Issue 10, 2025

Research on cluster hollow fiber membrane proton transfer reaction mass spectrometry (CHFM-PTR-MS) and its application in odorous gas detection

Abstract

Odorous gas emission is one of the world's seven major public nuisances, easily causing disturbances and complaints, and posing a threat to air quality and public health. Emissions of odorous substances are characterized by their sudden and instantaneous nature, with some odorous compounds having extremely low olfactory thresholds. Therefore, it is essential to develop highly sensitive on-site rapid detection techniques. This paper presents a new technology that combines a cluster hollow fiber membrane (CHFM) with mobile proton transfer reaction mass spectrometry (PTR-MS), developing a cluster hollow fiber membrane-proton transfer reaction mass spectrometry (CHFM-PTR-MS) technique. Due to the large membrane area (1000 cm2) of the cluster hollow fiber membrane module, the CHFM-PTR-MS shows improved sensitivity for eight tested odorous substances by 7.6 to 12.2 times and an enhanced limit of detection by 6.7 to 12.4 times compared to traditional direct-injection PTR-MS. Through a 28-hour continuous monitoring experiment of odorous gases released from household waste, the capability of the new CHFM-PTR-MS technology for on-site rapid detection of trace odorous organic compounds was verified. The CHFM-PTR-MS is expected to provide a new technique and device for on-site rapid detection of odorous organic compounds with high sensitivity.

Graphical abstract: Research on cluster hollow fiber membrane proton transfer reaction mass spectrometry (CHFM-PTR-MS) and its application in odorous gas detection

Supplementary files

Article information

Article type
Paper
Submitted
23 Jan 2025
Accepted
28 Mar 2025
First published
09 Apr 2025

Analyst, 2025,150, 2101-2107

Research on cluster hollow fiber membrane proton transfer reaction mass spectrometry (CHFM-PTR-MS) and its application in odorous gas detection

F. Sun, X. Bao, Q. Zhang, J. Jin, Q. Xia, K. Gu, Q. Liang, W. Xu, X. Zou, C. Huang, C. Shen and Y. Chu, Analyst, 2025, 150, 2101 DOI: 10.1039/D5AN00084J

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