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New Oxidation Mechanism for Sulfur Dioxide
Systematic Review of Prenatal Exposure to PM_2.5 and Its Chemical Components and Their Effects on Neurodevelopmental Outcomes in Neonates
Expanding Continuous Carbon Isotope Measurements of CO₂ and CH₄ in the Italian ICOS Atmospheric Consortium: First Results from the Continental POT Station in Potenza (Basilicata)

Journal Description

Atmosphere

Atmosphere is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Testimonials: See what our editors and authors say about Atmosphere.
Companion journals for Atmosphere include: Meteorology and Aerobiology.

Impact Factor: 2.3 (2024); 5-Year Impact Factor: 2.5 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2073-4433

Latest Articles

26 pages, 18639 KB

Open AccessArticle

Comparison of Two Miniaturized, Rectifiable Aerosol Photometers for Personal PM_2.5 Monitoring in a Dusty Occupational Environment

by James D. Johnston, Scott C. Collingwood, James D. LeCheminant, Neil E. Peterson, Andrew J. South, Clifton B. Farnsworth, Ryan T. Chartier, Mary E. Thiel, Tanner P. Brown, Elisabeth S. Goss, Porter K. Jones, Seshananda Sanjel, Jayson R. Gifford and John D. Beard

Atmosphere 2025, 16(11), 1233; https://doi.org/10.3390/atmos16111233 (registering DOI) - 25 Oct 2025

Wearable, rectifiable aerosol photometers (WRAPs), instruments with combined nephelometer and on-board filter-based sampling capabilities, generally show strong correlations with reference instruments across a range of ambient and household PM_2.5 concentrations. However, limited data exist on their performance when challenged by mixed aerosol [...] Read more.

Wearable, rectifiable aerosol photometers (WRAPs), instruments with combined nephelometer and on-board filter-based sampling capabilities, generally show strong correlations with reference instruments across a range of ambient and household PM_2.5 concentrations. However, limited data exist on their performance when challenged by mixed aerosol exposures, such as those found in dusty occupational environments. Understanding how these instruments perform across a spectrum of environments is critical, as they are increasingly used in human health studies, including those in which concurrent PM_2.5 and coarse dust exposures occur simultaneously. The authors collected co-located, ~24 h. breathing zone gravimetric and nephelometer PM_2.5 measures using the MicroPEM v3.2A (RTI International) and the UPAS v2.1 PLUS (Access Sensor Technologies). Samples were collected from adult brick workers (n = 93) in Nepal during work and non-work activities. Median gravimetric/arithmetic mean (AM) PM_2.5 concentrations for the MicroPEM and UPAS were 207.06 (interquartile range [IQR]: 216.24) and 737.74 (IQR: 1399.98) µg/m³, respectively (p < 0.0001), with a concordance correlation coefficient (CCC) of 0.26. The median stabilized inverse probability-weighted nephelometer PM_2.5 concentrations, after gravimetric correction, for the MicroPEM and UPAS were 169.16 (IQR: 204.98) and 594.08 (IQR: 1001.00) µg/m³, respectively (p-value < 0.0001), with a CCC of 0.31. Digital microscope photos and electron micrographs of filters confirmed large particle breakthrough for both instruments. A possible explanation is that the miniaturized pre-separators were overwhelmed by high dust exposures. This study was unique in that it evaluated personal PM_2.5 monitors in a high dust occupational environment using both gravimetric and nephelometer-based measures. Our findings suggest that WRAPs may substantially overestimate personal PM_2.5 exposures in environments with concurrently high PM_2.5 and coarse dust levels, likely due to large particle breakthrough. This overestimation may obscure associations between exposures and health outcomes. For personal PM_2.5 monitoring in dusty environments, the authors recommend traditional pump and cyclone or impaction-based sampling methods in the interim while miniaturized pre-separators for WRAPs are designed and validated for use in high dust environments. Full article

(This article belongs to the Section Air Quality and Health)

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13 pages, 2365 KB

Open AccessArticle

A Novel Algorithm for Detecting Convective Cells Based on H-Maxima Transformation Using Satellite Images

by Jia Liu and Qian Zhang

Atmosphere 2025, 16(11), 1232; https://doi.org/10.3390/atmos16111232 (registering DOI) - 25 Oct 2025

Mesoscale convective systems (MCSs) play a pivotal role in the occurrence of severe weather phenomena, with convective cells constituting their fundamental elements. The precise identification of these cells from satellite imagery is crucial yet presents significant challenges, including issues related to merging errors [...] Read more.

Mesoscale convective systems (MCSs) play a pivotal role in the occurrence of severe weather phenomena, with convective cells constituting their fundamental elements. The precise identification of these cells from satellite imagery is crucial yet presents significant challenges, including issues related to merging errors and sensitivity to threshold parameters. This study introduces a novel detection algorithm for convective cells that leverages H-maxima transformation and incorporates multichannel data from the FY-2F satellite. The proposed method utilizes H-maxima transformation to identify seed points while maintaining the integrity of core structural features, followed by a novel neighborhood labeling method, region growing and adaptive merging criteria to effectively differentiate adjacent convective cells. The neighborhood labeling method improves the accuracy of seed clustering and avoids “over-clustering” or “under-clustering” issues of traditional neighborhood criteria. When compared to established methods such as RDT, ETITAN, and SA, the algorithm demonstrates superior performance, attaining a Probability of Detection (POD) of 0.87, a False Alarm Ratio (FAR) of 0.21, and a Critical Success Index (CSI) of 0.71. These results underscore the algorithm’s efficacy in elucidating the internal structures of convective complexes and mitigating false merging errors. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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19 pages, 1202 KB

Open AccessArticle

Comparison of the Applicability of Mainstream Objective Circulation Type Classification Methods in China

by Minjin Ma, Ran Chen and Xingyu Zhang

Atmosphere 2025, 16(11), 1231; https://doi.org/10.3390/atmos16111231 (registering DOI) - 24 Oct 2025

Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather forecasting accuracy and supports climate change research. China has complex topography and significant [...] Read more.

Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather forecasting accuracy and supports climate change research. China has complex topography and significant spatiotemporal variability in its circulation patterns, making the study of circulation type classification in this region highly significant. This study aims to evaluate the applicability of several mainstream objective CTC methods in the China region. We applied methods including T-mode principal component analysis (PCT), Ward linkage, K-means, and Self-Organizing Maps (SOM) to classify the sea-level pressure daily mean fields from 1993 to 2023 in the study area, and compared the classification results in terms of internal metrics, continuity, seasonal variation, separability of related meteorological variables (e.g., temperature, precipitation), and stability to spatiotemporal resolution. The results show that each method has its advantages in different contexts, with the K-means method showing the best overall performance. Additionally, an optimized approach combining PCT and K-means is proposed. Full article

(This article belongs to the Section Meteorology)

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26 pages, 982 KB

Open AccessArticle

Climate Change Through Urbanization: The Coupling Effects of Urbanization, Water Resources and Forests on Carbon Emissions

by Shengyuan Wang, Xiaolan Wu, Ying Liu and Rong Wang

Atmosphere 2025, 16(11), 1230; https://doi.org/10.3390/atmos16111230 (registering DOI) - 24 Oct 2025

The purpose of this paper is to quantitatively study the impact mechanism of urbanization, water resources, and forestry system coupling on carbon emissions, and explore new ways to reduce carbon emissions, as complex relationships exist among urbanization, water resources, and forestry systems. Based [...] Read more.

The purpose of this paper is to quantitatively study the impact mechanism of urbanization, water resources, and forestry system coupling on carbon emissions, and explore new ways to reduce carbon emissions, as complex relationships exist among urbanization, water resources, and forestry systems. Based on the data of provincial regions in mainland China from 2015 to 2024, this paper analyzes the impact of urbanization, water resources, and forestry system coupling on carbon emissions by constructing the STIRPAT model. The findings reveal significant heterogeneity in the impact of the coupling degree among urbanization, water resources, and forestry systems on carbon emissions across Chinese provinces. Most regions exhibit insufficient carbon reduction effects. Enhancing the carbon mitigation effect through improving the coupling coordination of urbanization, water resources, and forestry systems presents a novel pathway toward achieving carbon neutrality during urbanization processes. Heterogeneity analysis further indicates that disparities in economic aggregate alter the mechanisms through which the STIRPAT model influences carbon emissions. The main contribution of this paper is to establish the evaluation index system of urbanization, water resources, and forestry development, analyze the mechanism of urbanization, water resources, and forestry coupling system affecting carbon emissions with the STIRPAT model, and explore new pathways for achieving carbon neutrality within urbanizing systems. Full article

(This article belongs to the Special Issue Urban Emissions and Climate Action: Strategies for a Low-Carbon Future)

29 pages, 1060 KB

Open AccessReview

Do Environmental Education Programs Reduce Pollution and Improve Air Quality? Impacts on Knowledge and Behavior Based on Evidence from a Mapping Review

by Rubia Truppel, Anderson D’Oliveira, Laura Canale, Luca Stabile, Giorgio Buonanno and Alexandro Andrade

Atmosphere 2025, 16(11), 1229; https://doi.org/10.3390/atmos16111229 - 23 Oct 2025

This review investigates and analyzes the state of the art on scientific evidence related to educational interventions to improve air quality indoors and outdoors through a mapping review. The review followed proposed guidelines for mapping reviews in environmental sciences and the steps described [...] Read more.

This review investigates and analyzes the state of the art on scientific evidence related to educational interventions to improve air quality indoors and outdoors through a mapping review. The review followed proposed guidelines for mapping reviews in environmental sciences and the steps described in the Template for a Mapping Study Protocol. The search was conducted in PubMed, Web of Science, Embase, Cinahl, and Google Scholar with no language restrictions, and was completed in January 2025. Three filters were applied: search, selection with inclusion and exclusion criteria (PECOS strategy), and data extraction. Two independent reviewers assessed article eligibility, and disagreements were resolved by a third researcher. Twenty-four studies that met the eligibility criteria were included. Five research questions were answered. Studies published between 1977 and 2024 were included, totaling 7289 participants aged 12 to 85. The geographic distribution was concentrated in China (five studies) and the United States (four studies), followed by South Korea, India, Australia, and other countries, with fewer publications. The methodological predominance was experimental studies; observational studies were also analyzed, although less frequently. The period with the greatest increase in the number of publications was between 2020 and 2024. The educational methods most commonly used in the studies were lectures and the delivery of information leaflets. Particulate matter with diameters of 2.5 μm and 10 μm (PM_2.5 and PM₁₀) were the most widely investigated pollutants in the studies. From our analyses, it was observed that the educational interventions to improve air quality, adopted in the selected studies, resulted in the acquisition of knowledge about the environmental effects and the importance of individual actions. The changes in behavior included the adoption of more sustainable practices and an improvement in air quality in the environment, with a significant reduction in pollutant emissions. We conclude that interventions through environmental education demonstrate great potential to improve air quality. Based on the mapped evidence, governments and global policymakers can use this information to develop new strategies or improve existing ones to reduce air pollution in affected environments and regions. Full article

(This article belongs to the Section Air Quality)

15 pages, 1594 KB

Open AccessArticle

Improved Evaluation of Wind Turbine Lightning Exposure: Modeling Upward Leader Effects on Equivalent Collection Area

by Ning Yang, Ying Wen, Zheng Shi, Hongyu Zheng, Cuicui Ji and Maowen Liu

Atmosphere 2025, 16(11), 1228; https://doi.org/10.3390/atmos16111228 - 23 Oct 2025

There has been a growing demand for clean energy in recent years, with the advancement of the carbon neutrality vision. Wind power has occupied a significant percentage of clean energy sources. Usually deployed in open fields, on mountaintops, and in offshore areas, wind [...] Read more.

There has been a growing demand for clean energy in recent years, with the advancement of the carbon neutrality vision. Wind power has occupied a significant percentage of clean energy sources. Usually deployed in open fields, on mountaintops, and in offshore areas, wind turbines are particularly vulnerable to lightning strikes due to their unique operational characteristics. Therefore, accurately evaluating the lightning strike risk of wind turbines is an important issue that should be addressed. Current IEC standards lack a physically grounded approach for calculating the equivalent collection area, leading to an overestimation of this value. This paper employs an upward leader initiation model to develop a novel calculation method for the equivalent collection area of wind turbines. By considering the impact of upward leader channel initiation and development, the model demonstrates accuracy through comparison with observational data (0.7761 strikes/year), showing only a −7.1% discrepancy. This study also examines the impact of various blade rotation angles, stepped leader speeds, and peak current of the return stroke on the equivalent collection area. Results indicate that the lightning strike distance specified in IEC standards underestimates the equivalent collection area due to neglecting the upward leader channel, resulting in significant differences compared to our approach, with a maximum deviation of up to 313.12%. Full article

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17 pages, 12394 KB

Open AccessArticle

Characteristics and Driving Factors of PM_2.5 Concentration Changes in Central China

by Yue Zhao, Ke Wang, Xiaoyong Liu, Qixiang Xu, Le Luo, Panpan Liu, Yanhua He, Yan Yu, Fangcheng Su and Ruiqin Zhang

Atmosphere 2025, 16(11), 1227; https://doi.org/10.3390/atmos16111227 - 23 Oct 2025

Despite nationwide control efforts, central China experiences persistently high annual PM_2.5 concentrations (~50 μg/m³), which are particularly severe in January (exceeding 110 μg/m³). This study employs an integrated approach combining a Multiple Linear Regression (MLR) model derived from [...] Read more.

Despite nationwide control efforts, central China experiences persistently high annual PM_2.5 concentrations (~50 μg/m³), which are particularly severe in January (exceeding 110 μg/m³). This study employs an integrated approach combining a Multiple Linear Regression (MLR) model derived from random forest analysis with the WRF-CMAQ chemical transport modeling system to quantitatively disentangle the driving factors of PM_2.5 concentrations in central China. Key findings reveal significant spatiotemporal heterogeneity in anthropogenic contributions, evidenced by consistently higher north–south gradients in regression residuals (reflecting emission impacts), linked to spatially varying industrial and transportation influences. Critically, the reduction in anthropogenic impacts over six years was substantially smaller in winter (January: 27 to 23 μg/m³) compared to summer (15 to −18 μg/m³, July), highlighting the profound role of emissions in driving severe January pollution events. Furthermore, WRF-CMAQ simulations demonstrated that adverse meteorological conditions in January 2020 counteracted emission controls, causing a net increase in PM_2.5 of +13 μg/m³ relative to 2016, thereby offsetting ~68% of the reductions achieved through emission abatement (−19 μg/m³). Significant regional transport, especially affecting northern and central Henan, further weakened local control efficacy. These quantitative insights into the mechanisms of PM_2.5 pollution, particularly the counteracting effects of meteorology on emission reductions in critical winter periods, provide a vital scientific foundation for designing more effective and targeted air quality management strategies in central China. Full article

(This article belongs to the Special Issue Secondary Atmospheric Pollution Formations and Its Precursors)

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22 pages, 7295 KB

Open AccessArticle

An Artificial Intelligence-Driven Precipitation Downscaling Method Using Spatiotemporally Coupled Multi-Source Data

by Chao Li, Long Ma, Xing Huang, Chenyue Wang, Xinyuan Liu, Bolin Sun and Qiang Zhang

Atmosphere 2025, 16(11), 1226; https://doi.org/10.3390/atmos16111226 - 22 Oct 2025

Addressing the challenges posed by sparse ground meteorological stations and the insufficient resolution and accuracy of reanalysis and satellite precipitation products, this study establishes a multi-source environmental feature system that precisely matches the target precipitation data resolution (1 km × 1 km). Based [...] Read more.

Addressing the challenges posed by sparse ground meteorological stations and the insufficient resolution and accuracy of reanalysis and satellite precipitation products, this study establishes a multi-source environmental feature system that precisely matches the target precipitation data resolution (1 km × 1 km). Based on this foundation, it innovatively proposes a Random Forest-based Dual-Spectrum Adaptive Threshold algorithm (RF-DSAT) for key factor screening and subsequently integrates Convolutional Neural Network (CNN) with Gated Recurrent Unit (GRU) to construct a Spatiotemporally Coupled Bias Correction Model for multi-source data (CGBCM). Furthermore, by integrating these technological components, it presents an Artificial Intelligence-driven Multi-source data Precipitation Downscaling method (AIMPD), capable of downscaling precipitation fields from 0.1° × 0.1° to high-precision 1 km × 1 km resolution. Taking the bend region of the Yellow River Basin in China as a case study, AIMPD demonstrates superior performance compared to bicubic interpolation, eXtreme Gradient Boosting (XGBoost), CNN, and Long Short-Term Memory (LSTM) networks, achieving improvements of approximately 1.73% to 40% in Nash-Sutcliffe Efficiency (NSE). It exhibits exceptional accuracy, particularly in extreme precipitation downscaling, while significantly enhancing computational efficiency, thereby offering novel insights for global precipitation downscaling research. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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27 pages, 1817 KB

Open AccessArticle

Examination of Long-Term Temperature Change in Türkiye: Comparative Evaluation of an Advanced Quartile-Based Approach and Traditional Trend Detection Methods

by Omer Levend Asikoglu, Harun Alp, Ibrahim Temel and Pegah Kamali

Atmosphere 2025, 16(11), 1225; https://doi.org/10.3390/atmos16111225 - 22 Oct 2025

The fact that 2023 and subsequently 2024 were the hottest years in history makes it even more important to monitor temperature changes over time. In this study, trends in the mean, maximum, and minimum temperature data of 81 provinces in Türkiye were examined [...] Read more.

The fact that 2023 and subsequently 2024 were the hottest years in history makes it even more important to monitor temperature changes over time. In this study, trends in the mean, maximum, and minimum temperature data of 81 provinces in Türkiye were examined using three traditional methods (Mann–Kendall, Linear Regression Analysis and Sen’s slope), one innovative method (ITA), and the QuarTrend (QT) method proposed in this study, which uses quartiles of the data series. The objectives of this research are (1) to determine and evaluate the long-term temperature trends in Türkiye (1960–2022) and (2) to comparatively evaluate the trend results of the proposed QT method, traditional trend detection methods, and ITA. In the study, a statistically significant (p < 0.05) increasing trend was found in the mean (0.027 °C/year), maximum (0.031 °C/year), and minimum (0.038 °C/year) annual temperatures of Türkiye. While traditional trend tests detected similar trends with ITA and QT for mean temperatures; ITA and QT detected more trends than traditional methods for maximum and minimum temperatures. The results have direct implications for the impacts of climate change in the study region. The results have the potential to support the development of climate-resilient and adaptive policies for effective water resource planning and management to sustain the environment and agricultural productivity in Türkiye. Full article

(This article belongs to the Section Meteorology)

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25 pages, 8373 KB

Open AccessArticle

Sensitivity of Airborne Methane Retrieval Algorithms (MF, ACRWL1MF, and DOAS) to Surface Albedo and Types: Hyperspectral Simulation Assessment

by Jidai Chen, Ding Wang, Lizhou Huang and Jiasong Shi

Atmosphere 2025, 16(11), 1224; https://doi.org/10.3390/atmos16111224 - 22 Oct 2025

Methane (CH₄) emissions are a major contributor to greenhouse gases and pose significant challenges to global climate mitigation efforts. The accurate determination of CH₄ concentrations via remote sensing is crucial for emission monitoring but remains impeded by surface spectral heterogeneity—notably [...] Read more.

Methane (CH₄) emissions are a major contributor to greenhouse gases and pose significant challenges to global climate mitigation efforts. The accurate determination of CH₄ concentrations via remote sensing is crucial for emission monitoring but remains impeded by surface spectral heterogeneity—notably albedo variations and land cover diversity. This study systematically assessed the sensitivity of three mainstream algorithms, namely, matched filter (MF), albedo-corrected reweighted-L1-matched filter (ACRWL1MF), and differential optical absorption spectroscopy (DOAS), to surface type, albedo, and emission rate through high-fidelity simulation experiments, and proposed a dynamic regularized adaptive matched filter (DRAMF) algorithm. The experiments simulated airborne hyperspectral imagery from the Airborne Visible/InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) with known CH₄ concentrations over diverse surfaces (including vegetation, soil, and water) and controlled variations in albedo through the large-eddy simulation (LES) mode of the Weather Research and Forecasting (WRF) model and the MODTRAN radiative transfer model. The results show the following: (1) MF and DOAS have higher true positive rates (TP > 90%) in high-reflectivity scenarios, but the problem of false positives is prominent (TN < 52%); ACRWL1MF significantly improves the true negative rate (TN = 95.9%) through albedo correction but lacks the ability to detect low concentrations of CH₄ (TP = 63.8%). (2) All algorithms perform better at high emission rates (1000 kg/h) than at low emission rates (500 kg/h), but ACRWL1MF performs more robustly in low-albedo scenarios. (3) The proposed DRAMF algorithm improves the F1 score (0.129) by about 180% compared to the MF and DOAS algorithms and improves TP value (81.4%) by about 128% compared to the ACRWL1MF algorithm through dynamic background updates and an iterative reweighting mechanism. In practical applications, the DRAMF algorithm can also effectively monitor plumes. This research indicates that algorithms should be selected considering the specific application scenario and provides a direction for technical improvements (e.g., deep learning model) for monitoring gas emission. Full article

(This article belongs to the Special Issue Satellite Remote Sensing Applied in Atmosphere (3rd Edition))

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22 pages, 11555 KB

Open AccessArticle

Precipitation Variation Characteristics in Gannan Prefecture, China: Application of the Innovative Trend Analysis and the BEAST (Bayesian Estimator of Abrupt Change, Seasonality, and Trend) Ensemble Algorithm

by Hui Zhou, Linjing Wei and Yanqiang Cui

Atmosphere 2025, 16(11), 1223; https://doi.org/10.3390/atmos16111223 - 22 Oct 2025

This study examined the trend changes as well as the spatial distribution of average precipitation and the abrupt change characteristics of precipitation in Gannan Prefecture, China, using daily precipitation monitoring data from 1980 to 2021 at eight meteorological stations. Analytical methods employed included [...] Read more.

This study examined the trend changes as well as the spatial distribution of average precipitation and the abrupt change characteristics of precipitation in Gannan Prefecture, China, using daily precipitation monitoring data from 1980 to 2021 at eight meteorological stations. Analytical methods employed included the climate change trend rate, anomaly analysis, Innovative Trend Analysis (ITA), ITA-change boxes (ITA-CB), ArcGIS technology, and BEAST Ensemble Algorithm. Long-term average precipitation variability was comprehensively analyzed across multiple temporal scales. Results indicated that over the 42 years, interannual precipitation exhibited a significant increasing trend, with an annual rate of 14.363 mm/decade, and abrupt changes were detected in 1984, 2003, and 2018. The distribution of average precipitation varied substantially from year to year. July was the month with the highest average monthly precipitation, and December was the month with the lowest. Summer precipitation contributed the most to annual totals (51.33%), whereas winter precipitation contributed the least (2.01%). Interdecadal precipitation exhibited a pattern of an initial decrease followed by an increase over the study period. Based on the mean and standard deviation of the series’ first half, which was divided by the ITA method, we established a three-category classification for mean precipitation (low, medium, and high). Annual average and seasonal average precipitation showed non-monotonic variations. While the overall trend of annual average precipitation showed a modest augmentation, the increasing tendencies in the middle-value and high-value categories slowed. In spring, the decreasing trend in high-value categories slowed. In summer, decreasing trends in middle-value categories and overall zones slowed, with an enhanced increasing trend observed in autumn and winter overall. At the spatial scale, the average precipitation across Gannan Prefecture exhibited a decreasing trend from south to north. Higher precipitation was recorded at meteorological stations in the southwest (Maqu), west (Luqu), and south (Diebu), primarily influenced by the interaction between the Qinghai–Tibetan Plateau monsoon and westerly circulation, as well as regional topographic effects. The research findings have significant implications for agricultural and pastoral production planning and sustainable economic development in Gannan Prefecture, China. Full article

(This article belongs to the Section Climatology)

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28 pages, 5659 KB

Open AccessArticle

Airborne Microplastics: Source Implications from Particulate Matter Composition

by Hiroyuki Sasaki, Tsukasa Takahashi, Mari Futami, Tomomi Endo, Mizuho Hirano, Yuka Kotake and Kim-Oanh Pham

Atmosphere 2025, 16(11), 1222; https://doi.org/10.3390/atmos16111222 - 22 Oct 2025

Microplastics (MPs) are emerging pollutants detected in diverse environments and human tissues. Among them, airborne MPs (AMPs) remain poorly characterized due to limited data and methodological inconsistencies. Although regarded as analogous to particulate matter (PM), detailed comparisons with its components are scarce. To [...] Read more.

Microplastics (MPs) are emerging pollutants detected in diverse environments and human tissues. Among them, airborne MPs (AMPs) remain poorly characterized due to limited data and methodological inconsistencies. Although regarded as analogous to particulate matter (PM), detailed comparisons with its components are scarce. To address this gap, this study implemented a unified and seasonal protocol for simultaneous measurement of AMPs and PM across three sites in Japan. AMPs were identified using micro-Raman spectroscopy, enabling polymer- and morphology-resolved analysis. A total of 106 AMPs were identified across all sites and seasons. Polyethylene (PE) was consistently dominant, followed by polyethylene terephthalate (PET) and polyamide (PA). Site-specific variation was evident, with certain polymers being relatively more abundant depending on the local environment. Feret diameter analysis showed a modal range of 4–6 μm, with fragments predominating over granular and fibrous particles. Significant correlations between AMP concentrations and PM components were determined, including syringaldehyde (SYAL), tungsten (W), cobalt (Co), and chromium (Cr), suggesting links to local sources, while indicating that AMP dynamics are not always aligned with PM behavior. This study provides one of the first integrated datasets of AMPs and PM components, offering insights into their occurrence, sources, and atmospheric relevance. Full article

(This article belongs to the Special Issue Micro- and Nanoplastics in the Atmosphere)

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38 pages, 4558 KB

Open AccessReview

Recent Advances in Wildland Fire Smoke Dynamics Research in the United States

by Yongqiang Liu, Warren E. Heilman, Brian E. Potter, Craig B. Clements, William A. Jackson, Nancy H. F. French, Scott L. Goodrick, Adam K. Kochanski, Narasimhan K. Larkin, Pete W. Lahm, Timothy J. Brown, Joshua P. Schwarz, Sara M. Strachan and Fengjun Zhao

Atmosphere 2025, 16(11), 1221; https://doi.org/10.3390/atmos16111221 - 22 Oct 2025

Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more [...] Read more.

Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more extensive application of prescribed fires in the U.S. have posed great challenges and immediate actions for advancing smoke plume dynamics and improving smoke predictions and impact assessments to mitigate smoke impacts. Numerous efforts have been made recently to address these needs and challenges. This paper synthesizes advances in smoke plume dynamics research mainly conducted in the U.S. in the recent decade, identifies gaps, and suggests future research needs. The main advances include smoke data collections from comprehensive field campaigns, new satellite products, improved understanding of smoke plume properties and chemistry, structure and evolution, evaluation and improvement of smoke modeling and prediction systems, the development of coupled smoke models, and applications of machine-learning techniques. The major remaining gaps are the lack of comprehensive simultaneous measurements of smoke, fuels, fire, and atmospheric interactions during wildfires, high-resolution coupled modeling systems of these components, and real-time smoke prediction capacity. The findings from this synthesis study are expected to support smoke research and management to meet various challenges under increasing wildland fires and impacts. Full article

(This article belongs to the Section Air Quality)

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16 pages, 1293 KB

Open AccessArticle

Associations Between Air Pollution and Hospital Admissions for Cardiovascular and Respiratory Diseases in Makkah, Saudi Arabia, During the Hajj Cultural Events and the COVID-19 Outbreak

by Albaraa A. Milibari, Ivan C. Hanigan, Hatim M. Badri, Wahaj A. Khan and Krassi Rumchev

Atmosphere 2025, 16(10), 1220; https://doi.org/10.3390/atmos16101220 - 21 Oct 2025

Air pollution is a global issue affecting health and the environment. This study investigated associations between PM₁₀, NO₂, and admissions from cardiovascular and respiratory diseases in Makkah (2019–2022), comparing Hajj cultural events and the COVID-19 lockdown with non-event periods, [...] Read more.

Air pollution is a global issue affecting health and the environment. This study investigated associations between PM₁₀, NO₂, and admissions from cardiovascular and respiratory diseases in Makkah (2019–2022), comparing Hajj cultural events and the COVID-19 lockdown with non-event periods, using time-series Poisson regression models adjusted for time and seasonality. Event interactions, particularly the impact of the Hajj and COVID-19 periods, were examined to assess potential effects on morbidity. The study findings showed that PM₁₀ was significantly associated with increased respiratory admissions during the Hajj period (lag 0: RR = 1.066; 95% CI: 1.030–1.104), and with decreased risk during the non-Hajj period (lag 0: RR = 0.966; 95% CI: 0.942–0.991) and non-COVID periods (lag 0: RR = 0.946; 95% CI: 0.920–0.973). NO₂ demonstrated a strong positive association with respiratory admissions during the Hajj period across all lags, peaking at lag 0 with a 16.2% increased risk (RR = 1.162; 95% CI: 1.118–1.207). Exposure to PM₁₀ during Hajj was associated with a 3.1% increased risk of cardiovascular admissions (lag 0: RR = 1.031; 95% CI: 1.012–1.050) and decreased risk during non-Hajj (lag 0: RR = 0.981; 95% CI: 0.963–0.999) and non-COVID periods (lag 0: RR = 0.962; 95% CI: 0.942–0.983). NO₂ exposure was positively associated with cardiovascular admissions during Hajj (lag 0: RR = 1.039; 95% CI: 1.019–1.056) and non-COVID periods (lag 0: RR = 1.037; 95% CI: 1.007–1.068). These findings provide event-specific evidence to guide targeted air quality management during mass gatherings, helping policymakers protect the health of Makkah’s residents and visitors. Full article

(This article belongs to the Section Air Quality and Health)

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25 pages, 7246 KB

Open AccessArticle

Research on the Distribution Characteristics and Health Effects of O₃ in the Fenwei Plain

by Qianqian Wang, Chunhui Yang, Man Liu and Ruifeng Yan

Atmosphere 2025, 16(10), 1219; https://doi.org/10.3390/atmos16101219 - 21 Oct 2025

In recent years, coal-combustion-related air pollution has declined markedly, whereas tropospheric ozone (O₃) pollution has emerged as a growing environmental concern. Long-term exposure to O₃ can severely impact human health and ecosystems, constraining socioeconomic development. The Fenwei Plain has complex [...] Read more.

In recent years, coal-combustion-related air pollution has declined markedly, whereas tropospheric ozone (O₃) pollution has emerged as a growing environmental concern. Long-term exposure to O₃ can severely impact human health and ecosystems, constraining socioeconomic development. The Fenwei Plain has complex topographical conditions and a relatively simple industrial structure, and at present, O₃ is one of the main pollutants affecting air quality in this region. Therefore, studying the distribution of O₃ pollution in the Fenwei Plain can provide a reference for developing plans to control O₃ pollution in the area, which is important for safeguarding local public health and economic development. Currently, the number of pollutant monitoring stations in China is limited, spatially discontinuous, and significantly affected by environmental factors, making it difficult to obtain high-precision, large-scale observational data. Satellite-based remote sensing provides broad spatial coverage and is free from topographic constraints, thereby serving as an effective complement to ground-based monitoring networks. This provides important technical support for studying the distribution characteristics of O₃ pollution and its associated health risks. This study focuses on the Fenwei Plain, utilizing machine learning models to estimate continuous O₃ concentrations from 2015 to 2022 and analyze the spatiotemporal distribution of O₃. Based on this, an assessment and analysis of the health risks associated with near-surface O₃ exposure in the study area will be conducted, incorporating the population exposed in the Fenwei Plain and individuals with chronic obstructive pulmonary disease (COPD). Full article

(This article belongs to the Section Air Quality and Health)

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10 pages, 5749 KB

Open AccessArticle

Clear-Air Turbulence over China: Climatology and Multiscale Mechanisms from First Long-Term Aircraft Reports

by Wei Zhang, Xiaochen Zhang, Wei Yuan, Chongyu Zhang, Minghua Hu and Ting Yang

Atmosphere 2025, 16(10), 1218; https://doi.org/10.3390/atmos16101218 - 21 Oct 2025

Clear-air turbulence (CAT), as a key meteorological hazard threatening aviation safety, urgently requires the revelation of its spatiotemporal distribution patterns and formation mechanisms within the China region. Based on the first release of 12,539 aircraft turbulence voice reports from China’s civil aviation from [...] Read more.

Clear-air turbulence (CAT), as a key meteorological hazard threatening aviation safety, urgently requires the revelation of its spatiotemporal distribution patterns and formation mechanisms within the China region. Based on the first release of 12,539 aircraft turbulence voice reports from China’s civil aviation from 2022 to 2024 and ERA5 high-resolution reanalysis data, this study constructs for the first time a climatological portrait of aircraft turbulence over China, revealing the spatiotemporal distribution characteristics and formation mechanisms of CAT in the region: turbulence occurs predominantly at 3000–8000 m (accounting for 61.0%), peaking at 7000–8000 m, driven by strong low-level jet wind shear and Kelvin–Helmholtz instability (KHI); wintertime exhibits a high frequency (33.4%) stemming from strong upper-level jets (>30 m s⁻¹), while summer is dominated by low-level thermal convection (21.0%); the high-incidence zones of Central-South and Southwest China (>2800 events) are jointly governed by a mid-level strong horizontal gradient of vertical vorticity, divergence perturbations, and jet shear, with the winter jet shifting southward (22–30° N), further intensifying the turbulence risk. The findings establish a dynamic–thermodynamic coupling mechanism for CAT over China, providing a scientific basis for aviation safety early warning. Full article

(This article belongs to the Section Aerosols)

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10 pages, 1521 KB

Open AccessArticle

Estimation of Ionosphere Electron Density Structure Related to the Solar Terminator

by Alexey Andreyev, Vyacheslav Somsikov, Vitaliy Kapytin, Yekaterina Chsherbulova and Stanislav Utebayev

Atmosphere 2025, 16(10), 1217; https://doi.org/10.3390/atmos16101217 - 20 Oct 2025

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response [...] Read more.

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response of the medium through which it passes and determine its state. However, our knowledge of the atmospheric phenomena generated by the terminator is far from complete. One clear indication of the terminator’s influence is geomagnetic disturbances manifested in the vertical and eastward components of the magnetic field measured at magnetic observatories. To determine the sources of geomagnetic disturbances from the solar terminator, which can be identified by the strict phase correlation of these disturbances with the moments of terminator passage, ionospheric irregularities arising during terminator passage were studied. Ionospheric irregularities extending along the boundary of the morning solar terminator were detected in total electron content data, based on measurements by GNSS receivers. Assumptions are made about the possible parameters of the ionospheric current structure that creates variations in the magnetic field associated with the passage of the solar terminator. Full article

(This article belongs to the Special Issue Advanced GNSS for Ionospheric Sounding and Disturbances Monitoring)

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20 pages, 1428 KB

Open AccessArticle

A Framework to Minimise the Impacts of Climate Change on UK Residential Buildings and Occupants

by Ehis Lawrence Onus, Ezekiel Chinyio, Emmanuel Itodo Daniel and Michael Gerges

Atmosphere 2025, 16(10), 1216; https://doi.org/10.3390/atmos16101216 - 20 Oct 2025

Residential buildings, the bastions of shelter and protection, are facing an escalating threat from climate change. The need to bolster the resilience of UK residential buildings is becoming more urgent, given the nature and frequency of the impact of climate change. This study [...] Read more.

Residential buildings, the bastions of shelter and protection, are facing an escalating threat from climate change. The need to bolster the resilience of UK residential buildings is becoming more urgent, given the nature and frequency of the impact of climate change. This study employed a sequential explanatory mixed-method approach. The first phase involved surveying 313 households, revealing that Climate Change on Buildings (CCB) and Climate Change Measures (CCM) significantly influenced Climate Change on Occupants (CCO). Moreover, climate-positive measures were found to have a significant impact on building occupants. The second phase involved semi-structured interviews with ten UK construction experts to gather insights into the effects of climate change on residential buildings and strategies for mitigation. The findings from both phases underscore the need for government incentives, green loans, and increased stakeholder awareness to mitigate the impacts of climate change. To fully address climate change and improve the quality of life for residents, all stakeholders, including policy makers, construction professionals, and the community, must participate actively in these efforts. Consequently, a framework was developed to minimise the impacts of climate change on UK residential buildings. Full article

(This article belongs to the Section Climatology)

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18 pages, 12942 KB

Open AccessArticle

Unfavorable Local Meteorological Conditions in the Vicinity of the Planned Nuclear Power Plant in Jordan

by Shatha S. Ali-Saleh, Marwan M. Al-Kloub, Shatha Alsadi, Safaa Marei, Alexander Baklanov, Alexander Mahura, Nahid Atashi and Tareq Hussein

Atmosphere 2025, 16(10), 1215; https://doi.org/10.3390/atmos16101215 - 20 Oct 2025

The development of nuclear energy in Jordan necessitates a detailed understanding of local meteorological behavior, particularly during unfavorable weather conditions. This study uses the METEO mesoscale model to simulate wind fields, vertical motions, and surface–air temperature differences under unfavorable wind directions (15°, 105°, [...] Read more.

The development of nuclear energy in Jordan necessitates a detailed understanding of local meteorological behavior, particularly during unfavorable weather conditions. This study uses the METEO mesoscale model to simulate wind fields, vertical motions, and surface–air temperature differences under unfavorable wind directions (15°, 105°, and 195°) and two wind speeds (1 m/s and 5 m/s), across cold season (January) and warm season (July), near the Samra Energy Power Plant (SEPP)—a proposed location for Jordan’s nuclear plant. Simulations reveal that low wind speeds create stable atmospheric layers with limited vertical motion (±0.1 m/s), enhancing the risk of pollutant accumulation in valleys. Higher wind speeds promote vertical mixing (up to ±0.15 m/s) and lower temperature gradients (within ±0.2 °C), dispersing pollutants more efficiently. These results suggest that specific wind thresholds could determine the spatial extent of emergency response zones, including “shelter-in-place” areas and evacuation perimeters. This study offers valuable insights for nuclear safety planning and environmental risk assessment in complex terrain. Full article

(This article belongs to the Section Meteorology)

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20 pages, 2426 KB

Open AccessArticle

Comprehensive Health Risk Assessment of PM_2.5 Chemical Composition in an Urban Megacity: A Case Study from Greater Cairo Area

by Eliane Farah, Marc Fadel, Hassan R. Dhaini, Nansi Fakhri, Minas Iakovides, Salwa K. Hassan, Mohamed Boraiy, Mostafa El-Nazer, Ali Wheida, Magdy Abdelwahab, Stéphane Sauvage, Agnès Borbon, Jean Sciare, Frédéric Ledoux, Charbel Afif and Dominique Courcot

Atmosphere 2025, 16(10), 1214; https://doi.org/10.3390/atmos16101214 - 20 Oct 2025

While many studies on the health effects of PM_2.5 exist, the risks of PM_2.5 species remain largely unexplored in Middle Eastern and North African countries. This study assesses, for the first time, the carcinogenic and non-carcinogenic health risks for elements, polycyclic [...] Read more.

While many studies on the health effects of PM_2.5 exist, the risks of PM_2.5 species remain largely unexplored in Middle Eastern and North African countries. This study assesses, for the first time, the carcinogenic and non-carcinogenic health risks for elements, polycyclic aromatic hydrocarbons (PAHs), phthalates, polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (DL-PCBs) bound to PM_2.5 in the Greater Cairo Area. A total of 59 samples were collected from an urban site in Dokki (November 2019–January 2020). Chemical analysis showed higher concentrations of PCDFs (5418 fg/m³) than PCDDs (1469 fg/m³), with DL-PCBs being the most abundant (6577 fg/m³). Health risk assessment for inhalation showed non-carcinogenic risks for all age groups, especially for newborns. Manganese (Mn) and lead (Pb) posed the highest elemental non-carcinogenic risk, while the hazard quotient (HQ) for PAHs exceeded 1 across all ages. PCDDs, PCDFs, and DL-PCBs showed an estimated cancer risk reaching 10⁻⁶ in adults, indicating a significant health concern. Key contributors to cancer risk included arsenic (As), chromium (Cr(VI)), and vanadium (V), which accounted for over 80% of the total elemental cancer risk. Major and trace elements posed the highest lifetime cancer risk, nearly 37 times the acceptable level. Full article

(This article belongs to the Section Air Quality and Health)

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