Abstract
The conditions of the weather have an effect on both the amount of emissions and the quality of the air. A change in meteorological conditions has a substantial effect on particulate matter (PM) levels. In this study, we will first use statistics and wavelet calculations to look at the links between particulate matter (PM10 and PM2.5) and relative humidity (RH). RH influences the natural deposition of PM concentrations. Then, we’ll examine how wind direction (WD) and wind speed (WS) affect PM. The results show that both PM10 and PM2.5 are high in February and that July and August have the lowest levels. In contrast, RH is low in February and maximum in October. Whenever the RH increases, the PM concentration decreases, and vice versa. The correlation coefficients between PM10 and RH are 0.3433 during the winter, 0.7181 during the summer, and 0.0052 during the rainy season. This illustrates the significant seasonal correlation between PM and RH. The results from wavelet coherence analysis indicate that PM and RH have close negative correlations. Significantly high wavelet power in the 8–30 day waveband exists in winter each year in the observed time horizon. There is also another common power found throughout the spectrum. PM and RH in these wavebands are out of phase with one another, with RH slightly leading PM. Moreover, the WS and WD also have an effect on PM concentration. If the wind speed is high and exceeds a specific threshold, the wind will take PM away, causing the PM concentration to decrease. In February 2023, the NE and NNE winds carried the most PM into the Bangkok region, followed with less concentration, by the WSW, SW, and W winds. Since PM is one of the primary air contaminants that has been linked to a deterioration in human health, it is extremely important to have a solid understanding of how PM concentrations change over time.
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