scholarly journals Sensing and Delineating Mixed-VOC Composition in the Air Using a Single Metal Oxide Sensor

2021 ◽  
Vol 3 (3) ◽  
pp. 519-533
Author(s):  
Govind S. Thakor ◽  
Ning Zhang ◽  
Rafael M. Santos
Keyword(s):  
Mathematical Model ◽  
Air Quality ◽  
Metal Oxide ◽  
Total Concentration ◽  
Environmental Pollutants ◽  
Model Parameters ◽  
Output Resistance ◽  
Numerous Model ◽  
Experimental Findings ◽  
Metal Oxide Sensor

Monitoring volatile organic compounds (VOCs) places a crucial role in environmental pollutants control and indoor air quality. In this study, a metal-oxide (MOx) sensor detector (used in a commercially available monitor) was employed to delineate the composition of air containing three common VOCs (ethanol, acetone, and hexane) under various concentrations. Experiments with a single component and double components were conducted to investigate how the solvents interact with the metal oxide sensor. The experimental results revealed that the affinity between VOC and sensor was in the following order: acetone > ethanol > n-hexane. A mathematical model was developed, based on the experimental findings and data analysis, to convert the output resistance value of the sensor into concentration values, which, in turn, can be used to calculate a VOC-based air quality index. Empirical equations were established based on inferences of vapour composition versus resistance trends, and on an approach of using original and diluted air samples to generate two sets of resistance data per sample. The calibration of numerous model parameters allowed matching simulated curves to measured data. Therefore, the predictive mathematical model enabled quantifying the total concentration of sensed VOCs, in addition to estimating the VOC composition. This first attempt to obtain semiquantitative data from a single MOx sensor, despite the remaining selectivity challenges, is aimed at expanding the capability of mobile air pollutants monitoring devices.

scholarly journals Sensing and Delineating Mixed-VOC Composition in Air Using a Single Metal-Oxide Sensor

2021 ◽  
Author(s):  
Govind S. Thakor ◽  
Ning Zhang ◽  
Rafael M. Santos
Keyword(s):  
Mathematical Model ◽  
Air Quality ◽  
Metal Oxide ◽  
Total Concentration ◽  
Environmental Pollutants ◽  
Model Parameters ◽  
Output Resistance ◽  
Numerous Model ◽  
Experimental Findings ◽  
Metal Oxide Sensor

Monitoring volatile organic compounds (VOCs) places a crucial role in environmental pollutants control and indoor air quality. In this study, a metal-oxide (MOx) sensor detector (uRAD A3 mobile air quality monitor) was employed to delineate the composition of air containing three common VOCs (ethanol, acetone and hexane) under various concentrations. Experiments with a single component and double components were conducted to investigate how the solvents interact with the metal oxide sensor. The experimental results revealed that the affinity between VOC and sensor was in the following order: acetone > ethanol > n-hexane. A mathematical model was developed, based on the experimental findings and data analysis, to convert the output resistance value of the sensor into concentration values, which in turn can be used to calculate a VOC-based air quality index. Empirical equations were established based on inferences of vapor composition versus resistance trends, and on an approach of using original and diluted air samples to generate two sets of resistance data per sample. The calibration of numerous model parameters allowed matching simulated curves to measured data. As such, the predictive mathematical model enabled quantifying not only the total concentration of sensed VOCs, but also estimating the VOC composition. This first attempt to obtain semi-quantitative data from a single MOx sensor is aimed at expanding the capability of mobile air pollutants monitoring devices.

scholarly journals An Approximation for Metal-Oxide Sensor Calibration for Air Quality Monitoring Using Multivariable Statistical Analysis

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4781
Author(s):  
Diego Sales-Lérida ◽  
Alfonso J. Bello ◽  
Alberto Sánchez-Alzola ◽  
Pedro Manuel Martínez-Jiménez
Keyword(s):  
Air Quality ◽  
Metal Oxide ◽  
Least Squares Method ◽  
Low Cost ◽  
Quality Monitoring ◽  
Sensor Calibration ◽  
Calibration Data ◽  
Air Quality Monitoring ◽  
Human Beings ◽  
Metal Oxide Sensor

Good air quality is essential for both human beings and the environment in general. The three most harmful air pollutants are nitrogen dioxide (NO2), ozone (O3) and particulate matter. Due to the high cost of monitoring stations, few examples of this type of infrastructure exist, and the use of low-cost sensors could help in air quality monitoring. The cost of metal-oxide sensors (MOS) is usually below EUR 10 and they maintain small dimensions, but their use in air quality monitoring is only valid through an exhaustive calibration process and subsequent precision analysis. We present an on-field calibration technique, based on the least squares method, to fit regression models for low-cost MOS sensors, one that has two main advantages: it can be easily applied by non-expert operators, and it can be used even with only a small amount of calibration data. In addition, the proposed method is adaptive, and the calibration can be refined as more data becomes available. We apply and evaluate the technique with a real dataset from a particular area in the south of Spain (Granada city). The evaluation results show that, despite the simplicity of the technique and the low quantity of data, the accuracy obtained with the low-cost MOS sensors is high enough to be used for air quality monitoring.

scholarly journals Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ram Kumar Singh ◽  
Martin Drews ◽  
Manuel De la Sen ◽  
Prashant Kumar Srivastava ◽  
Bambang H. Trisasongko ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Global Economy ◽  
Respiratory Diseases ◽  
Environmental Pollutants ◽  
Atmospheric Pollutants ◽  
Geospatial Technology ◽  
The World ◽  
Community Transmission ◽  
Global Threat

AbstractThe new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.

scholarly journals Field Study of Metal Oxide Semiconductor Gas Sensors in Temperature Cycled Operation for Selective VOC Monitoring in Indoor Air

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 647
Author(s):  
Tobias Baur ◽  
Johannes Amann ◽  
Caroline Schultealbert ◽  
Andreas Schütze
Keyword(s):  
Air Quality ◽  
Metal Oxide ◽  
Gas Sensor ◽  
Gas Sensors ◽  
Indoor Air ◽  
Ambient Air ◽  
Quantitative Agreement ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
High Temporal Resolution

More and more metal oxide semiconductor (MOS) gas sensors with digital interfaces are entering the market for indoor air quality (IAQ) monitoring. These sensors are intended to measure volatile organic compounds (VOCs) in indoor air, an important air quality factor. However, their standard operating mode often does not make full use of their true capabilities. More sophisticated operation modes, extensive calibration and advanced data evaluation can significantly improve VOC measurements and, furthermore, achieve selective measurements of single gases or at least types of VOCs. This study provides an overview of the potential and limits of MOS gas sensors for IAQ monitoring using temperature cycled operation (TCO), calibration with randomized exposure and data-based models trained with advanced machine learning. After lab calibration, a commercial digital gas sensor with four different gas-sensitive layers was tested in the field over several weeks. In addition to monitoring normal ambient air, release tests were performed with compounds that were included in the lab calibration, but also with additional VOCs. The tests were accompanied by different analytical systems (GC-MS with Tenax sampling, mobile GC-PID and GC-RCP). The results show quantitative agreement between analytical systems and the MOS gas sensor system. The study shows that MOS sensors are highly suitable for determining the overall VOC concentrations with high temporal resolution and, with some restrictions, also for selective measurements of individual components.

Prenatal exposure to persistent organic pollutants as a risk factor of offspring metabolic syndrome development during childhood

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Marlene Cervantes González
Keyword(s):  
Metabolic Syndrome ◽  
Organic Pollutants ◽  
Prenatal Exposure ◽  
Persistent Organic Pollutants ◽  
Animal Studies ◽  
Polychlorinated Biphenyl ◽  
Environmental Pollutants ◽  
Epidemiological Studies ◽  
Experimental Findings

Abstract Persistent Organic Pollutants (POPs) are exogenous, artificially made chemicals that can disrupt the biological system of individuals and animals. POPs encompass a variety of chemicals including, dioxins, organochlorines (OCs), polychlorinated biphenyl (PCBs), and perfluoroalkyl substances (PFASs) that contain a long half-life and highly resistant to biodegradation. These environmental pollutants accumulate over time in adipose tissues of living organisms and alter various insulin function-related genes. Childhood Metabolic Syndrome (MetS) consists of multiple cardiovascular risk factors, insulin function being one of them. Over the years, the incidence of the syndrome has increased dramatically. It is imperative to explore the role of persistent organic pollutants in the development of Childhood Metabolic Syndrome. Some epidemiological studies have reported an association between prenatal exposure to POPs and offspring MetS development throughout childhood. These findings have been replicated in animal studies in which these pollutants exercise negative health outcomes such as obesity and increased waist circumference. This review discusses the role of prenatal exposure to POPs among offspring who develop MetS in childhood, the latest research on the MetS concept, epidemiological and experimental findings on MetS, and the POPs modes of action. This literature review identified consistent research results on this topic. Even though the studies in this review had many strengths, one major weakness was the usage of different combinations of MetS criteria to measure the outcomes. These findings elucidate the urgent need to solidify the pediatric MetS definition. An accurate definition will permit scientists to measure the MetS as a health outcome properly and allow clinicians to diagnose pediatric MetS and provide individualized treatment appropriately.

Precise gas discrimination with cross-reactive graphene and metal oxide sensor arrays

2018 ◽  
Vol 113 (22) ◽  
pp. 222102 ◽  
Author(s):  
Chen Shi ◽  
Huixian Ye ◽  
Hui Wang ◽  
Dimitris E. Ioannou ◽  
Qiliang Li
Keyword(s):  
Metal Oxide ◽  
Sensor Arrays ◽  
Metal Oxide Sensor

scholarly journals In silico trial of baroreflex activation therapy for the treatment of obesity-induced hypertension

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259917
Author(s):  
John S. Clemmer ◽  
W. Andrew Pruett ◽  
Robert L. Hester
Keyword(s):  
Current Model ◽  
Plasma Renin ◽  
Model Parameters ◽  
Experimental Population ◽  
Baroreflex Activation Therapy ◽  
Virtual Population ◽  
Key Variables ◽  
Activation Therapy ◽  
Antihypertensive Response ◽  
Experimental Findings

Clinical trials evaluating the efficacy of chronic electrical stimulation of the carotid baroreflex for the treatment of hypertension (HTN) are ongoing. However, the mechanisms by which this device lowers blood pressure (BP) are unclear, and it is uncertain which patients are most likely to receive clinical benefit. Mathematical modeling provides the ability to analyze complicated interrelated effects across multiple physiological systems. Our current model HumMod is a large physiological simulator that has been used previously to investigate mechanisms responsible for BP lowering during baroreflex activation therapy (BAT). First, we used HumMod to create a virtual population in which model parameters (n = 335) were randomly varied, resulting in unique models (n = 6092) that we define as a virtual population. This population was calibrated using data from hypertensive obese dogs (n = 6) subjected to BAT. The resultant calibrated virtual population (n = 60) was based on tuning model parameters to match the experimental population in 3 key variables: BP, glomerular filtration rate, and plasma renin activity, both before and after BAT. In the calibrated population, responses of these 3 key variables to chronic BAT were statistically similar to experimental findings. Moreover, blocking suppression of renal sympathetic nerve activity (RSNA) and/or increased secretion of atrial natriuretic peptide (ANP) during BAT markedly blunted the antihypertensive response in the virtual population. These data suggest that in obesity-mediated HTN, RSNA and ANP responses are key factors that contribute to BP lowering during BAT. This modeling approach may be of value in predicting BAT responses in future clinical studies.

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

scholarly journals A mathematical model of common-cold epidemics on Tristan da Cunha

1971 ◽  
Vol 69 (3) ◽  
pp. 423-433 ◽  
Author(s):  
B. J. Hammond ◽  
D. A. J. Tyrrell
Keyword(s):  
Mathematical Model ◽  
Common Cold ◽  
Average Duration ◽  
Model Parameters ◽  
Epidemic Threshold ◽  
Tristan Da Cunha ◽  
Simulation Techniques ◽  
Time Courses ◽  
The Mathematical Model ◽  
Computer Simulation Techniques

SUMMARYRecords of seven common-cold outbreaks on the island of Tristan da Cunha are compared with the corresponding time courses given by the mathematical model of Kermack & McKendrick (1927) and with an alternative model that directly involves a constant average duration of individual infection. Using computer simulation techniques the latter model is shown to be preferred and is then closely matched to the field data to obtain values for the model parameters. Consideration is then given to the intensity of epidemics predicted by the model and to the distribution of the actual epidemics relative to the theoretical epidemic threshold.

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