Air Quality Assessment in Petaling Jaya Using Principal Component Analysis

Air pollution, a major environmental concern, negatively affects human health and the environment. In Malaysia, urban areas such as Petaling Jaya (PJ) in Selangor have suffered from increased air pollution due to heavy industrial activities, dense populations, and high vehicular traffic, which are particularly vulnerable. This study identified Selangor’s air quality trends using the Department of Environment (DOE) data. The monitoring station in PJ was selected based on six air pollutants (sulphur dioxide (SO2), particulate matter below 10 microns (PM10), ozone (O3), nitrogen dioxide (NO2), carbon monoxide (CO) and particulate matter below 2.5 microns (PM2.5) during three years from January 1, 2020, to December 31, 2022. This study aims to use the principal component analysis (PCA) method to classify the variables that predict the air pollution index (API) in PJ, Selangor. PCA was used to reduce dimensionality and identify significant pollutant predictors, with Bartlett’s test and KMO measure supporting data suitability and rotating PCA by reducing predictor variables. As a result, two principal components that highlighted PM10, PM2.5 and O3 as the most important pollutants in PJ were revealed after the PCA was rotated using varimax rotation. The finding could assist DOE management in identifying the types of pollutants responsible for air pollution.