Long-term monitoring of particulate matter in an Asian community using research-grade low-cost sensors

Abstract

Particulate matter with an aerodynamic diameter of 2.5 µm or less (PM_2.5) poses significant health risks, necessitating comprehensive exposure assessment. Long-term community monitoring can provide representative exposure levels for environmental epidemiological studies. This study deployed nine research-grade low-cost sensors (AS-LUNG-O) for 3.5 years of street-level PM_2.5 monitoring in an Asian community, evaluating temporospatial variations, hotspots, and emission sources. The hourly mean PM_2.5 concentrations from December 2017 to July 2021 were 24.3 ± 14.1 µg/m³. PM_2.5 levels were typically higher in winter, on weekends, and during religious events compared to summer, weekdays, and typical days, with some peak concentrations occurring randomly. Daytime PM_2.5 levels generally exceeded nighttime background levels by 30–50%, with certain religious activities causing up to 80% increases. Spatial analysis identified temples and markets as pollution hotspots. Using a generalized additive mixed model, we found that the COVID-19 pandemic shutdown and higher wind speeds negatively impacted PM concentrations. Religious events, traffic, and vendors were significant PM sources, continually influencing community air quality throughout the 3.5-year monitoring period. This study demonstrates the value of long-term PM monitoring in capturing unexpected peaks, identifying critical sources, and revealing intricate temporospatial distributions. Research-grade low-cost sensor networks complement traditional monitoring stations by facilitating source identification in targeted communities and providing representative PM exposure data for long-term environmental epidemiological research.