Evaluation of effective factors on air pollution using optimized cellular automata: A case study of Tehran

Abstract

Vehicles and traffic congestion have been known as the main reasons for air pollution in urban areas, and Cellular Automata (CA) holds a great promise for predicting this hazard. Urban air pollution is a complex phenomenon and many factors involve in its distribution and diffusion. In this paper, the traffic map was used as the source of the air pollutant. Also, the prediction of urban pollution has been done using different data sources such as green space, buildings, wind direction and speed. The coefficient of these factors got estimated with Genetic Algorithm, and a comparison between different modes of the model got done. With considering the effect of these factors an accuracy of 58.4% was obtained.