The 9th International Conference on Stellenbosch Institute for Advanced Studies Conference Centre, Sustainable Development in the Minerals Industry Stellenbosch, Cape Town, South Africa Park Royal Darling Harbour, Sydney , Australia Email: [email protected] Contact: Georgios Barakos Website: https://www.ifacmmm2019.org/ Tel: +49(0)3731 39 3602, Fax: +49(0)3731 39 2087 4–5 September 2019 — Surface Mining Masterclass 2019 E-mail: [email protected] Birchwood Hotel & OR Tambo Conference Centre, Johannesburg Website: http://sdimi.ausimm.com/ Contact: Camielah Jardine 5–6 June 2019 — New Technology Conference and Trade Show Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 ‘Embracing the Fourth Industrial Revolution in the Minerals E-mail: [email protected], Website: http://www.saimm.co.za Industry’ 16–17 October 2019 —Tailing Storage Conference 2019 Driving competitiveness through people, processes and technology ‘Investing in a Sustainable Future’ in a modernised environment Birchwood Hotel & OR Tambo Conference Centre, Johannesburg The Canvas Riversands, Fourways, Johannesburg, South Africa Contact: Camielah Jardine Contact: Yolanda Ndimande Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 E-mail: [email protected], Website: http://www.saimm.co.za E-mail: [email protected], Website: http://www.saimm.co.za 13–15 November 2019 —XIX International Coal Preparation 24–27 June 2019 — Ninth International Conference on Deep Congress & Expo 2019 and High Stress Mining 2019 New Delhi, India Misty Hills Conference Centre, Muldersdrift, Johannesburg Contact: Coal Preparation Society of India Contact: Camielah Jardine Tel/Fax: +91-11-26136416, 4166 1820 Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 E-mail: cpsidelhi. [email protected], [email protected]. E-mail: [email protected], Website: http://www.saimm.co.za [email protected], [email protected] 4–5 July 2019 — Smart Mining, Smart Environment, Smart Society 20 ‘Implementing change now, for the mine of the future’ 25–29 May 2020 — The 11th International Conference on Accolades Boutique Venue, Midrand Molten Slags, Fluxes and Salts Contact: Yolanda Ndimande The Westin Chosun Seoul Hotel, Seoul, Korea Tel: +27 11 834-1273/7, Fax: +27 11 838-5923/833-8156 Tel: +82-2-565-3571, Email: [email protected] E-mail: [email protected], Website: http://www.saimm.co.za http://www.molten2020.org

VOLUME 119

         
  
 vii L  
RungePincockMinarco Limited Rustenburg Platinum Mines Limited Salene Mining (Pty) Ltd Sandvik Mining and Construction Delmas (Pty) Ltd Sandvik Mining and Construction RSA(Pty) Ltd SANIRE Schauenburg (Pty) Ltd Sebilo Resources (Pty) Ltd SENET (Pty) Ltd Senmin International (Pty) Ltd Smec South Africa Sound Mining Solution (Pty) Ltd SRK Consulting SA (Pty) Ltd Technology Innovation Agency Time Mining and Processing (Pty) Ltd Timrite Pty Ltd Tomra (Pty) Ltd Ukwazi Mining Solutions (Pty) Ltd Umgeni Water Webber Wentzel Weir Minerals Africa Worley Parsons RSA (Pty) Ltd Murray and Roberts Cementation Nalco Africa (Pty) Ltd Ltd Namakwa Sands(Pty) Ltd Ncamiso Trading (Pty) (Pty) Limited New Concept Mining - Zondereinde Northam Platinum Ltd OPTRON (Pty) Ltd PANalytical (Pty) Ltd Paterson & Cooke Consulting Engineers (Pty) Ltd Perkinelmer Polysius A Division Of Thyssenkrupp Industrial Sol Precious Metals Refiners Rand Refinery Limited Redpath Mining (South Africa) (Pty) Ltd Rocbolt Technologies Rosond (Pty) Ltd Royal Bafokeng Platinum Roytec Global (Pty) Ltd          VOLUME 119 Company Affiliates Company Expectra 2004 (Pty) Ltd Exxaro Coal (Pty) Ltd Exxaro Resources Limited Filtaquip (Pty) Ltd Ltd FLSmidth Minerals (Pty) Ltd Fluor Daniel SA (Pty) Franki Africa (Pty) Ltd-JHB Ltd Fraser Alexander (Pty) G H H Mining Machines (Pty) Ltd Geobrugg Southern Africa (Pty) Ltd Glencore Hall Core Drilling (Pty) Ltd Hatch (Pty) Ltd Herrenknecht AG HPE Hydro Power Equipment (Pty) Ltd Immersive Technologies IMS Engineering (Pty) Ltd Ingwenya Mineral Processing Ivanhoe Mines SA Joy Global Inc.(Africa) Kudumane Manganese Resources Leco Africa (Pty) Limited Longyear South Africa (Pty) Ltd Lonmin Plc Lull Storm Trading (Pty) Ltd Maccaferri SA (Pty) Ltd Magnetech (Pty) Ltd MAGOTTEAUX (PTY) LTD Maptek (Pty) Ltd MBE Minerals SA Pty Ltd MCC Contracts (Pty) Ltd MD Mineral Technologies SA (Pty) Ltd MDM Technical Africa (Pty) Ltd Metalock Engineering RSA (Pty)Ltd Metorex Limited Metso Minerals (South Africa) Pty Ltd Minerals Council of South Africa Minerals Operations Executive (Pty) Ltd MineRP Holding (Pty) Ltd Mintek MIP Process Technologies (Pty) Limited Modular Mining Systems Africa (Pty) Ltd MSA Group (Pty) Ltd Multotec (Pty) Ltd   
 The following organizations have been admitted to the Institute as Company Affiliates the Institute as Company been admitted to organizations have The following viii 3M South Africa (Pty) Limited 3M South Africa (Pty) AECOM SA (Pty) Ltd Limited AEL Mining Services Air Liquide (Pty) Ltd Africa (Pty) Ltd Alexander Proudfoot AMEC Foster Wheeler Africa (Pty) Ltd AMIRA International Ltd ANDRITZ Delkor(Pty) Anglo Operations Proprietary Limited Anglogold Ashanti Ltd Arcus Gibb (Pty) Ltd ASPASA Atlas Copco Holdings South Africa (Pty) Limited Aurecon South Africa (Pty) Ltd Aveng Engineering Aveng Mining Shafts and Underground Axis House Pty Ltd Bafokeng Rasimone Platinum Mine Barloworld Equipment -Mining BASF Holdings SA (Pty) Ltd BCL Limited Becker Mining (Pty) Ltd BedRock Mining Support Pty Ltd BHP Billiton Energy Coal SA Ltd Blue Cube Systems (Pty) Ltd Bluhm Burton Engineering Pty Ltd Bouygues Travaux Publics CDM Group CGG Services SA Coalmin Process Technologies CC Concor Opencast Mining Concor Technicrete Council for Geoscience Library CRONIMET Mining Processing SA Pty Ltd CSIR Natural Resources and the Environment (NRE) Data Mine SA Digby Wells and Associates DRA Mineral Projects (Pty) Ltd DTP Mining - Bouygues Construction Duraset Elbroc Mining Products (Pty) Ltd eThekwini Municipality L Size It matters! Our high-level academic staff offers specialist higher degrees and produces the largest number of graduates in the English-speaking world. Substance

Africa, Africa and the World. The School is student-centred

bring the environment to our students. Style Our multi-disciplinary and specialist postgraduate programme leads to sustained research output, fascilitating regular step changes in industry.

School of Mining Engineering University of the Witwatersrand, Johannesburg

www.wits.ac.za/miningeng/ The Journal of the Southern African Institute of Mining and Metallurgy SPECIAL 125TH ANNIVERSARY ISSUE

A SPECIAL COMMEMORATIVE PUBLICATION The SAIMM will be celebrating its 125th Anniversary in July 2019. This is an occasion worthy of the attention of the minerals industry in particular and of South Africa as a whole. This souvenir issue will showcase the SAIMM and the mineral industry’s challenges and achievements since 1994. It will be distributed to members and company affiliates of the SAIMM, Government Departments, kindred organisations locally and internationally, as well as to delegates attending the SAIMM conferences in 2019. SAIMM Affiliates, key industry players, equipment suppliers and major companies in mining and metallurgy can equally demonstrate their support of this commemorative edition with congratulatory messages and profiles of their own developments and successes over the last 25 years. Organisations wanting to align their message with a particular Past President, or next to an identified topic, will need to secure this positioning urgently.

To advertise in this Special Publication contact: Barbara Spence, Avenue Advertising, Telephone (011) 463-7940, E-mail: [email protected]