Journal Description
Atmosphere
Atmosphere
is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere, published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Atmosphere.
- Companion journals for Atmosphere include: Meteorology and Aerobiology.
Impact Factor:
2.3 (2024);
5-Year Impact Factor:
2.5 (2024)
Latest Articles
Shadow and Micrometeorological Conditions That Influence the Air Quality in Houses near High Rise Buildings—Field Results
Atmosphere 2026, 17(5), 474; https://doi.org/10.3390/atmos17050474 (registering DOI) - 6 May 2026
Abstract
In urban environments, large buildings influence air quality in their surroundings by altering natural wind patterns, obstructing airflow or creating high-velocity wind tunnels, often resulting in stagnant zones that trap pollutants. Furthermore, the extensive shadows cast by these structures reduce ground-level temperatures. For
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In urban environments, large buildings influence air quality in their surroundings by altering natural wind patterns, obstructing airflow or creating high-velocity wind tunnels, often resulting in stagnant zones that trap pollutants. Furthermore, the extensive shadows cast by these structures reduce ground-level temperatures. For urban planners, accounting for these aerodynamic, thermal and air quality effects is important to fostering healthier, more livable cities. In this work, measurements assessing how shadow and micrometeorological conditions—driven by the proximity of large buildings—influence PM2.5 levels were conducted in an urban commune of Santiago, Chile, during the winter and spring seasons. This commune is characterized by a mixture of one-story houses and high-rise buildings. PM2.5 and meteorological parameters were measured outside three pairs of houses in winter of 2021, one of which received shadow from a nearby building and the other was under the sun. In one pair of houses, PM2.5 concentrations were elevated in the shaded site exclusively during the winter months. This was attributed to shadow-induced temperature reductions, which likely increased local atmospheric stability and inhibited pollutant dispersion. However, this effect was limited to periods of low wind speed; during the spring, the transition to a higher wind speed regime facilitated sufficient mechanical mixing to neutralize the thermal influence of the shadow, resulting in no detectable difference between the sites. In another pair of houses, the result was attributed to the difference in wind speed in one of the houses, because the building acts as a windbreak, no shading effect were observed. Regarding the third pair of houses, no significant impact on PM2.5 concentrations was observed in the whole period. This lack of variation is likely attributable to the absence of substantial micrometeorological differences between the two sites.
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(This article belongs to the Topic Air Quality and the Built Environment, 2nd Edition)
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Open AccessArticle
Summertime Biogenic Volatile Organic Compounds in China: Emissions and Their Modulation on O3 and PM2.5 Pollution
by
Changlei Sun, Tong Zhou, Huijuan Han, Xiangkai Wang, Yan Jiang and Lingyu Li
Atmosphere 2026, 17(5), 473; https://doi.org/10.3390/atmos17050473 - 5 May 2026
Abstract
Coordinated control of fine particulate matter (PM2.5) and ozone (O3) is an urgent national strategic priority for China’s air pollution governance. Biogenic volatile organic compounds (BVOCs) are important precursors of O3 and secondary organic aerosol (SOA). To quantify
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Coordinated control of fine particulate matter (PM2.5) and ozone (O3) is an urgent national strategic priority for China’s air pollution governance. Biogenic volatile organic compounds (BVOCs) are important precursors of O3 and secondary organic aerosol (SOA). To quantify the species-specific impacts of BVOCs, we used the Model of Emissions of Gases and Aerosols from Nature (MEGAN, v3.2) and the Community Multiscale Air Quality (CMAQ, v5.3.2) model to investigate BVOC emission characteristics and their modulating effects on summertime O3 and PM2.5 across China. In July 2020, total BVOC emissions were 6.50 × 106 tons, showing a spatial pattern that decreased from southeast to northwest and a unimodal diurnal variation that peaked at 13:00–14:00. BVOC emissions significantly promoted O3 formation, with a maximum concentration increment of 47.36 μg m−3 in VOC-limited regions such as the Sichuan Basin (SCB) and Yangtze River Delta (YRD). Their impact on PM2.5 was limited, with most regional increments below 3 μg m−3. Isoprene dominated O3 enhancement, while monoterpenes acted as the key BVOC for PM2.5 via SOA formation. Anthropogenic emission reductions elevated the relative contribution of BVOC emissions to air pollution in most regions. These findings highlighted the importance of considering BVOC emissions and their species-specific effects in China’s coordinated PM2.5-O3 control strategies for more precise air quality management.
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(This article belongs to the Special Issue Solar Radiation, Aerosol, and Multiple Interactions Between Solar Radiation and Atmospheric Substances)
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Open AccessArticle
Multi-Source Vertical Sensing of a Winter Dust Event: Quantifying Transport, Microphysics, and Environmental Impacts in Coastal Eastern China
by
Minjuan Mao, Fangping Deng, Houtong Liu, Zhicheng Wang and Qiong Li
Atmosphere 2026, 17(5), 472; https://doi.org/10.3390/atmos17050472 - 4 May 2026
Abstract
Based on a bimodal normal distribution for dust size distribution, a quantitative method for estimating dust input was established in this study, and then the transport, microphysics, and environmental effects of a dust event from 26 to 28 November 2025 were investigated based
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Based on a bimodal normal distribution for dust size distribution, a quantitative method for estimating dust input was established in this study, and then the transport, microphysics, and environmental effects of a dust event from 26 to 28 November 2025 were investigated based on a multi-source vertical remote sensing system in Zhejiang. The results indicate that the net PM10 input was approximately 7760 tons, exhibiting a spatial distribution that decreased from northeast to southwest. The net input per unit area ranged from 0.001 to 0.293 t/km2. The dust was coarse-dominated, initially lowering the PM2.5/PM10 ratio, which later recovered due to gravitational settling and aging. A distinct “upper-small, lower-large” depolarization ratio profile, caused by gravitational settling and hygroscopic absorption, signaled dust intrusion into the breathing zone and an imminent rise in surface PM10, thereby providing a potential early-warning indicator. Dust influx first elevated the relative humidity below the dust layer via radiative cooling but later reduced the near-surface humidity through hygroscopic absorption after settlement. Additionally, decreases in SO2 and NO2 suggested a potential mitigation of atmospheric acidity by the dust. The O3 response showed spatial heterogeneity: in most areas, it was negatively correlated with NO2, reflecting NO2 titration effects under a VOC-controlled regime, while, in a few areas, both decreased synchronously. These findings underscore the dual physical–chemical impacts of dust on regional air quality and support the development of dust-related pollution early-warning systems.
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(This article belongs to the Special Issue Particulate Matter: Source and Concentrations)
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Open AccessArticle
Responses of Vegetation Coverage to Temperature and Precipitation in the Yellow River Basin in Inner Mongolia, China
by
Xueyi Xun, Min Zhang, Ziqi Qian, Fei Zhao, Qingxiao Chang and Guowei Deng
Atmosphere 2026, 17(5), 471; https://doi.org/10.3390/atmos17050471 - 2 May 2026
Abstract
The Yellow River Basin in Inner Mongolia (YRBIM) is a typical arid—semiarid ecological transition zone highly sensitive to climate change. Using long-term Normalized Difference Vegetation Index (NDVI) data together with meteorological and land cover data, this study applied the Sen+Mann–Kendall method and path
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The Yellow River Basin in Inner Mongolia (YRBIM) is a typical arid—semiarid ecological transition zone highly sensitive to climate change. Using long-term Normalized Difference Vegetation Index (NDVI) data together with meteorological and land cover data, this study applied the Sen+Mann–Kendall method and path coefficient analysis to quantify the direct and indirect effects of climatic factors on vegetation coverage. The YRBIM experienced a non-significant warm–wet trend from 1998 to 2019, characterized by slight increases in precipitation and temperature with asynchronous spatial patterns. Vegetation coverage generally improved, with high coverage areas expanding by 12.66% and low coverage areas decreasing by 10.04%. Improvement occurred mainly in eastern croplands and grasslands, while degradation in the northwest coincided with urban expansion and mining. Precipitation showed a highly significant positive correlation with the NDVI at 0.7510. The direct effect of precipitation was dominant at 0.7515, while the indirect effect was negligible at 0.0005. Temperature showed a weak inhibitory effect with a comprehensive effect of 0.0302, where the indirect inhibitory effect at 0.0400 slightly exceeded the direct promotional effect at 0.0098. These response patterns were consistent across most land cover types, except in rural settlements and unused land where temperature showed a weak positive influence. This study provides a scientific basis for ecological conservation and sustainable management in arid—semiarid transition zones.
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(This article belongs to the Special Issue Vegetation and Climate Relationships (3rd Edition))
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Urban Renewal as a Passive Heat Adaptation Strategy: Distance–Decay and Spatial Extent of Microclimate Effects in High-Density Subtropical Cities
by
Wen-Yung Chiang, Yen-An Chen, Vincent Y. Chen, Wei-Ling Tsou, Chien-Hung Chen, Hsi-Chuan Tsai and Chen-Yi Sun
Atmosphere 2026, 17(5), 470; https://doi.org/10.3390/atmos17050470 - 2 May 2026
Abstract
Urban areas in subtropical regions are increasingly exposed to heat stress as climate change intensifies extreme heat events. In high-density cities, urban renewal is widely implemented to upgrade aging building stock, yet its potential role as a passive heat adaptation strategy remains insufficiently
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Urban areas in subtropical regions are increasingly exposed to heat stress as climate change intensifies extreme heat events. In high-density cities, urban renewal is widely implemented to upgrade aging building stock, yet its potential role as a passive heat adaptation strategy remains insufficiently understood, particularly for projects below environmental impact assessment thresholds. This study examines how urban renewal influences neighborhood-scale microclimates through a comparative analysis of six residential renewal cases using computational fluid dynamics (CFD) simulations. Pre- and post-renewal scenarios are evaluated to assess changes in wind environment and thermal conditions, with a particular focus on the spatial extent and distance–decay characteristics of renewal-induced effects. The results reveal a consistent distance–decay pattern of microclimate responses across all cases. The influence of urban renewal is strongest within 0–50 m, remains detectable up to approximately 100 m, and diminishes substantially beyond 100–150 m, indicating a clear neighborhood-scale impact radius. Ventilation performance improves systematically following renewal, while thermal responses are more heterogeneous. Localized cooling of up to 1.5 °C is observed in selected cases, whereas others exhibit negligible temperature change despite enhanced airflow. These findings demonstrate that improved ventilation alone does not guarantee thermal mitigation. Instead, thermal outcomes depend on the interaction between airflow, solar exposure, and surface thermal properties. Urban renewal can therefore function as a form of passive heat adaptation when morphological changes are coordinated with shading and surface design strategies. By quantifying the spatial limits of renewal-induced microclimate effects, this study provides empirical evidence for integrating microclimate considerations into neighborhood-scale planning. The identified influence radius offers a practical reference for climate-responsive urban renewal, particularly in high-density subtropical cities where incremental redevelopment plays a dominant role.
Full article
(This article belongs to the Special Issue Urban Adaptation to Heat and Climate Change)
Open AccessArticle
The Differential Impact of PM2.5 on the Health of Vulnerable Groups in the Context of Rapid Urbanization: An Empirical Analysis Based on Jiangsu Province (2010–2020)
by
Hui Wang, Ziyu Zhang, Zhouzhou Qiu, Shuyuan Ma, Wei Zhou, Zhitao Tong, Chun Yin and Dong Liu
Atmosphere 2026, 17(5), 469; https://doi.org/10.3390/atmos17050469 - 30 Apr 2026
Abstract
The impact of PM2.5 pollution on the health inequality of vulnerable groups is a core issue in environmental justice research. However, existing studies in China mostly focus on severely polluted areas in northern China. They lack comparative cases in economically developed eastern
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The impact of PM2.5 pollution on the health inequality of vulnerable groups is a core issue in environmental justice research. However, existing studies in China mostly focus on severely polluted areas in northern China. They lack comparative cases in economically developed eastern regions. They also rarely consider changes in the impact of air pollution on residents’ health amid rapid urbanization. Based on multi-source data, this study employed spatial visualization, spatial autocorrelation analysis and spatial regression models. It investigated the impact of PM2.5 pollution on the health inequality of vulnerable elderly groups in 92 districts and counties of Jiangsu Province from 2010 to 2020. The results show that: first, the regional pattern of health inequality between PM2.5 pollution and vulnerable elderly groups in Jiangsu has continuously evolved, with a “lower in the south and higher in the north” pollution pattern and high overlap between high-pollution areas and high elderly health risk areas in northern Jiangsu. Second, the spatial coupling between PM2.5 and elderly health risks has gradually strengthened, showing significant positive spatial agglomeration in 2020, confirming obvious spatial agglomeration characteristics of air pollution’s health impact. Third, the adverse health impact of PM2.5 on vulnerable elderly groups became significant in 2020, exhibiting cumulative and lagged characteristics; urbanization and regional coordinated development have played a positive role in alleviating regional health inequality, while a lagging energy structure further exacerbates the health vulnerability of the elderly. This study fills the gap of insufficient research on economically developed eastern regions and provides targeted empirical references for urban refined governance and precise prevention and control of environmental health inequality.
Full article
(This article belongs to the Special Issue Geospatial Analytics for Healthy Cities: Exploring Air Pollution and Socio-Spatial Inequality in Urban Environments)
Open AccessArticle
Accuracy Assessment of Atmospheric Large Eddy Simulations to Support Uncrewed Aircraft Systems Operations at GrandSKY, North Dakota
by
Claiborne Wooton, Mounir Chrit, Marwa Majdi and Aaron Sykes
Atmosphere 2026, 17(5), 468; https://doi.org/10.3390/atmos17050468 - 30 Apr 2026
Abstract
Severe and unpredictable wind conditions significantly disrupt flight safety, mission planning, and scheduling. Traditional wind forecasting methods rely on low-resolution mesoscale models or resource-intensive instrumentation. This study evaluates the accuracy of 40 m Large-Eddy Simulations (LESs), nested within a mesoscale framework, to better
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Severe and unpredictable wind conditions significantly disrupt flight safety, mission planning, and scheduling. Traditional wind forecasting methods rely on low-resolution mesoscale models or resource-intensive instrumentation. This study evaluates the accuracy of 40 m Large-Eddy Simulations (LESs), nested within a mesoscale framework, to better resolve hazardous wind phenomena over GrandSKY, North Dakota, the first large-scale commercial Uncrewed Aircraft System (UAS) test park in the United States, serving as a hub for UAS innovation and Beyond Visual Line of Sight operations. Using low-altitude airborne observations from Meteodrone flights, satellite data, and ground-based measurements, we assess the model’s accuracy in predicting wind speed and direction during both summer and winter. Results demonstrate that the 40 m LES provides improved predictions of wind gust variability compared to the 1 km forecast, and the impact on flight safety is quantified. The LES also reveals notable discrepancies in UAS flyability predictions, which result in up to a 17% reduction in operational windows during the summer. This study’s novelty lies in using a 40 m resolution LES nested within a 1 km WRF simulation, combined with multi-source observations, to resolve low-altitude turbulence and quantify its impact on UAS operations. A 10–18% correction factor can be applied to TKE (or derived wind variability) in coarser WRF runs to better estimate maximum wind speeds without LES. The findings highlight the potential of high-resolution LES modeling to support reliable UAS operations in weather-sensitive environments, laying the groundwork for broader integration of advanced simulation techniques in national airspace management systems.
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
Open AccessArticle
Impact of YunYao GNSS-RO Refractivity Data Assimilation on Typhoon Forecasts: A Case Study of Typhoon BEBINCA (2024)
by
Liang Kan, Fenghui Li, Jinxiao Li, Manyi Huang, Pengcheng Wang, Yan Cheng, Jiawen Cui, Dan Yan, Wenxi Zhang, Chaochao He, Xuewei Liang, Zili Shen and Wen Zhou
Atmosphere 2026, 17(5), 467; https://doi.org/10.3390/atmos17050467 - 30 Apr 2026
Abstract
The accuracy of numerical weather prediction largely depends on the quality of the initial conditions. Global Navigation Satellite System radio occultation (GNSS-RO) observations, with their high vertical resolution, play an important role in reducing initial condition errors. In this study, multiple simulations with
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The accuracy of numerical weather prediction largely depends on the quality of the initial conditions. Global Navigation Satellite System radio occultation (GNSS-RO) observations, with their high vertical resolution, play an important role in reducing initial condition errors. In this study, multiple simulations with different initialization times were conducted during the development of Typhoon BEBINCA using the WRF-GSI assimilation system to evaluate the impact of YunYao GNSS-RO observations on improving extreme weather simulation performance and to investigate the sensitivity of refractivity assimilation to different cloud microphysics parameterization schemes. The results show that assimilating YunYao GNSS-RO data significantly improves the consistency between the model initial fields and observations and enhances the analysis quality in the middle and upper troposphere. Compared with ERA5 reanalysis data, the assimilation experiments better reproduce the spatial and temporal evolution of key atmospheric variables, and the improvements persist from 36 h to 120 h forecast lead time. Statistical results from multiple initializations show that the maximum RMSE reductions exceed 0.2 K for temperature, 0.1 m s−1 for wind speed, and geopotential height shows consistent improvements throughout the entire atmosphere. In addition, the assimilation experiments improve the simulation of Typhoon BEBINCA’s track and intensity. Statistical results from multiple initializations indicate that the 84 h track error is reduced by approximately 30 km on average, and the minimum central pressure bias is also reduced. Sensitivity experiments further show that the WSM6 microphysics scheme performs better in track forecasting, while the Thompson scheme is more suitable for intensity forecasting. Overall, YunYao GNSS-RO assimilation effectively improves typhoon forecast accuracy and demonstrates strong potential for operational applications.
Full article
(This article belongs to the Special Issue Multi-Source Observations and Intelligent Data Assimilation for Improving High-Impact Weather Prediction)
Open AccessArticle
Spatial Decoupling of Surface and Atmospheric Urban Heat: Differential Land Cover Associations in Zagreb
by
Dino Bečić and Mateo Gašparović
Atmosphere 2026, 17(5), 466; https://doi.org/10.3390/atmos17050466 - 30 Apr 2026
Abstract
Urban heat islands present a significant obstacle to climate adaptation strategies, yet the interplay between surface and atmospheric thermal elements is not fully understood. This research investigates the spatial relationship between land surface temperature (LST) and near-surface air temperature (TAIR) across Zagreb’s 218
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Urban heat islands present a significant obstacle to climate adaptation strategies, yet the interplay between surface and atmospheric thermal elements is not fully understood. This research investigates the spatial relationship between land surface temperature (LST) and near-surface air temperature (TAIR) across Zagreb’s 218 local councils during the summer of 2024, assessing the premise that these constitute separate thermal dimensions with varying land cover correlations. Landsat 8/9-derived LST and CERRA-derived TAIR, temporally aligned to the Landsat overpass slot (09:00 UTC), were examined through spatial autocorrelation (Moran’s I, Getis–Ord Gi*), correlation analysis, and Fisher’s z-tests to compare the effects of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The findings indicated partial coupling (r = 0.537, R2 = 0.288), with 71.2% of the variance remaining unexplained, suggesting considerable surface-atmospheric decoupling. Furthermore, hot spot overlap analysis revealed limited convergence (11.9% of neighborhoods), while 44.5% displayed divergent thermal extremes. Land cover showed much stronger connections with LST (NDVI: r = −0.970, R2 = 0.941; NDBI: r = +0.973, R2 = 0.947) than with TAIR (NDVI: r = −0.478; NDBI: r = +0.496), representing reductions in explained variance of 63–64% (p < 0.001). These findings suggest that surface and atmospheric urban heat are related but distinct thermal aspects.
Full article
(This article belongs to the Special Issue Urban Impact on the Low Atmosphere Processes)
Open AccessArticle
Energy and Cost Analysis of a Methanol Fuel Cell and Solar System for an Environmentally Friendly and Smart Catamaran
by
Giovanni Briguglio, Yordan Garbatov and Vincenzo Crupi
Atmosphere 2026, 17(5), 465; https://doi.org/10.3390/atmos17050465 - 30 Apr 2026
Abstract
Maritime transport is under increasing pressure to cut greenhouse gas and pollutant emissions to meet global decarbonization goals and tighter environmental standards. Ship electric propulsion systems offer a promising solution for short-range maritime operations, particularly for small vessels and coastal activities. Full-electric vessels
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Maritime transport is under increasing pressure to cut greenhouse gas and pollutant emissions to meet global decarbonization goals and tighter environmental standards. Ship electric propulsion systems offer a promising solution for short-range maritime operations, particularly for small vessels and coastal activities. Full-electric vessels can significantly reduce operational emissions; however, a key challenge is the extensive charging time for onboard energy storage, which can affect operational continuity and logistical efficiency. This study examines mission planning and energy management for a hybrid multi-source electric mail boat operating in the Aeolian archipelago. It evaluates the viability and performance of a daily inter-island route powered by a high-temperature methanol fuel cell, batteries, and photovoltaic panels. A routing and simulation framework was developed to model the boat’s itinerary among seven islands, accounting for realistic navigation speeds, scheduled stops, solar energy availability, and battery state-of-charge constraints. The study analyzes distance, travel time, energy consumption, solar power generation, and fuel–electric usage with high temporal resolution, enabling detailed analysis of power flows during sailing and docking. Several operational strategies were assessed, including periods of increased speed supported by battery assistance and fuel–electric cell output, combined with coordinated energy management to keep battery levels above a lower acceptable threshold while completing the route in a single day. The methodology provides a practical tool for planning low-emission island networks and supports the integration of innovative energy systems into small electric workboats operating in specific maritime regions.
Full article
(This article belongs to the Topic Advances in Low-Carbon, Climate-Resilient, and Sustainable Built Environment)
Open AccessReview
A Review and Perspectives on Wind Speed Forecasting for High-Speed Railways in China
by
Lei Hu, Zhen Ma and Huijin Fu
Atmosphere 2026, 17(5), 464; https://doi.org/10.3390/atmos17050464 - 30 Apr 2026
Abstract
Extreme meteorological phenomena—characterized by gale-force winds, torrential rainfall, and ice-snow accumulation—pose significant threats to the operational safety of high-speed railways, with wind-induced hazards being especially critical. Such events can trigger catastrophic incidents, including train derailments and service disruptions, as evidenced by numerous documented
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Extreme meteorological phenomena—characterized by gale-force winds, torrential rainfall, and ice-snow accumulation—pose significant threats to the operational safety of high-speed railways, with wind-induced hazards being especially critical. Such events can trigger catastrophic incidents, including train derailments and service disruptions, as evidenced by numerous documented cases worldwide. To bolster the wind resilience of high-speed railway systems, high-precision wind speed prediction has become a cornerstone for ensuring operational safety. This research presents a systematic review of international advancements in railway wind early warning systems, critically evaluating the technical attributes and performance constraints of four primary paradigms: physical numerical models, statistical methods, machine learning algorithms, and hybrid frameworks. Moving beyond a simple taxonomy, this paper delineates the strengths, limitations, and domain-specific applicability of each approach within the high-speed railways context. Furthermore, it assesses the transformative potential of emerging large-scale Artificial Intelligence (AI) meteorological models for wind speed forecasting. A quantitative comparison is provided to facilitate rigorous methodological assessment. The findings reveal four critical technical bottlenecks: (1) low computational efficiency of numerical models; (2) insufficient spatiotemporal resolution of monitoring data; (3) poor generalization of predictive models; and (4) the “black-box” nature and weak interpretability of AI models. To address these, this paper posits that future research should prioritize key technologies including multi-source heterogeneous data fusion, algorithmic optimization, design of intelligent algorithms, probabilistic risk forecasting, and the synergistic integration of AI with numerical weather prediction (NWP). Such advancements will catalyze the development of more robust HSR wind warning systems, ensuring sustained safety and operational efficiency under volatile meteorological conditions.
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
Open AccessArticle
Analysis of the Impact of Biometeorological Thermal Indices on Summer Peak Power Load Forecasting in Guangdong Province
by
Jingqi Miao, Hui Yang, Yu Zhang, Quancheng Hao, Liying Peng, Feng Xu and Haibo Shen
Atmosphere 2026, 17(5), 463; https://doi.org/10.3390/atmos17050463 - 30 Apr 2026
Abstract
Accurate prediction of electricity demand during hot seasons is essential for maintaining power system reliability, particularly in humid subtropical regions such as Guangdong, China, where high temperatures strongly influence consumption. However, many models rely primarily on air temperature and may not fully capture
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Accurate prediction of electricity demand during hot seasons is essential for maintaining power system reliability, particularly in humid subtropical regions such as Guangdong, China, where high temperatures strongly influence consumption. However, many models rely primarily on air temperature and may not fully capture combined atmospheric effects. This study evaluates the potential of biometeorological thermal indices for improving summer electricity load forecasting. Daily maximum load and meteorological data during May–September 2019–2021 were analyzed using Back-Propagation Neural Network (BP), Random Forest (RF), and a Stacking ensemble model. Three indices—Effective Temperature (ET), Physiological Equivalent Temperature (PET), and the Universal Thermal Climate Index (UTCI)—were introduced as predictors. The ensemble model achieved the best performance, with Ensemble–UTCI yielding the highest accuracy (R2 = 0.559, RMSE = 60.96 × 104 kW, MAE = 45.10 × 104 kW). Compared with temperature-based models, biometeorological indices consistently improved predictions, with UTCI performing best (average RMSE = 62.81 × 104 kW). Bayesian analysis shows strong evidence of improvement in RF and ensemble models, but not in BP or linear models, indicating model dependence. During the July 2021 heat event, RF showed greater robustness, with PET–RF achieving the lowest error (MAPE = 3.03%). These results demonstrate the value of biometeorological indices for load forecasting in humid subtropical regions.
Full article
(This article belongs to the Special Issue Urban Overheating, UHI Adaptation, and Nexus with Energy Transition in the Context of the Urban Landscape and Environment)
Open AccessArticle
Ammonia (NH3) Mitigation in Intensive Pig Housing via a Novel Feed-Based Intervention: Real-Scale Evidence from High-Frequency Indoor Concentration Monitoring
by
Marcello Ermido Chiodini, Daniele Aspesi, Lorenzo Poggianella and Marco Acutis
Atmosphere 2026, 17(5), 462; https://doi.org/10.3390/atmos17050462 - 30 Apr 2026
Abstract
Ammonia (NH3) from intensive agriculture is a primary precursor for secondary fine particulate matter (PM2.5), necessitating mitigation under the EU National Emission Ceilings (NEC) Directive. This study evaluated a novel feed-based intervention assessed under real-scale commercial conditions in weaning
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Ammonia (NH3) from intensive agriculture is a primary precursor for secondary fine particulate matter (PM2.5), necessitating mitigation under the EU National Emission Ceilings (NEC) Directive. This study evaluated a novel feed-based intervention assessed under real-scale commercial conditions in weaning and growing pig units. Indoor NH3 concentrations were monitored at high frequency (2 h resolution), and treatment effects were analyzed using a Circular Block Bootstrap (CBB) approach to account for diurnal cyclicity and temporal autocorrelation. In the weaning unit, where pits were fully emptied before the trial, the mean indoor NH3 concentration decreased from 7.51 ppm to 1.37 ppm, representing an 81.7% reduction. In the growing unit, which operated under pre-existing slurry and an overflow system, a significant reduction of 20.9% was observed (from 5.45 ppm to 4.31 ppm). These results demonstrate the intervention’s efficacy in preventing NH3 release from fresh excreta and suggest that its impact in systems managed under slurry overflow can be further optimized by initially activating pre-existing material. This infrastructure-free solution offers a scalable, economically sustainable pathway to align livestock production with zero-pollution targets while supporting multiple Sustainable Development Goals related to human health, worker welfare, and environmental protection.
Full article
(This article belongs to the Special Issue Ammonia Emissions and Particulate Matter (2nd Edition))
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Open AccessArticle
Analysis of Precipitation Characteristics in the Middle and Lower Reaches of the Jinsha River Basin Based on Warm-Season Observations (2023–2025)
by
Hantao Wang, Ye Yin, Cuihua Chen and Peipei Yu
Atmosphere 2026, 17(5), 461; https://doi.org/10.3390/atmos17050461 - 30 Apr 2026
Abstract
To investigate the influence of complex terrain on precipitation characteristics in the Jinsha River Basin (JRB), this study analyzes the spatiotemporal distribution of precipitation amount, frequency, and intensity under different topographic factors in the middle and lower reaches of the JRB (MLJRB), based
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To investigate the influence of complex terrain on precipitation characteristics in the Jinsha River Basin (JRB), this study analyzes the spatiotemporal distribution of precipitation amount, frequency, and intensity under different topographic factors in the middle and lower reaches of the JRB (MLJRB), based on hourly precipitation observations from 1745 ground stations deployed by the China Meteorological Administration. The results indicate the following: (1) Precipitation amount increases gradually from low altitudes, peaks at sub-high altitudes, and then decreases. The highest precipitation frequency occurs at high altitudes, while the greatest precipitation intensity is observed at mid altitudes. (2) Spatially, a high-precipitation center with high frequency and intensity is formed in the lower reaches of the JRB, whereas the northern part of the study area exhibits a low center for both frequency and intensity. (3) Pronounced diurnal and monthly variations are observed at all altitudes. Precipitation amount and intensity peak during nighttime hours. On a monthly scale, both precipitation amount and intensity increase from May to July or August and then decrease, while the trend for precipitation frequency is not entirely consistent. (4) Precipitation amount shows little change with increasing slope gradient. Precipitation frequency increases with slope gradient, whereas precipitation intensity exhibits a clear decreasing trend. Eastern slopes receive higher precipitation amount and frequency compared to other aspects, followed by southern slopes, with western slopes receiving the lowest; however, differences in precipitation intensity among different slope aspects are minimal. In conclusion, the MLJRB exhibits strong spatiotemporal variability, distinct vertical differentiation, and pronounced periodic variation in precipitation. Precipitation frequency and intensity in this region are also associated with micro-topography.
Full article
(This article belongs to the Special Issue The Qinghai-Tibet Plateau: Its Climate/Ecology and Its Impact on Global Climate/Ecology)
Open AccessArticle
Study on Wind-Blown Snow Hazards and Snow Fence Parameters Based on Different Cutting Depths of Mountain Highways
by
Haojie Tang, Ruixin Liu, Jian Liu, Fenglong Wang, Zhixuan Hu and Haiwei Xie
Atmosphere 2026, 17(5), 460; https://doi.org/10.3390/atmos17050460 - 30 Apr 2026
Abstract
To address the severe snow accumulation within road cuttings triggered by wind-blown snow on mountainous highways, and to elucidate the influence mechanisms of cutting depth and snow fence parameters on the wind–snow flow field, this study presents a systematic investigation based on typical
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To address the severe snow accumulation within road cuttings triggered by wind-blown snow on mountainous highways, and to elucidate the influence mechanisms of cutting depth and snow fence parameters on the wind–snow flow field, this study presents a systematic investigation based on typical sections of the G577 Grade I mountain highway in the Xinjiang Uygur Autonomous Region, China. First, indoor wind tunnel experiments were conducted to observe the distribution characteristics of the wind– snow field inside and outside the cuttings and around the snow fences under varying cutting depths and fence parameters. Second, numerical simulations were performed using the Analysis System Fluent software with models identical to those used in the wind tunnel tests to analyze the airflow field and snow particle movement patterns. Finally, experimental results were compared with field observations of winter snow accumulation to validate the reliability of both the numerical simulations and wind tunnel experiments. The results indicate that under small intersection angles (15–30°), deep cuttings significantly exacerbate snowdrift accumulation trends, reducing wind speed within the cutting and increasing snow accumulation at the bottom (an increase of 31–81% per 5 m of depth). Furthermore, a nonlinear relationship regarding the impact of different snow fence parameters on flow field distribution. These findings provide theoretical support and valuable engineering references for optimizing road cutting design and snow fence construction in mountainous regions.
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(This article belongs to the Special Issue Atmosphere–Frozen Soil Interactions)
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Open AccessArticle
Spatiotemporal Characteristics and Multiscale Driving Mechanisms of Droughts and Floods in Jiangsu Province Based on EOF and Cross-Wavelet Analyses
by
Tianqi Yao, Guixia Yan, Jian He and Shuang Luo
Atmosphere 2026, 17(5), 459; https://doi.org/10.3390/atmos17050459 - 30 Apr 2026
Abstract
Based on monthly meteorological observations from 57 stations in Jiangsu Province during 1961–2022, the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated to characterize regional dry–wet variability. Empirical Orthogonal Function (EOF) analysis was applied to extract the dominant spatially coherent dry–wet modes, and cross-wavelet
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Based on monthly meteorological observations from 57 stations in Jiangsu Province during 1961–2022, the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated to characterize regional dry–wet variability. Empirical Orthogonal Function (EOF) analysis was applied to extract the dominant spatially coherent dry–wet modes, and cross-wavelet analysis was further employed to examine, in the time–frequency domain, the mode-specific responses to multiscale climate drivers, including the El Niño–Southern Oscillation (ENSO), Sunspot Number (SSN), Arctic Oscillation (AO), and Pacific Decadal Oscillation (PDO). The results show that dry–wet variability in Jiangsu Province is primarily organized by a regionally coherent mode (EOF1, explaining 56.3% of the total variance) and a north–south dipole mode (EOF2, explaining 17.8%), with the zero-value line of EOF2 closely aligned with the Huaihe River–Subei Irrigation Canal climatic transition zone. The temporal coefficient of EOF1 (PC1) exhibits a significant regime shift around 2013, followed by a pronounced wetting trend across the entire region. This change may reflect recent hydroclimatic adjustments in the study area, although the present study does not attempt a formal attribution of the respective thermal and precipitation contributions. In contrast, the temporal coefficient of EOF2 (PC2) undergoes an abrupt change around 1980, indicating a transition of the spatial dry–wet pattern from “southern drought–northern flood” to “southern flood–northern drought,” broadly consistent with an interdecadal climatic transition. Cross-wavelet analysis further reveals that PC1 is closely associated with ENSO at interannual timescales, with a lag of approximately 4–6 months, while its long-term variability shows time–frequency coherence with SSN. PC2 also exhibits time–frequency coherence with SSN at longer timescales, with an apparent phase transition around the 1980s; however, this low-frequency signal should be interpreted cautiously because the underlying physical mechanism remains uncertain. Overall, this study shows that dry–wet variability in Jiangsu Province is organized by two leading spatial modes with distinct temporal evolution and scale-dependent climate linkages. These findings provide new evidence for understanding hydroclimatic variability in monsoon transition zones and offer a basis for spatially differentiated drought–flood risk assessment.
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(This article belongs to the Section Climatology)
Open AccessArticle
Comparative Evaluation of ecPoint and EMOS for CMA-GEPS Precipitation Forecast over Eastern China
by
Sonum Stejik, Phuntsok Tsewang, Pu Liu and Jialing Wang
Atmosphere 2026, 17(5), 458; https://doi.org/10.3390/atmos17050458 - 30 Apr 2026
Abstract
Post-processing of numerical weather prediction (NWP) models constitutes a pivotal link in enhancing forecast performance. Despite their recognition as cutting-edge point-based post-processing techniques, systematic comparative evaluations of ecPoint (ECWMF for point forecasts) and Ensemble Model Output Statistics (EMOS)—particularly assessments of their applicability outside
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Post-processing of numerical weather prediction (NWP) models constitutes a pivotal link in enhancing forecast performance. Despite their recognition as cutting-edge point-based post-processing techniques, systematic comparative evaluations of ecPoint (ECWMF for point forecasts) and Ensemble Model Output Statistics (EMOS)—particularly assessments of their applicability outside Europe and to Chinese ensemble forecasting systems—remain sparse. In this study, we evaluate two advanced post-processing techniques—EMOS and the ecPoint—for calibrating ensemble precipitation forecasts. A comprehensive assessment of the performance of these ensemble post-processing methods is conducted using the CMA-GEPS (China Meteorological Administration’s Global Ensemble Forecasting System forecast over eastern China. The results demonstrate that both methods significantly mitigate systematic biases and improve the reliability and dispersion of ensemble forecasts. Notably, improvement in forecast accuracy is observed even under convective weather conditions and early-warning capability of extreme precipitation events is improved. Overall, while both methods show comparable performance, they exhibit distinct behaviours across different regions. The ecPoint method slightly outperforms EMOS in terms of Continuous Ranked Probability Score (CRPS) and provides improved resolution and early-warning capabilities at various precipitation thresholds.
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(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems (2nd Edition))
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Open AccessArticle
Seasonal Variability and Environmental Factors Influencing Deposition of Airborne Microplastics in Oxford Mississippi, USA
by
Ruojia Li, Kendall Wontor, Boluwatife S. Olubusoye, Taylor Gregory, John Stephen Brewer and James V. Cizdziel
Atmosphere 2026, 17(5), 456; https://doi.org/10.3390/atmos17050456 - 30 Apr 2026
Abstract
Airborne microplastics (MPs) are increasingly recognized as a pervasive pollutant with potential implications for environmental and human health. Despite growing concern, the influence of seasonal dynamics and environmental conditions on MP distribution remains poorly understood. This study investigates the temporal variability and environmental
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Airborne microplastics (MPs) are increasingly recognized as a pervasive pollutant with potential implications for environmental and human health. Despite growing concern, the influence of seasonal dynamics and environmental conditions on MP distribution remains poorly understood. This study investigates the temporal variability and environmental drivers of MPs across outdoor settings, highlighting how factors such as temperature, wind speeds, and precipitation modulate their behaviors. Using a combination of shielded gravitational deposition sampling (Sigma-2) and bulk deposition sampling over four seasons, coupled with μ-FTIR single particle analysis, we quantified MP abundance, size distribution, morphology, and polymer composition across contrasting environments. Deposition fluxes differed between samplers, with bulk samplers yielding 131–1589 MP/m2/d and Sigma-2 samplers yielding 4208–39,126 MP/m2/d. Multivariate analyses indicate that temperature was significantly correlated with MP loading in the Sigma-2 sampler, whereas precipitation effects were not detectable within the temporal resolution of our dataset. Polymer profiles differed between samplers, with Sigma-2 samples enriched in polyamide (PA) and resin-type particles, and bulk samples containing higher proportions of rubber and acrylate. Spherical and irregular particles were the predominant morphologies across both samplers. Together, these findings provide new insights into the environmental controls governing airborne MP deposition and underscore the need for long-term, meteorology-integrated, and methodologically standardized monitoring strategies to improve exposure assessment and inform mitigation efforts.
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(This article belongs to the Special Issue Micro- and Nanoplastics in the Atmosphere)
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Open AccessArticle
Association Between Ozone-Polluted Air and Birth Weight in Rural and Suburban Spain
by
Susan Moss-Pérez, Lidia Pérez Ormita, María Alonso-Colón, Juan Antonio Ortega-García, Diana Gómez-Barroso, Beatriz Núñez-Corcuera and Rebeca Ramis-Prieto
Atmosphere 2026, 17(5), 457; https://doi.org/10.3390/atmos17050457 - 29 Apr 2026
Abstract
Low birth weight (LBW) is associated with neonatal morbidity, mortality and long-term health complications. Global studies report an association between air pollution, such as tropospheric ozone, and LBW. This study aims to analyze the association between ozone exposure during pregnancy and LBW in
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Low birth weight (LBW) is associated with neonatal morbidity, mortality and long-term health complications. Global studies report an association between air pollution, such as tropospheric ozone, and LBW. This study aims to analyze the association between ozone exposure during pregnancy and LBW in 130 municipalities in rural and semi-urban Spain. We conducted a retrospective population-based cohort study using data from the Instituto Nacional de Estadística (INE) and air quality data from the Spanish Government for the 2001–2017 period. We performed descriptive analysis, logistic regression and linear regression analyses adjusted for various covariates. In addition, we fitted generalized additive models (GAMs) to estimate non-linear relationships. An association between decreased neonatal weight and high ozone exposure was found, especially in the first and second trimester. An increase in ozone concentration could lower neonatal weight but not enough evidence demonstrates an association with LBW. More research is needed to understand the impact of ozone exposure on neonates during pregnancy.
Full article
(This article belongs to the Section Air Quality and Health)
Open AccessArticle
Multi-Stage Statistical Approach for PM2.5 Source Identification in Baghdad
by
Omar S. Noaman, Alison S. Tomlin and Hu Li
Atmosphere 2026, 17(5), 455; https://doi.org/10.3390/atmos17050455 - 29 Apr 2026
Abstract
Although prior research focused on Baghdad has identified variability in fine particulate matter concentrations (PM2.5) and their origins, there remains uncertainty in the identification of the relative importance of local and long-range PM2.5 sources. This study analysed hourly air pollutant
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Although prior research focused on Baghdad has identified variability in fine particulate matter concentrations (PM2.5) and their origins, there remains uncertainty in the identification of the relative importance of local and long-range PM2.5 sources. This study analysed hourly air pollutant concentrations and meteorological data from three monitoring sites over the year 2019 in Baghdad, namely Al-Wazeriya (WZ), Al-Andalus Square (AS), and Al-Saiydiya (SA) sites, to determine the nature of PM2.5 sources. Multi-stage statistical models were utilised to address inherent data limitations and varying sampling dates caused by limitations on power supplies to monitoring equipment, thus improving the identification of urban particulate sources. Bivariate polar plots, concentration ratios, and conditional bivariate probability function (CBPF) plots were used to identify local sources of PM2.5. Potential Source Contribution Function (PSCF) and concentration weighted trajectory (CWT) methods were employed for distant and regional source apportionment. Domestic diesel generators are suggested to be the primary local source of PM2.5 pollutants in Baghdad’s WZ area (categorised as residential with significant traffic volumes). Gasoline- and diesel-fueled motor vehicles significantly contribute to PM2.5 concentrations in the AS and SA areas, which are commercial areas with the latter having close proximity to motorway sources. Additional impacts result from gas flaring and thermal power plants in these regions. Long-range PM2.5 transport may be attributed to the combustion of low-quality heavy fuel oils from several potential sources, including Nahrawan brick factories, oil fields, and Al-Musayyab thermal power plants, primarily towards the northeast, east, and southeast of Baghdad. Transboundary contributions to PM2.5 concentrations in Baghdad were also identified, from industrial sources in western Iran and eastern Syria, as well as dust particulates, and oil and gas production from southwestern Iran’s Khuzestan Province, Kuwait, and the Arabian Gulf. Low to medium wind speeds (1–4 ms−1) were linked with the highest source contributions, suggesting local emission sources to be the most significant contributors to high PM2.5 at the studied sample locations.
Full article
(This article belongs to the Special Issue Advances in Air Quality Monitoring and Source Apportionment)
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