Comprehensive food chain management requires the monitoring of many parameters including temperature, humidity, and multiple gases. The latter is highly challenging because no low-cost technology for the simultaneous chemical analysis of multiple gaseous components currently exists. This contribution proposes the use of cavity enhanced Raman spectroscopy to enable online monitoring of all relevant components using a single laser source. A laboratory scale setup is presented and characterized in detail. Power enhancement of the pump light is achieved in an optical resonator with a Finesse exceeding 2500. A simulation for the light scattering behavior shows the influence of polarization on the spatial distribution of the Raman scattered light. The setup is also used to measure three relevant showcase gases to demonstrate the feasibility of the approach, including carbon dioxide, oxygen and ethene.

Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases. The concentration information is often retrieved by fitting absorption profiles to the acquired spectra, utilizing spectroscopic databases. In complex gas matrices an expanded parameter space leads to long computation times of the fitting routines due to the increased number of spectral features that need to be computed for each iteration during the fit. This hinders the capability of real-time analysis of the gas matrix. Here, an artificial neural network (ANN) is employed for rapid prediction of gas concentrations in complex infrared absorption spectra composed of mixtures of CO and N2O. Experimental data is acquired with a mid-infrared dual frequency comb spectrometer. To circumvent the experimental collection of huge amounts of training data, the network is trained on synthetically generated spectra. The spectra are based on simulated absorption profiles making use of the HITRAN database. In addition, the spectrometer’s influence on the measured spectra is characterized and included in the synthetic training data generation. The ANN was tested on measured spectra and compared to a non-linear least squares fitting algorithm. An average evaluation time of 303 µs for a single measured spectrum was achieved. Coefficients of determination were 0.99997 for the predictions of N2O concentrations and 0.99987 for the predictions of CO concentrations, with uncertainties on the predicted concentrations between 0.04 and 0.18 ppm for 0 to 100 ppm N2O and between 0.05 and 0.18 ppm for 0 to 60 ppm CO.

Dual-frequency comb spectroscopy has emerged as a disruptive technique for measuring wide-spanning spectra with high resolution, yielding a particularly powerful technique for sensitive multi-component gas analysis. We present a spectrometer based on two electro-optical combs with subsequent conversion to the mid-infrared via tunable difference frequency generation, operating in the range from 3 to 4.7 µm. The repetition rate of the combs can be tuned from 250 to 500 MHz. For 500 MHz, the number of detected comb modes is 440 with a signal-to-noise ratio exceeding 105 in 1 s. The conversion preserves the coherence of the combs within 3 s measurement time. Concentration measurements of 5 ppm methane at 3.3 µm, 100 ppm nitrous oxide at 3.9 µm and a mixture of 15 ppm carbon monoxide and 5% carbon dioxide at 4.5 µm are demonstrated with a noise-equivalent absorption coefficient of 6.4(3) x 10−6 cm−1 Hz−1/2.

A dual comb spectrometer is used as gas sensor for the parallel detection of nitrous oxide (N2O) and carbon monoxide (CO). These gases have overlapping absorption features in the mid-infrared (MIR) at a wavelength of 4.6 µm. With a spectra acquisition rate of 10 Hz, concentrations of 50 ppm N2O and 30 ppm CO are monitored with a relative precision of 6 × 10 − 3 6\times {10^{-3}} and 3 × 10 − 3 3\times {10^{-3}} respectively. The limit of detections are 91 ppb for N2O and 50 ppb for CO for an integration time of 25 s. The system exhibits a linear sensitivity from 2 ppm to 100 ppm with coefficients of determination of 0.99998 for N2O and 0.99996 for CO.

A dual frequency comb spectrometer is realized by electro-optic modulation of a 1550 nm laser and subsequent conversion to the mid-infrared by difference-frequency generation (DFG). Using an optical parametric oscillator for the DFG the combs can be tuned from 3 µm to 4.7 µm with 440 comb modes covering 220 GHz (> 6 cm -1 ). Trace gas detection of nitrous oxide, carbon dioxide and methane is demonstrated with a 7.2-m-multi-pass cell while a sufficiently low noise-equivalent absorbance is reached in already 1 s. The bandwidth normalized noise-equivalent-absorption coefficient is consistently below 2.8 x 10 -6 Hz -1/2 cm -1 while the precision of the determined concentrations is better 2 % Hz -1/2 .