Ni-Bin Chang

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.

A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems

Abstract The emphasis of waste reduction and recycling requirements prior to incineration and the protection of environmental quality during waste shipping, treatment, and disposal have resulted in a set of new solid waste management goals in system planning. However, the inherent uncertainties in the perception of both priority and scale of those economic and environmental goals may generate additional difficulties in management decision making. This paper applies a fuzzy goal programming approach for the optimal planning of solid waste management systems in a metropolitan region. In particular, it demonstrates how fuzzy, or imprecise, objectives of the decision maker can be quantified through the use of specific membership functions in various types of solid waste management alternatives.

A fuzzy interval multiobjective mixed integer programming approach for the optimal planning of solid waste management systems

Various deterministic mathematical programming models were developed to evaluate single objective or multiple objectives planning alternatives for municipal solid waste management. The common objective of minimizing the present value of overall management cost/benefit was extended to deal explicitly with environmental considerations, such as air pollution, traffic flow limitation, and leachate and noise impacts. But uncertainty plays an important role in the search for sustainable solid waste management strategies. This paper proposes a new approach a fuzzy interval multiobjective mixed integer programming (FIMOMIP) model m for the evaluation of management strategies for solid waste management in a metropolitan region. In particular, it demonstrates how uncertain messages can be quantified by specific membership functions and combined through the use of interval numbers in a multiobjective analytical framework.

Recycling of construction and demolition waste via a mechanical sorting process

Abstract This paper assesses a construction and demonstration (C&D) waste recycling program in relation to technical, institutional, and economic considerations. The focus is primarily placed on a feasibility study for a new mechanical sorting process that was installed with several unit operations, including bar screening, trommel screening, air classifier, disk screening, and final manual sorting. Lab analyses, consisting of sieve analysis, LA abrasion test, friability test, organic content test, and fineness test, with respect to three types of product streams (A, B, and C) were conducted in accordance with selected physical and chemical properties. Findings clearly indicate that the reuse of fine particle generated in product stream A as construction materials in roadbed is highly recommended if the impurities can be removed beforehand. The product stream B could be suitable for reusing as the covering materials in daily operation of sanitary landfills. Yet it could also be used as backfill materials in the construction projects if the impurities can be removed in advance. Only does the LA abrasion test support the reuse of product stream C as coarse aggregate or pavement subbase for those new structures. Once the secondary materials market is stable and the institution settings are sufficient, it is worthwhile addressing that the associated cost-benefit analysis does confirm the economic potential for such a management practice.

System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts

Accurate prediction of municipal water demand is critically important to water utilities in fast-growing urban regions for drinking water system planning, design, and water utility asset management. Achieving the desired prediction accuracy is challenging, however, because the forecasting model must simultaneously consider a variety of factors associated with climate changes, economic development, population growth and migration, and even consumer behavioral patterns. Traditional forecasting models such as multivariate regression and time series analysis, as well as advanced modeling techniques (e.g., expert systems and artificial neural networks), are often applied for either short- or long-term water demand projections, yet few can adequately manage the dynamics of a water supply system because of the limitations in modeling structures. Potential challenges also arise from a lack of long and continuous historical records of water demand and its dependent variables. The objectives of this study were to (1) thoroughly review water demand forecasting models over the past five decades, and (2) propose a new system dynamics model to reflect the intrinsic relationship between water demand and macroeconomic environment using out-of-sample estimation for long-term municipal water demand forecasts in a fast-growing urban region. This system dynamics model is based on a coupled modeling structure that takes into account the interactions among economic and social dimensions, offering a realistic platform for practical use. Practical implementation of this water demand forecasting tool was assessed by using a case study under the most recent alternate fluctuations of economic boom and downturn environments.

Siting recycling drop-off stations in urban area by genetic algorithm-based fuzzy mulitobjective nonlinear integer programming modeling

Due to the rapid depletion of landfill space and the time-consuming process for siting and building new municipal incinerators, solid waste management strategies have to be reorganized in light of the success of recycling, recovery and reuse of secondary materials. Effective planning of solid waste recycling programs, however, is currently a substantial challenge in many solid waste management systems. One of such efforts is how to effectively allocate the recycling drop-off stations with appropriate size in the solid waste collection network to maximize the recycling achievement with minimum expense. This paper illustrates a new approach with a view to optimizing siting and routing aspects using a fuzzy multiobjective nonlinear integer programming model as a means that is particularly solved by a genetic algorithm. The case study, based on one of the administrative districts in the city of Kaohsiung in Taiwan, presents the application potential of such a planning methodology.

Prediction analysis of solid waste generation based on grey fuzzy dynamic modeling

Abstract Successful planning of a solid waste management system depends critically on the prediction accuracy of solid waste generation. But the prediction condition of generation trend in many developing countries is quite different from those in developed countries. The lack of sampling and analysis in many developing countries due to insufficient budget and unavailable management task force has resulted in a situation where the historical record of solid waste generation and composition can never be completed in the long term. To effectively handle these problems with only limited samples and fulfil the prediction analysis of solid waste generation with reasonable accuracy, a special analytical technique must be developed and applied before the subsequent system planning for urban solid waste management is carried out. This study presents a new theory — grey fuzzy dynamic modeling — for the prediction of solid waste generation in the urban area based on a set of limited samples. The practical implementation has been accessed by a case study in the city of Tainan in Taiwan. It shows that such a new forecasting technique may achieve better prediction accuracy than those of the conventional grey dynamic model, least-squares regression method, and the fuzzy goal regression technique.

A fuzzy multi-objective programming approach for optimal management of the reservoir watershed

Abstract This paper applies a fuzzy multi-objective programming model for the evaluation of sustainable management strategies of optimal land development in the reservoir watershed. The environmental goals lie in the conservation of reservoir water quality and the economic goals focus on the rewards from various uses of land within the watershed. Carrying capacity of the land and assimilative capacity of the reservoir are two major limitations encountered in systems analysis. In particular, it demonstrates how imprecise information in such a system can be quantified by specific membership functions in a fuzzy multi-objective analytical framework. It shows that the fuzzy outputs associated with different weight distribution sin decision analysis can successfully reflect system complexity and generate more realistic management policies. A case study of the planning for land use programs in the Tweng-Wen reservoir watershed in Taiwan was demonstrated.

Corporate optimal production planning with varying environmental costs: A grey compromise programming approach

Abstract Corporate environmental and resources management has become more strategically oriented when many pollution charges, environmental taxes, and resources conservation fees have been gradually imposing to the industry. The need for explicit consideration and incorporation of varying environmental costs within production-planning program is becoming critical to corporate management. This paper attempts to assess an optimal production-planning program in response to varying environmental costs in an uncertain environment. The optimal production strategy concerning numerous screening of possible production alternatives of dyeing cloth in a textile-dyeing firm in terms of market demand, resources availability, and impact of environmental costs is treated as an integral part of the multi-criteria decision-making framework based on the grey compromise programming approach. It covers not only the regular part of production costs and the direct income from product sales but also the emission/effluent charges and water resource fees reflecting part of the goals for internalization of external cost in a sustainable society. In particular, all the crucial variables in the model are addressed by interval expressions, the same as they are frequently applied in the grey systems theory, in support of a vital uncertainty assessment, which is much better suited for this particular study than other approaches. Research results demonstrate the applicability and significance of such an approach based on a case study. Industry looking for the competitive advantage of environmental management must be aware of the potential benefits from such an integrated production-planning program once the trend of increasing pollution charges, environmental taxes, and resources conservation fees remains.

An analysis of recycling impacts on solid waste generation by time series intervention modeling

Abstract Successful operation of solid waste management systems frequently depends on accurate predictions of solid waste generation. Conventional prediction models are usually estimated based on demographic and socioeconomic factors in a per-capita basis. The per-capita coefficients may be taken as fixed over time or they may be projected to change with time. However, time series data of solid waste generation consist of observations made over a number of years at the same location. By analyzing time series data, forecasters can identify trends embedded in solid waste generation over time and can develop hypotheses regarding the policy change or the continuation of these trends into the future. At present, the impacts of recycling activities has received wide attention at different levels of government agency and the effect of successful recycling programs inevitably adds more uncertainties in the prediction of solid waste generation. This analysis applies time series intervention modeling to evaluate recycling impacts on solid waste generation. A demonstration of how this forecasting information can be used for the capacity evaluation of incinerators in Taipei City of Taiwan is also included in this paper.