Twelve factors influencing sustainable recycling of municipal solid waste in developing countries

Sustainable management of solid waste is a global concern, as exemplified by the United Nations Millennium Development Goals (MDG) that 191 member states support. The seventh MDG indirectly advocates for municipal solid waste management (MSWM) by aiming to ensure environmental sustainability into countries’ policies and programs and reverse negative environmental impact. Proper MSWM will likely result in relieving poverty, reducing child mortality, improving maternal health, and preventing disease, which are MDG goals one, four, five, and six, respectively (UNMDG, 2005). Solid waste production is increasing worldwide as the global society strives to obtain a decent quality of life. Several means exist in which the amount of solid waste going to a landfill can be reduced, such as incineration with energy production, composting of organic wastes, and material recovery through recycling, which are all considered sustainable methods by which to manage MSW. In the developing world, composting is already a widely-accepted method to reduce waste fated for the landfill, and incineration for energy recovery can be a costly capital investment for most communities. Therefore, this research focuses on recycling as a solution to the municipal solid waste production problem while considering the three dimensions of sustainability environment, society, and economy. First, twenty-three developing country case studies were quantitatively and qualitatively examined for aspects of municipal solid waste management. The municipal solid waste (MSW) generation and recovery rates, as well as the composition were compiled and assessed. The average MSW generation rate was 0.77 kg/person/day, with recovery rates varying from 5 – 40%. The waste streams of nineteen of these case studies consisted of 0 – 70% recyclable material and 17 – 80% organic material. All twenty-three case studies were analyzed qualitatively by identifying any barriers or incentives to recycling, which justified the creation of twelve factors influencing sustainable municipal solid waste management (MSWM) in developing countries. The presence of regulations, enforcement of laws, and use of incentive schemes constitutes the first factor, Government Policy. Cost of MSWM operations, the budget allocated to MSWM by local to national governments, as well as the stability and reliability of funds comprise the Government Finances factor influencing recycling in the third world. Many case studies indicated that understanding features of a waste stream such as the generation and recovery rates and composition is the first measure in determining proper management solutions, which forms the third factor Waste Characterization. The presence and efficiency of waste collection and segregation by scavengers, municipalities, or private contractors was commonly addressed by the case studies, which justified Waste Collection and Segregation as the fourth factor. Having knowledge of MSWM and an understanding of the linkages between human behavior, waste handling, and health/sanitation/environment comprise the Household Education factor. Individuals’ income influencing waste handling behavior (e.g., reuse, recycling, and illegal dumping), presence of waste collection/disposal fees, and willingness to pay by residents were seen as one of the biggest incentives to recycling, which justified them being combined into the Household Economics factor. The MSWM Administration factor was formed following several references to the presence and effectiveness of private and/or public management of waste through collection, recovery, and disposal influencing recycling activity. Although the MSWM Personnel Education factor was only recognized by six of the twenty-two case studies, the lack of trained laborers and skilled professionals in MSWM positions was a barrier to sustainable MSWM in every case but one. The presence and effectiveness of a comprehensive, integrative, long-term MSWM strategy was highly encouraged by every case study that addressed the tenth factor, MSWM Plan. Although seemingly a subset of private MSWM administration, the existence and profitability of market systems relying on recycled-material throughput, involvement of small businesses, middlemen, and large industries/exporters is deserving of the factor Local Recycled-Material Market. Availability and effective use of technology and/or human workforce and the safety considerations of each were recurrent barriers and incentives to recycling to warrant the Technological and Human Resources factor. The Land Availability factor takes into consideration land attributes such as terrain, ownership, and development which can often times dictate MSWM. Understanding the relationships among the twelve factors influencing recycling in developing countries, made apparent the collaborative nature required of sustainable MSWM. Factors requiring the greatest collaborative inputs include waste collection and segregation, MSWM plan, and local recycled-material market. Aligning each factor to the societal, environmental, and economic dimensions of sustainability revealed the motives behind the institutions contributing to each factor. A correlation between stakeholder involvement and sustainability existed, as supported by the fact that the only three factors driven by all three dimensions of sustainability were the same three that required the greatest collaboration with other factors. With increasing urbanization, advocating for improved health for all through the MDG, and changing consumption patterns resulting in increasing and more complex waste streams, the utilization of the collaboration web offered by this research is ever needed in the developing world. Through its use, the institutions associated with each of the twelve factors can achieve a better understanding of the collaboration necessary and beneficial for more sustainable MSWM.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.