Spatial modelling of PM2.5 concentrations in Tehran using Kriging and inverse distance weighting (IDW) methods

  • Kazhal Masroor
  • Farzad Fanaei
  • Somayeh Yousefi
  • Mohammad Raeesi
  • Hossein Abbaslou
  • Abbas Shahsavani
  • Mostafa Hadei
Keywords: Exposure; Interpolation; Particulate matter; Ambient air pollution; GIS


Introduction: Estimating air pollution levels in areas with no measurements is a major concern in health-related studies. Therefore, the aim of this study was to investigate the amount of exposure to particulate matter below 2.5 µ (PM2.5) in the metropolis of Tehran.

Materials and methods: The hourly concentrations of PM2.5  during 2017-2018 period were acquired from the Department of Environment (DOE) and Air Quality Control Company of Tehran (AQCC). The hourly concentrations were validated and 24-h concentrations were calculated. Inverse distance weighting (IDW), Universal Kriging, and Ordinary Kriging were used to spa- tially model the PM2.5  over Tehran metropolis area. Root Mean Square Error (RMSE) and Mean Error (ME) were used to measure and control for the  ac- curacy of the methods.

Results: The results of this study showed that RMSE and MENA values in Kriging method was less than the IDW, which indicates that the Kriging was the best method to estimate PM2.5 concentrations. According to the final map, the highest annual concentrations of PM2.5 were observed in the southern and southwestern areas of Tehran (districts 10, 15, 16, 17, and 18). The lowest exposure to PM2.5 was found to be in districts 1, 2, 3, 6, and 8.

Conclusion: It can be concluded that Kriging method can predict spatial vari- ations of PM2.5 more accurately than IDW method.