Preparation of PM2.5 Pollution Hazard Map of Tehran Using Ordered Weighted Averaging Algorithm

Document Type : Applied Article


School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran



PM2.5 pollution is one of the critical environmental problems that occurs after industrialization and the increase in the population of cities. Information about pollutant concentration, including PM2.5 pollutants, significantly impacts how city managers make decisions to improve cities' health. This study used the ordered weighted averaging (OWA) technique to produce PM2.5 pollutant zonation. For this purpose, meteorological information layers include wind speed, maximum temperature, minimum temperature, average temperature, 24-hour precipitation and humidity, normalized vegetation difference index layers (NDVI), and road density are used. The gradient descent algorithm has been used to calculate the weights related to the order of the values to apply the OWA algorithm. The optimal learning rate parameter has been obtained to achieve the optimal value of the weights. Also, the layers of information were combined based on the obtained weights from OWA. Finally, the RMSE index was used to evaluate the obtained results, and the PM2.5 pollutant estimated for the summer and winter seasons had the lowest and highest errors, respectively. The error values for these two seasons were 0.129 and 0.190, respectively. Also, Aqdasiyeh station had the lowest error in all seasons, and Golberg, Region 11, and Shahr-e-ray stations had the highest error.


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