Exploration of a practical approach to providing RH corrections to low cost sensor networks

Low-cost PM2.5 sensors have been deployed extensively for high spatio-temporal resolution air quality monitoring. However, environmental factors, especially relative humidity (RH), cause discrepancies for low-cost sensors when compared with regulatory-grade instruments. Developing methods of correcting or accounting for this RH discrepancy is therefore key to attaining data from low-cost air quality sensors, which can be used to monitor compliance with global air quality guidelines. Here, we developed a simple aerosol dryer and placed a pair of Plantower PMS7003 sensors before and after it, continuously monitoring the impact of drying on the reported particle mass concentrations. During the monitoring period, drying reduced the reported mass concentration for Brisbane’s PM2.5 by 25–40%. This measured drying effect was then used to calculate a real-time RH correction factor, enabling adjustment of particle mass concentrations reported by a sensor network, accounting for fluctuations in RH and the contribution of hygroscopic sources to ambient PM2.5.