A chemometric analysis of the airbone heavy metals in selected location in Malaysia / Nor Najwa Syazwani Che Jaafar

The purpose of this research was to assess the content of heavy metals in four separate treated regions. These heavy metal contaminants were identified using a technique using the bark of the Jati tree (Tectona grandis). During the sampling, tree bark samples were gathered. These samples were taken from four distinct zones in four different treated locations. The rise of human activities, along with the limitations of particular technologies for detecting substances in the atmosphere, has led to the widespread use of methods such as biomonitoring, which involves the use of living creatures in the region as biomonitors. This biomonitoring method was used in this study, which included four study areas: Malaysian Cement Plant, Chuping, Perlis, Lafarge Cement Plant, Langkawi, Kedah, Penang Urban Area and Coal Power Plant Manjung in order to detect the heavy metal element present in the atmosphere, as the quality of air in the areas has drastically changed due to the increase of these activities, particularly industrial activities. All heavy metal contaminants were analysed using ICP-OES (inductively coupled plasma - optical emission spectrometry) (ICP-OES). This study was based on secondary data that surveyed public opinion on the variables that contribute to rising air pollution in the Penang Industrial Area, Malaysian Cement Plant, Chuping, Perlis, Lafarge Cement Plant, Langkawi, Kedah and the Manjung Coal Plant. The data was analysed in order to assess and identify heavy metal contaminants, as well as their levels of preference, which may be altered by the development of certain places. The instrument's output was then analysed utilising chemometric analysis, which included descriptive analysis, analysis of variance (ANOVA), cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA). These techniques are widely used when dealing with complex and large data, in which the techniques simplify the data into information that are easily to be understand.