MULTIPLE LINEAR REGRESSION AND INVERSE DISTANCE WEIGHT (IDW) INTERPOLATION FOR SPATIAL ANALYSIS OF PM10 AND SO2 IN BURSA CITY, TURKEY

Air pollution is one of the most significant environmental problems in Bursa city. The aim of this paper is to investigate the spatial distribution of air pollutants such as sulfur dioxide (SO2) and particulate matter (PM10) by using IDW interpolation method and influence of meteorological conditions on the levels of air pollution based on seasonality data collected from online website during the period summer 2014 to winter 2017. Then comparing the results with Turkish Air Pollution standards, where PM10 concentration levels at most stations in two seasons are above the permissible limit as 48 mu g/m(3), while SO2 concentration is lower than the Turkish standards (20 mu g/m(3)) in most stations. Lastly, the main relationships were used to obtain a multiple linear regression equation linking PM10 and SO2 concentrations in summer and winter with meteorological parameters. Climatic variables also influenced as negative and positive on the PM10 and SO2 concentrations, differ from season to another as shown in the Table 1. Where best correlation between the pollutant concentration and meteorological parameters happened in the summer 2015 for PM10 (R-2 = 0.43) and in summer 2014 for SO2 (R-2 = 0.48).