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Isoprene Emissions, Oxidation Chemistry and Environmental Impacts
Summer Diurnal LST Variability Across Local Climate Zones Using ECOSTRESS Data in Lecce and Milan

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 16.1 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2024).
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 the Atmosphere.
Companion journals for Atmosphere include: Meteorology and Aerobiology.

Impact Factor: 2.5 (2023); 5-Year Impact Factor: 2.6 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2073-4433

Latest Articles

19 pages, 10912 KiB

Open AccessArticle

Influence of the South Asian High and Western Pacific Subtropical High Pressure Systems on the Risk of Heat Stroke in Japan

by Takehiro Morioka, Kenta Tamura and Tomonori Sato

Atmosphere 2025, 16(6), 693; https://doi.org/10.3390/atmos16060693 (registering DOI) - 8 Jun 2025

Weather patterns substantially influence extreme weathers in Japan. Extreme high temperature events can cause serious health problems, including heat stroke. Therefore, understanding weather patterns, along with their impacts on human health, is critically important for developing effective public health measures. This study examines [...] Read more.

Weather patterns substantially influence extreme weathers in Japan. Extreme high temperature events can cause serious health problems, including heat stroke. Therefore, understanding weather patterns, along with their impacts on human health, is critically important for developing effective public health measures. This study examines the impact of weather patterns on heat stroke risk, focusing on a two-tiered high-pressure system (DH: double high) consisting of a lower tropospheric western Pacific subtropical high (WPSH) and an overlapping upper tropospheric South Asian high (SAH), which is thought to cause high-temperature events in Japan. In this study, the self-organizing map technique was utilized to investigate the relationship between pressure patterns and the number of heat stroke patients in four populous cities. The study period covers July and August from 2008 to 2021. The results show that the average number of heat stroke patients in these cities is higher on DH days than on WPSH days in which SAH is absent. The probability of an extremely high daily number of heat stroke patients is more than twice as high on DH days compared to WPSH days. Notably, this result remains true even when WPSH and DH days are compared within the same air temperature range. This is attributable to the higher humidity and stronger solar radiation under DH conditions, which enhances the risk of heat stroke. Large-scale circulation anomalies similar to the Pacific–Japan teleconnection are found on DH days, suggesting that both high humidity and cloudless conditions are among the large-scale features controlled by this teleconnection. Early countermeasures to mitigate heat stroke risk, including advisories for outdoor activities, should be taken when DH-like weather patterns are predicted. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Past, Current and Future)

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27 pages, 4693 KiB

Open AccessReview

Observation of Multilayer Clouds and Their Climate Effects: A Review

by Jianing Xue, Cheng Yuan, Yawei Qu and Yifei Huang

Atmosphere 2025, 16(6), 692; https://doi.org/10.3390/atmos16060692 (registering DOI) - 7 Jun 2025

Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud [...] Read more.

Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud detection capabilities. Multilayer clouds are widely distributed around the world, showing significant regional differences. Many studies have been carried out on the formation mechanism of multilayer clouds, and observational evidence indicates a close relationship between multilayer cloud development and water vapor supply, updraft, atmospheric circulation, as well as wind shear; however, a unified and comprehensive theoretical framework has not yet been constructed to fully explain the underlying mechanism. In addition, the unique vertical structure of multilayer clouds exhibits different climate effects when compared with single-layer clouds, affecting global climate patterns by regulating precipitation processes and radiative energy budgets. This article reviews the research progress related to multilayer cloud observations and their climate effects and looks forward to the research that needs to be carried out in the future. Full article

(This article belongs to the Special Issue Application of Emerging Methods in Aerosol Research)

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21 pages, 7172 KiB

Open AccessArticle

Future Streamflow and Hydrological Drought Under CMIP6 Climate Projections

by Tao Liu, Yan Liu, Zhenjiang Si, Longfei Wang, Yusu Zhao and Jing Wang

Atmosphere 2025, 16(6), 691; https://doi.org/10.3390/atmos16060691 - 6 Jun 2025

Droughts caused by runoff are an important environmental issue in the context of global climate change, with profound impacts on ecosystems, agriculture and water resource management. To assess the impact of future climate change on the hydrological response of watersheds, this study combines [...] Read more.

Droughts caused by runoff are an important environmental issue in the context of global climate change, with profound impacts on ecosystems, agriculture and water resource management. To assess the impact of future climate change on the hydrological response of watersheds, this study combines the SWAT (Soil and Water Assessment Tool) and MODFLOW (MODular groundwater FLOW model) models to predict future changes in runoff and hydrological drought in watersheds using data from two scenarios under 15 CMIP6 climate models. The results show that: (1) The R² and NSE values of monthly runoff at the Caizuzi station in the Naoli River basin are greater than 0.60 in different periods; (2) the ensemble of climate models after screening can effectively improve the accuracy of runoff simulation and reduce the prediction uncertainty of a single climate model; (3) under different scenarios, the temperature generally increases, the precipitation increases and evapotranspiration increased under the SSP2-4.5 scenario and decreased under the SSP5-8.5 scenario; (4) runoff showed an increasing trend under the SSP2-4.5 scenario and the opposite trend under the SSP5-8.5 scenario; (5) the frequency of winter runoff droughts decreased in the future period, while the frequency of spring and summer droughts increased, with the change trend being more pronounced under the SSP5-8.5 scenario; (6) compared with the baseline period (1965–2014), under the SSP2-4.5 and SSP5-8.5 scenarios, the average annual temperature in the watershed increased by 1.89 °C and 3.22 °C, respectively, and the annual precipitation increased by 32% and 36.19%, respectively, but the summer and autumn runoff decreased; and (7) The SRI-3 model analysis indicates that hydrological droughts will significantly intensify under both future emission scenarios. Under the SSP5-8.5 scenario, droughts will worsen earlier and the abrupt change will occur earlier, while under the SSP2-4.5 scenario, although the abrupt change will occur later, the drought intensity will be higher. The critical drought transition periods are 2030–2047 (SSP5-8.5) and 2045–2055 (SSP2-4.5). This study provides important scientific basis for adaptive water resources management and drought mitigation strategies in cold-region watersheds under future climate scenarios. Full article

(This article belongs to the Special Issue Spatial and Temporal Variability in Drought: Exploring Regional Drought Indicators and Indices)

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14 pages, 1371 KiB

Open AccessArticle

Regional Total Electron Content Disturbance During a Meteorological Storm

by Olga P. Borchevkina, Aleksandr V. Timchenko, Fedor S. Bessarab, Yuliya A. Kurdyaeva, Ivan V. Karpov, Galina A. Yakimova, Maxim G. Golubkov, Ilya G. Stepanov, Sudipta Sasmal and Alexei V. Dmitriev

Atmosphere 2025, 16(6), 690; https://doi.org/10.3390/atmos16060690 - 6 Jun 2025

This study presents a comprehensive analysis of the impact of Storm Laura, which was observed over Europe and the Baltic Sea on 12 March 2020, on the thermosphere–ionosphere system. The investigation of ionospheric disturbances caused by the meteorological storm was carried out using [...] Read more.

This study presents a comprehensive analysis of the impact of Storm Laura, which was observed over Europe and the Baltic Sea on 12 March 2020, on the thermosphere–ionosphere system. The investigation of ionospheric disturbances caused by the meteorological storm was carried out using a combined modeling approach, incorporating the regional AtmoSym and the global GSM TIP models. This allowed for the consideration of acoustic and internal gravity waves (AWs and IGWs) generated by tropospheric convective sources and the investigation of wave-induced effects in both the neutral atmosphere and ionosphere. The simulation results show that, three hours after the activation of the additional heat source, an area of increased temperature exceeding 100 K above the background level formed over the meteorological storm region. This temperature change had a significant impact on the meridional component of the thermospheric wind and total electron content (TEC) variations. For example, meridional wind changes reached 80 m/s compared a the meteorologically quiet day, while TEC variations reached 1 TECu. Good agreement was obtained with experimental TEC maps from CODE (Center for Orbit Determination in Europe), MOSGIM (Moscow Global Ionospheric Map), and WD IZMIRAN (West Department of Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation Russian Academy of Sciences), which revealed a negative TEC value effect over the meteorological storm region. Full article

(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))

12 pages, 5998 KiB

Open AccessArticle

Composition and Source Apportionment of Heavy Metals in Aerosols at the Great Wall Station, Antarctica

by Haiyu Zeng, Xiaoning Liu, Gaoen Wu, Jianjun Wang and Haitao Ding

Atmosphere 2025, 16(6), 689; https://doi.org/10.3390/atmos16060689 - 6 Jun 2025

To elucidate the compositional characteristics and sources of heavy metals in aerosols at China’s Great Wall Station in Antarctica, high-volume aerosol sampling was conducted from 4 January to 26 December 2022, on Fildes Peninsula, King George Island. Ten heavy metals (V, Cr, Mn, [...] Read more.

To elucidate the compositional characteristics and sources of heavy metals in aerosols at China’s Great Wall Station in Antarctica, high-volume aerosol sampling was conducted from 4 January to 26 December 2022, on Fildes Peninsula, King George Island. Ten heavy metals (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, and Pb) in total suspended particulates (TSPs) were quantified via inductively coupled plasma mass spectrometry (ICP-MS). Enrichment factor (EF) analysis, correlation metrics, and backward trajectory clustering were integrated to identify potential sources. The results revealed pronounced enrichment (EF > 10) for Cr, As, Zn, Cd, and Pb, indicating dominant non-crustal contributions. Source apportionment identified three pathways: (1) long-range transported anthropogenic emissions, including Southern Hemisphere marine traffic (e.g., V and Ni from ship fuel combustion) and industrial pollutants from South America (Pb and Cd); (2) local anthropogenic sources, primarily diesel generators and tourism-related gasoline combustion (Cu and Zn); and (3) crustal inputs via glacial melt and weathering (Fe and Mn). This study pioneers the quantification of direct anthropogenic impacts (e.g., power generation and tourism) on aerosol heavy metals in Antarctic research zones, offering critical insights into transboundary pollutant dynamics and regional mitigation strategies. Full article

(This article belongs to the Section Aerosols)

17 pages, 3678 KiB

Open AccessArticle

Independent Component Analysis-Based Composite Drought Index Development for Hydrometeorological Analysis

by Yejin Kong, Joo-Heon Lee and Taesam Lee

Atmosphere 2025, 16(6), 688; https://doi.org/10.3390/atmos16060688 - 6 Jun 2025

Drought is a complex and interconnected natural phenomenon, involving multiple drought types that mutually influence each other. To capture this complexity, various composite drought indices have been developed using diverse methodologies. Traditionally, Principal Component Analysis (PCA) has served as the primary method for [...] Read more.

Drought is a complex and interconnected natural phenomenon, involving multiple drought types that mutually influence each other. To capture this complexity, various composite drought indices have been developed using diverse methodologies. Traditionally, Principal Component Analysis (PCA) has served as the primary method for extracting index weights, predominantly capturing linear relationships among variables. This study proposes an innovative approach by employing Independent Component Analysis (ICA) to develop an ICA-based Composite Drought Index (ICDI), capable of addressing both linear and nonlinear interdependencies. Three drought indices—representing meteorological, hydrological, and agricultural droughts—were integrated. Specifically, the Standardized Precipitation Index (SPI) was adopted as the meteorological drought indicator, whereas the Standardized Reservoir Supply Index (SRSI) was utilized to represent both hydrological (SRSI(H)) and agricultural (SRSI(A)) droughts. The ICDI was derived by extracting optimal weights for each drought index through ICA, leveraging the optimization of non-Gaussianity. Furthermore, constraints (referred to as ICDI-C) were introduced to ensure all index weights were positive and normalized to unity. These constraints prevented negative weight assignments, thereby enhancing the physical interpretability and ensuring that no single drought index disproportionately dominated the composite. To rigorously assess the performance of ICDI, a PCA-based Composite Drought Index (PCDI) was developed for comparative analysis. The evaluation was carried out through three distinct performance metrics: difference, model, and alarm performance. The difference performance, calculated by subtracting composite index values from individual drought indices, indicated that PCDI and ICDI-C outperformed ICDI, exhibiting comparable overall performance. Notably, ICDI-C demonstrated a superior preservation of SRSI(H) values, yielding difference values closest to zero. Model performance metrics (Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and correlation) highlighted ICDI’s comparatively inferior performance, characterized by lower correlations and higher RMSE and MAE. Conversely, PCDI and ICDI-C exhibited similar performance across these metrics, though ICDI-C showed notably higher correlation with SRSI(H). Alarm performance evaluation (False Alarm Ratio (FAR), Probability of Detection (POD), and Accuracy (ACC)) further confirmed ICDI’s weakest reliability, with notably high FAR (up to 0.82), low POD (down to 0.13), and low ACC (down to 0.46). PCDI and ICDI-C demonstrated similar results, although PCDI slightly outperformed ICDI-C as meteorological and agricultural drought indicators, whereas ICDI-C excelled notably in hydrological drought detection (SRSI(H)). The results underscore that ICDI-C is particularly adept at capturing hydrological drought characteristics, rendering it especially valuable for water resource management—a critical consideration given the significance of hydrological indices such as SRSI(H) in reservoir management contexts. However, ICDI and ICDI-C exhibited limitations in accurately capturing meteorological (SPI(6)) and agricultural droughts (SRSI(A)) relative to PCDI. Thus, while the ICA-based composite drought index presents a promising alternative, further refinement and testing are recommended to broaden its applicability across diverse drought conditions and management contexts. Full article

(This article belongs to the Section Meteorology)

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18 pages, 2014 KiB

Open AccessArticle

The Variation in Emission Characteristics and Sources of Atmospheric VOCs in a Polymer Material Chemical Industrial Park in the Yangtze River Delta Region, China

by Wenjuan Li, Jian Wu, Chengcheng Xu and Rupei Wang

Atmosphere 2025, 16(6), 687; https://doi.org/10.3390/atmos16060687 - 6 Jun 2025

To characterize the temporal variation in and source contribution of volatile organic compounds (VOCs) in a polymer industrial park, a two-year offline monitoring campaign (2018–2019) at Shangyu Industrial Park in the Yangtze River Delta was conducted. The study quantified the VOCs composition, seasonal [...] Read more.

To characterize the temporal variation in and source contribution of volatile organic compounds (VOCs) in a polymer industrial park, a two-year offline monitoring campaign (2018–2019) at Shangyu Industrial Park in the Yangtze River Delta was conducted. The study quantified the VOCs composition, seasonal variation, and ozone formation potential (OFP), with source apportionment performed using the Positive Matrix Factorization (PMF) model. During the observation period, the average concentration of total VOCs in 2019 was 286.1 ppb, showing a 22.6% reduction compared to that in 2018. Seasonal analysis revealed decreases in the total VOCs concentration by 41.8%, 38.4%, and 6.1% during spring, summer and winter, respectively, while an increase of 13.8% was observed in autumn, primarily attributed to industrial restructuring in the second half of 2019. Notable reductions were observed in specific VOCs components: oxygen-containing volatile organic compounds (OVOCs), alkane, halogenated hydrocarbon, alkene, and alkyne decreased by 34.5%, 27.9%, 26.3%, 24.6%, and 20.4%, respectively. The average OFP in 2019 was 2402.0 μg/m³, representing a 1.8% reduction from 2018. Contributions to total OFP from alkane, OVOCs, alkyne, and alkene decreased by 32.9%, 26.0%, 20.7%, and 15.0%, respectively, while halogenated hydrocarbons and aromatic hydrocarbons increased by 50.1% and 7.0%. PMF analysis identified four major VOCs sources: industrial production (44.9%), biomass combustion (17.8%), vehicle exhaust (11.0%), and solvent usage (26.3%). From 2018 to 2019, contributions from vehicle exhaust and solvent usage increased by 4.8% and 5.9%, respectively, while industrial production and biomass combustion decreased by 10.5% and 0.3%. Full article

(This article belongs to the Section Air Quality)

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17 pages, 7878 KiB

Open AccessArticle

Projection of the UV Radiation for Vitamin D Production Changes Between 2015–2024 and 2090–2099 Periods

by Vladimir Zubov, Eugene Rozanov and Tatiana Egorova

Atmosphere 2025, 16(6), 686; https://doi.org/10.3390/atmos16060686 - 6 Jun 2025

We evaluate changes in the daily doses of surface ultraviolet radiation (UV) necessary for vitamin D production (UVpD) during the 21st century caused by the evolution of the Earth’s climate and the atmospheric ozone layer. Experiments with the Earth system model SOCOLv4 (version [...] Read more.

We evaluate changes in the daily doses of surface ultraviolet radiation (UV) necessary for vitamin D production (UVpD) during the 21st century caused by the evolution of the Earth’s climate and the atmospheric ozone layer. Experiments with the Earth system model SOCOLv4 (version 4 of the Solar-Climate Ozone Links Chemistry-Climate Model) and an atmospheric radiative transfer model indicated a significant (20–80%) decrease in UVpD doses at the Earth’s surface between 2015–2024 and 2090–2099 in middle latitudes in both hemispheres and an increase of 30–40% in some areas of lower latitudes. These changes are driven by strong greenhouse gas growth and ozone-depleting substance reductions. The experiments also provided estimates of the relative contributions of the total ozone column (TOC), cloud parameters, and surface albedo changes to the corresponding variations in UVpD daily doses. Outside the tropics, the primary factor contributing to the decrease in UVpD doses (50% to 80%) is the increase in TOC. Changes in cloud parameters account for 20% to 30% of the decrease, while the decline in surface albedo contributes less than 20%. However, in the polar regions of the Northern Hemisphere, this contribution can reach up to 50%. In the lower latitudes, diminishing TOC and liquid water column of cloud (LWCC) provide the main contributions to the increase in UVpD doses. Full article

(This article belongs to the Special Issue Ozone Evolution in the Past and Future (2nd Edition))

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21 pages, 6140 KiB

Open AccessArticle

Investigating Dual Character of Atmospheric Ammonia on Particulate NH₄NO₃: Reducing Evaporation Versus Promoting Formation

by Hongxiao Huo, Yating Gao, Lei Sun, Yang Gao, Huiwang Gao and Xiaohong Yao

Atmosphere 2025, 16(6), 685; https://doi.org/10.3390/atmos16060685 - 5 Jun 2025

Ammonium nitrate (NH₄NO₃) is a major constituent of fine particulate matter (PM_2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH₃) in both the formation and [...] Read more.

Ammonium nitrate (NH₄NO₃) is a major constituent of fine particulate matter (PM_2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH₃) in both the formation and volatilization of NH₄NO₃ under ambient atmospheric conditions remains inadequately understood. To address this gap, we conducted high-resolution field measurements at a clean tropical coastal site in China using an integrated system of Aerosol Ion Monitor-Ion Chromatography, a Scanning Mobility Particle Sizer, and online OC/EC analyzers. These observations were complemented by thermodynamic modeling (E-AIM) and source apportionment via a Positive Matrix Factorization (PMF) model. The E-AIM simulations revealed persistent thermodynamic disequilibrium, with particulate NO₃⁻ tending to volatilize even under NH_3gas-rich conditions during the northeast monsoon. This suggests that NH₄NO₃ in PM_2.5 forms rapidly within fresh combustion plumes and/or those modified by non-precipitation clouds and then undergoes substantial evaporation as it disperses through the atmosphere. Under the southeast monsoon conditions, reactions constrained by sea salt aerosols became dominant, promoting the formation of particulate NO₃⁻ while suppressing NH₄NO₃ formation despite ongoing plume influence. In scenarios of regional accumulation, elevated NH₃ concentrations suppressed NH₄NO₃ volatilization, thereby enhancing the stability of particulate NO₃⁻ in PM_2.5. PMF analysis identified five source factors, with NO₃⁻ in PM_2.5 primarily associated with emissions from local power plants and the large-scale regional background, showing marked seasonal variability. These findings highlight the complex and dynamic interplay between the formation and evaporation of NH₄NO₃ in NH_3gas-rich coastal atmospheres. Full article

(This article belongs to the Special Issue Atmospheric Aerosols: How Are They Emitted, Generated, Transported, Aged, and Deposited?)

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15 pages, 1439 KiB

Open AccessArticle

COVID-19 Mortality Among Hospitalized Medicaid Patients in Kentucky (2020–2021): A Geospatial Study of Social, Medical, and Environmental Risk Factors

by Shaminul H. Shakib, Bert B. Little, Seyed M. Karimi and Michael Goldsby

Atmosphere 2025, 16(6), 684; https://doi.org/10.3390/atmos16060684 - 5 Jun 2025

(1) Background: Geospatial associations for COVID-19 mortality were estimated using a cohort of 28,128 hospitalized Medicaid patients identified from the 2020–2021 Kentucky Health Facility and Services administrative claims data. (2) Methods: County-level patient information (age, sex, chronic obstructive pulmonary disease [COPD], and mechanical [...] Read more.

(1) Background: Geospatial associations for COVID-19 mortality were estimated using a cohort of 28,128 hospitalized Medicaid patients identified from the 2020–2021 Kentucky Health Facility and Services administrative claims data. (2) Methods: County-level patient information (age, sex, chronic obstructive pulmonary disease [COPD], and mechanical ventilation use [96 hrs. plus]); social deprivation index (SDI) scores; physician and nurse rates per 100,000; and annual average particulate matter 2.5 (PM_2.5) were used as the predictors. Ordinary least-squares (OLS) regression and multiscale geographically weighted regression (MGWR) with the dependent variable, COVID-19 mortality per 100,000, were performed to compute global and local effects, respectively. (3) Results: MGWR (adjusted R²: 0.52; corrected Akaike information criterion [AICc]: 292.51) performed better at explaining the association between the dependent variable and predictors than the OLS regression (adjusted R²: 0.36; AICc: 301.20). The percentages of patients with COPD and who were mechanically ventilated (96 hrs. plus) were significantly associated with COVID-19 mortality, respectively (OLS standardized βCOPD: 0.22; βventilation: 0.53; MGWR mean βCOPD: 0.38; βventilation: 0.57). Other predictors were not statistically significant in both models. (4) Conclusions: A risk of COVID-19 mortality was observed among patients with COPD and prolonged mechanical ventilation use, after controlling for social determinants, the healthcare workforce, and PM_2.5 in rural and Appalachian counties of Kentucky. These counties are characterized by persistent poverty, healthcare workforce shortages, economic distress, and poor population health outcomes. Improving population health protection through multisector collaborations in rural and Appalachian counties may help reduce future health burdens. Full article

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

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14 pages, 2457 KiB

Open AccessArticle

Temporal Trends and Meteorological Associations of Particulate Matter and Gaseous Air Pollutants in Tehran, Iran (2017–2021)

by Fatemeh Yousefian, Zohreh Afzali Borujeni, Fatemeh Akbarzadeh and Gholamreza Mostafaii

Atmosphere 2025, 16(6), 683; https://doi.org/10.3390/atmos16060683 - 5 Jun 2025

Air pollution is a major environmental risk factor that contributes significantly to the global burden of disease, particularly through its impact on respiratory and cardiovascular health. The aim of this study is to investigate the temporal variations of ambient air pollutants and the [...] Read more.

Air pollution is a major environmental risk factor that contributes significantly to the global burden of disease, particularly through its impact on respiratory and cardiovascular health. The aim of this study is to investigate the temporal variations of ambient air pollutants and the influence of MPs (MPs) on their concentrations in the metropolitan area of Tehran from 2017 to 2021. Hourly data for PM_2.5, PM₁₀, O₃, NO₂, SO₂, and CO from all air quality monitoring stations were obtained. Effects of MPs for the same period were assessed. The results revealed that Tehran’s residents are continuously exposed to harmful levels of PM_2.5 (5.7 to 6.3 times), PM₁₀ (4.5–5.6 times), and NO₂ (8.7–10.0 times) that are significantly higher than the updated World Health Organization (WHO) air quality guidelines. All other air pollutants (except for O₃) showed the lowest and highest concentrations during summer and winter, respectively. The highest concentration of O₃ was found on weekends (weekend effect), while other ambient air pollutants had higher levels on weekdays (holiday effect). Although other air pollutants exhibited two peaks, in the morning and late evening, the hourly concentration of O₃ reached its maximum level at 3:00 pm. Approximately 51% to 65% of the Air Quality Index (AQI) values were classified as unhealthy for sensitive groups. Throughout the study period, PM_2.5 was identified as the primary pollutant affecting air quality in Tehran. Among MPs, temperature was the most important factor in increasing the concentration of O₃, while the other ambient pollutants decreased under the influence of wind speed. Given the current situation, effective and evidence-based air quality management strategies, like those that have been successfully applied elsewhere, are now a necessity to avoid the public health impact and economic losses from air pollution. Although this research focuses on Tehran as a model case of rapidly developing cities facing severe air quality challenges, the findings and recommendations have broader applicability to similar urban environments worldwide. Full article

(This article belongs to the Special Issue Air Quality, Health, and Environmental Sustainability: Challenges and Solutions)

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23 pages, 6569 KiB

Open AccessArticle

Comparative Analysis of the Impact of Built Environment and Land Use on Monthly and Annual Mean PM_2.5 Levels

by Anjian Song, Zhenbao Wang, Shihao Li and Xinyi Chen

Atmosphere 2025, 16(6), 682; https://doi.org/10.3390/atmos16060682 - 5 Jun 2025

Urban planners are progressively recognizing the significant effects of the built environment and land use on PM_2.5 levels. However, in analyzing the drivers of PM_2.5 levels, researchers’ reliance on annual mean and seasonal means may overlook the monthly variations in PM [...] Read more.

Urban planners are progressively recognizing the significant effects of the built environment and land use on PM_2.5 levels. However, in analyzing the drivers of PM_2.5 levels, researchers’ reliance on annual mean and seasonal means may overlook the monthly variations in PM_2.5 levels, potentially impeding accurate predictions during periods of high pollution. This study focuses on the area within the Sixth Ring Road of Beijing, China. It utilizes gridded monthly and annual mean PM_2.5 data from 2019 as the dependent variable. The research selects 33 independent variables from the perspectives of the built environment and land use. The Extreme Gradient Boosting (XGBoost) method is employed to reveal the driving impacts of the built environment and land use on PM_2.5 levels. To enhance the model accuracy and address the randomness in the division of training and testing sets, we conducted twenty comparisons for each month. We employed Shapley Additive Explanations (SHAP) and Partial Dependence Plots (PDP) to interpret the models’ results and analyze the interactions between the explanatory variables. The results indicate that models incorporating both the built environment and land use outperformed those that considered only a single aspect. Notably, in the test set for April, the R² value reached up to 0.78. Specifically, the fitting accuracy for high pollution months in February, April, and November is higher than the annual mean, while July shows the opposite trend. The coefficient of variation for the importance rankings of the seven key explanatory variables exceeds 30% for both monthly and annual means. Among these variables, building density exhibited the highest coefficient of variation, at 123%. Building density and parking lots density demonstrate strong explanatory power for most months and exhibit significant interactions with other variables. Land use factors such as wetlands fraction, croplands fraction, park and greenspace fraction, and forests fraction have significant driving effects during the summer and autumn seasons months. The research on time scales aims to more effectively reduce PM_2.5 levels, which is essential for developing refined urban planning strategies that foster healthier urban environments. Full article

(This article belongs to the Special Issue Modeling and Monitoring of Air Quality: From Data to Predictions)

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21 pages, 6906 KiB

Open AccessArticle

Hydro-Climatic Variability and Peak Discharge Response in Zarrinehrud River Basin, Iran, Between 1986 and 2018

by Farnaz Mohammadi, Jaan H. Pu, Yakun Guo, Prashanth Reddy Hanmaiahgari, Ozra Mohammadi, Mirali Mohammadi, Ebrahim Al-Qadami and Mohd Adib Mohammad Razi

Atmosphere 2025, 16(6), 681; https://doi.org/10.3390/atmos16060681 - 4 Jun 2025

In recent years, both anthropogenic and climate changes have caused the depletion of surface water resources, shifts in rainfall and accelerations in temperature, which indicates the importance of their examination to flood forecasting analyses. This paper studies the importance of synchronised water management [...] Read more.

In recent years, both anthropogenic and climate changes have caused the depletion of surface water resources, shifts in rainfall and accelerations in temperature, which indicates the importance of their examination to flood forecasting analyses. This paper studies the importance of synchronised water management strategies, considering upstream and downstream dynamics using field data from 1986 to 2018. Seasonal and decadal variations show the need for adaptive management strategies to address potential climate change impacts on discharge, precipitation and temperature patterns in the Zarrinehrud River, Iran. The regression analysis was considered via R² values, and the statistical analysis was regarded by p-values. The regression analysis of monthly river peak discharge indicates strong correlations between the discharge of specific months (September–October upstream, December–January downstream). By the 2000s and 2020s, both stations showed a shift in peak precipitation to the spring months (April–May for upstream and May–June for downstream). This confirms a synchronisation of rainfall trends, which are influenced by climate changes or regional hydrological patterns. This temporal offset between stations confirms the spatial and seasonal variation in rainfall distribution across the basin. Higher temperatures during the dominant months, particularly late summer to early autumn, accelerate snowmelt from upstream catchments. This aligns with the river discharge peaks observed in the hydrograph. The statistical analysis of river peak discharge indicated that the Weibull (p-value = 0.0901) and the Lognormal (p-value = 0.1736) distributions are the best fitted distributions for the upstream and downstream stations, respectively. Full article

(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change)

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16 pages, 4440 KiB

Open AccessArticle

El Niño Magnitude and Western Pacific Warm Pool Displacement. Part I: Historical Insights from CMIP6 Models

by Zhuoxin Gu and De-Zheng Sun

Atmosphere 2025, 16(6), 680; https://doi.org/10.3390/atmos16060680 - 4 Jun 2025

Observations indicate a robust relationship between the magnitude of El Niño events and the longitudinal displacement of the eastern edge of the Western Pacific Warm Pool (WPWP). Are the state-of-the-art coupled models also capturing this strong relationship? Here, we address this question by [...] Read more.

Observations indicate a robust relationship between the magnitude of El Niño events and the longitudinal displacement of the eastern edge of the Western Pacific Warm Pool (WPWP). Are the state-of-the-art coupled models also capturing this strong relationship? Here, we address this question by analyzing the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The results show that 31 out of 33 models replicate the observed strong correlation between El Niño magnitude and WPWP displacement. However, the models overestimate both El Niño strength and the extent of eastward WPWP movement, while underrepresenting the inter-event variability. These findings support the notion that El Niño may be largely regarded as an eastward extension of the WPWP, while also highlighting some model–observation discrepancies that may warrant particular attention. Full article

(This article belongs to the Section Climatology)

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19 pages, 5158 KiB

Open AccessArticle

Impact of Background Error Length Scale Tuning in WRF-3DVAR System on High-Resolution Radar Data Assimilation for Typhoon Doksuri Simulation

by Weidi Zhai, Feifei Shen, Jing Liu, Haiyan Fei, Liu Yi, Shen Wan and Xiaolin Yuan

Atmosphere 2025, 16(6), 679; https://doi.org/10.3390/atmos16060679 - 3 Jun 2025

To improve the prediction of Typhoon Doksuri (2023), this paper explores how variations in horizontal scale factors used in assimilating radar-derived wind velocities influence the performance of numerical simulations and forecasts. Using the WRF-ARW model in conjunction with the WRF-3DVAR data assimilation system, [...] Read more.

To improve the prediction of Typhoon Doksuri (2023), this paper explores how variations in horizontal scale factors used in assimilating radar-derived wind velocities influence the performance of numerical simulations and forecasts. Using the WRF-ARW model in conjunction with the WRF-3DVAR data assimilation system, two assimilation configurations were tested with horizontal length scale factors of 1.0 and 0.25. Results show that a reduced length scale facilitates a more detailed reconstruction of mesoscale features, including the typhoon’s eye and inner-core circulation, leading to improved accuracy in short-term intensity and structure forecasts. The experiment utilizing the 0.25 length scale exhibited a tighter warm core, stronger cyclonic wind bands, and a better representation of the vortex’s three-dimensional structure. However, this configuration also led to growing forecast deviations in the latter stages, likely due to imbalances introduced by excessive localization. In contrast, the 1.0-scale experiment produced smoother but less accurate structures and demonstrated larger track deviations. These findings highlight a key trade-off between localized observational influence and long-term forecast stability. The study underscores the importance of optimizing horizontal scale parameterization in variational assimilation to enhance the forecasting accuracy of high-impact tropical cyclones and offers practical insights for operational forecasting systems in regions frequently affected by typhoon activity. Full article

(This article belongs to the Special Issue Advances in Hazardous Weather Prediction: Data Assimilation, Numerical Model and Tools (3rd Edition))

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15 pages, 1018 KiB

Open AccessArticle

Particulate-Bound Polycyclic Aromatic Hydrocarbons and Heavy Metals in Indoor Air Collected from Religious Places for Human Health Risk Assessment

by Thitisuda Kanchana-at, Win Trivitayanurak, Sopannha Chy and Narisa Kengtrong Bordeerat

Atmosphere 2025, 16(6), 678; https://doi.org/10.3390/atmos16060678 - 3 Jun 2025

Particulate matter (PM) has been associated with various health issues. However, the most hazardous constituents of fine particles remain unclear, particularly in Asia where the chemical compositions are highly diverse and understudied. This study investigated the concentration and health risks of particulate-bound polycyclic [...] Read more.

Particulate matter (PM) has been associated with various health issues. However, the most hazardous constituents of fine particles remain unclear, particularly in Asia where the chemical compositions are highly diverse and understudied. This study investigated the concentration and health risks of particulate-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals in the indoor air of religious spaces in Bangkok, Thailand. Air samples were collected from four religious sites during periods of high activity using a six-stage NanoSampler to capture particle sizes ranging from <0.1 to >10 µm. Chemical analyses were conducted using gas chromatography-mass spectrometry (GC-MS/MS) for PAHs and inductively coupled plasma-mass spectrometry (ICP-MS) for heavy metals. The results revealed significantly elevated concentrations of PM2.5, PAHs (notably benzo[a]anthracene (BaA), chrysene (CHR), and fluoranthene (FLU)), and heavy metals (particularly Mn, Ni, and Cu). Health risk assessments indicated that both the incremental lifetime cancer risk (ILCR) and hazard quotient (HQ) values for several pollutants exceeded the U.S. EPA safety thresholds, suggesting serious cancer and non-cancer health risks for workers exposed to these environments over prolonged periods. This study highlights incense burning as a dominant source of toxic indoor air pollutants and underscores the urgent need for mitigation strategies to reduce occupational exposure in religious buildings. Full article

(This article belongs to the Special Issue Atmospheric Aerosols: How Are They Emitted, Generated, Transported, Aged, and Deposited?)

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32 pages, 10281 KiB

Open AccessArticle

Evaluating Outdoor Human Thermal Comfort Through Climate-Resilient Adaptation: A Case Study at School of Science and Technology (NOVA FCT) Campus

by Pedro Torgal Mendes, André Santos Nouri and Andreas Matzarakis

Atmosphere 2025, 16(6), 677; https://doi.org/10.3390/atmos16060677 - 3 Jun 2025

Urbanization and climate change present increasing challenges to outdoor human thermal comfort, particularly in university campuses where academic, social, and recreational activities converge. This study assesses microclimatic risk factors along the main avenue of the NOVA FCT campus by analyzing outdoor human thermal [...] Read more.

Urbanization and climate change present increasing challenges to outdoor human thermal comfort, particularly in university campuses where academic, social, and recreational activities converge. This study assesses microclimatic risk factors along the main avenue of the NOVA FCT campus by analyzing outdoor human thermal comfort using the physiologically equivalent temperature (PET) and modified PET (mPET) indices. Field measurements of air temperature, humidity, wind velocity, and radiation were conducted at multiple Points Of Interest (POIs) to evaluate thermal stress levels and identify critical zones of discomfort. Results indicate significant spatial and temporal variations in thermal stress, with sun-exposed areas (G2) experiencing PET values exceeding 50 °C, during peak summer hours, while shaded locations (G1) showed substantial thermal relief (PET reductions up to 27 °C between G1 and G2 POIs). Wind velocity and urban morphology played crucial roles in modulating microclimatic conditions. Wind velocity above 2.0 m/s was associated with perceptible thermal relief (3–8 °C PET/mPET reduction), especially in narrow, shaded passages. Significant spatial variability was observed, linked to differences in urban morphology, surface materials, and vegetation coverage. This research provides actionable insights for urban planners and campus administrators, contributing to the development of more sustainable and thermally comfortable outdoor environments in educational settings. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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19 pages, 5934 KiB

Open AccessArticle

Variation in Total Electron Content During a Severe Geomagnetic Storm, 23–24 April 2023

by Atirsaw Muluye Tilahun, Edward Uluma and Yohannes Getachew Ejigu

Atmosphere 2025, 16(6), 676; https://doi.org/10.3390/atmos16060676 - 3 Jun 2025

In this paper, we study the geomagnetic storm that occurred on 23–24 April 2023. We present variations in the values of interplanetary magnetic field (IMF-Bz), solar wind parameters (Vsw, Nsw, Tsw, and Psw), geomagnetic index (SYM-H), and vertical total electron content (VTEC) obtained [...] Read more.

In this paper, we study the geomagnetic storm that occurred on 23–24 April 2023. We present variations in the values of interplanetary magnetic field (IMF-Bz), solar wind parameters (Vsw, Nsw, Tsw, and Psw), geomagnetic index (SYM-H), and vertical total electron content (VTEC) obtained from 18 GPS-TEC stations situated in equatorial, mid-latitude, and high-latitude regions. We analyze the variations in total electron content (TEC) before, during, and after the storm using VTEC plots, dTEC% plots, and global ionospheric maps for each GNSS receiver station, all referenced to universal time (UT). Our results indicate that GNSS receiver stations located at high latitudes detected an increase in ionospheric density during the main phase and a decrease during the recovery phase. In contrast, stations in equatorial and mid-latitude regions detected a decrease in ionospheric density during the main phase and an increase during the recovery phase. Large dTEC% values ranging from −80 to 190 TECU were observed a few hours before and during the storm period (23–24 April 2023); these can be compared to values ranging from −10 to 20 TECU on the day before (22 April 2023) and the day after (25 April 2023). Notably, higher dTEC% values were observed at stations in high and middle latitudes compared to those in the equatorial region. As the storm progressed, the TEC intensification observed on global ionospheric maps appeared to shift from east to west. A detailed analysis of these maps showed that equatorial and low-latitude regions experienced larger spatial and temporal TEC variations during the storm period compared to higher-latitude regions. Full article

(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))

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20 pages, 7606 KiB

Open AccessArticle

Convection-Permitting Ability in Simulating an Extratropical Cyclone Case over Southeastern South America

by Matheus Henrique de Oliveira Araújo Magalhães, Michelle Simões Reboita, Rosmeri Porfírio da Rocha, Thales Chile Baldoni, Geraldo Deniro Gomes and Enrique Vieira Mattos

Atmosphere 2025, 16(6), 675; https://doi.org/10.3390/atmos16060675 - 2 Jun 2025

Between 14 and 16 June 2023, an extratropical cyclone affected the south-southeastern coast of Brazil, causing significant damage and loss of life. In the state of Rio Grande do Sul, Civil Defense authorities reported at least 16 fatalities. Although numerical models can simulate [...] Read more.

Between 14 and 16 June 2023, an extratropical cyclone affected the south-southeastern coast of Brazil, causing significant damage and loss of life. In the state of Rio Grande do Sul, Civil Defense authorities reported at least 16 fatalities. Although numerical models can simulate the general characteristics of extratropical cyclones, they often struggle to accurately represent the intensity and timing of strong winds and heavy precipitation. One approach to improving such simulations is the use of convective-permitting models (CPMs), in which convection is explicitly resolved. In this context, the main objective of this study is to assess the performance of the Weather Research and Forecasting (WRF) model in CP mode, nested in the ERA5 reanalysis, in representing both the synoptic and mesoscale structures of the cyclone, as well as its associated strong winds and precipitation. The WRF-CP successfully simulated the cyclone’s track, though with some discrepancies in the cyclone location during the first 12 h. Comparisons with radar-based precipitation estimates indicated that the WRF-CP captured the location of the observed precipitation bands. During the cyclone’s occlusion phase—when precipitation was particularly intense—hourly simulated precipitation and 10 m wind (speed, zonal, and meridional components) were evaluated against observations from meteorological stations. WRF-CP demonstrated strong skill in simulating both the timing and intensity of precipitation, with correlation coefficients exceeding 0.4 and biases below 0.5 mm h⁻¹. Some limitations were observed in the simulation of 10 m wind speed, which tended to be overestimated. However, the model performed well in simulating the wind components, particularly the zonal component, as indicated by predominantly high correlation values (most above 0.4), suggesting a good representation of wind direction, which is a function of the zonal and meridional components. Overall, the simulation highlights the potential of WRF-CP for studying extreme weather events, including the small-scale structures embedded within synoptic-scale cyclones responsible for producing adverse weather. Full article

(This article belongs to the Special Issue Weather and Climate Extremes: Past, Current and Future)

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20 pages, 1980 KiB

Open AccessArticle

Spatiotemporal Variations and Health Assessment of Heavy Metals and Polycyclic Aromatic Hydrocarbons (PAHs) in Ambient Fine Particles (PM_1.1) of a Typical Copper-Processing Area, China

by Weiqian Wang, Jie Ruan and Qingyue Wang

Atmosphere 2025, 16(6), 674; https://doi.org/10.3390/atmos16060674 - 1 Jun 2025

This study investigates the concentrations, health risks, and potential sources of heavy metal elements and polycyclic aromatic hydrocarbons (PAHs) in PM_1.1 particles in Zhuji, a major copper-processing city in China. The ratios of heavy metals (summer: 0.906; winter: 0.619) and PAHs (>0.750 [...] Read more.

This study investigates the concentrations, health risks, and potential sources of heavy metal elements and polycyclic aromatic hydrocarbons (PAHs) in PM_1.1 particles in Zhuji, a major copper-processing city in China. The ratios of heavy metals (summer: 0.906; winter: 0.619) and PAHs (>0.750 in both seasons) in PM_1.1/PM_2.0 suggest significant accumulation in ultrafine particles. In winter, heavy metal concentrations in PM_1.1 reached up to 448 ng/m³, and PAH concentrations were 13.4 ng/m³—over ten times higher than in summer. Health risk assessments revealed that hazard index (HI) values exceeded 1.00 for five age groups (excluding infants) during winter, indicating chronic exposure risks. Incremental lifetime cancer risk (ILCR) values surpassed the upper acceptable limit (1.0 × 10⁻⁴) for four age groups, with Cr, As, Cd, and Pb as major contributors. PAH-related ILCRs were also elevated in winter, with benzo[a]pyrene (BaP) identified as the most potent carcinogen. Enrichment factor (EF) and principal component analysis (PCA) indicated that industrial activities and traffic emissions were the dominant anthropogenic sources of heavy metals. Diagnostic ratio analysis further showed that PAHs mainly originated from vehicle and coal combustion. These findings provide critical insights into pollution patterns in industrial cities and underscore the importance of targeted mitigation strategies. Full article

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

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