Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

Development and machine learning-based calibration of low-cost multiparametric stations for the measurement of CO2 and CH4 in air

The pressing issue of atmospheric pollution has prompted the exploration of affordable methods for measuring and monitoring air contaminants as complementary techniques to standard methods, able to produce high-density data in time and space. The main challenge of this low-cost approach regards the in-field accuracy and reliability of the sensors. This study presents the development of low-cost stations for high-time resolution measurements of CO2 and CH4 concentrations calibrated via an in-field machine learning-based method. The calibration models were built based on measurements parallelly performed with the low-cost sensors and a CRDS analyzer for CO2 and CH4 as reference instrument, accounting for air temperature and relative humidity as external variables. To ensure versatility across locations, diversified datasets were collected, consisting of measurements performed in various environments and seasons. The calibration models, trained with 70 % for modeling, 15 % for validation, and 15 % for testing, demonstrated robustness with CO2 and CH4 predictions achieving R2 values from 0.8781 to 0.9827 and 0.7312 to 0.9410, and mean absolute errors ranging from 3.76 to 1.95 ppm and 0.03 to 0.01 ppm, for CO2 and CH4, respectively. These promising results pave the way for extending these stations to monitor additional air contaminants, like PM, NOx, and CO through the same calibration process, integrating them with remote data transmission modules to facilitate real-time access, control, and processing for end-users.

AI-Driven Sensing Technology: Review

Machine learning and deep learning technologies are rapidly advancing the capabilities of sensing technologies, bringing about significant improvements in accuracy, sensitivity, and adaptability. These advancements are making a notable impact across a broad spectrum of fields, including industrial automation, robotics, biomedical engineering, and civil infrastructure monitoring. The core of this transformative shift lies in the integration of artificial intelligence (AI) with sensor technology, focusing on the development of efficient algorithms that drive both device performance enhancements and novel applications in various biomedical and engineering fields. This review delves into the fusion of ML/DL algorithms with sensor technologies, shedding light on their profound impact on sensor design, calibration and compensation, object recognition, and behavior prediction. Through a series of exemplary applications, the review showcases the potential of AI algorithms to significantly upgrade sensor functionalities and widen their application range. Moreover, it addresses the challenges encountered in exploiting these technologies for sensing applications and offers insights into future trends and potential advancements.

VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM

Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing odor evaluation methods are subjective, costly, and potentially harmful to the health of evaluators. In this study, we analyzed 139 automotive interior parts and 92 vehicles, establishing a cost-effective, data-driven method for odor evaluation. The contents of benzene, toluene, ethylbenzene, xylene, styrene, formaldehyde, acetaldehyde, acrolein, and total volatile organic compounds (TVOC) were detected by thermal desorption gas chromatography-mass spectrometry (TD-GC/MS) and high-performance liquid chromatography with an ultraviolet detector (HPLC-UV). Professional odor evaluators assessed the odors, identifying intensity levels from 2.0 to 4.5 in interior parts and 2.5 to 3.5 in whole vehicles. Leveraging this data, we applied four supervised learning algorithms to develop predictive models for the odor intensity of both interior parts and entire vehicles. During model training, we implemented early stopping techniques for the artificial neural network (ANN) and convolutional neural network-bidirectional long short-term memory (CNN-BiLSTM) models, while optimizing the support vector machine (SVM) and extreme gradient boosting (XGBoost) models using the GridSearch algorithm. The evaluation results reveal that the CNN-BiLSTM model performs the best, achieving an average accuracy of 89% for unknown samples within an odor intensity level of 0.5. The root mean square error (RMSE) is 0.24, and the mean absolute error (MAE) is 0.08. The model also underwent a sevenfold cross-validation, achieving an accuracy of 83.43%. Additionally, we employed SHapley Additive exPlanations (SHAP) for the interpretative analysis of the model, which confirmed the consistency of each VOC's odor contribution with human olfactory rules. By predicting odors based on VOCs through supervised learning, this study reduces the costs and enhances the efficiency and applicability of odor assessment across various vehicle interiors.

Molecularly imprinted polymer nanoparticle-carbon nanotube composite electrochemical gas sensor for highly selective and sensitive detection of methanol vapour

An electrochemical gas sensor has been fabricated using molecularly imprinted polymer nanoparticles (nanoMIPs) and multiwalled carbon nanotubes on screen-printed electrodes. Methanol vapour was chosen as the target due to its toxicity as its suitability as a model for more harmful pollutant gases. The sensor functions under ambient conditions and in the required concentration range, in contrast to all previous MIP-based gas sensors for methanol. The sensitivity of the sensor was greatly improved by the addition of multiwall carbon nanotubes, resulting in a limit of detection of approximately 10 ppm. The nanoMIPs provide an inherent selectivity for the target inherent in its design. Selectivity studies were performed with structurally analogous alcohols at various concentrations, demonstrating selectivity for methanol 12.1 times that for ethanol at 2 mmol dm-3 and 4.2 times that for ethanol at 1 mmol dm-3. Interactions with isopropanol and n-propanol were found to be non-specific, and the response to water was negligible. This demonstrates an improvement over previous methanol gas sensors based on molecularly imprinted polymers. No response was observed with carbon nanotubes alone, and no selectivity was observed with non-imprinted equivalents of the nanoMIP sensor. The resulting device is by far the most practical MIP-based instrument for methanol gas sensing thus far described in the literature, being the only example capable of functioning at the necessary methanol vapour concentrations and at the required temperature and humidity. With the selectivity and sensitivity described and the simple design, the developed device provides a substantial advance in the field of molecularly imprinted gas sensors.

Environmental Quality bOX (EQ-OX): A Portable Device Embedding Low-Cost Sensors Tailored for Comprehensive Indoor Environmental Quality Monitoring

The continuous monitoring of indoor environmental quality (IEQ) plays a crucial role in improving our understanding of the prominent parameters affecting building users' health and perception of their environment. In field studies, indoor environment monitoring often does not go beyond the assessment of air temperature, relative humidity, and CO2 concentration, lacking consideration of other important parameters due to budget constraints and the complexity of multi-dimensional signal analyses. In this paper, we introduce the Environmental Quality bOX (EQ-OX) system, which was designed for the simultaneous monitoring of quantities of some of the main IEQs with a low level of uncertainty and an affordable cost. Up to 15 parameters can be acquired at a time. The system embeds only low-cost sensors (LCSs) within a compact case, enabling vast-scale monitoring campaigns in residential and office buildings. The results of our laboratory and field tests show that most of the selected LCSs can match the accuracy required for indoor campaigns. A lightweight data processing algorithm has been used for the benchmark. Our intent is to estimate the correlation achievable between the detected quantities and reference measurements when a linear correction is applied. Such an approach allows for a preliminary assessment of which LCSs are the most suitable for a cost-effective IEQ monitoring system.

Prediction of the Response of a Photoionization Detector to a Complex Gaseous Mixture of Volatile Organic Compounds Produced by α-Pinene Oxidation

Photoionization detectors (PIDs) are lightweight and respond in real time to the concentrations of volatile organic compounds (VOCs), making them suitable for environmental measurements on many platforms. However, the nonselective sensing mechanism of PIDs challenges data interpretation, particularly when exposed to the complex VOC mixtures prevalent in the Earth's atmosphere. Herein, two approaches to this challenge are investigated. In the first, quantum-chemistry calculations are used to estimate photoionization cross sections and ionization potentials of individual species. In the second, machine learning models are trained on these calculated values, as well as empirical PID response factors, and then used for prediction. For both approaches, the resulting information for individual species is used to model the overall PID response to a complex VOC mixture. In complement, laboratory experiments in the Harvard Environmental Chamber are carried out to measure the PID response to the complex molecular mixture produced by α-pinene oxidation under various conditions. The observations show that the measured PID response is 15% to 30% smaller than the PID response modeled by quantum-chemistry calculations of the photoionization cross section for the photo-oxidation experiments and 15% to 20% for the ozonolysis experiments. By comparison, the measured PID response is captured within a 95% confidence interval by the use of machine learning to model the PID response based on the empirical response factor in all experiments. Taken together, the results of this study demonstrate the application of machine learning to augment the performance of a nonselective chemical sensor. The approach can be generalized to other reactive species, oxidants, and reaction mechanisms, thus enhancing the utility and interpretability of PID measurements for studying atmospheric VOCs.

Improving the adsorption performance of non-polar benzene vapor by using lignin-based activated carbon

Both indoor and outdoor contamination continually contain benzene vapor. It has primary concerns about long-term health risks to the living environment. Benzene is a crucial airborne pollutant in the environment due to its apparent acute toxicity, high volatility, and poor degradability. It is especially urgent to restrain benzene emissions due to the persistent concentration increase and stringent processes. Benzene adsorption is a highly efficient mechanism with low cost, low energy consumption, and a simple process. In this study, biomass-derived porous carbon materials (TCACs) were synthesized by pyrolysis activation combined with H3PO4, HNO3, and HCl. TCAC44 has the best activation conclusion, showing that surface area and pore volume were 1107 m2/g and 0.58 cm3/g treated with H3PO4 and so was chosen for subsequent benzene adsorption/desorption tests. The adsorption capacities of benzene for TCAC44 were increased from 58 mg/g for 35 °C + 95% RH to 121 mg/g for 25 °C + 15% RH and presented a higher adsorption capacity of benzene than TCAC101 and TCAC133. Otherwise, well recyclability of TCAC44 was revealed as the benzene adsorption capacity reductions were 22.49% after five adsorption-desorption cycles. Furthermore, the present study established the property-application relationships to promote and encourage future research on the newly synthesized innovative TCAC44 for benzene removal.

Biotemplate synthesis of a Co3O4 microtube sensor for fast triethylamine detection

A low operating temperature and short response/recovery time are essential factors for sensors. Hence, it is necessary to create a sensor that can quickly detect target gas at a relatively low temperature. In this work, Co₃O₄ microtube based sensors were fabricated by a bio-template method using absorbent cotton. Co₃O₄ microtube sensors prepared in different concentrations of a salt solution displayed different sensitivities to triethylamine (TEA). The Co₃O₄-0.10 microtube sensor exhibited excellent sensitivity to TEA at 160 °C. The response of the Co₃O₄-0.10 sensor to 100 ppm TEA gas was 31.27 and the detection limit of TEA was 50 ppb. Meanwhile, the Co₃O₄-0.10 sensor also showed a short response/recovery time, such as 95 s/38 s to 100 ppm TEA, high selectivity, a good linear relationship (R² = 0.994 for 1-100 ppm TEA and R² = 0.991 for 50-1000 ppb TEA gas), fine repeatability and long-term stability, and strong humidity resistance. Thus, Co₃O₄ microtube based sensors prepared using a bio-template method have potential application prospects for the detection of TEA gas.

Electrochemical and Optical Sensors for the Detection of Chemical Carcinogens Causing Leukemia

The incidence and mortality due to neoplastic diseases have shown an increasing tendency over the years. Based on GLOBOCAN 2020 published by the International Agency for Research on Cancer (IARC), leukemias are the thirteenth most commonly diagnosed cancer in the world, with 78.6% of leukemia cases diagnosed in countries with a very high or high Human Development Index (HDI). Carcinogenesis is a complex process initiated by a mutation in DNA that may be caused by chemical carcinogens present in polluted environments and human diet. The IARC has identified 122 human carcinogens, e.g., benzene, formaldehyde, pentachlorophenol, and 93 probable human carcinogens, e.g., styrene, diazinone. The aim of the following review is to present the chemical carcinogens involved or likely to be involved in the pathogenesis of leukemia and to summarize the latest reports on the possibility of detecting these compounds in the environment or food with the use of electrochemical sensors.

Multi-Channel MEMS-FAIMS Gas Sensor for VOCs Detection

Aimed at the problems of a large equipment size, long time and high price of environmental VOC gas detection, the FAIMS-VOC gas sensor was designed and prepared according to the principle that the ionization energy of the common VOC gas is less than 10.6 eV. The sensor is small in size, fast in detection, low in power consumption, and can work continuously. The sensor was fabricated through the MEMS process, a specific process which included photolithography, etching, anodic bonding, etc. The sensor is 5160 μm long, 5300 μm wide and 800 μm high. We built a test system to detect two typical VOC gases: isobutylene and acetone. The results show that in the detection of isobutylene gas and acetone gas, the sensor voltage value changes with the change of gas concentration. The linearity of testing isobutylene is 0.961, and the linearity of testing acetone is 0.987. When the isobutylene gas concentration is 50 ppm, the response time is 8 s and the recovery time is 6 s; when the acetone gas concentration is 50 ppm, the response time is 9 s and the recovery time is 10 s. In addition, the sensor demonstrates good repeatability and stability, which are conducive to the detection of VOCs in the environment.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions

PURPOSE OF REVIEW

We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale.

RECENT FINDINGS

Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

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.

Harnessing the cation-π interactions of metalated gold monolayer-protected clusters to detect aromatic volatile organic compounds

The strong, non-covalent interactions between π-systems and cations have been the focus of numerous studies on biomolecule structure and catalysis. These interactions, however, have yet to be explored as a sensing mechanism for detecting trace levels of volatile organic compounds (VOCs). In this article, we provide evidence that cation-π interactions can be used to elicit sensitive and selective chemiresistor responses to aromatic VOCs. The chemiresistors are fitted with carboxylate-linked alkali metals bound to the surface of gold monolayer-protected clusters formulated on microfabricated interdigitated electrodes. Sensor responses to aromatic and non-aromatic VOCs are consistent with a model for cation-π interactions arising from association of electron-rich aromatic π-systems to metal ions with the relative strength of attraction following the order K⁺ > Na⁺ > Li⁺. The results point toward cation-π interactions as a promising research avenue to explore for developing aromatic VOC-selective sensors.

Source identification with high-temporal resolution data from low-cost sensors using bivariate polar plots in urban areas of Ghana

The emergence of low-cost sensors for atmospheric observations presents a new opportunity for identifying atmospheric emission sources based on high-resolution data reporting. Low-cost sensors have been widely assessed for use in source monitoring and identification of hotspots of key atmospheric species in advanced countries (e.g., for CO, NOx, CO₂, SO₂, O₃, VOCs and PM (PM₁₀, PM_2.5 including emerging PM₁). In contrast, research in recent years has focused on their utility for real-time monitoring, understanding precision and associated calibration requirements in technologically lagging environments. This leads to limited evidence on the utility of high-resolution data from low-cost sensor networks for air pollution source identification in Ghana and more widely across the African continent. In this paper, we demonstrate the potential of low-cost sensors for emission source apportionment in urban areas of Ghana when used with analytical tools such as sectoral and cluster analysis. With a 14-week dataset from a low-cost sensor deployment study at Cape Coast in the Central Region of Ghana, we aimed to identify sources of particulate matter (PM_2.5 and PM₁₀). PM pollution was local (associated with increased PM at wind speeds of ≤2 m s^-1). High levels of PM during this study were associated with transport from the NNE. For coarse PM, hourly levels as high as 125 μg m^-3 were observed at higher wind speeds (7-8 m s^-1) indicating the importance of meteorology in the transport of PM. This study suggests that low-cost sensors could be deployed to (1) augment any existing sparsely distributed air quality monitoring and (2) undertake air quality monitoring for source apportionment studies in areas with no existing air quality observational capability (with appropriate calibration and operation in both cases). The urban landscape monitored in this study is typical of both Ghana and wider areas across Sub-Saharan Africa demonstrating the reproducibility of this study.

High-density volatile organic compound monitoring network for identifying pollution sources

The elusive sources of air pollution have hampered effective control across all sectors, with long-term consequences for the greenhouse effect and human health. Multiple monitoring systems have been highly desired for locating the sources. However, when faced with extensive sources, diverse air environments and meteorological conditions, the low spatiotemporal resolution, poor reliability and high cost of existing monitors were significant obstacles to their applications. Extending our previous demonstration of sensitive and reliable electrochemical sensors, we here present a machine-learning-assisted sensor arrays for monitoring typical volatile organic compounds (VOCs), which shows the consistent response with gas chromatography-mass spectrometry in the actual air environment. As a proof-of-concept, a low-cost and high-resolution VOC network of 152 sets of monitors across ~55 km² of mixed-used land is established in southwest Beijing. Benefiting from the strong reliability, the pollution sources are revealed by the VOC network and supported by the joint mobile sampling of a vehicle-mounted gas chromatography-mass spectrometry system. With the sustained help of the network, the sources polluted by the local industrial facilities, traffic, and restaurants are effectively site-specific abatement by the local authorities and enterprises during the next half-year. Our findings open up a promising path toward more effective tracing of regional pollution sources, as well as accelerate the long-term transformation of industry and cities.

Selective and Reversible Solvent Uptake in Tetra-4-(4-pyridyl)phenylmethane-based Supramolecular Organic Frameworks

The dynamic behavior of supramolecular organic frameworks (SOFs) based on the rigid tetra-4-(4-pyridyl)phenylmethane (TPPM) organic tecton has been elucidated through 3D electron diffraction, X-ray powder diffraction and differential scanning calorimetry (DSC) analysis. The SOF undergoes a reversible single-crystal-to-single-crystal transformation when exposed to vapours of selected organic solvents, moving from a closed structure with isolated small voids to an expanded structure with solvated channels along the b axis. The observed selectivity is dictated by the fitting of the guest in the expanded SOF, following the degree of packing coefficient. The effect of solvent uptake on TPPM solid-state fluorescence was investigated, evidencing a significant variation in the emission profile only in the presence of chloroform.

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.

Sampling Volatile Organic Compound Emissions from Consumer Products: A Review

Volatile organic compounds (VOCs) are common constituents of many consumer products. Although many VOCs are generally considered harmless at low concentrations, some compound classes represent substances of concern in relation to human (inhalation) exposure and can elicit adverse health effects, especially when concentrations build up, such as in indoor settings. Determining VOC emissions from consumer products, such as toys, utensils or decorative articles, is of utmost importance to enable the assessment of inhalation exposure under real-world scenarios with respect to consumer safety. Due to the diverse sizes and shapes of such products, as well as their differing uses, a one-size-fits-all approach for measuring VOC emissions is not possible, thus, sampling procedures must be chosen carefully to best suit the sample under investigation. This review outlines the different sampling approaches for characterizing VOC emissions from consumer products, including headspace and emission test chamber methods. The advantages and disadvantages of each sampling technique are discussed in relation to their time and cost efficiency, as well as their suitability to realistically assess VOC inhalation exposures.

Impact of simulating real microplastics on toluene removal from contaminated soil using thermally enhanced air injection

This paper investigated the impacts of various real microplastics (MPs), i.e., polyethylene (PE) and polyethylene terephthalate (PET) with different sizes (1000-2000 and 100-200 μm) and different dosages (0.5 and 5% on a dry weight basis), on the toluene removal during the thermally enhanced air injection treatment. First, microscopic tests were carried out to determine the MPs' microstructure and behavior. The PE was mainly a small block, and PET appeared filamentous and sheeted with a larger slenderness ratio. Second, the interactions between MPs and toluene-contaminated soils were revealed by batch adsorption equilibrium experiments and low-field magnetic resonance. The morphological differences and dosage of the MPs impacted soils' total porosity (variation range: 39.2-42.7%) and proportion of the main pores (2-200 μm). Third, the toluene removal during the air injection consisted of compaction, rapid growth, rapid reduction, and tailing stages, and the MPs were regarded as an emerging solid state to affect these removal stages. The final cumulative toluene concentrations of soil-PET mixtures were influenced by total porosity, and those of soil-PE mixtures were controlled by total porosity (influence weight: 0.67) and adsorption capacity (influence weight: 0.33); meanwhile, a self-built comprehensive coefficient of MPs can reflect the relationship between them and cumulative concentrations (correlation coefficient: 0.783).

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.

Determination of Air Pollutants: Application of a Low-Cost Method for Preparation of VOC Mixtures at Known Concentration

Gas chromatography (GC) is an excellent tool to obtain qualitative and quantitative information on volatile organic compounds (VOCs) present in gaseous samples. However, to carry out an appropriate quantitative analysis of unknown samples, the use of known concentration gas mixtures, to exploit as standards, is required. Commonly, these mixtures are obtained from cylinders of compressed gas at known concentrations: this involves a considerable economic outlay and problems relating to their handling. This paper aims to apply a method, proposed as a versatile, simple, and economical alternative to the use of such cylinders, for preparing gaseous calibration standards useful to obtain calibration curves for quantification of air pollutants. In addition, the operative limits of this method were investigated. The method involves the continuous injection of volatile compounds in liquid form into a stream of neutral gas, such as air or nitrogen. Exploiting the high volatility of the compounds used, it is possible to generate a continuous gas stream containing the chosen VOC at the desired concentration based on the mass balance of the system. This method proved to be suitable for compounds with volatility ranging from 36 kPa to 0.1 kPa at 293 K and it showed relative bias and relative standard deviation (RSD) values of less than 16% and 8%, respectively. The described dynamic method results are repeatable and accurate. It can be used effectively for compounds with vapour pressure values within the stated limits and provides a more versatile and cost-effective alternative to compressed gas cylinders.

Comparison of Sb2O3 and Sb2O3/SiO2 Double Stacked pH Sensing Membrane Applied in Electrolyte-Insulator-Semiconductor Structure

In this study, electrolyte-insulator-semiconductor (EIS) capacitors with Sb₂O₃/SiO₂ double stacked sensing membranes were fabricated with pH sensing capability. The results indicate that Sb₂O₃/SiO₂ double stacked membranes with appropriate annealing had better material quality and sensing performance than Sb₂O₃ membranes did. To investigate the influence of double stack and annealing, multiple material characterizations and sensing measurements on membranes including of X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) were conducted. These analyses indicate that double stack could enhance crystallization and grainization, which reinforced the surface sites on the membrane. Therefore, the sensing capability could be enhanced, Sb₂O₃/SiO₂-based with appropriate annealing show promises for future industrial ion sensing devices.

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.

Laser-based selective BTEX sensing using deep neural networks

A mid-infrared absorption-based laser sensor is developed for selective and simultaneous benzene, toluene, ethylbenzene, and xylenes (BTEX) measurements under ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.3 µm. Wavelength tuning and deep neural networks were employed to differentiate the broadband absorbance of BTEX species. The sensor was validated with gas mixtures and real-time measurements were demonstrated at a temporal resolution of 1 s. Minimum detection limits for BTEX in air are 8, 20, 5, and 46 ppm, respectively. This sensor can be utilized to monitor BTEX emissions in the petrochemical, rubber, and paint industries to avoid hazardous health effects.

Tracing of Heavy Metals Embedded in Indoor Dust Particles from the Industrial City of Asaluyeh, South of Iran

Assessment of indoor air quality is especially important, since people spend substantial amounts of time indoors, either at home or at work. This study analyzes concentrations of selected heavy metals in 40 indoor dust samples obtained from houses in the highly-industrialized Asaluyeh city, south Iran in spring and summer seasons (20 samples each). Furthermore, the health risk due to exposure to indoor air pollution is investigated for both children and adults, in a city with several oil refineries and petrochemical industries. The chemical analysis revealed that in both seasons the concentrations of heavy metals followed the order of Cr > Ni > Pb > As > Co > Cd. A significant difference was observed in the concentrations of potential toxic elements (PTEs) such as Cr, As and Ni, since the mean (±stdev) summer levels were at 60.2 ± 9.1 mg kg−1, 5.6 ± 2.7 mg kg−1 and 16.4 ± 1.9 mg kg−1, respectively, while the concentrations were significantly lower in spring (17.6 ± 9.7 mg kg−1, 3.0 ± 1.7 mg kg−1 and 13.5 ± 2.4 mg kg−1 for Cr, As and Ni, respectively). Although the hazard index (HI) values, which denote the possibility of non-carcinogenic risk due to exposure to household heavy metals, were generally low for both children and adults (HI < 1), the carcinogenic risks of arsenic and chromium were found to be above the safe limit of 1 × 10−4 for children through the ingestion pathway, indicating a high cancer risk due to household dust in Asaluyeh, especially in summer.

Cavitand Decorated Silica as a Selective Preconcentrator for BTEX Sensing in Air

The monitoring of benzene and other carcinogenic aromatic volatile compounds at the ppb level requires boosting both the selectivity and sensitivity of the corresponding sensors. A workable solution is the introduction in the devices of preconcentrator units containing molecular receptors. In particular, quinoxaline cavitands (QxCav) resulted in very efficient preconcentrator materials for the BTEX in air to the point that they have been successfully implemented in a commercial sensor. In this work, we report a highly efficient quinoxaline-based preconcentrator material, in which the intrinsic adsorption capacity of the QxCav has been maximized. The new material consists of silica particles covalently coated with a suitable functionalized QxCav derivative (QxCav@SiO₂). In this way, all the cavities are exposed to the analyte flux, boosting the performance of the resulting preconcentration cartridge well above that of the pure QxCav. It is noteworthy that the preconcentrator adsorption capacity is independent of the relative humidity of the incoming air.

Smartphone Case-Based Gas Sensing Platform for On-site Acetone Tracking

Gas sensor-embedded smartphones would offer the opportunity of on-site tracking of gas molecules for various applications, for example, harmful air pollutant alarms or noninvasive assessment of health status. Nevertheless, high power consumption and difficulty in replacing malfunctioned sensors as well as limited space in the smartphone to host the sensor restrain the relevant advancements. In this article, we create a smartphone case-based sensing platform by integrating the functional units into a smartphone case, which performs a low detection limit of 117 ppb to acetone and high specificity. Particularly, dimming glass-regulated light fidelity (Li-Fi) communication is successfully developed, allowing the sensing platform to operate with relatively low power consumption (around 217 mW). Experimental proof on harmful gas sensing and potential clinic application is implemented with the sensing platform, demonstrating satisfactory sensing performance and acceptable health risk pre-warning accuracy (87%). Thus, the developed smartphone case-based sensing platform would be a good candidate for realizing harmful gas alarms and noninvasive assessment of health status.

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.

Field Test of Mini Photoionization Detector-Based Sensors—Monitoring of Volatile Organic Pollutants in Ambient Air

The determination of the concentrations of the organic compounds in ambient air using reference methods is a time-consuming process. The samples must be collected on a specific sorbent material and analyzed. In the best-case scenario, the analysis may be performed on site by portable chromatography techniques; otherwise, transport and laboratory analysis is necessary. Continuous sensory measurement is advantageous, especially concerning speed, resolution, price and ease of use. On the other hand, questions are raised, especially on the subject of the quality of data obtained by sensory measurements. The authors tested several types of volatile organic compound (VOC) sensors. The chosen type was deployed in a 25-unit sensor network for further testing by parallel measurements with the reference technique within the CLAIRO project.

The Porcine Odorant-Binding Protein as a Probe for an Impedenziometric-Based Detection of Benzene in the Environment

Odorant-binding proteins (OBPs) are a group of small and soluble proteins present in both vertebrates and insects. They have a high level of structural stability and bind to a large spectrum of odorant molecules. In the environmental field, benzene is the most dangerous compound among the class of pollutants named BTEX (benzene, toluene, ethylbenzene, and xylene). It has several effects on human health and, consequently, it appears to be important to monitor its presence in the environment. Commonly, its detection requires the use of very sophisticated and time-consuming analytical techniques (GC-MS, etc.) as well as the presence of specialized personnel. Here, we present the application of an odorant-binding protein (pOBP) isolated from pigs as a molecular recognition element (MRE) for a low-energy impedenziometric biosensor for outdoor and real-time benzene detection. The obtained results show that the biosensor can detect the presence of 64 pM (5 µg/m³) benzene, the limit value of exposure for human health set by the European Directive 2008/50/EC.

Continuous VOCs Monitoring in Saturated and Unsaturated Zones Using Thermal Desorber and Gas Chromatography: System Development and Field Application

Subsurface VOC monitoring has been mainly based on manual sampling, transport, and analysis, which would require a sufficient amount of samples to ensure data accuracy and reliability, and additional costs to ensure sample quality. Therefore, a continuous on-site monitoring system is desirable for accurate measurement and subsequent risk assessment. In this study, benzene, toluene, ethylbenzene, and xylene (BTEX) were continuously monitored by the system based on a thermal desorber (TD) and gas chromatography (GC) in an oil-contaminated site that consisted of saturated and unsaturated zones. For the saturated zone, fully automated groundwater sampling and purging processes were performed, and the gasified samples were applied to the TD–GC system. For the unsaturated zone, the gaseous sample in the site was directly applied to the TD–GC system. After verifying the accuracy and precision of the monitoring system, the continuous monitoring system was successfully operated for more than a month in the field. The monitoring system used in this study is applicable to other sites for continuous monitoring, thus providing a scientific background for advanced risk assessment and policy development.

Enhancement of photoacoustic spectroscopy with sorption enrichment for ppt-level benzene detection

A real-time trace gas detector for benzene is demonstrated. The measurement system takes advantage of modest enrichment through short adsorption periods to reach a ppt-level detection limit with a sampling cycle of 90 s, which includes sample adsorption, desorption, and a spectroscopic measurement. Benzene is collected on Tenax TA sorbent for 30 s and then detected from the enriched samples with photoacoustic spectroscopy. High sensitivity is achieved using cantilever-enhanced photoacoustic spectroscopy and a continuous-wave quantum cascade laser emitting at 14.8 µm wavelength, which corresponds to the absorption wavelength of the strongest benzene infrared band. We reach a detection limit of 150 ppt of benzene, over one sampling cycle. Interference from humidity and other common petrochemicals is evaluated.

Miniaturized thermal acoustic gas sensor based on a CMOS microhotplate and MEMS microphone

We present a miniaturised thermal acoustic gas sensor, fabricated using a CMOS microhotplate and MEMS microphone. The sensing mechanism is based on the detection of changes in the thermal acoustic conversion efficiency which is dependent on the physical properties of the gas. An active sensing element, consisting of a MEMS microphone, is used to detect the target gas while a reference element is used for acoustic noise compensation. Compared to current photoacoustic gas sensors, our sensor requires neither the use of gas-encapsulated microphones, nor that of optical filters. In addition, it has all the benefits of CMOS technology, including production scalability, low cost and miniaturization. Here we demonstrate its application for CO\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_2$$\end{document}2 gas detection. The sensor could be used for gas leak detection, for example, in an industrial plant.

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.

Paving the Way for a Green Transition in the Design of Sensors and Biosensors for the Detection of Volatile Organic Compounds (VOCs)

The efficient and selective detection of volatile organic compounds (VOCs) provides key information for various purposes ranging from the toxicological analysis of indoor/outdoor environments to the diagnosis of diseases or to the investigation of biological processes. In the last decade, different sensors and biosensors providing reliable, rapid, and economic responses in the detection of VOCs have been successfully conceived and applied in numerous practical cases; however, the global necessity of a sustainable development, has driven the design of devices for the detection of VOCs to greener methods. In this review, the most recent and innovative VOC sensors and biosensors with sustainable features are presented. The sensors are grouped into three of the main industrial sectors of daily life, including environmental analysis, highly important for toxicity issues, food packaging tools, especially aimed at avoiding the spoilage of meat and fish, and the diagnosis of diseases, crucial for the early detection of relevant pathological conditions such as cancer and diabetes. The research outcomes presented in the review underly the necessity of preparing sensors with higher efficiency, lower detection limits, improved selectivity, and enhanced sustainable characteristics to fully address the sustainable manufacturing of VOC sensors and biosensors.

Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

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.

Automatic Optical Measurement and Control of Benzene and Benzenoids in Natural Gas Pipelines

The presence of benzene and similar aromatic compounds in civil environments is due to anthropic actions but also to natural sources. Natural gas consists of a gas mixture where benzene and related compounds are usually presents. Thus, the detection of these compounds in natural gas pipelines is of the utmost importance as well as the control of the concentration level, which must remain below the limits consented by law. In this regard, it is of striking interest to engineer devices able to detect these compounds by automatic and continuous remote control. Here, we discuss the application of an optical device designed for the measurement of sulfured odorizing agents in natural gas pipelines aiming at the detection and the measurement of benzene, toluene, and xylenes (BTX) in the same contexts. The instrument consists of a customized UV spectrophotometer connected to an automatic control system able to provide in-field detections of BTX through a continuous and remote check of the gaseous mixture. Relatively to benzene, the instrument is characterized by values of LOD (level of detection) and LOQ (level of quantification) equal to 0.55 and 1.84 mg/Sm3, respectively. Similar limits are found for toluene and xylenes (LOD of 0.81, 1.05, 1.41, and 1.00 mg/Sm3 for toluene, meta-, ortho-, and para-xylene, respectively).

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.

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.

Fluorescent lamp tungsten filament thermionic emission gun as a novel humidity optical sensor

Detecting humidity have been remained a continuing concern within some important areas such as structural health, food processing, industrial as well as agricultural products. In this study, a novel humidity optical sensor is introduced based on the thermionic emission of tungsten filament using the fluorescent lamp set-up. Estimated blue compliant using a charged coupling device camera in optical image of the tungsten filament was confirmed as an appropriate detection system for relative humidity (RH) sensing. The fabricated optical sensor has wide linear range (2.0–98% RH), improved detection limit (< 5.0% RH), acceptable saturated limit (> 99.0% RH), improved percentage of relative standard deviation (4.18%, n = 2), adequate hysteresis (< 4.0% RH) and a shorter rise time (< 5.0 s), respectively. The mechanism behind this detection system is based on the interaction between H₂O and tungsten filament during formation of W\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{O}}_{3}$$\end{document}O3.x \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{H}}_{2}$$\end{document}H2O (x = 1–2) in terms of some spectroscopic obtained evidences as well as Fourier transform infrared and X-ray diffraction spectrometries.

Application of Low-Cost Sensors for Building Monitoring: A Systematic Literature Review

In recent years, many scholars have dedicated their research to the development of low-cost sensors for monitoring of various parameters. Despite their high number of applications, the state of the art related to low-cost sensors in building monitoring has not been addressed. To fill this gap, this article presents a systematic review, following well-established methodology, to analyze the state of the art in two aspects of structural and indoor parameters of buildings, in the SCOPUS database. This analysis allows to illustrate the potential uses of low-cost sensors in the building sector and addresses the scholars the preferred communication protocols and the most common microcontrollers for installation of low-cost monitoring systems. In addition, special attention is paid to describe different areas of the two mentioned fields of building monitoring and the most crucial parameters to be monitored in buildings. Finally, the deficiencies in line with limited number of studies carried out in various fields of building monitoring are overviewed and a series of parameters that ought to be studied in the future are proposed.

Assessment of the applicability of a low-cost sensor-based methane monitoring system for continuous multi-channel sampling

Systems that are made of several low-cost gas sensors with automatic gas sampling may have the potential to serve as reliable fast methane analyzers. However, there is a lack of reports about such types of systems evaluated under field conditions. Here, we developed a continuous methane monitoring system with automated gas sampling unit using low-cost gas sensors, TGS 2611 and MQ-4, that use a simple cloud-based data acquisition platform. We verified the consistency, repeatability, and reproducibility of the data obtained by TGS 2611 and MQ-4 low-cost gas sensors by measuring high- and low-concentration methane samples. The normalized root-mean-square errors (NRMSEs) of the samples with high methane concentrations, [CH₄] of 3, 4, 6, and 7%, were 0.0788, 0.0696, 0.1198, and 0.0719 for the TGS 2611 sensor, respectively, and were confirmed using a gas chromatograph as a reference analyzer. The NRMSEs of the samples with low [CH₄] of 0.096, 0.145, 0.193, and 0.241% measured by the TGS 2611 sensor were 0.0641, 0.1749, 0.0157, and 0.1613, whereas those NRMSEs of the same concentrations measured by the MQ-4 sensor were 0.3143, 0.5766, 0.6301, and 0.6859, respectively. Laboratory-scale anaerobic digesters were tested using the developed system. The anaerobic digesters were continuously operated for 2 months, demonstrating the potential use of sensors for detecting and monitoring methane in the field level application. This study utilized a unique way to combine the advantages of low-cost sensors and develop a reliable monitoring system by minimizing drawbacks of low-cost sensors.