ESTIMATION OF PM10 USING SPATIAL INTERPOLATION TECHNIQUES

Abstract

Air pollution, especially the haze problem caused by the accumulation of smoke and dust in the air is another important problem in Thailand. Especially at present, this issue has become increasingly serious respectively. This study aimed to study the relationship between Particulate Matter (PM10) content in the southern region and the physical factors of the area and to assess PM10 quantity by Spatial Interpolation Techniques, as well as to study the suitability of each method. The results of the study found that the 24-hour mean of the three-year average PM10 intake between 2017 to 2019 was the highest in February, with the mean concentration from all measuring stations of 36 µg/m³. It was followed by March, July, and January. The smallest concentration was in October. When analyzing the physical characteristics of the area with high levels of fine dust, it was found that the southern region was characterized by a sharp topography or the land extending into the sea, which was influenced by the southwest monsoon at the south into western Thailand was a major factor in getting dust from wildfires and burning in the open air that was carried by winds from many places, including neighboring countries. Using mean PM10 data from six Pollution Control Department (PCD) measuring stations, PM10 was assessed by Spatial Interpolation Techniques method using four different methods: Inverse Distance Weighting (IDW), Kriging, Spline, and Trend, it was found that Trend method was the most suitable method for map that showed the distribution of PM10 concentration data, especially from January to April with the highest particulate matter.