Next Issue
Volume 17, April
Previous Issue
Volume 17, February
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.9
2.3
Journals
Atmosphere
Volume 17
Issue 3
share announcement

Atmosphere, Volume 17, Issue 3 (March 2026) – 105 articles

Cover Story (view full-size image): Ammonia plays a significant role in both odor complaints and the formation of fine particulate matter. In South Korea, Hanwoo farms generate substantial ammonia emissions, similar to other livestock sectors. This study focused on the ammonia released during the composting process of Hanwoo manure, aiming to conduct realistic measurements for the registration of national emission factors. By utilizing actual on-farm composting sheds as flux chambers, we investigated the impacts of seasonal variations and turning (agitation) operations on ammonia emissions. Contrary to previous research, the large-scale measurements in this study yielded lower values; however, these are considered more representative as they reflect actual on-farm conditions. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
16 pages, 3682 KB  
Article
Horizontally Inhomogeneous Ionospheric Refraction Correction for Ground-Based Radar
by Yunfei Zhu, Zhen Dong and Yifei Ji
Atmosphere 2026, 17(3), 331; https://doi.org/10.3390/atmos17030331 - 23 Mar 2026
Viewed by 284
Abstract
Atmospheric refraction often influences the localization accuracy of ground-based radar for detecting space targets. Traditional methods generally utilize the measured troposphere and ionosphere data from the local station for atmospheric refraction correction and thus neglect the influence of atmospheric horizontal inhomogeneity. However, in [...] Read more.
Atmospheric refraction often influences the localization accuracy of ground-based radar for detecting space targets. Traditional methods generally utilize the measured troposphere and ionosphere data from the local station for atmospheric refraction correction and thus neglect the influence of atmospheric horizontal inhomogeneity. However, in practice, a horizontally inhomogeneous ionosphere often causes considerable residual errors in the measured range and elevation angle after refraction correction, especially for targets with low elevation angles. The ionospheric electron density profile along the wave propagation path is significantly different from that in the vertical direction of the local station, which further brings about challenges in the modeling and correction of atmospheric refraction errors. To address the above challenge, the effect of a horizontally inhomogeneous ionosphere on the range and elevation angle measured by ground-based radar is analyzed, and a geographic division modeling strategy for the ionospheric electron density along the propagation path for atmospheric refraction correction is proposed in this paper. The simulation results show that the oblique electron density distribution obtained from the proposed model agrees well with the results calculated by the International Reference Ionosphere (IRI) model, and the proposed methodology effectively suppresses residual errors in radar atmospheric refraction correction in the low-elevation detection case. Full article
(This article belongs to the Special Issue Radar Sensing Atmosphere: Modelling, Imaging and Prediction (2nd Edition))
►▼ Show Figures

Figure 1

22 pages, 13824 KB  
Article
Spatiotemporal Heterogeneity of Intensifying Extreme Precipitation in China During the 21st Century and Its Asymmetric Climate Response
by Zhansheng Li and Dapeng Gong
Atmosphere 2026, 17(3), 330; https://doi.org/10.3390/atmos17030330 - 23 Mar 2026
Viewed by 270
Abstract
Extreme precipitation events are projected to change under climate change in terms of frequency, intensity and duration, which would cause serious impacts on water resources, agriculture, urban systems and socioeconomic conditions in the future. Based on 10 CMIP5 simulations statistically downscaled to 0.25° [...] Read more.
Extreme precipitation events are projected to change under climate change in terms of frequency, intensity and duration, which would cause serious impacts on water resources, agriculture, urban systems and socioeconomic conditions in the future. Based on 10 CMIP5 simulations statistically downscaled to 0.25° resolution through the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) initiative, seven precipitation climate extreme indices, as well as the probability ratio (PR) calculated by the Generalized Extreme Value (GEV) model for daily precipitation, were analyzed under scenarios RCP4.5 and RCP8.5. The results show that: (1) Annual precipitation is projected to increase significantly across China during the 21st century. The increasing rates are 1.4%/decade under RCP4.5 and 2.9%/decade under RCP8.5, respectively. The Tibetan Plateau exhibits the largest increase, particularly over the Karakoram Mountain area. Precipitation will also significantly increase in winter (13.59%/decade and 16.40%/decade) and spring (4.30%/decade and 6.33%/decade). (2) Precipitation extremes are projected to intensify markedly across China, with pronounced intensification in Southwest China and the Tibetan Plateau. (3) The more extreme the precipitation events, the greater the projected increase in the probability ratio (PR). It should be noted that the magnitude of the PR increase under RCP4.5 is significantly larger with respect to RCP8.5. These findings enhance the understanding of climate change and provide detailed regional-scale information to support adaptive policy-making. Full article
(This article belongs to the Section Climatology)
►▼ Show Figures

Figure 1

24 pages, 1461 KB  
Article
Simulation of Temperature and Water Vapor Profiles Retrieved from FORUM and IASI-NG Measurements
by Elisa Butali, Simone Ceccherini, Cecilia Tirelli, Gabriele Poli, Ugo Cortesi, Samantha Melani, Luca Rovai and Alberto Ortolani
Atmosphere 2026, 17(3), 329; https://doi.org/10.3390/atmos17030329 - 23 Mar 2026
Viewed by 299
Abstract
To advance our understanding of atmospheric processes and climate dynamics, improved knowledge of outgoing long-wave radiation (OLR) spectral emission is essential. The FORUM mission, selected for the ninth cycle of the European Space Agency’s Earth Explorer programme, is specifically designed to address the [...] Read more.
To advance our understanding of atmospheric processes and climate dynamics, improved knowledge of outgoing long-wave radiation (OLR) spectral emission is essential. The FORUM mission, selected for the ninth cycle of the European Space Agency’s Earth Explorer programme, is specifically designed to address the long-standing observational gap in the far-infrared (FIR) spectral region. When combined with measurements from the IASI-NG instrument, FORUM will provide complete spectral coverage of Earth’s OLR emission (spanning 100 to 2760 cm−1 wavenumber, or 3.62 to 100 μm wavelength), thereby enabling robust climate model validation and enhanced understanding of climate change processes. While IASI-NG’s primary mission is to support numerical weather prediction, FORUM is designed to measure key climate variables, which also enable the retrieval of atmospheric parameters in the troposphere and lower stratosphere. In this study, we assess the information content of FORUM and IASI-NG measurements for atmospheric profiling through a simulation-based approach. Synthetic retrieval products are generated using a linearized formulation of the retrieval transfer function, allowing an efficient and physically consistent evaluation of the sensitivity of the two instruments to atmospheric temperature and water vapor profiles. The analysis reveals a non-negligible sensitivity of FORUM to atmospheric temperature extending into the stratosphere, resulting in significant information content at altitudes higher than previously reported. This finding highlights the potential of far-infrared observations to contribute to atmospheric temperature profiling beyond the lower troposphere. The complementary capabilities of FORUM and IASI-NG suggest that their combined use can enhance the characterization of the atmospheric thermal structure. These results represent a first step toward evaluating the potential role of FORUM Level-2 products in future numerical weather prediction applications. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Figure 1

19 pages, 2458 KB  
Article
Concentrations and Health Risk Assessment of Ambient PM2.5-Bound Elements in Windsor, Ontario, Canada
by Tianchu Zhang, Yushan Su, James Gilmore, Jerzy Debosz, Michael Noble, Anthony Munoz, Chris Charron and Xiaohong Xu
Atmosphere 2026, 17(3), 328; https://doi.org/10.3390/atmos17030328 - 23 Mar 2026
Viewed by 327
Abstract
Hourly concentrations of PM2.5-bound elements were continuously monitored in Windsor, Canada, from April 2021 to April 2023. Health risk assessment methods of the USEPA were utilized to quantify lifetime cumulative cancer risks (CRs) using six PM2.5-bound elements, and chronic [...] Read more.
Hourly concentrations of PM2.5-bound elements were continuously monitored in Windsor, Canada, from April 2021 to April 2023. Health risk assessment methods of the USEPA were utilized to quantify lifetime cumulative cancer risks (CRs) using six PM2.5-bound elements, and chronic non-cancer hazard quotients (HQs) using 11 elements, for each season, each source factor, and each hour of day. The two-year average PM2.5 mass concentration was 9.2 μg/m3, slightly exceeding Ontario’s Ambient Air Quality Criteria of 8.8 μg/m3. A discernible diurnal concentration pattern was noted for most elements, peaking during morning rush hours and tapering during the daytime, largely attributed to local human activities and changes in atmospheric mixing heights. Despite this, both the total lifetime cumulative CR (4.1 × 10−5) and non-cancer total HQ (0.82) from exposure to ambient elements remained below the corresponding USEPA-acceptable levels. The seasonal variation in CRs and HQs was minimal. However, the diurnal variation was strong, with higher risks during morning rush hours (6:00–8:00) when traffic volume peaks, and lower risks during the daytime (12:00–20:00) when atmospheric mixing height is enhanced. Metal processing emerged as the most significant contributor to the total CR (52%) and HQ (60%), followed by coal/heavy oil burning (19% and 16%, respectively), and vehicular exhaust (19% and 12%, respectively). The remaining two source factors accounted for 10% of CR and 12% of HQ. Cd (62%) was the largest contributor to CRs, followed by Cr(VI) (25%), Co (6%), As (5%), Ni (2%), and Pb (<0.1%). Similarly, Cd dominated HQs (73%), followed by Mn (11%), Ni (6.3%), with the remaining eight elements collectively contributing 9.7%. Although levels of CRs and HQs are low, efforts to mitigate ambient Cd emissions from metal processing sources will help reduce exposure and protect the environment and human health, given Cd is the primary contributor to the total CR and HQ during the study period. Full article
(This article belongs to the Special Issue Air Pollution: Health Risks and Mitigation Strategies)
►▼ Show Figures

Figure 1

34 pages, 8747 KB  
Article
Emergent Constraint on the Projection of Compound Dry and Hot Events in Guangdong Province by CMIP6 Models
by Liying Peng, Hui Yang, Yu Zhang, Quancheng Hao, Jingqi Miao and Feng Xu
Atmosphere 2026, 17(3), 327; https://doi.org/10.3390/atmos17030327 - 22 Mar 2026
Viewed by 272
Abstract
In the context of global warming, compound dry-hot events (CDHEs) are intensifying in Guangdong, yet CMIP6 projections remain uncertain. This study employs CMIP6 data and the Standardized Compound Event Indicator (SCEI) to quantify CDHEs severity, applying an observational constraint approach to reduce inter-model [...] Read more.
In the context of global warming, compound dry-hot events (CDHEs) are intensifying in Guangdong, yet CMIP6 projections remain uncertain. This study employs CMIP6 data and the Standardized Compound Event Indicator (SCEI) to quantify CDHEs severity, applying an observational constraint approach to reduce inter-model uncertainty. The results show that, after observational constraint, uncertainties decrease by about 63% and 77% in Period I and II under SSP126 and by about 57% and 59% under SSP585, greatly improving projection robustness. CDHE risk is highest in SSP585-Period II. Future dry-hot intensification in Guangdong generally increases from north to south, with western Guangdong most strongly affected. Although CDHEs weaken in other periods, western Guangdong shows persistent aggravation. Mechanism analyses indicate that SSP585-Period I is mainly linked to cold sea surface temperature (SST) anomalies in the South Atlantic and waters near Australia. After correction, dry-hot conditions show a marked weakening across Guangdong, although slight intensification persists over the Leizhou Peninsula. SSP585-Period II is primarily influenced by warm SST anomalies in the eastern Pacific and South Atlantic and cold anomalies in the North Pacific. The two SSP126 periods are associated with warm SST anomalies in the South Atlantic and waters near Australia and with cold anomalies in the South Atlantic, North Pacific, and North Atlantic, respectively. After correction, CDHEs generally weaken across Guangdong, although southern and south-central areas remain relatively severe. These findings indicate that historical key SST biases can strongly influence future CDHEs projections in Guangdong by modulating large-scale atmospheric circulation, including the Pacific-South American wave train, Indian Ocean SST anomalies, and the Western North Pacific Subtropical Anticyclone. Full article
(This article belongs to the Section Climatology)
►▼ Show Figures

Figure 1

28 pages, 5437 KB  
Article
Trend Analysis of Heat Waves and Cold Spells in Major Turkish Cities Under Climate Change
by Ebrar Öztürk, Gökay Bayram, Veli Yavuz, Yiğitalp Kara, Caner Temiz and Anthony R. Lupo
Atmosphere 2026, 17(3), 326; https://doi.org/10.3390/atmos17030326 - 22 Mar 2026
Viewed by 558
Abstract
This study analyzes heat waves (HWs), cold spells (CSs), and mean temperature trends in Türkiye’s three major metropolises (Istanbul, Ankara, and Izmir) using long-term station data. HW and CS events were defined via a percentile-based threshold approach, utilizing daily maximum (Tmax) [...] Read more.
This study analyzes heat waves (HWs), cold spells (CSs), and mean temperature trends in Türkiye’s three major metropolises (Istanbul, Ankara, and Izmir) using long-term station data. HW and CS events were defined via a percentile-based threshold approach, utilizing daily maximum (Tmax) and minimum (Tmin) temperature data from a total of 15 meteorological stations. Temporal trends in annual and seasonal wave frequencies, alongside mean temperature series, were evaluated using the Mann–Kendall test and Sen’s slope estimator. The findings indicate that HW frequencies have significantly increased across the majority of stations, whereas CS frequencies have decreased at most locations. It was determined that while HWs predominantly concentrate in summer and CSs in winter, heat extremes can extend into transitional seasons. Mean temperatures exhibit a statistically significant upward trend across all stations. Furthermore, HWs have become more prominent and CSs have dissipated more rapidly in urban and coastal stations. These results reveal that the risk of heat extremes is escalating while cold extreme events are weakening in Türkiye’s major cities due to warming climate conditions. Full article
(This article belongs to the Section Climatology)
►▼ Show Figures

Figure 1

14 pages, 3184 KB  
Article
Vertical Variability and Source Apportionment of Black and Brown Carbon During Urban Seasonal Haze
by Samita Kladin, Parkpoom Choomanee, Surat Bualert, Thunyapat Thongyen, Nattakit Jintauschariya and Wladyslaw W. Szymanski
Atmosphere 2026, 17(3), 325; https://doi.org/10.3390/atmos17030325 - 22 Mar 2026
Viewed by 358
Abstract
This study investigates the vertical variation and temporal characteristics and indicates the sources of black carbon (BC) and brown carbon (BrC) within particulate matter fraction PM1 during light (November–December 2024) and heavy (January–February 2025) haze episodes in Bangkok, Thailand, a topic where [...] Read more.
This study investigates the vertical variation and temporal characteristics and indicates the sources of black carbon (BC) and brown carbon (BrC) within particulate matter fraction PM1 during light (November–December 2024) and heavy (January–February 2025) haze episodes in Bangkok, Thailand, a topic where data are still limited data regarding Southeast Asian megacities. Continuous measurements were conducted at 30 and 110 m above ground level, together with particle size distribution measurement, micrometeorological observations, and backward air mass trajectory analysis. During the haze periods, the highest particle number concentrations occurred in the 0.3–0.4 µm size range, indicating dominant contributions from combustion-related emissions and secondary aerosol formation. Mean PM1 mass concentrations during the heavy haze episodes were more than 2.5 times higher than those during light haze. BC concentrations increased substantially during heavy haze, while the BC fraction of PM1 remained relatively constant (~10%). In contrast, the BrC fraction reached nearly 20%, reflecting an increasing influence of biomass burning emissions associated with regional transport. Combined analyses of BC/BrC relationships, wind-direction dependence, and air mass trajectories demonstrate mixed contributions from local fossil fuel combustion and long-range transport of biomass burning aerosols during severe haze events. Full article
(This article belongs to the Section Air Quality and Health)
►▼ Show Figures

Graphical abstract

24 pages, 12433 KB  
Article
Atmospheric Loss of Energetic Electrons and Protons from the Radiation Belts After the Exceptional Injection of the 11 May 2024 Superstorm Leading to Four Electron Belts
by Viviane Pierrard and Alexandre Winant
Atmosphere 2026, 17(3), 324; https://doi.org/10.3390/atmos17030324 - 22 Mar 2026
Viewed by 256
Abstract
The exceptionally strong geomagnetic storm of 10–11 May 2024 injected new energetic protons and electrons into the terrestrial radiation belts, creating extraordinary conditions to study the loss mechanisms scattering these particles into the atmosphere after the storm. For the first time, four electron [...] Read more.
The exceptionally strong geomagnetic storm of 10–11 May 2024 injected new energetic protons and electrons into the terrestrial radiation belts, creating extraordinary conditions to study the loss mechanisms scattering these particles into the atmosphere after the storm. For the first time, four electron belts were observed during several weeks. We show that this structure was due to electron loss, highly dependent on specific positions. Using the proton and electron fluxes measured by the Energetic Particle Telescope, EPT, on board PROBA-V, we determine the lifetimes of these populations depending on their energy ranges and positions. We show that the lifetimes are much longer for protons than for electrons, which enables us to determine their time variations independently. For electrons, the wave–particle loss mechanisms depend on the background ionosphere–plasmasphere density. The lifetimes determined after the May 2024 and 10 October 2024 big events are compared with average ones to understand their unusual specificity for the formation of four and three belts, respectively. For the injected protons of 9.5 to 13 MeV, the lifetime is minimum at L~1.9, where the fluxes are maximum, showing a lifetime depending on the flux intensity. Loss is due to pitch angle diffusion and collisions with electrons and nuclei in the ambient plasma and neutral atmosphere. At the outer edge of the proton belt, the flux is depleted at all energies after the geomagnetic perturbation, and we determine that the progressive time of refilling after the storm generally reaches more than 40 days. There is an excellent discrimination between the different populations of energetic electrons (0.5–8 MeV) and the injected protons (9.5–13 MeV) that are still observed several months after the event. Such results contribute to advancing understanding of the interactions between the terrestrial atmosphere and space radiation. Full article
(This article belongs to the Special Issue Advances in Observation and Simulation Studies of Ionosphere)
►▼ Show Figures

Figure 1

20 pages, 85988 KB  
Article
Vertical Structure and Dynamical Regimes of Mediterranean Tropical-like Cyclones from High-Resolution WRF Simulations
by Christian Natale Gencarelli and Francesco Carbone
Atmosphere 2026, 17(3), 323; https://doi.org/10.3390/atmos17030323 - 21 Mar 2026
Viewed by 273
Abstract
Mediterranean tropical-like cyclones (MTLCs), commonly referred to as Medicanes, are high-impact weather systems characterized by complex interactions between baroclinic forcing and tropical-like processes. Despite growing interest, their vertical structures and dynamical regimes remain incompletely understood. In this study, high-resolution Weather Research and Forecasting [...] Read more.
Mediterranean tropical-like cyclones (MTLCs), commonly referred to as Medicanes, are high-impact weather systems characterized by complex interactions between baroclinic forcing and tropical-like processes. Despite growing interest, their vertical structures and dynamical regimes remain incompletely understood. In this study, high-resolution Weather Research and Forecasting (WRF) simulations at 1 km resolution are used to investigate the structure and evolution of two dynamically contrasting MTLCs: Ianos (2020) and Qendresa (2014). The analysis focuses on the temporal evolution of kinetic energy and turbulent dissipation as well as on the three-dimensional organization of wind and temperature fields during representative phases of the cyclone life cycle. The results reveal pronounced differences between the two events, with Ianos exhibiting a compact, vertically coherent, convection-dominated structure and Qendresa showing a wider, more asymmetric, and less stationary organization influenced by baroclinic processes. A comparative framework with the ERA5 reanalysis is employed to contextualize cyclone intensity, with ERA5 used as a dynamically consistent large-scale reference rather than as an observational benchmark. Overall, the study highlights the importance of vertical structure and boundary-layer processes in shaping Mediterranean tropical-like cyclones and demonstrates the added value of high-resolution numerical simulations for distinguishing between different dynamical regimes. Full article
(This article belongs to the Section Meteorology)
►▼ Show Figures

Figure 1

18 pages, 855 KB  
Article
Associations Between Emergency Room Visits for Respiratory Diseases and Exposure to Zip Code-Level Criteria Air Pollutants in New York State
by Tamba S. Lebbie, Laura E. Jones, Najm Alsadat Madani and David O. Carpenter
Atmosphere 2026, 17(3), 322; https://doi.org/10.3390/atmos17030322 - 20 Mar 2026
Viewed by 261
Abstract
We assess associations between emergency room (ER) visits, scaled to per 105 population per year, for asthma and chronic obstructive pulmonary disease (COPD), two of the most common respiratory diseases, and zip code-level exposure to criteria air pollutants (CAPs) coming from point [...] Read more.
We assess associations between emergency room (ER) visits, scaled to per 105 population per year, for asthma and chronic obstructive pulmonary disease (COPD), two of the most common respiratory diseases, and zip code-level exposure to criteria air pollutants (CAPs) coming from point sources in New York State (NYS) from 2010 to 2018. Exposure data on point source CAPs were retrieved from the United States Environmental Protection Agency (USEPA) National Emission Inventory (NEI) database, and ER visits for asthma and COPD were acquired from the New York State Department of Health (NYSDOH) Statewide Planning and Research Cooperative System (SPARCS). To account for within-county variability, we used log-linear mixed effects models, adjusted for year, sex, age category, county-level poverty, smoking, PM2.5, volatile organic compounds (VOCs), and CAPs sources within the study period. Results show significant associations between ER visits for asthma and COPD and most of the pollutants in the study, even after adjusting for the effects of poverty and smoking. Although point source emissions comprise a small portion of total air pollution, our findings show that zip code-level point source CAPs, especially the gaseous pollutants, pose a modest but significant contribution to the risk of respiratory disease-related ER visits. Full article
(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter (2nd Edition))
►▼ Show Figures

Figure 1

19 pages, 4016 KB  
Article
Satellite-Based Identification of VOC-Driven HCHO Hotspots and Their Role in Ozone Pollution Formation in the Beijing–Tianjin–Hebei Region
by Shuo Dong, Jeon-Teo Dong, Ziwei Chai, Jingxuan Zhao, Lijuan Zhang, Hui Chen, Xingchuan Yang, Linhan Chen, Ruimin Deng, Guolei Chen, Aimei Zhao, Qishuai Zhang, Yi Yang, Wenji Zhao and Pengfei Ma
Atmosphere 2026, 17(3), 321; https://doi.org/10.3390/atmos17030321 - 20 Mar 2026
Viewed by 284
Abstract
With the acceleration of global climate change and urbanization, air pollution, particularly ozone pollution, has become a critical environmental issue, especially in the Beijing–Tianjin–Hebei region of China. This study investigates the spatiotemporal distribution of ozone pollution and its precursors, focusing on formaldehyde as [...] Read more.
With the acceleration of global climate change and urbanization, air pollution, particularly ozone pollution, has become a critical environmental issue, especially in the Beijing–Tianjin–Hebei region of China. This study investigates the spatiotemporal distribution of ozone pollution and its precursors, focusing on formaldehyde as a key indicator of volatile organic compounds. Utilizing high-resolution remote sensing data from the China High-Resolution Air Pollutants dataset and TROPOMI HCHO observations from 2013 to 2022, we employed advanced techniques such as the Kolmogorov–Zurbenko filter and high-value area identification to analyze ozone pollution trends, meteorological influences, and the spatial distribution of HCHO concentrations. Our findings reveal a significant increase in ozone concentrations across BTH, with an annual growth rate of 2.51 μg/m3, peaking during the summer months. The KZ filter decomposition highlighted that short-term and seasonal variations dominate ozone fluctuations, driven by meteorological factors such as solar radiation and temperature. Furthermore, the identification of HCHO HVAs demonstrated that urban agglomeration and expansion zones exhibit higher HCHO concentrations, with VOCs-limited zones showing the most pronounced HCHO levels. The study also introduced the PHV (Percentage Higher than Vicinity) index to quantify anomalous HCHO emissions, providing a robust tool for pinpointing pollution hotspots. Based on these insights, we propose targeted emission control strategies for key regions, including urban expansion zones in Zhangjiakou and non-urban zones in Qinhuangdao, to mitigate ozone pollution effectively. This research offers valuable scientific support for regional air quality management and the formulation of precise pollution control measures in the Beijing–Tianjin–Hebei region. Full article
(This article belongs to the Section Air Quality)
►▼ Show Figures

Figure 1

15 pages, 1747 KB  
Article
Nitrogen Oxide Emissions as a Proxy for Simplifying Large-Scale Emission Inventories and Tracking Decarbonization
by Banyan Lehman and Bill Van Heyst
Atmosphere 2026, 17(3), 320; https://doi.org/10.3390/atmos17030320 - 20 Mar 2026
Cited by 1 | Viewed by 270
Abstract
Decarbonizing energy production is critical to slowing the effects of climate change and furthering global sustainability. Progress is often gauged via carbon dioxide (CO2) emissions; however, sources of CO2 vary beyond combustion, presenting a significant challenge to accurate tracking due [...] Read more.
Decarbonizing energy production is critical to slowing the effects of climate change and furthering global sustainability. Progress is often gauged via carbon dioxide (CO2) emissions; however, sources of CO2 vary beyond combustion, presenting a significant challenge to accurate tracking due to these various sources and sinks and the ubiquitous nature of CO2 in the atmosphere. Nitrogen oxide (NOX) emissions have previously been proposed as a surrogate for tracking sustainability, as they are primarily released from combustion processes. Facility-level data from Canada’s National Pollutant Release Inventory and Greenhouse Gas Reporting Program over a six-year period is used to assess the correlation between NOX and CO2 emissions from integrated facilities across Canada. Combustion-related CO2 emissions accounting for approximately 94% of Canadian industrial emissions are examined, targeting eleven industries which together encompass over 90% of combustion emissions. Multiple linear regressions (MLRs) on each industry correlating NOX, CO2, and the inventory methods used (i.e., emission factors (EFs), source monitoring, mass balance, engineering estimates, and speciation) show R2 values ranging from 0.81 to 0.96 for all but one industry. Several industries indicate that the methods used to calculate emissions influence the correlation of CO2 to NOX, highlighting issues in the current inventory techniques. The NOX-to-CO2 ratios calculated for the integrated facilities are similar to the ratios of the published main process-level EFs for NOX to CO2 (where available). These MLR models on NOX could be used to predict CO2 emissions with relative ease and accuracy in other jurisdictions, thereby simplifying large-scale emission inventory compilation while tracking sustainability. Full article
(This article belongs to the Special Issue Emission Inventories and Modeling of Air Pollution)
►▼ Show Figures

Graphical abstract

13 pages, 3868 KB  
Article
Seasonal Trends in Major Pollen Allergens in East Anglia, UK, Ipswich Site, with Comparison to Other UK Regions
by Janette Bartle and Beverley Adams-Groom
Atmosphere 2026, 17(3), 319; https://doi.org/10.3390/atmos17030319 - 20 Mar 2026
Viewed by 289
Abstract
Grass and birch pollen are major allergens in the United Kingdom (UK), responsible for seasonal respiratory diseases between late March and July. East Anglia is an under-represented region in pollen allergy research, while patterns of continuous days of high pollen levels have not [...] Read more.
Grass and birch pollen are major allergens in the United Kingdom (UK), responsible for seasonal respiratory diseases between late March and July. East Anglia is an under-represented region in pollen allergy research, while patterns of continuous days of high pollen levels have not been studied at all. Analysis of pollen statistics and trends in East Anglia addresses a regional gap for pollen exposure in the UK and assesses the intensity of the exposure. Trends and statistics for start, end, length, first high day (FH), number of high days (NH), seasonal pollen integral (SPIn) and number of high days occurring in a run together were presented. Birch pollen occurred from late March to late April, with little indication that onset, end or duration were changing temporally. Severity (SPIn) and the number of days in a run together have increased, in line with severity trends in nearby regions. Grass pollen occurred from late May until the third week in July, with almost no indication of changing trends in this region, apart from a likely earlier first high day. These results inform clinicians that the information and advice on when to treat hay fever symptoms and for how long should not change at the present time. Full article
(This article belongs to the Special Issue Pollen Monitoring and Health Risks)
►▼ Show Figures

Figure 1

3 pages, 166 KB  
Editorial
Advancing Resilience in the Nexus of Urban Heat Islands, Global Warming, and Human Health
by Tiziana Susca and Fabio Zanghirella
Atmosphere 2026, 17(3), 318; https://doi.org/10.3390/atmos17030318 - 20 Mar 2026
Viewed by 213
Abstract
The synergy between accelerated global urbanization and anthropogenic climate change has transformed the Urban Heat Island (UHI) [...] Full article
(This article belongs to the Special Issue Urban Heat Islands, Global Warming and Effects)
22 pages, 3494 KB  
Article
Terrestrial Net Ecosystem Productivity on the Tibetan Plateau: Characteristics, Climate Drivers and Future Changes
by Yiming Li, Mingwang Li, Yiming Su, Qiong Li and Shouji Pang
Atmosphere 2026, 17(3), 317; https://doi.org/10.3390/atmos17030317 - 19 Mar 2026
Viewed by 356
Abstract
Variations in terrestrial carbon flux influence atmospheric CO2 exchange and related climate feedback, with Net ecosystem productivity (NEP) serving as a key metric for assessing ecosystem carbon source–sink dynamics. Given the vital ecological barrier function of the Tibetan Plateau (TP), understanding the [...] Read more.
Variations in terrestrial carbon flux influence atmospheric CO2 exchange and related climate feedback, with Net ecosystem productivity (NEP) serving as a key metric for assessing ecosystem carbon source–sink dynamics. Given the vital ecological barrier function of the Tibetan Plateau (TP), understanding the spatiotemporal variability of NEP and its climatic controls is essential for elucidating carbon sink and climate interactions under ongoing climate change. The spatiotemporal dynamics of NEP across the TP from 1979 to 2018 are investigated using the process-based Community Land Model version 5.0 (CLM5.0). And climate sensitivity experiments are conducted to quantify the relative contributions of different climate factors to NEP variability. Furthermore, future changes in NEP for the period 2025–2100 under multiple Shared Socioeconomic Pathway (SSP) scenarios are projected. The results indicate that the TP functioned predominantly as a net carbon sink during the historical period, with a multi-year mean NEP of 23.96 g C m2 yr−1. Spatially, NEP showed a significantly increasing gradient from the northwest to the southeast. During 1979–2018, NEP exhibited an overall decreasing trend across most regions of the TP. Air temperature was identified as the dominant controlling factor, accounting for approximately 68% of the interannual NEP variability, followed by solar radiation (21%) and precipitation (11%). The dominant climatic drivers of NEP variation differ among regions: air temperature predominates in the southwestern and southeastern regions, radiation dominates in the northwestern and central areas, and precipitation exerts a controlling effect in the northern and western regions. Future projections suggest that NEP remains positive under all SSP scenarios, indicating that the TP is likely to persist as a carbon sink throughout the 21st century. This study provides important reference for the development of ecological protection, restoration planning, and regional carbon neutrality strategies. Full article
(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change (2nd Edition))
►▼ Show Figures

Figure 1

16 pages, 3471 KB  
Article
Unraveling Spatiotemporal Synergistic Features of PM2.5–O3 and Systematic Management Policy Based on Multiple Scenario-Driven Factor Analysis in the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, Central China
by Wujian Zhang, Changhong Ou, Jinpeng Fang, Miao Tian, Jinyuan Guo and Fei Li
Atmosphere 2026, 17(3), 316; https://doi.org/10.3390/atmos17030316 - 19 Mar 2026
Viewed by 256
Abstract
Fine particulate matter (PM2.5) and ozone (O3) are the key factors restricting the continuous improvement of air quality in the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZT). Due to the potential correlation between variations in urban PM2.5–O3 concentration, the analysis of its composite [...] Read more.
Fine particulate matter (PM2.5) and ozone (O3) are the key factors restricting the continuous improvement of air quality in the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZT). Due to the potential correlation between variations in urban PM2.5–O3 concentration, the analysis of its composite pollution characteristics is helpful in formulating accurate and thorough air control policies. Based on the long-term concentration change in PM2.5 and O3, this study analyzed the features and synergistic factors of PM2.5–O3 pollution in the CZT by using spatial autocorrelation and a linear driving model of PM2.5–O3. The results showed that from 2017 to 2023, under the current Chinese atmospheric environment standard, the CZT saw four combined pollution days. However, if the daily limit values were viewed in line with Grade II of the WHO transition period (O3: 120 μg/m3, PM2.5: 50 μg/m3), the combined pollution days would reach 111. The concentration of O3 in Zhuzhou and Xiangtan was about 10 μg/m3 lower than that in Changsha. Lower SO2 levels in Changsha might influence the partitioning of OH radicals and reactive nitrogen species, potentially affecting local O3 formation efficiency. NO2 and meteorological conditions jointly influence the co-variation in PM2.5 and O3, with NO2 playing a more significant role in PM2.5 formation. The long-term time series and daily concentrations of PM2.5 and O3 in the CZT showed opposing values, but there were short-term synergistic events on the scale of daily concentrations, and the time period was typically 3–10 days. Low humidity and strong sunlight may cause antagonistic events in which the concentration of O3 rises rapidly. Under static and stable weather conditions with low wind speed, no rainfall and moderate humidity, the concentration of PM2.5 and O3 rose alternately on sunny and cloudy days, demonstrating synergistic growth. Full article
(This article belongs to the Special Issue Sources Influencing Air Pollution and Their Control)
►▼ Show Figures

Figure 1

21 pages, 30483 KB  
Article
Preliminary Assessment of ICON-LAM Performance in Romania: Sensitivity Studies
by Amalia Iriza-Burcă, Ioan-Ştefan Gabrian, Ştefan Dinicilă, Mihaela Silvana Neacşu and Rodica Claudia Dumitrache
Atmosphere 2026, 17(3), 315; https://doi.org/10.3390/atmos17030315 - 19 Mar 2026
Viewed by 287
Abstract
The Earth system model ICON (ICOsahedral Nonhydrostatic general circulation) is a flexible framework that can be configured and tuned for various applications such as weather forecasting, simulations of aerosols and trace gases, and climate modelling. The numerical weather prediction component ICON is used [...] Read more.
The Earth system model ICON (ICOsahedral Nonhydrostatic general circulation) is a flexible framework that can be configured and tuned for various applications such as weather forecasting, simulations of aerosols and trace gases, and climate modelling. The numerical weather prediction component ICON is used in limited area mode (ICON-LAM) in Romania to obtain realistic weather simulations that support operational forecasting activities. The sensitivity of ICON-LAM is preliminarily evaluated for the geographical area of Romania. Numerical simulations using two parameterization schemes for radiation processes, two convection settings and different values for the laminar resistance of heat transfer from the surface to the air are evaluated against a control run employed for operational forecasts at the National Meteorological Administration. The validation is performed focusing on the precipitation field and surface continuous parameters. All configurations were integrated for a short period in summer when forecasted precipitation was strongly overestimated. Further on, selected configurations were evaluated for winter cases. The experiment with the shallow convection only, the ecRad radiation parameterization, and the laminar heat value 10 emerged as the best fit for Romania. This configuration (considered optimal) was evaluated alongside the operational control run for August 2022. Overall results indicate the selected optimal configuration generally outperforms the control run both with regard to precipitation and in forecasting surface parameters. This experiment has been adapted and implemented in operational workflow. Full article
(This article belongs to the Section Meteorology)
►▼ Show Figures

Figure 1

24 pages, 6908 KB  
Article
Comparison of Near-Surface Turbulence Spectral Shapes over Built and Open Terrain Using Commercial Drones as Portable Probes
by Aaron Daniel G. Delima, Winston Keith Cunanan, Rhodgene Abenoja Carcuevas, Francis Paul Alvarez, Vincent Rhey Montebon, Christian Bengal, Christian Dimas and Michael Loretero
Atmosphere 2026, 17(3), 314; https://doi.org/10.3390/atmos17030314 - 19 Mar 2026
Viewed by 323
Abstract
Monitoring atmospheric turbulence data of the near-surface sublayer presents a difficult challenge on complex and heterogeneous terrain such as mixed land areas where weather facilities are not always available. This study uses tilt data derived from the flight logs of two hovering unmanned [...] Read more.
Monitoring atmospheric turbulence data of the near-surface sublayer presents a difficult challenge on complex and heterogeneous terrain such as mixed land areas where weather facilities are not always available. This study uses tilt data derived from the flight logs of two hovering unmanned aerial vehicles (UAVS) as portable probes (DJI Mavic 2 and DJI Mavic 3 Classic) to compare the turbulence spectral characteristics of two adjacent contrasting surfaces; a built open courtyard and an open grass field. Turbulence spectra were divided into three ranges: E1 (0.05–0.2 Hz), E2 (0.2–1 Hz), and E3 (1–5 Hz). A 30 s moving mean and welch methods were used to filter out noise to ensure that the resulting spectra only showed the small tilts that were derived to show atmospheric turbulence. Normalization was applied to compare spectral shapes. Comparisons were made within platform (M2 vs. M2, M3 vs. M3). Observations show that spectral shapes generally agree. Contrasts were systematic within the energy bands and were not global. The study concludes on the notion that the unobstructed surfaces produce stronger fluctuations at the largest scales, whereas the built environments intensify turbulence at smaller scales. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Graphical abstract

30 pages, 18009 KB  
Article
A Multi-Agglomeration Assessment of Air Quality Responses to Top-Down NOx Emission Changes: Insights from Trends in Surface NO2 and O3 Across Urban China (2014–2021)
by Yang Shen, Shuzhuang Feng, Rui Zhang, Chenchen Peng, Zihan Yang, Yuanyuan Yang and Guoen Wei
Atmosphere 2026, 17(3), 313; https://doi.org/10.3390/atmos17030313 - 19 Mar 2026
Viewed by 198
Abstract
China’s stringent clean air policies have substantially reduced nitrogen oxides (NOx) emissions, leading to a general decline in nitrogen dioxide (NO2). However, surface ozone (O3) pollution remains severe, creating a complex challenge due to the non-linear relationship [...] Read more.
China’s stringent clean air policies have substantially reduced nitrogen oxides (NOx) emissions, leading to a general decline in nitrogen dioxide (NO2). However, surface ozone (O3) pollution remains severe, creating a complex challenge due to the non-linear relationship between O3 and its precursors. To disentangle the drivers behind these trends, this study quantifies the impacts of interannual variations in top-down constrained NOx emissions on surface NO2 and O3 concentrations from 2014 to 2021 across mainland China and five national urban agglomerations. We employed the WRF-CMAQ model with a fixed-emission simulation approach, using an observationally optimized NOx emission inventory derived from the assimilation of surface NO2 measurements. Results reveal that NO2 reductions were predominantly emission-driven (>80% post-2017), with declines most pronounced in winter. A strong linear consistency was found between interannual changes in top-down NOx emissions and attributed NO2 concentration variations, validating the methodology. In contrast, O3 responses to NOx reductions were spatially and seasonally heterogeneous, reflecting a non-linear photochemical regime. In major urban agglomerations (e.g., Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD)), NOx reductions post-2018 showed limited effectiveness in mitigating summertime O3 and even increased O3 in spring and autumn, indicating a prevalent VOC-sensitive regime where NOx reduction can disinhibit O3 formation. Conversely, certain provinces (e.g., Anhui, Shanxi, Jilin) exhibited O3 decreases, suggesting a NOx-sensitive regime. The area benefiting from NOx reductions expanded steadily in summer after 2017 but not in other seasons. This study confirms the efficacy of NOx-focused policies for reducing primary NO2 pollution but highlights that mitigating persistent O3 requires a strategic shift to synergistic, region-specific control of volatile organic compounds alongside NOx, informed by local chemical sensitivity. Full article
(This article belongs to the Special Issue Advances in Air Pollution Control and Air Quality Improvement in Chinese Megacity Clusters: From Formation Mechanisms to Mitigation Strategies)
►▼ Show Figures

Figure 1

26 pages, 10653 KB  
Review
AI/ML-Enhanced Wind Forecasts for Reducing Uncertainty in Prescribed Fire Planning
by Sara Brambilla, Shane Xavier Coffing, Jesse Edward Slaten, Diego Rojas, David Joseph Robinson and Arvind Thanam Mohan
Atmosphere 2026, 17(3), 312; https://doi.org/10.3390/atmos17030312 - 18 Mar 2026
Viewed by 356
Abstract
Prescribed fire is a vital tool for ecosystem management and wildfire risk reduction but its escalation is constrained by overly conservative burn windows because of uncertainties, for instance, in wind forecasts. This review describes the state of the art in weather product use [...] Read more.
Prescribed fire is a vital tool for ecosystem management and wildfire risk reduction but its escalation is constrained by overly conservative burn windows because of uncertainties, for instance, in wind forecasts. This review describes the state of the art in weather product use by fire/smoke models and identifies three priority research gaps that artificial intelligence/machine learning (AI/ML) is well positioned to address: (1) spatial and temporal downscaling to meter-scale, sub-hourly wind fields; (2) bias correction for systematic model errors in complex terrain; and (3) robust uncertainty quantification to inform ensemble-based simulations. Emerging AI/ML techniques offer promising frameworks to address all three challenges. By providing high-resolution, bias-corrected, and probabilistic wind fields, AI/ML-enhanced forecasts will allow for expanded burn windows, improved ignition strategy design and a reduced reliance on expert intuition, especially when a prescribed fire is introduced into new areas. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Figure 1

19 pages, 4249 KB  
Article
A High-Precision Prediction Method of Atmospheric Absorption Attenuation on Over-the-Horizon Propagation Trajectories
by Qinglin Zhu, Hao An, Fang Sun, Jie Han, Xiang Dong, Shoubao Zhang, Changsheng Lu, Ying Ci and Bin Xu
Atmosphere 2026, 17(3), 311; https://doi.org/10.3390/atmos17030311 - 18 Mar 2026
Viewed by 273
Abstract
Abnormal refraction phenomena such as atmospheric ducts due to temperature inversions or rapid decreases in humidity often happen in the lower troposphere over the sea and coastal area, which can make low-elevation signals in the duct layer propagate beyond the horizon, and the [...] Read more.
Abnormal refraction phenomena such as atmospheric ducts due to temperature inversions or rapid decreases in humidity often happen in the lower troposphere over the sea and coastal area, which can make low-elevation signals in the duct layer propagate beyond the horizon, and the ray trajectories extend horizontally over long distances. This paper uses ray tracing technology based on a second-order Taylor approximation to accurately predict the low-elevation ray trajectories within atmospheric ducts. The meteorologic parameters at the heights traversed by the rays are extracted to accumulate atmospheric absorption attenuation by line-by-line calculations, and a high-precision prediction method for atmospheric absorption attenuation in over-the-horizon propagation links is established; meanwhile, we also implement visualization of atmospheric absorption attenuation changes along the ray trajectories in atmospheric duct environments. By comparing the results of the atmospheric absorption attenuation models for horizontal terrestrial paths in the ITU-R P.676 recommendation and GJB Z87-1997 in atmospheric duct environments, we found that the high-precision model proposed in this paper can improve the prediction accuracy of atmospheric absorption attenuation by about 15% in surface ducts and 28% in elevated ducts, significantly improving the propagation performance of low-elevation signals under atmospheric ducts and other abnormal refraction conditions for electronic systems such as surveillance, detection, communication, and navigation. Full article
(This article belongs to the Special Issue Radiowave Propagation in the Atmosphere: Bridging Signal Physics and Technological Innovation)
►▼ Show Figures

Figure 1

16 pages, 6421 KB  
Article
Evaluation of Wind Field for ERA5 Reanalysis Data in Offshore East China Sea
by Yibo Yuan, Yining Ma, Li Dai, Yuxin Zang, Keteng Ke and Xiaoxiang Huang
Atmosphere 2026, 17(3), 310; https://doi.org/10.3390/atmos17030310 - 18 Mar 2026
Viewed by 312
Abstract
This study evaluates the applicability of ERA5 wind speed (WS) and wind direction (WD) in the East China Sea, using high-resolution vertical wind profiles measured by a floating LiDAR at the Shanghai Nanhui Offshore Wind Farm from 15 January 2022 to 15 January [...] Read more.
This study evaluates the applicability of ERA5 wind speed (WS) and wind direction (WD) in the East China Sea, using high-resolution vertical wind profiles measured by a floating LiDAR at the Shanghai Nanhui Offshore Wind Farm from 15 January 2022 to 15 January 2023. Key findings are as follows: (1) Strong positive correlations exist between LiDAR-measured and ERA5 WS across all evaluated heights, with correlation coefficients of 0.76 (ground level), 0.86 (50 m), 0.88 (100 m), and 0.90 (200 m), respectively, and corresponding root mean square errors (RMSEs) of 2.33 m/s, 1.78 m/s, 1.73 m/s, and 1.77 m/s. This systematic improvement in correlation and modest reduction in RMSE with increasing height indicate that ERA5 captures vertical wind structure with progressively higher fidelity above the surface layer. (2) Both the ERA5 dataset and LiDAR measurements consistently show dominant wind frequencies in the NNE and SSE directions, with peaks at approximately 1000 occurrences. The minimal differences in the two datasets demonstrate the ERA5’s robust representation of near-surface offshore WD climatology. (3) The ERA5 reanalysis data of typhoon Muifa can better illustrate the increase in the initial WS and its subsequent decreases. However, the peak WS lags behind measurements by 2 h, and the extreme WS is significantly lower than that measured. Evaluations of the multi-year return period WS demonstrate an underestimation of extreme WS by 16.06–16.51% for the ERA5 data. Regarding the WD, the measured direction is clockwise, while that of the ERA5 is counterclockwise, revealing a fundamental deficiency in its representation of mesoscale cyclonic wind structure. Therefore, ERA5 reanalysis data provides reliable characterization of typical offshore WS and WD within the operational wind turbine hub-height range (100–200 m). For typhoon-related wind engineering assessments, the applicability of ERA5 data necessitates caution and potentially bias correction. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
►▼ Show Figures

Figure 1

15 pages, 2680 KB  
Article
Climate Change Impacts on Olive Growing in Extremadura (Spain) Based on Different Bioclimatic Indices and Future Climate Scenarios
by Virginia Alberdi Nieves
Atmosphere 2026, 17(3), 309; https://doi.org/10.3390/atmos17030309 - 18 Mar 2026
Viewed by 215
Abstract
Olive cultivation is widespread throughout the Mediterranean basin, where the world’s main producing countries are located. Regions such as Extremadura are considered to be at high risk from the effects of climate change in the near future. In particular, olive cultivation is highly [...] Read more.
Olive cultivation is widespread throughout the Mediterranean basin, where the world’s main producing countries are located. Regions such as Extremadura are considered to be at high risk from the effects of climate change in the near future. In particular, olive cultivation is highly sensitive to climate change and can suffer profound effects on phenology and yield. This crop depends directly on variables such as maximum and minimum temperatures and rainfall. In this study, we have analysed how olive cultivation could be affected by calculating two bioclimatic indices, the Dryness Index (DI) and the Cool Night Index (CI), for three future periods. The methodology used projected ten combinations of climate models in two scenarios, RCP 4.5 and RCP 8.5. The results showed significant variations in the bioclimatic indices over the periods, which were used to calculate the water stress and extreme temperatures that these crops could suffer. They indicate that most of Extremadura will continue to be suitable for cultivation in the near future (2006–2035), while by the middle of the century (2036–2065) 67% of the area will remain temperate, where 72% of the olive groves are located, with a Dryness Index of 18% in the very dry category. By the end of the century (2066–2095), the zone will be 60–34% warm and very dry, with a Dryness Index of 72%. These results show that it will probably be necessary to create new areas suitable for olive cultivation and new varieties. Full article
(This article belongs to the Special Issue Climate Change and Its Effects over Spain)
►▼ Show Figures

Figure 1

16 pages, 4589 KB  
Article
Estimation of PM2.5 Concentration in Yangquan City from 2015 to 2024 Based on MODIS Image and Meteorological Data and Analysis of Spatial and Temporal Variation
by Qinfeng Yao, Jinjun Liu, Shenghua Chen, Yongxiang Ning and Sunwen Du
Atmosphere 2026, 17(3), 308; https://doi.org/10.3390/atmos17030308 - 18 Mar 2026
Viewed by 243
Abstract
This study employed Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth data meteorological data, Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), and ground monitoring data for particulate matter (PM2.5) to construct a model for estimating the PM2.5 concentration in Yangquan City, Shanxi [...] Read more.
This study employed Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth data meteorological data, Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), and ground monitoring data for particulate matter (PM2.5) to construct a model for estimating the PM2.5 concentration in Yangquan City, Shanxi Province, from 2015 to 2024. The spatial and temporal changes in the PM2.5 concentration were analyzed. The results revealed the following: (1) The random forest model was more accurate than the multiple linear regression model. The spring model R2 increased by 38.7%, and the Root Mean Square Error (RMSE) decreased by 92.6%. The summer model R2 increased by 65.1%, and the RMSE decreased by 92.5%. The autumn model R2 increased by 2.7%, and the RMSE decreased by 83.4%. The winter model R2 increased by 25.4%, and the RMSE decreased by 95.5%. (2) The PM2.5 concentration in Yangquan City showed an upward trend from 2015 to 2017, and then a downward trend from 2018 to 2024, with an average decrease of 18.3 μg/m3. The highest concentration of PM2.5 was 55–85 μg/m3 in winter, and the lowest concentration of PM2.5 was 25–40 μg/m3 in summer. In terms of spatial distribution, the PM2.5 concentration in Yangquan City exhibits a pattern of being lower in the northwest and higher in the southeast. The high values are primarily concentrated in the central urban areas and major industrial zones in the southeast. Full article
(This article belongs to the Special Issue Remote Sensing of Aerosols and Clouds: Current Status and Emerging Challenges)
►▼ Show Figures

Figure 1

20 pages, 7304 KB  
Article
Critical Inflection Points Govern PM2.5 Decline Dynamics in the Guangdong–Hong Kong–Macao Region
by Meng Wang, Zhengfeng An, Zhongwen Huang, Wenjie Lin and Yanlong Jia
Atmosphere 2026, 17(3), 307; https://doi.org/10.3390/atmos17030307 - 17 Mar 2026
Viewed by 304
Abstract
The Guangdong–Hong Kong–Macao (GHM) region (especially the Greater Bay Area), a low-lying economic hub in southern China, faces complex particulate matter (PM2.5) pollution dynamics under the combined influence of monsoonal systems and global warming. While long-term PM2.5 reductions are documented, [...] Read more.
The Guangdong–Hong Kong–Macao (GHM) region (especially the Greater Bay Area), a low-lying economic hub in southern China, faces complex particulate matter (PM2.5) pollution dynamics under the combined influence of monsoonal systems and global warming. While long-term PM2.5 reductions are documented, phase-specific trends remain obscured. Here, we analyze high-resolution ChinaHighPM2.5 dataset observations (2000–2023) using moving averages and piecewise regression to quantify abrupt shifts in interannual and seasonal PM2.5 trends across the region. We identify 2014 and 2016 as critical breakpoints for annual PM2.5 concentration (Mean-5y-Year) and its linear acceleration rate (k-5y-Year), respectively. Critical breakpoints delineate phases where declines persisted but decelerated. Prior to 2014, the PM2.5 levels exhibited an upward trend (+0.203 µg·m−3·a−1, p > 0.05), which reversed sharply post-2014 (−2.046 μg·m−3·a−1, p < 0.01). Spatially, breakpoints clustered post-2014 for concentrations, while acceleration rate shifts reveal a latitudinal divergence near 23° N (23.873°~22.812° N); southern areas transitioned earlier (2010–2011) versus post-2014 in the north. Post-inflection declines are strongest toward the GBA urban core, with winter and autumn driving seasonal improvements (winter: steepest decline −2.646 μg·m−3·a−1; autumn: largest trend reversal Δ−3.961 μg·m−3·a−1), while improvement rates narrowed post-2016 (Δk = +0.527 µg·m−3·a−2). This study establishes that apparent regional PM2.5 reductions mask significant spatiotemporal heterogeneity, underscoring the necessity of phase-specific analysis for effective pollution control in climatically vulnerable megaregions. Full article
(This article belongs to the Section Air Quality)
►▼ Show Figures

Figure 1

24 pages, 3321 KB  
Article
On the Stable Integration of Neural Network Parameterization in Numerical Models
by Yifan Wang, Weizhi Huang, Hao Geng, Yi Ma and Leyi Wang
Atmosphere 2026, 17(3), 306; https://doi.org/10.3390/atmos17030306 - 17 Mar 2026
Viewed by 197
Abstract
Deep learning-based parameterizations of subgrid-scale processes have become a major research focus in recent years, offering the potential to remedy inaccuracies inherent in traditional physics-based schemes. However, their integral stability within numerical models remains insufficiently explored. In this study, we develop deep learning [...] Read more.
Deep learning-based parameterizations of subgrid-scale processes have become a major research focus in recent years, offering the potential to remedy inaccuracies inherent in traditional physics-based schemes. However, their integral stability within numerical models remains insufficiently explored. In this study, we develop deep learning parameterizations for the tropical cyclone boundary layer and implement them in the WRF model. We find that one-dimensional convolutional neural network fails to integrate stably, whereas a fully connected network succeeds. Further analysis shows that the limited receptive field of the convolutional network makes its outputs overly sensitive to certain input perturbations, ultimately causing integral instability. We examine three stabilization strategies—training data augmentation with Gaussian noise, spectral norm regularization, and L2 regularization—and find that all three methods effectively mitigate the network’s output sensitivity to input perturbations, enabling stable integration in WRF and yielding physically reasonable tropical cyclone simulations. Full article
(This article belongs to the Special Issue Atmospheric Modeling with Artificial Intelligence Technologies)
►▼ Show Figures

Figure 1

23 pages, 4658 KB  
Article
LUCIDiT: A Lean Urban Comfort Intelligent Digital Twin for Quick Mean Radiant Temperature Assessment
by Michele Baia, Giacomo Pierucci and Carla Balocco
Atmosphere 2026, 17(3), 305; https://doi.org/10.3390/atmos17030305 - 17 Mar 2026
Viewed by 259
Abstract
The intensification of Global Warming and Urban Heat Island phenomena necessitates advanced, computationally effective tools for evaluating outdoor thermal comfort and microclimatic dynamics by means of Mean Radiant Temperature assessment. However, existing high-resolution physical models often suffer from prohibitive computational costs. This research [...] Read more.
The intensification of Global Warming and Urban Heat Island phenomena necessitates advanced, computationally effective tools for evaluating outdoor thermal comfort and microclimatic dynamics by means of Mean Radiant Temperature assessment. However, existing high-resolution physical models often suffer from prohibitive computational costs. This research proposes LUCIDiT (Lean Urban Comfort Intelligent Digital Twin), a physically based modeling framework implemented for a quick mean radiant temperature assessment inside complex urban morphologies. The method integrates a simplified balance of mutual radiative heat exchanges with recursive time-series filtering to account for the thermal inertia of different urban materials, alongside greenery heat exchange due to evapotranspiration. This architecture creates an operational urban comfort digital twin that reduces computational times by orders of magnitude for large-scale mappings, without sacrificing physical accuracy. Validation against drone-acquired thermographic data and the established Urban Multi-scale Environmental Predictor model demonstrates high reliability and coherence with the real physical phenomena and context. The application to an urban pilot site in Florence reveals that strategic interventions, such as substituting impervious surfaces with irrigated greenery and arboreal canopies, can mitigate radiant loads by up to 20 °C. Findings show that the proposed urban comfort digital twin can be a robust, scalable instrument for designing evidence-based climate adaptation strategies and quick testing mitigation scenarios to enhance urban resilience. Full article
(This article belongs to the Special Issue Advanced Studies on Climate Change in Urban Areas: Emerging Technologies and Strategies to Address Heat Waves and Improve Thermo-Hygrometric Comfort)
►▼ Show Figures

Figure 1

16 pages, 1881 KB  
Article
Comparative Evaluation of Short-Range Extreme Rainfall Forecast by Two High-Resolution Global Models
by Tanmoy Goswami, Seshagiri Rao Kolusu, Subharthi Chowdhuri, Malay Ganai and Medha Deshpande
Atmosphere 2026, 17(3), 304; https://doi.org/10.3390/atmos17030304 - 17 Mar 2026
Viewed by 291
Abstract
Accurate prediction of extreme rainfall events during the Indian Summer Monsoon (ISM, June to September) is critical for disaster preparedness and mitigation. This study evaluates the performance of two operational numerical weather prediction models, a high-resolution version of Global Forecast System (GFS T1534) [...] Read more.
Accurate prediction of extreme rainfall events during the Indian Summer Monsoon (ISM, June to September) is critical for disaster preparedness and mitigation. This study evaluates the performance of two operational numerical weather prediction models, a high-resolution version of Global Forecast System (GFS T1534) and the control member of the Met Office Global and Regional Ensemble Prediction System-Global (MOGREPS-G), in forecasting such events during the ISM from 2020 to 2023. The results demonstrate that, with respect to observations, both models tend to underestimate the mean and variability of rainfall; GFS-T1534 represents the mean and correlation better while MOGREPS-G represents the variability better over the Indian landmass. To assess the models’ performance for extreme rainfall prediction, we fix a rainfall threshold of 50 mm day−1, and the skill scores are computed including Probability of Detection, False Alarm Rate, Bias score and F1 score. Together, these scores indicate that both models show potential in short-range forecasting of extreme rainfall events, particularly within 24 h, but their skills remain limited at longer lead times. Specifically, the model biases vary over different geographical locations, often showing contrasting features. This underscores the need for model-specific post-processing and calibration techniques if these forecasts are to be used effectively for operational decision-making. Full article
(This article belongs to the Special Issue Novel Approaches to Predict Extreme Events in Atmospheric Flows: From Turbulence to Climate)
►▼ Show Figures

Figure 1

19 pages, 11970 KB  
Article
CFD Assessment of Near-Surface Dust Release and Transport in Near-Field Flows Under Different Atmospheric Stability Conditions
by Peng Sun, Hongfei Li, Chen Chen, Liang Zhang and Haowen Yan
Atmosphere 2026, 17(3), 303; https://doi.org/10.3390/atmos17030303 - 16 Mar 2026
Viewed by 290
Abstract
Because dust-emission processes driven by local, small-scale winds (e.g., terrain-induced winds) are difficult to accurately capture with mesoscale or larger-scale predictive models, this study employed a CFD-Lagrangian particle-tracking approach to numerically simulate near-surface dust release and transport under different atmospheric stability conditions in [...] Read more.
Because dust-emission processes driven by local, small-scale winds (e.g., terrain-induced winds) are difficult to accurately capture with mesoscale or larger-scale predictive models, this study employed a CFD-Lagrangian particle-tracking approach to numerically simulate near-surface dust release and transport under different atmospheric stability conditions in the same local flow field. The novelty of this work was the integration of MOST-based stable/neutral/unstable inflow construction with Lagrangian particle tracking, enabling a consistent comparison of stability effects within one framework. This framework is useful for assessing local blowing-sand impacts on short-range receptors. A near-surface source term was specified for PM10-class mineral dust, and particles were emitted using a vertically exponential allocation. Simulations were conducted over a kilometer-scale flow domain containing an idealized cosine hill, and the low-level concentration patterns and dispersion-height variations in the resulting dust cloud were analyzed. Compared with neutral conditions, stable stratification produced higher near-surface concentrations and a lower dispersion height, whereas unstable stratification yielded lower near-surface concentrations and a higher dispersion height; as the L increased, the unstable cases gradually approached the neutral state. The influence of reference wind speed exhibited clear stability dependence: under stable conditions, stronger winds intensified the buoyancy-related suppression of dust dispersion, while under unstable conditions, stronger winds inhibited the vertical spreading of the dust cloud. In addition, reduced air density representative of plateau environments resulted in lower dust-cloud concentrations and higher dispersion heights. These findings highlight the coupled effects of stratification and wind speed on near-field dust dispersion and provide a reference for assessing local dust emissions over complex terrain. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Figure 1

18 pages, 3175 KB  
Article
Examining the Super Intense Geomagnetic Storm on 10–11 May, 2024 via Artificial Neural Networks
by Sercan Bulbul, Fuat Basciftci, Burhaneddin Bilgen and Elif Tekin Gok
Atmosphere 2026, 17(3), 302; https://doi.org/10.3390/atmos17030302 - 16 Mar 2026
Viewed by 333
Abstract
This study investigates the super intense geomagnetic storm of 10–11 May 2024, during which the Dst index reached −412 nT, marking the most severe event of the last two decades. An artificial neural network (ANN) model was developed to estimate the geomagnetic storm [...] Read more.
This study investigates the super intense geomagnetic storm of 10–11 May 2024, during which the Dst index reached −412 nT, marking the most severe event of the last two decades. An artificial neural network (ANN) model was developed to estimate the geomagnetic storm indices Dst, Kp, and ap using hourly solar wind parameters (Bz, E, P, N, and V) obtained from the OMNI database. The model successfully reproduced the rapid and nonlinear variations observed during the main phase of the storm. The correlation coefficients (R) between observed and estimated values were 99.5%, 98.8%, and 99.1% for Dst, Kp, and ap, respectively. The corresponding mean square error (RMSE) values were 5.9 nT for Dst, 4.2 for Kp, and 2.1 nT for ap. Despite the extreme geomagnetic disturbance conditions, the ANN architecture maintained high estimative stability and accuracy, particularly during the sharp Dst decrease associated with southward Bz excursions. These results demonstrate that ANN-based approaches can effectively model the nonlinear dynamics of superstorms and provide a reliable complementary tool for forecasting extreme geomagnetic events. Full article
(This article belongs to the Special Issue Geomagnetic Storms and Their Consequences: Advances in Prediction Models)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-105
Previous Issue
Next Issue
Back to TopTop