Landfill location selection for healthcare waste of urban areas using hybrid BWM-grey MARCOS model based on GIS

Abstract

Healthcare waste generated by medical activities in big cities includes a vast spectrum of materials, from blood, body parts, medical devices, pharmaceuticals, chemicals, diagnostic samples, soiled dressings, syringes and needles, and radioactive material. Improper management of health-care waste places the urban community and society, urban residents, patients, and water resources at risk from the toxic effects of environmental pollution, which can bring up many social and environmental costs for municipalities. Location selection for sitting a landfill for health-care waste with a sustainable development perspective is a complicated decision making problem in the urban and social planning area. This study develops a novel integrated decision-making model for landfill location selection for the health-care waste system. In this study, Geographic Information System (GIS), Best-Worst Method (BWM), and Measurement of alternatives and ranking according to COmpromise solution (MARCOS) method under grey interval set considering sustainability factors. To generate the GIS suitability maps, location criteria are first calculated using the BWM model. The GIS suitability maps suggest eight potential locations for landfilling, which are prioritized using G-MARCOS in order to select the best alternative location. To the best of our knowledge, the present study is the first study to integrate GIS, BWM, and G-MAROCS methods for sustainable landfill location selection problem for health-care waste. This paper investigates a real case of the municipality of Hamedan, Iran, to show the applicability of the developed methodology for urban planning problems. Sensitivity analysis tests are performed to establish the reliability and robustness of the results. Alternative A7, A8, and A4 are selected respectively as the top three potential location for sitting a landfill for health-care waste. However, locations A6, and A1 are the least suitable alternatives for sitting in a landfill.