Abstract
The relationship between PM2.5 pollutant distribution and urbanization, population and meteorological factors has been investigated using geographic information system (GIS) as an analysis tool. The study is focused on how the variation of PM2.5 in year 2016 and 2019 and also the factors that contribute to the PM2.5 distribution in Malaysia. The main objective of this study was to analyze the spatial variability of the pollutants by taking Peninsular Malaysia as a study area that consists of 47 monitoring station, and focus on the study area for factors that contribute to the pollutants in Selangor as a case study, by identifying the area of high concentration of PM2.5 pollutants and their relationship with urbanization, population and meteorological factors. A correlation test was performed to establish the relationship between PM2.5 pollutants, urban area, population density and temperature in Selangor station. Land use map was generated using remote sensing tool, Erdas Imagine, which performs land use classification by identifying the urbanization in study area. The main finding of this study is the comparison between spatial and non-spatial analysis approaches, which indicated that the correlation analysis and the inversed distance weighted analysis using the average of level of PM2.5 pollutants by group of few monitoring stations are relatively suitable methods for assessing the health effect of PM2.5 pollutants distribution.
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Talib, N., Sallehuddin, N.S.M., Sa’aid, N.A.M., Saad, N.M. (2020). PM2.5 Pollutant Distributions in Years 2016 and 2019 Using GIS Spatial Analyst. In: Alias, N., Yusof, R. (eds) Charting the Sustainable Future of ASEAN in Science and Technology . Springer, Singapore. https://doi.org/10.1007/978-981-15-3434-8_15
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DOI: https://doi.org/10.1007/978-981-15-3434-8_15
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