A versatile low-cost platform for particulate matter, volatile organic compound, and noise monitoring

Abstract

Millions of people die prematurely each year from exposure to air pollution and other environmental hazards, and many more experience chronic disease. Mortality, morbidity, and other key indicators of adverse health are typically analyzed for large populations using city-, county-, or census track-level exposure data. A more local, or ideally, an individual-level understanding of human exposures would reduce uncertainty significantly and provide more actionable data. With the advent of affordable microelectronics, low-cost instruments for air quality and environmental monitoring are becoming increasingly common and more accessible to the public, but the data-quality gap between reference-grade monitors and low-cost alternatives is substantial. Combining the data-quality standards of reference-grade monitors with the accessibility of new consumer electronics would advance the state-of-the-art in environmental monitoring. This work describes the development and validation of a platform to monitor and collect particle and gas pollutants, and other environmental factors, at a lower cost than established technologies, while preserving the rigor and data-quality objectives associated with reference-grade methods. We developed a platform based on the AirPen, a low-cost monitor for assessing personal exposure to particulate matter and volatile organic compounds. Variations of the platform with different form factors, sensors, and sampling media compatibility were designed, and then tested in the field. Our platform implemented previously validated methods such as NIOSH method 0500 for total particulate matter and EPA method TO-11A for carbonyls. The sampling throughputs achieved in two field studies were considerably higher (5x – 10x) than those typically achieved with conventional instruments within similar timeframes and populations. The spatial and temporal coverage of our results revealed insights on exposure that could be missed by more sparse monitoring. Results from this work demonstrate that new technology can bridge the data-quality gap and address the barriers of entry (e.g., cost, ease of use), to complement the limited regulatory (reference-grade) monitoring efforts currently in place.