The intensity of use of a mineral is traditionally defined as the consumption (production plus net imports) of the mineral divided by gross national product. It has been proposed that this ratio of raw material input to gross economic output is a predictable function of per capita income and that the relationship is based on economic theory. Though the theory has never been clearly defined, the intensity of use method has been used to make long term forecasts. This dissertation formulates a theoretical model of the consumption of minerals and the resulting intensity of use which is used to test the validity of the traditional intensity of use measure and its forecasting ability. Previous justifications of the intensity of use hypothesis state that changes in technical efficiency, substitution rates among inputs, and demands are explained by per capita income, which, as it grows, produces a regular intensity of use pattern. The model developed in this research shows that the life of the goods in use, foreign trade of raw and final goods, prices, consumer preferences, technical innovations, as well as the above factors fully explain economic use, which is not simply a function of per capita income. The complete model is used to restate the traditional theory of intensity of use and to examine the sensitivity of traditional measures to changes in the explanatory variables which are commonly omitted. The full model demonstrates the parameters that must be examined when making a long term forecast. Regular intensity of use patterns are observed for many minerals in many nations. Setting aside the theoretical questions, the intensity of use method is often used to make long term projections based on these trends in intensity of use as well as the trends in population and gross national product. This dissertation examines the forecasting ability of the traditional intensity of use method and finds that it is not necessarily an improvement over naive consumption time trend forecasts. Furthermore, it is unstable for very long term projections.

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Thesis (M.Eng.(Mining Engineering))--University of Pretoria, 2009. / Abstract in English. Includes bibliographical references.

M.Com. (Business Management) / All valuations of mineral assets in South Africa are guided by the South African Mineral Resources Committee (SAMREC) and South African Mineral Valuation (SAMVAL) codes. They have also been adopted by the Johannesburg Securities Exchange (JSE) in order to protect shareholders. Different capital budgeting methods are used for mineral assets valuation in South Africa. These are the net present value (NPV), internal rate of return (IRR), payback period, cost, market and real options methods. It is not known which capital budgeting method is most often used for mining property valuations, as South African mining companies and associations are not required to share their capital budgeting processes with the public. In addition, the SAMVAL code does not recommend the use of the real options method and no reasons are provided. The study was aimed at establishing the capital budgeting method most often used for mining property valuations in South Africa, as well as the reasons why the real options method is not recommended by the SAMVAL code. A judgement sample of expert valuators was utilised in the study and interviews were carried out using open ended questions. The research revealed that NPV is the capital budgeting method most often used for mining property valuations followed by the IRR method. Outside South Africa, Bhappu & Guzman (1995) found that these preferences were reversed. Since the IRR method represents a notional rather than an actual return on investment, South African valuators were found to be more rational than their overseas counterparts in the application of these discounted cash flow (DCF) methods. The findings also revealed that the cost, market and payback methods were less preferred to the NPV and IRR methods. The reasons given were all consistent with the theory. The cost method was avoided because it uses historical cost data which is not usually applicable, the market method was limited due to the lack of available information on truly comparable projects and the payback method was shunned for undervaluing mining properties by ignoring cash flows that arrive after the payback period. The respondents also indicated that the real options method is the least used. The method (which includes the value of embedded optionality) was regarded as complex and not widely understood and this was also thought to explain why it is not recommended by the SAMVAL code. This finding indicated that in South Africa the embedded optionality in mining projects may not be taken into account and as a result, opportunities for the exploitation of its mineral assets could be missed.

Thesis is submitted in partial fulfilment of the requirements for the degree of Master of Science in Engineering to the Faculty of Engineering and the Built Environment, School of Mining Engineering, University of the Witwatersrand, Johannesburg, 2018 / Iron ore prices rallied from USD15/DMT during 2004 and experienced a significant drop from USD 140/DMT during the latter part of 2013. The purpose of the work is to identify the key drivers impacting on iron ore demand globally. Understanding the supply and demand balance and impact on price, is key to informed decision making relating to the iron ore business. The research methodology applied largely followed a quantitative methodology. Key drivers of iron ore demand, supply and demand balance and the impact on price were evaluated. The method applied consisted of gathering data from secondary sources and a detailed quantitative analysis on GDP, stage of economic development, steel consumption, supply and demand of iron ore and intensity of use. Approximately 98% of all iron ore is used for steel making and on that basis steel consumption is the primary driver for iron ore demand. Steel is mostly used for construction and manufacturing and is driven by emerging economies of which China is currently the largest contributor. Global GDP growth correlates well with steel consumption and is primarily driven by emerging economies. Urbanisation was and still is a key driver for construction in China, to provide housing and related infrastructure for transportation and services. Scrap steel recycling, currently at 15%, affect the demand for new steel and indirectly iron ore. Iron ore is abundant and can easily meet the demand. The significant growth from 2004/5 to 2013/14 and the unprecedented demand for steel resulted in elevated iron ore prices, introducing high cost iron ore, predominantly from Chinese State owned companies. From late 2013, the iron ore prices reduced significantly. This was mainly due to the steel consumption in China slowing down; delivering of large scale, low cost iron ore projects in Australia and Brazil and a significant reduction in oil prices. The key drivers impacting iron ore demand is: global GDP growth, industrialisation and urbanisation of emerging economies, recycling of steel, supply and demand balance of iron ore, the cost of production and the price of global iron ore. For the medium term outlook, the iron ore market will be structurally over-supplied and, as a result, the demand could be met at significantly lower cost of production levels than that seen during the period leading up to the price collapse in 2013. This is primarily because of the increase in low-cost supply from the major suppliers displacing higher cost producers. China will continue to grow and drive the global demand for steel and iron ore during the medium term albeit at much lower rates when compared to the last decade. The demand for steel will increase until 2020 according to various analyst views. The iron ore prices are expected to trade between USD50/DMT to USD70/DMT from 2016 to 2020 mainly because of the over-supply situation and demand being mostly met by large scale, low-cost producers. The decision around the continuation of high cost, state owned Chinese iron ore producers, new large-scale low cost production and the oil price will impact on the price outlook. / MT2018

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The surface stoichiometry of five samples, two semiconductors (GaAs and InP) and three minerals (galena (PbS), pyrite (FeS2) and sphalerite (Zn, Fe) S), has been determined by a range of surface analysis techniques: ToF-SIMS, XPS, RBS, NRA and PIXE. The strengths and limitations of the five surface and interface analytical techniques have also been assessed by challenging each technique with the above mentioned samples. As a result, a strategy tree for the quantitative surface analysis of real mixed mineral systems has been developed for novice investigators as an operational guide. ToF-SIMS is a technique able to detect species from hydrogen to very complex organic modules with very high sensitivity. SIMS is generally not a quantitative technique due primarily to the matrix effect, i.e. the strong dependence of secondary ion yields on the chemical composition of the sample. However, for well defined systema, quantitative analyses are possible if suitable calibration standards are accessible. / In this study, a preliminary RSF (Relative Sensitivity Factor) study has been conducted on five samples to give RSFs of the major constituents of each sample. XPS is broadly recognised as a surface analysis technique with the ability of determining the elemental composition near the surface region as well as chemical information, but the depth resolution of XPS is poor. RBS is capable of revealing the concentration depth profiles within the sample without destroying the solid surface. RBS is also considered a good quantitative analytical technique. The main disadvantages of RBS are the poor surface sensitivity and the low efficiency in detecting light elements in a high Z substrate. PIXE is a non-destructive multi-element analytical technique based on X-ray spectroscopy and good at detecting medium Z elements (Z~/= 20~30). By using L X-ray lines instead of K X-ray lines, PIXE is also able to detect high Z (>40) elements. However, due to the very low detection efficiency of Si (Li) detectors (typical PIXE detectors) at low X-ray energies, elements lighter than sodium can not be analysed. Another major shortcoming of PIXE is the lack of depth information. Various surface textures of pyrite have been studied in order to investigate the influence of surface conditions on the quantitative results for the individual techniques utilised in this study and the activation induced chemical alteration on pyrite surfaces has also been studied in detail. By comparing the results from these surface analysis techniques, a good understanding of the elemental composition of the mixed minerals has been achieved. / Thesis (PhD)--University of South Australia, 2004.

Thesis (M.S.)--Ohio University, November, 1987. / Title from PDF t.p.