Population and urbanization growth necessitate investigations on sustainable development of cities. The air pollution in cities caused by liquid, solid particles and specified gasses in the air has several hazardous effects on the environment and human health. It is also associated with a significant cost to the global economy. Recently, researchers have suggested mobile and immobile air-purifiers for improving air quality in urban environments. This paper adopts Bayesian network (BN), MCDM, and optimization techniques to determine the optimum site location to place the immobile air-purifier stations in metropolitan areas as a sustainable perspective in urban development. The study investigates the critical factors that must be considered for locating an air-purifier station in a special area in a city and benefits from experts and real collected data to compare three decision-making approaches. The developed methodologies are applied to Tehran city as a highly polluted city suffering from air pollution most of the year. Results present the differences in the outcomes of the applied methods. The study helps the decision-makers to exploit the priorities of locations according to the considered environmental and operational constraints.
- Risk assessment
- Bayesian Network
- Multi-criteria decision-making
- Site selection