Landfill Site Selection Using combination of fuzzy logic and multi criteria decision making Method (Case Study: Arak, Iran)

The rapid increase of urban population and waste production is one of the most important environmental problems in developed and developing countries. Million of tons of waste material are produced annually in the world, the correct disposal and management of which presents a main concern in the human societies. With the increase in population, and industrialization of societies accompanied by economic growth, the production of waste material has increased throughout the world. It is predicted that the population of the world will increase 2 to 3 Milliard people in the next 30 years. This means that urban waste material production will increase 3 to 4 times. Along with health and environmental adverse effects of the landfill site, emissions of carbon dioxide, the intensification of the process of global warming on a global scale also will follow. Absence appropriate supervision over management and accumulation of these outputs can engender many environmental problems, especially for people who live near the landfill to be followed. Thus, appropriate urban landfill site selection is a main issue related to the stability of cities and human environments. Geographical information systems (GIS) have appeared as useful, computer-based tools for the spatial operations like entry, storage, manipulation, analysis, and display of geographical data. Since GIS can manage a large amount of spatial data, it can serve as an ideal tool in the siting studies. In addition to the use of GIS in the landfill site selection studies, multi-criteria evaluation method to deal with the issues that decision makers and experts face with in landfill site selection is used. Combination of GIS and multi-criterion evaluation method provides a valuable tool for the solution of landfill site selection problems. In this study, fuzzy logic based on Weighted Linear Combination (WLC) were used for urban waste landfill site selection in Arak city in ARC GIS 10.1 software environment with respect to the ecological, and socio-economic parameters.
In this research, reviewing the international obligations in landfill site selection and using environmental expert views on weighting the effective ecologic, and socio-economic criteria in landfill site selection it was revealed that ecologic sub-criteria, including depth of groundwater resources, distance from surface water resources, and flood potential were of great importance in urban landfill siting. Moreover, among the socio-economic sub-criteria, distance from rural and urban population centers were vital in urban landfill site selection. In the present study, after the production of the final suitability map with fuzzy logic based on WLC, the spatial desirability was divided into 5 classes. The spatial desirability for landfill sites lies in the fuzzy membership degree of between 0.3 and 0.87. Around 11033 polygons with an area of 4146.03 square kilometers were found whose spatial suitability in the fuzzy membership degree of 0.3 to 0.87. The most spatial suitability lie in the fuzzy membership degree between 0.69 to 0.87. The spatial suitability of these areas with their fuzzy membership degree is as follows: very low suitability with the fuzzy membership degree of 0.3 to 0.47, low suitability with the fuzzy membership degree of 0.47 to 0.56, moderate suitability with the fuzzy membership degree of 0.56 to 0.63, high suitability with the fuzzy membership degree of 0.63 to 0.69, and very high suitability with the fuzzy membership degree of 0.69 to 0.87. The area of the existing polygons and their number are as follows: very low suitability polygons with the area of 270.73 km2 and number of 328 polygons, low suitability polygons with the area of 683.48 and number of 1687 polygons km2, moderate suitability polygons with the area of 1187.02 km2 and number of 3006, high suitability polygons with the area of 1212.44 km2 and number of 3954 polygons, very high suitability polygons with the area of 792.36 km2 and number of 2058 polygons.