A novel spherical fuzzy AHP method to managing waste from face masks and gloves: an Istanbul-based case study


Konyalıoğlu A., Bereketli I., Özcan T.

International Journal of Environmental Science and Technology, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s13762-024-05871-7
  • Dergi Adı: International Journal of Environmental Science and Technology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Anahtar Kelimeler: Decision support system, Disaster management, Healthcare waste, Medical waste management, Spherical fuzzy sets
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Waste management has emerged as a critical issue in the wake of the COVID-19 pandemic and the earthquake that struck southeast Turkey on February 6th, 2023, particularly regarding the disposal of face masks and gloves. Extensively utilized for disease prevention and maintaining personal hygiene, these items are categorized as medical waste, presenting significant disposal challenges in Turkey. This study aims to overcome these challenges by prioritizing key factors in waste management during the COVID-19 era through the application of the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) in Istanbul. By conducting a comprehensive literature review and consulting with experts, relevant criteria for managing this medical waste have been identified and prioritized. Furthermore, a sensitivity analysis of the decision support model is performed to evaluate its robustness. The data highlight the crucial importance of recycling, landfilling, and incineration capacities, regulatory frameworks, and incineration costs as primary determinants and criteria shaping the waste management landscape. The sensitivity analysis highlights the resilience of our proposed methodology, demonstrating consistent and robust prioritization outcomes even with varying criteria weights, thereby validating the reliability of the methodology in informing policy decisions. The originality of this study lies in its innovative application of spherical fuzzy sets—offering high accuracy and compatibility with human reasoning—to the management of face masks and gloves waste, an area not previously explored using Spherical Fuzzy Multi-Criteria Decision Making (SF-MCDM) in current literature. This novel approach introduces a rigorous and pioneering methodology for investigating this specific aspect of waste management and enriches the academic conversation by providing a practical SF-MCDM framework.