IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

An evaluation of alternative household solid waste treatment practices using life cycle inventory assessment mode

Waste disposal is an important part of the life cycle of a product and is associated with environmental burdens like any other life-cycle stages. In this study, an integrated assessment for solid waste treatment practices, especially household solid waste, was undertaken to evaluate the impact contribution of household solid waste treatment alternatives towards the sustainable development by using Life Cycle Inventory Assessment method. A case study has been investigated under various possible scenarios, such as (1) landfill without landfill gas recovery, (2) landfill with landfill gas recovery and flaring, (3) landfill with landfill gas recovery and electric generation, (4) composting, and (5) incineration. The evaluation utilized the Life Cycle Inventory Assessment method for multiple assessments based on various aspects, such as greenhouse gas emission/reduction, energy generation/consumption, economic benefit, investment and operating cost, and land use burden. The results showed that incineration was the most efficient alternative for greenhouse gas emission reduction, economic benefit, energy recovery, and land use reduction, although it was identified as the most expensive for investment and operating cost, while composting scenario was also an efficient alternative with quite economic benefit, low investment and operating cost, and high reduction of land use, although it was identified as existing greenhouse gas emission and no energy generation. Furthermore, the aim of this study was also to establish localized assessment methods that waste management agencies, environmental engineers, and environmental policy decision makers can use to quantify and compare the contribution to the impacts from different waste treatment options.     

The effects of socioeconomic parameters on household solid-waste generation and composition in developing countries (a case study: Ahvaz,Iran)

Environment problems associated with the generation of waste are part of societal changes where households play an important role. These societal changes influence the size, structure and characteristic of given households. For the effective planning of solid-waste handling infrastructure, it is essential to know the quantity of waste generation and its composition. This paper presents the findings of a study carried out in an urban municipal area in Iran to determine the household solid-waste generation rate and waste composition based on field surveys and to determine the related socioeconomic parameters. The dependent variables were waste generation and composition, and independent variables were family size, family employment, age, number of room and education. Over 400 sample households were selected for the study using a stratified random sampling methodology and from five different socioeconomic groups. Waste collected from all groups of households were segregated and weighted. Waste generation rate was 5.4 kg/household/day. Household solid waste comprised of ten categories of wastes and with the largest component (76.9%). The generation and composition of household solid waste were correlated with family size, education level and households income. This paper adequately suggests new insights concerning the role of socioeconomic parameters in affecting the generation of household waste.     

Assessment of plastic waste generation and its potential recycling of household solid waste in Can Tho City, Vietnam

Plastic solid waste has become a serious problem when considering the disposal alternatives following the sequential hierarchy of sound solid waste management. This study was undertaken to assess the quantity and composition of household solid waste, especially plastic waste to identify opportunities for waste recycling. A 1-month survey of 130 households was carried out in Can Tho City, the capital city of the Mekong Delta region in southern Vietnam. Household solid waste was collected from each household and classified into ten physical categories; especially plastic waste was sorted into 22 subcategories. The average household solid waste generation rate was 281.27 g/cap/day. The compostable and recyclable shares respectively accounted for high percentage as 80.74% and 11%. Regarding plastic waste, the average plastic waste generation rate was 17.24 g/cap/day; plastic packaging and plastic containers dominated with the high percentage, 95.64% of plastic waste. Plastic shopping bags were especially identified as the major component, accounting for 45.72% of total plastic waste. Relevant factors such as household income and household size were found to have an existing correlation to plastic waste generation in detailed composition. The household habits and behaviors of plastic waste discharge and the aspects of environmental impacts and resource consumption for plastic waste disposal alternatives were also evaluated.     

Optimal water and waste-load allocations in rivers using a fuzzy transformation technique: a case study

In this paper, a new methodology is developed for integrated allocation of water and waste-loads in river basins utilizing a fuzzy transformation method (FTM). The fuzzy transformation method is used to incorporate the existing uncertainties in model inputs. In the proposed methodology, the FTM, as a simulation model, is utilized in an optimization framework for constructing a fuzzy water and waste-loads allocation model. In addition, economic as well as environmental impacts of water allocation to different water users are considered. For equitable water and waste load allocation, all possible coalition of water users are considered and total benefit of each coalition, which is a fuzzy number, is reallocated to water users who are participating in the coalition. The fuzzy cost savings are reallocated using a fuzzy nucleolus cooperative game and the FTM. As a case study, the Dez River system in south-west of Iran is modeled and analyzed using the methodology developed here. The results show the effectiveness of the methodology in optimal water and waste-loads allocations under uncertainty.     

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology.     

A Strategic Project Appraisal framework for ecologically sustainable urban infrastructure

Actors in the built environment are progressively considering environmental and social issues alongside functional and economic aspects of development projects. Infrastructure projects represent major investment and construction initiatives with attendant environmental, economic and societal impacts across multiple scales. To date, while sustainability strategies and frameworks have focused on wider national aspirations and strategic objectives, they are noticeably weak in addressing micro-level integrated decision making in the built environment, particularly for infrastructure projects. The proposed approach of this paper is based on the principal that early intervention is the most cost-effective and efficient means of mitigating the environmental effects of development projects, particularly macro infrastructure developments. A strategic overview of the various project alternatives, taking account for stakeholder and expert input, could effectively reduce project impacts/risks at low cost to the project developers but provide significant benefit to wider communities, including communities of future stakeholders. This paper is the first exploratory step in developing a more systematic framework for evaluating strategic alternatives for major metropolitan infrastructure projects, based on key sustainability principles. The developed Strategic Project Appraisal (SPA) framework, grounded in the theory of Strategic Environmental Assessment (SEA), provides a means of practically appraising project impacts and alternatives in terms of quantified ecological limits; addresses the neglected topic of metropolitan infrastructure as a means of delivering sustainability outcomes in the urban context and more broadly, seeks to open a debate on the potential for SEA methodology to be more extensively applied to address sustainability challenges in the built environment. Practically applied and timed appropriately, the SPA framework can enable better decision-making and more efficient resource allocation ensuring low impact infrastructure development.     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.     

A Superiority-Inferiority-Based Inexact Fuzzy Stochastic Programming Approach for Solid Waste Management Under Uncertainty

A superiority–inferiority-based inexact fuzzy stochastic programming (SI-IFSP) model was developed for planning municipal solid waste management systems under uncertainty. The SI-IFSP approach represents a new attempt to tackle multiple uncertainties in objective function coefficients which are beyond the capabilities of existing inexact programming methods. Through introducing the concept of fuzzy random boundary interval, SI-IFSP is capable of reflecting multiple uncertainties (i.e., interval values, fuzzy sets, probability distributions, and their combinations) in both the objective function and constraints, leading to enhanced system robustness. The developed SI-IFSP method was applied to a case study of long-term municipal solid waste management. Useful solutions were generated. A number of decision alternatives could be generated based on projected applicable conditions, reflecting the compromise between system optimality and reliability as well as the tradeoffs between economic and environmental objectives. Moreover, the consequences of system violations could be quantified through introducing a set of economic penalties, reflecting the relationships between system costs and constraint violation risks. The results suggest that the proposed SI-IFSP method can explicitly address complexities in municipal solid waste management systems and is applicable to practical waste management problems.     

Selection of suitable alternatives to reduce the environmental impact of road traffic noise using a fuzzy multi-criteria decision model

Road traffic noise is one of the most significant environmental impacts generated by transport systems. To this regard, the recent implementation of the European Environmental Noise Directive by Public Administrations of the European Union member countries has led to various noise action plans (NAPs) for reducing the noise exposure of EU inhabitants. Every country or administration is responsible for applying criteria based on their own experience or expert knowledge, but there is no regulated process for the prioritization of technical measures within these plans. This paper proposes a multi-criteria decision methodology for the selection of suitable alternatives against traffic noise in each of the road stretches included in the NAPs. The methodology first defines the main criteria and alternatives to be considered. Secondly, it determines the relative weights for the criteria and sub-criteria using the fuzzy extended analytical hierarchy process as applied to the results from an expert panel, thereby allowing expert knowledge to be captured in an automated way. A final step comprises the use of discrete multi-criteria analysis methods such as weighted sum, ELECTRE and TOPSIS, to rank the alternatives by suitability. To illustrate an application of the proposed methodology, this paper describes its implementation in a complex real case study: the selection of optimal technical solutions against traffic noise in the top priority road stretch included in the revision of the NAP of the regional road network in the province of Almeria (Spain).     

An environmental pressure index proposal for urban development planning based on the analytic network process

This paper introduces a new approach to prioritize urban planning projects according to their environmental pressure in an efficient and reliable way. It is based on the combination of three procedures: (i) the use of environmental pressure indicators, (ii) the aggregation of the indicators in an Environmental Pressure Index by means of the Analytic Network Process method (ANP) and (iii) the interpretation of the information obtained from the experts during the decision-making process.The method has been applied to a proposal for urban development of La Carlota airport in Caracas (Venezuela). There are three options which are currently under evaluation. They include a Health Club, a Residential Area and a Theme Park. After a selection process the experts chose the following environmental pressure indicators as ANP criteria for the project life cycle: used land area, population density, energy consumption, water consumption and waste generation. By using goal-oriented questionnaires designed by the authors, the experts determined the importance of the criteria, the relationships among criteria, and the relationships between the criteria and the urban development alternatives.The resulting data showed that water consumption is the most important environmental pressure factor, and the Theme Park project is by far the urban development alternative which exerts the least environmental pressure on the area. The participating experts coincided in appreciating the technique proposed in this paper is useful and, for ranking ordering these alternatives, an improvement from traditional techniques such as environmental impact studies, life-cycle analysis, etc.     

Conceptualising and managing trade-offs in sustainability assessment

One of the defining characteristics of sustainability assessment as a form of impact assessment is that it provides a forum for the explicit consideration of the trade-offs that are inherent in complex decision-making processes. Few sustainability assessments have achieved this goal though, and none has considered trade-offs in a holistic fashion throughout the process. Recent contributions such as the Gibson trade-off rules have significantly progressed thinking in this area by suggesting appropriate acceptability criteria for evaluating substantive trade-offs arising from proposed development, as well as process rules for how evaluations of acceptability should occur. However, there has been negligible uptake of these rules in practice. Overall, we argue that there is inadequate consideration of trade-offs, both process and substantive, throughout the sustainability assessment process, and insufficient considerations of how process decisions and compromises influence substantive outcomes. This paper presents a framework for understanding and managing both process and substantive trade-offs within each step of a typical sustainability assessment process. The framework draws together previously published literature and offers case studies that illustrate aspects of the practical application of the framework. The framing and design of sustainability assessment are vitally important, as process compromises or trade-offs can have substantive consequences in terms of sustainability outcomes delivered, with the choice of alternatives considered being a particularly significant determinant of substantive outcomes. The demarcation of acceptable from unacceptable impacts is a key aspect of managing trade-offs. Offsets can be considered as a form of trade-off within a category of sustainability that are utilised to enhance preferred alternatives once conditions of impact acceptability have been met. In this way they may enable net gains to be delivered; another imperative for progress to sustainability. Understanding the nature and implications of trade-offs within sustainability assessment is essential to improving practice.     

An Interval-Parameter Fuzzy-Stochastic Programming Approach for Municipal Solid Waste Management and Planning

In this study, an integrated fuzzy-stochastic linear programming model is developed and applied to municipal solid waste management. Methods of chance-constrained programming and fuzzy linear programming are incorporated within a general interval-parameter mixed-integer linear programming framework. It improves upon the existing optimization methods with advantages in uncertainty reflection, data availability, and computational requirement. The model can be used for answering questions related to types, times and sites of solid waste management practices, with the objective of minimizing system costs over the planning horizon. The model can effectively reflect dynamic, interactive, and uncertain characteristics of municipal waste management systems. In its solution process, the model is transformed into two deterministic submodels, corresponding to upper and lower bounds of the desired objective function values under a given significance level, based on an interactive algorithm. Results of the method's application to a hypothetical case indicate that reasonable outputs have been obtained. It demonstrates the practical applicability of the proposed methodology.     

Fuzzy Possibilistic Modeling for Closed Loop Recycling Collection Networks

Nowadays, in the competitive market, commercial companies due to their economic problems and also restrictions imposed by international organizations to comply with environmental regulations are making noticeable efforts to reduce the level of their wastes in their manufacturing systems and consequently the level of waste in consumers’ products. In harmony with this issue, one of the most effective ways which has successfully been used and proven to be economically profitable is to take products lifecycles into consideration. Consideration of products lifecycle has made supply chain practitioners to investigate the reverse logistics activities in addition to forward logistics activities. Hence, corporations, in order to reduce their cost on the one hand and boosting their efficiency on the other hand, were obligated to employ closed loop supply chain models to concurrently benefit from its economical and environmental advantages. Therefore, in this paper, a mixed nonlinear facility location–allocation model is proposed for recycling collection centers. The considered closed loop logistics model consists of multiple echelons, multiple suppliers, multiple collection centers, multiple time period and also multiple facilities. In real-life problems parameters like demand, cost, capacity, distances, and quantities of returned products are always uncertain. Therefore, in order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed model. Subsequently, to solve fuzzy mixed nonlinear programming model, one of the most effective technique in the literature is used. Additionally, in order to demonstrate the behavior of the parameters employed in the model, a comprehensive sensitivity analysis is conducted. Computational results demonstrate that the proposed model can show favorable efficiency in solving supply chain problems.     

Renewable energy from solid waste: life cycle analysis and social welfare

In this study, municipal solid waste (MSW) composition in distinct world locations is compared and a case study is assessed. Three waste-to-energy (WtE) techniques are employed within the framework of an industrial partnership. Life cycle assessment (LCA) and a brief social contextualization including the production of renewable energy from the waste generated worldwide were held to attain a holistic view and attract the interest of multiple stakeholders.Incineration depicted a sustainable profile with improved results for global warming potential and terrestrial ecotoxicity potential. Regular gasification revealed the best results for eutrophication, acidification, marine aquatic ecotoxicity and human toxicity potential. Two-stage plasma gasification showed negative values for all impact categories i.e. achieving environmental credits. The estimate of the electricity produced from the waste generated per capita showed a fair coverage of the electrical demand in distinct world areas.To the best of the authors' knowledge, there are no reports connecting the electricity use, the waste production and the renewable energy achieved from WtE for different world regions. Therefore, this study supports the replacement of fossil fuels with renewable alternatives, reducing greenhouse gas emissions while maintaining the comfort and commodities suitable for a comfortable quality of life.     

Factors affecting waste generation: a study in a waste management program in Dhaka City, Bangladesh

Information on waste generation, socioeconomic characteristics, and willingness of the households to separate waste was obtained from interviews with 402 respondents in Dhaka city. Ordinary least square regression was used to determine the dominant factors that might influence the waste generation of the households. The results showed that the waste generation of the households in Dhaka city was significantly affected by household size, income, concern about the environment, and willingness to separate the waste. These factors are necessary to effectively improve waste management, growth and performance, as well as to reduce the environmental degradation of the household waste.     

The development and practices of Strategic Environmental Assessment in Shandong Province, China

Strategic Environmental Assessment (SEA), a newly-developed decision-making support tool, has been used in many developed and developing countries for predicting and evaluating potential environmental impact of policies, plans, and programs (PPPs), as well as for providing alternatives to avoid, mitigate, or compensate for these impacts. Unfortunately, due to the complexity and flexibility of SEA, to date there has been no consensus on a system which could be suitable for the contexts of different regions or countries. Different requirements and practices are observed in the different typical stages of SEA. Controversial areas include the appropriate indicators to apply in the early baseline setting stage, suitable methodologies for the impact assessment, and appropriate procedures for the SEA process. Given this, it is important to review and refine the SEA system specific to the context but informed by internationally agreed norms. As an illustration, this study reviews and proposes steps to refine the SEA system in Shandong Province, an economically powerful province of China, aiming to achieve sustainable development. Supported by the Environmental Impact Assessment Law of the People's Republic of China, Shandong Province employed SEA to reform the traditionally economy-oriented decision-making and incorporate consideration of environmental consequences into government deliberation on proposed PPPs. This paper illustrates the developmental process, procedures, and legal support for SEA in Shandong Province. By analyzing five SEA cases carried out by Shandong Province Environment Protection Bureau (SEPB) and Shandong University, problems in the SEA system were identified, and recommendations were made for improving the SEA system not only in Shandong Province but also other similar regions or countries.     

A decision-support system for sustainable urban metabolism in Europe

Urban metabolism components define the energy and material exchanges within a city and, therefore, can provide valuable information on the environmental quality of urban areas. Assessing the potential impact of urban planning alternatives on urban metabolism components (such as energy, water, carbon and pollutants fluxes) can provide a quantitative estimation of their sustainability performance. Urban metabolism impact assessment can, therefore, contribute to the identification of sustainable urban structures with regards, for example, to building types, materials and layout, as well as to location and capacity of transportation and infrastructural developments. In this way, it enables the formulation of planning and policy recommendations to promote efficient use of resources and enhance environmental quality in urban areas.The European FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) has developed a decision-support system (DSS) that systematically integrates urban metabolism components into impact assessment processes with the aim of accurately quantifying the potential effects of proposed planning interventions. The DSS enables integration of multiple spatial and non-spatial datasets (e.g. physical flows of energy and material with variables of social and economic change) in a systematic manner to obtain spatially defined assessment results and to thus inform planners and decision-makers. This multi-criteria approach also enables incorporation of stakeholders' perceptions in order to prioritise decisive assessment criteria. This paper describes the methodological framework used to develop the DSS and critically examines the results of its practical application in five European cities.     

A stochastic conflict resolution model for trading pollutant discharge permits in river systems

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.