Suitability of Low-Cost Sensors for Submicron Aerosol Particle Measurement

Author:

Stoll Daniel1ORCID,Kerner Maximilian1,Paas Simon1,Antonyuk Sergiy1ORCID

Affiliation:

1. Institute of Particle Process Engineering, University of Kaiserslautern-Landau, 67663 Kaiserslautern, Germany

Abstract

The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement monitoring of the anthropogenic aerosol spreading is necessary. For indoor aerosol measurements usually standard lab equipment is used. However, these devices are time-consuming, expensive and unwieldy. The idea is to replace this standard laboratory equipment with low-cost sensors widely used for monitoring fine dust (particulate matter—PM). Due to the low acquisition costs, many sensors can be used to determine the aerosol load, even in large rooms. Thus, the aim of this work is to verify the measurement capability of low-cost sensors. For this purpose, two different models of low-cost sensors are compared with established laboratory measuring instruments. The study was performed with artificially prepared NaCl aerosols with a well-defined size and morphology. In addition, the influence of the relative humidity, which can vary significantly indoors, on the measurement capability of the low-cost sensors is investigated. For this purpose, a heating stage was developed and tested. The results show a discrepancy in measurement capability between low-cost sensors and laboratory measuring instruments. This difference can be attributed to the partially different measuring method, as well as the different measuring particle size ranges. The determined measurement accuracy is nevertheless good, considering the compactness and the acquisition price of the low-cost sensors.

Funder

VolswagenStiftung

Publisher

MDPI AG

Subject

Artificial Intelligence,Applied Mathematics,Industrial and Manufacturing Engineering,Human-Computer Interaction,Information Systems,Control and Systems Engineering

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