Assessing Diurnal and Spatial Variations of PM2.5 in Urban Environments: A Case Study with Low-Cost Sensors in an Environmental Justice Community

Air Monitoring, Methods, and Technology
Oral Presentation

Prepared by I. Han
Temple University College of Public Health, 1301 Cecil B. Moore Avenue, #907, Philadelphia, Pennsylvania, 19122, United States


Contact Information: [email protected]; 215-204-4766

ABSTRACT

Given established association between ambient air particulate matter (PM) and adverse health effects, evaluating community exposures to ambient air PM have drawn attention to community members. Applications of low-cost particulate matter sensors (LCPMS) have been a citizen science tool to monitor ambient PM in locally and temporarily. In this pilot study, a LCPMS, Dylos DC1700 was employed to assess the diurnal and spatial variation of ambient air PM2.5 within a low-income residential community of Galena Park, Texas. Ambient air PM2.5 were measured at six different locations for 20 days. Of six locations, three locations were < 500 meters to a major road and an industrial zone whereas the other three locations were > 500 meters from these sources. Meteorological parameters were also recorded during the sampling days. After field-based calibration efforts, the overall mean PM2.5 mass was 12.3 ± 7.3 µg/m3 (Range: 1.9 – 48.4 µg/m3). A multiple linear regression confirmed that time of day, wind direction, and windspeed were significant variables for ambient air PM2.5 within Galena Park. Mean ambient air PM2.5 mass was 56% greater in the mornings (15.0 ± 7.6 µg/m3) compared with the evenings (9.6 ± 6.0 µg/m3, p<0.01). Additionally, when windspeed was >2m/s, the predicted ambient air PM2.5 during downwind period was 30.5 µg/m3 greater than during upwind period. Due to the easiness of use and deployment, the Dylos DC1700 or other LCPMS could be applied to assess community exposure to PM2.5. Citizen scientists or residents can easily and frequently use the LCPMS to evaluate short-term and long-term spatial and temporal variations of PM in their communities, particularly in areas where central air monitoring stations are not present. Such information is valuable because susceptible individuals and the community members can develop and implement personalized strategies to avoid exposure during the peak, transient, or long-term periods.