Published in

MDPI, Atmosphere, 5(13), p. 747, 2022

DOI: 10.3390/atmos13050747

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Differentiating Semi-Volatile and Solid Particle Events Using Low-Cost Lung-Deposited Surface Area and Black Carbon Sensors

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Low-cost particle sensors have proven useful in applications such as source apportionment, health, and reactivity studies. The benefits of these instruments increase when used in parallel, as exemplified with a 3-month long deployment in an urban background site. Using two lung-deposited surface area (LDSA) instruments, a low-cost method was developed to assess the solid component of an aerosol by applying a catalytic stripper to the inlet stream of one LDSA instrument, resulting in only the solid fraction of the sample being measured (LDSAc). To determine the semi-volatile fraction of the sample, the LDSAC was compared to the LDSA without a catalytic stripper, thus measuring all particles (LDSAN). The ratio of LDSA (LDSAC/LDSAN) was used to assess the fraction of solid and semi-volatile particles within a sample. Here, a low ratio represents a high fraction of semi-volatile particles, with a high ratio indicating a high fraction of solid particles. During the 3-month urban background study in Birmingham, UK, it is shown that the LDSA ratios ranged from 0.2–0.95 indicating a wide variation in sources and subsequent semi-volatile fraction of particles. A black carbon (BC) instrument was used to provide a low-cost measure of LDSA to BC ratio. Comparatively, the LDSA to BC ratios obtained using low-cost sensors showed similar results to high-cost analyses for urban environments. During a high LDSAC/LDSAN ratio sampling period, representing high solid particle concentrations, an LDSA to BC probability distribution was shown to be multimodal, reflecting urban LDSA to BC ratio distributions measured with laboratory-grade instrumentation. Here, a low-cost approach for data analyses presents insight on particle characteristics and insight into PM composition and size, useful in source apportionment, health, and atmospheric studies.