Landfill Site Selection for Medical Waste Using an Integrated SWARA-WASPAS Framework Based on Spherical Fuzzy Set

Selecting suitable locations for the disposal of medical waste is a serious matter. This study aims to propose a novel approach to selecting the optimal landfill for medical waste using Multi-Criteria Decision-Making (MCDM) methods. For better considerations of the uncertainty in choosing the optimal landfill, the MCDM methods are extended by spherical fuzzy sets (SFS). The identified criteria affecting the selection of the optimal location for landfilling medical waste include three categories; environmental, economic, and social. Moreover, the weights of the 13 criteria were computed by Spherical Fuzzy Step-Wise Weight Assessment Ratio Analysis (SFSWARA). In the next step, the alternatives were analyzed and ranked using Spherical Fuzzy Weighted Aggregated Sum Product Assessment (SFWASPAS). Finally, in order to show the accuracy and validity of the results, the proposed approach was compared with the IF-SWARA-WASPAS method. Examination of the results showed that in the IF environment the ranking is not complete, and the results of the proposed method are more reliable. Furthermore, ten scenarios were created by changing the weight of the criteria, and the results were compared with the proposed method. The overall results were similar to the SF-SWARA-WASPAS method.

Landfill Site Selection Using GIS and (AHP): Case Study of Ranya City

Ranya City is located in North West of Sulaymaniyah Governorate, Iraq. It has an area of (76.7) km2. In 2018, it was home for (102,571) inhabitants. Presently, there are no landfills in the study area that fulfills necessary environmental requirements; thus, informal and unsuitable solid waste dumping is negatively impacting human health and the environment. Land fill site selection can be a difficult task as it is impacted by different factors and regulations. This study is an attempt to identify and evaluate suitable landfill locations in the study area using Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). Ten criteria are used in this process which includes: groundwater depth, surface water, residential areas, Geological formations, slope, elevation, soil type, land use, roads and archeological sites. AHP was used to determine the weight for each criteria using pairwise comparison matrix. Three classes of suitability index were found: unsuitable (98.47%), moderately suitable (0.003%) and suitable (1.52%) of the study area. Three suitable landfill sites were identified as candidate sites that meet the requirements with an area of (0.29) km2, (0.12) km2 and (0.098) km2 respectively.

Insights for Landfill Site Selection Using GIS: A Case Study in the Tanjero River Basin, Kurdistan Region, Iraq

The increasing world population and the growing quantity of solid waste have become a challenging problem facing governments and policy makers because of the scarcity of suitable sites for new landfills and the negative perception of these sites by the people. This study aims to evaluate the performance of different Multi-Criteria Decision-Analysis (MCDA) approaches using remote sensing and Geographic Information System (GIS) data for identifying suitable landfill sites (LFSs). We evaluated the methodologies used by various investigators and selected appropriate ones as suitable sites for Municipal Solid Waste (MSW) landfill in the Tanjero River Basin (TRB) in the Iraqi Kurdistan region. We applied Boolean Overlay (BO), Weighted Sum Method (WSM), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP), and Technique for Order Performance by Similarity to an Ideal Solution (TOPSIS) to allow combined use of 15 thematic layers as predictive factors (PFs). In this study, we applied the Topographic Position Index (TPI) for the first time to select MSW LFSs. Almost all methods showed reliable results and we identified eight suitable sites situated in the western part of the TRB having total area of ~18.35 km2. The best accuracy was achieved using the AHP approach. This paper emphasizes that the approach of the used method is useful for selecting LFSs in other areas, which are located in similar environments.

Methods for safety-related weighting and comparative assessment in the site selection process (MABeSt)

The Federal Office for the Safety of Nuclear Waste Management (BASE) supervises the site selection process in Germany and in particular has the task to review the proposals made by the implementer (Federal Company for Radioactive Waste Disposal, BGE) for determining the siting regions and sites in accordance with §§ 14, 16 and 18 of the German Repository Site Selection Act (StandAG). To determine the siting regions from the sub-areas and the sites from the siting regions, it is likely that safety-related weighting of the results from the application of the geoscientific weighting criteria (§ 24 StandAG) and the application of the preliminary safety investigations (§ 27 StandAG) are necessary. In order to be able to assess and evaluate the proposals of the BGE with respect to the methodological procedure for determining the siting regions and sites, the research project “Methods for safety-related weighting and comparative assessment in the site selection process” (MABeSt) was initiated by BASE. The objective of the research project was to research and explain the state of the art in science and technology (S&T) with respect to safety-oriented weighting and comparative assessment methods and their potential applicability for the selection of siting regions and sites in the site selection process. The status of S&T for safety-oriented weighting and comparative assessment methods was examined and evaluated with respect to site selection procedures for repositories in Germany and abroad (e.g. Switzerland) and also to methodological approaches from other topics (e.g. landfill site selection). The site selection process represents a multicriteria decision problem, which means that methods from the research field of decision theory appear to be suitable. In particular, methods from the multiattribute decision making/aid (MADM) category were identified as suitable and their potential applicability was examined and evaluated. Specific challenges (e.g. data uncertainties, different scales of evaluation criteria) for the relevant procedural steps of the site selection process were taken into account. We present the results and conclusions of the project MABeSt (funding code/4718F13001) carried out by GRS gGmbH and initiated and funded by BASE.

A novel MADM algorithm for landfill site selection based on q-rung orthopair probabilistic hesitant fuzzy power Muirhead mean operator

With the rapid development of economy and the acceleration of urbanization, the garbage produced by urban residents also increases with the increase of population. In many big cities, the phenomenon of "garbage siege" has seriously affected the development of cities and the lives of residents. Sanitary landfill is an important way of municipal solid waste disposal. However, due to the restriction of social, environmental and economic conditions, landfill site selection has become a very challenging task. In addition, landfill site selection is full of uncertainty and complexity due to the lack of cognitive ability of decision-makers and the existence of uncertain information in the decision-making process. Therefore, a novel multi-attribute decision making method based on q-rung orthopair probabilistic hesitant fuzzy power weight Muirhead mean operator is proposed in this paper, which can solve the problem of landfill site selection well. This method uses probability to represent the hesitance of decision maker and retains decision information more comprehensively. The negative effect of abnormal data on the decision result is eliminated by using the power average operator. Muirhead mean operator is used to describe the correlation between attributes. Then, an example of landfill site selection is given to verify the effectiveness of the proposed method, and the advantages of the proposed method are illustrated by parameter analysis and comparative analysis. The results show that this method has a wider space for information expression, gives the decision maker a great degree of freedom in decision-making, and has robustness.