Retrieval of bulk hygroscopicity from PurpleAir PM_2.5 sensor measurements

Abstract

PurpleAir sensors offer a unique opportunity for a large-scale and densely populated array of sensors to study surface air quality. While PurpleAir sensors are inexpensive and abundant, they must be corrected to better agree with validated coincident measurements from more sophisticated instrumentation. Traditionally, this correction is performed using statistical methods. We propose a method to both correct PurpleAir PM2.5 measurements and allow for an estimate of the hygroscopic growth of aerosols, using a novel correction approach based on the optimal estimation method (OEM). The hygroscopic growth of aerosols can be retrieved using the sensitivity of the correction to water activity, which influences the measured size distribution of the aerosols. By employing the physically based correction using calibrated measurements from the nearby Ontario Ministry of the Environment, Conservation and Parks air quality site, the average daily mean absolute error (MAE) of the PurpleAir PM2.5 measurements is decreased from 5.58 to 1.68 µg m−3, and the average daily bias decreases from 4.75 to −0.23 µg m−3. This improvement in the correction is comparable to that seen using conventional statistical methodologies. Our OEM retrieval also allowed us to estimate seasonal bulk hygroscopicity values ranging from 0.33 to 0.40. These values are consistent with the accepted ranges of bulk hygroscopicity for atmospheric particulate matter (0.1 to 0.9) determined in previous studies using calibrated air quality measurement instruments, which suggests that our method allows a new aerosol product to be determined from a large sensor network.