Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Optical Sensing Approach to Recognition of Different Types of Particulate Matters for Sustainable Indoor Environment Management

Version 1 : Received: 19 October 2020 / Approved: 20 October 2020 / Online: 20 October 2020 (15:05:25 CEST)

How to cite: Ahn, H.; Kang, J.S.; Choi, G.; Choi, A.H.J. Optical Sensing Approach to Recognition of Different Types of Particulate Matters for Sustainable Indoor Environment Management. Preprints 2020, 2020100415 (doi: 10.20944/preprints202010.0415.v1). Ahn, H.; Kang, J.S.; Choi, G.; Choi, A.H.J. Optical Sensing Approach to Recognition of Different Types of Particulate Matters for Sustainable Indoor Environment Management. Preprints 2020, 2020100415 (doi: 10.20944/preprints202010.0415.v1).

Abstract

As climate changes, our daily life has been much influenced by abnormal meteorological phenomena such as heavy rainfall, heat wave, heavy snowfall, and fine dust. Atmospheric air quality is worsening day by day and indoor air quality is also affected by interconnected daily activities throughout the inside and outside of buildings and houses. Nowadays, pollutants from various sources are emitted, transformed by sunlight, vapor, and ozone and transported into the city from country to country. Due to these reasons, there have been high demands to monitor the transportation of particulate matters and improve air quality. Monitoring of pollutants and identification of type and its concentration enables us to track and control its generation and consequently find out the solution. However, monitoring of pollutants, especially, particulate matter generation and its transportation is still not fully operated in atmospheric air due to its open nature and meteorological factors. Even though indoor air is relatively easy to monitor and control than outdoor in the aspect of specific volume and contaminant source, but it still needs to consider the meteorological parameters because indoor air is not fully separated from the outdoor air flow and contaminants transportation. In this study, optical approach using spectral sensor was attempted to reveal the feasibility of wavelength and chromaticity values of reflected light from specific particles. From the analysis of reflected light of various particulate matters according to different liquid additives, parameter studies were performed to investigate which experimental conditions can contribute to the enhanced selective sensing of particulate matters. Five different particulate matters such as household dust, soil, talc powder, gypsum powder and yellow pine tree pollen were utilized and observed to elucidate the relationship between property of particulate matter and detected light spectrum. Applicable approaches to assist current particle matter sensors and improve the selective sensing were suggested.

Subject Areas

optical sensing; particulate matter; sustainable indoor environment; contaminant control

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