Influence of traffic volumes and meteorological conditions on particulate matter levels at highway toll stations: A case study in inner and outer Bangkok, Thailand

Abstract

Particulate matter (PM) serves as a widely recognized proxy indicator for air pollution, with vehicle emissions being a major contributing factor. This study assessed the influence of traffic emissions and meteorological conditions on PM<inf>10</inf>and PM<inf>2.5</inf>at highway toll stations in Bangkok, including Chatuchot (outer) and Rama IV-1 (inner), using low-cost air quality monitoring sensors. The results revealed that the PM<inf>10</inf>and PM<inf>2.5</inf>concentrations at Rama IV-1, averaging 52.22 ± 26.06 and 35.86 ± 22.20 μg/m³, respectively, were significantly higher than those at Chatuchot, averaging 42.26 ± 16.77 and 25.59 ± 9.64 μg/m³, respectively (p < 0.05). At Rama IV-1, average PM concentrations during weekdays were significantly higher than weekends (p < 0.05), while the opposite trend was observed at Chatuchot. The average PM<inf>10</inf>and PM<inf>2.5</inf>concentrations were significantly higher than the background levels at both sites (p < 0.05). The average PM<inf>2.5</inf>/PM<inf>10</inf>ratio across both stations was 0.64 ± 0.10. The LULC map revealed that built-up areas accounted for 98.91 % and 64.06 % of total areas at Rama IV-1 and Chatuchot, respectively. PM<inf>10</inf>and PM<inf>2.5</inf>concentrations were significantly correlated with light-duty trucks and passenger vehicles at Chatuchot, while only PM<inf>10</inf>was significantly correlated with passenger vehicles at Rama IV-1. Temperature and relative humidity were primarily linked to PM concentration at Chatuchot, whereas additional influences of wind speed, pressure, and boundary layer height were observed at Rama IV-1. The study provides a baseline understanding of site-specific interactions between PM concentrations, traffic density, and meteorological conditions, but further research is needed to strengthen the evidence base for developing effective policy decisions.