DEVELOPING A DECISION SUPPORT INDEX TO QUANTIFY AIR QUALITY: A MATHEMATICAL MODELING APPROACH

The air pollution is a burdensome problem worldwide due to urbanization, rapid development and starting of new industries. The most obvious impact of poor air quality is related to health hazards and corresponding medical care and treatments. Therefore, it is important to identify the levels of
the air pollution in cities and predetermine actions to improve the quality of air.
The objective of this study is to develop a model to quantify air pollution in cities without using direct measurements. Factors such as industries, population density, trac intensity, green coverage and weather conditions are considered. Since this process consists of imprecise data, fuzzy AHP is applied. The weights of the proposed model are obtained considering a linear combination of Chang's extent analysis method and geometric mean method. The cities are ranked using TOPSIS method.