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Assessment of air pollutants spatial trends in Penuelas, Puerto Rico using low cost air quality sensors
Citation:
Reece, S., N. Feinberg, R. Williams, M. Colon, A. Iglesias, E. Huertas, M. OShea, P. Sheridan, AND D. Southgate. Assessment of air pollutants spatial trends in Penuelas, Puerto Rico using low cost air quality sensors. 2018 Air Sensors International Conference, Oakland, CA, September 12 - 14, 2018.
Impact/Purpose:
Poster provides a general summary of EPA activities concerning air quality monitoring using low cost sensors in support of Region 2 and citizen science. Presentation will highlight ORD cooperation with EPA Region 2 scientific interests and air quality monitoring interests of Puerto Rico-based community group (DISUR).
Description:
A citizen science led effort conducted between October 2016–February 2017 collected real-time measurements of the particulate matter size fraction 2.5 micron (PM2.5), total volatile organic compounds (tVOCs), and nitrogen dioxide (NO2) across eight locations in the south area of Puerto Rico (Tallaboa-Encarnación, Peñuelas) with little historical data on pollutant spatial variability. Pollutant concentrations were measured at 5-minute intervals using the EPA developed Citizen Science Air Monitor (CSAM), a package of low-cost (<$2,500) original equipment manufacturer (OEM) sensors. In addition to the CSAMs, meteorological parameters (wind speed, wind directions, temperature, relative humidity) were obtained from four collocated Vantage Vue weather stations. The 1-hour averaged concentrations for the PM2.5, tVOC, and NO2 sensors ranged between 0.3-136.2 µg/m3 , 0.9-1220.2 ppb, and 0.9-50.6 ppb, respectfully. Evaluation of the weather stations indicated winds were active (wind speeds ≥2 mph) between 17%-51% of the deployment, predominantly from the east-southeast direction. Initial comparisons of 1-hour averaged pollutant concentrations and meteorological parameters observed pollutant concentrations change with local wind directions indicating unique micro-environments across locations. Supplemental analysis will use wind-based receptor models and local 5-minute weather data from Weather Underground to calculate local back-trajectories to assess the impact of local sources.
