The CICAM method for in situ detection of aerosol acidity using colorimetry integrated with camera

Abstract

The measurement of aerosol acidity is important to have a comprehensive understanding of aerosol chemistry, the adverse health effects of particulate matter, and climate. The Colorimetry Integrated with CAMera (CICAM) method is demonstrated to detect the color change of a filter (impregnated with an acid indicator), after the application of an acidic aerosol, using digital images. The CICAM images were analyzed by a computer program that employs the Matplotlib Library in python to decouple the camera image to the Red-Green-Blue (RGB) scale. The calibration of the CICAM method for the detection of proton concentration ([H⁺], mol L⁻¹) in aerosol was performed with regard to the change of the G color component. The Colorimetry integrated with Reflective UV spectrometry (C-RUV) method that has recently been developed to detect [H⁺] in aerosol collected on a dyed filter using a micro-UV spectrometer can provide a lower uncertainty and a limit of detection that is an order of magnitude lower than the CICAM method, but is significantly more expensive. The CICAM method allows for the online detection of aerosol acidity utilizing a commercialized camera and LED light. The relationship between CICAM and C-RUV was also demonstrated by translating C-RUV spectral data into RGB values. Remarkably, the Green values measured by CICAM were statistically similar to the Green values obtained from C-RUV data. Therefore, we conclude that the CICAM and C-RUV method are comparable in their use for the prediction of proton concentration.

Copyright © 2021 American Association for Aerosol Research

EDITOR:

• Jim Smith

Additional information

Funding

This research was supported by the award from NSF (AGS1923651) and the award from the National Strategic Project-Fine particle of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (2017M3D8A1090654).