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Advanced Sensing Technologies for Aerosol Measurement and Its Applications
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Advanced Sensing Technologies for Aerosol Measurement and Its Applications

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 6308

Special Issue Editor

Prof. Dr. Alexander Bergmann

E-Mail Website
Guest Editor
Institute of Electrical Measurement and Sensor Systems, Graz University of Technology, Inffeldgasse 33/I, 8010 Graz, Austria
Interests: environmental sensors; sensor networks; sensor effects; aerosol sensors; photonic sensors; electronic sensor systems; silicon photonics; biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, it has become increasingly important to actively measure and control aerosol emissions. While the application of aerosols remains essential to a wide range of industries, including manufacturing and agriculture, there is also growing societal concern about the impact aerosols have in terms of air pollution, climate change, nanotechnology, chemical manufacturing, medicine, and pharmaceuticals.

This Special Issue invites contributions on advanced technologies for the sensing and measurement of aerosol physical, optical, chemical, and biological properties.

Prof. Dr. Alexander Bergmann
Guest Editor

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

  • aerosol
  • particulate
  • particle emission
  • aerosol optical properties
  • aerosol sensor
  • aerosol chemical composition
  • bioaerosol

Published Papers (4 papers)

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Research

28 pages, 10814 KiB  
Article
Improving Dust Aerosol Optical Depth (DAOD) Retrieval from the GEOKOMPSAT-2A (GK-2A) Satellite for Daytime and Nighttime Monitoring
by Soi Ahn, Hyeon-Su Kim, Jae-Young Byon and Hancheol Lim
Sensors 2024, 24(5), 1490; https://0-doi-org.brum.beds.ac.uk/10.3390/s24051490 - 25 Feb 2024
Viewed by 493
Abstract
The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 h) over surface properties, particularly [...] Read more.
The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 h) over surface properties, particularly over deserts. In this study, dust events in northeast Asia from 2020 to 2021 were investigated using five GK-2A thermal IR bands (8.7, 10.5, 11.4, 12.3, and 13.3 μm). For the dust cloud, the brightness temperature differences (BTDs) of 10.5 and 12.3 μm were consistently negative, while the BTD of 8.7 and 10.5 μm varied based on the dust intensity. This study exploited these optical properties to develop a physical approach for DAOD lookup tables (LUTs) using IR channels to retrieve the DAOD. To this end, the characteristics of thermal radiation transfer were simulated using the forward model; dust aerosols were explained by BTD (10.5, 12.3 μm)—an intrinsic characteristic of dust aerosol. The DAOD and dust properties were gained from a brightness temperature (BT) of 10.5 μm and BTD of 10.5, 12.3 μm. Additionally, the cumulative distribution function (CDF) was employed to strengthen the continuity of 24-h DAOD. The CDF was applied to the algorithm by calculating the conversion value coefficient for the DAOD error correction of the IR, with daytime visible aerosol optical depth as the true value. The results show that the DAOD product can be successfully applied during the daytime and nighttime to continuously monitor the flow of yellow dust from the GK-2A satellite in northeast Asia. In particular, the validation results for IR DAOD were similar to the active satellite product (CALIPSO/CALIOP) results, which exhibited a tendency similar to that for IR DAOD at night. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies for Aerosol Measurement and Its Applications)
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16 pages, 6910 KiB  
Article
Characterization of Particle Shape with an Improved 3D Light Scattering Sensor (3D-LSS) for Aerosols
by Marc Weirich, Dzmitry Misiulia and Sergiy Antonyuk
Sensors 2024, 24(3), 955; https://0-doi-org.brum.beds.ac.uk/10.3390/s24030955 - 01 Feb 2024
Viewed by 636
Abstract
To characterize fine particulate products in industrial gas–solid processes, insights into the particle properties are accessible via various measurement techniques. For micron particles, online imaging techniques offer a fast and reliable assessment of their size and shape. However, for the shape analysis of [...] Read more.
To characterize fine particulate products in industrial gas–solid processes, insights into the particle properties are accessible via various measurement techniques. For micron particles, online imaging techniques offer a fast and reliable assessment of their size and shape. However, for the shape analysis of submicron particles, only offline techniques, such as SEM and TEM imaging, are available. In this work, an online sensor system based on the principle of elastic light scattering of particles in the gas phase is developed to measure the shape factor of non-spherical particles in the size range of 500 nm to 5 µm. Single aerosol particles are guided through a monochromatic circularly polarized laser light beam by an aerodynamic focusing nozzle, which was developed based on the CFD simulation of the flow and particle movement. The intensity of the scattered light is measured at several discrete positions in the azimuthal direction around the particles. An algorithm computes the sphericity of the particles based on the distribution of the intensity signals. The sensor construction, data processing and analysis are described. Model aerosols with particles of different shapes are investigated to test the developed sensor and show its performance in the determination of the sphericity distribution of particles. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies for Aerosol Measurement and Its Applications)
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16 pages, 3429 KiB  
Article
Optimizing the Sensitivity of Biological Particle Detectors through Atmospheric Particle Analysis According to Climatic Characteristics in South Korea
by Hyunsoo Seo, Kibong Choi and Young-Su Jeong
Sensors 2022, 22(9), 3374; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093374 - 28 Apr 2022
Cited by 1 | Viewed by 1454
Abstract
Biological agents used in biological warfare or bioterrorism are also present in bioaerosols. Prompt identification of a biological weapon and its characteristics is necessary. Herein, we optimized an environmentally adaptive detection algorithm that can better reflect changes in the complex South Korean environment [...] Read more.
Biological agents used in biological warfare or bioterrorism are also present in bioaerosols. Prompt identification of a biological weapon and its characteristics is necessary. Herein, we optimized an environmentally adaptive detection algorithm that can better reflect changes in the complex South Korean environment than the current models. The algorithm distinguished between normal and biological particles using a laser-induced fluorescence-based biological particle detector capable of real-time measurements and size classification. We ensured that the algorithm operated with minimal false alarms in any environment by training based on experimental data acquired from an area where rainfall, snow, fog and mist, Asian dust, and water waves on the beach occur. To prevent time and money wastage due to false alarms, the detection performance for each level of sensitivity was examined to enable the selection of multiple sensitivities according to the background, and the appropriate level of sensitivity for the climate was determined. The basic sensitivity was set more conservatively than before, with a 3% alarm rate at 20 agent-containing particles per liter of air (ACPLA) and a 100% alarm rate at 63 ACPLA. The reliability was increased by optimizing five variables. False alarms did not occur in situations where no alarm was unnecessary. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies for Aerosol Measurement and Its Applications)
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11 pages, 2390 KiB  
Communication
Detection of Airborne Nanoparticles through Enhanced Light Scattering Images
by Yan Ye, Qisheng Ou, Weiqi Chen, Qingfeng Cao, Dong-Bin Kwak, Thomas Kuehn and David Y. H. Pui
Sensors 2022, 22(5), 2038; https://0-doi-org.brum.beds.ac.uk/10.3390/s22052038 - 05 Mar 2022
Cited by 4 | Viewed by 2571
Abstract
A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is [...] Read more.
A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies for Aerosol Measurement and Its Applications)
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