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Evaluation of landfill sites using GIS-based MCDA with hesitant fuzzy linguistic term sets

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Abstract

There are many criteria to be considered in environmental, social, and economic issues for the landfill site selection (LSS). Multi-criteria decision analysis (MCDA) methods are often used to solve complex decision-making problems such as LSS. However, decision-makers (DMs) may hesitate during the evaluation of the landfill sites with possible incorrect evaluation concerns. Therefore, the inclusion of the hesitant fuzzy linguistic term sets (HFLTS), which considers the hesitations in the preferences of DMs, is suitable for the solution of the problem. On the other hand, geographic information systems (GIS) is an important decision support tool that can analyze different types of spatial data. The aim of this study is to evaluate landfill sites. To do so, the applied approach includes the processes of identifying appropriate alternative sites for landfills by combining HFLTS-based MCDA method and GIS and evaluation of alternative sites with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The applicability of the proposed approach is tested on Samsun city, Turkey. As a result, scenario analysis, which is dominated by environmental criteria, provides better results dominated by social-economic criteria. Consequently, 12 alternative locations are selected and evaluated for the LSS. Atakum and Canik districts of Samsun city are determined as very suitable locations for landfill sites.

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Acknowledgments

The authors are very grateful to Professor Orhan Dengiz, Professor Nurdan Gamze Turan, and Environmental Engineer Levent Arslan for their constructive comments and suggestions.

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Correspondence to Eren Özceylan.

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Appendix 1 Pairwise comparisons of DMs

Appendix 1 Pairwise comparisons of DMs

Table 16 Pairwise comparisons for main criteria
Table 17 Pairwise comparisons for environmental criteria
Table 18 Pairwise comparisons for social/economic criteria

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Özkan, B., Sarıçiçek, İ. & Özceylan, E. Evaluation of landfill sites using GIS-based MCDA with hesitant fuzzy linguistic term sets. Environ Sci Pollut Res 27, 42908–42932 (2020). https://doi.org/10.1007/s11356-020-10128-0

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