Abstract
The current well-being of the general population is significantly affected by air pollution. Notably, particulate matter measuring 2.5 µm or less in diameter (PM2.5) is a primary concern due to its ability to infiltrate the respiratory system thoroughly. Therefore, this study investigated the temporal correlations between the 2021 PM2.5 levels in Klang Valley, Malaysia, using a vector auto-regressive model (VAR). The methodology in this study also involved examining the dynamics of the daily average PM2.5 levels within the same year by utilizing two approaches: variance decomposition and impulse response function (IRF). Consequently, the primary factor responsible for the PM2.5 level variations was the self-contribution of PM2.5, accounting for approximately 80.94% of the total variations. Other contributions produced negligible effects on PM2.5 levels over long periods, including wind speed (WS, 3.55%), humidity (Hum., 3.23%), and carbon monoxide (CO, 1.47%). A rapid decrease in PM2.5 levels was observed based on one standard deviation (SD) shock in PM2.5. Meanwhile, lower PM2.5 levels were reported due to temperature (Temp.) with Hum. disturbances, whereas the constant CO disturbances appeared throughout the observed period. In contrast, higher PM2.5 levels were correlated with NO2 disturbances. This observation was attributed to ground level O3, WS, and wind direction (WD) fluctuations, occasionally generating temporary declines lasting up to five days. Overall, the PM2.5-based air pollution in Klang Valley could be addressed in this study by emphasizing the significance of implementing specific measures. The relevance of policies prioritizing local emission sources and promoting efficient pollution management techniques should be highlighted.