Importance�Cperformance analysis of municipal solid waste management in uncertainty

The aim of this study was to evaluate and position the perceptions of importance and performance of municipal solid waste management aspects and criteria. The study results propose dependence relations among four aspects and 33 criteria pertaining to metropolitan Taipei. Evaluation was based on linguistically described preferences and multiple aspects and criteria analysis; in particular, applied fuzzy set theory was used to evaluate linguistic vagueness, and the analytic network process was applied for dependence relations among the aspects and criteria. In order to compile managerial implications and concluding remarks, importance?Cperformance analysis was conducted, using several mathematical techniques applied to the objectives as well as the participation and input of professionals and academicians. Overall results and concluding remarks are discussed.     

An assessment of cause and effect decision-making model for firm environmental knowledge management capacities in uncertainty

Environmental practices in knowledge management capability (EKMC) is a complex and uncertainty concept that is difficult to determine based on a firm’s real situation because measuring EKMC requires a set of qualitative and quantitative measurement. The objective of this study is to develop a cause and effect model in uncertainty using the fuzzy set theory and Decision Making Trial and Evaluation Laboratory (DEMATEL) method. A framework for evaluating EKMC is proposed. An approach of fuzzy linguistic is proposed to evaluate the firm EKMC. The evaluation results of EKMC obtained through the proposed approach are objective and unbiased due to two reasons. Firstly, the results are generated by a group of experts in the presence of motile attributes. Secondly, the fuzzy linguistic approach has more advantage to reduce distortion and losing of information. Through evaluating the result of EKMC, managers could judge the necessity to improve the EKMC and determine which criteria are the needed directions to improve. The managerial implication and conclusions are discussed.     

Classification of air quality using fuzzy synthetic multiplication

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.     

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O<Subscript>3</Subscript> Air Quality Monitoring Network in Vojvodina Province,Serbia

A monitoring network of ground-level ozone (O₃) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O₃ monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O₃ monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.     

Application of ANP and DEMATEL to evaluate the decision-making of municipal solid waste management in Metro Manila

A municipal solid waste management (MSW) expert group was consulted in order to mirror how government officials might reach an effective solution regarding municipal solid waste management in Metro Manila. A critical issue regarding this is how the expert group can better evaluate and select a favorable MSW management solution using a series of criteria. MSW management solution selection is a multiple criteria decision-making (MCDM) problem, which requires the consideration of a large number of complex criteria. A robust MCDM method should consider the interactions among these criteria. The analytic network process (ANP) is a relatively new MCDM method which can deal with all kinds of interactions systematically. The Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a structural model, but also can be used as a way to handle the inner dependences within a set of criteria. Hence, this paper applies an effective solution based on a combined ANP and DEMATEL method to assist the expert group evaluating different MSW management solutions. According to the results, the best solution is for each city to have its own type of thermal process technology and resource recovery facility before landfill rather than entering a joint venture with enterprises or going into build-operate-transfer projects in order to be able to construct thermal process technologies and resource recovery facilities.     

Assessment of trace metals pollution in estuarine sediments using SEM-AVS and ERM?CERL predictions

In this paper a PSIAC-based multi-parameter fuzzy pattern recognition (MPFPR) model is proposed and applied for classifying and ranking the potential soil erosion (PSE). In this approach, standard value matrix is used to define the membership degrees of each catchment to each class and the feature values are used for alternative ranking. The characteristic of PSE for each class is expressed by linguistic variables. The proposed method is straightforward, easy to understand, very practical, and its results may easily be interpreted. To assess the performance of the model, the results of PSIAC MPFPR and original PSIAC method are interpreted and compared with the observed data. It is shown that the proposed approach reflects the fuzzy nature of the soil erosion more efficiently and is quite robust for application in real world cases.     

Utility of fuzzy cross-impact simulation in environmental assessment

Fuzzy cross-impact simulation is a qualitative technique, where interactions within a system are represented by a cross-impact matrix that includes linguistic elements. It can be used effectively to visualize dynamic evolution of a system. The utility of the fuzzy cross-impact simulation approach is: (1) in dealing with uncertainties in environment-development systems; (2) scoping cumulative effect assessment; and (3) integrating societal response structure in environment impact assessment. Use of the method is illustrated in a case concerning the textile industry in Indore, India. Consequences of policy alternatives for cleanup and pollution abatement are predicted in terms of environmental quality and quality of life, using the simulation model. The consequence analysis is used to arrive at preferred policy options.     

Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Application of fuzzy DEMATEL to develop a cause and effect model of municipal solid waste management in Metro Manila

The municipal solid waste management (MSW) evaluation is usually evaluated in subjective and qualitative in nature described in linguistic information; it is very difficult for expert groups to express the preferences using exact numerical values. A MSW expert group is consulted in order to mirror how government officials might reach a cause-effect model regarding MSW management in Metro Manila. A critical issue regarding this is how the expert group can better evaluate the MSW management criteria in uncertainty. A cause and effect model development can help the processing of decision making problem. The Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a model but also can be used as a way to handle the inner dependences within a set of criteria. The post survey is further discussed and proved the validity result.     

Development of fuzzy air quality index using soft computing approach

Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.     

Land suitability assessment for wind power plant site selection using ANP-DEMATEL in a GIS environment: case study of Ardabil province,Iran

Wind energy is a renewable energy resource that has increased in usage in most countries. Site selection for the establishment of large wind turbines, called wind farms, like any other engineering project, requires basic information and careful planning. This study assessed the possibility of establishing wind farms in Ardabil province in northwestern Iran by using a combination of analytic network process (ANP) and decision making trial and evaluation laboratory (DEMATEL) methods in a geographical information system (GIS) environment. DEMATEL was used to determine the criteria relationships. The weights of the criteria were determined using ANP and the overlaying process was done on GIS. Using 13 information layers in three main criteria including environmental, technical and economical, the land suitability map was produced and reclassified into 5 equally scored divisions from least suitable to most suitable areas. The results showed that about 6.68 % of the area of Ardabil province is most suitable for establishment of wind turbines. Sensitivity analysis shows that significant portions of these most suitable zones coincide with suitable divisions of the input layers. The efficiency and accuracy of the hybrid model (ANP-DEMATEL) was evaluated and the results were compared to the ANP model. The sensitivity analysis, map classification, and factor weights for the two methods showed satisfactory results for the ANP-DEMATEL model in wind power plant site selection.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.     

Spatial�Ctemporal assessment and redesign of groundwater quality monitoring network: a case study

Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation?Cdistance (T?CD) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy equivalence relations. As a result, the sampling (temporal) frequency determination method also recommends the future sampling frequencies for each location based on certain criteria such as direction, magnitude, correlation with neighboring stations, and uncertainty of the concentration trend derived from representative historical concentration data. The proposed methodology is applied to groundwater resources in the Tehran?CKaradj aquifer, Tehran, Iran.     

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.     

Developing a fuzzy neural network-based support vector regression (FNN-SVR) for regionalizing nitrate concentration in groundwater

The aim of this study is to develop a fuzzy neural network-based support vector regression model (FNN-SVR) for mapping crisp-input and fuzzy-output variables. In this model, an artificial neural network (ANN) estimator based on multilayer perceptron (MLP) is considered as the kernel function of the SVR, whereas asymmetric triangular fuzzy H-level sets are assumed for model parameters including weight and biases of the ANN model. A genetic algorithm (GA) with real coding is implemented to optimize the model parameters during the training phase. To evaluate the efficiency and applicability of the proposed model, it is applied for simulating and regionalizing nitrate concentration in Karaj Aquifer in Iran. The goodness-of-fit criteria indicate a better performance of the FNN-SVR compared to some benchmark models such as geostatistic techniques as well as traditional SVR models with linear, quadratic, polynomial, and Gaussian kernel functions for modeling nitrate concentrations in groundwater.     

LCA Integrated ANP Framework for Selection of Sustainable Manufacturing Processes

In recent times, the focus of sustainable development has been shifted toward the process domain to achieve greater environmental benefits. Improved sustainability in the process domain can be achieved by selecting sustainable process or through improvement studies. In this study, sustainability performance of injection molding (IM) and selective laser sintering (SLS) processes are compared to select the sustainable process. Life cycle assessment (LCA) has been widely accepted for assessing the environmental performance of manufacturing process. However, the problem with LCA is the interpretation of impact category scores when comparing alternate processes. Therefore, an effort has been made to integrate analytical network process (ANP) methodology with LCA in which LCA methodology calculates the impact score and ANP computes the Single Point Process Sustainability Score (SPPSS) to compare alternate processes. Based on the inventory data collected for higher production rates, SPPSS for IM and SLS processes are computed as 0.038 and 0.068, respectively. Based on the score, IM has been identified as a sustainable process for higher production volume. Hence, the practical usability of the proposed methodology is validated by the study. This study also appreciates the application of ANP along with LCA for decision making in the real-time scenario.     

A water quality monitoring network design using fuzzy theory and multiple criteria analysis

A proper water quality monitoring design is required in a watershed, particularly in a water resource protected area. As numerous factors can influence the water quality monitoring design, this study applies multiple criteria analysis to evaluate the suitability of the water quality monitoring design in the Taipei Water Resource Domain (TWRD) in northern Taiwan. Seven criteria, which comprise percentage of farmland area, percentage of built-up area, amount of non-point source pollution, green cover ratio, landslide area ratio, ratio of over-utilization on hillsides, and density of water quality monitoring stations, are selected in the multiple criteria analysis. The criteria are normalized and weighted. The weighted method is applied to score the subbasins. The density of water quality stations needs to be increased in priority in the subbasins with a higher score. The fuzzy theory is utilized to prioritize the need for a higher density of water quality monitoring stations. The results show that the need for more water quality stations in subbasin 2 in the Bei-Shih Creek Basin is much higher than those in the other subbasins. Furthermore, the existing water quality station in subbasin 2 requires maintenance. It is recommended that new water quality stations be built in subbasin 2.     

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.     

Promoting corporate sustainability through sustainable resource management: A hybrid decision-making approach incorporating social media data

Previous studies revealed triple bottom line cannot entirely cover the concept of corporate sustainability. This study thus uses sustainable resource management (SRM) to improve corporate sustainability (CS) performance considering the socio-environmental, socio-economical, and eco-efficiency aspects. In this study, the vague set (VS) theory and the technique for order preference by similarity to ideal solution (TOPSIS) method are integrated as a hybrid decision-making tool by which social media data can be transformed into entropy weights. The results indicate eco-efficiency and society should be prioritized to improve the corporate sustainability performance. Specifically, the aspects should be promoted through encouraging environmental innovation, redesigning consumers' offer, raising support of the institutions and policy measures, and organizing synergetic involvement. The contributions of this study are three-fold: (i) establishing a comprehensive framework for guiding firms make effective improvements; (ii) developing a hybrid VS-TOPSIS method to process the assessment data and social media information and address the interrelationships; (3) identifying the decisive SRM criteria to precisely guide the Chinese automobile industry towards CS under severe resource constraints.