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Atmosphere
Special Issues
Observation and Properties of Atmospheric Aerosol
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Observation and Properties of Atmospheric Aerosol

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

Deadline for manuscript submissions: 31 May 2026 | Viewed by 5578

Special Issue Editors

Dr. Florin Unga

E-Mail Website
Guest Editor
Institute of Atmospheric Sciences and Climate (ISAC), National Research Council (CNR), Str. Prv. Lecce-Monteroni km 1.2, 73100 Lecce, Italy
Interests: aerosol; atmospheric pollution; microphysical properties; chemical properties; optical properties; aerosol mixing state; aerosol ageing; aerosol in situ measurements; aerosol remote sensing; analytical microscopy; aerosol single-particle analysis; aerosol chemical composition; elemental composition of aerosol; aerosol typing; modeling of aerosol optical properties; aerosol sampling techniques; aerosol sources and apportionment; long-range transport of aerosols
Dr. Marius M. Cazacu

E-Mail Website
Guest Editor
Department of Physics, Gheorghe Asachi Technical University of Iași, 700050 Iași, Romania
Interests: remote sensing techniques for environmental monitoring; long-range transport of aerosols; pollution; environmental engineering; atmospheric pollution; analytical microscopy; nanoscale imaging and spectroscopy; optical atmosphere; spectroscopy and lasers; physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atmospheric aerosol microphysical, microchemical, and optical properties are the core characteristics for understanding their role in assessing air pollution, radiative forcing, and health impacts. Improved aerosol observations and characterization are currently achieved by long-term monitoring and measurement campaigns, using in situ, remote sensing from ground-based methods and satellites, as well as laboratory off-line analysis techniques. Monitoring of aerosols and their properties is carried out at fixed locations via air quality and research networks, through mobile measurements with transportable stations, and via measurements during movement involving instrumentation boarding vehicles, scientific flights with UAVs as well as manned aircraft, and research vessels.

For this purpose, we are pleased to announce a Special Issue with a focus on observations and properties of atmospheric aerosol, involving topics for characterizing atmospheric aerosol properties, such as size, shape, mixing state, chemical composition, and optical properties, and their source and ageing mechanisms during transport, achieved by observations during long-term and measurement campaigns, via fixed or mobile measurements.

The following areas are of interest, but are not limited to them:

  • Observations and properties of atmospheric aerosol via long-term monitoring and campaign measurements;
  • Aerosol microphysical properties, chemical composition, aerosol typing, and source apportionment;
  • On-line measurements and off-line aerosol single-particle or bulk chemical analysis;
  • Aerosol morphology (size, shape, and mixing state), ageing, and effects on optical properties, radiative forcing, climate models, and human health;
  • In situ, remote sensing, and off-line laboratory analyses of aerosol properties, as well as their synergy and the intercomparison of methods;
  • Air quality monitoring and air pollution studies via fixed or mobile stations;
  • Chamber studies of aerosol properties;
  • Applications of effective-cost sensors for observations of atmospheric aerosol properties;
  • Machine learning techniques for atmospheric aerosol property classification and typing.

We are eager to receive your submission articles for this new Special Issue.

Dr. Florin Unga
Dr. Marius M. Cazacu
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 250 words) can be sent to the Editorial Office for assessment.

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

  • atmospheric aerosol and air pollution
  • microphysical properties
  • chemical composition
  • optical properties
  • aerosol typing and source apportionment
  • mixing state
  • long-term measurements
  • campaign measurements
  • mobile measurements
  • machine learning

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

37 pages, 21906 KB  
Article
Monitoring Aerosol Dynamics in the Beijing–Tianjin–Hebei Region: A High-Resolution, All-Day AOD Dataset from 2018 to 2023
by Jinyu Yang, Boqiong Zhang, Yiyao Yang, Sijia Liu, Bo Li, Wenhao Zhang and Xiufeng Yang
Atmosphere 2026, 17(2), 168; https://doi.org/10.3390/atmos17020168 - 4 Feb 2026
Viewed by 492
Abstract
The Beijing–Tianjin–Hebei (BTH) region is a critical political and economic hub in China, which has long faced challenges related to atmospheric conditions. Traditional aerosol optical depth (AOD) monitoring methods suffer from issues of data discontinuity and gaps, limiting the ability for continuous long-term [...] Read more.
The Beijing–Tianjin–Hebei (BTH) region is a critical political and economic hub in China, which has long faced challenges related to atmospheric conditions. Traditional aerosol optical depth (AOD) monitoring methods suffer from issues of data discontinuity and gaps, limiting the ability for continuous long-term observation of aerosols. Aerosols have significant impacts on climate change and air quality, with AOD serving as a key indicator for characterizing atmospheric particulate concentration. Therefore, this study applied a machine learning model to improve all-day AOD estimation based on ground-level air quality and meteorological data, generating a long-term dataset spanning from 2018 to 2023. The results of the all-day AOD estimation method were evaluated through comparisons with Himawari-8, the Aerosol Robotic Network (AERONET), and the Copernicus Atmosphere Monitoring Service (CAMS). The estimated AOD demonstrated good agreement with AHI data, achieving an annual R2 greater than 0.96 and RMSE less than 0.1. Spatially, the estimated AOD also showed strong consistency with AHI, AERONET, and CAMS. Additionally, the annual, seasonal, and hourly distribution characteristics of AOD from 2018 to 2023 were analyzed. Two typical cases of aerosol variation in the BTH region were selected and examined: a dust storm event in 2023 and changes during the Spring Festival in 2021. This method provides continuous data support for air pollution monitoring and control in the BTH region and offers valuable references for pollution prevention efforts. Full article
(This article belongs to the Special Issue Observation and Properties of Atmospheric Aerosol)
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21 pages, 3146 KB  
Article
Seasonal Variability, Sources and Markers of the Impact of PAH-Bonded PM10 on Health During the COVID-19 Pandemic in Krakow
by Rakshit Jakhar, Przemysław Furman, Alicja Skiba, Dariusz Wideł, Mirosław Zimnoch, Lucyna Samek and Katarzyna Styszko
Atmosphere 2026, 17(2), 120; https://doi.org/10.3390/atmos17020120 - 23 Jan 2026
Viewed by 479
Abstract
The main objective of this research was to evaluate the seasonal variability of PM10-bound polycyclic aromatic hydrocarbons (PAHs), their sources, and analyse their health impacts We confirmduring the COVID-19 pandemic period. The chemical composition of PM10 in terms of PAH [...] Read more.
The main objective of this research was to evaluate the seasonal variability of PM10-bound polycyclic aromatic hydrocarbons (PAHs), their sources, and analyse their health impacts We confirmduring the COVID-19 pandemic period. The chemical composition of PM10 in terms of PAH content was carried out using the gas chromatography-mass spectrometry (GC-MS) technique. PM10 samples were collected in Krakow from 2020 to 2021. A total of 92 samples of particulate matter (PM10 fraction) were analysed. The analyses contained 16 basic PAHs identified by the United States Environmental Protection Agency (U.S. EPA) as the most harmful. The information obtained on the concentrations of PAHs was used to determine the profiles of pollution sources, exposure profiles, and the values of toxic equivalency factors recommended by the EPA: mutagenic equivalent to B[a]P (ang. mutagenic equivalent, MEQ), toxic equivalent to B[a]P (ang. toxic equivalent, TEQ), and carcinogenic equivalent to 2,3,7,8-tetrachlorodibenzo-p-dioxin (ang. carcinogenic equivalent, CEQ). In Kraków, heavy PAHs accounted for over 90% of the total PAHs detected in the PM10 samples. In addition, air trajectory frequency analysis was performed to obtain information on the possibility of transporting pollutants from selected areas in the vicinity of the studied site. Interpreting the trajectory results provided information on the nature of air pollution sources. Analysis of Kraków’s air mass trajectory showed that the highest daily concentration of PM10 in the air flow was from the southwest and east for days. Full article
(This article belongs to the Special Issue Observation and Properties of Atmospheric Aerosol)
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20 pages, 8003 KB  
Article
Construction of a Model for Estimating PM2.5 Concentration in the Yangtze River Delta Urban Agglomeration Based on Missing Value Interpolation of Satellite AOD Data and a Machine Learning Algorithm
by Jiang Qiu, Xiaoyan Dai and Liguo Zhou
Atmosphere 2026, 17(1), 11; https://doi.org/10.3390/atmos17010011 - 22 Dec 2025
Viewed by 615
Abstract
Air pollution is an important environmental issue that affects social development and human life. Atmospheric fine particulate matter (PM2.5) is the primary pollutant affecting the air quality of most cities in the authors’ country. It can cause severe haze, reduce air [...] Read more.
Air pollution is an important environmental issue that affects social development and human life. Atmospheric fine particulate matter (PM2.5) is the primary pollutant affecting the air quality of most cities in the authors’ country. It can cause severe haze, reduce air visibility and cleanliness, and affect people’s daily lives and health. Therefore, it has become a primary research object. Ground monitoring and satellite remote sensing are currently the main ways to obtain PM2.5 data. Satellite remote sensing technology has the advantages of macro-scale, dynamic, and real-time functioning, which can make up for the limitations of the uneven distribution and high cost of ground monitoring stations. Therefore, it provides an effective means to establish a mathematical model—based on atmospheric aerosol optical thickness data obtained through satellite remote sensing and PM2.5 concentration data measured by ground monitoring stations—in order to estimate the PM2.5 concentration and temporal and spatial distribution. This study takes the Yangtze River Delta region as the research area. Based on the measured PM2.5 concentration data obtained from 184 ground monitoring stations in 2023, the newly released sixth version of the MODIS aerosol optical depth product obtained via the US Terra and Aqua satellites is used as the main prediction factor. Dark-pixel AOD data with a 3 km resolution and dark-blue AOD data with a 10 km resolution are combined with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis meteorological, land use, road network, and population density data and other auxiliary prediction factors, and XGBoost and LSTM models are used to achieve high-precision estimation of the spatiotemporal changes in PM2.5 concentration in the Yangtze River Delta region. Full article
(This article belongs to the Special Issue Observation and Properties of Atmospheric Aerosol)
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24 pages, 9545 KB  
Article
Analysis of the PM2.5/PM10 Ratio in Three Urban Areas of Northeastern Romania
by Liliana Drăgoi (Oniu), Marius-Mihai Cazacu and Iuliana-Gabriela Breabăn
Atmosphere 2025, 16(6), 720; https://doi.org/10.3390/atmos16060720 - 13 Jun 2025
Cited by 3 | Viewed by 2945
Abstract
The study was conducted in Suceava, Iasi, and Botosani, three geographically different cities in Romania with increasing PM10 concentrations, especially during the colder months. In order to assess the contributions of PM2.5 and PM10, the PM2.5/PM10 ratios were analyzed for the period 2019–2023. [...] Read more.
The study was conducted in Suceava, Iasi, and Botosani, three geographically different cities in Romania with increasing PM10 concentrations, especially during the colder months. In order to assess the contributions of PM2.5 and PM10, the PM2.5/PM10 ratios were analyzed for the period 2019–2023. The results showed a downward trend in PM10 and PM2.5 concentrations, with a more significant decrease observed for PM2.5. However, although the annual PM2.5/PM10 ratios also decreased, their decrease did not follow the same pattern as the decrease in PM10 and PM2.5 concentrations. The annual PM2.5/PM10 ratios varied from 0.48 to 0.61 in Botosani, from 0.54 to 0.72 in Iasi and from 0.60 to 0.71 in Suceava. The seasonal analysis of the data showed that the highest ratios were observed in winter in Suceava, where wood is also used for residential heating. The frequency distribution of the ratios was examined for each season to determine the nature of the emissions: natural or anthropogenic. The analysis of the spatial variation of the PM2.5/PM10 ratio showed that the greatest differences occurred between Iasi and Botosani as indicated by a coefficient of divergence (COD) value of 0.236. Furthermore, the temperature was used to analyze its potential relationships in relation with the PM2.5/PM10 ratio. Full article
(This article belongs to the Special Issue Observation and Properties of Atmospheric Aerosol)
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