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Atmospheric total ozone column evaluation with a smartphone image sensor
Authors:Damien P. Igoe  Alfio V. Parisi  Abdurazaq Amar  Nathan J. Downs  Joanna Turner
Affiliation:1. Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia;2. College of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia
Abstract:
A new method for quantifying the total ozone column (TOC) using a smartphone image sensor has been developed and validated. The TOC has been evaluated for relatively cloud free days at high air masses for solar zenith angles between 49.7° and 76.7° at a sub-tropical site. The method is based on the evaluation of the direct solar irradiances at 305 and 312 nm using the red colour pixel values of the solar disc recorded at these wavelengths by a smartphone camera. Narrow bandpass filters of 2 nm full width at half maximum at each of the two wavelengths were used in turn placed over the camera sensor to directly image the solar disc. The calibration of the pixel values of the solar disc to provide the direct solar irradiances at each of these two wavelengths allowed evaluation of the TOC calibrated to a portable sun photometer. The root mean square error (RMSE) for the smartphone-derived ozone values calibrated to corresponding values from a portable sun photometer was 4.3 Dobson Units (DU). The validation measurements for the smartphone-derived ozone values provided an average residual of 3.5% (up to a maximum of 11%) compared to the corresponding portable sun photometer values, with an RMSE of 8.4 DU during days of intermittent inclement weather conditions. The evaluation of the TOC based on a widely available device such as a smartphone has the potential to increase current citizen science initiatives valued by the general public and school-aged learners by enhancing knowledge and awareness of ozone and the resulting influences on the solar ultraviolet environment.
Keywords:Ozone  ozone layer  solar radiation  smartphone image sensor  remote sensing  environmental modelling
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