Multivariate analysis on trace elements of fine particulate matter (PM2. 5) in industrial and sub-urban area

S Shith - International Journal of Integrated Engineering, 2019 - penerbit.uthm.edu.my
International Journal of Integrated Engineering, 2019penerbit.uthm.edu.my
Study on fine particles (PM2. 5) and its effects towards health and environment has become
as main concerned of present study. Therefore, the study was conducted to identify PM2. 5,
tracking the elements and sources at industrial and sub-urban area. E-BAM was used to
measure the concentration of PM2. 5 and meteorological parameters during sampling. The
PM2. 5 samples were analyzed to identify elements using inductively coupled plasma-
optical emission spectrometry (ICP-OES). PM2. 5 concentrations were higher in industrial …
Study on fine particles (PM2.5) and its effects towards health and environment has become as main concerned of present study. Therefore, the study was conducted to identify PM2.5, tracking the elements and sources at industrial and sub-urban area. E-BAM was used to measure the concentration of PM2.5 and meteorological parameters during sampling. The PM2.5 samples were analyzed to identify elements using inductively coupled plasma - optical emission spectrometry (ICP-OES). PM2.5 concentrations were higher in industrial site (46.00 μg m-3) compared to sub-urban site (16.67 μg m-3), due to anthropogenic sources which were factories and major roads that located nearby study area. From PM2.5 samples analysis, it showed that Al, K, and Ca elements were the highest average among 13 elements measured in PM2.5 at both sites.  Finally, based on PCA analysis, it showed that three main component groups had been identified: Na, Al, K, Ca, Ti, Sr, Cr and Mg can be associated with natural sources, Mn, Fe, Ni and Zn sources were linked to industrial activity sources, while Pb had been identified as a vehicle source for each area. In conclusion, the concentration of PM2.5 and its elements in different locations provide different readings which depending on the sources of PM2.5 at site. The finding from this study can assist local authorities to monitor and predict the highest concentration of PM2.5 in problematic areas.
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