Urban PM2.5 pollution dynamics in Petaling Jaya, Malaysia: a temporal approach

Abstract

In 2021, Malaysia experienced a 25% increase in fine particulate matter (PM2.5) concentrations compared to 2020. During this period, Petaling Jaya was recognised as one of the most polluted cities in the country. The study intended to investigate the dynamics of daily average concentrations of particulate matter smaller than 2.5 micrometres (PM2.5) and other air pollutants with notable significant levels in 2021 in Petaling Jaya, Malaysia, for the year 2021 relative to the levels in 2020. To achieve this, an autoregressive distributed lag (ARDL) model was employed. Results from the paired sample t-test indicated sulphur dioxide (SO2) as having significantly higher concentrations in 2021 compared to 2020. The ARDL bound test established a long-term association between SO2 and PM2.5. The Augmented Dickey (ADF) unit root test supported the suitability of the ARDL model by demonstrating variable integration at different levels. The ARDL model analysis revealed that SO2 had a significant long-term negative impact on PM2.5, while exhibiting a significant effect in the short term. An adjustment speed of 34% indicated that the system could rectify approximately one-third of any deviation from the long-term equilibrium between SO2 and PM2.5, one day following a disturbance. Various reasons could be cited for the discrepancies in model performance across different time frames and pollutants, such as seasonal fluctuations, changes in human activities, adjustments to regulations, and external influences. This study provides crucial insights into the dynamic interactions between air pollutants and contributes to more effective air quality management strategies.