An ozone monitoring system employing passive sampling and a smartphone-based sensing and detection device

An ozone monitoring system composed of two parts, monitoring device (passive sampling tube and ready-to-use indigotrisulfonate (ITS) immobilized pad) for sampling and sensing with smartphone detection is presented. The detection was based on bleaching of ITS by ozone and color evaluation via image processing. Correlation of the change of blue color (Red intensity) with amount of the immobilized ITS leads to ozone concentration by applying Fick's first law of diffusion. The conditions for monitoring were optimized by considering amount of ITS, sampling time, and ambient ozone concentration. The proposed system offers flexibility in ozone monitoring. Under an investigation condition, in real ambient air, ozone detection in the mixing ratio range 10-40 ppbv (20-78 μg m<sup>-3</sup>) is possible, and results have been validated by the continuous ozone monitoring method. The proposed system was applied to ozone monitoring in ambient air within a district of Berlin (Germany) at 16 sites (about 0.5 km<sup>2</sup>). The data were then used for calculation of the spatial distribution of the entire area. Monitoring can be carried out by transporting the monitoring devices from various sampling sites to the central lab; over 100 samples per day can be analyzed by a single operator. Alternatively, parallel operation could be performed in many different sampling sites by different operators, leading to semi-real time monitoring. The proposed system is cost-effective (less than 1 USD/device for materials) and very simple to use. The proposed system supports several UN Sustainable Development Goals (SDGs) and has potential for citizen science applications.

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Publication Details

Journal
Environmental Pollution
Published
2026-01-09
DOI
https://doi.org/10.1016/j.envpol.2026.127658
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
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article

An ozone monitoring system employing passive sampling and a smartphone-based sensing and detection device

Andreas Held, Wolfgang Frenzel, Kanokwan Kiwfo, Kate Grudpan
Environmental Pollution
Air Quality Monitoring and Forecasting
article

An ozone monitoring system employing passive sampling and a smartphone-based sensing and detection device

Andreas Held, Wolfgang Frenzel, Kanokwan Kiwfo, Kate Grudpan
article en

Abstract

An ozone monitoring system composed of two parts, monitoring device (passive sampling tube and ready-to-use indigotrisulfonate (ITS) immobilized pad) for sampling and sensing with smartphone detection is presented. The detection was based on bleaching of ITS by ozone and color evaluation via image processing. Correlation of the change of blue color (Red intensity) with amount of the immobilized ITS leads to ozone concentration by applying Fick's first law of diffusion. The conditions for monitoring were optimized by considering amount of ITS, sampling time, and ambient ozone concentration. The proposed system offers flexibility in ozone monitoring. Under an investigation condition, in real ambient air, ozone detection in the mixing ratio range 10-40 ppbv (20-78 μg m<sup>-3</sup>) is possible, and results have been validated by the continuous ozone monitoring method. The proposed system was applied to ozone monitoring in ambient air within a district of Berlin (Germany) at 16 sites (about 0.5 km<sup>2</sup>). The data were then used for calculation of the spatial distribution of the entire area. Monitoring can be carried out by transporting the monitoring devices from various sampling sites to the central lab; over 100 samples per day can be analyzed by a single operator. Alternatively, parallel operation could be performed in many different sampling sites by different operators, leading to semi-real time monitoring. The proposed system is cost-effective (less than 1 USD/device for materials) and very simple to use. The proposed system supports several UN Sustainable Development Goals (SDGs) and has potential for citizen science applications.

Environmental PollutionVol. 392
Technische Universität Berlin (DE), Chiang Mai University (TH)
Openalex Percentile: Top 94%
Air Quality Monitoring and Forecasting
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