**5. Conclusions**

Color- and light-spectrum-assisted optical sensing of particulate matters was operated on a laboratory scale and under controlled experimental conditions. The chromaticity values and reflected light spectrum in terms of wavelength and intensity revealed the di fference between samples according to color and water or refractive-index-liquid additives. Noticeable results can be summarized as below.

Five di fferent particulate matters such as household dust, soil dust, pine tree pollen, talc and gypsum powders were optically characterized under as prepared, water-added and refractive-index-liquid-added cases combined with seven colors of light filter.

Depending on the intrinsic color of the as prepared sample, the non-white color group particulate matters including grey household dust, yellowish soil dust and pine tree pollen were selectively detected by observing the amount of chromaticity value shift in the vector. The white color group samples such as the talc and gypsum powders were distinguished by observing the unique peak positions in wavelength using a spectral sensor.

The intrinsic color of particulate matters can be the distinct point for identifying the types of non-white group samples such as household dust, soil dust and pine tree pollen under chromameter characterization rather than for the white color samples. Under the combined conditions of a cellophane filter and refractive index liquid, yellowish soil dust and pine tree pollen showed relatively large shifts in the chromaticity diagram in the vector. However, white color samples including talc and gypsum powers did not reveal a noticeable change. This was attributed to the intrinsic white color of powders under the xenon lamp.

In light spectrum measurements, the white color group samples showed more meaningful results than previous color measurements. All samples had consistent peaks at approximately 420 nm and 680 nm in wavelength. At other positions, a unique peak was observed depending on the type of particulate matter. Talc powder was the only sample that did not show any change in spectrum regardless of the additives and under no light filter conditions. An additional peak was observed at approximately 720 nm with water.

In the case of the pink filter, the gypsum sample revealed an obviously unique result in that a distinct peak at approximately 820 nm was detected for the as prepared case and peak position shifts from 439 nm to 453 nm were observed. When both water and the pink filter were used, the peak at approximately 490 nm was the index peak for talc powder. It can be concluded that the light spectrum study was more e ffective to identify white color powders and distinguish them from other non-white group powders in terms of distinct peak position and peak shift.

Two approaches using a chromameter and spectral sensor were attempted and meaningful results were observed. Simple color and reflectance change by water or refractive index liquid were able to draw the noticeable di fferences in observation. However, these still have limitations in intuitive observation, such as the way of the camera. Post analysis was inevitable to perform chromaticity value sorting and calculation.

It was our observation that there is a noticeable relationship between the intrinsic color of the particulate matter and the appropriate approach, whether it is chromaticity value, shift or the peak of the reflectance spectrum. In addition, water or refractive index liquid were found to be e ffective to enhance the relative deviation in color or reflected light depending on the type of particulate matter. An appropriate combination of chromameter and spectral sensor can be an alternative approach to detect particulate matters with higher selectivity. In future studies, various colors of particulate matters are required to be characterized to determine the relationship between the intrinsic color of particles and optical identification. It is also our hope that particulate matters less than 10 and 2.5 μm in aerodynamic diameter should be separated to investigate their size dependence under the above approaches.

**Author Contributions:** Conceptualization, methodology, validation, formal analysis, investigation, writing—original draft preparation, H.A.; data acquisition, experiments, data processing, H.-J.C.; writing—review and editing, G.-S.C.; resources, project administration, J.S.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by a gran<sup>t</sup> (20AUDP-B151639-02) from KAIA Urban Construction Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

**Acknowledgments:** Authors would like to thank KICT supporting division members for their sincere assistance regarding this research related experiments, data acquisition, and sample preparation from the field and laboratories.

**Conflicts of Interest:** To the best of our knowledge, authors have no conflict of interest, finance or otherwise.
