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

• Urban Rama IV-1 had notably higher PM 10 and PM 2.5 levels than suburban Chatuchot. • Light vehicles and light trucks contributed to PM 10 and PM 2.5 levels at Chatuchot. • Only light vehicles contributed to PM 10 level at Rama IV-1. • Wind speed, pressure, and BLH influenced PM levels only at Rama IV-1. 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 10 and PM 2.5 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 10 and PM 2.5 concentrations at Rama IV-1, averaging 52.22 ± 26.06 and 35.86 ± 22.20 μg/m 3 , respectively, were significantly higher than those at Chatuchot, averaging 42.26 ± 16.77 and 25.59 ± 9.64 μg/m 3 , 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 10 and PM 2.5 concentrations were significantly higher than the background levels at both sites ( p < 0.05). The average PM 2.5 /PM 10 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 10 and PM 2.5 concentrations were significantly correlated with light-duty trucks and passenger vehicles at Chatuchot, while only PM 10 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.