Nivar

Nivar

Investigating the CAMS model ability to predict the concentration of PM10, PM2.5, and NO2 pollutants in Tehran (3 case studies)

Document Type : Original Article

Authors
1 RIMAS
2 RIMAS, Atmospheric Hazard Forecasting group
Abstract
In recent years, air pollution has become a major problem in industrial cities around the world. issuing timely warnings as a result of accurate prediction of pollutant concentrations in metropolitan areas can greatly reduce the damage caused by air pollution. In this study, three cases of air pollution caused by PM10, PM2.5 and NO2 pollutants in Tehran were investigated and the output of the CAMS model in predicting the concentrations of these pollutants was compared with observational data. For this purpose, data from the Mehrabad Airport Synoptic Station, ERA5 reanalysis data and air pollution data from air quality monitoring stations in Tehran were used. Comparison of time series of pollutant concentration, horizontal visibility and relative humidity (RH) showed that in the case of PM10 pollution, no relationship was observed between pollutant concentration and RH. In the case of PM2.5 and NO2 pollutions, it can be said to some extent that RH had an inverse relationship with horizontal visibility and a direct relationship with concentration. Based on synoptic analysis, during the PM10 case study, a thermal low pressure was located on the Iranian plateau, but in the cases of PM2.5 and NO2, high pressure patterns prevailed in the region and the 10-meter wind was weak. Comparing the 24-hour forecast of the CAMS model with the pollutant concentration map obtained from air pollution monitoring stations in Tehran showed that the model had a large underestimation in estimating the concentration value. The highest underestimation was related to PM10 pollutant and the lowest was related to NO2.
Keywords
Subjects

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  • Receive Date 08 April 2025
  • Revise Date 07 June 2025
  • Accept Date 04 August 2025
  • Publish Date 23 September 2025