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

Particulate matter with an aerodynamic diameter of 2.5 µm or less (PM<sub>2.5</sub>) 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<sub>2.5</sub> monitoring in an Asian community, evaluating temporospatial variations, hotspots, and emission sources. The hourly mean PM<sub>2.5</sub> concentrations from December 2017 to July 2021 were 24.3 ± 14.1 µg/m<sup>3</sup>. PM<sub>2.5</sub> 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<sub>2.5</sub> 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.

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Publication Details

Journal
Environmental Monitoring and Assessment
Published
2025-05-14
DOI
https://doi.org/10.1007/s10661-025-14098-z
Citations
2
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
1.60

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article

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

Shih‐Chun Candice Lung, Ming‐Chien Mark Tsou, Liu Chun-hu, Li-Te Chang et al.
2 citations
Environmental Monitoring and Assessment
Air Quality Monitoring and Forecasting
1.60
article

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

Shih‐Chun Candice Lung, Ming‐Chien Mark Tsou, Liu Chun-hu, Li-Te Chang, Tzu-Yao Julia Wen, Tzu-Chi Chieh
article en
2 citations

Abstract

Particulate matter with an aerodynamic diameter of 2.5 µm or less (PM<sub>2.5</sub>) 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<sub>2.5</sub> monitoring in an Asian community, evaluating temporospatial variations, hotspots, and emission sources. The hourly mean PM<sub>2.5</sub> concentrations from December 2017 to July 2021 were 24.3 ± 14.1 µg/m<sup>3</sup>. PM<sub>2.5</sub> 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<sub>2.5</sub> 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.

Environmental Monitoring and AssessmentVol. 197(6)
Research Center for Environmental Changes, Academia Sinica (TW), Feng Chia University (TW)
Academia Sinica, National Science and Technology Council
Openalex Percentile: Top 18%
Air Quality Monitoring and Forecasting
1.60
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