Determining PM_2.5 calibration curves for a low-cost particle monitor: common indoor residential aerosols

Abstract

Real-time particle monitors are essential for accurately estimating exposure to fine particles indoors. However, many such monitors tend to be prohibitively expensive for some applications, such as a tenant or homeowner curious about the quality of the air in their home. A lower cost version (the Dylos Air Quality Monitor) has recently been introduced, but it requires appropriate calibration to reflect the mass concentration units required for exposure assessment. We conducted a total of 64 experiments with a suite of instruments including a Dylos DC1100, another real-time laser photometer (TSI SidePak™ Model AM-510 Personal Aerosol Monitor), and a gravimetric sampling apparatus to estimate Dylos calibration factors for emissions from 17 different common indoor sources including cigarettes, incense, fried bacon, chicken, and hamburger. Comparison of minute-by-minute data from the Dylos with the gravimetrically calibrated SidePak yielded relationships that enable the conversion of the raw Dylos particle counts less than 2.5 μm (in #/0.01 ft(3)) to estimated PM2.5 mass concentration (e.g. μg m(-3)). The relationship between the exponentially-decaying Dylos particle counts and PM2.5 mass concentration can be described by a theoretically-derived power law with source-specific empirical parameters. A linear relationship (calibration factor) is applicable to fresh or quickly decaying emissions (i.e., before the aerosol has aged and differential decay rates introduce curvature into the relationship). The empirical parameters for the power-law relationships vary greatly both between and within source types, although linear factors appear to have lower uncertainty. The Dylos Air Quality Monitor is likely most useful for providing instantaneous feedback and context on mass particle levels in home and work situations for field-survey or personal awareness applications.

Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions

“…The “> 0 times” of indoor smoking group ( n = 55) had median levels close to 2000 counts greater than the “0 times” group ( n = 201) with the distributions diverging so that at the upper tail indoor smoking could contribute up to 20,000 more weekly mean counts. This finding is consistent with previous research that shows smoking cigarettes elevates particle levels in individual rooms of homes on the order of 100’s of μg/m 3 (e.g., Ott et al 2003 [16]), which are roughly equivalent to counts on the order of 20,000 counts per 0.01 cubic feet as measured by the Dylos Air Quality Monitor for secondhand smoke [40]. In California, medical marijuana use is legal.…”

“…The Dylos monitor and other real-time particle monitors are not best-suited for estimating absolute mass particle concentration due to differential sensitivity of the monitor to source types and removal rates [40,61]. While mass levels are typically assessed using a “gold standard” filter-and-pump approach, the Dylos may still be used as an approximate indication of the magnitude of indoor levels and occupants exposures.…”

Comparison of methods for converting Dylos particle number concentrations to PM2.5 mass concentrations

“…Dacunto et al (2015) performed experiments where different types of food were cooked and where a fit curve was produced for each experiment and for all data together (which was used in the current study). They reported a variance of calibration curve parameters within the different experiments using the same sources and between different sources, suggesting that differences in experimental conditions can produce a wide range of fit curves for conversion of Dylos PNC to PMC, particularly for the higher concentration ranges . This finding is in line with our observations which were obtained under real‐life circumstances.…”

“…Nevertheless, the performance of these sensors has not been thoroughly tested and there is still room for improvements. One of these low‐cost PM sensors is the Dylos DC1700™ which has been investigated in several studies and expresses particle number concentrations (PNC) in two size bins (>0.5 µm and >2.5 µm) …”

Fine Particle Sensor Based on Multi-Angle Light Scattering and Data Fusion

“…Therefore, most of these instruments are used indoors or in situations where particle composition remains constant. Numerous studies have been carried out to analyze the calibration of different kinds of PM2.5 [7,8,9]. It is a great challenge to accurately estimate PM2.5 mass concentration for diverse kinds of PM2.5.…”