Özet:

Abstract enAir pollution is a problem that accumulates with urbanization and threatens human health. The quality of the air we breathe is more important for the cities like İstanbul, having the busiest traffic flow and highest population in Turkey. In this work, in order to measure the air quality of İstanbul, the trend of air quality data will be estimated. Turkey, according to the data of Environment Performance Index 2014 prepared by Yale University, is listed low especially on air quality. In accordance with the agreements signed with the European Union the environmental indicators and thus our air quality should be improved. For this reason, in order to reduce air pollution a program is prepared and an Air Quality Index is formed Turkey-wide. Also in İstanbul, via many stations the air pollutants are being monitored. To increase the air quality, it is necessary to monitor the change within time of these pollutants and estimate their trend. However, the pollutants listed in the air quality index, as in all the environmental data, is a data that consists outliers and missing observations, asymmetrical, seasonal, serial dependent, do not fit the normal distribution. As of these properties, the trend analysis of the air pollutants are done via tests that are nonparametric In detecting the existence of a trend in the air quality data carrying seasonal effect the Seasonal Kendall Test is being used.In this study the trend of air pollutants for İstanbul is tested via the monthly data gathered through 2005-2014 from different monitoring stations established by the İstanbul Metropolitan Municipality,. Among the pollutants especially in SO2 emission, in all monitoring stations, statistically significant negative seasonal trend is seen. CO emission is also determined to be in decrease. However PM10 and NO2 emissions are determined to be increasing in some stations. Besides, the homogeneity testing of pollutants between seasons and stations is also performed. According to this test, SO2 has a homogeneous trend between stations and seasons.

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