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Characterization of exhaled e-cigarette aerosols in a vape shop using a field-portable holographic on-chip microscope.


ABSTRACT: The past decade marked a drastic increase in the usage of electronic cigarettes. The adverse health impact of secondhand exposure due to exhaled e-cig particles has raised significant concerns, demanding further research on the characteristics of these particles. In this work, we report direct volatility measurements on exhaled e-cig aerosols using a field-portable device (termed c-Air) enabled by deep learning and lens-free holographic microscopy; for this analysis, we performed a series of field experiments in a vape shop where customers used/vaped their e-cig products. During four days of experiments, we periodically sampled the indoor air with intervals of ~ 16 min and collected the exhaled particles with c-Air. Time-lapse inline holograms of the collected particles were recorded by c-Air and reconstructed using a convolutional neural network yielding phase-recovered microscopic images of the particles. Volumetric decay of individual particles due to evaporation was used as an indicator of the volatility of each aerosol. Volatility dynamics quantified through c-Air experiments showed that indoor vaping increased the percentage of volatile and semi-volatile particles in air. The reported methodology and findings can guide further studies on volatility characterization of indoor e-cig emissions.

SUBMITTER: Cetintas E 

PROVIDER: S-EPMC8873257 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Characterization of exhaled e-cigarette aerosols in a vape shop using a field-portable holographic on-chip microscope.

Çetintaş Ege E   Luo Yi Y   Nguyen Charlene C   Guo Yuening Y   Li Liqiao L   Zhu Yifang Y   Ozcan Aydogan A  

Scientific reports 20220224 1


The past decade marked a drastic increase in the usage of electronic cigarettes. The adverse health impact of secondhand exposure due to exhaled e-cig particles has raised significant concerns, demanding further research on the characteristics of these particles. In this work, we report direct volatility measurements on exhaled e-cig aerosols using a field-portable device (termed c-Air) enabled by deep learning and lens-free holographic microscopy; for this analysis, we performed a series of fie  ...[more]

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