Modeling the concentration distribution of NO2 and O3 pollutants with an appropriate spatial resolution by combining ground and satellite data.

Document Type : Original Article

Authors

1 دانشجو

2 Department of Geomatics, Faculty of Civil and Transportation Engineering, University of Isfahan, Isfahan, Iran

Abstract

Air pollution is one of the most important crises that most countries are facing today due to the progress of industry and technology. The country of Iran and especially the city of Tehran is not exempt from this phenomenon. Air pollution measurement stations at city level, in spite of the high accuracy of the measurement of pollutants, are not generalizable due to time and place limits and point measurement. A complementary and sometimes alternative solution is the use of remote sensing and satellite data, which is a suitable method for monitoring air pollution due to the optimal cost and wide coverage. Nitrogen dioxide (NO2) and ozone (O3) pollutants are among the most important indicators of air pollution. In this research, an effort will be made to model the distribution of their concentration in the city of Tehran with the same spatial resolution (almost one kilometer) and higher accuracy than satellite data. For this purpose, the concentration distribution of these two pollutants has been modeled by using an innovative method based on the kriging interpolation method and simultaneous use of pollution measurement station data and high spatial resolution of Sentinel 5P satellite data. In order to evaluate the results, air pollution measurement station data were used, and the average monthly error of this model has decreased from 16.8 to 1.73% for NO2 pollutants and from 21.9 to 2.53% for O3 pollutants compared to the data of the Sentinel 5P satellite. Also, the root mean square error (RMSE) of this model for NO2 and O3 pollutants is equal to 2.79 ppb and 0.86 ppb, respectively, which shows the proper performance of this model in modeling the concentration distribution of pollutants.

Keywords

Iranian Journal of Remote Sensing & GIS

Articles in Press, Accepted Manuscript
Available Online from 24 July 2023

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