Journal of Research in Atmospheric Science, vol.1, no.1, pp.42-48, 2019 (Refereed Journals of Other Institutions)
Environmental pollution problems have become more serious due to perceivable global climate change
effects in the 21st century. Air pollution is one of the major pollution problems like water pollution, soil
pollution. To protect people from fatal health diseases and extreme weather events as effects of air pollution,
many countries have been trying to reduce their own emissions in keeping with agreements such as Paris
Agreement, Kyoto Protocols. It is thought that remarking air pollution problems for Ankara in this study
would be so essential for Turkey due to its critical daily air quality index values and also creating enlarging
public awareness about air pollution. In this study, parameters like wind, pressure, temperature, humidity
and precipitation are used for changeable air pollution parameter values like PM10, SO2 and NO2. WRF
model was operated for 2017 and 2018 years by using global NOAA’s GDAS data with 9 km resolution.
Air pollution measurement data from the Ministry of Environment and Urbanization for six points in
Ankara and meteorological variables obtained from the WRF model were used to predict air quality for
Ankara. To train about the relationship between air pollution and meteorological variables, the machine
learning package H2O was used in the R software. The educated model was tested with last one month data
of 2018 and for the final step, the model performance rates and errors were obtained by RMSE (Root Mean
Square Error), MAE (Mean Absolute Error) and correlation values..