Ozone estimation on the ground surface using multivariate linear regression and parameter determination

Ground level ozone (O3) is one of most dangerous pollutants for human health in urban areas. The aim of this study was to identify the factors affecting the formation of ozone and modeling the spatial and temporal variations of ozone concentration in Tehran metropolitan area.
The data used in this research included meteorological data and pollution concentration data for 2014. First, we studied the impact and correlation of parameters to ozone concentration using the coefficient of Pearson, and then we did modeling of ozone concentration using a multivariate linear regression method.
The developed model had the ability to describe 79% of the data changes for 2014. The temporal analysis of the ozone concentration showed that the best coefficient of determination of the model was R2 = 0.771 in the summer and R2 = 0.778 in July. These results also showed that among the air quality monitoring station of Tehran, station 4 had the lowest coefficient of determination (R2 = 0.6) and Aqdasieh station had the highest coefficient of determination (R2 = 0.79). Finally, the spatial distribution of the estimated ozone concentration was consistent with the measured ozone concentration at the station level.
According to the results, all the parameters related to air pollution concentration and meteorological parameters were effective parameters on modeling of ozone concentration on the ground level. The spatial distribution of ozone concentration in Tehran showed a greater concentration of ozone in the South and East than the North and West of the city.