Currently Commercially Available Chemical Sensors Employed for Detection of Volatile Organic Compounds in Outdoor and Indoor Air

A Low-Cost Method for Producing User-Specified Concentrations of VOCs

Monitoring volatile organic compounds is critical to mitigate the risks they pose to human health and the environment. Developing technologies for detection of VOCs requires methods to produce the desired concentrations for benchmarking. Herein, we present a simple, inexpensive, and flexible platform capable of producing user-specified concentrations of a gas-phase analyte for the purpose of fine-tuning and benchmarking VOC detection technologies. This technology, the gas-phase dilution apparatus (GPDA), is built around two mass flow controllers that mix precise flows of the analyte and dilution gas. We used a custom APPI-MS configuration as well as a commercial photoionization detector to detect benzene and toluene. These two detection methods were employed to assess the linear output of concentrations over a combined range of 1-20 000 ppbV which yielded average R2 values of 0.9980 and 0.9988 for benzene and toluene, respectively. Additionally, output stability was assessed at 10 ppbV, 1 ppmV, and 5 ppmV of benzene and toluene. Six measurements were averaged over the course of 30 min, and RSDs were below 2% for all three concentrations of both compounds. These results suggest that GPDA is capable of producing precise and repeatable concentrations of gas-phase analytes.

Enhanced sensitivity of chimeric insect olfactory co-receptors for detecting odorant molecules

Insect olfactory receptors (ORs) are seven-transmembrane domain ion channels that function by forming heteromeric complexes with olfactory receptor co-receptors (Orcos). In this study, we investigated the potential for enhancing sensitivity of odor detection and responsivity through genetic modification of Orcos, considering its wider application in odor sensing. First, we measured the intensity of response to 1-octen-3-ol for the mosquito Aedes aegypti OR (AaOR8) when complexed individually with an Orco from the same mosquito (AaOrco), the honeybee Apis mellifera (AmOrco), the silkworm Bombyx mori (BmOrco), or the fruit fly Drosophila melanogaster (DmOrco). Relative to the other Orcos, AmOrco demonstrated higher sensitivity and responsivity, with a 1.8 to 21-fold decrease in the half-maximal effective concentration (EC50) and a 1.6-8.8-fold increase in the maximal effect (Emax), respectively. Furthermore, AmOrco co-expressed with AaOR10, BmOR56, or DmOR47a showed higher sensitivity and responsivity than AaOrco, BmOrco, or DmOrco co-expressed with their respective ORs. To further increase sensitivity and responsivity, we engineered chimeric Orcos by fusing AmOrco with DmOrco, considering the domain characteristics of Orcos. The response to 1-octen-3-ol was evaluated for AaOR8 when complexed individually with AmOrco, as well as for a mutant that combines DmOrco from the N-terminal (NT) to the C-terminal region of the fourth transmembrane domain (TM4) with the region of AmOrco following TM4 (Dm[NT-TM4]AmOrco). When compared to AmOrco, Dm(NT-TM4)AmOrco showed higher sensitivity and responsivity, with a 1.4-fold decrease in the EC50 and a 1.4-fold increase in the Emax, respectively. In addition, Dm(NT-TM4)AmOrco co-expressed with either DmOR47a or BmOR56 demonstrated higher sensitivity and responsivity than AmOrco co-expressed with their respective ORs. These results suggest that AmOrco could be a relatively more sensitive Orco, and further enhancement of sensitivity and responsivity could be achieved through recombination with heterologous Orcos near the TM4 of AmOrco.

New Architecture Based on Metal-Organic Frameworks and Spin Crossover Complexes to Detect Volatile Organic Compounds

We present here the encapsulation of a spin crossover complex C1 [FeII(L)] (L: 4-amino-, 2-(2-pyridinylmethylene)hydrazide) inside MOF-808(Zr), a chemically robust Metal-Organic Framework. The compound C1⊂MOF-808 retains its crystallinity as well as a partial porosity compared to pristine MOF and shows solvatochromism under Volatile Organic compounds (VOCs) sorption associated to a spin state change of the guest complex. More specifically, this compound shows an interesting reversible color change under formaldehyde and formic acid vapor sorption and can therefore be considered as a new kind of optical VOCs chemosensor, opening new doors for developing a broad range of VOCs optical sensors.

Co3O4-Based Materials as Potential Catalysts for Methane Detection in Catalytic Gas Sensors

The present work deals with the development of Co3O4-based catalysts for potential application in catalytic gas sensors for methane (CH4) detection. Among the transition-metal oxide catalysts, Co3O4 exhibits the highest activity in catalytic combustion. Doping Co3O4 with another metal can further improve its catalytic performance. Despite their promising properties, Co3O4 materials have rarely been tested for use in catalytic gas sensors. In our study, the influence of catalyst morphology and Ni doping on the catalytic activity and thermal stability of Co3O4-based catalysts was analyzed by differential calorimetry by measuring the thermal response to 1% CH4. The morphology of two Co3O4 catalysts and two NixCo3-xO4 with a Ni:Co molar ratio of 1:2 and 1:5 was studied using scanning transmission electron microscopy and energy dispersive X-ray analysis. The catalysts were synthesized by (co)precipitation with KOH solution. The investigations showed that Ni doping can improve the catalytic activity of Co3O4 catalysts. The thermal response of Ni-doped catalysts was increased by more than 20% at 400 °C and 450 °C compared to one of the studied Co3O4 oxides. However, the thermal response of the other Co3O4 was even higher than that of NixCo3-xO4 catalysts (8% at 400 °C). Furthermore, the modification of Co3O4 with Ni simultaneously brings stability problems at higher operating temperatures (≥400 °C) due to the observed inhomogeneous Ni distribution in the structure of NixCo3-xO4. In particular, the NixCo3-xO4 with high Ni content (Ni:Co ratio 1:2) showed apparent NiO separation and thus a strong decrease in thermal response of 8% after 24 h of heat treatment at 400 °C. The reaction of the Co3O4 catalysts remained quite stable. Therefore, controlling the structure and morphology of Co3O4 achieved more promising results, demonstrating its applicability as a catalyst for gas sensing.

Species-Selective Detection of Volatile Organic Compounds by Ionic Liquid-Based Electrolyte Using Electrochemical Methods

The detection of volatile organic compounds (VOCs) is an important topic for environmental safety and public health. However, the current commercial VOC detectors suffer from cross-sensitivity and low reproducibility. In this work, we present species-selective detection for VOCs using an electrochemical cell based on ionic liquid (IL) electrolytes with features of high selectivity and reliability. The voltammograms measured with the IL-based electrolyte absorbing different VOCs exhibited species-selective features that were extracted and classified by linear discriminant analysis (LDA). The detection system could identify as many as four types of VOCs, including methanol, ethanol, acetone, formaldehyde, and additional water. A mixture of methanol and formaldehyde was detected as well. The sample required for the VOCs classification system was 50 μL, or 1.164 mmol, on average. The response time for each VOC measurement is as fast as 24 s. The volume of VOCs such as formaldehyde in solution could also be quantified by LDA and electrochemical impedance spectroscopy techniques, respectively. The system showed a tunable detection range for 1.6 and 16% (w/v) CH2O solution by adjusting the composition of the electrolyte. The limit of detection was as low as 1 μL. For the 1.6% CH2O solution, the linearity calibration range was determined to be from 5.30 to 53.00 μmol with a limit of detection at 0.53 μmol. The mechanisms for VOCs determination and quantification are also thoroughly discussed. It is expected that this work could provide a new insight into the concept of electrochemical detection of VOCs with machine learning analysis and be applied to both VOCs gas monitoring and fluid detection.

Detection of Propionic Acids Trapped in Thin Zeolite Layer Using Thermal Desorption Analysis

Volatile organic compounds (VOCs) have recently received considerable attention for the analysis and monitoring of different biochemical processes in biological systems such as humans, plants, and microorganisms. The advantage of using VOCs to gather information about a specific process is that they can be extracted using different types of samples, even at low concentrations. Therefore, VOC levels represent the fingerprints of specific biochemical processes. The aim of this work was to develop a sensor based on a photoionization detector (PID) and a zeolite layer, used as an alternative analytic separation technique for the analysis of VOCs. The identification of VOCs occurred through the evaluation of the emissive profile during the thermal desorption phase, using a stainless-steel chamber for analysis. Emission profiles were evaluated using a double exponential mathematical model, which fit well if compared with the physical system, describing both the evaporation and diffusion processes. The results showed that the zeolite layer was selective for propionic acid molecules if compared to succinic acid molecules, showing linear behavior even at low concentrations. The process to define the optimal adsorption time between the propionic acid molecules was performed in the range of 5 to 60 min, followed by a thermal desorption process at 100 °C. An investigation of the relationship between the evaporation and diffusion rates showed that the maximum concentration of detected propionic acid molecules occurred in 15 min. Other analyses were performed to study how the concentration of VOCs depended on the desorption temperature and the volume of the analysis chamber. For this purpose, tests were performed using three analysis chambers with volumes of 25 × 10-6, 50 × 10-6, and 150 × 10-6 m3 at three different desorption temperatures of 20 °C, 50 °C, and 100 °C, respectively. The results demonstrated that the evaporation rate of the VOCs increased rapidly with an increasing temperature, while the diffusion rate remained almost constant and was characterized by a slow decay time. The diffusion ratio increased when using a chamber with a larger volume. These results highlight the capabilities of this alternative technique for VOC analysis, even for samples with low concentrations. The coupling of a zeolite layer and a PID improves the detection selectivity in portable devices, demonstrating the feasibility of extending its use to a wide range of new applications.

Nonequilibrium sensing of volatile compounds using active and passive analyte delivery

Although sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch, the development of artificial noses is significantly behind their biological counterparts. This largely stems from the sophistication of natural olfaction, which relies on both fluid dynamics within the nasal anatomy and the response patterns of hundreds to thousands of unique molecular-scale receptors. We designed a sensing approach to identify volatiles inspired by the fluid dynamics of the nose, allowing us to extract information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) rather than relying on a large sensor array. By accentuating differences in the nonequilibrium mass-transport dynamics of vapors and training a machine learning algorithm on the sensor output, we clearly identified polar and nonpolar volatile compounds, determined the mixing ratios of binary mixtures, and accurately predicted the boiling point, flash point, vapor pressure, and viscosity of a number of volatile liquids, including several that had not been used for training the model. We further implemented a bioinspired active sniffing approach, in which the analyte delivery was performed in well-controlled 'inhale-exhale' sequences, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. Our results outline a strategy to build accurate and rapid artificial noses for volatile compounds that can provide useful information such as the composition and physical properties of chemicals, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.

Retention Time Trajectory Matching for Peak Identification in Chromatographic Analysis

Retention time drift caused by fluctuations in physical factors such as temperature ramping rate and carrier gas flow rate is ubiquitous in chromatographic measurements. Proper peak matching and identification across different chromatograms is critical prior to any subsequent analysis but is challenging without using mass spectrometry. The purpose of this work was to describe and validate a peak matching and identification method called retention time trajectory (RTT) matching that can be used in targeted analyses free of mass spectrometry. This method uses chromatographic retention times as the only input and identifies peaks associated with any subset of a predefined set of target compounds. An RTT is a two-dimensional (2D) curve formed uniquely by the retention times of the chromatographic peaks. The RTTs obtained from the chromatogram of a sample under test and those pre-installed in a library are matched and statistically compared. The best matched pair implies identification. Unlike most existing peak-alignment methods, no mathematical warping or transformation is involved. Based on the experimentally characterized RTT, an RTT hybridization method was also developed to rapidly generate more RTTs and expand the library without performing actual time-consuming chromatographic measurements, which enables successful peak matching even for chromatograms with severe retention time drifts. Additionally, 3.15 × 10⁵ tests using experimentally obtained gas chromatograms and 2 × 10¹² tests using two publicly available fruit metabolomics datasets validated the proposed method, demonstrating real-time peak/interferent identification.

Evaluation of Red Wine Acidification Using an E-Nose System with Venturi Tool Sampling

The quality of wine is checked both during the production process and upon consumption. Therefore, manual wine-tasting work is still valuable. Due to the nature of wine, many volatile components are released, and it is therefore difficult to determine which elements need to be controlled. Acetic acid is one of the substances found in wine and is a crucial substance for wine quality. Gas sensor systems may be a potential alternative for manual wine tasting. In this work, we have developed a TGS2620 gas sensor module to analyze acetic acid levels in red wine. The gas sensor module was refined according to the Venturi effect along with signal slope analysis, providing promising results. The example included in this paper demonstrates that there is a direct relationship between the slope of the MOS gas sensor response and the acetic acid concentration. This relationship is useful to evaluate the ethanol oxidation in acetic acid in red wine during its production process.

Portable FBAR based E-nose for cold chain real-time bananas shelf time detection

Being cheap, nondestructive, and easy to use, gas sensors play important roles in the food industry. However, most gas sensors are suitable more for laboratory-quality fast testing rather than for cold-chain continuous and cumulative testing. Also, an ideal electronic nose (E-nose) in a cold chain should be stable to its surroundings and remain highly accurate and portable. In this work, a portable film bulk acoustic resonator (FBAR)-based E-nose was built for real-time measurement of banana shelf time. The sensor chamber to contain the portable circuit of the E-nose is as small as a smartphone, and by introducing an air-tight FBAR as a reference, the E-nose can avoid most of the drift caused by surroundings. With the help of porous layer by layer (LBL) coating of the FBAR, the sensitivity of the E-nose is 5 ppm to ethylene and 0.5 ppm to isoamyl acetate and isoamyl butyrate, while the detection range is large enough to cover a relative humidity of 0.8. In this regard, the E-nose can easily discriminate between yellow bananas with green necks and entirely yellow bananas while allowing the bananas to maintain their biological activities in their normal storage state, thereby showing the possibility of real-time shelf time detection. This portable FBAR-based E-nose has a large testing scale, high sensitivity, good humidity tolerance, and low frequency drift to its surroundings, thereby meeting the needs of cold-chain usage.

On-Site Detection of Volatile Organic Compounds (VOCs)

Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.

Micromachined Thermal Gas Sensors-A Review

In recent years, there has been a growing desire to monitor and control harmful substances arising from industrial processes that impact upon our health and quality of life. This has led to a large market demand for gas sensors, which are commonly based on sensors that rely upon a chemical reaction with the target analyte. In contrast, thermal conductivity detectors are physical sensors that detect gases through a change in their thermal conductivity. Thermal conductivity gas sensors offer several advantages over their chemical (reactive) counterparts that include higher reproducibility, better stability, lower cost, lower power consumption, simpler construction, faster response time, longer lifetime, wide dynamic range, and smaller footprint. It is for these reasons, despite a poor selectivity, that they are gaining renewed interest after recent developments in MEMS-based silicon sensors allowing CMOS integration and smart application within the emerging Internet of Things (IoT). This timely review focuses on the state-of-the-art in thermal conductivity sensors; it contains a general introduction, theory of operation, interface electronics, use in commercial applications, and recent research developments. In addition, both steady-state and transient methods of operation are discussed with their relative advantages and disadvantages presented. Finally, some of recent innovations in thermal conductivity gas sensors are explored.

Estimating the relationship between liquid- and vapor-phase odorant concentrations using a photoionization detector (PID)-based approach

Olfactory studies frequently utilize odor stimuli consisting of volatiles created from liquid dilutions of various chemicals. A problem arises if the researcher relies on these liquid dilutions to extrapolate vapor concentrations based on ideal gas behavior. For most chemicals, the relationship between liquid and vapor concentration deviates from these laws of proportionality due to interactions between the chemical and the solvent. Here, we describe a method to estimate vapor-phase concentrations of diluted odorants using a photoionization detector. To demonstrate the utility of this method, we assessed the relationship between liquid-/vapor-phase concentrations for 14 odorants (7 alcohols, 1 ester, and 6 aldehydes) in 5 different solvents (water, mineral oil, diethyl phthalate, dipropylene glycol, and propylene glycol). An analysis of 7 additional esters is also included to assess how carbon chain length and functional group, interacts with these solvents (for a total of 105 odorant/solvent pairs). Our resulting equilibrium equations successfully corrected for behavioral sensitivity differences observed in mice tested with the same odorant in different solvents and were overall similar to published measurements using a gas chromatography-based approach. In summary, this method should allow researchers to determine the vapor-phase concentration of diluted odorants and will hopefully assist in more accurate comparisons of odorant concentrations across olfactory studies.

Field application of cost-effective sensors for the monitoring of NH3, H2S, and TVOC in environmental treatment facilities and the estimation of odor intensity

Odor is usually a complex mixture of various compounds. In many countries, odor complaints have been addressed using the air dilution olfactory method (ADOM) to reduce their malodor complaint. In this study, continuous monitoring of ammonia, hydrogen sulfide, and total volatile organic compounds (TVOC) using sensors was conducted in facilities for municipal and livestock wastewater treatment (LWT), and for food waste composting (FWC). Odor intensity was modeled by multivariate linear regression using sensor monitoring data with air dilution measured by the ADOM. In testing the performance of sensors in the lab, all three sensors showed acceptable values for linearity, accuracy, repeatability, lowest detection limit, and response time, so the sensors were acceptable for application in the field. In on-site real-time monitoring, the three sensors functioned well in the three environmental facilities during the testing period. Average ammonia and hydrogen sulfide concentrations were high in the LWT facility, while TVOC showed the highest concentration in the FWC facility. A longer sampling time is necessary for ammonia monitoring. Odor intensity from individual sensor data correlated well to complex odor measured by the ADOM. Finally, we suggest a protocol for field application of sensor monitoring and odor data reproduction.Implications: We suggest a protocol for the field application of sensor monitoring and odor data estimation in this study. This study can be useful to a policy maker and field operator to reduce odor emission through the determination of a more effective treatment technology and removal pathway for individual odorants.

Airborne Toluene Detection Using Metal-Organic Frameworks

The pollution of indoor air is a major worldwide concern in our modern society for people's comfort, health, and safety. In particular, toluene, present in many substances including paints, thinners, candles, leathers, cosmetics, inks, and glues, affects the human health even at very low concentrations throughout its action on the central nervous system. Its prevalence in many workplace environments can fluctuate considerably, which led to firm regulation with exposure limits varying between 50 and 400 ppm depending on exposure time. This therefore requires the development of technologies for an accurate detection of this contaminant. Metal-organic frameworks have been proposed as promising candidates to detect and monitor a series of molecules at even extremely low concentrations owing to the high tunability of their functionality. Herein, a high-throughput Monte Carlo screening approach was devised to identify the best MOFs from the computation-ready, experimental (CoRE) metal-organic framework (MOF) density-derived electrostatic and chemical (DDEC) database for the selective capture of toluene from air at room temperature, with the consideration of a ternary mixture composed of extremely low-level concentration of toluene (10 ppm) in oxygen and nitrogen to mimic the composition of air. An aluminum MOF, DUT-4, with channel-like micropores was identified as an excellent candidate for the selective adsorption of toluene from air with a predicted adsorption uptake of 0.5 g/g at 10 ppm concentration and room temperature. The toluene adsorption behavior of DUT-4 at low equivalent concentrations, alongside its sensing performance, was further experimentally investigated by its incorporation in a quartz crystal microbalance sensor, confirming the promises of DUT-4. Decisively, the resulting high sensitivity and fast kinetics of our developed sensor highlight the applicability of this hand-in-hand computational-experimental methodology to porous material screening for sensing applications.

Naphthalene Detection in Air by Highly Sensitive TiO2 Sensor: Real Time Response to Concentration Changes Monitored by Simultaneous UV Spectrophotometry

Volatile low-weight polycyclic aromatic hydrocarbons (PAHs) are known to be potentially toxic to humans and animals. Their detection in ambient air has been of great interest in recent years and various detection methods have been implemented. In this study, we used naphthalene as a basic model of such compounds and constructed our own version of a titanium oxide-based sensor system for its detection. The main goal of the study was to clearly demonstrate the effectiveness of this type of sensor, record its response under well-controlled conditions, and compare that response to concentration measurements made by the widely accepted spectrophotometric method. With that goal in mind, we recorded the sensor response while monitoring naphthalene vapor concentrations down to 95 nM as measured by spectrophotometry. Air flow over the sensor was passed continuously and sample measurements were made every 3 min for a period of up to 2 h. Over that period, several cycles of naphthalene contamination and cleaning were implemented and measurements were recorded. The relative humidity and temperature of the air being sampled were also monitored to assure no major variations occurred that could affect the measurements. The sensor showed high sensitivity and a reproducible response pattern to changes in naphthalene concentration. It could be easily "cleaned" of the compound in ten minutes by means of the application of UV light and the passing of fresh air. Pending testing with other volatile PAH, this type of sensor proves to be an effective and inexpensive way to detect naphthalene in air.

Synergistic Effect of Surface Acidity and PtOx Catalyst on the Sensitivity of Nanosized Metal-Oxide Semiconductors to Benzene

Benzene is a potentially carcinogenic volatile organic compound (VOC) and its vapor must be strictly monitored in air. Metal-oxide semiconductors (MOS) functionalized by catalytic noble metals are promising materials for sensing VOC, but basic understanding of the relationships of materials composition and sensors behavior should be improved. In this work, the sensitivity to benzene was comparatively studied for nanocrystalline n-type MOS (ZnO, In₂O₃, SnO₂, TiO₂, and WO₃) in pristine form and modified by catalytic PtO_x nanoparticles. Active sites of materials were analyzed by X-ray photoelectron spectroscopy (XPS) and temperature-programmed techniques using probe molecules. The sensing mechanism was studied by in situ diffuse-reflectance infrared (DRIFT) spectroscopy. Distinct trends were observed in the sensitivity to benzene for pristine MOS and nanocomposites MOS/PtO_x. The higher sensitivity of pristine SnO₂, TiO₂, and WO₃ was observed. This was attributed to higher total concentrations of oxidation sites and acid sites favoring target molecules' adsorption and redox conversion at the surface of MOS. The sensitivity of PtO_x-modified sensors increased with the surface acidity of MOS and were superior for WO₃/PtO_x. It was deduced that this was due to stabilization of reduced Pt sites which catalyze deep oxidation of benzene molecules to carbonyl species.

The Application of In Situ Methods to Monitor VOC Concentrations in Urban Areas—A Bibliometric Analysis and Measuring Solution Review

Urbanisation development affects urban vegetation both directly and indirectly. Since this process usually involves a dramatic change in land use, it is seen as likely to cause ecological pressure on local ecosystems. All forms of human activity, including urbanisation of areas close to residential buildings, significantly impact air quality. This study aims to identify and characterise different measurement solutions of VOCs, allowing the quantification of total and selective compounds in a direct at source (in situ) manner. Portable devices for direct testing can generally be divided into detectors, chromatographs, and electronic noses. They differ in parameters such as operating principle, sensitivity, measurement range, response time, and selectivity. Direct research allows us to obtain measurement results in a short time, which is essential from the point of view of immediate reaction in the case of high concentrations of tested compounds and the possibility of ensuring the well-being of people. The paper also attempts to compare solutions and devices available on the market and assess their application.

Effect of the Dispersion Process and Nanoparticle Quality on Chemical Sensing Performance

On the surface of chemiresistive films, the scarce heterogeneity of a molecularly capped gold nanoparticle (MCGNP) colloidal dispersion and uneven evaporation of the MCGNP-contained drying drop applied to this surface are among the main factors that affect reproducibility, and repeatable fabrication of thin films of MCGNPs. This article shows that an increase in reproducibility and repeatability is possible using a dispersant and a surfactant during the deposition and annealing processes of the MCGNP. The results show higher sensitivity and accuracy of the sensors for the detection of volatile organic compounds in air and an increased limit of detection. These simple and practical additions might serve as a launching pad for fabrication of other types of thin-film-based sensors.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Electronic Noses and Their Applications for Sensory and Analytical Measurements in the Waste Management Plants-A Review

Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.

Selective Detection of Volatile Organics in a Mixture Using a Photoionization Detector and Thermal Desorption from a Nanoporous Preconcentrator

The selective detection of individual hazardous volatile organic compounds (VOCs) within a mixture is of great importance in industrial contexts due to environmental and health concerns. Achieving this with inexpensive, portable detectors continues to be a significant challenge. Here, a novel thermal separator system coupled with a photoionization detector has been developed, and its ability to selectively detect the VOCs isopropanol and 1-octene from a mixture of the two has been studied. The system includes a nanoporous silica preconcentrator in conjunction with a commercially available photoionization detector (PID). The PID is a broadband total VOC sensor with little selectivity; however, when used in conjunction with our thermal desorption approach, selective VOC detection within a mixture can be achieved. VOCs are adsorbed in the nanoporous silica over a 5 min period at 5 °C before being desorbed by heating at a fixed rate to 70 °C and detected by the PID. Different VOCs desorb at different times/temperatures, and mathematical analysis of the set of PID responses over time enabled the contributions from isopropanol and 1-octene to be separated. The concentrations of each compound individually could be measured in a mixture with limits of detection less than 10 ppb_v and linearity errors less than 1%. Demonstration of a separation of a mixture of chemically similar compounds, benzene and o-xylene, is also provided.

Low-Cost Sensors for Air Quality Monitoring - the Current State of the Technology and a Use Overview

In recent years the monitoring of air quality using cheap sensors has become an interesting alternative to conventional analytical techniques. Apart from vast price differences conventional techniques need to be performed by the trained personnel of commercial or research laboratories. Sensors capable of measuring dust, ozone, nitrogen and sulphur oxides, or other air pollutants are relatively simple electronic devices, which are comparable in size to a mobile phone. They provide the general public with the possibility to monitor air quality which can contribute to various projects that differ in regional scale, commercial funding or community-base. In connection with the low price of sensors arises the question of the quality of measured data. This issue is addressed by a number of studies focused on comparing the sensor data with the data of reference measurements. Sensory measurement is influenced by the monitored analyte, type and design of the particular sensor, as well as by the measurement conditions. Currently sensor networks serve as an additional source of information to the network of air quality monitoring stations, where the density of the network provides concentration trends in the area that may exceed specific measured values of pollutant concentrations and low uncertainty of reference measurements. The constant development of all types of sensors is leading to improvements and the difference in data quality between sensors and conventional monitoring techniques may be reduced.

Porous carbon nanoarchitectonics for the environment: detection and adsorption

As a post-nanotechnology concept, nanoarchitectonics has emerged from the 20th century to the 21st century. This review summarizes the recent progress in the field of metal-free porous carbon nanoarchitectonics.

A New Testing Facility to Investigate the Removal Processes of Indoor Air Contaminants with Different Cleaning Technologies and to Better Assess and Exploit Their Performances

Residential air cleaners exploiting different technologies re commonly used today to remove air contaminants from indoor environments. Different methods have been developed in the USA and Europe to test their efficiency. The one used in the USA provides a more comprehensive view of indoor processes, because testing is performed in a large simulation chamber (28.5 m3), using anthropogenic emissions, such as cigarette smoke, to generate pollution. Testing rooms are also important to investigate new removal technologies, or to improve them. Since no such testing facilities exist in Italy, one of 12.4 m3 was built in which cigarette smoke, resuspended dust from agricultural soil and, for the first time, diesel exhaust emissions were used to generate indoor pollution. Performances were tested with two air cleaning systems, exploiting completely different removal technologies. Accurate values of decay rates of indoor pollutants were obtained using a suite of on-line and out-of-line monitors for the measurement of particulate matter, volatile organic compounds (VOCs) and some inorganic gases. Proton-transfer mass spectrometry (PTR-MS) provided an almost real-time detection of several VOCs and H2S, at trace levels (0.01 ppbv). A method using a common in vitro bioassay was developed to assess the ability of air cleaners to remove indoor toxic substances.

Quantitative volatile organic compound sensing with liquid crystal core fibers

Polymer fibers with liquid crystals (LCs) in the core have potential as autonomous sensors of airborne volatile organic compounds (VOCs), with a high surface-to-volume ratio enabling fast and sensitive response and an attractive non-woven textile form factor. We demonstrate their ability to continuously and quantitatively measure the concentration of toluene, cyclohexane, and isopropanol as representative VOCs, via the impact of each VOC on the LC birefringence. The response is fully reversible and repeatable over several cycles, the response time can be as low as seconds, and high sensitivity is achieved when the operating temperature is near the LC-isotropic transition temperature. We propose that a broad operating temperature range can be realized by combining fibers with different LC mixtures, yielding autonomous VOC sensors suitable for integration in apparel or in furniture that can compete with existing consumer-grade electronic VOC sensors in terms of sensitivity and response speed.

Assessing volatile organic compound level in selected workplaces of Kathmandu Valley

Volatile organic compounds (VOCs) are one of the major contributors to poor indoor air quality. Due to advancements in sensor technologies, continuous if not regular monitoring total VOC (TVOC) and or some specific VOC in potential high risk workplaces is possible even in resource limited settings. In this study, we implemented a portable VOC sensor to measure concentration of TVOC and formaldehyde (HCHO) in six types of potential high risk workplaces (n = 56 sites) of Katmandu Valley. For comparison, concentration was also measured in immediate surroundings (n = 56) of all the sites. To get preliminary information on safety practices, a survey study was also conducted. The mean TVOC and HCHO concentration in the sites ranged from 1.5‒8 mg/m³ and <0.01–5.5 mg/m³, respectively. The indoor: outdoor TVOC and HCHO ratio (I/O) was found to be significantly higher (I/O > 1.5 and p < 0.05) in 34 (~61%) and 47 sites (∼84%), respectively. A strong positive correlation between HCHO and TVOC concentration was observed in furniture industry (R = 0.91) and metal workshops (R = 0.98). Interestingly, we found TVOC and HCHO concentration higher than WHO safe limit in ∼64% and ∼32% sites, respectively. A rough estimate of chronic daily intake (CDI) of formaldehyde showed that CDI is higher than WHO limit in four sites. These findings suggested that indoor air quality in the significant number of the workplaces is poor and possible measures should be taken to minimize the exposure.

Enhanced Refractive Index Sensitivity through Combining a Sol-Gel Adsorbate with a TiO2 Nanoimprinted Metasurface for Gas Sensing

We combine a gas-adsorbent microporous hybrid silica layer and a dense TiO2 Mie resonator array (metasurface), both obtained by sol-gel deposition and nanoimprint lithography, to form nanocomposite systems with high sensitivity for refractive index (RI) variations induced by gas adsorption. Using optical transduction based on direct specular reflection, we show spectral shifts of 4470 nm/RIU corresponding to 0.2 nm/ppm gas (air concentration) and reflection intensity changes of R* = 17 (R/RIU) and 0.55 × 10-3 R/ppm (air concentration). The metasurface is composed of hexagonally arranged TiO2 nanopillar arrays, whereas the surrounding sensitive material is a class II microporous hybrid silica, containing methyl and phenyl covalently bonded organic functions. This hybrid layer shows efficient adsorption capability of volatile organic molecules such as isopropanol, which is used to induce slight variations of RI around the TiO2 antennas. Specular reflectance variations at 45° incidence and refractive index measurements are performed using a spectroscopic ellipsometer. The presence of the titania metasurface enhances the signal by almost an order of magnitude with respect to the 2D counterpart (simulated as an effective medium approximation) and is attributed to the antenna effect, enhancing the interaction of the confined electromagnetic wave with the sensitive microporous medium. This sol-gel nanocomposite system presents many advantages such as high throughput and low-cost elaboration of elements and a high chemical, mechanical, and thermal resistance, ensuring high stability as a potential gas-sensitive nanocomposite layer for long periods. This work is a case study of improving the sensitivity of sol-gel gas-sensitive materials in optical transduction, which will be exploited in further works to develop artificial noses.

Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots

In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous vapors, which especially do arise if accidents or leakages occur. For the fast detection of such or similar situations a modular IoT-sensor node was developed. The sensor node consists of four hardware layers, which can be configured individually regarding basic functionality and measured parameters for varying application focuses. In this paper the sensor node is equipped with two gas sensors (BME688, SGP30) for a continuous TVOC measurement. In investigations under controlled laboratory conditions the general sensors’ behavior regarding different VOCs and varying installation conditions are performed. In practical investigations the sensor node’s integration into simple laboratory applications using stationary and mobile robots is shown and examined. The investigation results show that the selected sensors are suitable for the early detection of solvent vapors in life science laboratories. The sensor response and thus the system’s applicability depends on the used compounds, the distance between sensor node and vapor source as well as the speed of the automation systems.

Optimization of training and measurement protocol for eNose analysis of urine headspace aimed at prostate cancer diagnosis

More than one million new cases of prostate cancer (PCa) were reported worldwide in 2020, and a significant increase of PCa incidence up to 2040 is estimated. Despite potential treatability in early stages, PCa diagnosis is challenging because of late symptoms' onset and limits of current screening procedures. It has been now accepted that cell transformation leads to release of volatile organic compounds in biologic fluids, including urine. Thus, several studies proposed the possibility to develop new diagnostic tools based on urine analysis. Among these, electronic noses (eNoses) represent one of the most promising devices, because of their potential to provide a non-invasive diagnosis. Here we describe the approach aimed at defining the experimental protocol for eNose application for PCa diagnosis. Our research investigates effects of sample preparation and analysis on eNose responses and repeatability. The dependence of eNose diagnostic performance on urine portion analysed, techniques involved for extracting urine volatiles and conditioning temperature were analysed. 192 subjects (132 PCa patients and 60 controls) were involved. The developed experimental protocol has resulted in accuracy, sensitivity and specificity of 83% (CI_95% 77-89), 82% (CI_95% 73-88) and 87% (CI_95% 75-94), respectively. Our findings define eNoses as valuable diagnostic tool allowing rapid and non-invasive PCa diagnosis.

Application of Chemical Sensors and Olfactometry Method in Ecological Audits of Degraded Areas

Mineral excavation is a common process throughout the world. The open pits remaining after the closure of a mine require well-considered and meticulous reclamation activities aimed at restoring the environmental properties of a given area. The inspections carried out in Poland indicate numerous irregularities in implementing the reclamation process. The research in this study was conducted in six measurement series and includes both chemical and olfactometry determinations by devices: multisensor portable gas detector and field olfactometer. Statistical analysis of the results obtained show high concentrations in ambient air of both chemical compounds (NH₃, VOCs, H₂S, CH₃SH) and odour, excluding the possibility of occurrence in the pit of only waste types contained in the administrative decision on reclamation. In addition to the unpleasant odour, the listed compounds can have dangerous effects on the health and life of living organisms. This paper presents a suitable method of control and detection of irregularities in the conducted processes. The main advantage is the relatively low cost of purchasing sensors and field olfactometers compared to other devices, and the possibility to test the polluted air in situ, without the risk of chemical processes occurring during transport of gas samples to the laboratory.

High-Sensitivity Micro-Gas Chromatograph-Photoionization Detector for Trace Vapor Detection

Rapid in situ detection and analysis of trace vapor concentrations at a sub-parts per billion to parts per trillion level remains a challenge for many applications such as indoor air-quality analysis and detection of explosives and narcotics. Micro-gas chromatography (μGC) together with a micro-photoionization detector (μPID) is a prominent method for portable analysis of complex vapor mixtures, but current μPID technology demonstrates poor detection performance compared to benchtop flame ionization detectors (FIDs). This work demonstrates the development of a significantly improved μPID with a sub-picogram detection limit (as low as ∼0.2 pg) comparable to or exceeding that of a benchtop FID, with a large linear dynamic range (>4 orders of magnitude) and robustness (high stability over 200 h of plasma activation). Based on this μPID, a complete μGC-PID system was built and tested on standard sample chromatograms in a laboratory setting to show the system's analytical capabilities and the detection limit down to sub-parts per trillion concentrations (as low as 0.14 ppt). Practical in-field chromatograms on breath and car exhaust were also generated to demonstrate applicability for in situ experimentation. This work shows that μGC-PID systems can be competitive with traditional GC-FID methods and thus opens a door to rapid trace vapor analysis in the field.

Feasibility of a Portable Electronic Nose for Detection of Oral Squamous Cell Carcinoma in Sudan

BACKGROUND

Oral squamous cell carcinoma (OSCC) is increasing at an alarming rate particularly in low-income countries. This urges for research into noninvasive, user-friendly diagnostic tools that can be used in limited-resource settings. This study aims to test and validate the feasibility of e-nose technology for detecting OSCC in the limited-resource settings of the Sudanese population.

METHODS

Two e-nose devices (Aeonose™, eNose Company, Zutphen, The Netherlands) were used to collect breath samples from OSCC (n = 49) and control (n = 35) patients. Patients were divided into a training group for building an artificial neural network (ANN) model and a blinded control group for model validation. The Statistical Package for the Social Sciences (SPSS) software was used for the analysis of baseline characteristics and regression. Aethena proprietary software was used for data analysis using artificial neural networks based on patterns of volatile organic compounds.

RESULTS

A diagnostic accuracy of 81% was observed, with 88% sensitivity and 71% specificity.

CONCLUSIONS

This study demonstrates that e-nose is an efficient tool for OSCC detection in limited-resource settings, where it offers a valuable cost-effective strategy to tackle the burden posed by OSCC.

The Use of Chemical Sensors to Monitor Odour Emissions at Municipal Waste Biogas Plants

Municipal waste treatment plants are an important element of the urban area infrastructure, but also, they are a potential source of odour nuisance. Odour impact from municipal waste processing plants raises social concerns regarding the well-being of employees operating the plants and residents of nearby areas. Chemical methods involve the determination of the quantitative composition of compounds comprising odour. These methods are less costly than olfactometry, and their efficiency is not dependent on human response. The relationship between the concentration of a single odorant and its odour threshold (OT) is determined by the odour activity value (OAV) parameter. The research involved the application of a multi-gas detector, MultiRae Pro. Measurements by means of the device were conducted at three municipal waste biogas plants located in Poland. In this paper we describe the results obtained when using a detector during the technological processes, the unitary procedures conducted at the plants, and the technological regime. The determination of these relationships could be useful in the development of odour nuisance minimization procedures at treatment plants and the adjustment to them. This is of paramount importance from the viewpoint of the safety and hygiene of the employees operating the installations and the comfort of residents in the areas surrounding biogas plants. Monitoring of expressed odorant emissions allows the course of technological processes and conducted unit operations to be controlled.

Fiber Optic Gas Sensors Based on Lossy Mode Resonances and Sensing Materials Used Therefor: A Comprehensive Review

Pollution in cities induces harmful effects on human health, which continuously increases the global demand of gas sensors for air quality control and monitoring. In the same manner, the industrial sector requests new gas sensors for their productive processes. Moreover, the association between exhaled gases and a wide range of diseases or health conditions opens the door for new diagnostic applications. The large number of applications for gas sensors has permitted the development of multiple sensing technologies. Among them, optical fiber gas sensors enable their utilization in remote locations, confined spaces or hostile environments as well as corrosive or explosive atmospheres. Particularly, Lossy Mode Resonance (LMR)-based optical fiber sensors employ the traditional metal oxides used for gas sensing purposes for the generation of the resonances. Some research has been conducted on the development of LMR-based optical fiber gas sensors; however, they have not been fully exploited yet and offer optimal possibilities for improvement. This review gives the reader a complete overview of the works focused on the utilization of LMR-based optical fiber sensors for gas sensing applications, summarizing the materials used for the development of these sensors as well as the fabrication procedures and the performance of these devices.

Low-Cost Benzene Toluene Xylene Measurement Gas System Based on the Mini Chromatographic Cartridge

Benzene, toluene and xylene (BTX) are an important part of the volatile organic compounds (VOCs) to be detected and monitored in the air, due to their toxicity towards human health. One of the most reliable technique used in BTX detection is gas chromatography (GC), which presents a high sensitivity. On the other hand, it has important drawbacks, such as high costs, the need for qualified personnel and frequent maintenance. To overcome these drawbacks, this work reports the development of a low cost and portable BTX gas detection system based on a mini chromatographic cartridge, a photo ionization detector (PID), a simple control unit (based on Arduino architecture) and a mini pump. In order to separate the BTX components, we propose the use of a cartridge 80 mm in length, composed of several commercial chromatographic column sections. To test the system performances, we have injected different amounts (from about 0.3 to 5.3 µg) of benzene, toluene and xylene and two of the most frequent possible interferents (ethanol, acetone). Experimental results have shown different retention time values (i.e., 25 ± 0.5 s, 51 ± 1.2 s and 117 ± 4 s, respectively) for benzene, toluene and xylene.

Metal Oxide Nanolayer-Decorated Epitaxial Graphene: A Gas Sensor Study

In this manuscript, we explore the sensor properties of epitaxially grown graphene on silicon carbide decorated with nanolayers of CuO, Fe₃O₄, V₂O₅, or ZrO₂. The sensor devices were investigated in regard to their response towards NH₃ as a typical reducing gas and CO, C₆H₆, CH₂O, and NO₂ as gases of interest for air quality monitoring. Moreover, the impact of operating temperature, relative humidity, and additional UV irradiation as changes in the sensing environment have been explored towards their impact on sensing properties. Finally, a cross-laboratory study is presented, supporting stable sensor responses, and the final data is merged into a simplified sensor array. This study shows that sensors can be tailored not only by using different materials but also by applying different working conditions, according to the requirements of certain applications. Lastly, a combination of several different sensors into a sensor array leads to a well-performing sensor system that, with further development, could be suitable for several applications where there is no solution on the market today.

Decision Support Algorithm Based on the Concentrations of Air Pollutants Visualization

As medical technologies are continuously evolving, consumer involvement in health is also increasing significantly. The integration of the Internet of Things (IoT) concept in the health domain may improve the quality of healthcare through the use of wearable sensors and the acquisition of vital and environmental parameters. Currently, there is significant progress in developing new approaches to provide medical care and maintain the safety of the life of the population remotely and around the clock. Despite the standards for emissions of harmful substances into the atmosphere established by the legislation of different countries, the level of pollutants in the air often exceeds the permissible limits, which is a danger not only for the population but also for the environment as a whole. To control the situation an Air Quality Index (AQI) was introduced. For today, many works discuss AQI, however, most of them are aimed rather at studying the methodologies for calculating the index and comparing air quality in certain regions of different countries, rather than creating a system that will not only calculate the index in real-time but also make it publicly available and understandable to the population. Therefore we would like to present a decision support algorithm for a solution called “Environmental Sensing to Act for a Better Quality of Life: Smart Health” with the primary goal of ensuring the transformation of raw environmental data collected by special sensors (data which typically require scientific interpretation) into a form that can be easily understood by the average user; this is achieved through the proposed algorithm. The obtained result is a system that increases the self-awareness and self-adaptability of people in environmental monitoring by offering easy to read and understand suggestions. The algorithm considers three types of parameters (concentration of PM10 (particulate matter), PM2.5, and NO₂) and four risk levels for each of them. The technical implementation is presented in a step-like procedure and includes all the details (such as calculating the Air Quality Index—AQI, for each parameter). The results are presented in a front-end where the average user can observe the results of the measurements and the suggestions for decision support. This paper presents a supporting decision algorithm, highlights the basic concept that was used in the development process, and discusses the result of the implementation of the proposed solution.

Mitochondrial DNA copy number and cytogenetic damage among fuel filling station attendants

Fuel filling attendants are constantly exposed to the complex mixture of gasoline and all refinery environments are probably carcinogenic for humans. These workers are considered as an unorganized group in India and unaware of the risk. The present study was focused to monitor workplace pollutants (particulate matter size 10 [PM10 μm], total volatile organic compound [VOC], and carbon monoxide [CO]), benzene exposure (phenol), and to evaluate their genotoxicity effect with reference to relative mitochondrial DNA copy number (MtDNAcn), 8-OHdG (8-hydroxy-2'-deoxyguanosine), and micronuclei (MN) frequency (%) among fuel filling attendants. This study recorded 318 ± 134 and 1,050 ± 260 μg/m³ time-weighted average concentration of PM10 and CO, respectively. However, total VOC levels recorded were below the detectable level (BDL) to 290 ± 50 μg/m³ . A total of 53 subjects (26 exposed and 27 control) participated in this study with similar sociodemographic information. It was noticed that fuel filling attendants were not using proper personal protective equipment (PPE) and are younger generation. The significantly (p = <.001) higher level of phenol, a metabolite of benzene, was detected in the exposed group. The significantly elevated level of urinary 8-OHdG (p = .01), MN frequency (p = .001), and relative MtDNAcn (p = .001) was observed in exposed group as compared to the control group. The study exemplify that workers were exposed to the benzene, workplace pollutant, and observed genotoxicity suggest malignancy risk. This study highlights the importance of biomonitoring in occupational settings to avoid malignancies. The possible engineering controls, frequent health check-ups, awareness about the risks, and PPE use can reduce health hazards.

Chameleon skin-inspired polymeric particles for the detection of toluene vapor

Inspired by the structural coloring in nature, especially the crystalline ordering and responsive characteristics of those found in chameleon skins, artificial photonic materials for sensor applications were fabricated. Cholesteric liquid crystals (CLCs) were employed in the templated synthesis of polymeric particles with periodic structures that allow visible light to undergo Bragg reflection and their response was tested against volatile organic compounds (VOCs). We demonstrate that the particles were responsive against toluene with detection limits on the order of 100 ppm. Such sensitivity was shown to be achieved due to the critical steps followed during the CLC-templated synthesis of particles that resulted in the storage of elastic energy in the anisotropic glassy polymer network. In addition, the design of particle-assisted sensor chips that allow easy integration into wearable optical devices for reliable, continuous and online tracking of VOC concentrations is presented. These results proved that sensors developed from the CLC-templated particles can be used multiple times without a significant loss of sensitivity and offered rapid, sensitive and battery-free detection.

Advancements in Microfabricated Gas Sensors and Microanalytical Tools for the Sensitive and Selective Detection of Odors

In recent years, advancements in micromachining techniques and nanomaterials have enabled the fabrication of highly sensitive devices for the detection of odorous species. Recent efforts done in the miniaturization of gas sensors have contributed to obtain increasingly compact and portable devices. Besides, the implementation of new nanomaterials in the active layer of these devices is helping to optimize their performance and increase their sensitivity close to humans' olfactory system. Nonetheless, a common concern of general-purpose gas sensors is their lack of selectivity towards multiple analytes. In recent years, advancements in microfabrication techniques and microfluidics have contributed to create new microanalytical tools, which represent a very good alternative to conventional analytical devices and sensor-array systems for the selective detection of odors. Hence, this paper presents a general overview of the recent advancements in microfabricated gas sensors and microanalytical devices for the sensitive and selective detection of volatile organic compounds (VOCs). The working principle of these devices, design requirements, implementation techniques, and the key parameters to optimize their performance are evaluated in this paper. The authors of this work intend to show the potential of combining both solutions in the creation of highly compact, low-cost, and easy-to-deploy platforms for odor monitoring.

Decentralized Multi-agent information-theoretic control for target estimation and localization: finding gas leaks

This article presents a new decentralized multi-agent information-theoretic (DeMAIT) control algorithm for mobile sensors (agents). The algorithm leverages Bayesian estimation and information-theoretic motion planning for efficient and effective estimation and localization of a target, such as a chemical gas leak. The algorithm consists of: (1) a non-parametric Bayesian estimator, (2) an information-theoretic trajectory planner that generates “informative trajectories” for agents to follow, and (3) a controller and collision avoidance algorithm to ensure that each agent follows its trajectory as closely as possible in a safe manner. Advances include the use of a new information-gain metric and its analytical gradient, which do not depend on an infinite series like prior information metrics. Dynamic programming and multi-threading techniques are applied to efficiently compute the mutual information to minimize measurement uncertainty. The estimation and motion planning processes also take into account the dynamics of the sensors and agents. Extensive simulations are conducted to compare the performance between the DeMAIT algorithm to a traditional raster-scanning method and a clustering method with coordination. The main hypothesis that the DeMAIT algorithm outperforms the other two methods is validated, specifically where the average localization success rate for the DeMAIT algorithm is (a) higher and (b) more robust to changes in the source location, robot team size, and search area size than the raster-scanning and clustering methods. Finally, outdoor field experiments are conducted using a team of custom-built aerial robots equipped with gas concentration sensors to demonstrate efficacy of the DeMAIT algorithm to estimate and find the source of a propane gas leak.

Innovative Approach to Photo-Chemiresistive Sensing Technology: Surface-Fluorinated SnO2 for VOC Detection

Transparent electronics continues to revolutionize the way we perceive futuristic devices to be. In this work, we propose a technologically advanced volatile organic compound (VOC) sensor in the form of a thin-film transparent display fabricated using fluorinated SnO₂ films. A solution-processed method for surface fluorination of SnO₂ films using Selectfluor as a fluorinating agent has been developed. The doped fluorine was optimized to be <1%, resulting in a significant increase in conductivity and reduction in persistent photoconductivity accompanied by a faster decay of the photogenerated charge carriers. A combination of these modified properties, together with the intrinsic sensing ability of SnO₂, was exploited in designing a transparent display sensor for ppm-level detection of VOCs at an operating temperature of merely 150 °C. Even a transparent metal mesh heater is integrated with the sensor for ease of operation, portability, and less power usage. A sensor reset method is developed while shortening the UV exposure time, enabling complete sensor recovery at low operating temperatures. The sensor is tested toward a variety of polar and nonpolar VOCs (amines, alcohols, carbonyls, alkanes, halo-alkanes, and esters), and it exhibits an easily differentiable response with sensitivity in line with the electron-donating tendency of the functional group present. This work opens up the door for multiplexed sensor arrays with the ability to detect and analyze multiple VOCs with specificity.

Sniffing Out Urinary Tract Infection-Diagnosis Based on Volatile Organic Compounds and Smell Profile

Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1-2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24-72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography-mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent's resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

The Impact of Technological Processes on Odorant Emissions at Municipal Waste Biogas Plants

Municipal waste treatment is inherently associated with odour emissions. The compounds characteristic of the processes used for this purpose, and at the same time causing a negative olfactory sensation, are organic and inorganic sulphur and nitrogen compounds. The tests were carried out at the waste management plant, which in the biological part, uses the methane fermentation process and is also equipped with an installation for the collection, treatment, and energetic use of biogas. The tests include measurements of the four odorant concentrations and emissions, i.e., volatile organic compounds (VOCs), ammonia (NH3), hydrogen sulphide (H2S), and methanethiol (CH3SH). Measurements were made using a MultiRae Pro portable gas detector sensor. The tests were carried out in ten series for twenty measurement points in each series. The results show a significant impact of technological processes on odorant emissions. The types of waste going to the plant are also important in shaping this emission. On the one hand, it relates to the waste collection system and, on the other hand, the season of year. In addition, it has been proved that the detector used during the research is a valuable tool enabling the control of technological processes in municipal waste processing plants.

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by A Software Platform for Optimized Farm Management

The huge spreading of Internet of things (IoT)-oriented modern technologies is revolutionizing all fields of human activities, leading several benefits and allowing to strongly optimize classic productive processes. The agriculture field is also affected by these technological advances, resulting in better water and fertilizers' usage and so huge improvements of both quality and yield of the crops. In this manuscript, the development of an IoT-based smart traceability and farm management system is described, which calibrates the irrigations and fertigation operations as a function of crop typology, growth phase, soil and environment parameters and weather information; a suitable software architecture was developed to support the system decision-making process, also based on data collected on-field by a properly designed solar-powered wireless sensor network (WSN). The WSN nodes were realized by using the ESP8266 NodeMCU module exploiting its microcontroller functionalities and Wi-Fi connectivity. Thanks to a properly sized solar power supply system and an optimized scheduling scheme, a long node autonomy was guaranteed, as experimentally verified by its power consumption measures, thus reducing WSN maintenance. In addition, a literature analysis on the most used wireless technologies for agri-food products' traceability is reported, together with the design and testing of a Bluetooth low energy (BLE) low-cost sensor tag to be applied into the containers of agri-food products, just collected from the fields or already processed, to monitor the main parameters indicative of any failure or spoiling over time along the supply chain. A mobile application was developed for monitoring the tracking information and storing conditions of the agri-food products. Test results in real-operative scenarios demonstrate the proper operation of the BLE smart tag prototype and tracking system.