Significance of sources and size distribution on calibration of low-cost particle sensors: Evidence from a field sampling campaign

Low-cost sensors (LCS) are gathering the interest of researchers and monitoring agencies worldwide due to their compact size and economic feasibility. However, the data recorded by LCS is often of low quality owing to its calibration dependencies and biases. An intensive field sam-pling campaign was conducted at five sites inside the IIT Bombay campus to understand the fundamental issues associated with LCS. PA-II and OPC-N2 LCS were collocated with BAM-1020 and OPS-3330 at the sampling locations for inter-comparison. LCS shows a good correlation with BAM-1020 at sites where the contributing sources produce more particles in the 1-2.5 mu m size range than particles in below 1 mu m (PM1) and 2.5-10 mu m size range. The performance decreased with an increase in mass fractions of PM1 and PM10. The overall performance of both PA-II (R2 = 0.72) and OPC-N2 (R2 = 0.73) are comparable. Both PA-II and OPC-N2 have substandard per-formance with R2 in the range of 0.30-0.39 and 0.42-0.53 at the construction and main gate site respectively. Comparing the two calibration approaches used in this study indicates the impor-tance of including size distribution parameters in the calibration of LCS. The calibration models were developed for each site and were compared with the general model developed for PA-II and OPC-N2. Results indicate that the site-specific models are in better agreement with the reference instrument than the general calibration model. The number concentration recorded by PA-II was poorly correlated with OPS-3330, especially for particles >1 mu m and vice versa for OPC-N2. The particle count for PM > 2.5 mu m recorded by PA-II is predominantly zero, which is inconsistent with the mass concentration data recorded by the sensor. The size distribution results indicate that LCS assumes a universal monotonically decreasing function of number concentration with respect to the particle diameter. It is one of the critical problems with LCS measurements as any error in the number measurement is increased 3-fold in the mass conversion. This study shows the need for site-specific robust calibration of LCS based on the particle size distribution and provides a direction in their development.