In this invited paper, a compact dense-pattern multipass cell-based near-infrared sensor system was demonstrated for detection of parts-per-billion in volume (ppbv)-level methane (CH₄) and ethane (C₂H₆). The dimension size of the fabricated gas cell is 18.5 × 8 × 9 cm³ with an absorption path length of 9.39 m. CH₄ measurement was realized within a spectral range of 6,046–6,048 cm⁻¹ and an absorption line of 6,046.95 cm⁻¹. The spectral range for C₂H₆ detection is 5,951–5,953 cm⁻¹ with an absorption line of 5,951.73 cm⁻¹. Allan deviation analysis was used for evaluating the dual-gas sensing performance, and a detection limit of 78 ppbv for CH₄ and 190 ppbv for C₂H₆ were achieved, respectively, with an averaging time of 0.8 s. Furthermore, CH₄ measurement in the indoor and outdoor atmosphere was both performed to verify the field sensing capability of the sensor system. Compared with two separate sensor systems for CH₄/C₂H₆ sensing, the proposed dual-gas sensor system using two near-infrared lasers and one multipass cell has the advantages of low-cost, compact-size without decreasing the selectivity and sensitivity.

The composition of volatile organic compounds (VOCs) in large-scale livestock farms is complex, which seriously affects the health of livestock and is difficult to evaluate. In order to quickly analyze the pollution degree of VOCs in livestock farms, electronic nose technology was used in this study to detect and analyze the gases in pig and chicken houses, respectively. Firstly, the gas chromatography–mass spectrometry (GC–MS) and electronic nose were used to analyze the VOCs in the pig and chicken houses at different time and locations. The types and relative contents of VOCs were obtained from different livestock farms by GC–MS analysis. The sensor array response of the electronic nose showed similar results. In addition, linear discriminant analysis (LDA), K nearest neighbor (KNN) and support vector machine (SVM) analyses were performed on the electrical signal that was generated by the sensors of electronic nose, respectively. Finally, the classification rate of different odor sources in livestock farms was the highest (>85%), which indicates that SVM is a more effective method suitable for volatile gases recognition in livestock farms. The results have shown that the developed electronic nose sensor is a promising and feasible instrument for characterizing volatile odors in livestock farms.

A mid-infrared carbon monoxide (CO) sensor system was developed for early fire identification in cotton harvesting operations. Measurements and field deployments on a harvester verified the good practicability of the sensor system.

A compact and high-sensitivity sensing system is required for the exploration of natural gas hydrates (NGHs) to measure dissolved CO ₂ in seawater. In this study, a mid-infrared (MIR) CO ₂ -sensing system was investigated by wavelength modulation spectroscopy. The system contained an interband cascade laser operating in MIR wavelength, an optical multipass gas cell, and an MIR mercury cadmium telluride detector. A combination of three absorption lines was utilized to achieve measurement with a wide CO ₂ -concentration range. Additionally, we proposed and introduced in detail a method of optimizing the operating temperature, pressure, and modulation depth. The optimum minimum detection limit of 11 ppbv was achieved when the integration time was 145 s. In the northern South China Sea, a deep-sea test was performed, and the test results validated the satisfactory performance of the sensing system for deep-sea NGH exploration.

A methane (CH₄) sensor based on off-axis integrated cavity output spectroscopy (OA-ICOS) was developed, equipped with two measurement schemes: direct absorption spectroscopy (DAS) and wavelength modulation spectroscopy (WMS). The sensor used an optical resonant cavity composed of two high reflection mirrors (reflectivity > 99%). With a cavity length of 7 cm, an effective optical path length of 10.8 m and a cavity volume of 8.9 mL were achieved. A distributed feedback laser was used to precisely target the CH₄ absorption line near 1.6537 µm. Compared with the original system, the cavity mode noise of the CH₄ sensor was further reduced by adding white noise perturbations. The white noise perturbations were generated by the broadband random noise from the signal generator. The special customized narrowband RF noise source was not required. The system complexity and cost could be reduced. In DAS mode, the signal-to-noise ratio (SNR) of the OA-ICOS was 16.2 and the minimum detection limit (MDL) was 2.2 ppm at 117 s. In WMS mode, the SNR of the OA-ICOS was 113.9 and the MDL was 1.2 ppm at 106 s. Compared with the results obtained from the WMS mode and DAS mode, the SNR and MDL was improved 7.0 times and 1.8 times, respectively. The proposed sensor system not only enabled high-accuracy trace gas measurement, but also demonstrated strong potential for applications due to its compact design and low cost.