Monitoring of hydrogen sulfide via substrate-integrated hollow waveguide mid-infrared sensors in real-time

Abstract

Hydrogen sulfide is a highly corrosive, harmful, and toxic gas produced under anaerobic conditions within industrial processes or in natural environments, and plays an important role in the sulfur cycle. According to the U.S. Occupational Safety and Health Administration (OSHA), the permissible exposure limit (during 8 hours) is 10 ppm. Concentrations of 20 ppm are the threshold for critical health issues. In workplace environments with human subjects frequently exposed to H2S, e. g., during petroleum extraction and refining, real-time monitoring of exposure levels is mandatory. Sensors based on electrochemical measurement principles, semiconducting metal-oxides, taking advantage of their optical properties, have been described for H2S monitoring. However, extended response times, limited selectivity, and bulkiness of the instrumentation are common disadvantages of the sensing techniques reported to date. Here, we describe for the first time usage of a new generation of compact gas cells, i.e., so-called substrate-integrated hollow waveguides (iHWGs), combined with a compact Fourier transform infrared (FTIR) spectrometer for advanced gas sensing of H2S. The principle of detection is based on the immediate UV-assisted conversion of the rather weak IR-absorber H2S into much more pronounced and distinctively responding SO2. A calibration was established in the range of 10-100 ppm with a limit of detection (LOD) at 3 ppm, which is suitable for occupational health monitoring purposes. The developed sensing scheme provides an analytical response time of less than 60 seconds. Considering the substantial potential for miniaturization using e. g., a dedicated quantum cascade laser (QCL) in lieu of the FTIR spectrometer, the developed sensing approach may be evolved into a hand-held instrument, which may be tailored to a variety of applications ranging from environmental monitoring to workplace safety surveillance, process analysis and clinical diagnostics, e. g., breath analysis.