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.     

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.     

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.     

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.     

Performance assessment for municipal solid waste collection in Taiwan

Collecting municipal solid waste (MSW) is a major and expensive task for local waste management authorities, thus efficient MSW collection is a necessity. This study presents a procedure for developing an aggregate indicator (AI) to assess MSW collection efficiency based on multiple factors. The applicabilities of various key performance indicators (KPIs) are evaluated based on five selection criteria, and five KPIs are chosen to form the AI. The relative efficiencies of local MSW collection services are analyzed by the data envelopment analysis (DEA) method. A set of common weights for all five KPIs is then generated based on DEA results and four selection rules by modifying a previous approach. Finally, the proposed AI is applied to assess the MSW collection services provided by 307 local governments in Taiwan, and associated results are compared and discussed.     

Options for management of municipal solid waste in New York City: a preliminary comparison of health risks and policy implications

Landfill disposal and waste-to-energy (WTE) incineration remain the two principal options for managing municipal solid waste (MSW). One critical determinant of the acceptability of these options is the different health risks associated with each. In this analysis relying on published data and exposure modeling, we have performed health risk assessments for landfill disposal versus WTE treatment options for the management of New York City's MSW. These are based on the realistic scenario of using a waste transfer station (WTS) in Brooklyn and then transporting the untreated MSW by truck to a landfill in Pennsylvania or using a WTE facility in Brooklyn and then transporting the resultant ash by truck to a landfill in Pennsylvania. The overall results indicate that the individual cancer risks for both options would be considered generally acceptable, although the risk from landfilling is approximately 5 times greater than from WTE treatment; the individual non-cancer health risks for both options would be considered generally unacceptable, although once again the risk from landfilling is approximately 5 times greater than from WTE treatment. If one considers only the population in Brooklyn that would be directly affected by the siting of either a WTS or a WTE facility in their immediate neighborhood, individual cancer and non-cancer health risks for both options would be considered generally acceptable, but risks for the former remain considerably higher than for the latter. These results should be considered preliminary due to several limitations of this study such as: consideration of risks only from inhalation exposures; assumption that only volume and not composition of the waste stream is altered by WTE treatment; reliance on data from the literature rather than actual measurements of the sites considered, assuming comparability of the sites. However, the results of studies such as this, in conjunction with ecological, socioeconomic and equity considerations, should prove useful to environmental managers, regulators, policy makers, community representatives and other stakeholders in making sound and acceptable decisions regarding the optimal handling of MSW.     

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.     

An inexact reverse logistics model for municipal solid waste management systems

This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred.     

Flexible interval mixed-integer bi-infinite programming for environmental systems management under uncertainty

A number of inexact programming methods have been developed for municipal solid waste management under uncertainty. However, most of them do not allow the parameters in the objective and constraints of a programming problem to be functional intervals (i.e., the lower and upper bounds of the intervals are functions of impact factors). In this study, a flexible interval mixed-integer bi-infinite programming (FIMIBIP) method is developed in response to the above concern. A case study is also conducted; the solutions are then compared with those obtained from interval mixed-integer bi-infinite programming (IMIBIP) and fuzzy interval mixed-integer programming (FIMIP) methods. It is indicated that the solutions through FIMIBIP can provide decision support for cost-effectively diverting municipal solid waste, and for sizing, timing and siting the facilities’ expansion during the entire planning horizon. These schemes are more flexible than those identified through IMIBIP since the tolerance intervals are introduced to measure the level of constraints satisfaction. The FIMIBIP schemes may also be robust since the solutions are “globally-optimal” under all scenarios caused by the fluctuation of gas/energy prices, while the conventional ones are merely “locally-optimal” under a certain scenario.     

Clean fuels from municipal solid waste for fuel cell buses in metropolitan areas

Increasing volumes of municipal solid waste (MSW) pose disposal problems for many cities. Costs are rising as landfilling becomes more difficult. The production of clean transportation fuels (methanol or hydrogen) from MSW is one economically and environmentally promising option for dealing with these problems. An attractive feature is that elimination of essentially all air pollutant emissions is inherent in the process. Current and future air emissions standards should be easily met. Methanol or hydrogen used in fuel cell vehicles (FCV) can help address problems of deteriorating urban air quality due to vehicle pollution and heavy dependence of the transport sector on imported petroleum. Buses are initial targets for commercial application of fuel cells. Coupled with FCVs, MSW could become a major transportation energy resource. For example, less than 25% of New York City's MSW supply would be sufficient to produce the methanol or hydrogen needed to fuel the entire city's bus fleet, if the buses were fuel cell powered. Estimated breakeven tipping fees required for hydrogen or methanol from MSW to compete with the cost of these fuels made from natural gas today are $52 to $89/raw tonne MSW for hydrogen and $64 to $104/raw tonne MSW for methanol (in 1991$), depending on the gasification technology considered. For comparison, the average tipping fee today in New York City is $74/tonne (1991$). Because of the high fuel economies expected for fuel cell buses, total lifecycle costs per bus-km could be lower than for conventional diesel-engine buses.     

An inexact dynamic optimization model for municipal solid waste management in association with greenhouse gas emission control

Municipal solid waste (MSW) should be properly disposed in order to help protect environmental quality and human health, as well as to preserve natural resources. During MSW disposal processes, a large amount of greenhouse gas (GHG) is emitted, leading to a significant impact on climate change. In this study, an inexact dynamic optimization model (IDOM) is developed for MSW-management systems under uncertainty. It grounds upon conventional mixed-integer linear programming (MILP) approaches, and integrates GHG components into the modeling framework. Compared with the existing models, IDOM can not only deal with the complex tradeoff between system cost minimization and GHG-emission mitigation, but also provide optimal allocation strategies under various emission-control standards. A case study is then provided for demonstrating applicability of the developed model. The results indicate that desired waste-flow patterns with a minimized system cost and GHG-emission amount can be obtained. Of more importance, the IDOM solution is associated with over 5.5 million tonnes of TEC reduction, which is of significant economic implication for real implementations. Therefore, the proposed model could be regarded as a useful tool for realizing comprehensive MSW management with regard to mitigating climate-change impacts.     

Alternative treatments for the municipal solid waste and domestic sewage in Campinas,Brazil

The treatments of municipal solid waste (MSW) and the domestic sewage (DS) are critical issues of the current political and environment discussions. These concerns are due to the lack of dumping areas, the continuous increase of the population, and public health issues. The adequate treatment and management of MSW and DS can produce many benefits such as financial funds, heat and energy production, reduction of emissions and recuperation of water for reuse. Currently in Campinas MSW and DS are deposited in landfills or discharged into rivers and other sites. In the present study two scenarios are evaluated for the treatment of MSW and DS in Campinas: recycling with biological treatment and recycling with thermal treatment. The most suitable treatments for Campinas, based on the data from the present analysis and taking into consideration the local conditions, maximization of energy potential and environmental benefits, are incineration for the MSW and biological treatment for DS, both with energy recuperation. The main gains of this option are substantial environmental benefits, generated energy which can reach 18% of the total electrical energy consumed in Campinas while about 53% recuperation of the total amount of water treated for Campinas in 2010.     

An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina

In this study, an interval-parameter two-stage mixed integer linear programming (ITMILP) model is developed for supporting long-term planning of waste management activities in the City of Regina. In the ITMILP, both two-stage stochastic programming and interval linear programming are introduced into a general mixed integer linear programming framework. Uncertainties expressed as not only probability density functions but also discrete intervals can be reflected. The model can help tackle the dynamic, interactive and uncertain characteristics of the solid waste management system in the City, and can address issues concerning plans for cost-effective waste diversion and landfill prolongation. Three scenarios are considered based on different waste management policies. The results indicate that reasonable solutions have been generated. They are valuable for supporting the adjustment or justification of the existing waste flow allocation patterns, the long-term capacity planning of the City's waste management system, and the formulation of local policies and regulations regarding waste generation and management.     

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.     

Multiple regression models for the lower heating value of municipal solid waste in Taiwan

A multiple regression analysis was used to develop two predictive models of lower heating value (LHV) for municipal solid waste (MSW), using 180 samples gathered from cities and counties in Taiwan during 2001-2002. These models are referred to as the original proposed model (OPM) and the simplified model (SM). The coefficients of multiple determinations for the OPM and SM were 0.983 and 0.975, respectively. To verify the feasibility of the models, a demonstration program based on sampling of MSW in Kaohsiung City was conducted. As a result, the OPM showed superior precision in terms of relative percentage deviation (RPD) and mean absolute percentage error (MAPE), when compared to the conventional models based on the proximate analysis, physical composition and ultimate analysis. The SM was derived by neglecting the three minor physical components used in the OPM. The resulting SM was less precise when compared to the OPM, but it was still acceptable, with a precision level better than the conventional models. It was concluded that the predictability of empirical models could be improved significantly through selection of the appropriate physical components and multiple regression analysis.     

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).     

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.     

Management of urban solid waste: Vermicomposting a sustainable option

Solid waste management is a worldwide problem and it is becoming more and more complicated day by day due to rise in population, industrialization as well as changes in our life style. Presently most of the waste generated is either disposed of in an open dump in developing countries or in landfills in the developed ones. Landfilling as well as open dumping requires lot of land mass and could also result in several environmental problems. Land application of urban/municipal solid waste (MSW) can be carried out as it is rich in organic matter and contains significant amount of recyclable plant nutrients. The presence of heavy metals and different toxics substances restricts its land use without processing. Vermicomposting of MSW, prior to land application may be a sustainable waste management option, as the vermicast obtained at the end of vermicomposting process is rich in plant nutrients and is devoid of pathogenic organism. Utilization of vermicast produced from urban/municipal solid waste in agriculture will facilitate in growth of countries economy by lowering the consumption of inorganic fertilizer and avoiding land degradation problem. Vermicomposting of urban/MSW can be an excellent practice, as it will be helpful in recycling valuable plant nutrients. This review deals with various aspects of vermicomposting of MSW.     

Evaluation of municipal solid waste composting kinetics

Most modern municipal solid waste (MSW) composting operations have emphasized the enhancement of decomposition of the organic fraction of the waste to comply with strict environmental regulations. This can be achieved once the composting process kinetics are well understood. This study examined process kinetics through experimentation with bench-scale reactors under controlled composting conditions to show the interdependence between biological, chemical and physical factors during composting of MSW. The effects of temperature, moisture content, waste particle size and carbon to nitrogen (C/N) ratio on process kinetics were evaluated. The results obtained revealed that these factors should be carefully controlled in order to achieve optimum process performance. It has been found that the organic matter degradation during composting follows a first-order kinetic model.     

城市固体废弃物管理系统温室气体排放核算研究综述

城市固体废弃物管理系统是产生温室气体的一个不可忽视的排放源。随着社会经济的快速发展和城市化水平的提高,城市固体废弃物排放量逐年增多,如何准确地核算城市固体废弃物管理系统温室气体排放已成为国内外关注的热点问题之一。本文概述了城市固体废弃物管理系统的演进与优化研究进展,重点对城市固体废弃物管理系统温室气体排放核算规范和标准及其影响因素的研究进行了综述,指出了研究中存在的问题。并进一步建议今后在城市不同类别的固体废弃物管理系统演进过程及其影响、温室气体排放的核算方法、温室气体排放的校正系数、城市固体废弃物管理系统的优化模式及温室气体减排机制等方面加强研究。