High precision and fast measurement of gas concentrations is important for both understanding and monitoring various phenomena, from industrial and environmental to medical and scientific applications. This article deals with the recent progress in ammonia detection using in-situ solid-state and optical methods. Due to the continuous progress in material engineering and optoelectronic technologies, these methods are among the most perceptive because of their advantages in a specific application. We present the basics of each technique, their performance limits, and the possibility of further development. The practical implementations of representative examples are described in detail. Finally, we present a performance comparison of selected practical application, accumulating data reported over the preceding decade, and conclude from this comparison.

Purpose: – This paper aims to present the methods of improving selectivity and sensitivity of resistance gas sensors. Design/methodology/approach: – This paper compares various methods of improving gas sensing by temperature modulation, UV irradiation or fluctuation-enhanced sensing. The authors analyze low-frequency resistance fluctuations in commercial Taguchi gas sensors and the recently developed tungsten trioxide (WO₃) gas-sensing layers, exhibiting a photo-catalytic effect. Findings: – The efficiency of using low-frequency fluctuations to improve gas detection selectivity and sensitivity was confirmed by numerous experimental studies in commercial and prototype gas sensors. Research limitations/implications: – A more advanced measurement setup is required to record noise data but it will reduce the number of gas sensors necessary for identifying the investigated gas mixtures. Practical implications: – Fluctuation-enhanced sensing can reduce the energy consumption of gas detection systems and assures better detection results. Originality/value: – A thorough comparison of various gas sensing methods in resistance gas sensors is presented and supported by exemplary practical applications.

This paper analyses the effectiveness of determining gas concentrations by using a prototype WO₃ resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration of each constituent in a mixture. We confirmed that the accuracy of the estimated gas concentration could be significantly improved by applying temperature change and ultraviolet irradiation of the WO₃ layer. Fluctuation-enhanced sensing allowed us to predict the concentration of both component gases.