Multivariate Calibration for Selective Analysis of Hydrogen Sulfide and Carbon Monoxide with Thermal Modulation of the SnO2–PdO Sensor

In this study, multivariate data processing during thermal modulation of the SnO2–PdO gas sensor was performed using the multivariate calibration (MC) method. We propose to supplement this method with a procedure that allows the solving of problems of both quantitative and qualitative analysis. The advantage of the extended method (Multivariate Calibration for Selective Analysis, MCSA) compared to other methods is its modest requirements for computing resources, which allows it to be easily implemented on standard microcontrollers. The MCSA method opens up the prospect of creating compact gas analyzers of a new generation, capable of selective gas analysis in hard-to-reach places in an autonomous mode. The implementation of the MCSA method was demonstrated using the example of selective determination of hydrogen sulfide and carbon monoxide by a sensor whose temperature periodically changed from 100 to 450 °C. The training sample data were transformed by the MCSA method, which allowed for successful qualitative and quantitative analysis of the test sample data.