Determination of the best interpolation method in estimating the concentration of environmental air pollutants in Tehran city in 2015

Introduction: Air pollution is one of the important issues in developing countries, due to increased population and industrialization. In this research, the spatial distribution of ambient air concentration such as CO, NO2, SO2, PM2.5, PM10, O3 and Air quality Index (AQI) in Tehran city in 2015 were evaluated using different deterministic ( inverse distance weighted, local polynomial, global polynomial, radial basis functions) and geostatistical (Kriging, Cokriging) methods. Materials and methods: Root Mean Square Error (RMSE) and Mean Error (ME) using cross-evaluation methods were used to control the accuracy of the interpolation. To find the secondary variables in the cokriging method, the Pearson coefficient of each pollutant was calculated with another pollutant. Results: The Kolmogorov-Smirnov test showed that all data followed normal distribution. Also the results indicated that in most cases, geostatistical methods were the best methods to estimate ambient air concentration. Finally, after selecting the best interpolation method, the zoning map of the pollutant was drawn with ArcGIS. Conclusion: The results of 71 methods showed that in most cases, the geostatistical method is better than the deterministic method.