Analysis on PM2.5 pollutant distribution in 2016 and 2019 by using GIS spatial analyst : a case study in Selangor / Nur Syahirah Mohamad Sallehuddin

In this thesis, the relationship between PM2.5 pollutant distribution with urbanization, population and meteorological factor has been investigated utilising Geographic Information System (GIS) as an analysis tool. The research focused on how the variation of PM2.5 from 2016 to 2019 and the factor that gives the contribution to the PM2.5 distribution in Malaysia. The main objective of this study was to analyse the spatial variability of the pollutants, taking Peninsular Malaysia that consist with 47 monitoring station as a study area and the focus study area on factor that contribute to the pollutants in Selangor as a case study, by identification of the area of high concentration of PM2.5 pollutants and their relationship with urbanization, population and meteorological factor. A correlation test was performing to establish the relationship between PM2.5 pollutants, urban area, population density, and temperature in Selangor station. Landuse was generated using remote sensing tool which is Erdas Imagine to perform landuse classification in identifying the urbanization area in study area. GIS was utilized to investigate the spatial distribution of the PM2.5 pollutants. The main finding of this research is the comparison between spatial and non-spatial analysis approaches, which indicated that correlation analysis and Inversed Distance Weighted analysis using the average of level of PM2.5 pollutants by group of few monitoring stations is a relatively a suitable method for assessing the health effect of PM2.5 Pollutants distribution. There was a significant positive correlation between variable under consideration, and the research show a decreasing trends of concentration of PM2.5 pollutants in Malaysia and increasing trends at Selangor. The statistical analysis show that there exist a positive relationship between the level of PM2.5 pollutants with urbanization and temperature but the population are more to strong positive relationship as certain section due to the population are more vulnerable to the exposure.