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Research Article

Smartphone-based colorimetric detection of formaldehyde in the air

Meng Yang1Jin Ye2Tao Yu3Ying Song4Hua Qian1Tianyi Liu5Yang Chen5,6,7,8Junqi Wang9,10Shi-jie Cao9,10,11Cong Liu1,10( )
School of Energy and Environment, Southeast University, Nanjing 210096, China
School of Energy and Power, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
Wuhan Second Ship Design and Research Institute, Wuhan 430205, China
Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test, Hubei Provincial Institute for Food Supervision and Test, Wuhan 430075, China
Laboratory of Image Science and Technology, the School of Computer Science and Engineering, Southeast University, Nanjing, China
Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, Southeast University, Nanjing, China
School of Cyber Science and Engineering Southeast University, Nanjing, China
Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China
School of Architecture, Southeast University, China
Jiangsu Province Engineering Research Center of Urban Heat and Pollution Control, Southeast University, China
Global Centre for Clean Air Research (GCARE), University of Surrey, UK
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Abstract

Adverse impacts of exposure to formaldehyde on human health significantly increases attention in monitoring formaldehyde concentrations in the air. Conventional formaldehyde detection methods typically rely on large and costly instruments and requires high skills of expertise, preventing it from being widely accessible to civilians. This study introduced a novel approach utilizing smartphone-based colorimetric analysis. Changes of green channel signals of digital images by a smartphone successfully capture variation of purple color of 4-amino-3-hydrazino-5-mercapto-1,2,4-triazol solution, which is proportional to formaldehyde concentrations. It is because that green and purple are complimentary color pairs. A calibration curve was established between green channel signals and formaldehyde concentrations, with a correlation coefficient of 0.98. Detection limit of the smartphone-based method is 0.008 mg/m³. Measurement errors decrease as formaldehyde concentrations increase, with median relative errors of 34%, 17%, and 6% for concentration ranges of 0–0.06 mg/m3, 0.06–0.12 mg/m3, and 0.12–0.35 mg/m3, respectively. This method replaced scientific instrumentation with ordinary items, greatly reducing cost and operation bars. It would provide an opportunity to realize onsite measurements for formaldehyde by occupants themselves and increase awareness of air quality for better health protection.

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Building Simulation
Pages 2007-2015

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Cite this article:
Yang M, Ye J, Yu T, et al. Smartphone-based colorimetric detection of formaldehyde in the air. Building Simulation, 2024, 17(11): 2007-2015. https://doi.org/10.1007/s12273-024-1172-z

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Received: 11 May 2024
Revised: 21 July 2024
Accepted: 27 July 2024
Published: 03 September 2024
© Tsinghua University Press 2024