Cost-Effective Platform for Particulate Matter Rapid Monitoring

Luciano André  Barbosa Da Silva; Otavio Chase; Glauber Tadaiesky Marques; José Felipe Souza de Almeida; Milena Marília  Nogueira de Andrade

doi:10.31686/ijier.vol8.iss1.2147

Authors

Luciano André Barbosa Da Silva Federal Rural University of Amazonia (UFRA)
Otavio Chase https://orcid.org/0000-0003-0246-8339
Glauber Tadaiesky Marques Federal Rural University of Amazonia (UFRA)
José Felipe Souza de Almeida Federal Rural University of Amazonia (UFRA) https://orcid.org/0000-0001-7732-6955
Milena Marília Nogueira de Andrade Federal Rural University of Amazonia (UFRA) https://orcid.org/0000-0001-5799-7321

DOI:

https://doi.org/10.31686/ijier.vol8.iss1.2147

Keywords:

Air-quality monitoring, Embedded system, Particulate matter

Abstract

Particles in the air with volume ≤ 2.5 μm³ have been classified as carcinogenic by the World Health Organization (WHO). Therefore, rapid monitoring systems are crucial to obtain information about particulate matter (PM) concentrations and make this information publicly available. Supported by WHO criteria, this text focuses on the development of a field-portable cost-effective platform for rapid monitoring, data acquisition of particulate matter (PM₁₀ and PM_2.5) and measurements of environmental variables (relative air humidity and temperature) at the micrometeorological level, in addition to providing access via the Internet of Thing (IoT). The platform was tested, as well as validating its results when compared to those made available at the National Meteorology Institute-INMET (Instituto Nacional de Meteorologia). Based on this technology, tests and measurements have been performed in the local presence of the population and vehicle traffic, in order to identify the concentrations of PM in public places. Between the results obtained, the device recorded higher temperature and low humidity, at 12 noon, and the average hourly reached 175.3 µg/m³ (PM₁₀) and 164.2 µg/m³ (PM_2.5), which means a warning sign. This computational platform would be useful for cost-effective and rapid quantification of PM density even in field and resource-poor settings.

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