The approach to adjusting commercial PM2.5 sensors with a filter-based gravimetric method

Abstract

The measurements of temporal change to indoor contaminant concentrations are critical to understanding pollution characteristics. As commercial sensors are becoming increasingly commonplace, concentration accuracy is still a critical issue. The most common methods for measuring indoor particulate pollutants based on filter-based gravimetric methods. However, the gravimetric method is expensive, time-consuming, and often provides little temporal information. More and more commercial sensors are utilized to collect larger and temporal information about indoor air pollutants. Nevertheless, limited data support the accuracy of commercial sensors so far. Thus, this study aims to evaluate the performance of commercial sensors. PM2.5 were collected for 30 days by personal environmental monitors with an airflow of 2 L/min on 37-mm Teflon filters and commercial sensors, simultaneously in a three-story house. Moreover, the intra-sensor comparison was conducted for 24 hours by the resolution in 1 minute. Finally, the linear regression model was built to adjust commercial sensors. The intra-sensor comparison results revealed that 24 hours average coefficient of variation (CV value) of PM2.5 in this study were under 10% and the R2 of the adjusted equation was 0.9394. We provide an accurate concentration of commercial sensors to estimate the association between pollutants exposure and health.