Poor air quality is linked to numerous adverse health effects, including heart attacks and premature death. Microclimates of poor air quality can occur in areas with concentrated vehicle emissions, such as pickup/drop off zones. Air quality monitoring in these microclimates can provide helpful insight about environmental, health, and safety concerns. However, these monitors can be costly and require specialized training. The purpose of this research is to characterize low-cost sensor performance with an emphasis on identifying emissions from idling vehicles. Specifically, we examined inter-sensor variability and the effects of temperature and relative humidity on the Alphasense CO-B4 carbon monoxide (CO) sensors. We designed and conducted laboratory testing to analyze each sensor's response to varying levels of carbon monoxide concentration, as well as atmospherically relevant temperatures and relative humidity levels. We found that there was low inter-sensor variability among twelve sensors. The average R-squared value from our linear regression of all sensors versus a reference measurement of carbon monoxide was 0.933. The average root mean square error (RMSE) was 118,979 microVolts. We also found that the temperature and relative humidity both affected sensor readings (in microVolts) and adding these two parameters improved the linear regression fit of the low-cost CO sensors compared to reference CO measurements. This research shows that we can measure CO concentration relatively accurately at $138 per sensor. Cost effective, accurate air quality measurements can allow individuals, communities, and policy makers to make informed decisions about exposure levels.
University / Institution: University of Utah
Format: In Person
SESSION D (3:30-5:00PM)
Area of Research: Engineering
Faculty Mentor: Kerry Kelly