Determination Of Gas Concentrations Research Articles

Squeezed dual-comb spectroscopy.

Optical frequency combs have enabled distinct advantages in broadband, high-resolution spectroscopy and precision interferometry. However, quantum mechanics ultimately limits the metrological precision achievable with laser frequency combs. Quantum squeezing has led to substantial measurement improvements with continuous wave lasers, but experiments demonstrating metrological advantage with squeezed combs are less developed. Using the Kerr effect in nonlinear optical fiber, a 1-gigahertz frequency comb centered at 1560 nanometers is amplitude-squeezed by >3 decibels (dB) over a 2.5-terahertz bandwidth. Dual-comb interferometry yields mode-resolved spectroscopy of hydrogen sulfide gas with a signal-to-noise ratio nearly 3 dB beyond the shot-noise limit. The quantum noise reduction leads to a twofold quantum speedup in the determination of gas concentration, with implications for high-speed measurements of multiple species in dynamic chemical environments.

Enhancing the Reliability of NO2 Monitoring Using Low-Cost Sensors by Compensating for Temperature and Humidity Effects

The study investigates methods to enhance the reliability of NO2 monitoring using low-cost electrochemical sensors to measure gaseous pollutants in air by addressing the impacts of temperature and relative humidity. The temperature within a plastic container was controlled using an internal mica heater, an external hot air blower, or cooling packs, while relative humidity was adjusted using glycerine solutions. Findings indicated that the auxiliary electrode signal is susceptible to temperature and moderately affected by relative humidity. In contrast, the working electrode signal is less affected by temperature and relative humidity; however, adjustments are still required to determine gas concentrations accurately. Tests involving on/off cycles showed that the auxiliary electrode signal experiences exponential decay before stabilizing, requiring the exclusion of initial readings during monitoring activities. Additionally, calibration experiments in zero air allowed the determination of the compensation factor nT across different temperatures and humidity levels. These results highlight the importance of compensating for temperature and humidity effects to improve the accuracy and reliability of NO2 measurements using low-cost electrochemical sensors. This refinement makes the calibration applicable across a broader range of environmental conditions. However, the experiments also show a lack of repeatability in the zero air calibration.

Study of Neural Network Architectures for Determining Gas Concentrations by Spectra

A study of a number of neural networks of different architectures for determining gas concentrations from spectra obtained using an optical emission gas analyzer, which measures the spectrum of electromagnetic radiation emitted by gases when excited by an electric discharge, is presented. The neural network is trained on data from the optical spectroscopy laboratory and is able to predict gas concentrations from spectra at high speed. The research concerned the deep neural network architectures with convolutional and recurrent layers. Convolutional layers highlight the features of the spectra, while recurrent layers take into account the consistent structure of the data. The quality of the neural network is evaluated by the R2 coefficient of determination, and the comparison between networks by the RMSE indicator between the predicted and real gas concentrations.

Self-calibrated NICE-OHMS based on an asymmetric signal: theoretical analysis and experimental validation.

As an ultra-sensitive detection technique, the noise-immune cavity enhanced optical heterodyne molecular spectroscopy (NICE-OHMS) technique has great potential for assessment of the concentration of trace gases. To determine gas concentrations at the ppt or lower level with high accuracy, it is desirable that the technique exhibits self-calibration (or calibration-free) capabilities. Although being sensitive, NICE-OHMS has so far not demonstrated any such ability. To remedy this, this paper provides a self-calibrated realization of NICE-OHMS that is based on a switching of the feedback target of the DeVoe-Brewer (DVB) locking procedure from the modulation frequency of the frequency modulation spectroscopy (FMS) to the cavity length, which creates an asymmetrical signal whose form and size can be used to unambiguously assess the gas concentration. A comprehensive theoretical model for self-calibrated NICE-OHMS is established by analyzing the shift of cavity modes caused by intracavity absorption, demonstrating that gas absorption information can be encoded in both the laser frequency and the NICE-OHMS signal. To experimentally verify the methodology, we measure a series of dispersion signals under different levels of absorbance using a built experimental setup. An instrument factor and the partial pressure are obtained by fitting the measured signal through theoretical expressions. Our results demonstrate that fitted values are more accurate for higher partial pressures than for lower. To improve on the accuracy at low partial pressures, it is shown that the instrument factor obtained by fitting the signal at large partial pressures (in this case, above 7.8 µTorr) can be set to a fixed value for all fits. By this, the partial pressures can be assessed with a relative error below 0.65%. This technique has the potential to enable calibration-free ultra-sensitive gas detection.

Investigation of adsorption-desorption characteristics of CO and H2 on Cu2+ doped SnO2 for identifying gas components by temperature modulation

The identification and quantification of mixed gas species have been still the research hotspot and difficulty of resistive gas sensor. In this work, Cu 2+ doped SnO 2 gas-sensing materials were prepared to quantitatively identify CO and H 2 gas mixture, and PID (Proportional-Integral-Differential) temperature control technology was combined to test the temperature modulation of gas-sensing materials more precisely. The results show that under the condition of Cu 2+ doping, the gas sensing performance for SnO 2 gas-sensing materials are improved, mainly because of the oxygen vacancy and the lattice distortion caused by doping. On the basis of this, the resistance value and the ratio of following-up time were taken as static and dynamic factors respectively to quantificationally distinguish CO and H 2 components. The resistance value and the following-up time ratio under different condition of temperature modulation were used to establish preliminarily a novel model for quantitatively determining the gas concentration, where the possibility of the composition of the two gases was first determined by the following-up time ratio, and then the gas concentration was determined by the comparison of the resistance. The simple mathematical model lays a foundation for the quantitative analysis of multicomponent gases. • Cu 2+ doped SnO 2 gas-sensing material were successfully prepared. • Effect of Cu 2+ on crystal structure and gas sensing performance was investigated. • PID technology was combined to ensure the accuracy of temperature modulation. • The dynamic and static adsorption-desorption characteristics of gas were analyzed. • A new model for quantitatively determining gas concentration is established.

Determination of the Radon Concentration of Gas 222Rn Emitted From Sludge Samples Located in the Radioactive Waste Collection Warehouse in Khader Al-Maa South of Basra City – Iraq

Thirty-one samples of sludge were taken, stored at the natural radioactive waste collection site, NORM, in Khidir Al-Maa, south of Basra city, resulting from the operations of extracting and filtering crude oil in oil fields in Basra Oil Company, to determine gas concentrations Radon 222Rn and other radioisotopes in Sludge models. The rapid electronic technology was adopted through the RAD7 device, the active method, and the gamma analysis technique using HPGe High Purity Germanium Detectors to determine the specific activity of radioactive elements. The measurements for this study showed 98463±7031 Bq.m-3 in sample no. S10 a barrel of sludge was brought from the third Degassing Station plant in the northern Rumaila oil field and least concentrated is 8317±594 Bq.m-3 in sample no. S14 sludge belonging to the sixth Degassing Station / West Qurna-1, the study also revealed the presence of high concentrations of the specific effectiveness of radioactive isotopes (214Pb, 212Bi, 226Ra) and (212Pb, 212Bi, 228Ac) of the uranium-238 series and Thorium-232 series in a sludge form selected from a barrel returning to the third gas isolation plant - North Rumaila Oilfield and stockpile at the collection site, where the specific activity value of radium was 226 Ra 133851 Bq.k-1 of the uranium-238 series and for lead 212Pb 56432 Bq.k-1 of For uranium-238 series compared to their concentrations, 32 Bq.k-1 45 Bq.k-1 in a natural soil model. The effective dose to which on-site workers would be exposed in contact was calculated and found to be 196.92 Svh-1, a dose that exceeded the proposed 50 Sv. h-1 dose limits by the US EPA. The probability of developing cancer due to exposure to radon per million people was found and it was found to be a high value compared to the suggested value (170-230) per million people previously by ICRP.

Selective gas detection of H2 and CO by a single MOX-sensor

Abstract The temperature modulation of the SnO 2 -based metal oxide sensor with the addition of PdO x opened up the possibility of selective analysis of both conventionally one-component systems “hydrogen in air”, “carbon monoxide in air” and conditionally two-component system “hydrogen and carbon monoxide in air”. The aim of this work was the quantitative and qualitative analysis of gases using a single MOX sensor based on a small number of training sample concentrations in the range from 1 to 100 ppm. Gas concentrations in test experiments differed from gas concentrations in the training sample. We also studied the effect of air humidity on the error of the selective determination of gas concentrations in conventionally one- and two-component systems. To reduce multidimensional data in determining analyte concentrations, we used a specific combination of PCA regression analysis algorithms. The temperature modulation of the SnO 2 -sensor with the addition of PdO x allowed us to increase the sensor responses for concentrations from 10 to 100 ppm by about two orders of magnitude compared to the stationary temperature regime.

Моніторинг концентрацій газів, розчинених у трансформаторному маслі, під час експлуатації силового трансформаторного обладнання

The peculiarities of application of stationary gas analyzers of power oil of filled equipment in main and distribution networks, as well as at power generation enterprises are analyzed. The problem of discrepancies in the values of concentrations of gases dissolved in oil obtained from stationary gas analyzers in the mode of continuous monitoring and obtained by the results of tests of transformer oil samples performed by laboratory chromatographers is investigated. A comparative analysis of different principles for measuring gas concentrations based on two groups of methods: chromatography method and infrared spectroscopy methods by Bouguer–Lambert–Beer law. The features of application, advantages and disadvantages of the main methods of infrared spectroscopy are considered. The results of the laboratory comparison of the analysis of the mixture of reference gases and the analysis of gases obtained from oil-filled transformer equipment, which is in operation, conducted by a stationary gas analyzer and laboratory. It is established that both laboratory devices and stationary gas analyzers have similar errors in determining gas concentrations in prepared laboratory mixtures. The coefficients of linear regression, constructed as a function of dependence of the indications of a stationary gas analyzer on the indications of a laboratory device, are given, when analyzing the same oil samples. Conclusions were made about the main reasons that affect the discrepancy of the obtained results, which allowed to determine the feasibility of using stationary gas analyzers, on the basis of spectroscopy, as devices capable of fixing the trend of increasing gas concentrations, and to make decisions on unscheduled oil samples for laboratory analysis based on their indications.

Алгоритмы обработки данных отклика чувствительных элементов сенсоров газа в химически агрессивных средах

Currently, much attention is paid to environmental monitoring. This is in many cases characterized by the use of highly efficient solid state gas analyzers based on semiconductors. At the same time, it is necessary not only to use high-quality components, but also to process data quickly, meeting the requirements for accuracy and quality. Such processing makes it possible to diagnose the current performance of sensors, more accurately and faster determine the concentration of the target gas, and control the characteristics. The study introduces a method for processing the response data of the sensitive elements of gas sensors in chemically aggressive media, including the construction of calibration dependencies which increase the accuracy of determining gas concentrations

A Fiber-Optic Gas Sensor and Method for the Measurement of Refractive Index Dispersion in NIR.

This paper presents a method for gas concentration determination based on the measurement of the refractive index dispersion of a gas near the gas resonance in the near-infrared region (NIR). The gas refractive index dispersion line shape is reconstructed from the variation in the spectral interference fringes’ periods, which are generated by a low-finesse Fabry-Perot interferometer during the DFB diode’s linear-over-time optical frequency sweep around the gas resonance frequency. The entire sensing system was modeled and then verified experimentally, for an example of a low concentration methane-air mixture. We demonstrate experimentally a refractive index dispersion measurement resolution of 2 × 10−9 refractive index units (RIU), which corresponds to a change in methane concentration in air of 0.04 vol% at the resonant frequency of 181.285 THz (1653.7 nm). The experimental and modeling results show an excellent agreement. The presented system utilizes a very simple optical design and has good potential for the realization of cost-efficient gas sensors that can be operated remotely through standard telecom optical fibers.

Application of Neural Networks in the Problem of Quantitative Analysis of Air Composition

Purpose of reseach is to develop a method for generating training data to enable the use of artificial neural networks (ANN) method in gas analyzer systems. The problem of increasing the accuracy of separate determination of gas concentrations in multicomponent mixtures under conditions of environmental parameters changes is considered. It is proposed to increase the accuracy of determining target gas concentrations by using the ANN method for joint processing of sensor signals.Methods: Training data for the neural network were generated using numerical experiments and mathematical simulation methods. To assess the accuracy of training, the standard deviation (SD) was used and the relative error was calculated. ANN training and research were conducted in the MATLAB environment (the Neural Networks Toolbox application). When developing mathematical models of gas sensors, the theory of electrical circuits, electronic theory of chemisorption and the adsorption theory of heterogeneous catalysis were applied.Results: A method for generating training data sets using mathematical models of gas sensors is described. The proposed training method has been tested on a specific task, in particular, a decision-making device based on ANN for a four-component gas analyzer has been developed. The efficiency of using neural networks for tuning out from the mutual cross-sensitivity of sensors was evaluated.Conclusion: A method for generating training data using simulation models is proposed, which allows automazing the process of training, research, choosing the architecture and structure of ANN and their testing. The method was tested. Based on the analysis of the obtained errors, conclusions are made about the efficiency of using neural networks to reduce errors caused by cross sensitivity at different concentrations of the main and interfering gases.

Low-cost method for quantification of hydrogen and methane in continuous flow bioreactors

Bioreactors of industrial scale for gaseous biofuels constitute a field of research worldwide. Automation at a profitable technical and economic level has not been possible because of fluctuating biological systems. The quantification of biogas in continuous flow is difficult to implement by Gas Chromatography and it is very expensive in account of special sensors. In this work, we developed a system with MQ8 hydrogen and MQ4 methane sensors, used in the detection of industrial leaks, for the determination of gas concentration. The sensors were installed on Arduino cards and programmed to plot the concentration in real time. Calibration curves were made for these sensors making use of a standardized mixture of gases, in hermetic jars of known volume. The result is exponential and reproducible, and when using real biogas samples, no problems of interference with other gases are observed. The prototypes are very low cost with respect to the GC equipment and can be installed at the gas outlet of bioreactors with a mechatronic system that allows the monitoring of the composition in real time, which will allow to obtain microbial kinetics in semi-continuous flow in a very economical way.

Role of Spectral Line Profile in Laser IR Analysis of Multicomponent Gas Mixtures

Topical issues of the quantitative analysis of multicomponent gas mixtures with use of laser absorption infrared technologies are addressed. It is shown that a number of questions exist regarding the detection of pollutants using these technologies, and these concern not only the position of the center of the analytical line of the detected substance but also the shape of its profile, especially in case of strong intermolecular interactions under conditions of open atmosphere. A number of examples show various aspects of the influence of the error of the spectroscopic model embedded in the solution of the inverse problem (the width and shape of the laser spectral line and gas absorption lines) on the determination of gas concentrations. The parameters of the sensitivity and selectivity of laser gas analysis that support making the optimal choice of laser radiation frequencies for studying specific gas mixtures are discussed. The importance of the high monochromaticity of laser lines, the smooth tuning of the radiation frequency over a wide spectral range, and the adequate simulation of the IR spectra of multicomponent gas mixtures are demonstrated.

Open-circuit respirometry: real-time, laboratory-based systems.

This review explores the conceptual and technological factors integral to the development of laboratory-based, automated real-time open-circuit mixing-chamber and breath-by-breath (B × B) gas-exchange systems, together with considerations of assumptions and limitations. Advances in sensor technology, signal analysis, and digital computation led to the emergence of these technologies in the mid-20th century, at a time when investigators were beginning to recognise the interpretational advantages of nonsteady-state physiological-system interrogation in understanding the aetiology of exercise (in)tolerance in health, sport, and disease. Key milestones include the 'Auchincloss' description of an off-line system to estimate alveolar O2 uptake B × B during exercise. This was followed by the first descriptions of real-time automated O2 uptake and CO2 output B × B measurement by Beaver and colleagues and by Linnarsson and Lindborg, and mixing-chamber measurement by Wilmore and colleagues. Challenges to both approaches soon emerged: e.g., the influence of mixing-chamber washout kinetics on mixed-expired gas concentration determination, and B × B alignment of gas-concentration signals with respired flow. The challenging algorithmic and technical refinements required for gas-exchange estimation at the alveolar level have also been extensively explored. In conclusion, while the technology (both hardware and software) underpinning real-time automated gas-exchange measurement has progressively advanced, there are still concerns regarding accuracy especially under the challenging conditions of changing metabolic rate.

Using the Transient Response of WO₃ Nanoneedles under Pulsed UV Light in the Detection of NH₃ and NO₂.

Here we report on the use of pulsed UV light for activating the gas sensing response of metal oxides. Under pulsed UV light, the resistance of metal oxides presents a ripple due to light-induced transient adsorption and desorption phenomena. This methodology has been applied to tungsten oxide nanoneedle gas sensors operated either at room temperature or under mild heating (50 °C or 100 °C). It has been found that by analyzing the rate of resistance change caused by pulsed UV light, a fast determination of gas concentration is achieved (ten-fold improvement in response time). The technique is useful for detecting both oxidizing (NO2) and reducing (NH3) gases, even in the presence of different levels of ambient humidity. Room temperature operated sensors under pulsed UV light show good response towards ammonia and nitrogen dioxide at low power consumption levels. Increasing their operating temperature to 50 °C or 100 °C has the effect of further increasing sensitivity.

Determination of gas concentration in the lubricant of transmissions of energy-saturated agricultural tractors

Ensuring the trouble-free operation of the transmission during the operation of energy-saturated tractors is an important task. The reliability of its operation largely depends on the presence of gas in the lubrication system. The aim of the study is to develop a methodology for determining the quantitative content of gas in a gas-oil mixture. In the tractor transmissions, the composition of the gas-oil mixture can have different values, which are determined mainly by the geometric dimensions of the elements of the assembly units, the speed mode of operation, the temperature and the grade of the lubricant. The influence of these parameters can be determined by recording the composition of the gas-oil mixture during tests, both assembly units and transmissions in general, when mounted on a test bench or on a tractor. The choice of the method for recording the composition of a gas-oil mixture was carried out on the basis of an analysis of a number of studies in which various techniques for analyzing the composition of two-phase mixtures are given. Demonstrating the requirement of universality of the method, consisting in a uniform method of its application, both in bench and in object conditions, the most interesting is the method associated with sample sludge. The most successful points of the transmission lubrication system are suggested, from which it is most convenient to take samples, as well as those characterized by the largest content of gas in the oil. Also the most simple and informative method for determining the volumetric gas content in the mixture is proposed. Calculated dependences are derived, allowing to take into account the change in the volumetric ratio of oil to gas during the sampling time. The developed method allows to make an assessment of the required capacity of bilge pumps of forced lubrication systems. The technique can be used both for bench and for road tests.

Multi-parameter monitoring of binary gas mixtures: Concentration and flow rate by DC excitation of thermal sensor arrays

Abstract This contribution presents a thermal sensor, which is capable of simultaneously determining gas concentrations of a binary gas mixture under flow conditions and its flow rate. The sensor design corresponds to the calorimetric principle. The multi-parameter detection is achieved by the use of two time independent excitation modes (power and temperature). Due to the developed sensor design, a flow independent, but gas sensitive region is obtained in power mode. In this flow range, the thermal conductivity is measured by analyzing the temperature of the downstream element. Gas concentration of the binary gas mixture is derived from the theoretical relationship to thermal conductivity. Afterwards, the flow rate is detected by evaluating the temperature difference between the down- and upstream temperature sensors in temperature excitation mode. This measurement technique has been successfully proven under laboratory conditions, where a flowing mixture of e.g. methane and carbon dioxide has been analyzed. The carried out measurements show an accuracy of ±5% in gas concentration and of ±3.3% in flow rate. This measuring method seems to be sufficient to analyze biogas in anaerobic distinctions. However, further investigation is needed to open this technique for this application.

The Application of Noninvasive Headspace Analysis to Media Fill Inspection.

A novel analytical technique has been demonstrated for detecting microbial growth in media-filled pharmaceutical containers. This analytical technique, laser-based headspace analysis, uses tunable diode laser absorption spectroscopy to determine gas concentrations in the headspace of a pharmaceutical container. For detecting microbial growth, the levels of headspace oxygen and carbon dioxide are measured. The study shows that once aerobic microorganisms begin to grow after the lag phase and enter the exponential growth phase there will be a significant consumption of oxygen in the sealed container as well as a corresponding production of carbon dioxide. Headspace analysis can accurately measure and monitor these changes in the headspace gas composition and could therefore be used to detect contaminated pharmaceutical containers. Because the technique can be automated to analyze hundreds of containers a minute on-line, there are opportunities for implementing a headspace inspection machine to perform automated inspection of media fills used to validate aseptic filling operations.

Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm

Abstract 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.

Novel Gas Concentration Measurements based on Harmonic Detection and a Broadband Light Source

The determination of gas concentration based on harmonic detection was studied theoretically and experimentally. The principle of second harmonic detection technology based on a broadband light source and the impact of modulation parameters on the harmonic signals were analyzed theoretically. The principles of multiple modulation were analyzed in order to improve the detection resolution. A fiber Bragg grating bonded to a carbon fiber cantilever was designed to achieve wavelength modulation. The impact of the modulation frequency and voltage amplitude on the second harmonic signals were studied experimentally. The output of the detector and the impact of the random noise were analyzed at different modulation frequencies and amplitudes. The optimum frequency and amplitude were determined to be 40 Hz and 2 V. The measurement of acetylene was carried out using this system. The results show that the gas measurement limit was 500 ppm, the stability was 3.92%, and the system sensitivity was 1 µV/ppm.