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Optical Sensing for Environmental Monitoring-2nd Edition

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

Deadline for manuscript submissions: 30 September 2024 | Viewed by 739

Special Issue Editors


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Guest Editor
School of Engineering, Robert Gordon University, Aberdeen AB10 7GJ, UK
Interests: leakage detection; optical fibre-based sensors; robots; hollow core photonic crystal fibres; biosensors and instrumentation; environmental sensing and monitoring; clean technology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen AB107GJ, UK
Interests: nanomaterials; graphene and graphene-based compounds; energy storage devices; 2D materials; functional materials; sensors; environmental and pharmaceutical devices
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Senior Analytical Chemist, The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, Scotland, UK
Interests: in development of analytical methodologies and assessments of organic and inorganic contaminants in different environmental compartments
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of our Sensors Special Issue entitled “Optical Sensing for Environmental Monitoring”, we would like to once again invite our colleagues from across the world to contribute their expertise, insights, and findings in the form of original research articles and reviews for the second edition of the Special Issue, entitled “Optical Sensing for Environmental Monitoring-2nd Edition”.

Environmental monitoring has become essential for human sustainability and for the efficient and safe use of environmental resources. It plays a vital role in pollution mitigation, the preservation of biodiversity, and providing data for assessing the impacts of climate change. Environmental monitoring typically involves sampling and analyzing data with the help of sophisticated instruments to characterize and monitor the quality of the environment (air/water/soil). However, this usually involves sample collection, transport, storage and off-site analysis, which may not be cost-effective and may alter sample characteristics. The use of sensors is fast gaining traction because of their ability for in situ monitoring and rapid transmission of real-time data. Various types of sensors can be used for environmental monitoring, based on optical and spectroscopic (fluorescence, Raman, and IR) techniques. Typical detection may involve the monitoring of environmental changes in the ocean, atmosphere, or nuclear/industrial facilities under harsh conditions (e.g., subsea pipelines) in both the temporal and spatial domains. This may be carried out remotely, involving multiple parameters. Optical or optical fiber-based sensors are emerging as potential for environmental monitoring. Optical fibers have advantages like smaller size, immunity to electromagnetic interference, freedom from corrosion, chemical inertness and large bandwidth, which can accommodate the growing needs of sensing and monitoring in challenging environments.

Current trends in environmental sensor development are to realize in-situ-type, smaller, easy-to-use, and rapid sensors with “smart” capabilities. Future sensors are expected to have high sensitivity and selectivity with real-time monitoring or multi-analyte detection capability based on the “lab-on-a-chip” principle. This can simplify the analysis, reduce the cost, and extend reliable monitoring outside the central laboratory. Optical biosensors based on bio-affinity molecules can provide very good sensitivity and selectivity for monitoring. Sensor arrays or CCD-based imaging can be implemented for monitoring various spatial locations or multi-parameter sensing. Again, Artificial Intelligence (AI)-based approaches are being integrated for simplifying sensor data or image analysis. This Special Issue will include featured research articles on environmental monitoring based on optical techniques.

Prof. Dr. Radhakrishna Prabhu
Dr. Carlos Fernandez
Dr. Sandhya Devalla
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.

Published Papers (1 paper)

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Research

19 pages, 8287 KiB  
Article
Vertical Distribution Mapping for Methane Fugitive Emissions Using Laser Path-Integral Sensing in Non-Cooperative Open Paths
by Di Wang, Yushuang Li, Yu Pu, Yan Lv, Mingji Wang, Hui Yang, Xuefeng Zhao and Dong Li
Sensors 2024, 24(4), 1307; https://0-doi-org.brum.beds.ac.uk/10.3390/s24041307 - 18 Feb 2024
Viewed by 531
Abstract
Observing the vertical diffusion distribution of methane fugitive emissions from oil/gas facilities is significant for predicting the pollutant’s spatiotemporal transport and quantifying the random emission sources. A method is proposed for methane’s vertical distribution mapping by combining the laser path-integral sensing in non-non-cooperative [...] Read more.
Observing the vertical diffusion distribution of methane fugitive emissions from oil/gas facilities is significant for predicting the pollutant’s spatiotemporal transport and quantifying the random emission sources. A method is proposed for methane’s vertical distribution mapping by combining the laser path-integral sensing in non-non-cooperative open paths and the computer-assisted tomography (CAT) techniques. It uses a vertical-plume-mapping optical path configuration and adapts the developed dynamic relaxation and simultaneous algebraic reconstruction technique (DR-SART) into methane-emission-distribution reconstruction. A self-made miniaturized TDLAS telemetry sensor provides a reliable path to integral concentration information in non-non-cooperative open paths, with Allan variance analysis yielding a 3.59 ppm·m sensitivity. We employed a six-indexes system for the reconstruction performance analysis of four potential optical path-projection configurations and conducted the corresponding validation experiment. The results have shown that that of multiple fan-beams combined with parallel-beam modes (MFPM) is better than the other optical path-projection configurations, and its reconstruction similarity coefficient (ε) is at least 22.4% higher. For the different methane gas bag-layout schemes, the reconstruction errors of maximum concentration (γm) are consistently around 0.05, with the positional errors of maximum concentration (δ) falling within the range of 0.01 to 0.025. Moreover, considering the trade-off between scanning duration and reconstruction accuracy, it is recommended to appropriately extend the sensor measurement time on a single optical path to mitigate the impact of mechanical vibrations induced by scanning motion. Full article
(This article belongs to the Special Issue Optical Sensing for Environmental Monitoring-2nd Edition)
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