GIS based investigation of spatial dependency of the air pollution : The example of Afyonkarahisar

Air pollution causes many diseases directly or indirectly. The causes of air pollution, which is a global problem, should be investigated and solution suggestions carried out. In this study, the relationship of air pollution with spatial parameters was explained with GIS-based spatial statistical methods and pollution distribution maps were created. Within the scope of the study, 26 points covering the central district of Afyonkarahisar were selected from 36 points where air pollutant parameters were measured by passive sampling method within the scope of the project carried out by the Ministry of Environment and Urbanization (MoEU) in 2015. Measurement data (monthly averages) for all seasons of sulfur dioxide (SO2) and nitrogen dioxide (NO2), which are among the air pollutant parameters, were used. A database was created using the location information of the measurement stations, the concentration values of the pollutant parameters, the building data in the study area, the types of land use (green, open or industrial areas), the heating type information on the neighborhood and the road types. An area (buffer zone) with a diameter of 500 meters was created for each station where the concentration level of the pollution parameters was measured. Exploratory Regression Analysis was used to determine whether there is a significant relationship between dependent and independent variables in the buffer zones and the effect of independent variables on air pollution. By using Single Regression Analysis method, the relationship between pollutant parameters and environmental factors was tried to be explained. Clusters were investigated with spatial autocorrelation tests and pollution distribution maps were created using the Inverse Distance Weighted Interpolation method. In the pollution distribution maps created for all seasons, the neighborhoods within the study area were examined separately and the spatial dependence of the pollutant parameters was tried to be explained. According to the results, SO2 pollution is highest in winter season. In addition, as the building floor area and the number of floors increase, the SO2 pollution level increases, while the structureless area increases, the SO2 pollution level decreases. As the main road lengths and green area size increase, the NO2 pollution level increases. Aslo the season with the highest concentration of NO2 pollutants was found to be summer.