Evaluating a small deposit next to an economically viable gold mine in West Africa from the points of view of the mining company,the government and the local community

This paper addresses the question of evaluating how much the different stakeholders stand to gain from a mining project. By carefully analysing the breakdown of the cash-flows generated, we were able to estimate the amounts received by the local community and by the national community (outside the mining area), the taxes and royalties received by the government and the profits made by the mining company. A real options framework was used to take account of the inherent uncertainty on the commodity price and the reserves, and the operating flexibility (that is, the possibility for the company to stop mining if the commodity price drops and/or the reserves prove to be lower than that had been envisaged). A synthetic case-study of a gold mine in West Africa was used to illustrate how this procedure could be applied in practice. By using the real option framework we were able to envisage scenarios for developing an extension to a deposit as a function of future values of the commodity price. The procedure proposed should provide governments and NGOs with more objective data for making policy decisions.     

Determination of the effect of operating cost uncertainty on mining project evaluation

Mining projects are complex businesses that demand constant risk assessment. This is because several kinds of uncertainties influence the value of a mine project, typically. These uncertainties may be classified as exploration uncertainties, economic uncertainties and engineering uncertainties. The evaluation of a mine project under these uncertainties is a complicated job, which may lead to making a wrong decision by managers and stockholders. Therefore, at first, the engineers must recognize the mining uncertainties before carrying out the project evaluation. The economic uncertainties are the most important factors, which may affect the project evaluation. Among the mentioned uncertainties, the operating cost uncertainty is an important and effective factor, which is ignored to a certain extent.     

A Technicoeconomic Approach for the Selection of a Site Remediation Strategy—Part A: Theory

A technicoeconomic model is developed to select an optimal strategy for the remediation of a contaminated site and to determine the value of this remediation strategy. The model is an extension of actual cost–benefit analysis, with consideration of “irreversible” remediation technology choices, technology effectiveness, and uncertainty on the site's level of contamination. The model considers the possibility of reducing uncertainty by both acquiring more and better information on the level of contamination and by offering the decision-maker the opportunity to reevaluate his decision and switch to a more appropriate technology. It is believed that this model will help decision-makers in the selection of a remediation strategy by presenting all potentially feasible strategies, and how uncertainty on the site's level of contamination affects these strategies.     

Valuing uncertain asset cash flows when there are no options: A real options approach

The real option valuation method is often presented as an alternative to the traditional discounted cash flow (DCF) approach because it is able to quantify the additional asset value arising from flexible asset management. However, these two valuation methods differ on a more fundamental level: their approach to determining the effects of cash flow uncertainty on asset value. Real option valuation adjusts for risk within the cash flow components while the DCF method discounts for risk at the aggregate net cash flow. This seemingly small difference allows the real option method to differentiate assets according to their unique risk characteristics, while the conventional DCF approach cannot.This paper presents an overview of the real options and conventional DCF frameworks for valuing uncertain cash flows. To emphasize the approaches' different treatment of risk we assume an absence of managerial flexibility. Using simple algebra, this paper demonstrates that the traditional DCF method fails to adequately discount net cash flow risk, no matter what discount rate is used. Finally, in a stylized mining example we show that DCF rules would lead a developer to forego $24.5 million in value creation, at a profitability index of 1.49, by making a poor investment decision.     

Risk-based evaluation of wastewater treatment projects: A case study in Niasar city,Iran

For sustainable wastewater management, it is essential to consider social, environmental, geological and technical features as well as economic feature in the decision-making process. A limitation of many of the earlier works on wastewater management is that they take into account only financial criteria to make a decision for a given problem. Moreover, the decision-makers’ (DMs) attitude to risk, or optimism degree, when faced with uncertainty is not considered. In this paper, we study the application of risk-based multi-attribute decision-making (RB-MADM) methods to achieve sustainable wastewater management. Consideration of uncertainty, value tradeoffs, and different risk attitudes of decision makers are the important features of the developed methodology. A case study on the Iranian city of Niasar is presented to illustrate how this methodology can be applied to select the most preferred alternative for wastewater management among a set of options. The most preferred option is selected with respect to nine attributes under different optimism/pessimism degrees, using six different MADM methods. The results show that the ranking of options is sensitive to the optimism degree of the DMs. The proposed approach may help policy makers to achieve sustainable wastewater management.     

Theory of storage,inventory and volatility in the LME base metals

The theory of storage, as related to commodities, makes two predictions involving the quantity of the commodity held in inventory. When inventory is low (i.e. a situation of scarcity), spot prices will exceed futures prices, and spot price volatility will exceed futures price volatility. Conversely, during periods of no scarcity, both spot prices and spot price volatility will remain relatively subdued. We test these predictions for the six base metals traded on the London Metal Exchange (aluminium, copper, lead, nickel, tin and zinc), and find strong validation for the theory. Including Chinese inventories reported by the Shanghai Futures Exchange strengthens the relationship further. We also introduce the concepts of excess volatility, inventory-implied spot price and inventory-implied spot volatility and illustrate some applications.     

Adrift on a sea of platitudes: Why we will not resolve the greenhouse issue

The issue of greenhouse warming has received a great deal of attention in recent years. It has become the object of much scientific scrutiny, media coverage, and political rhetoric. What is our current state of knowledge regarding this phenomenon? What are the possible options for preventing or slowing its advance, or for living with its consequences? What obstructs our taking actions to deal with this issue? These are the questions addressed here. Beginning with a brief overview of our current knowledge, I then examine potential policy options, and finally assess the likelihood of constructive actions. The conclusion reached is that we will probably not deal with this issue, not because we lack a sufficient understanding of the phenomenon, its consequences and workable solutions, but because we lack the philosophical, ethical, and political will to do so. As a result we are likely to continue to drift across a sea of platitudes.     

Optimization of regional economic and environmental systems under fuzzy and random uncertainties

Environmental problems associated with socio-economic development have been growing concerns faced by many regional and/or national authorities. However, effective planning may encounter difficulties since uncertainties existing in a number of impact factors and pollution-related processes are often not well acknowledged and reflected. This study advances an interval-fuzzy chance-constrained programming (IFCP) method for planning regional economic and environmental systems, where uncertainties presented as intervals, fuzzy sets and probability distributions can be tackled. The developed method is applied to a real-world case for economic and environmental planning in the New Binhai District in the Municipality of Tianjin, China. Two scenarios based on multiple environmental constraints are examined. The results can help identify desired alternatives for planning regional development strategies, where compromised schemes are provided under an integrated consideration of economic efficiency and environmental protection under multiple uncertainties.     

Pathology and failure in the design and implementation of adaptive management

The conceptual underpinnings for adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex ecological systems as a result non-linear interactions among components and emergence, yet management decisions must still be made. The strength of adaptive management is in the recognition and confrontation of such uncertainty. Rather than ignore uncertainty, or use it to preclude management actions, adaptive management can foster resilience and flexibility to cope with an uncertain future, and develop safe to fail management approaches that acknowledge inevitable changes and surprises. Since its initial introduction, adaptive management has been hailed as a solution to endless trial and error approaches to complex natural resource management challenges. However, its implementation has failed more often than not. It does not produce easy answers, and it is appropriate in only a subset of natural resource management problems. Clearly adaptive management has great potential when applied appropriately. Just as clearly adaptive management has seemingly failed to live up to its high expectations. Why? We outline nine pathologies and challenges that can lead to failure in adaptive management programs. We focus on general sources of failures in adaptive management, so that others can avoid these pitfalls in the future. Adaptive management can be a powerful and beneficial tool when applied correctly to appropriate management problems; the challenge is to keep the concept of adaptive management from being hijacked for inappropriate use.     

Discovering meaningful information from large amounts of environment and health data to reduce uncertainties in formulating environmental policies

This study uses knowledge discovery concepts to analyze large amounts of data step by step for the purpose of assisting in the formulation of environmental policy. We performed data cleansing and extracting from existing nation-wide databases, and used regression and classification techniques to analyze the data. The current water hardness in Kaohsiung, Taiwan contributes to the prevention of cardiovascular disease (CVD) but exacerbates the development of renal stones (RS). However, to focus on water hardness alone to control RS would not be cost effective at all, because the existing database parameters do not adequately allow for a clear understanding of RS. Analysis of huge amounts of data can most often turn up the most reliable and convincing results and the use of existing databases can be cost-effective.     

A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

Market imperfections in recycling markets: conceptual issues and empirical study of price volatility in plastics

The effectiveness of recycling depends upon efficient functioning of secondary material markets. This paper focus on the role that price volatility can play in slowing investment and market development. However, a statistical analysis of the relative volatility of secondary and primary material prices does not confirm the widely-held belief that relative price volatility is higher in secondary than in primary materials, at least at national levels.An econometric estimation of the determinants of plastic recovery volumes in Seattle contributes to the literature in four ways: the use of monthly (as opposed to annual) data; the use of local (as opposed to national) data; the use of an explanatory variable to reflect price volatility; and, the focus on plastics, which have not been examined previously. Some tentative conclusions can be made: the results generally support the principal hypothesis that price volatility has a negative effect on recovery of secondary materials; in addition, and consistent with previous studies, price elasticities are low and insignificant; and finally, policy factors are clearly important. The concluding section treats the economic and policy implications of market inefficiency in secondary material markets.     

Impact of crude oil price volatility on economic activities: An empirical investigation in the Thai economy

This paper empirically examines the impact of oil price volatility on key macroeconomic indicators of Thailand. Following Andersen et al. [2004. Analytical evaluation of volatility forecasts. International Economic Review 45(4), 1079–1110], quarterly oil price volatility is measured by using the realized volatility (RV). The impact of the oil price volatility is investigated using the vector auto-regression (VAR) system. The Granger causality test, impulse response functions, and variance decomposition show that oil price volatility has significant impact on macroeconomic indicators, such as unemployment and investment, over the period from 1993Q1 to 2006Q4. Perron's [1997. Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics 80(2), 355–385] test identifies structural breaks in all the concerned variables during the time of the Asian Financial Crisis (1997–1998). A VAR for the post-crisis period shows that the impact of oil price volatility is transmitted to budget deficit. The floating exchange rate regime introduced after the crisis may be the key contributor to this new channel of impact.     

State ownership and the price sensitivity of supply: The case of the copper mining industry

The paper attempts to verify the claim that output in state owned copper mining industries is less sensitive to price changes than in private ones. This is done by comparing the price sensitivity of copper supply in countries with state and privately owned copper industries and by testing whether nationalization leads to changes in the supply behaviour of copper mining industries. It is found that low supply elasticities and nationalizations are both the result of a country's high dependence on copper and are not themselves causally related.     

On modelling the global copper mining rates,market supply,copper price and the end of copper reserves

The world supply and turnover of copper was modelled using simple empirical estimates and a COPPER systems dynamics model developed for this study. The model combines mining, trade markets, price mechanisms, population dynamics, use in society and waste as well as recycling, into a whole world system. The degree of sustainability and resource time horizon was estimated using four different methods including (1) burn-off rates, (2) peak discovery early warning, (3) Hubbert's production model, and (4) COPPER, a system dynamics model. The ultimately recoverable reserves (URR) have been estimated using different sources that converge around 2800 million tonne, where about 800 million tonne have already been mined, and 2000 million tonne remain. The different methods independently suggest peak copper mine production in the near future. The model was run for a longer period to cover all systems dynamics and delays. The peak production estimates are in a narrow window in time, from 2031 to 2042, with the best model estimate in 2034, or 21 years from the date of writing. In a longer perspective, taking into account price and recycling, the supply of copper to society is estimated to run out sometime after 2400. The outputs from all models put focus on the importance of copper recycling so that society can become more sustainable with respect to copper supply.     

Assessing Uncertainty in Estimates of Nitrogen Loading to Estuaries for Research, Planning, and Risk Assessment

Parametric (propagation for normal error estimates) and nonparametric methods (bootstrap and enumeration of combinations) to assess the uncertainty in calculated rates of nitrogen loading were compared, based on the propagation of uncertainty observed in the variables used in the calculation. In addition, since such calculations are often based on literature surveys rather than random replicate measurements for the site in question, error propagation was also compared using the uncertainty of the sampled population (e.g., standard deviation) as well as the uncertainty of the mean (e.g., standard error of the mean). Calculations for the predicted nitrogen loading to a shallow estuary (Waquoit Bay, MA) were used as an example. The previously estimated mean loading from the watershed (5,400 ha) to Waquoit Bay (600 ha) was 23,000 kg N yr⁻¹. The mode of a nonparametric estimate of the probability distribution differed dramatically, equaling only 70% of this mean. Repeated observations were available for only 8 of the 16 variables used in our calculation. We estimated uncertainty in model predictions by treating these as sample replicates. Parametric and nonparametric estimates of the standard error of the mean loading rate were 12–14%. However, since the available data include site-to-site variability, as is often the case, standard error may be an inappropriate measure of confidence. The standard deviations were around 38% of the loading rate. Further, 95% confidence intervals differed between the nonparametric and parametric methods, with those of the nonparametric method arranged asymmetrically around the predicted loading rate. The disparity in magnitude and symmetry of calculated confidence limits argue for careful consideration of the nature of the uncertainty of variables used in chained calculations. This analysis also suggests that a nonparametric method of calculating loading rates using most frequently observed values for variables used in loading calculations may be more appropriate than using mean values. These findings reinforce the importance of including assessment of uncertainty when evaluating nutrient loading rates in research and planning. Risk assessment, which may need to consider relative probability of extreme events in worst-case scenarios, will be in serious error using normal estimates, or even the nonparametric bootstrap. A method such as our enumeration of combinations produces a more reliable distribution of risk.     

Modeling Long-Term Risk to Environmental and Human Systems at the Hanford Nuclear Reservation: Scope and Findings from the Initial Model

The Groundwater Protection Project at the US Department of Energy Hanford Site in Washington State is currently developing the means to assess the cumulative impact to human and ecological health and the regional economy and cultures from radioactive and chemical waste that will remain at the Hanford Site after the site closes. This integrated system is known as the System Assessment Capability (SAC). The SAC Risk/Impact Module discussed in the article uses media- and time-specific concentrations of contaminants estimated by the transport models of the integrated system to project potential impacts on the ecology of the Columbia River corridor, the health of persons who might live in or use the corridor or the upland Hanford environment, the local economy, and cultural resources. Preliminary Monte Carlo realizations from the SAC modeling system demonstrate the feasibility of large-scale uncertainty analysis of the complex relationships in the environmental transport of contaminants on the one hand and ecological, human, cultural, and economic risk on the other. Initial impact results show very small long-term risks for the 10 radionuclides and chemicals evaluated. The analysis also helps determine science priorities to reduce uncertainty and suggests what actions matter to reduce risks.     

Strategic Environmental Assessment of Plans and Programs: A Methodology for Estimating Effects on Biodiversity

We developed a methodology for biodiversity evaluations within the process of Strategic Environmental Assessment and we applied it to the estimation of the effect of two Regional Plans of Development on all bird species inhabiting the Castilla y León region (northwestern Spain). The methodology is based on the evaluation of the effects of main development actions on the habitat requirements of species. From these evaluations, and from data on the current distribution and population size (number of individuals) of each species, we estimated the most likely pattern of distribution and population size after the full implementation of the plans for each species. The impacts of the plans were quantified as the differences between the pre- and postproject patterns after codifying them to compensate for differences in the quality of the information available among species. Overall, we conclude that the proposed methodology fulfills the requirements for its use within the SEA process as it allows for the assessment of cumulative impacts on every species, highlighting the development directions and the habitat types with major impacts, and ascertaining whether impacts affect species with either low or high conservation and/or economic value. Generalization of the proposed methodology to other regions or species will require wildlife-habitat models adequate for SEA analyses, so that we also propose guidelines for the development and validation of these models.     

Estimating Current and Future Groundwater Resources of the Maldives

The water resources of the atolls of the Republic of Maldives are under continual threat from climatic and anthropogenic stresses, including land surface pollution, increasing population, drought, and sea‐level rise (SLR). These threats are particularly acute for groundwater resources due to the small land surface area and low elevation of each island. In this study, the groundwater resources, in terms of freshwater lens thickness, total volume of fresh groundwater, and safe yield are estimated for the 52 most populous islands of the Maldives for current conditions and for the year 2030, with the latter accounting for projected SLR and associated shoreline recession. An algebraic model, designed in previous studies to estimate the lens thickness of atoll islands, is expanded in this study to also estimate volume of groundwater. Results indicate that average current lens thickness, groundwater volume, and per capita safe yield are approximately 4.6 m, 1,300 million liters, and 300 l/day, and that these values will decrease by approximately 10, 11, and 34%, respectively, by the year 2030. Based on results, it is demonstrated that groundwater, in terms of quantity, is a viable source of water for the islands of the Maldives both now and in coming decades, particularly for islands with large surface area and low population. Study results can provide water resource managers and government officials with valuable data for consideration in water security measures.     

Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply

While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to uncertainty than revegetation with a commercial pine plantation.