Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter

• Published in: Sensors (Basel, Switzerland) Vol. 18; no. 9; p. 2790
• Main Authors: Di Antonio, Andrea, Popoola, Olalekan A M, Ouyang, Bin, Saffell, John, Jones, Roderic L
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.08.2018; MDPI
• Subjects: Air pollution; environmental monitoring; Humidity; Light; Low cost; low cost sensors; Particle size; Particle size distribution; Particulate emissions; particulate matter; Portable equipment; Radiation counters; Relative humidity; relative humidity correction; Sensors; Time series; United Kingdom > UK; low cost sensors; particulate matter; environmental monitoring; air pollution; relative humidity correction
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18092790

There is increasing concern about the health impacts of ambient Particulate Matter (PM) exposure. Traditional monitoring networks, because of their sparseness, cannot provide sufficient spatial-temporal measurements characteristic of ambient PM. Recent studies have shown portable low-cost devices (e.g., optical particle counters, OPCs) can help address this issue; however, their application under ambient conditions can be affected by high relative humidity ( ) conditions. Here, we show how, by exploiting the measured particle size distribution information rather than PM as has been suggested elsewhere, a correction can be derived which not only significantly improves sensor performance but which also retains fundamental information on particle composition. A particle size distribution⁻based correction algorithm, founded on κ -Köhler theory, was developed to account for the influence of on sensor measurements. The application of the correction algorithm, which assumed physically reasonable κ values, resulted in a significant improvement, with the overestimation of PM measurements reduced from a factor of ~5 before correction to 1.05 after correction. We conclude that a correction based on particle size distribution, rather than PM mass, is required to properly account for effects and enable low cost optical PM sensors to provide reliable ambient PM measurements.