Development and evaluation of correction models for a low-cost fine particulate matter monitor

Abstract. Four correction models with differing forms were developed on a training dataset of 32 PurpleAir–Federal Equivalent Method (FEM) hourly fine particulate matter (PM2.5) observation colocation sites across North America (NA). These evaluated in comparison four existing from external sources using the data 15 additional NA sites. Colocation determined automatically based proximity and novel quality control process. The Canadian Air Quality Health Index Plus (AQHI+) system was used to make comparisons range concentrations common NA, as well provide operational health-related context evaluations. model found perform best our Model 2, PM2.5-corrected=PM2.5-cf-1/(1+0.24/(100/RH%-1)), where RH is limited [30 %,70 %], which growth by Crilley et al. (2018). Corrected this moderate high range, most impactful human health, outperformed all other comparisons. 7 (Barkjohn al., 2021) close runner-up excelled low-concentration (most NA). do not same at different locations, thus we recommend testing several nearby utilizing that performs if possible. If no site available, 2. This study provides robust framework for evaluation low-cost PM2.5 sensor presents an optimized American PurpleAir (PA) sensors.