Analysis and zoning of air pollution in urban landscape using different models of spatial analysis (Case study: Tehran)

Document Type: Research Paper


1 Faculty of Agriculture and Natural Resources, Lorestan University, Iran

2 Faculty of Environment, College of Engineering, University of Tehran, Iran


In this study, spatial zoning models were compared to evaluate the concentrations of PM 2.5 on a large scale in the urban landscape of Tehran. The spatial analysis of PM 2.5 concentration was conducted based on the data from twenty-four stations that measure and monitor the air in Tehran. Three interpolation models were used to assess the air pollution status via Arc GIS 10.6.1 software: universal kriging (UK), ordinary kriging (OK), and inverse distance weighted (IDW). The root mean square error (RMSE) and correlation coefficient (R2) were applied to compare the spatial models and select the best model. Standardized root-mean-square error (RMSE) was used to select the best conditions for running the OK and UK models. The results showed that the southern and central regions of Tehran had high concentrations of PM 2.5, and the annual mean of all the stations exceeded the EPA standard (15 μ/m3). According to the annual average, station 16 had the highest concentration of PM2.5 (112.75 μ/m3). The results of RMSE showed that the OK model was more suitable than the others for the spatial zoning of air pollution in the urban landscape (RMSE=9.322).


Main Subjects

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