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Atmosphere
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Characteristics and Control of Particulate Matter
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Characteristics and Control of Particulate Matter

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Pollution Control".

Deadline for manuscript submissions: 25 June 2025 | Viewed by 7931

Special Issue Editors

Dr. Jianlong Li

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Guest Editor
School of Resources and Environment, Nanchang University, Nanchang 330031, China
Interests: particulate matter; filtration; dust control; filter regeneration; gas-particle flow
Special Issues, Collections and Topics in MDPI journals
Dr. Jianwu Chen

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Guest Editor
Institute of Occupational Health, China Academy of Safety Science and Technology, Beijing 100012, China
Interests: particulate matter; occupational health; indoor air purification; respiratory protection; health risk assessment
Prof. Dr. Hong Huang

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Guest Editor
School of Resources and Environment, Nanchang University, Nanchang 330031, China
Interests: atmosphere aerosol characterization; carbon aerosol emission characteristics; toxicological effect of particulate matter; aging mechanism of aerosol; optical property of aerosol
Dr. Cuiping Yan

E-Mail Website
Guest Editor
Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education, School of Environment and Resource, Southwest University of Science and Technology, Mianyang 621010, China
Interests: particulate matter control; dust filtration; dust collector optimization; filter regeneration; particulate matter characterization

Special Issue Information

Dear Colleagues,

PM is harmful to human health and the environment. PM can arise from natural sources or anthropogenic sources. It comes in many sizes and shapes and has a huge surface area. PM can enrich hundreds of chemical toxicants. For this Special Issue, we aim to compile high-quality research and provide the community with a valuable resource on the study of the characteristics and control of particulate matter.

This Special Issue welcomes contributions focused on particulate-matter physicochemical properties, specific measurement techniques, recent developments and applications of novel control or purification design, control-system optimization and purification-mechanism understanding. Alternatively, authors can contribute manuscripts that focus on particulate-matter monitoring, migration and simulation. Finally, topics relating to particle pollution, individual respiratory protection and health impacts are also welcome in this Special Issue. If any doubts about the suitability of the research for this Special Issue arise, potential authors are invited to discuss the topic with the Guest Editor before preparing the paper.

Dr. Jianlong Li
Dr. Jianwu Chen
Prof. Dr. Hong Huang
Dr. Cuiping Yan
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. Atmosphere is an international peer-reviewed open access monthly 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 2400 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

  • particulate-matter properties
  • particle pollution
  • health impacts
  • control approach
  • filtration and purification
  • individual respiratory protection
  • particulate-matter monitoring
  • particle migration and simulation

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Published Papers (6 papers)

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Research

14 pages, 6124 KiB  
Article
Feature Extraction and Attribute Recognition of Aerosol Particles from In Situ Light-Scattering Measurements Based on EMD-ICA Combined LSTM Model
by Heng Zhao, Yanyan Zhang, Dengxin Hua, Jiamin Fang, Jie Zhang and Zewen Yang
Atmosphere 2024, 15(12), 1441; https://doi.org/10.3390/atmos15121441 - 30 Nov 2024
Viewed by 513
Abstract
Accurate identification and monitoring of aerosol properties is crucial for understanding their sources and impacts on human health and the environment. Therefore, we propose a feature extraction and attribute recognition method from in situ light-scattering measurements based on Bayesian Optimization, wavelet scattering transform, [...] Read more.
Accurate identification and monitoring of aerosol properties is crucial for understanding their sources and impacts on human health and the environment. Therefore, we propose a feature extraction and attribute recognition method from in situ light-scattering measurements based on Bayesian Optimization, wavelet scattering transform, and long short-term memory neural network (BO-WST-LSTM), with empirical mode decomposition (EMD) and independent component analysis (ICA) algorithm for signal preprocessing. In this study, an experimental platform was utilized to gather light-scattering signals from particles with varying characteristics. The signals are then processed using the EMD-ICA noise reduction technique. Then, the wavelet scattering network is used to realize the adaptive extraction of the characteristics of the particle light-scattering signal, and the Bayesian Optimization model is used to optimize the hyperparameters of the LSTM neural network. The extracted scattering coefficient matrix is input into the LSTM for iterative training. Finally, the SoftMax layer’s probability classification method is applied to the identification of particle attributes. The results show that the multi-angle particle light-scattering signal detection system designed and built in this study performs well and is capable of effectively collecting particle light-scattering signals. At the same time, the proposed new method for particle property recognition demonstrates good classification performance for six different types of particles with a particle size of 2 μm, achieving a classification accuracy of 98.83%. This proves its effectiveness in recognizing particle properties and provides a solid foundation for particle identification. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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20 pages, 6817 KiB  
Article
Genotoxicity and Cytotoxicity Induced In Vitro by Airborne Particulate Matter (PM2.5) from an Open-Cast Coal Mining Area
by Claudia Galeano-Páez, Hugo Brango, Karina Pastor-Sierra, Andrés Coneo-Pretelt, Gean Arteaga-Arroyo, Ana Peñata-Taborda, Pedro Espitia-Pérez, Dina Ricardo-Caldera, Alicia Humanez-Álvarez, Elizabeth Londoño-Velasco, Roger Espinosa-Sáez, Basilio Diaz-Ponguta, Juliana da Silva, Dione Silva Corrêa and Lyda Espitia-Pérez
Atmosphere 2024, 15(12), 1420; https://doi.org/10.3390/atmos15121420 - 26 Nov 2024
Viewed by 724
Abstract
This study evaluates the cytotoxic and genotoxic effects of PM2.5 collected from an open-cast coal mining area in northern Colombia. Cyclohexane (CH), dichloromethane (DCM), and acetone (ACE) extracts were obtained using Soxhlet extraction to isolate compounds of different polarities. Human lymphocytes were [...] Read more.
This study evaluates the cytotoxic and genotoxic effects of PM2.5 collected from an open-cast coal mining area in northern Colombia. Cyclohexane (CH), dichloromethane (DCM), and acetone (ACE) extracts were obtained using Soxhlet extraction to isolate compounds of different polarities. Human lymphocytes were exposed to the extracted compounds, and cytotoxicity and genotoxicity were assessed using the cytokinesis block micronucleus (CBMN) and comet assays, incorporating FPG and ENDO III enzymes to detect oxidative DNA damage. Chemical analysis revealed that the organic fractions consisted mainly of modified hydrocarbons and volatile organic compounds. The CBMN assay showed a significant increase in micronuclei in binucleated (MNBN) and mononucleated (MNMONO) cells and nucleoplasmic bridges (NPB) in exposed lymphocytes. The comet assay revealed substantial oxidative DNA damage, particularly with the ACE extract, which significantly increased oxidized purines and pyrimidines. DCM induced similar effects, while CH showed moderate effects. CREST immunostaining revealed aneugenic activity, particularly in cells exposed to ACE and DCM extracts. These results suggest that polar fractions of PM2.5, likely containing metals and modified PAHs, contribute to DNA damage and chromosomal instability. The study highlights the need to monitor the composition of PM2.5 in mining regions to implement stricter environmental policies to reduce exposure and health risks. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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16 pages, 6787 KiB  
Article
Influence of Particle Surface Energy and Sphericity on Filtration Performance Based on FLUENT-EDEM Coupling Simulation
by Qing Wu, Zhenqiang Xing, Dejun Chen, Jianwu Chen, Bin Yang, Jianfang Zhong, Hong Huang, Zhifei Ma, Shan Huang, Da You, Jianlong Li and Daishe Wu
Atmosphere 2024, 15(7), 787; https://doi.org/10.3390/atmos15070787 - 29 Jun 2024
Viewed by 1247
Abstract
The adhesion of dust particles on the surface of the dust collector tends to cause great resistance to the dust collector and affects the operating efficiency. In order to visualize particles in the filtration process and to grasp the mechanism of particle viscosity [...] Read more.
The adhesion of dust particles on the surface of the dust collector tends to cause great resistance to the dust collector and affects the operating efficiency. In order to visualize particles in the filtration process and to grasp the mechanism of particle viscosity and sphericity on filtration performance, a numerical simulation study was conducted to investigate the deposition behavior of particles during filtration, employing FLUENT-EDEM coupling technology. By examining the deposition process, the role of particle characteristics on dust behavior within the entire filtration system was elucidated. The effects of varying particle surface energy and particle sphericity on filtration pressure drop and cake porosity were analyzed. The findings reveal that under the force of the air, particles on the surface of the filter membrane experience compaction, leading to a reduction in the porosity of the formed cake layer. The diminution of porosity serves to impede the air, consequently augmenting the pressure drop across the filtration system and hindering the operational efficacy of the dust collector. As the surface energy of the particles increases, the adhesive forces between particles are intensified, leading to an elevation in the porosity of the cake layer and a subsequent decrease in the pressure drop. When the surface energy of the particles is increased from 0.01 J/m2 to 0.04 J/m2, the porosity experiences a modest increase of only 9.1%, yet the pressure drop is significantly reduced by half, amounting to a decrease of 1594 Pa. Under high particle surface energy, as filtration air velocity increases, particles are compressed, resulting in a decrease in cake porosity and an increase in pressure drop. Concurrently, our findings indicate that as the sphericity of particles increases, their surfaces become increasingly smooth which in turn results in a decreased porosity of the cake layer and, consequently, an elevation in the filtration pressure drop. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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16 pages, 3965 KiB  
Article
Wind Tunnel Evaluation of Plant Protection Products Drift Using an Integrated Chemical–Physical Approach
by Lorenzo Becce, Giovanna Mazzi, Ayesha Ali, Mara Bortolini, Elena Gregoris, Matteo Feltracco, Elena Barbaro, Daniele Contini, Fabrizio Mazzetto and Andrea Gambaro
Atmosphere 2024, 15(6), 656; https://doi.org/10.3390/atmos15060656 - 30 May 2024
Cited by 1 | Viewed by 1121
Abstract
The use of plant protection products (PPPs) has become fundamental to guarantee excellent field productivity. Nevertheless, their usage presents critical issues, such as the quantity of substances used, the relative toxicity, and the contamination of nearby fields caused by atmospheric drift. This study [...] Read more.
The use of plant protection products (PPPs) has become fundamental to guarantee excellent field productivity. Nevertheless, their usage presents critical issues, such as the quantity of substances used, the relative toxicity, and the contamination of nearby fields caused by atmospheric drift. This study focuses on the characterization of aerosol droplets of PPPs produced by spraying a chemical marker, fluorescein, with an orchard airblast sprayer equipped with conventional hollow cone (HC) and anti-drift air inclusion (AI) nozzles, using a wind tunnel as a controlled environment. A particle/droplet image analysis was employed to study the droplet production of the nozzles, while a liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis allowed us to evaluate samples collected using a cascade impactor located at 5 m, 10 m, and 20 m from the emission point. Overall, HC nozzles are very accurate at producing specific drop size distributions (DSDs), while AI nozzles produce a much wider DSD, concentrating the largest part of the distributed volume into droplets of a larger size. The marker concentration was much lower for the AI nozzles compared to the HC nozzles; moreover, the two nozzles show a similar trend in the coarse droplet range, while significantly differing in the fine droplet spectrum. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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17 pages, 3935 KiB  
Article
Study on Dynamic Characteristics of Magnetic Coagulation of Fe-Based Fine Particles in Iron and Steel Industry
by Dengke Xu, Zuxiang Hu, Li’an Zhang and Wenqing Zhang
Atmosphere 2023, 14(9), 1434; https://doi.org/10.3390/atmos14091434 - 14 Sep 2023
Viewed by 1280
Abstract
Fine dust, represented by Fe-based fine particles and emitted from the production process of the iron and steel industry, is the primary factor causing many diseases represented by industrial pneumoconiosis, and ultra-low dust emission has always been a thorny problem to be solved [...] Read more.
Fine dust, represented by Fe-based fine particles and emitted from the production process of the iron and steel industry, is the primary factor causing many diseases represented by industrial pneumoconiosis, and ultra-low dust emission has always been a thorny problem to be solved urgently. To explore the magnetic coagulation effect of Fe-based fine particles in the magnetic field when removing them from industrial flue gas by the magnetic field effect in the iron and steel industry, using FLUENT software, magnetic dipole force was added between particles through user defined function (UDF) based on the computational fluid dynamics-discrete phase model (CFD-DPM) method so that the collision process of particles was then equivalent to their mutual trapping process. Next, the effects of particle size, particle volume fraction, external magnetic field strength, and particle magnetic susceptibility on the magnetic coagulation process were comprehensively studied. Meanwhile, the proton balance equation (PBE) was solved using the partition method on the basis of the computational fluid dynamics-population balance model (CFD-PBM) to compare the coagulation removal effect under random and aligned orientations of magnetic dipoles, respectively. The results showed that the magnetic coagulation strength under the random orientation of magnetic dipoles was greater than that under the aligned orientation. When the particle size of Fe-based fine particles increased from 0.5 μm to 1.5 μm, the magnetic coagulation coefficient decreased from 0.5414 to 0.2882, and the difference in the removal efficiency under the two different orientations of magnetic dipoles became smaller. When the particle volume fraction increased from 0.01 to 0.03, the magnetic coagulation coefficient increased from 0.2353 to 0.5061, and the difference in the removal efficiency under two orientations was enlarged. When the applied external magnetic field strength increased from 0.5 T to 1.0 T, the magnetic coagulation coefficient increased from 0.3940 to 0.5288, and the magnetic susceptibility increased from 0.0250 to 0.0500, the coagulation coefficient increased from 0.3940 to 0.5288, and the difference under two orientations basically stayed unchanged. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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19 pages, 4763 KiB  
Article
Seasonal Distribution and Source Apportionment of Chemical Compositions in PM2.5 in Nanchang, Inland Area of East China
by Hong Huang, Xin Yin, Yuan Tang, Changwei Zou, Jianlong Li, Chenglong Yu and Fangxu Zhu
Atmosphere 2023, 14(7), 1172; https://doi.org/10.3390/atmos14071172 - 20 Jul 2023
Cited by 3 | Viewed by 1880
Abstract
PM2.5 was sampled in four seasons of 2021 in Nanchang. Organic carbon (OC), elemental carbon (EC), and water-soluble ions were the main chemical compositions in PM2.5. The annual average of OC/PM2.5 and EC/PM2.5 was 17.1% and 2.1%, respectively, [...] Read more.
PM2.5 was sampled in four seasons of 2021 in Nanchang. Organic carbon (OC), elemental carbon (EC), and water-soluble ions were the main chemical compositions in PM2.5. The annual average of OC/PM2.5 and EC/PM2.5 was 17.1% and 2.1%, respectively, while nine water-soluble ions were 56.7%. The order of each ion percentage in PM2.5 was NO3− > SO42− > K+ > Na+ > NH4+ > Cl− > NO2− > Ca2+ > Mg2+. The OC/EC (6.54, 13.17, 8.95, 7.99) and Char-EC/Soot-EC (0.88, 0.64, 1.32, 3.74) indicated that the carbon aerosols mainly originated from coal combustion, biomass combustion, and motor-vehicle emissions. High concentrations of Cl− and Ca2+ in spring were associated with dust sources. A good correlation between Na+, SO42−, and NO3− suggests the formation of Na2SO4 and NaNO3. The results of PM2.5 source apportionment by positive matrix factorisation (PMF) showed five main sources: motor-vehicle sources (18–33%), secondary sources (16–36%), coal combustion sources (16–30%), biomass-combustion sources (10–28%), and dust sources (5–7%). Backward trajectory clustering analysis showed PM2.5 in spring and autumn were more influenced by medium distance and local air but mainly influenced by local sources in winter. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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