The effect of recycling price uncertainty on municipal waste management choices

This paper analyzes the effect of price uncertainty and irreversible investment on the decision of municipalities to switch from landfill waste disposal to recycling by developing a model to predict recycling adoption behavior and applying it to empirical data. It is shown that uncertainty regarding the price of recycled materials may induce a risk neutral municipality to prefer landfill disposal, even when recycling is less expensive. A model is developed to describe the switching process and estimate its parameters using empirical data from 79 municipalities in Israel. The model is then used to predict municipalities' recycling adoption decisions under various assumptions regarding price uncertainty. The results support the hypothesis that price uncertainty is a major obstacle for recycling. Finally, several options for price stabilization are sketched and it is argued that these policies may be effective in establishing viable recycling markets.     

Violation analysis for solid waste management systems: an interval fuzzy programming approach

This paper introduces a violation analysis approach for the planning of regional solid waste management systems under uncertainty, based on an interval-parameter fuzzy integer programming (IPFIP) model. In this approach, several given levels of tolerable violation for system constraints are permitted. This is realized through a relaxation of the critical constraints using violation variables, such that the model's decision space can be expanded. Thus, solutions from the violation analysis will not necessarily satisfy all of the model's original constraints. Application of the developed methodology to the planning of a waste management system indicates that reasonable solutions can be generated through this approach. Considerable information regarding decisions of facility expansion and waste flow allocation within the waste management system were generated. The modeling results help to generate a number of decision alternatives under various system conditions, allowing for more in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability.     

LCA: A decision support tool for environmental assessment of MSW management systems

Life cycle assessment (LCA) can be successfully applied to municipal solid waste (MSW) management systems to identify the overall environmental burdens and to assess the potential environmental impacts. In this study, two methods used for current MSW management in Phuket, a province of Thailand, landfilling (without energy recovery) and incineration (with energy recovery), are compared from both energy consumption and greenhouse gas emission points of view. The comparisons are based on a direct activity consideration and also a life cycle perspective. In both cases as well as for both parameters considered, incineration was found to be superior to landfilling. However, the performance of incineration was much better when a life cycle perspective was used. Also, landfilling reversed to be superior to incineration when methane recovery and electricity production were introduced. This study reveals that a complete picture of the environmental performance of MSW management systems is provided by using a life cycle perspective.     

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.     

Euro-trash: searching Europe for a more sustainable approach to waste management

How an economically affordable, environmentally effective and socially acceptable municipal solid waste management system can be developed is currently unclear. Considerable research has been carried out on the practical aspects of municipal waste management (i.e. transport, treatment and disposal) and how citizens feel about source separation, recycling, incineration and landfill but the perspective of the waste manager within the context of long term planning is often ignored. In this study, waste managers from 11 different leading-edge European municipal solid waste programs in nine different countries were interviewed. The economic, social, political, environmental, legal and technical factors of their specific programs were explored and analyzed. The transition of municipal solid waste management to urban resources management was observed and key ‘system drivers’ for more sustainable waste management practices were identified. Programs visited were: Brescia (I), Copenhagen (DK), Hampshire (UK), Helsinki (FI), Lahn-Dill-Kreis (D), Malmö (SE), Pamplona (E), Prato (I), Saarbrücken (D), Vienna (A), and Zürich (CH).     

IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty

In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.     

Self-organizing systems and environmental management

The characteristics of self-organizing systems are described and their implications for environmental management are discussed. It is concluded that the aim of management should be to enhance the capacity of the system for self-management, with active intervention being used only to steer it away from large discontinuities. Environmental managers must view ecosystems and themselves as parts of a larger sociobiophysical system, cultivate the capacity of environmental systems for self-management, and learn to live with change and uncertainty. Practical consequences of this approach for plans, policies, programs, and institutions are discussed.     

Inexact multistage stochastic integer programming for water resources management under uncertainty

In this study, an inexact multistage stochastic integer programming (IMSIP) method is developed for water resources management under uncertainty. This method incorporates techniques of inexact optimization and multistage stochastic programming within an integer programming framework. It can deal with uncertainties expressed as both probabilities and discrete intervals, and reflect the dynamics in terms of decisions for water allocation through transactions at discrete points of a complete scenario set over a multistage context. Moreover, the IMSIP can facilitate analyses of the multiple policy scenarios that are associated with economic penalties when the promised targets are violated as well as the economies-of-scale in the costs for surplus water diversion. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that reasonable solutions have been generated for both binary and continuous variables. For all scenarios under consideration, corrective actions can be undertaken dynamically under various pre-regulated policies and can thus help minimize the penalties and costs. The IMSIP can help water resources managers to identify desired system designs against water shortage and for flood control with maximized economic benefit and minimized system-failure risk.     

A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty

In this study, a dual-interval fixed-mix stochastic programming (DFSP) method is developed for planning water resources management systems under uncertainty. DFSP incorporates interval-parameter programming (IPP) and fuzzy vertex analysis (FVA) within a fixed-mix stochastic programming (FSP) framework to address uncertain parameters described as probability distributions and dual intervals. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. A real case for water resources management planning of Zhangweinan River Basin in China is then conducted for demonstrating the applicability of the developed DFSP method. Solutions in association with α-cut levels are generated by solving a set of deterministic submodels, which are useful for generating a range of decision alternatives under compound uncertainties. The results can help to identify desired water-allocation schemes for local sustainable development that the prerequisite water demand can be guaranteed when the available water resource is scarce.     

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency.     

A two-stage support-vector-regression optimization model for municipal solid waste management - a case study of Beijing, China

In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through coupling the support-vector-regression (SVR) model with an interval-parameter mixed integer linear programming (IMILP). The developed TSOM can not only predict the city's future waste generation amount, but also reflect dynamic, interactive, and uncertain characteristics of the MSW management system. Four kernel functions such as linear kernel, polynomial kernel, radial basis function, and multi-layer perception kernel are chosen based on three quantitative simulation performance criteria [i.e. prediction accuracy (PA), fitting accuracy (FA) and over all accuracy (OA)]. The SVR with polynomial kernel has accurate prediction performance for MSW generation rate, with all of the three quantitative simulation performance criteria being over 96%. Two cases are considered based on different waste management policies. The results are valuable for supporting the adjustment of the existing waste-allocation patterns to raise the city's waste diversion rate, as well as the capacity planning of waste management system to satisfy the city's increasing waste treatment/disposal demands.     

Assessing instruments for mixed household solid waste collection services in the Flemish region of Belgium

Instruments to reduce waste can be divided into three groups: first, pecuniary incentives; second, service level; finally, measurements stimulating prevention and waste reduction. Also specific characteristics of the community determine the amount of waste generated. We evaluate whether findings in literature on effectiveness of policy measures are valid for Belgium, specifically for the Flemish region. The policy mix instituted by the Flemish authorities in the ‘implementation plan household waste 2003–2007’ and implemented by local authorities, is assessed. Multiple regression analysis identifies those measurements having the greatest impact on household solid waste.We found an income elasticity of 0.326. Also the provided service level has a significant impact. Pecuniary incentives are effective instruments in reducing waste, with a price elasticity of −0.139. Furthermore, a higher percentage of direct costs, directly attributable to waste services, borne by households, reduces waste. A consequent implementation of the ‘polluter pays’ principle proves to be effective.     

A mixed integer linear programming model for optimisation of organics management in an integrated solid waste system

In this paper, the authors propose a mixed integer linear programming model for designing an Integrated Solid Waste Management System (ISWMS) to meet specific economic goals. The model refers to a set of municipalities, known as ‘local basin’, which have to share a common waste management system. At the municipal level the model allows for an identification of the optimal collection service option; at the local basin level, the model provides the optimal waste flow appropriate to the collection service option of each municipality. The model has been applied to a full-scale case study of an area located in southeast Italy. A scenario analysis was carried out to investigate alternative municipal solid waste management options, which fundamentally differ in the organic flow mass rate to be either collected and composted or landfilled. Findings show that an increase in the cost of landfilling determines the optimal collection scenario and the configuration plants tend to recover higher rates of organics in separate collection and thus higher refuse derived fuel productions. The results obtained validate the application of the model in both the strategic planning and operational phases, by supporting public administrators at both municipality and local basin level in decision making and evaluation of technical and economic performances of ISWMSs.     

Solid waste management in European countries: a review of systems analysis techniques

In the past few decades, solid waste management systems in Europe have involved complex and multi-faceted trade-offs among a plethora of technological alternatives, economic instruments, and regulatory frameworks. These changes resulted in various environmental, economic, social, and regulatory impacts in waste management practices which not only complicate regional policy analysis, but also reshape the paradigm of global sustainable development. Systems analysis, a discipline that harmonizes these integrated solid waste management strategies, has been uniquely providing interdisciplinary support for decision making in this area. Systems engineering models and system assessment tools, both of which enrich the analytical framework of waste management, were designed specifically to handle particular types of problems. Though how to smooth out the barriers toward achieving appropriate systems synthesis and integration of these models and tools to aid in the solid waste management schemes prevalent in European countries still remains somewhat uncertain. This paper conducts a thorough literature review of models and tools illuminating possible overlapped boundaries in waste management practices in European countries and encompassing the pros and cons of waste management practices in each member state of the European Union. Whereas the Southern European Union (EU) countries need to develop further measures to implement more integrated solid waste management and reach EU directives, the Central EU countries need models and tools with which to rationalize their technological choices and management strategies. Nevertheless, considering systems analysis models and tools in a synergistic way would certainly provide opportunities to develop better solid waste management strategies leading to conformity with current standards and foster future perspectives for both the waste management industry and government agencies in European Union.     

Two-stage planning for sustainable water-quality management under uncertainty

In water-quality management problems, uncertainties may exist in a number of impact factors and pollution-related processes (e.g., the volume and strength of industrial wastewater and their variations can be presented as random events through identifying a statistical distribution for each source); moreover, nonlinear relationships may exist among many system components (e.g., cost parameters may be functions of wastewater-discharge levels). In this study, an inexact two-stage stochastic quadratic programming (ITQP) method is developed for water-quality management under uncertainty. It is a hybrid of inexact quadratic programming (IQP) and two-stage stochastic programming (TSP) methods. The developed ITQP can handle not only uncertainties expressed as probability distributions and interval values but also nonlinearities in the objective function. It can be used for analyzing various scenarios that are associated with different levels of economic penalties or opportunity losses caused by improper policies. The ITQP is applied to a case of water-quality management to deal with uncertainties presented in terms of probabilities and intervals and to reflect dynamic interactions between pollutant loading and water quality. Interactive and derivative algorithms are employed for solving the ITQP model. The solutions are presented as combinations of deterministic, interval and distributional information, and can thus facilitate communications for different forms of uncertainties. They are helpful for managers in not only making decisions regarding wastewater discharge but also gaining insight into the tradeoff between the system benefit and the environmental requirement.     

An interval-based regret-analysis method for identifying long-term municipal solid waste management policy under uncertainty

In this study, an interval-based regret-analysis (IBRA) model is developed for supporting long-term planning of municipal solid waste (MSW) management activities in the City of Changchun, the capital of Jilin Province, China. The developed IBRA model incorporates approaches of interval–parameter programming (IPP) and minimax–regret (MMR) analysis within an integer programming framework, such that uncertainties expressed as both interval values and random variables can be reflected. The IBRA can account for economic consequences under all possible scenarios associated with different system costs and risk levels without making assumptions on probabilistic distributions for random variables. A regret matrix with interval elements is generated based on a matrix of interval system costs, such that desired decision alternatives can be identified according to the interval minimax regret (IMMR) criterion. The results indicate that reasonable solutions have been generated. They can help decision makers identify the desired alternatives regarding long-term MSW management with a compromise between minimized system cost and minimized system-failure risk.     

The limitations of environmental management systems in Australian agriculture

The efficacy of government-supported programs to encourage improved management of land and water systems associated with agricultural land in Australia has been mixed. The broad approach of Australian governments is reviewed briefly. Evidence is presented from case assessments of a program to promote adoption of environmental management systems (EMSs) to improve environmental outcomes from agricultural practices. EMSs are systems implemented to manage the environmental impacts and ameliorate environmental risk associated with business activity. Data are presented on reported EMS activity and experience of four selected groups of farmers in Victoria, south-eastern Australia, representing broad-acre cropping, beef and dairy farming. The pro-environmental behaviours of farmers were mediated through voluntary adoption of government and industry sponsored EMSs, often with financial incentives and other support. Findings from the study were that adoption of EMS practices with sufficient public benefits is unlikely to occur at sufficient scale for significant environmental impact. Farmers more readily adopted practices which were financially beneficial than those which had a positive environmental impact. Although the focus on voluntary market-based instrument (MBI) type programs is popular in western countries, enforcing regulation is an important, but usually politically unpopular, component of land use policy. The comparative advantage of EMSs differed for the industries studied, but overall there were insufficient market drivers for widespread EMS adoption in Australia. Environmental outcomes could be more effectively achieved by directly funding land management practices which have highest public net benefits. Having a clear and unambiguous management objective for a particular land management policy is more likely to achieve outcomes than having multiple objectives as occurs in a number of international programs currently.     

Issues for small businesses with waste management

Participation by small and medium enterprise (SME) in corporate social responsibility issues has been found to be lacking. This is a critical issue, as individually SMEs may have little impact on the environment but their collective footprint is significant. The management style and ethical stance of the owner-manager affects business decision making and therefore has a direct impact on the environmental actions of the business. Although adoption of environmental practices to create competitive advantage has been advocated, many businesses see implementation as a cost which cannot be transferred to their customers. After a brief review of pertinent literature this paper reports on an exploratory investigation into the issue. Results show that whereas owner-managers of small enterprises express concern regarding the environment, this does not then translate into better waste management practices.     

Solid waste management in urban areas: Development and application of a decision support system

A decision support system (DSS) developed to assist the planner in decisions concerning the overall management of solid waste at a municipal scale is described. The DSS allows to plan the optimal number of landfills and treatment plants, and to determine the optimal quantities and the characteristics of the refuse that has to be sent to treatment plants, to landfills and to recycling. The application of the DSS is based on the solution of a constrained non-linear optimization problem. Various classes of constraints have been introduced in the problem formulation, taking into account the regulations about the minimum requirements for recycling, incineration process requirements, sanitary landfill conservation, and mass balance. The cost function to be minimized includes recycling, transportation and maintenance costs. The DSS has been tested on the municipality of Genova, Italy, and the results obtained are presented.     

Interactive two-stage stochastic fuzzy programming for water resources management

In this study, an interactive two-stage stochastic fuzzy programming (ITSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact two-stage stochastic programming (ITSP) framework. ITSFP can not only tackle dual uncertainties presented as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints, but also permit in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised policy targets are violated. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees has been generated for planning the water resources allocation. They can help the decision makers (DMs) to conduct in-depth analyses of tradeoffs between economic efficiency and constraint-violation risk, as well as enable them to identify, in an interactive way, a desired compromise between satisfaction degree of the goal and feasibility of the constraints (i.e., risk of constraint violation).