Atmosphere

14 pages, 2075 KB

Open AccessEditor’s ChoiceArticle

Quantifying Polar Mesospheric Clouds Thermal Impact on Mesopause

by Arseniy Sokolov, Elena Savenkova, Andrey Koval, Nikolai Gavrilov, Karina Kravtsova, Kseniia Didenko and Tatiana Ermakova

Atmosphere 2025, 16(8), 922; https://doi.org/10.3390/atmos16080922 - 30 Jul 2025

Viewed by 420

Abstract

The article is focused on the quantitative assessment of the thermal impact of polar mesospheric clouds (PMCs) on the mesopause caused by the emission of absorbed solar and terrestrial infrared (IR) radiation by cloud particles. For this purpose, a parameterization of mesopause heating [...] Read more.

The article is focused on the quantitative assessment of the thermal impact of polar mesospheric clouds (PMCs) on the mesopause caused by the emission of absorbed solar and terrestrial infrared (IR) radiation by cloud particles. For this purpose, a parameterization of mesopause heating by PMC crystals has been developed, the main feature of which is to incorporate the thermal properties of ice and the interaction of cloud particles with the environment. Parametrization is based on PMCs zero-dimensional (0-D) model and uses temperature, pressure, and water vapor data in the 80–90 km altitude range retrieved from Solar Occultation for Ice Experiment (SOFIE) measurements. The calculations are made for 14 PMC seasons in both hemispheres with the summer solstice as the central date. The obtained results show that PMCs can make a significant contribution to the heat balance of the upper atmosphere, comparable to the heating caused, for example, by the dissipation of atmospheric gravity waves (GWs). The interhemispheric differences in heating are manifested mainly in the altitude structure: in the Southern Hemisphere (SH), the area of maximum heating values is 1–2 km higher than in the Northern Hemisphere (NH), while quantitatively they are of the same order. The most intensive heating is observed at the lower boundary of the minimum temperature layer (below 150 K) and gradually weakens with altitude. The NH heating median value is 5.86 K/day, while in the SH it is 5.24 K/day. The lowest values of heating are located above the maximum of cloud ice concentration in both hemispheres. The calculated heating rates are also examined in the context of the various factors of temperature variation in the observed atmospheric layers. It is shown in particular that the thermal impact of PMC is commensurate with the influence of dissipating gravity waves at heights of the mesosphere and lower thermosphere (MLT), which parameterizations are included in all modern numerical models of atmospheric circulation. Hence, the developed parameterization can be used in global atmospheric circulation models for further study of the peculiarities of the thermodynamic regime of the MLT. Full article

(This article belongs to the Special Issue Observations and Analysis of Upper Atmosphere (2nd Edition))

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21 pages, 3828 KB

Open AccessEditor’s ChoiceArticle

Can a Global Climate Model Reproduce a Tornado Outbreak Atmospheric Pattern? Methodology and a Case Study

by Paulina Ćwik, Renee A. McPherson, Funing Li and Jason C. Furtado

Atmosphere 2025, 16(8), 923; https://doi.org/10.3390/atmos16080923 - 30 Jul 2025

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Abstract

Tornado outbreaks can cause substantial damage, injuries, and fatalities, highlighting the need to understand their characteristics for assessing present and future risks. However, global climate models (GCMs) lack the resolution to explicitly simulate tornado outbreaks. As an alternative, researchers examine large-scale atmospheric ingredients [...] Read more.

Tornado outbreaks can cause substantial damage, injuries, and fatalities, highlighting the need to understand their characteristics for assessing present and future risks. However, global climate models (GCMs) lack the resolution to explicitly simulate tornado outbreaks. As an alternative, researchers examine large-scale atmospheric ingredients that approximate tornado-conducive environments. Building on this approach, we tested whether patterns of covariability between WMAXSHEAR and 500-hPa geopotential height anomalies, previously identified in ERA5 reanalysis, could approximate major U.S. May tornado outbreaks in a GCM. We developed a proxy-based methodology by systematically testing pairs of thresholds for both variables to identify the combination that best reproduced the leading pattern selected for analysis. These thresholds were then applied to simulations from the high-resolution MPI-ESM1.2-HR model to assess its ability to reproduce the original pattern. Results show that the model closely mirrored the observed tornado outbreak pattern, as indicated by a low normalized root mean square error, high spatial correlation, and similar distributions. This study demonstrates a replicable approach for approximating tornado outbreak patterns, applied here to the leading pattern, within a GCM, providing a foundation for future research on how such environments might evolve in a warming climate. Full article

(This article belongs to the Section Meteorology)

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29 pages, 16630 KB

Open AccessEditor’s ChoiceArticle

Impact of Radar Data Assimilation on the Simulation of Typhoon Morakot

by Lingkun Ran and Cangrui Wu

Atmosphere 2025, 16(8), 910; https://doi.org/10.3390/atmos16080910 - 28 Jul 2025

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Abstract

The high spatial resolution of radar data enables the detailed resolution of typhoon vortices and their embedded structures; the assimilation of radar data in the initialization of numerical weather prediction exerts an important influence on the forecasting of typhoon track, intensity, and structures [...] Read more.

The high spatial resolution of radar data enables the detailed resolution of typhoon vortices and their embedded structures; the assimilation of radar data in the initialization of numerical weather prediction exerts an important influence on the forecasting of typhoon track, intensity, and structures up to at least 12 h. For the case of typhoon Morakot (2009), Taiwan radar data was assimilated to adjust the dynamic and thermodynamic structures of the vortex in the model initialization by the three-dimensional variation data assimilation system in the Advanced Region Prediction System (ARPS). The radial wind was directly assimilated to tune the original unbalanced velocity fields through a 3-dimensional variation method, and complex cloud analysis was conducted by using the reflectivity data. The influence of radar data assimilation on typhoon prediction was examined at the stages of Morakot landing on Taiwan Island and subsequently going inland. The results showed that the assimilation made some improvement in the prediction of vortex intensity, track, and structures in the initialization and subsequent forecast. For example, besides deepening the central sea level pressure and enhancing the maximum surface wind speed, the radar data assimilation corrected the typhoon center movement to the best track and adjusted the size and inner-core structure of the vortex to be close to the observations. It was also shown that the specific humidity adjustment in the cloud analysis procedure during the assimilation time window played an important role, producing more hydrometeors and tuning the unbalanced moisture and temperature fields. The neighborhood-based ETS revealed that the assimilation with the specific humidity adjustment was propitious in improving forecast skill, specifically for smaller-scale reflectivity at the stage of Morakot landing, and for larger-scale reflectivity at the stage of Morakot going inland. The calculation of the intensity-scale skill score of the hourly precipitation forecast showed the assimilation with the specific humidity adjustment performed skillful forecasting for the spatial forecast-error scales of 30–160 km. Full article

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

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19 pages, 12174 KB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Trends and Exceedance Drivers of Ozone Concentration in the Yangtze River Delta Urban Agglomeration, China

by Junli Xu and Jian Wang

Atmosphere 2025, 16(8), 907; https://doi.org/10.3390/atmos16080907 - 26 Jul 2025

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Abstract

The Yangtze River Delta urban agglomeration, characterized by high population density, an advanced transportation system, and a concentration of industrial activity, is one of the regions severely affected by O₃ pollution in central and eastern China. Using data collected from 251 monitoring [...] Read more.

The Yangtze River Delta urban agglomeration, characterized by high population density, an advanced transportation system, and a concentration of industrial activity, is one of the regions severely affected by O₃ pollution in central and eastern China. Using data collected from 251 monitoring stations between 2015 and 2025, this paper analyzed the spatio-temporal variation of 8 h O₃ concentrations and instances of exceedance. On the basis of exploring the influence of meteorological factors on regional 8 h O₃ concentration, the potential source contribution areas of pollutants under the exceedance condition were investigated using the HYSPLIT model. The results indicate a rapid increase in the 8 h O₃ concentration at a rate of 0.91 ± 0.98 μg·m⁻³·a⁻¹, with the average number of days exceeding concentration standards reaching 41.05 in the Yangtze River Delta urban agglomeration. Spatially, the 8 h O₃ concentrations were higher in coastal areas and lower in inland regions, as well as elevated in plains compared to hilly terrains. This distribution was significantly distinct from the concentration growth trend characterized by higher levels in the northwest and lower levels in the southeast. Furthermore, it diverged from the spatial characteristics where exceedances primarily occurred in the heavily industrialized northeastern region and the lightly industrialized central region, indicating that the growth and exceedance of 8 h O₃ concentrations were influenced by disparate factors. Local human activities have intensified the emissions of ozone precursor substances, which could be the key driving factor for the significant increase in regional 8 h O₃ concentrations. In the context of high temperatures and low humidity, this has contributed to elevated levels of 8 h O₃ concentrations. When wind speeds were below 2.5 m·s⁻¹, the proportion of 8 h O₃ concentrations exceeding the standards was nearly 0 under almost calm wind conditions, and it showed an increasing trend with rising wind speeds, indicating that the potential precursor sources that caused high O₃ concentrations originated occasionally from inland regions, with very limited presence within the study area. This observation implies that the main cause of exceedances was the transport effect of pollution from outside the region. Therefore, it is recommended that the Yangtze River Delta urban agglomeration adopt economic and technological compensation mechanisms within and between regions to reduce the emission intensity of precursor substances in potential source areas, thereby effectively controlling O₃ concentrations and improving public living conditions and quality of life. Full article

(This article belongs to the Special Issue Characteristics and Trends of Air Pollutants and Their Relationship to Atmospheric Circulations)

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29 pages, 32010 KB

Open AccessEditor’s ChoiceArticle

Assessing Environmental Sustainability in the Eastern Mediterranean Under Anthropogenic Air Pollution Risks Through Remote Sensing and Google Earth Engine Integration

by Mohannad Ali Loho, Almustafa Abd Elkader Ayek, Wafa Saleh Alkhuraiji, Safieh Eid, Nazih Y. Rebouh, Mahmoud E. Abd-Elmaboud and Youssef M. Youssef

Atmosphere 2025, 16(8), 894; https://doi.org/10.3390/atmos16080894 - 22 Jul 2025

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Abstract

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using [...] Read more.

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman’s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values ≥ 0.75, and statistical significance was assessed at a p < 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region’s complex political-economic landscape. NO₂ concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 × 10⁻⁸ mol/m²) and weak correlations with climatic variables (<0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: −2.6 × 10⁻⁷ mol/m²) with stronger climate–pollutant correlations (0.30–0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate–pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development. Full article

(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))

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17 pages, 2818 KB

Open AccessEditor’s ChoiceArticle

Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus

by Wenzhen Zong, Zhengni Chen, Quanlin Ma, Lei Ling and Yiming Zhong

Atmosphere 2025, 16(7), 890; https://doi.org/10.3390/atmos16070890 - 20 Jul 2025

Viewed by 323

Abstract

The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and carbon (C) reservoir in China. Studying the main drivers of C density changes in forest ecosystems is crucial to enhance the C sink potential of those ecosystems [...] Read more.

The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and carbon (C) reservoir in China. Studying the main drivers of C density changes in forest ecosystems is crucial to enhance the C sink potential of those ecosystems in ecologically fragile regions. In this study, four stand types at different succession stages in the transition zone of Xinglong Mountain were selected as the study objective. The C densities of the ecosystem, vegetation, plant debris, and soil of each stand type were estimated, and the related driving factors were quantified. The results showed that the forest ecosystem C density continuously increased significantly with natural succession (381.23 Mg/hm² to 466.88 Mg/hm²), indicating that the ecosystem has a high potential for C sequestration with progressive forest succession. The increase in ecosystem C density was mainly contributed to by the vegetation C density, which was jointly affected by the vegetation characteristics (C sink, mean diameter at breast height, mean tree height), litter C/N (nitrogen), and surface soil C/N, with factors explaining 95.1% of the variation in vegetation C density, while the net effect of vegetation characteristics was the strongest (13.9%). Overall, this study provides a new insight for understanding the C cycle mechanism in ecologically fragile areas and further improves the theoretical framework for understanding the C sink function of forest ecosystems. Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

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24 pages, 50503 KB

Open AccessEditor’s ChoiceArticle

Quantifying the Influence of Sea Surface Temperature Anomalies on the Atmosphere and Precipitation in the Southwestern Atlantic Ocean and Southeastern South America

by Mylene Cabrera, Luciano Pezzi, Marcelo Santini and Celso Mendes

Atmosphere 2025, 16(7), 887; https://doi.org/10.3390/atmos16070887 - 19 Jul 2025

Viewed by 554

Abstract

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the [...] Read more.

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the effects of oceanic mesoscale activity during the periods of maximum and minimum Antarctic sea ice extent (September 2019 and February 2020), numerical experiments were conducted using a coupled regional model and an online two-dimensional spatial filter to remove high-frequency sea surface temperature (SST) oscillations. The largest SST anomalies were observed in the Brazil–Malvinas Confluence and along oceanic fronts in September, with maximum SST anomalies reaching 4.23 °C and −3.71 °C. In February, the anomalies were 2.18 °C and −3.06 °C. The influence of oceanic mesoscale activity was evident in surface atmospheric variables, with larger anomalies also observed in September. This influence led to changes in the vertical structure of the atmosphere, affecting the development of the marine atmospheric boundary layer (MABL) and influencing the free atmosphere above the MABL. Modulations in precipitation patterns were observed, not only in oceanic regions, but also in adjacent continental areas. This research provides a novel perspective on ocean–atmosphere thermodynamic coupling, highlighting the mesoscale role and importance of its representation in the study region. Full article

(This article belongs to the Special Issue Recent Advances in Air-Sea Interactions, Climate Variability, and Predictability (2nd Edition))

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18 pages, 6313 KB

Open AccessEditor’s ChoiceArticle

Unveiling PM_2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment

by Yong Pan, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong and Hang Xiao

Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883 - 18 Jul 2025

Cited by 1 | Viewed by 366

Abstract

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory [...] Read more.

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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37 pages, 7235 KB

Open AccessEditor’s ChoiceArticle

New Challenges for Tropical Cyclone Track and Intensity Forecasting in an Unfavorable External Environment in the Western North Pacific—Part II: Intensifications near and North of 20° N

by Russell L. Elsberry, Hsiao-Chung Tsai, Wen-Hsin Huang and Timothy P. Marchok

Atmosphere 2025, 16(7), 879; https://doi.org/10.3390/atmos16070879 - 17 Jul 2025

Viewed by 623

Abstract

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° [...] Read more.

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° N. In this Part II, five other 2024 season typhoons that formed and intensified near and north of 20° N are documented. One change is that the Cooperative Institute for Meteorological Satellite Studies ADT + AIDT intensities derived from the Himawari-9 satellite were utilized for initialization and validation of the ECEPS intensity forecasts. Our first objective of providing earlier track and intensity forecast guidance than the Joint Typhoon Warning Center (JTWC) five-day forecasts was achieved for all five typhoons, although the track forecast spread was large for the early forecasts. For Marie (06 W) and Ampil (08 W) that formed near 25° N, 140° E in the middle of the unfavorable external environment, the ECEPS intensity forecasts accurately predicted the ADT + AIDT intensities with the exception that the rapid intensification of Ampil over the Kuroshio ocean current was underpredicted. Shanshan (11 W) was a challenging forecast as it intensified to a typhoon while being quasi-stationary near 17° N, 142° E before turning to the north to cross 20° N into the unfavorable external environment. While the ECEPS provided accurate guidance as to the timing and the longitude of the 20° N crossing, the later recurvature near Japan timing was a day early and 4 degrees longitude to the east. The ECEPS provided early, accurate track forecasts of Jebi’s (19 W) threat to mainland Japan. However, the ECEPS was predicting extratropical transition with V_max ~35 kt when the JTWC was interpreting Jebi’s remnants as a tropical cyclone. The ECEPS predicted well the unusual southward track of Krathon (20 W) out of the unfavorable environment to intensify while quasi-stationary near 18.5° N, 125.6° E. However, the rapid intensification as Krathon moved westward along 20° N was underpredicted. Full article

(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))

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23 pages, 3620 KB

Open AccessEditor’s ChoiceArticle

Temperature Prediction at Street Scale During a Heat Wave Using Random Forest

by Panagiotis Gkirmpas, George Tsegas, Denise Boehnke, Christos Vlachokostas and Nicolas Moussiopoulos

Atmosphere 2025, 16(7), 877; https://doi.org/10.3390/atmos16070877 - 17 Jul 2025

Viewed by 682

Abstract

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, [...] Read more.

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

(This article belongs to the Special Issue Urban Heat Islands, Global Warming and Effects)

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19 pages, 2337 KB

Open AccessEditor’s ChoiceArticle

Gas–Particle Partitioning and Temporal Dynamics of Pesticides in Urban Atmosphere Adjacent to Agriculture

by Dani Khoury, Supansa Chimjarn, Olivier Delhomme and Maurice Millet

Atmosphere 2025, 16(7), 873; https://doi.org/10.3390/atmos16070873 - 17 Jul 2025

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Abstract

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and [...] Read more.

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and particle phases using GC-MS/MS and LC-MS/MS. Herbicides and fungicides were the most frequently detected classes, appearing in 98% of both phases followed by insecticides. Key compounds such as metalaxyl-M, diphenylamine, and bifenthrin were present in over 90% of samples. Concentrations ranged from 2.5 to 63 ng m⁻³ weekly, with cumulative annual loads exceeding 1200 ng m⁻³. Gas–particle partitioning revealed that highly volatile compounds like azinphos-ethyl favored the gas phase, while less volatile ones like bifenthrin and tebuconazole partitioned >95% into particles. A third-degree polynomial regression (R² of 0.74) revealed a nonlinear relationship between Kₚ and particle-phase concentrations, highlighting a threshold above Kₚ of 0.025 beyond which compounds accumulate disproportionately in the particulate phase. Seasonal variability showed that 36% of the annual pesticide load occurred in autumn, with total airborne levels peaking near 400 ng m⁻³, while the lowest load occurred during summer. Principal component analysis identified rainfall and total suspended particles as major drivers of pesticide phase distribution. The inhalation health risk assessed yielded hazard index values < 1 × 10⁻⁷ for all population groups, suggesting negligible non-cancer risk. This study highlights the prevalence, seasonal dynamics, and partition behavior of airborne pesticides in urban air and underscores the need for regulatory attention to this overlooked exposure route. Full article

(This article belongs to the Section Air Quality)

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15 pages, 3070 KB

Open AccessEditor’s ChoiceArticle

Characteristics and Sources of VOCs During a Period of High Ozone Levels in Kunming, China

by Chuantao Huang, Yufei Ling, Yunbo Chen, Lei Tong, Yuan Xue, Chunli Liu, Hang Xiao and Cenyan Huang

Atmosphere 2025, 16(7), 874; https://doi.org/10.3390/atmos16070874 - 17 Jul 2025

Viewed by 505

Abstract

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on [...] Read more.

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on the emission characteristics and source analysis of VOCs is important for controlling urban ozone pollution. In this study, hourly concentrations of 57 VOC species in four groups were obtained in April 2022, a period of high ozone pollution in Kunming, China. The ozone formation potential analysis showed that the accumulated reactive VOCs significantly contributed to the subsequent ozone formation, particularly aromatics (44.16%) and alkanes (32.46%). In addition, the ozone production rate in Kunming is mainly controlled by VOCs based on the results of the empirical kinetic modeling approach (K_NOx/K_VOCs = 0.25). The hybrid single-particle Lagrangian integrated trajectory model and polar coordinate diagram showed high VOC and ozone concentrations from the southwest outside the province (50.28%) and the south in local areas (12.78%). Six factors were obtained from the positive matrix factorization model: vehicle exhaust (31.80%), liquefied petroleum gas usage (24.16%), the petrochemical industry (17.81%), fuel evaporation (11.79%), coal burning (7.47%), and solvent usage (6.97%). These findings underscore that reducing anthropogenic VOC emissions and strengthening controls on the related sources could provide a scientifically robust strategy for mitigating ozone pollution in Kunming. Full article

(This article belongs to the Section Air Quality)

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18 pages, 3353 KB

Open AccessEditor’s ChoiceArticle

An Evaluation of a Novel Air Pollution Abatement System for Ammonia Emissions Reduction in a UK Livestock Building

by Andrea Pacino, Antonino La Rocca, Donata Magrin and Fabio Galatioto

Atmosphere 2025, 16(7), 869; https://doi.org/10.3390/atmos16070869 - 17 Jul 2025

Viewed by 619

Abstract

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock [...] Read more.

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

(This article belongs to the Special Issue Impacts of Anthropogenic Emissions on Air Quality)

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23 pages, 3967 KB

Open AccessEditor’s ChoiceArticle

Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest

by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris and Panagiotis Stefanidis

Atmosphere 2025, 16(7), 851; https://doi.org/10.3390/atmos16070851 - 12 Jul 2025

Viewed by 543

Abstract

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression [...] Read more.

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting Regression (GBR), and K-Nearest Neighbors (KNN)—in predicting daily PET using limited meteorological data from a high-altitude in Central Greece. The ML models were trained and tested using easily available meteorological inputs—temperature, relative humidity, and extraterrestrial solar radiation—on a dataset covering 11 years (2012–2023). Among the tested configurations, RFR showed the best performance (R² = 0.917, RMSE = 0.468 mm/d, MAPE = 0.119 mm/d) when all the above-mentioned input variables were included, closely approximating FAO56–PM outputs. Results bring to light the potential of machine learning models to reliably estimate PET in data-scarce conditions, with RFR outperforming others, whereas the inclusion of the easily estimated extraterrestrial radiation parameter in the ML models training enhances PET prediction accuracy. Full article

(This article belongs to the Special Issue Observation and Modeling of Evapotranspiration)

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16 pages, 3426 KB

Open AccessEditor’s ChoiceArticle

Climate Projections and Time Series Analysis over Roma Fiumicino Airport Using COSMO-CLM: Insights from Advanced Statistical Methods

by Edoardo Bucchignani

Atmosphere 2025, 16(7), 843; https://doi.org/10.3390/atmos16070843 - 11 Jul 2025

Viewed by 625

Abstract

The evaluation of climate change effects on airport infrastructures is important to maintain safety and flexibility in air travel operations. Airports are particularly vulnerable to extreme weather events and temperature fluctuations, which can disrupt operations, compromise passenger safety, and cause economic losses. Issues [...] Read more.

The evaluation of climate change effects on airport infrastructures is important to maintain safety and flexibility in air travel operations. Airports are particularly vulnerable to extreme weather events and temperature fluctuations, which can disrupt operations, compromise passenger safety, and cause economic losses. Issues such as flooded runways and the disruption of power supplies highlight the need for strong adaptation strategies. The study focuses on the application of the high-resolution regional model COSMO-CLM to assess climate change impacts on Roma Fiumicino airport (Italy) under the IPCC RCP8.5 scenario. The complex topography of Italy requires fine-scale simulation to catch localized climate dynamics. By employing advanced statistical methods, such as fractal analysis, this research aims to increase an understanding of climate change and improve the model prediction capability. The findings provide valuable insights for designing resilient airport infrastructures and updating operational protocols in view of evolving climate risks. A consistent increase in daily temperatures is projected, along with a modest positive trend in annual precipitation. The use of advanced statistical methods revealed insights into the fractal dimensions and frequency components of climate variables, showing an increasing complexity and variability of future climatic patterns. Full article

(This article belongs to the Section Climatology)

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20 pages, 8902 KB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Variation Patterns of and Response Differences in Water Conservation in China’s Nine Major River Basins Under Climate Change

by Qian Zhang and Yuhai Bao

Atmosphere 2025, 16(7), 837; https://doi.org/10.3390/atmos16070837 - 10 Jul 2025

Viewed by 357

Abstract

As a crucial manifestation of ecosystem water regulation and supply functions, water conservation plays a vital role in regional ecosystem development and sustainable water resource management. This study investigates nine major Chinese river basins (Songliao, Haihe, Huaihe, Yellow, Yangtze, Pearl, Southeast Rivers, Southwest [...] Read more.

As a crucial manifestation of ecosystem water regulation and supply functions, water conservation plays a vital role in regional ecosystem development and sustainable water resource management. This study investigates nine major Chinese river basins (Songliao, Haihe, Huaihe, Yellow, Yangtze, Pearl, Southeast Rivers, Southwest Rivers, and Inland Rivers) through integrated application of the InVEST model and geographical detector model. We systematically examine the spatiotemporal heterogeneity of water conservation capacity and its driving mechanisms from 1990 to 2020. The results reveal a distinct northwest–southeast spatial gradient in water conservation across China, with lower values predominating in northwestern regions. Minimum conservation values were recorded in the Inland River Basin (15.88 mm), Haihe River Basin (42.07 mm), and Yellow River Basin (43.55 mm), while maximum capacities occurred in the Pearl River Basin (483.68 mm) and Southeast Rivers Basin (517.21 mm). Temporal analysis showed interannual fluctuations, peaking in 2020 at 130.98 mm and reaching its lowest point in 2015 at 113.04 mm. Precipitation emerged as the dominant factor governing spatial patterns, with higher rainfall correlating strongly with enhanced conservation capacity. Land cover analysis revealed superior water retention in vegetated areas (forests, grasslands, and cultivated land) compared to urbanized and bare land surfaces. Our findings demonstrate that water conservation dynamics result from synergistic interactions among multiple factors rather than single-variable influences. Accordingly, we propose that future water resource policies adopt an integrated management approach addressing climate patterns, land use optimization, and socioeconomic factors to develop targeted conservation strategies. Full article

(This article belongs to the Special Issue Response of Vegetation to Climatic and Anthropogenic Drivers in the Plateau)

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19 pages, 4001 KB

Open AccessEditor’s ChoiceArticle

Simulating Lightning Discharges: The Influence of Environmental Conditions on Ionization and Spark Behavior

by Gabriel Steinberg and Naomi Watanabe

Atmosphere 2025, 16(7), 831; https://doi.org/10.3390/atmos16070831 - 9 Jul 2025

Viewed by 461

Abstract

This study investigates the behavior of spark discharges under various environmental conditions to simulate aspects of early-stage lightning dynamics, with a focus on their spectral characteristics, propagation, and ionization behavior. In a laboratory setting, spark discharges generated by a Tesla coil operating with [...] Read more.

This study investigates the behavior of spark discharges under various environmental conditions to simulate aspects of early-stage lightning dynamics, with a focus on their spectral characteristics, propagation, and ionization behavior. In a laboratory setting, spark discharges generated by a Tesla coil operating with high-frequency alternating current (AC) were analyzed under varying air humidity and water surface conductivity. Spectral analysis revealed that the discharges are dominated by the second positive system of molecular nitrogen N₂ (2P) and also exhibit the first negative system of molecular nitrogen ions N₂⁺ (1N). Notably, the N₂ (2P) emissions show strong peaks in the 350–450 nm range, closely matching spectral features typically associated with corona and streamer discharges in natural lightning. Environmental factors significantly influenced discharge morphology: in dry air, sparks exhibited longer and more branched paths, while in moist air, the discharges were shorter and more confined. Over water surfaces, the sparks spread radially, forming star-shaped patterns. Deionized (DI) water, with low conductivity, supported wider lateral propagation, whereas higher conductivity in tap water and saltwater suppressed discharge spread. The gap between the electrode tip and the surface also affected discharge extent and brightness. These findings demonstrate that Tesla coil discharges reproduce key features of early lightning processes and offer insights into how environmental factors influence discharge development. Full article

(This article belongs to the Special Issue Global Space Weather Variability with a Specific Focus on Ionospheric Climatological Forecasting and Predictive Modelling)

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19 pages, 1214 KB

Open AccessEditor’s ChoiceArticle

Physical and Chemical Characteristics of Different Aerosol Fractions in the Southern Baikal Region (Russia) During the Warm Season

by Liudmila P. Golobokova, Tamara V. Khodzher, Vladimir A. Obolkin, Vladimir L. Potemkin and Natalia A. Onischuk

Atmosphere 2025, 16(7), 829; https://doi.org/10.3390/atmos16070829 - 8 Jul 2025

Viewed by 348

Abstract

The Baikal region, including areas with poor environmental conditions, has significant clean background zones. In the summer of 2023, we analyzed the physical and chemical parameters of aerosol particles with different size fractions at Irkutsk and Listvyanka monitoring stations. Reduced wildfires and minimal [...] Read more.

The Baikal region, including areas with poor environmental conditions, has significant clean background zones. In the summer of 2023, we analyzed the physical and chemical parameters of aerosol particles with different size fractions at Irkutsk and Listvyanka monitoring stations. Reduced wildfires and minimal impact from fuel and energy industries allowed us to observe regional and transboundary pollution transport. A large data array indicated that, during the shift of cyclones from Mongolia to the south of the Baikal region, the concentrations of Na⁺, Ca²⁺, Mg²⁺, K⁺, and Cl⁻ ions increased at the Irkutsk station, dominated by NH₄⁺ and SO₄²⁻. The growth of the ionic concentrations at the Listvyanka station was observed in aerosol particles during the northwesterly transport. When air masses arrived from the southerly direction, the atmosphere was the cleanest. The analysis of 27 elements in aerosols revealed that Al, Fe, Mn, Cu, and Zn made the greatest contribution to air pollution at the Irkutsk station, while Fe, Al, Cu, Cr, Mn, and Ni made the greatest contribution to air pollution at the Listvyanka station. The dynamics of the investigated elements were mainly due to natural processes in the air under various synoptic situations and weather conditions in the region, although anthropogenic factors also affected the formation of aerosol composition wth certain directions of air mass transport. Full article

(This article belongs to the Special Issue Chemistry, Environmental Effects, and Source Analysis of Particulate Matters)

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13 pages, 2769 KB

Open AccessEditor’s ChoiceArticle

Assessment of Vertical Redistribution of Electron Density in Ionosphere During an X-Class Solar Flare Using GNSS Data

by Susanna Bekker

Atmosphere 2025, 16(7), 825; https://doi.org/10.3390/atmos16070825 - 7 Jul 2025

Viewed by 387

Abstract

The impact of solar flares on the Earth’s ionosphere has been studied for many decades using both experimental and theoretical approaches. However, the accuracy of predicting ionospheric layer dynamics in response to variations in solar radiation remains limited. In particular, understanding the vertical [...] Read more.

The impact of solar flares on the Earth’s ionosphere has been studied for many decades using both experimental and theoretical approaches. However, the accuracy of predicting ionospheric layer dynamics in response to variations in solar radiation remains limited. In particular, understanding the vertical redistribution of charged particles in the ionosphere during flares with different spectral characteristics presents a significant challenge. In this study, a method is presented for reconstructing the temporal evolution of the vertical electron concentration (

N e

) profile based on GNSS (Global Navigation Satellite Systems) measurements of total electron content along partially illuminated satellite-receiver paths. Using this method, vertical profiles of

N e

were reconstructed during various phases of the X13.3-class solar flare that occurred on 6 September 2017. The resulting profiles correctly respond to the observed variations in solar extreme ultraviolet and X-ray radiation. This indicates that the method can be effectively applied to analyse other powerful solar events. Full article

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

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23 pages, 1622 KB

Open AccessEditor’s ChoiceArticle

The Beneficial Spatial Spillover Effects of China’s Carbon Emissions Trading System on Air Quality

by Diwei Zheng and Daxin Dong

Atmosphere 2025, 16(7), 819; https://doi.org/10.3390/atmos16070819 - 5 Jul 2025

Viewed by 560

Abstract

Between 2013 and 2020, China had implemented a pilot cap-and-trade carbon emissions trading system (ETS) in some cities. Previous research has reported that this policy significantly reduces air pollution in the policy-implementing districts. However, whether and to what extent there are spatial spillover [...] Read more.

Between 2013 and 2020, China had implemented a pilot cap-and-trade carbon emissions trading system (ETS) in some cities. Previous research has reported that this policy significantly reduces air pollution in the policy-implementing districts. However, whether and to what extent there are spatial spillover effects of this policy on air pollution in other regions has not been sufficiently analyzed. The research objective of this study is to quantitatively assess the spatial spillover effects of China’s carbon ETS on air pollution. Based on data from 288 Chinese cities between 2005 and 2020, this study employs a multiple linear regression approach to estimate the policy effects. Our study finds that the policy significantly reduces the concentrations of black carbon (BC), nitrogen dioxide (NO₂), organic carbon (OC), particulate matter less than 1 micron in size (PM₁), fine particulate matter (PM_2.5), and particulate matter less than 10 microns in size (PM₁₀) in non-ETS regions. This indicates that the carbon ETS has beneficial impacts on air quality beyond the areas where the policy was implemented. The heterogeneity tests reveal that the beneficial spatial spillover effects of the ETS can be observed across cities with different levels of industrialization, population density, economic development, resource endowments, and geographical locations. Further mechanism analyses show that although the policy does not affect the degree of environmental regulation in other regions, it promotes green innovation, low-carbon energy transition, and industrial structure upgrading there, which explains the observed spatial spillover effects. Full article

(This article belongs to the Special Issue Air Pollution in China (4th Edition))

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24 pages, 17002 KB

Open AccessEditor’s ChoiceArticle

The Role of Air Mass Advection and Solar Radiation in Modulating Air Temperature Anomalies in Poland

by Olga Zawadzka-Mańko and Krzysztof M. Markowicz

Atmosphere 2025, 16(7), 820; https://doi.org/10.3390/atmos16070820 - 5 Jul 2025

Viewed by 1413

Abstract

This study examines the roles of air mass advection and solar radiation in shaping daily air temperature anomalies in Warsaw, Poland, from 2008 to 2023. It integrates solar radiation data, HYSPLIT back-trajectories, air temperature measurements, and machine learning methods, which are key atmospheric [...] Read more.

This study examines the roles of air mass advection and solar radiation in shaping daily air temperature anomalies in Warsaw, Poland, from 2008 to 2023. It integrates solar radiation data, HYSPLIT back-trajectories, air temperature measurements, and machine learning methods, which are key atmospheric factors contributing to temperature anomalies in different seasons. Radiation dominates during warm seasons, while advection-related geographic factors are more influential during winter. Increased solar radiation is observed across all seasons during high-positive temperature anomalies (exceeding two standard deviations). In contrast, cold anomalies in summer are accompanied by strong negative solar radiation anomalies (−136.3 W/m²), while winter cold events may still coincide with positive radiation anomalies (25.7 W/m²). Very slow circulation over Central Europe, which occurs twice as often in summer as in winter, leads to positive temperature (1.3 °C) and negative radiation (−2.1 W/m²) anomalies in summer and to negative temperature (−1.9 °C) anomalies and slightly positive radiation (0.3 W/m²) anomalies in winter. The seasonal variability in the spatial origin of air masses reflects shifts in synoptic-scale circulation patterns. These findings highlight the importance of considering the combined influence of radiative and advective processes in driving temperature extremes and their seasonal dynamics in mid-latitude climates. Full article

(This article belongs to the Section Meteorology)

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26 pages, 5006 KB

Open AccessEditor’s ChoiceArticle

Kilometer-Scale Regional Modeling of Precipitation Projections for Bulgaria Using HPC Discoverer

by Rilka Valcheva and Ivan Popov

Atmosphere 2025, 16(7), 814; https://doi.org/10.3390/atmos16070814 - 3 Jul 2025

Viewed by 630

Abstract

The main goal of this study is to present future changes in various precipitation indices at a kilometer-scale resolution for Bulgaria on an annual and seasonal basis. Numerical simulations were conducted using the Non-Hydrostatic Regional Climate Model version 4 (RegCM4-NH) following the Coordinated [...] Read more.

The main goal of this study is to present future changes in various precipitation indices at a kilometer-scale resolution for Bulgaria on an annual and seasonal basis. Numerical simulations were conducted using the Non-Hydrostatic Regional Climate Model version 4 (RegCM4-NH) following the Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study protocol for three 10-year periods (1995–2004, 2041–2050, and 2090–2099), with horizontal grid resolutions of 15 km and 3 km, on the petascale supercomputer HPC Discoverer at Sofia Tech Park. Data from the Hadley Centre Global Environment Model version 2 (HadGEM2-ES), based on the Representative Concentration Pathway 8.5 (RCP8.5) scenario, were used as boundary conditions for the regional climate model (RCM) simulations, which were subsequently downscaled to the kilometer-scale (3 km) simulations using a one-way nesting approach. High-resolution model data were compared with high-resolution observational datasets as well as lower-resolution (15 km) data. Future changes in precipitation indices were analyzed on both annual and seasonal scales, including mean daily and hourly precipitation, the frequency and intensity of wet days (>1 mm/day) and wet hours (>0.1 mm/hour), extreme daily precipitation (99th percentile, p99), and extreme hourly precipitation (99.9th percentile, p99.9) for both future periods. Additionally, changes in near-surface (2 m) temperature and surface snow amount were also presented. There is no substantial difference in projected temperature change between the resolutions. A positive trend in annual mean precipitation is expected in the near future. Extreme precipitation (p99 and p99.9) is projected to increase in spring and winter, accompanied by a rise in daily and hourly precipitation intensity across both future periods. An increase in surface snow amount is observed in the central Danubian Plain, Thracian Lowland, and parts of the Rila and Pirin mountains for the near-future period. However, surface snow amount is expected to decrease by the end of the century. Full article

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

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12 pages, 2714 KB

Open AccessEditor’s ChoiceArticle

Pollen Vertical Transportation Above Paris, France, up to 150 m Using the Beenose Instrument on the Tourist Attraction “Ballon de Paris” in 2024

by Jean-Baptiste Renard, Johann Lauthier and Jérôme Giacomoni

Atmosphere 2025, 16(7), 795; https://doi.org/10.3390/atmos16070795 - 30 Jun 2025

Viewed by 522

Abstract

Pollen allergies represent a growing public health concern that necessitates enhancements to the network of instruments and modeling calculations in order to facilitate a more profound comprehension of pollen transportation. The Beenose instrument quantifies the light scattered by particles that traverse a laser [...] Read more.

Pollen allergies represent a growing public health concern that necessitates enhancements to the network of instruments and modeling calculations in order to facilitate a more profound comprehension of pollen transportation. The Beenose instrument quantifies the light scattered by particles that traverse a laser beam at four angles. This methodology enables the differentiation of pollen particles from other particulate matter, predominantly mineral and carbonaceous in nature, thereby facilitating the retrieval of pollen concentrations. The Beenose instrument has been installed on the tourist balloon known as “Ballon de Paris” in a large park situated in the southwest of Paris, France. The measurement period is from April to November 2024, coinciding with the pollen seasons of trees and grasses. The balloon conducts numerous flights per day, reaching an altitude of 150 m when weather conditions are conducive, which occurs approximately 58% of the time during this period. The data are averaged to produce vertical profiles with a resolution of 30 m. Concentrations of the substance decrease with altitude, although a secondary layer is observed in spring. This phenomenon may be attributed to the presence of emissions from a proximate forest situated at a higher altitude. The average decrease in concentration of 11 ± 8% per 10 m is consistent with the findings of previous studies. The long-term implementation of Beenose measurements on this tourist balloon is intended to enhance the precision of the results and facilitate the differentiation of the various parameters that can influence the vertical transportation of pollen. Full article

(This article belongs to the Section Air Quality)

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55 pages, 3334 KB

Open AccessEditor’s ChoiceReview

Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions

by Lili Zhao, Xuncheng Fan and Tao Hong

Atmosphere 2025, 16(7), 791; https://doi.org/10.3390/atmos16070791 - 28 Jun 2025

Cited by 2 | Viewed by 4293

Abstract

This study systematically reviews the development and application of remote sensing technology in monitoring and evaluating urban heat island (UHI) effects. The urban heat island effect, characterized by significantly higher temperatures in urban areas compared to surrounding rural regions, has become a widespread [...] Read more.

This study systematically reviews the development and application of remote sensing technology in monitoring and evaluating urban heat island (UHI) effects. The urban heat island effect, characterized by significantly higher temperatures in urban areas compared to surrounding rural regions, has become a widespread environmental issue globally, with impacts spanning public health, energy consumption, ecosystems, and social equity. The paper first analyzes the formation mechanisms and impacts of urban heat islands, then traces the evolution of remote sensing technology from early traditional platforms such as Landsat and NOAA-AVHRR to modern next-generation systems, including the Sentinel series and ECOSTRESS, emphasizing improvements in spatial and temporal resolution and their application value. At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. Through analyzing the heat island differences between metropolitan areas and small–medium cities, the relationship between urban morphology and thermal environment, and regional specificity and global universal patterns, this study revealed that the proportion of impervious surfaces is the primary driving factor of heat island intensity while simultaneously finding that vegetation cover exhibits significant cooling effects under suitable conditions, with the intensity varying significantly depending on vegetation types, management levels, and climatic conditions. In terms of applications, the paper elaborates on the practical value of remote sensing technology in identifying thermally vulnerable areas, green space planning, urban material optimization, and decision support for UHI mitigation. Finally, in light of current technological limitations, the study anticipates the application prospects of artificial intelligence and emerging analytical methods, as well as trends in urban heat island monitoring against the backdrop of climate change. The research findings not only enrich the theoretical framework of urban climatology but also provide a scientific basis for urban planners, contributing to the development of more effective UHI mitigation strategies and enhanced urban climate resilience. Full article

(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data (2nd Edition))

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24 pages, 15859 KB

Open AccessEditor’s ChoiceArticle

The Analysis of the Extreme Cold in North America Linked to the Western Hemisphere Circulation Pattern

by Mohan Shen and Xin Tan

Atmosphere 2025, 16(7), 781; https://doi.org/10.3390/atmos16070781 - 26 Jun 2025

Viewed by 455

Abstract

The Western Hemisphere (WH) circulation pattern was discovered in recent years through Self-Organizing Maps (SOMs) clustering of the Northern Hemisphere 500 hPa geopotential height during winter. For example, the extremely cold wave that occurred in North America during 2013–14 is associated with WH [...] Read more.

The Western Hemisphere (WH) circulation pattern was discovered in recent years through Self-Organizing Maps (SOMs) clustering of the Northern Hemisphere 500 hPa geopotential height during winter. For example, the extremely cold wave that occurred in North America during 2013–14 is associated with WH circulation anomalies. We discussed the extremely cold weather conditions within the WH pattern during the winter season from 1979 to 2023. The variations of cold air in North America during the WH pattern have been demonstrated using the NCEP/NCAR reanalysis datasets. By defining WH events and North American extremely cold events, we have identified a connection between the two. In extremely cold events, linear winds are the key factor driving the temperature drop, as determined by calculating temperature advection. The ridge in the Gulf of Alaska serves as an early signal for this cold weather. The WH circulation anomaly triggers an anomalous ridge in the Gulf of Alaska region, leading to trough anomalies downstream over North America. This results in the southward movement of cold air from the polar regions, causing cooling in the mid-to-northern parts of North America. With the maintenance of the stationary wave in the North Pacific (NP), the anomalous trough over North America can be deepened, driving cold air into the continent. Influenced by the low pressure over Greenland and the storm track, the cold anomalies are concentrated in the central and northern parts of North America. This cold air situation persists for approximately two weeks. The high-level patterns of the WH pattern in both the 500 hPa height and the troposphere level have been identified using SOM. This cold weather is primarily a tropospheric phenomenon with limited correlation to stratospheric activities. Full article

(This article belongs to the Section Climatology)

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16 pages, 3613 KB

Open AccessEditor’s ChoiceArticle

Temporal and Spatial Dynamics of Dust Storms in Uzbekistan from Meteorological Station Records (2010–2023)

by Natella Rakhmatova, Bakhriddin E. Nishonov, Lyudmila Shardakova, Albina Akhmedova, Alisher Khudoyberdiev, Valeriya Rakhmatova and Dmitry A. Belikov

Atmosphere 2025, 16(7), 782; https://doi.org/10.3390/atmos16070782 - 26 Jun 2025

Viewed by 1700

Abstract

This study provides a comprehensive spatiotemporal analysis of sand and dust storms (SDSs) in Uzbekistan using ground-based meteorological data from 2010 to 2023. The results reveal significant spatial heterogeneity in the SDS activity, with the highest frequency of SDS days observed in the [...] Read more.

This study provides a comprehensive spatiotemporal analysis of sand and dust storms (SDSs) in Uzbekistan using ground-based meteorological data from 2010 to 2023. The results reveal significant spatial heterogeneity in the SDS activity, with the highest frequency of SDS days observed in the southern and western regions, including Surkhandarya, Kashkadarya, Bukhara, Khorezm, and Republic of Karakalpakstan. In the most vulnerable areas, such as Karakalpakstan, Surkhandarya, and Kashkadarya, the annual number of SDS days can exceed 80 in certain years, reflecting a high recurrence of extreme dust events in certain climatic zones. About 53% of the SDS events were regional, affecting several stations, while 47% were localized, indicating a combination of large-scale dust transport and localized emissions. Seasonal patterns showed a peak SDS activity between March and August, coinciding with the dry season characterized by elevated temperatures, reduced soil moisture, and intense agricultural activity, all of which contribute to the surface exposure and increased vulnerability. This study found a significant variation in the event duration across regions, with Karakalpakstan and Surkhandarya experiencing the highest proportion of prolonged events due to its orography and persistent southerly wind patterns. Using ERA5 data and a decision tree regressor, the analysis identified the wind direction and mean wind speed as the most influential meteorological factors, followed by the maximum wind speed and soil temperature, with other variables such as solar radiation and soil moisture playing moderate roles. This study highlights the importance of regional wind patterns and geomorphology in SDS formation, with prevailing wind directions from the northwest, west, and south. The integration of the ERA5 reanalysis and machine learning techniques offers significant potential for improving SDS monitoring and studies. Full article

(This article belongs to the Section Meteorology)

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19 pages, 15701 KB

Open AccessEditor’s ChoiceArticle

The Response of NDVI to Climate Change in the Lowest and Hottest Basin in China

by Chunlan Li, Yang Yu, Lingxiao Sun, Jing He, Haiyan Zhang, Yuanbo Lu, Zengkun Guo, Lingyun Zhang, Ireneusz Malik, Malgorzata Wistuba and Ruide Yu

Atmosphere 2025, 16(7), 778; https://doi.org/10.3390/atmos16070778 - 25 Jun 2025

Viewed by 496

Abstract

The response mechanisms of vegetation dynamics to climate change in arid regions, particularly under extreme low-altitude and high-temperature environments, remain unclear. Focusing on China’s lowest and hottest Turpan-Hami Basin, this study investigates the spatiotemporal evolution of vegetation cover (using MODIS NDVI) and its [...] Read more.

The response mechanisms of vegetation dynamics to climate change in arid regions, particularly under extreme low-altitude and high-temperature environments, remain unclear. Focusing on China’s lowest and hottest Turpan-Hami Basin, this study investigates the spatiotemporal evolution of vegetation cover (using MODIS NDVI) and its response to temperature, precipitation, and potential evapotranspiration (PET) based on data from 2001 to 2020. Theil–Sen trend analysis, the Mann–Kendall test, and Pearson correlation were employed. Key findings include the following: (1) NDVI exhibited a significant increasing trend, with the largest rise in winter and peak values in summer. Spatially, high NDVI was concentrated in oasis and mountainous forest-grassland zones, while low values prevailed in desert Gobi regions; 34.2% of the area showed significant improvement, though localized degradation occurred. (2) Temperature showed no significant overall correlation with NDVI, except for strong positive correlations in limited high-altitude cold zones (2.9%). Precipitation had minimal influence (no correlation in 75.4% of the area), with localized positive responses in northwestern foothills linked to runoff. PET exhibited positive correlations (weak or strong) with NDVI across nearly half of the region (46.8%), predominantly in oasis-desert and piedmont transition zones. (3) Human activities, notably irrigation and shelterbelt projects, are key drivers of oasis vegetation restoration. Critically, the positive PET-NDVI correlation challenges the conventional paradigm viewing evapotranspiration solely as water stress. This study elucidates the compound responses of vegetation dynamics to climatic and anthropogenic factors in a low-altitude arid region, providing a scientific basis for ecological restoration and water resource management optimization. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands (2nd Edition))

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4 pages, 149 KB

Open AccessEditor’s ChoiceEditorial

Editorial for the Special Issue “Transport Emissions and Their Environmental Impact”

by Jana Moldanová, Yan Zhang and Volker Matthias

Atmosphere 2025, 16(7), 775; https://doi.org/10.3390/atmos16070775 - 24 Jun 2025

Viewed by 353

Abstract

The transport of passengers and freight around the world has increased dramatically in recent decades [...] Full article

(This article belongs to the Special Issue Transport Emissions and Their Environmental Impacts)

12 pages, 1459 KB

Open AccessEditor’s ChoiceEssay

Research on Ship Carbon-Emission Monitoring Technology and Suggestions on Low-Carbon Shipping Supervision System

by Mingjun Li, Mengchun Qiu, Yue Li, Huaiwu Tang, Rui Wu, Zhiwei Yu, Yonglin Zhang, Shanshan Ye, Chaohui Zheng, Ying Qu, Liguo Zhang, Tao Xu, Runhe Cheng, Cheng Zhou, Jinxiang Cheng and Darong Liang

Atmosphere 2025, 16(7), 773; https://doi.org/10.3390/atmos16070773 - 24 Jun 2025

Viewed by 589

Abstract

Ship carbon-emission monitoring is critical for implementing the IMO’s GHG reduction strategy. This study comprehensively introduces four methods for ship carbon monitoring and carbon calculation and systematically compares four vessel CO₂-monitoring methodologies, assessing their accuracy, influencing factors, real-time performance, and regulatory [...] Read more.

Ship carbon-emission monitoring is critical for implementing the IMO’s GHG reduction strategy. This study comprehensively introduces four methods for ship carbon monitoring and carbon calculation and systematically compares four vessel CO₂-monitoring methodologies, assessing their accuracy, influencing factors, real-time performance, and regulatory applicability. The analysis of China’s current carbon supervision framework informs proposed enhancements for low-carbon shipping governance. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions (2nd Edition))

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20 pages, 6074 KB

Open AccessEditor’s ChoiceArticle

Characterization of Hybrid Lightning Flashes Observed by Fast Antenna Lightning Mapping Array in Summer Thunderstorms

by Dongdong Shi, Jie Shao, Rubin Jiang, Daohong Wang, Ting Wu and Li Wang

Atmosphere 2025, 16(7), 765; https://doi.org/10.3390/atmos16070765 - 22 Jun 2025

Viewed by 374

Abstract

Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with [...] Read more.

Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with negative leaders originating from the upper parts of bi-level structures of IC flashes. Hereinafter, we refer to these hybrid flashes as hybrid A, B, and C, respectively. The statistical comparisons indicate that characteristics from preliminary breakdown (PB) to return stroke (RS) are significantly different. On average, hybrid A and C flashes have higher initiation altitudes, larger PB–RS intervals, and longer propagation lengths than hybrid B flashes (7.9, 7.8 vs. 5.7 km; 430.3, 239.3 vs. 54.4 ms; 6.4, 7.8 vs. 2.3 km). Compared to 1562 IC and 844 CG flashes, hybrid flashes unsurprisingly have much larger horizontal flash sizes (189, 210, and 126.9 km² vs. 86.1 and 80.2 km²). In addition, hybrid B flashes tend to produce more RSs and larger RS1st peak currents. The striking points of hybrid C flashes appear to be close to or out of the cloud edge. Based on these statistical results, we discuss the formation mechanisms of three types of hybrid flashes. Full article

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

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23 pages, 847 KB

Open AccessEditor’s ChoiceReview

Carbon Flux Estimation for Potato Production: A Literature-Based Study

by Shu Zhang, Xiuquan Wang and Muhammad Awais

Atmosphere 2025, 16(7), 764; https://doi.org/10.3390/atmos16070764 - 21 Jun 2025

Viewed by 512

Abstract

This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were [...] Read more.

This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were compiled from field-scale studies (primarily using eddy covariance) and life cycle assessment studies. The results indicate that potato production can act as a carbon sink or a carbon source, depending on the production scenario. In Scenario 1, which represents the worst-case scenario, potato production acts as a carbon source, with a carbon flux of 13,874.816 kg CO₂ eq ha⁻¹ season⁻¹. In contrast, in Scenario 2, the best-case scenario, potato production acts a carbon sink with a carbon flux of −12,830.567 kg CO₂ eq ha⁻¹ season⁻¹. Similarly, in Scenario 3, which is the average scenario, potato production acts as a carbon sink, though a minor one, with a carbon flux of −90.703 kg CO₂ eq ha⁻¹ season⁻¹. Notably, the growing phase has the most significant impact on potato production’s overall carbon flux, as it is the period in which the highest levels of carbon sequestration and emissions occur. Fertilization is the primary carbon source among all potato production operations, averaging 1219.225 kg CO₂ eq ha⁻¹ season⁻¹. Optimizing farming practices, including fertilization, irrigation, tillage methods, and cultivar selection, are essential to enhance carbon sequestration and reduce greenhouse gas emissions. Additionally, further research through controlled experiments is recommended to deepen the understanding of the relationships between various farming factors and carbon flux, ultimately supporting more sustainable potato production practices. Full article

(This article belongs to the Section Air Pollution Control)

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12 pages, 6138 KB

Open AccessEditor’s ChoiceArticle

Machine Learning Model Optimization for Antarctic Blowing Snow Height and Optical Depth Diagnosis

by Surendra Bhatta and Yuekui Yang

Atmosphere 2025, 16(7), 760; https://doi.org/10.3390/atmos16070760 - 21 Jun 2025

Viewed by 451

Abstract

Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the [...] Read more.

Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). This paper extends that work by optimizing an ML model to estimate blowing snow height and optical depth for operational data production. Observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) serve as ground truth for training. The optimization process involves selecting relevant input features and identifying the most effective ML regressor. As a result, 21 MERRA-2 fields were identified as key input features, and Extreme Gradient Boosting emerged as the most effective regressor. Feature importance analysis highlights wind components and surface pressure as the most significant predictors for blowing snow height and optical depth. Individual models were developed for each month. Using 10 years of CALIPSO data (2007–2016) for training, these optimized models can be applied across the full MERRA-2 dataset, spanning from 1980 to the present. This enables the generation of hourly blowing snow height and optical depth data on the MERRA-2 grid for the entire MERRA-2 time span. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence in Atmospheric Sciences)

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29 pages, 7501 KB

Open AccessEditor’s ChoiceArticle

Theoretical Analysis of Suspended Road Dust in Relation to Concrete Pavement Texture Characteristics

by Hojun Yoo, Gyumin Yeon and Intai Kim

Atmosphere 2025, 16(7), 761; https://doi.org/10.3390/atmos16070761 - 21 Jun 2025

Viewed by 509

Abstract

Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse [...] Read more.

Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse spatial and traffic conditions. This study investigates the influence of concrete pavement macrotexture—specifically the Mean Texture Depth (MTD) and surface wavelength—on PM₁₀ resuspension. Field data were collected using a vehicle-mounted DustTrak 8530 sensor following the TRAKER protocol, enabling real-time monitoring near the tire–pavement interface. A multivariable linear regression model was used to evaluate the effects of MTD, wavelength, and the interaction between silt loading (sL) and PM₁₀ content, achieving a high adjusted R² of 0.765. The surface wavelength and sL–PM₁₀ interaction were statistically significant (p < 0.01). The PM₁₀ concentrations increased with the MTD up to a threshold of approximately 1.4 mm, after which the trend plateaued. A short wavelength (<4 mm) resulted in 30–50% higher PM₁₀ emissions compared to a longer wavelength (>30 mm), likely due to enhanced air-pumping effects caused by more frequent aggregate contact. Among pavement types, Transverse Tining (T.Tining) exhibited the highest emissions due to its high MTD and short wavelength, whereas Exposed Aggregate Concrete Pavement (EACP) and the Next-Generation Concrete Surface (NGCS) showed lower emissions with a moderate MTD (1.0–1.4 mm) and longer wavelength. Mechanistically, a low MTD means there is a lack of sufficient voids for dust retention but generates less turbulence, producing moderate emissions. In contrast, a high MTD combined with a very short wavelength intensifies tire contact and localized air pumping, increasing emissions. Therefore, an intermediate MTD and moderate wavelength configuration appears optimal, balancing dust retention with minimized turbulence. These findings offer a texture-informed framework for integrating pavement surface characteristics into PM emission models, supporting sustainable and emission-conscious pavement design. Full article

(This article belongs to the Special Issue Traffic Related Emission (3rd Edition))

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13 pages, 4411 KB

Open AccessEditor’s ChoiceArticle

Construction of a High-Resolution Temperature Dataset at 40–110 KM over China Utilizing TIMED/SABER and FY-4A Satellite Data

by Qian Ye, Mohan Liu, Dan Du and Xiaoxin Zhang

Atmosphere 2025, 16(7), 758; https://doi.org/10.3390/atmos16070758 - 20 Jun 2025

Viewed by 423

Abstract

This study aims to develop a high-resolution temperature dataset from 40 km to 110 km over China by machine learning techniques, with a horizontal resolution of 0.5° × 0.5° and vertical resolution of 1 km, utilizing measurements from SABER onboard the Thermosphere, Ionosphere, [...] Read more.

This study aims to develop a high-resolution temperature dataset from 40 km to 110 km over China by machine learning techniques, with a horizontal resolution of 0.5° × 0.5° and vertical resolution of 1 km, utilizing measurements from SABER onboard the Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics (TIMED) and Fengyun 4A (FY-4A) satellites. Accurate temperature profiles play a critical role in understanding the atmospheric dynamics and climate change. However, because of the limitation of traditional detecting methods, the measurements of the upper stratosphere and mesosphere are rare. In this study, a new method is developed to construct a high-resolution temperature dataset over China in the middle atmosphere based on the XGBoost technique. The model’s performance is also validated based on rocket observations and ERA5 reanalysis data. The results indicate that the model effectively captures the characteristics of the vertical and seasonal variations in temperature, which provide a valuable opportunity for further research and improvement of climate models. The model demonstrates the highest accuracy below 80 km with RMSE < 12 K, while its performance decreases above 100 km, where RMSE can exceed 20 K, indicating optimal performance in the upper stratosphere and lower mesosphere regions. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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22 pages, 4168 KB

Open AccessEditor’s ChoiceArticle

Assessment of CH₄ and CO₂ Emissions from a Municipal Waste Landfill: Trends, Dispersion, and Environmental Implications

by Georgeta Olguta Gavrila, Gabriela Geanina Vasile, Simona Mariana Calinescu, Cristian Constantin, Gheorghita Tanase, Alexandru Cirstea, Valentin Stancu, Valeriu Danciulescu and Cristina Orbeci

Atmosphere 2025, 16(7), 752; https://doi.org/10.3390/atmos16070752 - 20 Jun 2025

Cited by 1 | Viewed by 759

Abstract

The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH₄) and carbon dioxide (CO₂), produced through the anaerobic digestion of various residual materials. This [...] Read more.

The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH₄) and carbon dioxide (CO₂), produced through the anaerobic digestion of various residual materials. This study aimed to investigate CH₄ and CO₂ concentrations from municipal solid waste in biogas capture wells in a landfill in Romania between 2023 and 2024. A peak in CH₄ concentrations occurred in the fall of 2024 (P4 well), while the highest CO₂ content was recorded in the summer of 2023 (P3 well). The Aermod View software platform (version 11.2.0) was employed to model the dispersion of pollutants in the surrounding air. A worst-case scenario was applied to estimate the highest ground-level pollutant concentrations. The highest recorded CH₄ concentration was 90.1 mg/m³, while CO₂ reached 249 mg/m³ within the landfill. The highest CH₄ concentrations were found in the southern part of the site, less than 1 km from the landfill, while CO₂ was highest in the northern area. In conclusion, municipal solid waste landfills behave like unpredictable bioreactors, and without proper management and oversight, they can pose significant risks. An integrated system that combines prevention, reuse, and correct disposal is critical to minimizing these negative effects. Full article

(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry (2nd Edition))

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29 pages, 4175 KB

Open AccessEditor’s ChoiceArticle

Assessing Long-Term Post-Conflict Air Pollution: Trends and Implications for Air Quality in Mosul, Iraq

by Zena Altahaan and Daniel Dobslaw

Atmosphere 2025, 16(7), 756; https://doi.org/10.3390/atmos16070756 - 20 Jun 2025

Viewed by 955

Abstract

Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality [...] Read more.

Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality in conflict-affected regions, comprehensive assessments integrating long-term data and localized measurements remain scarce. This study addresses this gap by analyzing the environmental consequences of sustained instability in Mosul, focusing on air pollution trends using both remote sensing data (1983–2023) and in situ monitoring of key pollutants—including PM_2.5, PM₁₀, TVOCs, NO₂, SO₂, and formaldehyde—at six urban sites during 2022–2023. The results indicate marked seasonal variations, with winter peaks in combustion-related pollutants (NO₂, SO₂) and elevated particulate concentrations in summer driven by sandstorm activity. Annual average concentrations of all six pollutants increased by 14–51%, frequently exceeding WHO air quality guidelines. These patterns coincide with worsening meteorological conditions, including higher temperatures, reduced rainfall, and more frequent storms, suggesting synergistic effects between climate stress and pollution. The findings highlight severe public health risks and emphasize the urgent need for integrated urban recovery strategies that promote sustainable infrastructure, environmental restoration, and resilience to climate change. Full article

(This article belongs to the Special Issue Emissions of Volatile Organic Compounds (VOCs): Characterization, Environmental Impacts and Control)

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16 pages, 1812 KB

Open AccessEditor’s ChoiceArticle

The Cost of Heat: Health and Economic Burdens in Three Brazilian Cities

by Daniela Debone, Nilton Manuel Évora do Rosário and Simone Georges El Khouri Miraglia

Atmosphere 2025, 16(7), 755; https://doi.org/10.3390/atmos16070755 - 20 Jun 2025

Viewed by 782

Abstract

Excess mortality due to heat is a major public health concern globally. In this study, we investigated the association between extreme heat and mortality in three distinct locations in São Paulo state, Brazil—São Paulo city (the capital), Campinas (a large countryside city), and [...] Read more.

Excess mortality due to heat is a major public health concern globally. In this study, we investigated the association between extreme heat and mortality in three distinct locations in São Paulo state, Brazil—São Paulo city (the capital), Campinas (a large countryside city), and Marília (a typical medium-sized rural city)—from 2004 to 2018. We applied a generalized linear model (GLM) with a Poisson distribution and a logarithmic link function for each city, using the excess heat factor (EHF) as the exposure metric. The results showed that increases in the EHF were associated with relative risks of 1.0018 (95% CI: 1.0015–1.0022) in São Paulo, 1.0029 (95% CI: 1.0023–1.0036) in Campinas, and 1.0033 (95% CI: 1.0025–1.0041) in Marília. Altogether, 2319 heat-attributable deaths were estimated, representing an economic burden of USD 6.03 billion based on the value of a statistical life. By integrating economic valuation with mortality risk estimates, our study offers a broader perspective on the consequences of extreme heat, reinforcing the need for public health and policy interventions. Full article

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

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16 pages, 10425 KB

Open AccessEditor’s ChoiceArticle

Pressure and Temperature Observations in Venice by Bernardino Zendrini from 1738 to 1743

by Dario Camuffo, Antonio della Valle and Francesca Becherini

Atmosphere 2025, 16(7), 759; https://doi.org/10.3390/atmos16070759 - 20 Jun 2025

Viewed by 403

Abstract

This study aims to recover, interpret and analyse the early meteorological observations made in Venice by Bernardino Zendrini from 1738 to 1743. Zendrini used a cistern barometer, an Amontons-type air thermometer and an additional mercury thermometer, i.e., a de l’Isle one. By comparing [...] Read more.

This study aims to recover, interpret and analyse the early meteorological observations made in Venice by Bernardino Zendrini from 1738 to 1743. Zendrini used a cistern barometer, an Amontons-type air thermometer and an additional mercury thermometer, i.e., a de l’Isle one. By comparing and interpreting the existing details, the instruments have been re-imagined, interpreted and discussed; finally their unknown scale and calibration points have been calculated. The barometer readings needed standard corrections, which were not known at that time. The scale of the air thermometers was in inches of mercury. Zendrini used a reversed scale, with boiling water set to 0, but neglected the second calibration point and the length of the tube. In addition, he gave the thermoscopic readings without the corresponding pressures. The methodology for the calibration, validation and transformation of the readings into modern units, i.e., hPa and °C, is carefully discussed. This paper provides and analyses new data, and improves our knowledge about the history of science, meteorological measurements, instruments and observations in the first half of the 18th century. Full article

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

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12 pages, 2395 KB

Open AccessEditor’s ChoiceArticle

Comparative Analysis of Air Pollution in Beijing and Seoul: Long-Term Trends and Seasonal Variations

by Hana Na and Woo-Sik Jung

Atmosphere 2025, 16(7), 753; https://doi.org/10.3390/atmos16070753 - 20 Jun 2025

Viewed by 663

Abstract

This study compares long-term air pollution trends and seasonal patterns in Beijing and Seoul from 2014 to 2024, focusing on PM2.5, PM10, CO, NO₂, SO₂, and O₃. Using statistical analyses including Mann–Kendall tests and generalized additive models, [...] Read more.

This study compares long-term air pollution trends and seasonal patterns in Beijing and Seoul from 2014 to 2024, focusing on PM2.5, PM10, CO, NO₂, SO₂, and O₃. Using statistical analyses including Mann–Kendall tests and generalized additive models, we found that Beijing achieved notable reductions in particulate matter, largely due to stricter industrial controls and reduced coal use, though winter pollution peaks remain. In contrast, Seoul’s improvements were slower, mainly due to persistent vehicular emissions and recurring spring dust storms from northern China. Seasonal analysis showed winter peaks in Beijing linked to coal heating, and spring peaks in Seoul driven by transboundary dust, with higher summer ozone in Seoul reflecting photochemical activity. These findings highlight the need for city-specific air quality management and regional cooperation, recommending further reductions in vehicular emissions for Seoul and continued transition from coal in Beijing to mitigate health impacts. This study identifies specific seasonal trends and pollution sources that require targeted policy interventions to improve air quality. Full article

(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry (2nd Edition))

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24 pages, 5147 KB

Open AccessEditor’s ChoiceArticle

Research on Air Temperature Inversion Method Based on Land Surface Temperature of Different Land Surface Cover

by Rui Fang, Xiaofang Shan and Qinli Deng

Atmosphere 2025, 16(7), 754; https://doi.org/10.3390/atmos16070754 - 20 Jun 2025

Viewed by 557

Abstract

This study explores a method for deriving air temperature (AT) from land surface temperature (LST) based on different urban land-use types, aiming to address the accuracy of urban heat island (UHI) effect measurements. Using Wuhan as a case study, the research integrates remote [...] Read more.

This study explores a method for deriving air temperature (AT) from land surface temperature (LST) based on different urban land-use types, aiming to address the accuracy of urban heat island (UHI) effect measurements. Using Wuhan as a case study, the research integrates remote sensing data with ground meteorological observations to develop various models, analyze their accuracy and applicability, and generate LST and AT maps to validate model reliability. The results indicate that when establishing the LST–AT relationship, polynomial regression performs best for water bodies (R² = 0.905), while random forest yields the highest R² for built-up areas, cropland, and vegetation at 0.942, 0.953, and 0.924, respectively. Due to the characteristics of the algorithms, it is recommended to prioritize random forest for prediction when the sample range covers the observed data range and to use BP neural networks when it does not. The generated maps reveal that in summer, using LST significantly overestimates UHI intensity in the study area, while differences between UHI intensities in winter are negligible. In resource-constrained scenarios, LST can be directly used to assess the UHI effect. Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

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17 pages, 2555 KB

Open AccessEditor’s ChoiceArticle

A Bibliometric Analysis of the Impact of Extreme Weather on Air Transport Operations

by Kristína Kováčiková, Andrej Novák, Martina Kováčiková and Alena Novak Sedlackova

Atmosphere 2025, 16(6), 740; https://doi.org/10.3390/atmos16060740 - 17 Jun 2025

Viewed by 724

Abstract

Extreme weather events pose increasing risks to air transport operations, affecting flight safety, scheduling, and infrastructure resilience. This paper provides a comprehensive bibliometric analysis of scientific literature addressing the impacts of extreme weather on aviation, based on 1000 documents retrieved from the Web [...] Read more.

Extreme weather events pose increasing risks to air transport operations, affecting flight safety, scheduling, and infrastructure resilience. This paper provides a comprehensive bibliometric analysis of scientific literature addressing the impacts of extreme weather on aviation, based on 1000 documents retrieved from the Web of Science Core Collection (2010–2024). Using VOSviewer software, keyword co-occurrence, overlay visualization, co-authorship networks, and citation analyses were conducted. Results revealed a clear thematic shift from environmental impact assessments toward research emphasizing operational resilience, technological adaptation, and mitigation strategies. Collaboration networks highlighted strong international cooperation, particularly among institutions in the United States, Germany, and the United Kingdom, with growing contributions from emerging research regions. Highly cited studies predominantly focused on emissions modeling and operational mitigation measures. Despite notable advances, the field remains fragmented and geographically uneven, underscoring the need for broader interdisciplinary integration and empirical validation of adaptation strategies. This paper offers a systematic overview of the evolving research landscape and identifies critical directions for future efforts to enhance the resilience and sustainability of global air transport systems under increasing climatic volatility. Full article

(This article belongs to the Section Meteorology)

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16 pages, 1754 KB

Open AccessEditor’s ChoiceArticle

The Impact of Air Pollution on Morbidity in the Industrial Areas of the East Kazakhstan Region

by Gulnaz Sadykanova, Sanat Kumarbekuly and Ayauzhan Yessimbekova

Atmosphere 2025, 16(6), 736; https://doi.org/10.3390/atmos16060736 - 17 Jun 2025

Viewed by 1715

Abstract

Atmospheric air pollution is a major environmental and public health concern, particularly in industrialized regions. The East Kazakhstan Region exhibits high rates of oncological, cardiovascular, and respiratory diseases. However, the specific impact of industrial emissions on morbidity remains insufficiently studied. This study employed [...] Read more.

Atmospheric air pollution is a major environmental and public health concern, particularly in industrialized regions. The East Kazakhstan Region exhibits high rates of oncological, cardiovascular, and respiratory diseases. However, the specific impact of industrial emissions on morbidity remains insufficiently studied. This study employed correlation and regression analyses using data on pollutant emissions and population morbidity indicators from 2014 to 2023. Correlation and regression methods, along with geoinformation technologies, were applied. A moderate positive correlation was found between industrial emission volumes and the incidence of neoplasms (r = 0.59, R² = 0.35), especially in areas with high concentrations of sulfur dioxide, nitrogen oxides, and particulate matter. The findings confirm the significant influence of polluted air—particularly mixed pollutants—on the increase in cancer-related diseases. The conclusions emphasize the urgent need to implement emission reduction measures, enhance environmental monitoring and disease prevention, and carry out further epidemiological research. Full article

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

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27 pages, 2653 KB

Open AccessEditor’s ChoiceArticle

Temporal and Machine Learning-Based Principal Component and Clustering Analysis of VOCs and Their Role in Urban Air Pollution and Ozone Formation

by Balendra V. S. Chauhan, Maureen J. Berg, Ajit Sharma, Kirsty L. Smallbone and Kevin P. Wyche

Atmosphere 2025, 16(6), 724; https://doi.org/10.3390/atmos16060724 - 15 Jun 2025

Viewed by 877

Abstract

This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside [...] Read more.

This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside ozone (O₃) and meteorological data, were analysed using correlation matrices, regression, cross-correlation, diurnal/seasonal analysis, wind-sector analysis, PCA (Principal Component Analysis), and clustering. Strong inter-VOC correlations (e.g., benzene–ethylbenzene: r = 0.86, R² = 0.75; ethene–propene: r = 0.68, R² = 0.53) highlighted dominant vehicular sources. Diurnal peaks of benzene, toluene, and ethylbenzene aligned with rush hours, while O₃ minima occurred in early mornings due to NO titration. VOCs peaked in winter under low mixing heights, whereas O₃ was highest in summer. Wind-sector analysis revealed dominant VOC emissions from SSW (south-southwest)–WSW (west-southwest) directions; ethyne peaked from the E (east)/ENE (east-northeast). O₃ concentrations were highest under SE (southeast)–SSE (south-southeast) flows. PCA showed 39.8% of variance linked to traffic-related VOCs (PC1) and 14.8% to biogenic/temperature-driven sources (PC2). K-means clustering (k = 3) identified three regimes: high VOCs/low O₃ in stagnant, cool air; mixed conditions; and low VOCs/high O₃ in warmer, aged air masses. Findings highlight complex VOC–O₃ interactions and stress the need for source-specific mitigation strategies in urban air quality management. Full article

(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)

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17 pages, 6114 KB

Open AccessEditor’s ChoiceReview

Impact of El Niño–Southern Oscillation on Global Vegetation

by Jie Jin, Dongnan Jian, Xin Zhou, Quanliang Chen and Yang Li

Atmosphere 2025, 16(6), 701; https://doi.org/10.3390/atmos16060701 - 10 Jun 2025

Viewed by 2029

Abstract

El Niño–Southern Oscillation (ENSO), as the strongest source of interannual variability in the tropics, has far-reaching impacts on global climate through teleconnections. As a key factor modulating the vegetation changes, the impact of ENSO has been studied over the past two decades using [...] Read more.

El Niño–Southern Oscillation (ENSO), as the strongest source of interannual variability in the tropics, has far-reaching impacts on global climate through teleconnections. As a key factor modulating the vegetation changes, the impact of ENSO has been studied over the past two decades using satellite observations. The paper aims to review results from the past 10–20 years and put together into a consistent picture of ENSO global impacts on vegetation. While ENSO affects vegetation worldwide, its impact varies regionally. Different ENSO flavors, Central Pacific and Eastern Pacific events, can have distinct impacts in the same regions. The underlying mechanisms involve ENSO-driven changes in precipitation and temperature, modulated by the background climate states, with varying response from vegetations of different types. However, the interactions between vegetation and ENSO remain largely unexplored, highlighting a critical gap for future research. Full article

(This article belongs to the Section Meteorology)

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17 pages, 2703 KB

Open AccessEditor’s ChoiceArticle

Applicability Evaluation of Antarctic Ozone Reanalysis and Merged Satellite Datasets

by Junzhe Chen, Yu Zhang, Houxiang Shi, Hao Hu and Jianjun Xu

Atmosphere 2025, 16(6), 696; https://doi.org/10.3390/atmos16060696 - 10 Jun 2025

Viewed by 1129

Abstract

In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient [...] Read more.

In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient (R), root-mean-square error (RMSE), interannual variability skill score (IVS), and linear trend bias (TrBias). The results show that for interannual variation, C3S-MSR performs well at multiple stations, while JRA-55 performs poorly at most stations, especially Marambio, Rothera, and Faraday/Vernadsky, which are located at lower latitudes on the Antarctic Peninsula. Additionally, all datasets show significantly higher RMSE at Dumont D’Urville and Arrival Heights, which generally are located around the edge of the Antarctic stratospheric vortex where total column ozone values are more variable and on average larger than in the core of the vortex. The comprehensive ranking results show that C3S-MSR performs the best, followed by ERA5 and NIWA-BS, with MERRA-2 and JRA-55 ranking lower. For the long-term trend, each of the datasets has large bias values at Arrival Heights, and the absolute TrBias values of JRA-55 are larger at three stations on the Antarctic Peninsula. The overall averaged results show that C3S-MSR and NIWA-BS have the smallest absolute TrBias, and perform best in reflecting the Antarctic ozone trends, while ERA5 and JRA-55 significantly overestimate the Antarctic ozone recovery trend and perform poorly. Based on our analysis, the C3S-MSR dataset can be recommended to be prioritized when analyzing the interannual variations in Antarctic stratospheric ozone, and both the C3S-MSR reanalysis and NIWA-BS datasets should be prioritized for trend analysis. Full article

(This article belongs to the Section Climatology)

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18 pages, 292 KB

Open AccessEditor’s ChoiceReview

Integrating Traffic Dynamics and Emissions Modeling: From Classical Approaches to Data-Driven Futures

by Xin Wang, Xianfei Yue, Jianchang Huang and Shubin Li

Atmosphere 2025, 16(6), 695; https://doi.org/10.3390/atmos16060695 - 9 Jun 2025

Viewed by 1654

Abstract

A persistent disconnect between traffic modeling and environmental emissions modeling, stemming from their independent disciplinary evolution, continues to impede the accurate integration of traffic dynamics into emissions prediction. This misalignment frequently results in inconsistencies in simulation outputs and limits the reliability of traffic-based [...] Read more.

A persistent disconnect between traffic modeling and environmental emissions modeling, stemming from their independent disciplinary evolution, continues to impede the accurate integration of traffic dynamics into emissions prediction. This misalignment frequently results in inconsistencies in simulation outputs and limits the reliability of traffic-based environmental assessments. From a traffic engineering perspective, it is essential that emissions models more precisely reflect real-world vehicle behavior and the complexities of dynamic traffic conditions. In addressing this gap, the present study offers a comprehensive and critical review of the integration between traffic dynamics and emissions modeling across macro-, meso-, and micro-scales. Emissions models are systematically classified into four categories—driving cycle-based, speed–acceleration matrix-based, engine power-based, and vehicle-specific power-based—and assessed in terms of their responsiveness to dynamic traffic inputs. Furthermore, the review highlights the emerging challenges associated with connected and autonomous vehicles and AI-driven modeling techniques, underscoring the urgent need for modular, real-time adaptable modeling frameworks. Through a detailed examination of parameter requirements, data integration issues, and validation challenges, this study provides structured insights to guide the development of scientifically robust and operationally relevant emissions models tailored to the demands of increasingly complex and intelligent transportation systems. Full article

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

11 pages, 1727 KB

Open AccessEditor’s ChoiceArticle

Filtration of Mineral and Biological Aerosols by Natural Plant Panels

by Nathalie Tomson, Ruby Naomi Michael and Igor E. Agranovski

Atmosphere 2025, 16(6), 694; https://doi.org/10.3390/atmos16060694 - 9 Jun 2025

Viewed by 895

Abstract

This study investigated the potential of Tillandsia plants, which can be arranged as a soil-free living green panel, and Banksia flower spikes, which could be arranged as a non-living natural panel, to filter particulate matter (PM) and airborne microorganisms. The Tillandsia panels demonstrated [...] Read more.

This study investigated the potential of Tillandsia plants, which can be arranged as a soil-free living green panel, and Banksia flower spikes, which could be arranged as a non-living natural panel, to filter particulate matter (PM) and airborne microorganisms. The Tillandsia panels demonstrated superior PM filtration, achieving up to 74% efficiency for large particles (>10 μm) at air velocities of 1.0 and 1.5 m/s without increasing pressure drop substantially. Conversely, Banksia performed better at 0.5 m/s, filtering up to 53% of PM compared to Tillandsia’s 13%. Notably, both panel types demonstrated significant fungal filtration, removing over 50% of airborne spores at 1.5 m/s. These findings suggest that incorporating plant-based panels into urban environments can enhance air quality and public health especially for allergenic particles and microorganisms. Full article

(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)

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17 pages, 3678 KB

Open AccessEditor’s ChoiceArticle

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

Viewed by 445

Abstract

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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17 pages, 7878 KB

Open AccessEditor’s ChoiceArticle

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

Viewed by 767

Abstract

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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16 pages, 4440 KB

Open AccessEditor’s ChoiceArticle

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

Viewed by 527

Abstract

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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