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Chemical Gas Sensors for Environment Monitoring
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Chemical Gas Sensors for Environment Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Chemical Sensors".

Deadline for manuscript submissions: closed (15 February 2022) | Viewed by 15720

Special Issue Editors

Prof. Dr. Santiago Marco

E-Mail Website
Guest Editor
1. Signal and information processing for sensing systems, Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain.
2. Department of Electronics, University of Barcelona, Barcelona, Spain
Interests: chemical sensors; instrumentation; signal processing; machine learning; chemometrics
Special Issues, Collections and Topics in MDPI journals
Dr. Yinsheng Chen

E-Mail Website
Guest Editor
1. Signal and information processing for sensing systems, Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain.
2. School of Measurements and Communication Engineering, Harbin University of Science and Technology, Harbin, China.
Interests: machine olfaction; smart sensor system; multidimensional signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Chemical sensing in gas phase is a cornerstone of environmental monitoring. Chemical sensing is used for continuous monitoring of industrial emissions, to detect fugitive toxic and potential hazardous emissions and to monitor outdoor air quality in densely populated or industrial settings for environmental health, indoor air quality, cabin air quality in aerial, terrastrial or maritime transportation, odorous emissions in waste treatment plants, as well as for safety and hygiene considerations at the work place. There are also novel applications in agricultural and farm emission, forest monitoring, etc. Lighweight sensing solutions are suited also for integration in terrestrial and aerial robotic platforms that allow automation of environmental monitoring replacing fixed stations with mobile units.

On the other hand, the landscape of chemical sensing for environmental issues has expanded in the last decade: from rack format instrumentation based on laser absortion spectroscopy, to mm-size metal oxide sensor elements with integrated analog and digital circuitry, and from elements which are able to measure concentrations on the percentatge range to instruments which are capable of sub-ppbv detection limits. The enormous diversity of sensor technologies matches the large diversity of metrological needs in diverse applications.

Small-size and low-cost chemical sensors allow dense spatial monitoring and the elaboration of chemical maps, fusing also meteorological information to predict future dispersion of chemicals into the surroundings. Alternatevely, when the goal is to identify a toxic fugitive emission, retrotrajectories, inverse Lagrangian dispersion models, and Bayesian inference methods based on gaussian plumes are also used.

Finally, new developments in signal processing, chemometrics, machine learning, and data fusion have extended the information that can be retrieved from chemical sensor signals.

In this context, this Special Issue on “Chemical Gas Sensors for Environmental Applications” invites original research and comprehensive reviews on, but not limited to:

  • Optical technologies for gas sensing tailored to environmental monitoring:
    • Open path and closed path methods;
    • Gas imaging systems and methods;
    • Photoacoustic sensors;
    • Photoionization sensors;
    • Nondispersive optical absorption sensors;
  • Solid state gas sensing technologies;
  • Electrochemical sensors, colorimetric sensors, thermally based chemical sensors;
  • Sensor integration and instrumental development for chemical sensing;
  • Wireless sensor networks;
  • Applications of chemical sensing in:
    • Toxic and hazardous industrial emissions;
    • Emissions of greenhouse gases;
    • Indoor air quality;
    • Air quality at the workplace;
    • Odor emissions in waste treatment, farms, etc.;
    • Fusing emission data with dispersion modeling;
  • Integration of sensors in robotic platforms for environmental monitoring;
  • Chemical gas sensing in turbulent chemical plumes;
  • Chemical mapping and chemical source localization;
  • Applications of chemometrics and machine learning for environmental monitoring based on chemical sensors;
  • Standarization activities for chemical sensors and the environment

Prof. Dr. Santiago Marco
Dr. Yinsheng Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Open path and closed path methods
  • Gas imaging systems and methods
  • Photoacoustic sensors
  • Photoionization sensors
  • Nondispersive optical absorption sensors
  • Toxic and hazardous industrial emissions
  • Emissions of greenhouse gases
  • Indoor air quality
  • Air quality at the workplace
  • Odor emissions in waste treatment, farms, etc.
  • Fusing emission data with dispersion modeling

Published Papers (5 papers)

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Research

18 pages, 9314 KiB  
Article
A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists
by Jaime Gómez-Suárez, Patricia Arroyo, Raimundo Alfonso, José Ignacio Suárez, Eduardo Pinilla-Gil and Jesús Lozano
Sensors 2022, 22(3), 1272; https://0-doi-org.brum.beds.ac.uk/10.3390/s22031272 - 08 Feb 2022
Cited by 9 | Viewed by 3333
Abstract
We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and [...] Read more.
We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and an optical particle-matter (PM) sensor for PM2.5 and PM10 concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R2 > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user’s understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform. Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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13 pages, 1600 KiB  
Article
Fast Sensing of Hydrogen Cyanide (HCN) Vapors Using a Hand-Held Ion Mobility Spectrometer with Nonradioactive Ionization Source
by Victor Bocos-Bintintan and Ileana Andreea Ratiu
Sensors 2021, 21(15), 5045; https://0-doi-org.brum.beds.ac.uk/10.3390/s21155045 - 26 Jul 2021
Cited by 8 | Viewed by 3253
Abstract
Sensitive real-time detection of vapors produced by toxic industrial chemicals (TICs) always represents a stringent priority. Hydrogen cyanide (HCN) is definitely a TIC, being widely used in various industries and as an insecticide; it is a reactive, very flammable, and highly toxic compound [...] Read more.
Sensitive real-time detection of vapors produced by toxic industrial chemicals (TICs) always represents a stringent priority. Hydrogen cyanide (HCN) is definitely a TIC, being widely used in various industries and as an insecticide; it is a reactive, very flammable, and highly toxic compound that affects the central nervous system, cardiovascular system, eyes, nose, throat, and also has systemic effects. Moreover, HCN is considered a blood chemical warfare agent. This study was focused toward quick detection and quantification of HCN in air using time-of-flight ion mobility spectrometry (ToF IMS). Results obtained clearly indicate that IMS can rapidly detect HCN at sub-ppmv levels in air. Ion mobility spectrometric response was obtained in the negative ion mode and presented one single distinct product ion, at reduced ion mobility K0 of 2.38 cm2 V−1 s−1. Our study demonstrated that by using a miniaturized commercial IMS system with nonradioactive ionization source model LCD-3.2E (Smiths Detection Ltd., London, UK), one can easily measure HCN at concentrations of 0.1 ppmv (0.11 mg m−3) in negative ion mode, which is far below the OSHA PEL-TWA value of 10 ppmv. Measurement range was from 0.1 to 10 ppmv and the estimated limit of detection LoD was ca. 20 ppbv (0.02 mg m−3). Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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12 pages, 3411 KiB  
Communication
A Ratiometric Optical Dual Sensor for the Simultaneous Detection of Oxygen and Carbon Dioxide
by Divyanshu Kumar and Cheng-Shane Chu
Sensors 2021, 21(12), 4057; https://0-doi-org.brum.beds.ac.uk/10.3390/s21124057 - 12 Jun 2021
Cited by 12 | Viewed by 2749
Abstract
Simultaneous detection of carbon dioxide (CO2) and oxygen (O2) has attracted considerable interest since CO2 and O2 play key roles in various industrial and domestic applications. In this study, a new approach based on a fluorescence ratiometric [...] Read more.
Simultaneous detection of carbon dioxide (CO2) and oxygen (O2) has attracted considerable interest since CO2 and O2 play key roles in various industrial and domestic applications. In this study, a new approach based on a fluorescence ratiometric referencing method was reported to develop an optical dual sensor where platinum (II) meso-tetrakis(pentafluorophenyl)porphyrin (PtTFPP) complex used as the O2-sensitive dye, CdSe/ZnS quantum dots (QDs) combined with phenol red used as the CO2-sensitive dye, and CdSe/ZnS QDs used as the reference dye for the simultaneous detection of O2 and CO2. All the dyes were immobilized in a gas-permeable matrix poly (isobutyl methacrylate) (PolyIBM) and subjected to excitation using a 380 nm LED. The as-obtained distinct fluorescence spectral intensities were alternately exposed to analyte gases to observe changes in the fluorescence intensity. In the presence of O2, the fluorescence intensity of the Pt (II) complex was considerably quenched, while in the presence of CO2, the fluorescence intensity of QDs was increased. The corresponding ratiometric sensitivities of the optical dual sensor for O2 and CO2 were approximately 13 and 144, respectively. In addition, the response and recovery for O2 and CO2 were calculated to be 10 s/35 s and 20 s/60 s, respectively. Thus, a ratiometric optical dual gas sensor for the simultaneous detection of O2 and CO2 was successfully developed. Effects of spurious fluctuations in the intensity of external and excitation sources were suppressed by the ratiometric sensing approach. Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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13 pages, 4804 KiB  
Article
A Simulation Framework for the Integration of Artificial Olfaction into Multi-Sensor Mobile Robots
by Pepe Ojeda, Javier Monroy and Javier Gonzalez-Jimenez
Sensors 2021, 21(6), 2041; https://0-doi-org.brum.beds.ac.uk/10.3390/s21062041 - 14 Mar 2021
Cited by 9 | Viewed by 2821
Abstract
The simulation of how a gas disperses in a environment is a necessary asset for the development of olfaction-based autonomous agents. A variety of simulators already exist for this purpose, but none of them allows for a sufficiently convenient integration with other types [...] Read more.
The simulation of how a gas disperses in a environment is a necessary asset for the development of olfaction-based autonomous agents. A variety of simulators already exist for this purpose, but none of them allows for a sufficiently convenient integration with other types of sensing (such as vision), which hinders the development of advanced, multi-sensor olfactory robotics applications. In this work, we present a framework for the simulation of gas dispersal and sensing alongside vision by integrating GADEN, a state-of-the-art Gas Dispersion Simulator, with the Unity 3D, a video game development engine that is used in many different areas of research and helps with the creation of visually realistic, complex environments. We discuss the motivation for the development of this tool, describe its characteristics, and present some potential use cases that are based on cutting-edge research in the field of olfactory robotics. Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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20 pages, 1314 KiB  
Article
Research on a Gas Concentration Prediction Algorithm Based on Stacking
by Yonghui Xu, Ruotong Meng and Xi Zhao
Sensors 2021, 21(5), 1597; https://0-doi-org.brum.beds.ac.uk/10.3390/s21051597 - 25 Feb 2021
Cited by 21 | Viewed by 2446
Abstract
Machine learning algorithms play an important role in the detection of toxic, flammable and explosive gases, and they are extremely important for the study of mixed gas classification and concentration prediction methods. To solve the problem of low prediction accuracy of gas concentration [...] Read more.
Machine learning algorithms play an important role in the detection of toxic, flammable and explosive gases, and they are extremely important for the study of mixed gas classification and concentration prediction methods. To solve the problem of low prediction accuracy of gas concentration regression prediction algorithms, a gas concentration prediction algorithm based on a stacking model is proposed in the current research. In this paper, the stochastic forest, extreme random regression tree and gradient boosting decision tree (GBDT) regression algorithms are selected as the base learning devices and use the stacking algorithm to take the output of each base learning device as input to train a new model to produce a final output. Through the stacking model, the grid search algorithm is studied to automatically optimize the parameters so that the performance of the entire system can reach the optimal parameters. Through experimental simulation, the gas concentration prediction algorithm based on stacking model has better prediction effect than other integrated frame algorithms and the accuracy of mixed gas concentration prediction is improved. Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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