24 Apr 2023
 | 24 Apr 2023
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

A Highly Sensitive and Selective Laser-Based BTEX Sensor for Occupational and Environmental Monitoring

Mhanna Mhanna, Mohamed Sy, Ayman Arfaj, Jose Llamas, and Aamir Farooq

Abstract. A mid-infrared laser-based sensor is designed and demonstrated for trace detection of benzene, toluene, ethylbenzene, and xylene isomers at ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.29 μm and an off-axis cavity-enhanced absorption spectroscopy configuration with an optical gain of ~2800. Wavelength tuning and a deep neural networks (DNN) model were employed to enable simultaneous and selective BTEX measurements. The sensor performance was demonstrated by measuring BTEX mole fractions in various mixtures. At an integration time of 10 seconds, minimum detection limits of 11.4, 9.7, 9.1, 10, 15.6, and 12.9 ppb were achieved for benzene, toluene, ethylbenzene, m-xylene, o-xylene, and p-xylene, respectively. The sensor can be used to detect tiny BTEX leaks in petrochemical facilities and to monitor air quality in residential and industrial areas for workplace pollution.

Mhanna Mhanna et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2023-514', Dean Venables, 25 Apr 2023 reply
    • AC1: 'Reply on CC1', Mhanna Mhanna, 08 May 2023 reply
  • RC1: 'Comment on egusphere-2023-514', Anonymous Referee #1, 15 May 2023 reply
    • AC2: 'Reply on RC1', Mhanna Mhanna, 16 Jun 2023 reply

Mhanna Mhanna et al.

Mhanna Mhanna et al.


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Short summary
The recent advancement in machine learning models enabled scientists to use powerful tools in various applications. In the case of having similar molecules, it is very hard for lasers to distinguish between them; thus we used a special machine learning method to solve this problem. We have developed a highly sensitive laser sensor which can differentiate between very similar chemicals using machine learning.