As sensor technologies rapidly evolve, they become more accessible for citizen scientist use; however, use of these sensors with incomplete understanding of their capabilities and limitations can result in data that may be unreliable due to operational biases. The key aim of this work is to deploy low-cost air quality sensors that provide high-quality data, resulting in better estimates of personal exposure to air pollutants. Specifically, this work will focus on traffic-related air pollution (TRAP), namely carbon monoxide, ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM). The project will be conducted through collaboration with a team of citizen scientists comprised of local high school students near Columbus, OH. Jointly, the citizen scientists and research team will develop training modules for teachers or other students in order to reach a broader audience at Hilliard City School District.
It is recognized that there are limitations of current technologies targeted for use in citizen science, the PIs' hypothesize that low-cost air quality sensors can be utilized by citizen scientists to provide reliable air quality data within micro-environments where they live, work and play. Initially, this will require careful guidance from the PIs, but in the future, limited oversight will be needed as training materials are developed. The PIs have developed a project plan with the following objectives: 1. Engage and recruit citizen scientists to fabricate and deploy a Wi-Fi-enabled, low-cost air quality sensor network, 2. Monitor ambient air quality with the sensor network in the Hilliard City School District in Franklin County, OH. 3. Develop and deploy a cloud-computing solution to provide publically-available, near-real-time air quality data based on this sensor network. 4. Develop outreach activities to engage high school students about local air quality within their neighborhoods where they live, play and go to school. The overall research plan is organized into a series of tasks. Task 1 is the fabrication of the air quality monitors by the citizen scientists, Task 2 is the use of these monitors to conduct outdoor air quality measurements as a sensor network, and, Task 3 is the interpretation and visualization of the data collected. This work will contribute to the development, refinement, and practical application of low-cost air pollution sensors with an emphasis on deployment of local sensor networks by citizen scientists. By providing a cloud-computing solution to process the data collected by the sensor network, the PI can account for biases and outliers, thus mitigating some of the concerns related to data reliability, validity, and trustworthiness. This project will benefit society while promoting teaching, training, and learning. The deployed network of air quality monitors will provided estimates of personal exposure to air pollution within key micro-environments in the Hilliard City School District in Hilliard, OH, thus enabling better practices for prevention or management of acute asthma exacerbation for district residents. This award received co-funding from CISE Directorate Big Data Hubs (BDHubs) Program.
