Identifying PM_2.5 samples collected in different environment by using terahertz time-domain spectroscopy

Abstract

Particulate matter with the diameter of less than 2.5 mm (PM_2.5) is the most important causation of air pollution. In this study, PM_2.5 samples were collected in three different environment including ordinary atmospheric environment, lampblack environment and the environment with an air conditioning exhaust fan, and analyzed by using terahertz time-domain spectroscopy (THz-TDS). The linear regression analysis and the principal component analysis (PCA) are used to identify PM_2.5 samples collected in different environment. The results indicate that combining THz-TDS with statistical methods can serve as a contactless and efficient approach to identify air pollutants in different environment.

Keywords

PM_2.5 / terahertz time-domain spectroscopy (THz-TDS) / statistical methods

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 11574401), the National Basic Research Program of China (No. 2014CB744302).

RIGHTS & PERMISSIONS

2018 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature