Utilizing Low-Cost Clarity Node S Sensors Network to Monitor Local PM Concentrations in Lubbock, TX

KARIN ARDON-DRYER, John Garber, Joshua Shankles, Adam Hernandez, Department of Geosciences, Texas Tech University

     Abstract Number: 78
     Working Group: Aerosol Exposure

Abstract
Measurement of particulate matter (PM) and the establishment of a sensor network are important to ensure improved air quality levels and living conditions. A recent study in Lubbock, TX, suggests that several neighborhoods, especially those near industrial areas, experience increased health problems likely due to elevated PM concentrations from nearby industrial sources. Currently, no sensor network exists to measure local PM concentrations, as only one official PM2.5 monitor is situated within city limits. However, the sensor is located at the edge of town, far from residential areas.

This work is part of the Lubbock Environmental Action Plan (LEAP) for Communities project that aims to provide information on air quality across the city. The Clarity Node S sensor was selected for this project. The Clarity Node S is a low-cost sensor that holds a built-in solar panel and SIM card port, which allows the sensors to be operated without a direct power source and Wi-Fi. At first, the 42 sensors were collocated with a reference Grimm EDM-180 for an initial period. The Clarity Node S sensors demonstrated very good correlation with each other, with R2 values above 0.9. The 42 Clarity Node S sensors were calibrated to the EDM-180 and were distributed across the city of Lubbock to create a spatial and temporal network for PM2.5 and PM10 (particles with a diameter smaller than 2.5 and 10µm, respectively). Once the sensors were deployed, analysis was performed on each sensor to identify if specific neighborhoods experienced higher pollution levels. Such information will be a critical first step to improving the air quality in these specific neighborhoods and provide awareness of the effects of PM on human health. Comparison between the sensors and identification of polluted neighborhoods will be presented.